Global Rebalancing of Cellular Resources by Pleiotropic Point Mutations Illustrates a Multi-scale Mechanism of Adaptive Evolution

Abstract

Summary Pleiotropic regulatory mutations affect diverse cellular processes, posing a challenge to our understanding of genotype-phenotype relationships across multiple biological scales. Adaptive Laboratory Evolution (ALE) allows for such mutations to be found and characterized in the context of clear selection pressures. Here, several ALE-selected single-mutation variants in Escherichia coli's RNA polymerase (RNAP) are detailed using an integrated multi-scale experimental and computational approach. While these mutations increase cellular growth rates in steady environments, they reduce tolerance to stress and environmental fluctuations. We detail structural changes in the RNAP that rewire the transcriptional machinery to rebalance proteome and energy allocation towards growth and away from several hedging and stress functions. We find that while these mutations occur in diverse locations in the RNAP, they share a common adaptive mechanism. In turn, these findings highlight the resource allocation tradeoffs organisms face and suggest how the structure of the regulatory network enhances evolvability.

Principles of proteome allocation are revealed using proteomic data and genome-scale models

“…Using genome-scale models, we show how such proteomics resources can be used to reveal principles underlying proteome allocation. ME models compute growth optimal proteomes consistent with laboratory evolved strains accurately14, but are unable to compute processes that are not directly related to growth (e.g., stress response, preparation for unfavorable conditions)15. In anticipation of environmental change, generalist (wild-type) E. coli allocate a fraction of the proteome to non-growth related functions.…”

“…In anticipation of environmental change, generalist (wild-type) E. coli allocate a fraction of the proteome to non-growth related functions. Collectively, such allocation can be viewed as “hedging” against unknown enviromental challenges14, reflecting the evolutionary history of the organism and its successful survival strategy. Recent studies have estimated that 20% of the expressed proteome confers no direct fitness benefit15.…”

Laboratory Evolution to Alternating Substrate Environments Yields Distinct Phenotypic and Genetic Adaptive Strategies

“…Many of the repeatedly mutated genes are seen frequently in other evolution experiments, with the fitness benefit already either known or inferred-pyrE-rph mutations for improved minimal medium growth (23), pykF and hns-tdk mutations for glucose growth (24,25), glpK mutations for glycerol growth (26), and rpoB and rpoC mutations to serve as large-scale transcriptional rewirings (27,28). In addition to these oft seen mutational targets, several genes stood out as indicators of differing adaptive strategies between dynamic and static conditions.…”

“…Similarly, mutations in ptsP (3 unique dynamic mutations, with 2 in one lineage), relA (3 unique dynamic mutations), and sapB (2 unique dynamic mutations) appeared to be dynamically favored, while mutations in rho (4 unique static mutations) and xylR (2 unique static mutations) appeared statically favored. Although, as a whole, these data indicate differing adaptive strategies for dynamic and static growth environments, the explicit biochemical mechanisms through which such mutations enable fitness improvements remain unclear without detailed follow-up analyses (26,28). Physiological analysis of evolved strains.…”

Mathematical modelling of microbes: metabolism, gene expression and growth

“…Moreover, in addition to contributing to the beauty of living systems [132], the molecular details of regulatory mechanisms may also be important for matching the model with quantitative data and for understanding evolutionary trajectories of microorganisms. As an illustration of the latter point, a recent study attributed the increased growth of an E. coli strain in minimal media observed in adaptive laboratory evolution experiments to specific point mutations in the b subunit of RNA polymerase [133].…”