Escherichia coli achieves faster growth by increasing catalytic and translation rates of proteins
- 10 June 2013
- journal article
- research article
- Published by Royal Society of Chemistry (RSC) in Molecular BioSystems
- Vol. 9 (9), 2344-2358
- https://doi.org/10.1039/c3mb70119k
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.Keywords
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