An integrated computational and experimental study for overproducing fatty acids in Escherichia coli

Sridhar Ranganathan, Ting Wei Tee, Anupam Chowdhury, Ali R. Zomorrodi, Jong Moon Yoon, Yanfen Fu, Jacqueline V. Shanks, Costas D. Maranas

Research output: Contribution to journalArticlepeer-review

93 Scopus citations


Increasing demands for petroleum have stimulated sustainable ways to produce chemicals and biofuels. Specifically, fatty acids of varying chain lengths (C6-C16) naturally synthesized in many organisms are promising starting points for the catalytic production of industrial chemicals and diesel-like biofuels. However, bio-production of fatty acids from plants and other microbial production hosts relies heavily on manipulating tightly regulated fatty acid biosynthetic pathways. In addition, precursors for fatty acids are used along other central metabolic pathways for the production of amino acids and biomass, which further complicates the engineering of microbial hosts for higher yields. Here, we demonstrate an iterative metabolic engineering effort that integrates computationally driven predictions and metabolic flux analysis techniques to meet this challenge. The OptForce procedure was used for suggesting and prioritizing genetic manipulations that overproduce fatty acids of different chain lengths from C6 to C16 starting with wild-type E. coli. We identified some common but mostly chain-specific genetic interventions alluding to the possibility of fine-tuning overproduction for specific fatty acid chain lengths. In accordance with the OptForce prioritization of interventions, fabZ and acyl-ACP thioesterase were upregulated and fadD was deleted to arrive at a strain that produces 1.70g/L and 0.14g fatty acid/g glucose (~39% maximum theoretical yield) of C14-16 fatty acids in minimal M9 medium. These results highlight the benefit of using computational strain design and flux analysis tools in the design of recombinant strains of E. coli to produce free fatty acids.

Original languageEnglish (US)
Pages (from-to)687-704
Number of pages18
JournalMetabolic engineering
Issue number6
StatePublished - Nov 2012

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology


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