The E. coli molecular phenotype under different growth conditions.

Autor:	Caglar MU; Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA.; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA., Houser JR; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA., Barnhart CS; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA., Boutz DR; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA., Carroll SM; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA.; Axcella Health Inc, Cambridge, Massachusetts, USA., Dasgupta A; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Women's Infectious Diseases Research, Division of Infectious Diseases, Department of Internal Medicine, Washington University School of Medicine, St. Louis, Missouri, USA., Lenoir WF; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA., Smith BL; Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA.; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA., Sridhara V; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA.; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA., Sydykova DK; Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Computational Biology and Bioinformatics, The University of Texas at Austin, Austin, Texas, USA.; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA., Vander Wood D; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA., Marx CJ; Department of Biological Sciences, University of Idaho, Moscow, Idaho, USA.; Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho, USA., Marcotte EM; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA., Barrick JE; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA., Wilke CO; Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, Texas, USA.; Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas, USA.; Department of Molecular Biosciences, The University of Texas at Austin, Austin, Texas, USA.
Jazyk:	angličtina
Zdroj:	Scientific reports [Sci Rep] 2017 Apr 18; Vol. 7, pp. 45303. Date of Electronic Publication: 2017 Apr 18.
DOI:	10.1038/srep45303
Abstrakt:	Modern systems biology requires extensive, carefully curated measurements of cellular components in response to different environmental conditions. While high-throughput methods have made transcriptomics and proteomics datasets widely accessible and relatively economical to generate, systematic measurements of both mRNA and protein abundances under a wide range of different conditions are still relatively rare. Here we present a detailed, genome-wide transcriptomics and proteomics dataset of E. coli grown under 34 different conditions. Additionally, we provide measurements of doubling times and in-vivo metabolic fluxes through the central carbon metabolism. We manipulate concentrations of sodium and magnesium in the growth media, and we consider four different carbon sources glucose, gluconate, lactate, and glycerol. Moreover, samples are taken both in exponential and stationary phase, and we include two extensive time-courses, with multiple samples taken between 3 hours and 2 weeks. We find that exponential-phase samples systematically differ from stationary-phase samples, in particular at the level of mRNA. Regulatory responses to different carbon sources or salt stresses are more moderate, but we find numerous differentially expressed genes for growth on gluconate and under salt and magnesium stress. Our data set provides a rich resource for future computational modeling of E. coli gene regulation, transcription, and translation.
Databáze:	MEDLINE
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