Year: 2026
Type: preprint
Abstract: Non-oxidative glycolysis (NOG) converts glucose to acetyl-CoA without emitting CO 2 during Escherichia coli bioproduction. Although 13 C-metabolic flux analysis ( 13 C-MFA) has the potential to evaluate NOG flux distribution in vivo , the precision of these estimates depends on the labeling patterns of glucose tracers. Because E. coli has multiple native glycolysis pathways, selecting the optimal glucose tracer is important for precise estimates. This study used simulations to evaluate the performance of 18 commercially available glucose tracers in precisely predicting NOG flux. We artificially generated flux distributions of central metabolic pathways, including three types of NOG pathways, and obtained 13 C labeling patterns of amino acids metabolized from each glucose tracer. Using these data, we then calculated 95% confidence intervals (CIs) for NOG pathway fluxes. Comparing the sum of CI widths from three NOG fluxes showed that estimation with [1,3- 13 C]-glucose yielded the narrowest CIs. Several tracers, including [2,3- 13 C]glucose, were capable of determining fluxes with high precision, but [1- 13 C]glucose was not one of them, despite often being used for estimating glycolytic fluxes. We then experimentally evaluated [2,3- 13 C]- and [1- 13 C]glucose as tracers in E. coli strains with and without the expression of phosphoketolase, which is required for NOG pathways to function. The results suggested that [1- 13 C]glucose could not detect NOG fluxes, whereas [2,3- 13 C]glucose estimated the fluxes of all three NOG pathways with narrow CIs.
Institution: The University of Osaka
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: リボゾーム結合部位配列の改変による大腸菌代謝フラックスの制御と物質生産への応用, High performance microbial cell factories development by model based metabolic design and adaptive laboratory evolution, G4141038795, バイオ製造とグローバルバイオエコノミー実現に向けた信頼性および拡張性の高いバイオファウンドリ国際共同研究拠点, 多様な微生物機能の開拓のためのバイオものづくりDBTL技術の開発, Development of metabolic reactivation techniques based on optogenetics
OpenAlex ID: W7225414525