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2012-02-02T13:13:00.000-08:00

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Molecular golems
- Nat Nanotechnol 7(1):1-2 (2012)
Nature Nanotechnology | Thesis Molecular golems * Chris Toumey1Journal name:Nature NanotechnologyVolume: 7,Pages:1–2Year published:(2012)DOI:doi:10.1038/nnano.2011.239Published online 28 December 2011 Corrected online19 January 2012 The golem stories of Jewish history can provide a framework for thinking about some of the ethical questions involved in nanotechnology and nanomedicine, as explains. Subject terms: * Ethical, legal and other societal issues Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg © EUREKA ENTERTAINMENT LTD/ROWMAN & LITTLEFIELD PUBLISHING GROUP One of the contributions of Jewish thought to Western ethics has been a series of golem stories. In these tales, which began to appear in the third century AD, a golem was a humanoid creature made of earth or clay. It was assembled and brought to life by a holy man using divine knowledge, used for a virtuous purpose, and then returned to its lifeless earthen origin. A later variation depicts the golem-maker as using secular knowledge, or having a non-virtuous reason for assembling a golem, or being irresponsible and failing to control the creature. Mary Shelley's Frankenstein is the best-known example of the latter1. "Golem stories raise issues about the reasons why one makes artificial life." Golem stories raise issues about the reasons why one makes artificial life, about the status of the golem, and about the ethical obligations of the golem-maker. Under what circumstances is it legitimate for someone to create humanoid life outside of natural processes of reproduction? What are the rights of the golem? What are the responsibilities of the golem-maker? As there were multiple versions of the golem story, there are many different ways to express and explore these ethical questions2. Many of these questions are relevant to visions of the future that involve advanced robots, cognitive-enhancing drugs (that is, drugs that are not needed for therapeutic purposes, such as the use of Ritalin by students to help them do better in exams), and the possibility that nanotechnology will enable the human brain to be interfaced with information technology so that people can permanently store their personal thoughts and emotional experiences3. The essence of who you are as an individual could endure eternally so long as the hardware available preserved the record of your spiritual self and made that data available to others4. I prefer to think of nanomedicine in terms of modest and realistic near-future developments, such as targeted drug delivery and lab-on-a-chip-based diagnostic tools, but I understand that others expect that nanomedicine will deliver more dramatic changes, which is why these sorts of ethical issues deserve attention. Golem stories might help us th! ink about these possibilities. Beginning in 1966, a small number of Jewish writers began to use the ethical issues in golem stories as a template for thinking about issues in information technology and biotechnology. If a certain technology had a quality similar to a human quality — intelligence, reasoning ability or the power to direct human reproduction, for example — then golem stories might help researchers think about the ethical implications of the technology. "Scholem suggested that a new computer at the Weizmann Institute should be named Golem Aleph (Golem One)." In 1966, in an article5 that is considered the original text for the golem-technology analogy, Gershom Scholem suggested that a new computer at the Weizmann Institute in Israel should be named Golem Aleph (Golem One). Scholem's reasoning took the form of a series of similarities between legendary golems and the computer, especially the idea that both represent man's creative powers and each was "a technical servant of man's needs". Scholem adopted a friendly tone in his article, asking the reader not to fear the power of the computer, and concluding with the following message for golems and computers: "Develop peacefully and don't destroy the world". An article on the same topic by Azriel Rosenfeld later the same year was more alarmist6. Rosenfeld warned that the development of intelligent robots would raise a number of troubling questions: * What is a man? "How much of a person's body can be replaced by artificial limbs and organs before he is no longer a 'man'?" * If biologists synthesize sperm and ova to make human bodies without parents, is the creature a human or an android? * If the intelligence of dolphins and other higher animals approaches human intelligence, do these animals deserve a human-like status? Then golems entered his discussion. There were solid reasons why a golem was not considered "legally human", wrote Rosenfeld, and why it was more like "an animal in human form". But if an intelligent golem expressed itself by speaking, should it not be considered human? Decades later, Byron Sherwin developed the golem-technology analogy more fully. In a book2, Golems Among Us, and a subsequent paper7, he created a framework for thinking about how, in Jewish tradition, technology was permitted to affect nature. This had two themes. First, God's creation of the natural world is incomplete, which gives humans an invitation, even a responsibility, to improve the creation through technology, provided that this is "tempered by moral wisdom". Secondly, Talmudic tradition and other Jewish sources say that it is permissible within certain limits to create artificial life. Sherwin indicated that, according to these two principles, genetically modified food and cloning were acceptable2. Sherwin also included an atom manipulated by nanotechnology in his list of modern-day golems2, but based on the principle that a golem is not permitted to procreate, self-replicating nanobots were excluded from the list. However, with the power to create artificial! life must come wisdom and responsibility. One of the lessons from the golem stories is that the golem-maker has a responsibility to control the creature he or she makes. This is the difference between Rabbi Loew of Prague, the most famous of all golem-makers, and Victor Frankenstein. Loew controlled his golem; Frankenstein did not. This framework of ethical insights provided by golem stories could help to guide our thinking about the tools and procedures of nanomedicine and the people who make them. But there is a caveat. The idea of golems in nanomedicine constitutes a thought experiment by Sherwin and his predecessors. It is a provocative idea that is worth exploring, but the applications of nanomedicine will not always fit neatly into the moral lessons that we find in golem stories. Some Christian thinkers have had similar ideas. Irving Hexham has written that robots in science fiction offer us "a debate on the meaning and purpose of existence"8. What is a person? What is a soul? How should a technology be controlled? For Hexham, robot stories were a way to ask these questions: indeed, he wrote that Christian theology was inferior to science fiction in pursuing these questions. Nanomedicine and other forms of nanotechnology confront us with questions about how we might change human life and human nature. Some might say that this is so novel that there are no precedents for the moral issues that accompany these possibilities. That is wrong. In these issues there are more difficult questions than there are easy answers, but the golems of the past 1,800 years can visit us again to remind us that there are precedents for thinking about how technology makes human nature interesting. Change history * Change history * References * Author informationCorrected online 19 January 2012In the Thesis article 'Molecular golems' (Nature Nanotech.7, 1–2; 2012), the surname of the author of ref. 5 was spelled incorrectly in the main text; it should have read Scholem. This has now been corrected in the HTML and PDF versions. References * Change history * References * Author information * Toumey, C.Sci. Technol. Hum. Val.17, 411–437 (1992). * Article * Sherwin, B.Golems Among Us (Ivan R. Dee, 2004). * Bainbridge, W.The Futurist25–29 (March–April 2006). * Walker, R.NY Times Magazine30–37, 44, 46 (8 January 2011). * Scholem, G.Commentary41, 62–65 (January 1966). * Rosenfeld, A.Tradition8, 15–23 (Fall 1966). * Sherwin, B.Zygon42, 133–143 (2007). * Article * Hexham, I.The Christian Century97, 574–578 (21 May 1980). Download references Author information * Change history * References * Author information Affiliations * Chris Toumey is at the University of South Carolina NanoCenter Corresponding author Correspondence to: * Chris Toumey Author Details * Chris Toumey Contact Chris Toumey Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Our choice from the recent literature
- Nat Nanotechnol 7(1):3 (2012)
Nature Nanotechnology | Research Highlights Our choice from the recent literature Journal name:Nature NanotechnologyVolume: 7,Page:3Year published:(2012)DOI:doi:10.1038/nnano.2011.244Published online 28 December 2011 Electron beams: An atom-sized vortex * Electron beams: An atom-sized vortex * Magnetic nanoparticles: At the crime scene * Nanoelectromechanical systems: Keeping the noise down * Electron microscopy: Mapping ensembles Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Appl. Phys. Lett. 99, 203109 (2011) © 2011 AIP Electron beams are typically plane waves. This means that the beam phase is identical for all points in a plane perpendicular to the beam direction. The phase of an electron vortex beam, on the other hand, describes a spiral. As a result, vortex beams carry orbital angular moment and magnetic moment, which leads to unique interactions with matter. Jo Verbeeck of the University of Antwerp and colleagues from Austria, the Netherlands and Canada have now demonstrated an electron vortex beam with a diameter of less than 1.2 Å. Electron vortex beams were first created by passing a plane wave beam through a graphite film that spontaneously formed a spiral structure, and acted as a phase plate. This was difficult to reproduce and gave limited control over the resulting beam. Verbeeck and co-workers had improved on this approach by creating a vortex beam with a holographic mask inside a transmission electron microscope. However, the effective beam diameter was several micrometres. Verbeek and colleagues have now reduced this beam diameter to atomic dimensions by placing a holographic mask in the condenser plane of a state-of-the-art microscope with double aberration correction. At 1.2 Å, the beam size is comparable to the size of the 2p orbital in a nitrogen atom (see image; left and right panels show the beam and the 2p orbital respectively, drawn approximately to scale). The tiny vortex beam may allow atomic-resolution mapping of magnetic states. MS Magnetic nanoparticles: At the crime scene * Electron beams: An atom-sized vortex * Magnetic nanoparticles: At the crime scene * Nanoelectromechanical systems: Keeping the noise down * Electron microscopy: Mapping ensembles Analysthttp://dx.doi.org/10.1039/c1an15200a (2011) DNA profiling is widely used by forensic investigators to identify an offender from just a single cell. However, equally valuable is the ability to detect and identify traces of body fluids such as saliva, semen and blood on various objects at the crime scene. At present, methods and tests used to analyse body fluids are destructive and have a low specificity. Now, Nunzianda Frascione and colleagues at King's College London have shown that magnetic nanoparticles conjugated with specific antibodies can detect and identify blood and saliva in situ on different types of substrates. The researchers functionalized magnetic nanoparticles with fluorescently labelled antibodies that recognize specific components of red blood cells, white blood cells or saliva. They applied the nanoparticles to human blood or saliva that had been smeared onto a glass slide. After 30 mins the unbound nanoparticles were removed by a magnet and the bound conjugates were visualized under a fluorescent microscope. The antibodies showed good specificity and had little cross reactivity with other body fluids. Furthermore, blood stains that were treated with the nanoparticles could still be used for DNA profiling, suggesting that this method could potentially save money as DNA profiling would only be carried out on identified sections of the samples. The method also worked on samples on substrates such as ceramic, paper and dark fabrics, thereby increasing the likelihood of uncovering important evidence at the crime scene. ALC Nanoelectromechanical systems: Keeping the noise down * Electron beams: An atom-sized vortex * Magnetic nanoparticles: At the crime scene * Nanoelectromechanical systems: Keeping the noise down * Electron microscopy: Mapping ensembles Nature480, 351–354 (2011) Any device that amplifies a signal inevitably adds noise, and quantum mechanics prevents this added noise being reduced below a certain value. It is possible to approach this quantum limit by using superconducting devices to amplify electrical signals, but these devices are complex. Now Francesco Massel and co-workers at Aalto University and the VTT Technical Research Centre of Finland have shown that nanomechanical resonators can amplify microwave signals, and that it may be possible to reach the quantum limit with this approach. The Finnish team start by using lithography and focused ion-beam etching to define a mechanical resonator and a microwave cavity in a 150-nm-thick layer of aluminium on a silica surface. When a pump signal is fed into this system, energy is transferred from the cavity to the resonator if the pump frequency is higher than the resonance frequency of the cavity, and vice versa. And if a weak probe signal is sent into the system when energy is being transferred to the resonator, this probe can also be amplified. Massel and co-workers show that approximately 20 noise quanta are added to the signal, and predict that it should be possible to reach the quantum limit of adding just half a quantum of noise. PR Electron microscopy: Mapping ensembles * Electron beams: An atom-sized vortex * Magnetic nanoparticles: At the crime scene * Nanoelectromechanical systems: Keeping the noise down * Electron microscopy: Mapping ensembles Nano Lett.http://dx.doi.org/10.1021/nl203975u (2011) Electron microscopy is routinely used to characterize the structure of metal nanoparticles, and with the help of electron energy-loss spectroscopy, chemical maps with atomic resolution can also be obtained. A chemical map of a single particle can, however, take hours to record. Therefore, acquiring a statistically significant sample of a system that contains nanoparticles with a variety of different compositions, such as a heterogeneous catalyst, is impractical. David Muller, Zhongyi Liu and colleagues at Cornell University, General Motors and Florida International University have now shown that the improved electron optics of an aberration-corrected electron microscope can allow hundreds of platinum–cobalt nanoparticles to be chemically mapped. The US team used a scanning transmission electron microscope that can correct up to the fifth-order of aberrations and allows data to be collected around a thousand times faster than on a conventional microscope. With the instrument, the platinum–cobalt nanoparticles — which are promising as a fuel-cell catalyst but are known to degrade over time — were mapped at various stages of ageing in a proton-exchange-membrane fuel cell. By mapping ensembles of nanoparticles, the precise structure and composition of the catalyst could be linked to its bulk electrochemical performance with statistical confidence. OV Written by Ai Lin Chun, Peter Rodgers, Michael Segal and Owain Vaughan. Author information * Electron beams: An atom-sized vortex * Magnetic nanoparticles: At the crime scene * Nanoelectromechanical systems: Keeping the noise down * Electron microscopy: Mapping ensembles Additional data
Molecular electronics: Flipping a single proton switch
- Nat Nanotechnol 7(1):5-6 (2012)
Nature Nanotechnology | News and Views Molecular electronics: Flipping a single proton switch * Peter Liljeroth1Journal name:Nature NanotechnologyVolume: 7,Pages:5–6Year published:(2012)DOI:doi:10.1038/nnano.2011.242Published online 28 December 2011 A four-level conductance switch can be created by using a scanning tunnelling microscope to remove a hydrogen atom from the central cavity of a porphyrin molecule. Subject terms: * Molecular machines and motors * Surface patterning and imaging Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The basic idea of molecular electronics — using molecules as components in electrical circuitry — has been verified experimentally by using molecules as diodes, switches and transistors1, 2, 3. The use of molecules in electronics is conceptually appealing because the required function can be encoded into the molecule through chemical synthesis, making molecules an ideal tunable nanoscale building block. However, the molecular components have to be interfaced with the macroscopic world and this places a number of constraints on their design. In molecular switches, for example, the switching action should not change the overall size of the molecule because this will disturb the external contacts to the switch. Ideally, small changes of the atomic structure of the molecule should lead to changes in the electronic properties of the whole molecule that are large enough to allow the different states to be distinguished from each other by measuring the electric current through the molecule. The switching unit should also be protected in some way so that the switch is not affected by changes in its immediate environment. In addition to these strict requirements, it might also be beneficial to have access to more than two levels (states) in a switch. Furthermore, if the switching unit is part of a molecule that already has a well-developed chemistry, this could help broaden the range of different molecular architectures that the switch can be incorporated into. Writing in Nature Nanotechnology, Willi Auwärter and colle! agues at the Technical University, Munich, now report using a porphyrin molecule to create a four-level molecular switch that fulfils all of the above criteria4. Porphyrins are flat organic molecules composed of four modified pyrrole (C4H4NH) subunits connected by CH bridges. The molecules have a central cavity that can incorporate a metal ion or two hydrogen atoms. When the porphyrin has two central hydrogen atoms — a free-base porphyrin — the two protons can transfer between the two pairs of opposing nitrogens in the cavity of the molecule, a reaction know as tautomerization. It has also been shown previously that a related molecule (a phthalocyanine) can function as a tautomerization-based two-level molecular switch5. To upgrade such two-state systems, Auwärter and colleagues used voltage pulses from the tip of a low-temperature scanning tunnelling microscope (STM) to controllably remove one of the hydrogens from the cavity of a porphyrin molecule that was deposited on a silver surface (Fig. 1a). This allowed the remaining central hydrogen to then hop between the four pyrrole rings giving rise to a four-level molecular switch! based on the transfer of a single proton. Figure 1: Atomic control of molecular switches based on porphyrin molecules. , An STM is used to selectively remove one of the two hydrogen atoms (shown in green) from the central cavity of a free-base porphyrin molecule. The position of the remaining hydrogen atom can be switched between the four different positions that give rise to four distinct electric current levels through the molecule. , Porphyrins that can be linked together to from long chain-like molecules with multiple cavities, such as butadiyne-linked oligo-porphyrins6 () and meso-meso-linked oligo-porphyrins7 (), could also prove useful in molecular electronics. * Full size image (203 KB) The above process is initiated by electrons from the STM tip that have sufficient energy to excite certain molecular vibrations and drive the molecule over the reaction's activation-energy barrier. The switching reaction only occurs with high STM bias voltages and STM imaging at low bias voltages can therefore be used to accurately record the position of the hydrogen atom. Furthermore, the position of the hydrogen atom affects the symmetry of the molecular orbitals and determines the current measured through the STM tip positioned anywhere over the molecule. That is, the switching action is confined to the central cavity of the molecule, but it is reflected in electronic changes over the entire molecule, which would lead to different current levels if the switch was coupled to external leads. The switch is also robust and can function directly on a metal surface. Despite the progress that has been made in developing new molecular switches and the increased atomic control of the switching process itself, it is unlikely that devices based on single molecular switches will form the basis of a viable post-CMOS (complementary metal-oxide-semiconductor) technology. This is due in particular to the formidable problems that exist in reliably wiring single molecules with mesoscopic leads. However, if several active molecular components can be coupled in a controlled manner, more complex molecular devices could be constructed from modular building blocks. In the end, only the complete device would then have to be wired up to the external world. For example, a molecule-based logic gate could be built from suitably coupled molecular switches that control the charge transport through the system. This would allow basic logic operations (AND, OR and so on) to be carried out on a molecular circuit. The controlled coupling of active molecular-scale building blocks is naturally demanding, and sufficient levels of control perhaps requires the use of covalent bonds defined through chemical synthesis. In this regard, porphyrins have a particular strength because their chemistry is well developed. For example, there are strategies for synthesizing covalently linked oligo-porphyrins based on butadiyne-6 or meso-meso-linked7 porphyrins (Fig. 1b,c). These molecules have been synthesized in the past because of their useful properties in organic optoelectronics, for example as near-infrared dyes and organic conductors. Their conductivity stems from the conjugated structure, which also suggests that they could act as molecular wires. Such species could be used to form well defined, covalently connected one- and two-dimensional arrays of molecular switches. By making this chemical treasure trove available for molecular electronics, the work of Auwärter and co-workers could lead to! the construction of novel computing units at the molecular scale. References * References * Author information * Chen, F., Hihath, J., Huang, Z., Li, X. & Tao, N. J.Annu. Rev. Phys. Chem.58, 535–565 (2007). * ChemPort * ISI * PubMed * Article * Van der Molen, S. J. & Liljeroth P.J. Phys. Condens. Matter22, 133001 (2010). * ChemPort * PubMed * Article * Song, H., Reed, M. A. & Lee, T.Adv. 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Nanofluidics: Neither shaken nor stirred
- Nat Nanotechnol 7(1):6-7 (2012)
Nature Nanotechnology | News and Views Nanofluidics: Neither shaken nor stirred * Aldo Jesorka1 * Owe Orwar1, 2 * Affiliations * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:6–7Year published:(2012)DOI:doi:10.1038/nnano.2011.236Published online 28 December 2011 Bioinspired nanoreactor arrays can be used to controllably mix subattolitre volumes of liquids. Subject terms: * Nanofluidics * Nanomaterials Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The controlled mixing of reactants and catalysts is an important first step in carrying out chemical and biochemical reactions, but is a significant practical challenge when using ultrasmall volumes of material. Reducing the scale on which a reaction takes place decreases the consumption of reagents and allows the products of the reaction to be screened with high throughput. Working at the nanoscale also allows researchers to perform single-molecule studies that can yield insights that are difficult to obtain when using larger volumes. Therefore, considerable effort has been devoted to developing reactors with ultrasmall volumes1, 2. Biologically inspired nanoreactors are of particular interest because they could be used to control volumes much smaller than 10−12 l, which is the typical limit of microfabricated fluidic devices. Writing in Nature Nanotechnology, Dimitrios Stamou and colleagues at the University of Copenhagen now report an artificial bioreactor system compos! ed of unilamellar vesicles that can mix aqueous volumes as small as 10−19 l in a reproducible and parallelized fashion3. Microfluidics and microelectrofluidics that use channel- or droplet-based4, 5 protocols are well-established. However, the engineering of chemical reactor systems with nanoscale dimensions is still at an early stage of developement6, 7, 8. There are several elegant examples of solid-state reactor systems that operate at this scale9, 10, but such structures often use top-down fabrication techniques that require traditional clean-room processes and can therefore be difficult to implement. Thus, creating nanoreactors using dynamic self-assembly or self-organizing materials would be significantly simpler. The self-assembly of such structures is not exactly new. The biological cell is capable of precisely mixing, processing and separating catalysts, reactants and products, and achieves this using nanoscale vesicular and tubular lipid-membrane containers. Artificial nanoreactors have yet to reach such levels of structural complexity and diversity, but by borrowing operating principles from nature a number of notable technological advances have been achieved11, 12. Stamou and colleagues have developed a platform that uses phospholipid vesicles to mix subattolitre (1 attolitre = 10−18 litre) volumes of liquids (Fig. 1). Repeated reactions are achieved by placing one set of reactants in target vesicles that are immobilized on a surface, and placing a complementary set of reactants in mobile cargo vesicles. The target vesicles are immobilized by patterning a glass surface with the protein streptavidin, which binds instantly and tightly to biotin, a small organic molecule attached to the surface of the target vesicles. The fusion of the vesicles and the formation of the products are monitored using fluorescence microscopy. Figure 1: Simplified schematic illustrating sequential enzymatic reactions initiated by the fusion of nanoscale phospholipid vesicles. , The target vesicles (blue spheres with orange outer layer) have diameters of ~400 nm, are immobilized on a surface, contain a hydrolase enzyme (the catalyst; dark-blue shapes), and have a positively charged membrane. The cargo vesicles (yellow) are mobile, contain an enzyme substrate (the reactant; white circles), and have a negatively charged membrane. The membranes of the target and cargo vesicles are also fitted with the acceptor and donor moieties of a FRET dye. When a suspension containing the cargo vesicles is deposited on the surface, the target and cargo vesicles fuse, and fluorescent emission from the FRET dye is observed. The enzyme substrate then enters the target vesicle and reacts with the catalyst to produce fluorescein (green circles), which can be detected through its fluorescent emission. ,, By depositing a second suspension containing different cargo vesicles on the same target vesicles, a second set of reactions can be initiated. Stamou and colleagues3 r! eported up to four consecutive reactions. , After all the reactions are complete the target vesicles are now mostly neutral and highly fluorescent. * Full size image (134 KB) Previously, there were no reliable means to initiate chemical reactions in containers of such a small size. For larger, micrometre-sized vesicles, which typically encapsulate picolitre volumes, this has been achieved by direct injection, electrofission, electroporation or nanotube-mediated merging13. Stamou and colleagues were able to carry out the controlled fusion of their nanocontainers by functionalizing the target and cargo vesicles with lipids of opposite charge to create an attractive interaction between them. The target vesicles are loaded with alkaline phosphatase — a hydrolase enzyme capable of catalysing the removal of phosphate groups from organic molecules — and their membranes are fitted with the acceptor moiety of a fluorescence resonance energy transfer (FRET) dye. The cargo vesicles contain the enzyme substrate — a fluorescein derivative in which the emission of light is blocked by phosphate groups — and their membranes are fitted with the donor moiety of the FRET dye. When the cargo and target vesicles fuse, it is possible to excite the FRET donor and simultaneously detect emission from the acceptor (when the acceptor and donor moieties come into close proximity and energy is transferred between them). It also becomes possible to detect product emission (at a different wavelength) once the hydrolase enzyme has catalysed the removal of the phosphate groups from the fluorescein. Approximately 88% of the surface-immobilized containers generated product. Furthermore! , up to four consecutive fusion-reaction events could be performed by tuning the size ratio and charge balance between the target and cargo containers. The Copenhagen team also illustrates the versatility of the approach by carrying out two further catalytic reactions; one involving a membrane-activated lipase from a thermophile source and the other using a horseradish peroxidase. Efficient, precise and reproducible solution processing is a requirement of all modern bioanalytical applications, and the work of Stamou and colleagues could be useful in a number of these applications. Assays used in medical diagnostics, and the rapid screening of large chemical libraries to discover novel biologically relevant chemical entities, would, in particular, benefit from an ultrasmall volume fluidic platform technology. However, a number of challenges must be overcome for such developments to become possible. These include improving control over the reactor geometry and increasing the percentage of active reactors, as well as developing simpler surface immobilization schemes and improving the shelf-life of the devices. Methods to transfer or harvest products from such vesicle reactors in a similarly controlled way would be highly desirable. References * References * Author information * Renggli, K.et al. Adv. Funct. Mater.21, 1241–1259 (2011). * ChemPort * ISI * Article * Van Oijen, A. M.Curr. Opin. Biotechnol.22, 75–80 (2011). * ChemPort * ISI * PubMed * Article * Christensen, S. M., Bolinger, P-Y., Hatzakis, N. S., Mortensen, M. W. & Stamou, D.Nature Nanotech.7, 51–55 (2012). * Article * Whitesides, G. M.Nature442, 368–373 (2006). * ChemPort * ISI * PubMed * Article * Wheeler, A. R.Science322, 539–540 (2008). * ChemPort * ISI * PubMed * Article * Monteiro, M. J.Macromolecules43, 1159–1168 (2010). * ChemPort * ISI * Article * Tanner, P.et al. FEBS Lett.585, 1699–1706 (2011). * ChemPort * ISI * PubMed * Article * Bolinger, P. Y., Stamou, D. & Vogel, H.J. Am. Chem. Soc.126, 8594–8595 (2004). * ChemPort * ISI * PubMed * Article * Levene, M. J.et al. Science299, 682–686 (2003). * ChemPort * ISI * PubMed * Article * Bruckbauer, A., Zhou, D., Ying, L., Abell, C. & Klenerman, D.Nano Lett.4, 1859–1862 (2004). * ChemPort * ISI * Article * Collier, C. P. & Simpson, M. L.Curr. Opin. Biotechnol.22, 516–526 (2011). * ChemPort * ISI * PubMed * Article * Comellas-Aragones, M.et al. Nature Nanotech.2, 635–639 (2007). * ChemPort * Article * Jesorka, A.et al. Nature Protoc.6, 791–805 (2011). * ChemPort * ISI * Article Download references Author information * References * Author information Affiliations * Department of Chemical and Biological Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden * Aldo Jesorka & * Owe Orwar * Sanofi-Aventis R&D, 91385 Chilly-Mazarin Cedex, France * Owe Orwar Corresponding author Correspondence to: * Owe Orwar Author Details * Aldo Jesorka Search for this author in: * NPG journals * PubMed * Google Scholar * Owe Orwar Contact Owe Orwar Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Nanoimaging: Image contrast using time
- Nat Nanotechnol 7(1):8-9 (2012)
Nature Nanotechnology | News and Views Nanoimaging: Image contrast using time * Kevin Tvrdy1 * Michael S. Strano1 * Affiliations * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:8–9Year published:(2012)DOI:doi:10.1038/nnano.2011.241Published online 28 December 2011 Laser-based imaging can distinguish between semiconducting and metallic nanotubes in vitro and in vivo, offering a way to study the interactions of carbon nanostructures in biological systems without the use of labels. Subject terms: * Carbon nanotubes and fullerenes * Surface patterning and imaging Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg "Astronomy is not like a physics lab," said Brian Schmidt shortly after it had been announced that he had shared the 2011 Nobel Prize in Physics1. "You can't design an experiment. You need to look up into the heavens, and sort of figure out what the cosmos has given you." What Schmidt and his fellow laureates, Saul Perlmutter and Adam Reiss, did in their prize-winning work was something that astronomers have been doing for decades — they looked back in time. But what they discovered shocked the world of physics and astronomy — the expansion of the universe was accelerating. Traditionally, biologists have designed microscopy experiments around two- or three-dimensional spatial imaging. Now, writing in Nature Nanotechnology, Ji-Xin Cheng and co-workers2 at Purdue University — much like this years' winners of the Nobel Prize in Physics — show that using the fourth dimension of time can lead to a new form of image contrast in biological samples. They used a method called pump–probe spectroscopy3 to distinguish between metallic and semiconducting single-walled carbon nanotubes in vitro (in cells) and in vivo (in mice), offering a technique to better understand the interactions of carbon nanostructures with biological systems. Pump–probe spectroscopy is a dynamic technique that involves using a laser pulse (the pump) to perturb the sample, and a second pulse (the probe) to measure the sample after it has been perturbed. To use time as a dimension, Cheng and colleagues spatially overlapped the pump beam (which is modulated at a controlled frequency) with the probe beam, which is monitored at the same frequency (Fig. 1). A lock-in amplifier was used to measure the phase shift (the time delay) between the pump and probe pulse trains. This phase shift, which is insensitive to the broad range of bandgaps in a sample of unsorted nanotubes, was used to identify whether the nanotubes were metallic or semiconducting. Figure 1: Schematic showing the experimental set-up used to image carbon nanotubes in the time domain. The intensity of the pump beam (blue) is modulated by a Pockels cell at a controlled frequency of 1.13 MHz. The pump beam perturbs the electronic states of the carbon nanotubes and the enhanced (shown) or reduced absorption of the probe beam (red) is indicative of the semiconducting or metallic nature of the nanotubes. When the overlapping pump and probe beams emerge from the sample (blue rectangle), the phase shift between the two beams, which depends on the nature of the material in the sample, is measured by the lock-in amplifier. The nanotubes can be distinguished because semiconducting nanotubes produce a positive signal, whereas metallic nanotubes produce a negative signal. Because both signals are independent of the thermal lens signals from red blood cells, the technique can be used for in vivo imaging with submicrometre resolution. * Full size image (260 KB) Cheng and colleagues first tested the spatial resolution of the method by obtaining a phase-shift map of aligned nanotubes grown on a quartz substrate. A line-scan across two nanotubes, one of which was metallic and the other semiconducting, revealed a lateral resolution of less than 400 nm for both tubes. At this spatial resolution, they studied how a sample of DNA-wrapped carbon nanotubes4 with different metallicity behaved inside an intact mammalian cell. It turns out that incubating the nanotube sample with cells for more than eight hours caused the metallic nanotubes to aggregate in the cell culture medium and on the cell surface, whereas no such aggregation of the semiconducting nanotubes was observed. Although the aggregation behaviours were different, both the semiconducting and metallic nanotubes showed similar trafficking mechanisms inside the cell. For example, both were actively transported into the cells by fusion with the cell membrane and were eventually retur! ned to the cell surface for expulsion from the cells. Because this imaging technique relies on relatively low laser power, the intracellular trafficking of the nanotubes could be monitored without the risk of photobleaching or photodamage5. Furthermore, the method could be used to image and track nanotubes in vivo. In biological samples, the signal of interest has to be detected against a high level of background noise produced by various biological components, particularly the red blood cells. Cheng and co-workers injected nanotubes into mice and monitored the nanotubes in a blood vessel in the mouse ear-lobe. Because the method can monitor the signals from the nanotubes and those from the red blood cells in separate lock-in detector channels, both signals could be observed at the same time without the need for signal deconvolution. The technique demonstrated by Cheng and co-workers is similar in some ways to transient absorption microscopy6, but the reported signal is unique, due to a lack of direct comparison between transmission of the probe pulse when there is a pump pulse with the transmission when there is no pump pulse. However, the origins of the phase differences measured by the Purdue team are still not completely understood2, 3. To fully utilize this technique, further investigations on the origin of the signal, its presence in other nanomaterials, and the type of quantitative data that can be drawn from it would be required. Being able to visualize and differentiate metallic and semiconducting nanotubes with submicrometre resolution and without any tissue damage will clearly have a big impact in various fields of nanotechnology and in cell biology. And as scientists, it is useful to remember that whether gazing into the heavens or squinting at the darkest corners of a living cell, doing so within the time domain offers an entirely new, and sometimes unforeseen, dimension of insight. References * References * Author information * http://www.nobelprize.org/nobel_prizes/physics/laureates/2011/schmidt-telephone.html * Tong, L.et al. Nature Nanotech.7, 56–61 (2012). * Article * Jung, Y.et al. Phys. Rev. Lett.105, 217401 (2010). * ChemPort * PubMed * Article * Zheng, M.et al. Nature Mater.2, 338–342 (2003). * ChemPort * ISI * Article * Lin, Y.et al. J. Mater. Chem.14, 527–541 (2004). * ChemPort * Article * Berera, R., van Grondelle, R. & Kennis, J. T. M.Photosynth. Res.101, 105–118 (2009). * ChemPort * PubMed * Article Download references Author information * References * Author information Affiliations * Kevin Tvrdy and Michael S. Strano are in the Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, USA Corresponding author Correspondence to: * Michael S. Strano Author Details * Kevin Tvrdy Search for this author in: * NPG journals * PubMed * Google Scholar * Michael S. Strano Contact Michael S. Strano Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Bionanoscience: Nanoparticles in the life of a cell
- Nat Nanotechnol 7(1):9-10 (2012)
Nature Nanotechnology | News and Views Bionanoscience: Nanoparticles in the life of a cell * Huw Summers1Journal name:Nature NanotechnologyVolume: 7,Pages:9–10Year published:(2012)DOI:doi:10.1038/nnano.2011.207Published online 06 November 2011 The cycle of cell birth, growth and division can affect the uptake and dilution of nanoparticles in cells, suggesting that the evolution of nanoparticle dose within a cell population is linked to the life cycle of cells. Subject terms: * Nanomedicine * Nanoparticles * Environmental, health and safety issues Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nanomedicine promises to use nanotechnology to treat diseases at the cellular level using drug therapies that are targeted to malignant tissues. Over the past decade, new nanoparticles have been developed for drug delivery, imaging, the detection of biomarkers, and other diagnostic and therapeutic applications1. It has been shown that nanomaterial properties such as size and surface charge can affect the dose of nanoparticles that is delivered into a biological system2. However, more recently it has been realized that cells are active components in this delivery and uptake process, and that the biology of mammalian cells is therefore extremely important in determining the pharmacology of nanodrugs. Now, writing in Nature Nanotechnology, Kenneth Dawson and colleagues at University College Dublin report that the cycle of cell birth, growth and proliferation has an important role in determining nanoparticle dose3, with cells early in the cell growth cycle accumulating more nanoparticles than those later in the cycle. The cell growth cycle, which leads to cell division and replication, consists of four phases: G0/G1, S, G2 and M. In most studies on nanoparticle uptake, cells are exposed to fluorescently labelled nanoparticles and the fluorescence of the nanoparticles inside the cells (as a result of uptake) is measured by flow cytometry. However, this measurement gives the mean fluorescence averaged over all the cells, each in different phases of their life cycle. Because various cellular processes (such as expression of membrane proteins) vary in each phase of the cell cycle, it is important to understand how the different phases may affect nanoparticle uptake. To directly correlate the dose of fluorescent polystyrene nanoparticles with the phase of the cell cycle on a cell-by-cell basis, Dawson and co-workers exposed cells to different concentrations of nanoparticles for different periods of time, and resolved the population of treated cells into different phases of the cell cycle by monitoring DNA synthesis. The cell nucleus is stained with a fluorescent dye that binds to DNA to give a measure of the total nuclear content of the cell. As cells pass from initial growth (G0/G1 phase) to synthesis of DNA (S phase), the fluorescence intensity of the cell nucleus doubles and then subsequently halves as the cells divide into daughter cells during the G2 and M phases. This generates a distribution of cell fluorescence that resolves the total nuclear fluorescent signal from flow cytometry measurements into different phases of the cell cycle for the population of nanoparticle-treated cells examined4. Thus, the nanoparticle fluorescence in! individual cells can be directly related to their nuclear fluorescence to obtain measures of particle dose and cell cycle position. Although the dilution of nanoparticle dose through cell division has been studied previously5, these are the first detailed measurements of the kinetics of how accumulation of nanoparticle dose competes with its dilution when the cell divides. Dawson and co-workers find that the rate of uptake of nanoparticles is constant across the cell cycle, and so the total accumulated dose increases linearly with time until a cell divides, at which point the dose is shared between the two daughter cells. Under these conditions, the maximum nanoparticle dose delivered to a given cell is dependent on its age at the start of nanoparticle exposure; new-born cells will accumulate nanoparticles across the whole of their life cycle (approximately 22 hours for the cancer cells used in the study), whereas older cells will have a limited accumulation period before the dose is reduced by division (Fig. 1). Figure 1: The cell cycle is a series of events that lead to cell division and replication. As the cycle progresses from left to right, cells prepare for cell division. , When cells (green ovals) in the early phase of the cycle are exposed to nanoparticles (red dots), there is plenty of time for the nanoparticle dose to increase before they are ready to divide. , Cells in the late phase of the cycle have less time to accumulate nanoparticles before cell division occurs, and the division process further reduces the nanoparticle dose. * Full size image (161 KB) By specifically labelling S-phase cells and tracking their progression through the cell cycle, they show that the nanoparticle dose is constant until the point of cell division. This confirms that dose dilution is due to cell proliferation rather than particle expulsion from the cells. Further evidence for the linear dose accumulation hypothesis is provided by experiments in which the whole cell population is forced into the early phase of the cell cycle by depriving them of serum. In this case, the maximum nanoparticle dose showed an increase because all cells accumulated particles for their entire life cycle. Mathematical modelling of the dose kinetics corroborates the experimental data. The evolution of the nanoparticle dose within a cell population is intrinsically linked to the point in the life cycle of the cells at which the nanoparticles are introduced. These findings are particularly important for the development of nanotherapeutics that deliver nanoparticles to tumour cells, either as direct anticancer agents or as delivery vectors for other drugs6. As cancer cells have a higher rate of proliferation, nanoparticles may be diluted more rapidly and this can affect the dose. Knowing the phase in which the majority of the cells are in may in effect help us deliver an optimum dose of drugs. In future work, we will need to unravel how the complex behaviour of an active biological system interacts with the molecular dynamics of nanoparticles, and taking into account the life cycle of cells is the first step. Recent work on the variability of viral infection across a colony of cells7 highlights the need to start considering cell–nanoparticle interactions by viewing cells within the context of a community. The cell's position within the web of interactions found in a cohesive colony, such as a tumour, may affect individual cell behaviour through the spatial, temporal and lineage relationships that link populations of cells. It is only with this community perspective that full knowledge of the impact of nanoparticles on the life of cells will be gained. References * References * Author information * Murthy, S. K.Int. J. Nanomed.2, 129–141 (2007). * ChemPort * ISI * Hardman, R.Environ. Health Persp.114, 165–172 (2006). * ISI * Article * Kim, J. A., Åberg, C., Salvati, A. & Dawson, K. A.Nature Nanotech.http://dx.doi.org/10.1038/nnano.2011.191 (2011). * Krishnan, A.J. Cell Biol.66, 188–193 (1975). * ChemPort * ISI * PubMed * Article * Summers, H. D.et al. Nature Nanotech.6, 170–174 (2011). * ChemPort * Article * Ferrari, M.Nature Rev. Cancer5, 161–171 (2005). * Article * Snijder, B.Nature461, 520–523 (2009). * ChemPort * ISI * PubMed * Article Download references Author information * References * Author information Affiliations * Huw Summers is in the Centre for Nanohealth, College of Engineering, Swansea University, Singleton Park, Swansea SA2 8PP, UK Corresponding author Correspondence to: * Huw Summers Author Details * Huw Summers Contact Huw Summers Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
The properties and applications of nanodiamonds
- Nat Nanotechnol 7(1):11-23 (2012)
