Hot off the presses! Oct 01 Nat Methods

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Latest Articles Include:

• From lab bench to product catalog
  - Nat Methods 8(10):779 (2011)
  Nature Methods | Editorial From lab bench to product catalog Journal name:Nature MethodsVolume: 8,Page:779Year published:(2011)DOI:doi:10.1038/nmeth.1728Published online29 September 2011 Commercialization of academic research is increasing and provides important benefits, but it remains difficult, and recent developments bring new challenges. View full text Additional data
• The author file: Abbas El Gamal and Mark Schnitzer
  - Nat Methods 8(10):781 (2011)
  Nature Methods | This Month The author file: Abbas El Gamal and Mark Schnitzer * Monya BakerJournal name:Nature MethodsVolume: 8,Page:781Year published:(2011)DOI:doi:10.1038/nmeth.1713Published online29 September 2011 Two-gram microscopes make brain images in moving mice. View full text Additional data
• Points of view: Layout
  - Nat Methods 8(10):783 (2011)
  Article preview View full access options Nature Methods | This Month Points of view: Layout * Bang Wong1Journal name:Nature MethodsVolume: 8,Page:783Year published:(2011)DOI:doi:10.1038/nmeth.1711Published online29 September 2011 Layout is the act of arranging text and images on the page according to an overall aesthetic scheme and for the purpose of clarifying a presentation. In graphic arts, it is the elephant in the room; layout underlies everything we do when we communicate visually. Well-structured content can guide readers through complex information, but when the material we present lacks order, it can confuse or, worse yet, agitate readers trying to make sense of the material. Many artists and architects achieve balanced outcomes by proportioning their work to approximate the golden section. The golden section is a special mathematical relationship that comes from dividing a line into two segments where the ratio of the total length (x + y) to the length of the longer segment (x) is the same as that of the length of the longer segment (x) to the length of the shorter segment (y) (Fig. 1a), or 13:8. Many celebrated paintings since at least the Renaissance exhibit these proportions (Fig. 1b). Figure 1: Infallible proportions. () The golden section is a line segment divided by the golden ratio 13:8 such that (x + y) is to x as x is to y. () In Bathers at Asnières, Georges-Pierre Seurat used the golden section to position the horizon and subjects in the composition (http://en.wikipedia.org/wiki/File:Seurat_bathers.png). () The 'rule of thirds' is a simplified version of the golden section used to form interesting compositions. * Full size image (59 KB) * Figures index * Next figure Compositional aesthetics may serve a fundamentally different purpose from designs aimed to communicate. However, the Fibonacci numbers, which are also linked to the golden ratio, heavily influence graphic design. This sequence of numbers starts with 0 and 1 and each subsequent integer is the sum of the previous two (that is, 0, 1, 1, 2, 3, 5, 8, 13 and so on). The quotient of successive pairs of numbers, with the exception of the first few, is approximately 1.6180 (or 13:8). The harmonious relationships of the Fibonacci integers are often used as measurements for font sizes and determining page layouts in books. Figures at a glance * Figure 1: Infallible proportions. () The golden section is a line segment divided by the golden ratio 13:8 such that (x + y) is to x as x is to y. () In Bathers at Asnières, Georges-Pierre Seurat used the golden section to position the horizon and subjects in the composition (http://en.wikipedia.org/wiki/File:Seurat_bathers.png). () The 'rule of thirds' is a simplified version of the golden section used to form interesting compositions. * Figure 2: Gridlines help to structure layouts. () Examples of gridline systems for presentation slides. () Arrange elements according to the order in which they should be read. () Surrounding an element in ample white space helps it get noticed first. Article preview Read the full article * Instant access to this article: US$32 Buy now * Subscribe to Nature Methods for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * 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 & 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 Additional data
• SignalP 4.0: discriminating signal peptides from transmembrane regions
  - Nat Methods 8(10):785-786 (2011)
  Nature Methods | Correspondence SignalP 4.0: discriminating signal peptides from transmembrane regions * Thomas Nordahl Petersen1 * Søren Brunak1, 2 * Gunnar von Heijne3, 4 * Henrik Nielsen1 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:785–786Year published:(2011)DOI:doi:10.1038/nmeth.1701Published online29 September 2011 To the Editor: The secretory signal peptide is a ubiquitous protein-sorting signal that targets its passenger protein for translocation across the endoplasmic reticulum membrane in eukaryotes and the cytoplasmic membrane in prokaryotes1. Many methods have been published for predicting signal peptides from the amino acid sequence, including SignalP2, 3, 4, PrediSi5, SPEPlip6, Signal-CF7, Signal-3L8 and Signal-BLAST9. A benchmark study done in 2009 found SignalP 3.0 to be the best method10. View full text Subject terms: * Bioinformatics * Proteomics 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 Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. * Thomas Nordahl Petersen, * Søren Brunak & * Henrik Nielsen * Novo Nordisk Foundation Center for Protein Research, Health Sciences Faculty, University of Copenhagen, Copenhagen, Denmark. * Søren Brunak * Center for Biomembrane Research, Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden. * Gunnar von Heijne * Science for Life Laboratory, Stockholm University, Solna, Sweden. * Gunnar von Heijne Competing financial interests The downloadable version of SignalP 4.0 (for local use) has been commercialized by the Technical University of Denmark. (It is provided for a fee to commercial users.) The revenue from these commercial sales is divided between the program developers (T.N.P., S.B., G.v.H. and H.N.) and the Technical University of Denmark, where T.N.P., S.B. and H.N. are employed. Corresponding author Correspondence to: * Henrik Nielsen Author Details * Thomas Nordahl Petersen Search for this author in: * NPG journals * PubMed * Google Scholar * Søren Brunak Search for this author in: * NPG journals * PubMed * Google Scholar * Gunnar von Heijne Search for this author in: * NPG journals * PubMed * Google Scholar * Henrik Nielsen Contact Henrik Nielsen Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (224K) Supplementary Methods, Supplementary Results Additional data
• Sorting out sequencing data
  - Nat Methods 8(10):799-803 (2011)
  Nature Methods | Technology Feature Sorting out sequencing data * Monya Baker1Journal name:Nature MethodsVolume: 8,Pages:799–803Year published:(2011)DOI:doi:10.1038/nmeth.1702Published online29 September 2011 The toughest work is not sequencing a genome: it is finding the mutations that matter. View full text Author information Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Monya Baker is technology editor for Nature and Nature Methods Corresponding author Correspondence to: * Monya Baker Author Details * Monya Baker Contact Monya Baker Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Induced pluripotent stem cells for conserving endangered species?
  - Nat Methods 8(10):805-807 (2011)
  Article preview View full access options Nature Methods | News and Views Induced pluripotent stem cells for conserving endangered species? * Vimal Selvaraj1 * David E Wildt2 * Budhan S Pukazhenthi2 * Affiliations * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:805–807Year published:(2011)DOI:doi:10.1038/nmeth.1715Published online29 September 2011 Induced pluripotent stem cells have been derived from two endangered wildlife species. There are exciting possibilities, yet formidable challenges, for these cells to contribute to real-life species preservation. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Methods for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Vimal Selvaraj is at the Department of Animal Science, Cornell University, Ithaca, New York, USA. * David E. Wildt and Budhan S. Pukazhenthi are at the Smithsonian Conservation Biology Institute, National Zoological Park, Front Royal, Virginia, USA. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Budhan S Pukazhenthi Author Details * Vimal Selvaraj Search for this author in: * NPG journals * PubMed * Google Scholar * David E Wildt Search for this author in: * NPG journals * PubMed * Google Scholar * Budhan S Pukazhenthi Contact Budhan S Pukazhenthi Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• The proteomes of native and induced pluripotent stem cells
  - Nat Methods 8(10):807-808 (2011)
  Article preview View full access options Nature Methods | News and Views The proteomes of native and induced pluripotent stem cells * Martin F Pera1Journal name:Nature MethodsVolume: 8,Pages:807–808Year published:(2011)DOI:doi:10.1038/nmeth.1707Published online29 September 2011 A comparison of embryonic stem cells and induced pluripotent stem cells on the proteome level reveals subtle distinctions between these cell types that might explain differences in their ability to differentiate into specific lineages. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Methods for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Martin F. Pera is at the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California, Los Angeles, California, USA, the Florey Neuroscience Institute, and the Walter and Eliza Hall Institute of Medical Research, Melbourne, Australia. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Martin F Pera Author Details * Martin F Pera Contact Martin F Pera Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Cells see the light to bring signaling under control
  - Nat Methods 8(10):808-809 (2011)
  Article preview View full access options Nature Methods | News and Views Cells see the light to bring signaling under control * Jason M Haugh1Journal name:Nature MethodsVolume: 8,Pages:808–809Year published:(2011)DOI:doi:10.1038/nmeth.1708Published online29 September 2011 The combination of optogenetics with feedback control counteracts variability in cellular signaling responses to promote a deeper understanding of the biochemical mechanisms involved. Article preview Read the full article * Instant access to this article: US$18 Buy now * Subscribe to Nature Methods for full access: Subscribe * Personal subscribers: Log in Additional access options: * Login via Athens * Login via your Institution * Purchase a site license * Use a document delivery service * British Library Document Supply Centre * Infotrieve * Thompson ISI Document Delivery * You can also request this document from your local library through inter-library loan services. Author information Article tools * Print * Email * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg Affiliations * Jason M. Haugh is in the Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, North Carolina, USA. Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Jason M Haugh Author Details * Jason M Haugh Contact Jason M Haugh Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Optical sectioning microscopy with planar or structured illumination
  - Nat Methods 8(10):811-819 (2011)
