A framework for the identification of promising bio‐based chemicals. Issue 9 (10th July 2018)

• Record Type: Journal Article
• Authors: Wu, Wenzhao; Long, Matthew R.; Zhang, Xiaolin; Reed, Jennifer L.; Maravelias, Christos T.
• Is Part Of: Biotechnology and bioengineering. Volume 115:Issue 9(2018)
• Page Start: 2328
• Page End: 2340
• Publication Date: 2018-07-10
• Subjects: bio‐based chemicals -- value‐added chemicals -- HPV chemicals -- bio‐conversion -- flux balance analysis -- biorefinery; Biotechnology -- Periodicals; Bioengineering -- Periodicals; 660.6
• DOI: 10.1002/bit.26779
• Languages: English
• ISSNs: 0006-3592

Abstract

Abstract: Recent progress in metabolic engineering and synthetic biology enables the use of microorganisms for the production of chemicals—"bio‐based chemicals." However, it is still unclear which chemicals have the highest economic prospect. To this end, we develop a framework for the identification of such promising ones. Specifically, we first develop a genome‐scale constraint‐based metabolic modeling approach, which is used to identify a candidate pool of 209 chemicals (together with the estimated yield, productivity, and residence time for each) from the intersection of the high‐production‐volume chemicals and the KEGG and MetaCyc databases. Second, we design three screening criteria based on a chemical's profit margin, market volume, and market size. The total process cost, including the downstream separation cost, is systematically incorporated into the evaluation. Third, given the three aforementioned criteria, we identify 32 products as economically promising if the maximum yields can be achieved, and 22 products if the maximum productivities can be achieved. The breakeven titer that renders zero profit margin for each product is also presented. Comparisons between extracellular and intracellular production, as well as Escherichia coli and Saccharomyces cerevisiae systems are also discussed. The proposed framework provides important guidance for future studies in the production of bio‐based chemicals. It is also flexible in that the databases, yield estimations, and criteria can be modified to customize the screening. Abstract : Wu and coworkers develop a framework to guide development of bioprocesses for chemicals. The framework includes: (1) a genome‐scale metabolic modeling approach to identify candidate high production volume chemicals; (2) methods to estimate production cost, including downstream separation costs, for both intracellular and extracellular production, as well as for both E. coli and S. cerevisiae systems; and (3) three screening criteria (profit margin, market volume and market size), which are used to identify 32 chemicals whose microbial production appears promising.