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Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica, Debaryomyces hansenii, and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions. 

Abstract Probiotic yeasts are emerging as preventative and therapeutic solutions for disease. Often ingested via cultured foods and beverages, they can survive the harsh conditions of the gastrointestinal tract and adhere to it, where they provide nutrients and inhibit pathogens like Candida albicans. Yet, little is known of the genomic determinants of these beneficial traits. To this end, we have sequenced 2 food-derived probiotic yeast isolates that mitigate fungal infections. We find that the first strain, KTP, is a strain of Saccharomyces cerevisiae within a small clade that lacks any apparent ancestry from common European/wine S. cerevisiae strains. Significantly, we show that S. cerevisiae KTP genes involved in general stress, pH tolerance, and adherence are markedly different from S. cerevisiae S288C but are similar to the commercial probiotic yeast species S. boulardii. This suggests that even though S. cerevisiae KTP and S. boulardii are from different clades, they may achieve probiotic effect through similar genetic mechanisms. We find that the second strain, ApC, is a strain of Issatchenkia occidentalis, one of the few of this family of yeasts to be sequenced. Because of the dissimilarity of its genome structure and gene organization, we infer that I. occidentalis ApC likely achieves a probiotic effect through a different mechanism than the Saccharomyces strains. Therefore, this work establishes a strong genetic link among probiotic Saccharomycetes, advances the genomics of Issatchenkia yeasts, and indicates that probiotic activity is not monophyletic and complimentary mixtures of probiotics could enhance health benefits beyond a single species.