Streamlining the Analysis of Dynamic ¹³C-Labeling Patterns for the Metabolic Engineering of <i>Corynebacterium glutamicum</i> as <span style="font-variant: small-caps">l</span>-Histidine Production Host

Abstract

Today’s possibilities of genome editing easily create plentitudes of strain mutants that need to be experimentally qualified for configuring the next steps of strain engineering. The application of design-build-test-learn cycles requires the identification of distinct metabolic engineering targets as design inputs for subsequent optimization rounds. Here, we present the pool influx kinetics (PIK) approach that identifies promising metabolic engineering targets by pairwise comparison of up- and downstream 13C labeling dynamics with respect to a metabolite of interest. Showcasing the complex l-histidine production with engineered Corynebacterium glutamicuml-histidine-on-glucose yields could be improved to 8.6 ± 0.1 mol% by PIK analysis, starting from a base strain. Amplification of purA, purB, purH, and formyl recycling was identified as key targets only analyzing the signal transduction kinetics mirrored in the PIK values.

Keywords

• design-build-test-learn (DBTL) cycle
• metabolomics
• strain engineering
• l-histidine%22%2C%22default_operator%22%3A%22AND%22%7D%7D%7D"> <span style="font-variant: small-caps">l</span>-histidine
• <i>Corynebacterium glutamicum</i>
• hydrophilic interaction chromatography (HILIC)