S52: The design, engineering, and optimization of a microbial process for manufacturing of 1,4-butanediol

Monday, July 25, 2011: 3:30 PM
Bayside BC, 4th fl (Sheraton New Orleans)
Stephen Van Dien, Genomatica, Inc., San Diego, CA
Genomatica has established an integrated computational/experimental metabolic engineering platform to design, create, and optimize novel high-producing organisms and bioprocesses.  Here we present the use of our platform to develop E. coli strains for the production of the industrial chemical 1,4-butanediol (BDO) from glucose and sucrose. BDO is a four-carbon diol that currently is manufactured exclusively through various petrochemical routes. It is part of a large volume family of solvents and polymer intermediates with an overall market opportunity exceeding $4.0B. Therefore, this product represents an opportunity to make a significant impact on the replacement of traditional petrochemical processes with benign bioprocesses using renewable feedstocks.

Here we describe application of this technology platform to design and construct a high-performing microorganism capable of producing BDO from carbohydrates for the first time. The Biopathway Predictor algorithm was employed to elucidate all possible routes to BDO from central metabolites, and choose the most favorable for implementation. We then utilized the OptKnock methodology to identify a set of gene deletions designed to couple product formation to growth. After design-based construction of the biocatalyst, our models facilitated the analysis of fermentation data to evaluate performance. Systems biology approaches including microarrays, 13C-flux analysis, and metabolomics were applied to characterize the strain, identify targets for further improvement, and optimize the fermentation process. The presentation will show how significant progress was made in BDO titer, production rate, and yield through model-guided strain and process improvement, ultimately resulting in an economically attractive process that was validated at the pilot scale.