Nature Nanotechnology | Review The properties and applications of nanodiamonds * Vadym N. Mochalin1 * Olga Shenderova2 * Dean Ho3, 4 * Yury Gogotsi1 * Affiliations * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:11–23Year published:(2012)DOI:doi:10.1038/nnano.2011.209Published online 18 December 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nanodiamonds have excellent mechanical and optical properties, high surface areas and tunable surface structures. They are also non-toxic, which makes them well suited to biomedical applications. Here we review the synthesis, structure, properties, surface chemistry and phase transformations of individual nanodiamonds and clusters of nanodiamonds. In particular we discuss the rational control of the mechanical, chemical, electronic and optical properties of nanodiamonds through surface doping, interior doping and the introduction of functional groups. These little gems have a wide range of potential applications in tribology, drug delivery, bioimaging and tissue engineering, and also as protein mimics and a filler material for nanocomposites. View full text Subject terms: * Nanomaterials * Nanomedicine * Synthesis and processing Figures at a glance * Figure 1: Detonation synthesis of nanodiamonds. , To synthesize nanodiamonds, explosives with a negative oxygen balance (for example a mix of 60 wt% TNT (C6H2(NO2)3CH3) and 40 wt% hexogen (C3H6N6O6)) are detonated in a closed metallic chamber in an atmosphere of N2, CO2 and liquid or solid H2O. After detonation, diamond-containing soot is collected from the bottom and the walls of the chamber. , Phase diagram showing that the most stable phase of carbon is graphite at low pressures, and diamond at high pressures, with both phases melting when at temperatures above 4,500 K (with the precise melting temperature for each phase depending on the pressure). The phase diagrams for nanoscale carbon are similar, but the liquid phase is found at lower temperatures38, 39. During detonation, the pressure and temperature rise instantaneously, reaching the Jouguet point (point A), which falls within the region of liquid carbon clusters of 1–2 nm in size for many explosives. As the temperature and pressure decrease along the isentrope! (red line), carbon atoms condense into nanoclusters, which further coalesce into larger liquid droplets and crystallize39. When the pressure drops below the diamond–graphite equilibrium line, the growth of diamond is replaced by the formation of graphite. , Schematic of the detonation wave propagation showing (I) the front of the shock wave caused by the explosion; (II) the zone of chemical reaction in which the explosive molecules decompose; (III) the Chapman–Jouguet plane (where P and T correspond to point A in Fig. 1b, indicating the conditions when reaction and energy release are essentially complete); (IV) the expanding detonation products; (V) the formation of carbon nanoclusters; (VI) the coagulation into liquid nanodroplets; and (VII) the crystallization, growth and agglomeration of nanodiamonds39. * Figure 2: Structure of a single nanodiamond particle. , Schematic model illustrating the structure of a single ~5-nm nanodiamond after oxidative purification. The diamond core is covered by a layer of surface functional groups, which stabilize the particle by terminating the dangling bonds. The surface can also be stabilized by the conversion of sp3 carbon to sp2 carbon. A section of the particle has been cut along the amber dashed lines and removed to illustrate the inner diamond structure of the particle. , Close-up views of two regions of the nanodiamond shown in . The sp2 carbon (shown in black) forms chains and graphitic patches (). The majority of surface atoms are terminated with oxygen-containing groups (; oxygen atoms are shown in red, nitrogen in blue). Some hydrocarbon chains (green, lower left of ) and hydrogen terminations (hydrogen atoms are shown in white) are also seen. , Each nanodiamond is made up of a highly ordered diamond core. Some nanodiamonds are faceted, such as the one shown in this transmission electr! on micrograph, whereas most have a rounded shape, as shown in . The inset is a fast Fourier transform of the micrograph, which confirms that this nanodiamond has a highly ordered diamond core. Panel , reproduced with permission from ref. 19, © 2011 ACS. * Figure 3: Raman spectroscopy and structure of nanodiamond. Electron micrographs showing detonation soot (bottom), purified nanodiamond (middle) and oxidized nanodiamond (top). The diamond cores in detonation soot seem to be completely covered by graphitic shells, and this is confirmed by the Raman spectrum (black line), which is dominated by the G-band of graphitic carbon at 1,590 cm−1 and has no diamond peak. Purified nanodiamonds are partially covered by a thin layer of graphite, so a diamond peak can be seen at 1,328 cm−1 in the Raman spectrum (blue line). This thin layer of graphite is completely removed by oxidation in air, so the Raman spectrum of oxidized nanodiamonds has an even stronger diamond peak (red line). The diamond peak in the Raman spectrum of purified and air oxidized nanodiamond (inset ) is a combination of peaks originating from larger (I) and smaller (II) coherence scattering domains. The phonon confinement model84 gives a good fit (blue line) to experimental data (open circles). The broad feature at 1,500�! ��1,800 cm−1 in the spectrum of air oxidized nanodiamond (inset ) originates from surface functional groups and adsorbed molecules, with some contribution from sp2 carbon atoms. The Raman spectra were recorded following excitation by an ultraviolet laser (325 nm). * Figure 4: Optical properties of nanodiamonds. , De-aggregation by salt-assisted dry milling reduces the size of diamond particles from ~1 μm to less than 10 nm (), and makes suspensions of the particles both darker and more transparent (). The changes in colour are not related to the presence of graphitic carbon56. , Photonic structures formed by centrifugation of suspensions of nanodiamonds in deionized water. , Covalently attaching ODA to nanodiamonds changes their optical properties. ND–ODA absorbs and re-emits light over a wide range of wavelengths, as can be seen in these excitation (purple) and emission (blue) spectra (). Moreover, and in contrast to non-functionalized nanodiamond, ND–ODA is strongly blue fluorescent when illuminated with ultraviolet light (). , ND–ODA can be used for bio-imaging, as illustrated by this confocal micrograph of the fluorescent scaffold made of ND–ODA–PLLA with 7F2 osteoblasts grown on it (see main text for details). Panel , reproduced with permission from ref. 62, © 2008! IOP. * Figure 5: Surface modification. Precise control over surface chemistry requires a sample of purified nanodiamond with only one kind of functional group attached to its surface. Nanodiamond terminated with carboxylic groups (ND–COOH; green region) is a common starting material (and is made by air oxidation or ozone treatment of nanodiamond, followed by treatment in aqueous HCl to hydrolyse anhydrides and remove metal impurities). The surface of ND–COOH can be modified by high-temperature gas treatments (red) or ambient-temperature wet chemistry techniques (blue). Heating in NH3, for example, can result in the formation of a variety of different surface groups including NH2, C–O–H, C≡N and groups containing C=N (refs 9, 48). Heating in Cl2 produces acylchlorides, and F2 treatment forms C–F groups (not shown)67, 137, 138. Treatment in H2 completely reduces C=O to C–O–H and forms additional C–H groups. Hydroxyl (OH) groups may be removed at higher temperatures or with longer hydrogenation tim! es, or by treatment in hydrogen plasma66. Annealing in N2, Ar or vacuum completely removes the functional groups and converts the nanodiamonds into graphitic carbon nano-onions139, 140. A wide range of surface groups and functionalized nanodiamonds can also be produced using wet chemistry treatments. * Figure 6: Advanced atomic-level composite design with nanodiamond. , Three examples of the interfaces between nanodiamond and different matrices. Nanodiamond can bind to SiC through C–Si bonds between the surface of the nanodiamond and the Si atoms in the SiC to produce ND–SiC (left). Carboxylic groups present on the nanodiamond surface can form salts by ion exchange reactions with different metal ions, such as Cu2+ (middle; ref. 141). Metal ions can be later reduced, forming an atomically thin metal layer around the particle. These metallized particles can be used as a means to disperse nanodiamonds in metals that do not wet carbon, and also to produce wear-resistant ND–Cu sliding contacts. Nanodiamonds with surface carboxylic groups can be functionalized through covalent attachment of ODA by amide bond formation (right). , Stress–strain curves for six ND–ODA–PLLA composites that contain different amounts of ND–ODA11. The Young's modulus of a given composite is proportional to the slope of its stress–strain curve. , Aminate! d nanodiamond, produced through covalent attachment of ethylenediamine to carboxylic groups on the surface of the nanodiamond, can replace traditional epoxy curing agents (amines) in reaction with epoxy resin. This results in the covalent incorporation of the nanodiamond into the epoxy polymer network at a molecular level, improving the mechanical properties of the polymer matrix14. * Figure 7: Nanodiamonds and drug delivery. , DNA can be electrostatically attached to nanodiamonds by first covering negatively charged carboxylated nanodiamonds with positively charged PEI800 molecules. A similar electrostatic binding strategy has been used to attach siRNA and doxorubicin (Dox) to nanodiamond104. , Schematic representation of a proposed mechanism for ND–Dox complexes interacting with a cell. 1, Endocytosis of the ND–drug complexes. 2, Diffusion of free drug molecules across the cell membrane. 3, ABC transporter proteins efflux free drug molecules out of the cell, whereas ND–drug complexes are able to remain inside the cell and deliver a steady, lethal dose of the drug to the tumour. , Photographs of breast-cancer tumours after treatment with ND–Dox (top), Dox (middle) and a control (PBS; bottom). Two representative tumours are shown in each case. The large size of the tumours excised after long-term treatment with Dox or PBS illustrates a reduced ability of Dox to inhibit tumour growth owing! to the extreme resistance of the 4T1 breast cancer to chemotherapy. In contrast, treatment with ND–Dox clearly reduces the size of the tumours. Figure reproduced with permission from: , ref. 127, © 2009 ACS; , ref. 142, © 2011 AAAS; , ref. 104, © 2011 AAAS. Author information * Abstract * Author information Affiliations * Department of Materials Science and Engineering and A. J. Drexel Nanotechnology Institute, Drexel University, Philadelphia, Pennsylvania 19104, USA * Vadym N. Mochalin & * Yury Gogotsi * International Technology Center, Raleigh, North Carolina 27617, USA * Olga Shenderova * Departments of Biomedical and Mechanical Engineering, Northwestern University, Evanston, Illinois 60208, USA * Dean Ho * Institute for BioNanotechnology in Medicine (IBNAM) and Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, Illinois 60611, USA * Dean Ho Corresponding author Correspondence to: * Yury Gogotsi Author Details * Vadym N. Mochalin Search for this author in: * NPG journals * PubMed * Google Scholar * Olga Shenderova Search for this author in: * NPG journals * PubMed * Google Scholar * Dean Ho Search for this author in: * NPG journals * PubMed * Google Scholar * Yury Gogotsi Contact Yury Gogotsi Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Synthetically programmable nanoparticle superlattices using a hollow three-dimensional spacer approach
- Nat Nanotechnol 7(1):24-28 (2012)
Nature Nanotechnology | Letter Synthetically programmable nanoparticle superlattices using a hollow three-dimensional spacer approach * Evelyn Auyeung1, 2, 5 * Joshua I. Cutler2, 3, 5 * Robert J. Macfarlane2, 3 * Matthew R. Jones1, 2 * Jinsong Wu4 * George Liu4 * Ke Zhang2, 3 * Kyle D. Osberg1, 2 * Chad A. Mirkin1, 2, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:24–28Year published:(2012)DOI:doi:10.1038/nnano.2011.222Received 14 July 2011 Accepted 14 November 2011 Published online 11 December 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Crystalline nanoparticle arrays and superlattices with well-defined geometries can be synthesized by using appropriate electrostatic1, 2, 3, hydrogen-bonding4, 5 or biological recognition interactions6, 7, 8, 9, 10, 11. Although superlattices with many distinct geometries can be produced using these approaches, the library of achievable lattices could be increased by developing a strategy that allows some of the nanoparticles within a binary lattice to be replaced with 'spacer' entities that are constructed to mimic the behaviour of the nanoparticles they replace, even though they do not contain an inorganic core. The inclusion of these spacer entities within a known binary superlattice would effectively delete one set of nanoparticles without affecting the positions of the other set. Here, we show how hollow DNA nanostructures can be used as 'three-dimensional spacers' within nanoparticle superlattices assembled through programmable DNA interactions7, 11, 12, 13, 14! , 15, 16. We show that this strategy can be used to form superlattices with five distinct symmetries, including one that has never before been observed in any crystalline material. View full text Subject terms: * Molecular self-assembly * Synthesis and processing Figures at a glance * Figure 1: Use of a three-dimensional spacer in DNA-programmable crystallization of gold nanoparticles. , Schematic of the synthesis of three-dimensional spacer particles by crosslinking alkyne-modified DNA on the gold nanoparticle surface and subsequent dissolution of the gold nanoparticle template to create hollow particles (shown in grey). ,, Assembly using a non-self-complementary binary DNA linker system (red and blue strands) results in a bcc lattice when only SNA–AuNPs are used (), and in a simple cubic lattice when a spacer particle is used (). The shaded region surrounding the gold nanoparticle and spacer particles denotes the crosslinked layer between the DNA binding region and the gold (or hollow) core. * Figure 2: SAXS data for seven distinct gold nanoparticle superlattices and 'lattice X'. –, One- and two-dimensional X-ray scattering patterns (left and bottom right of each panel) and schematic unit cell (top right; crosslinked shell omitted) showing the formation of the following superlattices: bcc (); simple cubic (); AB2 (isostructural with AlB2) (); simple hexagonal (); graphite-type (); AB6 (isostructural with Cs6C60) (); bcc (); 'lattice X' (). Five of the seven lattices (,,,,) are made using a mixture of gold and hollow SNA particles. Red traces are the experimentally obtained scattering patterns and the black peaks are the theoretical scattering for each respective lattice. Higher reflections were not indexed for the purpose of clarity. * Figure 3: SAXS data for cubic lattices made from nanoparticles of different sizes. SAXS data with indexed reflections corresponding to a simple cubic lattice made from 5 nm gold nanoparticles (grey line), 10 nm gold nanoparticles (black) and 20 nm gold nanoparticles (red). A hollow SNA particle is incorporated into the centre of each unit cell. Crosslinked shells in the schematic unit cells are omitted for clarity. Lines between particles denote edges of the unit cell, not direct connections between gold nanoparticles. * Figure 4: TEM images of the AB6-type lattices. , AB6-type lattice formed from 20 nm and 10 nm gold nanoparticles. , A bcc lattice formed from 20 nm gold nanoparticles and 10 nm hollow SNA spacers. , Lattice X structure formed from 20 nm hollow SNA spacers and 10 nm gold nanoparticles. All scale bars, 200 nm. Lattice projections shown in the insets are outlined in the TEM images. A three-dimensional reconstruction of a thin (~100 nm) section of the lattice in was obtained from electron tomography. , Representative snapshot of TEM images obtained in the tilt series, where the hole was used as a reference point for alignment (scale bar, 200 nm). ,, Snapshots from the reconstructed lattice along the [100] zone axis () and [111] zone axis () of a bcc lattice. Insets: perfect bcc lattice along each respective zone axis. A unit cell in each reconstructed lattice is outlined in red for clarity. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work * Evelyn Auyeung & * Joshua I. Cutler Affiliations * Department of Materials Science and Engineering, Evanston, Illinois 60208-3113, USA * Evelyn Auyeung, * Matthew R. Jones, * Kyle D. Osberg & * Chad A. Mirkin * International Institute for Nanotechnology, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208-3113, USA * Evelyn Auyeung, * Joshua I. Cutler, * Robert J. Macfarlane, * Matthew R. Jones, * Ke Zhang, * Kyle D. Osberg & * Chad A. Mirkin * Department of Chemistry, Evanston, Illinois 60208-3113, USA * Joshua I. Cutler, * Robert J. Macfarlane, * Ke Zhang & * Chad A. Mirkin * Electron Probe Instrumentation Center, Northwestern University, Evanston, Illinois 60208-3113, USA * Jinsong Wu & * George Liu Contributions E.A. and J.I.C. designed the experiments, prepared the materials, collected and analysed the data, and wrote the manuscript. R.J.M. designed the experiments and collected and analysed the data. M.R.J. collected and analysed the data. J.W. and G.L. analysed data for the tomography experiments. K.Z. and K.D.O. designed the experiments. C.A.M. designed the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Chad A. Mirkin Author Details * Evelyn Auyeung Search for this author in: * NPG journals * PubMed * Google Scholar * Joshua I. Cutler Search for this author in: * NPG journals * PubMed * Google Scholar * Robert J. Macfarlane Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew R. Jones Search for this author in: * NPG journals * PubMed * Google Scholar * Jinsong Wu Search for this author in: * NPG journals * PubMed * Google Scholar * George Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Ke Zhang Search for this author in: * NPG journals * PubMed * Google Scholar * Kyle D. Osberg Search for this author in: * NPG journals * PubMed * Google Scholar * Chad A. Mirkin Contact Chad A. Mirkin Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (3,504 KB) Supplementary information Movies * Supplementary information (2,399 KB) Supplementary movie 1 * Supplementary information (2,308 KB) Supplementary movie 2 * Supplementary information (3,189 KB) Supplementary movie 3 Additional data
Direct visualization of large-area graphene domains and boundaries by optical birefringency
- Nat Nanotechnol 7(1):29-34 (2012)
Nature Nanotechnology | Letter Direct visualization of large-area graphene domains and boundaries by optical birefringency * Dae Woo Kim1, 3 * Yun Ho Kim1, 2, 3 * Hyeon Su Jeong1 * Hee-Tae Jung1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:29–34Year published:(2012)DOI:doi:10.1038/nnano.2011.198Received 12 September 2011 Accepted 13 October 2011 Published online 20 November 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The boundaries between domains in single-layer graphene1, 2, 3, 4 strongly influence its electronic properties5, 6, 7, 8, 9, 10, 11, 12. However, existing approaches for domain visualization, which are based on microscopy and spectroscopy2, 12, 13, 14, 15, 16, are only effective for domains that are less than a few micrometres in size. Here, we report a simple method for the visualization of arbitrarily large graphene domains by imaging the birefringence of a graphene surface covered with nematic liquid crystals. The method relies on a correspondence between the orientation of the liquid crystals and that of the underlying graphene, which we use to determine the boundaries of macroscopic domains. View full text Subject terms: * Electronic properties and devices * Molecular self-assembly * Nanometrology and instrumentation * Structural properties * Surface patterning and imaging * Synthesis and processing Figures at a glance * Figure 1: Schematic of 4-n-alkyl-4′-cyanobiphenyl (nCB) liquid crystals on graphene and TEM image of the graphene film and its domain boundary. , Liquid-crystal film on graphene transferred to various substrates. Graphene was transferred onto glass or SiO2/Si substrates. Bottom: Schematic of liquid crystal film, graphene and substrate, and molecular structure of nematic () liquid-crystal materials and the thermal transition temperature. , The graphene film was transferred on a holey carbon grid (optical microscopy (OM) image) and SAED patterns were taken from square regions; these indicate good long-range order. , Magnified image of the graphene film; a sharp and single hexagonal SAED pattern was obtained from the bright region. * Figure 2: Optical visibility of the domain boundaries of graphene using aligned liquid-crystal material (5CB) and birefringent colour transition while rotating the sample. , POM images of liquid crystal-coated graphene films on a SiO2/Si substrate. Although the domains or boundaries of the graphene are not observable without liquid crystal (inset, optical microscopy), the POM image shows graphene domains and boundaries on the SiO2/Si substrate. was spin-coated on the same sample, which was then heated to 40 °C and subsequently cooled to room temperature. , Liquid-crystal molecules have different orientations depending on the graphene domain, resulting in various birefringent colours. , When the sample in was rotated 30° in a clockwise direction, the greenish region (indicated by the red dashed circle) became dark, because the optical axis of the liquid-crystal molecules anchored on the graphene domain were now parallel to the polarizer direction. Reddish regions in (indicated by the yellow dashed circle) became white as the sample was rotated. ,, Schematic illustrations of and as liquid-crystal molecules are rotated (by rotation of the samp! le stage), resulting in a colour change. P, polarizer; A, analyser. * Figure 3: Schematic of liquid crystal alignment on the surface of the graphene. The alkyl chains of occupy alternate positions on the hexagons within the graphene surface. Graphene grown on the surface of the copper foil has multiple domains with different lattice orientations. The alignment directions of liquid-crystal molecules differ in accordance with the graphene domains. Red arrows indicate the aligned director field of the liquid crystal. Short yellow lines indicate liquid-crystal molecules lying (or planar anchoring) on the graphene film. * Figure 4: Thermal and electric-field recovery of liquid-crystal molecules (5CB) on graphene. , Liquid-crystal molecules aligned on the graphene. , Above the isotropic transition temperature (40 °C), the transmitted intensity of the polarized light is quite low, with the dark colour therefore representing the isotropic state. , As the sample is cooled, liquid-crystal molecules become re-aligned. , In an electric field (2 V µm−1), liquid-crystal molecules undergo a transition that results in a vertically aligned structure of the molecules. When the electric field is removed, the liquid-crystal molecules again become aligned. The inset in Fig. 4e shows a conoscopic interference pattern. * Figure 5: Relationships between copper domains and graphene domains. , Optical image of copper domains after graphene growth. To mark the selected region, gold (40 nm) was evaporated using an electron-beam evaporator. , POM image of graphene with liquid crystals; graphene has been transferred from the copper region of to the glass substrate. , Extracted boundaries of copper domains in overlapped on the POM image of . The shape and size of the graphene domains match those of the copper domains relatively well. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work * Dae Woo Kim & * Yun Ho Kim Affiliations * National Research Lab, for Organic Opto-Electronic Materials, Department of Chemical and Biomolecular Eng. (BK-21), Korea Advanced Institute of Science and Technology, Daejeon 305-701, Korea * Dae Woo Kim, * Yun Ho Kim, * Hyeon Su Jeong & * Hee-Tae Jung * Department of Biomedical Engineering, Washington University in St Louis, 1 Brookings Drive, St Louis, Missouri 63130, USA * Yun Ho Kim Contributions D.W.K., Y.H.K., H.S.J. and H-T.J. wrote the paper. D.W.K., Y.H.K. and H-T.J. conceived and directed the research. D.W.K. prepared graphene and carried out characterization using electron microscopy. D.W.K., Y.H.K. and H.S.J. carried out liquid-crystal cell experiments and interpreted liquid-crystal alignment on the graphene. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Hee-Tae Jung Author Details * Dae Woo Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Yun Ho Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Hyeon Su Jeong Search for this author in: * NPG journals * PubMed * Google Scholar * Hee-Tae Jung Contact Hee-Tae Jung Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (955 KB) Supplementary information Additional data
Mechanically controlled molecular orbital alignment in single molecule junctions
- Nat Nanotechnol 7(1):35-40 (2012)
Nature Nanotechnology | Letter Mechanically controlled molecular orbital alignment in single molecule junctions * Christopher Bruot1 * Joshua Hihath1, 2 * Nongjian Tao1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:35–40Year published:(2012)DOI:doi:10.1038/nnano.2011.212Received 20 September 2011 Accepted 31 October 2011 Published online 04 December 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Research in molecular electronics often involves the demonstration of devices that are analogous to conventional semiconductor devices, such as transistors and diodes1, but it is also possible to perform experiments that have no parallels in conventional electronics. For example, by applying a mechanical force to a molecule bridged between two electrodes, a device known as a molecular junction, it is possible to exploit the interplay between the electrical and mechanical properties of the molecule to control charge transport through the junction2, 3, 4, 5, 6, 7, 8. 1,4′-Benzenedithiol is the most widely studied molecule in molecular electronics9, 10, 11, 12, 13, 14, 15, 16, 17, 18, and it was shown recently that the molecular orbitals can be gated by an applied electric field11. Here, we report how the electromechanical properties of a 1,4′-benzenedithiol molecular junction change as the junction is stretched and compressed. Counterintuitively, the conductance increases ! by more than an order of magnitude during stretching, and then decreases again as the junction is compressed. Based on simultaneously recorded current–voltage and conductance–voltage characteristics, and inelastic electron tunnelling spectroscopy, we attribute this finding to a strain-induced shift of the highest occupied molecular orbital towards the Fermi level of the electrodes, leading to a resonant enhancement of the conductance. These results, which are in agreement with the predictions of theoretical models14, 15, 16, 17, 19, 20, also clarify the origins of the long-standing discrepancy between the calculated and measured conductance values of 1,4′-benzenedithiol, which often differ by orders of magnitude21. View full text Subject terms: * Electronic properties and devices Figures at a glance * Figure 1: Changes in conductance of BDT due to stretching. , Schematic of a molecular junction (top). Schematic energy diagram (bottom) showing how the energy of the HOMO changes relative to EF of the electrodes as electrode separation increases. , Characteristic conductance histograms at room temperature (black) and 4.2 K (red). Histograms offset for clarity. ,, Plots of conductance (in units of G0) versus electrode displacement measured at 4.2 K. For some junctions the conductance increases with displacement (), whereas for others the conductance–displacement curves are either flat or bowl-shaped (). Different colours in and represent different junctions, and the traces have been offset for clarity. * Figure 2: Differential conductance and IETS of BDT junctions as a result of stretching and compressing. , Plot of conductance G versus electrode displacement for a junction during repeated stretching and compressing at 4.2 K. , Differential conductance curves (G versus V) for positions 1–8 in . The curves show clear, reversible changes in asymmetry as the mechanical force changes. , IET spectra (d2I/dV2 versus V) also show reversible changes. Both the G–V curves and the IET spectra are offset for clarity. ,, Plots of rectification ratio at V = 0.2 V () and peak height ratio for the ±14 mV mode () versus electrode displacement. Red curves are fits to guide the eye. See Supplementary Information for all G–V curves and IET spectra for this junction, including the assignment of vibration modes to the observed peaks. * Figure 3: Conductance switching behaviour of two BDT junctions. , Plot of conductance G versus electrode displacement showing switching and increasing conductance behaviour. , Differential conductance (G–V) curves at the four different positions indicated in : the curve at position 3 is clearly more symmetric than at position 2. ,, IET spectra at positions 1 and 2 () and 3 and 4 () in , showing that changes in the conductance lead to changes in the intensity and shape of the peaks. IET spectra are plotted on the same scale and are offset for clarity. , Plot of conductance versus displacement for a different junction, showing the conductance first decreasing and then increasing after a switching event. , G–V curves from positions 1 and 2 in . All measurements performed at 4.2 K. * Figure 4: Exploring the energy levels of a molecular junction. , Plot of conductance versus electrode displacement of a BDT junction at 4.2 K recorded with the junction being stretched and compressed much faster than the plots shown in Figs 2 and 3. The conductance decreases when the junction is compressed, and then increases to a relatively high value when the junction is stretched. , Plots of current I versus bias voltage V at the three positions indicated in , recorded with V being swept much faster than the plots shown in Figs 2 and 3. Thin lines are fits to the data. , Plots of ln(I/V2) versus 1/V for three different values of the displacement (based on fits to the I–V curves in ). The height of the barrier that electrons have to tunnel through is determined by the transition voltage, which is the voltage corresponding to the minimum of each plot (indicated by arrows). The height of the barrier decreases as the molecule is stretched. Author information * Abstract * Author information * Supplementary information Affiliations * Center for Bioelectronics and Biosensors, Biodesign Institute, School of Electrical, Energy and Computer Engineering, Arizona State University; Tempe, Arizona 85287-5801, USA * Christopher Bruot, * Joshua Hihath & * Nongjian Tao * Department of Electrical and Computer Engineering, University of California Davis, Davis, California 95616, USA * Joshua Hihath Contributions N.J.T. conceived the experiment. C.B. and J.H. performed the experiment and analysed the data. C.B., J.H. and N.J.T. co-wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Nongjian Tao Author Details * Christopher Bruot Search for this author in: * NPG journals * PubMed * Google Scholar * Joshua Hihath Search for this author in: * NPG journals * PubMed * Google Scholar * Nongjian Tao Contact Nongjian Tao Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (1,746 KB) Supplementary information Additional data
A surface-anchored molecular four-level conductance switch based on single proton transfer
- Nat Nanotechnol 7(1):41-46 (2012)
Nature Nanotechnology | Letter A surface-anchored molecular four-level conductance switch based on single proton transfer * Willi Auwärter1, 2 * Knud Seufert1, 2 * Felix Bischoff1 * David Ecija1 * Saranyan Vijayaraghavan1 * Sushobhan Joshi1 * Florian Klappenberger1 * Niveditha Samudrala1 * Johannes V. Barth1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:41–46Year published:(2012)DOI:doi:10.1038/nnano.2011.211Received 13 June 2011 Accepted 31 October 2011 Published online 11 December 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The development of a variety of nanoscale applications1, 2 requires the fabrication and control of atomic3, 4, 5 or molecular switches6, 7 that can be reversibly operated by light8, a short-range force9, 10, electric current11, 12 or other external stimuli13, 14, 15. For such molecules to be used as electronic components, they should be directly coupled to a metallic support and the switching unit should be easily connected to other molecular species without suppressing switching performance. Here, we show that a free-base tetraphenyl-porphyrin molecule, which is anchored to a silver surface, can function as a molecular conductance switch. The saddle-shaped molecule has two hydrogen atoms in its inner cavity that can be flipped between two states with different local conductance levels using the electron current through the tip of a scanning tunnelling microscope. Moreover, by deliberately removing one of the hydrogens, a four-level conductance switch can be created. The res! ulting device, which could be controllably integrated into the surrounding nanoscale environment, relies on the transfer of a single proton and therefore contains the smallest possible atomistic switching unit. View full text Subject terms: * Molecular machines and motors * Surface patterning and imaging Figures at a glance * Figure 1: Double proton transfer in 2H-TPP on Ag(111). , Pseudo three-dimensional rendering of a high-resolution STM image of 2H-TPP adsorbed on Ag(111). , Corresponding model consistent with the NEXAFS data (cf. Supplementary Fig. S1) highlights the saddle-shaped deformation resulting in two inequivalent pairs of pyrrole rings (α-pyr, marked in orange, and κ-pyr) , STM image of configuration Hα (I = 0.1 nA, U = −0.2 V). , Model highlighting the saddle-shaped deformation and the position of the hydrogen pair in configuration Hα. , STM image of configuration Hκ (I = 0.1 nA, U = −0.2 V). , Model of configuration Hκ. , Spatial dependence of the switching rate displayed with colour-coded dots (recorded at −1.6 V and 2 nA). The highest rates (yellow markers) are observed above the α-pyr. , Current versus time trace recorded at −1.9 V at the position indicated in . A switching between two current levels representing the high (h) and low (l) conductance states is clearly discernible. * Figure 2: Sequential deprotonation of 2H-TPP on Ag(111). , STM image of 2H-TPP (I = 0.2 nA, U = −0.2 V). , STM image of 1H-TPP. , STM image of 0-TPP. –, Tentative models illustrating the 2H-TPP, singly deprotonated 1H-TPP and fully deprotonated 0H-TPP species. , I(t) trace recorded at the centre of 2H-TPP at 1.9 V. The sudden decrease in current represents the single deprotonation to 1H-TPP. * Figure 3: Visualization of the four proton positions in 1H-TPP on Ag(111). –, STM images (–) of the same 1H-TPP molecule in four configurations representing the hydrogen positions schematically shown in corresponding models – (I = 0.2 nA, U = −0.2 V). , Current trace recorded in a slightly asymmetric position on a κ-pyr position (marked by the dot in ). The four conductance levels are clearly discernible (I = 0.4 nA, U = −1.6 V). * Figure 4: Current dependence of switching rate S for 2H-TPP and 1H-TPP recorded on an α-pyr position. , S increases linearly with tunnelling current I, pointing to a one-electron process driving proton transfer. Every single data point represents one I(t) spectrum where the current is averaged over the whole spectrum. The absolute rate depends on tip geometry (see Supplementary Information). The tip used for this experiment yields a rate S2H-TPP of 3.0 ± 0.1 s−1 nA−1 at a constant voltage of −1.6 V. , Comparison of S for 2H-TPP and 1H-TPP for five molecules. The blue line represents the normalized fits for the 2H-TPP species. Normalization to one average rate for 2H-TPP was performed to ease the comparison to 1H-TPP as the absolute rates for 2H-TPP vary from molecule to molecule. The green and red lines show the corresponding rates for the same molecules measured with an identical tip after the first deprotonation. Although the rates are generally similar for 2H-TPP and 1H-TPP, the ratio S1H-TPP/S2H-TPP varies between 0.76 (dark green) and 1.36 (dark red). * Figure 5: Voltage dependence of the switching rate S for 2H-TPP and 1H-TPP excited on an α-pyr position. , Voltage dependences measured at constant currents of 0.5, 2 and 4 nA, respectively, showing a threshold for switching of ~500 mV followed by a sharp increase with similar slope for both polarities (all data points were normalized to 1 at −1.5 V using scaling factors of 0.28 and 0.13, respectively). , Characteristic scanning tunnelling spectra recorded above an α-pyr position of 2H-TPP representing the local density of states, which is clearly asymmetric for both polarities. The broad feature around 700 mV is identified as the LUMO, whereas no occupied resonance is observed at negative bias voltages. The discontinuities observed at elevated voltages of both polarities are effects of proton transfer. , Scheme sketching the stepwise proton transfer via a cis-like intermediate state for 2H-TPP (the phenyl groups are omitted for clarity; see text for discussion). The macrocycle deformation on adsorption potentially lifts the degeneracy of both trans-configurations. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work * Willi Auwärter & * Knud Seufert Affiliations * Physik Department E20, Technische Universität München, D-85748 Garching, Germany * Willi Auwärter, * Knud Seufert, * Felix Bischoff, * David Ecija, * Saranyan Vijayaraghavan, * Sushobhan Joshi, * Florian Klappenberger, * Niveditha Samudrala & * Johannes V. Barth Contributions K.S., W.A., F.B., D.E., S.V., S.J. and N.S. performed the STM experiments and analysed and interpreted the experimental data. F.K. supported the data analysis and contributed to the NEXAFS experiments. W.A., K.S. and J.V.B conceived the studies and co-wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Willi Auwärter Author Details * Willi Auwärter Contact Willi Auwärter Search for this author in: * NPG journals * PubMed * Google Scholar * Knud Seufert Search for this author in: * NPG journals * PubMed * Google Scholar * Felix Bischoff Search for this author in: * NPG journals * PubMed * Google Scholar * David Ecija Search for this author in: * NPG journals * PubMed * Google Scholar * Saranyan Vijayaraghavan Search for this author in: * NPG journals * PubMed * Google Scholar * Sushobhan Joshi Search for this author in: * NPG journals * PubMed * Google Scholar * Florian Klappenberger Search for this author in: * NPG journals * PubMed * Google Scholar * Niveditha Samudrala Search for this author in: * NPG journals * PubMed * Google Scholar * Johannes V. Barth Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (1,179 KB) Supplementary information Additional data
Hole spin relaxation in Ge–Si core–shell nanowire qubits
- Nat Nanotechnol 7(1):47-50 (2012)
Nature Nanotechnology | Letter Hole spin relaxation in Ge–Si core–shell nanowire qubits * Yongjie Hu1, 2, 4 * Ferdinand Kuemmeth2 * Charles M. Lieber1, 3 * Charles M. Marcus2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NanotechnologyVolume: 7,Pages:47–50Year published:(2012)DOI:doi:10.1038/nnano.2011.234Received 30 September 2011 Accepted 21 November 2011 Published online 18 December 2011 Abstract * Abstract * Author information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Controlling decoherence is the biggest challenge in efforts to develop quantum information hardware1, 2, 3. Single electron spins in gallium arsenide are a leading candidate among implementations of solid-state quantum bits, but their strong coupling to nuclear spins produces high decoherence rates4, 5, 6. Group IV semiconductors, on the other hand, have relatively low nuclear spin densities, making them an attractive platform for spin quantum bits. However, device fabrication remains a challenge, particularly with respect to the control of materials and interfaces7. Here, we demonstrate state preparation, pulsed gate control and charge-sensing spin readout of hole spins confined in a Ge–Si core–shell nanowire. With fast gating, we measure T1 spin relaxation times of up to 0.6 ms in coupled quantum dots at zero magnetic field. Relaxation time increases as the magnetic field is reduced, which is consistent with a spin–orbit mechanism that is usually masked by hyperfine ! contributions. View full text Subject terms: * Electronic properties and devices * Quantum information Figures at a glance * Figure 1: Spin qubit device based on a Ge–Si heterostructure nanowire. Scanning electron micrograph (with false colour) of a Ge–Si nanowire (horizontal) contacted by four palladium contacts (Sdd, Ddd, Ss, Ds, grey) and covered by a HfO2 gate dielectric layer. Top gates L, M and R (blue) induce a double quantum dot on the left device. Plunger gates LP and RP (orange) change the chemical potential of each dot independently, and side gates EL and ER (purple) improve electrical contact to the nanowire. A single quantum dot on the right half of the nanowire (isolated by chemical etching between Ddd and Ds) is capacitively coupled to a floating gate (green) and a tuning gate (yellow), and senses the charge state of the double dot. Inset: transmission electron microscope image of a typical nanowire with a single-crystal germanium core and an epitaxial silicon shell. * Figure 2: Zeeman splitting of confined holes in a single quantum dot. , Differential conductance gdd as a function of source–drain bias VSD and gate voltage VLP. Bright features with VSD > 0 correspond to discrete quantum states of N + 1 holes (N = even) in a single dot formed between gates L and M. , Slices of gdd along dashed lines in (VLP ≈ 655 mV) reveals Zeeman splitting of the N + 1 ground state for a magnetic field of B = 5 T. , Zeeman splitting ΔEZ versus B and a linear fit (dashed line) yield a g-factor of 1.02 ± 0.05. * Figure 3: Hole-spin doublets in a Ge–Si double dot. , Differential conductance dgs/dVL through the sensor dot versus B in the absence of current through the double quantum dot (source–drain bias = 0). Peaks in dgs/dVL versus VL indicate ground-state transitions when holes are removed from the left dot. , B dependence of reduced Coulomb spacings, , where VN are the peak ordinates (emphasized black dotted lines in ). , Data of plotted with guide lines g = 1.0 assuming a gate coupling efficiency α = 0.37 extracted from the single dot device in Fig. 2. * Figure 4: Pulsed gate measurements of spin relaxation times. , Sensor conductance gS near a spin-blocked charge transition between the left and right dot. Spin-to-charge conversion results in pulse triangles that fade away with increasing measurement time τM. Here, N and M indicate an odd number of holes in the left and right dots (denoted (1,1) in the main text). , Visibility I(τM) measured at the centre of the pulse triangle versus τM at different magnetic fields. The fitting curves (solid lines) give T1 = 0.6, 0.3 and 0.2 ms at B = 0 (red), 0.1 (blue) and 1 T (green), respectively. Inset: blue arrows visualize the T1 pulse sequence in gate voltage space when the measurement point is held in the centre of the pulse triangle. Author information * Abstract * Author information Affiliations * Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA * Yongjie Hu & * Charles M. Lieber * Department of Physics, Harvard University, Cambridge, Massachusetts 02138, USA * Yongjie Hu, * Ferdinand Kuemmeth & * Charles M. Marcus * School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, USA * Charles M. Lieber * Present address: Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, USA * Yongjie Hu Contributions Y.H. and F.K. performed the experiments. Y.H. prepared the materials and fabricated the devices. Y.H., F.K., C.M.L. and C.M.M. analysed the data and co-wrote the paper. All authors discussed the results and commented on the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Charles M. Lieber or * Charles M. Marcus Author Details * Yongjie Hu Search for this author in: * NPG journals * PubMed * Google Scholar * Ferdinand Kuemmeth Search for this author in: * NPG journals * PubMed * Google Scholar * Charles M. Lieber Contact Charles M. Lieber Search for this author in: * NPG journals * PubMed * Google Scholar * Charles M. Marcus Contact Charles M. Marcus Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Mixing subattolitre volumes in a quantitative and highly parallel manner with soft matter nanofluidics
- Nat Nanotechnol 7(1):51-55 (2012)
Nature Nanotechnology | Letter Mixing subattolitre volumes in a quantitative and highly parallel manner with soft matter nanofluidics * Sune M. Christensen1, 2, 3, 4 * Pierre-Yves Bolinger1, 2, 4 * Nikos S. Hatzakis1, 2, 3 * Michael W. Mortensen1, 2 * Dimitrios Stamou1, 2, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:51–55Year published:(2012)DOI:doi:10.1038/nnano.2011.185Received 01 August 2011 Accepted 27 September 2011 Published online 30 October 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Handling and mixing ultrasmall volumes of reactants in parallel can increase the throughput1, 2 and complexity3 of screening assays while simultaneously reducing reagent consumption1. Microfabricated silicon and plastic can provide reliable fluidic devices4, 5, 6, 7, 8, but cannot typically handle total volumes smaller than ~1 × 10–12 l. Self-assembled soft matter nanocontainers9, 10, 11, 12, 13, 14, 15, 16 can in principle significantly improve miniaturization and biocompatibility, but exploiting their full potential is a challenge due to their small dimensions17. Here, we show that small unilamellar lipid vesicles can be used to mix volumes as small as 1 × 10–19 l in a reproducible and highly parallelized fashion. The self-enclosed nanoreactors are functionalized with lipids of opposite charge to achieve reliable fusion. Single vesicles encapsulating one set of reactants are immobilized on a glass surface and then fused with diffusing vesicles of opposite charge that! carry a complementary set of reactants. We find that ~85% of the ~1 × 106 cm–2 surface-tethered nanoreactors undergo non-deterministic fusion, which is leakage-free in all cases, and the system allows up to three to four consecutive mixing events per nanoreactor. View full text Subject terms: * Nanofluidics * Nanomaterials Figures at a glance * Figure 1: Mixing of subattolitre volumes by fusion of SUVs of opposite charge. , Target SUV reactors containing alkaline phosphatase were immobilized at a PLL-g-PEG/PLL-g-PEG-biotin functionalized glass surface via biotin–neutravidin coupling. Fusion of cargo SUV reactors carrying FDP with the targets caused mixing of enzyme and substrate, thus triggering a biochemical reaction within the confined volumes of the surface-tethered reactors. , Histograms of reactor volumes for populations extruded with 50 nm and 400 nm filters, respectively. , The scheme in monitored by confocal microscopy of Texas Red-DHPE in the target reactor membrane (top), DiD in the cargo reactor membrane (middle) and fluorescein produced from the enzymatic reaction (bottom). Scale bar, 5 µm. A threshold was applied to the images to improve visualization. , Fusion monitored by FRET following lipid mixing. In this experiment target reactors were labelled with DiI (energy acceptor) and cargo reactors with DiO (energy donor). Lipid mixing upon fusion of a reactor pair gave rise to a! n abrupt increase in acceptor fluorescence with a corresponding FRET efficiency above the threshold for lipid mixing (dashed line). , Enzymatic production of fluorescein on fusion of a single reactor pair. Traces show the fluorescence intensity of the cargo reactor membrane label (DiD) and fluorescein. * Figure 2: Characterization of operational performance of the platform. , Scheme showing delivery of FDP to target reactors loaded with alkaline phosphatase (AP). , Volume histograms of all target reactors (N = 1,972) and reactors exhibiting product formation (on average 88%) for the AP–FDP system after 10 min incubation with cargo reactors. The black curve shows the percentage of successful product formation events as a function of reactor volume. The graph includes data from two independent experiments. , Scheme showing reaction experiment with membrane-activated lipase TLL. , Average density of reaction events for three enzyme–substrate systems. AR, Amplex Red. The numbers of fusion events used to calculate reaction densities were 1,676 (AP–FDP), 134 (TLL–CFDA), 42 (HRP–AR). , Leakage assay. , Time traces of the three labels corresponding to a single fusion event characterized by quenching of the donor (target reactor, DiI) and simultaneous increase in acceptor (cargo reactor, DiD) fluorescence. The steady signal of the lumen report! er, A488, demonstrates that the reactor remained sealed during the fusion process. , FRET efficiency trace corresponding to the fusion event in . , Histogram of retained A488 fluorescence quantified from single fusion events such as the one shown in . The retained percentage of A488 was obtained from the average A488 intensity before and after reactor fusion. Fitting the data with a normal distribution showed that the reactors retained 100 ± 1% (s.d.) of the encapsulated fluorophores. * Figure 3: Consecutive mixing events triggered in single target reactors. , Scheme showing repetitive fusion of cargo reactors to a single target. , Time course demonstrating two consecutive product formation events in a single target reactor (horizontal bars have been added to guide the eye). , Lipid mixing traces of cargo and target reactor fluorescence for a target accepting several events. The spikes in donor fluorescence between the labelled events correspond to cargo reactors diffusing in the vicinity of the target without fusing. , Accumulated fusion counts for all target reactors on the surface. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work * Sune M. Christensen & * Pierre-Yves Bolinger Affiliations * Bionanotechnology and Nanomedicine Laboratory, Department of Neuroscience and Pharmacology, University of Copenhagen, 2100 Copenhagen, Denmark * Sune M. Christensen, * Pierre-Yves Bolinger, * Nikos S. Hatzakis, * Michael W. Mortensen & * Dimitrios Stamou * Nano-Science Center, University of Copenhagen, 2100 Copenhagen, Denmark * Sune M. Christensen, * Pierre-Yves Bolinger, * Nikos S. Hatzakis, * Michael W. Mortensen & * Dimitrios Stamou * Lundbeck Foundation Center for Biomembranes in Nanomedicine, University of Copenhagen, 2100 Copenhagen, Denmark * Sune M. Christensen, * Nikos S. Hatzakis & * Dimitrios Stamou Contributions D.S. designed and supervised the project. S.M.C. and P-Y.B. conducted most experiments and data analysis and contributed equally to this work. S.M.C. and D.S. wrote the paper. All authors helped design experiments, discussed the results and commented on the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Dimitrios Stamou Author Details * Sune M. Christensen Search for this author in: * NPG journals * PubMed * Google Scholar * Pierre-Yves Bolinger Search for this author in: * NPG journals * PubMed * Google Scholar * Nikos S. Hatzakis Search for this author in: * NPG journals * PubMed * Google Scholar * Michael W. Mortensen Search for this author in: * NPG journals * PubMed * Google Scholar * Dimitrios Stamou Contact Dimitrios Stamou Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (767 KB) Supplementary information Additional data
Label-free imaging of semiconducting and metallic carbon nanotubes in cells and mice using transient absorption microscopy
- Nat Nanotechnol 7(1):56-61 (2012)
