Machine learning enables identification of an alternative yeast galactose utilization pathway

Abstract

How genomic differences contribute to phenotypic differences is a major question in biology. The recently characterized genomes, isolation environments, and qualitative patterns of growth on 122 sources and conditions of 1,154 strains from 1,049 fungal species (nearly all known) in the yeast subphylum Saccharomycotina provide a powerful, yet complex, dataset for addressing this question. We used a random forest algorithm trained on these genomic, metabolic, and environmental data to predict growth on several carbon sources with high accuracy. Known structural genes involved in assimilation of these sources and presence/absence patterns of growth in other sources were important features contributing to prediction accuracy. By further examining growth on galactose, we found that it can be predicted with high accuracy from either genomic (92.2%) or growth data (82.6%) but not from isolation environment data (65.6%). Prediction accuracy was even higher (93.3%) when we combined genomic and growth data. After the GAL actose utilization genes, the most important feature for predicting growth on galactose was growth on galactitol, raising the hypothesis that several species in two orders, Serinales and Pichiales (containing the emerging pathogen Candida auris and the genus Ogataea , respectively), have an alternative galactose utilization pathway because they lack the GAL genes. Growth and biochemical assays confirmed that several of these species utilize galactose through an alternative oxidoreductive D-galactose pathway, rather than the canonical GAL pathway. Machine learning approaches are powerful for investigating the evolution of the yeast genotype–phenotype map, and their application will uncover novel biology, even in well-studied traits.

Convergent expansions of keystone gene families drive metabolic innovation in a major eukaryotic clade

“…Metabolic traits for each species were sourced from Harrison et al 2024 22 , and supplemented with experimental assays from Opulente et al 2024 21 . Metabolic traits were considered present if cultures were able to grow on 96-well plates containing the carbon or nitrogen source in minimal media.…”

“…To overcome these issues, we selected 56 metabolic traits, each of which evolved dozens to thousands of times across 400 million years of evolution, providing unprecedented statistical power for investigating convergent evolutionary events. These 56 metabolic traits have been experimentally tested 21 , 22 for 993 species of Saccharomycotina yeasts (“yeasts” hereafter). Yeasts are able to metabolize alcohols, ketones, organic acids and more, which has enabled them to colonize virtually every continent and biome on the planet 23 , 24 .…”