| Literature DB >> 33465077 |
Ke Chen1, Amitesh Anand1, Connor Olson1, Troy E Sandberg1, Ye Gao2, Nathan Mih1, Bernhard O Palsson1,2,3.
Abstract
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.Entities:
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Year: 2021 PMID: 33465077 PMCID: PMC7846111 DOI: 10.1371/journal.pcbi.1008596
Source DB: PubMed Journal: PLoS Comput Biol ISSN: 1553-734X Impact factor: 4.475