Nature Nanotechnology | Letter Label-free imaging of semiconducting and metallic carbon nanotubes in cells and mice using transient absorption microscopy * Ling Tong1 * Yuxiang Liu2 * Bridget D. Dolash3 * Yookyung Jung4 * Mikhail N. Slipchenko2 * Donald E. Bergstrom3, 5 * Ji-Xin Cheng1, 2, 5 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:56–61Year published:(2012)DOI:doi:10.1038/nnano.2011.210Received 02 September 2011 Accepted 31 October 2011 Published online 04 December 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg As interest in the potential biomedical applications of carbon nanotubes increases1, there is a need for methods that can image nanotubes in live cells, tissues and animals. Although techniques such as Raman2, 3, 4, photoacoustic5 and near-infrared photoluminescence imaging6, 7, 8, 9, 10 have been used to visualize nanotubes in biological environments, these techniques are limited because nanotubes provide only weak photoluminescence and low Raman scattering and it remains difficult to image both semiconducting and metallic nanotubes at the same time. Here, we show that transient absorption microscopy offers a label-free method to image both semiconducting and metallic single-walled carbon nanotubes in vitro and in vivo, in real time, with submicrometre resolution. By using appropriate near-infrared excitation wavelengths, we detect strong transient absorption signals with opposite phases from semiconducting and metallic nanotubes. Our method separates background signals gen! erated by red blood cells and this allows us to follow the movement of both types of nanotubes inside cells and in the blood circulation and organs of mice without any significant damaging effects. View full text Subject terms: * Surface patterning and imaging Figures at a glance * Figure 1: Semiconducting and metallic nanotubes exhibit strong transient absorption signals with opposite phases. , Extinction spectra of pure S-SWNT (left), pure M-SWNT (middle) and DNA-wrapped nanotubes (DNA-SWNT) (right) solutions. E11M, first optical transition of M-SWNTs; E22S, second optical transition of S-SWNTs. , Transient absorption images of pure S-SWNTs (left), pure M-SWNTs (middle) and DNA-SWNTs (right) in the in-phase channel. S-SWNTs and M-SWNTs showed positive and negative contrast, respectively. Scale bars, 2 µm. For all transient absorption images, pump and probe beams were at 707 nm and 885 nm, respectively. The laser power after the objective was 0.7 mW for the pump beam and 1.3 mW for the probe beam. , Raman spectra from pure S-SWNTs (left), pure M-SWNTs (middle) and DNA-SWNTs (right). * Figure 2: Comparison of transient absorption and AFM images of the same nanotube sample show that transient absorption microscopy can detect M-SWNTs and S-SWNTs in a chirality-insensitive manner. –, Transient absorption image (,) and AFM image () of pure S-SWNTs in the same area. –, Transient absorption image (,) and AFM image () of pure M-SWNTs in the same area. The pump and probe polarization directions are vertical in and and horizontal in and , as indicated by two-headed arrows above the transient absorption images. Nanotubes that are detected by transient absorption images are labelled with arrows on both the transient absorption and AFM images. In total, 21 of 25 S-SWNTs (84%) and 15 of 17 M-SWNTs (88%) seen in the AFM image were shown in the transient absorption image, respectively. Scale bars, 1 µm. Laser power post-objective was 0.7 mW for the pump beam and 1.3 mW for the probe beam. ,, Height analyses along the blue dotted lines in and , respectively, show individual nanotubes, not bundles. * Figure 3: Cellular uptake and intracellular trafficking of DNA-SWNTs monitored in real time by transient absorption microscopy. , Transient absorption image of DNA-SWNTs internalized by CHO cells after 24 h incubation. , Time-lapse images showing the fusion process for two nanotubes (indicated by white circle). , Time-lapse images showing the transport of a nanotube (indicated by white circle) back to the cell surface. The yellow line outlines the cell. Grey, transmission of cells; green, S-SWNTs; red, M-SWNTs. Scale bars, 5 µm. Pump, 707 nm; probe, 885 nm. The laser power post-objective was 1 mW for the pump beam and 1.6 mW for the probe beam. * Figure 4: Imaging of RBCs and F127-wrapped SWNTs (F127-SWNTs) circulating in the blood vessels of a mouse earlobe. , Thermal lens signals from isolated RBCs at different z-positions with z = 0 µm as the middle plane of a RBC. Pump, 707 nm; probe, 885 nm. , Phase of thermal lens signals from a RBC as a function of focus position. , In-phase channel signal (X), quadrature channel signal (Y) and amplitude of the thermal lens signal (R = (X2 + Y2)1/2) from a RBC as a function of focus position. ,, Intravital thermal lens imaging of RBCs in the blood vessel inside the earlobe of a mouse injected with pure saline when the pump beam is at 707 nm () and 790 nm (). The probe beam was fixed at 885 nm for both cases. Images were taken by line scanning (x–t scanning, 132 pixels per line). , Intravital imaging of F127-SWNTs in the blood vessel inside the earlobe of a mouse by line scanning (x–t scanning, 105 pixels per line). In-phase channel: transient absorption signals from F127-SWNTs. Quadrature channel: thermal lens signals from RBCs. Pump and probe beams were at 790 nm and 885 nm, respecti! vely. Laser power post-objective was 16 mW for both beams. Scale bars (–), 3 µm. , Intensity profile showing three peaks corresponding to the three dots in . * Figure 5: F127-SWNTs in different organs of treated mice are visualized by transient absorption microscopy at the cellular level. , Image of F127-SWNTs in liver tissue with Kupffer cells labelled with ED-1 antibody. Green, S-SWNTs; red, M-SWNTs; blue, two-photon fluorescent signal from antibody. , A zoom-in image of nanotubes in a Kupffer cell in the liver. , Image of normal liver tissue without nanotubes. , Image of nanotubes in spleen tissue. Grey, transmission of tissue. Scale bars, 5 µm. Pump, 707 nm; probe, 885 nm. Laser power post-objective was 1.0 mW for the pump beam and 1.6 mW for the probe beam. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA * Ling Tong & * Ji-Xin Cheng * Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, USA * Yuxiang Liu, * Mikhail N. Slipchenko & * Ji-Xin Cheng * Department of Medical Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, Indiana 47907, USA * Bridget D. Dolash & * Donald E. Bergstrom * Department of Physics, Purdue University, West Lafayette, Indiana 47907, USA * Yookyung Jung * Birck Nanotechnology Center, Purdue University, West Lafayette, Indiana 47907, USA * Donald E. Bergstrom & * Ji-Xin Cheng Contributions L.T. and J.X.C. conceived and designed the experiments. L.T. and Y.L. performed the experiments. L.T. and Y.L. analysed the data. B.D.D., Y.J., M.N.S. and D.E.B. contributed materials and analysis tools. L.T. and J.X.C. co-wrote the paper. All authors discussed the results and commented on the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ji-Xin Cheng Author Details * Ling Tong Search for this author in: * NPG journals * PubMed * Google Scholar * Yuxiang Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Bridget D. Dolash Search for this author in: * NPG journals * PubMed * Google Scholar * Yookyung Jung Search for this author in: * NPG journals * PubMed * Google Scholar * Mikhail N. Slipchenko Search for this author in: * NPG journals * PubMed * Google Scholar * Donald E. Bergstrom Search for this author in: * NPG journals * PubMed * Google Scholar * Ji-Xin Cheng Contact Ji-Xin Cheng Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (4,809 KB) Supplementary information Movies * Supplementary information (1,017 KB) Supplementary movie 1 * Supplementary information (457 KB) Supplementary movie 2 * Supplementary information (1,442 KB) Supplementary movie 3 Additional data
Role of cell cycle on the cellular uptake and dilution of nanoparticles in a cell population
- Nat Nanotechnol 7(1):62-68 (2012)
Nature Nanotechnology | Letter Role of cell cycle on the cellular uptake and dilution of nanoparticles in a cell population * Jong Ah Kim1 * Christoffer Åberg1 * Anna Salvati1 * Kenneth A. Dawson1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature NanotechnologyVolume: 7,Pages:62–68Year published:(2012)DOI:doi:10.1038/nnano.2011.191Received 07 July 2011 Accepted 04 October 2011 Published online 06 November 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nanoparticles are considered a primary vehicle for targeted therapies because they can pass biological barriers and enter and distribute within cells by energy-dependent pathways1, 2, 3. So far, most studies have shown that nanoparticle properties, such as size4, 5, 6 and surface7, 8, can influence how cells internalize nanoparticles. Here, we show that uptake of nanoparticles by cells is also influenced by their cell cycle phase. Although cells in different phases of the cell cycle were found to internalize nanoparticles at similar rates, after 24 h the concentration of nanoparticles in the cells could be ranked according to the different phases: G2/M > S > G0/G1. Nanoparticles that are internalized by cells are not exported from cells but are split between daughter cells when the parent cell divides. Our results suggest that future studies on nanoparticle uptake should consider the cell cycle, because, in a cell population, the dose of internalized nanoparticles in each ce! ll varies as the cell advances through the cell cycle. View full text Subject terms: * Nanoparticles * Nanomedicine * Environmental, health and safety issues Figures at a glance * Figure 1: The cell cycle and its role in nanoparticle uptake. , The cell cycle, which is a series of events that lead to cell division and replication, consists of four phases: G1, S, G2 and M. Cells in the different phases are distinguished by blue, pink and green nuclei for the G1, S and G2/M phases, respectively. The cell cycle commences with the G1 phase, during which the cell increases its size. During the S phase the cell synthesizes DNA, and in the G2 phase it prepares for cell division, which occurs during the M phase. The two daughter cells then enter the G1 phase. , A cell culture contains a mixture of cells in different phases of their cell cycle, simultaneously undergoing progression and cell division. , Nanoparticle uptake in a cycling cell. The yellow-green circles represent the nanoparticles, which, inside cells, accumulate in the lysosomes, represented by the oval compartment. When the cell divides, the internalized nanoparticles are split between the two daughter cells. Figure not to scale. * Figure 2: Internalization of nanoparticles and ranking of the concentration of nanoparticles in the cells. A549 cells were exposed to 40 nm yellow-green PS-COOH (25 µg ml−1 in cMEM) for up to 72 h before imaging and flow cytometry measurements. , Confocal images after 5, 24 and 72 h of exposure show nanoparticles accumulated in the lysosomes. Blue, nuclei (DAPI); red, lysosomes (LAMP1 antibody); green, nanoparticles. , Mean cell fluorescence intensity obtained by flow cytometry as a function of time shows a linear increase due to particle uptake, but plateaus after one day due to cell division. Error bars are standard deviation over three replicates. ,, A549 cells were exposed to similar nanoparticles for up to 28 h before flow cytometry measurements. Mean fluorescence intensity as a function of exposure time () and flow cytometry distributions of cell fluorescence intensity after 2, 12 and 28 h of exposure to nanoparticles () for all cells and cells in the G0/G1, S and G2/M phases (defined in Supplementary Fig. S5). The results and the scheme show that the intracellular conce! ntration of nanoparticles is ranked according to the cell cycle phases: G2/M > S > G0/G1. ,, Numerical simulation corresponding to data in and , respectively, showing good agreement with experimental results. * Figure 3: Nanoparticle export is negligible. A549 cells were exposed to 40 nm yellow-green PS-COOH (25 µg ml−1 in cMEM) for 4 h, then the S-phase cells were EdU-labelled for 30 min and cells grown further in nanoparticle-free media, before cell fluorescence measurement by flow cytometry. , EdU–DNA double-scatter plots 0, 5 and 8 h after EdU-labelling. (For full time course see Supplementary Fig. S10.) The indicated regions show EdU-labelled cells after division ('After division') and all other cells ('Complement'). , Fraction of divided EdU-labelled cells, showing excellent agreement with the prediction from the corresponding numerical simulation (solid line). , Mean cell fluorescence of all cells, divided EdU-labelled cells and their complement. The solid line is a fit to the result expected due to cell division alone. Dashed lines are horizontal fits. The good agreement indicates that export is negligible and the internalized nanoparticle load decreases only as a result of cell division. * Figure 4: Nanoparticle uptake rates during the different phases of the cell cycle. Independent uptake experiments of 40 nm yellow-green PS-COOH nanoparticles (25 µg ml−1 in cMEM) were performed on A549 cells 2, 6 and 12 h after EdU-labelling, at which times many EdU-positive cells are in the S, G2/M and G0/G1 phases, respectively (Supplementary Fig. S12). The presented values are the means of the cell fluorescence intensity of cells in the S, G2/M and G0/G1 phases (as defined in Supplementary Fig. S13) obtained by flow cytometry. Error bars represent the standard deviation of three replicates. Solid lines are linear fits performed to determine the uptake rates. The results show that the uptake rate is comparable for all phases of the cell cycle. * Figure 5: Nanoparticle uptake in synchronized cell cultures. , DNA histograms (obtained by propidium iodide staining) of non-synchronized A549 cells, a population enriched in G0/G1 phase by serum deprivation ('synchronized'), and populations synchronized by the same procedure and subsequently exposed to nanoparticle-free cMEM (for 6 and 24 h) to revert the synchronization and restart cell cycle progression ('restarted'). , Mean cell fluorescence intensity obtained by flow cytometry after exposure to nanoparticles (40 nm yellow-green PS-COOH 25 µg ml−1 in cMEM) in synchronized and non-synchronized A549 cells (with the same starting cell number). Error bars represent standard deviation of three independent replicates. The results show similar nanoparticle uptake during the first 5 h of exposure, but over 24 h the synchronized cells accumulate more nanoparticles. Author information * Abstract * Author information * Supplementary information Affiliations * Centre for BioNano Interactions, School of Chemistry and Chemical Biology and Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland * Jong Ah Kim, * Christoffer Åberg, * Anna Salvati & * Kenneth A. Dawson Contributions J.A.K. performed experiments, analysed and interpreted data, and wrote the paper. C.Å. developed the numerical simulations and analytical tools, analysed and interpreted data, and wrote the paper. A.S. supervised the experimental work, analysed and interpreted data, and wrote the paper. K.A.D. interpreted data and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Kenneth A. Dawson or * Anna Salvati Author Details * Jong Ah Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Christoffer Åberg Search for this author in: * NPG journals * PubMed * Google Scholar * Anna Salvati Contact Anna Salvati Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth A. Dawson Contact Kenneth A. Dawson Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (3,852 KB) Supplementary information Other * Supplementary information (368 KB) Supplementary information Additional data
One- and two-dimensional photonic crystal microcavities in single crystal diamond
- Nat Nanotechnol 7(1):69-74 (2012)
Nature Nanotechnology | Article One- and two-dimensional photonic crystal microcavities in single crystal diamond * Janine Riedrich-Möller1 * Laura Kipfstuhl1 * Christian Hepp1 * Elke Neu1 * Christoph Pauly2 * Frank Mücklich2 * Armin Baur3 * Michael Wandt3 * Sandra Wolff4 * Martin Fischer5 * Stefan Gsell5 * Matthias Schreck5 * Christoph Becher1 * Affiliations * Contributions * Corresponding authorJournal name:Nature NanotechnologyVolume: 7,Pages:69–74Year published:(2012)DOI:doi:10.1038/nnano.2011.190Received 09 August 2011 Accepted 30 September 2011 Published online 13 November 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Diamond is an attractive material for photonic quantum technologies because its colour centres have a number of outstanding properties, including bright single photon emission and long spin coherence times. To take advantage of these properties it is favourable to directly fabricate optical microcavities in high-quality diamond samples. Such microcavities could be used to control the photons emitted by the colour centres or to couple widely separated spins. Here, we present a method for the fabrication of one- and two-dimensional photonic crystal microcavities with quality factors of up to 700 in single crystal diamond. Using a post-processing etching technique, we tune the cavity modes into resonance with the zero phonon line of an ensemble of silicon-vacancy colour centres, and we measure an intensity enhancement factor of 2.8. The controlled coupling of colour centres to photonic crystal microcavities could pave the way to larger-scale photonic quantum devices based on si! ngle crystal diamond. View full text Subject terms: * Photonic structures and devices * Synthesis and processing Figures at a glance * Figure 1: SEM images of two-dimensional and one-dimensional fabricated PhC cavities. , SEM image of the fabricated M7 cavity with lattice constant a ≈ 275 nm and radii R ≈ 85 nm. , Close-up of the cavity centre. , Cross-sectional image (tilt angle, 52°). A thin platinum layer was deposited on the PhC to allow for a straight cut through the diamond membrane using FIB. From the cross-sectional image, a diamond film thickness of 300 nm can be inferred. The sidewalls of the milled air holes exhibit a tilt angle of ~6°. ,, Top () and side () views of the fabricated one-dimensional nanobeam cavity with a pitch:width:height ratio of 2:3:3 (a ≈ 200 nm). The hole radii monotonically decrease from R ≈ 83 nm at the cavity centre to R ≈ 72 nm at the waveguide edge. , Close-up of the one-dimensional waveguide–cavity. * Figure 2: Photoluminescence spectra. ,, Experimental photoluminescence spectra of an M7 cavity () and a nanobeam cavity () are shown in black, and the reference spectra of the unstructured membrane are shown in grey. The intensity of the reference spectra is scaled to account for the smaller collection efficiency from unpatterned areas of the sample (see Supplementary Information). Coloured curves show the simulated cavity modes for different symmetric boundary conditions. Ex and Ey mode profiles for fundamental mode e1 and various higher-order modes are shown above. The spectrum of the M7 cavity () shows several cavity modes close to the SiV centre zero phonon line at λ = 738 nm (yellow area). The simulated spectrum (coloured curves, arbitrary amplitude) of an ideal M7 cavity with R = 0.31a and h = 1.1a matches the experimental results very well. The spectrum of the nanobeam cavity () shows three cavity modes close to the design wavelength λ = 637 nm of the NV− centre zero phonon line. The calculated modes! (coloured curves, arbitrary amplitude) of an ideal nanobeam cavity with h = w = 1.5a and radii that decrease from R = 0.42a at the cavity centre to R = 0.37a at the structure edge, agree very well with the experimental measurement. ,, Polarization analysis of an M7 cavity () and a nanobeam cavity (). Photoluminescence spectra taken without a polarizer are shown in black. The even modes are pronounced for a polarizer oriented in the y-direction (red curves), whereas the odd modes are prominent for polarizer oriented along the x-axis (blue curves). * Figure 3: Cavity tuning. , Cavity spectrum taken before the first oxidation step (black) and after one, two, three and four oxidation steps (coloured curves). When the cavity mode o2 (marked by *) is tuned into resonance with the emission line of SiV centres, the intensity of the zero phonon line (the peak in the yellow region) is clearly enhanced. , Wavelengths for various cavity modes are blueshifted by 3 nm on average per oxidation step. The four lines at the bottom show higher-order modes (e4, o3, o4, o5; not labelled for clarity). In total, the cavity modes are tuned up to 15 nm. , Quality factors of the fundamental cavity modes show no significant degradation following tuning. Author information * Abstract * Author information * Supplementary information Affiliations * Universität des Saarlandes, Fachrichtung 7.2 (Experimentalphysik), 66123 Saarbrücken, Germany * Janine Riedrich-Möller, * Laura Kipfstuhl, * Christian Hepp, * Elke Neu & * Christoph Becher * Universität des Saarlandes, Fachrichtung 8.4 (Materialwissenschaft und Werkstofftechnik), 66123 Saarbrücken, Germany * Christoph Pauly & * Frank Mücklich * University of Freiburg, Department of Microsystems Engineering (IMTEK), Cleanroom Service Center, 79110 Freiburg, Germany * Armin Baur & * Michael Wandt * TU Kaiserslautern, Nano + Bio Center, 67653 Kaiserslautern, Germany * Sandra Wolff * Universität Augsburg, Lehrstuhl für Experimentalphysik IV, 86159 Augsburg, Germany * Martin Fischer, * Stefan Gsell & * Matthias Schreck Contributions J.R-M. and L.K. fabricated the photonic crystals, performed the experiments and carried out the numerical modelling of the structures. M.F., S.G. and M.S. developed the CVD growth process for the diamond films on iridium buffer layers. A.B. and M.W. prepared the diamond membrane. J.R-M. and S.W. thinned the diamond film. C.P., J.R-M., L.K. and F.M. performed FIB milling. C.H. and E.N. contributed experimental tools and helped with the photoluminescence measurements and interpretation of data. C.B. conceived and designed the experiments. J.R-M. and C.B. wrote the manuscript. All authors discussed the results and commented on the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Christoph Becher Author Details * Janine Riedrich-Möller Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Kipfstuhl Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Hepp Search for this author in: * NPG journals * PubMed * Google Scholar * Elke Neu Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Pauly Search for this author in: * NPG journals * PubMed * Google Scholar * Frank Mücklich Search for this author in: * NPG journals * PubMed * Google Scholar * Armin Baur Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Wandt Search for this author in: * NPG journals * PubMed * Google Scholar * Sandra Wolff Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Fischer Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Gsell Search for this author in: * NPG journals * PubMed * Google Scholar * Matthias Schreck Search for this author in: * NPG journals * PubMed * Google Scholar * Christoph Becher Contact Christoph Becher Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary information (3,964 KB) Supplementary information Additional data
Electrically tuned spin–orbit interaction in an InAs self-assembled quantum dot
- Nat Nanotechnol 7(1):75 (2012)
Nature Nanotechnology | Corrigendum Electrically tuned spin–orbit interaction in an InAs self-assembled quantum dot * Y. Kanai * R. S. Deacon * S. Takahashi * A. Oiwa * K. Yoshida * K. Shibata * K. Hirakawa * Y. Tokura * S. TaruchaJournal name:Nature NanotechnologyVolume: 7,Page:75Year published:(2012)DOI:doi:10.1038/nnano.2011.228Published online 28 December 2011 Article tools * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Nature Nanotechnology6, 511–516 (2011); published online 24 July 2011; corrected after print 22 November 2011. In the version of this Letter originally published, in the discussion of Fig. 5c on page 514, the fitting function should have been Δ = A|cos(θ − θ0 ± π/2)| + B, and the offsets of θ0 should have been −30 ± 4° and −39 ± 5° for Vsg = −0.5 V and 1.0 V, respectively. These errors have been corrected in the HTML and PDF versions of the Letter. Author information Author Details * Y. Kanai Search for this author in: * NPG journals * PubMed * Google Scholar * R. S. Deacon Search for this author in: * NPG journals * PubMed * Google Scholar * S. Takahashi Search for this author in: * NPG journals * PubMed * Google Scholar * A. Oiwa Search for this author in: * NPG journals * PubMed * Google Scholar * K. Yoshida Search for this author in: * NPG journals * PubMed * Google Scholar * K. Shibata Search for this author in: * NPG journals * PubMed * Google Scholar * K. Hirakawa Search for this author in: * NPG journals * PubMed * Google Scholar * Y. Tokura Search for this author in: * NPG journals * PubMed * Google Scholar * S. Tarucha Search for this author in: * NPG journals * PubMed * Google Scholar Additional data Author Details * Y. Kanai Search for this author in: * NPG journals * PubMed * Google Scholar * R. S. Deacon Search for this author in: * NPG journals * PubMed * Google Scholar * S. Takahashi Search for this author in: * NPG journals * PubMed * Google Scholar * A. Oiwa Search for this author in: * NPG journals * PubMed * Google Scholar * K. Yoshida Search for this author in: * NPG journals * PubMed * Google Scholar * K. Shibata Search for this author in: * NPG journals * PubMed * Google Scholar * K. Hirakawa Search for this author in: * NPG journals * PubMed * Google Scholar * Y. Tokura Search for this author in: * NPG journals * PubMed * Google Scholar * S. Tarucha Search for this author in: * NPG journals * PubMed * Google Scholar

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All things being equal
- Nat Methods 9(2):111 (2012)
Nature Methods | Editorial All things being equal Journal name:Nature MethodsVolume: 9,Page:111Year published:(2012)DOI:doi:10.1038/nmeth.1891Published online 30 January 2012 Direct comparisons of tool or method performance under standardized experimental conditions yield highly valuable information for both method users and developers. View full text Additional data
The author file: Susan Cox
- Nat Methods 9(2):113 (2012)
Nature Methods | This Month The author file: Susan Cox * Monya BakerJournal name:Nature MethodsVolume: 9,Page:113Year published:(2012)DOI:doi:10.1038/nmeth.1866Published online 30 January 2012 Using Bayesian statistics to speed super-resolution microscopy View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Author Details * Monya Baker Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Points of view: Networks
- Nat Methods 9(2):115 (2012)
Nature Methods | This Month Points of view: Networks * Nils Gehlenborg1 * Bang Wong2 * AffiliationsJournal name:Nature MethodsVolume: 9,Page:115Year published:(2012)DOI:doi:10.1038/nmeth.1862Published online 30 January 2012 We describe graphing techniques to support exploration of networks. View full text Figures at a glance * Figure 1: Node-link diagrams. () A directed graph typical of a biological pathway. () An undirected graph with nodes arranged in a circle. () A spring-embedded layout of data from . * Figure 2: Adjacency matrices. () Nodes are ordered as rows and columns; connections are indicated as filled cells. () A matrix representation of data from Figure 1b. Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Nils Gehlenborg is a research associate at Harvard Medical School and the Broad Institute. * Bang Wong is the creative director of the Broad Institute of the Massachusetts Institute of Technology and Harvard and an adjunct assistant professor in the Department of Art as Applied to Medicine at The Johns Hopkins University School of Medicine. Competing financial interests The authors declare no competing financial interests. Author Details * Nils Gehlenborg Search for this author in: * NPG journals * PubMed * Google Scholar * Bang Wong Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Improved Mos1-mediated transgenesis in C. elegans
- Nat Methods 9(2):117-118 (2012)
Nature Methods | Correspondence Improved Mos1-mediated transgenesis in C. elegans * Christian Frøkjær-Jensen1, 2 * M Wayne Davis1 * Michael Ailion1, 3 * Erik M Jorgensen1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:117–118Year published:(2012)DOI:doi:10.1038/nmeth.1865Published online 30 January 2012 To the Editor: The ability to add or delete genes to the genome of genetic model organisms is essential. Previously, we had developed methods based on the Mos1 transposon1 to make targeted transgene insertions (Mos1-mediated single-copy transgene insertions; MosSCI2) and targeted deletions (Mos1-mediated deletions; MosDEL3) in Caenorhabditis elegans, the latter published in Nature Methods. Here we present new reagents that improve the efficiency, facilitate the selection for transgenic strains and expand the set of MosSCI insertion sites (Supplementary Table 1). View full text Subject terms: * Genetics * Molecular Engineering * Model Organisms * Gene Expression Author information * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Howard Hughes Medical Institute, Department of Biology, University of Utah, Salt Lake City, Utah, USA. * Christian Frøkjær-Jensen, * M Wayne Davis, * Michael Ailion & * Erik M Jorgensen * Department of Biomedical Sciences and Danish National Research Foundation Centre for Cardiac Arrhythmia, University of Copenhagen, Copenhagen, Denmark. * Christian Frøkjær-Jensen * Present address: Department of Biochemistry, University of Washington, Seattle, Washington, USA. * Michael Ailion Competing financial interests E.M.J. is an author of a patent covering techniques described in this paper (US patent 7,196,244 and European patent pending). Corresponding author Correspondence to: * Erik M Jorgensen Author Details * Christian Frøkjær-Jensen Search for this author in: * NPG journals * PubMed * Google Scholar * M Wayne Davis Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Ailion Search for this author in: * NPG journals * PubMed * Google Scholar * Erik M Jorgensen Contact Erik M Jorgensen Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (5.2M) Supplementary Figures 1–5, Supplementary Table 1 and Supplementary Methods Additional data
Generating transgenic nematodes by bombardment and antibiotic selection
- Nat Methods 9(2):118-119 (2012)
Nature Methods | Correspondence Generating transgenic nematodes by bombardment and antibiotic selection * Jennifer I Semple1 * Laura Biondini1 * Ben Lehner1, 2 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:118–119Year published:(2012)DOI:doi:10.1038/nmeth.1864Published online 30 January 2012 To the Editor: In an extension of methods we1 and others2 have previously described in Nature Methods, we report here single- or dual-antibiotic selection to isolate transgenic nematodes after microparticle bombardment. The protocol makes it straightforward to generate integrated transgenes in diverse Caenorhabditis strains and species. View full text Subject terms: * Genetics * Genomics * Model Organisms * Gene Expression Author information * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * European Molecular Biology Laboratory Centre for Genomic Regulation Systems Biology Unit, Barcelona, Spain. * Jennifer I Semple, * Laura Biondini & * Ben Lehner * Institució Catalana de Recerca i Estudis Avançats, Centre for Genomic Regulation and Pompeu Fabra University, Barcelona, Spain. * Ben Lehner Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ben Lehner Author Details * Jennifer I Semple Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Biondini Search for this author in: * NPG journals * PubMed * Google Scholar * Ben Lehner Contact Ben Lehner Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (7.3M) Supplementary Figures 1–9, Supplementary Tables 1–4 and Supplementary Methods Additional data
Structural variation: the genome's hidden architecture
- Nat Methods 9(2):133-137 (2012)
Nature Methods | Technology Feature Structural variation: the genome's hidden architecture * Monya Baker1Journal name:Nature MethodsVolume: 9,Pages:133–137Year published:(2012)DOI:doi:10.1038/nmeth.1858Published online 30 January 2012 Next-generation sequencing is uncovering more variants than ever before, but it also faces limitations. View full text Figures at a glance * Figure 1: Structural variation occurs in all forms and sizes. Genome structural variation encompasses polymorphic rearrangements 50 base pairs to hundreds of kilobases in size and affects about 0.5% of the genome of a given individual. * Figure 2: Entries for structural variation are increasing in the scientific literature (a) and in the Database of Genomic Variants (DGV; b), which posts curated data from peer-reviewed studies on human samples. It draws from two other databases (DGVa and dbVAR) that accept open submissions for data. * Figure 3: Several analytic techniques are used to find structural variation. Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Monya Baker is technology editor for Nature and Nature Methods Corresponding author Correspondence to: * Monya Baker Author Details * Monya Baker Contact Monya Baker Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Super resolution for common probes and common microscopes
- Nat Methods 9(2):139-141 (2012)
Article preview View full access options Nature Methods | News and Views Super resolution for common probes and common microscopes * Keith A Lidke1Journal name:Nature MethodsVolume: 9,Pages:139–141Year published:(2012)DOI:doi:10.1038/nmeth.1863Published online 30 January 2012 Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A sophisticated analysis approach based on the concept of fluorophore localization provides dynamic super-resolution data of GFP-labeled live cells using a common, arc lamp–based wide-field fluorescence microscope. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Methods for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Affiliations * Keith A. Lidke is at the University of New Mexico, Albuquerque, New Mexico, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Keith A Lidke Author Details * Keith A Lidke Contact Keith A Lidke Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Making sense out of nonsense to visualize editing in the fly nervous system
- Nat Methods 9(2):141-143 (2012)
Article preview View full access options Nature Methods | News and Views Making sense out of nonsense to visualize editing in the fly nervous system * Chammiran Daniel1 * Marie Öhman1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:141–143Year published:(2012)DOI:doi:10.1038/nmeth.1860Published online 30 January 2012 Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg In vivo methods to capture processing events such as RNA editing in specific cell types are sparse. Researchers have now developed a method to visualize adenosine-to-inosine editing activity in individual fruit fly neurons using a reverse-engineered fluorescent reporter. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Methods for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Affiliations * Chammiran Daniel and Marie Öhman are in the Department of Molecular Biology and Functional Genomics, Stockholm University, Stockholm, Sweden. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Marie Öhman Author Details * Chammiran Daniel Search for this author in: * NPG journals * PubMed * Google Scholar * Marie Öhman Contact Marie Öhman Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
DNA methylome analysis using short bisulfite sequencing data
- Nat Methods 9(2):145-151 (2012)
Nature Methods | Review DNA methylome analysis using short bisulfite sequencing data * Felix Krueger1, 3 * Benjamin Kreck2, 3 * Andre Franke2 * Simon R Andrews1 * Affiliations * Corresponding authorsJournal name:Nature MethodsVolume: 9,Pages:145–151Year published:(2012)DOI:doi:10.1038/nmeth.1828Published online 30 January 2012 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Bisulfite conversion of genomic DNA combined with next-generation sequencing (BS-seq) is widely used to measure the methylation state of a whole genome, the methylome, at single-base resolution. However, analysis of BS-seq data still poses a considerable challenge. Here we summarize the challenges of BS-seq mapping as they apply to both base and color-space data. We also explore the effect of sequencing errors and contaminants on inferred methylation levels and recommend the most appropriate way to analyze this type of data. View full text Subject terms: * Bioinformatics * Genetics * Epigenetics * Genomics Figures at a glance * Figure 1: Effect of bisulfite treatment of DNA. Bisulfite conversion of genomic DNA and subsequent PCR amplification gives rise to two PCR products and up to four potentially different DNA fragments for any given locus. (Hydroxy)methylated cytosine residues are resistant to bisulfite conversion and can be used as a readout of the DNA methylation state. mC, 5-methylcytosine; hmC, 5-hydroxymethylcytosine; OT, original top strand; CTOT, strand complementary to the original top strand; OB, original bottom strand; and CTOB, strand complementary to the original bottom strand. * Figure 2: Performance and accuracy of unbiased base-space and color-space BS-seq alignment tools. () A total of 106 random mouse genomic sequences of different lengths were aligned to the mouse genome (NCBIM37) with Bowtie as an example of methylation-aware mapping (biased) or with Bismark as an example of unbiased mapping (unbiased). Non-unique alignments were discarded. (,) A total of 106 random mouse base-space (Bismark; ) or human color-space (B-SOLANA; ) reads (75 base pairs) were simulated with different rates of bisulfite conversion (context is indicated) and aligned to the mouse (NCBIM37) or human (NCBI37) genomes. Bismark accurately detected various simulated methylation levels at a constant mapping efficiency. Alignment of color-space reads with B-SOLANA was efficient, and methylation calls were accurate only when methylation in non-CpG context was fairly low (ideally less than 5%). H (in CHG and CHH) stands for C, T or A. () Reads as in , were simulated with typical mammalian methylation levels (CpG context, 70%; CHG and CHH context, 3%) using Sherman (http://! www.bioinformatics.bbsrc.ac.uk/projects/sherman/). * Figure 3: Recommended workflow for the primary analysis of BS-seq data. Black arrows depict required steps, gray arrows indicate optional steps. *, only works with base-space data. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Felix Krueger & * Benjamin Kreck Affiliations * Bioinformatics Group, The Babraham Institute, Cambridge, UK. * Felix Krueger & * Simon R Andrews * Institute of Clinical Molecular Biology, Christian Albrechts University, Kiel, Germany. * Benjamin Kreck & * Andre Franke Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Andre Franke or * Simon R Andrews Author Details * Felix Krueger Search for this author in: * NPG journals * PubMed * Google Scholar * Benjamin Kreck Search for this author in: * NPG journals * PubMed * Google Scholar * Andre Franke Contact Andre Franke Search for this author in: * NPG journals * PubMed * Google Scholar * Simon R Andrews Contact Simon R Andrews Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (520K) Supplementary Figures 1–3 and Supplementary Table 1 Additional data
Immunolabeling artifacts and the need for live-cell imaging
- Nat Methods 9(2):152-158 (2012)
Nature Methods | Perspective Immunolabeling artifacts and the need for live-cell imaging * Ulrike Schnell1 * Freark Dijk1 * Klaas A Sjollema1 * Ben N G Giepmans1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:152–158Year published:(2012)DOI:doi:10.1038/nmeth.1855Published online 30 January 2012 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Fluorescent fusion proteins have revolutionized examination of proteins in living cells. Still, studies using these proteins are met with criticism because proteins are modified and ectopically expressed, in contrast to immunofluorescence studies. However, introducing immunoreagents inside cells can cause protein extraction or relocalization, not reflecting the in vivo situation. Here we discuss pitfalls of immunofluorescence labeling that often receive little attention and argue that immunostaining experiments in dead, permeabilized cells should be complemented with live-cell imaging when scrutinizing protein localization. View full text Subject terms: * Cell Biology * Microscopy * Imaging * Sensors and Probes Figures at a glance * Figure 1: Fixation and permeabilization can affect epitope accessibility. () Fluorescence images of 293T cells expressing EGFP fixed with 2% PFA and 0.05% glutaraldehyde for 30 min at room temperature (18–22 °C) and permeabilized with 0.05% Triton X-100 for 30 min with subsequent immunostaining with an antibody to GFP (anti-GFP) and mounting in Mowiol. Also shown are merged and differential interference contrast (DIC) images. Scale bar, 20 μm. () Images of 293T cells expressing tight junction protein Claudin-7–EGFP (CLDN7-EGFP) immunostained with an antibody to Claudin-7 (anti-CLDN7) after fixation with 4% PFA (30 min) and permeabilized with either methanol (MeOH; −20 °C) for 1 min or 0.1% Triton X-100 (Triton) for 15 min at room temperature. Scale bar, 10 μm. * Figure 2: Effects of standard fixation and permeabilization protocols on protein localization and epitope accessibility in different cell lines. () Images of 293T and MDCK cells transfected with EGFP-encoding plasmids and imaged live or after fixation with 4% PFA. () Images of 293T and MDCK cells after fixation as in and permeabilizion with 0.05% Triton X-100 (Triton; 15 min) or methanol (MeOH; 1 min −20 °C) and immunostaining with an antibody to GFP (anti-GFP). () Images of 293T cells transfected with plasmids encoding EGFP fusion proteins that localize in inidicated compartments. ER, endoplasmic reticulum. 'Tubulin', MDCK cells stably expressing EYFP–α-tubulin. Cells were recorded live, after fixation with 4% PFA or after fixation and permeabilization with Triton X-100 or MeOH and immunostaining with anti-GFP. Whereas laser intensity and pinhole were the same in each experiment, gain and offset settings were chosen for each condition. All scale bars, 20 μm. * Figure 3: Effects of standard immunostaining methods on protein extraction and EGFP fluorescence. () Images of MDCK cells stably expressing EpCAM-EGFP and fixed with methanol in real time (imaged every 2 min). The initial methanol (first time MeOH) was replaced (second time MeOH) and cells were washed 3× with PBS. Note that EGFP fluorescence is lost during dehydration but recovers after rehydration. (,) Real-time imaging of MDCK cells stably expressing EGFP, fixed with 2% or 4% PFA and permeabilized with 0.1% Triton X-100 (Triton; 15 min) or methanol (MeOH; 1 min at −20 °C when added to the dish). After permeabilization, cells were washed 6× with PBS to mimic the washing steps during the immunostaining procedure. EGFP fluorescence was recorded every 3 min using the same microscope settings for each condition. Scale bars, 20 μm. () Normalized average fluorescence of cells in five different microscope fields. AU, arbitrary units. Error bars, s.d. (n = 5 different fields). * Figure 4: Ultrastructural changes after fixation and permeabilization. (–) Electron micrographs of MDCK cells fixed with 2% or 4% PFA (–), methanol () or glutaraldehyde (). To mimic the immunostaining procedure, PFA-fixed cells were permeabilized with 0.05% Triton X-100 (15 min; ,) or MeOH (1 min at −20 °C; ,). All samples were washed (6× PBS), then fixed with 2% glutaraldehyde for 10 min and processed for electron microscopy. Scale bars, 2 μm. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Cell Biology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. * Ulrike Schnell, * Freark Dijk, * Klaas A Sjollema & * Ben N G Giepmans Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Ben N G Giepmans Author Details * Ulrike Schnell Search for this author in: * NPG journals * PubMed * Google Scholar * Freark Dijk Search for this author in: * NPG journals * PubMed * Google Scholar * Klaas A Sjollema Search for this author in: * NPG journals * PubMed * Google Scholar * Ben N G Giepmans Contact Ben N G Giepmans Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–9 and Supplementary Methods Additional data
Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins
- Nat Methods 9(2):159-172 (2012)
Nature Methods | Analysis Principles for applying optogenetic tools derived from direct comparative analysis of microbial opsins * Joanna Mattis1, 2, 7 * Kay M Tye1, 7 * Emily A Ferenczi1, 2, 7 * Charu Ramakrishnan1 * Daniel J O'Shea1, 2 * Rohit Prakash1, 2 * Lisa A Gunaydin1, 2 * Minsuk Hyun1 * Lief E Fenno1, 2 * Viviana Gradinaru1, 3 * Ofer Yizhar1, 4 * Karl Deisseroth1, 2, 3, 5, 6 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:159–172Year published:(2012)DOI:doi:10.1038/nmeth.1808Received 09 May 2011 Accepted 10 November 2011 Published online 18 December 2011 Corrected online10 January 2012Corrected online10 January 2012 Abstract * Abstract * Accession codes * Change history * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Diverse optogenetic tools have allowed versatile control over neural activity. Many depolarizing and hyperpolarizing tools have now been developed in multiple laboratories and tested across different preparations, presenting opportunities but also making it difficult to draw direct comparisons. This challenge has been compounded by the dependence of performance on parameters such as vector, promoter, expression time, illumination, cell type and many other variables. As a result, it has become increasingly complicated for end users to select the optimal reagents for their experimental needs. For a rapidly growing field, critical figures of merit should be formalized both to establish a framework for further development and so that end users can readily understand how these standardized parameters translate into performance. Here we systematically compared microbial opsins under matched experimental conditions to extract essential principles and identify key parameters for the! conduct, design and interpretation of experiments involving optogenetic techniques. View full text Subject terms: * Neuroscience Figures at a glance * Figure 1: Properties of depolarizing optogenetic tools. () Depolarizing tool classes. White bars indicate mutations. () Construct design and representative image for in vitro characterization. Scale bar, 50 μm. () Normalized representative photocurrents. Scale bars, 400 pA, 200 ms. Horizontal scale bar applies to all traces. Color and shape legend applies throughout the figure. () Action spectra (n = 5–11). () Peak (filled bars) and steady-state (hollow bars) photocurrents to 1 s light (n = 8–27). () Time to peak (n = 8–27) versus τdes (n = 8–50). Traces show normalized representative ChR2 (black) and C1V1TT (red) onset photocurrents. Vertical scale bars represent 200 pA, bars indicate time to peak, and blue arrow indicates ongoing light pulse. () Recovery from desensitization (n = 5–20). Vertical and horizontal scale bars represent 1 nA and 2 s. () Normalized representative traces and summary plots of τoff (n = 8–53). Scale bars, 200 pA and 25 ms. () Peak and steady-state photocurrents across light intensities. In! set, representative ChR2 photocurrents at low (light gray) versus high (dark gray) light intensity. Scale bars, 250 pA and 250 ms. EPD50 for peak (filled bars) and steady state (hollow bars) (n = 5–15). () τoff versus EPD50 and peak and steady-state photocurrents. All population data are plotted as mean ± s.e.m. *P < 0.05, **P < 0.01 and ***P < 0.001. Unless otherwise indicated, C1V1T and C1V1TT were activated with 560-nm light, and all other tools were activated with 470-nm light at ~5 mW mm−2. * Figure 2: Performance of depolarizing tools. () Proportion of successfully evoked spikes (of 40 pulses; 5–100 Hz) at different light intensities (n = 8–18). Colors and shapes apply throughout the figure. () Temporal stationarity at 20 Hz, 2 mW mm−2 (n = 8–18), based on the proportion of successful spikes in each quartile of pulses. Vertical and horizontal scale bars represent 40 mV and 1 s, respectively. () Representative evoked spiking across stimulation frequencies for ChIEF, FR and CatCh with closely matched ~1.5 nA steady-state photocurrents at 6 mW mm−2. Vertical and horizontal scale bars represent 40 mV and 1 s, respectively. () Comparison of spiking performance between ChR2R (n = 19) and CatCh (n = 12) in cell-attached mode at 6 mW mm−2. () Plateau potential across pulse frequencies at 6 mW mm−2 (n = 5–17). () Mean plateau potential for each opsin plotted against τoff, steady-state photocurrents and projected peak photocurrents. All values taken from the 6 mW mm−2 condition. () Latency spread ! across a pulse train, illustrated by representative traces of 40 consecutive ChR2 spikes in a train, aligned to the light pulse and overlaid. Vertical and horizontal scale bars represent 40 mV and 10 ms, respectively. All population data are plotted as mean ± s.e.m. *P < 0.05 and **P < 0.01. C1V1T and C1V1TT were activated with 560-nm light, and all other opsins were activated with 470-nm light. * Figure 3: Properties and performance of ultrafast depolarizing tools. () Schemata and normalized photocurrents for ChETAs and ChR2. White bars indicate mutations. Colors and shapes apply throughout the figure. Scale bars, 500 pA and 500 ms. Horizontal scale bar applies to all traces. () Action spectra (n = 5–12). () Peak (filled bars) and steady-state (hollow bars) photocurrents (n = 9–35). () Recovery from desensitization (n = 8–20). () ChETAA and ChETATR expression in fast-spiking neurons using a Cre recombinase–dependent strategy. Scale bar, 50 μm. () Steady-state photocurrents (n = 9), τoff (n = 7), and consecutively evoked spikes for ChETAA and ChETATR (5 Hz, 2-ms light pulses). Scale bars, 20 mV and 1 ms. () τoff at −70 mV to +50 mV (n = 7–12). () ChETAA and ChIEF expression (scale bar, 50 μm). () Steady-state photocurrents (n = 9–13), τoff (n = 7), and evoked high and low frequency firing (200 Hz and 20 Hz). Scale bars, 25 mV and 25 ms. () ChIEF-expressing neurons with small (190 pA) or large (510 pA) photocurrents, u! nder stringent or permissive conditions (1 ms or 5 ms pulse width). Vertical scale bar, 20 mV. Horizontal scale bars, 50 ms (left) and 10 ms (right). Spiking performance and multiple spike likelihood (under those same conditions) for all cells. All population data is plotted as mean ± s.e.m. *P < 0.05 and ***P < 0.001. Cells were illuminated with 470-nm light at ~5 mW mm−2, unless otherwise specified. * Figure 4: Relationship between off kinetics and light sensitivity of optogenetic tools. Summary plot (on a log-log scale) of the relationship between τoff versus EPD50 for all depolarizing tools from Figures 1 and 3, plus VChR1, SFO(C128S) and SSFO(C128S/D156A). Dashed line represents best fit regression with R2 = 0.83; Spearman correlation coefficient R = −0.93, P < 0.001. Values for SFO and SSFO were estimated from previous publications11, 15 and did not contribute to the regression or correlation calculations. * Figure 5: Properties of hyperpolarizing tools. () NpHR is an inward chloride pump (halorhodopsin type; HR), whereas Arch, ArchT, and Mac are outward proton pumps (bacteriorhodopsin type; BR). The 3.0 versions include the endoplasmic reticulum export sequence (ER) after the fluorophore (which constitutes the 2.0 version) as well as a trafficking sequence (TS) between opsin and fluorophore. () Confocal images of 1.0 (the originally described version of the molecule) and 3.0 versions (green) expressed in culture and immunolabeled with an ER marker (KDEL; red). Scale bar, 25 μm. () Representative traces and raw photocurrents in response to 1 s light for 1.0 (open bars) versus 3.0 versions (closed bars) for Arch (n = 15–19), ArchT (n = 14–16) and Mac (n = 8–12). Vertical and horizontal scale bars represent 500 pA and 500 ms, respectively. Photocurrents were normalized to eNpHR3.0 values from within the same experiment to enable direct comparisons across opsins (n = 8–35). () Action spectra for 3.0 versions (n = 7–2! 0) alongside ChR2 (black). () τon and τoff (n = 7–35). Vertical and horizontal scale bars represent 200 pA and 5 ms, respectively. () EPD50 values for all hyperpolarizing opsins (n = 5–14). Raw photocurrent versus light power density plotted alongside within-experiment eNpHR3.0 (n = 5–14). Population data are plotted as mean ± s.e.m. *P < 0.05, **P < 0.01 and ***P < 0.001. Unless otherwise indicated, eNpHR3.0 was activated with 590-nm light, and all other tools were activated with 560-nm light, both at ~5 mW mm−2. * Figure 6: Performance of hyperpolarizing tools. () Confocal images of eNpHR3.0 and eArch3.0 expression at the injection site in medial prefrontal cortex (mPFC) and the downstream basolateral amygdala (BLA). Scale bars, 250 μm and 25 μm. DAPI staining (white) delineates cell bodies. () Mean input resistances for opsin-expressing cells and eYFP controls (n = 10–22). () Representative traces and mean onset photocurrents for eNpHR3.0 and eArch3.0 in response to 60 s 5 mW mm−2 light pulses (n = 8–10). Vertical and horizontal scale bars represent 400 pA and 10 s, respectively. () Mean peak hyperpolarization generated by eNpHR3.0 and eArch3.0 with 60 s 5 mW mm−2 light pulses (n = 6–10). () Suppression of current injection–evoked spiking in reliably firing cells by 60 s of continuous light in cells expressing eNpHR3.0 or eArch3.0. Cells were illuminated with light power densities set to achieve approximately matched hyperpolarization. Vertical and horizontal scale bars represent 40 mV and 20 s, respectively. () Rela! tionship between hyperpolarization magnitude and cell stability. Post-light recovery of evoked spiking (relative to pre-light performance) and change in resting potential plotted against light-evoked hyperpolarization. Population data are plotted as mean ± s.e.m. *P < 0.05 and **P < 0.01. eNpHR3.0 was activated with 590-nm light, and eArch3.0 was activated with 560-nm light. Accession codes * Abstract * Accession codes * Change history * Author information * Supplementary information Referenced accessions GenBank * ACD70142.1 Change history * Abstract * Accession codes * Change history * Author information * Supplementary informationCorrected online 10 January 2012In the version of this article initially published online, the x-axis labels in Figure 5d were incorrectly labeled. The error has been corrected for the print, PDF and HTML versions of this article.Corrected online 10 January 2012In the version of this article initially published online, in the Discussion the statement "to achieve sufficient activation of cells far from the light source may require excessive hyperpolarization" was incorrect. The error has been corrected for the print, PDF and HTML versions of this article. Author information * Abstract * Accession codes * Change history * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Joanna Mattis, * Kay M Tye & * Emily A Ferenczi Affiliations * Department of Bioengineering, Stanford University, Stanford, California, USA. * Joanna Mattis, * Kay M Tye, * Emily A Ferenczi, * Charu Ramakrishnan, * Daniel J O'Shea, * Rohit Prakash, * Lisa A Gunaydin, * Minsuk Hyun, * Lief E Fenno, * Viviana Gradinaru, * Ofer Yizhar & * Karl Deisseroth * Neuroscience Program, Stanford University, Stanford, California, USA. * Joanna Mattis, * Emily A Ferenczi, * Daniel J O'Shea, * Rohit Prakash, * Lisa A Gunaydin, * Lief E Fenno & * Karl Deisseroth * CNC Program, Stanford University, Stanford, California, USA. * Viviana Gradinaru & * Karl Deisseroth * Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel. * Ofer Yizhar * Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA. * Karl Deisseroth * Howard Hughes Medical Institute, Stanford University, Stanford, California, USA. * Karl Deisseroth Contributions J.M., K.M.T., E.A.F., C.R., R.P., O.Y. and K.D. contributed to study design and data interpretation. J.M. coordinated all experiments and data analysis. J.M., K.M.T., E.A.F., D.J.O., R.P. and L.E.F. contributed to acquisition of electrophysiological data. C.R. cloned all constructs, cultured primary neurons, performed transfections and managed viral packaging processes. D.J.O. wrote custom analysis scripts and analyzed all electrophysiological data. M.H. contributed to data analysis. J.M., K.M.T., C.R., L.A.G. and V.G. contributed to the histological processing and fluorescence imaging. K.D. supervised all aspects of the work. J.M., K.M.T., E.A.F. and K.D. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Karl Deisseroth Author Details * Joanna Mattis Search for this author in: * NPG journals * PubMed * Google Scholar * Kay M Tye Search for this author in: * NPG journals * PubMed * Google Scholar * Emily A Ferenczi Search for this author in: * NPG journals * PubMed * Google Scholar * Charu Ramakrishnan Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel J O'Shea Search for this author in: * NPG journals * PubMed * Google Scholar * Rohit Prakash Search for this author in: * NPG journals * PubMed * Google Scholar * Lisa A Gunaydin Search for this author in: * NPG journals * PubMed * Google Scholar * Minsuk Hyun Search for this author in: * NPG journals * PubMed * Google Scholar * Lief E Fenno Search for this author in: * NPG journals * PubMed * Google Scholar * Viviana Gradinaru Search for this author in: * NPG journals * PubMed * Google Scholar * Ofer Yizhar Search for this author in: * NPG journals * PubMed * Google Scholar * Karl Deisseroth Contact Karl Deisseroth Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–17, Supplementary Tables 1–2 Additional data
HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment
- Nat Methods 9(2):173-175 (2012)
Nature Methods | Brief Communication HHblits: lightning-fast iterative protein sequence searching by HMM-HMM alignment * Michael Remmert1 * Andreas Biegert1 * Andreas Hauser1 * Johannes Söding1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:173–175Year published:(2012)DOI:doi:10.1038/nmeth.1818Received 29 July 2011 Accepted 01 December 2011 Published online 25 December 2011 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Sequence-based protein function and structure prediction depends crucially on sequence-search sensitivity and accuracy of the resulting sequence alignments. We present an open-source, general-purpose tool that represents both query and database sequences by profile hidden Markov models (HMMs): 'HMM-HMM–based lightning-fast iterative sequence search' (HHblits; http://toolkit.genzentrum.lmu.de/hhblits/). Compared to the sequence-search tool PSI-BLAST, HHblits is faster owing to its discretized-profile prefilter, has 50–100% higher sensitivity and generates more accurate alignments. View full text Subject terms: * Bioinformatics * Structural Biology * Biophysics Figures at a glance * Figure 1: Workflow and benchmark comparison. () HHblits can iteratively search for homologous sequences in large databases such as UniProt. The HHblits database is a clustered version in which each set of full-length alignable sequences is represented by an HMM. Sequences from matched HMMs with a statistically significant E value are added to the query MSA, from which a new HMM is calculated for the next search iteration. A prefilter reduces the number of full HMM-HMM alignments by ~2,500-fold. () Median run times for searches with 100 test sequences through the UniProt or UniProt20 database (the inset shows the test sequence length distribution). () True positive pairs (same SCOP fold) compared to false positive pairs (different SCOP fold) for one and three search iterations in an all-against-all comparison. FDR, false discovery rate. () Mean fraction of correctly aligned residue pairs out of all structurally alignable pairs (sensitivity) compared to the fraction of correctly aligned pairs out of all the aligned pairs! (precision). The parameter mact controls the alignment greediness (Supplementary Fig. 10). * Figure 2: Structure predictions for Pfam families and the modeling of human Pip49 (also known as FAM69B). () Families to which only HHblits and both HHblits and HMMER3 assigned a structural template below a given E value. () Homology model of human Pip49 kinase domain (blue) with the inserted EF hand (green). () Catalytic center showing the conserved residues (red) for protein kinase activity. () EF hand insertion with the conserved residues (magenta) for the predicted Ca2+-dependent activation. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Protein Data Bank * 1RDQ * 3C1V * 1RDQ * 3C1V Author information * Accession codes * Author information * Supplementary information Affiliations * Gene Center and Center for Integrated Protein Science Munich, Ludwig-Maximilians Universität München, Munich, Germany. * Michael Remmert, * Andreas Biegert, * Andreas Hauser & * Johannes Söding Contributions M.R. performed research, J.S. initiated and guided research, A.B. generated the profile-column alphabet, A.H. contributed code for fast file access, and M.R. and J.S. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Johannes Söding Author Details * Michael Remmert Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Biegert Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Hauser Search for this author in: * NPG journals * PubMed * Google Scholar * Johannes Söding Contact Johannes Söding Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–10, Supplementary Tables 1 and 2 Text files * Supplementary Data 1 (57K) 100 random sequences from the nr database used for run time benchmark. * Supplementary Data 2 (90K) List of query-template pairs for alignment benchmark. * Supplementary Data 3 (168K) 3D homology model of PIP49/FAM69B. * Supplementary Data 4 (180K) Training and test set of SCOP domain sequence for sensitivity benchmark. * Supplementary Data 5 (721K) FASTA formatted multiple sequence alignment for human PIP49/FAM69B built by HHblits. Additional data
Detection of structural variants and indels within exome data
- Nat Methods 9(2):176-178 (2012)
Nature Methods | Brief Communication Detection of structural variants and indels within exome data * Emre Karakoc1 * Can Alkan1, 2 * Brian J O'Roak1 * Megan Y Dennis1 * Laura Vives1 * Kenneth Mark1 * Mark J Rieder1 * Debbie A Nickerson1 * Evan E Eichler1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:176–178Year published:(2012)DOI:doi:10.1038/nmeth.1810Received 15 July 2011 Accepted 16 November 2011 Published online 18 December 2011 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We report an algorithm to detect structural variation and indels from 1 base pair (bp) to 1 Mbp within exome sequence data sets. Splitread uses one end–anchored placements to cluster the mappings of subsequences of unanchored ends to identify the size, content and location of variants with high specificity and sensitivity. The algorithm discovers indels, structural variants, de novo events and copy number–polymorphic processed pseudogenes missed by other methods. View full text Subject terms: * Bioinformatics * Genomics * Sequencing * Genetics Figures at a glance * Figure 1: Splitread definition and analyses. () Schematic diagrams for mapping paired-end sequences in cases of a deletion (red) or an insertion (blue) with respect to the reference sequence. In each case, one end–anchored sequence was used to map one read in a pair. The second (unmapped) read was then decomposed into either two equal subsequences (balanced split) or two unequal subsequences (unbalanced split). () Number of Splitread predictions called by 1000 Genomes versus total number of Splitread predictions using indicated threshold numbers of balanced and unbalanced reads, respectively. () Venn diagram of variants detected by Splitread exome analysis versus whole-genome sequence analysis of NA12891 (black) or all variants within dbSNP130 (red). To intersect, variants must be at same position and within 10 bp of the predicted size. () Length distribution of predicted insertions and deletions mapping within coding region of NA12891. Red, events with multiples of 3 bp; blue, events that would disrupt the frame. ()! Venn diagram of Pindel, GATK and Splitread call sets on NA12891. Black, total number of events; red, events previously detected as part of dbSNP130 and/or the 1000 Genomes Project. * Figure 2: Validation of processed pseudogenes. () Gene models and predicted intron deletions of processed pseudogenes. Primers (red triangles) were designed in coding regions. We detected the expected product size for processed pseudogenes for TMEM5 (), C13orf3 (), ATP9B (), MFF () and TMEM66 () in our PCR experiments. In , we genotyped the processed pseudogenes MFF and TMEM66 within eight HapMap samples; each was amplified only in the predicted sample (boxed in yellow, NA19238 (MFF) and NA12891 (TMEM66)). All PCRs amplified the normal gene (signal on top), with only one sample each amplifying the processed gene. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Sequence Read Archive * SRA039053 Author information * Accession codes * Author information * Supplementary information Affiliations * Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA. * Emre Karakoc, * Can Alkan, * Brian J O'Roak, * Megan Y Dennis, * Laura Vives, * Kenneth Mark, * Mark J Rieder, * Debbie A Nickerson & * Evan E Eichler * Howard Hughes Medical Institute, Seattle, Washington, USA. * Can Alkan & * Evan E Eichler Contributions E.K. designed and implemented the Splitread algorithm; E.K. and C.A. analyzed data; B.J.O., L.V., M.J.R. and D.A.N. generated sequencing data; M.Y.D. and K.M. carried out validation experiments and analyzed processed pseudogenes and E.K., C.A. and E.E.E. wrote the manuscript. Competing financial interests E.E.E. is a member of the Scientific Advisory Board of Pacific Biosciences. Corresponding author Correspondence to: * Evan E Eichler Author Details * Emre Karakoc Search for this author in: * NPG journals * PubMed * Google Scholar * Can Alkan Search for this author in: * NPG journals * PubMed * Google Scholar * Brian J O'Roak Search for this author in: * NPG journals * PubMed * Google Scholar * Megan Y Dennis Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Vives Search for this author in: * NPG journals * PubMed * Google Scholar * Kenneth Mark Search for this author in: * NPG journals * PubMed * Google Scholar * Mark J Rieder Search for this author in: * NPG journals * PubMed * Google Scholar * Debbie A Nickerson Search for this author in: * NPG journals * PubMed * Google Scholar * Evan E Eichler Contact Evan E Eichler Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1 and 2, Supplementary Tables 1–6 and Supplementary Note Additional data
A linear complexity phasing method for thousands of genomes
- Nat Methods 9(2):179-181 (2012)
Nature Methods | Brief Communication A linear complexity phasing method for thousands of genomes * Olivier Delaneau1, 2 * Jonathan Marchini2 * Jean-François Zagury1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:179–181Year published:(2012)DOI:doi:10.1038/nmeth.1785Received 15 March 2011 Accepted 17 October 2011 Published online 04 December 2011 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Human-disease etiology can be better understood with phase information about diploid sequences. We present a method for estimating haplotypes, using genotype data from unrelated samples or small nuclear families, that leads to improved accuracy and speed compared to several widely used methods. The method, segmented haplotype estimation and imputation tool (SHAPEIT), scales linearly with the number of haplotypes used in each iteration and can be run efficiently on whole chromosomes. View full text Figures at a glance * Figure 1: Illustration of the model and the associated graphs for a simple example. (,) In this example, contains K = 8 haplotypes (rows in ) and the individual's genotype contains four heterozygous SNPs (), both defined over M = 8 markers (columns). In , we illustrate how the graph g is built by splitting the haplotypes of between markers 4 and 5, resulting in two segments that each contain J = 3 distinct haplotypes. The nodes of the graph are labeled either with allele 1 or allele 0. Each edge is weighted by the number of haplotypes in that traverse it. A haplotype of and its corresponding path in g is illustrated in magenta. In , we illustrate how the graph g is built by making two segments of five and three SNP markers, each one containing two heterozygous markers in (represented as state 1; state 0 and 2 are wild type and homozygous, respectively). Each segment has four possible haplotypes compatible with . A pair of paths in g compatible with is colored blue and green. * Figure 2: Accuracy and computational burden as a function of the number of conditioning states. (–) Switch error rate plotted against N for all the methods tested on the European, WTCCC2 and Vietnamese datasets, respectively. For SHAPEIT, this is the number of collapsed states (N = J). For Impute2 and MaCH, it is the size of the subset of the K haplotypes used in each iteration. Error rates of Fastphase and Beagle are represented as lines because default settings were used. (–) Running times plotted against N. We fit linear regression to the SHAPEIT running times and quadratic regression to the Impute2 and MaCH running times; these lines are plotted. Dashed lines are extrapolations. Author information * Author information * Supplementary information Affiliations * Chaire de Bioinformatique, Laboratoire Génomique, Bioinformatique, et Applications (Equipe d'accueil 4627), Conservatoire National des Arts et Métiers, Paris, France. * Olivier Delaneau & * Jean-François Zagury * Department of Statistics, University of Oxford, Oxford, UK. * Olivier Delaneau & * Jonathan Marchini Contributions O.D. derived the algorithm and carried out all the experiments. J.-F.Z. supervised the research. J.M. gave advice on experiments and the interpretation of results. O.D., J.-F.Z. and J.M. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jean-François Zagury Author Details * Olivier Delaneau Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan Marchini Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-François Zagury Contact Jean-François Zagury Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–3, Supplementary Tables 1–3 and Supplementary Note Additional data
Blotting protein complexes from native gels to electron microscopy grids
- Nat Methods 9(2):182-184 (2012)
Nature Methods | Brief Communication Blotting protein complexes from native gels to electron microscopy grids * Roland Wilhelm Knispel1, 2 * Christine Kofler1, 2 * Marius Boicu1 * Wolfgang Baumeister1 * Stephan Nickell1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:182–184Year published:(2012)DOI:doi:10.1038/nmeth.1840Received 18 May 2011 Accepted 05 December 2011 Published online 08 January 2012 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We report a simple and generic method for the direct transfer of protein complexes separated by native gel electrophoresis to electron microscopy grids. After transfer, sufficient material remains in the gel for identification and characterization by mass spectrometry. The method should facilitate higher-throughput single-particle analysis by substantially reducing the time needed for protein purification, as demonstrated for three complexes from Thermoplasma acidophilum. View full text Subject terms: * Biochemistry * Biophysics * Structural Biology Figures at a glance * Figure 1: Grid-blotting procedure. () Two different protein mixtures containing protein complexes of thermosomes (Ths.; lanes 1 and 1′), 20S proteasomes (20S; lanes 2 and 2′) and VAT (lanes 2 and 2′) were loaded in duplicate with a molecular weight marker (M) on a native electrophoresis gel. Both fractions originated from our protein-complex enrichment scheme and contained smaller molecular weight proteins as impurities. After electrophoresis, the gel was split (dashed line) into 'reference lanes' (M, 1 and 2; stained with Coomassie Blue and then de-stained) and 'blotting lanes' (1′ and 2′; kept at 4 °C in a humid environment). () Then both gel parts were aligned, and nonstained protein bands were localized by manually extrapolating from the position of stained bands across horizontal lines toward the 'blotting lanes'. () At the localized protein spots, the gel surface was roughened. () Protein complexes were blotted by placing the electron microscopy grids directly onto the gel. The grid-gel inter! faces were wetted by applying 5 μl of electrophoresis buffer. After 2 min the grids were removed and either negatively stained or plunge-frozen. * Figure 2: Electron micrographs of protein complexes blotted from native gels. (–) Micrographs of thermosomes (), 20S proteasomes () and VAT () negatively stained with 2% uranyl acetate after grid blotting. (–) Micrographs of vitrified, unstained samples obtained using continuous carbon film with a thickness of ~2 nm; as shown for thermosomes () and for 20S proteasomes (). In the case of holey carbon films, protein complexes tend to adsorb at the carbon support film, thereby depleting the protein concentration in the free ice layer. This effect is illustrated by showing the accumulation of 20S proteasome particles at Lacey carbon bars (). The applied defocus setting was between −2 and −2.6 μm for – and −4.5 μm for . Insets in – show representative class averages for each particle species and have an edge length of 20 nm × 20 nm. Scale bars, 40 nm. Author information * Author information * Supplementary information Affiliations * Max Planck Institute of Biochemistry, Department of Molecular Structural Biology, Martinsried, Germany. * Roland Wilhelm Knispel, * Christine Kofler, * Marius Boicu, * Wolfgang Baumeister & * Stephan Nickell * Present addresses: ChemAxon Kft., Budapest, Hungary (R.W.K.), Tietz Video and Image Processing Systems GmbH, Gauting, Germany (C.K.) and Carl Zeiss NTS GmbH, Oberkochen, Germany (S.N.). * Roland Wilhelm Knispel, * Christine Kofler & * Stephan Nickell Contributions R.W.K., C.K. and S.N. designed and conducted the grid-blotting experiments. R.W.K. and M.B. prepared protein samples. R.W.K. and S.N. acquired electron microscopy data, analyzed images and prepared the figures. R.W.K., W.B. and S.N. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Wolfgang Baumeister Author Details * Roland Wilhelm Knispel Search for this author in: * NPG journals * PubMed * Google Scholar * Christine Kofler Search for this author in: * NPG journals * PubMed * Google Scholar * Marius Boicu Search for this author in: * NPG journals * PubMed * Google Scholar * Wolfgang Baumeister Contact Wolfgang Baumeister Search for this author in: * NPG journals * PubMed * Google Scholar * Stephan Nickell Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–4 and Supplementary Table 1 Additional data
Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton
- Nat Methods 9(2):185-188 (2012)
Nature Methods | Brief Communication Dual-objective STORM reveals three-dimensional filament organization in the actin cytoskeleton * Ke Xu1 * Hazen P Babcock2 * Xiaowei Zhuang1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:185–188Year published:(2012)DOI:doi:10.1038/nmeth.1841Received 12 October 2011 Accepted 04 December 2011 Published online 08 January 2012 Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg By combining astigmatism imaging with a dual-objective scheme, we improved the image resolution of stochastic optical reconstruction microscopy (STORM) and obtained <10-nm lateral resolution and <20-nm axial resolution when imaging biological specimens. Using this approach, we resolved individual actin filaments in cells and revealed three-dimensional ultrastructure of the actin cytoskeleton. We observed two vertically separated layers of actin networks with distinct structural organizations in sheet-like cell protrusions. View full text Subject terms: * Microscopy * Imaging * Cell Biology Figures at a glance * Figure 1: Experimental setup and spatial resolution of dual-objective 3D STORM. () Schematic of setup. Two microscope objectives are placed opposite each other and focused on the same spot of the sample. Astigmatism is introduced into the images collected by both objectives using a cylindrical lens. M, mirror; Obj., objective; LP, long-pass filter; CL, cylindrical lens; BP, band-pass filter. () Localization precision of Alexa Fluor 647 molecules in fixed cells measured with dual-objective STORM. Each molecule gives a cluster of localizations owing to repetitive activation of the same molecule. Localizations from 108 clusters (each containing >10 localizations) are aligned by their center of mass to generate the 3D presentation of the localization distribution. Histograms of distribution in x, y and z are fit to Gaussian functions, and the resultant s.d. (σx, σy and σz) is shown. () Distribution of number of photons detected for individual Alexa Fluor 647 molecules through both objectives (red; average, 10,600) and from a single objective (black; aver! age, 5,200). () Images of activated Alexa Fluor 647 molecules obtained from two objectives in a single frame. A molecule that appears elongated in x through one objective should appear elongated in y through the opposing objective (examples, green and blue arrows). In contrast, if two nearby molecules were mistaken for a single molecule, the images obtained through both objectives would appear elongated in the same direction along the line that connects the two molecules (example, magenta arrows). Scale bar, 2 μm. * Figure 2: Dual-objective 3D STORM resolves individual actin filaments in cells. () Dual-objective STORM image of actin (labeled with Alexa Fluor 647-phalloidin) in a COS-7 cell. The z positions are color coded (violet and red, positions closest to and farthest from substratum, respectively). () Close-up of boxed region in . () STORM image of same area obtained by using only information collected by Objective 1 of dual-objective setup. () Conventional fluorescence image of same area. () Cross-sectional profile of eight filaments aligned by the center of each filament. Red line, Gaussian fit with FWHM of 12 nm. () Cross-sectional profiles for two nearby filaments in , (white arrows). Gray bars, dual-objective images in ; red line, single-objective image in . Scale bars, 2 μm (), 500 nm (–). * Figure 3: Sheet-like cell protrusion comprises two layers of actin networks with distinct structures. () Dual-objective STORM image of actin in a BSC-1 cell. The z positions are color coded (color bar). (,) Vertical cross sections (each 500-nm wide in x or y) of cell in along dotted and dashed lines, respectively. When far from cell edge, z position of dorsal layer increases quickly and falls out of imaging range. (,) The z profiles for two points along vertical section (red and yellow arrows in , respectively). Each histogram is fit to two Gaussians (red curves), yielding apparent thickness of ventral and dorsal layers and peak separation between the two layers. () Quantification of apparent thickness averaged over two layers and dorsal-ventral separation obtained from x–z cross-section profile in . (,) Ventral and dorsal actin layers of cell in . (,) Ventral and dorsal actin layers of a COS-7 cell treated with blebbistatin. (,) Vertical cross sections (each 500-nm wide in x or y) of cell along dotted and dashed lines, respectively. () Actin density of ventral and dorsal ! layers along yellow box in ,, measured by localization density. Scale bars, 2 μm (,–); 100 nm for z and 2 μm for x and y (,,,). Author information * Author information * Supplementary information Affiliations * Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA. * Ke Xu & * Xiaowei Zhuang * Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA. * Hazen P Babcock * Department of Physics, Harvard University, Cambridge, Massachusetts, USA. * Xiaowei Zhuang Contributions K.X., H.P.B. and X.Z. designed research. K.X. did experiments and data analysis. H.P.B. assisted with the optical setup. K.X. and X.Z. prepared the manuscript. X.Z. supervised the project. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Xiaowei Zhuang Author Details * Ke Xu Search for this author in: * NPG journals * PubMed * Google Scholar * Hazen P Babcock Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaowei Zhuang Contact Xiaowei Zhuang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (24M) Supplementary Figures 1–7, Supplementary Results, Supplementary Discussion and Supplementary Protocols 1–2 Zip files * Supplementary Software (8K) Analysis software Additional data
Visualizing adenosine-to-inosine RNA editing in the Drosophila nervous system
- Nat Methods 9(2):189-194 (2012)
Nature Methods | Article Visualizing adenosine-to-inosine RNA editing in the Drosophila nervous system * James E C Jepson1, 2 * Yiannis A Savva1 * Kyle A Jay1, 3 * Robert A Reenan1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:189–194Year published:(2012)DOI:doi:10.1038/nmeth.1827Received 08 June 2011 Accepted 17 November 2011 Published online 25 December 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Informational recoding by adenosine-to-inosine RNA editing diversifies neuronal proteomes by chemically modifying structured mRNAs. However, techniques for analyzing editing activity on substrates in defined neurons in vivo are lacking. Guided by comparative genomics, here we reverse-engineered a fluorescent reporter sensitive to Drosophila melanogaster adenosine deaminase that acts on RNA (dADAR) activity and alterations in dADAR autoregulation. Using this artificial dADAR substrate, we visualized variable patterns of RNA-editing activity in the Drosophila nervous system between individuals. Our results demonstrate the feasibility of structurally mimicking ADAR substrates as a method to regulate protein expression and, potentially, therapeutically repair mutant mRNAs. Our data suggest variable RNA editing as a credible molecular mechanism for mediating individual-to-individual variation in neuronal physiology and behavior. View full text Subject terms: * Molecular Biology * Molecular Engineering * Neuroscience * Sensors and Probes Figures at a glance * Figure 1: Molecular design of a fluorescent reporter of RNA editing. () Organization of endogenous Syt1 (top) and experimentally verified dsRNA secondary structures8 in the pre-mRNA (bottom). Exonic sequences (black) base pair with intronic sequences (blue) to generate this structure. I/V and I/M refer to amino-acid alterations owing to editing at sites C and D, respectively. () Insertion of Syt1 intron 9 into the open reading frame of GFP in such a way that the second-position guanosine (green) of a tryptophan codon (TGG) is positioned at precisely the same position as the edited adenosine of site D. () Mutations (red) introduced into the construct in restore the secondary structure (but not primary sequence) of the endogenous Syt1 dADAR substrate, and the tryptophan codon has been converted to an amber (UAG) nonsense codon. () Same structure as in , except that the tryptophan codon is wild type (UGG), and the construct (YFPsplice) encodes YFP rather than GFP. * Figure 2: GFPedit–derived fluorescence in Drosophila tissues. (,) Bright-field (top) and epi-fluorescence (excitation at 488 nm; bottom) whole-mount images of heads () and forelegs () of 1–2-day-old males expressing the YFPsplice control (left) or GFPedit in a wild-type (middle) or dAdar5g1 (right) background, driven by tub-Gal4. Lab, labelum; cly, clypeus. Images shown in the middle and on the right were exposed to the same fluorescence intensity. Scale bars, 100 μm. (,) In the adult nervous system, YFPsplice () and GFPedit () were driven by tub-Gal4. YFP and GFP were visualized using an antibody to GFP and a fluorescent Cy5-conjugated secondary antibody. z-dimension stacks show expression in the mushroom body lobes (α, β and γ) and antennal lobes (AL) (top). Confocal slices detail expression in the central complex (bottom; highlighted by arrowheads). Neuropil regions were labeled with an antibody to Bruchpilot (nc82). Scale bars, 20 μm. * Figure 3: Neuron-specific modulation of GFPedit–derived fluorescence by alterations in dADAR auto-editing. () Diagrams of the dAdar locus illustrating engineered mutations introduced using homologous recombination. The dAdarhyp allele is a result of insertion of a mini-white+ (mw+) marker into intron 7 of the dAdar locus, flanked by two LoxP sites (triangles). Excision of the mw+ by Cre recombinase leaves a single LoxP site. dAdarS and dAdarG recombinant flies have targeted mutations in the edited serine codon in exon 7 that either disrupts (dAdarS) or hard-wires (dAdarG) auto-editing. () Representative confocal z-dimension stacks of GFPedit–derived expression in the mushroom bodies (MBs) and antennal lobes (ALs) of hemizygous males of indicated genotypes. Merged confocal images of nc82 (antibody to Bruchpilot) and GFP (top). GFP fluorescence shown in glowscale to illustrate relative intensities (bottom). () Quantification of GFPedit–derived fluorescence in α/β and γ lobes of MBs and ALs in dAdarhyp (n = 14, 12 and 12, respectively), dAdarG (n = 65, 40 and 40) and dAdarS (! n = 66, 42 and 42) males, normalized to dAdarLoxP controls (n = 79, 48 and 48). ***P < 0.0001 relative to dAdarLoxP controls (one-way ANOVA with Dunnett post-hoc test). Error bars, s.e.m. Scale bars, 20 μm. * Figure 4: Variability in dADAR activity between individual male Drosophila. () Whole-head fluorescence images of five individual adult males expressing GFPedit (top; boxed regions are magnified below). Arrowheads highlight variable fluorescence in regions corresponding to the antennal lobes (ALs) and the Kenyon cells. () Examples of GFPedit–derived fluorescence in adult male forelegs. Scale bars, 100 μm. (–) Histograms of YFPsplice–derived (,) or GFPedit–derived (,) fluorescence in the clypeus (,) and in the large segment of adult forelegs (,). Values for the population studied were normalized such that the average fluorescence = 1. * Figure 5: Nonstereotypical patterns of RNA editing in Drosophila neurons. (,) Example images of variation in YFPsplice–derived () and GFPedit–derived () fluorescence in the mushroom bodies (MBs) and antennal lobes (ALs). Scale bars, 20 μm. (–) Histograms of YFPsplice–derived and GFPedit–derived expression in ALs and α/β and γ lobes of the MBs. () Correlation between the sensitivity of ten edited adenosines to changes in dADAR levels and coefficient of variation (CV) values between individuals for editing of each site in 14 male flies. Each edited mRNA was amplified from cDNA derived from individual head and thorax tissue, and the mean editing level calculated from 3–5 PCRs. As a proxy for sensitivity to dADAR expression changes, we used the percentage reduction relative to controls of editing in dAdarhyp thoraxes15. () Normalized mean editing levels in each fly (flies 1–14) relative to the group mean for sites (n = 6) that are reduced in editing in thoraxes of dAdarhyp flies (and also have CV > 0.08). Flies 1, 2 and 6 had signifi! cant deviations from the mean for the combined six editing sites (*P < 0.05, ***P < 0.0005, paired t-test), suggesting that dADAR activity was broadly higher (fly 2) or lower (flies 1 and 6). () For sites that were not reduced in editing in thoraxes of dAdarhyp flies (that is, were insensitive to changes in dADAR expression) (n = 4), only minimal variation between flies was observed, as expected. Error bars, s.e.m. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Molecular Biology, Cell Biology and Biochemistry, Brown University, Providence, Rhode Island, USA. * James E C Jepson, * Yiannis A Savva, * Kyle A Jay & * Robert A Reenan * Department of Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, USA. * James E C Jepson * Department of Biochemistry and Biophysics, University of California, San Francisco, California, USA. * Kyle A Jay Contributions J.E.C.J. performed all imaging experiments and analyzed the data. Y.A.S. and J.E.C.J. performed RNA-editing analysis. R.A.R. designed the GFPedit reporter. K.A.J. and R.A.R. cloned the GFPedit and YFPsplice constructs and performed in vitro validation experiments. Y.A.S. and J.E.C.J. generated the recombinant dAdar alleles. J.E.C.J. and R.A.R. wrote the paper, with contributions from Y.A.S. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Robert A Reenan Author Details * James E C Jepson Search for this author in: * NPG journals * PubMed * Google Scholar * Yiannis A Savva Search for this author in: * NPG journals * PubMed * Google Scholar * Kyle A Jay Search for this author in: * NPG journals * PubMed * Google Scholar * Robert A Reenan Contact Robert A Reenan Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–8 and Supplementary Table 1 Additional data
Bayesian localization microscopy reveals nanoscale podosome dynamics
- Nat Methods 9(2):195-200 (2012)
Nature Methods | Article Bayesian localization microscopy reveals nanoscale podosome dynamics * Susan Cox1, 7 * Edward Rosten2, 3, 7 * James Monypenny1 * Tijana Jovanovic-Talisman4 * Dylan T Burnette4 * Jennifer Lippincott-Schwartz4 * Gareth E Jones1 * Rainer Heintzmann1, 5, 6 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:195–200Year published:(2012)DOI:doi:10.1038/nmeth.1812Received 25 December 2010 Accepted 02 November 2011 Published online 04 December 2011 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We describe a localization microscopy analysis method that is able to extract results in live cells using standard fluorescent proteins and xenon arc lamp illumination. Our Bayesian analysis of the blinking and bleaching (3B analysis) method models the entire dataset simultaneously as being generated by a number of fluorophores that may or may not be emitting light at any given time. The resulting technique allows many overlapping fluorophores in each frame and unifies the analysis of the localization from blinking and bleaching events. By modeling the entire dataset, we were able to use each reappearance of a fluorophore to improve the localization accuracy. The high performance of this technique allowed us to reveal the nanoscale dynamics of podosome formation and dissociation throughout an entire cell with a resolution of 50 nm on a 4-s timescale. View full text Subject terms: * Microscopy * Imaging * Cell Biology * Biophysics Figures at a glance * Figure 1: Correlative measurements using PALM imaging and Bayesian localization imaging on tubulin. (,) Wide-field images created by averaging all the frames in the PALM image dataset of PA-GFP–tubulin () and by averaging all of the frames in the Bayesian localization image dataset of mCherry-tubulin (). (,) Super-resolution images generated by analyzing the PALM PA-GFP–tubulin dataset from using a standard PALM analysis5 () and by analyzing the mCherry-tubulin dataset from using a 3B analysis (). () An image generated from the PAGFP dataset from using a 3B analysis. () Overlay of and . Green arrows indicate regions with differences in apparent structure that arise from labeling differences. Linescans corresponding to lines i–iii are shown in –, respectively, with the 3B analysis data shown in blue, PALM data shown in pink, the 3B analysis PALM data shown in green and the wide-field data shown in black. Scale bars, 1 μm. AU, arbitrary units. * Figure 2: A 3B analysis of vinculin in fixed cells containing podosomes and labeled with Alexa 488. () An example of a maximum likelihood estimate for one set of MCMC samples superimposed on a wide-field image created by averaging all 300 images. () A probability map created by combining MAP positions created using different sets of MCMC samples. Scale bars, 500 nm. (,) A whole cell showing a wide-field () and 3B analysis (). The green rectangle corresponds to the enlarged image in , the blue rectangle corresponds to the enlarged image in , and the white rectangle corresponds to the enlarged image in . Scale bars, 500 nm (,); 2 mm (,); and 500 nm (–). * Figure 3: Podosomes, visualized using an mCherry-tagged truncated talin construct, forming and dissociating in a live cell. (,) A podosome being dissociated. Scale bars, 400 nm. () Podosomes being formed. Scale bar, 1 μm. () A steady-state podosome. Scale bar, 400 nm. Each reconstructed frame used 200 frames (4 s), and frames are spaced 600 frames (12 s) apart. Videos of the podosomes shown in – are provided as Supplementary Videos 3,4,5,6, respectively. * Figure 4: Dissociation and formation of groups of podosomes in a motile cell. (,) Dissociation and formation of linked podosomes. () Separated podosomes joining together. Each reconstructed frame used 200 frames (4 s), and frames are spaced 1,000 frames (20 s) apart. A video containing the podosomes shown in – as well as the rest of the cell is provided as Supplementary Video 7. Scale bars, 800 nm. * Figure 5: A 3B analysis of fixed-cell data to determine the colocalization of vinculin and the truncated talin construct in podosomes. () Wide-field image of vinculin labeled with Alexa 488. (,) The individual 3B analysis images shown in glowscale for talin () and vinculin (). () Superposition of images from the 3B analysis showing the truncated talin construct (in cyan) and vinculin 3B data (in magenta). Scale bars, 1 μm. * Figure 6: Simulations showing the performance of the 3B analysis method. (–) Ground truth simulated image data (,) and 3B analysis reconstructions (,). (–) For the simulations, the simulated wide-field image created by averaging all frames (,) and a typical frame (,) are shown. Images in and correspond to the boxed regions in and , respectively. (,) Linescans of the simulations and 3B analysis reconstructions show the 3B analysis method achieving good reproduction of the structure and a resolution of 50 nm. Scale bars, 50 nm (,); otherwise, 200 nm. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Susan Cox & * Edward Rosten Affiliations * Randall Division, King's College London, Guy's Campus, London, UK. * Susan Cox, * James Monypenny, * Gareth E Jones & * Rainer Heintzmann * Department of Engineering, University of Cambridge, Cambridge, UK. * Edward Rosten * Computer Vision Consulting Ltd., Lynton House, Woking, Surrey, UK. * Edward Rosten * National Institutes of Health, Cell Biology and Metabolism Branch, Bethesda, Maryland, USA. * Tijana Jovanovic-Talisman, * Dylan T Burnette & * Jennifer Lippincott-Schwartz * Institute of Physical Chemistry, Friedrich-Schiller University Jena, Jena, Germany. * Rainer Heintzmann * Institute of Photonic Technology, Jena, Germany. * Rainer Heintzmann Contributions S.C., J.M., T.J.–T., D.T.B., J.L.-S., G.E.J. and R.H. conceived of and designed the experiments. S.C. and E.R. conceived of and designed the analysis. J.M. prepared the podosome samples, and T.J.–T. and D.T.B. prepared the samples for correlative measurements. S.C. and J.M. performed live-cell experiments, S.C. carried out fixed-cell experiments on podosomes, and T.J.–T. and D.T.B. carried out the correlative measurements. E.R. and S.C. carried out the data analysis and wrote the manuscript, and all authors revised the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Susan Cox Author Details * Susan Cox Contact Susan Cox Search for this author in: * NPG journals * PubMed * Google Scholar * Edward Rosten Search for this author in: * NPG journals * PubMed * Google Scholar * James Monypenny Search for this author in: * NPG journals * PubMed * Google Scholar * Tijana Jovanovic-Talisman Search for this author in: * NPG journals * PubMed * Google Scholar * Dylan T Burnette Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer Lippincott-Schwartz Search for this author in: * NPG journals * PubMed * Google Scholar * Gareth E Jones Search for this author in: * NPG journals * PubMed * Google Scholar * Rainer Heintzmann Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (413K) Supplementary Figures 1–4 and Supplementary Note Movies * Supplementary Video 1 (766K) Raw data video of vinculin in fixed podosome samples. Samples were labeled with Alexa 488 and mounted in PBS with 100 mM mercaptoethanol added as a reducing agent to induce blinking. Sample was illuminated using a laser at 488nm with a nominal power of 1 kW/cm2. A series of 300 images were collected, taken at 50 frames per second. Scalebar is 500 nm. * Supplementary Video 2 (2.5M) Raw data video of live THP-1 cells stably expressing an mCherry tagged, truncated talin construct. Sample was illuminated with a Xenon arc lamp in the wavelength range 615-687 nm. Video shows the first 500 of 8,000 images taken at frame rates of 50 fps. Scalebar is 2 μm. * Supplementary Video 3 (406K) Widefield (left) and 3B (right) video of a podosome being dissociated by unwinding. A truncated talin construct is labeled. This video corresponds to Figure 3a in the main text. Each widefield and 3B image is generated from 200 frames (4 seconds) of raw data, and are spaced 50 frames (1 second) apart. Widefield images are created by averaging. Cells were maintained at 37C during imaging. Scalebar is 1 μm. * Supplementary Video 4 (577K) Widefield (left) and 3B (right) video of a podosome being dissociate by being drawn into its center. A truncated talin construct is labeled. This video corresponds to Figure 3b in the main text. Each widefield and 3B image is generated from 200 frames (4 s) of raw data, and are spaced 50 frames (1 s) apart. Widefield images are created by averaging. Cells were maintained at 37C during imaging. Scalebar is 1 μm. * Supplementary Video 5 (975K) Widefield (left) and 3B (right) video of podosomes being constructed. A truncated talin construct is labeled. This video corresponds to Figure 3c in the main text. Each widefield and 3B image is generated from 200 frames (4 seconds) of raw data, and are spaced 50 frames (1 second) apart. Widefield images are created by averaging. Cells were maintained at 37C during imaging. Scalebar is 1 μm. * Supplementary Video 6 (343K) Widefield (left) and 3B (right) video of a steady state podosome in which a truncated talin construct is labeled. This video corresponds to Figure 3d in the main text. Each widefield and 3B image is generated from 200 frames (4 seconds) of raw data, and are spaced 50 frames (1 second) apart. Widefield images are created by averaging. Cells were maintained at 37C during imaging. Scalebar is 500 nm. * Supplementary Video 7 (5M) Widefield (left) and 3B (right) video reveals podosomes in a motile cell to be highly dynamic. A truncated talin construct is labeled in these cells. This video includes, as a small part, the areas shown in Figure 4a–c in the main text. Each widefield and 3B image is generated from 200 frames (4 seconds) of raw data, and are spaced 100 frames (2 s) apart. Widefield images are created by averaging. Cells were maintained at 37C during imaging. Scalebar is 2 μm. Zip files * Supplementary Software (1.7M) 3B analysis software. Contains source code, test data and instructions for use. Additional data
Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes
- Nat Methods 9(2):201-208 (2012)
