Hot off the presses! May 01 Nat Meth

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Latest Articles Include:

• Analyze this
  - Nat Meth 8(5):361 (2011)
  Nature Methods | Editorial Analyze this Journal name:Nature MethodsVolume: 8,Page:361Year published:(2011)DOI:doi:10.1038/nmeth0511-361Published online28 April 2011 In an era of stagnant funding, comparative analyses of methods and tool performance can help researchers do more with less. View full text Additional data
• The author file: Rohit Bhargava and Carol Hirschmugl
  - Nat Meth 8(5):363 (2011)
  Nature Methods | This Month The author file: Rohit Bhargava and Carol Hirschmugl * Monya BakerJournal name:Nature MethodsVolume: 8,Page:363Year published:(2011)DOI:doi:10.1038/nmeth0511-363Published online28 April 2011 Multiple synchrotron beams make infrared imaging faster and clearer. View full text Additional data
• Points of view: The overview figure
  - Nat Meth 8(5):365 (2011)
  Nature Methods | This Month Points of view: The overview figure * Bang Wong1Journal name:Nature MethodsVolume: 8,Page:365Year published:(2011)DOI:doi:10.1038/nmeth0511-365Published online28 April 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. Our goal when writing research papers is to convey information as clearly as possible. In past columns I have suggested several graphic design techniques to improve the clarity of figures. In addition to refining data figures, including overview figures in a research paper provides a framework for readers to understand the experimental design and reported findings. Illustrative schematics in overview figures can make publications accessible to a wider audience. They give context to the data presented. An example of such a figure is one I illustrated (Fig. 1)1. It depicts technology called Hi-C used to determine how cells organize the billions of DNA base pairs. This opening figure is effective because it constructs a mental model for understanding the technology and primes readers to expect DNA sequence information as the primary data type. Figure 1: Overview figures can clarify concepts. Outline of the Hi-C technique used to decipher the three-dimensional structure of the human genome. Reprinted from reference 1. * Full size image (67 KB) * Figures index * Next figure Typical overview figures illustrate a procedure (Fig. 1) or compare conditions such as 'control' and 'experimental' (Fig. 2)2. These figures portray a continuous process as discrete steps. As such, it is imperative that we create continuity through imagery and written descriptions. Each step in the progression is understood by relating it to the previous and subsequent step. For comparisons, differences in the corresponding steps between processes should also be highlighted (Fig. 2). View full text Figures at a glance * Figure 1: Overview figures can clarify concepts. Outline of the Hi-C technique used to decipher the three-dimensional structure of the human genome. Reprinted from reference 1. * Figure 2: Well-ordered compositions and clear visual encodings make schematics easy to follow. Schematic comparing experimental conditions in a pooled RNA interference screen. Reprinted from reference 2. 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
• PhymmBL expanded: confidence scores, custom databases, parallelization and more
  - Nat Meth 8(5):367 (2011)
  Nature Methods | Correspondence PhymmBL expanded: confidence scores, custom databases, parallelization and more * Arthur Brady1 * Steven Salzberg1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Page:367Year published:(2011)DOI:doi:10.1038/nmeth0511-367Published online28 April 2011 : PhymmBL1 is a classification system designed for metagenomics experiments that assigns taxonomic labels to short DNA reads. Since the introduction of PhymmBL in 2009, we made extensive changes and added new features, of which we outline the most important ones here (Supplementary Table 1). We also describe results indicating that PhymmBL effectively classifies samples containing mixed eukaryotic and prokaryotic DNA. PhymmBL combines two components: (i) composition-directed taxonomic predictions from Phymm and (ii) basic local alignment search tool (BLAST)-based homology results2. PhymmBL combines these to label each input sequence with its best guess as to the taxonomy of the source organism. Input sequences as short as 100 base pairs can be phylogenetically classified with PhymmBL more accurately than with any other existing method1 including recently introduced methods (Supplementary Note 1). PhymmBL predicts species, genus, family, order, class and phylum for each read, allowing users to arrange results according to levels of specificity relevant to their research goals. We describe how to configure and operate PhymmBL in a parallelized or grid environment in Supplementary Note 2. PhymmBL's open-source software runs on all UNIX-like systems, is written in Perl and C++ and can be downloaded free of charge (http://www.cbcb.umd.edu/software/phymmbl/; currently version 3.2). To demonstrate PhymmBL's ability to classify eukaryotic DNA, we classified 2,278,901 short reads (average, 276 base pairs) from a permafrost-preserved woolly mammoth bone metagenome3. Before classification, we added a variety of genomes to PhymmBL's local database, representing plants, multicellular animals and protists (Supplementary Table 2). We also built models for the elephant (Loxodonta africana) genome (Elephant Genome Project), expecting that woolly mammoth reads would be labeled as elephant. Our goal was to examine whether PhymmBL could identify eukaryotic DNA as accurately as it had identified bacterial DNA. The most abundant label (59.7%) was indeed elephant (Fig. 1). The next three most abundant predictions were Flavobacterium johnsoniae (2.4%), Polaromonas naphthalenivorans (1.6%) and Polaromonas sp. JS666 (1.0%), all three of which are known Arctic bacteria. These likely represent modern bacterial species present on the mammoth bone. PhymmBL therefore effectively separated eukaryotic from prokaryotic reads and accurately predicted the closest relative of the particular eukaryote that was sequenced, despite the presence of other potentially competing eukaryotic genomes in the local database. Details of the computational resources used by PhymmBL are available in Supplementary Note 3. back to article Figure 1: Screenshot of predicted genus-level taxonomic distribution for the mammoth metagenome, focused on genus Loxodonta. * Figures index back to article View full text Author information * Author information * Supplementary information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA. * Arthur Brady & * Steven Salzberg Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Arthur Brady Author Details * Arthur Brady Contact Arthur Brady Search for this author in: * NPG journals * PubMed * Google Scholar * Steven Salzberg Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (156K) Supplementary Tables 1–2, Supplementary Notes 1–4 Additional data
• Brain function marries anatomy
  - Nat Meth 8(5):369 (2011)
  Nature Methods | Research Highlights Brain function marries anatomy * Erika PastranaJournal name:Nature MethodsVolume: 8,Page:369Year published:(2011)DOI:doi:10.1038/nmeth0511-369Published online28 April 2011 Researchers have taken first steps toward functional connectomics. By combining large-scale serial electron microscopy and functional imaging data, the structure of neural networks can be related to their function. View full text Subject terms: * Neuroscience Additional data Author Details * Erika Pastrana Search for this author in: * NPG journals * PubMed * Google Scholar
• Understanding sleeping sickness
  - Nat Meth 8(5):370-371 (2011)
  Nature Methods | Research Highlights Understanding sleeping sickness * Nicole RuskJournal name:Nature MethodsVolume: 8,Pages:370–371Year published:(2011)DOI:doi:10.1038/nmeth0511-370bPublished online28 April 2011 High-coverage sequencing of RNA interference targets gives insight into parasite phenotypes. View full text Subject terms: * Genomics Additional data Author Details * Nicole Rusk Search for this author in: * NPG journals * PubMed * Google Scholar
• One particle to rule them all?
