ArticleMolecular systems biology2021
Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection.
Article in Molecular systems biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- A Transferable Genomic Language Model Framework for Fungal Gene Essentiality Prediction.bioRxiv : the preprint server for biology · 2026Article
- AlphaGEM enables precise genome-scale metabolic modelling by integrating protein structure alignment with deep-learning-based dark metabolism mining.Nature communications · 2026Article
- Horizontal gene transfer in Saccharomyces cerevisiae and other Saccharomycotina yeasts: a review.World journal of microbiology & biotechnology · 2026Review
- EnzymeTuning improves enzyme-constrained metabolic modeling and proteome abundance prediction through deep learning.Nature communications · 2026Article
- Model-driven exploration of lactose and galactose metabolism via an oxidoreductive pathway in Sungouiella intermedia for cell factory applications.Microbial cell factories · 2026Article
- Systems biology of yeast metabolism.FEMS yeast research · 2026Review
- Yeast adapts to diverse ecological niches driven by genomics and metabolic reprogramming.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Machine learning reveals genes impacting oxidative stress resistance across yeasts.Nature communications · 2025Article
- Genome-scale metabolic modeling reveals specific vaginalMicrobiology spectrum · 2025Article
- Genome-wide characterization and expression analysis of WRKY family genes in the biosynthesis of triptolide in Tripterygium wilfordii.BMC genomics · 2025Article
- Integrating yeast biodiversity and machine learning for predictive metabolic engineering.FEMS yeast research · 2025Review
- Enhancing bioactive profiles of elderberry juice through yeast fermentation: a pathway to low-sugar functional beverages.Current research in food science · 2025Article
- Modeling for understanding and engineering metabolism.QRB discovery · 2025Article
- Chromosome-level genome assembly and characterization of the Calophaca sinica genome.DNA research : an international journal for rapid publication of reports on genes and genomes · 2024Article
- Logistic PCA explains differences between genome-scale metabolic models in terms of metabolic pathways.PLoS computational biology · 2024Article
- Metabolomes evolve faster than metabolic network structures.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The metabolic domestication syndrome of budding yeast.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Reconstruction, simulation and analysis of enzyme-constrained metabolic models using GECKO Toolbox 3.0.Nature protocols · 2024Review
- Structural and biochemical insights of xylose MFS and SWEET transporters in microbial cell factories: challenges to lignocellulosic hydrolysates fermentation.Frontiers in microbiology · 2024Review
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11 authors.
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Abstract
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.
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