  Nature Methods | Review Optical sectioning microscopy with planar or structured illumination * Jerome Mertz1Journal name:Nature MethodsVolume: 8,Pages:811–819Year published:(2011)DOI:doi:10.1038/nmeth.1709Published online29 September 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 key requirement for performing three-dimensional (3D) imaging using optical microscopes is that they be capable of optical sectioning by distinguishing in-focus signal from out-of-focus background. Common techniques for fluorescence optical sectioning are confocal laser scanning microscopy and two-photon microscopy. But there is increasing interest in alternative optical sectioning techniques, particularly for applications involving high speeds, large fields of view or long-term imaging. In this Review, I examine two such techniques, based on planar illumination or structured illumination. The goal is to describe the advantages and disadvantages of these techniques. View full text Figures at a glance * Figure 1: PIM configurations. () PIM with widefield () and line-scanning () illumination. Illumination light is shown in blue. Resulting fluorescence is collected with an objective. The detection PSF (on axis only) is shown in green. The grid pattern in both panels corresponds to the Nx × Ny camera pixels projected into the illumination plane. * Figure 2: Demonstration of high-speed volumetric imaging with 2P-PIM. Fluorescently labeled chromosomes in mitosis were imaged at volume speeds of 1 Hz (frame speeds of 200 Hz). Two chromatids (green and purple) are traced through the series during the fast imaging period in anaphase, in which the two chromatids separate (arrowheads). Times indicate min:s. Scale bar, 5 mm. Reprinted from ref. 18. * Figure 3: Demonstrations of long-term developmental imaging with PIM. () 1P-PIM of a zebrafish embryo (diameter of ~700 mm) allows the 3D tracking of cell divisions and migrations (color-encoded migration directions are shown on the left) over 24 h. The embryo was embedded in agarose and labeled with chromatin-targeted GFP. Scale bar, 100 μm. Reprinted from ref. 12. () 2P-PIM of a live fruit fly embryo with GFP-labeled nuclei enables 3D renderings at various developmental stages. Scale bar, 50 μm. Reprinted from ref. 17. * Figure 4: Demonstration of anatomical imaging with 1P-PIM operated in bidirectional widefield illumination mode. Blood vessel system of a mouse embryo cleared with benzyl alchohol:benzyl benzonate is made visible by the excitation of autofluorescence. Note the large FOV. Scale bar, 2 mm. Reprinted from ref. 10. * Figure 5: Schematics of different optical sectioning configurations with structured illumination. () Illumination and fluorescence are shown in blue and green, respectively. In the spinning-disk microscopy configuration (), out-of-focus fluorescence background is physically rejected with a sparse pinhole mask. In the DSD microscopy configuration (), background is rejected partially physically with a dense grid mask and partially numerically by weighted background subtraction. In the SIM configuration (), background is rejected numerically. Note that tilt of mask in is greatly exaggerated. * Figure 6: Molecular Probes fluorescently labeled mouse intestine slide imaged with grid-illumination DSD microscopy. () Raw data as seen by the camera: on the left is the image transmitted through the disk (that is, in-focus signal plus one-half out-of-focus background); on the right is the image reflected from the disk (one-half out-of-focus background). () Subtraction of the right from the left image, resulting in a sectioned image of the in-focus signal only. Note that the sum of both halves corresponds to a standard nonsectioned widefield image. Scale bar, 10 μm. Image courtesy of Aurox Ltd. * Figure 7: Confocal versus HiLo microscopy. () Comparison of maximum-intensity projections of image stacks acquired with a commercial single-point CLSM instrument (Olympus Fluoview 1000; ), and a speckle-based HiLo microscope (). The imaged sample is cytoplasmic GFP-labeled neurons in a 100-μm fixed mouse brain slice. Scale bar, 50 μm. Reprinted from ref. 61. Author information Affiliations * Department of Biomedical Engineering, Boston University, Boston, Massachusetts, USA. * Jerome Mertz Competing financial interests The author declares no competing financial interests. Corresponding author Correspondence to: * Jerome Mertz Author Details * Jerome Mertz Contact Jerome Mertz Search for this author in: * NPG journals * PubMed * Google Scholar Additional data
• Proteomic and phosphoproteomic comparison of human ES and iPS cells
  - Nat Methods 8(10):821-827 (2011)
  Nature Methods | Resource Proteomic and phosphoproteomic comparison of human ES and iPS cells * Douglas H Phanstiel1, 2, 7 * Justin Brumbaugh2, 3, 4, 7 * Craig D Wenger1, 2 * Shulan Tian4 * Mitchell D Probasco4 * Derek J Bailey1, 2 * Danielle L Swaney1, 2 * Mark A Tervo1, 2 * Jennifer M Bolin4 * Victor Ruotti4 * Ron Stewart4 * James A Thomson4, 5, 6 * Joshua J Coon1, 2, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:821–827Year published:(2011)DOI:doi:10.1038/nmeth.1699Received22 February 2011Accepted08 August 2011Published online11 September 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 Combining high-mass-accuracy mass spectrometry, isobaric tagging and software for multiplexed, large-scale protein quantification, we report deep proteomic coverage of four human embryonic stem cell and four induced pluripotent stem cell lines in biological triplicate. This 24-sample comparison resulted in a very large set of identified proteins and phosphorylation sites in pluripotent cells. The statistical analysis afforded by our approach revealed subtle but reproducible differences in protein expression and protein phosphorylation between embryonic stem cells and induced pluripotent cells. Merging these results with RNA-seq analysis data, we found functionally related differences across each tier of regulation. We also introduce the Stem Cell–Omics Repository (SCOR), a resource to collate and display quantitative information across multiple planes of measurement, including mRNA, protein and post-translational modifications. View full text Subject terms: * Proteomics * Stem Cells * Cell Biology * Mass Spectrometry Figures at a glance * Figure 1: Figures of merit for peptide identification and quantification. () Peptide identifications as a function of precursor and product mass tolerance. Using proteins isolated from human ESC whole-cell lysate, we performed liquid chromatography tandem mass spectrometry for each combination of dissociation method and mass analyzer. IT, ion-trap detection; FT, orbitrap detection. We searched data using fragment-ion tolerances of 0.01–5.0 Da, filtered results by precursor mass tolerances of 0.5–1,000 p.p.m. and filtered identifications to achieve 1% FDR. We performed experiments in triplicate and averaged the results. The number of peptide spectrum matches (PSMs) is proportional to circle size; number of unique peptides is represented by circle color as indicated. () R2 values for all peptides in each protein (H1 versus NFF comparison; fourplex experiment) were calculated as a metric for quality of quantification. () Characterization of quantification. Data points represent reporter ion intensities for a single protein mixed in the indicated ! ratios. Lines represent the theoretical value for the mixtures presented. * Figure 2: A transcriptomic, proteomic and phosphoproteomic comparison of ESC lines H1 and H9, iPSC line DF19. 7 and NFF line. () Heat maps depict all quantified transcripts, proteins and phosphorylation sites. Values were median-normalized. () Overlap between transcripts and proteins identified in the fourplex experiment. We considered transcripts 'present' if the reads per kilobase of exon per million mapped reads (RPKM) value was greater than 1 for all four cell types, and we determined protein identification via P-value filtering (1% FDR). () Cytoscape schematic of mRNA, protein and phosphorylation quantification from the fourplex experiment for genes known to have an interaction with NANOG, SOX2 or POU5F1 (search tool for the retrieval of interacting genes-proteins (STRING) database, confidence score > 0.90). Data are identified by protein name. * Figure 3: Kinase substrate analysis between ESCs and NFFs (adapted from ref. 24 with permission from the American Association for the Advancement of Science). Highlighted are kinase substrates for sets of phosphorylation sites that were enriched (changed by more than twofold) in ESCs (red; P < 0.05) and in NFFs (blue; P < 0.05). * Figure 4: Comparison of four ESC and four iPSC lines. () Differentially regulated transcripts, proteins and phosphorylation sites are shown as a function of the number of comparisons (n). We performed differential expression analysis using subsets of data. For example, the n = 2 value reflects the number of differences detected from comparing just two ESC lines and two iPSC lines without biological replicate, whereas n = 12 represents the differences detected from comparing all four ESC lines and all four iPSC lines in biological triplicate. The number of differentially regulated elements for a given fold difference is indicated by different colors. The lines connect data point for ease of interpretation. () Heatmaps depicting differentially regulated transcripts, proteins and phosphorylation sites (P < 0.05, Student's t-test, with Benjamini-Hochberg correction). Only transcripts exhibiting at least a 1.5-fold difference and protein and phosphorylation sites exhibiting at least a 1.2-fold difference are shown. () Randomly selec! ted examples of differentially regulated transcripts, proteins and phosphorylation sites. Bar heights represent relative reporter ion intensity (arbitrary units). *P < 0.05 (Student's t-test), (ESCs compared to iPSCs). () Differentially regulated transcripts detected based on either a comparison between biological triplicates of H1 and DF4.7 cell lines or a comparison of biological triplicates of all four ESC and all four iPSC lines. () Overlap between differentially regulated proteins and transcripts (left; only genes with both a quantified protein and transcript were included) and differentially regulated proteins and phosphorylation sites (right; only genes with both a quantified protein and phosphorylation site were included). Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Douglas H Phanstiel & * Justin Brumbaugh Affiliations * Department of Chemistry, University of Wisconsin, Madison, Wisconsin, USA. * Douglas H Phanstiel, * Craig D Wenger, * Derek J Bailey, * Danielle L Swaney, * Mark A Tervo & * Joshua J Coon * Genome Center of Wisconsin, University of Wisconsin, Madison, Wisconsin, USA. * Douglas H Phanstiel, * Justin Brumbaugh, * Craig D Wenger, * Derek J Bailey, * Danielle L Swaney, * Mark A Tervo & * Joshua J Coon * Department of Biomolecular Chemistry, University of Wisconsin, Madison, Wisconsin, USA. * Justin Brumbaugh & * Joshua J Coon * Morgridge Institute for Research, Madison, Wisconsin, USA. * Justin Brumbaugh, * Shulan Tian, * Mitchell D Probasco, * Jennifer M Bolin, * Victor Ruotti, * Ron Stewart & * James A Thomson * Department of Cell and Regenerative Biology, University of Wisconsin, Madison, Wisconsin, USA. * James A Thomson * Department of Molecular, Cellular and Developmental Biology, University of California, Santa Barbara, California, USA. * James A Thomson Contributions D.H.P. designed research, prepared samples, performed mass spectrometry, wrote software, analyzed data and wrote the manuscript. J.B. designed research, grew cells, prepared samples, analyzed data and wrote the manuscript. C.D.W. wrote software. S.T. and V.R. analyzed data. M.D.P. grew cells. D.J.B. designed websites. D.L.S. helped with phosphorylation analysis. M.A.T. optimized the labeling procedure. J.M.B. performed RNA sequencing. R.S. designed research and analyzed data. J.A.T. and J.J.C. designed research and wrote the manuscript. 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. J.J.C. is a consultant for Thermo Fisher Scientific. Corresponding author Correspondence to: * Joshua J Coon Author Details * Douglas H Phanstiel Search for this author in: * NPG journals * PubMed * Google Scholar * Justin Brumbaugh Search for this author in: * NPG journals * PubMed * Google Scholar * Craig D Wenger Search for this author in: * NPG journals * PubMed * Google Scholar * Shulan Tian Search for this author in: * NPG journals * PubMed * Google Scholar * Mitchell D Probasco Search for this author in: * NPG journals * PubMed * Google Scholar * Derek J Bailey Search for this author in: * NPG journals * PubMed * Google Scholar * Danielle L Swaney Search for this author in: * NPG journals * PubMed * Google Scholar * Mark A Tervo 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 * Ron Stewart Search for this author in: * NPG journals * PubMed * Google Scholar * James A Thomson Search for this author in: * NPG journals * PubMed * Google Scholar * Joshua J Coon Contact Joshua J Coon Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (10M) Supplementary Figures 1–5, Supplementary Tables 4,8,9 Excel files * Supplementary Table 1 (6M) Proteomic identification and quantification. * Supplementary Table 2 (10M) Phosphoproteomic identification and quantification. * Supplementary Table 3 (717K) Enrichment analysis from fourplex experiment. * Supplementary Table 5 (5M) Transcriptomic identification and quantification. * Supplementary Table 6 (1M) Transcripts, proteins, and phosphorylation sites that differ between ESCs and iPSCs. * Supplementary Table 7 (238K) Enrichment analysis from eightplex experiment. Additional data
• Induced pluripotent stem cells from highly endangered species
  - Nat Methods 8(10):829-831 (2011)
