Aranguiz Katarina, Horianopoulos Linda C, Elkin Logan, Abá Kenia Segura, Jordahl Drew, Overmyer Katherine A, Wrobel Russell L, Coon Joshua J, Shiu Shin-Han, Rokas Antonis, Hittinger Chris Todd
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.
Nat Commun. 2025 Jul 1;16(1):5866. doi: 10.1038/s41467-025-60189-3.
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.
活性氧（ROS）是酵母在常规代谢过程中以及与其他生物体相互作用（包括宿主感染）时遇到的高反应性分子。在这里，我们描述了整个古老酵母亚门子囊菌纲对ROS诱导化合物叔丁基过氧化氢的抗性变化，并使用机器学习（ML）来识别基因家族大小可预测ROS抗性的基因家族。最具预测性的特征在与细胞壁组织相关的基因家族中富集，包括两个还原酶基因家族。我们估计了各特征对每个物种分类的定量贡献，以指导实验验证，并表明老黄色酶（OYE）还原酶的过表达增加了乳酸克鲁维酵母对ROS的抗性，而缺乏多个编码甘露糖基转移酶基因的酿酒酵母突变体对ROS高度敏感。总之，这项工作提供了一个框架，说明ML如何揭示不同物种间性状变异的遗传机制，并为临床和生物技术应用中的性状操纵提供信息。
