Latest Articles Include:
- Into the fold
- Nat Meth 8(3):185 (2011)
Nature Methods | Editorial Into the fold Journal name:Nature MethodsVolume: 8,Page:185Year published:(2011)DOI:doi:10.1038/nmeth0311-185Published online25 February 2011 In spite of its promise, nanotechnology has seen little uptake among biologists. DNA origami may be able to avoid this fate. View full text Additional data - The author file: Thomas Clandinin
- Nat Meth 8(3):187 (2011)
Nature Methods | This Month The author file: Thomas Clandinin * Monya BakerJournal name:Nature MethodsVolume: 8,Page:187Year published:(2011)DOI:doi:10.1038/nmeth0311-187Published online25 February 2011 A new genetic construct enhances enhancer traps. View full text Additional data - Points of view: Points of review (part 2)
- Nat Meth 8(3):189 (2011)
Nature Methods | This Month Points of view: Points of review (part 2) * Bang Wong1Journal name:Nature MethodsVolume: 8,Page:189Year published:(2011)DOI:doi:10.1038/nmeth0311-189Published online25 February 2011 Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. I will continue to demonstrate how judicious choice of graphical representations can improve visual communication. Here I will focus on data figures. The power and primary purpose of graphs is to reveal connections in data. As opposed to tables, in which there is little visual association between individual values, graphs and charts depend on readers to form patterns. In reading graphs, we observe individual data points, keep each of them in memory and construct an image from the constituents. The entire process can be exceedingly fast and attest to the power of visual perception. Graphical encoding needs to support the detection and assembly process of reading graphs. We are more accurate at certain types of visual estimation than others (September 2010 column)1. For example, to understand relative differences between categories, a standard bar chart might be easier to read than a pie chart, particularly to appreciate the direction and magnitude of change (Fig. 1). Small differences are more readily apparent when we compare length of bars (Fig. 1c) than sizes of pie slices (Fig. 1a)2. Figure 1: Certain visual encodings are easier to read. (,) Analysis of genetic interactions. Adapted and reprinted from Nature Methods2. () A bar chart showing data from the pie chart in . () A method for ordering slices of a pie chart. () Multiple views to show overlapping data from . Former 'yellow' and 'blue' categories are shown in purple and green, respectively. * Full size image (80 KB) * Figures index * Next figure Pie charts can be useful. Although they are not intended to show complex relationships, pie charts do well to depict parts of a whole. The Wall Street Journal Guide to Information Graphics3 suggests an ordering of slices to aid reading: place the largest wedge to the right of 12 o'clock, the second largest to the left of 12 o'clock and the remainder counter-clockwise descending in size (Fig. 1d). In this way, the largest (and presumably most important) wedges end up at the top. With the two largest slices sharing a vertical edge, we can rely on reading angles to estimate proportion. View full text Figures at a glance * Figure 1: Certain visual encodings are easier to read. (,) Analysis of genetic interactions. Adapted and reprinted from Nature Methods2. () A bar chart showing data from the pie chart in . () A method for ordering slices of a pie chart. () Multiple views to show overlapping data from . Former 'yellow' and 'blue' categories are shown in purple and green, respectively. * Figure 2: Color is not ideal for presenting quantitative data. () Shifts in color scales (circles) are not visually commensurate with change in value. Reprinted from Nature Methods2, 5. () A gradation from 10–90% black produces even transitions. 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 * 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. Author Details * Bang Wong Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$32Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data - Taxonomic metagenome sequence assignment with structured output models
- Nat Meth 8(3):191-192 (2011)
Nature Methods | Correspondence Taxonomic metagenome sequence assignment with structured output models * Kaustubh R Patil1 * Peter Haider2 * Phillip B Pope3 * Peter J Turnbaugh4 * Mark Morrison3 * Tobias Scheffer2 * Alice C McHardy1, 5 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:191–192Year published:(2011)DOI:doi:10.1038/nmeth0311-191Published online25 February 2011 To the Editor: Computational inference of the taxonomic origin of sequence fragments is an essential step in metagenome analysis1. Fragments can be assigned to individual populations or corresponding higher-level evolutionary clades using methods based on homology, sequence similarity or sequence composition2. This is a challenging task, as for most uncultured microorganisms reference sequences are unavailable, and large amounts of data have to be processed. With this in mind, we introduce PhyloPythiaS a successor of our previously published method PhyloPythia3. It is a fast and accurate sequence compositional classifier based on the structured output paradigm4. We evaluated PhyloPythiaS on simulated and real metagenome data in comparison to four other methods: PhyloPythia3, metagenome analyzer (MEGAN)5, Phymm and PhymmBL6. PhyloPhythiaS performed particularly well for taxonomic assignment of populations from novel genera, order or higher-level clades, when limited amounts of reference data were available. We observed that accurate assignments were obtained based on 100 kilobases (kb) of training data for a sample population. We observed this for simulated data (Fig. 1a, Supplementary Fig. 1 and Supplementary Table 1) and a predominant population of a novel family of the order of Aeromonadales from the Australian Tammar wallaby gut (Fig. 1b, Supplementary Fig. 2 and Supplementary Tables 2–4). We performed experiments on simulated data for four settings: with genomes of the same species for the dominant strains made available as reference data (known species) or with genomes of the corresponding higher-level clades (genus, order an! d class) removed, while retaining 100 kb of sequence for the dominant strains. In this scenario, alignment-based methods performed poorly. If closely related genomeswere available, the performance of all methods became more similar, with a slight advantage for alignment-based approaches. We observed this for simulated data and the predominant genera of two human gut metagenomes (Supplementary Tables 5–8). back to article Figure 1: Comparison of taxonomic classification methods. () Average performance per contig for the simMC dataset at genus rank. () Scaffold-contig consistency for the WG-1 population (uncultured Succinivibrionaceae bacterium) of the Tammar wallaby gut metagenome. Contig coloring reflects taxonomic assignment consistency with respect to WG-1. Only scaffolds longer than 20 kb are shown. () Empirical execution time evaluated on a Linux machine with 3-gigahertz processor and 4 gigabytes main memory. Results for MEGAN and PhymmBL were determined with a reference database of size 2.1 gigabases. View full text 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 * Max-Planck Research Group for Computational Genomics and Epidemiology, Max Planck Institute for Informatics, Saarbrücken, Germany. * Kaustubh R Patil & * Alice C McHardy * University of Potsdam, Department of Computer Science, Potsdam, Germany. * Peter Haider & * Tobias Scheffer * Commonwealth Scientific and Industrial Research Organization Livestock Industries, Queensland Bioscience Precinct, St Lucia, Australia. * Phillip B Pope & * Mark Morrison * Harvard Faculty of Arts and Sciences Center for Systems Biology, Cambridge Massacusetts, USA. * Peter J Turnbaugh * Department of Algorithmic Bioinformatics, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany. * Alice C McHardy Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Alice C McHardy Author Details * Kaustubh R Patil Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Haider Search for this author in: * NPG journals * PubMed * Google Scholar * Phillip B Pope Search for this author in: * NPG journals * PubMed * Google Scholar * Peter J Turnbaugh Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Morrison Search for this author in: * NPG journals * PubMed * Google Scholar * Tobias Scheffer Search for this author in: * NPG journals * PubMed * Google Scholar * Alice C McHardy Contact Alice C McHardy Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–5, Supplementary Tables 1–14, Supplementary Note Additional data * Journal home * Current issue * For authors * Subscribe * E-alert sign up * RSS feed Science jobs from naturejobs * Research Scientist – Gene Therapy * GlaxoSmithKline * Stevenage, Hertfordshire, UK * Junior-Professor W 1 "New Innovative Materials for Photonic Technologies" * Friedrich-Schiller-Universitat Jena * Jena, Germany * Research Professorship "Clinical Epidemiology / Public Health" (W2) * Friedrich-Schiller-Universitat Jena * Jena, Germany * Post a free job * More science jobs Related content Articles * Recovery of intact DNA nanostructures after agarose gel–based separation Nature Methods 25 Feb 2011 * Designer enzymes for glycosphingolipid synthesis by directed evolution Nature Chemical Biology 14 Jun 2009 * Gene-specific RNA polymerase II phosphorylation and the CTD code Nature Structural & Molecular Biology 12 Sep 2010 * The human cytomegalovirus microRNA miR-UL112 acts synergistically with a cellular microRNA to escape immune elimination Nature Immunology 08 Aug 2010 * A point mutation in KINDLIN3 ablates activation of three integrin subfamilies in humans Nature Medicine 22 Feb 2009 View all Open innovation challenges * Derivation of Trophoblast Stem Cells from Human iPS Cells or Human ES Cells Deadline:Mar 13 2011Reward:$50,000 USD The Seeker wishes to derive trophoblast stem (TS) cells from human induced pluripotent stem (iPS) ce… * RNAi Sequences Targeted to the Asian Citrus Psyllid Genome Deadline:May 03 2011Reward:$100,000 USD The non-profit Citrus Research and Development Foundation, desires proposals for RNA sequences that … * Powered by: * More challenges Top content Emailed * Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns Nature Methods 06 Feb 2011 * Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster Nature Methods 06 Feb 2011 * High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision Nature Methods 18 Apr 2010 * Strategies for protein coexpression in Escherichia coli Nature Methods 01 Jan 2006 * Unrestrained worms bridled by the light Nature Methods 28 Jan 2011 View all Downloaded * Mapping and quantifying mammalian transcriptomes by RNA-Seq Nature Methods 30 May 2008 * Confined activation and subdiffractive localization enables whole-cell PALM with genetically expressed probes Nature Methods 13 Feb 2011 * A microprobe for parallel optical and electrical recordings from single neurons in vivo Nature Methods 13 Feb 2011 * Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster Nature Methods 06 Feb 2011 * Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns Nature Methods 06 Feb 2011 View all Blogged * Limitations of next-generation genome sequence assembly Nature Methods 21 Nov 2010 * Rapid blue-light–mediated induction of protein interactions in living cells Nature Methods 31 Oct 2010 View all * Nature Methods * ISSN: 1548-7091 * EISSN: 1548-7105 * About NPG * Contact NPG * RSS web feeds * Help * Privacy policy * Legal notice * Accessibility statement * Terms * Nature News * Naturejobs * Nature Asia * Nature EducationSearch:Go © 2011 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.partner of AGORA, HINARI, OARE, INASP, CrossRef and COUNTER - Recovery of intact DNA nanostructures after agarose gel–based separation
- Nat Meth 8(3):192-194 (2011)
