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A framework for the identification of promising bio‐based chemicals
Author(s) -
Wu Wenzhao,
Long Matthew R.,
Zhang Xiaolin,
Reed Jennifer L.,
Maravelias Christos T.
Publication year - 2018
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.26779
Subject(s) - identification (biology) , biochemical engineering , computational biology , microbiology and biotechnology , chemistry , biology , engineering , ecology
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.