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- Nat Meth 8(4):273 (2011)
Nature Methods | Editorial Tweet me Journal name:Nature MethodsVolume: 8,Page:273Year published:(2011)DOI:doi:10.1038/nmeth0411-273Published online30 March 2011 Meeting organizers and speakers are increasingly open to blogging and microblogging—an encouraging trend that should be expanded with clearly defined restrictions. View full text Additional data - The author file: Jeanne Loring and Franz-Josef Müller
- Nat Meth 8(4):275 (2011)
Nature Methods | This Month The author file: Jeanne Loring and Franz-Josef Müller * Monya BakerJournal name:Nature MethodsVolume: 8,Page:275Year published:(2011)DOI:doi:10.1038/nmeth0411-275Published online30 March 2011 An open-access tool tells researchers whether a human cell line is pluripotent. View full text Additional data - Points of view: Typography
- Nat Meth 8(4):277 (2011)
Nature Methods | This Month Points of view: Typography * Bang Wong1Journal name:Nature MethodsVolume: 8,Page:277Year published:(2011)DOI:doi:10.1038/nmeth0411-277Published online30 March 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. Typography is the art and technique of arranging type. Like a person's speaking style and skill, the quality of our treatment of letters on a page can influence how people respond to our message. It is an essential act of encoding and interpretation, linking what we say to what people see. Typography has been known to affect perception of credibility. In one study, identical job resumes printed using different typefaces were sent out for review. Resumes with typefaces deemed appropriate for a given industry resulted in applicants being considered more knowledgeable, mature, experienced, professional, believable and trustworthy than when less appropriate typefaces were used1. In this case, picking the right typeface can help someone's chances of landing a job. The term typeface is frequently conflated with font; Arial is a 'typeface' that may include roman, bold and italic 'fonts'. Most generally we categorize letterforms as serif or sans serif. Primary characteristics of a letterform are illustrated in Figure 1a. Serif typefaces tend to be thinner, more formal and easier to read in multiline blocks of text because the 'feet' help our eyes follow the line. Sans serif typefaces have simpler letterforms, are informal and, according to some, less readable in long stretches, so are appropriate for short bursts of text such as headings and labels. In general, sans serif fonts work well for slides and serif fonts for posters and printed documents. Figure 1: Typefaces. () The anatomy of letterform for serif (Garamond) and sans serif (Univers) type both set at 58 point. () Four of the most readily available fonts. * Full size image (39 KB) * Figures index * Next figure Picking type is a matter of personal taste, but typography exists to honor content. The four most common typefaces are Baskerville, Helvetica, Palatino and Times New Roman (Fig. 1b), and a good rule is: when limited to the palette of type preinstalled on our computers, pick one and ignore the rest. The acclaimed poet and typographer Robert Bringhurst eloquently states that these four typefaces are "faces with nothing to offer one another except for public disagreement"2. If nothing else, the single typeface approach ensures consistency. Uniformity is one form of beauty; contrast is another. Of course, typefaces can be combined, but the operation requires care and craft. View full text Figures at a glance * Figure 1: Typefaces. () The anatomy of letterform for serif (Garamond) and sans serif (Univers) type both set at 58 point. () Four of the most readily available fonts. * Figure 2: Spacing can reveal structure and give meaning to text. () Uniform carriage return (CR) spacing is incongruous with hierarchical content. () Relative spacing using paragraph formatting expresses relationships in the text. Numbers are 'space after' values given in point sizes. 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 - DAOSTORM: an algorithm for high- density super-resolution microscopy
- Nat Meth 8(4):279-280 (2011)
Nature Methods | Correspondence DAOSTORM: an algorithm for high- density super-resolution microscopy * Seamus J Holden1 * Stephan Uphoff1 * Achillefs N Kapanidis1 * Affiliations * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:279–280Year published:(2011)DOI:doi:10.1038/nmeth0411-279Published online30 March 2011 To the Editor: Astronomy and biology have more in common than you might expect. Here we show that methods originally used to study crowded stellar fields can improve the performance of localization-based super-resolution microscopies (stochastic optical reconstruction microscopy (STORM)1, photoactivated localization microscopy2 and others), which currently have slow imaging rates (typically < 0.01 image s−1), limiting their utility in studies of live-cell dynamics. These techniques, which use stochastic photoswitching to resolve closely spaced fluorophores and thus reconstruct super-resolved images, require that the specimen has a low density of active fluorophores (hereafter called 'imaging density'; <1 molecule μm−2), limiting imaging speed and spatial resolution (Supplementary Discussion). A major cause of this issue is that current super-resolution localization algorithms work by fitting images of fluorescent molecules using only a single model point spread function (PSF; the diffraction-limited image of a fluorophore). We observed that astronomy software, DAOPHOT II (refs. 3,4), can simultaneously fit overlapping molecular PSFs (hereafter called 'molecules') with multiple model PSFs instead of just one, facilitating analysis at high imaging density (up to 10 molecules μm−2). We developed DAOSTORM (Supplementary Software and Supplementary Note), which adapts DAOPHOT II for super-resolution imaging by increasing its automation! and robustness (Supplementary Fig. 1 and Supplementary Methods). We compared DAOSTORM to two common localization algorithms. 'Sparse algorithm 1' (SA1)1 fits candidate molecules with a single Gaussian PSF of variable size and ellipticity. Localizations arising from overlapping molecules are rejected if the fitted PSF appears too elliptical (shape-based filtering), too large or too small (size-based filtering). 'Sparse algorithm 2' (SA2)5 fits candidate molecules with a single Gaussian PSF of fixed shape and size, without shape- or size-based filtering. We first investigated the qualitative performance of each algorithm for images of Alexa Fluor 647–immunolabeled microtubules in fixed COS-7 cells. We recorded data at high imaging density using total internal reflection fluorescence microscopy and direct (d)STORM photoswitching conditions5 (100 ms integration time, ~4,000 photons fluorophore−1 frame−1). We plotted localizations on raw images, illustrating the characteristic performance of each algorithm (Fig. 1a). SA1 only localized isolated molecules, which were fitted with small localization error. SA2 localized a larger fraction of the molecules but yielded large localization errors for overlapping molecules. DAOSTORM outperformed both sparse algorithms, identifying almost all molecules with small localization error. back to article Figure 1: Comparison of DAOSTORM to existing super-resolution localization algorithms. () A single image of fluorescently labeled microtubules was analyzed using SA1, SA2 and DAOSTORM. Crosses represent localizations for each algorithm (,) Recall () and localization error () of the algorithms used in measured for simulated images of randomly distributed surface-immobilized molecules. Error bars, s.d. (n = 10). () Super-resolved microtubule images from a 2,000-frame data series. () Line plots of cross-section indicated by dashed lines in . Scale bars, 1 μm. View full text Subject terms: * Microscopy * Imaging * 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 Affiliations * Biological Physics Research Group, Clarendon Laboratory, Department of Physics, University of Oxford, Oxford UK. * Seamus J Holden, * Stephan Uphoff & * Achillefs N Kapanidis Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Seamus J Holden or * Achillefs N Kapanidis Author Details * Seamus J Holden Contact Seamus J Holden Search for this author in: * NPG journals * PubMed * Google Scholar * Stephan Uphoff Search for this author in: * NPG journals * PubMed * Google Scholar * Achillefs N Kapanidis Contact Achillefs N Kapanidis Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information Zip files * Supplementary Software (356K) The DAOSTORM software, a user's manual, installation instructions, test data and a licensing agreement. PDF files * Supplementary Text and Figures (769K) Supplementary Figures 1–4, Supplementary Methods, Supplementary Discussion, Supplementary Note Additional data * Journal home * Current issue * For authors * Subscribe * E-alert sign up * RSS feed Science jobs from naturejobs * Five Center Directorships, Multiple Vacancies for Open-Rank Tenure-Track Faculty, and Postdoctoral Research Fellows * Frontier Institute of Science and Technology, Xi'an Jiaotong University * Xi'an, Shaanxi, P.R.China * Postdoctoral Researcher for FIRST Program * Immunology Frontier Research Center (IFReC), Osaka University * Suita City, Osaka, Japan * Chair in Atmospheric Chemistry Modelling * University of York * York, UK * Post a free job * More science jobs Related content Articles * Whole genome–amplified DNA: insights and imputation Nature Methods 01 Apr 2008 * Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination Nature Methods 04 Mar 2011 * Confined activation and subdiffractive localization enables whole-cell PALM with genetically expressed probes Nature Methods 13 Feb 2011 * Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network Nature Methods 14 Dec 2008 * Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues Nature Methods 27 Dec 2009 View all Open innovation challenges * Delayed Release Formulation for Aqueous Protein Solution Deadline:Apr 02 2011Reward:$40,000 USD A delayed release technology is required for a boosting agent that would allow the simultaneous deli… * Quantifying (meth)Acrylate Polymer in Complex Matrices Deadline:May 29 2011Reward:$15,000 USD A sensitive and specific assay for the quantitative detection of acrylate and methacrylate polymers … * Powered by: * More challenges Top content Emailed * A bioinformatic assay for pluripotency in human cells Nature Methods 06 Mar 2011 * Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination Nature Methods 04 Mar 2011 * Multiple displacement amplification compromises quantitative analysis of metagenomes Nature Methods 29 Nov 2010 * Cheap third-generation sequencing Nature Methods 01 Apr 2009 * Combined atomic force microscopy and side-view optical imaging for mechanical studies of cells Nature Methods 12 Apr 2009 View all Downloaded * Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination Nature Methods 04 Mar 2011 * Mapping and quantifying mammalian transcriptomes by RNA-Seq Nature Methods 30 May 2008 * Simultaneous assessment of rodent behavior and neurochemistry using a miniature positron emission tomograph Nature Methods 13 Mar 2011 * Next-generation sequencing transforms today's biology Nature Methods 19 Dec 2007 * qPCR: quicker and easier but don't be sloppy Nature Methods 25 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 * A bioinformatic assay for pluripotency in human cells Nature Methods 06 Mar 2011 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 - Diffraction before destruction