Nature Methods | Article Fast two-photon in vivo imaging with three-dimensional random-access scanning in large tissue volumes * Gergely Katona1, 5 * Gergely Szalay1, 5 * Pál Maák2, 5 * Attila Kaszás1, 3, 5 * Máté Veress2 * Dániel Hillier4 * Balázs Chiovini1 * E Sylvester Vizi1 * Botond Roska4 * Balázs Rózsa1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 9,Pages:201–208Year published:(2012)DOI:doi:10.1038/nmeth.1851Received 26 May 2011 Accepted 12 December 2011 Published online 08 January 2012 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The understanding of brain computations requires methods that read out neural activity on different spatial and temporal scales. Following signal propagation and integration across a neuron and recording the concerted activity of hundreds of neurons pose distinct challenges, and the design of imaging systems has been mostly focused on tackling one of the two operations. We developed a high-resolution, acousto-optic two-photon microscope with continuous three-dimensional (3D) trajectory and random-access scanning modes that reaches near-cubic-millimeter scan range and can be adapted to imaging different spatial scales. We performed 3D calcium imaging of action potential backpropagation and dendritic spike forward propagation at sub-millisecond temporal resolution in mouse brain slices. We also performed volumetric random-access scanning calcium imaging of spontaneous and visual stimulation–evoked activity in hundreds of neurons of the mouse visual cortex in vivo. These expe! riments demonstrate the subcellular and network-scale imaging capabilities of our system. View full text Subject terms: * Imaging * Neuroscience * Microscopy Figures at a glance * Figure 1: Design and characterization of the two-photon microscope setup. () Schematics of microscope setup. Material-dispersion compensation was adjusted with a four prism compressor and a Ti:S laser. A Faraday isolator eliminated coherent back reflections. Motorized mirrors (M) stabilized the position of the beam on the surface of two quadrant detectors (Q) before the beam expander. Two AO deflectors optimized for diffraction efficiency controlled the z focusing of the beam (AO z focusing). A 2D AO scanner unit (2D-AO scanning) performed x-y scanning and drift compensation during z scanning. A spherical field lens in the second telecentric lens system (Tc3 and Tc4) provided additional angular dispersion compensation. PMT, photomultiplier tubes. () The maximal field of view (compensated, black bar) is shown when both deflector pairs were used for deflection (no deflector grouping) or when optically rotated deflectors (no acoustic rotation), small aperture objectives (60× objective), no angular dispersion compensation (with angular dispersion) or! small aperture acousto-optic deflectors were used (small aperture). () The compensated PSF size along x axis (PSFx) (central, black bar) at (x, y, z) = (150, 150, 100) μm coordinates (lateral) or when no angular dispersion compensation (with angular dispersion), no electronic compensation (no electric compensation) or reduced AO apertures were applied (no large apertures). () PSFz and PSFx variation as a function of z depth and lateral AO scanning (x shift). Error bars are mean ± s.d., n = 5. () Temporal width of the laser pulse at the laser output (original), and before the objective lens with and without dispersion compensation (prechirp). () Five fluorescent beads (diameter 6 μm; locations, blue points) were repetitively scanned in random-access mode in an 800 μm × 600 μm × 500 μm sample. Image shows bead locations (right). Five overlaid fluorescence measurements are shown (left). * Figure 2: Three-dimensional measurement of BAPs with sub-millisecond resolution. () A 3D view of the dendritic arbor of a CA1 pyramidal cell imaged with 3D AO scanning (top, z stack); spheres represent the measurement locations. Maximum intensity z-projection image of the same neuron (bottom left); recorded dendrites are numbered. Schema of the apical trunk and the dendritic branches of the neuron (bottom right) showing calcium transients recorded near-simultaneously in each of the dendrites, averaged from five traces. Scale bars, 100 μm. () Dendritic Ca2+ transients measured from the same dendritic point of the apical trunk (average of five traces) and corresponding somatic voltage traces (Vm). () Experimental arrangement for signal propagation experiments. Signal propagation speed was measured by somatic whole-cell current-clamp (Vm, black), cell-attached current-clamp (cyan, purple) and 3D two-photon calcium imaging (orange, pink, green and blue). The same color-coding is used in –. () Triggered action potential peak and averaged and normalized bac! kpropagating calcium transients (mean ± s.e.m.; n = 54; top). Linear fits (red dashed lines) define onset latency times. Maximal temporal resolution achieved: 39 μs (SEMT, x-axis projection of s.e.m., inset). Cell-attached somatic voltage recording (cyan) peaked at the maximum of the derivate (δVm / δt) of Vm (brown trace; bottom). Somatic (orange) versus dendritic (green) Ca2+ transients and position-matched cell-attached signals (dendritic, magenta; somatic, cyan). Arrows point to the lag of the Ca2+ signals. () Transients in in extended time scale. () First derivatives of the Ca2+ transients shown in . () Onset latency times (mean ± s.e.m., n = 54) of Ca2+ transients in as a function of dendritic distance. Linear fit: average propagation speed. () Dendritic propagation speeds at different temperatures (mean ± s.e.m., n = 5 cells). * Figure 3: Point-by-point and continuous 3D trajectory scanning of dendritic Ca2+ spike propagation in CA1 pyramidal cells. () Maximum-intensity projection AO image of a CA1 pyramidal cell. Ca2+ transients in dendritic spines (orange and magenta traces) after induction of dendritic Ca2+ spike by focal extracellular stimulation (electrode, yellow). Enlarged views are shown in insets. Purple dots represent scanning points in a dendrite. () Spatially normalized and projected Ca2+ signals in the purple dotted dendritic region in (average of five subthreshold responses). Black dashed line, stimulus onset. Column labeled 'S', somatic Ca2+ response. () Ca2+ transients derived from the color-coded and numbered regions indicated in . Baseline-shifted Ca2+ transients measured in the region contained in the dashed box in (right). Yellow dots, onset latency times at the half-maximum. () Onset latency times at the peak of the derivate (δF(t)/δt) of Ca2+ transients shown in . () Onset latency times as a function of dendritic distance from the soma for somatic subthreshold (d-spike, black) and suprathreshold ! (d-spike+AP, blue) dendritic Ca2+ spikes. () Point-by-point and continuous 3D trajectory scanning of dendritic segments. Schema of the scanning modes (top right; blue, point-by-point scanning; green, continuous scanning). Example of Ca2+ responses measured by point-by-point (top left) and continuous trajectory modes (bottom). Traces were spatially normalized. () Image of a fluorescent bead in continuous trajectory scanning mode. The bead image was elongated because the focal spot was moving during PMT integration. Scale bar, 2 μm. * Figure 4: High-speed 3D calcium imaging of spontaneous neuronal network activity in vivo. () Sketch of in vivo experimental arrangement. Staining by bolus loading (OGB-1-AM and SR-101) in mouse V1. () Five representative planes at different depths imaged with 3D AO scanning. Scale bar, 100 μm. Depths are measured relative to the pia. () Example of an image plane at 200 μm depth showing neurons (green) and glial cells (magenta and white). Scale bar, 100 μm. () Image and intensity profiles of a pre-selected bright glial cell (purple box in ) used to establish the coordinate system. Scale bar, 5 μm. () A 35 μm z-projection of the dashed boxed region marked in (top). Neuronal somata detected with the aid of an algorithm in a subvolume (shown with projections, neurons in white and glial cells in black; bottom). Scale bar, 50 μm. () Maximal intensity side and z projections of the entire z stack (400 μm × 400 μm × 500 μm) with autodetected cell locations (spheres) color-coded in relation to depth following the legend in Figure 2a. The set detection threshold ! yields 532 neurons. Scale bar, 100 μm. () Spontaneous neuronal network activity measured in the 532 cells in . Example of a raw trace in which each line corresponds to a cell (left). Spatially normalized traces (middle) and corresponding Ca2+ transients (right). * Figure 5: 3D measurement of neuronal network activity in vivo in response to visual stimuli. () Sketch of in vivo experimental arrangement. Visual stimulation was induced by moving bars in eight directions of motion in 45° steps. () Maximal intensity side- and z-projection image of the entire z stack (280 μm × 280 μm × 230 μm; bolus loading with OGB-1-AM and SR-101). Spheres represent 375 autodetected neuronal locations color-coded by depth following scale in Figure 2a. Scale bars, 50 μm. () Parallel 3D recording of spontaneous Ca2+ responses from the 375 locations. Rows, single cells measured in random-access scanning mode. Scale bar, 5 s. () Examples of Ca2+ transients showing active neurons in . () Ca2+ responses from the same 375 neuronal locations (visual stimulation, moving bar at −45°). Rows, single cells from a single 3D measurement. Scale bar, 2 s. () Examples of Ca2+ transients from neurons in , preferentially responding to the −45° bar direction. () Stimulation with a 90° oriented stimulus (at −135°) in the same neurons in . () Examples o! f responses from simultaneously recorded neurons in . One nonselective, one orientation–selective and two direction-selective neurons are shown. Top rows, mean ± s.e.m. (n = 4–12 trials per orientation) in black; bottom rows, three color-coded single trials for each direction. Polar plot radius values from top to bottom: 0.2, 0.15, 0.2, 0.2 ΔF/F. () Three-dimensional map of orientation- and direction-selective cells measured in three dimensions in the volume in . Scale bar, 40 μm. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Gergely Katona, * Gergely Szalay, * Pál Maák & * Attila Kaszás Affiliations * Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary. * Gergely Katona, * Gergely Szalay, * Attila Kaszás, * Balázs Chiovini, * E Sylvester Vizi & * Balázs Rózsa * Department of Atomic Physics, Budapest University of Technology and Economics, Budapest, Hungary. * Pál Maák & * Máté Veress * The Faculty of Information Technology, Pázmány Péter Catholic University, Budapest, Hungary. * Attila Kaszás & * Balázs Rózsa * Neural Circuit Laboratories, Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland. * Dániel Hillier & * Botond Roska Contributions Optical design was performed by P.M., G.S. and M.V. Software was written by G.K. In vitro measurements were performed by B.C., A.K., G.S. and Ba.R. In vivo measurements were designed by D.H. and performed by D.H., A.K., G.S. and Ba.R. Analysis was carried out by Ba.R., A.K., G.K. and G.S. This manuscript was written by Ba.R., Bo.R., D.H., G.K., A.K. and P.M., with comments from all authors. Ba.R., Bo.R., E.S.V. and P.M. supervised the project. Competing financial interests G.K., E.S.V. and Ba.R. are owners of Femtonics and the patent WO2010076579. Corresponding author Correspondence to: * Balázs Rózsa Author Details * Gergely Katona Search for this author in: * NPG journals * PubMed * Google Scholar * Gergely Szalay Search for this author in: * NPG journals * PubMed * Google Scholar * Pál Maák Search for this author in: * NPG journals * PubMed * Google Scholar * Attila Kaszás Search for this author in: * NPG journals * PubMed * Google Scholar * Máté Veress Search for this author in: * NPG journals * PubMed * Google Scholar * Dániel Hillier Search for this author in: * NPG journals * PubMed * Google Scholar * Balázs Chiovini Search for this author in: * NPG journals * PubMed * Google Scholar * E Sylvester Vizi Search for this author in: * NPG journals * PubMed * Google Scholar * Botond Roska Search for this author in: * NPG journals * PubMed * Google Scholar * Balázs Rózsa Contact Balázs Rózsa Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (17M) Supplementary Figures 1–14, Supplementary Results 1–3, Supplementary Discussion, Supplementary Notes 1–9 and Supplementary Protocols 1–3 Movies * Supplementary Video 1 (6M) A 3D virtual reality environment for 3D two-photon imaging. This movie shows a surface-fitted pyramidal cell (located in the hippocampal CA1 region) and selected 3D measurement locations used to record the bAP-induced Ca2+ transients shown in Figure 2a. Using the 3D virtual reality environment, the 3D measurement locations can be freely modified or observed from any angle. Head-tracked shutter glasses ensure that the virtual objects maintain a stable, 'fixed' virtual position even when viewed from different viewpoints and angles. That is, the cell's virtual coordinate system is locked in space when the viewer's head position (view angle) changes; however, it can be rotated or shifted by the 3D 'bird' mouse. The bird also allows the 3D measurement points to be picked and repositioned in the virtual 3D space of the cell. * Supplementary Video 2 (1M) Automatic selection of the measurement points for 3D two-photon imaging in vivo. This movie shows a bulk-loaded cell assembly located in the mouse visual cortex, visualized with real-time maximum-intensity projection in the 3D virtual-reality environment. After detecting putative neuron locations from the stack (see Supplementary Note 5), the experimenter can set the selection threshold with real-time control of the number of selected cells and their localization. * Supplementary Video 3 (1M) Millimeter-range image stack captured without mechanical movement. This movie shows a 3D image stack of neurons from a fluorescently labeled invertebrate ganglion also shown in Figure 1g. While capturing the images, the microscope objective was fixed; images were taken by AO z-focusing. The stack dimensions are 717 μm × 717 μm × 1,071 μm; 40 slices. Zip files * Supplementary Software 1 (250K) Use of AD9910. This summary contains information about the usage of the AD9910 DDS chip used to generate frequency signals for the acousto-optic crystals. Wiring to the FPGA, routines used to initialize the chip and Matlab code segments calculating the necessary register values during scanning are incorporated. * Supplementary Software 2 (23M) A 3D interactive workstation module. This program provides a 3D VR environment with an open-source Matlab interface. It is possible to visualize and interact with 3D MIP projected volume data, surfaces and various annotation objects needed for controlling the experiments and for visualizing the results. It can perform mono or anaglyph views or be used in combination with the Leonar3Do virtual reality hardware. * Supplementary Software 3 (20K) Automatic drift-compensation algorithm. Description and code parts used for maintaining scan locations on the cells to measure. * Supplementary Software 4 (500K) Automatic detection of fluorescently labeled cells. Matlab code identifying cell centers using three dimensional two-channel measurement data was developed for combined OGB-1 and SR-101 bolus loading experiments (Supplementary Note 9 and Supplementary Video 2). Accompanying sample data help evaluate the performance of the code. Additional data

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Finding the missing links in EGFR
- Nat Struct Mol Biol 19(1):1-3 (2012)
ARTICLE NAVIGATION - ISSUE Previous January 2012, Volume 19 No 1 pp1-127 * News and Views * Research Highlights * Review * Articles * Brief Communication * Technical ReportsAbout the cover News and Views Finding the missing links in EGFR - pp1 - 3 Nicholas J Bessman & Mark A Lemmon doi:10.1038/nsmb.2221 Structural studies of the epidermal growth factor receptor (EGFR) have advanced greatly in recent years, but they have used a 'divide-and-conquer' approach for independent study of the intracellular and extracellular regions. Several recent papers provide important new perspectives on 'undivided' EGFR and describe the initial steps in reconstructing signaling behavior of the intact receptor. Full Text - Finding the missing links in EGFR | PDF (638 KB) - Finding the missing links in EGFR Claims and counterclaims of X-chromosome compensation - pp3 - 5 James A Birchler doi:10.1038/nsmb.2218 Is there upregulation of the single active X chromosome in mammals or not? Recent studies take different points of view. Full Text - Claims and counterclaims of X-chromosome compensation | PDF (414 KB) - Claims and counterclaims of X-chromosome compensation See also:Article by Yildirim et al. Thresholds of replication stress signaling in cancer development and treatment - pp5 - 7 Jiri Bartek, Martin Mistrik & Jirina Bartkova doi:10.1038/nsmb.2220 Oncogene-induced replication stress and DNA damage are among the hallmarks of cancer. A recent study explores how different levels of replication stress affect animal development and tumorigenesis, and how targeting of the replication stress–signaling pathway of ATR and Chk1 kinases can be exploited for selective killing of cancer cells. Full Text - Thresholds of replication stress signaling in cancer development and treatment | PDF (8,036 KB) - Thresholds of replication stress signaling in cancer development and treatment Research Highlights * Methylating fingers * Structural basis of silencing * Stalled out * Rli1 does the splits Review New approaches for dissecting protease functions to improve probe development and drug discovery - pp9 - 16 Edgar Deu, Martijn Verdoes & Matthew Bogyo doi:10.1038/nsmb.2203 Abstract - New approaches for dissecting protease functions to improve probe development and drug discovery | Full Text - New approaches for dissecting protease functions to improve probe development and drug discovery | PDF (2,959 KB) - New approaches for dissecting protease functions to improve probe development and drug discovery | Supplementary information Articles RAD51- and MRE11-dependent reassembly of uncoupled CMG helicase complex at collapsed replication forks - pp17 - 24 Yoshitami Hashimoto, Fabio Puddu & Vincenzo Costanzo doi:10.1038/nsmb.2177 A system to reconstitute a collapsed replication fork using Xenopus laevis egg extracts is developed. The study shows that upon fork collapse, DNA Pol epsilon and the GINS complex are uncoupled from the replisome, and their reloading onto DNA requires repair proteins Rad51 and Mre11. Abstract - RAD51- and MRE11-dependent reassembly of uncoupled CMG helicase complex at collapsed replication forks | Full Text - RAD51- and MRE11-dependent reassembly of uncoupled CMG helicase complex at collapsed replication forks | PDF (915 KB) - RAD51- and MRE11-dependent reassembly of uncoupled CMG helicase complex at collapsed replication forks | Supplementary information A unique H2A histone variant occupies the transcriptional start site of active genes - pp25 - 30 Tatiana A Soboleva, Maxim Nekrasov, Anuj Pahwa, Rohan Williams, Gavin A Huttley & David J Tremethick doi:10.1038/nsmb.2161 The histone variant H2A.Bbd inhibits folding of nucleosomal arrays and reverses chromatin-mediated transcriptional repression in vitro. New studies have uncovered the related mouse H2A variant H2A.Lap1 as a novel component of the transcription start site of active genes during specific stages of spermatogenesis, which enables transcriptional activation by unfolding the chromatin locally. Abstract - A unique H2A histone variant occupies the transcriptional start site of active genes | Full Text - A unique H2A histone variant occupies the transcriptional start site of active genes | PDF (1,514 KB) - A unique H2A histone variant occupies the transcriptional start site of active genes | Supplementary information Signal-dependent dynamics of transcription factor translocation controls gene expression - pp31 - 39 Nan Hao & Erin K O'Shea doi:10.1038/nsmb.2192 The Msn2 transcription factor is translocated to the nucleus to activate transcription of hundreds of genes in response to various environmental stimuli. Experimental and computational single-molecule analyses reveal how different stimuli elicit different dynamical patterns of Msn2 translocation, which are interpreted by promoters with distinct properties to produce specific patterns of target gene expression. Abstract - Signal-dependent dynamics of transcription factor translocation controls gene expression | Full Text - Signal-dependent dynamics of transcription factor translocation controls gene expression | PDF (1,086 KB) - Signal-dependent dynamics of transcription factor translocation controls gene expression | Supplementary information Intrinsic tethering activity of endosomal Rab proteins - pp40 - 47 Sheng-Ying Lo, Christopher L Brett, Rachael L Plemel, Marissa Vignali, Stanley Fields, Tamir Gonen & Alexey J Merz doi:10.1038/nsmb.2162 Rab small G proteins regulate membrane trafficking events by recruiting effectors that mediate vesicle tethering. In vitro studies now suggest that Vps21 and other endosomal Rabs in budding yeast can undergo GTP-regulated Rab-Rab interactions that drive tethering in the absence of effectors, implying that they have an intrinsic tethering activity that may function in concert with conventional effectors. Abstract - Intrinsic tethering activity of endosomal Rab proteins | Full Text - Intrinsic tethering activity of endosomal Rab proteins | PDF (1,333 KB) - Intrinsic tethering activity of endosomal Rab proteins | Supplementary information Ndc10 is a platform for inner kinetochore assembly in budding yeast - pp48 - 55 Uhn-Soo Cho & Stephen C Harrison doi:10.1038/nsmb.2178 * PDB code * 3SQI * 3T79 * 3D view * 3SQI * 3T79 Kinetochores assemble on centromeric DNA and link centromeres to spindle microtubules, thus allowing proper segregation during mitosis. The kinetochore subunit Ndc10 makes contacts with centromeric DNA elements, which are now directly observed in a crystal structure. Along with biochemical analyses, the work indicates that Ndc10 functions as a central organizing hub to assemble the inner kinetochore. Abstract - Ndc10 is a platform for inner kinetochore assembly in budding yeast | Full Text - Ndc10 is a platform for inner kinetochore assembly in budding yeast | PDF (1,395 KB) - Ndc10 is a platform for inner kinetochore assembly in budding yeast | Supplementary information X-chromosome hyperactivation in mammals via nonlinear relationships between chromatin states and transcription - pp56 - 61 Eda Yildirim, Ruslan I Sadreyev, Stefan F Pinter & Jeannie T Lee doi:10.1038/nsmb.2195 In addition to balancing X-chromosome dosage between males and females via X inactivation, mammals also balance dosage of X chromosomes and autosomes. Allele-specific chromatin immunoprecipitation with deep sequencing (ChIP-seq) analyses now show that the active X chromosome is upregulated at the level of both transcription initiation and elongation. Abstract - X-chromosome hyperactivation in mammals via nonlinear relationships between chromatin states and transcription | Full Text - X-chromosome hyperactivation in mammals via nonlinear relationships between chromatin states and transcription | PDF (1,029 KB) - X-chromosome hyperactivation in mammals via nonlinear relationships between chromatin states and transcription | Supplementary information See also:News and Views by Birchler An ankyrin-repeat ubiquitin-binding domain determines TRABID's specificity for atypical ubiquitin chains - pp62 - 71 Julien D F Licchesi, Juliusz Mieszczanek, Tycho E T Mevissen, Trevor J Rutherford, Masato Akutsu, Satpal Virdee, Farid El Oualid, Jason W Chin, Huib Ovaa, Mariann Bienz & David Komander doi:10.1038/nsmb.2169 * PDB code * 3ZRH * 3D view * 3ZRH The OTU domain deubiquitinase TRABID specifically hydrolyzes atypical Lys29- and Lys33-linked diubiquitin chains. Structural analysis of TRABID reveals an unpredicted ankyrin-repeat domain that binds ubiquitin and is crucial for TRABID efficiency and linkage specificity in vitro and in vivo. Abstract - An ankyrin-repeat ubiquitin-binding domain determines TRABID's specificity for atypical ubiquitin chains | Full Text - An ankyrin-repeat ubiquitin-binding domain determines TRABID's specificity for atypical ubiquitin chains | PDF (2,198 KB) - An ankyrin-repeat ubiquitin-binding domain determines TRABID's specificity for atypical ubiquitin chains | Supplementary information Mechanism of mismatch recognition revealed by human MutSβ bound to unpaired DNA loops - pp72 - 78 Shikha Gupta, Martin Gellert & Wei Yang doi:10.1038/nsmb.2175 * PDB code * 3THY * 3THX * 3THW * 3THZ * 3D view * 3THY * 3THX * 3THW * 3THZ Eukaryotic MutSβ is a heterodimer composed of Msh2 and Msh3 that recognizes insertion-deletion loops (IDLs) and 3′ overhangs during mismatch repair. Now crystal structures of MutSβ in complex with DNA, containing IDLs of varying lengths, reveal that this complex interacts with its substrate differently than MutSα and bacterial MutS do. Abstract - Mechanism of mismatch recognition revealed by human MutSβ bound to unpaired DNA loops | Full Text - Mechanism of mismatch recognition revealed by human MutSβ bound to unpaired DNA loops | PDF (1,980 KB) - Mechanism of mismatch recognition revealed by human MutSβ bound to unpaired DNA loops | Supplementary information The extracellular chaperone clusterin sequesters oligomeric forms of the amyloid-β1−40 peptide - pp79 - 83 Priyanka Narayan, Angel Orte, Richard W Clarke, Benedetta Bolognesi, Sharon Hook, Kristina A Ganzinger, Sarah Meehan, Mark R Wilson, Christopher M Dobson & David Klenerman doi:10.1038/nsmb.2191 Genome-wide association studies have established a link between the extracellular chaperone clusterin and susceptibility to Alzheimer's disease. A fluorescence approach is now used to reveal that clusterin sequesters Aβ1–40 oligomers and prevents them from undergoing further aggregation. Abstract - The extracellular chaperone clusterin sequesters oligomeric forms of the amyloid-β1−40 peptide | Full Text - The extracellular chaperone clusterin sequesters oligomeric forms of the amyloid-β1−40 peptide | PDF (625 KB) - The extracellular chaperone clusterin sequesters oligomeric forms of the amyloid-β1−40 peptide | Supplementary information Structural basis of pre-let-7 miRNA recognition by the zinc knuckles of pluripotency factor Lin28 - pp84 - 89 Fionna E Loughlin, Luca F R Gebert, Harry Towbin, Andreas Brunschweiger, Jonathan Hall & Frdric H-T Allain doi:10.1038/nsmb.2202 * PDB code * 2LI8 * 3D view * 2LI8 Lin28 prevents the processing of pre-let-7 RNAs, but it is not clear where the Lin28 RNA binding domains interact with the RNA. The NMR structure of the Lin28 zinc knuckles with a short RNA motif reveals that each knuckle interacts with an AG dinucleotide, allowing the determination of a consensus motif for pre-let-7 recognition. Abstract - Structural basis of pre-let-7 miRNA recognition by the zinc knuckles of pluripotency factor Lin28 | Full Text - Structural basis of pre-let-7 miRNA recognition by the zinc knuckles of pluripotency factor Lin28 | PDF (1,138 KB) - Structural basis of pre-let-7 miRNA recognition by the zinc knuckles of pluripotency factor Lin28 | Supplementary information Tudor domain ERI-5 tethers an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi - pp90 - 97 Caroline Thivierge, Neetha Makil, Mathieu Flamand, Jessica J Vasale, Craig C Mello, James Wohlschlegel, Darryl Conte Jr & Thomas F Duchaine doi:10.1038/nsmb.2186 The type III ribonuclease DCR-1 is essential for ERI endogenous RNAi and exogenous RNAi in Caenorhabditis elegans. A new study shows that DCR-1 forms exclusive complexes in each pathway, and characterization of the ERI complex implicates a tudor domain protein in tethering an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi. Abstract - Tudor domain ERI-5 tethers an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi | Full Text - Tudor domain ERI-5 tethers an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi | PDF (727 KB) - Tudor domain ERI-5 tethers an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi | Supplementary information Mispaired rNMPs in DNA are mutagenic and are targets of mismatch repair and RNases H - pp98 - 104 Ying Shen, Kyung Duk Koh, Bernard Weiss & Francesca Storici doi:10.1038/nsmb.2176 Ribonucleoside monophosphates (rNMPs) are often incorporated into genomic DNA. Misincorporated rNMPs are now shown to be repaired by mismatch repair and RNases H. If not repaired, they can serve as a template for DNA synthesis and can cause mutagenesis in Escherichia coli and yeast. Abstract - Mispaired rNMPs in DNA are mutagenic and are targets of mismatch repair and RNases H | Full Text - Mispaired rNMPs in DNA are mutagenic and are targets of mismatch repair and RNases H | PDF (445 KB) - Mispaired rNMPs in DNA are mutagenic and are targets of mismatch repair and RNases H | Supplementary information A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide - pp105 - 112 Nour Sayed, Ambre Jousselin & Brice Felden doi:10.1038/nsmb.2193 Cis-encoded antisense RNAs (asRNAs) are transcribed from the DNA strand opposite another gene and function by pairing with RNAs expressed from the complementary strand. A new study provides evidence that a bacterial cis-asRNA acts in trans, using a domain outside of its target complementarity sequence, suggesting the need for a mechanistic re-evaluation of asRNA-based gene regulation. Abstract - A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide | Full Text - A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide | PDF (1,611 KB) - A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide | Supplementary information Brief Communication Single-molecule studies reveal the function of a third polymerase in the replisome - pp113 - 116 Roxana E Georgescu, Isabel Kurth & Mike E O'Donnell doi:10.1038/nsmb.2179 Recent work has indicated that the Escherichia coli replisome contains three DNA polymerases that are used to replicate two parental strands. A single-molecule approach is now used to compare replisomes reconstituted with two or three polymerases, revealing that the presence of a third polymerase ensures higher processivity overall and more efficient replication of the lagging strand. Abstract - Single-molecule studies reveal the function of a third polymerase in the replisome | Full Text - Single-molecule studies reveal the function of a third polymerase in the replisome | PDF (728 KB) - Single-molecule studies reveal the function of a third polymerase in the replisome | Supplementary information Technical Reports Fluorescent fusion protein knockout mediated by anti-GFP nanobody - pp117 - 121 Emmanuel Caussinus, Oguz Kanca & Markus Affolter doi:10.1038/nsmb.2180 The combination of an F-box domain with a single-domain antibody that recognizes green fluorescent protein (GFP) now allows controlled depletion of GFP fusions in mammalian cells and in flies. This system, called deGradFP, should be widely useful, as GFP fusions are available for many proteins in model organisms. Abstract - Fluorescent fusion protein knockout mediated by anti-GFP nanobody | Full Text - Fluorescent fusion protein knockout mediated by anti-GFP nanobody | PDF (1,208 KB) - Fluorescent fusion protein knockout mediated by anti-GFP nanobody | Supplementary information A metal switch for controlling the activity of molecular motor proteins - pp122 - 127 Jared C Cochran, Yu Cheng Zhao, Dean E Wilcox & F Jon Kull doi:10.1038/nsmb.2190 * PDB code * 3PXN * 3D view * 3PXN NTPases use a metal ion, typically Mg2+, coordinated by a conserved serine or threonine residue, to enable phosphate binding and catalysis. Now cysteine substitutions at the switch 1 motif of different kinesins render them able to use Mn2+ instead of Mg2+, allowing their enzymatic and motor activities to be modulated by the ratio of Mg2+ to Mn2+. Abstract - A metal switch for controlling the activity of molecular motor proteins | Full Text - A metal switch for controlling the activity of molecular motor proteins | PDF (1,145 KB) - A metal switch for controlling the activity of molecular motor proteins | Supplementary information
Claims and counterclaims of X-chromosome compensation
- Nat Struct Mol Biol 19(1):3-5 (2012)
Article preview View full access options Nature Structural & Molecular Biology | News and Views Claims and counterclaims of X-chromosome compensation * James A Birchler1Journal name:Nature Structural & Molecular BiologyVolume: 19,Pages:3–5Year published:(2012)DOI:doi:10.1038/nsmb.2218Published online 05 January 2012 Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Is there upregulation of the single active X chromosome in mammals or not? Recent studies take different points of view. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Structural & Molecular Biology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Affiliations * James A. Birchler is in the Division of Biological Sciences, University of Missouri, Columbia, Missouri, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * James A Birchler Author Details * James A Birchler Contact James A Birchler Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
Thresholds of replication stress signaling in cancer development and treatment
- Nat Struct Mol Biol 19(1):5-7 (2012)
Article preview View full access options Nature Structural & Molecular Biology | News and Views Thresholds of replication stress signaling in cancer development and treatment * Jiri Bartek1, 2 * Martin Mistrik2 * Jirina Bartkova1 * Affiliations * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:5–7Year published:(2012)DOI:doi:10.1038/nsmb.2220Published online 05 January 2012 Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Oncogene-induced replication stress and DNA damage are among the hallmarks of cancer. A recent study explores how different levels of replication stress affect animal development and tumorigenesis, and how targeting of the replication stress–signaling pathway of ATR and Chk1 kinases can be exploited for selective killing of cancer cells. Figures at a glance * Figure 1: Impact of different levels of ATR signaling on organismal development and tumorigenesis. Whereas wild-type and heterozygous mice develop normally, both human patients17 and the corresponding mouse model18 with pronounced genetic defects in ATR suffer from a complex developmental disorder (Seckel syndrome). The role of ATR in tumorigenesis also depends on a signaling threshold, as heterozygous mice are haploinsufficient for tumor suppression22, 23. Murga et al.4 show that excessive replication stress under in vivo conditions of very low ATR with concomitant overexpression of the Myc oncogene leads to synthetic lethality at the cellular level, resulting in exacerbation of the Seckel syndrome (*) and the virtual absence of tumors (**). * Figure 2: Distinct roles of the ATR-Chk1 pathway during multistep tumorigenesis. Oncogene activation in early lesions leads to replication stress and DNA damage, consequently triggering the DDR machinery and leading to checkpoint-imposed senescence or death of nascent tumor cells3, 4, 5, 6, 7. In tumors where the DDR barrier is overcome (for example, by selection for p53 mutations), disease progression may ensue. The advanced tumors still experience the oncogene-induced replication stress and genetic instability and often adapt to such challenge. In the context of disabled cell-cycle checkpoints and apoptosis, the abilities of the ATR-Chk1 signaling module to support the replication machinery and promote DNA repair can thus be 'hijacked' to boost the overall fitness of the malignant tumor. * Figure 3: Potential exploitation of replication stress as a target for cancer therapy. Many, but not all, tumors feature enhanced replication stress (RS)4, 12, 24. Subsets of cancers of diverse tissue origin might therefore be examined for markers of replication stress and/or activated RSR in order to select individuals who might benefit from treatment with drugs that inhibit the ATR or Chk1 kinases. Examples of preclinical results of such a treatment approach are reported by Murga et al.4. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Structural & Molecular Biology for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Affiliations * Jiri Bartek and Jirina Bartkova are at the Centre for Genotoxic Stress Research, Danish Cancer Society, Copenhagen, Denmark. * Martin Mistrik and Jiri Bartek are at the Institute of Molecular and Translational Medicine, Palacky University, Olomouc, Czech Republic. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jiri Bartek Author Details * Jiri Bartek Contact Jiri Bartek Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Mistrik Search for this author in: * NPG journals * PubMed * Google Scholar * Jirina Bartkova Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
New approaches for dissecting protease functions to improve probe development and drug discovery
- Nat Struct Mol Biol 19(1):9-16 (2012)
Nature Structural & Molecular Biology | Review New approaches for dissecting protease functions to improve probe development and drug discovery * Edgar Deu1 * Martijn Verdoes1 * Matthew Bogyo1, 2 * Affiliations * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:9–16Year published:(2012)DOI:doi:10.1038/nsmb.2203Published online 05 January 2012 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Proteases are well-established targets for pharmaceutical development because of their known enzymatic mechanism and their regulatory roles in many pathologies. However, many potent clinical lead compounds have been unsuccessful either because of a lack of specificity or because of our limited understanding of the biological roles of the targeted protease. In order to successfully develop protease inhibitors as drugs, it is necessary to understand protease functions and to expand the platform of inhibitor development beyond active site–directed design and in vitro optimization. Several newly developed technologies will enhance assessment of drug selectivity in living cells and animal models, allowing researchers to focus on compounds with high specificity and minimal side effects in vivo. In this review, we highlight advances in the development of chemical probes, proteomic methods and screening tools that we feel will help facilitate this paradigm shift in drug discovery. View full text Figures at a glance * Figure 1: Mechanism of substrate hydrolysis by the primary families of proteases. () Protease substrates bind through interactions of the side chain residues (P and P′ residues) with the substrate pockets of the protease (S and S′ pockets). The red dashed line indicates a scissile bond. (–) The architecture of the active site and mechanism of hydrolysis for N-terminal threonine, serine and cysteine proteases that use an acyl-enzyme intermediate formed through nucelophilic attack by the catalytic side chain residue. (,) In the case of zinc metalloproteases (), aspartate proteases () and glutamate proteases (not depicted), a carboxylic acid group or metal ion activates a water molecule, leading to acid-base catalysis. The seventh and newest protease family, the asparagine peptide lyases, cleave themselves using an asparagine residue as the nucleophile2 (not depicted). * Figure 2: Schematic presentation of the hit-to-lead process. () In a classical protease drug discovery approach, the emphasis of screening and optimization is on maximizing the potency of a hit compound for a recombinant protease. Off-target effects and efficacy are usually tested after the optimization process, and problems encountered when testing the compounds in cultures and in vivo require either modifying the structure of the lead inhibitor to solve a particular issue or selecting a different chemotype for further optimization. () In this review, we propose a holistic approach, in which the emphasis is on identifying hits in a more complex and relevant context (intact cells), incorporating the specificity profile of hits to identify and optimize lead compounds. We believe that placing the emphasis of the hit-to-lead optimization process on selectivity instead of just on potency will help prevent off-target effects and thus increase the chances for developing protease inhibitor drugs with minimum side effects. * Figure 3: Activity-based probes report on tightly regulated protease activity. () Proteases are not only regulated on the transcription and translation levels but also highly regulated on the protein level. Expressed as zymogens, proteases are activated in a variety of ways and by a variety of factors, depending on the protease, including allosteric activation, environmental changes, localization, protein-protein interactions and processing by upstream proteases. Endogenous inhibitors and targeted degradation form yet another layer of regulation. () Activity-based probes are small-molecule reporters that use the active protease's own chemistry to distinguish it from its zymogen or inhibited form. Most ABPs consist of three parts: a warhead (an electrophilic moiety that reacts with the active site nucleophile to result in a covalent and irreversible adduct), a spacer and/or recognition element that targets the probe to a specific target protease and a tag (usually a fluorescent dye and/or an affinity handle, like biotin). * Figure 4: Chemical tools to study protease function and to measure target inhibition. () Forward chemical genetics allows for target identification through the introduction of an affinity tag to the hit compound. () Near-infrared fluorescently labeled ABPs can be applied to top-down characterization of a target protease. Whole-animal noninvasive imaging techniques allow the visualization of target distribution, and extracted tissue can be analyzed ex vivo. Histology shows target distribution on a microscopic level, FACS analysis identifies the types of cells that contain active protease and biochemical analysis allows characterization at the protein level. Treatment with a lead compound before labeling provides information on target inhibition. Mouse images are from our previous publication39. () Broad-spectrum protease probes enable a readout of the inhibition profile of a lead compound for an entire protease family in a proteome. Members of the targeted family can be resolved on a gel, and inhibition results in diminished labeling of individual proteases. (! ) Global profiling of all reactive cysteines in a proteome; iodoacetamide-based reporter molecules will react primarily with the more reactive cysteines. Using isotopically labeled reporter molecules, this method can be used to predict functional cysteines in proteomes as well as to identify targets. When the methods described here are used to evaluate the specificity profile of a reversible inhibitor, the labeling conditions should be adjusted so that the covalent probe does not outcompete the inhibitor. Because these methods have a good dynamic range, this can be accomplished by lowering the probe concentration or decreasing the labeling times. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Pathology, Stanford University School of Medicine, Stanford, California, USA. * Edgar Deu, * Martijn Verdoes & * Matthew Bogyo * Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, USA. * Matthew Bogyo Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Matthew Bogyo Author Details * Edgar Deu Search for this author in: * NPG journals * PubMed * Google Scholar * Martijn Verdoes Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew Bogyo Contact Matthew Bogyo Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (74K) Supplementary Box 1 Additional data
RAD51- and MRE11-dependent reassembly of uncoupled CMG helicase complex at collapsed replication forks
- Nat Struct Mol Biol 19(1):17-24 (2012)
Nature Structural & Molecular Biology | Review New approaches for dissecting protease functions to improve probe development and drug discovery * Edgar Deu1 * Martijn Verdoes1 * Matthew Bogyo1, 2 * Affiliations * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:9–16Year published:(2012)DOI:doi:10.1038/nsmb.2203Published online 05 January 2012 Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Proteases are well-established targets for pharmaceutical development because of their known enzymatic mechanism and their regulatory roles in many pathologies. However, many potent clinical lead compounds have been unsuccessful either because of a lack of specificity or because of our limited understanding of the biological roles of the targeted protease. In order to successfully develop protease inhibitors as drugs, it is necessary to understand protease functions and to expand the platform of inhibitor development beyond active site–directed design and in vitro optimization. Several newly developed technologies will enhance assessment of drug selectivity in living cells and animal models, allowing researchers to focus on compounds with high specificity and minimal side effects in vivo. In this review, we highlight advances in the development of chemical probes, proteomic methods and screening tools that we feel will help facilitate this paradigm shift in drug discovery. View full text Figures at a glance * Figure 1: Mechanism of substrate hydrolysis by the primary families of proteases. () Protease substrates bind through interactions of the side chain residues (P and P′ residues) with the substrate pockets of the protease (S and S′ pockets). The red dashed line indicates a scissile bond. (–) The architecture of the active site and mechanism of hydrolysis for N-terminal threonine, serine and cysteine proteases that use an acyl-enzyme intermediate formed through nucelophilic attack by the catalytic side chain residue. (,) In the case of zinc metalloproteases (), aspartate proteases () and glutamate proteases (not depicted), a carboxylic acid group or metal ion activates a water molecule, leading to acid-base catalysis. The seventh and newest protease family, the asparagine peptide lyases, cleave themselves using an asparagine residue as the nucleophile2 (not depicted). * Figure 2: Schematic presentation of the hit-to-lead process. () In a classical protease drug discovery approach, the emphasis of screening and optimization is on maximizing the potency of a hit compound for a recombinant protease. Off-target effects and efficacy are usually tested after the optimization process, and problems encountered when testing the compounds in cultures and in vivo require either modifying the structure of the lead inhibitor to solve a particular issue or selecting a different chemotype for further optimization. () In this review, we propose a holistic approach, in which the emphasis is on identifying hits in a more complex and relevant context (intact cells), incorporating the specificity profile of hits to identify and optimize lead compounds. We believe that placing the emphasis of the hit-to-lead optimization process on selectivity instead of just on potency will help prevent off-target effects and thus increase the chances for developing protease inhibitor drugs with minimum side effects. * Figure 3: Activity-based probes report on tightly regulated protease activity. () Proteases are not only regulated on the transcription and translation levels but also highly regulated on the protein level. Expressed as zymogens, proteases are activated in a variety of ways and by a variety of factors, depending on the protease, including allosteric activation, environmental changes, localization, protein-protein interactions and processing by upstream proteases. Endogenous inhibitors and targeted degradation form yet another layer of regulation. () Activity-based probes are small-molecule reporters that use the active protease's own chemistry to distinguish it from its zymogen or inhibited form. Most ABPs consist of three parts: a warhead (an electrophilic moiety that reacts with the active site nucleophile to result in a covalent and irreversible adduct), a spacer and/or recognition element that targets the probe to a specific target protease and a tag (usually a fluorescent dye and/or an affinity handle, like biotin). * Figure 4: Chemical tools to study protease function and to measure target inhibition. () Forward chemical genetics allows for target identification through the introduction of an affinity tag to the hit compound. () Near-infrared fluorescently labeled ABPs can be applied to top-down characterization of a target protease. Whole-animal noninvasive imaging techniques allow the visualization of target distribution, and extracted tissue can be analyzed ex vivo. Histology shows target distribution on a microscopic level, FACS analysis identifies the types of cells that contain active protease and biochemical analysis allows characterization at the protein level. Treatment with a lead compound before labeling provides information on target inhibition. Mouse images are from our previous publication39. () Broad-spectrum protease probes enable a readout of the inhibition profile of a lead compound for an entire protease family in a proteome. Members of the targeted family can be resolved on a gel, and inhibition results in diminished labeling of individual proteases. (! ) Global profiling of all reactive cysteines in a proteome; iodoacetamide-based reporter molecules will react primarily with the more reactive cysteines. Using isotopically labeled reporter molecules, this method can be used to predict functional cysteines in proteomes as well as to identify targets. When the methods described here are used to evaluate the specificity profile of a reversible inhibitor, the labeling conditions should be adjusted so that the covalent probe does not outcompete the inhibitor. Because these methods have a good dynamic range, this can be accomplished by lowering the probe concentration or decreasing the labeling times. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Pathology, Stanford University School of Medicine, Stanford, California, USA. * Edgar Deu, * Martijn Verdoes & * Matthew Bogyo * Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, USA. * Matthew Bogyo Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Matthew Bogyo Author Details * Edgar Deu Search for this author in: * NPG journals * PubMed * Google Scholar * Martijn Verdoes Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew Bogyo Contact Matthew Bogyo Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (74K) Supplementary Box 1 Additional data
A unique H2A histone variant occupies the transcriptional start site of active genes
- Nat Struct Mol Biol 19(1):25-30 (2012)