  - Nat Meth 8(5):370-371 (2011)
  Nature Methods | Research Highlights One particle to rule them all? * Natalie de SouzaJournal name:Nature MethodsVolume: 8,Pages:370–371Year published:(2011)DOI:doi:10.1038/nmeth0511-370aPublished online28 April 2011 Nanoparticles made of the natural pigment porphyrin combine desirable properties of both organic and inorganic particles. View full text Subject terms: * Imaging Additional data Author Details * Natalie de Souza Search for this author in: * NPG journals * PubMed * Google Scholar
• News in brief
  - Nat Meth 8(5):371 (2011)
  Nature Methods | Research Highlights News in brief Journal name:Nature MethodsVolume: 8,Page:371Year published:(2011)DOI:doi:10.1038/nmeth0511-371Published online28 April 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. Temperature-sensitive yeast mutants Li et al. present a collection of temperature-sensitive mutants of almost half of the essential genes in yeast, in a genetic background appropriate for interaction screening using the synthetic genetic array method. Barcoding of the collection permits chemical-genetic suppression screening and combination with fluorescent markers of subcellular structures enables high-content screening of double-mutant phenotypes in single cells. Li, Z.et al. Nat. Biotechnol. 29, 361–367 (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
• Highlighting enhancers
  - Nat Meth 8(5):373 (2011)
  Nature Methods | Research Highlights Highlighting enhancers * Monya BakerJournal name:Nature MethodsVolume: 8,Page:373Year published:(2011)DOI:doi:10.1038/nmeth0511-373Published online28 April 2011 Maps of chromatin-state dynamics identify regulatory elements across nine human cell types. View full text Subject terms: * Epigenetics Additional data Author Details * Monya Baker Search for this author in: * NPG journals * PubMed * Google Scholar
• Speeding up RNAi
  - Nat Meth 8(5):374 (2011)
  Nature Methods | Research Highlights Speeding up RNAi * Erika PastranaJournal name:Nature MethodsVolume: 8,Page:374Year published:(2011)DOI:doi:10.1038/nmeth0511-374Published online28 April 2011 A recent study turns the creation of conditional short hairpin RNA transgenic mice into a rapid, flexible and scalable process. View full text Subject terms: * Molecular Biology Additional data Author Details * Erika Pastrana Search for this author in: * NPG journals * PubMed * Google Scholar
• A fountain of youth (for worms)
  - Nat Meth 8(5):376 (2011)
  Nature Methods | Research Highlights A fountain of youth (for worms) * Allison DoerrJournal name:Nature MethodsVolume: 8,Page:376Year published:(2011)DOI:doi:10.1038/nmeth0511-376Published online28 April 2011 A compound for staining amyloid aggregates is found to slow aging and increase lifespan in Caenorhabditis elegans. View full text Subject terms: * Model Organisms Additional data Author Details * Allison Doerr Search for this author in: * NPG journals * PubMed * Google Scholar
• Long noncoding RNAs: the search for function
  - Nat Meth 8(5):379-383 (2011)
  Nature Methods | Technology Feature Long noncoding RNAs: the search for function * Monya Baker1Journal name:Nature MethodsVolume: 8,Pages:379–383Year published:(2011)DOI:doi:10.1038/nmeth0511-379Published online28 April 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 Transcripts are easy to find: sorting out what they do is a challenge. View full text Author information * Abstract * Author information 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
• Shining a new light into molecular workings
  - Nat Meth 8(5):385-387 (2011)
  Nature Methods | News and Views Shining a new light into molecular workings * Francis L Martin1Journal name:Nature MethodsVolume: 8,Pages:385–387Year published:(2011)DOI:doi:10.1038/nmeth.1594Published online28 April 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 technique to substantially increase the resolution and imaging area of Fourier-transform infrared microspectroscopy, while decreasing the amount of time required for image acquisition, may augment the use of this technology in biomedical and environmental research. 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 * Francis L. Martin is at the Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Francis L Martin Author Details * Francis L Martin Contact Francis L Martin 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
• Keeping things simple
  - Nat Meth 8(5):389-390 (2011)
  Nature Methods | News and Views Keeping things simple * Mahendra Rao1Journal name:Nature MethodsVolume: 8,Pages:389–390Year published:(2011)DOI:doi:10.1038/nmeth.1598Published online28 April 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. Improved methods for human pluripotent stem cell culture and for reprogramming of human somatic cells to pluripotency may bring us closer to the routine generation of personalized pluripotent stem cells. 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 * Mahendra Rao is at Stem Cells and Regenerative Medicine, Life Technologies, Frederick, Maryland, USA. Competing financial interests M.R. is an employee of LIFE Technology, which makes tools and reagents for the regenerative medicine space. Corresponding author Correspondence to: * Mahendra Rao Author Details * Mahendra Rao Contact Mahendra Rao 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
• High-content screening: getting more from less
  - Nat Meth 8(5):390-391 (2011)
  Nature Methods | News and Views High-content screening: getting more from less * J. Philip McCoy Jr1Journal name:Nature MethodsVolume: 8,Pages:390–391Year published:(2011)DOI:doi:10.1038/nmeth.1599Published online28 April 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 parallel microfluidic cytometer combines low-pixel-count, one-dimensional images with parallel-channel flow cytometry for high-speed, high-throughput screening of cells. 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 * J. Philip McCoy Jr. is at the Flow Cytometry Core, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * J. Philip McCoy Jr Author Details * J. Philip McCoy Jr Contact J. Philip McCoy Jr 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
• Two-photon absorption properties of fluorescent proteins
  - Nat Meth 8(5):393-399 (2011)
  Nature Methods | Perspective Two-photon absorption properties of fluorescent proteins * Mikhail Drobizhev1 * Nikolay S Makarov1, 4 * Shane E Tillo2, 4 * Thomas E Hughes2 * Aleksander Rebane1, 3 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:393–399Year published:(2011)DOI:doi:10.1038/nmeth.1596Published online28 April 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 Two-photon excitation of fluorescent proteins is an attractive approach for imaging living systems. Today researchers are eager to know which proteins are the brightest and what the best excitation wavelengths are. Here we review the two-photon absorption properties of a wide variety of fluorescent proteins, including new far-red variants, to produce a comprehensive guide to choosing the right fluorescent protein and excitation wavelength for two-photon applications. View full text Subject terms: * Biophysics * Molecular Engineering * Imaging * Sensors and Probes Figures at a glance * Figure 1: One- and two-photon absorption spectra of fluorescent proteins with different chromophores. Two-photon absorption spectra (σ2) are presented versus laser wavelength, used for excitation. For the purpose of comparison, in one-photon absorption spectra (ε) the actual excitation wavelength is multiplied by a factor of two. All spectra are presented in absolute values determined per mature chromophore. Data are reproduced in part from ref. 11. Copyright 2009 American Chemical Society. * Figure 2: Structure of the two-photon absorption spectrum of a fluorescent protein. One-photon absorption and two-photon absorption spectra of TagRFP (top). Jablonski diagram of 1PA and 2PA transitions (bottom). * Figure 3: One-photon absorption of the 'Fruit' proteins does not predict which is the brightest two-photon probe. (,) The 1PA () and 2PA () spectra of the Fruit series of fluorescent proteins. Adopted from ref. 11. Copyright 2009 American Chemical Society. * Figure 4: Two-photon absorption is highly sensitive to the electric field in the protein environment. Dependence of the 2PA peak cross-section and the 1PA peak extinction on the change of permanent dipole moment of chromophore upon excitation, |Δ10| in the 'Fruit' protein series. |Δ10| is a metric of electric field intensity. Error bars, s.d. * Figure 5: Matching of two-photon excitation spectra of red fluorescent proteins with the optimum tissue transparency and with the wavelengths of some short-pulse laser systems. () Typical tissue transparency window39 (gray) presented as attenuation coefficient (left y axis), two-photon excitation (2PE) brightness spectra per protein chain of tdTomato and tdKatushka2, (right y axis), and their corresponding normalized fluorescence spectra. () Effective laser efficiency relevant to two-photon excitation (average power squared divided by repetition rate and pulse duration) of several commercial femtosecond lasers. Author information * Abstract * Author information * Supplementary information Affiliations * Department of Physics, Montana State University, Bozeman, Montana, USA. * Mikhail Drobizhev, * Nikolay S Makarov & * Aleksander Rebane * Department of Cell Biology and Neuroscience, Montana State University, Bozeman, Montana, USA. * Shane E Tillo & * Thomas E Hughes * National Institute of Chemical Physics and Biophysics, Akadeemia tee, Tallinn, Estonia. * Aleksander Rebane * Present addresses: School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, USA (N.S.M.) and Vollum Institute, Oregon Health and Science University, Portland, Oregon, USA (S.E.T.). * Nikolay S Makarov & * Shane E Tillo Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Mikhail Drobizhev Author Details * Mikhail Drobizhev Contact Mikhail Drobizhev Search for this author in: * NPG journals * PubMed * Google Scholar * Nikolay S Makarov Search for this author in: * NPG journals * PubMed * Google Scholar * Shane E Tillo Search for this author in: * NPG journals * PubMed * Google Scholar * Thomas E Hughes Search for this author in: * NPG journals * PubMed * Google Scholar * Aleksander Rebane 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 1–3, Supplementary Tables 1–2, Supplementary Methods Additional data