- Nat Meth 8(4):283 (2011)
Nature Methods | Research Highlights Diffraction before destruction * Allison DoerrJournal name:Nature MethodsVolume: 8,Page:283Year published:(2011)DOI:doi:10.1038/nmeth0411-283Published online30 March 2011 Two recent reports demonstrate the first applications of X-ray free-electron lasers to look at biological structures. View full text Subject terms: * Structural biology Additional data Author Details * Allison Doerr Search for this author in: * NPG journals * PubMed * Google Scholar - Nanopillars of light
- Nat Meth 8(4):284-285 (2011)
Nature Methods | Research Highlights Nanopillars of light * Natalie de SouzaJournal name:Nature MethodsVolume: 8,Pages:284–285Year published:(2011)DOI:doi:10.1038/nmeth0411-284aPublished online30 March 2011 Illuminating cells through tiny transparent pillars permits spatially confined excitation of fluorescent molecules. View full text Subject terms: * Biophysics Additional data Author Details * Natalie de Souza Search for this author in: * NPG journals * PubMed * Google Scholar - Dissecting signaling at the speed of light
- Nat Meth 8(4):284-285 (2011)
Nature Methods | Research Highlights Dissecting signaling at the speed of light * Allison DoerrJournal name:Nature MethodsVolume: 8,Pages:284–285Year published:(2011)DOI:doi:10.1038/nmeth0411-284bPublished online30 March 2011 Researchers use light-activated photo-uncaging to dissect the elementary steps in protein kinase signaling networks in living human cells. View full text Subject terms: * Signal Transduction Additional data Author Details * Allison Doerr Search for this author in: * NPG journals * PubMed * Google Scholar - News in brief
- Nat Meth 8(4):285 (2011)
Nature Methods | Research Highlights News in brief Journal name:Nature MethodsVolume: 8,Page:285Year published:(2011)DOI:doi:10.1038/nmeth0411-285Published online30 March 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. Dissecting neural networks with Brainbow Neurotropic viruses—which replicate in neurons and can cross synapses—are useful as neural circuit tracing tools. Card et al. combine this technology with the Brainbow approach to highlight neuronal connections within a larger network. They inserted the Brainbow cassette into the genome of an engineered pseudorabies virus, which resulted in the expression of either yellow or cyan fluorescent reporters in response to Cre recombinase–mediated recombination, allowing synaptic connections to be traced. Card, J.P.et al. Proc. Natl. Acad. Sci. USA108, 3377–3382 (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 - Testing pluripotency
- Nat Meth 8(4):287 (2011)
Nature Methods | Research Highlights Testing pluripotency * Natalie de SouzaJournal name:Nature MethodsVolume: 8,Page:287Year published:(2011)DOI:doi:10.1038/nmeth0411-287Published online30 March 2011 Reference datasets of gene expression and DNA methylation in human pluripotent stem cell lines are reported. View full text Subject terms: * Stem Cells Additional data Author Details * Natalie de Souza Search for this author in: * NPG journals * PubMed * Google Scholar - Identifying order in a plaque
- Nat Meth 8(4):288 (2011)
Nature Methods | Research Highlights Identifying order in a plaque * Monya BakerJournal name:Nature MethodsVolume: 8,Page:288Year published:(2011)DOI:doi:10.1038/nmeth0411-288Published online30 March 2011 An image-analysis technique deconvolutes combinations of labels, revealing which bacteria are where in microbial communities. View full text Subject terms: * Microbiology Additional data Author Details * Monya Baker Search for this author in: * NPG journals * PubMed * Google Scholar - Building a megabrain atlas
- Nat Meth 8(4):290 (2011)
Nature Methods | Research Highlights Building a megabrain atlas * Erika PastranaJournal name:Nature MethodsVolume: 8,Page:290Year published:(2011)DOI:doi:10.1038/nmeth0411-290Published online30 March 2011 A digital platform has been created to incorporate multiple brain data resources into a common global mouse atlas. View full text Subject terms: * Neuroscience Additional data Author Details * Erika Pastrana Search for this author in: * NPG journals * PubMed * Google Scholar - Stem cells in culture: defining the substrate
- Nat Meth 8(4):293-297 (2011)
Nature Methods | Technology Feature Stem cells in culture: defining the substrate * Monya Baker1Journal name:Nature MethodsVolume: 8,Pages:293–297Year published:(2011)DOI:doi:10.1038/nmeth0411-293Published online30 March 2011 Abstract * Abstract * Author information Efforts to improve stem cell culture are shifting to the surface. View full text Author information * Abstract * 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 - Large-scale genetic epistasis networks using RNAi
- Nat Meth 8(4):299-301 (2011)
Nature Methods | News and Views Large-scale genetic epistasis networks using RNAi * Xiaoyue Wang1 * Kevin P White1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:299–301Year published:(2011)DOI:doi:10.1038/nmeth0411-299Published online30 March 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. Abstract * Abstract * Author information Pairwise quantitative genetic interactions are mapped by combinatorial RNA interference in metazoan cells. View full text Author information * Abstract * 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 * Xiaoyue Wang and Kevin P. White are at the Institute for Genomics and Systems Biology and Department of Human Genetics, University of Chicago, Chicago, Illinois, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Kevin P White Author Details * Xiaoyue Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Kevin P White Contact Kevin P White 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 - Functional whole-brain imaging in behaving rodents
- Nat Meth 8(4):301-303 (2011)
Nature Methods | News and Views Functional whole-brain imaging in behaving rodents * Simon R Cherry1Journal name:Nature MethodsVolume: 8,Pages:301–303Year published:(2011)DOI:doi:10.1038/nmeth0411-301Published online30 March 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. A wearable imaging device allows functional whole-brain imaging of awake, freely moving rats. This technology opens up a noninvasive window for simultaneously assessing brain function and behavior in response to a wide variety of interventions in living rats. 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 * Simon R. Cherry is in the Department of Biomedical Engineering and at the Center for Molecular and Genomic Imaging, University of California, Davis, Davis, California, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Simon R Cherry Author Details * Simon R Cherry Contact Simon R Cherry 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 - An in-depth view
- Nat Meth 8(4):304-305 (2011)
Nature Methods | News and Views An in-depth view * Bo Huang1Journal name:Nature MethodsVolume: 8,Pages:304–305Year published:(2011)DOI:doi:10.1038/nmeth0411-304Published online30 March 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. Two fluorescence microscopy techniques provide alternative routes to obtaining three-dimensional super-resolution images with greater axial depth. 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 * Bo Huang is in the Department of Pharmaceutical Chemistry and Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Bo Huang Author Details * Bo Huang Contact Bo Huang 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 - Foreword
- Nat Meth 8(4):307 (2011)
Nature Methods | Foreword Foreword * Natalie de SouzaJournal name:Nature MethodsVolume: 8,Page:307Year published:(2011)DOI:doi:10.1038/nmeth0411-307Published online30 March 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. Biological systems are complex, and the cells that comprise them are, more often than not, molecularly and functionally distinct. This is true for the cells that make up a tissue in a multicellular organism—the highly heterogenous neurons of the human brain, for instance—but also for isogenic single-celled bacteria and for mammalian cells in vitro. Stem cells, in particular, are increasingly recognized as being divisible into subpopulations that, at least in some cases, have distinct functional properties. Cellular heterogeneity may come about for several nonexclusive reasons: because of genetic or epigenetic differences, as a consequence of differing microenvironments or because there is a stochastic component to the molecular processes occurring in otherwise identical cells. Whatever the source, there are many circumstances in which heterogeneity is an inherent and also a desirable property of cells. View full text 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 - Summary of the supplement on single-cell analysis
- Nat Meth 8(4):308-309 (2011)
Nature Methods | Summaries Summary of the supplement on single-cell analysis Journal name:Nature MethodsVolume: 8,Pages:308–309Year published:(2011)DOI:doi:10.1038/nmeth0411-308Published online30 March 2011 Read the supplement at http://www.nature.com/nmeth/journal/v8/n4s/index.html. View full text Additional data - Single-cell genomics
- Nat Meth 8(4):311-314 (2011)
