Open AccessYeast metabolic innovations emerged via expanded metabolic network and gene positive selection
Author(s) -
Lu Hongzhong,
Li Feiran,
Yuan Le,
Domenzain Iván,
Yu Rosemary,
Wang Hao,
Li Gang,
Chen Yu,
Ji Boyang,
Kerkhoven Eduard J,
Nielsen Jens
Publication year - 2021
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.15252/msb.202110427
Subject(s) - biology , metabolic network , gene , metabolic pathway , trait , gene duplication , genetics , phenotype , selection (genetic algorithm) , gene regulatory network , computational biology , negative selection , phenotypic plasticity , evolutionary biology , genome , gene expression , artificial intelligence , computer science , programming language
Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome‐scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence‐level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.