• A parallel microfluidic flow cytometer for high-content screening
  - Nat Meth 8(5):401-403 (2011)
  Nature Methods | Brief Communication A parallel microfluidic flow cytometer for high-content screening * Brian K McKenna1 * James G Evans1 * Man Ching Cheung1 * Daniel J Ehrlich1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:401–403Year published:(2011)DOI:doi:10.1038/nmeth.1595Received14 January 2011Accepted18 March 2011Published online10 April 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg A parallel microfluidic cytometer (PMC) uses a high-speed scanning photomultiplier-based detector to combine low-pixel-count, one-dimensional imaging with flow cytometry. The 384 parallel flow channels of the PMC decouple count rate from signal-to-noise ratio. Using six-pixel one-dimensional images, we investigated protein localization in a yeast model for human protein misfolding diseases and demonstrated the feasibility of a nuclear-translocation assay in Chinese hamster ovary (CHO) cells expressing an NFκB-EGFP reporter. View full text Subject terms: * Bioinformatics * Imaging * Lab-on-a-chip * Cell Biology Figures at a glance * Figure 1: High-content screening on a PMC. () Schematic of the device. () Left, simulated 2D microscopy images. The dashed arrow shows the location of the single 1D scan with reporter fluorescence shown in green and a red fluorescent whole-cell marker in orange. Right, typical two-color 1D images that are produced by the PMC. (,) Simulation of phenotyping with 1D images of the 'positive' S. cerevisiae phenotype exhibiting induced α-Syn–GFP focal aggregates () and the negative phenotype with diffuse and membrane localized α-Syn–GFP (). Scale bars, 5 μm. () Simulation model counts of 1D image classes (Sym, Asym and RO) from 400 scans, when a cell was scanned with the indicated round (1−7 μm diameter) and rectangular (8 μm × 1 μm to 8 μm × 5 μm) laser spots. * Figure 2: Phenotyping α-Syn–GFP aggregation by PMC imaging. () Kolmogorov-Smirnov test of 82 features for three positive (S12–S14) and three negative (S21–S23) samples displayed as a P-value heatmap with increasing probability from blue to red. () Plots of cumulative distribution functions (CDFs) for the Kolmogorov-Smirnov test (K-S), shown for two features for a positive and negative sample (left). Kolmogorov-Smirnov heat-map signatures (right) show the difference in CDF plots generated for six yeast samples across seven features. Control red features were total intensity ratio around signal peak (F60), intensity perimeter around signal peak (F64) and red perimeter ratio around calculated object center (F65). Discriminating features were green area around red peak (F63), green perimeter ratio around object center (F67), the ratio F67:F65 (F71) and green P2A:red P2A (P2A = perimeter2/2π × area) (F82). () Images showing aggregated (positive) S. cerevisiaeα-Syn–GFP samples (S12 and S14) and nonaggregated (negative) samples (S2! 1 and S23). Scale bar, 15 μm. () Single-cell event distribution across three 1D image classes for positive and negative samples. Author information * Author information * Supplementary information Affiliations * Boston University, Departments of Biomedical Engineering, and Electrical and Computer Engineering, Boston, Massachusetts, USA. * Brian K McKenna, * James G Evans, * Man Ching Cheung & * Daniel J Ehrlich Contributions B.K.M., J.G.E., M.C.C. and D.J.E. designed the research; B.K.M., M.C.C., J.G.E. and D.J.E. performed the engineering and experiments; B.K.M. and M.C.C. wrote analytical software and performed the data analysis; and all authors contributed to writing the paper. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Daniel J Ehrlich Author Details * Brian K McKenna Search for this author in: * NPG journals * PubMed * Google Scholar * James G Evans Search for this author in: * NPG journals * PubMed * Google Scholar * Man Ching Cheung Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel J Ehrlich Contact Daniel J Ehrlich Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (5M) Supplementary Figures 1–14, Supplementary Table 1 Additional data
• A genome-scale shRNA resource for transgenic RNAi in Drosophila
  - Nat Meth 8(5):405-407 (2011)
  Nature Methods | Brief Communication A genome-scale shRNA resource for transgenic RNAi in Drosophila * Jian-Quan Ni1, 5, 6 * Rui Zhou1, 5, 6 * Benjamin Czech2, 6 * Lu-Ping Liu1, 5 * Laura Holderbaum1 * Donghui Yang-Zhou1 * Hye-Seok Shim1 * Rong Tao1 * Dominik Handler3 * Phillip Karpowicz1 * Richard Binari1 * Matthew Booker1 * Julius Brennecke3 * Lizabeth A Perkins4 * Gregory J Hannon2 * Norbert Perrimon1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:405–407Year published:(2011)DOI:doi:10.1038/nmeth.1592Received22 November 2010Accepted14 March 2011Published online03 April 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Existing transgenic RNAi resources in Drosophila melanogaster based on long double-stranded hairpin RNAs are powerful tools for functional studies, but they are ineffective in gene knockdown during oogenesis, an important model system for the study of many biological questions. We show that shRNAs, modeled on an endogenous microRNA, are extremely effective at silencing gene expression during oogenesis. We also describe our progress toward building a genome-wide shRNA resource. View full text Subject terms: * Small RNAs * Genetics * Genomics Figures at a glance * Figure 1: Design of shRNA constructs and phenotypes of shRNA-mediated gene silencing. () Structure of the Drosophila miR-1 and shRNA hairpins (miR-1 nucleotides replaced by the sequence of interest are indicated by N). () Phase contrast images showing ovary phenotypes associated with knockdown of bag-of-marbles (shRNA to bam, labeled shRNA-bam) and ovarian tumor (shRNA-otu) in MTD-Gal4/UAS-shRNA females (using Valium20). DAPI images show single tumorous egg chamber and wild-type egg chamber. Scale bars, 500 μm (phase contrast) and 200 μm (DAPI). () Dark field images of the cuticle of wild-type embryo and embryos derived from MTD-Gal4/UAS-shRNA females. Scale bars, 100 μm. () Knockdown of Notch in the wing using C96-Gal4/UAS-shRNA-N. Scale bars, 400 μm. () Knockdown of white using GMR-Gal4. In the labels, hp stands for hairpin. Scale bars, 100 μm. * Figure 2: Analysis of the piRNA pathway during oogenesis. () Immunofluorescence staining of early egg chambers showing depletion of the indicated piRNA pathway components using specific antibodies (green) upon shRNA expression via MTD-Gal4 (using Valium22). DNA was visualized with DAPI (blue). Black and white images are of the antibody staining only. Scale bars, 20 μm. () Fertility rates of females in which the indicated genes were knocked down with shRNAs in the germline via MTD-Gal4 (using Valium22). For each knockdown 300–500 eggs were counted. () Fold changes in steady-state RNA levels of the transposable elements HeT-A and blood in comparison to the germline-specific nanos transcript upon knockdown of the indicated genes via shRNAs. The data were compared to a control sample in which the white gene was knocked down (rp49 transcript levels were used for normalization). Data are averages of three independent biological replicates; error bars, s.d. () Immunofluorescence staining of early egg chambers with an antibody to the I-! element ORF1p. Left two images are of flies expressing shRNA-spn-E with MTD-Gal4 (using Valium22); right two images are of wild-type flies. DNA was visualized with DAPI (blue). Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE27039 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Jian-Quan Ni, * Rui Zhou & * Benjamin Czech Affiliations * Department of Genetics, Harvard Medical School, Howard Hughes Medical Institute, Boston, Massachusetts, USA. * Jian-Quan Ni, * Rui Zhou, * Lu-Ping Liu, * Laura Holderbaum, * Donghui Yang-Zhou, * Hye-Seok Shim, * Rong Tao, * Phillip Karpowicz, * Richard Binari, * Matthew Booker & * Norbert Perrimon * Watson School of Biological Sciences, Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. * Benjamin Czech & * Gregory J Hannon * Institute of Molecular Biotechnology, Vienna, Austria. * Dominik Handler & * Julius Brennecke * Pediatric Surgical Research Labs, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA. * Lizabeth A Perkins * Present addresses: Gene Regulation Laboratory and Tsinghua Fly Center, School of Life Sciences and School of Medicine, Tsinghua University, Beijing, China (J.-Q.N. and L.-P.L.) and Sanford-Burnham Medical Research Institute, La Jolla, California, USA (R.Z.). * Jian-Quan Ni, * Rui Zhou & * Lu-Ping Liu Contributions J.-Q.N., R.Z. and B.C. carried out major experiments; L.-P.L., L.H., D.Y.-Z., H.-S.S., R.B., M.B. and L.A.P. produced the TRiP lines; P.K. performed the luciferase experiments in ovaries; D.H. and J.B. analyzed the piRNA pathway during oogenesis; and G.J.H. and N.P. supervised the project. R.Z., B.C., J.-Q.N., D.H., J.B., G.J.H. and N.P. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Norbert Perrimon Author Details * Jian-Quan Ni Search for this author in: * NPG journals * PubMed * Google Scholar * Rui Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Benjamin Czech Search for this author in: * NPG journals * PubMed * Google Scholar * Lu-Ping Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Laura Holderbaum Search for this author in: * NPG journals * PubMed * Google Scholar * Donghui Yang-Zhou Search for this author in: * NPG journals * PubMed * Google Scholar * Hye-Seok Shim Search for this author in: * NPG journals * PubMed * Google Scholar * Rong Tao Search for this author in: * NPG journals * PubMed * Google Scholar * Dominik Handler Search for this author in: * NPG journals * PubMed * Google Scholar * Phillip Karpowicz Search for this author in: * NPG journals * PubMed * Google Scholar * Richard Binari Search for this author in: * NPG journals * PubMed * Google Scholar * Matthew Booker Search for this author in: * NPG journals * PubMed * Google Scholar * Julius Brennecke Search for this author in: * NPG journals * PubMed * Google Scholar * Lizabeth A Perkins Search for this author in: * NPG journals * PubMed * Google Scholar * Gregory J Hannon Search for this author in: * NPG journals * PubMed * Google Scholar * Norbert Perrimon Contact Norbert Perrimon Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–8, Supplementary Tables 1–3 and Supplementary Notes 1–3 Additional data
