Abstract
The microorganisms constituting the Mycobacterium tuberculosis complex are associated with important human and animal diseases. Mycobacterium tuberculosis is estimated to infect a third of the world’s population whilst Mycobacterium bovis is a zoonotic pathogen primarily infecting cattle and other livestock. M. bovis is thought to have evolved from a M. tuberculosis-like ancestor and is itself the ancestor of the BCG vaccine strain, Mycobacterium bovis BCG. These mycobacteria demonstrate distinct differences in virulence, host range and metabolism, but the role of metabolic differences in pathogenicity is unknown. Systems biology approaches have previously been applied to investigate the metabolism of M. tuberculosis but not to probe differences between strains within the complex. Genome scale metabolic networks of M. bovis and M. bovis BCG were constructed based on genome annotation, biochemical data and detailed bioinformatics analyses. The networks (in parallel with an updated M. tuberculosis network) were interrogated by flux balance analysis to predict growth rates, substrate utilisation and gene essentiality, with the predictions compared against high-throughput phenotype and published gene essentiality data. The models correctly predicted 87-91% of substrate utilisation data, 75-77% of gene essentiality data and in silico-predicted growth rates closely corresponded with in vitro-measured substrate consumption and growth rates. The comparisons also revealed discrepancies between in silico predictions and in vitro data, highlighting areas of incomplete metabolic knowledge. Several of these discrepancies were examined by experimental studies revealing novel insights into metabolism that may be relevant to mycobacterial pathogenicity. Information discovered from the analysis of these models, along with additional published literature, was used to update and expand the original networks. These networks also successfully simulate many aspects of the growth and physiology of the M. tuberculosis, M. bovis and M. bovis BCG strains and provide an invaluable tool for their study.