Bioprospecting and evolving alternative xylose and arabinose pathway enzymes for use in Saccharomyces cerevisiae

Abstract

Bioprospecting is an effective way to find novel enzymes from strains with desirable phenotypes. Such bioprospecting has enabled organisms such as Saccharomyces cerevisiae to utilize nonnative pentose sugars. Yet, the efficiency of this pentose catabolism (especially for the case of arabinose) remains suboptimal. Thus, further pathway optimization or identification of novel, optimal pathways is needed. Previously, we identified a novel set of xylan catabolic pathway enzymes from a superior pentose-utilizing strain of Ustilago bevomyces. These enzymes were used to successfully engineer a xylan-utilizing S. cerevisiae through a blended approach of bioprospecting and evolutionary engineering. Here, we expanded this approach to xylose and arabinose catabolic pathway engineering and demonstrated that bioprospected xylose and arabinose catabolic pathways from U. bevomyces offer alternative choices for enabling efficient pentose catabolism in S. cerevisiae. By introducing a novel set of xylose catabolic genes from U. bevomyces, growth rates were improved up to 85 % over a set of traditional Scheffersomyces stipitis pathway genes. In addition, we suggested an alternative arabinose catabolic pathway which, after directed evolution and pathway engineering, enabled S. cerevisiae to grow on arabinose as a sole carbon source in minimal medium with growth rates upwards of 0.05 h−1. This pathway represents the most efficient growth of yeast on pure arabinose minimal medium. These pathways provide great starting points for further strain development and demonstrate the utility of bioprospecting from U. bevomyces.

DOI: 10.1007/s00253-015-7211-z

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Cite this paper

@article{Lee2015BioprospectingAE, title={Bioprospecting and evolving alternative xylose and arabinose pathway enzymes for use in Saccharomyces cerevisiae}, author={Sun-Mi Lee and Taylor Jellison and Hal S. Alper}, journal={Applied Microbiology and Biotechnology}, year={2015}, volume={100}, pages={2487-2498} }