Nature Methods | Correspondence Recovery of intact DNA nanostructures after agarose gel–based separation * Gaëtan Bellot1, 2, 4 * Mark A McClintock1, 2, 4 * Chenxiang Lin1, 2, 3 * William M Shih1, 2, 3 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:192–194Year published:(2011)DOI:doi:10.1038/nmeth0311-192Published online25 February 2011 To the Editor: Molecular self-assembly using DNA as a structural building block has proven an efficient route for construction of nanoscale objects and arrays of ever-increasing complexity1. An important catalyst for advancing the field in recent years has been the scaffolded DNA origami strategy, in which a long 'scaffold' strand derived from a viral genome (M13) can be folded with hundreds of short synthetic 'staple' strands into a variety of custom two- and three-dimensional shapes2, 3. This technology is being used to develop molecular tools for applications in fields such as structural biology4, single-molecule biophysics and drug delivery. Many of these applications require a homogenous sample of properly folded nanostructures greatly enriched over the misfolded intermediates and large aggregates characteristic of multilayer DNA-origami self-assembly. Agarose-gel electrophoresis is now the most effective method available for high-resolution separation of well-folded objects on this size scale, but extraction of intact DNA nanostructures with high yield from the agarose matrix is problematic. Existing methods rely on thermal, chemical and/or mechanical destruction of the agarose gel or else electroelution of the DNA to a solid support, leading to problems of low yield, damage to structures and/or contamination with residual agarose. We modified a DNA electroelution method for recovery of DNA from a standard horizontal agarose-gel electrophoresis apparatus to optimize it for efficient, high-resolution and scalable recovery of large and complex intact DNA nanostructures5, 6. Our initial attempts to purify DNA nanostructures by electroelution revealed the need for a well-sealed elution bed to eliminate high-conductivity buffer paths that served as escape routes for the nanostructures. To address this problem, we poured a 1–! 2% agarose resolving gel on top of a thinner and more rigid basement layer of 4% agarose previously set in the gel-casting tray (Supplementary Fig. 1 and Supplementary Methods). Once the sample was sufficiently resolved on our dual-layer agarose system, we cut an elution well in the resolving gel directly in front of the band of interest and filled it with a viscous solution of 30–50% sucrose. The elution well is simple to cut down to the interface with the 4% agarose layer because of the difference in rigidity of the layers, and the seal between the layers adjacent to the elution well is not disturbed. To eliminate high-conductivity paths in buffer above the gel, we maintained the running buffer level even with, or below, the surface of the resolving gel. We eluted the band by electrophoresis of the sample into the sucrose bed where movement of the DNA was slowed enough to allow efficient recovery by UV-light detection and micropipetting. The identity of the elution buffer has profound consequences for the efficacy of purification. Using a 400-nm-long 6-helix bundle nanostructure as a model to assess purification performance (Fig. 1a and Supplementary Table 1), we screened three solutes at varying concentrations. Use of glycerol or polyethylene glycol resulted in retarded migration of the DNA band and a slow elution time of 1–3 hours, with inconsistent recovery yields between 20% and 60% (Supplementary Fig. 2). We obtained the greatest yields with solutions of 30–50% sucrose (Supplementary Fig. 3). ImageJ analysis of the gels for purified 6-helix bundles indicated 71 ± 3% of the well-folded structure could be recovered from the agarose matrix versus 15 ± 5% by the pellet-pestle homogenization method7. Our analysis by negative-stain transmission electron microscopy (TEM) also indicated a strong enrichment of the properly folded structures. back to article Figure 1: Agarose-gel and TEM analyses of various DNA origami objects after gel purification. (–) Cylinder models (left; each cylinder represents a DNA double helix) of a 6-helix bundle (), 12-helix bundle (), 6-helix bundle ring () and prestressed tensegrity-structure kite (). In gel images (middle), lanes for each object were cropped from a single gel. Ladder, kilobase ladder. For unpurified DNA nanostructures (unpurified), arrows indicate the region of each lane that was extracted from the gel during purification before TEM imaging. Also shown are 30% sucrose gel–purified nanostructures (sucrose) and pellet-pestle homogenization–recovered gel-purified nanostructures (homogenization), with estimates of yields after purification indicated. TEM micrographs (right) of the nanostructures after 30% sucrose gel purification. Scale bars, 100 nm (,,), 50 nm () and in insets, 70 nm (), 80 nm (), 25 nm () and 50 nm (). View full text Subject terms: * Molecular Engineering * Single Molecule 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 Primary authors * These authors contributed equally to this work. * Gaëtan Bellot & * Mark A McClintock Affiliations * Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. * Gaëtan Bellot, * Mark A McClintock, * Chenxiang Lin & * William M Shih * Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts, USA. * Gaëtan Bellot, * Mark A McClintock, * Chenxiang Lin & * William M Shih * Wyss Institute for Biologically Inspired Engineering at Harvard, Cambridge, Massachusetts, USA. * Chenxiang Lin & * William M Shih Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * William M Shih Author Details * Gaëtan Bellot Search for this author in: * NPG journals * PubMed * Google Scholar * Mark A McClintock Search for this author in: * NPG journals * PubMed * Google Scholar * Chenxiang Lin Search for this author in: * NPG journals * PubMed * Google Scholar * William M Shih Contact William M Shih Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–9, Supplementary Table 1, Supplementary Methods Additional data * Journal home * Current issue * For authors * Subscribe * E-alert sign up * RSS feed Science jobs from naturejobs * Research Professorship "Clinical Epidemiology / Public Health" (W2) * Friedrich-Schiller-Universitat Jena * Jena, Germany * Research Scientist – Gene Therapy * GlaxoSmithKline * Stevenage, Hertfordshire, UK * Professor for Radiology (W3) * Friedrich-Schiller-Universitat Jena * Jena, Germany * Post a free job * More science jobs Related content Articles * Inhibition of a viral enzyme by a small-molecule dimer disruptor Nature Chemical Biology 26 Jul 2009 * Pathological responses to oncogenic Hedgehog signaling in skin are dependent on canonical Wnt/β-catenin signaling Nature Genetics 01 Aug 2008 * Taxonomic metagenome sequence assignment with structured output models Nature Methods 25 Feb 2011 * Correlated conformational events in EF-G and the ribosome regulate translocation Nature Structural & Molecular Biology 07 Nov 2010 * Structural basis for the unfolding of anthrax lethal factor by protective antigen oligomers Nature Structural & Molecular Biology 31 Oct 2010 View all Open innovation challenges * Derivation of Trophoblast Stem Cells from Human iPS Cells or Human ES Cells Deadline:Mar 13 2011Reward:$50,000 USD The Seeker wishes to derive trophoblast stem (TS) cells from human induced pluripotent stem (iPS) ce… * Chordoma Cancer Cell Lines Needed to Save Lives! Deadline:Mar 13 2011Reward:$10,000 USD The Chordoma Foundation requests cell lines or animal models that can be used for research into chor… * Powered by: * More challenges Top content Emailed * Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns Nature Methods 06 Feb 2011 * Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster Nature Methods 06 Feb 2011 * High-speed in vivo calcium imaging reveals neuronal network activity with near-millisecond precision Nature Methods 18 Apr 2010 * Strategies for protein coexpression in Escherichia coli Nature Methods 01 Jan 2006 * Unrestrained worms bridled by the light Nature Methods 28 Jan 2011 View all Downloaded * Mapping and quantifying mammalian transcriptomes by RNA-Seq Nature Methods 30 May 2008 * Confined activation and subdiffractive localization enables whole-cell PALM with genetically expressed probes Nature Methods 13 Feb 2011 * A microprobe for parallel optical and electrical recordings from single neurons in vivo Nature Methods 13 Feb 2011 * Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster Nature Methods 06 Feb 2011 * Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns Nature Methods 06 Feb 2011 View all Blogged * Limitations of next-generation genome sequence assembly Nature Methods 21 Nov 2010 * Rapid blue-light–mediated induction of protein interactions in living cells Nature Methods 31 Oct 2010 View all * Nature Methods * ISSN: 1548-7091 * EISSN: 1548-7105 * About NPG * Contact NPG * RSS web feeds * Help * Privacy policy * Legal notice * Accessibility statement * Terms * Nature News * Naturejobs * Nature Asia * Nature EducationSearch:Go © 2011 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.partner of AGORA, HINARI, OARE, INASP, CrossRef and COUNTER - TALEs for the masses
- Nat Meth 8(3):197 (2011)
Nature Methods | Research Highlights TALEs for the masses * Nicole RuskJournal name:Nature MethodsVolume: 8,Page:197Year published:(2011)DOI:doi:10.1038/nmeth0311-197Published online25 February 2011 An optimized transcription activator–like effector (TALE) and an improved assembly method promise efficient genome editing and transcriptome modulation. View full text Subject terms: * Genomics Additional data Author Details * Nicole Rusk Search for this author in: * NPG journals * PubMed * Google Scholar - Brains gone wild
- Nat Meth 8(3):198-199 (2011)
Nature Methods | Research Highlights Brains gone wild * Erika PastranaJournal name:Nature MethodsVolume: 8,Pages:198–199Year published:(2011)DOI:doi:10.1038/nmeth0311-198aPublished online25 February 2011 Analyzing brain signals from freely moving rodents in the wild is possible using a wireless neural recording system. View full text Subject terms: * Neuroscience Additional data Author Details * Erika Pastrana Search for this author in: * NPG journals * PubMed * Google Scholar - Bacteria's puppeteers
- Nat Meth 8(3):198-199 (2011)
Nature Methods | Research Highlights Bacteria's puppeteers * Erika PastranaJournal name:Nature MethodsVolume: 8,Pages:198–199Year published:(2011)DOI:doi:10.1038/nmeth0311-198bPublished online25 February 2011 Gene expression in bacteria can be modulated in response to unnatural amino acids with engineered transcriptional systems. View full text Subject terms: * Synthetic Biology Additional data Author Details * Erika Pastrana Search for this author in: * NPG journals * PubMed * Google Scholar - News in brief
- Nat Meth 8(3):199 (2011)
Nature Methods | Research Highlights News in brief Journal name:Nature MethodsVolume: 8,Page:199Year published:(2011)DOI:doi:10.1038/nmeth0311-199Published online25 February 2011 Read the full article * FREE access with registration Register now * Already have a Nature.com account? Login Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Advances in label-free chemical imaging Stimulated Raman scattering is a label-free biomedical imaging technique based on vibrational spectroscopy. In its original implementation, narrow-band laser beams had been used to excite a single Raman-active mode, but molecules with overlapping Raman bands could not be distinguished. Freudiger et al. now introduce spectrally tailored excitation-stimulated Raman scattering (STE-SRS) microscopy, which applies collective excitation of selected vibrational frequencies to allow specific molecules to be imaged, even when interfering species are present. Freudiger, C.W.et al. Nat. Photonics5, 103–109 (2011). View full text Read the full article * FREE access with registration Register now * Already have a Nature.com account? Login Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data - A day in the half-life of a protein
- Nat Meth 8(3):201 (2011)
Nature Methods | Research Highlights A day in the half-life of a protein * Allison DoerrJournal name:Nature MethodsVolume: 8,Page:201Year published:(2011)DOI:doi:10.1038/nmeth0311-201Published online25 February 2011 Researchers describe a method called bleach-chase to quantitatively measure the half-lives of fluorescently tagged proteins in human cancer cells. View full text Subject terms: * Proteomics Additional data Author Details * Allison Doerr Search for this author in: * NPG journals * PubMed * Google Scholar - Imaging impedance
