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Predictive evolution of metabolic phenotypes using model‐designed environments
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Journal Article
Predictive evolution of metabolic phenotypes using model‐designed environments
2022
Overview
Adaptive evolution under controlled laboratory conditions has been highly effective in selecting organisms with beneficial phenotypes such as stress tolerance. The evolution route is particularly attractive when the organisms are either difficult to engineer or the genetic basis of the phenotype is complex. However, many desired traits, like metabolite secretion, have been inaccessible to adaptive selection due to their trade‐off with cell growth. Here, we utilize genome‐scale metabolic models to design nutrient environments for selecting lineages with enhanced metabolite secretion. To overcome the growth‐secretion trade‐off, we identify environments wherein growth becomes correlated with a secondary trait termed tacking trait. The latter is selected to be coupled with the desired trait in the application environment where the trait manifestation is required. Thus, adaptive evolution in the model‐designed selection environment and subsequent return to the application environment is predicted to enhance the desired trait. We experimentally validate this strategy by evolving
Saccharomyces cerevisiae
for increased secretion of aroma compounds, and confirm the predicted flux‐rerouting using genomic, transcriptomic, and proteomic analyses. Overall, model‐designed selection environments open new opportunities for predictive evolution.
Synopsis
EvolveX, a new algorithm enabling model‐guided design of chemical environments for targeted adaptive evolution, is applied to evolve a wine yeast strain for increased aroma secretion.
EvolveX predicts environment‐dependence of trait‐fitness correlations using genome‐scale metabolic models.
Multi‐omics analysis shows agreement with the model‐predicted metabolic changes.
EvolveX enables devising adaptive evolution strategies for improving traits uncorrelated with cell fitness.
Graphical Abstract
EvolveX, a new algorithm enabling model‐guided design of chemical environments for targeted adaptive evolution, is applied to evolve a wine yeast strain for increased aroma secretion.
Publisher
Nature Publishing Group UK,EMBO Press,John Wiley and Sons Inc,Springer Nature
Subject