  Nature Methods | Brief Communication Induced pluripotent stem cells from highly endangered species * Inbar Friedrich Ben-Nun1 * Susanne C Montague1 * Marlys L Houck2 * Ha T Tran1 * Ibon Garitaonandia1 * Trevor R Leonardo1 * Yu-Chieh Wang1 * Suellen J Charter2 * Louise C Laurent1, 3 * Oliver A Ryder2 * Jeanne F Loring1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:829–831Year published:(2011)DOI:doi:10.1038/nmeth.1706Received08 February 2011Accepted19 August 2011Published online04 September 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg For some highly endangered species there are too few reproductively capable animals to maintain adequate genetic diversity, and extraordinary measures are necessary to prevent extinction. We report generation of induced pluripotent stem cells (iPSCs) from two endangered species: a primate, the drill, Mandrillus leucophaeus and the nearly extinct northern white rhinoceros, Ceratotherium simum cottoni. iPSCs may eventually facilitate reintroduction of genetic material into breeding populations. View full text Subject terms: * Stem Cells * Cell Biology * Genetics * Molecular Biology Figures at a glance * Figure 1: Characterization of drill iPSCs. () Phase-contrast micrograph of representative drill iPSCs. () Karyotypes of drill fibroblasts and drill iPSC line G (passage 10). () Quantitative PCR analysis of exogenous reprogramming factors POU5F1, SOX2, KLF4 and MYC in drill iPSC lines and in fibroblasts collected 10 d after transduction with viruses encoding the exogenous transcription factors. Expression was normalized to GAPDH levels. () Normalized expression of endogenous POU5F1, SOX2 and NANOG analyzed in drill iPSC lines and fibroblasts by quantitative PCR. () Micrographs show representative immunocytochemical staining of drill iPSCs with antibodies to the indicated pluripotency markers (all four drill iPSC lines had the same immunocytochemical marker profile). () Hematoxylin and eosin staining of teratoma derived from drill iPSC line J. Endoderm lineage is represented by seromucinous gland, mesoderm lineage by cartilage and ectoderm by neural rosettes. All scale bars, 100 μm. * Figure 2: Characterization of northern white rhinoceros iPSCs. () Phase-contrast micrograph of northern white rhinoceros iPSCs. () Karyotype of northern white rhinoceros fibroblasts and iPSCs (line C, passage 4). () Quantitative reverse-transcription–PCR analysis of the exogenous sequences for the human reprogramming factors in northern white rhinoceros iPSC lines. () Micrographs show immunocytochemical staining of northern white rhinoceros iPSC lines with antibodies to the indicated pluripotency markers. () Micrographs show immunocytochemistry analysis for markers of all three germ layers in northern white rhinoceros embryoid bodies. SMA, smooth muscle actin. All scale bars, 100 μm. Author information * Author information * Supplementary information Affiliations * Center for Regenerative Medicine, Department of Chemical Physiology, The Scripps Research Institute, La Jolla, California, USA. * Inbar Friedrich Ben-Nun, * Susanne C Montague, * Ha T Tran, * Ibon Garitaonandia, * Trevor R Leonardo, * Yu-Chieh Wang, * Louise C Laurent & * Jeanne F Loring * San Diego Zoo Institute for Conservation Research, Escondido, California, USA. * Marlys L Houck, * Suellen J Charter & * Oliver A Ryder * Department of Reproductive Medicine, University of California, San Diego, California, USA. * Louise C Laurent & * Jeanne F Loring Contributions J.F.L., O.A.R. and I.F.B.-N. conceived the study. I.F.B.-N. designed and performed the experiments. S.C.M. assisted with tissue-culture work. O.A.R., M.L.H. and S.J.C. generated the fibroblast cell lines and karyotyped the cells. H.T.T., I.G. and T.R.L. assisted with teratoma formation. Y.-C.W. performed glycomic profiling. L.C.L. contributed to experiment design. I.F.B.-N. 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: * Jeanne F Loring Author Details * Inbar Friedrich Ben-Nun Search for this author in: * NPG journals * PubMed * Google Scholar * Susanne C Montague Search for this author in: * NPG journals * PubMed * Google Scholar * Marlys L Houck Search for this author in: * NPG journals * PubMed * Google Scholar * Ha T Tran Search for this author in: * NPG journals * PubMed * Google Scholar * Ibon Garitaonandia Search for this author in: * NPG journals * PubMed * Google Scholar * Trevor R Leonardo Search for this author in: * NPG journals * PubMed * Google Scholar * Yu-Chieh Wang Search for this author in: * NPG journals * PubMed * Google Scholar * Suellen J Charter Search for this author in: * NPG journals * PubMed * Google Scholar * Louise C Laurent Search for this author in: * NPG journals * PubMed * Google Scholar * Oliver A Ryder Search for this author in: * NPG journals * PubMed * Google Scholar * Jeanne F Loring Contact Jeanne F Loring Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (2.5M) Supplementary Figures 1–11, Supplementary Table 1 Additional data
• FaST linear mixed models for genome-wide association studies
  - Nat Methods 8(10):833-835 (2011)
  Nature Methods | Brief Communication FaST linear mixed models for genome-wide association studies * Christoph Lippert1, 2, 3 * Jennifer Listgarten1, 3 * Ying Liu1 * Carl M Kadie1 * Robert I Davidson1 * David Heckerman1, 3 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:833–835Year published:(2011)DOI:doi:10.1038/nmeth.1681Received05 April 2011Accepted02 August 2011Published online04 September 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/). View full text Subject terms: * Genomics * Bioinformatics Figures at a glance * Figure 1: Computational costs of FaST-LMM and EMMAX. (,) Memory footprint () and run time () of the algorithms running on a single processor as a function of the cohort size in synthetic datasets based on GAW14 data. In each run, we used 7,579 SNPs both to estimate genetic similarity (RRM for FaST-LMM and identity by state for EMMAX) and to test for association. In the 'FaST-LMM full' analysis, the variance parameters were re-estimated for each test, and in the FaST-LMM analysis these parameters were estimated only once for the null model, as in EMMAX. FaST-LMM and FaST-LMM full had the same memory footprint. EMMAX would not run on the datasets that contained 20 or more times the cohort size of the GAW14 data because the memory required to store the large matrices exceeded the 32 GB available. * Figure 2: Accuracy of association P values resulting from SNP sampling on WTCCC data for the Crohn's disease phenotype. Each point in the plot shows the negative log P values of association for a particular SNP from an LMM using a 4,000-SNP sample and all SNPs to compute the RRM. The complete set used all 340,000 SNPs from all but chromosome 1, whereas the 4,000-SNP sample used equally spaced SNPs from these chromosomes. All 28,000 SNPs in chromosome 1 were tested. Dashed lines show the genome-wide significance threshold (5 × 10−7). The correlation for the points in the plot is 0.97. Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Christoph Lippert, * Jennifer Listgarten & * David Heckerman Affiliations * Microsoft Research, Los Angeles, California, USA. * Christoph Lippert, * Jennifer Listgarten, * Ying Liu, * Carl M Kadie, * Robert I Davidson & * David Heckerman * Max Planck Institutes Tübingen, Tübingen, Germany. * Christoph Lippert Contributions C.L., J.L. and D.H. designed and performed research, contributed analytic tools, analyzed data and wrote the paper. Y.L. designed and performed research. C.M.K. and R.I.D contributed analytic tools. Competing financial interests C.L., J.L., C.M.K., R.I.D. and D.H. are employees of Microsoft. Y.L. was employed by Microsoft while performing this research. Corresponding authors Correspondence to: * Christoph Lippert or * Jennifer Listgarten or * David Heckerman Author Details * Christoph Lippert Contact Christoph Lippert Search for this author in: * NPG journals * PubMed * Google Scholar * Jennifer Listgarten Contact Jennifer Listgarten Search for this author in: * NPG journals * PubMed * Google Scholar * Ying Liu Search for this author in: * NPG journals * PubMed * Google Scholar * Carl M Kadie Search for this author in: * NPG journals * PubMed * Google Scholar * Robert I Davidson Search for this author in: * NPG journals * PubMed * Google Scholar * David Heckerman Contact David Heckerman Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (406K) Supplementary Figure 1, Supplementary Notes 1–2 Zip files * Supplementary Software 1 (106M) FaST-LMM software and associated files. Additional data
• Light-based feedback for controlling intracellular signaling dynamics
  - Nat Methods 8(10):837-839 (2011)
  Nature Methods | Brief Communication Light-based feedback for controlling intracellular signaling dynamics * Jared E Toettcher1, 2 * Delquin Gong1 * Wendell A Lim2, 3 * Orion D Weiner1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:837–839Year published:(2011)DOI:doi:10.1038/nmeth.1700Received11 April 2011Accepted04 August 2011Published online11 September 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg The ability to apply precise inputs to signaling species in live cells would be transformative for interrogating and understanding complex cell-signaling systems. Here we report an 'optogenetic' method for applying custom signaling inputs using feedback control of a light-gated protein-protein interaction. We applied this strategy to perturb protein localization and phosphoinositide 3-kinase activity, generating time-varying signals and clamping signals to buffer against cell-to-cell variability or changes in pathway activity. View full text Subject terms: * Cell Biology * Systems Biology * Signal Transduction Figures at a glance * Figure 1: Feedback control to modulate plasma-membrane recruitment of PIF-tagged inputs. () Schematic of feedback control of the Phy-PIF optogenetic module. Upon ligation to the small-molecule chromophore phycocyanobilin (PCB), membrane-fused, fluorescent Phy fusion proteins can be used to drive fluorescent PIF-tagged proteins to the plasma membrane by exposure to 650-nm light, and this interaction can be reversed by exposure to 750-nm light. By automatically tuning input light levels, feedback control sets the activity state at downstream nodes for which live-cell readouts are available. () Schematic of the feedback control system. The user specifies a target function, which is compared to live-cell measurements of intracellular activity (output). The resulting error signal is supplied to the feedback controller to determine the proper light input to an optogenetically gated intracellular signal. (,) Feedback control of Phy-PIF binding in individual live cells to constant () or time-varying () membrane binding. The controller drives membrane binding (top) to a ! desired trajectory (target function; dashed black lines) by adjusting 650-nm LED voltage (bottom). φ, feedback strength. PIF-BFP membrane binding (labeled PIF-BFP) is shown in arbitrary units (a.u.). * Figure 2: Feedback control can decrease cell-to-cell variability in the optogenetic response. () Schematic of how different light inputs must be applied to drive the same recruitment in cells expressing different amounts of optogenetic components. () Histograms of PIF membrane recruitment under a constant light input (simultaneous illumination with 0.2 V, 650-nm light and 0.1 V, 750-nm light) and during feedback control. () The feedback-controlled voltages applied over time to each cell in , showing that light inputs required to compensate for cell-to-cell heterogeneity span a large range of intensities. (,) The mean () and s.d. () of PIF recruitment in the presence or absence of feedback control for the cell populations shown in . * Figure 3: Feedback control can clamp PIP3 levels against cellular perturbations. () Schematic of PI3K recruitment to a membrane target (Phy-mCherry-CAAX) using a fluorescent PIF fusion protein (iSH-YFP-PIF) that constitutively binds endogenous PI3K. The 3′ phosphoinositide lipid amounts were assayed by measuring PHAkt-Cerulean recruitment to the plasma membrane. () Schematic of feedback control used to clamp perturbations in upstream signaling nodes by adjusting light levels to compensate for these changes (such as LY294002-based PI3K inhibition or serum-based PI3K activation). (,) Single-cell time courses in response to a constant light input or with feedback control (top graphs). At 400 s, 3′ phosphoinositide lipid production was perturbed (gray line) by addition of 1 μm LY294002 (PI3K inhibitor; ) or 10% serum (PI3K activator; ). Time-varying light input used by the feedback controller to clamp 3′ phosphoinositide lipid amounts (bottom graphs). Dashed lines indicate the target function. Author information * Author information * Supplementary information Affiliations * Cardiovascular Research Institute and Department of Biochemistry, University of California San Francisco, San Francisco, California, USA. * Jared E Toettcher, * Delquin Gong & * Orion D Weiner * Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, California, USA. * Jared E Toettcher & * Wendell A Lim * Howard Hughes Medical Institute, University of California San Francisco, San Francisco, California, USA. * Wendell A Lim Contributions J.E.T. conceived and implemented the feedback controller. O.D.W. and W.A.L. supervised the project. All authors designed experiments, which J.E.T. and D.G. performed. J.E.T. analyzed data. J.E.T., W.A.L. and O.D.W. wrote the paper, which all authors edited. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Orion D Weiner or * Wendell A Lim Author Details * Jared E Toettcher Search for this author in: * NPG journals * PubMed * Google Scholar * Delquin Gong Search for this author in: * NPG journals * PubMed * Google Scholar * Wendell A Lim Contact Wendell A Lim Search for this author in: * NPG journals * PubMed * Google Scholar * Orion D Weiner Contact Orion D Weiner Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (1M) Supplementary Figures 1–9, Supplementary Note 1 Zip files * Supplementary Software 1 (33K) Matlab toolbox for microscope control (via Micro-Manager) and the feedback controller. Additional data
