Yeast probiotics, particularly Saccharomyces boulardii, are used in clinical, nutritional and biotechnological settings, yet their strain-specific mechanisms remain incompletely understood. This review examines how systems biology and multi-omics approaches can improve understanding of probiotic yeast function. We discuss comparative genomics and pangenomics, transcriptomic responses to gastrointestinal stress, cell-surface proteins involved in pathogen interactions, and metabolomic outputs including organic acids and other potential postbiotic metabolites. We then consider genome-scale metabolic models, flux balance analysis, and 13C metabolic flux analysis as complementary tools for converting omics observations into testable hypotheses about pathway activity and strain-specific metabolic traits. Published comparisons of S. boulardii and S. cerevisiae illustrate this framework. Conserved and strain-specific genomic variation, differential stress responses, acetate production, pathogen binding and host-cell effects can be examined together, while causal links between most variants and probiotic effects remain unresolved. The review also compares the systems-data, metabolic-modeling, and genome-engineering readiness of Kluyveromyces marxianus and Debaryomyces hansenii, two non-conventional yeasts with thermotolerance or halotolerance, but less direct evidence for human probiotic function. Finally, we discuss CRISPR-based engineering, machine learning, data standards, regulatory considerations and future possibilities for strain-specific computational models. Progress will require standardized experimental conditions, well-annotated strain resources, integrated multi-omics datasets, and experimental validation of model predictions.
* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.