Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production

Research output: Contribution to journalJournal articlepeer-review

  • Kevin W George
  • Amy Chen
  • Aakriti Jain
  • Batth, Tanveer Singh
  • Edward E K Baidoo
  • George Wang
  • Paul D Adams
  • Christopher J Petzold
  • Jay D Keasling
  • Taek Soon Lee

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.

Original languageEnglish
JournalBiotechnology and Bioengineering
Volume111
Issue number8
Pages (from-to)1648-1658
Number of pages11
ISSN0006-3592
DOIs
Publication statusPublished - 2014
Externally publishedYes

    Research areas

  • Acetates/metabolism, Biofuels/microbiology, Biosynthetic Pathways, Escherichia coli/genetics, Escherichia coli Proteins/genetics, Glucose/metabolism, Industrial Microbiology/methods, Metabolic Engineering/methods, Models, Biological, Pentanols/metabolism, Proteomics/methods

ID: 204046836