Nature Methods | Commentary Single-cell genomics * Tomer Kalisky1 * Stephen R Quake2 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:311–314Year published:(2011)DOI:doi:10.1038/nmeth0411-311Published online30 March 2011 Abstract * Abstract * 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 Methods for genomic analysis at single-cell resolution enable new understanding of complex biological phenomena. Single-cell techniques, ranging from flow cytometry and microfluidics to PCR and sequencing, are used to understand the cellular composition of complex tissues, find new microbial species and perform genome-wide haplotyping. View full text Figures at a glance * Figure 1: High-throughput single-cell gene expression using microfluidic chips for studying the cellular hierarchy of solid tissues and tumors. A typical workflow is shown: a tissue sample is disaggregated into a single-cell suspension and stained for the desired surface markers. Single cells are sorted into individual wells using flow cytometry. Predetermined gene targets are reverse-transcribed and amplified using multiplex PCR. Subsequently, the amplified cDNA is multiplexed on a microfluidic chip (scale bar, 1 cm) with up to 96 gene-specific primers and probes, and quantified by PCR. Statistical analysis of the single-cell gene expression data can be used to identify cellular subpopulations comprising the tissue. * Figure 2: Single-cell genome sequencing using microfluidics. A mixture of cells sampled from a complex microbial ecosystem is introduced into the chip. Single cells are selected using an optical trap, and are sorted into chambers for cell lysis and genome amplification. Genomes are amplified in nanoliter MDA reactions to produce larger quantities of DNA (shown are SYBR Green–stained products in microfluidic reaction chambers). Sequencing libraries are created from the amplified genomic DNA for sequencing on a high-throughput DNA sequencer. The sequence reads are assembled to recover the genome sequence, which is annotated to identify genes and pathways present in the original cell. The microfluidics image was reprinted from ref. 35. Author information * Abstract * Author information Affiliations * Tomer Kalisky is in the Department of Bioengineering, Stanford University, Stanford, California, USA. * Stephen R. Quake is in the Departments of Applied Physics and Bioengineering, Stanford University, Stanford, California, USA and Howard Hughes Medical Institute, Chevy Chase, Maryland, USA. Competing financial interests S.R.Q. is a founder, consultant and shareholder of Fluidigm corp. Corresponding author Correspondence to: * Stephen R Quake Author Details * Tomer Kalisky Search for this author in: * NPG journals * PubMed * Google Scholar * Stephen R Quake Contact Stephen R Quake Search for this author in: * NPG journals * PubMed * Google Scholar Additional data - A bioinformatic assay for pluripotency in human cells
- Nat Meth 8(4):315-317 (2011)
Nature Methods | Brief Communication A bioinformatic assay for pluripotency in human cells * Franz-Josef Müller1, 11 * Bernhard M Schuldt2, 11 * Roy Williams3 * Dylan Mason4 * Gulsah Altun5 * Eirini P Papapetrou6 * Sandra Danner7 * Johanna E Goldmann5, 8 * Arne Herbst1 * Nils O Schmidt9 * Josef B Aldenhoff1 * Louise C Laurent5, 10 * Jeanne F Loring5 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:315–317Year published:(2011)DOI:doi:10.1038/nmeth.1580Received13 September 2010Accepted03 February 2011Published online06 March 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Pluripotent stem cells (PSCs) are defined by their potential to generate all cell types of an organism. The standard assay for pluripotency of mouse PSCs is cell transmission through the germline, but for human PSCs researchers depend on indirect methods such as differentiation into teratomas in immunodeficient mice. Here we report PluriTest, a robust open-access bioinformatic assay of pluripotency in human cells based on their gene expression profiles. View full text Subject terms: * Stem Cells * Gene Expression * Bioinformatics * Cell Biology Figures at a glance * Figure 1: A multidimensional data model for assessing PSCs. () Schematic for PluriTest. (,) Assessment of pluripotent and somatic cell samples in the training dataset with the pluripotency score only () and with both PluriTest scores (). (–) PluriTest classifiers tested on datasets generated using four different microarray platforms: Illumina WG6v1 (, 177 samples)5, HT12v3 (, 498 samples), HT12v4 (, 38 samples) and Affymetrix U133A (, 5,372 samples)10. Samples for these datasets were independently generated (,) and/or curated from published stu dies (,,). In , the lines in the plot indicate empirically determined thresholds for defining normal pluripotent lines. * Figure 2: Output of PluriTest. (–) PluriTest results for known pluripotent cells and somatic cells and tissues (), for fully and partially reprogrammed iPSC lines () and for an hESC line (WA09) differentiated into neural precursors, at the indicated time points (). () PluriTest results for mixed samples of hESC and hESC-derived neural precursor RNA (day 0 and day 14 from the data shown in ) at the indicated ratios. hiPSC, human iPSC. The background encodes an empirical density map indicating pluripotency and novelty as indicated by the color bar. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE21973 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Franz-Josef Müller & * Bernhard M Schuldt Affiliations * Zentrum für Integrative Psychiatrie, Kiel, Germany. * Franz-Josef Müller, * Arne Herbst & * Josef B Aldenhoff * Aachen Institute for Advanced Study in Computational Engineering Science, Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany. * Bernhard M Schuldt * Sanford Burnham Medical Research Institute, La Jolla, California, USA. * Roy Williams * Independent consultant, Encinitas, California, USA. * Dylan Mason * Center for Regenerative Medicine, Department of Chemical Physiology, The Scripps Research Institute, La Jolla, California, USA. * Gulsah Altun, * Johanna E Goldmann, * Louise C Laurent & * Jeanne F Loring * Center for Cell Engineering and Molecular Pharmacology and Chemistry Program, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. * Eirini P Papapetrou * Fraunhofer Research Institution for Marine Biotechnology, Lübeck, Germany. * Sandra Danner * Institut für Biochemie, Freie Universität Berlin, Berlin, Germany. * Johanna E Goldmann * Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. * Nils O Schmidt * University of California, San Diego, Department of Reproductive Medicine, La Jolla, California, USA. * Louise C Laurent Contributions F.-J.M. conceived and designed the study. F.-J.M. and B.M.S. developed the PluriTest algorithm. F.-J.M., J.F.L., L.C.L. and J.B.A. oversaw the sample collection, microarray analysis and coordinated biological and bioinformatic experiments. R.W., D.M., B.M.S. and A.H. implemented the online bioinformatic platform. R.W., D.M., F.-J.M., B.M.S. and G.A. provided bioinformatic analyses. E.P.P., S.D., J.E.G. and N.O.S. prepared biological samples. F.-J.M., B.M.S. and J.F.L. wrote the manuscript with input from all authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Franz-Josef Müller Author Details * Franz-Josef Müller Contact Franz-Josef Müller Search for this author in: * NPG journals * PubMed * Google Scholar * Bernhard M Schuldt Search for this author in: * NPG journals * PubMed * Google Scholar * Roy Williams Search for this author in: * NPG journals * PubMed * Google Scholar * Dylan Mason Search for this author in: * NPG journals * PubMed * Google Scholar * Gulsah Altun Search for this author in: * NPG journals * PubMed * Google Scholar * Eirini P Papapetrou Search for this author in: * NPG journals * PubMed * Google Scholar * Sandra Danner Search for this author in: * NPG journals * PubMed * Google Scholar * Johanna E Goldmann Search for this author in: * NPG journals * PubMed * Google Scholar * Arne Herbst Search for this author in: * NPG journals * PubMed * Google Scholar * Nils O Schmidt Search for this author in: * NPG journals * PubMed * Google Scholar * Josef B Aldenhoff Search for this author in: * NPG journals * PubMed * Google Scholar * Louise C Laurent Search for this author in: * NPG journals * PubMed * Google Scholar * Jeanne F Loring Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information Excel files * Supplementary Table 1 (3M) Samples used for PluriTest model generation and validation Zip files * Supplementary Data (11M) PluriTest R/Bioconductor workspace PDF files * Supplementary Text and Figures (10M) Supplementary Figures 1–6, Supplementary Notes 1–3 Additional data - A microprobe for parallel optical and electrical recordings from single neurons in vivo
- Nat Meth 8(4):319-325 (2011)
Nature Methods | Article A microprobe for parallel optical and electrical recordings from single neurons in vivo * Yoan LeChasseur1, 2 * Suzie Dufour1, 2, 4 * Guillaume Lavertu1, 4 * Cyril Bories1 * Martin Deschênes1, 3 * Réal Vallée1, 2 * Yves De Koninck1, 2, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:319–325Year published:(2011)DOI:doi:10.1038/nmeth.1572Received15 July 2010Accepted20 January 2011Published online13 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 Recording electrical activity from identified neurons in intact tissue is key to understanding their role in information processing. Recent fluorescence labeling techniques have opened new possibilities to combine electrophysiological recording with optical detection of individual neurons deep in brain tissue. For this purpose we developed dual-core fiberoptics–based microprobes, with an optical core to locally excite and collect fluorescence, and an electrolyte-filled hollow core for extracellular single unit electrophysiology. This design provides microprobes with tips <10 μm, enabling analyses with single-cell optical resolution. We demonstrate combined electrical and optical detection of single fluorescent neurons in rats and mice. We combined electrical recordings and optical Ca2+ measurements from single thalamic relay neurons in rats, and achieved detection and activation of single channelrhodopsin-expressing neurons in Thy1::ChR2-YFP transgenic mice. The microprob! e expands possibilities for in vivo electrophysiological recording, providing parallel access to single-cell optical monitoring and control. View full text Subject terms: * Neuroscience * Sensors and Probes * Physiology Figures at a glance * Figure 1: The microprobe. () Schematic of the microprobe (not drawn to scale), which is based on a dual-core optical fiber: a graded index optical core and a hollow core. The optical core is connected at one end to a multimode optical fiber, and the other end is tapered. () Schematic of the optical fiber preform design: a series of different-size silica rods are assembled to position the optical and hollow cores side by side in an inclusion tube. Scale bar, 2 mm. () Diagram of the experimental setup. Light delivery and collection as well as electrical recording are all achieved through the same fiber probe. PMT, photomultiplier tube. () Illustration of the directionality of optical recording and the nondirectionality of electrical recording, with intensity profiles along the trajectory of the microprobe and interpeak distance shown on the right. * Figure 2: Microprobe optical resolution. (,) Fluorescence intensity profile as a function of transverse () and axial () probe displacement around single Lucifer yellow–labeled neurons in brain slices. Zero displacement in corresponds to the center of the cell body, zero displacement in is at nearest approach to the cell body. Shown are seven superimposed detection profiles (thin black lines), average detection profile (thick black line) and