ArticleMetabolic engineering communications2025
Model-guided chemical environment and metabolic network design to couple pathways with cell fitness.
Article in Metabolic engineering communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Heterologous compound production is a complex trait since the native metabolic fluxes supplying the precursors, redox power, and energy are under multilevel cellular regulation. Improving complex traits using targeted engineering needs combinatorially charting the complex genetic underpinnings. While this is laborious, adaptive laboratory evolution (ALE) has been used to improve many traits of microbial strains that are of application relevance such as tolerance of harsh conditions and nutrient utilization. However, in contrast to such traits, heterologous production can seldom be intuitively coupled with cellular fitness. Here, a novel method EvolveXGA was developed for genome-scale metabolic model guided design of strategies combining chemical environments and genetic engineering of the metabolic network to allow ALE of desired traits. Adaptive evolution of traits occurs when the co-variance between the traits and fitness involves a genetic dependency like a flux coupling would indicate. Thus, combinations of chemical environments and metabolic network structures were searched using a genetic algorithm to identify those that render desired traits (i.e., sets of metabolic fluxes) flux-coupled with fitness. The search was performed for the production of 29 heterologous compounds in yeast
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