Multiscale Model of Mycobacterium tuberculosis Infection Maps Metabolite and Gene Perturbations to Granuloma Sterilization Predictions
Granulomas are a hallmark of tuberculosis. Inside granulomas, the pathogenMycobacterium tuberculosismay enter a metabolically inactive state that is less susceptible to antibiotics. UnderstandingM. tuberculosismetabolism within granulomas could contribute to reducing the lengthy treatment required for tuberculosis and provide additional targets for new drugs. Two key adaptations ofM. tuberculosisare a nonreplicating phenotype and accumulation of lipid inclusions in response to hypoxic conditions. To explore how these adaptations influence granuloma-scale outcomesin vivo, we present a multiscalein silicomodel of granuloma formation in tuberculosis. The model comprises host immunity,M. tuberculosismetabolism,M. tuberculosisgrowth adaptation to hypoxia, and nutrient diffusion. We calibrated our model toin vivodata from nonhuman primates and rabbits and apply the model to predictM. tuberculosispopulation dynamics and heterogeneity within granulomas. We found that bacterial populations are highly dynamic throughout infection in response to changing oxygen levels and host immunity pressures. Our results indicate that a nonreplicating phenotype, but not lipid inclusion formation, is important for long-termM. tuberculosissurvival in granulomas. We used virtualM. tuberculosisknockouts to predict the impact of both metabolic enzyme inhibitors and metabolic pathways exploited to overcome inhibition. Results indicate that knockouts whose growth rates are below ∼66% of the wild-type growth rate in a culture medium featuring lipid as the only carbon source are unable to sustain infections in granulomas. By mapping metabolite- and gene-scale perturbations to granuloma-scale outcomes and predicting mechanisms of sterilization, our method provides a powerful tool for hypothesis testing and guiding experimental searches for novel antituberculosis interventions.