Nature Structural & Molecular Biology | Article RAD51- and MRE11-dependent reassembly of uncoupled CMG helicase complex at collapsed replication forks * Yoshitami Hashimoto1 * Fabio Puddu1 * Vincenzo Costanzo1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:17–24Year published:(2012)DOI:doi:10.1038/nsmb.2177Received 16 May 2011 Accepted 29 September 2011 Published online 04 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg In higher eukaryotes, the dynamics of replisome components during fork collapse and restart are poorly understood. Here we have reconstituted replication fork collapse and restart by inducing single-strand DNA lesions that create a double-strand break in one of the replicated sister chromatids after fork passage. We found that, upon fork collapse, the active CDC45–MCM–GINS (CMG) helicase complex loses its GINS subunit. A functional replisome is restored by the reloading of GINS and polymerase ɛ onto DNA in a fashion that is dependent on RAD51 and MRE11 but independent of replication origin assembly and firing. PCNA mutant alleles defective in break-induced replication (BIR) are unable to support restoration of replisome integrity. These results show that, in higher eukaryotes, replisomes are partially dismantled after fork collapse and fully re-established by a recombination-mediated process. View full text Figures at a glance * Figure 1: RAD51 is required for DNA replication in the presence of forks collapsed by a single-strand break in the template. () The requirement of RAD51 and PCNA modification at Lys164 for replication of undamaged sperm DNA (control) or MMS- or UV-treated sperm DNA was tested using GST-labeled BRC4, which sequesters RAD51, and PCNA K164R mutant. Replication products (labeled with [32P]dATP) were resolved by neutral agarose gel electrophoresis and subjected to autoradiography (left). The quantification of the signal is shown in the graph as photon emission intensity expressed in arbitrary units (AU) (right). The data shown here and hereafter represent typical findings of three or more experiments. () A model for ssDNA-specific endonuclease-dependent fork collapse and RAD51-dependent restart. () The requirement of RAD51 for DNA replication in the presence of S1 nuclease was tested using sperm nuclei (4,000 nuclei per microliter) incubated for 80 min in the presence or absence of 1 μg ml−1 aphidicolin (Low aph) and S1 nuclease (0, 2.92, 1.46, 0.73, 0.37 U μl−1). Replication products were detect! ed by autoradiography with quantification shown on the right, as in . SYBR Green staining shows total DNA. * Figure 2: RAD51 is required for stable chromatin association of fork proteins in the presence of template breakage. () Association of fork proteins to chromatin isolated from extracts treated with GST or GST-BRC4 and 0, 2.92, 0.97 and 0.32 U μl−1 S1 nuclease in the presence of 1 μg ml−1 aphidicolin (Low aph). () Chromatin status of fork proteins, histone H2AX and PCNA in extracts treated with GST or GST-BRC4 2.92 (1/100) and 0.37 (1/800) U μl−1 S1 nuclease and aphidicolin. () Chromatin binding of PSF2 and CDC45 in the presence of 0.97 U μl−1 S1 nuclease in mock- or RAD51-depleted (–RAD51) extracts. () Chromatin binding of the indicated proteins over time in extracts treated with GST or GST-BRC4 and 1.46 U μl−1 of S1 nuclease and aphidicolin. () Nuclear CHK1 phosphorylation (P-CHK1) on Ser345 in extracts treated with 1 μg ml−1 aphidicolin alone or in combination with 1.46 U μl−1 of S1 nuclease. In –, western blotting was performed using antibodies against the indicated chromatin binding factors. 'Ext' in and indicates lanes containing 0.5 μl egg extract loaded as ! a control. Chromatin and nuclear fractions were isolated 60 min after the addition of sperm DNA to egg extracts unless otherwise indicated. * Figure 3: RAD51 is required for origin-independent fork restart and reloading of replisome components after fork collapse. (,) Replication fork restart was monitored following incubation of sperm nuclei in the first extract for 60 min with or without 10 μg ml−1 aphidicolin, and then nuclear fractions that were untreated or briefly incubated with mung bean nuclease were transferred to a second extract containing 320 nM geminin, 1 mM roscovitine and GST or GST-BRC4 () or to mock- or RAD51-depleted (–RAD51) extracts containing recombinant RAD51 (rRAD51) (). Replication products were monitored by incorporation of [32P]dATP added to the second extract and resolved by alkaline () or neutral () agarose gel electrophoresis followed by autoradiography. Quantification of signals is shown at the bottom of the gel in and in the graph in . () Chromatin binding of RAD51 and CDC45 was monitored in egg extracts that were mock- or RAD51-depleted and supplemented with the indicated amount of rRAD51. () The status of replication fork proteins bound to chromatin isolated from extracts treated as in . * Figure 4: MRE11 nuclease activity is required for DNA replication upon fork collapse. (,) Effects of the MRE11 nuclease inhibitor mirin on replication of sperm nuclei that were untreated or treated with MMS in the presence or absence of GST-BRC4 () or on sperm nuclei incubated in extracts treated with 0, 0.73, 0.37 or 0.18 U μl−1 S1 nuclease and aphidicolin (). Replication products were monitored by [32P]dATP incorporation and resolved on neutral agarose gels, which were subjected to autoradiography. Signal intensities are reported in the graphs. () Effect of mirin on replication proteins bound to chromatin isolated after a 50-min incubation in extracts treated with 0, 1.46, 0.73, 0.37 or 0.18 U μl−1 S1 nuclease. () Binding of the indicated fork proteins to chromatin incubated for 45 min in egg extracts that were untreated or supplemented with 0.73 U μl−1 S1 nuclease and mirin following protein cross-linking, sonication-induced DNA fragmentation and immunoprecipitation with control and anti-CDC45 serum. 'Ext' indicates 0.5 μl egg extract loaded as a! control in and . * Figure 5: The role of PCNA in DNA replication and chromatin association of replication proteins upon fork collapse. () Replication of sperm nuclei incubated in extracts for 80 min in the presence of 1 μg ml−1 aphidicolin and 0, 0.73, 0.37 or 0.18 U μl−1 S1 nuclease and wild-type PCNA (WT), PCNA K164R (KR), PCNA Y249A Y250A (YA) or PCNA K164R Y249A Y250A (KR YA) recombinant proteins. Replication products were resolved by neutral agarose gel electrophoresis and subjected to autoradiography (left). Signal intensities are shown in the graph (right). () Binding to chromatin of the indicated proteins was monitored by immunoblotting of chromatin treated with 200 J m−2 UV or incubated in extracts treated with 1 μg ml−1 aphidicolin, 0.97 U μl−1 S1 nuclease or EcoRI and recombinant wild-type PCNA, PCNA K164R or PCNA Y249A Y250A as indicated. 'Ext' indicates 0.5 μl egg extract loaded as a control. () The interaction of PCNA and replication proteins in egg extract was monitored by incubation of His6-tagged wild type and mutant PCNA proteins followed by pull-down with Ni-NTA–Sepharose! . The interacting proteins were detected by immunoblotting as indicated. * Figure 6: A model of replication fork collapse and restart. The presence of a ssDNA lesion in the template creates a one-sided DSB upon passage of the replisome (1), leading to the dissociation of the GINS and Pol ɛ from the fork, whereas MCM and CDC45 remain stably bound to collapsed fork (2). The one-sided DSB undergoes MRE11-mediated nuclease resection and RAD51-dependent strand annealing and invasion of the intact template. The MRE11 complex might also tether the broken DNA strand to the intact one (3). This process requires BIR-proficient PCNA, which promotes Pol η–dependent strand extension (4). Reloading of the GINS and Pol ɛ in an origin-independent fashion promotes reassembly of a functional replisome (5). Author information * Abstract * Author information * Supplementary information Affiliations * Genome Stability Unit, Clare Hall Laboratories, London Research Institute, South Mimms, Hertfordshire, UK. * Yoshitami Hashimoto, * Fabio Puddu & * Vincenzo Costanzo Contributions Y.H. and F.P. performed experiments. Y.H. and V.C. analyzed the results and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Vincenzo Costanzo Author Details * Yoshitami Hashimoto Search for this author in: * NPG journals * PubMed * Google Scholar * Fabio Puddu Search for this author in: * NPG journals * PubMed * Google Scholar * Vincenzo Costanzo Contact Vincenzo Costanzo Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3.5 MB) Supplementary Figures 1–6 Additional data Entities in this article * DNA repair protein RAD51 homolog A rad51-a Xenopus laevis * View in UniProt * View in Entrez Gene * Double-strand break repair protein MRE11 mre11a Xenopus laevis * View in UniProt * View in Entrez Gene * Cell division control protein 45 homolog cdc45 Xenopus laevis * View in UniProt * View in Entrez Gene * Proliferating cell nuclear antigen pcna Xenopus laevis * View in UniProt * View in Entrez Gene * Proliferating cell nuclear antigen PCNA Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * E3 ubiquitin-protein ligase RAD18 RAD18 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Protein RecA recA Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA repair protein RAD51 homolog 1 RAD51 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Double-strand break repair protein MRE11A MRE11A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA repair protein RAD50 RAD50 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Nibrin NBN Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA polymerase delta subunit 3 POL32 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Origin recognition complex subunit 1 ORC1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Origin recognition complex subunit 6 ORC6 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Cell division control protein 6 CDC6 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Cell division cycle protein CDT1 TAH11 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA replication licensing factor MCM2 MCM2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA replication licensing factor MCM7 MCM7 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Cell division control protein 45 CDC45 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA replication complex GINS protein SLD5 SLD5 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA replication complex GINS protein PSF1 PSF1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA replication complex GINS protein PSF2 PSF2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA replication complex GINS protein PSF3 PSF3 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Breast cancer type 2 susceptibility protein BRCA2 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Geminin GMNN Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * GINS complex subunit 4 (Sld5 homolog) gins4 Xenopus laevis * View in UniProt * View in Entrez Gene * DNA replication complex GINS protein PSF2 gins2 Xenopus laevis * View in UniProt * View in Entrez Gene * DNA replication licensing factor mcm2 mcm2 Xenopus laevis * View in UniProt * View in Entrez Gene * Histone H2A type 1 h2afx Xenopus laevis * View in UniProt * View in Entrez Gene * Serine/threonine-protein kinase Chk1 chek1 Xenopus laevis * View in UniProt * View in Entrez Gene * DNA replication licensing factor mcm7-A mcm7-a Xenopus laevis * View in UniProt * View in Entrez Gene * Proliferating cell nuclear antigen POL30 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ubiquitin-like-specific protease 1 ULP1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Maternal DNA replication licensing factor mcm3 mcm3 Xenopus laevis * View in UniProt * View in Entrez Gene * DNA replication licensing factor mcm5-A mcm5-a Xenopus laevis * View in UniProt * View in Entrez Gene * Serine/threonine-protein kinase Chk1 CHEK1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Origin recognition complex subunit 2 orc2 Xenopus laevis * View in UniProt * View in Entrez Gene
Signal-dependent dynamics of transcription factor translocation controls gene expression
- Nat Struct Mol Biol 19(1):31-39 (2012)
Nature Structural & Molecular Biology | Article A unique H2A histone variant occupies the transcriptional start site of active genes * Tatiana A Soboleva1 * Maxim Nekrasov1 * Anuj Pahwa1 * Rohan Williams1, 2 * Gavin A Huttley1 * David J Tremethick1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:25–30Year published:(2012)DOI:doi:10.1038/nsmb.2161Received 02 June 2011 Accepted 21 September 2011 Published online 04 December 2011 Corrected online11 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Change history * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Transcriptional activation is controlled by chromatin, which needs to be unfolded and remodeled to ensure access to the transcription start site (TSS). However, the mechanisms that yield such an 'open' chromatin structure, and how these processes are coordinately regulated during differentiation, are poorly understood. We identify the mouse (Mus musculus) H2A histone variant H2A.Lap1 as a previously undescribed component of the TSS of active genes expressed during specific stages of spermatogenesis. This unique chromatin landscape also includes a second histone variant, H2A.Z. In the later stages of round spermatid development, H2A.Lap1 dynamically loads onto the inactive X chromosome, enabling the transcriptional activation of previously repressed genes. Mechanistically, we show that H2A.Lap1 imparts unique unfolding properties to chromatin. We therefore propose that H2A.Lap1 coordinately regulates gene expression by directly opening the chromatin structure of the TSS at ge! nes regulated during spermatogenesis. View full text Figures at a glance * Figure 1: H2A.Lap1 dynamically loads onto the sex chromosomes in late round spermatids. () Seminiferous tubule sections were indirectly immunostained with Lap1 antibodies (red) and stained with peanut agglutinin Alexa Fluor 488 conjugate (LectinPNA, green) to allow identification of the various spermatid stages on the basis of acrosome maturation9. DNA was costained with DAPI (blue). P, mid-pachytene spermatocytes; LP, late-pachytene spermatocytes; RS, round spermatids. Arrow marks residual bodies (RB; Supplementary Fig. 8). Scale bars, 25 μm. () Surface spreads of leptotene and zygotene cells were prepared from pre-pachytene testes of 12-day-old mice. Surface spreads of pachytene spermatocytes, round spermatids and elongating spermatids were prepared from adult mice. Different cell types were immunostained with SCP3 (a marker for the progression of chromosome synapsis), γX (a component of the XY body in pachytene spermatocytes) or macroH2A1.2 (enriched in centromeric heterochromatin of the Y chromosome in round spermatids). Filled white arrow, XY body. Unfil! led white arrow, Y chromosome centromeric heterochromatin. Scale bar, 10 μm. () Fluorescence in situ hybridization analyses of round spermatids using specific chromosome-X or chromosome-Y paints (reproduced with permission from our previous published study5). White lines in merged images indicate the paths used to determine fluorescence intensity across the sex chromosomes and the chromocenter, graphed at right. C, hromocenter. Scale bars, 10 μm. () Round spermatids were immunostained with Lap1 antibodies and stained with DAPI. Round spermatids were also stained with LectinPNA to distinguish whether a round spermatid was at an early or late stage of development. White lines in merged images indicate the paths used to determine the fluorescence intensity of Lap1 across the DAPI stained sex chromosome, graphed at right. Scale bar, 10 μm. * Figure 2: H2A.Lap1 is located at the TSS of active genes. () H2A.Lap1 ChIP profiles on genes active in round-spermatid X-chromosomes. Each line represents 50 genes, grouped by expression level using published gene expression data6; coloring indicates average gene expression rank in the group. The sum of frequency tag counts in the group is plotted at each base pair relative to the TSS. () Lap1 ChIP profile showing sum of frequency tag counts on 44 X-linked Group C genes, aligned between −1 kb and +1 kb from the TSS. (,) Lap1 ChIP profiles for genes on chromosome 1 () and for the whole genome (), grouped by expression level using global expression of all mouse genes in the 30-day-old testis. We separated 23 groups of 50 genes on chromosome 1 and 201 groups of 100 genes in the whole genome; coloring is as in . Note that for the whole-genome plot, the sum of all shown frequency tag counts equals 1. () Lap1 ChIP profile for the 1,000 most highly expressed mouse genes in the 30-day-old testis, aligned between −5 and +5 kb from the T! SS. () Lap1 ChIP profiles for all mouse genes expressed at the pachytene stage, grouped by expression level (164 groups of 100 genes) using published pachytene expression data6. Coloring is as in . * Figure 3: Targeting of H2A.Lap1 to X chromosome–linked genes occurs in late round spermatids. Six round spermatid–specific X-linked genes were chosen for H2A.Lap1 ChIP and gene expression analyses. () H2A.Lap1 enrichment for each gene in mouse testes at 18, 24, or 30 d of development, relative to Dusp21 at 18 d. H2A.Lap1 signal was assayed by ChIP. ChIP-seq libraries, normalized to the same DNA concentration, were analyzed by quantitative PCR using gene-specific primers that target the TSS. Data shown are means and s.d. of three repeats. () The mRNA level of each gene at each stage of testes development, determined by real-time quantitative PCR, relative to β-actin. Data shown are means and s.d. of three repeats. () H2A.Z ChIP profiles at TSS of all mouse genes expressed in the 30-day-old testis; genes are grouped by average gene expression rank as in Figure 2d (201 groups of 100 genes). () Normalized ChIP profiles of H2A.Z and H2A.Lap1 (with confidence intervals estimated by resampling) for the 1,000 most highly expressed genes in the 30-day-old mouse testis. () ! Cartoon depicting the location of H2A.Z- and H2A.Lap1-containing nucleosomes at the −2 and −1 positions, respectively, relative to the TSS. * Figure 4: H2A.Lap1 has gained a single acidic amino acid residue, which enables nucleosome arrays to partially fold. () Sedimentation coefficient distribution plots of arrays containing human Bbd in the absence or presence of 0.3 mM MgCl2 (reproduced from our previous published study3). (,) Sedimentation coefficient distribution plots of arrays containing wild-type (WT) H2A or Lap1 in the absence or presence of 1.2 mM MgCl2. (,) Sedimentation coefficient distribution plots of arrays containing WT H2A, Lap1 or mutant Lap1 (D100T) in the absence or presence of 0.4 mM MgCl2. Accession codes * Abstract * Accession codes * Change history * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE29781 Change history * Abstract * Accession codes * Change history * Author information * Supplementary informationCorrected online 11 December 2011In the version of this article initially published, the incorrect PDB code for the MthK open channel structure was provided in the legend to Figure 1. The correct PDB code for this structure is 1LNQ. The error has been corrected in the HTML and PDF versions of the article. Author information * Abstract * Accession codes * Change history * Author information * Supplementary information Affiliations * The John Curtin School of Medical Research, The Australian National University, Canberra, Australian Capital Territory, Australia. * Tatiana A Soboleva, * Maxim Nekrasov, * Anuj Pahwa, * Rohan Williams, * Gavin A Huttley & * David J Tremethick * Present address: Singapore Centre on Environmental Life Sciences Engineering, National University of Singapore, Singapore. * Rohan Williams Contributions T.A.S. helped design the experiments, cloned H2A.Lap, conducted all spermatogenesis experiments, prepared chromatin for ChIP-seq experiments and conducted the gene expression and ChIP experiments on individual X-chromosome genes. M.N. conducted the biochemical and biophysical experiments on the nucleosome arrays and prepared DNA ChIP libraries for high-throughput sequencing. R.W. developed and did data analysis of global mouse gene expression data. G.A.H. designed and executed the analysis of the Illumina short-read data. A.P. assisted with the analyses of Illumina short-read data. D.J.T. conceived the project, helped design the experiments and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * David J Tremethick Author Details * Tatiana A Soboleva Search for this author in: * NPG journals * PubMed * Google Scholar * Maxim Nekrasov Search for this author in: * NPG journals * PubMed * Google Scholar * Anuj Pahwa Search for this author in: * NPG journals * PubMed * Google Scholar * Rohan Williams Search for this author in: * NPG journals * PubMed * Google Scholar * Gavin A Huttley Search for this author in: * NPG journals * PubMed * Google Scholar * David J Tremethick Contact David J Tremethick Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–8, Supplementary Table 1 and Supplementary Methods Additional data Entities in this article * Histone H2A.Z H2afz Mus musculus * View in UniProt * View in Entrez Gene * Histone H2A.x H2afx Mus musculus * View in UniProt * View in Entrez Gene * Core histone macro-H2A.1 H2afy Mus musculus * View in UniProt * View in Entrez Gene * Dual specificity phosphatase 21 Dusp21 Mus musculus * View in UniProt * View in Entrez Gene * MCG52127 4930557A04Rik Mus musculus * View in UniProt * View in Entrez Gene
Intrinsic tethering activity of endosomal Rab proteins
- Nat Struct Mol Biol 19(1):40-47 (2012)
Nature Structural & Molecular Biology | Article Signal-dependent dynamics of transcription factor translocation controls gene expression * Nan Hao1, 2, 3 * Erin K O'Shea1, 2, 3, 4 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:31–39Year published:(2012)DOI:doi:10.1038/nsmb.2192Received 13 June 2011 Accepted 13 October 2011 Published online 18 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Information about environmental stimuli is often transmitted using common signaling molecules, but the mechanisms that ensure signaling specificity are not entirely known. Here we show that the identities and intensities of different stresses are transmitted by modulation of the amplitude, duration or frequency of nuclear translocation of the Saccharomyces cerevisiae general stress response transcription factor Msn2. Through artificial control of the dynamics of Msn2 translocation, we reveal how distinct dynamical schemes differentially affect reporter gene expression. Using a simple model, we predict stress-induced reporter gene expression from single-cell translocation dynamics. We then demonstrate that the response of natural target genes to dynamical modulation of Msn2 translocation is influenced by differences in the kinetics of promoter transitions and transcription factor binding properties. Thus, multiple environmental signals can trigger qualitatively different dyna! mics of a single transcription factor and influence gene expression patterns. View full text Figures at a glance * Figure 1: Msn2 translocates to the nucleus with different dynamics in response to different stresses. (–) Time traces of YFP-tagged Msn2 nuclear translocation are shown for glucose limitation (), osmotic stress () and oxidative stress (). In each panel, top row: averages of single-cell time traces of Msn2-YFP translocation in response to the indicated stresses (solid circles, averages of single-cell experimental data; solid lines, s.d. of single-cell responses of ~60 cells, from at least two independent experiments); bottom row: representative single-cell time traces of Msn2-YFP nuclear translocation. AU, arbitrary units of fluorescence. Additional single-cell traces are shown in Supplementary Figure 1a,b. * Figure 2: Quantification of single-cell Msn2-YFP translocation traces. () A schematic defines the initial peak of Msn2 nuclear translocation and subsequent sporadic bursts in a single-cell time trace. () Duration (top row) and amplitude (middle row) of the initial peak are quantified for the indicated stress conditions (open circles, mean value of single cells; error bars, s.d. of single-cell responses of ~60 cells, from at least two independent experiments). Duration is not quantified for the H2O2 treatment, because a sustained translocation event was observed under this condition. () Frequency, amplitude, burst duration and interval durations of sporadic bursts in response to glucose limitation. Frequency of sporadic bursts under osmotic stress is also quantified (right). The distributions of amplitude, duration, and frequency of sporadic nuclear burst in response to glucose limitation are shown in Supplementary Figure 2a–c. Autocorrelation analysis of Msn2 localization traces upon glucose limitation are presented in Supplementary Figure 2d. * Figure 3: Experimental and computational analysis of gene expression in response to modulation of Msn2 nuclear translocation dynamics. () A diagram describes the analog-sensitive system used to control Msn2 nuclear translocation. () Gene expression model. A detailed description of the model construction and fitting procedure are included in Supplementary Results. () Averages of single-cell time traces of Msn2-YFP nuclear localization and reporter gene expression (cyan fluorescent protein, CFP) measured in the same cells in response to inhibitor treatments (black solid circles, averages of time-trace data; black solid lines, s.d. of single-cell data of ~50 cells, from at least two independent experiments; green solid line, curve fitting of Msn2 translocation traces; red solid line, model simulation). The time traces of Msn2 nuclear localization were fit with a piecewise exponential function (Supplementary Fig. 3) to produce continuous time-dependent profiles, TF(t), which served as input for the model. The model in was fit to the averages of single-cell time traces of reporter gene expression (Supplementary ! Results). The complete dataset is included in Supplementary Figures 3–5. * Figure 4: The dynamics of Msn2 nuclear translocation influences target gene expression. () The relationship between gene expression and the area under the curve (AUC) of Msn2 inputs (open circles, experimental data; solid lines, model simulation; error bars, s.d. of single-cell data of ~50 cells, from at least two independent experiments). The integrals of Msn2 inputs were quantified from the data in Supplementary Figures 3–5. Single Msn2 inputs with 10 min (blue), 20 min (red) or 40 min (black) durations were compared with oscillatory Msn2 inputs for 5-min pulse duration (orange). () Relationship between dynamic of Msn2 nuclear inputs and reporter gene expression. Left, gene expression versus Msn2 input amplitude (input duration: black = 40 min; red = 20 min; blue = 10 min); center, gene expression versus Msn2 input duration (input amplitude: yellow green = 2,190 AU; orange = 1,751 AU; black = 1,309 AU; green = 1,010 AU; red = 672 AU; blue = 406 AU); right, gene expression versus Msn2 input frequency (input amplitude = 1,751 AU; pulse duration = 5 min). () M! odel simulations reproduce the measured expression responses to natural stresses. For the indicated stress conditions, each single-cell trace of Msn2 translocation was used as input for the gene expression model. The simulated single-cell expression traces were averaged to generate the simulation curves (solid lines, top row) and compared with averages of measured single-cell expression (solid circles, bottom row). * Figure 5: The model predicts that target genes have distinct responses to different input regimes. Two sets of parameters were varied, and alterations in gene expression output were predicted using the expression model: parameters that govern transcription factor binding, Kd and n; and parameters that govern kinetics of promoter transition, k1 and k2. The inputs are selected to be in the physiological ranges of the natural stress responses (Fig. 2). () The expression curves upon amplitude modulation (AM), duration modulation (DM) and frequency modulation (FM) (left column) and the expression ratios (the ratio of gene expression level upon low stimulus to expression level upon high stimulus) calculated from the expression curves (right column, same genes use same colors for curves and ratios) are shown for hypothetical genes with different binding parameters (Kd, n) and the same promoter kinetics (k1, k2). The values below the bar graph represent the fold changes from the parameter values obtained from fitting the reporter response data (Fig. 3). () Model predictions are s! hown for hypothetical genes with the same binding parameters and different promoter kinetics. () Natural target genes may differ in both binding parameters and promoter kinetics. Model predictions for four hypothetical genes with different binding parameters and different promoter kinetics. Genes 1 and 2 have the same slow promoter kinetics, whereas Genes 3 and 4 have the same fast promoter kinetics. Genes 1 and 3 have the same high transcription factor binding, whereas Genes 2 and 4 have the same low transcription factor binding. * Figure 6: Analysis of a simplified model. () Schematic of the simplified model. () The model behaviors in response to duration modulation inputs when the timescale of promoter transition is longer () and shorter () than input duration. The input durations are Ta and Tb. () The model behaviors in response to frequency modulation inputs. () The responses when the timescales of promoter activation and deactivation are longer than pulse duration and pulse interval, respectively. (–) The responses when the timescale of promoter activation is shorter than pulse duration or when the timescale of promoter inactivation is shorter than pulse interval. Pulse duration is Ton; the interval durations are Toff_a and Toff_b. For and , ω, inputs; P2, promoter activity; R, gene product. () The simulated relationship between gene expression output and input duration. Equations used in simulations are indicated; these relationships are calculated with the median value of the input duration we used in the simulation. Black dashed lin! es, the curve of RAUC = T; red dashed lines, the curve of RAUC = T2. () The simulated relationship between gene expression output and oscillatory input pulse number (n). Black dashed lines, the curve of RAUC = n; red dashed lines, the curve of RAUC = n2. Left: we set k2 = ω · k1 and changed k2 + ω · k1 to the equations used in simulations as indicated. With increasing frequency (pulse number), the interval duration changes from smaller than 1/Ton to larger than 1/Ton. Right: we set k2 + ω · k1 = 0.1 × (1/Ton) and changed Toff to the equations used in simulations as indicated. The variables k2, ω, k1 and Ton are fixed. In this case, pulse number does not correlate with pulse frequency. * Figure 7: Microarray analysis to evaluate the model predictions. () Msn2 nuclear localization response to different 1-NM-PP1 treatments: red line, 120 nM 1-NM-PP1, 20 min; green line, 3 μM 1-NM-PP1, 20 min; blue line, 3 μM 1-NM-PP1, 40 min; orange line, 750 nM 1-NM-PP1, 5 min × 3; black line, 750 nM 1-NM-PP1, 5 min × 6. () Measured time courses of mRNA levels from representative target genes (solid circles: normalized fold change of mRNA level with baseline subtracted). The inputs in panel were used experimentally to produce the measured mRNA time traces (the input and the corresponding response use the same color). () Distributions of Msn2 binding sites (red) relative to the experimentally determined nucleosome profile (blue, data not shown) within promoters of target genes. The averaged nucleosome profiles were obtained by dividing the sum of nucleosome positioning signals of all genes in one group by the gene numbers. The distribution of Msn2 binding sites (5′-AGGGG-3′ or 5′-CCCCT-3′) is represented by bars corresponding to! the sum of the numbers of Msn2 binding sites in each ten-base-pair window. () mRNA ratios of target genes in different encoding regimes (blue, Group I genes; red, Group II genes). The mRNA ratio of each gene is calculated by dividing the area under the curve of the mRNA time course (which correlates with gene expression level, Supplementary Fig. 7) at low transcription factor inputs by the area under the curve at high inputs. Accession codes * Abstract * Accession codes * Author information * Supplementary information Primary accessions Gene Expression Omnibus * GSE32703 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Howard Hughes Medical Institute, Harvard University, Cambridge, Massachusetts, USA. * Nan Hao & * Erin K O'Shea * Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Cambridge, Massachusetts, USA. * Nan Hao & * Erin K O'Shea * Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA. * Nan Hao & * Erin K O'Shea * Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA. * Erin K O'Shea Contributions N.H. and E.K.O. designed the project. N.H. carried out the experiments and analyzed the data. N.H. and E.K.O. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Erin K O'Shea Author Details * Nan Hao Search for this author in: * NPG journals * PubMed * Google Scholar * Erin K O'Shea Contact Erin K O'Shea Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (7M) Supplementary Figures 1–15, Supplementary Results and Supplementary Methods Audio files * Supplementary Video 1 (3M) Time-lapse video of Msn2-YFP in response to 0.1% glucose limitation. * Supplementary Video 2 (3M) Time-lapse video of Msn2-YFP in response to 0.375 M KCl. * Supplementary Video 3 (4M) Time-lapse video of Msn2-YFP in response to 0.01 mM H2O2. * Supplementary Video 4 (2M) Time-lapse video of Msn2-YFP in response to oscillatory 1-NM-PP1 treatment. Additional data Entities in this article * Zinc finger protein MSN2 MSN2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Transcriptional regulator CRZ1 CRZ1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Zinc finger protein MSN4 MSN4 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * cAMP-dependent protein kinase type 1 TPK1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * cAMP-dependent protein kinase type 2 TPK2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * cAMP-dependent protein kinase type 3 TPK3 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Glutaredoxin-1 GRX1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Uncharacterized membrane protein YLR312C YLR312C Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Cellular tumor antigen p53 TP53 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia
Ndc10 is a platform for inner kinetochore assembly in budding yeast
- Nat Struct Mol Biol 19(1):48-55 (2012)
Nature Structural & Molecular Biology | Article Intrinsic tethering activity of endosomal Rab proteins * Sheng-Ying Lo1, 2 * Christopher L Brett1, 5 * Rachael L Plemel1 * Marissa Vignali3 * Stanley Fields3, 4 * Tamir Gonen1, 4, 5 * Alexey J Merz1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:40–47Year published:(2012)DOI:doi:10.1038/nsmb.2162Received 30 May 2010 Accepted 22 September 2011 Published online 11 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Rab small G proteins control membrane trafficking events required for many processes including secretion, lipid metabolism, antigen presentation and growth factor signaling. Rabs recruit effectors that mediate diverse functions including vesicle tethering and fusion. However, many mechanistic questions about Rab-regulated vesicle tethering are unresolved. Using chemically defined reaction systems, we discovered that Vps21, a Saccharomyces cerevisiae ortholog of mammalian endosomal Rab5, functions in trans with itself and with at least two other endosomal Rabs to directly mediate GTP-dependent tethering. Vps21-mediated tethering was stringently and reversibly regulated by an upstream activator, Vps9, and an inhibitor, Gyp1, which were sufficient to drive dynamic cycles of tethering and detethering. These experiments reveal a previously undescribed mode of tethering by endocytic Rabs. In our working model, the intrinsic tethering capacity Vps21 operates in concert with convent! ional effectors and SNAREs to drive efficient docking and fusion. View full text Figures at a glance * Figure 1: GTP-bound Vps21 tethers liposomes. () Experimental configuration. Full details are in Online Methods and Supplementary Methods. () Liposome particle size distributions were measured by QLS after 60-min incubation in the presence of the indicated Rab-His10 proteins, preloaded with GDP or GTP. Error bars indicate mean and s.e.m. for three independent experiments. () TEM images of negatively stained samples taken from experiment in . () Liposomes were prepared as in –, except that fluorescent lipid was incorporated. Liposomes were incubated for 20 or 40 min, then a drop of the suspension was imaged by epifluorescence microscopy (200 ms exposure). Brightness and contrast adjustments are identical for the panels shown. Traces below the images show pixel intensities along the indicated dashed lines (AU, arbitrary units). Untethered liposomes are small and move rapidly and appear as diffuse fluorescence. As tethering proceeds, clusters grow in size and the fluorescent background markedly decreases indicating that ! most individual liposomes in the population have tethered. Liposomes with GDP- His10-Vps21 are shown at 20 min incubation and were indistinguishable from those at 40 min incubation. * Figure 2: Vps21 surface density and tethering activity. (,) Liposome tethering, measured by QLS, was examined as a function of Vps21 membrane surface density. Vps21 was loaded with GTP () or GDP (). Insets, onset of tethering at low Vps21 surface densities. Additional surface density data for Vps21 and Ypt7 are in Supplementary Figure 1. () To test effect of ionic strength, liposomes were decorated with Vps21-GDP or Vps21-GTP at two different surface densities, and tethering was monitored by QLS in buffers containing indicated salt concentrations. As in ,, indicated Vps21 surface densities are upper-bound estimates. Data are mean and s.e.m. from three independent experiments. * Figure 3: Vps21 interactions in trans are required for efficient tethering. () Schematic of two possible mechanisms of Rab-mediated tethering. () Schematic of bead-liposome tethering assay. () GTP-loaded GST–Vps21 beads were photographed after incubation for 20 or 60 min in presence of fluorescent liposomes containing 6 mol% Ni2+-NTA-DOGS and GTP-loaded Vps21-His10. Images are representative of nine independent experiments. () As in (inset) but without GTP-loaded Vps21-His10. () As in (inset), but liposomes were prepared without Ni2+-NTA-DOGS. () As in , except that after 20 min incubation, 10 mM reduced glutathione was added (left), or buffer without glutathione was added (right). Samples were then incubated for 4 min more, then photographed. Scale bars, 15 μm () and 75 μm (–). * Figure 4: The Vps21 C-terminal linker is not required for tethering. () Vps21-His10 fusion proteins lacking last 10, 20 or 30 residues of the Vps21 C-terminal linker were prepared. Purified proteins (5 μg) were analyzed by SDS-PAGE. () Liposomes bearing these proteins were assayed by QLS for the ability to drive tethering over indicated range of surface densities. Each construct was loaded with either GTP (filled symbols) or GDP (open symbols). Liposomes contained 4.5 mol% Ni2+-NTA-DOGS. Error bars indicate mean and s.e.m. from four independent experiments. * Figure 5: Vps21-GTP interacts with known effectors and with itself in yeast two-hybrid assays. A positive interaction in the yeast two-hybrid assay is indicated by yeast colony growth on medium lacking tryptophan, leucine and histidine, and supplemented with 1.5 mM 3-aminotriazole. The Vps21 effectors Vac1 (also known as Pep7), Vps3 and Vps8 are positive controls for interaction selectivity with Vps21-GTP, whereas Vps9 is a control for interaction selectivity with Vps21-GDP. * Figure 6: Vps21 interacts with Ypt53 and Ypt10 to drive GTP-dependent heterotypic tethering. () Heterotypic Rab-Rab tethering was assayed as in Figure 3 except that beads were decorated with various GTP-loaded GST-Rab fusion proteins, as indicated. Bottom, representative fields of beads under epifluorescence illumination. Top, fluorescence intensity profile plots of representative beads. () Assays were done as in , except that the Rabs were preloaded with either GTP or GDP. Ypt6, which does not interact with Vps21, was a negative control. Scale bars, 75 μm. * Figure 7: Regulation and reversibility of Vps21-mediated liposome tethering. () GEF-stimulated tethering. Tethering by GDP-loaded Vps21-decorated liposomes was measured by QLS after addition of 0.2 mM GTP and varying concentrations of Vps9. Data are mean and s.e.m.; data points from three independent experiments were binned into 10-min intervals. () GAP-mediated reversal of tethering. GTP-loaded Vps21-decorated liposome tethering was measured by QLS after addition of Gyp1TBC or Gyp1TBC-R343K. Error bars indicate mean and s.e.m.; data from three independent experiments were binned into 2-min intervals. () Regulated cycle of tethering and detethering. Vps21-mediated liposome tethering, measured by QLS, was examined during sequential addition of 20 μM GTP, 5 μM Vps9 and 10 μM Gyp1TBC. Data are representative of three independent experiments. () Histograms of Vps21-decorated liposome size distributions, derived from QLS, at time points indicated in . () TEM images of negatively stained samples withdrawn at indicated time points from experiment analyze! d in ,. * Figure 8: Model for Rab-Rab driven tethering in endosome docking and fusion. In this working model, three representative Rab functions are shown: classical effector-mediated tethering, Rab-Rab tethering and coordination of trans-SNARE complex assembly by a Rab-mediated recruitment of a SNARE-binding regulator. Together, these mechanisms could in principle coordinate an ordered tethering, docking and fusion sequence. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Biochemistry, University of Washington School of Medicine, Seattle, Washington, USA. * Sheng-Ying Lo, * Christopher L Brett, * Rachael L Plemel, * Tamir Gonen & * Alexey J Merz * Department of Chemistry, University of Washington, Seattle, Washington, USA. * Sheng-Ying Lo * Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington, USA. * Marissa Vignali & * Stanley Fields * Howard Hughes Medical Institute, University of Washington School of Medicine, Seattle, Washington, USA. * Stanley Fields & * Tamir Gonen * Present addresses: Department of Biology, Concordia University, Montreal, Quebec, Canada (C.L.B.); and Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA (T.G.). * Christopher L Brett & * Tamir Gonen Contributions S.Y.L. and A.J.M. conceived the project. S.Y.L. developed and validated the QLS-based tethering system; expressed, purified and characterized proteins; prepared liposomes and carried out and interpreted all QLS tethering experiments. C.L.B. and A.J.M. conceived and C.L.B. and S.Y.L. implemented the fluorescence microscopy-based tethering assays. T.G. did the E M. S.F. and M.V. developed the high-throughput yeast two-hybrid technology, and R.L.P. and M.V. executed and interpreted yeast two-hybrid screens and assays. S.Y.L. and A.J.M. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Alexey J Merz Author Details * Sheng-Ying Lo Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher L Brett Search for this author in: * NPG journals * PubMed * Google Scholar * Rachael L Plemel Search for this author in: * NPG journals * PubMed * Google Scholar * Marissa Vignali Search for this author in: * NPG journals * PubMed * Google Scholar * Stanley Fields Search for this author in: * NPG journals * PubMed * Google Scholar * Tamir Gonen Search for this author in: * NPG journals * PubMed * Google Scholar * Alexey J Merz Contact Alexey J Merz Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–4, Supplementary Tables 1–4 and Supplementary Methods Additional data Entities in this article * Vacuolar protein sorting-associated protein 21 VPS21 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ras-related protein Rab-5A RAB5A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Vacuolar protein sorting-associated protein 9 VPS9 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * GTPase-activating protein GYP1 GYP1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Early endosome antigen 1 EEA1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Thyroid receptor-interacting protein 11 TRIP11 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * ADP-ribosylation factor 1 ARF1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * GTP-binding protein YPT7 YPT7 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ras-related protein Rab-3A RAB3A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Rab GDP-dissociation inhibitor GDI1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Rab proteins geranylgeranyltransferase component A MRS6 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Protein transport protein YIF1 YIF1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * GTP-binding protein YPT52 YPT52 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * GTP-binding protein YPT53 YPT53 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * GTP-binding protein YPT10 YPT10 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ras-related protein Rab-6A RAB6A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * GTP-binding protein YPT6 YPT6 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ras-related protein Rab-7a RAB7A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Vacuolar protein sorting-associated protein 3 VPS3 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Vacuolar protein sorting-associated protein 8 VPS8 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Vacuolar segregation protein PEP7 PEP7 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Small COPII coat GTPase SAR1 SAR1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ras-related protein Rab-5B RAB5B Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ras-related protein Rab-5C RAB5C Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ras-related protein Rab-9A RAB9A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ras-related protein Rab-11A RAB11A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Carboxypeptidase Y PRC1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Vacuolar protein sorting-associated protein 45 VPS45 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Rabenosyn-5 ZFYVE20 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia
X-chromosome hyperactivation in mammals via nonlinear relationships between chromatin states and transcription
- Nat Struct Mol Biol 19(1):56-61 (2012)
Nature Structural & Molecular Biology | Article Ndc10 is a platform for inner kinetochore assembly in budding yeast * Uhn-Soo Cho1 * Stephen C Harrison1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:48–55Year published:(2012)DOI:doi:10.1038/nsmb.2178Received 14 June 2010 Accepted 20 September 2011 Published online 04 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Kinetochores link centromeric DNA to spindle microtubules and ensure faithful chromosome segregation during mitosis. In point-centromere yeasts, the CBF3 complex Skp1–Ctf13–(Cep3)2–(Ndc10)2 recognizes a conserved centromeric DNA element through contacts made by Cep3 and Ndc10. We describe here the five-domain organization of Kluyveromyces lactis Ndc10 and the structure at 2.8 Å resolution of domains I–II (residues 1–402) bound to DNA. The structure resembles tyrosine DNA recombinases, although it lacks both endonuclease and ligase activities. Structural and biochemical data demonstrate that each subunit of the Ndc10 dimer binds a separate fragment of DNA, suggesting that Ndc10 stabilizes a DNA loop at the centromere. We describe in vitro association experiments showing that specific domains of Ndc10 interact with each of the known inner-kinetochore proteins or protein complexes in budding yeast. We propose that Ndc10 provides a central platform for inner-kinetocho! re assembly. View full text Figures at a glance * Figure 1: Domains of K. lactis Ndc10 and crystal structure of DI–II. () Domain organization of Ndc10; numbers show residues at the domain boundaries and are derived either from limited proteolysis or from the crystal structure. () Structure of K. lactis Ndc10 (DI–II; 1–402) with 30-bp poly(dA-dT) DNA. Domain I (N domain, residues 1–100) is in cyan, and domain II (DNA-binding domain, residues 101–402) is in dark blue. Dashed lines represent disordered residues 36–39 and 283–292. A second, symmetry-related, 15-bp DNA fragment is shown in gray. The DNA has been modeled as poly(dA-dT) (see text), with the sequences of 5′-TTAATTTATAAAATT-3′ (1–15) and 5′-AAATTTTATAAATTA-3′ (1′–15′), as indicated. () Sequence conservation of Ndc10 among point-centromere yeasts. Location of insertions (red) in S. cerevisiaeNdc10 DI–II with respect to K. lactis Ndc10 DI–II, shown on a schematic representation of the primary sequence and on a ribbon representation of the structure. All molecular illustrations were made with PyMOL (Delan! o Scientific). * Figure 2: Surface charge distribution and DNA contacts of Ndc10 DI–II. () Two views of the surface charge distribution of Ndc10 DI–II; bound DNA is shown in worm representation. () Sugar-phosphate backbone interactions. Residues involved in DNA contacts are labeled and shown in stick representation. Colors as in Figure 1b. () EMSA of wild-type and mutant Ndc10 (10% (w/v) TBE acrylamide gel stained sequentially with ethidium bromide and Coomassie blue). * Figure 3: Structural alignment of K. lactis Ndc10 DI–II with Flp recombinases. () Monomer structure of Flp (PDB 1M6X) aligned with the K. lactis Ndc10 DI–II. The N domain and the DNA-binding domain of Flp recombinase are colored in orange and yellow, respectively. In Flp, the DNA structure of the Holliday junction was replaced by 30-bp CDEIII DNA for simple comparison. () Folding diagrams of K. lactis Ndc10 DI–II and Flp recombinase. Secondary-structure elements are labeled according to their position in the polypeptide chain; domains are colored as in panel . * Figure 4: Dimerization of K. lactis Ndc10 DI–III. () Views of the probable Ndc10 DI–II dimer (symmetry axis along b in the C2221 space group). The subunits of the dimer contact different pseudocontinuous DNA duplexes. Domains I and II of the Ndc10 dimer are colored in cyan and blue for the one molecule, and green and orange for the other. () EMSA of Ndc10 DI–III with increasing amounts of 30-bp CDEIII DNA. Color code for proteins is the same as in . () DNA-capture assay with two different labels. Either Ndc10 DI–III or Ndc10 DI–II was incubated with a mixture of equal amounts of biotinylated and unmodified CDEIII DNA, the latter including 32P-labeled product (10%). (–) Ratio of Ndc10 DI–III and CDEIII DNA, as determined by analytical size-exclusion chromatography. * Figure 5: Interactions of Ndc10-associated proteins or protein complexes in the inner kinetochore. (–) Ni2+ affinity pulldown of 35S-labeled, in vitro translated prey proteins with purified, His-tagged bait protein, analyzed by SDS-PAGE and visualized by phosphoimaging. Each panel includes a lane loaded with 10% of the in vitro translation reaction mixture (to monitor extent of synthesis) and either in vitro translated maltose-binding protein as a prey or purified His-tagged MBP as a bait (negative controls). * Figure 6: Interaction of Ndc10 domain IV–V with N-terminal Scm3. () Ni2+ affinity pulldown of 35S-labeled, in vitro translated Ndc10 proteins with purified, His-tagged Scm3 proteins, analyzed by SDS-PAGE and visualized by phosphoimaging. () In vitro amylose pulldown of purified MBP-tagged Scm3 proteins with Ndc10 domain IV–V. () Schematic overview of domain association of K. lactis Ndc10 with other kinetochore proteins. Ndc10 DI interacts with CBF3 core; Ndc10 DI–II, with Cbf1 (229–359) and Bir1p (1–328). Scm3 N (1–28) associates with Ndc10 DIV–V but not with DV. Interaction of Cbf1 with Ndc10 was confirmed by analytical size-exclusion chromatography using purified proteins (Supplementary Fig. 6). * Figure 7: Schematic model of Ndc10 interactions on budding yeast centromeres. Cbf1 and CBF3 core recognize CDEI and CDEIII, respectively. Ndc10 does not have sequence-specific DNA contacts, but it binds in defined register through its interactions with Cbf1 and CBF3 core. We propose that these contacts bring CDEI and CDEIII together to form a loop. Two potential loop configurations are shown. The Scm3–Cse4–H4 heterotrimeric complex can be recruited through Scm3–Ndc10 interaction. Accession codes * Abstract * Accession codes * Author information * Supplementary information Primary accessions Protein Data Bank * 3SQI * 3T79 * 3SQI * 3T79 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Jack and Eileen Connors Structural Biology Laboratory and Howard Hughes Medical Institute, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA. * Uhn-Soo Cho & * Stephen C Harrison Contributions U.-S.C. designed and conducted experiments, determined and refined the structures, analyzed data and wrote the manuscript; S.C.H directed the project, analyzed data and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Stephen C Harrison Author Details * Uhn-Soo Cho Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen C Harrison Contact Stephen C Harrison Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (10.1 MB) Supplementary Figures 1–8 and Supplementary Methods Additional data Entities in this article * Suppressor of kinetochore protein 1 SKP1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Centromere DNA-binding protein complex CBF3 subunit C CTF13 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Centromere DNA-binding protein complex CBF3 subunit B CEP3 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Centromere DNA-binding protein complex CBF3 subunit A CBF2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Histone H3-like centromeric protein A CENPA Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Histone H4 Homo sapiens * View in UniProt * View in Antibodypedia * Histone H3-like centromeric protein CSE4 CSE4 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Protein MIF2 MIF2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Centromere protein C 1 CENPC1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Centromere-binding protein 1 CBF1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Protein SCM3 SCM3 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * S-phase kinase-associated protein 1 SKP1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * S-phase kinase-associated protein 2 SKP2 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Cullin-1 CUL1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Spindle assembly checkpoint kinase IPL1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Inner centromere protein-related protein SLI15 SLI15 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Protein BIR1 BIR1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * N-terminal-borealin-like protein NBL1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Aurora kinase B AURKB Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Inner centromere protein INCENP Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Baculoviral IAP repeat-containing protein 5 BIRC5 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Borealin CDCA8 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Histone H3-like centromeric protein CSE4 KLLA0C12529g Kluyveromyces lactis (strain ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37) * View in UniProt * View in Entrez Gene * Site-specific recombinase Flp Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * Recombinase cre cre Enterobacteria phage P1 * View in UniProt * View in Entrez Gene * Centromere-associated factor Kluyveromyces lactis * View in UniProt * Centromere-binding protein 1 Kluyveromyces lactis (strain ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37) * View in UniProt * Holliday junction recognition protein HJURP Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Histone H4 Kluyveromyces lactis (strain ATCC 8585 / CBS 2359 / DSM 70799 / NBRC 1267 / NRRL Y-1140 / WM37) * View in UniProt
