Bayesian multi-model-based 13C15N-metabolic flux analysis quantifies carbon-nitrogen metabolism in mycobacteria

Khushboo Borah, Martin Bey, Ye Xu, Jim Barber, Catia Costa, Jane Newcombe, Axel Theorell, Melanie J Bailey, Dany JV Beste, Johnjoe McFadden,* Katharina Nöh
bioRxiv preprint
AI/ML Published: (Mar/2022)
DOI: https://doi.org/10.1101/2022.03.08.483448
Abstract:

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 pathogen Mycobacterium tuberculosis (Mtb), this is particularly important in informing the development of effective drugs targeting Mtb’s metabolism. Here we performed 13C15N dual isotopic labelling of mycobacterial steady state cultures and quantified intracellular carbon-nitrogen (CN) and nitrogen (N) fluxes in addition to carbon (C) fluxes and inferred their reaction bidirectionalities. The combination of 13C15N-MFA with a Bayesian multi-model approach allowed us to resolve C and N fluxes simultaneously which was not possible with classical 13C-MFA. We quantified CN fluxes for amino acid and, for the first time, nucleotide biosynthesis. Our analysis identified glutamate as the central CN and N node in mycobacteria, and improved resolution of the anaplerotic node. Our study describes a powerful platform to measure carbon and nitrogen metabolism in any biological system with statistical rigor.

Leave a comment