Carbon metabolism is the energy superhighway of life. Heterotrophs, such as yeasts and animals, view the world as a buffet of diverse carbon sources storing the energy captured by plants from the sun. Diverse yeasts have evolved over hundreds of millions of years to manage carbon and energy differently. The gene networks governing these decisions and capabilities determine their diverse ecologies, lifestyles, and potential applications. Yeasts provide an unmatched experimental system to answer several questions:
How are metabolic functions genetically encoded?
How did they evolve?
How can they be manipulated for sustainable human benefit?
What general principles do they reveal about life?
Research projects fall into five broad areas.
1. Yeast biodiversity, evolutionary genomics, and molecular mechanisms of evolution.
Yeasts are diverse! Budding yeasts of the subphylum Saccharomycotina have evolved over the last 400 million years to include the model yeast Saccharomyces cerevisiae and the opportunistic pathogen Candida albicans. More than 1000 species are known, and they are genetically as diverse as the entire plant or animal kingdom. They have evolved to fill metabolically diverse niches in every biome. Through the Y1000+ Project, we are sequencing and analyzing the genomes of every known species of budding yeast to understand how their genomes encode diverse phenotypes, how they have evolved, and how they can be used to benefit humanity. Highlights include a comprehensive genotype-phenotype map, reconstruction of a strong trend of gene and trait loss through evolution, discovery of the first budding yeast secondary metabolite gene cluster, discovery of a seven-gene operon horizontally transferred from bacteria into a group of yeasts, and investigations into the molecular mechanisms of evolution using the model GALactose utilization pathway. Representative publications include:
Shen XX, Opulente DA, Kominek J, Zhou X et al. 2018. Tempo and mode of genome evolution in the budding yeast subphylum. Cell 175: 1533-45.
Opulente DA et al. 2018. Factors driving metabolic diversity in the budding yeast subphylum. BMC Biol 16: 26.
Kominek J, Doering DT et al. 2019. Eukaryotic acquisition of a bacterial operon. Cell 176: 1356-66. Steenwyk JL et al. 2019. Extensive loss of cell-cycle and DNA repair genes in an ancient lineage of bipolar budding yeasts. PLoS Biol 17: e3000255.
Krause DJ et al. 2018. Functional and evolutionary characterization of a secondary metabolite gene cluster in budding yeasts. Proc Natl Acad Sci USA 115: 11030-5.
Haase MAB, Kominek J et al. Repeated horizontal gene transfer of GALactose metabolism genes violates Dollo’s law of irreversible loss. Genetics accepted: bioRxiv https://doi.org/10.1101/2020.07.22.216101.
Kuang MC et al. 2018. Repeated cis-regulatory tuning of a metabolic bottleneck gene during evolution. Mol Biol Evol 35: 1968-81. (ADD COVER)
Kuang MC et al. 2016. Ongoing resolution of duplicate gene functions shapes the diversification of a metabolic network. eLife 5: e19027.
Hittinger CT et al. 2015. Genomics and the making of yeast biodiversity. Curr Opin Genet Dev 35: 100-9.
2. Saccharomyces evolutionary genomics and brewing applications.
Since we discovered the wild ancestor of hybrid lager-brewing yeasts in 2011, we have determined the global distribution and genomic diversity of Saccharomyces eubayanus. We have also shown how this and other species combined with S. cerevisiae to form fermentation hybrids, including with up to four species. We have also determined the genetic bases of key traits for brewing lager beers, including cold tolerance and fermentation of maltotriose. Many questions remain and about the molecular mechanisms underlying these traits and their evolution, and these investigations are ongoing. Representative publications include:
Langdon QK et al. 2020. Postglacial migration shaped the genomic diversity and global distribution of the wild ancestor of lager-brewing hybrids. PLoS Genet 16: e1008680.
Langdon QK et al. 2019. Fermentation innovation through complex hybridization of wild and domesticated yeasts. Nat Ecol Evol 3: 1576-1586.
Baker EP, Hittinger CT. 2019. Evolution of a novel chimeric maltotriose transporter in Saccharomyces eubayanus from parent proteins unable to perform this function. PLoS Genet 15: e1007786.
Baker EP et al. 2019. Mitochondrial DNA and temperature tolerance in lager yeasts. Sci Adv 5: eaav1869. Hittinger CT et al. 2018. Diverse yeasts for diverse fermented beverages and foods. Curr Opin Biotechnol 49: 199-206.