• Toward the blood-borne miRNome of human diseases
  - Nat Methods 8(10):841-843 (2011)
  Nature Methods | Brief Communication Toward the blood-borne miRNome of human diseases * Andreas Keller1, 2, 21 * Petra Leidinger2, 21 * Andrea Bauer3 * Abdou ElSharawy4 * Jan Haas5 * Christina Backes2 * Anke Wendschlag6 * Nathalia Giese7 * Christine Tjaden7 * Katja Ott7 * Jens Werner7 * Thilo Hackert7 * Klemens Ruprecht8 * Hanno Huwer9 * Junko Huebers10 * Gunnar Jacobs4 * Philip Rosenstiel4 * Henrik Dommisch11 * Arne Schaefer4 * Joachim Müller-Quernheim12 * Bernd Wullich13 * Bastian Keck13 * Norbert Graf14 * Joerg Reichrath15 * Britta Vogel5 * Almut Nebel4 * Sven U Jager16 * Peer Staehler6 * Ioannis Amarantos6 * Valesca Boisguerin6 * Cord Staehler6 * Markus Beier6 * Matthias Scheffler6 * Markus W Büchler7 * Joerg Wischhusen17, 18 * Sebastian F M Haeusler17 * Johannes Dietl17 * Sylvia Hofmann4 * Hans-Peter Lenhof19 * Stefan Schreiber4, 20 * Hugo A Katus5 * Wolfgang Rottbauer5 * Benjamin Meder5 * Joerg D Hoheisel3 * Andre Franke4, 21 * Eckart Meese2, 21 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:841–843Year published:(2011)DOI:doi:10.1038/nmeth.1682Received09 May 2011Accepted27 July 2011Published online04 September 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg In a multicenter study, we determined the expression profiles of 863 microRNAs by array analysis of 454 blood samples from human individuals with different cancers or noncancer diseases, and validated this 'miRNome' by quantitative real-time PCR. We detected consistently deregulated profiles for all tested diseases; pathway analysis confirmed disease association of the respective microRNAs. We observed significant correlations (P = 0.004) between the genomic location of disease-associated genetic variants and deregulated microRNAs. View full text Subject terms: * Bioinformatics * Small RNAs * Gene Expression * Molecular Biology Figures at a glance * Figure 1: Bubble plot of miRNAs that are up- or downregulated in several diseases. Bubble sizes correspond to the number of deregulated miRNAs. Orange bubbles denote miRNAs that are more often significantly down-regulated (P < 0.05) than upregulated. Blue bubbles denote miRNAs that are either more often upregulated or equally frequent up- and downregulated. Homo sapiens (hsa)-miR-320d was significantly deregulated (P < 0.05) in 11 diseases. * Figure 2: Representative example for the physical proximity of a significantly deregulated miRNA and a known SNP. A schematic of the human chromosome 10q21 with hsa-miR-1296 (magenta) and four SNPs (arrows) including SNP rs2393967 (SNP database (dbSNP) accession number) that is associated with heart diseases. The plot shows expression and s.d. of hsa-miR-1296 in the blood of individuals with acute myocardial infarction (AMI, n = 20) compared to that in healthy controls (n = 70). P = 0.006. Accession codes * Accession codes * Author information * Supplementary information Referenced accessions Gene Expression Omnibus * GSE31568 Author information * Accession codes * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Andreas Keller, * Petra Leidinger, * Andre Franke & * Eckart Meese Affiliations * Biomarker Discovery Center, Heidelberg, Germany. * Andreas Keller * Institute of Human Genetics, Saarland University, Medical Faculty, Homburg, Germany. * Andreas Keller, * Petra Leidinger, * Christina Backes & * Eckart Meese * German Cancer Research Center, Functional Genome Analysis, Heidelberg, Germany. * Andrea Bauer & * Joerg D Hoheisel * Institute of Clinical Molecular Biology, Christian Albrechts University, Kiel, Germany. * Abdou ElSharawy, * Gunnar Jacobs, * Philip Rosenstiel, * Arne Schaefer, * Almut Nebel, * Sylvia Hofmann, * Stefan Schreiber & * Andre Franke * Department of Internal Medicine, University of Heidelberg, Heidelberg, Germany. * Jan Haas, * Britta Vogel, * Hugo A Katus, * Wolfgang Rottbauer & * Benjamin Meder * febit group, Heidelberg, Germany. * Anke Wendschlag, * Peer Staehler, * Ioannis Amarantos, * Valesca Boisguerin, * Cord Staehler, * Markus Beier & * Matthias Scheffler * Department of General Surgery, University of Heidelberg, Heidelberg, Germany. * Nathalia Giese, * Christine Tjaden, * Katja Ott, * Jens Werner, * Thilo Hackert & * Markus W Büchler * Department of Neurology, Charité University Hospital, Berlin, Germany. * Klemens Ruprecht * Department of Cardiothoracic Surgery, Voelklingen Heart Center, Voelklingen, Germany. * Hanno Huwer * Department of Pneumology, Voelklingen Lung Center, Voelklingen, Germany. * Junko Huebers * Department of Periodontology, Operative and Preventive Dentistry, University Hospital Bonn, Bonn, Germany. * Henrik Dommisch * Department of Pneumology, University Hospital Medical Center, Freiburg, Germany. * Joachim Müller-Quernheim * Department of Urology, University Clinic, Friedrich-Alexander University, Erlangen-Nuremberg, Nuremberg, Germany. * Bernd Wullich & * Bastian Keck * Department of Pediatric Hematology and Oncology, Saarland University, Medical Faculty, Homburg, Germany. * Norbert Graf * Clinic for Dermatology, Venerology and Allergology, Saarland University, Medical Faculty, Homburg, Germany. * Joerg Reichrath * Praxis für Dermatologie, Sulzbach, Germany. * Sven U Jager * Department of Obstetrics and Gynecology, Medical School, University of Wuerzburg, Wuerzburg, Germany. * Joerg Wischhusen, * Sebastian F M Haeusler & * Johannes Dietl * Interdisciplinary Center for Clinical Research, Junior Research Group 'Tumor progression and immune escape', Medical School, University of Wuerzburg, Wuerzburg, Germany. * Joerg Wischhusen * Center For Bioinformatics, Saarland University, Saarbruecken, Germany. * Hans-Peter Lenhof * First Medical Department, University Clinic Schleswig-Holstein, Kiel, Germany. * Stefan Schreiber Contributions A.K. initiated the study; E.M., P.R., J.M-Q., A.B., P.S., V.B., C.S., M.B., M.W.B., J.W., S.F.M.H., J.D., S.S., H.A.K., W.R., B.M., J.D.H. and A.F. designed the study; A.K., P.L., A.E., H.A.K., W.R., B.M., J.D.H., A.F., E.M., S.S. and B.V. wrote the manuscript; A.K., J.H., C.B., A.W., I.A., B.V. and H-P.L. analyzed data; P.L., A.B., C.T., A.E., N.G., K.O., J.W., T.H., G.J., H.D., A.S., B.W., B.K., N.G., A.N., V.B., B.V., S.H. and B.M. performed experiments; C.T., K.O., T.H., K.R., H.H., J.H., G.J., H.D., A.S., B.W., B.K., J.R., S.U.J., N.G., M.S., M.W.B., J.W. and S.F.M.H. collected samples. Competing financial interests A.K., C.B., A.W., I.A., P.S., V.B., C.S., M.B., MS have been affiliated with febit, a biotech company specializing in microarray screening. Corresponding author Correspondence to: * Andreas Keller Author Details * Andreas Keller Contact Andreas Keller Search for this author in: * NPG journals * PubMed * Google Scholar * Petra Leidinger Search for this author in: * NPG journals * PubMed * Google Scholar * Andrea Bauer Search for this author in: * NPG journals * PubMed * Google Scholar * Abdou ElSharawy Search for this author in: * NPG journals * PubMed * Google Scholar * Jan Haas Search for this author in: * NPG journals * PubMed * Google Scholar * Christina Backes Search for this author in: * NPG journals * PubMed * Google Scholar * Anke Wendschlag Search for this author in: * NPG journals * PubMed * Google Scholar * Nathalia Giese Search for this author in: * NPG journals * PubMed * Google Scholar * Christine Tjaden Search for this author in: * NPG journals * PubMed * Google Scholar * Katja Ott Search for this author in: * NPG journals * PubMed * Google Scholar * Jens Werner Search for this author in: * NPG journals * PubMed * Google Scholar * Thilo Hackert Search for this author in: * NPG journals * PubMed * Google Scholar * Klemens Ruprecht Search for this author in: * NPG journals * PubMed * Google Scholar * Hanno Huwer Search for this author in: * NPG journals * PubMed * Google Scholar * Junko Huebers Search for this author in: * NPG journals * PubMed * Google Scholar * Gunnar Jacobs Search for this author in: * NPG journals * PubMed * Google Scholar * Philip Rosenstiel Search for this author in: * NPG journals * PubMed * Google Scholar * Henrik Dommisch Search for this author in: * NPG journals * PubMed * Google Scholar * Arne Schaefer Search for this author in: * NPG journals * PubMed * Google Scholar * Joachim Müller-Quernheim Search for this author in: * NPG journals * PubMed * Google Scholar * Bernd Wullich Search for this author in: * NPG journals * PubMed * Google Scholar * Bastian Keck Search for this author in: * NPG journals * PubMed * Google Scholar * Norbert Graf Search for this author in: * NPG journals * PubMed * Google Scholar * Joerg Reichrath Search for this author in: * NPG journals * PubMed * Google Scholar * Britta Vogel Search for this author in: * NPG journals * PubMed * Google Scholar * Almut Nebel Search for this author in: * NPG journals * PubMed * Google Scholar * Sven U Jager Search for this author in: * NPG journals * PubMed * Google Scholar * Peer Staehler Search for this author in: * NPG journals * PubMed * Google Scholar * Ioannis Amarantos Search for this author in: * NPG journals * PubMed * Google Scholar * Valesca Boisguerin Search for this author in: * NPG journals * PubMed * Google Scholar * Cord Staehler Search for this author in: * NPG journals * PubMed * Google Scholar * Markus Beier Search for this author in: * NPG journals * PubMed * Google Scholar * Matthias Scheffler Search for this author in: * NPG journals * PubMed * Google Scholar * Markus W Büchler Search for this author in: * NPG journals * PubMed * Google Scholar * Joerg Wischhusen Search for this author in: * NPG journals * PubMed * Google Scholar * Sebastian F M Haeusler Search for this author in: * NPG journals * PubMed * Google Scholar * Johannes Dietl Search for this author in: * NPG journals * PubMed * Google Scholar * Sylvia Hofmann Search for this author in: * NPG journals * PubMed * Google Scholar * Hans-Peter Lenhof Search for this author in: * NPG journals * PubMed * Google Scholar * Stefan Schreiber Search for this author in: * NPG journals * PubMed * Google Scholar * Hugo A Katus Search for this author in: * NPG journals * PubMed * Google Scholar * Wolfgang Rottbauer Search for this author in: * NPG journals * PubMed * Google Scholar * Benjamin Meder Search for this author in: * NPG journals * PubMed * Google Scholar * Joerg D Hoheisel Search for this author in: * NPG journals * PubMed * Google Scholar * Andre Franke Search for this author in: * NPG journals * PubMed * Google Scholar * Eckart Meese Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Accession codes * Author information * Supplementary information PDF files * Supplementary Text and Figures (5M) Supplementary Figures 1–6, Supplementary Tables 1–8 Additional data
• Quantitative proteomics by amino acid labeling in C. elegans
  - Nat Methods 8(10):845-847 (2011)
  Nature Methods | Brief Communication Quantitative proteomics by amino acid labeling in C. elegans * Julius Fredens1 * Kasper Engholm-Keller1 * Anders Giessing1 * Dennis Pultz1 * Martin Røssel Larsen1 * Peter Højrup1 * Jakob Møller-Jensen1 * Nils J Færgeman1 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:845–847Year published:(2011)DOI:doi:10.1038/nmeth.1675Received02 February 2011Accepted26 July 2011Published online28 August 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 demonstrate labeling of Caenorhabditis elegans with heavy isotope–labeled lysine by feeding them with heavy isotope–labeled Escherichia coli. Using heavy isotope–labeled worms and quantitative proteomics methods, we identified several proteins that are regulated in response to loss or RNAi-mediated knockdown of the nuclear hormone receptor 49 in C. elegans. The combined use of quantitative proteomics and selective gene knockdown is a powerful tool for C. elegans biology. View full text Subject terms: * Biochemistry * Model Organisms * Proteomics Figures at a glance * Figure 1: Labeling of C. elegans with heavy isotope–labeled lysine. A lysine auxotroph E. coli strain was grown in defined medium containing Lys0 or Lys8 (light and heavy isotopes, respectively). Synchronized L1 worms were grown for 2–3 d on light isotope– or heavy isotope–labeled E. coli. L4 worm populations were mixed 1:1 and analyzed by LC-MS/MS. Relative protein expression was determined by comparing the intensity of light and heavy peptide doublets with a mass difference of 8 Da (heavy:light ratio). * Figure 2: Quantification of protein changes upon loss or knockdown of nhr-49. () In a label-switch experiment, heavy isotope– and light isotope–labeled nhr-49 and wild-type worms, respectively, were mixed, and proteomes were analyzed by LC-MS/MS. The log2-fold change values of all quantified proteins were compared to log2-fold change of the same proteins quantified in a similar experiment, except that nhr-49 was knocked down by RNAi, revealing a significant correlation (Spearman, r = 0.4764, P < 0.0001) between the two experiments. () Log2-fold change of heavy:light isotope ratios in duplicate nhr-49 RNAi experiments were plotted each against the other, revealing a significant correlation (Pearson, r = 0.6474, P < 0.0001) between the duplicate experiments. () GO-term distribution of proteins identified to be upregulated (162 proteins) or downregulated (168 proteins), in response to RNAi-mediated knockdown of nhr-49. Author information * Author information * Supplementary information Affiliations * Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark. * Julius Fredens, * Kasper Engholm-Keller, * Anders Giessing, * Dennis Pultz, * Martin Røssel Larsen, * Peter Højrup, * Jakob Møller-Jensen & * Nils J Færgeman Contributions J.F., K.E.