• A more efficient method to generate integration-free human iPS cells
  - Nat Meth 8(5):409-412 (2011)
  Nature Methods | Brief Communication A more efficient method to generate integration-free human iPS cells * Keisuke Okita1 * Yasuko Matsumura1 * Yoshiko Sato1 * Aki Okada1 * Asuka Morizane1, 2 * Satoshi Okamoto3 * Hyenjong Hong1 * Masato Nakagawa1 * Koji Tanabe1 * Ken-ichi Tezuka4 * Toshiyuki Shibata5 * Takahiro Kunisada4 * Masayo Takahashi1, 3 * Jun Takahashi1, 2 * Hiroh Saji6 * Shinya Yamanaka1, 7, 8, 9 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:409–412Year published:(2011)DOI:doi:10.1038/nmeth.1591Received29 October 2010Accepted08 February 2011Published online03 April 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We report a simple method, using p53 suppression and nontransforming L-Myc, to generate human induced pluripotent stem cells (iPSCs) with episomal plasmid vectors. We generated human iPSCs from multiple donors, including two putative human leukocyte antigen (HLA)-homozygous donors who match ~20% of the Japanese population at major HLA loci; most iPSCs are integrated transgene-free. This method may provide iPSCs suitable for autologous and allologous stem-cell therapy in the future. View full text Subject terms: * Stem Cells * Cell Biology Figures at a glance * Figure 1: Establishment of human iPSCs. () Combinations of reprogramming factors and episomal vectors used in this study. () Episomal expression vectors in the Y4 combination. CAG, CAG promoter; WPRE, woodchuck hepatitis post-transcriptional regulatory element; and pA, polyadenylation signal. () Schematic of the pla-iPSC induction protocol. DMEM, Dulbecco's modified Eagle medium; FBS, fetal bovine serum; MSCGM, mesenchymal stem cell growth medium; bFGF, basic fibroblast growth factor. () Numbers of colonies per 1.0 × 105 cells obtained with different combinations of reprogramming factors. Control, cells transduced with episomal vector encoding EGFP; MEF, mouse embryonic fibroblasts; SNL, mouse embryonic fibroblast cell line. Data are means ± s.d. of numbers of ESC-like colonies obtained from 15 independent induction experiments using five cell lines. ****P < 0.05 against T1, T2, T3 and control; ***P < 0.05 against T1, T3 and control; **P < 0.05 against T1 and control; *P < 0.05 against control. * Figure 2: Characterization of pla-iPSC clones. (,) Phase contrast images of an established pla-iPSC line. Scale bars, 1 mm () and 100 μm (). () RT-PCR analyses for pluripotent cell markers. Total RNA was isolated from pla-iPSC clones established with the Y1 (clone 454B-1), Y2 (454C-2), Y3 (454D-1) or Y4 (454E-2, 451F-3, 457C-1 and 453F-2) combinations, from retrovirus-derived iPSC clones (retro-iPSC) and from ESC lines. In the lanes labeled OCT3/4 and SOX2, PCR primers only detected endogenous gene expression; in the Ret-OCT lane, PCR primers specifically amplified the retroviral OCT3/4 transgene. GAPDH was used as a loading control. As a negative control, GAPDH amplification was also performed without reverse transcription (no RT). Fibroblasts 4 d after electroporation of the Y4 mixture (HDF-elepo) and mouse embryonic fibroblast cell line (SNL) were used as other negative controls. () DNA methylation status of the NANOG promoter region in the indicated cell lines. Open and closed circles indicate unmethylated and methy! lated CpG dinucleotides, respectively. () Copy numbers of episomal vectors in pla-iPSC clones. Numbers in parentheses indicate passage number. Also shown are the estimated numbers of cells analyzed for each clone. Fibroblasts 6 d after electroporation of the Y4 combination were analyzed (fibro-d6) as a positive control. (–) Differentiation of pla-iPSC clone (454E-2) into dopaminergic neurons. Micrographs are immunostained for Tuj1 () and tyrosine hydroxylase (TH) (). A merged image with nuclear staining using DAPI () is shown. Scale bars, 20 μm. (,) Differentiation of pla-iPS clone (454E-2) into retinal pigment epithelial cells. Scale bars, 100 μm () and 50 μm (). * Figure 3: Estimated coverage of the Japanese population by HLA homozygous donors. () Estimated cumulative coverage of the Japanese population by theoretical unique HLA homozygous donors at HLA-A, HLA-B and HLA-DRB1 loci with four-digit specification. () Estimated numbers of donors required to identify individuals with unique HLA homozygous haplotypes. Author information * Author information * Supplementary information Affiliations * Center for iPS Cell Research and Application, Kyoto University, Kyoto, Japan. * Keisuke Okita, * Yasuko Matsumura, * Yoshiko Sato, * Aki Okada, * Asuka Morizane, * Hyenjong Hong, * Masato Nakagawa, * Koji Tanabe, * Masayo Takahashi, * Jun Takahashi & * Shinya Yamanaka * Department of Biological Repair, Institute for Frontier Medical Sciences, Kyoto University, Kyoto, Japan. * Asuka Morizane & * Jun Takahashi * Laboratory for Retinal Regeneration, Center for Developmental Biology, RIKEN, Kobe, Japan. * Satoshi Okamoto & * Masayo Takahashi * Department of Tissue and Organ Development, Gifu University Graduate School of Medicine, Gifu, Japan. * Ken-ichi Tezuka & * Takahiro Kunisada * Department of Oral and Maxillofacial Science, Gifu University Graduate School of Medicine, Gifu, Japan. * Toshiyuki Shibata * Human Leukocyte Antigen (HLA) Laboratory, Kyoto, Japan. * Hiroh Saji * Institute for Integrated Cell-Material Sciences, Kyoto University, Kyoto, Japan. * Shinya Yamanaka * Yamanaka Induced Pluripotent Stem Cell Project, Japan Science and Technology Agency, Kawaguchi, Japan. * Shinya Yamanaka * Gladstone Institute of Cardiovascular Disease, San Francisco, California, USA. * Shinya Yamanaka Contributions K.O. and S.Y. conceived the project and wrote the manuscript. K.O. constructed the vectors with H.H., M.N. and K. Tanabe, and conducted most of the experiments with Y.M., Y. S. and A.O. A.M. and J.T. carried out the differentiation experiment into dopaminergic neurons. S.O. and M.T. performed differentiation into retinal pigment epithelial cells. K. Tezuka., T.S. and T.K. established dental pulp cell lines. H.S. performed HLA haplotyping in Japanese population and supervised HLA analysis. Competing financial interests K.O., M.N. and S.Y. are filing a patent application to Japan, US and EU based on the results reported in this paper (PCT/JP2010/063733). S.Y. is a member of Scientific Advisory Board for iPS Academia Japan Inc. and iPierian Inc., which manage the patents. Corresponding authors Correspondence to: * Keisuke Okita or * Shinya Yamanaka Author Details * Keisuke Okita Contact Keisuke Okita Search for this author in: * NPG journals * PubMed * Google Scholar * Yasuko Matsumura Search for this author in: * NPG journals * PubMed * Google Scholar * Yoshiko Sato Search for this author in: * NPG journals * PubMed * Google Scholar * Aki Okada Search for this author in: * NPG journals * PubMed * Google Scholar * Asuka Morizane Search for this author in: * NPG journals * PubMed * Google Scholar * Satoshi Okamoto Search for this author in: * NPG journals * PubMed * Google Scholar * Hyenjong Hong Search for this author in: * NPG journals * PubMed * Google Scholar * Masato Nakagawa Search for this author in: * NPG journals * PubMed * Google Scholar * Koji Tanabe Search for this author in: * NPG journals * PubMed * Google Scholar * Ken-ichi Tezuka Search for this author in: * NPG journals * PubMed * Google Scholar * Toshiyuki Shibata Search for this author in: * NPG journals * PubMed * Google Scholar * Takahiro Kunisada Search for this author in: * NPG journals * PubMed * Google Scholar * Masayo Takahashi Search for this author in: * NPG journals * PubMed * Google Scholar * Jun Takahashi Search for this author in: * NPG journals * PubMed * Google Scholar * Hiroh Saji Search for this author in: * NPG journals * PubMed * Google Scholar * Shinya Yamanaka Contact Shinya Yamanaka Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information Excel files * Supplementary Table 8 (406K) Haplotype frequency for HLA-A, HLA-B and HLA-DRB1 loci in Japanese population. PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–9 and Supplementary Tables 1–7 and 9, 10 Additional data
• High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams
  - Nat Meth 8(5):413-416 (2011)