Peris D, Langdon QK et al. 2016. Complex ancestries of lager-brewing hybrids were shaped by standing variation in the wild yeast Saccharomyces eubayanus. PLoS Genet 12: e1006155.
Baker E et al. 2015. The genome sequence of Saccharomyces eubayanus and the domestication of lager-brewing yeasts. Mol Biol Evol 32: 2818-31.
3. Yeast synthetic biology and bioenergy research.
Within the DOE Great Lakes Bioenergy Research Center, we are engineering S. cerevisiae and other yeasts for advanced biofuel and bioproduct production. We are particularly interested in overcoming the additional challenges required to sustainably convert dedicated bioenergy crops into isobutanol and high-value products to replace non-renewable hydrocarbons. Key traits include tolerance to toxins and high temperatures, xylose fermentation, and product synthesis pathways. We also develop synthetic biology tools to facilitate bioenergy research. Representative publications include:
Peris D et al. 2020. Synthetic hybrids of six yeast species. Nat Commun 11: 2085.
Peris D et al. 2017. Hybridization and adaptive evolution of diverse Saccharomyces species for cellulosic biofuel production. Biotechnol Biofuels 10: 78.
Sato TK et al. 2016. Directed evolution reveals unexpected epistatic interactions that alter metabolic regulation and enable anaerobic xylose use by Saccharomyces cerevisiae. PLoS Genet 12: e1006372.
McIlwain SJ et al. 2016. Genome sequence and analysis of a stress-tolerant, wild-derived strain of Saccharomyces cerevisiae used in biofuels research. G3 (Bethesda) 6: 1757-66.
Alexander WG et al. 2016. Efficient engineering of marker-free synthetic allotetraploids of Saccharomyces. Fungal Genet Biol 89: 10-7.
Alexander WG et al. 2014. High-efficiency genome editing and allele replacement in prototrophic and wild strains of Saccharomyces. Genetics 198: 859-66.
4. Wild YEAST (Yeast Exploration and Analysis Science Team) Program.
Over the last decade, dozens of our undergraduate researchers have isolated thousands of new yeast strains while learning genetics, microbiology, ecology, and bioinformatics. Many of these researchers (and the strains they have isolated) have made important contributions to other projects in the lab. Surprising discoveries include the isolation of the first strains of S. eubayanus from outside of South America and the isolation of dozens of strains of opportunistic pathogens from natural settings. Based on their discoveries, we are currently using genome sequences and rich phenotypic data to formally describe dozens of new species in the taxonomic literature. Nine of our trainees have already gone on to PhD programs, while many others have gone on to professional schools and biotechnology jobs. Representative publications include:
Libkind D et al. 2020. Towards yeast taxogenomics: lessons from novel species descriptions based on complete genome sequences. FEMS Yeast Res 20: foaa042.
Opulente DA et al. 2019. Pathogenic budding yeasts isolated outside of clinical settings. FEMS Yeast Res 19: foz032.
Haase MAB et al. 2017. Genome sequence and physiological analysis of Yamadazyma laniorum f.a. sp. nov. and a reevaluation of the apocryphal xylose fermentation of its sister species, Candida tenuis. FEMS Yeast Res 17: fox019.
Sylvester K et al. 2015. Temperature and host preferences drive the diversification of Saccharomyces and other yeasts: a survey and the discovery of eight new yeast species. FEMS Yeast Res 15: fov002.
5. Computational software for genome-enabled research.
We have developed software to design sgRNAs for CRISPR/Cas9 experiments for diverse populations (CRISpy-pop), analyze hybrid genomes using high-throughput sequencing (sppIDer), and simulate and assemble genomes de novo (iWGS).
Stoneman HR et al. CRISpy-pop: a web tool for designing CRISPR/Cas9-driven genetic modifications in diverse populations. G3 (Bethesda) accepted: bioRxiv https://doi.org/10.1101/2020.06.19.162099.
Langdon QK et al. 2018. sppIDer: a species identification tool to investigate hybrid genomes with high-throughput sequencing. Mol Biol Evol 35: 2835-49. Zhou X et al. 2016. in silico Whole Genome Sequencer & Analyzer (iWGS): a computational pipeline to guide the design and analysis of de novo genome sequencing studies. G3 (Bethesda) 6: 3655-62.