-K., A.G., P.H., M.R.L., J.M.-J. and N.J.F. designed research; J.F., K.E.-K., A.G., D.P., P.H., J.M.-J. and N.J.F. performed research and analyzed data; J.F. and N.F. wrote the manuscript, which K.E.K., P.H., M.R.L. and J.M.J. improved. N.F., J.M.J., M.R.L. and P.H. provided funding. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Nils J Færgeman Author Details * Julius Fredens Search for this author in: * NPG journals * PubMed * Google Scholar * Kasper Engholm-Keller Search for this author in: * NPG journals * PubMed * Google Scholar * Anders Giessing Search for this author in: * NPG journals * PubMed * Google Scholar * Dennis Pultz Search for this author in: * NPG journals * PubMed * Google Scholar * Martin Røssel Larsen Search for this author in: * NPG journals * PubMed * Google Scholar * Peter Højrup Search for this author in: * NPG journals * PubMed * Google Scholar * Jakob Møller-Jensen Search for this author in: * NPG journals * PubMed * Google Scholar * Nils J Færgeman Contact Nils J Færgeman 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 1–6 and Supplementary Table 2 Excel files * Supplementary Table 1 (2M) Protein list of all identified, quantified and regulated proteins in strain N2 and in nhr-49(nr2041) worms and in N2 nhr-49 RNAi worms. Additional data
• Stable-isotope labeling with amino acids in nematodes
  - Nat Methods 8(10):849-851 (2011)
  Nature Methods | Brief Communication Stable-isotope labeling with amino acids in nematodes * Mark Larance1, 4 * Aymeric P Bailly1, 3, 4 * Ehsan Pourkarimi1 * Ronald T Hay1 * Grant Buchanan2 * Sarah Coulthurst2 * Dimitris P Xirodimas1, 3 * Anton Gartner1 * Angus I Lamond1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:849–851Year published:(2011)DOI:doi:10.1038/nmeth.1679Received25 April 2011Accepted01 August 2011Published online28 August 2011 Article tools * Full text * Print * Email * Download PDF * Download citation * Order reprints * Rights and permissions * Share/bookmark * Connotea * CiteULike * Facebook * Twitter * Delicious * Digg We describe an approach for accurate quantitation of global protein dynamics in Caenorhabditis elegans. We adapted stable-isotope labeling with amino acids in cell culture (SILAC) for nematodes by feeding worms a heavy lysine– and heavy arginine–labeled Escherichia coli strain and report a genetic solution to elminate the problem of arginine-to-proline conversion. Combining our approach with quantitative proteomics methods, we characterized the heat-shock response in worms. View full text Subject terms: * Proteomics * Proteomics * Biochemistry * Microbiology Figures at a glance * Figure 1: Elimination of arginine-to-proline conversion using orn-1–targeted RNAi via feeding facilitates stable-isotope labeling with amino acids. Lysates from light isotope– or heavy isotope–labeled C. elegans were mixed in equal proportions, fractionated by denaturing size-exclusion chromatography and fraction 12 was analyzed by trypsin digestion and LC-MS/MS. A representative proline-containing peptide derived from EF-1α was examined. Shown are mass spectra for the indicated peptide sequences. The peak intensity of the depicted 'light' model peptide approximately equals the combined intensities of the corresponding heavy peptide and the peptide that contains heavy proline (3 replicates). * Figure 2: SILAC in nematodes, taking the analysis of the heat-shock response as an example. E. coli SLE1 strain expressing the orn-1 RNAi construct are grown in 'light' medium (M9 minimal medium with arginine and lysine) or 'heavy' medium (M9 minimal medium and 15N4-13C6-arginine and 15N2-13C6-lysine). Bacteria are concentrated by centrifugation and plated on Petri dishes, onto which adult worms are transferred. Upon ingesting bacteria, worms incorporate 'light' or 'heavy' amino acids and orn-1 knockdown occurs. Single worm progeny are transferred onto a new plate, which is then processed as shown. * Figure 3: Analysis of C. elegans heat-shock response using SILAC in nematodes. The abundance of ~1,400 proteins is indicated on the y axis using a log2 scale. The abundance of each protein indicated by the position of the dot on the y axis was determined by summing all individual light and heavy peptide intensities detected for each protein. The relative fold decrease or increase upon heat-shock treatment is indicated on the x axis. Heat shock–treated worms were grown on heavy isotope–labeled SLE1 bacteria, and untreated worms were grown on light bacteria (data from the average of two replicates are shown). Author information * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Mark Larance & * Aymeric P Bailly Affiliations * Wellcome Trust Centre for Gene Regulation and Expression, University of Dundee, Dundee, UK. * Mark Larance, * Aymeric P Bailly, * Ehsan Pourkarimi, * Ronald T Hay, * Dimitris P Xirodimas, * Anton Gartner & * Angus I Lamond * Department of Molecular Microbiology, College of Life Sciences, University of Dundee, Dundee, UK. * Grant Buchanan & * Sarah Coulthurst * Present address: Universités Montpellier 2 et 1, Centre de Recherche de Biochimie Macromoléculaire, Centre National de la Recherche Scientifique, Unité Mixte de Recherche 5237, Montpellier, France. * Aymeric P Bailly & * Dimitris P Xirodimas Contributions A.P.B. and E.P. cloned, passaged and treated all C. elegans samples. M.L. performed all protein analysis. M.L., A.P.B., A.G. and A.I.L. wrote the paper. A.P.B., R.T.H., G.B. and S.C. generated the E. coli auxotroph strains. D.P.X., A.G. and A.I.L. provided mentorship and financed the project. Competing financial interests The authors declare no competing financial interests. Corresponding authors Correspondence to: * Angus I Lamond or * Anton Gartner Author Details * Mark Larance Search for this author in: * NPG journals * PubMed * Google Scholar * Aymeric P Bailly Search for this author in: * NPG journals * PubMed * Google Scholar * Ehsan Pourkarimi Search for this author in: * NPG journals * PubMed * Google Scholar * Ronald T Hay Search for this author in: * NPG journals * PubMed * Google Scholar * Grant Buchanan Search for this author in: * NPG journals * PubMed * Google Scholar * Sarah Coulthurst Search for this author in: * NPG journals * PubMed * Google Scholar * Dimitris P Xirodimas Search for this author in: * NPG journals * PubMed * Google Scholar * Anton Gartner Contact Anton Gartner Search for this author in: * NPG journals * PubMed * Google Scholar * Angus I Lamond Contact Angus I Lamond Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Author information * Supplementary information PDF files * Supplementary Text and Figures (512K) Supplementary Figures 1–5 and Supplementary Table 2 Excel files * Supplementary Table 1 (2M) MaxQuant protein output for stable-isotope labeling with amino acids analysis. Additional data
• Antiviral restriction factor transgenesis in the domestic cat
  - Nat Methods 8(10):853-859 (2011)
  Nature Methods | Article Antiviral restriction factor transgenesis in the domestic cat * Pimprapar Wongsrikeao1 * Dyana Saenz1 * Tommy Rinkoski1 * Takeshige Otoi2 * Eric Poeschla1, 3 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:853–859Year published:(2011)DOI:doi:10.1038/nmeth.1703Received11 April 2011Accepted01 August 2011Published online11 September 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 Studies of the domestic cat have contributed to many scientific advances, including the present understanding of the mammalian cerebral cortex. A practical capability for cat transgenesis is needed to realize the distinctive potential of research on this neurobehaviorally complex, accessible species for advancing human and feline health. For example, humans and cats are afflicted with pandemic AIDS lentiviruses that are susceptible to species-specific restriction factors. Here we introduced genes encoding such a factor, rhesus macaque TRIMCyp, and eGFP, into the cat germline. The method establishes gamete-targeted transgenesis for the first time in a carnivore. We observed uniformly transgenic outcomes, widespread expression, no mosaicism and no F1 silencing. TRIMCyp transgenic cat lymphocytes resisted feline immunodeficiency virus replication. This capability to experimentally manipulate the genome of an AIDS-susceptible species can be used to test the potential of restrict! ion factors for HIV gene therapy and to build models of other infectious and noninfectious diseases. View full text Subject terms: * Model Organisms * Microbiology * Gene Expression Figures at a glance * Figure 1: Transgenic feline embryo generation. () Optimized transgenesis protocol. PMSG, pregnant mare serum gonadotropin; HCG, human chorionic gonadotropin; IU, international units; IVM, in vitro maturation; IVC, in vitro culture. () Transgene expression in hatching feline blastocysts developed in vitro after pre-IVF lentiviral vector microinjection (top left) of feline oocytes. Living GFP-transgenic cat blastocyst (bottom left) developed from oocyte transduced before IVF with TSinG. Confocal images (right) of fixed transgenic (TBDmGpT) and control (product of untransduced oocytes) blastocysts subjected to immunolabeling show HA-tagged rhTRIMCyp signal (HA); GFP fluorescence; DAPI staining for nuclear DNA and merged images. Scale bars, 100 μm (black bars) and 50 μM (white bars). * Figure 2: Transgenic kittens. () Ambient light– and 485 nM light–illuminated images showing GFP signal at indicated times after birth for TgCat3. In the 30 d and 5 month images TgCat3 was photographed with a non-transgenic control cat (right). Coat, claw, whisker, nose, tongue and oropharyngeal mucosa fluorescence are evident; fluorescence was relatively quenched in dark fur. () Southern blotting of genomic DNA from TgCat1, TgCat2 and TgCat3. Southern junction blot designs are shown. d, distance from vector-host DNA junction to nearest genomic AflIII or BamH1 site in base pairs; P, promoter; LTR, long terminal repeat; G, eGFP; T, TRIMCyp. Genomic DNA from tail tips was digested with AflIII (left blot). Genomic DNA from peripheral blood mononuclear cells was digested with BamH1 (right blot). After electrophoresis and Southern blot transfer, membranes were probed for integrated vector DNA as indicated. () Amplicons from semiquantitative PCR amplifications of kitten genomic DNA using primers for the rhT! RIMCyp sequence. M, marker. Cycles, number of PCR amplification cycles. Quantitative PCR showed that TgCat1 and TgCat2 had 15.2 ± 2.1 and 4.38 ± 0.2 GFP gene copies per cell equivalent respectively, using a value of 6.3 pg genomic DNA per diploid cell and normalizing to the signal obtained with GAPDH primers. * Figure 3: Immunoblotting and FIV challenge of transgenic PBMCs. () Representative immunoblots for GFP and HA-tagged rhTRIMCyp in PBMCs isolated from transgenic and control cats. All PBMC are activated (PHA-E) except for the TgCat1 sample labeled 'unactivated'. () Flow cytometry analysis of GFP expression in activated PBMCs. Percentages of cells that are GFP-positive are indicated. () GFP expression in PBMCs versus cat age (left) and GFP expression in PBMCs from a single time point, as a function of days in ex vivo culture; sampling here was at 3–4 months of age (arrow). () PBMCs from cat were infected with 105 Crandell feline kidney cells (CrFK) cell-infectious units of FIV on day 0, washed on day 1 and then followed by sampling for supernatant reverse transcriptase activity determination every 48 h as shown. RT, reverse transcriptase; SSC, side scatter. * Figure 4: Germline transmission and expression in F1 progeny. Sperm from the two males (20 months) and a control non-transgenic cat was filtered, pelleted, washed and then purified by the swim-up technique. Sperm genomic DNA was subjected to real time quantitative PCR with primers that amplify the GFP sequence. Images show four F1 progeny of a mating of TgCat1 and TgCat3, imaged for GFP expression; dark fur quenches such that in the black cat only claws were visibly green fluorescent (middle, right). * Figure 5: Whole body analyses of TgCat4 and late developmental stage fetuses. () Immunoblotting on lysates from indicated organs from non-transgenic control cat (lanes 1); preterm fetal tissues (lanes 2–5; and TgCat4 (lanes 6). Uncropped versions of these films are