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Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway
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 (C(5)–C(8)) alcohols from sugar. The first approach combines b...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Pub. Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673503/ https://www.ncbi.nlm.nih.gov/pubmed/26598135 http://dx.doi.org/10.1038/ncomms10005 |
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author | Mak, Wai Shun Tran, Stephen Marcheschi, Ryan Bertolani, Steve Thompson, James Baker, David Liao, James C. Siegel, Justin B. |
author_facet | Mak, Wai Shun Tran, Stephen Marcheschi, Ryan Bertolani, Steve Thompson, James Baker, David Liao, James C. Siegel, Justin B. |
author_sort | Mak, Wai Shun |
collection | PubMed |
description | 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 (C(5)–C(8)) 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. |
format | Online Article Text |
id | pubmed-4673503 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Pub. Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-46735032015-12-17 Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway Mak, Wai Shun Tran, Stephen Marcheschi, Ryan Bertolani, Steve Thompson, James Baker, David Liao, James C. Siegel, Justin B. Nat Commun Article 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 (C(5)–C(8)) 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. Nature Pub. Group 2015-11-24 /pmc/articles/PMC4673503/ /pubmed/26598135 http://dx.doi.org/10.1038/ncomms10005 Text en Copyright © 2015, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Mak, Wai Shun Tran, Stephen Marcheschi, Ryan Bertolani, Steve Thompson, James Baker, David Liao, James C. Siegel, Justin B. Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
title | Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
title_full | Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
title_fullStr | Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
title_full_unstemmed | Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
title_short | Integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
title_sort | integrative genomic mining for enzyme function to enable engineering of a non-natural biosynthetic pathway |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673503/ https://www.ncbi.nlm.nih.gov/pubmed/26598135 http://dx.doi.org/10.1038/ncomms10005 |
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