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      The quantitative proteome of a human cell line

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          Abstract

          The generation of mathematical models of biological processes, the simulation of these processes under different conditions, and the comparison and integration of multiple data sets are explicit goals of systems biology that require the knowledge of the absolute quantity of the system's components. To date, systematic estimates of cellular protein concentrations have been exceptionally scarce. Here, we provide a quantitative description of the proteome of a commonly used human cell line in two functional states, interphase and mitosis. We show that these human cultured cells express at least ∼10 000 proteins and that the quantified proteins span a concentration range of seven orders of magnitude up to 20 000 000 copies per cell. We discuss how protein abundance is linked to function and evolution.

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          Most cited references29

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

            We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.
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              Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes.

              Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.
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                Author and article information

                Journal
                Mol Syst Biol
                Mol. Syst. Biol
                Molecular Systems Biology
                Nature Publishing Group
                1744-4292
                2011
                08 November 2011
                08 November 2011
                : 7
                : 549
                Affiliations
                [1 ]European Molecular Biology Laboratory , Heidelberg, Germany
                [2 ]Biozentrum, University of Basel , Basel, Switzerland
                [3 ]Department of Immunotechnology, BMC , Lund, Sweden
                [4 ]Biognosys AG , Schlieren, Switzerland
                [5 ]Department of Computer Science, ETH Zurich , Zurich, Switzerland
                [6 ]Department of Biology, Institute of Molecular Systems Biology, ETH Zurich , Switzerland
                [7 ]Competence Center for Systems Physiology and Metabolic Diseases , Zurich, Switzerland
                [8 ]Department of Science, University of Zurich , Zurich, Switzerland
                Author notes
                [a ]Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Wolfgang-Pauli-Strasse 16, Zurich 8093, Switzerland. Tel.: +41 44 633 1071; Fax: +41 44 633 1051; aebersold@ 123456imsb.biol.ethz.ch
                [*]

                These authors contributed equally to this work

                Article
                msb201182
                10.1038/msb.2011.82
                3261713
                22068332
                620c9241-7d8b-4a5a-b390-1d4647684697
                Copyright © 2011, EMBO and Macmillan Publishers Limited

                This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial Share Alike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.

                History
                : 15 August 2011
                : 29 September 2011
                Categories
                Report

                Quantitative & Systems biology
                mass spectrometry,protein abundance,proteomics
                Quantitative & Systems biology
                mass spectrometry, protein abundance, proteomics

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