Proteomics

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Proteome resource allocation in bacteria


ABSTRACT: A central aim of cell biology is 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.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Escherichia Coli

SUBMITTER: Sheng Hui  

LAB HEAD: Terence Hwa

PROVIDER: PXD001467 | Pride | 2015-02-12

REPOSITORIES: Pride

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Publications

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

Hui Sheng S   Silverman Josh M JM   Chen Stephen S SS   Erickson David W DW   Basan Markus M   Wang Jilong J   Hwa Terence T   Williamson James R JR  

Molecular systems biology 20150212 1


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 grow  ...[more]

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