Machine learning reveals genes impacting oxidative stress resistance across yeasts.

Katarina Aranguiz, Linda C Horianopoulos, Logan Elkin, Kenia Segura Abá, Drew Jordahl, Katherine A Overmyer, Russell L Wrobel, Joshua J Coon, Shin-Han Shiu, Antonis Rokas, Chris Todd Hittinger

Journal: Nature communications 2025;16(1):5866

PMID: 40592811

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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.

Address: DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA.; Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA.; DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA.; Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA.; Cell Biology, Neurobiology and Anatomy, Medical College of Wisconsin, Milwaukee, WI, USA.; DOE Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, USA.; Genetics and Genome Science Program, Michigan State University, East Lansing, MI, USA.; Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA.; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA.; DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA.; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA.; DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA.; Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA.; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI, USA.; DOE Great Lakes Bioenergy Research Center, Michigan State University, East Lansing, MI, USA.; Genetics and Genome Science Program, Michigan State University, East Lansing, MI, USA.; Department of Plant Biology, Michigan State University, East Lansing, MI, USA.; Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, MI, USA.; Department of Biological Sciences and Evolutionary Studies Initiative, Vanderbilt University, Nashville, TN, USA.; DOE Great Lakes Bioenergy Research Center, University of Wisconsin-Madison, Madison, WI, USA. [email protected].; Wisconsin Energy Institute, Center for Genomic Science Innovation, J. F. Crow Institute for the Study of Evolution, Laboratory of Genetics, University of Wisconsin-Madison, Madison, WI, USA. [email protected].; Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA. [email protected].

DOI: 10.1038/s41467-025-60189-3

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MeSH Terms: Machine Learning, Oxidative Stress, Reactive Oxygen Species, Saccharomyces cerevisiae, Kluyveromyces, tert-Butylhydroperoxide, Oxidoreductases, Genes, Fungal, Gene Expression Regulation, Fungal, Fungal Proteins, Mannosyltransferases