Multi-Species, Genome-Wide Metabolic Network Reconstructions Reveal the Basis for Metabolic Versatility in Mycobacteria
- 1Centre Inria de l'Université Grenoble Alpes
Abstract
The genus Mycobacterium comprises over 200 species, many of which now have complete genome sequences. Some are major pathogens causing diseases like tuberculosis and leprosy, while others are harmless environmental organisms with useful abilities such as degrading pollutants. Environmental mycobacteria are often seen as metabolic generalists, able to utilise a wider range of carbon sources than host-associated species, which are typically more specialised due to their restricted habitats. This metabolic versatility has been proposed to stem from differences in nutrient uptake capabilities rather than catabolic pathways. In order to test this explanation, we developed and validated genome-scale metabolic models for five Mycobacterium species with varying lifestyles and growth rates, creating a computational approach enabled by CarveMe that allows rapid construction of models from genome information. By combining these models with microbiology experiments the study showed that the capacity of the bacteria to transport nutrients into the cell is indeed key to metabolic versatility. We notably found through load-partition experiments that, if a transporter is present but cannot take up its substrate at a rate sufficient for growth, the supply of multiple substrates can mitigate this rate-limiting step. This suggests that mycobacterial species have evolved high-affinity, low-rate systems for nutrient uptake in their ecological niches. More generally, our results demonstrate that a combination of automated annotation methods and straightforward bacterial physiology experiments allow the reconstruction of metabolic models of good predictive quality for hitherto little studied mycobacterial species.
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BibTeX
@misc{aguirre2026multispecies,
title = {{Multi-Species, Genome-Wide Metabolic Network Reconstructions Reveal the Basis for Metabolic Versatility in Mycobacteria}},
author = {I. Cancino Aguirre and M. Priya and A. Garza-Garcia and L. P. S. de Carvalho and H. de Jong and D. Ropers},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.02.748904},
url = {https://www.biorxiv.org/content/10.64898/2026.09.02.748904v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Multi-Species, Genome-Wide Metabolic Network Reconstructions Reveal the Basis for Metabolic Versatility in Mycobacteria
AU - I. Cancino Aguirre
AU - M. Priya
AU - A. Garza-Garcia
AU - L. P. S. de Carvalho
AU - H. de Jong
AU - D. Ropers
PY - 2026
DA - 2026/09/02
PB - bioRxiv
DO - 10.64898/2026.09.02.748904
UR - https://www.biorxiv.org/content/10.64898/2026.09.02.748904v1
AB - The genus Mycobacterium comprises over 200 species, many of which now have complete genome sequences. Some are major pathogens causing diseases like tuberculosis and leprosy, while others are harmless environmental organisms with useful abilities such as degrading pollutants. Environmental mycobacteria are often seen as metabolic generalists, able to utilise a wider range of carbon sources than host-associated species, which are typically more specialised due to their restricted habitats. This metabolic versatility has been proposed to stem from differences in nutrient uptake capabilities rather than catabolic pathways. In order to test this explanation, we developed and validated genome-scale metabolic models for five Mycobacterium species with varying lifestyles and growth rates, creating a computational approach enabled by CarveMe that allows rapid construction of models from genome information. By combining these models with microbiology experiments the study showed that the capacity of the bacteria to transport nutrients into the cell is indeed key to metabolic versatility. We notably found through load-partition experiments that, if a transporter is present but cannot take up its substrate at a rate sufficient for growth, the supply of multiple substrates can mitigate this rate-limiting step. This suggests that mycobacterial species have evolved high-affinity, low-rate systems for nutrient uptake in their ecological niches. More generally, our results demonstrate that a combination of automated annotation methods and straightforward bacterial physiology experiments allow the reconstruction of metabolic models of good predictive quality for hitherto little studied mycobacterial species.
ER -