Literature DB >> 25712329

Proteome reallocation in Escherichia coli with increasing specific growth rate.

Karl Peebo1, Kaspar Valgepea, Andres Maser, Ranno Nahku, Kaarel Adamberg, Raivo Vilu.   

Abstract

Cells usually respond to changing growth conditions with a change in the specific growth rate (μ) and adjustment of their proteome to adapt and maintain metabolic efficiency. Description of the principles behind proteome resource allocation is important for understanding metabolic regulation in response to changing μ. Thus, we analysed the proteome resource allocation dynamics of Escherichia coli into different metabolic processes in response to changing μ. E. coli was grown on minimal and defined rich media in steady state continuous cultures at different μ and characterised combining two LC-MS/MS-based proteomics methods: stable isotope labelling by amino acids in cell culture (SILAC) and intensity based label-free absolute quantification. We detected slowly growing cells investing more proteome resources in energy generation and carbohydrate transport and metabolism whereas for achieving faster growth cells needed to devote most resources to translation and processes closely related to the protein synthesis pipeline. Furthermore, down-regulation of energy generation and carbohydrate metabolism proteins with faster growth displayed very similar expression dynamics with the global transcriptional regulator CRP (cyclic AMP receptor protein), pointing to a dominant protein resource allocating role of this protein. Our data also suggest that acetate overflow may be the result of global proteome resource optimisation as cells saved proteome resources by switching from fully respiratory to respiro-fermentative growth. The presented results give a quantitative overview of how E. coli adjusts its proteome to achieve faster growth and in future could contribute to the design of more efficient cell factories through proteome optimisation.

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Year:  2015        PMID: 25712329     DOI: 10.1039/c4mb00721b

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  37 in total

1.  Pareto Optimality Explanation of the Glycolytic Alternatives in Nature.

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3.  Reciprocal Regulation of l-Arabinose and d-Xylose Metabolism in Escherichia coli.

Authors:  Santosh Koirala; Xiaoyi Wang; Christopher V Rao
Journal:  J Bacteriol       Date:  2015-11-02       Impact factor: 3.490

4.  Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitro kcat measurements.

Authors:  Dan Davidi; Elad Noor; Wolfram Liebermeister; Arren Bar-Even; Avi Flamholz; Katja Tummler; Uri Barenholz; Miki Goldenfeld; Tomer Shlomi; Ron Milo
Journal:  Proc Natl Acad Sci U S A       Date:  2016-03-07       Impact factor: 11.205

5.  Protein allocation and utilization in the versatile chemolithoautotroph Cupriavidus necator.

Authors:  Michael Jahn; Nick Crang; Markus Janasch; Andreas Hober; Björn Forsström; Kyle Kimler; Alexander Mattausch; Qi Chen; Johannes Asplund-Samuelsson; Elton Paul Hudson
Journal:  Elife       Date:  2021-11-01       Impact factor: 8.140

6.  Fundamental limits on the rate of bacterial growth and their influence on proteomic composition.

Authors:  Nathan M Belliveau; Griffin Chure; Christina L Hueschen; Hernan G Garcia; Jane Kondev; Daniel S Fisher; Julie A Theriot; Rob Phillips
Journal:  Cell Syst       Date:  2021-07-01       Impact factor: 11.091

7.  Effect of amino acids on transcription and translation of key genes in E. coli K and B grown at a steady state in minimal medium.

Authors:  Antonino Baez; Amit Kumar; Ashish K Sharma; Eric D Anderson; Joseph Shiloach
Journal:  N Biotechnol       Date:  2018-10-29       Impact factor: 6.490

8.  Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum.

Authors:  Kaspar Valgepea; Gert Talbo; Nobuaki Takemori; Ayako Takemori; Christina Ludwig; Vishnuvardhan Mahamkali; Alexander P Mueller; Ryan Tappel; Michael Köpke; Séan Dennis Simpson; Lars Keld Nielsen; Esteban Marcellin
Journal:  mSystems       Date:  2022-04-06       Impact factor: 7.324

9.  A Minimalistic Resource Allocation Model to Explain Ubiquitous Increase in Protein Expression with Growth Rate.

Authors:  Uri Barenholz; Leeat Keren; Eran Segal; Ron Milo
Journal:  PLoS One       Date:  2016-04-13       Impact factor: 3.240

10.  Overflow metabolism in Escherichia coli results from efficient proteome allocation.

Authors:  Markus Basan; Sheng Hui; Hiroyuki Okano; Zhongge Zhang; Yang Shen; James R Williamson; Terence Hwa
Journal:  Nature       Date:  2015-12-03       Impact factor: 49.962

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