title: Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.
abstract: The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways.
authors.affiliation: Joint BioEnergy Institute, Emeryville, California, 94608; Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California.
authors.forename: Kevin W
authors.initials: KW
authors.lastname: George
authors.forename: Amy
authors.initials: A
authors.lastname: Chen
authors.forename: Aakriti
authors.initials: A
authors.lastname: Jain
authors.forename: Tanveer S
authors.initials: TS
authors.lastname: Batth
authors.forename: Edward E K
authors.initials: EE
authors.lastname: Baidoo
authors.forename: George
authors.initials: G
authors.lastname: Wang
authors.forename: Paul D
authors.initials: PD
authors.lastname: Adams
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Petzold
authors.forename: Jay D
authors.initials: JD
authors.lastname: Keasling
authors.forename: Taek Soon
authors.initials: TS
authors.lastname: Lee
mesh_terms: D000085:Acetates / Q000378:metabolism; D056804:Biofuels / Q000382:microbiology*; D053898:Biosynthetic Pathways; D004926:Escherichia coli / Q000235:genetics / Q000254:growth & development / Q000378:metabolism*; D029968:Escherichia coli Proteins / Q000235:genetics / Q000378:metabolism*; D005947:Glucose / Q000378:metabolism; D007218:Industrial Microbiology / Q000379:methods*; D060847:Metabolic Engineering / Q000379:methods*; D008954:Models, Biological; D000439:Pentanols / Q000378:metabolism*; D040901:Proteomics / Q000379:methods
chemical_list: D000085:Acetates; D056804:Biofuels; D029968:Escherichia coli Proteins; D000439:Pentanols; C056744:isopentenol; D005947:Glucose
keywords: biofuel; correlation analysis; isopentenol; isoprenoid; metabolic engineering; proteomics