available in Supplementary Figure 4. These are minimal (<1 s) film exposures of the immunoblots; the central white-out in the heart GFP band is a result of heavy GFP expression causing artifactual exhaustion of chemiluminescent substrate. () Southern blotting for integrated vector DNA. Genomic DNA from heart tissue was digested to completion with NdeI and 5 μg were loaded per lane. Specific bands for intact integrated vector are predicted to be ≥ 1.6 kb. Feline T cell line (FetJ) (left control); control cat; TgPre1–4 from pregnancy C; and TgCat4 are shown. () Cardiac muscle from a control cat, TgPre1 and TgCat4 was subjected to indirect immunofluorescence with a monoclonal antibody to GFP. () GFP imaged directly in fresh thin sections of TgPre1 myocardium by epifluorescence microscop! y. () FACS analyses of fetalPBMCs. Scale bars, 100 μm (black bars) and 20 μM (white bars). Author information * Abstract * Author information * Supplementary information Affiliations * Department of Molecular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. * Pimprapar Wongsrikeao, * Dyana Saenz, * Tommy Rinkoski & * Eric Poeschla * Department of Veterinary Medicine, Yamaguchi University, Japan. * Takeshige Otoi * Division of Infectious Diseases, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. * Eric Poeschla Contributions All authors designed experiments, analyzed data and critiqued the manuscript. E.P. conceived the project and recruited P.W. and T.O. E.P. and T.O. oversaw the project. P.W. and D.S. produced vector and retrieved gametes; P.W. microinjected vector and did embryo cultures. P.W. transfered embryos with assistance from T.R. and E.P. with surgery. P.W., D.S and T.R. monitored cats, did cell and tissue assays and virology. P.W., D.S. and E.P. wrote the manuscript. Competing financial interests The authors declare no competing financial interests. Corresponding author Correspondence to: * Eric Poeschla Author Details * Pimprapar Wongsrikeao Search for this author in: * NPG journals * PubMed * Google Scholar * Dyana Saenz Search for this author in: * NPG journals * PubMed * Google Scholar * Tommy Rinkoski Search for this author in: * NPG journals * PubMed * Google Scholar * Takeshige Otoi Search for this author in: * NPG journals * PubMed * Google Scholar * Eric Poeschla Contact Eric Poeschla 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 1–5 and Supplementary Tables 1–3 Additional data
• Site-specific integration and tailoring of cassette design for sustainable gene transfer
  - Nat Methods 8(10):861-869 (2011)
  Nature Methods | Article Site-specific integration and tailoring of cassette design for sustainable gene transfer * Angelo Lombardo1, 2 * Daniela Cesana1, 2, 7 * Pietro Genovese1, 2, 7 * Bruno Di Stefano3, 6, 7 * Elena Provasi2, 4, 7 * Daniele F Colombo1, 2, 7 * Margherita Neri1, 2 * Zulma Magnani4 * Alessio Cantore1, 2 * Pietro Lo Riso1, 2 * Martina Damo1, 2 * Oscar M Pello1 * Michael C Holmes5 * Philip D Gregory5 * Angela Gritti1 * Vania Broccoli3 * Chiara Bonini4 * Luigi Naldini1, 2 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:861–869Year published:(2011)DOI:doi:10.1038/nmeth.1674Received08 February 2011Accepted29 July 2011Published online21 August 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 Integrative gene transfer methods are limited by variable transgene expression and by the consequences of random insertional mutagenesis that confound interpretation in gene-function studies and may cause adverse events in gene therapy. Site-specific integration may overcome these hurdles. Toward this goal, we studied the transcriptional and epigenetic impact of different transgene expression cassettes, targeted by engineered zinc-finger nucleases to the CCR5 and AAVS1 genomic loci of human cells. Analyses performed before and after integration defined features of the locus and cassette design that together allow robust transgene expression without detectable transcriptional perturbation of the targeted locus and its flanking genes in many cell types, including primary human lymphocytes. We thus provide a framework for sustainable gene transfer in AAVS1 that can be used for dependable genetic manipulation, neutral marking of the cell and improved safety of therapeutic applic! ations, and demonstrate its feasibility by rapidly generating human lymphocytes and stem cells carrying targeted and benign transgene insertions. View full text Subject terms: * Molecular Biology * Gene Expression * Epigenetics * Molecular Engineering Figures at a glance * Figure 1: Targeted integration and transgene expression in CCR5 and AAVS1 of human lymphoblastoid cells. () Schematics of ZFN-induced targeted integration into the indicated loci. The targeting constructs (donor IDLV) are depicted as reverse-transcribed IDLVs containing the expression cassette flanked by homology sequences (gray lines and boxes) to CCR5 or PPP1R12C. LTR: self-inactivating long terminal repeat. ψ, packaging signal. ZFN cleavage sites are indicated. BGHpA: poly(A) site from the bovine growth hormone gene. () EGFP+ cells (mean ± s.e.m., n = 4–7 for each cassette per locus) one month after transduction with the indicated donor IDLVs, with or without IDLVs expressing the indicated ZFNs. (,) Histograms (top) show the EGFP MFI (in arbitrary units; a.u.) of the indicated samples. Southern blots (middle) show targeted integration of the indicated cassettes into CCR5 (; blot probed for EGFP) or AAVS1 (; blots probed for AAVS1) in sorted EGFP+ cells and in single cell–derived clones from the donor and ZFNs conditions as in . In , vertical dashed line separates sampl! es treated with the indicated cassettes. Schematics (right) show the expected targeted integration (TI) of a single cassette or a donor head-to-tail vector concatemer into the target site (HT-TI), with the restriction sites and probes (colored bars) used for analysis. Most sorted cells and all clones contained mono- or biallelic (*) integration at the target site. PCR analyses (bottom) for the 5′ and 3′ junctions generated by targeted integration of the cassette into the locus (TI) or for the presence of head-to-tail vector concatamers (HT) that can be either targeted or not into the site. NA, not assessed. () Representative of three flow cytometry analyses of mock-treated (untransduced cells), or CCR5 or AAVS1 gene-targeted lymphoblastoid cells from showing the green fluorescence (in arbitrary units; a.u.) driven by the indicated promoters. The EGFP MFI of the indicated cassettes upon targeted integration into CCR5 or AAVS1 is shown in red or blue, respectively. () Rep! resentative green fluorescence and MFI from PGK-EGFP-pA casset! tes targeted into AAVS1 of lymphoblastoid cells together with the indicated DNA fragments from the CCR5 gene. * Figure 2: Upregulation of endogenous genes at the integration site depends on the exogenous promoter and target locus. () To-scale representation (top) of the 400 kb genomic region centered on CCR5 on human chromosome 3p21. Genes (boxes indicate exons) and their transcripts (arrows) are shown. The cassette integration site in exon 3 of CCR5 and its transcriptional orientation are indicated by the red arrow. Fold changes in expression (bottom) measured by qRT-PCR of the indicated genes in EGFP+ sorted B-lymphoblastoid cells relative to EGFP− sorted and mock-treated cells, upon targeting the indicated cassettes into CCR5. For RTP3, LUZZP, LRRC2 and CCR1 n = 2 for the EF1A and EF1A_intron cassettes; thus, mean ± range is indicated. For all other cassettes and all genes or conditons n = 6–12; thus, mean ± s.e.m. is indicated. *P < 0.05; **P < 0.01; ***P < 0.001 (one-way Anova with Bonferroni's multiple comparison post-test). ND, not detectable. Expression of each gene in mock-treated cells relative to B2M is indicated by change in cycle threshold (Ct); lower ΔCt correlates with higher exp! ression. NA, not applicable (Ct ≥ 37). Dashed line indicates the reference value in mock-treated cells. () Fold change in CCR5, CCR3 and B2M (latter for normalization) expression in the indicated samples relative to mock-treated cells. Horizontal bars indicate mean fold change; statistical analysis as in . Based on the variance in B2M and HPRT expression among all 200 samples analyzed, fold changes of 0.6–1.4 (dashed lines in the bottom plot) were not considered relevant. () Comparison of EGFP and CCR5 expression, expressed as ΔCt over B2M value, for the indicated cassettes in the EGFP+ B-lymphoblastoid cells from samples in and (mean ± s.e.m., n = 8–12 samples). () Similar analysis as in performed for the 400-kb genomic region surrounding AAVS1 on chromosome 19q13 upon targeting of indicated cassettes. For all genes tested n = 2 for the SFFV, EF1A and EF1A_intron cassettes; thus mean ± range is indicated by error bars. For the PGK cassette n = 4; thus mean ± s.e.! m. is indicated by error bars. Dashed line, reference value fo! r mock-treated cells. () EGFP MFI (arbitrary units; a.u.) of the indicated expression cassettes upon targeted integration into CCR5 or AAVS1 of HepG2 cells (mean ± s.e.m., n = 3). ET, enhanced transthyretin promoter (synthetic hepatocyte-specific promoter); hAAT, proximal promoter of the human α1-antitrypsin gene; ApoE, three copies of the enhancer of the apolipoprotein E gene cloned upstream of the hAAT promoter; and HCR, hepatic control region of the apolipoprotein genes cluster cloned upstream of the hAAT promoter. () EGFP+ sorted HepG2 cells from were analyzed as in and for expression of the indicated genes (mean ± s.e.m., n = 3 sorted cell pools per promoter per locus). Dashed line indicates the reference value in mock-treated cells. () CCR5 expression in EGFP+ lymphoblastoid cells upon targeting the SFFV-EGFP-pA cassette into CCR5 with or without the AAVS1 insulator (Ins) cloned in forward (InsF) or reverse (InsR) orientation (mean ± s.e.m.; n = 3 sorted cell pool! s per cassette). Prom., promoter. * Figure 3: Cassette design for unperturbed target gene expression. () Fold change in PPP1R12C and B2M expression in EGFP+ cells from sorted pools shown in Figure 2d and single cell–derived clones characterized for mono- or biallelic targeted integration of the indicated EGFP expression cassettes relative to mock-treated and EGFP− sorted cells (analysis as in Fig. 2d). Based on the variance in B2M and HPRT expression among all 200 samples analyzed, fold changes of 0.6–1.4 (dashed lines in the bottom plot) were not considered relevant. (,) RT-PCR analysis () of the indicated EGFP+ cells from shows aberrant PPP1R12C transcripts that contain exon 1 of the gene (; orange line) spliced to EGFP (; green line) in cells with targeted integration of the PGK and EF1A_intron cassettes. () PPP1R12C expression in EGFP+ sorted B lymphoblastoid cells upon targeting the modified PGK*-EGFP-pA cassette into AAVS1 (n = 3 sorted cell pools) relative to mock-treated cells. The two changes introduced in the PGK promoter sequence to abolish a splice acceptor! (SA) site are indicated. () Representative flow cytometry analysis of a cell clone with monoallelic integration of the EF1A_intron-EGFP-pA cassette into AAVS1 before (left; gate region indicates the single-positive cells, EGFP+ CFP−; percentage indicated) and after (right; gate region indicates the double-positive cells, EGFP+ CFP+) targeting of an EF1A_intron-CFP-pA cassette in reverse orientation relative to the transcription of the endogenous gene in the residual wild-type AAVS1. Schematics on top depict the AAVS1 genotype. () Fold changes in PPP1R12C expression in the single (EGFP+ CFP−) and double-positive (EGFP+ CFP+) sorted B lymphoblastoid cells from the right plot in (n = 3–6 sorted cell pools per condition) relative to mock-treated cells. () Flow cytometry data showing comparable EGFP expression upon targeted integration of an EF1A_intron cassette into AAVS1 in the same or reverse (r-EF1A_intron) orientation relative to PPP1R12C transcription. * Figure 4: Epigenetic analysis of CCR5 and AAVS1 before and after transgene insertion. () Schematic of the CCR5 locus in wild-type cells showing the transcription start site (TSS) and poly(A) site, the ZFN target site in exon 3 and the 9 regions investigated by qPCR (bars). ChIP analysis of wild-type B lymphoblastoid cells (bottom) showing the percentage of enrichment in RNA PolII (shaded area), histone H3 and the indicated histone H3 modifications (colored bars) versus the input, at the indicated distance from the TSS in base pairs (bp). () Similar analysis as in performed on a cell clone containing biallelic integration of SFFV-EGFP-pA cassette (schematic and inset) in CCR5. () Schematic of PPP1R12C and magnification of the genomic region chosen for the analysis. ChIP analysis of wild-type B lymphoblastoid cells as in . (–) ChIP analysis of cell clones containing biallelic integration of the indicated EGFP cassette (schematics and insets) into AAVS1 (bottom histograms). Shown are means or individual measurements (dots) from two independent ChIP experiments! each analyzed by replicate qPCRs. * Figure 5: AAVS1-targeted integration and