Bacterial adaptation: Macromolecular biosynthesis during diauxic growth of Escherichia coli

Madar, Raya

doi:10.1016/0378-1097(83)90078-2

Cited by 1 publication

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“…To tackle this question, we next followed gene expression during the course of the shift. Translation rates are known to severely fall with growth arrest upon glucose depletion (Madar & Zaritsky, 1983 ; Erickson et al , 2017 ). Given these low rates, the high stability of proteins synthesized before the glucose runout, and the technical challenges to detect low levels of novel proteins, it is difficult to analyze the proteome response in high resolution.…”

Section: Resultsmentioning

confidence: 99%

Suboptimal resource allocation in changing environments constrains response and growth in bacteria

Balakrishnan

Silva

Hwa

et al. 2021

Molecular Systems Biology

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To respond to fluctuating conditions, microbes typically need to synthesize novel proteins. As this synthesis relies on sufficient biosynthetic precursors, microbes must devise effective response strategies to manage depleting precursors. To better understand these strategies, we investigate the active response of Escherichia coli to changes in nutrient conditions, connecting transient gene expression to growth phenotypes. By synthetically modifying gene expression during changing conditions, we show how the competition by genes for the limited protein synthesis capacity constrains cellular response. Despite this constraint cells substantially express genes that are not required, trapping them in states where precursor levels are low and the genes needed to replenish the precursors are outcompeted. Contrary to common modeling assumptions, our findings highlight that cells do not optimize growth under changing environments but rather exhibit hardwired response strategies that may have evolved to promote fitness in their native environment. The constraint and the suboptimality of the cellular response uncovered provide a conceptual framework relevant for many research applications, from the prediction of evolution to the improvement of gene circuits in biotechnology.

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Section: Resultsmentioning

confidence: 99%