- Nat Meth 8(3):202 (2011)
Nature Methods | Research Highlights Imaging impedance * Allison DoerrJournal name:Nature MethodsVolume: 8,Page:202Year published:(2011)DOI:doi:10.1038/nmeth0311-202Published online25 February 2011 A label-free microscopy technique based on electrochemical impedance offers a new way of studying electrochemical processes in single cells. View full text Subject terms: * Microscopy Additional data Author Details * Allison Doerr Search for this author in: * NPG journals * PubMed * Google Scholar - What makes flies and worms tick
- Nat Meth 8(3):204 (2011)
Nature Methods | Research Highlights What makes flies and worms tick * Nicole RuskJournal name:Nature MethodsVolume: 8,Page:204Year published:(2011)DOI:doi:10.1038/nmeth0311-204Published online25 February 2011 The comprehensive mapping of transcripts, histone modifications and transcription factor binding allows for the functional annotation of fly and worm genomes. View full text Subject terms: * Systems Biology Additional data Author Details * Nicole Rusk Search for this author in: * NPG journals * PubMed * Google Scholar - qPCR: quicker and easier but don't be sloppy
- Nat Meth 8(3):207-212 (2011)
Nature Methods | Technology Feature qPCR: quicker and easier but don't be sloppy * Monya Baker1Journal name:Nature MethodsVolume: 8,Pages:207–212Year published:(2011)DOI:doi:10.1038/nmeth0311-207Published online25 February 2011 Gene profiling using quantitative PCR is becoming higher throughput, but researchers must be careful in gathering their data. 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 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 - A triple threat to single molecules
- Nat Meth 8(3):213-215 (2011)
Nature Methods | News and Views A triple threat to single molecules * Martin Gruebele1Journal name:Nature MethodsVolume: 8,Pages:213–215Year published:(2011)DOI:doi:10.1038/nmeth0311-213Published online25 February 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Three single-molecule methods promise to increase the time resolution of experiments, to allow better access to sparsely populated molecular states and to permit combinatorial high-throughput analysis. 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 Affiliations * Martin Gruebele is in the Departments of Chemistry and Physics, and in the Center for Biophysics and Computational Biology, University of Illinois, Urbana, Illinois, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Martin Gruebele Author Details * Martin Gruebele Contact Martin Gruebele Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data - Double Brainbow
- Nat Meth 8(3):217-218 (2011)
Nature Methods | News and Views Double Brainbow * Sebastian Cachero1 * Gregory S X E Jefferis1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:217–218Year published:(2011)DOI:doi:10.1038/nmeth0311-217Published online25 February 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Brainbow is a powerful genetic tool for multicolor labeling in mice with applications in fields including developmental biology and neuroanatomy. Now two groups have ported the approach to the fruit fly where it may have even greater impact. 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 Affiliations * Sebastian Cachero and Gregory S.X.E. Jefferis are in the Division of Neurobiology, Medical Research Council Laboratory of Molecular Biology, Cambridge, UK. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Gregory S X E Jefferis Author Details * Sebastian Cachero Search for this author in: * NPG journals * PubMed * Google Scholar * Gregory S X E Jefferis Contact Gregory S X E Jefferis Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data - Neutral not a loss: phosphoinositides beyond the head group
- Nat Meth 8(3):219-220 (2011)
Nature Methods | News and Views Neutral not a loss: phosphoinositides beyond the head group * Matthias P Wymann1 * Markus R Wenk2 * Affiliations * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:219–220Year published:(2011)DOI:doi:10.1038/nmeth0311-219Published online25 February 2011 Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Detection of cellular PtdIns(3,4,5)P3 by combination of chemical derivatization and tandem mass spectroscopy has been demonstrated. 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 Affiliations * Matthias P. Wymann is at the Institute of Biochemistry and Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland. * Markus R. Wenk is in the Department of Biochemistry and Department of Biological Sciences, National University of Singapore, Singapore, and the Swiss Tropical and Public Health Institute, University of Basel, Basel, Switzerland. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Matthias P Wymann or * Markus R Wenk Author Details * Matthias P Wymann Contact Matthias P Wymann Search for this author in: * NPG journals * PubMed * Google Scholar * Markus R Wenk Contact Markus R Wenk Search for this author in: * NPG journals * PubMed * Google Scholar Read the full article * Instant access to this article: US$18Buy now * Subscribe to Nature Methods for full access: SubscribeLogin for existing subscribers Additional access options: * Use a document delivery service * Login via Athens * Purchase a site license * Institutional access * 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. Additional data - A primer to scaffolded DNA origami
- Nat Meth 8(3):221-229 (2011)
Nature Methods | Perspective A primer to scaffolded DNA origami * Carlos Ernesto Castro1 * Fabian Kilchherr1 * Do-Nyun Kim2 * Enrique Lin Shiao1 * Tobias Wauer1 * Philipp Wortmann1 * Mark Bathe2 * Hendrik Dietz1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:221–229Year published:(2011)DOI:doi:10.1038/nmeth.1570Published online25 February 2011 Abstract * Abstract * 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 Molecular self-assembly with scaffolded DNA origami enables building custom-shaped nanometer-scale objects with molecular weights in the megadalton regime. Here we provide a practical guide for design and assembly of scaffolded DNA origami objects. We also introduce a computational tool for predicting the structure of DNA origami objects and provide information on the conditions under which DNA origami objects can be expected to maintain their structure. View full text Subject terms: * Biochemistry * Synthetic Biology * Molecular Engineering * Biophysics Figures at a glance * Figure 1: Examples of objects built with scaffolded DNA origami. () Designs of single-layer DNA origami shapes (top) and AFM images of these objects (middle and bottom). The pointed star and the smiley face each have diameters of ~100 nm. Reprinted from ref. 1. () AFM image of crystalline DNA origami arrays formed from several hundred copies of a cross-shaped single-layer DNA origami object. Inset, image of a 100-nm-long cross-shaped origami monomer. Reprinted from ref. 18. () Container-like DNA origami objects (left) imaged with negative-stain TEM (top) and cryogenic TEM (bottom); reprinted from ref. 5 (top) and ref. 6 (bottom). () Design and images of multilayer DNA origami objects7. () Image of a multimeric multilayer DNA origami object with global twist deformation8. () Design and images of space-filling multilayer DNA origami objects such as bent bars () and a gear with square teeth () displaying custom curvature8. () Tensegrity prism created by combining multilayer DNA origami struts and ssDNA strings; reprinted from ref. 16. () Des! ign and image of a single-layer DNA origami shape with site-directed protein attachments; reprinted from ref. 19. Scale bars, 100 nm (), 1,000 nm () and 20 nm (). * Figure 2: The scaffolded DNA origami design concept. () In primitives of scaffolded DNA origami, DNA double helices are represented schematically either as two adjacent lines (left; the white line represents the scaffold strand in white and the staple strand in color) or solid cylinders (middle). A detailed rendering of a B-form double-helical domain is also shown (right). () Individual DNA double-helical domains may be connected to adjacent double-helical domains by interhelix cross-overs (arrows). The interhelix connections are formed by U-turns of the covalent phosphate backbone of either the staple or scaffold strand. Interhelix connections are depicted schematically as lines perpendicular to the lines that represent helices. In the cylinder representation, cross-overs are not drawn. () Examples of single- and multilayer scaffold routing solutions through DNA origami object. () Examples for complete scaffold-staple layouts, with staples colored differently to highlight their individual paths through the structures. () Sing! le- and multilayer DNA origami objects in cylinder representation. * Figure 3: Packing and cross-over spacing rules for multilayer DNA origami. () Cross-sectional view of multilayer DNA origami objects in square lattice (left) and honeycomb lattice (right) packing. () Cross-overs in multilayer objects with honeycomb lattice packing, spaced in constant intervals of 7 bp along the helical axis to link double-helical domains to each of three possible neighbors. The cross-over spacing of 7 bp complies with the natural B-form DNA twist density of 10.5 bp per turn, which corresponds to an average backbone rotation of 240° for a given strand in a DNA double-helical domain. * Figure 4: CanDo. () caDNAno design diagram for multilayer DNA origami objects in honeycomb lattice packing with deviations from the constant 7-bp cross-over spacing rule (left). Base-pair insertions and deletions are depicted as loops and crosses, respectively. CanDo 3D structure and local flexibility prediction shown as a heatmap that indicates local root-mean-square fluctuations (RMSFs) (middle). Representative negative-stain TEM micrographs (right). Scale bars, 20 nm. The objects shown in and form circular gears upon multimerization as described elsewhere8. The object shown in was made for this work; note the asymmetry in RMSF between the two 'shoulders' of the object, which can be mapped to an asymmetric distribution of cross-overs in the object design. () CanDo 3D structure and flexibility prediction for a caDNAno design of a tetrameric 60-helix bundle object in honeycomb lattice packing in which insertions are used to create an effective underwinding to 11 bp per turn for each double-h! elical domain in the object. The caDNAno design file is provided in Supplementary Figure 5. CanDo predicts handedness correctly and reproduces within 15% error the extent of global twist deformation as quantified by direct TEM imaging8. Typical TEM data for the twisted ribbon is shown in Fig. 1e. Rendering of a 50 bp long B-form DNA double helix is included as a length reference (50 bp = 17 nm). * Figure 5: Thermal stability and resistance against nucleases of three multilayer scaffolded DNA origami test structures. () Cylinder models of three multilayer DNA origami objects in honeycomb packing used for the stability screens. The object lengths are 140 nm (18-helix bundle), 100 nm (24-helix bundle) and 70 nm (32-helix bundle). The cross-section of a 400-nm-long six-helix bundle was also subjected to melting experiments. () Representative negative-stain TEM micrographs of the three test origami objects. Scale bars, 20 nm. () Melting profiles for a 6-, 18-, 24- and 32-helix bundles, and for a 20-nucleotide DNA duplex of sequence 5′-ATTCATATGGTTTACCAGCG-3′. () Representative single-particle negative-stain TEM micrographs taken after incubating the objects for 2 h at 37 °C, 55 °C and 65 °C. Scale bars, 20 nm. () Representative single-particle negative-stain TEM micrographs taken after incubating an 18-helix bundle (left), 24-helix bundle (middle) and 32-helix bundle (right) with 10 units (U) of T7 endonuclease I and 1 U of DNase I as indicated. () Photograph of a UV-irradiated ethidi! um bromide–stained 2% agarose gel run after incubating purified 32-helix bundles with exo- and endonucleases (10 U each) at 37 °C for 1 h. () Photograph of a UV-light-irradiated ethidium bromide–stained 2% agarose gel after incubating 2 ng of a 24-helix bundle (left) and 65 ng of a conventional double-stranded DNA plasmid (pET24b, right) with DNase I for indicated amounts of time. * Figure 6: Step-by-step guide through molecular self-assembly with scaffolded DNA origami. Step 1 involves conceiving a target shape for the intended application. Our robot shape was divided into three modules: body (red), arms (blue) and legs (orange). Step 2 covers designing a scaffold-staple layout for the target shape, evaluating the design and determining the set of staple sequences to build the design. Black vertical lines trace the scaffold strand (as in Fig. 2c,d), and colored lines indicate the staple paths. In step 3, scaffold DNA is prepared and staple oligonucleotide synthesis (typically in multiwell plates) is performed. Step 4 involves pooling staple oligonucleotides according to structural modules. In step 5 self-assembly reactions are prepared and subjected to a thermal annealing procedure. Step 6 covers an analysis of the overall folding quality by agarose gel electrophoresis, followed by purification of desired species. Shown is an example of increasing folding quality as evidenced by increasing migration speed of DNA origami folding products obs! erved for longer thermal annealing left to right: annealing from 80 °C to 20 °C in 2 h, 5 h, 10 h, 1 d, 5 d and 7 d as well as scaffold without staples as reference). In step 7 purified objects are subjected to single-particle structural analysis. Scale bar, 70 nm. Author information * Abstract * Author information * Supplementary information Affiliations * Center for Integrated Protein Science Munich, Physics Department and Walter Schottky Institut, Technische Universität München, Garching, Germany. * Carlos Ernesto Castro, * Fabian Kilchherr, * Enrique Lin Shiao, * Tobias Wauer, * Philipp Wortmann & * Hendrik Dietz * Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. * Do-Nyun Kim & * Mark Bathe Competing financial interests A patent has been filed on behalf of the Massachusetts Institute of Technology and Dana Farber Cancer Institute by Ditthavong Mori & Steiner, P.C. listing M.B., D.K. and H.D. as co-inventors of CanDo. Corresponding author Correspondence to: * Hendrik Dietz Author Details * Carlos Ernesto Castro Search for this author in: * NPG journals * PubMed * Google Scholar * Fabian Kilchherr Search for this author in: * NPG journals * PubMed * Google Scholar * Do-Nyun Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Enrique Lin Shiao Search for this author in: * NPG journals * PubMed * Google Scholar * Tobias Wauer Search for this author in: * NPG journals * PubMed * Google Scholar * Philipp Wortmann Search for this author in: * NPG journals * PubMed * Google Scholar * Mark Bathe Search for this author in: * NPG journals * PubMed * Google Scholar * Hendrik Dietz Contact Hendrik Dietz Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–5, Supplementary Protocols 1–5, Supplementary Notes 1–2, Supplementary Methods Additional data - A versatile in vivo system for directed dissection of gene expression patterns
- Nat Meth 8(3):231-237 (2011)
Nature Methods | Resource A versatile in vivo system for directed dissection of gene expression patterns * Daryl M Gohl1 * Marion A Silies1 * Xiaojing J Gao2 * Sheetal Bhalerao1 * Francisco J Luongo1 * Chun-Chieh Lin3 * Christopher J Potter3 * Thomas R Clandinin1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:231–237Year published:(2011)DOI:doi:10.1038/nmeth.1561Received19 November 2010Accepted17 December 2010Published online30 January 2011 Abstract * Abstract * Accession codes * 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 Tissue-specific gene expression using the upstream activating sequence (UAS)–GAL4 binary system has facilitated genetic dissection of many biological processes in Drosophila melanogaster. Refining GAL4 expression patterns or independently manipulating multiple cell populations using additional binary systems are common experimental goals. To simplify these processes, we developed a convertible genetic platform, the integrase swappable in vivo targeting element (InSITE) system. This approach allows GAL4 to be replaced with any other sequence, placing different genetic effectors under the control of the same regulatory elements. Using InSITE, GAL4 can be replaced with LexA or QF, allowing an expression pattern to be repurposed. GAL4 can also be replaced with GAL80 or split-GAL4 hemi-drivers, allowing intersectional approaches to refine expression patterns. The exchanges occur through efficient in vivo manipulations, making it possible to generate many swaps in parallel. This! system is modular, allowing future genetic tools to be easily incorporated into the existing framework. View full text Subject terms: * Genetics * Model Organisms * Neuroscience Figures at a glance * Figure 1: The InSITE system. () Schematic illustration of the InSITE system, which can be used to convert a GAL4 enhancer trap to another sequence, X, which will then be expressed under the control of local enhancers (En). P/T, P transposase promoter; PB, piggyBac transposon. () Schematic illustration of the procedure for genetically swapping GAL4 with sequence X. (–) Fluorescence images showing the results of an immunohistochemical analysis of InSITE enhancer trap expression in the adult brain: P element line P{IT.GAL4}A110.1 (), P element line P{IT.GAL4}A130.1 () and PiggyBac line PBac{IT.GAL4}5.1 (). Green, anti-mCD8; magenta, anti-Bruchpilot. Scale bars, 100 μm. () Schematic illustrating the insertion of the InSITE-compatible enhancer fusion vector, pBMPGal4LWL into a genomic attP site. * Figure 2: Molecular and genetic validation of the enhancer-trap exchange. (,) Results of PCR analyses () to confirm each step of the genetic conversion of line PBac{IT.GAL4}6.1 to the VP16AD hemi-driver, with amplicons numbered as in schematics in . Locations of PCR primers are shown under each construct. () Images of flies with P{ID.VP16AD}D37.1/+ (left) and y, w, eyFLP2; P{ID.VP16AD}D37.1/+ (right), showing that genetic donor constructs lose mini-white expression when crossed to eyFLP2. (–) Images of heat-shocked adult flies carrying the InSITE donor and recipient transgenes, as well as hs-FLP and vas-ΦC31 integrase transgenes. () y, w (yw), hs-FLP, vas-ΦC31; P{ID.VP16AD}D33.1/CyO; PBac{IT.GAL4.w-}3.1/+. () y, w, hs-FLP, vas-ΦC31; P{ID.VP16AD}D33.1/CyO; PBac{IT.GAL4.w–}6.1/+. () mini-white expression in w; PBac{IS.VP16AD.GAL4}6.1/+ (top right), w; PBac{IS.VP16AD.w-}6.1/+, (bottom) and y, w, eyFLP2; PBac{IS.VP16AD.GAL4}6.1/+ (top left) flies. Scale bars, 100 μm. () Sequence of the PCR product of primer pair 5, including the loxP, FRT and ! attL sites. * Figure 3: Functional validation of the QF and LexA enhancer trap swaps. (–) Expression of the PBac{IT.GAL4.w–}6.1 enhancer trap. (,) Expression of the PBac{IT.GAL4}1.1 enhancer trap. (,) Expression of the PBac{IS.QF.w–}6.1 swap. () Expression of the PBac{IS.LexA.w–}1.1 swap. GFP fluorescence (,) in adult antennae (arrowheads) and maxillary palps (arrows). Adult brains immunostained with anti-mCD8 (green) and anti-Bruchpilot (magenta) () or with anti-GFP (green) and anti-Bruchpilot (magenta) (). mCD8 (green) channel only for images in and is shown in and , and GFP (green) channel only for images in and is shown in and . Asterisks denote a group of cells in which GFP expression was observed in PBac{IT.GAL4}1.1 but not in the PBac{IS.LexA.w–}1.1 swap. Scale bars, 100 μm (,), 50 μm (–,–). * Figure 4: Functional validation of the split-GAL4 and GAL80 enhancer trap swaps. (–) GFP expression in the antennae (arrowheads) of adult flies of the indicated lines. (–) Adult brains immunostained with anti-mCD8 (green) and anti-Bruchpilot (magenta). (–) mCD8 (green) channel only of images in –. (–) Adult brains immunostained with anti-mCD8 (green) and anti-Bruchpilot (magenta). (–) mCD8 (green) channel only of images in –. Asterisks denote a small number of central brain neurons not targeted by the split-GAL4 or GAL80 swaps. Scale bars, 100 μm (–) and 50 μm (–). Accession codes * Abstract * Accession codes * Author information * Supplementary information Referenced accessions Entrez Nucleotide * HQ888842 * HQ888843 * HQ888844 * HQ888845 * HQ888846 Author information * Abstract * Accession codes * Author information * Supplementary information Affiliations * Department of Neurobiology, Stanford University, Stanford, California, USA. * Daryl M Gohl, * Marion A Silies, * Sheetal Bhalerao, * Francisco J Luongo & * Thomas R Clandinin * Department of Biological Sciences, Stanford University, Stanford, California, USA. * Xiaojing J Gao * Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. * Chun-Chieh Lin & * Christopher J Potter Contributions D.M.G. and T.R.C. designed the experiments; D.M.G., M.A.S., X.J.G., F.J.L., C.-C.L., C.J.P. and T.R.C. performed the experiments; S.B. provided critical reagents; and D.M.G. and T.R.C. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Thomas R Clandinin Author Details * Daryl M Gohl Search for this author in: * NPG journals * PubMed * Google Scholar * Marion A Silies Search for this author in: * NPG journals * PubMed * Google Scholar * Xiaojing J Gao Search for this author in: * NPG journals * PubMed * Google Scholar * Sheetal Bhalerao Search for this author in: * NPG journals * PubMed * Google Scholar * Francisco J Luongo Search for this author in: * NPG journals * PubMed * Google Scholar * Chun-Chieh Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Christopher J Potter Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas R Clandinin Contact Thomas R Clandinin 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 (6M) Supplementary Figures 1–8 and Supplementary Tables 1–3 Additional data - Visualizing a one-way protein encounter complex by ultrafast single-molecule mixing
- Nat Meth 8(3):239-241 (2011)
Nature Methods | Brief Communication Visualizing a one-way protein encounter complex by ultrafast single-molecule mixing * Yann Gambin1, 3 * Virginia VanDelinder2, 3, 4 * Allan Chris M Ferreon1, 4 * Edward A Lemke1, 3 * Alex Groisman2 * Ashok A Deniz1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:239–241Year published:(2011)DOI:doi:10.1038/nmeth.1568Received09 September 2010Accepted14 January 2010Published online06 February 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We combined rapid microfluidic mixing with single-molecule fluorescence resonance energy transfer to study the folding kinetics of the intrinsically disordered human protein α-synuclein. The time-resolution of 0.2 ms revealed initial collapse of the unfolded protein induced by binding with lipid mimics and subsequent rapid formation of transient structures in the encounter complex. The method also enabled analysis of rapid dissociation and unfolding of weakly bound complexes triggered by massive dilution. View full text Subject terms: * Biophysics * Single Molecule * Lab-on-a-chip * Structural Biology Figures at a glance * Figure 1: Microfluidic setup for kinetic smFRET measurements. () After passing through a mixing region, the protein stream and two buffer streams (fed from three separate inlets) are directed to three outlets, which are connected to separate reservoirs, whose heights are adjusted to tune mixing and dilution. () Diagram of the device showing inlets and outlets. () Micrograph of the functional region with a fluorescent solution fed to the protein inlet. Arrows indicate buffer flow (blue), protein flow before mixing (yellow) and protein flow in mixing and detection regions (red). Scale bar, 25 μm. () Flow velocity as measured with fluorescence correlation spectroscopy and time after mixing or dilution, both as functions of the position along the channel in the deceleration region; dashed line is from three-dimensional flow simulations (Comsol). () Flow velocity (as in ) in the focusing, mixing and deceleration regions. () Flow diagram illustrating how the protein stream is squeezed horizontally by two buffer streams for medium exchange a! nd then directed to the smFRET detection region. () Simulations of flow velocities and streamlines in two device regions highlighted in insets. * Figure 2: Folding and unfolding of α-synuclein. (,) Histograms of EFRET for the folding () and unfolding () reactions, obtained at different time points, are used to generate a three-dimensional histogram (~50,000 events) in coordinates of time and EFRET, with the percentage of total events color-coded as indicated. () Representative EFRET histograms for various states: intrinsically disordered (U state, EFRET≈ 0.42, obtained before mixing), collapsed unfolded (U* state, EFRET≈ 0.6, 490 μs after mixing), intermediate (I state, EFRET≈ 0.8, 1.2 ms after mixing) and extended structures (F state, EFRET≈ 0.1, >10 ms after mixing). () Model of the α-synuclein conformational transitions; the mirror representation emphasizes the asymmetry between the folding and unfolding pathways. Shown are random coil (brown), α-helix (turquoise), as well as donor (green sphere) and acceptor (purple sphere) dye molecules. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Virginia VanDelinder & * Allan Chris M Ferreon Affiliations * Department of Molecular Biology, The Scripps Research Institute, La Jolla, California, USA. * Yann Gambin, * Allan Chris M Ferreon, * Edward A Lemke & * Ashok A Deniz * Department of Physics, University of California San Diego, San Diego, California, USA. * Virginia VanDelinder & * Alex Groisman * Present addresses: Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia (Y.G.) and Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany (V.V. and E.A.L.). * Yann Gambin, * Virginia VanDelinder & * Edward A Lemke Contributions Y.G., A.G. and A.A.D. designed research; Y.G. performed smFRET experiments; Y.G. and V.V. characterized the device; A.C.M.F. provided α-synuclein expertise and samples; E.A.L. provided instrumentation support; and all authors contributed to writing the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Yann Gambin or * Alex Groisman or * Ashok A Deniz Author Details * Yann Gambin Contact Yann Gambin Search for this author in: * NPG journals * PubMed * Google Scholar * Virginia VanDelinder Search for this author in: * NPG journals * PubMed * Google Scholar * Allan Chris M Ferreon Search for this author in: * NPG journals * PubMed * Google Scholar * Edward A Lemke Search for this author in: * NPG journals * PubMed * Google Scholar * Alex Groisman Contact Alex Groisman Search for this author in: * NPG journals * PubMed * Google Scholar * Ashok A Deniz Contact Ashok A Deniz Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–23 and Supplementary Note 1 Additional data - High-throughput single-molecule optofluidic analysis
- Nat Meth 8(3):242-245 (2011)
Nature Methods | Brief Communication High-throughput single-molecule optofluidic analysis * Soohong Kim1, 8 * Aaron M Streets2, 8 * Ron R Lin1 * Stephen R Quake2, 3, 4 * Shimon Weiss1, 5, 6 * Devdoot S Majumdar1, 7 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:242–245Year published:(2011)DOI:doi:10.1038/nmeth.1569Received09 July 2010Accepted12 January 2011Published online06 February 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We describe a high-throughput, automated single-molecule measurement system, equipped with microfluidics. The microfluidic mixing device has integrated valves and pumps to accurately accomplish titration of biomolecules with picoliter resolution. We demonstrate that the approach enabled rapid sampling of biomolecule conformational landscape and of enzymatic activity, in the form of transcription by Escherichia coli RNA polymerase, as a function of the chemical environment. View full text Subject terms: * Single Molecule * Lab-on-a-chip * Structural Biology * Biophysics Figures at a glance * Figure 1: A microfluidic formulator for high-throughput single-molecule FRET measurements. () Device image (left) with the mixing ring highlighted (arrow). Scale bar, 5 mm. The schematic (right) depicts critical features of the control and flow layer (control and flow channels). () A schematic plot representing smFRET measurements as a two-dimensional histogram of FRET versus stoichiometry. The subpopulations of interest are hybridized poly(dT) (low FRET population; dsDNA) and unhybridized poly(dT) (high FRET population; ssDNA). () Heat map of hybridization efficiency (ratio of dsDNA to total DNA) for various concentrations of NaCl and complementary strand. () Matrix of FRET-stoichiometry scatter plots with contour overlay of fits used to generate heat map shown in . * Figure 2: RNAP activity measured with smFRET. () A schematic of the assay depicts RNAP transcribing the template, thus producing complementary transcript that hybridizes to the poly(dT) probe. () A matrix of FRET-stoichiometry scatter plots (as in Fig. 1) depicting hybridization of the poly(dT) probe to newly produced transcript upon titrating RNAP and glutamate. () Heat map showing quantification of the data in . Amount of transcript is plotted for various concentrations of RNAP and glutamate. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Soohong Kim & * Aaron M Streets Affiliations * Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, California, USA. * Soohong Kim, * Ron R Lin, * Shimon Weiss & * Devdoot S Majumdar * Department of Applied Physics, Stanford University, Stanford, California, USA. * Aaron M Streets & * Stephen R Quake * Department of Bioengineering, Stanford University, Stanford, California, USA. * Stephen R Quake * Howard Hughes Medical Institute, Stanford, California, USA. * Stephen R Quake * Department of Physiology, University of California, Los Angeles, Los Angeles, California, USA. * Shimon Weiss * California NanoSystems Institute, University of California, Los Angeles, Los Angeles, California, USA. * Shimon Weiss * Present address: Division of Biology, California Institute of Technology, Pasadena, California, USA. * Devdoot S Majumdar Contributions S.K., A.M.S. and D.S.M. designed experiments, conducted experiments, wrote and implemented data acquisition and analysis software, and analyzed data. R.R.L. analyzed data. S.K., A.M.S., S.R.Q., S.W. and D.S.M. assisted in writing and editing of the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Devdoot S Majumdar or * Shimon Weiss Author Details * Soohong Kim Search for this author in: * NPG journals * PubMed * Google Scholar * Aaron M Streets Search for this author in: * NPG journals * PubMed * Google Scholar * Ron R Lin Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen R Quake Search for this author in: * NPG journals * PubMed * Google Scholar * Shimon Weiss Contact Shimon Weiss Search for this author in: * NPG journals * PubMed * Google Scholar * Devdoot S Majumdar Contact Devdoot S Majumdar Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information Zip files * Supplementary Software (116M) Software used in this study to control and coordinate microfluidics and optical components. PDF files * Supplementary Text and Figures (942K) Supplementary Figures 1–10, Supplementary Note 1, Supplementary Table 1 Additional data - Micropilot: automation of fluorescence microscopy–based imaging for systems biology
- Nat Meth 8(3):246-249 (2011)
Nature Methods | Brief Communication Micropilot: automation of fluorescence microscopy–based imaging for systems biology * Christian Conrad1 * Annelie Wünsche2 * Tze Heng Tan2 * Jutta Bulkescher1 * Frank Sieckmann3 * Fatima Verissimo2 * Arthur Edelstein4 * Thomas Walter2 * Urban Liebel2, 5 * Rainer Pepperkok1, 2 * Jan Ellenberg2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:246–249Year published:(2011)DOI:doi:10.1038/nmeth.1558Received26 May 2010Accepted06 December 2010Published online23 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Quantitative microscopy relies on imaging of large cell numbers but is often hampered by time-consuming manual selection of specific cells. The 'Micropilot' software automatically detects cells of interest and launches complex imaging experiments including three-dimensional multicolor time-lapse or fluorescence recovery after photobleaching in live cells. In three independent experimental setups this allowed us to statistically analyze biological processes in detail and is thus a powerful tool for systems biology. View full text Subject terms: * Cell Biology * Microscopy * Imaging * Systems Biology Figures at a glance * Figure 1: Schematic workflow of Micropilot. () After autofocussing different positions to find the best focal plane (yellow frame), low-resolution prescan images (optionally maximum z-dimension projections, gray frames) are presented to the automatic classification. If a cell is selected, a complex imaging protocol is executed; otherwise the system continues to prescan. After completion of the complex imaging protocol, the system loops back to prescan mode, continuing at the sample position where it stopped for the complex imaging mode. () Communication steps executed by the different microscope systems (red outlines) and the Micropilot software (blue outlines). The microscope sends the image path either via windows registry or socket interface to Micropilot. In the synchronous modes, each positive classification launches the complex imaging mode. In the asynchronous mode, microscope and Micropilot send and receive messages via transmission control protocol or internet protocol (TCP/IP), allowing classification of sev! eral different positions before launching the complex imaging protocol for a list of positions. () After reading the low-resolution image, Micropilot segments, extracts the feature set per object and classifies the cells during scanning to return eventually the positions of interest. After the criteria are met (time or number of positions) Micropilot deploys the complex imaging and the microscope switches back to prescan mode (). * Figure 2: Assays of SEC31 and H2B-tubulin HeLa cells. () Examples for Hoechst-labeled (blue; DNA label) and SEC31-labeled (green) cells representing null or artifact and anaphase or telophase cells (insets, close-up images). Scale bars, 10 μm. () Confusion matrix of the prediction shows true positives (TP) horizontally against the predicted class vertically for cells. At edges the total numbers of the cells are given (overall total, 10,793 cells) corresponding to PPV = TP / (TP + false positives) and sensitivity = TP / (TP + false negatives). () Examples of null or artifact (left) and anaphase or telophase (right) cells stained with Hoechst (blue) and ERES spot (green) (50 slices of 0.2 μm). Scale bar, 10 μm. () Number of ERES spots of 91 anaphase cells to late-telophase cells plotted versus volume of nuclei, with exponential fit plotted. Red and blue data points correspond to the nuclei in the left and right images in , respectively. () Example of negative control experiment (time resolution, 3 min; 30 slices of 1 μm; maxi! mum projections) started after prophase recognition. Times indicated are after prophase recognition. Scale bar, 10 μm.