Rational Engineering of the Methylerythritol Phosphate Pathway through Metabolic Control Analysis

RATIONAL ENGINEERING OF THE METHYLERYTHRITOL PHOSPHATE PATHWAY THROUGH METABOLIC CONTROL ANALYSIS

Daniel Volke¹, Benedikt Engels¹, Louwrance Wright², Jonathan Gershenzon², Stefan Jennewein¹

¹Fraunhofer Institute for Molecular Biology and Applied Ecology, Forckenbeckstraße 6, Aachen, Germany

²Max Planck Institute for Chemical Ecology, Hans-Knöll-Straße 8, Jena, Germany.

Facing an increasing demand of sustainable energy and chemicals, new strategies have to be explored to synthesis these in low-cost and environmental friendly processes. Isoprenoids are a promising source for a broad spectrum of valuable molecules, including fine and bulk chemicals, fuels, and pharmaceuticals.

Isoprenoids are the largest as well as most diverse class of chemical molecules synthesized by the natural world. All isoprenoids are derived from two common precursors, isopentenyl phosphate and dimethylallyl phosphate, which are synthesis via two distinct pathways. The long known mevalonate (MVA) pathway uses acetyl-CoA as substrate, while the recently discovered methylerythritol (MEP) pathway uses glycerinaldehyde-3-phosphate and pyruvate.

The MVA pathway has been engineered to produce large quantities of terpenoids, but similar attempts using the MEP pathway have met with only limited success. In part this reflects our lack of knowledge concerning the regulation of MEP pathway. This is unfortunately, because the MEP pathway seems energetically more efficient and balanced in the use of reduction equivalents.

A combinatorial approach of metabolic engineering and metabolic flux analysis was used for the production of the economical relevant isoprenoids isoprene and farnesene in E. coli. Metabolic flux analysis was used for the identification of target genes, which influence the flux through the MEP pathway. These genes were then further assessed with metabolic control analysis for their quantitative properties. Targeted proteomics enabled us to determine the enzyme concentrations and pools of pathway intermediates were measured through LC-MS/MS experiments. This allowed us to determine control coefficients and kinetic values for the pathway and integrate them in computational models. The acquired information was then used for rational engineering of the MEP pathway in E. coli.