ArticleNature communications2025
Machine learning reveals genes impacting oxidative stress resistance across yeasts.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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Who cites it
9 citing papers in PubMed.
- Oxidative stress impacts carbon metabolism and induces upregulation of redox enzymes andsmall secreted proteins in the wood-decay fungus.Fungal biology and biotechnology · 2026Article
- Convergent evolution of aerobic fermentation through divergent mechanisms acting on key shared glycolytic genes.The EMBO journal · 2026Article
- Template Switching as a Driver of Promoter Evolution in Yeast: Case Study of the GRE2 Gene.Genome biology and evolution · 2026Article
- The macroevolution of filamentation morphology across the Saccharomycotina yeast subphylum.FEMS yeast research · 2026Article
- AI-based methods for the assessment of DNA damage and repair mechanisms.Frontiers in systems biology · 2026Review
- The Macroevolution of Filamentation Morphology Across thebioRxiv : the preprint server for biology · 2025Article
- Convergent evolution of aerobic fermentation through divergent mechanisms acting on key shared glycolytic genes.bioRxiv : the preprint server for biology · 2025Article
- Celebrating the fifth edition of the International Symposium on Fungal Stress - ISFUS, a decade after its 2014 debut.Fungal biology · 2025Article
- Machine learning reveals genes impacting oxidative stress resistance across yeasts.Nature communications · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Reactive oxygen species (ROS) are highly reactive molecules encountered by yeasts during routine metabolism and during interactions with other organisms, including host infection. Here, we characterize the variation in resistance to the ROS-inducing compound tert-butyl hydroperoxide across the ancient yeast subphylum Saccharomycotina and use machine learning (ML) to identify gene families whose sizes are predictive of ROS resistance. The most predictive features are enriched in gene families related to cell wall organization and include two reductase gene families. We estimate the quantitative contributions of features to each species' classification to guide experimental validation and show that overexpression of the old yellow enzyme (OYE) reductase increases ROS resistance in Kluyveromyces lactis, while Saccharomyces cerevisiae mutants lacking multiple mannosyltransferase-encoding genes are hypersensitive to ROS. Altogether, this work provides a framework for how ML can uncover genetic mechanisms underlying trait variation across diverse species and inform trait manipulation for clinical and biotechnological applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.