Harnessing yeast biodiversity to identify superior chassis strains for metabolic engineering and precision fermentation

Abstract

Microbial cell factories are increasingly used for the sustainable production of fuels, chemicals and pharmaceuticals. Yeasts are particularly suitable as production hosts because of their metabolic flexibility, robustness, and expanding synthetic biology toolkits. Metabolic engineering of yeast historically relied on a narrow set of reference species and strains, especially Saccharomyces cerevisiae. Recent studies, however, show that applying identical pathway designs to different strain backgrounds or species can yield significant differences in titer, rate and yield (TRY). In this review, we examine how diversity within and between species in genomic features, metabolic regulation, substrate utilization and stress tolerance shapes chassis performance. We focus on eight species, including S. cerevisiae, Yarrowia lipolytica, Kluyveromyces marxianus, Komagataella phaffii, Ogataea polymorpha, Rhodotorula toruloides, Lipomyces starkeyi and Pichia kudriavzevii. We highlight that different species and strain backgrounds provide distinct advantages depending on the target product, pathway requirements, substrate, and process conditions. Finally, we discuss the transition from empirical strain screening toward diversity-informed and predictive chassis selection through multi-omics, phenotyping, metabolic modeling, and machine learning. We propose that chassis identity should be treated as a design variable, and that chassis selection should become an integral part of the Design–Build–Test–Learn cycle to develop optimal cell factories.