  Nature Methods | Brief Communication High-resolution Fourier-transform infrared chemical imaging with multiple synchrotron beams * Michael J Nasse1, 2 * Michael J Walsh3 * Eric C Mattson1 * Ruben Reininger4 * André Kajdacsy-Balla5 * Virgilia Macias5 * Rohit Bhargava3 * Carol J Hirschmugl1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:413–416Year published:(2011)DOI:doi:10.1038/nmeth.1585Received18 October 2010Accepted22 February 2011Published online20 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 Conventional Fourier-transform infrared (FTIR) microspectroscopic systems are limited by an inevitable trade-off between spatial resolution, acquisition time, signal-to-noise ratio (SNR) and sample coverage. We present an FTIR imaging approach that substantially extends current capabilities by combining multiple synchrotron beams with wide-field detection. This advance allows truly diffraction-limited high-resolution imaging over the entire mid-infrared spectrum with high chemical sensitivity and fast acquisition speed while maintaining high-quality SNR. View full text Subject terms: * Imaging * Chemical Biology * Microscopy * Chemistry Figures at a glance * Figure 1: FTIR imaging with a multibeam synchrotron source. () Schematic of the experimental setup. M1–M4 are mirror sets. () A full 128 × 128 pixel FPA image with 12 overlapping beams illuminating an area of ~50 μm × 50 μm. Scale bar, 40 μm. () A visible-light photograph of the 12 beams projected on a screen in the beam path (dashed box in ). Scale bar, ~1.5 cm. We display the beams as one beam from then on in the schematics. Each beam exhibits a shadow cast by a cooling tube upstream, which is not shown in . () Long-exposure photograph showing the combination of the 12 individual beams into the beam bundle by mirrors M3 and M4. Scale bar, ~20 cm. * Figure 2: Chemical images from various FTIR systems. (–) The same cancerous prostate tissue section (area, ~280 μm × 310 μm) measured with different instruments, using the integrated absorbance of the CH-stretching region (2,800–3,000 cm−1), without dyes or stains. We processed all images identically (baseline correction only) and used the same color scale (color bar in ; AU, absorbance units). Scale bars, 100 μm and in insets, 10 μm. Images acquired with a conventional table-top system (PerkinElmer Spotlight) equipped with a thermal source in raster-scanning mode (10 μm × 10 μm; ) and linear array mode (6.25 μm × 6.25 μm; ), with an FTIR imaging system (Varian Stingray) equipped with a 64 pixel × 64 pixel FPA (5.5 × 5.5 μm per pixel at the sample plane; ) and with our multibeam synchrotron-based imaging system (pixel size, 0.54 μm × 0.54 μm; ). () Hematoxylin and eosin (H&E)-stained prostate tissue (diameter, 0.75 mm). Scale bar, 100 μm. Dashed box specifies the corresponding area of a serial, unstaine! d section from which we generated images in –. () Typical unprocessed spectra from a single pixel acquired with each instrument (crosshairs in – indicate corresponding pixel positions in the infrared images). * Figure 3: High-resolution multibeam synchrotron FTIR imaging. () Hematoxylin and eosin (H&E)-stained image of cancerous prostate tissue with chronic inflammation obtained using visible light microscopy. (,) Multibeam synchrotron absorbance images obtained from an unstained serial section of the sample shown in . Spatial detail in images from the new system is highlighted for lymphocytes (blue arrow) and red blood cells (red arrow). () Image of the same unstained section imaged with a conventional table-top system (PerkinElmer Spotlight, linear array mode). () Expanded views of the boxed area in showing the typical appearance of lymphocytes in H&E stained samples (top), the new system (bottom left) and a conventional table-top instrument (bottom right). () H&E-stained visible light image (top), asymmetric CH-stretching (2,840 cm−1, center) and collagen-specific (1,245 cm−1, bottom) infrared images of an unstained section of normal breast tissue (terminal ductal lobular unit region). Epithelial (green arrow) and intralobular stromal ! regions (magenta arrow) are highlighted. () Spectra of epithelial and stromal cells recorded with a multibeam synchrotron versus a thermal source. () Absorbance image (2,840 cm−1; top) of an unstained cancerous prostate tissue showing two benign prostate glands. Inset, potential presence of basement membrane at the interface between stroma and epithelium is marked (arrows). Image (bottom) showing epithelial (green) and stromal (magenta) cells classified using previous algorithms. () Average spectra from epithelial, stromal (two each: one closer to the interface, one farther away), and interface pixels identified manually from data obtained using two different instruments. AU, absorbance units. Scale bars, 50 μm. Author information * Author information * Supplementary information Affiliations * Department of Physics, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA. * Michael J Nasse, * Eric C Mattson & * Carol J Hirschmugl * Synchrotron Radiation Center, University of Wisconsin–Madison, Stoughton, Wisconsin, USA. * Michael J Nasse * Department of Bioengineering, Micro and Nanotechnology Laboratory and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana–Champaign, Urbana, Illinois, USA. * Michael J Walsh & * Rohit Bhargava * Scientific Answers and Solutions, Mount Sinai, New York, USA. * Ruben Reininger * Department of Pathology, University of Illinois at Chicago, Chicago, Illinois, USA. * André Kajdacsy-Balla & * Virgilia Macias Contributions M.J.N., R.R. and C.J.H. designed research; M.J.N., M.J.W. and E.C.M. performed research; M.J.W., A.K.-B., V.M. and R.B. contributed prostate samples; M.J.N., M.J.W., E.C.M., R.B. and C.J.H. analyzed data; and M.J.N., R.B. and C.J.H. wrote the paper. Competing financial interests R.R. is an employee of Scientific Answers & Solutions and has received compensation for his scientific consultation related to this work. Corresponding authors Correspondence to: * Rohit Bhargava or * Carol J Hirschmugl Author Details * Michael J Nasse Search for this author in: * NPG journals * PubMed * Google Scholar * Michael J Walsh Search for this author in: * NPG journals * PubMed * Google Scholar * Eric C Mattson Search for this author in: * NPG journals * PubMed * Google Scholar * Ruben Reininger Search for this author in: * NPG journals * PubMed * Google Scholar * André Kajdacsy-Balla Search for this author in: * NPG journals * PubMed * Google Scholar * Virgilia Macias Search for this author in: * NPG journals * PubMed * Google Scholar * Rohit Bhargava Contact Rohit Bhargava Search for this author in: * NPG journals * PubMed * Google Scholar * Carol J Hirschmugl Contact Carol J Hirschmugl Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2M) Supplementary Figures 1–7, Supplementary Table 1 and Supplementary Notes 1–3 Additional data
• Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination
  - Nat Meth 8(5):417-423 (2011)
  Nature Methods | Article Rapid three-dimensional isotropic imaging of living cells using Bessel beam plane illumination * Thomas A Planchon1, 6 * Liang Gao1, 6 * Daniel E Milkie2 * Michael W Davidson3 * James A Galbraith4 * Catherine G Galbraith5 * Eric Betzig1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:417–423Year published:(2011)DOI:doi:10.1038/nmeth.1586Received24 September 2010Accepted27 February 2011Published online04 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 A key challenge when imaging living cells is how to noninvasively extract the most spatiotemporal information possible. Unlike popular wide-field and confocal methods, plane-illumination microscopy limits excitation to the information-rich vicinity of the focal plane, providing effective optical sectioning and high speed while minimizing out-of-focus background and premature photobleaching. Here we used scanned Bessel beams in conjunction with structured illumination and/or two-photon excitation to create thinner light sheets (<0.5 μm) better suited to three-dimensional (3D) subcellular imaging. As demonstrated by imaging the dynamics of mitochondria, filopodia, membrane ruffles, intracellular vesicles and mitotic chromosomes in live cells, the microscope currently offers 3D isotropic resolution down to ~0.3 μm, speeds up to nearly 200 image planes per second and the ability to noninvasively acquire hundreds of 3D data volumes from single living cells encompassing tens of ! thousands of image frames. View full text Subject terms: * Microscopy * Imaging * Cell Biology Figures at a glance * Figure 1: Challenges in fluorescence imaging with high spatiotemporal resolution. () Increasing volumetric spatial resolution demands smaller voxels (boxes) encompassing fewer signal-generating fluorescent molecules (spheres). () Increasing temporal resolution demands that fewer molecules be expended (black spheres) at each time point. () To obtain images of acceptable SNR, a certain minimum number of photons must be emitted from these molecules, no matter how few they may be. Scale bar, 5 μm. * Figure 2: Modes of Bessel beam plane illumination microscopy. () Wide-field illumination geometry (left) and maximum-intensity projection (MIP) in the x–z plane (right; z, detection axis) from a 3D image stack of a fixed human osteosarcoma cell (U2OS) transfected with plasmids encoding mEmerald fused to human pyruvate dehydrogenase alpha 1 (PDHA1). () Bessel sheet mode geometry (left), showing fluorescence excitation from Bessel side lobes (light green) as well as the central peak (dark green), and x–z plane MIP (right) from same cell as in . (,) Bessel SI mode geometry, showing periodic Bessel beam excitation pattern (left) and x–z plane MIPs with single-harmonic () and multiharmonic () excitation (right). () Two-photon excitation (TPE) Bessel sheet mode geometry (left), showing infrared excitation (red) of fluorescence in the central peak (green), with negligible fluorescence in side lobes and x–z plane MIP from a cell (right) similar to those in –. () Volume rendering in the multiharmonic SI mode (9 phases, 2.4 μm period)! of mEmerald-tagged microtubule associated protein 4 (MAP4) in a live U2OS cell. () Volume rendering in the TPE sheet mode of mEmerald-labeled mitochondria in a live pig kidney epithelial cell (LLC-PK1 cell line). Insets in and show MIPs along orthogonal axes of the cubical volumes shown. Scale bars, 10 μm except 3 μm in insets. * Figure 3: Comparisons of Bessel beam plane illumination to confocal microscopy and DSLM. (–) Comparative raw image slices in a plane orthogonal to the coverslip through antibody-labeled microtubules in fixed HeLa cells: point-scanning confocal microscopy (; Zeiss LSM 510, NA 1.2, 1 Airy unit filtering); line-scanning confocal microscopy (; Zeiss LSM 5 LIVE, same conditions as in ); DSLM (; NA 0.2); Bessel single harmonic SI mode (; 3 phases, 0.9-μm period), and Bessel TPE sheet mode (). Scale bars, 10 μm (inset, 1 μm). () Averages of linecuts (as shown in insets in –) through 40 microtubules for each method, with 50% intensity level (dashed line) shown for estimation of the FWHM. () Bleaching rates obtained from repeated 3D imaging of mEmerald fused to nuclear