Yeast identification: reassessment of assimilation tests as sole universal identifiers

Elevated Sporulation Efficiency in Fission Yeast Schizosaccharomyces japonicus Strains Isolated from Drosophila

The fission yeast Schizosaccharomyces japonicus, comprising S. japonicus var. japonicus and S. japonicus var. versatilis varieties, has unique characteristics such as striking hyphal growth not seen in other Schizosaccharomyces species; however, information on its diversity and evolution, in particular mating and sporulation, remains limited. Here we compared the growth and mating phenotypes of 17 wild strains of S. japonicus, including eight S. japonicus var. japonicus strains newly isolated from an insect (Drosophila). Unlike existing wild strains isolated from fruits/plants, the strains isolated from Drosophila sporulated at high frequency even under nitrogen-abundant conditions. In addition, one of the strains from Drosophila was stained by iodine vapor, although the type strain of S. japonicus var. japonicus is not stained. Sequence analysis further showed that the nucleotide and amino acid sequences of pheromone-related genes have diversified among the eight strains from Drosophila, suggesting crossing between S. japonicus cells of different genetic backgrounds occurs frequently in this insect. Much of yeast ecology remains unclear, but our findings suggest that insects such as Drosophila might be a good niche for mating and sporulation, and will provide a basis for the understanding of sporulation mechanisms via signal transduction, as well as the ecology and evolution of yeast.

Signatures of optimal codon usage in metabolic genes inform budding yeast ecology

Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism (GAL) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GALactose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter-species that have yet to be cultured in the lab or have only been identified by genomic material.

MALDI-TOF MS based identification of food-borne yeast isolates

In this study, food-borne yeast isolates (n=96), comprising at least 33 species, were identified using MALDI-TOF MS and conventional methods (API ID 32 C and Phoenix Yeast ID). Discrepancies of both methods were resolved by sequencing the ITS1-5.8S-rRNA-ITS2 region. For ten isolates, mainly classified to Rhodotorula and Trichosporon species, no clear final species identification was possible. 62 isolates were correctly identified to species level using either MALDI-TOF MS or conventional tests. 15 isolates were misidentified when applying conventional assays. In contrary, no species misidentifications were observed after MALDI-TOF MS based classification. In return, 16 isolates were not identifiable after matching their protein fingerprints against MALDI Biotyper 4.0.0.1 library. MALDI TOF MS in-house database update clearly improved the identification. In conclusion, the presented data suggest that MALDI-TOF MS is an appropriate platform for reliable classification and identification of food-borne yeast isolates.