Literature DB >> 26721212

Metabolic engineering of Saccharomyces cerevisiae for the overproduction of short branched-chain fatty acids.

Ai-Qun Yu1, Nina Kurniasih Pratomo Juwono1, Jee Loon Foo1, Susanna Su Jan Leong2, Matthew Wook Chang3.   

Abstract

Short branched-chain fatty acids (SBCFAs, C4-6) are versatile platform intermediates for the production of value-added products in the chemical industry. Currently, SBCFAs are mainly synthesized chemically, which can be costly and may cause environmental pollution. In order to develop an economical and environmentally friendly route for SBCFA production, we engineered Saccharomyces cerevisiae, a model eukaryotic microorganism of industrial significance, for the overproduction of SBCFAs. In particular, we employed a combinatorial metabolic engineering approach to optimize the native Ehrlich pathway in S. cerevisiae. First, chromosome-based combinatorial gene overexpression led to a 28.7-fold increase in the titer of SBCFAs. Second, deletion of key genes in competing pathways improved the production of SBCFAs to 387.4 mg/L, a 31.2-fold increase compared to the wild-type. Third, overexpression of the ATP-binding cassette (ABC) transporter PDR12 increased the secretion of SBCFAs. Taken together, we demonstrated that the combinatorial metabolic engineering approach used in this study effectively improved SBCFA biosynthesis in S. cerevisiae through the incorporation of a chromosome-based combinatorial gene overexpression strategy, elimination of genes in competitive pathways and overexpression of a native transporter. We envision that this strategy could also be applied to the production of other chemicals in S. cerevisiae and may be extended to other microbes for strain improvement.
Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Ehrlich pathway; Saccharomyces cerevisiae; Short branched-chain fatty acids; Transporters

Mesh:

Substances:

Year:  2015        PMID: 26721212     DOI: 10.1016/j.ymben.2015.12.005

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


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