Archive

  • Visit JGI.DOE.GOV
News & Publications
Home › Publications › Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway

Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway

Published in:

Nat Commun 6 , 10005 (Nov 24 2015)

Author(s):

Mak, W. S., Tran, S., Marcheschi, R., Bertolani, S., Thompson, J., Baker, D., Liao, J. C., Siegel, J. B.

DOI:

10.1038/ncomms10005

Abstract:

The ability to biosynthetically produce chemicals beyond what is commonly found in Nature requires the discovery of novel enzyme function. Here we utilize two approaches to discover enzymes that enable specific production of longer-chain (C5-C8) alcohols from sugar. The first approach combines bioinformatics and molecular modelling to mine sequence databases, resulting in a diverse panel of enzymes capable of catalysing the targeted reaction. The median catalytic efficiency of the computationally selected enzymes is 75-fold greater than a panel of naively selected homologues. This integrative genomic mining approach establishes a unique avenue for enzyme function discovery in the rapidly expanding sequence databases. The second approach uses computational enzyme design to reprogramme specificity. Both approaches result in enzymes with >100-fold increase in specificity for the targeted reaction. When enzymes from either approach are integrated in vivo, longer-chain alcohol production increases over 10-fold and represents >95% of the total alcohol products.

View Publication

Share this:

  • Click to share on Facebook (Opens in new window)
  • Click to share on LinkedIn (Opens in new window)
  • Click to share on Pinterest (Opens in new window)
  • Click to share on Twitter (Opens in new window)
  • Click to print (Opens in new window)
  • JGI.DOE.GOV
  • Disclaimer
  • Accessibility / Section 508
Lawrence Berkeley National Lab Biosciences Area
A project of the US Department of Energy, Office of Science

JGI is a DOE Office of Science User Facility managed by Lawrence Berkeley National Laboratory

© 1997-2025 The Regents of the University of California