histones in fixed HeLa cells, normalized to account for differences in SNR. In addition to modes described in –, Bessel linear sheet and Bessel SI multiharmonic 9-phase modes are included. Dashed lines represent a double exponential fit. () Maximum-intensity projections of mitochondria in live LLC! -PK1 cells for four image volumes as numbered at top from a series of 300 such volumes acquired by Bessel TPE sheet mode (top; 321 images per volume), confocal LSM 5 LIVE (middle; 294 images per volume) and confocal LSM 5 LIVE (bottom; 68 images per volume). Scale bar, 10 μm. () Photobleaching curves extracted from the data in , with 10 μm × 10 μm intensity-renormalized insets extracted from the boxed sub-region shown in the 300th volume in each case, showing mitochondrial fragmentation under confocal imaging. Scale bar, 3 μm. * Figure 4: Three-dimensional isotropic imaging of live-cell dynamics. () Images of ER in a live U2OS cell, visualized in the Bessel multiharmonic 9 phase SI mode, over 45 image volumes: representation of a subset of the 321 image planes (brown lines) comprising each volume (top); images from three indicated image planes; and image volumes after 10 and 30 min of observation. () Filopodia at the apical surface of a live HeLa cell, visualized in the Bessel TPE sheet mode over three consecutive image volumes from 100 such volumes taken at 6-s intervals. Filaments that wave (magenta and yellow arrowheads), extend outward (cyan arrowhead) or retract inward (green arrowhead) are marked. () African green monkey kidney cell (COS-7) transfected with plasmids encoding mEmerald–c-Src, demonstrating retrograde flow of membrane ruffles (left) and vacuole formation by macropinocytosis (right; arrowheads) in an exemplary plane in a translucent cell view (top). All data were extracted from 73 image stacks taken at 12-s intervals. Scale bars, 5 μm (,) and 10! μm (). * Figure 5: High-speed volumetric imaging of chromosomes in mitosis. () Eight image volumes from a series of 200 such volumes depicting mitosis in a LLC-PK1 cell transfected with plasmids encoding mEmerald–histone H2B and imaged in the Bessel TPE sheet mode. Each volume, composed of 200 image planes, was acquired in 1.0 s. The rest interval between stacks varied from 20 s in metaphase and telophase to no rest in early anaphase, to expend more of the photon budget at the points of most rapid evolution. Two chromatids (green and purple) are traced through the series. () Four consecutive image volumes from the series, during the fast imaging period in anaphase, in which the two chromatids separate (arrowheads). Times indicate min:s. Scale bars, 5 μm. * Figure 6: Three-dimensional isotropic imaging of protein pairs. () Two-color volume rendering acquired in the 9 phase multiharmonic SI mode of microtubules (green) and nuclei (red) in a pair of live U2OS cells transfected with plasmids encoding mEmerald-MAP4 and tdTomato–histone H2B. Images on the right show slices through the cell along the planes shown in the image on the left. () Evolution of the Golgi apparatus (magenta) during mitosis of a live LLC-PK1 cell, with views parallel (top) and perpendicular (bottom) to the mitotic plane, showing partial fragmentation in metaphase and anaphase and eventual recondensation in telophase. The Golgi and chromosomes (green) are visualized via mEmerald–Mann II and mEmerald–histone H2B fluorescence, respectively, and were manually segmented for these images. Scale bars, 5 μm. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Thomas A Planchon & * Liang Gao Affiliations * Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA. * Thomas A Planchon, * Liang Gao & * Eric Betzig * Coleman Technologies, Inc., Chadds Ford, Pennsylvania, USA. * Daniel E Milkie * National High Magnetic Field Laboratory and Department of Biological Science, Florida State University, Tallahassee, Florida, USA. * Michael W Davidson * National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA. * James A Galbraith * National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA. * Catherine G Galbraith Contributions E.B. conceived the project and designed the instrumentation; D.E.M. wrote the instrument control program under suggestions from T.A.P., L.G. and E.B.; M.W.D. supplied plasmids, figures and guidance on cell lines and useful targets therein; T.A.P. performed initial system characterization and confocal experiments; L.G. performed two-photon measurements; L.G., C.G.G. and J.A.G. performed live-cell experiments; T.A.P, L.G., C.G.G., J.A.G. and E.B. analyzed the data; and E.B. wrote the paper with input from all authors. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Eric Betzig Author Details * Thomas A Planchon Search for this author in: * NPG journals * PubMed * Google Scholar * Liang Gao Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel E Milkie Search for this author in: * NPG journals * PubMed * Google Scholar * Michael W Davidson Search for this author in: * NPG journals * PubMed * Google Scholar * James A Galbraith Search for this author in: * NPG journals * PubMed * Google Scholar * Catherine G Galbraith Search for this author in: * NPG journals * PubMed * Google Scholar * Eric Betzig Contact Eric Betzig Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information Movies * Supplementary Video 1 (17.2M) Volume rendering of aggregates of 352-nm-diameter fluorescent beads, acquired in the Bessel single-harmonic SI mode. * Supplementary Video 2 (7M) Volume rendering of microtubules in a live U2OS cell transfected with plasmids encoding mEmerald-tagged microtubule associated protein 4, acquired in the Bessel multiharmonic SI mode. Data correspond to Figure 2f. * Supplementary Video 3 (9.5M) Dynamics of mitochondria in a live LLC-PK1 cell over 300 volumes encompassing 96,000 image frames, acquired in the Bessel TPE sheet mode. Data correspond to Figure 2g. * Supplementary Video 4 (3.9M) Dynamics of the endoplasmic reticulum in a live U2OS cell, acquired in the Bessel multiharmonic SI mode, corresponding to the data in Figure 4a. * Supplementary Video 5 (13.5M) Volume renderings and orthogonal maximum intensity projections of filopodia dynamics at the apical surface of a live HeLa cell, corresponding to the data in Figure 4b. * Supplementary Video 6 (12.1M) Dynamics of membrane ruffling (top) and intracellular vesicle motion (bottom) in a cSrc-transfected COS-7 cell, corresponding to the data in Figure 4c. * Supplementary Video 7 (3.9M) Views parallel and perpendicular to the mitotic plane of chromosome dynamics in a dividing LLC-PK1 cell, with a plane (left) cutting through one daughter cell during anaphase to show an interior view of the opposite chromosomes (right). Data correspond to Figure 5. * Supplementary Video 8 (13.7M) Membrane trafficking in a single plane over 7,000 image frames at 137 frames s-1 in a live cSrc-transfected COS-7 cell. * Supplementary Video 9 (8.3M) Volume rendering of microtubules and nuclear histones in a live U2OS cell, acquired using two-color excitation in the Bessel multiharmonic SI mode, corresponding to the data in Figure 6a. * Supplementary Video 10 (8M) Three-color volume rendering of nuclear histones, the nuclear membrane and the actin cytoskeleton in a fixed LLC-PK1 cell, acquired in the Bessel multiharmonic SI mode. * Supplementary Video 11 (16.2M) Two-color volume rendering of filamentous actin and connexin-43 in a fixed HeLa cell, acquired in the Bessel TPE sheet mode. * Supplementary Video 12 (1.2M) Fragmentation and reconstitution of the Golgi apparatus (magenta) during mitosis in a LLC-PK1 cell, after three-dimensional segmentation of single color Golgi and histone (green) data. Data correspond to Figure 6b. PDF files * Supplementary Text and Figures (4.5M) Supplementary Figures 1–26, Supplementary Tables 1–4 Additional data
• Chemically defined conditions for human iPSC derivation and culture
  - Nat Meth 8(5):424-429 (2011)
  Nature Methods | Article Chemically defined conditions for human iPSC derivation and culture * Guokai Chen1, 2, 3 * Daniel R Gulbranson1, 2, 3 * Zhonggang Hou1, 2, 3 * Jennifer M Bolin1 * Victor Ruotti1 * Mitchell D Probasco1 * Kimberly Smuga-Otto4 * Sara E Howden1, 2, 3 * Nicole R Diol1, 2, 3 * Nicholas E Propson1, 2, 3 * Ryan Wagner1, 2, 3 * Garrett O Lee1, 2, 3 * Jessica Antosiewicz-Bourget1 * Joyce M C Teng5 * James A Thomson1, 2, 3, 6 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:424–429Year published:(2011)DOI:doi:10.1038/nmeth.1593Received28 October 2010Accepted17 February 2011Published online10 April 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 re-examine the individual components for human embryonic stem cell (ESC) and induced pluripotent stem cell (iPSC) culture and formulate a cell culture system in which all protein reagents for liquid media, attachment surfaces and splitting are chemically defined. A major improvement is the lack of a serum albumin component, as variations in either animal- or human-sourced albumin batches have previously plagued human ESC and iPSC culture with inconsistencies. Using this new medium (E8) and vitronectin-coated surfaces, we demonstrate improved derivation efficiencies of vector-free human iPSCs with an episomal approach. This simplified E8 medium should facilitate both the research use and clinical applications of human ESCs and iPSCs and their derivatives, and should be applicable to other reprogramming methods. View full text Subject terms: * Cell Biology Figures at a glance * Figure 1: Albumin is not required for human ESC culture. () Cloning efficiency (day 5) of H1 ESCs plated at clonal density (500 cells per well) with ROCK inhibitor on a Matrigel-coated surface in TeSR made with five different commercial batches of BSA. *P < 0.05 (n = 3) relative to BSA batch 1, the only batch supporting long-term self-renewal. Error bars, s.e.m. () Micrographs of colonies after 72 h of incubation in TeSR with indicated batches of BSA. Scale bar, 70 μm. () Flow cytometry analysis of OCT4 expression of cells depicted in . Green peak, OCT4 staining; unshaded peak, mouse immunoglobulin