() Spindle lengths after treatment with scrambled siRNA. () Example images after treatment with siRNA to CENPE, showing centrosome poles (arrows; left) for the first recognizable metaphase (acquisition as in ). Scale bar, 10 μm. () Normal mixture modeling of pole-pole distances in metaphase from 71 movies after treatment with siRNA to CENPE resulted in three distributions, which are shown as colored curves. * Figure 3: Examples and measurements of automatic FRAP on CBX1-EGFP cells. () After the automatic selection of an interphase or prophase cell with a trained prophase SVM classifier, a prebleached image was taken, followed by bleaching of the predefined upper half of the nucleus and subsequent time-lapse imaging with 2-s time resolution for 60 s (values in the lower images indicate time relative to bleaching). Scale bar, 5 μm. () Normalized intensities for CBX1-EGFP measured during fluorescence relaxation after photobleaching in interphase and prophase cells. We measured, normalized, averaged and plotted over time fluorescence intensities in the bleached region of the nucleus. Error bars, s.d. () Recovery rates as box plots for interphase and prophase cell populations. Author information * Author information * Supplementary information Affiliations * Advanced Light Microscopy Facility, European Molecular Biology Laboratory, Heidelberg, Germany. * Christian Conrad, * Jutta Bulkescher & * Rainer Pepperkok * Cell Biology and Biophysics Unit, European Molecular Biology Laboratory, Heidelberg, Germany. * Annelie Wünsche, * Tze Heng Tan, * Fatima Verissimo, * Thomas Walter, * Urban Liebel, * Rainer Pepperkok & * Jan Ellenberg * Leica Microsystems GmbH, Mannheim, Germany. * Frank Sieckmann * Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA. * Arthur Edelstein * Present address: Institute of Toxicology and Genetics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany. * Urban Liebel Contributions C.C. developed the 'Micropilot' software and drafted the manuscript. A.W. developed the Visual Basic for Applications macro and performed and analyzed the automatic FRAP experiments. T.H.T. developed the feature selection, extended classification to multiple channels and acquired and analyzed the ERES images. F.V. performed the ERES experiments. J.B. performed and analyzed the spindle length experiments. F.S. and U.L. developed the computer-aided microscopy interface and set up software prototypes. A.E. developed the communication of μManager with Micropilot. T.W. helped with image processing and object feature design. R.P. supervised the project. J.E. supervised the project and revised the manuscript. Competing financial interests F.S and U.L. filed a patent application covering the CAM approach (Patent Cooperation Treaty/European Patent 2007/059351/US patent application 20100103253). F.S. is employed by Leica Microsystems. Corresponding authors Correspondence to: * Rainer Pepperkok or * Jan Ellenberg Author Details * Christian Conrad Search for this author in: * NPG journals * PubMed * Google Scholar * Annelie Wünsche Search for this author in: * NPG journals * PubMed * Google Scholar * Tze Heng Tan Search for this author in: * NPG journals * PubMed * Google Scholar * Jutta Bulkescher Search for this author in: * NPG journals * PubMed * Google Scholar * Frank Sieckmann Search for this author in: * NPG journals * PubMed * Google Scholar * Fatima Verissimo Search for this author in: * NPG journals * PubMed * Google Scholar * Arthur Edelstein Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Walter Search for this author in: * NPG journals * PubMed * Google Scholar * Urban Liebel Search for this author in: * NPG journals * PubMed * Google Scholar * Rainer Pepperkok Contact Rainer Pepperkok Search for this author in: * NPG journals * PubMed * Google Scholar * Jan Ellenberg Contact Jan Ellenberg Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information Movies * Supplementary Video 1 (1M) Example video of H2B-tubulin HeLa cells negative control from prophase recognition on. * Supplementary Video 2 (3M) Example video of FRAP on CBX1-EGFP interphase. * Supplementary Video 3 (4M) Example video of FRAP on CBX1-EGFP early prophase (slow recovery). * Supplementary Video 4 (5M) Example video of FRAP on CBX1-EGFP late prophase (fast recovery). Zip files * Supplementary Software (38M) Micropilot software source code, documentation, microscope scripts and demonstration images. PDF files * Supplementary Text and Figures (328K) Supplementary Figures 1–3 and Supplementary Table 1 Additional data - Codon adaptation–based control of protein expression in C. elegans
- Nat Meth 8(3):250-252 (2011)
Nature Methods | Brief Communication Codon adaptation–based control of protein expression in C. elegans * Stefanie Redemann1 * Siegfried Schloissnig2 * Susanne Ernst1 * Andrey Pozniakowsky1 * Swathi Ayloo1 * Antony A Hyman1 * Henrik Bringmann3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:250–252Year published:(2011)DOI:doi:10.1038/nmeth.1565Received28 September 2010Accepted17 December 2010Published online30 January 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We present a method to control protein levels under native genetic regulation in Caenorhabditis elegans by using synthetic genes with adapted codons. We found that the force acting on the spindle in C. elegans embryos was related to the amount of the G-protein regulator GPR-1/2. Codon-adapted versions of any C. elegans gene can be designed using our web tool, C. elegans codon adapter. View full text Subject terms: * Cell Biology * Gene Expression * Synthetic Biology Figures at a glance * Figure 1: Codon-adaptation of the gpr-1 gene determines the amount of YFP–GPR-1 protein. () Fluorescence images showing localization of YFP–GPR-1 expressed from the indicated constructs in embryos at early anaphase. Images were acquired using different imaging conditions, and different contrast was used to display localization patterns. Scale bar, 10 μm. () Mean YFP fluorescence intensity over the surface of the embryo expressing the indicated constructs. yfp::gpr-1(endogenous, CAI 0.3), 28 ± 13 arbitrary units (mean ± s.d.; n = 6 embryos); yfp::gpr-1(synthetic, CAI 0.3), 12 ± 3 arbitrary units (n = 6 embryos); yfp::gpr-1(synthetic, CAI 0.6), 75 ± 22 arbitrary units (n = 6 embryos); and yfp::gpr-1(synthetic, CAI 1.0), 202 ± 34 arbitrary units (n = 6 embryos). N2, wild type expressing no transgene, 0 ± 5 arbitrary units (n = 6 embryos). * Figure 2: Increasing GPR-1 amounts causes an increase in force acting on the mitotic spindle. () Time-lapse images of an embryo expressing yfp::gpr-1(synthetic, CAI 1.0) throughout the first cell division. Scale bar, 10 μm. () Histogram of centrosomal velocity after spindle cut by a UV light laser and spindle break (n = 5 embryos for all three strains; error bars, s.d.). Author information * Author information * Supplementary information Affiliations * Max Planck Institute of Molecular Cell Biology and Genetics, Dresden Germany. * Stefanie Redemann, * Susanne Ernst, * Andrey Pozniakowsky, * Swathi Ayloo & * Antony A Hyman * European Molecular Biology Laboratory Heidelberg, Heidelberg, Germany. * Siegfried Schloissnig * Max Planck Institute for Biophysical Chemistry, Göttingen, Germany. * Henrik Bringmann Contributions S.R. characterized all strains. S.S. wrote the web tool algorithm and analyzed genome-wide CAI. S.E. bombarded all constructs. A.P. cloned constructs. S.A. filmed embryos. A.A.H. mentored and financed the project. S.R., A.A.H. and H.B. wrote the paper. H.B. conceived the general synthetic gene design, cloned gpr-1 constructs and preliminarily characterized gpr-1 strains. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Henrik Bringmann Author Details * Stefanie Redemann Search for this author in: * NPG journals * PubMed * Google Scholar * Siegfried Schloissnig Search for this author in: * NPG journals * PubMed * Google Scholar * Susanne Ernst Search for this author in: * NPG journals * PubMed * Google Scholar * Andrey Pozniakowsky Search for this author in: * NPG journals * PubMed * Google Scholar * Swathi Ayloo Search for this author in: * NPG journals * PubMed * Google Scholar * Antony A Hyman Search for this author in: * NPG journals * PubMed * Google Scholar * Henrik Bringmann Contact Henrik Bringmann Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–8 and Supplementary Table 1 Additional data - Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns
- Nat Meth 8(3):253-259 (2011)
Nature Methods | Article Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns * Stefanie Hampel1, 2 * Phuong Chung1, 2 * Claire E McKellar1 * Donald Hall1 * Loren L Looger1 * Julie H Simpson1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:253–259Year published:(2011)DOI:doi:10.1038/nmeth.1566Received19 August 2010Accepted20 December 2010Published online06 February 2011Corrected online16 February 2011 Abstract * Abstract * Accession codes * Change history * 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 We developed a multicolor neuron labeling technique in Drosophila melanogaster that combines the power to specifically target different neural populations with the label diversity provided by stochastic color choice. This adaptation of vertebrate Brainbow uses recombination to select one of three epitope-tagged proteins detectable by immunofluorescence. Two copies of this construct yield six bright, separable colors. We used Drosophila Brainbow to study the innervation patterns of multiple antennal lobe projection neuron lineages in the same preparation and to observe the relative trajectories of individual aminergic neurons. Nerve bundles, and even individual neurites hundreds of micrometers long, can be followed with definitive color labeling. We traced motor neurons in the subesophageal ganglion and correlated them to neuromuscular junctions to identify their specific proboscis muscle targets. The ability to independently visualize multiple lineage or neuron projections i! n the same preparation greatly advances the goal of mapping how neurons connect into circuits. View full text Subject terms: * Neuroscience * Imaging * Genetics Figures at a glance * Figure 1: Schematic of the dBrainbow construct. UAS-dBrainbow contains a UAS that allows its expression to be cell-specifically controlled by the presence of GAL4. Cre recombination occurs only between matched lox sites. The selection of lox site recombination in a given cell is stochastic. In the absence of recombinase, no fluorescent proteins are made because of a stop cassette with three-frame translation terminators and an SV40 polyadenylation signal. Recombination between lox2272 sites removes this stop cassette and permits expression of EGFP-V5; recombination between the lox5171 sites results in expression of EBFP2-HA; and recombination between loxP sites produces mKO2-Myc. Cre-mediated recombination is irreversible. Colors from one or two copies of UAS-dBrainbow are shown on the right. All fluorescent proteins are cytoplasmic and epitope-tagged as indicated. * Figure 2: Comparison of endogenous and antibody-based fluorescence of UAS-dBrainbow flies. (–) Projections of two 1-μm slices through the antennal lobes from adult brains of hs-Cre; GH146-GAL4; UAS-dBrainbow flies, imaged without fixation. Merged image () reveals endogenous fluorescence of EGFP (green), mKO2 (red) and EBFP2 (blue; arrow); there is some bleed-through into the GFP channel. Raw grayscale images show mKO2 (), EGFP () and EBFP2 () fluorescence; laser wavelengths are indicated in the images. (–) Flies of the same genotype were fixed and stained with primary antibodies to GFP (α-GFP), Myc (α-Myc) and HA (α-HA), and secondary antibodies coupled to Alexa Fluors 488, 568 and 633, respectively. Merged image () shows all three colors and individual images (–) show spectral separation of Alexa Fluor dyes and lack of antibody cross-reactivity. (–) Maximum intensity projections of 20× confocal stacks for whole brains labeled with the nc82 antibody as a neuropil marker (gray), with antibodies to GFP (green) and HA (blue), and showing mKO2 endogenous ! fluorescence (red). Merged image (), EGFP, mKO2 and EBFP signals alone (), and nc82 signal alone () are shown. Scale bars, 50 μm. * Figure 3: Expression of UAS-dBrainbow in three projection neuron lineages. (–) Single (–) and double (–) copies of UAS-dBrainbow were used along with hs-Cre; GH146-GAL4 to label the three projection neuron lineages that express GH146-GAL4 (adPN, lPN and vPN) as well as the axon tracts (iACT and mACT) that connect the projection neuron cell bodies to the lateral horn (LH) () and calyx (ca) (,–). Shown are maximum intensity projections of several 1-μm confocal sections (–) with each projection neuron lineage expressing a different fluorescent protein–epitope cassette and thus pseudocolored differently (arrowheads; ). The number and depth of confocal slices used to produce the merged images are indicated. In the right lPN lineage (arrowhead; ), recombination in the neuroblast occurred to select blue in one copy of UAS-dBrainbow but the recombinase did not act on the second copy until later to select green, so a subset of later-born neurons is labeled in cyan. In , the antennal lobe (AL) and efferent neurons projecting to the lateral horn ! via the mACT and iACT; individual neurites can also be traced from the antennal lobe to the lateral horn via an alternative pathway (arrows). Higher-magnification views of the lateral horn from different orientations (,–). Scale bars, 50 μm (–,) and 20 μm (,–). * Figure 4: dBrainbow labeling of lineages or individual neurons in different colors. (–) Maximum intensity projections of confocal stacks of OK107-GAL4 (–) and Tdc2-GAL4 (–) with UAS-dBrainbow and hs-Cre shown as merged images (,) and grayscale red (,) green (,) and blue (,) channels, with