Lung granulomas are the pathologic hallmark of tuberculosis (TB). T cells are a major cellular component of TB lung granulomas and are known to play an important role in containment of Mycobacterium tuberculosis (Mtb) infection. We used cynomolgus macaques, a non-human primate model that recapitulates human TB with clinically active disease, latent infection or early infection, to understand functional characteristics and dynamics of T cells in individual granulomas. We sought to correlate T cell cytokine response and bacterial burden of each granuloma, as well as granuloma and systemic responses in individual animals. Our results support that each granuloma within an individual host is independent with respect to total cell numbers, proportion of T cells, pattern of cytokine response, and bacterial burden. The spectrum of these components overlaps greatly amongst animals with different clinical status, indicating that a diversity of granulomas exists within an individual host. On average only about 8% of T cells from granulomas respond with cytokine production after stimulation with Mtb specific antigens, and few “multi-functional” T cells were observed. However, granulomas were found to be “multi-functional” with respect to the combinations of functional T cells that were identified among lesions from individual animals. Although the responses generally overlapped, sterile granulomas had modestly higher frequencies of T cells making IL-17, TNF and any of T-1 (IFN-γ, IL-2, or TNF) and/or T-17 (IL-17) cytokines than non-sterile granulomas. An inverse correlation was observed between bacterial burden with TNF and T-1/T-17 responses in individual granulomas, and a combinatorial analysis of pair-wise cytokine responses indicated that granulomas with T cells producing both pro- and anti-inflammatory cytokines (e.g. IL-10 and IL-17) were associated with clearance of Mtb. Preliminary evaluation suggests that systemic responses in the blood do not accurately reflect local T cell responses within granulomas. The characteristic feature of Mycobacterium tuberculosis (Mtb) infection is the formation of lesions, which are organized structures of immune cells in the lungs called granulomas, which contain the bacteria. When the granuloma functions effectively, it can kill the bacteria. T cells (a type of immune cell, also present in granulomas) are known to play an important role in control of tuberculosis. However, functions of T cells at individual granuloma levels are unknown. Here, we studied the functional characteristics of T cells, which are defined by the production of chemical messengers (cytokines) at the granuloma level in a non-human primate model. We compared the relationship between cytokine response and the number of bacteria (Mtb) in each granuloma. Each granuloma was found to be unique, suggesting different types exist within an animal. Only a small proportion of T cells produced any cytokine, but different types of cytokines were observed within each granuloma. A balance between different types of cytokine was associated with more killing of bacteria in granulomas. Understanding how to improve the T cell responses to obtain killing of bacteria in the granuloma will be important for vaccine development.

Macrophages in granulomas are both antimycobacterial effector and host cell for Mycobacterium tuberculosis, yet basic aspects of macrophage diversity and function within the complex structures of granulomas remain poorly understood. To address this, we examined myeloid cell phenotypes and expression of enzymes correlated with host defense in macaque and human granulomas. Macaque granulomas had upregulated inducible and endothelial NO synthase (iNOS and eNOS) and arginase (Arg1 and Arg2) expression and enzyme activity compared with nongranulomatous tissue. Immunohistochemical analysis indicated macrophages adjacent to uninvolved normal tissue were more likely to express CD163, whereas epithelioid macrophages in regions where bacteria reside strongly expressed CD11c, CD68, and HAM56. Calprotectin-positive neutrophils were abundant in regions adjacent to caseum. iNOS, eNOS, Arg1, and Arg2 proteins were identified in macrophages and localized similarly in granulomas across species, with greater eNOS expression and ratio of iNOS/Arg1 expression in epithelioid macrophages as compared with cells in the lymphocyte cuff. iNOS, Arg1, and Arg2 expression in neutrophils was also identified. The combination of phenotypic and functional markers support that macrophages with anti-inflammatory phenotypes localized to outer regions of granulomas, whereas the inner regions were more likely to contain macrophages with proinflammatory, presumably bactericidal, phenotypes. Together, these data support the concept that granulomas have organized microenvironments that balance antimicrobial anti-inflammatory responses to limit pathology in the lungs.

Immune responses to pathogens are complex and not well understood in many diseases, and this is especially true for infections by persistent pathogens. One mechanism that allows for long‐term control of infection while also preventing an over‐zealous inflammatory response from causing extensive tissue damage is for the immune system to balance pro‐ and anti‐inflammatory cells and signals. This balance is dynamic and the immune system responds to cues from both host and pathogen, maintaining a steady state across multiple scales through continuous feedback. Identifying the signals, cells, cytokines, and other immune response factors that mediate this balance over time has been difficult using traditional research strategies. Computational modeling studies based on data from traditional systems can identify how this balance contributes to immunity. Here we provide evidence from both experimental and mathematical/computational studies to support the concept of a dynamic balance operating during persistent and other infection scenarios. We focus mainly on tuberculosis, currently the leading cause of death due to infectious disease in the world, and also provide evidence for other infections. A better understanding of the dynamically balanced immune response can help shape treatment strategies that utilize both drugs and host‐directed therapies.

Significance: The colonization of the intestinal track by the trillions of bacteria that live in the gut (i.e., the gut microbiome) is a dynamic process. Through the use of next-generation sequencing and mathematical models, we were able to quantify the interpopulation interactions that occurred after a germfree mouse was inoculated with a murine microbiome. This approach was significant because we were able to quantify these interactions in vivo without the use of cultivation. Although colonization is most commonly associated with the development of a neonate’s microbiome, understanding the ecological mechanisms involved in the successional process is critical to understanding the recovery of the microbiome following antibiotic therapies, changes in diet, and shifts in health.

Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), induces formation of granulomas, structures in which immune cells and bacteria colocalize. Macrophages are among the most abundant cell types in granulomas and have been shown to serve as both critical bactericidal cells and targets forM. tuberculosisinfection and proliferation throughout the course of infection. Very little is known about how these processes are regulated, what controls macrophage microenvironment-specific polarization and plasticity, or why some granulomas control bacteria and others permit bacterial dissemination. We take a computational-biology approach to investigate mechanisms that drive macrophage polarization, function, and bacterial control in granulomas. We define a “macrophage polarization ratio” as a metric to understand how cytokine signaling translates into polarization of single macrophages in a granuloma, which in turn modulates cellular functions, including antimicrobial activity and cytokine production. Ultimately, we extend this macrophage ratio to the tissue scale and define a “granuloma polarization ratio” describing mean polarization measures for entire granulomas. Here we coupled experimental data from nonhuman primate TB granulomas to our computational model, and we predict two novel and testable hypotheses regarding macrophage profiles in TB outcomes. First, the temporal dynamics of granuloma polarization ratios are predictive of granuloma outcome. Second, stable necrotic granulomas with low CFU counts and limited inflammation are characterized by short NF-κB signal activation intervals. These results suggest that the dynamics of NF-κB signaling is a viable therapeutic target to promote M₁polarization early during infection and to improve outcome.