Central Metabolism and Growth Rate Impacts on Hydrogen and Carbon Isotope Fractionation During Amino Acid Synthesis in E. coli - Smith, Derek A.; Nakamoto, Bobby James; Suess, Melanie K.; Fogel, Marilyn L. (Frontiers in Microbiology, 2022)
Compound specific stable isotope analysis (CSIA) of amino acids from bacterial biomass is a newly emerging powerful tool for exploring central carbon metabolism pathways and fluxes. By comparing isotopic values and fractionations relative to water and growth substrate, the impact of variable flow path for metabolites through different central metabolic pathways, perturbations of these paths, and their resultant consequences on intracellular pools and resultant biomass may be elucidated. Here, we explore the effects that central carbon metabolism and growth rate can have on stable hydrogen (δ2H) and carbon (δ13C) compound specific isotopic values of amino acids, and whether diagnostic isotopic fingerprints are revealed by these paired analyses. We measured δ2H and δ13C in amino acids in the wild type Escherichia coli (MG1655) across a range of growth rates in chemostat cultures to address the unknown isotopic consequences as metabolic fluxes are shuffled between catabolic and anabolic metabolisms. Additionally, two E. coli knockout mutants, one with deficiency in glycolysis –pgi (LC1888) and another inhibiting the oxidative pentose phosphate pathway (OPPP) –zwf (LC1889), were grown on glucose and used as a comparison against the wild type E. coli (MG1655) to address the isotopic changes of amino acids produced in these perturbed metabolic pathways. Amino acid δ2H values, which collectively vary in composition by more than 400 ‰, are altered along with δ13C values demonstrating fundamental shifts in central metabolic pathways and/or fluxes. Within our linear discriminant analysis with a simple model organism to examine potential amino acid fingerprinting, our knockout strains and variable growth rate samples plot across a wider array of organism classification than merely within the boundaries of other bacterial data.