Codon Optimization Improves the Prediction of Xylose Metabolism from Gene Content in Budding Yeasts

Nalabothu, Rishitha L.; Fisher, Kaitlin J.; LaBella, Abigail Leavitt; Meyer, Taylor A.; Opulente, Dana A.; Wolters, John F.; Rokas, Antonis; Hittinger, Chris Todd

doi:10.1093/molbev/msad111

Title: Codon Optimization Improves the Prediction of Xylose Metabolism from Gene Content in Budding Yeasts

Journal Article · 08 May 2023 · Molecular Biology and Evolution

DOI: https://doi.org/10.1093/molbev/msad111 · OSTI ID:1992360

Nalabothu, Rishitha L. ^[1]; Fisher, Kaitlin J. ^[2]; LaBella, Abigail Leavitt ^[3]; Meyer, Taylor A. ^[1]; Opulente, Dana A. ^[4]; Wolters, John F. ^[1];

^[5];

^[1]

Univ. of Wisconsin, Madison, WI (United States)
Univ. of Wisconsin, Madison, WI (United States); State Univ. of New York (SUNY), Oswego, NY (United States)
Vanderbilt Univ., Nashville, TN (United States); Univ. of North Carolina, Charlotte, NC (United States)
Univ. of Wisconsin, Madison, WI (United States); Villanova Univ., PA (United States)
Vanderbilt Univ., Nashville, TN (United States)

Xylose is the second most abundant monomeric sugar in plant biomass. Consequently, xylose catabolism is an ecologically important trait for saprotrophic organisms, as well as a fundamentally important trait for industries that hope to convert plant mass to renewable fuels and other bioproducts using microbial metabolism. Although common across fungi, xylose catabolism is rare within Saccharomycotina, the subphylum that contains most industrially relevant fermentative yeast species. The genomes of several yeasts unable to consume xylose have been previously reported to contain the full set of genes in the XYL pathway, suggesting the absence of a gene–trait correlation for xylose metabolism. Here, we measured growth on xylose and systematically identified XYL pathway orthologs across the genomes of 332 budding yeast species. Although the XYL pathway coevolved with xylose metabolism, we found that pathway presence only predicted xylose catabolism about half of the time, demonstrating that a complete XYL pathway is necessary, but not sufficient, for xylose catabolism. We also found that XYL1 copy number was positively correlated, after phylogenetic correction, with xylose utilization. We then quantified codon usage bias of XYL genes and found that XYL3 codon optimization was significantly higher, after phylogenetic correction, in species able to consume xylose. Finally, we showed that codon optimization of XYL2 was positively correlated, after phylogenetic correction, with growth rates in xylose medium. We conclude that gene content alone is a weak predictor of xylose metabolism and that using codon optimization enhances the prediction of xylose metabolism from yeast genome sequence data.

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Research Organization:: Great Lakes Bioenergy Research Center (GLBRC), Madison, WI (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); USDA National Institute of Food and Agriculture; National Institutes of Health (NIH); National Institute of Allergy and Infectious Diseases (NIAID)

Grant/Contract Number:: SC0018409; DEB-1442148; DEB-2110403; DEB-1442113; DEB-2110404; R56 AI146096; R01 AI153356

OSTI ID:: 1992360

Journal Information:: Molecular Biology and Evolution, Vol. 40, Issue 6; ISSN 0737-4038

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

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59 BASIC BIOLOGICAL SCIENCES
codon optimization
yeasts
metabolic evolution
genome evolution

Title: Codon Optimization Improves the Prediction of Xylose Metabolism from Gene Content in Budding Yeasts

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