the imaged wavelengths indicated (blue was used to represent the Alexa Fluor 633). Arrows and arrowheads trace individual ventral unpaired medial (VUM) neurons (–). ASM, anterior superior medial protocerebrum and AL2, anterior lateral cluster 2. Arrowhead in indicates gamma lobe of the mushroom body. (–) Three 35-μm substacks of hs-Cre; UAS-dBrainbow; UAS-dBrainbow, FruM-GAL4 divide the ~2,000 neurons labeled by FruM-GAL4 into many subpopulations, demarcated by different colors. Arrowhead in indicates the pars intercerebrales. Scale bars, 50 μm. * Figure 5: Expression of UAS-dBrainbow in motor neurons that connect the subesophageal ganglion to the proboscis muscles in sections of a single example of an hs-cre; UAS-dBrainbow; R12D05-GAL4 fly. () Maximum projection confocal stack showing a cluster of several cell types in the subesophageal ganglion. () Frontal and lateral schematics of a fly head with proboscis extended, showing brain in gray and subesophageal ganglion (SOG) in darker gray. Two motor neuron types (D and V-L pairs) project to neuromuscular junctions on proboscis muscles. Proboscis was dissected separately (dashed lines) to allow antibody penetration. () Confocal substack showing dorsal motor neurons in red and green (arrowheads) that send axons out the pharyngeal nerve (arrow). Neurites in the middle do not belong to these neurons as they are labeled in blue and green. () Confocal substack showing a pair of ventrolateral neurons with C-shaped arbors in the SOG in blue and red (arrowheads). Axons exit via labial nerves (arrows). () Confocal substack of the rostrum, lateral view, as shown in the inset. The red and green axons travel through the proboscis together (arrows), to terminate at neuromuscul! ar junctions near the distal end of the rostrum (arrowheads). Background was caused by autofluorescence of intact cuticle. (,) Blue and red axons terminate in neuromuscular junctions on the transverse muscles in the distal end of the haustellum. Substacks at different levels show faint blue () and bright red () terminals (arrowheads). At higher gain (), autofluorescence in the blue channel also shows the muscle fibers of the haustellum: longitudinal muscles (vertical fibers in the image) and transverse muscles (horizontal). Scale bars, 50 μm. Accession codes * Abstract * Accession codes * Change history * Author information * Supplementary information Referenced accessions Entrez Nucleotide * JF267350 Change history * Abstract * Accession codes * Change history * Author information * Supplementary informationCorrigendum 16 February 2011In the version of this article initially published online, accession codes were not included. 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. * Stefanie Hampel & * Phuong Chung Affiliations * Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. * Stefanie Hampel, * Phuong Chung, * Claire E McKellar, * Donald Hall, * Loren L Looger & * Julie H Simpson Contributions S.H. designed and performed cloning, tested constructs in S2 cells and made the figures. P.C. performed the fly genetics, immunohistochemistry and confocal imaging. C.E.M. generated and analyzed the subesophageal ganglion and proboscis data. D.H. generated the recombinant fly stocks. L.L.L. advised on selection of fluorescent proteins, construct design and the conversion from endogenous fluorescence to antibody. J.H.S. conceived the project, cloned initial test constructs and wrote the paper with help from S.H., P.C., C.E.M. and L.L.L. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Julie H Simpson Author Details * Stefanie Hampel Search for this author in: * NPG journals * PubMed * Google Scholar * Phuong Chung Search for this author in: * NPG journals * PubMed * Google Scholar * Claire E McKellar Search for this author in: * NPG journals * PubMed * Google Scholar * Donald Hall Search for this author in: * NPG journals * PubMed * Google Scholar * Loren L Looger Search for this author in: * NPG journals * PubMed * Google Scholar * Julie H Simpson Contact Julie H Simpson 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 1–4 and Supplementary Tables 1–4 Additional data - Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster
- Nat Meth 8(3):260-266 (2011)
Nature Methods | Article Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster * Dafni Hadjieconomou1 * Shay Rotkopf2, 5 * Cyrille Alexandre3 * Donald M Bell4 * Barry J Dickson2 * Iris Salecker1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:260–266Year published:(2011)DOI:doi:10.1038/nmeth.1567Received28 October 2010Accepted28 December 2010Published online06 February 2011Corrected online16 February 2011 Abstract * Abstract * Accession codes * Change history * 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 To facilitate studies of neural network architecture and formation, we generated three Drosophila melanogaster variants of the mouse Brainbow-2 system, called Flybow. Sequences encoding different membrane-tethered fluorescent proteins were arranged in pairs within cassettes flanked by recombination sites. Flybow combines the Gal4-upstream activating sequence binary system to regulate transgene expression and an inducible modified Flp-FRT system to drive inversions and excisions of cassettes. This provides spatial and temporal control over the stochastic expression of one of two or four reporters within one sample. Using the visual system, the embryonic nervous system and the wing imaginal disc, we show that Flybow in conjunction with specific Gal4 drivers can be used to visualize cell morphology with high resolution. Finally, we demonstrate that this labeling approach is compatible with available Flp-FRT-based techniques, such as mosaic analysis with a repressible cell marke! r; this could further support the genetic analysis of neural circuit assembly and function. View full text Subject terms: * Neuroscience * Genetics * Model Organisms * Imaging Figures at a glance * Figure 1: Schematic of Flybow variants. (–) Pairs of fluorescent protein–encoding cDNAs are arranged in opposing orientations and flanked by mFRT71 sites (black arrowheads). Fluorescent proteins are membrane-tethered either by a Cd8a (cd8) or the palm-myr (pm) sequence of Lyn kinase. Fluorescent protein sequences are followed by SV40 and hsp70Ab polyadenylation (pA) signals. Constructs were subcloned into a modified pKC26 UAS vector, which contains ten UAS (10xUAS) sites and a short attB recognition sequence. mFlp5 under the control of the heat-shock promoter (hs-mFlp5) induces inversions of DNA cassettes by recombining mFRT71 sites in opposing orientations, or excisions (Flp-out) by recombining mFRT71 sites placed in the same orientation. FB1.0 () consists of one invertible cassette encoding two fluorescent proteins (mCherry and Cerulean-V5). FB1.1 () contains two invertible cassettes, each encoding two fluorescent proteins (EGFP and mCitrine; mCherry and Cerulean-V5). FB2.0 () contains an additional stop cas! sette, flanked by canonical FRT sites (white arrowheads) facing in the same orientation, which can be excised by wild-type Flp. The stop cassette consists of lamin cDNA, followed by two HA tag sequences and hsp70Aa and hsp27 polyadenylation signals. * Figure 2: Activity of FB1.0 and FB1.1 transgenes. (,) Schematic of the third instar larval (3L) () and adult visual system (). Shown are R1–R8 photoreceptor axons, lamina neurons (ln) L1–L5, and the medulla neuron (mn) and lobula neuron and lobula plate neuron subtypes Tm, TmY, Dm and T, which are main target neuron subtype classes. Glial subtypes include epithelial glia (eg), marginal glia (mg), medulla glia (meg) and medulla neuropil glia (mng)15. GMC, ganglion mother cell; LPC, lamina precursor cells; MF, morphogenetic furrow; Nb, neuroblasts; and OPC, outer proliferation center. () Schematic showing that FB1.0 enables expression of Cerulean-V5 instead of mCherry in a Gal4-expressing cell population upon heat-shock induction of mFlp5. (,) Confocal images of a larval eye disc () and optic lobe () with some R cells and lamina neurons expressing Cerulean-V5. la, lamina; me, medulla. () Schematic showing that FB1.1 leads to expression of EGFP, mCitrine, mCherry and Cerulean-V5. (,) Confocal images of larval R cells () an! d of lineages of younger (y, asterisks) and individual older (o, arrowheads) medulla neurons () expressing different fluorescent proteins. (–) Differentially labeled adult neuron subtypes14: lamina neurons L5 (,), lineage-related ascending T2–T5 neurons (), an amacrine Dm neuron and the transmedullary neurons Tm18 (arrows) and TmY5a (arrowheads) (). lo, lobula; lop, lobula plate. (,) Sagittal view of a live stage 16 embryo with clusters and single neurons expressing mCitrine or mCherry (arrowheads). Arrow, cluster expressing EGFP and mCherry owing to perdurance; asterisk, unlabeled cluster of Cerulean-V5–expressing neurons. Insets, live growth cone extending from the ventral nerve cord (VNC) into the peripheral nervous system (PNS). (,) Flat preparation of a fixed VNC with large (arrows) or smaller (arrowheads) growth cones exploring lateral (l) tracts and anterior (ac) or posterior (pc) commissures. () PNS neurons, including the lateral chordotonal organ (lch). elav-! Gal4c155 was used as pan-neuronal driver. EGFP, mCitrine and m! Cherry were detected using endogenous fluorescence signals and Cerulean using immunolabeling with antibody to V5. Scale bars, 50 μm (,,–) and 20 μm (insets, ). * Figure 3: Expression of FB1.1 transgenes in distinct cell populations. (–) Confocal images showing third instar larval (3L) and adult R1–R8 photoreceptor axons labeled using GMR-Gal4. R1–R6 growth cones (arrowheads) in the lamina (la), and young (double arrowheads) and mature (arrows). R8 growth cones in the medulla (me) are highlighted in ,. Adult R8 and R7 terminals in a column express the same fluorescent protein (arrowhead) or combinations of two fluorescent proteins (asterisks) (–). (–) Single optical sections (,) and a 10 μm z-stack projection of the mCitrine channel () of adult optic lobes in which MzVum-Gal4 drives FB1.1 expression in medulla neurons. One neuron (arrow; ,) traced through a series of consecutive sections had TmY5a neuron-like features; asterisks indicate additional or absent branches compared to reported morphology14. (,) Epithelial (eg) and marginal (mg) glia in the lamina, and medulla neuropil glia (mng) at the distal medulla neuropil border were labeled with different fluorescent proteins in third instar la! rval () and adult () optic lobes using repo-Gal4 and FB1.1. In , fluorescence signals in the lamina above the white line were reduced relative to those in the medulla. (–) Higher magnification of the image in , showing elaborate shapes of epithelial and medulla neuropil glia. () Area with overlapping medulla neuropil glial cell branches (arrowhead) in a medulla cross-section. (,) en-Gal4–driven expression of different fluorescent proteins in epithelial cell clones in the posterior (p) compartment of wing discs. d, dorsal. Scale bars, 50 μm (,,–,–) and 10 μm (,,,–). * Figure 4: FB2.0 facilitates sparse labeling of cells within a Gal4-expressing cell population. () Schematic showing that upon heat induction, Flp excises the upstream FRT stop cassette to enable reporter expression in a subset of Gal4-expressing cells. Induction of hs-mFlp5 randomizes the fluorescent protein selection as in FB1.1. Expression of four fluorescent proteins is restricted to cells with overlapping Gal4, Flp and mFlp5 activities. (–) Confocal images showing that elav-Gal4c155 in conjunction with FB2.0 led to fluorescent protein expression in only a small subset of R cells in eye discs posterior to the morphogenic furrow (), and of lamina and medulla neurons (mn) in larval () and adult (,) optic lobes. Labeling of fewer cells facilitated the identification of neuron subtypes in the dense neuropils of the lamina (la), medulla (me), lobula (lo) and lobula plate (lop). Surrounded by mCherry-expressing medulla neurons, lamina neurons subtype L3 can be identified by mCitrine expression in the adult medulla. Scale bars, 50 μm. * Figure 5: Combining Flybow and MARCM for functional mosaic analysis. () Schematic of Flp-FRT–mediated mitotic recombination in trans during the G2-M phase of the cell