gamma (IgG) control. FITC-A, FITC channel area intensity. () Survival of dissociated H1 ESCs 24 h after plating into simplified medium (TeSR core) with or without BSA. The 'survival index' represents the number of surviving cells divided by the number of input cells. *P < 0.05; n = 3. () Survival of dissociated cells 24 h after plating into TeSR-based medium with the indicated combinations of BSA and BME. The control medium is TeSR cor! e. *P < 0.05; n = 3. () In the cell culture described in , cell proliferation was measured 120 h after plating. *P < 0.05; n = 3. The 'proliferation index' represents the cell number at a specific time point divided by the number of input cells at time 0. Error bars, s.e.m. * Figure 2: Essential medium components for human ESC survival and proliferation. () Survival index of dissociated H1 ESCs 24 h after plating into the indicated medium on Matrigel-coated plates. *P < 0.05 (n = 3) relative to survival in TeSR. -insulin, medium without insulin; -FGF2, medium without FGF2. () Proliferation index of cells from 96 h after plating and culture in the same medium with daily medium change. *P < 0.05 (n = 3) relative to proliferation in TeSR. () The plots show survival (22 h after plating) and proliferation (129 h after plating) of human ESCs dissociated and plated in the indicated media. *P < 0.05; n = 3. LAA, L-ascorbic acid. -LAA, medium without LAA. () Number of H1 cells maintained in defined media (DMEM/F12, NaHCO3, insulin, FGF2 and LAA) for multiple passages with or without selenium (150,000 cells were seeded in each passage on days 0, 4 and 7). () Flow cytometry analysis of OCT4 expression in H1 cells grown in the indicated media for four passages. Green peak, OCT4 staining; unshaded peak, mouse IgG control. () Cloning effi! ciency of human foreskin iPSCs29 grown in the indicated defined media, with ROCK inhibitor HA100, in hypoxic conditions (*P < 0.05, n = 3). MEF conditioned medium. () Cloning efficiency of ESCs in indicated media under hypoxic and normoxic conditions. CM, *P < 0.05; n = 3. Error bars, s.e.m. () Fold expansion of ESCs (H1) and iPSCs15 cultured under hypoxic conditions in the indicated media (200,000 cells were plated at each passage). * Figure 3: Vitronectin-coated surfaces support human ESCs and iPSCs cultured in E8. () Schematics of wild-type vitronectin (VTN) and VTN-C, VTN-N and VTC-NC variants that were expressed and purified as coating materials for ESCs, with numbers indicating the amino acid number of the start and end of each construct. Somatomedin B domain30 (SMB) and V10 are functional domains31 of wild-type vitronectin; RGD, integrin-binding site. () Cell survival on the four vitronectin variants in E8 after 24 h. The survival index was normalized to cell survival on Matrigel. *P < 0.05; n = 3. () Cell survival after 24 h on VTN-NC and Matrigel in E8 (with TGFβ) medium after passaging with EDTA and a stable Trypsin-like enzyme, TrypLE (Invitrogen); *P < 0.05, n = 3. (,) Cell survival after 24 h () or cloning efficiency () on VTN-NC and Matrigel surfaces in the presence of the indicated chemical inhibitors. *P < 0.05; n = 3. Error bars, s.e.m. * Figure 4: Reprogramming fibroblast cells in fully defined conditions. () Schematic of procedure to derive integration-free iPSCs from fibroblast cells in fully defined conditions. () Micrographs of a typical iPSC colony 25 d after reprogramming and before picking (left), and after first passage (right). Scale bars, 200 μm (left) and 25 μm (right). This clone was maintained in E8 (with Nodal) on Matrigel. () Flow cytometry analysis of OCT4 and SSEA4 of a typical iPSC line derived from foreskin fibroblasts and maintained in E8 for 20 passages. Green peak, OCT4 staining; unshaded peak, mouse IgG control. (–) Reprogramming efficiency of human foreskin fibroblasts reprogrammed in the indicated media, scored after 30 d. In , sodium butyrate (100 μM) was added to both conditions to improve efficiency. In , and , *P < 0.05 (n = 3); experiments were repeated twice (,) and five times (), with similar results. In , owing to the inconsistency of reprogramming efficiency in TeSR, four independent experiments were each repeated three times; *P < 0.05 (! n = 12). Error bars, s.e.m. * Figure 5: Derivation of human iPSCs directly from biopsy samples in chemically defined conditions. (,) Analyses of growth of adult fibroblast cells plated on the indicated plate-coating materials in E8-based fibroblast medium and counted after 4 d () or cultured in the indicated media on vitronectin and counted 96 h after plating (). *P < 0.05; n = 3. Error bars, s.e.m. () Micrographs of three fibroblast cell lines derived from skin biopsies in defined fibroblast medium on vitronectin-coated plates. Scale bar, 100 μm. () Micrographs of representative iPSC colonies obtained by reprogramming fibroblasts shown in according to the procedure in Figure 4a, in the presence of butyrate. Colonies are shown after multiple passages in E8 (with TGFβ). Scale bars, 100 μm. (,) Flow cytometry analysis of pluripotency markers OCT4 and SSEA4 in iPSCs after ten passages. Author information * Abstract * Author information * Supplementary information Affiliations * Morgridge Institute for Research, Madison, Wisconsin, USA. * Guokai Chen, * Daniel R Gulbranson, * Zhonggang Hou, * Jennifer M Bolin, * Victor Ruotti, * Mitchell D Probasco, * Sara E Howden, * Nicole R Diol, * Nicholas E Propson, * Ryan Wagner, * Garrett O Lee, * Jessica Antosiewicz-Bourget & * James A Thomson * Department of Cell and Regenerative Biology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA. * Guokai Chen, * Daniel R Gulbranson, * Zhonggang Hou, * Sara E Howden, * Nicole R Diol, * Nicholas E Propson, * Ryan Wagner, * Garrett O Lee & * James A Thomson * The Genome Center of Wisconsin, University of Wisconsin, Madison, Wisconsin, USA. * Guokai Chen, * Daniel R Gulbranson, * Zhonggang Hou, * Sara E Howden, * Nicole R Diol, * Nicholas E Propson, * Ryan Wagner, * Garrett O Lee & * James A Thomson * Wisconsin National Primate Research Center, Madison, Wisconsin, USA. * Kimberly Smuga-Otto * University of Wisconsin, Dermatology Department, Madison, Wisconsin, USA. * Joyce M C Teng * Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, California, USA. * James A Thomson Contributions G.C. and J.A.T. conceived the experiment; G.C., D.R.G., J.M.B., K.S.-O. and S.E.H. performed the reprogramming; Z.H., G.C. and N.E.P. produced vitronectin; G.C., D.R.G., J.M.B., N.R.D., G.O.L. and J.A.-B. performed the cell culture test; G.C., M.D.P. and R.W. derived fibroblasts; J.M.C.T. obtained the skin biopsy; V.R. and G.C. analyzed global expression; and G.C. and J.A.T. wrote the paper. Competing financial interests J.A.T. is a founder, stockowner, consultant and board member of Cellular Dynamics International (CDI), and serves as scientific advisor to and has financial interests in Tactics II Stem Cell Ventures. Corresponding author Correspondence to: * James A Thomson Author Details * Guokai Chen Search for this author in: * NPG journals * PubMed * Google Scholar * Daniel R Gulbranson Search for this author in: * NPG journals * PubMed * Google Scholar * Zhonggang Hou Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer M Bolin Search for this author in: * NPG journals * PubMed * Google Scholar * Victor Ruotti Search for this author in: * NPG journals * PubMed * Google Scholar * Mitchell D Probasco Search for this author in: * NPG journals * PubMed * Google Scholar * Kimberly Smuga-Otto Search for this author in: * NPG journals * PubMed * Google Scholar * Sara E Howden Search for this author in: * NPG journals * PubMed * Google Scholar * Nicole R Diol Search for this author in: * NPG journals * PubMed * Google Scholar * Nicholas E Propson Search for this author in: * NPG journals * PubMed * Google Scholar * Ryan Wagner Search for this author in: * NPG journals * PubMed * Google Scholar * Garrett O Lee Search for this author in: * NPG journals * PubMed * Google Scholar * Jessica Antosiewicz-Bourget Search for this author in: * NPG journals * PubMed * Google Scholar * Joyce M C Teng Search for this author in: * NPG journals * PubMed * Google Scholar * James A Thomson Contact James A Thomson Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (6M) Supplementary Figures 1–4 and Supplementary Tables 1–3 Additional data
• mProphet: automated data processing and statistical validation for large-scale SRM experiments
  - Nat Meth 8(5):430-435 (2011)
  Nature Methods | Article mProphet: automated data processing and statistical validation for large-scale SRM experiments * Lukas Reiter1, 2, 3, 4, 9 * Oliver Rinner1, 2, 9 * Paola Picotti2, 8 * Ruth Hüttenhain2, 5 * Martin Beck2, 8 * Mi-Youn Brusniak6 * Michael O Hengartner3 * Ruedi Aebersold2, 5, 7 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:430–435Year published:(2011)DOI:doi:10.1038/nmeth.1584Received28 April 2010Accepted11 February 2011Published online20 March 2011Corrected online06 April 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 Selected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model. View full text Subject terms: * Proteomics * Mass Spectrometry * Bioinformatics Figures at a glance * Figure 1: Structure of SRM data and definition of terms. () Representation of the SRM measurement of one peptide. We name the precursor (Q1) to fragment ion (Q3) transitions, used to measure one targeted peptide, a transition group. The data resulting from the measurement of one transition or transition group are called a trace or transition group record, respectively. In one transition group record, several peak groups can be identified that potentially represent the peptide of interest. () Peak group features that can be used to identify a true peak group. Red indicates an unexpected behavior for true peak groups. If the peak group is derived from the targeted peptide, the peaks tend to have similar retention time profile and shape. Furthermore, the relative intensities of the fragment ions must correspond to previously measured intensity ratios (for example, from a consensus