Sustainable production of 2,3,5,6-Tetramethylpyrazine at high titer in engineered Corynebacterium glutamicum using statistical design of experiments

Abstract

BackgroundThe industrial amino acid production workhorse, Corynebacterium glutamicum naturally produces low levels of 2,3,5,6-tetramethylpyrazine (TMP), a valuable flavor, fragrance and commodity chemical. We have previously reported serendipitous production of TMP in C. glutamicum strains. In the present study, we demonstrate TMP production in C. glutamicum type strain ATCC13032 via the expression of a heterologous TMP pathway in a defined medium followed by statistical design of experiments to understand the effect of the media composition on TMP production. ResultsThe C. glutamicum strain engineered to overexpress acetolactate synthase and alpha-acetolactate decarboxylase from Lactococcus lactis produced [~]0.8 g/L TMP in CGXII minimal medium supplemented with 40 g/L glucose in 24-deep well plates. This engineered strain also demonstrated growth and TMP production when the minimal medium was supplemented with up to 40% (v/v) hydrolysates derived from ionic liquid pretreated sorghum biomass. A screen for improvements in media composition on TMP titer was conducted using fractional factorial design that identified glucose and urea as significant components affecting TMP production. These two components were further optimized using response surface methodology. In the optimized CGXII medium, the engineered strain could produce up to 3.56 g/L TMP (4-fold enhancement in titers and 2-fold enhancement in yield, mol/mol) from 80 g/L glucose and 11.9 g/L urea in shake flask batch cultivation. ConclusionsWe engineered the industrially relevant host, C. glutamicum for targeted production of TMP by heterologous expression of pathway proteins. We demonstrated the capability of the engineered strain for growth and TMP production utilizing real world carbon streams such as hydrolysates. We further identified glucose and urea as the key minimal media components significantly affecting TMP production using statistical media optimization.