transgene expression without perturbing endogenous gene expression in primary human T lymphocytes. () Frequency (mean ± s.e.m., n = 3 blood donors per cassette) of EGFP+ T cells 3 weeks after targeting the indicated cassettes into CCR5 or AAVS1. () Growth curves of T cells treated as indicated (mean ± s.e.m., n = 3 samples per condition). Ad5/35, adenoviral vector expressing the ZFNs. () Southern blot showing targeted integration of the indicated EGFP cassettes into AAVS1 (locus probe) of sorted EGFP+ lymphocytes from . Schematics as in Figure 1d. NA, not applicable. TI, percentage of AAVS1 alleles with targeted integration. () Histogram showing the relative EGFP MFI of T lymphocytes with targeted integration of the indicated cassettes into CCR5 or AAVS1 normalized to the amount of the PGK cassette into CCR5 (mean ± s.e.m., n = 3). () Fold change in expression of the indicated genes in sorted EGFP+ T cells upon targeting the indicated cassettes into AAVS1, relative to EGFP− sorted and mock-treated cells (mean ± s.e.m., n = 3). Statistical analysis as in Figure 2d. *! **P < 0.001; ****P < 0.0001. Dashed line indicates the reference value in mock-treated cells. * Figure 6: Transgene expression in human stem cells and their progeny after targeted integration into AAVS1. () Percentage of EGFP+ NSCs at the indicated time after transduction with PGK-EGFP-pA donor IDLV (with or without AAVS1 ZFNs), from a representative experiment of three. () Immunofluorescence images of neurospheres derived from the donor and ZFNs treated NSCs in . Scale bar, 100 μm. () Representative confocal images of in vitro differentiated NSCs from showing EGFP expression in neurons (TUJ1-immunopositive cells, left) or astrocytes (GFAP immunopositive cells, right). Merged signals are yellow; nuclei were counterstained with TO-PRO-3. Scale bar, 50 μm. Percentage of EGFP+ neurons or astrocytes upon in vitro differentiation of the indicated NSCs (right; mean ± s.e.m., n = 3). () Percentage of EGFP+ human iPSCs at the indicated time after transduction with EF1A_intron-EGFP-pA donor IDLV (with or without AAVS1-ZFNs; mean ± s.e.m., n = 3). () Representative immunofluorescence images of EGFP+ (green) iPSC clones showing expression of pluripotency markers (red). Scale bar, 1! 20 μm. () PCR analyses for the 5′ and 3′ junctions generated by targeted integration of the EGFP cassette into AAVS1 of EGFP+ iPSC clones. NTC, no template control. +, positive control for the PCR from a cell clone containing targeted integration of the EF1A_intron cassette. M, marker. () Phase contrast (top) and fluorescence microscopy (bottom) of 6-d-old embryoid bodies derived from the GT1 iPSC clone. () Representative immunofluorescence images of in vitro–differentiated GT1 iPSCs showing expression of lineage-specific markers (red). Nestin and Pax6 are expressed by neural rosettes; Sox17 or SMA are expressed by endoderm- or mesoderm-derived cells, respectively. DNA was stained with DAPI. Scale bar, 120 μm. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Daniela Cesana, * Pietro Genovese, * Bruno Di Stefano, * Elena Provasi & * Daniele F Colombo Affiliations * San Raffaele Telethon Institute for Gene Therapy, Division of Regenerative Medicine, Gene Therapy and Stem Cells, San Raffaele Institute, Milan, Italy. * Angelo Lombardo, * Daniela Cesana, * Pietro Genovese, * Daniele F Colombo, * Margherita Neri, * Alessio Cantore, * Pietro Lo Riso, * Martina Damo, * Oscar M Pello, * Angela Gritti & * Luigi Naldini * Vita-Salute San Raffaele University, Milan, Italy. * Angelo Lombardo, * Daniela Cesana, * Pietro Genovese, * Elena Provasi, * Daniele F Colombo, * Margherita Neri, * Alessio Cantore, * Pietro Lo Riso, * Martina Damo & * Luigi Naldini * Stem Cell and Neurogenesis Unit, Division of Neurosciences, San Raffaele Institute, Milan, Italy. * Bruno Di Stefano & * Vania Broccoli * Experimental Hematology Unit, Division of Regenerative Medicine, Gene Therapy and Stem Cells, Program in Immunology and Bio-immunotherapy of Cancer, San Raffaele Scientific Institute, Milan, Italy. * Elena Provasi, * Zulma Magnani & * Chiara Bonini * Sangamo BioSciences Inc., Richmond, California, USA. * Michael C Holmes & * Philip D Gregory * Present address: Hematopoietic Stem Cell Biology and Differentiation Group, Department of Differentiation and Cancer Centre for Genomic Regulation, Barcelona, Spain. * Bruno Di Stefano Contributions A.L., D.C., P.G., B.D.S., E.P. and D.F.C. designed and performed experiments, and interpreted data. M.N., Z.M., A.C., P.L.R., M.D. and O.M.P. performed experiments and interpreted data. M.C.H. and P.D.G. provided ZFNs. A.G., V.B. and C.B. coordinated NSC, iPSC and T-cell work, respectively. A.L. and L.N. conceived the project, coordinated all work and wrote the paper. Competing financial interests M.C.H. and P.D.G. are employees of Sangamo BioSciences Inc. Corresponding author Correspondence to: * Luigi Naldini Author Details * Angelo Lombardo Search for this author in: * NPG journals * PubMed * Google Scholar * Daniela Cesana Search for this author in: * NPG journals * PubMed * Google Scholar * Pietro Genovese Search for this author in: * NPG journals * PubMed * Google Scholar * Bruno Di Stefano Search for this author in: * NPG journals * PubMed * Google Scholar * Elena Provasi Search for this author in: * NPG journals * PubMed * Google Scholar * Daniele F Colombo Search for this author in: * NPG journals * PubMed * Google Scholar * Margherita Neri Search for this author in: * NPG journals * PubMed * Google Scholar * Zulma Magnani Search for this author in: * NPG journals * PubMed * Google Scholar * Alessio Cantore Search for this author in: * NPG journals * PubMed * Google Scholar * Pietro Lo Riso Search for this author in: * NPG journals * PubMed * Google Scholar * Martina Damo Search for this author in: * NPG journals * PubMed * Google Scholar * Oscar M Pello Search for this author in: * NPG journals * PubMed * Google Scholar * Michael C Holmes Search for this author in: * NPG journals * PubMed * Google Scholar * Philip D Gregory Search for this author in: * NPG journals * PubMed * Google Scholar * Angela Gritti Search for this author in: * NPG journals * PubMed * Google Scholar * Vania Broccoli Search for this author in: * NPG journals * PubMed * Google Scholar * Chiara Bonini Search for this author in: * NPG journals * PubMed * Google Scholar * Luigi Naldini Contact Luigi Naldini Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (7M) Supplementary Figures 1–13, Supplementary Tables 1–6 Additional data
• Miniaturized integration of a fluorescence microscope
  - Nat Methods 8(10):871-878 (2011)
  Nature Methods | Article Miniaturized integration of a fluorescence microscope * Kunal K Ghosh1, 2, 5 * Laurie D Burns2, 5 * Eric D Cocker2, 5 * Axel Nimmerjahn2 * Yaniv Ziv2 * Abbas El Gamal1 * Mark J Schnitzer2, 3, 4 * Affiliations * Contributions * Corresponding authorJournal name:Nature MethodsVolume: 8,Pages:871–878Year published:(2011)DOI:doi:10.1038/nmeth.1694Received29 November 2010Accepted02 August 2011Published online11 September 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 light microscope is traditionally an instrument of substantial size and expense. Its miniaturized integration would enable many new applications based on mass-producible, tiny microscopes. Key prospective usages include brain imaging in behaving animals for relating cellular dynamics to animal behavior. Here we introduce a miniature (1.9 g) integrated fluorescence microscope made from mass-producible parts, including a semiconductor light source and sensor. This device enables high-speed cellular imaging across ~0.5 mm2 areas in active mice. This capability allowed concurrent tracking of Ca2+ spiking in >200 Purkinje neurons across nine cerebellar microzones. During mouse locomotion, individual microzones exhibited large-scale, synchronized Ca2+ spiking. This is a mesoscopic neural dynamic missed by prior techniques for studying the brain at other length scales. Overall, the integrated microscope is a potentially transformative technology that permits distribution to man! y animals and enables diverse usages, such as portable diagnostics or microscope arrays for large-scale screens. View full text Subject terms: * Imaging * Microscopy * Neuroscience Figures at a glance * Figure 1: Design and fabrication of an integrated fluorescence microscope. () Computer-assisted design of an integrated microscope, shown in cross-section. Blue and green arrows mark illumination and emission pathways, respectively. () Image of an assembled integrated microscope. Insets, filter cube holding dichroic mirror and excitation and emission filters (bottom left), PCB holding the CMOS camera chip (top right) and PCB holding the LED illumination source (bottom right). The wire bundles for LED and CMOS boards are visible. Scale bars, 5 mm (,). () Schematic of electronics for real-time image acquisition and control. The LED and CMOS sensor each have their own PCB. These boards are connected to a custom, external PCB via nine fine wires (two to the LED and seven to the camera) encased in a single polyvinyl chloride sheath. The external PCB interfaces with a computer via a USB (universal serial bus) adaptor board. PD, flash programming device; OSC, quartz crystal oscillator; I2C, two-wire interintegrated circuit serial communication interface; ! and FPGA, field-programmable gate array. * Figure 2: Cerebellar microcirculatory dynamics in freely behaving mice. () Microvasculature in cerebellar cortex of a freely behaving mouse, after intravascular injection of fluorescein-dextran dye. The image (300 × 300 pixels; 440 μW illumination power at the specimen plane) is the s.d. of a 10-s movie, a computation that highlights vasculature. () Map of erythrocyte flow speeds averaged over 30-s for vessels shown in . Scale bars, 50 μm (,). (,) Erythrocyte flow speeds () and vessel diameter changes (), for the four vessels marked in . Blue, red and white shading mark periods of mouse's movement in the cage, running on an exercise wheel, and rest or when the mouse barely moved, respectively. Three different records from the same mouse and specimen field are shown. * Figure 3: Nonuniform regulation of cerebellar capillaries during locomotion. (,) Erythrocyte speeds () and vessel diameters () compared between rest and locomotion. Each data point represents a vessel location in the vermis. Data above the diagonal indicate upregulation in speed or diameter during motor activity. Shaded blue and red areas demarcate 1 s.d. of measurement fluctuations calculated using the data below the diagonal. () Cumulative histogram of changes in flow speeds during walking in the cage or wheel running compared to rest. Histogram portions above and to the right of areas enclosed by colored dashed lines represent data for vessel locations lying above the color corresponding shaded areas in . Inset, mean ± s.e.m. changes compared to rest. *P = 4 × 10−5 (walking compared to running) and **P = 2 × 10−4 (running compared to rest) using Wilcoxon signed-rank tests. () Cumulative histogram of changes in vessel diameters during walking or running compared to rest. Histogram portions outside areas enclosed by colored dashed lines repre! sent measurements lying above the corresponding shaded areas in . Inset, mean ± s.e.m. changes. *P = 6 × 10−3 (walking and running), **P = 10−3 and ***P = 10−4 (compared to rest) using Wilcoxon signed-rank tests. Data in – are for n = 97 vessel locations from three mice. * Figure 4: Purkinje neurons' Ca2+ spiking dynamics during motor behavior. () Contours of 206 Purkinje neurons identified in a freely behaving mouse, superimposed on a time-averaged fluorescence image (480 × 480 pixels; 170–250 μW illumination at the specimen plane) of the cerebellar surface after injection of the Ca2+ indicator Oregon Green 488–BAPTA-1-AM. Each color indicates one of nine identified microzones. Filled contours mark neurons whose activity is shown in . Scale bar, 100 μm. () Relative changes in fluorescence (ΔF/F) from filled neurons in . Black dots mark detected Ca2+ spikes. () Spike-train correlation coefficients for pairs of neurons during resting, grooming and locomotion. Colored outlines indicate microzones identified by cluster analysis of the correlation coefficients and correspond to those in . * Figure 5: Cerebellar microzones exhibit large-scale, synchronized Ca2+ spiking during motor behavior. () Ca2+ spike (black dots) raster plots for neurons shown in Figure 4a. Colored shading indicates the mouse's behavior as labeled. Microzone rasters (colored circles) show Ca2+ spiking by >35% (open circles) or >50% (closed circles) of neurons identified in each microzone. () Expanded view of the locomotion and first resting periods shown in . Scale bars, 5 s (,). () Mean ± s.e.m. rates of individual neuronal spiking (top) and synchronized microzone activation (bottom: >35% cells synchronized, unfilled bars; >50% cells, solid bars). () Spike rates for individual cells (dots) and synchronized microzonal activation (>35% cells, large open