the expected detection profile based on numerical simulations (red line). (,) Photomicrographs of two adjacent Lucifer yellow–labeled fluorescent neurons in fixed brain slices used for testing probe detection in transverse () and axial () translation axes. Microprobes are outlined in white, and the arrow shows the probe trajectories. Scale bars, 10 μm. Detected fluorescence during probe displacement is plotted; zero displacement corresponds to the start of the white arrows in the micrographs. () Rising distance from 50% to peak fluorescence plotted versus laser power. Dashe! d line indicates the fitted regression. () Simulated fluorescence collection field of a 9-μm-diameter probe in front of a 12-μm-diameter neuron plotted against the axial and transverse positions of the probe. Color coding is arbitrary. * Figure 3: Single-unit recordings from neurons in vivo. () Photomicrograph of a spinal cord transverse section in which spinothalamic tract neurons were retrograde-labeled with DiI. The overlaid drawing of a microprobe (gray) illustrates a typical descent (arrow). Inset, magnification of a stained neuron. Scale bars, 1 mm and 20 μm in inset. () Schematic representation of the experiment. () Distribution of labeled spinothalamic tract neuron diameters plotted as a cumulative probability (top) or a histogram (bottom). The dotted arrow indicates the distance between the optical and electrical signal maxima in ; more than 90% of cells had a diameter >16 μm. () Fluorescence signal and spikes evoked from the stimulation of the receptive field as the microprobe descended into the spinal cord at constant speed (6 μm s−1). () Plot of the data shown in , with the time scale converted to spatial position. () Data from shown on an expanded time scale. Asterisks indicate digitally subtracted movement artifacts. () Distribution of intersp! ike intervals for cell analyzed in –. Inset, 212 superimposed individual spikes. () Distribution of optical signal-to-noise ratio (S/N) obtained with 87 detected neurons (average S/N was 21; n = 87 cells). Inset, relationship between the optical S/N and microprobe tip diameter. * Figure 4: Optical and electrical signal profiles of single cells in vivo. (,) Schematics (top) show microprobe displacement (arrow) relative to neuron position. Spike amplitudes () as the microprobe passed by a neuron were detected (curve indicates the average) and normalized spike amplitude was plotted as a function of probe travel distance (bottom, average in blue, n = 15 cells). Typical fluorescence detection patterns (; middle) when the microprobe passed by four fluorescently labeled neurons and normalized fluorescence profiles (bottom), with the average (thick black line) (n = 14) and the expected profile from simulations (red line) shown. Dotted lines indicate value at 50% to peak. () Successive units detected by fluorescence and/or electrical signals during a 225-μm, bidirectional probe excursion. E1 and E2 represent two electrically recorded neurons and O1 and O2 represent two optically recorded ones. Insets, examples of spikes recorded in E1 and E2. () Photomicrograph of a GAD-GFP mouse brain section. The overlaid drawing of a microprobe! (gray) illustrates a typical descent (white arrow) into the reticular thalamic nucleus. Inset, high-magnification photomicrograph of GAD-GFP neurons. Scale bar, 1 mm (20 μm in inset). () Magnitude of optical signal and spikes as the probe passed by a reticular thalamic GFP-expressing neuron (bottom). Zero value on the x axis is aligned with the peak of the fluorescence curve. Continuous electrophysiological signal as the probe traveled through the tissue (top). () Distribution of interspike intervals. Inset, consecutive superimposed action potentials (n = 26). * Figure 5: Monitoring Ca2+ fluctuations confirm optical and electrical recording from the same neuron in vivo. (,) Spontaneous spiking and Ca2+ fluctuations in a thalamic relay neuron (recorded at a depth of 6 mm in the brain). The fluorescence signal and spike bursts (), and Ca2+ response (quantified as the area under the curve) plotted as a function of the number of spikes in each burst () for the same cell. The two parameters were linearly correlated (n = 24 bursts). ΔF/F = (F – F0)/F0, in which F is the fluorescence and F0 = F in the stained region – F outside the stained region. () Schematic representation of the whisker deflection using a piezoelectric mechanical stimulator. Inset, superposition of three spiking and calcium responses following a whisker deflection. () Peristimulus time histograms of spiking responses to 20 whisker deflections (four directions indicated in degrees) and the associated averaged Ca2+ response over the same 20 stimuli for the same neuron. The duration of whisker deflection is represented in gray. () The angular preferences of spike response lat! ency plotted against angular preference for Ca2+ response (n = 8 cells). Inset, polar representation of the normalized inverted spike latency after stimulation (black) and the normalized inverted latency of the Ca2+ response (green). () Comparison between Ca2+ responses (top) and spiking responses (middle and bottom) of a neuron-to-whisker deflection. Black traces indicate two representative successful responses, and gray traces indicate two representative failures to respond in the same cell. * Figure 6: Detection and activation of single ChR2-expressing neurons in vivo. () Photomicrograph of a sagittal brain section of a Thy1::ChR2-EYFP mouse. White boxes highlight recording sites. Scale bar, 1 mm. () Magnitude of optical and electrical signals of a ChR2-EYFP–expressing neuron as a function of probe position. Zero position was aligned to peak fluorescence value. () Response of the neuron in to light stimulation through the probe. Arrowheads point to the depolarization and repolarization of the cells at the pulse onset and offset. () Response of an individual neuron versus light intensity. Individual responses are shown in insets. () Spike amplitude as a function of light intensity at probe tip (same cell as in ). Each inset represents seven superimposed spikes. () Mean ± s.d. of the response delay to light stimulus for motor cortical neurons (MC) (n = 15) and thalamic neurons (Th) (n = 9). () Responses of a thalamic ChR2-expressing neuron to micro-whisker deflection, light stimulation or both. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Suzie Dufour & * Guillaume Lavertu Affiliations * Centre de recherche Université Laval Robert-Giffard, Québec, Canada. * Yoan LeChasseur, * Suzie Dufour, * Guillaume Lavertu, * Cyril Bories, * Martin Deschênes, * Réal Vallée & * Yves De Koninck * Centre d'optique, photonique et laser, Université Laval, Québec, Canada. * Yoan LeChasseur, * Suzie Dufour, * Réal Vallée & * Yves De Koninck * Department of Psychiatry and Neuroscience, Université Laval, Québec, Canada. * Martin Deschênes & * Yves De Koninck Contributions Y.L., R.V. and Y.D.K. designed the microprobe. Y.L., S.D., G.L., C.B., M.D. and Y.D.K. designed the experiments. Y.L., S.D., G.L. and Y.D.K. analyzed data. Y.L., S.D., G.L. and C.B. performed experiments. S.D. performed Ca2+ measurement and photostimulation experiments. Y.L. and S.D. performed numerical simulations. Y.L., S.D., G.L., C.B., M.D., R.V. and Y.D.K. contributed to writing the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Yves De Koninck Author Details * Yoan LeChasseur Search for this author in: * NPG journals * PubMed * Google Scholar * Suzie Dufour Search for this author in: * NPG journals * PubMed * Google Scholar * Guillaume Lavertu Search for this author in: * NPG journals * PubMed * Google Scholar * Cyril Bories Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Deschênes Search for this author in: * NPG journals * PubMed * Google Scholar * Réal Vallée Search for this author in: * NPG journals * PubMed * Google Scholar * Yves De Koninck Contact Yves De Koninck Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–4 and Supplementary Data Additional data - Confined activation and subdiffractive localization enables whole-cell PALM with genetically expressed probes
- Nat Meth 8(4):327-333 (2011)
Nature Methods | Article Confined activation and subdiffractive localization enables whole-cell PALM with genetically expressed probes * Andrew G York1 * Alireza Ghitani1 * Alipasha Vaziri2, 4 * Michael W Davidson3 * Hari Shroff1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:327–333Year published:(2011)DOI:doi:10.1038/nmeth.1571Received09 September 2010Accepted06 January 2011Published online13 February 2011Corrected online04 March 2011 Abstract * Abstract * 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 demonstrate three-dimensional (3D) super-resolution microscopy in whole fixed cells using photoactivated localization microscopy (PALM). The use of the bright, genetically expressed fluorescent marker photoactivatable monomeric (m)Cherry (PA-mCherry1) in combination with near diffraction-limited confinement of photoactivation using two-photon illumination and 3D localization methods allowed us to investigate a variety of cellular structures at <50 nm lateral and <100 nm axial resolution. Compared to existing methods, we have substantially reduced excitation and bleaching of unlocalized markers, which allows us to use 3D PALM imaging with high localization density in thick structures. Our 3D localization algorithms, which are based on cross-correlation, do not rely on idealized noise models or specific optical configurations. This allows instrument design to be flexible. By generating appropriate fusion constructs and expressing them in Cos7 cells, we could image invaginat! ions of the nuclear membrane, vimentin fibrils, the mitochondrial network and the endoplasmic reticulum at depths of greater than 8 μm. View full text Subject terms: * Microscopy * Imaging * Cell Biology * Single Molecule Figures at a glance * Figure 1: Experimental considerations for 3D PALM. () Wide-field activation (top) and excitation (middle) for localizing molecules (circles) throughout the entire cellular volume (bottom, filled circles). () Confined activation with wide-field excitation for localization. () Sectioning performance of different illumination modalities. Integrated axial response of ~800-nm-thick quantum dot film, moved through 80-μm axial range in 100-nm steps. Fluorescence was integrated over a 25 μm × 25 μm area, yielding the axial response under wide-field (488 nm, blue), conventional temporal focus (800 nm, red) and line-scanning temporal focus (800 nm, cyan) illumination. The last shows reduced FWHM compared to other excitation configurations, and reduced 'tails' at z positions farther from focus. () Images of a 100-nm gold bead at different axial positions. The PSF shape is only coarsely approximated by an elliptical Gaussian function, as