An ankyrin-repeat ubiquitin-binding domain determines TRABID's specificity for atypical ubiquitin chains
- Nat Struct Mol Biol 19(1):62-71 (2012)
Nature Structural & Molecular Biology | Article X-chromosome hyperactivation in mammals via nonlinear relationships between chromatin states and transcription * Eda Yildirim1, 2, 3, 4 * Ruslan I Sadreyev1, 2, 3, 4 * Stefan F Pinter1, 2, 3 * Jeannie T Lee1, 2, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:56–61Year published:(2012)DOI:doi:10.1038/nsmb.2195Received 11 October 2011 Accepted 08 November 2011 Published online 04 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Dosage compensation in mammals occurs at two levels. In addition to balancing X-chromosome dosage between males and females via X inactivation, mammals also balance dosage of Xs and autosomes. It has been proposed that X-autosome equalization occurs by upregulation of Xa (active X). To investigate mechanism, we perform allele-specific ChIP-seq for chromatin epitopes and analyze RNA-seq data. The hypertranscribed Xa demonstrates enrichment of active chromatin marks relative to autosomes. We derive predictive models for relationships among Pol II occupancy, active mark densities and gene expression, and we suggest that Xa upregulation involves increased transcription initiation and elongation. Enrichment of active marks on Xa does not scale proportionally with transcription output, a disparity explained by nonlinear quantitative dependencies among active histone marks, Pol II occupancy and transcription. Notably, the trend of nonlinear upregulation also occurs on autosomes. Th! us, Xa upregulation involves combined increases of active histone marks and Pol II occupancy, without invoking X-specific dependencies between chromatin states and transcription. View full text Figures at a glance * Figure 1: Allele-specific ChIP-seq. () Profiles for Pol II-S2P, H3K4me3 and H3K36me3 are mapped to M. castaneus (cast) or M. musculus (mus) alleles for two imprinted loci, Zim1 (ref. 47) and Peg3 (ref. 48) on chromosome 7. Composite tracks (comp) represent combination of cast, mus and neutral reads. Coverage values are normalized by input and are indicated on the y axis. () X chromosome shows a strong allelic skew in the occupancy of active histone marks and Pol II at the TSS and across the gene body. Bar plots show mean composite densities of Pol II-S5P, Pol II-S2P, H3K4me3 and H3K36me3 on autosomes (A) and X chromosome (X), with proportion of allelic coverage indicated by red (cast; active X) and blue (mus; inactive X) fractions. * Figure 2: Distributions of coverage densities for Pol II and active histone modifications on X chromosome and autosomes. Coverage density values are shown for H3K4me3 and Pol II-S5P at the TSS and for H3K36me3 and Pol II-S2P across the gene bodies as indicated. Distributions are plotted for actively transcribed (HCP+LCP, HCP and LCP) genes. Black line, autosomal genes; red line, X-linked genes. * Figure 3: Relationships between levels of gene expression, Pol II and active histone modifications. M. castaneus alleles of actively expressed autosomal HCP genes are represented as points, with point density shown by colored contour. Black line contour represents active HCP X-linked M. castaneus alleles (Xa). Expression, Pol II and histone modification levels are positively correlated, the relationships are nonlinear, and X-linked genes follow autosomal trends of dependency, albeit with a shift to higher values. (,) Pol II densities at the TSS () and across the gene body () versus expression (log-log scale). () H3K4me3 densities at the TSS versus expression (log-log scale). () H3K36me3 densities across the gene body versus expression (linear-log scale). () H3K4me3 versus Pol II densities at the TSS (log-log scale). (f H3K36me3 densities across the gene body versus Pol II densities at the TSS (linear-log scale). () H3K4me3 densities at the TSS versus Pol II densities across the gene body (log-log scale). () H3K36me3 versus Pol II densities across the gene body (linear-log ! scale). Decimal logarithms are used. * Figure 4: Autosomal relationships between active histone modifications, Pol II and expression are predictive of X-linked gene expression. () Actively expressed X-linked and autosomal genes show similar patterns of correlation between the levels of active marks and expression. Pearson correlation coefficients between the levels of all marks and expression (FPKM) are shown as heat maps for actively expressed (HCP+LCP, HCP and LCP) genes. In each plot, autosomal and X chromosome correlations are shown above and below diagonal, respectively. () Active X chromosome loci (X) and the corresponding set of autosomal loci (A) show similar nonlinear relationship between active marks and expression (blue curve), which produces a large average expression change in response to smaller changes in the mark occupancy (schematic). () Scatter plot of X-linked gene expression values predicted from autosome-based full linear model versus observed X-linked expression (decimal log-log scale). Shades of blue indicate point density. Identity line y = x is shown in red. Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE33823 Sequence Read Archive * SRA010053 Author information * Abstract * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Eda Yildirim & * Ruslan I Sadreyev Affiliations * Howard Hughes Medical Institute, Boston, Massachusetts, USA. * Eda Yildirim, * Ruslan I Sadreyev, * Stefan F Pinter & * Jeannie T Lee * Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, USA. * Eda Yildirim, * Ruslan I Sadreyev, * Stefan F Pinter & * Jeannie T Lee * Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA. * Eda Yildirim, * Ruslan I Sadreyev, * Stefan F Pinter & * Jeannie T Lee Contributions E.Y. and J.T.L. designed the research; E.Y. and S.F.P. conducted ChIP-seq experiments; R.I.S. performed the bioinformatics analysis; S.F.P. designed the allele-specific ChIP-seq strategy and performed allele-specific alignments; E.Y., R.I.S., S.F.P., and J.T.L. analyzed the data; and E.Y., R.I.S., and J.T.L. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Jeannie T Lee Author Details * Eda Yildirim Search for this author in: * NPG journals * PubMed * Google Scholar * Ruslan I Sadreyev Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan F Pinter Search for this author in: * NPG journals * PubMed * Google Scholar * Jeannie T Lee Contact Jeannie T Lee Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (16.4 MB) Supplementary Figures 1–4 and Supplementary Tables 1–3 Additional data Entities in this article * Zinc finger, imprinted 1 Zim1 Mus musculus * View in UniProt * View in Entrez Gene * Paternally-expressed gene 3 protein Peg3 Mus musculus * View in UniProt * View in Entrez Gene * Males-absent on the first protein mof Drosophila melanogaster * View in UniProt * View in Entrez Gene * RNA on the X 1 roX1 Drosophila melanogaster * View in Entrez Gene * RNA on the X 2 roX2 Drosophila melanogaster * View in Entrez Gene * Inactive X specific transcripts Xist Mus musculus * View in Entrez Gene * Proto-oncogene c-Fos Fos Mus musculus * View in UniProt * View in Entrez Gene * Transcription factor AP-1 Jun Mus musculus * View in UniProt * View in Entrez Gene
Mechanism of mismatch recognition revealed by human MutSβ bound to unpaired DNA loops
- Nat Struct Mol Biol 19(1):72-78 (2012)
Nature Structural & Molecular Biology | Article An ankyrin-repeat ubiquitin-binding domain determines TRABID's specificity for atypical ubiquitin chains * Julien D F Licchesi1 * Juliusz Mieszczanek1 * Tycho E T Mevissen1 * Trevor J Rutherford1 * Masato Akutsu1 * Satpal Virdee1, 3 * Farid El Oualid2 * Jason W Chin1 * Huib Ovaa2 * Mariann Bienz1 * David Komander1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:62–71Year published:(2012)DOI:doi:10.1038/nsmb.2169Received 07 April 2011 Accepted 29 September 2011 Published online 11 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Eight different types of ubiquitin linkages are present in eukaryotic cells that regulate diverse biological processes. Proteins that mediate specific assembly and disassembly of atypical Lys6, Lys27, Lys29 and Lys33 linkages are mainly unknown. We here reveal how the human ovarian tumor (OTU) domain deubiquitinase (DUB) TRABID specifically hydrolyzes both Lys29- and Lys33-linked diubiquitin. A crystal structure of the extended catalytic domain reveals an unpredicted ankyrin repeat domain that precedes an A20-like catalytic core. NMR analysis identifies the ankyrin domain as a new ubiquitin-binding fold, which we have termed AnkUBD, and DUB assays in vitro and in vivo show that this domain is crucial for TRABID efficiency and linkage specificity. Our data are consistent with AnkUBD functioning as an enzymatic S1′ ubiquitin-binding site, which orients a ubiquitin chain so that Lys29 and Lys33 linkages are cleaved preferentially. View full text Figures at a glance * Figure 1: Structure and specificity of an extended TRABID OTU domain. () Schematic representation of the functional domains of TRABID (top) and species conservation derived from a multiple sequence alignment (http://www.ensembl.org) (middle). An extended catalytic OTU domain was analyzed (residues 245–697, bottom). () Linkage specificity of the extended catalytic OTU domain of TRABID using diubiquitin molecules of all eight linkage types, analyzed as reported before26. TRABID was incubated with diubiquitin for the indicated times, and the reaction mixtures were resolved on an SDS-PAGE gel and silver stained. Ub, ubiquitin. () Structure of the extended TRABID OTU domain. The catalytic core is colored in shades of blue, where dark blue indicates the minimal OTU core domain, and the lighter blue indicates additional secondary structure elements found in the A20-like subfamily of OTU DUBs. The ankyrin repeats are shown in two shades of orange. The catalytic triad residues are indicated in ball-and-stick representation. () Structure of A20 (green! , left, PDB 2VFJ23) and superposition with TRABID (blue, right). () Catalytic triad residues of TRABID are shown in ball-and-stick representation with yellow sulfur, red oxygen and blue nitrogen atoms. A red sphere indicates a water molecule, and yellow dotted lines indicate hydrogen bonds. A 2Fo – Fc electron density map contoured at 1σ covers relevant residues. () The A20 catalytic triad is shown, with atoms colored as in . * Figure 2: TRABID contains two ankyrin repeats with roles in ubiquitin binding. () Structure of the ankyrin domain in TRABID showing the two repeats. () Structure of RNase L (PDB 1WDY47), the ankyrin-repeat protein with highest similarity to the TRABID ankyrin domain in a DALI search (Z score 8.4). The eight ankyrin repeats are numbered. () Superposition of the TRABID ankyrin domain and RNase L. () The minimal OTU domain of yeast Otu1 (green) with ubiquitin (yellow) bound at the S1 site (PDB 3BY4 (ref. 25)). The orientation matches that of the minimal OTU domain core indicated in Figure 1c. Ub, ubiquitin. () Superposition of TRABID and yeast Otu1 reveals the relative position of the S1 ubiquitin-binding site on TRABID, and this suggests that the ankyrin domain may constitute an S1′ ubiquitin-binding site. * Figure 3: A conserved hydrophobic surface on AnkUBD binds ubiquitin. () 1H-15N HSQC spectrum of 13C-15N–labeled TRABID ankyrin domain. () Closeup of the region within the red box in , showing resonances of the doubly labeled ankyrin domain (blue) and their shifts upon addition of 250 μM (yellow) or 1 mM (red) unlabeled ubiquitin (Ub). Arrows indicate the shift of individual resonances. () Weighted chemical shift perturbation map of the AnkUBD binding to ubiquitin. () AnkUBD residues are colored according to the degree of perturbation from blue (unperturbed) to red (strongly perturbed), and crucial residues are shown in stick representation. () The AnkUBD surface is shown colored as in and key residues are labeled. () Invariant residues derived from a species sequence alignment (Supplementary Fig. 2b) are shown in red on a white AnkUBD surface. * Figure 4: AnkUBD binds the ubiquitin hydrophobic patch. Ubiquitin (Ub) binding to the AnkUBD was confirmed by NMR shift mapping experiments, for which spectra of 15N ubiquitin were recorded in the absence and presence of AnkUBD (Supplementary Fig. 3). () Perturbation of a selected resonance (that of ubiquitin Leu43, yellow) by titration of increasing concentrations of AnkUBD (colored from red to cyan) is shown as an example. The complete spectra can be found in Supplementary Figure 3. () The resulting weighted chemical shift perturbation map reveals a familiar pattern seen when proteins bind to the ubiquitin hydrophobic patch. () Ubiquitin residues are colored according to the degree of perturbation from blue (unperturbed) to red (strongly perturbed) and crucial residues are shown in stick representation. () The ubiquitin surface is shown colored as in and crucial residues are labeled. () Titration experiments using indicated concentrations of AnkUBD mutants H317A (left), I320D (middle) and L332E (right) were conducted. The same ! resonance as in is shown. Mutant L332E did not perturb any resonances, whereas H317A and I320D perturbed a few resonances to a lesser degree (Supplementary Fig. 3). * Figure 5: Analysis of TRABID DUB activity. () Bacterial TRABID variants were incubated with polyubiquitin substrates for indicated times and visualized by silver staining. Comparison of activity and specificity of the isolated OTU domain (above, [E] 1.2 μM) with TRABID AnkOTU (below, [E] 0.2 μM, reproduced from Fig. 1b to allow comparison). Input enzyme levels are shown in OTU panel (see also Supplementary Fig. 4a). Ub, ubiquitin. (–) Mammalian TRABID variants were incubated with polyubiquitin substrates for indicated times and visualized by silver staining. Flag-tagged TRABID variants were purified from HEK293 cells and used in DUB assays. () Specificity of mammalian full-length (FL), AnkOTU and OTU TRABID against the diubiquitin panel after overnight (O/N, 16 h) incubation. () Time-course analysis of mammalian TRABID variants against its substrate linkages. FL ΔAnk means full-length, lacking AnkUBD. Input (Inp) controls highlight the stability of ubiquitin substrates in the absence of enzyme in the reaction mi! xture. () Activity of full-length TRABID with point mutations in the AnkUBD against its preferred diubiquitin substrates. Full-length C443S, catalytic mutant. DUB activity assays carried out with material obtained from Flag-empty vector (ev) immunoprecipitation showed no activity. () Time-course activity of TRABID variants against Lys63-linked hexaubiquitin. * Figure 6: Role of the NZF domains in cleaving longer ubiquitin chains. Mammalian TRABID variants were incubated with polyubiquitin substrates for indicated times and visualized by silver staining. () Activity of TRABID variants against Lys29, Lys33 and Lys63-linked diubiquitin (Ub2) at indicated time point. Full-length C443S, catalytic mutant; full-length NZFmut, full-length with mutations in all three NZF domains; FL ΔAnk, full-length, lacking AnkUBD; AnkOTU, crystallized fragment; OTU, OTU domain. () Time-course analysis of mammalian full-length TRABID, full-length NZFmut and AnkOTU activity toward Lys63-linked hexaubiquitin. () Model for the role of the AnkUBD as an S1′ ubiquitin-binding site in TRABID. () Model for the additional contribution of the NZF domains in cleaving longer polyubiquitin chains. * Figure 7: In vivo DUB assay NZF and AnkUBD are essential for TRABID puncta. () Localization studies with GFP-TRABID in COS-7 cells 18 h after transfection (left). Nuclei are stained using DAPI (middle). The right image is a merge of the channels. The domain structure of TRABID is shown above. () A GFP-tagged full-length TRABID catalytic mutant (C443S; a yellow star in the domain representation indicates the mutation) adopts a punctate localization in COS-7 (shown) and other cell types35. () FRAP experiments on a control (black) or puncta-containing volume (C443S, blue). Fluorescent recovery is recorded over time. () Localization studies of TRABID GFP-tagged AnkOTU C443S and GFP-tagged full-length NZFmut C443S, colored as in . The domain structure is shown (left), and the GFP fluorescence of either construct (right) shows that no puncta are formed. Ub, ubiquitin. () Puncta-forming GFP-tagged C443S (left image) was coexpressed with Flag-ubiquitin or single-lysine ('Konly') ubiquitin mutants (middle image). The merged image is shown to the right. Furth! er ubiquitin mutants are shown in Supplementary Figure 6a. (–) Dissolving TRABID assemblies requires the AnkUBD. () Puncta-forming GFP-tagged full-length TRABID C443S (left) was expressed in COS-7 cells and TRABID assemblies were visualized (left). Nuclei are stained using DAPI (middle). The merged image is shown to the right. (–) As in , but in addition, Flag-tagged full-length WT TRABID constructs (), full-length NZFmut () or full-length ΔAnk () were coexpressed (far left), and the presence of GFP puncta was assessed. Additional data are shown in Supplementary Figure 6b. Accession codes * Abstract * Accession codes * Author information * Supplementary information Primary accessions Protein Data Bank * 3ZRH * 3ZRH Referenced accessions Protein Data Bank * 2VFJ * 1WDY * 3BY4 * 2VFJ * 1WDY * 3BY4 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Medical Research Council Laboratory of Molecular Biology, Cambridge, UK. * Julien D F Licchesi, * Juliusz Mieszczanek, * Tycho E T Mevissen, * Trevor J Rutherford, * Masato Akutsu, * Satpal Virdee, * Jason W Chin, * Mariann Bienz & * David Komander * Division of Cell Biology, Netherlands Cancer Institute, Amsterdam, The Netherlands. * Farid El Oualid & * Huib Ovaa * Present address: Scottish Institute for Cell Signalling, Protein Ubiquitylation Unit, University of Dundee, Dundee, UK. * Satpal Virdee Contributions D.K., M.B. and J.D.F.L. designed the research. J.D.F.L., D.K., J.M., T.E.T.M., T.J.R. and M.A. conducted the experiments. F.E., H.O., S.V. and J.W.C. contributed reagents. D.K. wrote the manuscript, with help from all authors. Competing financial interests H.O. and F.E. are cofounders of UbiQ Bio BV. Corresponding author Correspondence to: * David Komander Author Details * Julien D F Licchesi Search for this author in: * NPG journals * PubMed * Google Scholar * Juliusz Mieszczanek Search for this author in: * NPG journals * PubMed * Google Scholar * Tycho E T Mevissen Search for this author in: * NPG journals * PubMed * Google Scholar * Trevor J Rutherford Search for this author in: * NPG journals * PubMed * Google Scholar * Masato Akutsu Search for this author in: * NPG journals * PubMed * Google Scholar * Satpal Virdee Search for this author in: * NPG journals * PubMed * Google Scholar * Farid El Oualid Search for this author in: * NPG journals * PubMed * Google Scholar * Jason W Chin Search for this author in: * NPG journals * PubMed * Google Scholar * Huib Ovaa Search for this author in: * NPG journals * PubMed * Google Scholar * Mariann Bienz Search for this author in: * NPG journals * PubMed * Google Scholar * David Komander Contact David Komander Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (5M) Supplementary Figures 1–6 and Supplementary Methods Additional data Entities in this article * Ubiquitin thioesterase ZRANB1 ZRANB1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Catenin beta-1 CTNNB1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ubiquitin thioesterase OTUB1 OTUB1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ubiquitin thioesterase OTUB2 OTUB2 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Tumor necrosis factor alpha-induced protein 3 TNFAIP3 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ubiquitin thioesterase OTU1 OTU1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Transitional endoplasmic reticulum ATPase VCP Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * OTU domain-containing protein 7B OTUD7B Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * AMSH-like protease STAMBPL1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * OTU domain-containing protein 5 OTUD5 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ubiquitin carboxyl-terminal hydrolase 5 USP5 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * E3 ubiquitin-protein ligase UBR5 UBR5 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * 2-5A-dependent ribonuclease RNASEL Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia
The extracellular chaperone clusterin sequesters oligomeric forms of the amyloid-β1−40 peptide
- Nat Struct Mol Biol 19(1):79-83 (2012)
Nature Structural & Molecular Biology | Article Mechanism of mismatch recognition revealed by human MutSβ bound to unpaired DNA loops * Shikha Gupta1 * Martin Gellert1 * Wei Yang1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:72–78Year published:(2012)DOI:doi:10.1038/nsmb.2175Received 09 August 2011 Accepted 12 October 2011 Published online 18 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg DNA mismatch repair corrects replication errors, thus reducing mutation rates and microsatellite instability. Genetic defects in this pathway cause Lynch syndrome and various cancers in humans. Binding of a mispaired or unpaired base by bacterial MutS and eukaryotic MutSα is well characterized. We report here crystal structures of human MutSβ in complex with DNA containing insertion-deletion loops (IDL) of two, three, four or six unpaired nucleotides. In contrast to eukaryotic MutSα and bacterial MutS, which bind the base of a mismatched nucleotide, MutSβ binds three phosphates in an IDL. DNA is severely bent at the IDL; unpaired bases are flipped out into the major groove and partially exposed to solvent. A normal downstream base pair can become unpaired; a single unpaired base can thereby be converted to an IDL of two nucleotides and recognized by MutSβ. The C-terminal dimerization domains form an integral part of the MutS structure and coordinate asymmetrical ATP hyd! rolysis by Msh2 and Msh3 with mismatch binding to signal for repair. View full text Figures at a glance * Figure 1: Overall structures of MutSβ–DNA complexes. () Orthogonal views of Loop3 structure in ribbon diagrams, with MSH2 in green and MSH3 in blue. The DNA is shown in a space-filling model with the backbone in red, bases in light pink, and the unpaired nucleotides in yellow and orange. ADP bound to MSH2 is shown in purple sticks. () Side views of DNA-binding domains and DNA in Loop2, Loop4 and Loop6 structures. Each unpaired CA dinucleotide repeat is shown in yellow and orange. Domain I of MSH3 is the MBD. MSH2 and MSH3 subunits are indicated by circled numbers 2 and 3, respectively. Domains I–V and dimerization domains are indicated. * Figure 2: Comparison of MutSα and MutSβ proteins. () Ribbon diagram of MSH2 from MutSβ. Domains I, II, III, IV, V and the DMDs are shown in blue, green, yellow, orange, pink and red, respectively. MSH2 of MutSα is superimposed and shown in gray. Domain interfaces between I and II and between II, III and V are highlighted in magenta. () Ribbon diagram of MSH3 in the same orientation and same color codes. Domains I (MBD) and IV (clamp) interact as indicated by the dotted oval. () Superposition of the mismatch-binding subunits in MutSα, MutSβ, E. coli and TaqMutS in the same orientation as in and . Except for domain IV, they superimpose very well. () A ribbon diagram of the interface between domains I in MutSβ. Protein residues in all figures are labeled in one-letter code for clarity. () On the left is a ribbon diagram of MSH3 MBD decorated by residues conserved among MutS homologs (shown as yellow-blue-red stick-and-ball models) and residues unique among MSH3 homologs (pink-blue-red stick-and-ball models). On the right ! is the superposition of MSH3 (blue) and MSH6 (gray) MBDs. The r.m.s. deviation between them is 0.7 Å over 87 pairs of Cα atoms. * Figure 3: IDL recognition by MutSβ. () A closeup comparison of MSH3–IDL interaction and TaqMutS with a single unpaired base (ΔT). () DNA-binding domains and DNA in Loop4. Domains I and IV of MSH2 are shown in green and yellow, and MBD and clamp domains of MSH3 in blue and orange, respectively. () Diagram of the protein-DNA interactions using the same color scheme as in . () Space-filling model of four IDLs and their interaction with domain I of MSH2 (green) and MBD of MSH3 (blue). The base pairs surrounding the IDL are shown in light (upstream) and dark (downstream) pink. For Loop2 and Loop4, a back view looking into the minor groove is also shown. * Figure 4: Dimerization domains (DMD) of MutSβ. (,) Orthogonal views of the C-terminal halves of DMDs. The hydrophobic side chains at the interface, and polar residues forming salt bridges that stabilize intrasubunit interactions, are shown as sticks with carbon in light gray, nitrogen in blue and oxygen in red. Glu901 and Lys912 of MSH2 form N- and C-caps of the MSH3 helices. () The ATPase domain (light green) and DMD (green) of MSH2 are shown with the trans-acting N2 (red and cyan) and DMD (blue) of MSH3. The ADP bound to MSH2 is shown as purple sticks. The two shaded ovals indicate the enlarged areas shown in , and . () A closeup view of the interactions between MSH3 DMD(N) and the ATPase domain of MSH2. Interactions between hydrophobic residues dominate, and two pairs of salt bridges (red dashes) may have alternative interacting partners (black dashes) if the two subunits slide relative to each other. * Figure 5: Asymmetric ATPase sites of MutSβ. () Ribbon diagram of the ATPase and dimerization domains. MSH2 is shown in light and dark green, and MSH3 in light and dark blue. The trans-acting N2 regions of MSH2 and MSH3 are highlighted in red. The aromatic side chains connecting the ATPase site to the DMD are shown as blue (MSH3) and green sticks (MSH2). () A view 180° from showing the asymmetric DMDs, biased toward the MSH2 ATPase site. () Comparison of the connection between the ATP binding site and DMD in MSH3 (blue), MSH6 with ADP (pink) and without (yellow) after superposition. The critical aromatic side chains are shown as sticks. * Figure 6: Mechanism of mismatch recognition. Msh2 is drawn in green and Msh3 and Msh6 in blue. The ATPase activities of the two subunits are indicated by the curved arrows: the thicker the arrow, the higher the activity. The DNA-binding domains are flexible in the apo form. Binding to normal DNA, which is resistant to bending, induces conformational changes in the DNA-binding domains and ATP hydrolysis. But the protein-DNA association is not stable, and MutS(α or β) can dissociate from or slide along DNA. Binding to a mismatched DNA, which is readily bent, leads to stable association of Msh3 or Msh6 with DNA and inhibition of its ATPase activity. ATP binding by Msh3 or Msh6, however, leads to release of the mismatched DNA. When Msh2 is bound to ATP and Msh3 or Msh6 to the mismatched DNA, MutS(α or β) can recruit MutLα to form a 'repairosome', thus initiating the repair process. Accession codes * Abstract * Accession codes * Author information * Supplementary information Primary accessions Protein Data Bank * 3THY * 3THX * 3THW * 3THZ * 3THY * 3THX * 3THW * 3THZ Referenced accessions Protein Data Bank * 1EWQ * 2O8E * 2O8B * 1EWQ * 2O8E * 2O8B Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Laboratory of Molecular Biology, National Institute of Diabetes and Digestive and Kidney Diseases, US National Institutes of Health, Bethesda, Maryland, USA. * Shikha Gupta, * Martin Gellert & * Wei Yang Contributions S.G. conducted all experiments and collected X-ray data. W.Y. determined and refined the structures. S.G., M.G. and W.Y. contributed to the experimental design, data interpretation and manuscript preparation. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Wei Yang Author Details * Shikha Gupta Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Gellert Search for this author in: * NPG journals * PubMed * Google Scholar * Wei Yang Contact Wei Yang Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (13M) Supplementary Figures 1–7 Additional data Entities in this article * DNA mismatch repair protein mutS mutS Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein Msh2 MSH2 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA mismatch repair protein Msh3 MSH3 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA mismatch repair protein mutL mutL Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein Msh6 MSH6 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA mismatch repair protein Msh3 Msh3 Mus musculus * View in UniProt * View in Entrez Gene * DNA mismatch repair protein Msh6 Msh6 Mus musculus * View in UniProt * View in Entrez Gene * DNA mismatch repair protein MSH3 MSH3 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein MSH6 MSH6 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein mutS Thermus aquaticus * View in UniProt * DNA mismatch repair protein MSH2 MSH2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene
Structural basis of pre-let-7 miRNA recognition by the zinc knuckles of pluripotency factor Lin28
- Nat Struct Mol Biol 19(1):84-89 (2012)
Nature Structural & Molecular Biology | Article The extracellular chaperone clusterin sequesters oligomeric forms of the amyloid-β1−40 peptide * Priyanka Narayan1 * Angel Orte1, 2 * Richard W Clarke1 * Benedetta Bolognesi1 * Sharon Hook1 * Kristina A Ganzinger1 * Sarah Meehan1 * Mark R Wilson3 * Christopher M Dobson1 * David Klenerman1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:79–83Year published:(2012)DOI:doi:10.1038/nsmb.2191Received 27 May 2011 Accepted 14 October 2011 Published online 18 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg In recent genome-wide association studies, the extracellular chaperone protein, clusterin, has been identified as a newly-discovered risk factor in Alzheimer's disease. We have examined the interactions between human clusterin and the Alzheimer's disease–associated amyloid-β1−40 peptide (Aβ1−40), which is prone to aggregate into an ensemble of oligomeric intermediates implicated in both the proliferation of amyloid fibrils and in neuronal toxicity. Using highly sensitive single-molecule fluorescence methods, we have found that Aβ1−40 forms a heterogeneous distribution of small oligomers (from dimers to 50-mers), all of which interact with clusterin to form long-lived, stable complexes. Consequently, clusterin is able to influence both the aggregation and disaggregation of Aβ1−40 by sequestration of the Aβ oligomers. These results not only elucidate the protective role of clusterin but also provide a molecular basis for the genetic link between clusterin and Al! zheimer's disease. View full text Figures at a glance * Figure 1: Bulk and single-molecule studies of Aβ1−40. () Appearance and disappearance of species populated during the aggregation of Aβ1−40 (2 μM at 37 °C with agitation). Fibril formation monitored by thioflavin (ThT) fluorescence (top). The inset is a transmission electron microscopy (TEM) image of the fibrils present after 24 h of incubation (scale bar, 200 nm). The concentration of soluble oligomers (dimers to 50-mers; middle) and of monomeric species (bottom) are both tracked using cTCCD. The data are averaged from multiple experimental repetitions (2 μM Aβ1−40, n = 3; error bars are s.e.m.). () A representative distribution of apparent sizes of oligomers formed during Aβ1−40 aggregation and disaggregation (error bars are s.d.). Insets are zoomed into regions of dimers to 15-mers and 16-mers to 50-mers to show greater detail. () A comparison of the distributions of apparent oligomer sizes during aggregation and disaggregation experiments (2 μM Aβ1−40 aggregation, n = 3; disaggregation, n = 12; 10−30 nM A�! �1−40 aggregation, n = 4; error bars are s.e.m.). () Time dependence of the concentration of soluble species released from a pellet of fibrils (n = 12; error bars are s.e.m.). * Figure 2: The effects of clusterin on the aggregation of Aβ1−40. () Fraction of oligomers detected in solution during the aggregation of Aβ1−40 with and without clusterin (Aβ1−40 and clusterin are both at a concentration of 600 nM; n = 3 and error bars are s.e.m.). () TIRFM image of the species present after 24 h of aggregation of a 2-μM solution of Aβ1−40 without clusterin (left). TIRFM image of a 2 μM solution of Aβ1−40 after 24 h of aggregation, but with clusterin added at a concentration of 2 μM 4 h after the start of the reaction, during the fibril growth phase (right). An approximately 50% reduction in the average dimensions of species present is observed in the presence of clusterin (from 1,400 ± 200 nm without clusterin to 780 ± 60 nm with clusterin, s.e.m., P-value is 0.01, two-sample independent, two-tailed t-test). Scale bars, 5 μm. () Fractions of species formed during the aggregation of a 2 μM solution that are oligomeric and that are in Aβ–clusterin complexes. (n = 3, error bars are s.e.m.). () Proporti! on of Aβ–clusterin complexes persisting at 10−20 nM (total peptide concentration) at 21 °C. Complexes were formed between clusterin and oligomers formed in both aggregation and disaggregation reactions. For both traces, n = 3 and error bars are s.e.m. There is no statistically significant change in the proportion of complexes with oligomers formed during either the disaggregation experiments (P value of 0.77, analysis of variance (ANOVA) single-factor) or the aggregation experiments (P value of 0.99, ANOVA single-factor). * Figure 3: The effects of clusterin on the disaggregation of Aβ1−40 fibrils. () Distributions of apparent sizes of oligomers formed during aggregation and disaggregation reactions with and without clusterin. (Aggregation without clusterin, n = 2 and error bars are range; aggregation with clusterin, n = 3; disaggregation without clusterin, n = 10; disaggregation with clusterin, n = 3 and error bars are s.e.m.). () Time dependence of the release of soluble species during the disaggregation experiments in the presence and absence of clusterin (top), increased oligomer concentration in the presence of clusterin in the concentration plateau region (significant, with a P value of 0.002) (bottom left) and decreased monomer concentration in the presence of clusterin, in the concentration plateau region (significant, with a P value of 0.0003) (bottom right). Both correlations were analyzed using a two-sample independent, two-tailed t-test; n = 8 and error bars are s.e.m. () TIRFM images of HiLyte488Fluor-labeled Aβ1−40 fibrils incubated overnight at 21 °C! with AlexaFluor647-labeled clusterin. Aβ1−40 fluorescence only (left), clusterin fluorescence only (middle) and colocalization of the two species (right). Scale bars, 5 μm. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Chemistry, University of Cambridge, Cambridge, UK. * Priyanka Narayan, * Angel Orte, * Richard W Clarke, * Benedetta Bolognesi, * Sharon Hook, * Kristina A Ganzinger, * Sarah Meehan, * Christopher M Dobson & * David Klenerman * Department of Physical Chemistry, Faculty of Pharmacy, University of Granada, Campus Cartuja, Granada, Spain. * Angel Orte * School of Biological Sciences, University of Wollongong, Wollongong, New South Wales, Australia. * Mark R Wilson Contributions P.N., A.O., S.M., M.R.W., C.M.D. and D.K. designed the experiments. P.N. conducted the cTCCD experiments. P.N., A.O. and R.W.C. refined analysis methods. A.O. and R.W.C. developed instrumentation. R.W.C. wrote the analysis software, and designed, built and calibrated the scanning stage used for cTCCD experiments. P.N. and B.B. conducted the bulk scale experiments. P.N. and K.A.G. conducted the TIRFM experiments. P.N., B.B., K.A.G. and A.O. analyzed the data. S.H. labeled the clusterin that was purified and provided by M.R.W. All authors discussed and interpreted results and contributed to the writing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Mark R Wilson or * Christopher M Dobson or * David Klenerman Author Details * Priyanka Narayan Search for this author in: * NPG journals * PubMed * Google Scholar * Angel Orte Search for this author in: * NPG journals * PubMed * Google Scholar * Richard W Clarke Search for this author in: * NPG journals * PubMed * Google Scholar * Benedetta Bolognesi Search for this author in: * NPG journals * PubMed * Google Scholar * Sharon Hook Search for this author in: * NPG journals * PubMed * Google Scholar * Kristina A Ganzinger Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah Meehan Search for this author in: * NPG journals * PubMed * Google Scholar * Mark R Wilson Contact Mark R Wilson Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher M Dobson Contact Christopher M Dobson Search for this author in: * NPG journals * PubMed * Google Scholar * David Klenerman Contact David Klenerman Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (979K) Supplementary Figures 1–6, Supplementary Methods and Supplementary Discussion Additional data Entities in this article * Clusterin CLU Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Amyloid beta A4 protein APP Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia
Tudor domain ERI-5 tethers an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi
- Nat Struct Mol Biol 19(1):90-97 (2012)
Nature Structural & Molecular Biology | Article Structural basis of pre-let-7 miRNA recognition by the zinc knuckles of pluripotency factor Lin28 * Fionna E Loughlin1 * Luca F R Gebert2 * Harry Towbin2 * Andreas Brunschweiger2 * Jonathan Hall2 * Frédéric H-T Allain1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:84–89Year published:(2012)DOI:doi:10.1038/nsmb.2202Received 20 May 2011 Accepted 10 November 2011 Published online 11 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Accession codes * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Lin28 inhibits the biogenesis of let-7 miRNAs through a direct interaction with the terminal loop of pre-let-7. This interaction requires the zinc-knuckle domains of Lin28. We show that the zinc knuckle domains of Lin28 are sufficient to provide binding selectivity for pre-let-7 miRNAs and present the NMR structure of human Lin28 zinc knuckles bound to the short sequence 5′-AGGAGAU-3′. The structure reveals that each zinc knuckle recognizes an AG dinucleotide separated by a single nucleotide spacer. This defines a new 5′-NGNNG-3′ consensus motif that explains how Lin28 selectively recognizes pre-let-7 family members. Binding assays in cell lysates and functional assays in cultured cells demonstrate that the interactions observed in the solution structure also occur between the full-length protein and members of the pre-let-7 family. The consensus sequence explains several seemingly disparate previously published observations on the binding properties of Lin28. View full text Figures at a glance * Figure 1: The ZnFs of Lin28 bind single-stranded regions of pre-let-7 terminal loops. () Domain structure of Lin28 and of the construct containing the two ZnFs used in this study. () Chemically synthesized biotinylated pre-miRNAs bound by immobilized, recombinant, purified Lin28 ZnF12. Pre-let-7 family members and pre-miRNAs that are known not to be regulated by Lin28 are shown. Error bars represent s.d. of triplicate determinations. One of two assays is shown. () Upper, secondary structure of the terminal loop of pre-let-7f-1, as predicted with Mfold29. Lower left, overlay of section of 15N HSQC spectra of Lin28 ZnF12, free (gray) and bound (green) to the terminal loop of pre-let-7f-1. Arrows show the changes of selected resonances. Lower right, overlay of section of 15N HSQC spectra of Lin28 ZnF12 bound to the terminal loops of pre-let-7f-1 (green) and bound to the single-stranded 5′-AGGAGAU-3′ (purple) sequence. TL, terminal loop. * Figure 2: The solution structure of Lin28 ZnF12 bound to 5′-AGGAGAU-3′. () Representative structures of the Lin28 ZnF12–5′-AGGAGAU-3′ complex. The ZnF ribbon is shown in green, the zinc atom in purple and the RNA in yellow. () G2 recognition by ZnF2. The hydrogen bonds are indicated by dotted black lines. () G5 recognition by ZnF1. Figures were generated by MOLMOL30. Arrows identify residues; bb indicates amino acid backbone. * Figure 3: Affinity of Lin28 variants for single-stranded and pre-let-7g RNAs and processing of pre-let-7g point mutants in Huh-7 cells. () Representative ITC data obtained by titration of Lin28 ZnF12 WT and point mutant into 5′-AGGAGAU-3′ (left). Kd of Lin28 ZnF12 WT and single–amino acid mutant binding to ssRNA (right). Error bars indicate s.d. of two measurements; for details see Supplementary Table 1. () Representative inhibition curves for full-length Myc-tagged Lin28 WT and single-point mutations in HeLa cell lysates (left). Relative binding affinities (Kd) of Myc-Lin28 for pre-let-7g in HeLa cell lysates (right, average of two replicate experiments, error bars indicate s.d.). () Representative ITC data obtained upon titration of Lin28 ZnF12 into ssRNA (left). Kd of Lin28 ZnF12 binding different RNAs (right). For details see Supplementary Table 1. () Levels of mature microRNAs (let-7g, mir-16 and mir-191) in Huh-7 cells transfected with graded concentrations (10, 5 and 2.5 nM) of in vitro transcribed pre-let-7g WT or point mutants, as determined by stem-loop RT-PCR after 24 h. Mir-191 was used for! normalization and error bars indicate s.e.m. of quadruplicate determinations. * Figure 4: Comparison between the structure of Lin28 ZnFs bound to 5′-AGGAGAU-3′ (this study) and HIV nucleocapsid (NC) bound to stem-loops of the RNA packaging signal. () Lin28 bound to 5′-AGGAGAU-3′ (green) overlaid with HIV NC bound to SL3 containing a GAG loop26 (purple; PDB 1A1T). () Lin28 bound to 5′-AGGAGAU-3′ (green) overlaid with HIV NC bound to SL2 containing a GUG loop27 (blue; PDB 1F6U). () Sequence alignment of Lin28 and HIV NC, indicating the insertion of Pro158. () Representative structures of the Lin28 ZnF12–5′-AGGAGAU-3′ complex. The ZnF ribbon is shown in green, the zinc atom in purple and the RNA in yellow. () Representative structures of HIV NC–bound SL3 containing a GAG sequence in the loop. The ZnF ribbon is shown in gray, the zinc atom in purple and the RNA in yellow. Accession codes * Abstract * Accession codes * Author information * Supplementary information Primary accessions Biological Magnetic Resonance Data Bank * 17883 Protein Data Bank * 2LI8 * 2LI8 Referenced accessions Protein Data Bank * 2CQF * 1A1T * 1F6U * 2CQF * 1A1T * 1F6U Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Institute of Molecular Biology and Biophysics, ETH Zürich, Zürich, Switzerland. * Fionna E Loughlin & * Frédéric H-T Allain * Institute of Pharmaceutical Sciences, ETH Zürich, Zürich, Switzerland. * Luca F R Gebert, * Harry Towbin, * Andreas Brunschweiger & * Jonathan Hall Contributions F.H.-T.A., F.E.L. and J.H. designed the project; F.E.L. prepared protein and RNA samples for structural studies; F.E.L. and F.H.-T.A. collected and analyzed NMR data; F.E.L. carried out the structure calculations and the ITC measurements; H.T. and A.B. did the Lin28 binding assay with miRNAs and L.F.R.G. did the quantitative PCR in cell assays. All authors discussed the results, wrote and approved the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Jonathan Hall or * Frédéric H-T Allain Author Details * Fionna E Loughlin Search for this author in: * NPG journals * PubMed * Google Scholar * Luca F R Gebert Search for this author in: * NPG journals * PubMed * Google Scholar * Harry Towbin Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Brunschweiger Search for this author in: * NPG journals * PubMed * Google Scholar * Jonathan Hall Contact Jonathan Hall Search for this author in: * NPG journals * PubMed * Google Scholar * Frédéric H-T Allain Contact Frédéric H-T Allain Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (8M) Supplementary Figures 1–6, Supplementary Table 1 and Supplementary Methods Additional data Entities in this article * Protein lin-28 homolog A LIN28A Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * GTPase KRas KRAS Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Myc proto-oncogene protein MYC Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * High mobility group protein HMGI-C HMGA2 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Ribonuclease 3 DROSHA Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Endoribonuclease Dicer DICER1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Terminal uridylyltransferase 4 ZCCHC11 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * POU domain, class 5, transcription factor 1 POU5F1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Homeobox protein NANOG NANOG Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Transcription factor SOX-2 SOX2 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Protein lin-28 homolog B LIN28B Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Protein lin-28 lin-28 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * microRNA let-7 C05G5.6 Caenorhabditis elegans * View in Entrez Gene * microRNA let-7g MIRLET7G Homo sapiens * View in Entrez Gene * microRNA let-7c MIRLET7C Homo sapiens * View in Entrez Gene * microRNA let-7f-1 MIRLET7F1 Homo sapiens * View in Entrez Gene * microRNA let-7a-1 MIRLET7A1 Homo sapiens * View in Entrez Gene * microRNA 191 MIR191 Homo sapiens * View in Entrez Gene * microRNA let-7a-3 MIRLET7A3 Homo sapiens * View in Entrez Gene * Gag-Pol polyprotein Human immunodeficiency virus type 1 group M subtype B (isolate YU-2) * View in UniProt
Mispaired rNMPs in DNA are mutagenic and are targets of mismatch repair and RNases H
- Nat Struct Mol Biol 19(1):98-104 (2012)