circles; >50% cells, large solid circles) plotted for periods of grooming versus rest (yellow) or locomotion versus rest (green). () Cumulative histograms of percentages of cell's spikes occurring during synchronized activation (>35% activation, open circles; >50% activation, solid circles; locomotion, green; grooming, yellow; and resting, g! ray). Data in – are for n = 3 mice, 336 cells and 16 microzones. Author information * Abstract * Author information * Supplementary information Primary authors * These authors contributed equally to this work. * Kunal K Ghosh, * Laurie D Burns & * Eric D Cocker Affiliations * David Packard Electrical Engineering Building, Stanford University, Stanford, California, USA. * Kunal K Ghosh & * Abbas El Gamal * James H. Clark Center, Stanford University, Stanford, California, USA. * Kunal K Ghosh, * Laurie D Burns, * Eric D Cocker, * Axel Nimmerjahn, * Yaniv Ziv & * Mark J Schnitzer * Howard Hughes Medical Institute, Stanford University, Stanford, California, USA. * Mark J Schnitzer * CNC Program, Stanford University, Stanford, California, USA. * Mark J Schnitzer Contributions K.K.G. performed optical analysis, designed electronic circuits, assembled microscopy systems, wrote cell-counting software and performed the zebrafish, tuberculosis and cell-counting experiments. L.D.B. performed optical analysis, designed the optical pathway, assembled microscopy systems, performed cerebellum and hippocampal imaging studies, and analyzed the Ca2+-imaging data. E.D.C. designed the mechanical housing, heat dissipation, focusing mechanisms and illumination control circuitry, assembled microscopy systems, designed and built behavioral enclosures with video acquisition, and analyzed the behavioral and microcirculation data. A.N. developed the cerebellar preparation and performed cerebellar imaging studies. Y.Z. developed and performed the hippocampal imaging methodology. A.E.G. supervised the project. M.J.S. supervised the project and wrote the paper. All authors designed experiments and edited the paper. Competing financial interests K.K.G., E.D.C., A.E.G. and M.J.S. have equity in a company (Inscopix) pursuing imaging applications based on the integrated microscope. Corresponding author Correspondence to: * Mark J Schnitzer Author Details * Kunal K Ghosh Search for this author in: * NPG journals * PubMed * Google Scholar * Laurie D Burns Search for this author in: * NPG journals * PubMed * Google Scholar * Eric D Cocker Search for this author in: * NPG journals * PubMed * Google Scholar * Axel Nimmerjahn Search for this author in: * NPG journals * PubMed * Google Scholar * Yaniv Ziv Search for this author in: * NPG journals * PubMed * Google Scholar * Abbas El Gamal Search for this author in: * NPG journals * PubMed * Google Scholar * Mark J Schnitzer Contact Mark J Schnitzer Search for this author in: * NPG journals * PubMed * Google Scholar Supplementary information * Abstract * Author information * Supplementary information PDF files * Supplementary Text and Figures (4M) Supplementary Figures 1–2, Supplementary Table 1 and Supplementary Methods Movies * Supplementary Video 1 (7M) Mouse behavior and microcirculation in the cerebellar vermis recorded concurrently in a mouse with an integrated microscope mounted on the cranium. This movie presents the simultaneous video clips of mouse behavior and microcirculation in the vermis for two example behaviors. The first example shows the mouse walking about the behavioral arena. The second example shows the mouse running on an exercise wheel. Behavioral data (left) were recorded at 30 Hz with an overhead camera and infrared illumination. Microcirculation (right) was recorded using the integrated microscope at 100 Hz after an intravenous injection of FITC-dextran. This fluorescent dye brightly labels the blood plasma, allowing erythrocytes to be seen in dark relief. Individual erythrocytes are apparent flowing through the capillaries. Brain motion artifacts are so minimal as to be virtually undetectable. Scale bar, 100 μm. Additional data
• Firefly luciferase mutants as sensors of proteome stress
  - Nat Methods 8(10):879-884 (2011)
  Nature Methods | Article Firefly luciferase mutants as sensors of proteome stress * Rajat Gupta1 * Prasad Kasturi1 * Andreas Bracher1 * Christian Loew1 * Min Zheng1 * Adriana Villella2 * Dan Garza2 * F Ulrich Hartl1, 3 * Swasti Raychaudhuri1 * Affiliations * Contributions * Corresponding authorsJournal name:Nature MethodsVolume: 8,Pages:879–884Year published:(2011)DOI:doi:10.1038/nmeth.1697Received02 March 2011Accepted26 July 2011Published online04 September 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 Maintenance of cellular protein homeostasis (proteostasis) depends on a complex network of molecular chaperones, proteases and other regulatory factors. Proteostasis deficiency develops during normal aging and predisposes individuals for many diseases, including neurodegenerative disorders. Here we describe sensor proteins for the comparative measurement of proteostasis capacity in different cell types and model organisms. These sensors are increasingly structurally destabilized versions of firefly luciferase. Imbalances in proteostasis manifest as changes in sensor solubility and luminescence activity. We used EGFP-tagged constructs to monitor the aggregation state of the sensors and the ability of cells to solubilize or degrade the aggregated proteins. A set of three sensor proteins serves as a convenient toolkit to assess the proteostasis status in a wide range of experimental systems, including cell and organism models of stress, neurodegenerative disease and aging. View full text Subject terms: * Sensors and Probes * Cell Biology * Systems Biology Figures at a glance * Figure 1: Thermal stability of luciferase sensor proteins. () Fluc-mediated enzymatic reaction and Fluc crystal structure (Protein Data Bank: 2d1r)26. Highlighted are N-terminal domain (blue) and C-terminal domain (gold) as well as mutated residues (pink) and their hydrogen bond interactors (orange; Asp107 and Tyr109, Glu18 and Gly20, and Thr43 and Asn50). Bound enzyme products AMP and oxyluciferin are shown in light blue and light green van-der-Waals envelopes, respectively. Generated mutations are listed, with those discussed in the paper shown in red. (–) Temperature-dependent Fluc activity of Fluc (), FlucSM () and FlucDM () measured at the indicated times and expressed as a percentage of the activity measured immediately after translation (set to 100%). Proteins were translated in reticulocyte lysate (90 min at 30 °C), followed by inhibition of translation and incubation at 20–37 °C. Error bars, s.d.; n = 3. () Specific luminescence activity of Fluc, FlucSM and FlucDM immediately after translation and after 2 h of incubat! ion at 30 °C (bottom). Amounts of Fluc variants were determined by immunoblotting of total reticulocyte lysate fractions (top) compared to GAPDH control and densitometry. Specific activity of wild-type Fluc was set to 100%. Error bars, s.d.; n = 3. * Figure 2: Chaperone dependence and thermal stability of sensor proteins in HeLa cells. () To test dependence of Fluc activity on Hsc70, Fluc, FlucSM and FlucDM were expressed for 48 h in cells treated with control endoribonuclease-prepared small interfering (esi)RNA to EGFP or esiRNA to HSPA8 (which encodes Hsc70). Specific activities in soluble extracts are shown relative to that of wild-type Fluc in control cells (set to 100%). Error bars, s.d.; n = 3. () Representative fluorescence micrographs of HeLa cells expressing Fluc-EGFP, FlucSM-EGFP or FlucDM-EGFP subjected to heat stress for 2 h at 43 °C or maintained at 37 °C (control), followed by recovery for 2 h at 37 °C with or without cycloheximide (CHX). EGFP fluorescence (white) was monitored (aggregates are marked by arrowheads). Nuclei were stained with DAPI (blue). Scale bars, 10 μm. () Cell-fractionation experiment showing total cell extract, detergent-soluble and insoluble fraction of FlucDM-EGFP–expressing HeLa cells treated as in . FlucDM-EGFP was detected by immunoblotting with an antibody to ! GFP. () Specific Fluc activity of EGFP-tagged sensor proteins upon heat stress and recovery. HeLa cells expressing Fluc-EGFP variants were treated as in . Specific activities in control cells maintained at 37 °C were set to 100%. Error bars, s.d.; n = 3. * Figure 3: Effect of Fluc-based sensors on the cytosolic stress response. () HeLa cells were transfected with the stress-responsive HSPA1A-Rluc reporter (top) along with the vectors encoding Fluc-EGFP variants or vector-only control. Rluc activity was measured either without stress or after subjecting the cells to heat stress for 2 h at 43 °C and recovery for 2 h at 37 °C. Error bars, s.d.; n = 3. RLU, relative luminiscence unit. () Amounts of stress-responsive Rluc and Fluc-EGFP variants in HeLa cells treated as in , detected by immunoblotting. GAPDH was used as a loading control. Asterisk indicates a nonspecific band. * Figure 4: Fluc-based sensors report on proteostasis impairment by small-molecule inhibitors or neurodegenerative disease protein. () HeLa cells were transfected with vector encoding Fluc-EGFP, FlucSM-EGFP or FlucDM-EGFP for 36 h, subsequently incubated with 0.1% DMSO, 0.5 μM 17-AAG or 5 μM MG132 (both in DMSO) for 8 h and Fluc activities were measured (DMSO control values were set to 100%) (left). Error bars, s.d.; n = 3. Representative fluorescence micrographs (right) show the distribution of Fluc-EGFP, FlucSM-EGFP and FlucDM-EGFP in cells treated as above. EGFP fluorescence is shown in white. Nuclei were stained with DAPI (blue). White arrowheads indicate aggregates. () Fluorescence micrographs of HEK293T cells 48 h after transfection with vectors encoding Fluc-EGFP variants and mCherry-tagged Htt exon 1 constructs encoding proteins with 20Q or 97Q. Nuclei were stained with DAPI. All scale bars, 10 μm. * Figure 5: Fluc-based sensors report on acute proteome stress during heat shock in C. elegans. (,) Representative fluorescence micrographs of young-adult worms (day 1) expressing Fluc-EGFP, FlucSM-EGFP or FlucDM-EGFP in body-wall muscle () or neuronal cells () under normal growth conditions at 20 °C, after heat stress for 1 h at 33 °C and after recovery at 20 °C for 6 h and 24 h (muscle-specific expression) or 6 h (neuron specific expression), as indicated. Scale bars, 10 μm. Insets in show digitally magnified central regions of the respective images. Bar graphs show relative mRNA amounts of FlucDM-EGFP, muscle-specific unc-54 () or neuron-specific unc-119 () determined by RT-PCR. Error bars, s.d.; n = 3. * Figure 6: Fluc-based sensors report on proteostasis decline during aging in C. elegans. (,) Fluorescence micrographs of worms expressing Fluc-EGFP, FlucSM-EGFP or FlucDM-EGFP in muscle () or neurons () imaged on indicated days. Scale bars, 10 μm. Insets show digitally magnified central region of the respective image. () FlucDM-EGFP–expressing worms containing aggregates on indicated days. Error bars, s.d.; n = 3. Forty worms were counted in each experiment. *P < 0.05 (Student's t-test). Author information * Abstract * Author information * Supplementary information Affiliations * Department of Cellular Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany. * Rajat Gupta, * Prasad Kasturi, * Andreas Bracher, * Christian Loew, * Min Zheng, * F Ulrich Hartl & * Swasti Raychaudhuri * Proteostasis Therapeutics Inc., Cambridge, Massachusetts, USA. * Adriana Villella & * Dan Garza * Center for Integrated Protein Science, München, Germany. * F Ulrich Hartl Contributions S.R. and F.U.H. conceived the idea and developed the method. A.B. designed Fluc mutants. R.G., C.L. and S.R. performed molecular biology and cell biology experiments. P.K. and M.Z. performed C. elegans experiments. A.V. and D.G. performed D. melanogaster S2 cell experiments. R.G. and S.R. analyzed results. S.R. and F.U.H. interpreted results and wrote the manuscript with assistance from D.G. Competing financial interests F.U.H is a paid consultant of Proteostasis Therapeutics Inc. A.V and D.G are employees of Proteostasis Therapeutics Inc. Corresponding authors Correspondence to: * F Ulrich Hartl or * Swasti Raychaudhuri Author Details * Rajat Gupta Search for this author in: * NPG journals * PubMed * Google Scholar * Prasad Kasturi Search for this author in: * NPG journals * PubMed * Google Scholar * Andreas Bracher Search for this author in: * NPG journals * PubMed * Google Scholar * Christian Loew Search for this author in: * NPG journals * PubMed * Google Scholar * Min Zheng Search for this author in: * NPG journals * PubMed * Google Scholar * Adriana Villella Search for this author in: * NPG journals * PubMed * Google Scholar * Dan Garza Search for this author in: * NPG journals * PubMed * Google Scholar * F Ulrich Hartl Contact F Ulrich Hartl Search for this author in: * NPG journals * PubMed * Google Scholar * Swasti Raychaudhuri Contact Swasti Raychaudhuri 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 1–8, Supplementary Tables 1–3, Supplementary Note 1 Additional data