aberrations cause the intensity center of mass of the PSF to vary axially and 'tails' to vary as! ymmetrically (arrows). Scale bar, 1 μm. * Figure 2: Improvement over existing 3D PALM. A Cos7 cell expressing PA-mCherry1 targeted to the mitochondrial matrix was simultaneously PALM imaged with both confined (above dashed yellow line) and wide-field (below dashed line) activation. Left: xy maximum-intensity projection. Right: zy maximum-intensity projection. The color map is identical over the entire image. Scale bars, 3 μm. * Figure 3: 3D super-resolution imaging of a mitochondrial network. () xy (top) and xz (bottom) maximum-intensity projections of mitochondrial matrix labeled with PA-mCherry1. White arrows show examples of 'core' regions of higher intensity inside mitochondria. About 1.2 million unlinked localizations are rendered in each view. () Higher-magnification xy (top) and xz (bottom) views of the yellow rectangular regions in , with super-resolved (left) and diffraction-limited (right) views compared. () Higher-magnification xy sections (top three rows) and xz maximum-intensity projections (bottom row) of the blue rectangular regions highlighted in . xy sections were constructed from all localizations in a 75-nm-thick z region, and relative z locations are indicated by dotted lines in the xz maximum-intensity projection. Super-resolved (left) and diffraction-limited (right) views are shown. Arrowheads indicate void regions that are invisible in the diffraction-limited views. Only localizations with correlation strength >0.4 are shown. Histogram bin ! sizes are 60 nm for and 25 nm for and . Supplementary Video 1 steps through xy slices with 60-nm pixel size and 60-nm z separation. Scale bars, 3 μm (), 0.5 μm (,). * Figure 4: 3D super-resolution imaging of an endoplasmic reticulum network. () xy (top) and xz (bottom) maximum-intensity projections of PA-mCherry1 targeted to the endoplasmic reticulum. About 820,000 unlinked localizations were rendered. () Magnified xy views of yellow rectangular region in , comparing super-resolved (left) and diffraction-limited (right) views. Localizations within a 25-nm z slice centered 600 nm above the coverslip are shown. Arrow highlights nuclear membrane, resolved to ~25 nm. () Magnification of blue rectangular region in . Super-resolved xy (left, 125-nm z slice centered 540 nm above coverslip) and xz (right, corresponding to the dotted line in xy view, 50-nm y slice) views are shown in top row, corresponding to the diffraction-limited images in bottom row. () Magnification of white rectangular region in . Super-resolved xy (top, 75-nm z slice centered 120 nm above coverslip) and xz (bottom, corresponding to the dotted line in xy view, 25-nm y slice) views are shown. () Magnification of white rectangular region in , showing! super-resolved (top) and diffraction-limited (bottom) xz views. Three successive xz views are shown, 25 nm thick in y and with 25-nm y spacing between views. Localizations with correlation strength >0.4 are shown. Histogram bin sizes: 60 nm () and 25 nm (–). Supplementary Video 2 steps through xy slices with 60-nm pixel size and 60-nm z separation. Scale bars, 3 μm (), 0.5 μm (–), 0.1 μm (). * Figure 5: 3D PALM imaging of a vimentin network. () xy (top) and xz (bottom) maximum-intensity projections of PA-mCherry1–vimentin. About 1 million unlinked localizations were rendered in each view. Insets show further magnification of white rectangles in xy (lines in xz) maximum-intensity projection, highlighting individual vimentin fibrils in 60-nm-thick z slices (localizations are linked). Arrow, region of fibril with apparent width <100 nm. () Axial extent of vimentin network with z location indicated as a color map. For clarity, localizations corresponding to 0–1.5 μm (top) and 1.5–3 μm (bottom) are shown separately. Arrowheads in and indicate a fibril that persists over >2 μm axially. Only linked localizations with correlation strength >0.4 are shown. Histogram bin sizes are 60 nm for all subfigures. Supplementary Video 3 steps through xy slices with 60-nm pixel size and 60-nm z separation. Scale bars, 3 μm (), 600 nm (insets), 3 μm (). * Figure 6: 3D PALM image up to ~7.5 μm in depth. Fifty-nanometer-thick xy slices of PA-mCherry1–lamin B1 fusions in a fixed Cos7 cell, at axial depths of 1.5 (left), 3 (middle) and 6 μm (right); scale bars, 3 μm. A magnified view (inset) of the highlighted region shows a thin section of membrane resolved to ~50 nm at an axial depth of 6.58 μm (indicated by arrow); scale bar, 1 μm. Only localizations with a correlation strength >0.4 are shown; bin sizes are 50 nm (main panels) and 25 nm (inset). Supplementary Video 4 steps through xy slices of this 3D image with 50-nm pixel size and 50-nm z separation, rendered from ~1.9 million unlinked localizations. Change history * Abstract * Change history * Author information * Supplementary informationCorrigendum 04 March 2011In the version of this article initially published online, the affiliation for Alipasha Vaziri was incorrect. The error has been corrected for the print, PDF and HTML versions of this article. Author information * Abstract * Change history * Author information * Supplementary information Affiliations * Section on High Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, Maryland, USA. * Andrew G York, * Alireza Ghitani & * Hari Shroff * Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. * Alipasha Vaziri * National High Magnetic Field Laboratory and Department of Biological Science, Florida State University, Tallahassee, Florida, USA. * Michael W Davidson * Present address: Research Institute of Molecular Pathology, Vienna, Austria, and Max F. Perutz Laboratories, University of Vienna, Vienna, Austria. * Alipasha Vaziri Contributions A.G.Y., A.G. and H.S. conceived, designed and built the experimental setup. A.G.Y. wrote the analysis code. A.G. and H.S. collected the data. A.G.Y., A.G. and H.S. analyzed the data. M.W.D. and A.V. contributed reagents and materials. A.G.Y., M.W.D. and H.S. wrote the paper. All authors edited and refined the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Andrew G York Author Details * Andrew G York Contact Andrew G York Search for this author in: * NPG journals * PubMed * Google Scholar * Alireza Ghitani Search for this author in: * NPG journals * PubMed * Google Scholar * Alipasha Vaziri Search for this author in: * NPG journals * PubMed * Google Scholar * Michael W Davidson Search for this author in: * NPG journals * PubMed * Google Scholar * Hari Shroff Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Change history * Author information * Supplementary information Movies * Supplementary Video 1 (1M) z-stack of PA-mCherry1-mito fusions, to accompany Figure 3. Histogram bin size is 60 nm, individual frames are separated by 60 nm z steps. Smoothing of σ = 0.4 pixels in each dimension was applied before plotting data. * Supplementary Video 2 (2M) z-stack of PA-mCherry1-ER fusions, to accompany Figure 4. Histogram bin size is 60 nm, individual frames are separated by 60 nm z steps. Smoothing of σ = 0.6 pixels in each dimension was applied before plotting data. * Supplementary Video 3 (4M) z-stack of PA-mCherry1-vimentin fusions, to accompany Figure 5. Histogram bin size is 60 nm, individual frames are separated by 60 nm z steps. Smoothing of σ = 0.6 pixels in each dimension was applied before plotting data. * Supplementary Video 4 (8M) z-stack of PA-mCherry1-lamin fusions, to accompany Figure 6. Histogram bin size is 50 nm, individual frames are separated by 50 nm z steps. Smoothing of σ = 0.75 pixels in each dimension was applied before plotting data. * Supplementary Video 5 (3M) z-stack of PA-mCherry1-lamin fusions, extending over > 8.5 μm imaging depth. Histogram bin size is 60 nm, individual frames are separated by 60 nm z steps. Smoothing of σ = 0.75 pixels in each dimension was applied before plotting data. Zip files * Supplementary Software (52KB) Supplementary Software PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–16, Supplementary Table 1 and Supplementary Notes 1–3 Additional data - Ultrahigh-resolution optical trap with single-fluorophore sensitivity
- Nat Meth 8(4):335-340 (2011)
Nature Methods | Article Ultrahigh-resolution optical trap with single-fluorophore sensitivity * Matthew J Comstock1 * Taekjip Ha1, 2, 3 * Yann R Chemla1, 2 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:335–340Year published:(2011)DOI:doi:10.1038/nmeth.1574Received07 September 2010Accepted18 January 2011Published online20 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 We present a single-molecule instrument that combines a time-shared ultrahigh-resolution dual optical trap interlaced with a confocal fluorescence microscope. In a demonstration experiment, we observed individual single fluorophore–labeled DNA oligonucleotides to bind and unbind complementary DNA suspended between two trapped beads. Simultaneous with the single-fluorophore detection, we clearly observed coincident angstrom-scale changes in tether extension. Fluorescence readout allowed us to determine the duplex melting rate as a function of force. The new instrument will enable the simultaneous measurement of angstrom-scale mechanical motion of individual DNA-binding proteins (for example, single-base-pair stepping of DNA translocases) along with the detection of properties of fluorescently labeled protein (for example, internal configuration). View full text Subject terms: * Biophysics * Single Molecule * Microscopy Figures at a glance * Figure 1: Combined ultrahigh-resolution optical trap and single-molecule fluorescence microscope setup. () Schematic of experimental setup showing dual optical traps (orange cones) trapping two beads with DNA tethered between them, and confocal laser excitation and detection (green cone) for measuring fluorescence from a single fluorophore-labeled molecule (magenta disk) bound to the DNA. Bead-DNA attachments were made via biotin (DNA)–streptavidin (bead) and digoxigenin (DNA)–anti-digoxigenin (bead) linkages. () Instrument layout showing optical paths for 1,064-nm trapping laser (orange), 532-nm fluorescence excitation laser (green), collected fluorescence (magenta) and blue LED for brightfield imaging (blue). Trap and fluorescence lasers were interlaced by AOM1 and AOM2, respectively, driven by RF synthesizers (RF synth) directly controlled by an FPGA chip-based data acquisition and control personal computer (PC) card. Synchronous with laser modulation, the FPGA reads three QPDs that measure trapped bead positions (QPD1) and trap and fluorescence excitation laser intensi! ties (QPD2 and QPD3, respectively, enabling laser intensity stabilization) along with a single-photon–counting APD measuring fluorescence. D1–D4, dichroic mirrors; F1–F4, filters; O1 and O2, objective lenses; PM, piezo mirror