Literature DB >> 23824091

Escherichia coli achieves faster growth by increasing catalytic and translation rates of proteins.

Kaspar Valgepea1, Kaarel Adamberg, Andrus Seiman, Raivo Vilu.   

Abstract

Regulation levels of the gene expression cascade controlling protein levels and metabolic fluxes for cells to achieve faster growth have not been elaborated in acceptable detail. Furthermore, there is need for specific growth rate (μ) dependent absolute quantitative transcriptome and proteome data to understand the molecular relationships for enabling cells to modify μ. We address these questions, for the first time, by presenting regulatory strategies for more efficient metabolism of Escherichia coli at higher μ by statistical covariance analysis of genome-wide intracellular mRNA and protein concentrations coupled to metabolic flux analysis in the steady state range of μ = 0.11-0.49 h(-1). Our analyses show dominating post-transcriptional control of protein abundances and post-translational control of flux rates. On average, E. coli achieved five-times faster growth through 3.7-fold increase of apparent catalytic rates of enzymes (kapp) and 2.5-fold increased translation rates, demonstrating the relevance of post-translational regulation for increasing flux throughput. Interestingly, pathways carrying the highest flux showed both high protein abundance and kapp values. Furthermore, co-regulation analysis of enzymatic capacities revealed tightly coupled regulatory dependencies of protein synthesis and RNA precursor synthesis, substrate utilization, biosynthetic and energy generation pathways carrying the highest flux. We also observed metabolic pathway and COG specific protein and metabolic flux control levels, protein expression costs and genome-wide principles for translation efficiency and transcription unit polarity. This work contributes to the much needed quantitative understanding of coordinated gene expression regulation and metabolic flux control. Our findings will also advance modeling and metabolic engineering of industrial strains.

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Year:  2013        PMID: 23824091     DOI: 10.1039/c3mb70119k

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


  47 in total

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Review 4.  Systems biology perspectives on minimal and simpler cells.

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5.  Automatic construction of metabolic models with enzyme constraints.

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6.  Mass spectrometry-based workflow for accurate quantification of Escherichia coli enzymes: how proteomics can play a key role in metabolic engineering.

Authors:  Mathieu Trauchessec; Michel Jaquinod; Aline Bonvalot; Virginie Brun; Christophe Bruley; Delphine Ropers; Hidde de Jong; Jérôme Garin; Gwenaëlle Bestel-Corre; Myriam Ferro
Journal:  Mol Cell Proteomics       Date:  2014-01-29       Impact factor: 5.911

7.  Optimal Allocation of Bacterial Protein Resources under Nonlethal Protein Maturation Stress.

Authors:  Qing Zhang; Rui Li; Junbai Li; Hualin Shi
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8.  Systems-level analysis of mechanisms regulating yeast metabolic flux.

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Review 9.  Computing the functional proteome: recent progress and future prospects for genome-scale models.

Authors:  Edward J O'Brien; Bernhard O Palsson
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10.  Ribosome biogenesis in replicating cells: Integration of experiment and theory.

Authors:  Tyler M Earnest; John A Cole; Joseph R Peterson; Michael J Hallock; Thomas E Kuhlman; Zaida Luthey-Schulten
Journal:  Biopolymers       Date:  2016-10       Impact factor: 2.505

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