spectrum). If a reference peptide is in the sample, the relative intensities for all corresponding traces as well as peak shape and elution time should be ! similar for intrinsic peptide and reference. * Figure 2: Generation of a gold-standard data set with assigned true peak groups. Synthetic peptides (100) in isotopically light and heavy forms were added at three different concentrations to three different background matrices (trypsinized protein extracts from L. interrogans, C. elegans and H. sapiens u2os cells) of increasing complexity. () Dilution series of a synthetic peptide mixed into a background matrix. The peptide was measured using SRM with five transitions in three different samples and at three different concentrations. Signal intensities (square root of counts per second) versus retention time for one transition group record at three different dilutions. Square root is used to visualize the full intensity range. The true peptide signal at 34 min, as we expected, is proportional to the peptide concentration, whereas a second signal (indicated by an asterisk) is constant among all three samples and thus designated a wrong peak group and neglected. () Systematic discrimination between true and false peak groups. Every peak group was compared ! to the peak groups of the other two dilutions in terms of retention time and expected intensity as shown here for the peak groups of the 64-fold dilution. The comparisons in black fulfill the stringent filtering. Only transition group records with one peak group fulfilling the criteria were accepted. () Histograms of subscore distributions of true and false peak groups; inset, corresponding ROC plots and AUC. * Figure 3: Combining features improves the separation of true and false peak groups. () Separation of true and false target peak groups in the test data set by mProphet after training of a classifier with a semisupervised learning strategy. () ROC plots for all the single subscores compared with the composite mProphet score. () Comparison of mProphet computed and true sensitivity and FDR in the test data set. () Signal-to-noise ratio of peak groups versus the mProphet score in the test data set. Signals with an SNR greater than ~10 were completely separated from false peak groups. () Dependence of the true-false intensity correlation score separation power on the number of transitions. ROC curves for the data set using three to five transitions recorded (six to ten including the heavy transitions). () Dependence of the mProphet separation power on the fraction of available decoy transition groups. ROC curves for 36%, 20%, 10%, 5% and 2% decoy transition group records relative to the total amount of target data. * Figure 4: Separation of true from false peak group signals in a total human u2os cell line lysate using decoy transitions and mProphet scoring. () Decoy transition groups were designed as pairs of decoy transitions for the endogenous isoform and the target transitions for the reference form. Both decoy and target transition groups were scored against the same reference (the spiked-in peptide). () Cumulative spectral counts in a shotgun mass spectrometry experiment of an off-gel electrophoresis fractionated u2os total human cell lysate of the peptides selected for targeting with SRM. () mProphet score distribution for target and decoy peak groups. Most of the target signals were separated from the decoy distribution. () Sensitivity and FDR as function of the mProphet score cutoff. Most peptides could be detected with a high confidence (FDR < 1%). () High-confidence low signal-to-noise identification by mProphet. () Dependence of mProphet separation on the number of transitions. ROC curves using two to six transitions recorded (six to ten including the heavy transitions). () Dependence of mProphet separation on the nu! mber of transitions when completely neglecting the reference peptide data. ROC curves for the data set using two to six transitions recorded. Change history * Abstract * Change history * Author information * Supplementary informationCorrigendum 06 April 2011In the version of this article initially published online, a 'greater than' sign was inadvertently reversed, and an author contribution was incorrectly attributed. The error has been corrected for the print, PDF and HTML versions of this article. Author information * Abstract * Change history * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Lukas Reiter & * Oliver Rinner Affiliations * Biognosys AG, Zurich, Switzerland. * Lukas Reiter & * Oliver Rinner * Institute of Molecular Systems Biology, Department of Biology, Swiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland. * Lukas Reiter, * Oliver Rinner, * Paola Picotti, * Ruth Hüttenhain, * Martin Beck & * Ruedi Aebersold * Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland. * Lukas Reiter & * Michael O Hengartner * PhD Program in Molecular Life Sciences Zurich, Zurich, Switzerland. * Lukas Reiter * Competence Center for Systems Physiology and Metabolic Diseases, Zurich, Switzerland. * Ruth Hüttenhain & * Ruedi Aebersold * Institute for Systems Biology, Seattle, Washington, USA. * Mi-Youn Brusniak * Faculty of Science, University of Zurich, Zurich, Switzerland. * Ruedi Aebersold * Present addresses: Institute of Biochemistry, Department of Biology, ETH Zurich, Zurich, Switzerland (P.P.) and European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany (M.B.). * Paola Picotti & * Martin Beck Contributions L.R., O.R., P.P., M.-Y.B. and R.A. designed the gold-standard data set. P.P. carried out the measurements on the gold-standard data set. L.R., O.R. and R.A. wrote the paper. L.R. and O.R. wrote the software and did the data analysis. L.R. did most of the statistical data analysis. R.H. contributed to the experiment involving the human plasma N-glycopeptide-enriched samples. M.B. contributed to the experiment involving the human u2os cell line. M.O.H. provided critical input on the project. R.A. supervised the project. Competing financial interests O.R. and L.R. are employees of Biognosys AG. This company funded parts of the work. Corresponding author Correspondence to: * Ruedi Aebersold Author Details * Lukas Reiter Search for this author in: * NPG journals * PubMed * Google Scholar * Oliver Rinner Search for this author in: * NPG journals * PubMed * Google Scholar * Paola Picotti Search for this author in: * NPG journals * PubMed * Google Scholar * Ruth Hüttenhain Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Beck Search for this author in: * NPG journals * PubMed * Google Scholar * Mi-Youn Brusniak Search for this author in: * NPG journals * PubMed * Google Scholar * Michael O Hengartner Search for this author in: * NPG journals * PubMed * Google Scholar * Ruedi Aebersold Contact Ruedi Aebersold Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Change history * Author information * Supplementary information Excel files * Supplementary Data 1 (3M) Table of transitions, table of peak groups, table with identification statistics and classifier of the gold standard data set analysis. The transitions sheet contains the precursor m/z (Q1), fragment ion m/z (Q3), an id that groups the transitions according to precursor (transition group id), an id for the transition (transition id), a string describing the isotopic labeling of the peptide (isotype), the collision energy used (CE), the expected retention time used for scheduled SRM (tR), the expected relative intensity of the fragment ions (relative intensity %), a string indicating whether the transition is a decoy or target (decoy) and an id to group corresponding target and decoy transition groups (target decoy transition group id). The mProphet peak groups sheet contains a row for each peak group. The most important columns are an id for a transition group measurement (transition_group_record), the features used for scoring (all columns starting with main_var or var_), a! column indicating the dilution of the synthetic peptides in the specific matrix (dilution), the species used for the background matrix (background), the class of the peak group in terms of identity as determined by the dilution alignment (real_class), a boolean indicating whether the peak group was derived from decoy or target transitions (real_decoy), a boolean indicating whether treated as decoy or target in the mProphet analysis (decoy) and the mProphet discrimination score (d_score). The mProphet all peak groups sheet contains the all peak groups of the analysis, not only the ones that rank highest in one transition group record (peak_group_rank). The mProphet stat sheet relates the mProphet discrimination score (cutoff) to the false discovery rate (FDR) and the sensitivity (sens). The mProphet classifier weight sheet contains the weights that were determined using the semi-supervised learning approach. * Supplementary Data 2 (4M) Table of transitions, table of peak groups, table with identification statistics and classifier of the human u2os cell line analysis. For a detailed description of the sheets see Supplementary Data 1 legend. * Supplementary Data 3 (1M) Table of transitions, table of peak groups, table with identification statistics and classifier of the human plasma analysis. For a detailed description of the sheets see Supplementary Data 1 legend. * Supplementary Data 4 (692M) Table of transitions and peak groups for the measurement of yeast target and decoy transitions in human plasma. The transitions sheet contains target transitions of yeast peptides and corresponding decoy transitions generated by two different decoy transition generation algorithms (ADD_RANDOM and REVERSE_PEP_AND_INCREASE_Q1). The mQuest peak groups sheet contains the data processed with mQuest. The mProphet analysis does result in meaningful results since the data contains no positive target measurements. For a detailed description of the sheets see Supplementary Data 1 legend. PDF files * Supplementary Text and Figures (7M) Supplementary Figures 1–12, Supplementary Table 1, Supplementary Results and Supplementary Note Additional data