stage; T1–T5, telescopes. Conjugate image planes are indicated by asterisks. * Figure 2: Interlacing and timesharing of optical trap and fluorescence excitation lasers. Two optical traps are created in sequence during time intervals A and B via the trap AOM switching between two trap laser intensities and deflection angles (traps in intervals A and B were set to different intensities for clarity in the figure). Trap data acquisition occurs at time points indicated by 'X' and '+' for traps 1 and 2, respectively. The fluorescence excitation laser is only on during time interval C while the trap laser is off. There were 625-ns delays (gray) between switching optical traps off (or on) and fluorescence excitation on (or off). Fluorescence is only collected during time interval C. Laser intensities in the plots were measured by photodetectors and recorded by a digital oscilloscope. * Figure 3: Single fluorophore–labeled oligonucleotide hybridization experiment. () Schematic of experimental setup showing two beads held in dual traps tethered together by 3-kbp dsDNA with a 19-nt single-stranded portion near the center. ssDNA probe strands diffuse in the surrounding solution and bind-unbind the complementary single-stranded region in the tethered DNA. () Fluorescence image acquired using the instrument in such an experiment, with the probe bound to the tethered DNA labeled. Scale bar, 1 μm. () Plot of fluorescence with the confocal measurement localized between the two beads at the probe strand binding location. Fluorescence increases and decreases indicate probe binding and unbinding, respectively. * Figure 4: Combined measurement of fluorescence and DNA tether extension. (–) Fluorescence (,,,, top; 333 ms per data point) and DNA tether extension (bottom; acquired at 66 kHz, boxcar averaged to 3 Hz; black dashed lines are mean extension between binding-unbinding events) were measured simultaneously. Fluorescence increases and decreases indicate probe binding and unbinding, respectively. Data are shown for 10 pN (–) and 3 pN (–) tether tension. Change in tether extension plotted for many binding and unbinding events (,; note that these histograms have transparency and cyan occurs where histograms overlap). () Mean change in tether extension upon binding and unbinding versus tether tension (s.e.m.; n = 90, 114, 63, 19 and 14 for 3, 5, 10, 17 and 20 pN, respectively (error bars are smaller than symbol sizes)). Data points at ~3, 5 and 10 pN include only binding events (to avoid confusing unbinding with photobleaching). The ~15 pN data point includes only unbinding events (photobleaching did not occur given short bound probe lifetime, and i! nsufficient counts of binding were obtained because acquisition was made using a 'wait-and-yank' technique; Online Methods). Dashed line is the zero level. () Semilog plot of duplex lifetime versus tension (s.e.m.; n = 156, 68, 52, 35, and 34 for 3, 5, 10, 17 and 20 pN, respectively). The ~15 and 20 pN data in and were acquired with wait-and-yank technique. Measurements in and at 3, 5, 10, 17 and 20 pN are derived from 71, 35, 20, 17 and 16 unique tether molecules, respectively. Models assume 9 nt or 7 nt (best fit to data) of the 9-nt probe strand stably bind to the tethered DNA. * Figure 5: Proposed reaction diagram illustrating the complete process of probe-strand annealing to and melting from complementary tethered DNA. Two free energy contours versus DNA tether extension are drawn for both the probe strand unbound and bound states. The initial annealing (binding) and final melting (unbinding) transitions are indicated by wavy lines. The location of the annealing transition at the extension of the melting transition was assumed given the reversibility of the reaction, although the precise location was not directly measured. Relaxations and excitations of the DNA tether along the reaction contours are indicated by black arrows. The change in DNA tether extension upon annealing is labeled Δxh. The distance to the melting transition state is labeled Δx0. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Physics and Center for the Physics of Living Cells, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. * Matthew J Comstock, * Taekjip Ha & * Yann R Chemla * Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA. * Taekjip Ha & * Yann R Chemla * Howard Hughes Medical Institute, Urbana, Illinois, USA. * Taekjip Ha Contributions Y.R.C. and T.H. conceived the combined high-resolution trapping with single-molecule fluorescence detection instrument project. M.J.C., Y.R.C. and T.H. designed the instrument. M.J.C. built the instrument including all optics, electronics and control software. M.J.C. performed all experiments and analyzed all the data. M.J.C., Y.R.C. and T.H. wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Yann R Chemla or * Taekjip Ha Author Details * Matthew J Comstock Search for this author in: * NPG journals * PubMed * Google Scholar * Taekjip Ha Contact Taekjip Ha Search for this author in: * NPG journals * PubMed * Google Scholar * Yann R Chemla Contact Yann R Chemla Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–7 and Supplementary Note 1 Additional data - Mapping of signaling networks through synthetic genetic interaction analysis by RNAi
- Nat Meth 8(4):341-346 (2011)
Nature Methods | Article Mapping of signaling networks through synthetic genetic interaction analysis by RNAi * Thomas Horn1, 2, 5 * Thomas Sandmann1, 3, 5 * Bernd Fischer4, 5 * Elin Axelsson4 * Wolfgang Huber4 * Michael Boutros1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:341–346Year published:(2011)DOI:doi:10.1038/nmeth.1581Received23 September 2010Accepted04 February 2011Published online06 March 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 The analysis of synthetic genetic interaction networks can reveal how biological systems achieve a high level of complexity with a limited repertoire of components. Studies in yeast and bacteria have taken advantage of collections of deletion strains to construct matrices of quantitative interaction profiles and infer gene function. Yet comparable approaches in higher organisms have been difficult to implement in a robust manner. Here we report a method to identify genetic interactions in tissue culture cells through RNAi. By performing more than 70,000 pairwise perturbations of signaling factors, we identified >600 interactions affecting different quantitative phenotypes of Drosophila melanogaster cells. Computational analysis of this interaction matrix allowed us to reconstruct signaling pathways and identify a conserved regulator of Ras-MAPK signaling. Large-scale genetic interaction mapping by RNAi is a versatile, scalable approach for revealing gene function and the con! nectivity of cellular networks. View full text Figures at a glance * Figure 1: A multiparametric approach to identify genetic interactions through double-RNAi. (–) Genetic interaction surfaces of double-RNAi treatments over a range of dsRNA concentrations. Axes indicate the amounts of the respective dsRNAs combined per well. Interaction scores (π scores based on cell number phenotypes) are shown on a color scale ranging from −2 (negative interaction) to 2 (positive interaction). () Schematic overview of π score calculation. Single RNAi effects (A and B) are compared to that of a negative control dsRNA targeting firefly luciferase (Fluc). The expected double-RNAi effect is obtained by multiplying the single RNAi effects (arrowhead points to the relative cell number of 50% expected in this example) and compared to the observed double-RNAi phenotype. The π score is the log2 ratio between the observed and the expected value. () Schematic overview of the combinatorial RNAi experiment. Each color corresponds to a single dsRNA in the assay plates. To each plate, a different second dsRNA (RNAi 1–192) is added to all wells. This de! sign creates all possible dsRNA combinations (arrows) targeting each pair of genes, A and B, with two dsRNAs (A1 and A2, and B1 and B2). * Figure 2: Clustering of genetic interaction profiles predicts gene function. () Hierarchical clustering of the genetic interaction profiles based on observed cell number. Known signaling components from the Ras-MAPK pathway (top right) and the JNK pathway (bottom right) are highlighted. mRNA-cap, gene encoding mRNA-capping enzyme. (,) Genetic interaction profiles for Ras-MAPK (right; dark gray) and JNK (right; light gray) regulators based on nuclear area per cell () or mean signal intensity (). Genes in and are ordered as in . * Figure 3: Phenotype-specific genetic interactions. (,) Single-RNAi and double-RNAi effects of targeting Rho1 and/or drk on nuclear area () or cell number (). Observed and expected phenotypes are indicated as percentage relative to the negative control treatment (Fluc dsRNA). () Schematic representation of drk and/or Rho1 RNAi effects on nuclear area and cell number. Images are fluorescence microscopic images of S2 cells after RNAi treatment, stained with Hoechst and antibodies to α-tubulin. Scale bars, 10 μm. * Figure 4: Multiparametric detection of interactions. () Numbers and overlap of genetic interactions based on three different phenotypes at 5% FDR. () Distribution of positive and negative interactions per gene based on analysis of cell numbers at 5% FDR. (,) Double-RNAi plot for CG10376 () and Gap1 (). X axes, single-RNAi effect of the template gene; dashed blue line, single-RNAi effect of the query gene; y axis, the double-RNAi effect; and orange line, expected phenotypes in the absence of interactions (deviations from it indicate positive or negative genetic interactions). () Classification results for known JNK regulators (green), positive (blue) and negative (orange) regulators of Ras-MAPK signaling based on their genetic interaction profiles. Position relative to the apices represents a probabilistic assignment to the three classes (cross-validated posterior class probabilities), circle diameter represents certainty (probability of assignment to either one of the three classes versus background). () Classification results! for all genes not included in the training set (axes and symbols as in ). * Figure 5: Cka is a conserved regulator of Ras/MAPK signaling. () Double-RNAi plot for Cka (axes and labels as in Fig. 4c,d). () Quantitative transcription–PCR analysis of sprouty (sty) mRNA levels. Two non-overlapping dsRNAs to Cka (Cka 1 and Cka 2) were assayed. Error bars s.e.m. (n = 6). *P < 0.05 and **P < 0.01 (Student's t-test), reduced expression compared to luciferase control. () Western blot analysis of basal Rolled phosphorylation in S2 cells after RNAi knockdown of firefly luciferase (Fluc, negative control), Ras85D (positive control) or Cka. () Western blot analysis of basal Erk1/Erk2 phosphorylation in human HEK293T cells after treatment with pGL3 control siRNAs (negative control), siRNAs targeting ERK1 (positive control) or siRNAs targeting Cka (pool of three 1–3 or individual siRNAs 1, 2 and 3). () Immunoprecipitation and western blot analysis of endogenous Cka from S2 cells transfected with HA-epitope-tagged GCKIII using either antibodies to Cka (anti-Cka) or (negative) control serum. () Wings from adult D. melanogas! ter females displaying wild-type (left), mild ectopic (center) or strong ectopic (right) veins. Histogram shows the relative frequency of these phenotypes in ElpB1/CyO controls (n = 30) ElpB1/CkaS1883 (n = 40) and ElpB1/Cka05836 (n = 23) flies. Scale bars, 300 μm (whole wing) and 100 μm (partial wing). () Schematic model of Cka's possible function in Raf activation. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Thomas Horn, * Thomas Sandmann & * Bernd Fischer Affiliations * German Cancer Research Center (Deutsches Krebsforschungszentrum), Division Signaling and Functional Genomics and Heidelberg University, Department of Cell and Molecular Biology, Faculty of Medicine Mannheim, Heidelberg, Germany. * Thomas Horn, * Thomas Sandmann & * Michael Boutros * Heidelberg University, Hartmut Hoffmann-Berling International Graduate School for Molecular and Cellular Biology, Heidelberg, Germany. * Thomas Horn * Heidelberg University, CellNetworks Cluster of Excellence, Heidelberg, Germany. * Thomas Sandmann * European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. * Bernd Fischer, * Elin Axelsson & * Wolfgang Huber Contributions T.H., T.S., B.F., W.H. and M.B. designed the study; T.H. and T.S. performed the experiments; B.F. analyzed the data; E.A. performed initial analyses; T.S., T.H., B.F., W.H. and M.B. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Michael Boutros or * Wolfgang Huber Author Details * Thomas Horn Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas Sandmann Search for this author in: * NPG journals * PubMed * Google Scholar * Bernd Fischer Search for this author in: * NPG journals * PubMed * Google Scholar * Elin Axelsson Search for this author in: * NPG journals * PubMed * Google Scholar * Wolfgang Huber Contact Wolfgang Huber Search for this author in: * NPG journals * PubMed * Google Scholar * Michael Boutros Contact Michael Boutros Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Excel files * Supplementary Table 1 (127K) Primer and amplicon sequences for all targeted genes * Supplementary Table 3 (6M) Genetic interaction data based on cell number, nuclear area, fluorescent intensity PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–22, Supplementary Tables 2,4,5 Additional data - Simultaneous assessment of rodent behavior and neurochemistry using a miniature positron emission tomograph
- Nat Meth 8(4):347-352 (2011)
Nature Methods | Article Simultaneous assessment of rodent behavior and neurochemistry using a miniature positron emission tomograph * Daniela Schulz1 * Sudeepti Southekal2, 5 * Sachin S Junnarkar3 * Jean-François Pratte3, 5 * Martin L Purschke4 * Sean P Stoll4 * Bosky Ravindranath2 * Sri Harsha Maramraju2 * Srilalan Krishnamoorthy2 * Fritz A Henn1, 5 * Paul O'Connor3 * Craig L Woody4 * David J Schlyer1, 2 * Paul Vaska1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:347–352Year published:(2011)DOI:doi:10.1038/nmeth.1582Received27 August 2010Accepted02 February 2011Published online13 March 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 Positron emission tomography (PET) neuroimaging and behavioral assays in rodents are widely used in neuroscience. PET gives insights into the molecular processes of neuronal communication, and behavioral methods analyze the actions that are associated with such processes. These methods have not been directly integrated, because PET studies in animals have until now required general anesthesia to immobilize the subject, which precludes behavioral studies. We present a method for imaging awake, behaving rats with PET that allows the simultaneous study of behavior. Key components include the 'rat conscious animal PET' or RatCAP, a miniature portable PET scanner that is mounted on the rat's head, a mobility system that allows considerable freedom of movement, radiotracer administration techniques and methods for quantifying behavior and correlating the two data sets. The simultaneity of the PET and behavioral data provides a multidimensional tool for studying the functions of di! fferent brain regions and their molecular constituents. View full text Subject terms: * Imaging * Neuroscience Figures at a glance * Figure 1: RatCAP tomograph and validation. () Assembled scanner with dimensions of enclosure. () Internal components during assembly, including lutetium yttrium oxyorthosilicate crystal arrays, avalanche photodiode arrays (APD), integrated circuit microchips (ASIC; not visible), and rigid-flexible printed circuit board. Scale bar, 2 cm. () Phantom validation study including the dimensions of the three-compartment phantom used in the study and the calibrated activity levels of [18F]fluorodeoxyglucose in each compartment (top), a reconstructed image of the phantom (middle) and a profile through compartments with high radioactivity concentration (bottom). Scale bar, 5 mm. () PET images through striata of a conscious rat after a 0.75-mCi injection of [11C]raclopride (5.4 nmol kg−1 body weight), including a horizontal slice summed over the whole 1-h scan overlaid to scale with a rat brain atlas figure30 without any adjustment for rat strain, sex or weight (top) and coronal slice from a single dynamic time frame spanning! 35–45 min after injection (bottom). Scale bars, 2 mm. * Figure 2: Animal mobility system. () Overview of key components of the animal mobility system. Scale bar, 8 cm. () Detail of top gimbal and rotation mechanism. Scale bar, 2 cm. () Three video frames exemplifying the typical range of motion of a rat wearing the PET scanner inside the chamber. Scale bar, 4 cm. () Drawings of actual trajectories made by the rat in the 40 × 40 cm2 test chamber. Tracks reflect the position of the rat's approximate center. Scale bar, 15 cm. () Photograph of a rat showing the result of surgery performed to affix screw sockets and a sleeve to attach the PET scanner to its head. Scale bar, 2 cm. () Photographs showing the improved, self-latching mounting mechanism that obviates the need for momentary anesthesia during attachment, including latched brackets (top), a detail of an animal bracket (bottom left) and a detail of a scanner bracket (bottom right). Scale bars, 2 cm. () Corticosterone levels in rat blood plasma measured at different time points of wearing the RatCAP. The measu! rements were performed on two occasions (sessions 1 and 2) that were 14 d apart. Sampling took place before and 10 min, 1 h, 2 h and 3 h after attachment of the RatCAP. The horizontal line (mean) and shaded area (± s.d.) indicate the levels of corticosterone in a group of rats (n = 10) that underwent only transport between rooms 30 min before the blood sampling. * Figure 3: D2 receptor neuroimaging using bolus injections of [11C]raclopride in the behaving and anesthetized rat. () Activity concentrations of the radiotracer (nCi ml−1) over time in different brain regions. Concentrations are normalized to the injected tracer dose (0.19–0.97 mCi of [11C]raclopride with a raclopride mass of 1.5–7.9 nmol kg−1). The data show average concentrations for the awake scans and scans performed under anesthesia (mean ± s.e.m., n = 5). Comparisons reflect t tests for paired samples. **P < 0.01. () Estimate of specific binding of [11C]raclopride in the striatum. STR, striatum uptake; CB, cerebellum uptake. Bars indicate BPND (mean ± s.e.m., n = 5) for the awake and anesthetized (anes.) states (paired t test, P = 0.18). () Behavioral activity summed for the last 30 min of the awake scans and plotted against specific binding in the striatum for [11C]raclopride ((STR / CB) – 1) (Spearman r = 0.9, P = 0.04, n = 5). All scores indicate ranks. A rank of 1 reflects the lowest score. * Figure 4: Transient changes in BPND in relation to behavioral activity during the PET scan. () Activity concentrations of the radiotracer [11C]raclopride (nCi ml−1) over time in different brain regions of an individual rat, normalized to the total injected dose (0.28 mCi of [11C]raclopride with a raclopride mass of 2.0 nmol kg−1), using B-I infusion. The relative flatness of the regression line fitting the cerebellum data indicates a steady-state condition of the radiotracer. () Estimate of specific binding in the striatum for [11C]raclopride ((STR / CB) – 1) and cumulative behavioral activity measured simultaneously in the same rat. Each point on the behavioral response curve reflects the summed activity over a 2-min period. A slope in the response curve indicates that the rat showed activity, whereas flat regions indicate the absence of activity. Regression lines show the changes in the slope of the behavioral response curve which reflect the slope changes in ((STR / CB) – 1). () Correlation of PET and behavioral data for data points starting at 20 min in! . We subtracted every two successive time points on the PET curve ((STR / CB) – 1) and used the difference scores for correlation with the behavioral data. We cumulated behavioral activity for the time frames provided by the PET data and used the differences between successive time points for correlation analysis. Spearman r = 0.75; P = 0.05. All scores indicate ranks. A rank of 1 reflects the lowest score. * Figure 5: Transient changes in BPND and behavior after D2 receptor blockade. () Activity concentrations of the radiotracer [11C]raclopride (nCi ml−1) over time in different brain regions of an individual rat, normalized to the total injected dose (0.4 mCi of [11C]raclopride with a raclopride mass of 2.5 nmol kg−1), using B-I infusion. Dashed line indicates infusion of cold raclopride (2 mg kg−1; intravenously (i.v.), in less than 1 min). () Images showing uptake of [11C]raclopride before and after the intervention with cold raclopride. Scale bars, 6 mm. () Cumulative behavioral activity before and after the intervention with cold raclopride. Each dot reflects the summed activity over 2 min. A slope in the response curve indicates that the rat showed activity, whereas flat regions indicate the absence of activity. Author information * Abstract * Author information * Supplementary information Affiliations * Medical Department, Brookhaven National Laboratory, Upton, New York, USA. * Daniela Schulz, * Fritz A Henn, * David J Schlyer & * Paul Vaska * Department of Biomedical Engineering, Stony Brook University, Stony Brook, New York, USA. * Sudeepti Southekal, * Bosky Ravindranath, * Sri Harsha Maramraju, * Srilalan Krishnamoorthy, * David J Schlyer & * Paul Vaska * Instrumentation Division, Brookhaven National Laboratory, Upton, New York, USA. * Sachin S Junnarkar, * Jean-François Pratte & * Paul O'Connor * Physics Department, Brookhaven National Laboratory, Upton, New York, USA. * Martin L Purschke, * Sean P Stoll & * Craig L Woody * Present addresses: Brigham & Women's Hospital, Boston, Massachusetts, USA (S.S.); Université de Sherbrooke, Sherbrooke, Quebec, Canada (J.