ACS Synthetic BiologySynthetic BiologyPeer-reviewed journal article
Discovery and Evaluation of Biosynthetic Pathwaysfor the Production of Five Methyl Ethyl Ketone Precursors
Milenko S. TokićiD, Noushin HadadiiD, Meriç AtamaniD, Dário NevesiD, Birgitta E. EbertiD, Lars M. BlankiD, Ljubiša MiškovićiD, Vassily Hatzimanikatis AiD
Abstract
The limited supply of fossil fuels and the establishment of new environmental policies shifted research in industry and academia towards sustainable production of the 2nd generation of biofuels, with Methyl Ethyl Ketone (MEK) being one promising fuel candidate. MEK is a commercially valuable petrochemical with an extensive application as a solvent. However, as of today, a sustainable and economically viable production of MEK has not yet been achieved despite several attempts of introducing biosynthetic pathways in industrial microorganisms. We used BNICE.ch as a retrobiosynthesis tool to discover all novel pathways around MEK. Out of 1325 identified compounds connecting to MEK with one reaction step, we selected 3-oxopentanoate, but-3-en-2-one, but-1-en-2-olate, butylamine, and 2-hydroxy-2-methyl-butanenitrile for further study. We reconstructed 3679610 novel biosynthetic pathways towards these 5 compounds. We then embedded these pathways into the genome-scale model of E. coli, and a set of 18622 were found to be most biologically feasible ones based on thermodynamics and their yields. For each novel reaction in the viable pathways, we proposed the most similar KEGG reactions, with their gene and protein sequences, as candidates for either a direct experimental implementation or as a basis for enzyme engineering. Through pathway similarity analysis we classified the pathways and identified the enzymes and precursors that were indispensable for the production of the target molecules. These retrobiosynthesis studies demonstrate the potential of BNICE.ch for discovery, systematic evaluation, and analysis of novel pathways in synthetic biology and metabolic engineering studies.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC=\"FIGDIR/small/209569_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@15bb5corg.highwire.dtl.DTLVardef@bfc12borg.highwire.dtl.DTLVardef@1230500org.highwire.dtl.DTLVardef@1d74d2_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG
- organism: E. coli
- assay: metabolomics
- research focus: gene regulatory network inference
- research focus: variant calling
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- Citations
- 35
- FWCI
- 1.42
- Field percentile
- top 18%
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