Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming
Journal article, 2025

The famous model organism Saccharomyces cerevisiae is widely present in a variety of natural and human-associated habitats. Despite extensive studies of this organism, the metabolic mechanisms driving its adaptation to varying niches remain elusive. We here gathered genomic resources from 1,807 S. cerevisiae strains and assembled them into a high-quality pangenome, facilitating the comprehensive characterization of genetic diversity across isolates. Utilizing the pangenome, 1,807 strain-specific genome-scale metabolic models (ssGEMs) were generated, which performed well in quantitative predictions of cellular phenotypes, thus helping to examine the metabolic disparities among all S. cerevisiae strains. Integrative analyses of fluxomics and transcriptomics with ssGEMs showcased ubiquitous transcriptional regulation of metabolic flux in specific pathways (i.e., amino acid synthesis) at a population level. Additionally, the gene/reaction inactivation analysis through the ssGEMs refined by transcriptomics showed that S. cerevisiae strains from various ecological niches had undergone reductive evolution at both the genomic and metabolic network levels when compared to wild isolates. Finally, the compiled analysis of the pangenome, transcriptome, and metabolic fluxome revealed remarkable metabolic differences among S. cerevisiae strains originating from distinct oxygen-limited niches, including human gut and cheese environments, and identified convergent metabolic evolution, such as downregulation of oxidative phosphorylation pathways. Together, these results illustrate how yeast adapts to distinct niches modulated by genomic and metabolic reprogramming, and provide computational resources for translating yeast genotype to fitness in future studies.

pangenome

environmental adaptation

strain-specific genome-scale metabolic model

metabolic reprogramming

Saccharomyces cerevisiae

Author

Haoyu Wang

Shanghai Jiao Tong University

Chinese Academy of Sciences

Jens B Nielsen

BioInnovation Institute

Chalmers, Life Sciences, Systems and Synthetic Biology

Yongjin Zhou

Chinese Academy of Sciences

Hongzhong Lu

Shanghai Jiao Tong University

Proceedings of the National Academy of Sciences of the United States of America

0027-8424 (ISSN) 1091-6490 (eISSN)

Vol. 122 32 e2502044122-

Subject Categories (SSIF 2025)

Bioinformatics and Computational Biology

Microbiology

DOI

10.1073/pnas.2502044122

PubMed

40763020

Related datasets

Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming [dataset]

URI: https://figshare.com/s/9c2faecc9d79d4825d0d

More information

Latest update

8/22/2025