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Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria

A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underly...

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Autores principales: Hui, Sheng, Silverman, Josh M, Chen, Stephen S, Erickson, David W, Basan, Markus, Wang, Jilong, Hwa, Terence, Williamson, James R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BlackWell Publishing Ltd 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4358657/
https://www.ncbi.nlm.nih.gov/pubmed/25678603
http://dx.doi.org/10.15252/msb.20145697
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author Hui, Sheng
Silverman, Josh M
Chen, Stephen S
Erickson, David W
Basan, Markus
Wang, Jilong
Hwa, Terence
Williamson, James R
author_facet Hui, Sheng
Silverman, Josh M
Chen, Stephen S
Erickson, David W
Basan, Markus
Wang, Jilong
Hwa, Terence
Williamson, James R
author_sort Hui, Sheng
collection PubMed
description A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies.
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spelling pubmed-43586572015-03-20 Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria Hui, Sheng Silverman, Josh M Chen, Stephen S Erickson, David W Basan, Markus Wang, Jilong Hwa, Terence Williamson, James R Mol Syst Biol Articles A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse-grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate-dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies. BlackWell Publishing Ltd 2015-02-12 /pmc/articles/PMC4358657/ /pubmed/25678603 http://dx.doi.org/10.15252/msb.20145697 Text en © 2015 The Authors. Published under the terms of the CC BY 4.0 license http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Hui, Sheng
Silverman, Josh M
Chen, Stephen S
Erickson, David W
Basan, Markus
Wang, Jilong
Hwa, Terence
Williamson, James R
Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
title Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
title_full Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
title_fullStr Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
title_full_unstemmed Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
title_short Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
title_sort quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4358657/
https://www.ncbi.nlm.nih.gov/pubmed/25678603
http://dx.doi.org/10.15252/msb.20145697
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