• Medientyp: E-Artikel
  • Titel: One‐shot 13C15N‐metabolic flux analysis for simultaneous quantification of carbon and nitrogen flux
  • Beteiligte: Borah Slater, Khushboo; Beyß, Martin; Xu, Ye; Barber, Jim; Costa, Catia; Newcombe, Jane; Theorell, Axel; Bailey, Melanie J; Beste, Dany J V; McFadden, Johnjoe; Nöh, Katharina
  • Erschienen: Springer Science and Business Media LLC, 2023
  • Erschienen in: Molecular Systems Biology
  • Sprache: Englisch
  • DOI: 10.15252/msb.202211099
  • ISSN: 1744-4292
  • Schlagwörter: Applied Mathematics ; Computational Theory and Mathematics ; General Agricultural and Biological Sciences ; General Immunology and Microbiology ; General Biochemistry, Genetics and Molecular Biology ; Information Systems
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  • Beschreibung: <jats:title>Abstract</jats:title><jats:p>Metabolic flux is the final output of cellular regulation and has been extensively studied for carbon but much less is known about nitrogen, which is another important building block for living organisms. For the tuberculosis pathogen, this is particularly important in informing the development of effective drugs targeting the pathogen's metabolism. Here we performed <jats:sup>13</jats:sup>C<jats:sup>15</jats:sup>N dual isotopic labeling of <jats:italic>Mycobacterium bovis</jats:italic> BCG steady state cultures, quantified intracellular carbon and nitrogen fluxes and inferred reaction bidirectionalities. This was achieved by model scope extension and refinement, implemented in a multi‐atom transition model, within the statistical framework of Bayesian model averaging (BMA). Using BMA‐based <jats:sup>13</jats:sup>C<jats:sup>15</jats:sup>N‐metabolic flux analysis, we jointly resolve carbon and nitrogen fluxes quantitatively. We provide the first nitrogen flux distributions for amino acid and nucleotide biosynthesis in mycobacteria and establish glutamate as the central node for nitrogen metabolism. We improved resolution of the notoriously elusive anaplerotic node in central carbon metabolism and revealed possible operation modes. Our study provides a powerful and statistically rigorous platform to simultaneously infer carbon and nitrogen metabolism in any biological system.</jats:p>
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