Journal
LIFE SCIENCE ALLIANCE
Volume 7, Issue 1, Pages -Publisher
LIFE SCIENCE ALLIANCE LLC
DOI: 10.26508/lsa.202302215
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In order to design strains that can efficiently function in complex industrial environments, it is important to consider their robustness, which is the stability of their performance when faced with disturbances. This study cultivated 24 Saccharomyces cerevisiae strains under conditions simulating perturbations encountered in lignocellulosic bioethanol production, and assessed the performance and robustness of multiple phenotypes simultaneously. The results demonstrated a trade-off between performance and robustness, confirming previous findings that showed a negative correlation between ethanol yield, biomass yield, and cell dry weight. The specific growth rate performance positively correlated with robustness, likely due to evolutionary selection for robust, fast-growing cells. The Ethanol Red strain exhibited both high performance and robustness, making it a good candidate for bioproduction in perturbation-prone environments.
To design strains that can function efficiently in complex industrial settings, it is crucial to consider their robustness, that is, the stability of their performance when faced with perturbations. In the present study, we cultivated 24 Saccharomyces cerevisiae strains under conditions that simulated perturbations encountered during lignocellulosic bioethanol production, and assessed the performance and robustness of multiple phenotypes simultaneously. The observed negative correlations confirmed a trade-off between performance and robustness of ethanol yield, biomass yield, and cell dry weight. Conversely, the specific growth rate performance positively correlated with the robustness, presumably because of evolutionary selection for robust, fast-growing cells. The Ethanol Red strain exhibited both high performance and robustness, making it a good candidate for bioproduction in the tested perturbation space. Our results experimentally map the robustness-performance trade-offs, previously demonstrated mainly by single-phenotype and computational studies.
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