Bacterial Fitness Landscapes Stratify Based on Proteome Allocation Associated with Discrete Aero-types
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ABSTRACT:
PROVIDER: PRJNA689602 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13350100_1.fastq.gz | Fastqsanger.gz | |||
| SRR13350100_2.fastq.gz | Fastqsanger.gz | |||
| SRR13350101_1.fastq.gz | Fastqsanger.gz | |||
| SRR13350101_2.fastq.gz | Fastqsanger.gz | |||
| SRR13350102_1.fastq.gz | Fastqsanger.gz |
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Project description:The fitness landscape is a concept commonly used to describe evolution towards optimal phenotypes. It can be reduced to mechanistic detail using genome-scale models (GEMs) from systems biology. We use recently developed GEMs of Metabolism and protein Expression (ME-models) to study the distribution of Escherichia coli phenotypes on the rate-yield plane. We found that the measured phenotypes distribute non-uniformly to form a highly stratified fitness landscape. Systems analysis of the ME-model simulations suggest that this stratification results from discrete ATP generation strategies. Accordingly, we define "aero-types", a phenotypic trait that characterizes how a balanced proteome can achieve a given growth rate by modulating 1) the relative utilization of oxidative phosphorylation, glycolysis, and fermentation pathways; and 2) the differential employment of electron-transport-chain enzymes. This global, quantitative, and mechanistic systems biology interpretation of fitness landscape formed upon proteome allocation offers a fundamental understanding of bacterial physiology and evolution dynamics.
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