Literature DB >> 30122293

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

Qing Zhang1, Rui Li2, Junbai Li3, Hualin Shi4.   

Abstract

Under different environmental stresses, bacteria optimize the allocation of cellular resources through a variety of mechanisms. Recently, researchers have used phenomenological models to quantitatively characterize the allocation of bacterial protein resources under metabolic and translational limitations. Some stresses interfere with protein maturation, thereby enhancing the expression of chaperones and proteases. However, the reallocation of protein resources caused by such environmental stresses has not been modeled quantitatively. Here, we developed a dynamic model of coarse-grained protein resource fluxes based on a self-replicator that includes protein maturation and degradation. Through flux balance analysis, it produces a constrained optimization problem that can be solved analytically. Accordingly, we predicted protein allocation fractions as functions of growth rate under different limitations, which are basically in line with empirical data. We cultured Escherichia coli in media containing different concentrations of chloramphenicol, acetic acid, and paraquat and measured the functional relationship between the expression level of β-galactosidase driven by a constitutive promoter and the bacterial growth rate, respectively. Taking into account the possible mode of stress limitation on the fluxes, our model reproduces this experimentally measured relationship. In addition, our model is in good agreement with the experimental relationship between growth rate and proteome fraction of unnecessary protein in E. coli, considering the unoptimized upregulation of chaperones with useless protein overexpression. The results provide a more systematic view of bacterial stress adaptation that may help in designing for bioengineering or medical interventions.
Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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Year:  2018        PMID: 30122293      PMCID: PMC6127457          DOI: 10.1016/j.bpj.2018.07.021

Source DB:  PubMed          Journal:  Biophys J        ISSN: 0006-3495            Impact factor:   4.033


  61 in total

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Journal:  Biotechnol Bioeng       Date:  1990-03-25       Impact factor: 4.530

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

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Journal:  PLoS Biol       Date:  2021-05-26       Impact factor: 8.029

  1 in total

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