MAESTRO uncovers tandem paralog dynamics as a core driver of fungal stress adaptation

作者：Ping-Hung Hsieh, Y. Sasaki, Chu-I Yang, Zong‐Yen Wu, Andrei Stecca Steindorff, Sajeet Haridas, Jing Ke, Zia Fatma, Zhiying Zhao, Dana A. Opulente, Siwen Deng, Chris Todd Hittinger, Igor V. Grigoriev, Bruce S. Dien, Huimin Zhao, Yi‐Pei Li, Yasuo Yoshikuni · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2025 · DOI：10.1101/2025.08.29.673034 · 被引用次数：3 · 研究领域：Plant Pathogens and Fungal Diseases、Mycorrhizal Fungi and Plant Interactions、Fungal Biology and Applications

SUMMARY Understanding how fungi adapt to diverse stresses is critical for mitigating emerging drug resistance and harnessing their robustness for biotechnology. Pichia kudriavzevii is a stress-tolerant and intrinsically drug-resistant yeast, with dual industrial and clinical importance. We analyzed 170 strains using MAESTRO, a machine-learning-assisted GWAS pipeline optimized for small cohorts. MAESTRO identified biologically meaningful features and revealed that copy number variation (CNV) of tandem paralogs (TPs) is a core mechanism of multi-stress adaptation. TPs were recurrently linked to tolerance of industrial inhibitors (HMF, phenolics, heat) and antifungal drugs (fluconazole, azoles), and deletion of the TP pair gene4260/gene4261 confirmed pleiotropic effects across stresses. These findings support a TP CNV model where recombination-driven TP CNVs and gene fusions enable rapid stress adaptation. Importantly, our results suggest that antifungal resistance can arise through co-option of mechanisms originally evolved for environmental stressors, raising a One Health concern about the environmental origins of drug-resistant pathogens.