Evaluation of Metabolic Engineering Strategies for Production of a Large Panel of Chemicals

Motivated by the possibilities that modern genome editing offers, metabolic engineers currently try to shift away from conventional practices of selection and random mutagenesis towards more rational engineering of microorganisms for the development of cell factories. In this line of work, we aim towards creating a scored and sorted list of chemicals that have a high potential of being sustainably produced, enabling metabolic engineers to make informed decisions on which products to target.

Constraint-based modeling of genome-scale metabolism enables prediction of heterologous pathways from an universal database of known biochemical reactions [1]. Using Cameo [2], a software for computer aided metabolic engineering, a total of 8,996 production pathways have been predicted for a set of 37 chemicals, using a database of 10,580 biochemical reactions (obtained from metanetx.org [3]) and genome-scale models of the two most commonly used cell factories, the yeast Saccharomyces cerevisiae and the bacterium Escherichia coli. The performance of each pathway has been assessed from different perspectives such as pathway length, thermodynamic feasibility ([4] and [5]), production envelopes for different carbon substrates, phylogenetic distance between host and heterologous genes, and freedom to operate (claims on genetic sequences have been obtained from lens.org [6]).

In the long term, we intend to make the developed framework publicly accessible to allow researchers to prioritize their work based on informed decisions, enabling a faster development of sustainable, bio-based products and faster time to market.

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[2] J.G.R Cardoso, K. Jensen, E. Özdemir, M. Herrgård, N. Sonnenschein, http://cameo.bio, doi:10.5281/zenodo.19827

[3] M. Ganter, T. Bernard, S. Moretti, J. Stelling, and M. Pagni, “MetaNetX.org: a website and repository for accessing, analysing and manipulating metabolic networks.,” Bioinformatics, vol. 29, no. 6, pp. 815–6, 2013.

[4] A. Bar-Even, E. Noor, A. Flamholz, J. M. Buescher, and R. Milo, “Hydrophobicity and charge shape cellular metabolite concentrations.,” PLoS Comput. Biol., vol. 7, no. 10, p. 1-7, 2011.

[5] A. Flamholz, E. Noor, A. Bar-Even, and R. Milo, “eQuilibrator--the biochemical thermodynamics calculator.,” Nucleic Acids Res., vol. 40, no. D1, pp. D770–775, 2012

[6] D. Köllhofer, P. Ajjikuttira, R. Jefferson, “Public disclosure of biological sequences in global patent practice.”, Under review, 2015