Big data mining, rational modification, and ancestral sequence reconstruction inferred multiple xylose isomerases for biorefinery

Abstract

The isomerization of xylose to xylulose is considered the most promising approach to initiate xylose bioconversion. Here, phylogeny-guided big data mining, rational modification, and ancestral sequence reconstruction strategies were implemented to explore new active xylose isomerases (XIs) for <i>Saccharomyces cerevisiae</i>. Significantly, 13 new active XIs for <i>S. cerevisiae</i> were mined or artificially created. Moreover, the importance of the amino-terminal fragment for maintaining basic XI activity was demonstrated. With the mined XIs, four efficient xylose-utilizing <i>S. cerevisiae</i> were constructed and evolved, among which the strain <i>S. cerevisiae</i> CRD5HS contributed to ethanol titers as high as 85.95 and 94.76 g/liter from pretreated corn stover and corn cob, respectively, without detoxifying or washing pretreated biomass. Potential genetic targets obtained from adaptive laboratory evolution were further analyzed by sequencing the high-performance strains. The combined XI mining methods described here provide practical references for mining other scarce and valuable enzymes.