-F.P.); Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA (F.A.H.). * Sudeepti Southekal, * Jean-François Pratte & * Fritz A Henn Contributions D.S. proposed and carried out most of the rat work, acquired and analyzed behavioral data and wrote the paper. S.S. developed quantitative PET data processing and reconstruction software and acquired and analyzed PET data. S.S.J. developed front-end and data acquisition electronics, software and firmware. J.-F.P. developed the front-end microchip. M.L.P. developed data processing and image reconstruction software. S.P.S. assembled and debugged scanner and mechanics. B.R. and S.H.M. acquired rat data and performed data analysis. S.K. constructed scanner components. F.A.H. contributed to the behavioral neuroimaging experiments. P.O. oversaw and conceived key aspects of the electronics. C.L.W. oversaw development of the scanner, especially the front-end detectors and electronics. D.J.S. oversaw development of the scanner and performed rat studies and data analysis. P.V. oversaw development of the scanner, software and mechanics, performed rat studies and wrote the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Paul Vaska Author Details * Daniela Schulz Search for this author in: * NPG journals * PubMed * Google Scholar * Sudeepti Southekal Search for this author in: * NPG journals * PubMed * Google Scholar * Sachin S Junnarkar Search for this author in: * NPG journals * PubMed * Google Scholar * Jean-François Pratte Search for this author in: * NPG journals * PubMed * Google Scholar * Martin L Purschke Search for this author in: * NPG journals * PubMed * Google Scholar * Sean P Stoll Search for this author in: * NPG journals * PubMed * Google Scholar * Bosky Ravindranath Search for this author in: * NPG journals * PubMed * Google Scholar * Sri Harsha Maramraju Search for this author in: * NPG journals * PubMed * Google Scholar * Srilalan Krishnamoorthy Search for this author in: * NPG journals * PubMed * Google Scholar * Fritz A Henn Search for this author in: * NPG journals * PubMed * Google Scholar * Paul O'Connor Search for this author in: * NPG journals * PubMed * Google Scholar * Craig L Woody Search for this author in: * NPG journals * PubMed * Google Scholar * David J Schlyer Search for this author in: * NPG journals * PubMed * Google Scholar * Paul Vaska Contact Paul Vaska Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Zip files * Supplementary Software (194MB) Raw code and input files necessary to process data from the RatCAP scanner into images, including coincidence processing and image reconstruction. PDF files * Supplementary Text and Figures (164K) Supplementary Note Additional data - Two-color nanoscopy of three-dimensional volumes by 4Pi detection of stochastically switched fluorophores
- Nat Meth 8(4):353-359 (2011)
Nature Methods | Article Two-color nanoscopy of three-dimensional volumes by 4Pi detection of stochastically switched fluorophores * Daniel Aquino1 * Andreas Schönle1 * Claudia Geisler1, 3 * Claas v Middendorff1 * Christian A Wurm1 * Yosuke Okamura2 * Thorsten Lang2 * Stefan W Hell1 * Alexander Egner1, 3 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:353–359Year published:(2011)DOI:doi:10.1038/nmeth.1583Received15 July 2010Accepted14 February 2011Published online13 March 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 We demonstrate three-dimensional (3D) super-resolution imaging of stochastically switched fluorophores distributed across whole cells. By evaluating the higher moments of the diffraction spot provided by a 4Pi detection scheme, single markers can be simultaneously localized with <10 nm precision in three dimensions in a layer of 650 nm thickness at an arbitrarily selected depth in the sample. By splitting the fluorescence light into orthogonal polarization states, our 4Pi setup also facilitates the 3D nanoscopy of multiple fluorophores. Offering a combination of multicolor recording, nanoscale resolution and extended axial depth, our method substantially advances the noninvasive 3D imaging of cells and of other transparent materials. View full text Subject terms: * Microscopy * Imaging * Single Molecule Figures at a glance * Figure 1: The 4Pi-SMS microscope. () The sample is sandwiched between two coverslips. Illumination for excitation (exc.) and on-off switching (swi.) occurs through the upper of the two water immersion objective lenses (Obja and Objb). The 4Pi cavity consists of two dichroic mirrors, two quarter-wave plates (λ/4), two modified Babinet-Soleil compensators (Ka and Kb) and a neutral beam splitter (BS). The linear s- and p-polarization states (sa, pa, sb and pb) are separated by the compensators in each cavity arm, and a respective phase difference (Δϕa, Δϕb) is introduced. The superimposed intermediate image pairs p1 and s1, and p2 and s2, generated by the tube lenses (L1), are clipped by the variable apertures (Ap) to fill one quadrant each of the EMCCD chip in parallel. The polarizing beam splitter (PBS) interchanges the partners of the image pairs, which are then imaged via lenses L2 and L3, the metalized prism (MP), a notch filter rejecting the excitation light, and a bandpass filter (N/BP) onto the cam! era. The mirrors are tilted to spatially separate the four detection channels. For two-color imaging, a dichroic filter can be placed in front of the camera. (,) Gaussian-weighted signal (M0; ) and Gaussian-weighted third central moment (M3; ) of the detection channels plotted as a function of the axial marker position. () The propagation of fluorescence light from out of focal plane emitters is described by a segment of a spherical wavefront. Solid and dashed lines represent the wavefronts corresponding to Obja and Objb, respectively. Phase difference between wavefronts is indicated in dark and light blue for the outer and inner parts of the counterpropagating wavefronts, respectively. () Plot of located versus stage position. For each stage position, 300 independent localizations were performed. Insets show distributions of z localizations for the boxed z positions. () Axial localization precision (σz) for a fluorescent bead containing randomly oriented emitters and the ! amount of mislocalization. () Lateral localization precision f! or x dimension (σx) and y dimension (σy). Solid curves in and represent cubic polynomial fits to the data. * Figure 2: 4Pi-SMS imaging of human platelets. () An x–y histogram image of the Rhodamine S–labeled GPIIb/IIIa receptor of a partially activated platelet. The color encodes the axial position of each label. (,) x′–z image (3D position data contracted in y′ direction) of the distribution of labels located in the respective regions indicated in . The color encodes z values as in . (,) z-position histograms for the regions marked in and , respectively. () x–y histogram image of the Atto 532–labeled GPIIb/IIIa receptor of a fully activated platelet. () y–z histogram image (that is, 3D position data contracted in x direction) of the distribution of labels located in the region marked in . The z axis is stretched by a factor of five. (,) z-position histograms for the regions marked in . Red arrows indicate FWHM. Scale bars, 1 μm (,), 200 nm (,), 200 nm () in x direction and z direction. * Figure 3: 4Pi-SMS imaging with extended axial depth. () x–y histogram image of Rhodamine S–labeled tubulin in a Vero cell. The color encodes the axial position of each label. () Close-up of the area indicated in . () z-position histograms for the two regions marked in . () x–z histogram image of the area indicated in . () x′–z histogram image of the distribution of labels located in respective areas indicated in (top), the same images smoothed with a Gaussian (σ = 3.2 nm) for better visibility and respective radial-position histograms. r = (x′2 + z2)0.5. Scale bars, 1 μm (), 500 nm (), 100 nm (), 30 nm (,). * Figure 4: Two-color imaging. () Fluorescence emission spectra of Atto 523 and Atto 565 as well as the transmission spectrum for s- and p-polarized light of the long-pass filter. () s-p histogram of events in the gauge measurement performed on samples immunostained for peroxysomes (Atto 532, cyan) and microtubles (Atto 565, red). Events from Atto 532 had a larger ratio of photons in the p channel versus the s channel (np and ns) owing to the higher transmission of the dichroic. White contours enclose areas with a classification confidence better than 80%. Only events inside these regions were used subsequently, reducing the cross-talk to < 6%. () x–y histogram image of a PtK2 cell immunostained for both peroxysomes (Atto 532) and microtubles (Atto 565). Scale bar, 1 μm. () x–y histogram image of the same cell as in color-coded for z position. Author information * Abstract * Author information * Supplementary information Affiliations * Max Planck Institute for Biophysical Chemistry, Department of NanoBiophotonics, Göttingen, Germany. * Daniel Aquino, * Andreas Schönle, * Claudia Geisler, * Claas v Middendorff, * Christian A Wurm, * Stefan W Hell & * Alexander Egner * Membrane Biochemistry Laboratory, Life and Medical Sciences Institute, University of Bonn, Bonn, Germany. * Yosuke Okamura & * Thorsten Lang * Present address: Laser Laboratory Göttingen e.V., Department of Optical Nanoscopy, Göttingen, Germany. * Claudia Geisler & * Alexander Egner Contributions A.E., A.S., T.L. and S.W.H. conceived and designed the study. D.A., C.G., C.A.W. and Y.O. performed experiments. D.A., A.E., A.S., C.v.M. and C.G. analyzed data. A.E., A.S., T.L. and S.W.H. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Stefan W Hell or * Alexander Egner Author Details * Daniel Aquino Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Schönle Search for this author in: * NPG journals * PubMed * Google Scholar * Claudia Geisler Search for this author in: * NPG journals * PubMed * Google Scholar * Claas v Middendorff Search for this author in: * NPG journals * PubMed * Google Scholar * Christian A Wurm Search for this author in: * NPG journals * PubMed * Google Scholar * Yosuke Okamura Search for this author in: * NPG journals * PubMed * Google Scholar * Thorsten Lang Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan W Hell Contact Stefan W Hell Search for this author in: * NPG journals * PubMed * Google Scholar * Alexander Egner Contact Alexander Egner Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (3M) Supplementary Figures 1–8 and Supplementary Notes 1–2 Additional data
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