Nature Structural & Molecular Biology | Article Tudor domain ERI-5 tethers an RNA-dependent RNA polymerase to DCR-1 to potentiate endo-RNAi * Caroline Thivierge1, 2, 6 * Neetha Makil1, 2, 6 * Mathieu Flamand1, 2 * Jessica J Vasale3 * Craig C Mello3, 4 * James Wohlschlegel5 * Darryl Conte Jr3 * Thomas F Duchaine1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:90–97Year published:(2012)DOI:doi:10.1038/nsmb.2186Received 25 June 2011 Accepted 14 October 2011 Published online 18 December 2011 Corrected online09 January 2012 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Change history * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Endogenous RNA interference (endo-RNAi) pathways use a variety of mechanisms to generate siRNA and to mediate gene silencing. In Caenorhabditis elegans, DCR-1 is essential for competing RNAi pathways—the ERI endo-RNAi pathway and the exogenous RNAi pathway—to function. Here, we demonstrate that DCR-1 forms exclusive complexes in each pathway and further define the ERI–DCR-1 complex. We show that the tandem tudor protein ERI-5 potentiates ERI endo-RNAi by tethering an RNA-dependent RNA polymerase (RdRP) module to DCR-1. In the absence of ERI-5, the RdRP module is uncoupled from DCR-1. Notably, EKL-1, an ERI-5 paralog that specifies distinct RdRP modules in Dicer-independent endo-RNAi pathways, partially compensates for the loss of ERI-5 without interacting with DCR-1. Our results implicate tudor proteins in the recruitment of RdRP complexes to specific steps within DCR-1-dependent and DCR-1-independent endo-RNAi pathways. View full text Figures at a glance * Figure 1: Distinct DCR-1 complexes initiate endo- and exo-RNAi. () Gel filtration on wild-type embryonic extract. DRH-1, RDE-4, DCR-1, RRF-3, ERI-5, ERI-1 and DRH-3 proteins were detected by western blot on fractions from a Superose S6 column. The fractionation of molecular weight (MW) standards is indicated. The asterisk (*) labels in DRH-1 (in the low molecular weight fractions) and RDE-4 filtration panels indicate non-specific bands. () Immunoprecipitation (IP) of DCR-1, DRH-1 and RDE-4 from WT, dcr-1, rde-4 or rde-1 mutant embryos. DCR-1, RDE-1, DRH-1 and RDE-4 proteins were detected in total lysate (LOAD) and IP by western blot. Tubulin was used as a loading control. The asterisk (*) to the right of the RDE-4 panels indicates background signal from the IgG heavy chains used for immunoprecipitation, which migrate with RDE-4 around 50 kDa. () Immunoprecipitation of DRH-1 in WT and drh-1 mutant embryos. DRH-1, DCR-1, DRH-3, ERI-5 and ERI-1 were detected by western blot. The asterisks (*) to the right and left of the DRH-1 panel indicat! e non-specific bands in the loading and DRH-1 IP lanes, respectively. () Immunoprecipitation of ERI-5 in WT and eri-5 mutant embryos. DRH-3, DRH-1 and ERI-5 proteins were detected by western blot. The asterisk (*) indicates the non-specific band detected in the input lanes (LOAD) of the DRH-1 blot, as in panel . () Interaction map of the proteins detected by MuDPIT analyses in WT embryonic extracts. Proteins circled in bold (DCR-1, ERI-5, ERI-1 and RDE-4) represent immunoprecipitation targets. See Online Methods section for details on the epitope targeted. Arrowheads indicate interactions detected. The interactions of ERI-5 and ERI-1 in RDE-4 immunoprecipitation included in the diagram were only detected by western blotting. The number of interactions detected exclusively in DCR-1 or ERI-1 MuDPIT experiments is indicated (17 or 11 single target hits) and may reflect divergent functions for these proteins. * Figure 2: ERI-5 promotes the association of an RdRP module to the DCR-1 N terminus. (,) Immunoprecipitation (IP) of DCR-1 and ERI-5 in WT, eri-5, rrf-3 del (deletion mutant, pk1426), rrf-3 pm (point mutant, mg373), eri-3 and eri-1 mutant embryos. DCR-1, RRF-3, DRH-3 and ERI-5 were detected by western blotting. Tubulin was used as a loading control. () Map of the DCR-1–GST constructs used for the GST pulldown of recombinant (r) ERI-5 or ERI-3 (top). The ability of each DCR-1–GST fusion to interact with rERI-5 or rERI-3 was assessed by western blot (bottom panel) to detect recombinant rERI-5-CBP or rERI-3–Flag. The results are summarized to the right of the DCR-1 map; the minus sign denotes weak or no interaction, and the plus sign denotes an interaction (see Supplementary Fig. 2c for Coomassie blue gel staining). Percentage (%) of the loading (bottom panel) represents the fraction of rERI-5 and rERI-3 used in the GST pulldown. () ERI-3 and ERI-5 bind to DCR-1 (272–1045) simultaneously. An increasing amount of rERI-3 was incubated with DCR-1 (272–10! 45) before addition of rERI-5 and pull-down of the DCR-1 fragment. * Figure 3: ERI-5 potentiates ERI endo-RNAi small RNA biogenesis. (,) Northern () and qrtPCR analysis () of C40A11.10 26G-RNA siRNA species (siR26-1) as indicated in WT, eri-5 and rrf-3 (pk1426) mutant embryos. The C40A11.10 probe detected both 26G and 22G RNAs. 5S ribosomal RNA (rRNA) ethidium bromide staining is shown as a loading control in . The mean of at least three independent experiments is depicted as the ratio of siR26-1 or X-cluster relative to actin. Error bars indicate s.d. () Box and whisker plots show the enrichment or depletion of small RNAs targeting 26G-RNA coding genes (red) and non-annotated 26G-RNA clusters (yellow) in the indicated mutant. The left panel is an analysis of 26-nt antisense reads from embryo small RNA libraries that target the 26G-RNA loci. The right panel is an analysis of all antisense reads from adult small RNA libraries that target the 26G-RNA loci. The majority of reads in the adult samples are 22G RNAs. Values approaching 1 indicate enrichment of small RNA; values approaching 0 indicate depletion. ! Relative enrichment was calculated as the ratio of mutant per (mutant plus wild type). The top and bottom of each box represent the 75th and 25th percentiles, respectively. The horizontal line within each box represents the median value. The number of loci used to generate box and whisker plots is indicated above each plot, and the data are provided in Supplementary Data 1 and 2. * Figure 4: Tandem tudor domain proteins are required for ERI endo-siRNA biogenesis. (,) Northern () and qrtPCR () analysis of C40A11.10 26G RNAs (siR26-1) in sel-1 (RNAi) (a negative control, marked with (−)), ekl-1(RNAi), eri-5 and eri-5, and in ekl-1(RNAi) embryos. The mean of at least three independent experiments is depicted as the ratio of siR26-1 relative to actin. Error bars indicate s.d. () qrtPCR analysis of C40A11.10 26G RNAs (siR26-1) in WT, eri-5, eri-4 and double eri-5, and in eri-4 mutant embryos. The mean of at least three independent experiments is depicted as the ratio of siR26-1 relative to actin. Error bars indicate s.d. () IP of EKL-1 and DCR-1 in WT and eri-5 mutant embryos. EKL-1 and DCR-1 proteins were detected by western blot. () Immunoprecipitation of RRF-3 in WT and eri-5 mutant embryos. DCR-1, RRF-3, EKL-1 and ERI-5 proteins were detected by western blot. Tubulin was used as a loading control. * Figure 5: Roles and paralog organization of RdRP modules in ERI endo-RNAi. () IP of EKL-1 in WT and ekl-1(RNAi) (ekl-1 lanes) embryos, and immunoprecipitation of ERI-5 in WT and eri-5 mutant embryos. The RdRPs EGO-1, RRF-1 and RRF-3, and the tudor domain proteins EKL-1 and ERI-5 were detected by western blot. Asterisk (*) indicates a non-specific band. () Model of the molecular compensation of ERI-5 by EKL-1. Interactions between the RdRP module and the N-terminal helicase domain of DCR-1 couple the generation of dsRNA by RRF-3 with processive DCR-1 activity. In the eri-5 mutant, this coupling is lost and the autoinhibitory function of the helicase domain predominates, resulting in inefficient 26G-RNA production. () Paralogous RdRP modules function sequentially in ERI endo-RNAi. An RdRP module comprised of RRF-3, DRH-3 and ERI-5 together with DCR-1 function at the initial step to generate 26G RNAs, the primary siRNAs of the ERI pathway that programs ERGO-1. A paralogous RdRP module comprised of RRF-1, DRH-3 and EKL-1 is responsible for secondary si! RNA generation that is independent of DCR-1. This abundant pool of small RNAs programs the WAGO Argonautes to effect endo-RNAi silencing. Paralogous EGO-1 complexes may be involved in this and other RNAi pathways. Some of the ERIC components were omitted from the model for clarity. Change history * Abstract * Change history * Author information * Supplementary informationCorrected online 09 January 2012In the version of this article initially published, information in Table 1 was inaccurate. "Newly described" should have been "novel" and "Argonaute protein domain" should have read "Argonaute protein." The errors have been corrected in the HTML and PDF versions of the article. Author information * Abstract * Change history * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Caroline Thivierge & * Neetha Makil Affiliations * Department of Biochemistry, McGill University, Montreal, Quebec, Canada. * Caroline Thivierge, * Neetha Makil, * Mathieu Flamand & * Thomas F Duchaine * Goodman Cancer Center, McGill University, Montreal, Quebec, Canada. * Caroline Thivierge, * Neetha Makil, * Mathieu Flamand & * Thomas F Duchaine * Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA. * Jessica J Vasale, * Craig C Mello & * Darryl Conte Jr * Howard Hughes Medical Institute, University of Massachusetts Medical School, Worcester, Massachusetts, USA. * Craig C Mello * Department of Biological Chemistry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA. * James Wohlschlegel Contributions C.T. conducted the experiments presented in Figures 1c, 2c,d, 3a,b, 4a,b,d and 5a, prepared the figures and assisted with the preparation of the manuscript. N.M. conducted the experiments presented in Figure 1a,d, the ERI-5 samples in 1e and 2a,b. M.F. conducted the experiments presented in Figure 4b,d, and assisted with the model. J.W. carried out the MuDPIT analyses of IP samples. D.C. and J.J.V. conducted the experiments in Figure 3c, under C.C.M.'s direction. D.C. provided scientific advice, and assisted with the redaction of the manuscript. T.F.D. conducted the experiments in Figure 1b, wrote the manuscript and directed the project. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Thomas F Duchaine Author Details * Caroline Thivierge Search for this author in: * NPG journals * PubMed * Google Scholar * Neetha Makil Search for this author in: * NPG journals * PubMed * Google Scholar * Mathieu Flamand Search for this author in: * NPG journals * PubMed * Google Scholar * Jessica J Vasale Search for this author in: * NPG journals * PubMed * Google Scholar * Craig C Mello Search for this author in: * NPG journals * PubMed * Google Scholar * James Wohlschlegel Search for this author in: * NPG journals * PubMed * Google Scholar * Darryl Conte Jr Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas F Duchaine Contact Thomas F Duchaine Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Change history * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–4, Supplementary Results and Supplementary Methods Excel files * Supplementary Data 1 (123K) Supplementary data of the coding loci targeted by 26G-RNAs in eri-5 and rrf-3 embryos. * Supplementary Data 2 (2M) Complement to Supplementary Figure 3: small RNA defect of eri-5 mutant. Additional data Entities in this article * Enhanced RNAi (RNA interference) protein 5 eri-5 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Endoribonuclease dcr-1 dcr-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Enhancer of Ksr-1 Lethality ekl-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * RNAi DEfective family member (rde-4) rde-4 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Dicer related helicase protein 1 drh-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * RNAi DEfective family member (rde-1) rde-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * RNA-dependent RNA polymerase family member (rrf-1) rrf-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * RNA-directed RNA polymerase related EGO-1 ego-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * ALG-3 T22B3.2 Caenorhabditis elegans * View in Entrez Gene * ALG-4 tag-76 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Endogenous-RNAi deficient argonaute protein 1 ergo-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * RNA-dependent RNA polymerase family member (rrf-3) rrf-3 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Dicer Related Helicase family member (drh-3) drh-3 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * 3'-5' exonuclease eri-1 eri-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Enhanced RNAi (RNA interference) protein 3 eri-3 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Enhanced RNAi (RNA interference) protein 9 C26E6.7 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Phosphatase Interacting with RNA/RNP family member (pir-1) pir-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Argonaute (plant)-Like Gene family member (alg-1) alg-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Argonaute (plant)-Like Gene alg-2 Caenorhabditis elegans * View in Entrez Gene * Protein T06A10.3 Caenorhabditis elegans * View in UniProt * Protein B0001.2 B0001.2 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Ribonuclease 3 DROSHA Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Microprocessor complex subunit DGCR8 DGCR8 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * Dicer-2 Dcr-2 Drosophila melanogaster * View in UniProt * View in Entrez Gene * R2D2 r2d2 Drosophila melanogaster * View in UniProt * View in Entrez Gene * Protein C40A11.10 C40A11.10 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Suppressor/Enhancer of Lin-12 family member (sel-1) sel-1 Caenorhabditis elegans * View in UniProt * View in Entrez Gene * Protein Dicer dcr1 Schizosaccharomyces pombe (strain 972 / ATCC 24843) * View in UniProt * View in Entrez Gene * Endoribonuclease Dicer DICER1 Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia
A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide
- Nat Struct Mol Biol 19(1):105-112 (2012)
Nature Structural & Molecular Biology | Article Mispaired rNMPs in DNA are mutagenic and are targets of mismatch repair and RNases H * Ying Shen1 * Kyung Duk Koh1 * Bernard Weiss2 * Francesca Storici1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:98–104Year published:(2012)DOI:doi:10.1038/nsmb.2176Received 21 December 2010 Accepted 16 September 2011 Published online 04 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Numerous studies have shown that ribonucleoside monophosphates (rNMPs) are probably abundant among all nonstandard nucleotides occurring in genomic DNA. Therefore, it is important to understand to what extent rNMPs may alter genome integrity and what factors affect their stability. We developed oligonucleotide-driven gene correction assays in Escherichia coli and Saccharomyces cerevisiae to show that mispaired rNMPs embedded into genomic DNA, if not removed, serve as templates for DNA synthesis and produce a genetic change. We discovered that isolated mispaired rNMPs in chromosomal DNA are removed by the mismatch repair system in competition with RNase H type 2. However, a mismatch within an RNA-DNA heteroduplex region requires RNase H type 1 for removal. In the absence of mismatch repair and RNases H, ribonucleotide-driven gene modification increased by a factor of 47 in yeast and 77,000 in E. coli. View full text Figures at a glance * Figure 1: Diagrams and sequences of the loci targeted by the RNA-containing oligonucleotides. () The lacZ locus containing a two-base deletion and a substitution mutation targeted by the LacZ.R6I2, LacZ.R2.47I2, LacZ.R1S1 or LacZ.R5S1 oligonucleotide. () The lacZ locus containing a substitution mutation targeted by the LacZ.R1S1 or LacZ.R5S1 oligonucleotide. () The rpsL locus targeted by the RpsL.R1S1 oligonucleotide. (–) The trp5 locus containing a two-base deletion and substitution mutations targeted by the TRP5.R2_R1I2_S1 oligonucleotide (), containing just a substitution mutation targeted by the TRP5.R1S1 oligonucleotide () or containing only a two-base deletion mutation targeted by the TRP5.R2I2 oligonucleotide (). In the name of the RNA-containing oligonucleotides, substitutions are indicated by a subscript capital 'S' and insertions by a subscript capital 'I'. The letters 'S' and 'I' are followed by a subscript number indicating the number of bases that are substituted or inserted, respectively. * Figure 2: RNase HII cleavage specificity. () Structural presentation of 5′-radiolabeled (32P, indicated by a purple asterisks) substrates (S1–S11) and cleavage percentage for each substrate, expressed as median and range (in parentheses) from three independent samples. Inverted triangles indicate the cleavage sites. () Denaturing polyacrylamide gels showing fragments resulting from cleavage using RNase HII. M, 20- to 100-nt oligonucleotide marker. The gel images were cropped above the 50-nt band of the marker. S1–S11, substrates used; nt, nucleotide. () Substrates used in the experiment shown in panel and their cleavage percentage, expressed as mean and range (in parentheses) from two independent samples. () Denaturing polyacrylamide gel showing fragments resulting from cleavage using reduced amount of RNase HII and shorter incubation time. M, 20- to 100-nt oligonucleotide marker. The gel image was cropped as in . S2, S4, S6, S11 are substrates used. Author information * Abstract * Author information * Supplementary information Affiliations * School of Biology, Georgia Institute of Technology, Atlanta, Georgia, USA. * Ying Shen, * Kyung Duk Koh & * Francesca Storici * Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia, USA. * Bernard Weiss Contributions Y.S. conducted most of the experiments on E. coli, all yeast experiments and statistical analyses of the data. K.D.K. carried out the RNase HII cleavage experiments, analyzed biochemical data and helped with the E. coli experiments. B.W. helped to design the experiments, conducted initial tests on E. coli and analyzed data. F.S. designed most of experiments, analyzed data and wrote the manuscript, with input from all authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Francesca Storici Author Details * Ying Shen Search for this author in: * NPG journals * PubMed * Google Scholar * Kyung Duk Koh Search for this author in: * NPG journals * PubMed * Google Scholar * Bernard Weiss Search for this author in: * NPG journals * PubMed * Google Scholar * Francesca Storici Contact Francesca Storici Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–2 and Supplementary Tables 1–6 Additional data Entities in this article * DNA topoisomerase 1 TOP1 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein mutS mutS Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Beta-galactosidase lacZ Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Ribonuclease HI rnhA Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Ribonuclease HII rnhB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * 30S ribosomal protein S12 rpsL Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Tryptophan synthase TRP5 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein MSH2 MSH2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * Ribonuclease H2 subunit A RNH201 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA polymerase epsilon catalytic subunit A POL2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA mismatch repair protein MSH6 MSH6 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene * DNA-directed DNA/RNA polymerase mu POLM Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA polymerase beta POLB Homo sapiens * View in UniProt * View in Entrez Gene * View in Antibodypedia * DNA polymerase III subunit epsilon dnaQ Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase III subunit alpha dnaE Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * 3-isopropylmalate dehydrogenase LEU2 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) * View in UniProt * View in Entrez Gene
Single-molecule studies reveal the function of a third polymerase in the replisome
- Nat Struct Mol Biol 19(1):113-116 (2012)
Nature Structural & Molecular Biology | Article A cis-antisense RNA acts in trans in Staphylococcus aureus to control translation of a human cytolytic peptide * Nour Sayed1 * Ambre Jousselin1 * Brice Felden1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:105–112Year published:(2012)DOI:doi:10.1038/nsmb.2193Received 09 July 2011 Accepted 31 October 2011 Published online 25 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Abstract * Abstract * Author information * Supplementary information Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Antisense RNAs (asRNAs) pair to RNAs expressed from the complementary strand, and their functions are thought to depend on nucleotide overlap with genes on the opposite strand. There is little information on the roles and mechanisms of asRNAs. We show that a cis asRNA acts in trans, using a domain outside its target complementary sequence. SprA1 small regulatory RNA (sRNA) and SprA1AS asRNA are concomitantly expressed in S. aureus. SprA1AS forms a complex with SprA1, preventing translation of the SprA1-encoded open reading frame by occluding translation initiation signals through pairing interactions. The SprA1 peptide sequence is within two RNA pseudoknots. SprA1AS represses production of the SprA1-encoded cytolytic peptide in trans, as its overlapping region is dispensable for regulation. These findings demonstrate that sometimes asRNA functional domains are not their gene-target complementary sequences, suggesting there is a need for mechanistic re-evaluation of asRNAs ex! pressed in prokaryotes and eukaryotes. View full text Figures at a glance * Figure 1: Genomic location, lengths, boundaries and expression of sprA1 and sprA1AS. () Location of sprA1-sprA1AS in S. aureus pathogenicity island SaPIn3 of the S. aureus strain Newman (NWMN) genome. () Right panels: northern-blot detection of SprA1 and SprA1AS in a wild-type Newman strain (lane 1) and in an isogenic sprA1-sprA1AS double deletion strain (lane 2). Left panels: length evaluation of SprA1 and SprA1AS adjoining synthetic labeled RNAs of known lengths combined to 5′ end determinations by RACE mapping. The nucleotide numberings of the SprA1 and SprA1AS ends refer to positions in the S. aureus Newman genomic sequence12. (,) SprA1 and SprA1AS expression profiles during S. aureus growth. The expression levels of SprA1 and SprA1AS during a 10-h growth of S. aureus Newman strain detected by northern blots. For loading controls, the blots were also probed for tmRNA. The growth curves of the Newman strains are presented, with the quantification of SprA1 (black triangles) and SprA1AS (gray diamonds) levels relative to the amount of tmRNA from the same ! RNA extraction. AU, arbitrary units. () Determination of the in vivo concentrations of SprA1 and SprA1AS in a wild-type S. aureus Newman strain during growth detected by northern blots. The quantification of SprA1 and SprA1ASin vivo levels (left panels) was carried out relative to increasing amounts of synthetic, gel-purified SprA1 and SprA1AS RNAs (the two right panels). In vivo, the ratios between the SprA1 and SprA1AS RNAs are 1:35, 1:92, 1:63 and 1:50 at A600nm levels of 4, 7, 10 and 12, respectively. * Figure 2: Detection of the interaction between SprA1 and SprA1ASin vivo and assessment of their binding constants. () Northern blot analysis of SprA1 (wild-type or tagged with a StreptoTag (ST) expression at mid-exponential (A600nm = 3) and stationary (A600nm = 11) phases in wild-type Newman (lane 3), isogenic Newman ΔsprA1-sprA1AS deletion mutant (lane 2) and Newman ΔsprA1-ΔsprA1AS pCN35Ω STsprA1-sprA1AS strain (lane 1). () Northern blot analysis of the affinity purification fractions from either Newman ΔsprA1-ΔsprA1AS pCN35ΩSTsprA1-sprA1AS extracts, or Newman wild-type pCN35ΩsprA1AS extracts, as a negative control. Labeled DNA probes were used for SprA1 (WT and tagged), for SprA1AS and for tmRNA used as an internal negative control. FT, flow through; W4, wash 4, W5, wash 5; E, elution. (,) Complex formation between purified SprA1 and SprA1AS by native gel retardation assays. Purified, labeled (asterisks) SprA1AS () or SprA1 () with increasing amounts of unlabeled SprA1 () or unlabeled SprA1AS (). The diamonds indicate the molar ratios used to perform the competition assays with! a 1,000-fold molar excess of yeast (Saccharomyces cerevisiae) total tRNAs or with a 20-fold molar excess of the indicated unlabeled RNA. The apparent binding constant between SprA1AS and SprA1 was inferred from these data: Kd = 15 ± 5 nM. * Figure 3: Experimental and phylogenetic evidence for the pairings between SprA1AS and SprA1. () Proposed pairings between SprA1 and SprA1AS. Shine-Dalgarno and 5′-GUG-3′ or 5′-AUG-3′ start codons are in red, and the SprA1AS and SprA1 interacting domains are boxed in red. Blue minus signs indicate the disappearance of the cleavages triggered by the structural probes in the RNA duplex. Triangles are the V1 cuts, arrows capped by circles are the S1 cuts, and uncapped arrows are the lead cleavages. The intensity of the cleavages is proportional to the darkness of the symbols. The blue S1 cut appears when the duplex forms. () Phylogenetic support for the proposed interaction between SprA1 and SprA1AS, when comparing the sequences of the two RNAs located in genomes and plasmids. Covariations are shown in gray, Shine-Dalgarno and start codons are boxed. (,) Experimentally supported structure of SprA1 and SprA1AS, emphasizing the 3′ overlapping sequence (yellow) as well as the experimentally and phylogenetically supported interaction region (red box). Covariations! are shown in gray. The other symbols are similar to those in panel . Structural changes detected upon complex formation are indicated in blue. The domains of the RNAs are indicated (SprA1: H1–H6, H1-H2 junction, L1–L6, PK1-PK2; SprA1AS: H1-H2AS, H1AS-H2AS junction and L1AS-L2AS) (see also Supplementary Figs. 3–5). * Figure 4: SprA1 and SprA1AS interact by their 5′ non-overlapping domains. Complex formation between labeled SprA1AS with increasing amounts of unlabeled 5′ SprA1 () or 3′ SprA1 () and between labeled SprA1 with increasing amounts of unlabeled 5′ SprA1AS () or 3′ SprA1AS (), as detected by native gel retardation assays. The apparent binding constants between the RNAs were inferred from these data. For SprA1AS–5′ SprA1, the Kd is 16 ± 5 nM. For SprA1–5′ SprA1AS, the Kd is 300 ± 50 nM. There is no duplex formation between SprA1 and 3′ SprA1AS or between 3′ SprA1 and SprA1AS. The black diamonds indicate the molar ratios used to carry out the competition assays with a 2,000-fold molar excess of poly(U) RNAs or with a 20-fold molar excess of the indicated unlabeled RNA. Asterisks indicate the 32P-radiolabeled RNAs (see also Supplementary Fig. 6). * Figure 5: SprA1 recruits the S. aureus ribosomes and is translated in vitro, and SprA1AS hinders SprA1 translation by its 5′ non-overlapping domain. () SprA1 structure indicating the ribosome toeprints (oval), the reverse transcriptase (RT) pause in the presence of sprA1AS (black arrows) and the mutated nucleotides in the SD–mutated SprA1 construct (rectangles, 12 mutated nucleotides to maintain H1 while modifying the Shine-Dalgarno sequence). The predicted initiation and termination codons are framed, and the nucleotide sequence overlapping with sprA1AS is in gray. () S. aureus ribosome toeprint assay of SprA1 (WT SprA1) and the disappearance of the toeprints in the SD-mutated SprA1. In the presence of SprA1AS at a 2:1 molar ratio, there are no toeprints, indicating that the asRNA impairs ribosome loading onto SprA1. The toeprints are indicated with a black bullet and the reverse transcriptase pause for SprA1, in the presence of SprA1AS, is indicated by an arrowhead. T, A, G and C are the SprA1 sequencing ladders. () In vitro translation of SprA1 (lane 1), of SprA1 in the presence of SprA1AS at a 1:1 molar ratio (lane! 2), of SprA1 in the presence of 5′ SprA1AS at a 1:10 molar ratio (lane 3), of SprA1 in the presence of 3′ SprA1AS at a 1:10 molar ratio (lane 4) and of SD-mutated SprA1 (lane 5). The translated SprA1-encoded polypeptide of ~3 kDa is indicated by an arrowhead. () Northern blot analysis of SprA1 and SprA1AS in Newman pCN35 and isogenic Newman pCN35ΩsprA1AS during growth. The 5S rRNAs are the controls. * Figure 6: SprA1AScis-RNA acts in trans to downregulate SprA1-encoded peptide expression in vivo. () Detection of the ~5 kDa SprA1-encoded flagged peptide at early (A600nm = 1) and mid-exponential (A600nm = 5) phases of growth in strains Newman ΔsprA1-ΔsprA1AS pCN34ΩsprA1tag pCN35 (lanes 1 and 3) and in isogenic Newman ΔsprA1-ΔsprA1AS pCN34ΩsprA1tag pCN35ΩsprA1AS strain (lanes 2 and 4) by immunoblots using anti-Flag antibodies. () Northern blot analysis for monitoring SprA1-Flag RNA (upper panel) and SprA1AS RNA (lower panel) expression levels at identical phases of growth. The 5S rRNAs are the internal loading controls. * Figure 7: The SprA1-encoded peptide is lytic for human cells. () Hemolytic activity of synthetic SprA1-encoded peptide compared to a non-hemolytic peptide used as a negative control. Controls: the minus sign indicates that PBS was added to the red blood cells (RBC), the plus sign indicates hypotonic solution was added to RBCs. RBC sedimentation indicates the absence of hemolysis, whereas a red supernatant implies hemolysis. () Differential hemolytic activity of the synthetic SprA1 peptide for human and sheep RBCs. The peptide induces a strong hemolysis on the human RBCs but a weak hemolysis on the sheep RBCs. () Proposed model for the downregulation of SprA1 sRNA internal translation in trans by the cis-encoded SprA1AS. The SprA1 internal ORF is shown in green and the SprA1 and SprA1AS 5′ non-overlapping interacting domains are in red. Their 3′ overlapping domains are in yellow. Upon duplex formation, the SprA1AS 5′ domain pairs at and around the SprA1 internal translation initiation signals (SD-sequence and start codon, red) by ! unfolding pseudoknot PK1. During S. aureus growth, translation of the SprA1-encoded peptide is repressed by base pairings in trans with SprA1AS RNA (see also Supplementary Fig. 7). Author information * Abstract * Author information * Supplementary information Affiliations * Laboratoire de Biochimie Pharmaceutique Inserm U835 Upres EA2311 Université de Rennes, Rennes, France. * Nour Sayed, * Ambre Jousselin & * Brice Felden Contributions N.S. and B.F. designed experiments, prepared samples, analyzed the data and wrote the manuscript. A.J. constructed the sRNA double mutant, did the Hfq experiment and participated in discussions and writing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Brice Felden Author Details * Nour Sayed Search for this author in: * NPG journals * PubMed * Google Scholar * Ambre Jousselin Search for this author in: * NPG journals * PubMed * Google Scholar * Brice Felden Contact Brice Felden Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–7 and Supplementary Tables 1–2 Additional data Entities in this article * Beta-lactamase blaZ Staphylococcus aureus * View in UniProt * View in Entrez Gene * RNA chaperone, host factor-1 protein NWMN_1212 Staphylococcus aureus (strain Newman) * View in UniProt * View in Entrez Gene * Delta-hemolysin Staphylococcus aureus * View in UniProt
Fluorescent fusion protein knockout mediated by anti-GFP nanobody
- Nat Struct Mol Biol 19(1):117-121 (2012)
Nature Structural & Molecular Biology | Brief Communication Single-molecule studies reveal the function of a third polymerase in the replisome * Roxana E Georgescu1 * Isabel Kurth1 * Mike E O'Donnell1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:113–116Year published:(2012)DOI:doi:10.1038/nsmb.2179Received 16 June 2011 Accepted 29 September 2011 Published online 11 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The Escherichia coli replisome contains three polymerases, one more than necessary to duplicate the two parental strands. Using single-molecule studies, we reveal two advantages conferred by the third polymerase. First, dipolymerase replisomes are inefficient at synthesizing lagging strands, leaving single-strand gaps, whereas tripolymerase replisomes fill strands almost to completion. Second, tripolymerase replisomes are much more processive than dipolymerase replisomes. These features account for the unexpected three-polymerase-structure of bacterial replisomes. View full text Figures at a glance * Figure 1: TriPol replisomes are more processive than DiPol replisomes. () Scheme of single-molecule experiments. For clarity, only the DiPol replisome is illustrated. () DNA products from either the DiPol (left) or TriPol (right) replisome, using 250 nM primase. The endpoints of two representative DNA products are marked with arrowheads. () DNA length distribution histograms. Numbers represent the single-exponential fit ± s.e.m. of the total number (N) of molecules analyzed. Gray bars represent DNA strand lengths below 15 kb that were undersampled because they were obscured by the width of the diffusion barrier. Left, DiPol replisomes, right, TriPol replisomes. () Processivity of DiPol and TriPol replisomes, where the indicated polymerase is present or absent from the buffer flow. * Figure 2: TriPol replisomes are more efficient on the lagging strand than DiPol replisomes are. () Scheme of the bead-based assay; the DiPol replisome is illustrated for simplicity. () Dipol and Tripol replisomes replicate DNA with similar rates. Left, autoradiogram of 0.8% alkaline agarose gel analysis of reactions, using either Tripol III* (20 nM) or DiPol III* (80 nM); DnaG primase concentration was 200 nM. Right, plot of DNA length versus time. () Left, leading- and lagging-strand replication products from bead-based reactions, resolved on denaturing agarose gels, using 320 nM DnaG primase. Right, quantitation of leading- and lagging-strand synthesis, normalized to the products of the TriPol replisome. * Figure 3: Analysis of ssDNA gaps in lagging strand products. () Magnified view of DNA products generated by DiPol and TriPol replisomes; the light and dark regions correspond to dsDNA segments and ssDNA gaps. () Comparative histogram showing the percentage of DNA strands with gaps (green) and without gaps (purple). () Histograms showing the distribution of gap length (in μm) using DiPol (red) and TriPol (blue) replisomes. () Model of TriPol and DiPol replisome action. Pol III cores are represented as right hands; with the β-clamp (red), clamp loader (dark green), DnaB helicase (blue hexamer), primase (light green) and SSB (purple). The τ-subunit C-terminal domains (IV and V) are illustrated as jointed lines that mediate connections to DnaB helicase and Pol III cores. The χψψ subunits of the clamp loader are omitted for clarity. The TriPol replisome depicts two Pol III cores extending two Okazaki fragments simultaneously, although there are other ways a TriPol replisome can be used (see text). The left illustration depicts one la! gging Pol III extending an RNA primer (red) to produce a DNA strand (yellow), and the other lagging Pol III core extends the DNA (blue) to fill a ssDNA gap. Author information * Author information * Supplementary information Affiliations * The Rockefeller University, Howard Hughes Medical Institute, New York, New York, USA. * Roxana E Georgescu, * Isabel Kurth & * Mike E O'Donnell Contributions R.E.G. and I.K. carried out experiments; R.E.G., I.K. and M.E.O. designed the experiments. R.E.G., I.K. and M.E.O. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Mike E O'Donnell Author Details * Roxana E Georgescu Search for this author in: * NPG journals * PubMed * Google Scholar * Isabel Kurth Search for this author in: * NPG journals * PubMed * Google Scholar * Mike E O'Donnell Contact Mike E O'Donnell Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (324K) Supplementary Figures 1–4 and Supplementary Methods Movies * Supplementary Video 1 (1M) Replication performed by Dipol replisomes. An example of a movie depicting real-time observation of coupled leading/lagging strand replication of a mini-rolling circle substrate by E. coli Dipol replisomes. The force of the hydrodynamic flow pushes the DNA-lipid complex to a diffusion barrier etched in the glass surface and concentrates numerous DNA molecules in the visual field shown here. The width of the visible area in the direction of the flow is 73 μm (equivalent to 220 kb) and the flow direction is from top to the bottom. Individual DNA molecules visualized with the fluorescent dye Yo-Pro1 are stretched by the buffer flow (100 μl/min) and imaged through Total Internal Reflection Fluorescence (TIRF) microscopy. Toward the end of the movie, the buffer-flow is stopped, letting the strands recoil, then the buffer flow is started again. Movie contains circa 7' 30″ of experimental data rendered at 20 frames per second (original data acquisition is 1 frame/s at 100 ms ex! posure per frame). * Supplementary Video 2 (332K) Replication performed by Tripol replisomes. The video depicts the recording of a replication reaction performed by Tripol replisomes. The movie contains circa 5' 30″ of experimental data rendered at 20 frames per second (original data acquisition is 1 frame/s at 100 ms exposure for each frame). * Supplementary Video 3 (451K) DNA molecules that harbor duplex regions contain gaps on the same molecule. The video depicts a recording at the end of a replication reaction using a DiPol replisome. The flow of the buffer solution is stopped then restarted, allowing the DNA strands to stretch and then recoil to their point of origin. * Supplementary Video 4 (2M) Use of fluorescent SSB to identify ssDNA in DNA products. The video depicts three successive recordings of different DNA products of DiPol replisomes, in which reactions contained fluorescently labeled SSB. The three successive recordings are easy to identify since they have different dimensions. The videos show that DNA products contain fluorescently labeled E. coli SSB (with Oregon Green488 Maleimide). The duplex DNA is not visualized because Yo-Pro1 is omitted from the buffer flow for these experiments. To distinguish SSB bound to DNA from SSB that binds non-specifically to the surface of the flow cell, the buffer-flow is alternatively stopped and restarted in order to observe the recoiling of the DNA strands. Fluorescent SSB bound to DNA recoils and re-extends in synchrony with the changes in buffer flow (while non-specifically bound SSB does not change position). Additional data Entities in this article * DNA polymerase III subunit tau dnaX Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Replicative DNA helicase dnaB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Single-stranded DNA-binding protein ssb Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase I polA Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase II polB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase IV dinB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA primase dnaG Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene
A metal switch for controlling the activity of molecular motor proteins
- Nat Struct Mol Biol 19(1):122-127 (2012)
Nature Structural & Molecular Biology | Brief Communication Single-molecule studies reveal the function of a third polymerase in the replisome * Roxana E Georgescu1 * Isabel Kurth1 * Mike E O'Donnell1 * Affiliations * Contributions * Corresponding authorJournal name:Nature Structural & Molecular BiologyVolume: 19,Pages:113–116Year published:(2012)DOI:doi:10.1038/nsmb.2179Received 16 June 2011 Accepted 29 September 2011 Published online 11 December 2011 Highlighting tool Genes and ProteinsUpdate Highlighting Article tools * Full text * Print * Email * pdf options * download pdf * view interactive pdfpowered by ReadCube * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The Escherichia coli replisome contains three polymerases, one more than necessary to duplicate the two parental strands. Using single-molecule studies, we reveal two advantages conferred by the third polymerase. First, dipolymerase replisomes are inefficient at synthesizing lagging strands, leaving single-strand gaps, whereas tripolymerase replisomes fill strands almost to completion. Second, tripolymerase replisomes are much more processive than dipolymerase replisomes. These features account for the unexpected three-polymerase-structure of bacterial replisomes. View full text Figures at a glance * Figure 1: TriPol replisomes are more processive than DiPol replisomes. () Scheme of single-molecule experiments. For clarity, only the DiPol replisome is illustrated. () DNA products from either the DiPol (left) or TriPol (right) replisome, using 250 nM primase. The endpoints of two representative DNA products are marked with arrowheads. () DNA length distribution histograms. Numbers represent the single-exponential fit ± s.e.m. of the total number (N) of molecules analyzed. Gray bars represent DNA strand lengths below 15 kb that were undersampled because they were obscured by the width of the diffusion barrier. Left, DiPol replisomes, right, TriPol replisomes. () Processivity of DiPol and TriPol replisomes, where the indicated polymerase is present or absent from the buffer flow. * Figure 2: TriPol replisomes are more efficient on the lagging strand than DiPol replisomes are. () Scheme of the bead-based assay; the DiPol replisome is illustrated for simplicity. () Dipol and Tripol replisomes replicate DNA with similar rates. Left, autoradiogram of 0.8% alkaline agarose gel analysis of reactions, using either Tripol III* (20 nM) or DiPol III* (80 nM); DnaG primase concentration was 200 nM. Right, plot of DNA length versus time. () Left, leading- and lagging-strand replication products from bead-based reactions, resolved on denaturing agarose gels, using 320 nM DnaG primase. Right, quantitation of leading- and lagging-strand synthesis, normalized to the products of the TriPol replisome. * Figure 3: Analysis of ssDNA gaps in lagging strand products. () Magnified view of DNA products generated by DiPol and TriPol replisomes; the light and dark regions correspond to dsDNA segments and ssDNA gaps. () Comparative histogram showing the percentage of DNA strands with gaps (green) and without gaps (purple). () Histograms showing the distribution of gap length (in μm) using DiPol (red) and TriPol (blue) replisomes. () Model of TriPol and DiPol replisome action. Pol III cores are represented as right hands; with the β-clamp (red), clamp loader (dark green), DnaB helicase (blue hexamer), primase (light green) and SSB (purple). The τ-subunit C-terminal domains (IV and V) are illustrated as jointed lines that mediate connections to DnaB helicase and Pol III cores. The χψψ subunits of the clamp loader are omitted for clarity. The TriPol replisome depicts two Pol III cores extending two Okazaki fragments simultaneously, although there are other ways a TriPol replisome can be used (see text). The left illustration depicts one la! gging Pol III extending an RNA primer (red) to produce a DNA strand (yellow), and the other lagging Pol III core extends the DNA (blue) to fill a ssDNA gap. Author information * Author information * Supplementary information Affiliations * The Rockefeller University, Howard Hughes Medical Institute, New York, New York, USA. * Roxana E Georgescu, * Isabel Kurth & * Mike E O'Donnell Contributions R.E.G. and I.K. carried out experiments; R.E.G., I.K. and M.E.O. designed the experiments. R.E.G., I.K. and M.E.O. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Mike E O'Donnell Author Details * Roxana E Georgescu Search for this author in: * NPG journals * PubMed * Google Scholar * Isabel Kurth Search for this author in: * NPG journals * PubMed * Google Scholar * Mike E O'Donnell Contact Mike E O'Donnell Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (324K) Supplementary Figures 1–4 and Supplementary Methods Movies * Supplementary Video 1 (1M) Replication performed by Dipol replisomes. An example of a movie depicting real-time observation of coupled leading/lagging strand replication of a mini-rolling circle substrate by E. coli Dipol replisomes. The force of the hydrodynamic flow pushes the DNA-lipid complex to a diffusion barrier etched in the glass surface and concentrates numerous DNA molecules in the visual field shown here. The width of the visible area in the direction of the flow is 73 μm (equivalent to 220 kb) and the flow direction is from top to the bottom. Individual DNA molecules visualized with the fluorescent dye Yo-Pro1 are stretched by the buffer flow (100 μl/min) and imaged through Total Internal Reflection Fluorescence (TIRF) microscopy. Toward the end of the movie, the buffer-flow is stopped, letting the strands recoil, then the buffer flow is started again. Movie contains circa 7' 30″ of experimental data rendered at 20 frames per second (original data acquisition is 1 frame/s at 100 ms ex! posure per frame). * Supplementary Video 2 (332K) Replication performed by Tripol replisomes. The video depicts the recording of a replication reaction performed by Tripol replisomes. The movie contains circa 5' 30″ of experimental data rendered at 20 frames per second (original data acquisition is 1 frame/s at 100 ms exposure for each frame). * Supplementary Video 3 (451K) DNA molecules that harbor duplex regions contain gaps on the same molecule. The video depicts a recording at the end of a replication reaction using a DiPol replisome. The flow of the buffer solution is stopped then restarted, allowing the DNA strands to stretch and then recoil to their point of origin. * Supplementary Video 4 (2M) Use of fluorescent SSB to identify ssDNA in DNA products. The video depicts three successive recordings of different DNA products of DiPol replisomes, in which reactions contained fluorescently labeled SSB. The three successive recordings are easy to identify since they have different dimensions. The videos show that DNA products contain fluorescently labeled E. coli SSB (with Oregon Green488 Maleimide). The duplex DNA is not visualized because Yo-Pro1 is omitted from the buffer flow for these experiments. To distinguish SSB bound to DNA from SSB that binds non-specifically to the surface of the flow cell, the buffer-flow is alternatively stopped and restarted in order to observe the recoiling of the DNA strands. Fluorescent SSB bound to DNA recoils and re-extends in synchrony with the changes in buffer flow (while non-specifically bound SSB does not change position). Additional data Entities in this article * DNA polymerase III subunit tau dnaX Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Replicative DNA helicase dnaB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * Single-stranded DNA-binding protein ssb Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase I polA Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase II polB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA polymerase IV dinB Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene * DNA primase dnaG Escherichia coli (strain K12) * View in UniProt * View in Entrez Gene

Hot off the presses! Feb 01 Nat Rev Immunol

2012-01-25T03:27:00.001-08:00

The Feb 01 issue of the Nat Rev Immunol is now up on Pubget (About Nat Rev Immunol): if you're at a subscribing institution, just click the link in the latest link at the home page. (Note you'll only be able to get all the PDFs in the issue if your institution subscribes to Pubget.)

Latest Articles Include:

Antibody responses: Neutrophils zone in to help B cells | PDF (280 KB)
- Nat Rev Immunol 12(2):73 (2012)
Neutrophils are key effector cells of the innate immune system that are rapidly recruited to infected tissues to clear pathogens. Recently, researchers have shown that neutrophils also shape adaptive immune responses by interacting with T cells and dendritic cells (DCs).
Trafficking: Effector T cells cross the line | PDF (158 KB)
- Nat Rev Immunol 12(2):74 (2012)
Effector T cells migrate through the endothelial cell wall of blood vessels into inflamed tissues. Selectins, integrins and chemokine receptors have a central role in T cell extravasation, which involves the steps of cell arrest, spreading, crawling and transendothelial migration.
T cells: The TFH-like transition of TH1 cells | PDF (254 KB)
- Nat Rev Immunol 12(2):74 (2012)
The extent to which T helper (TH) cell subsets — including T follicular helper (TFH) cells — are distinct cell lineages has been the subject of much debate in recent years. Now, new evidence suggests that early during their development TH1 cells pass through a TH1–TFH cell stage, which involves a dynamic balance of signals mediated by the transcription factors signal transducer and activator of transcription 4 (STAT4), T-bet and B cell lymphoma 6 (BCL-6).
Mucosal immunology: Multifunctional gut IgA+ plasma cells | PDF (262 KB)
- Nat Rev Immunol 12(2):75 (2012)
The production of polyreactive IgA by plasma cells in the gastrointestinal tract is important for maintaining mucosal homeostasis. But do plasma cells in the intestine have functions that go beyond IgA production?
Viral immunity: Lose TRAF1, lose control | PDF (137 KB)
- Nat Rev Immunol 12(2):76 (2012)
Recent research describes a new defect that is associated with CD8+ T cell dysfunction in chronic viral infection. An acquired loss of expression of the signalling adaptor TNFR-associated factor 1 (TRAF1) from virus-specific CD8+ T cells during HIV infection in humans and during chronic lymphocytic choriomeningitis virus (LCMV) infection in mice decreases their ability to control the virus.
Immunometabolism: IL-15 provides breathing space for memory | PDF (269 KB)
- Nat Rev Immunol 12(2):76 (2012)
Memory T cells promote long-term resistance to infection, and uncovering the mechanisms that control their development and function is an important goal for immunologists. Van der Windt et al.+ T cells possess greater mitochondrial spare respiratory capacity (SRC) than naive or effector T cells.
Autoimmunity: Interfering with brain inflammation | PDF (161 KB)
- Nat Rev Immunol 12(2):77 (2012)
Interferon-β (IFNβ) is a first-line therapy for patients with relapsing–remitting multiple sclerosis. This study provides insight into the pathways by which type I IFNs can suppress inflammation in the central nervous system (CNS) and suggests a new mechanism by which these pathways could be targeted therapeutically.
Innate immunity: Phagocytes come back even stronger | PDF (112 KB)
- Nat Rev Immunol 12(2):74 (2012)
Lauvau and colleagues have shown that inflammatory monocytes and neutrophils become better pathogen killers during memory responses. The authors found that the enhanced clearance of the intracellular pathogen Listeria monocytogenes following re-infection was associated with increased reactive oxygen species (ROS)-mediated bacterial killing.
- Nat Rev Immunol 12(2):74 (2012)
- Nat Rev Immunol 12(2):74 (2012)
Viral infection and the evolution of caspase 8-regulated apoptotic and necrotic death pathways
- Nat Rev Immunol 12(2):79 (2012)
Pathogens specifically target both the caspase 8-dependent apoptotic cell death pathway and the necrotic cell death pathway that is dependent on receptor-interacting protein 1 (RIP1; also known as RIPK1) and RIP3 (also known as RIPK3). The fundamental co-regulation of these two cell death pathways emerged when the midgestational death of mice deficient in FAS-associated death domain protein (FADD) or caspase 8 was reversed by elimination of RIP1 or RIP3, indicating a far more entwined relationship than previously appreciated. Thus, mammals require caspase 8 activity during embryogenesis to suppress the kinases RIP1 and RIP3 as part of the dialogue between two distinct cell death processes that together fulfil reinforcing roles in the host defence against intracellular pathogens such as herpesviruses.
How do plants achieve immunity? Defence without specialized immune cells
- Nat Rev Immunol 12(2):89 (2012)
Vertebrates have evolved a sophisticated adaptive immune system that relies on an almost infinite diversity of antigen receptors that are clonally expressed by specialized immune cells that roam the circulatory system. These immune cells provide vertebrates with extraordinary antigen-specific immune capacity and memory, while minimizing self-reactivity. Plants, however, lack specialized mobile immune cells. Instead, every plant cell is thought to be capable of launching an effective immune response. So how do plants achieve specific, self-tolerant immunity and establish immune memory? Recent developments point towards a multilayered plant innate immune system comprised of self-surveillance, systemic signalling and chromosomal changes that together establish effective immunity.
Transcriptional programming of the dendritic cell network
- Nat Rev Immunol 12(2):101 (2012)
Specialized subsets of dendritic cells (DCs) provide a crucial link between the innate and adaptive immune responses. The genetic programme that coordinates these distinct DC subsets is controlled by both cytokines and transcription factors. The initial steps in DC specification occur in the bone marrow and result in the generation of precursors committed to either the plasmacytoid or conventional DC pathways. DCs undergo further differentiation and lineage diversification in peripheral organs in response to local environmental cues. In this Review, we discuss new evidence regarding the coordination of the specification and commitment of precursor cells to different DC subsets and highlight the ensemble of transcription factors that control these processes.
Early immune events in the induction of allergic contact dermatitis
- Nat Rev Immunol 12(2):114 (2012)
The skin is a barrier site that is exposed to a wide variety of potential pathogens. As in other organs, pathogens that invade the skin are recognized by pattern-recognition receptors (PRRs). Recently, it has been recognized that PRRs are also engaged by chemical contact allergens and, in susceptible individuals, this elicits an inappropriate immune response that results in allergic contact dermatitis. In this Review, we focus on how contact allergens promote inflammation by activating the innate immune system. We also examine how innate immune cells in the skin, including mast cells and dendritic cells, cooperate with each other and with T cells and keratinocytes to initiate and drive early responses to contact allergens.
Immunomodulatory functions of type I interferons
- Nat Rev Immunol 12(2):125 (2012)
Interferon-α (IFNα) and IFNβ, collectively known as type I IFNs, are the major effector cytokines of the host immune response against viral infections. However, the production of type I IFNs is also induced in response to bacterial ligands of innate immune receptors and/or bacterial infections, indicating a broader physiological role for these cytokines in host defence and homeostasis than was originally assumed. The main focus of this Review is the underappreciated immunomodulatory functions of type I IFNs in health and disease. We discuss their function in the regulation of innate and adaptive immune responses, the response to bacterial ligands, inflammasome activation, intestinal homeostasis and inflammatory and autoimmune diseases.
Expanding roles for CD4+ T cells in immunity to viruses
- Nat Rev Immunol 12(2):136 (2012)
Viral pathogens often induce strong effector CD4+ T cell responses that are best known for their ability to help B cell and CD8+ T cell responses. However, recent studies have uncovered additional roles for CD4+ T cells, some of which are independent of other lymphocytes, and have described previously unappreciated functions for memory CD4+ T cells in immunity to viruses. Here, we review the full range of antiviral functions of CD4+ T cells, discussing the activities of these cells in helping other lymphocytes and in inducing innate immune responses, as well as their direct antiviral roles. We suggest that all of these functions of CD4+ T cells are integrated to provide highly effective immune protection against viral pathogens.