cycle and subsequent chromosome segregation, which leads to the loss of the Gal80 repressor in one of the daughter cells, enabling reporter gene expression. This Gal80-free cell is homozygous for any mutation located on the homologous chromosome arm (vertical bar on black chromosome). mFlp5-mFRT71–mediated recombination of the FB1.1 transgene in cis leads to the stochastic expression of one of four fluorescent proteins in progeny not expressing Gal80. (–) Confocal images of adult optic lobes (,) and higher magnifications of medulla neuropil (–) showing that elav-Gal4c155 in conjunction with FB1.1 drives expression of EGFP, mCitrine and mCherry in wild-type control and CadNM19 homozygous mutant neurons in the adult lamina (la), medulla (me), lobula (lo) and lobula plate (lop). ln, lamina neurons. R-cell axons were labeled with the photoreceptor-specific antibody mAb24B10 ! (blue). Shown are mCitrine-expressing lamina neuron L1 innervating layers M1 and M5 () and mCherry-expressing lamina neurons L5 terminating in the M1, M2 and M5 layers () in controls. In the latter, axonal arbors can be distinguished from overlapping branches of neighboring neurons expressing EGFP or mCitrine (arrowhead). Also shown are mCherry-expressing L1 and L5 neurons with aberrant projections in the absence of CadNM19 (). () Schematic illustrating the axonal arborizations of control and CadNM19 homozygous mutant L1 and L5 neurons. Scale bars, 50 μm (,) and 10 μm (–). Accession codes * Abstract * Accession codes * Change history * Author information * Supplementary information Referenced accessions Entrez Nucleotide * HQ998853 * HQ998854 * HQ998855 Change history * Abstract * Accession codes * Change history * Author information * Supplementary informationCorrigendum 16 February 2011In the version of this article initially published online, accession codes were not included. 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 Affiliations * Medical Research Council (MRC) National Institute for Medical Research, Division of Molecular Neurobiology, London, UK. * Dafni Hadjieconomou & * Iris Salecker * Research Institute of Molecular Pathology, Vienna, Austria. * Shay Rotkopf & * Barry J Dickson * MRC National Institute for Medical Research, Division of Developmental Neurobiology, London, UK. * Cyrille Alexandre * MRC National Institute for Medical Research, Confocal Image Analysis Laboratory, London, UK. * Donald M Bell * Present address: Weizmann Institute of Science, Department of Molecular Genetics, Rehovot, Israel. * Shay Rotkopf Contributions I.S., B.J.D., D.H. and C.A. designed the Flybow strategy. D.H. cloned the Flybow constructs, D.H. and I.S. generated the transgenic fly stocks, and D.H. conducted the experimental analysis. S.R. and B.J.D. developed the modified Flp-FRT system, and provided the original pKC26 UAS vector and the wild-type Flp-out cassette. C.A. provided expert advice for cloning, and D.M.B. provided expert advice for image acquisition and analysis. I.S. and D.H. wrote the manuscript in interaction with all contributing authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Iris Salecker Author Details * Dafni Hadjieconomou Search for this author in: * NPG journals * PubMed * Google Scholar * Shay Rotkopf Search for this author in: * NPG journals * PubMed * Google Scholar * Cyrille Alexandre Search for this author in: * NPG journals * PubMed * Google Scholar * Donald M Bell Search for this author in: * NPG journals * PubMed * Google Scholar * Barry J Dickson Search for this author in: * NPG journals * PubMed * Google Scholar * Iris Salecker Contact Iris Salecker 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 (647K) Supplementary Figures 1–5 and Supplementary Table 1 Additional data - Quantification of PtdInsP3 molecular species in cells and tissues by mass spectrometry
- Nat Meth 8(3):267-272 (2011)
Nature Methods | Article Quantification of PtdInsP3 molecular species in cells and tissues by mass spectrometry * Jonathan Clark1, 2, 5 * Karen E Anderson1, 5 * Veronique Juvin1 * Trevor S Smith1 * Fredrik Karpe3, 4 * Michael J O Wakelam1 * Len R Stephens1, 5 * Phillip T Hawkins1, 5 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:267–272Year published:(2011)DOI:doi:10.1038/nmeth.1564Received13 October 2010Accepted20 December 2010Published online30 January 2011 Abstract * Abstract * 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 Class I phosphoinositide-3-kinase (PI3K) isoforms generate the intracellular signaling lipid, phosphatidylinositol(3,4,5)trisphosphate (PtdIns(3,4,5)P3). PtdIns(3,4,5)P3 regulates major aspects of cellular behavior, and the use of both genetic and pharmacological intervention has revealed important isoform-specific roles for PI3Ks in health and disease. Despite this interest, current methods for measuring PtdIns(3,4,5)P3 have major limitations, including insensitivity, reliance on radiolabeling, low throughput and an inability to resolve different fatty-acyl species. We introduce a methodology based on phosphate methylation coupled to high-performance liquid chromatography–mass spectrometry (HPLC-MS) to solve many of these problems and describe an integrated approach to quantify PtdIns(3,4,5)P3 and related phosphoinositides (regio-isomers of PtdInsP and PtdInsP2 are not resolved). This methodology can be used to quantify multiple fatty-acyl species of PtdIns(3,4,5)P3 in un! stimulated mouse and human cells (≥105) or tissues (≥0.1 mg) and their increase upon appropriate stimulation. View full text Subject terms: * Mass Spectrometry * Chemistry * Cell Biology * Biochemistry Figures at a glance * Figure 1: Analysis of phosphoinositides in control and fMLP-stimulated human neutrophils. (–) Neutral loss scans of a derivatized phosphoinositide extract, from unstimulated control (,) or fMLP-stimulated (,) neutrophils. The two most abundant species of endogenous PtdIns(3,4,5)P3 and PtdInsP2 are labeled with full masses and corresponding fatty acid species of diacylglycerol unit. Cps, counts per second. () Overlay of m/z chromatograms for parent ions with masses similar to those of derivatized C18:0/C20:4-Ptdins(3,4,5)P3) from extracts from 105 human neutrophils, highlighting elution at 10.75 min (ions that increase with fMLP stimulation in a wortmannin-sensitive manner). () Overlay of MRM chromatograms (m/z 1,225 to m/z 627 + 598) of samples from . Data were collected using Quattro Ultima (Waters) (–) and QTRAP 4000 (AB Sciex) (–) mass spectrometers. Representative traces from several independent experiments are shown. * Figure 2: Validation of the robustness, signal-to-noise ratio and linearity of the assay. () C17:0/C16:0-PtdIns(3,4,5)P3 internal standard spiked into unstimulated human neutrophil extract. () C18:0/C20:4-PtdIns(3,4,5)P3 standard spiked into unstimulated human neutrophil extract. () Data for 0.25 ng C18:0/C20:4-PtdIns(3,4,5)P3 standard spiked into unstimulated neutrophil extract. Signal to noise, root mean square = 114. () Response to increasing amounts of C18:0/C20:4-PtdIns(3,4,5)P3 added to extracts of unstimulated neutrophils (2.25 × 106). () Relationship between cell number (fMLP-stimulated neutrophils) and estimated endogenous C18:0/C20:4-PtdIns(3,4,5)P3 by using the internal standard to correct for recovery. The term 'response ratio' in (,,) is the integrated ion current response to the defined phosphoinositide divided by that to the internal standard. () MRM chromatograms for 1 μg each of synthetic C18:0/C20:4-PtdIns(4,5)P2 (left), synthetic C18:0/C20:4-PtdIns(3,4,5)P3 (middle) and internal standard (C17:0/C16:0-PtdIns(3,4,5)P3) (right) in water. * Figure 3: fMLP-stimulated changes in C18:0/C20:4 and C18:0/C18:1 PtdInsP2 and PtdIns(3,4,5)P3 species in human neutrophils. (,) Amounts of the C18:0/C20:4 and C18:0/C18:1 molecular species of PtdInsP2 () and PtdIns(3,4,5)P3 () determined at indicated times after addition of fMLP. The data are expressed as either response ratios (as defined in Fig. 2), or through use of the calibration curve presented in Figure 2d and protein assays, picomoles of C18:0/C20:4 PtdIns(3,4,5)P3 per milligram protein. Error bars, s.e.m. (n = 4). () The ratio of the quantity of each molecular species of PtdIns(3,4,5)P3 divided by that of its respective PtdInsP2 species. * Figure 4: Identification and quantification of the molecular species of PtdIns(3,4,5)P3 in wild-type and PTEN−/− MCF10a cells. (,) Neutral loss scans of the common families of molecular species of PtdInsP2 () and PtdIns(3,4,5)P3 () in EGF-stimulated, wild-type MCF10a cells. Further fragmentation and analysis of the relevant daughter ions indicated they possessed the fatty acids indicated in . Data were collected using a QTRAP 4000 mass spectrometer. (,) The levels of these species of PtdInsP2 () and PtdIns(3,4,5)P3 () in the indicated cell lines and conditions are presented as mean response ratios normalized for cell input via the recovered C18:0/C18:1-PtdSer (error bars, s.e.m.; n = 3). () The ratio of the quantity of each molecular species of PtdIns(3,4,5)P3 divided by that of their respective PtdInsP2 species. * Figure 5: Detection and quantification of insulin-stimulated PtdIns(3,4,5)P3 responses in mouse liver and human adipose tissue. () Neutral loss scan, collected using a QTRAP 4000 mass spectrometer, of PtdIns(3,4,5)P3 species in wild-type, insulin-stimulated mouse liver. () Levels of C18:0/C20:4-PtdIns(3,4,5)P3 in the livers of wild-type (WT) or Gnasxlm+/p− mice after injection of insulin or saline (error bars, s.e.m.; n = 4). () Phosphorylation status of S473 in PKB for parallel samples to those analyzed in ; data were normalized for input material via immunoblotting for β-COP. () Neutral loss scan of PtdIns(3,4,5)P3 species in human adipose tissue after oral ingestion of glucose. () C18:0/C20:4-PtdIns(3,4,5)P3 amounts in healthy human adipose tissue after overnight starvation either before (fasting) or 90 min after (glucose) oral ingestion of glucose, for three individuals (error bars, s.e.m.; technical replicates n = 4). () Phosphorylation status of S473 in PKB for parallel samples to those analyzed in ; data normalized for input material via immunoblotting for actin. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jonathan Clark, * Karen E Anderson, * Len R Stephens & * Phillip T Hawkins Affiliations * Inositide Laboratory, Babraham Institute, Babraham Research Campus, Cambridge, UK. * Jonathan Clark, * Karen E Anderson, * Veronique Juvin, * Trevor S Smith, * Michael J O Wakelam, * Len R Stephens & * Phillip T Hawkins * Babraham Bioscience Technologies Ltd., Babraham Research Campus, Babraham, Cambridge, UK. * Jonathan Clark * Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK. * Fredrik Karpe * National Institute for Health Research, Oxford Biomedical Research Centre, Oxford Radcliffe Hospitals Trust, Churchill Hospital, UK. * Fredrik Karpe Contributions J.C. and K.E.A. designed and performed experiments, developed methods, analyzed data and contributed to writing the manuscript; V.J. designed and performed PKB experiments; T.S.S. performed experiments; F.K. designed experiments (Fig. 5 and Supplementary Figs. 9 and 10) to generate samples for analysis; M.J.O.W. developed methods and provided reagents; and L.R.S. and P.T.H. designed the study/experiments, developed methods, analyzed data and wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Phillip T Hawkins or * Len R Stephens Author Details * Jonathan Clark Search for this author in: * NPG journals * PubMed * Google Scholar * Karen E Anderson Search for this author in: * NPG journals * PubMed * Google Scholar * Veronique Juvin Search for this author in: * NPG journals * PubMed * Google Scholar * Trevor S Smith Search for this author in: * NPG journals * PubMed * Google Scholar * Fredrik Karpe Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J O Wakelam Search for this author in: * NPG journals * PubMed * Google Scholar * Len R Stephens Contact Len R Stephens Search for this author in: * NPG journals * PubMed * Google Scholar * Phillip T Hawkins Contact Phillip T Hawkins Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (904K) Supplementary Figures 1–10, Supplementary Tables 1–2, Supplementary Data 1–2 Additional data
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