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During most infections, the population of immune cells known as macrophages are key to taking up and killing bacteria as an integral part of the immune response. However, during infection with Mycobacterium tuberculosis (Mtb), host macrophages serve as the preferred environment for mycobacterial growth. Further, killing of Mtb by macrophages is impaired unless they become activated. Activation is induced by stimulation from bacterial antigens and inflammatory cytokines derived from helper T cells. The key macrophage-activating cytokines in Mtb infection are tumor necrosis factor-alpha (TNF) and interferon (IFN)-gamma. Due to differences in cellular sources and secretion pathways for TNF and IFN-gamma, the possibility of heterogeneous cytokine distributions exists, suggesting that the timing of macrophage activation from these signals may affect activation kinetics and thus impact the outcome of Mtb infection. Here we use a mathematical model to show that negative feedback from production of nitric oxide (the key mediator of mycobacterial killing) that typically optimizes macrophage responses to activating stimuli may reduce effective killing of Mtb. Statistical sensitivity analysis predicts that if TNF and IFN-gamma signals precede infection, the level of negative feedback may have a strong effect on how effectively macrophages kill Mtb. However, this effect is relaxed when IFN-gamma or TNF+IFN-gamma signals are received coincident with infection. Under these conditions, the model suggests that negative feedback induces fast responses and an initial overshoot of nitric oxide production for given doses of TNF and IFN-gamma, favoring killing of Mtb. Together, our results suggest that direct entry of macrophages into a granuloma site (and not distal to it) from lung vascular sources represents a preferred host strategy for mycobacterial control. We examine implications of these results in establishment of latent Mtb infection.

Pathogen killing is one of the primary roles of macrophages, utilizing potent effectors such as nitric oxide (NO) and involving other cellular machinery including iron regulatory apparatus. Macrophages become strongly activated upon receipt of appropriate signaling with cytokines and pathogen-derived endotoxins. However, they must resist activation in the absence of decisive signaling due to the energetic demands of activation coupled with the toxic nature of effector molecules to surrounding tissues. We have developed a mathematical model of the modular biochemical network of macrophages involved with activation, pathogen killing and iron regulation. This model requires synergistic interaction of multiple activation signals to overcome the quiescent state. To achieve a trade-off between macrophage quiescence and activation, strong activation signals are modulated via negative regulation by NO. In this way a single activation signal is insufficient for complete activation. In addition, our results suggest that iron regulation is usually controlled by activation signals. However, under conditions of partial macrophage activation, exogenous iron levels play a key role in regulating NO production. This model will be useful for evaluating macrophage control of intracellular pathogens in addition to the biochemical mechanisms examined here.