Simeone Marino

A Methodology For Performing Global Uncertainty And Sensitivity Analysis In Systems Biology

Accuracy of results from mathematical and computer models of biological systems is often complicated by the presence of uncertainties in experimental data that are used to estimate parameter values. Current mathematical modeling approaches typically use either single-parameter or local sensitivity analyses. However, these methods do not accurately assess uncertainty and sensitivity in the system as, by default, they hold all other parameters fixed at baseline values. Using techniques described within we demonstrate how a multi-dimensional parameter space can be studied globally so all uncertainties can be identified. Further, uncertainty and sensitivity analysis techniques can help to identify and ultimately control uncertainties. In this work we develop methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models. We compare two specific types of global sensitivity analysis indexes that have proven to be among the most robust and efficient. Through familiar and new examples of mathematical and computer models, we provide a complete methodology for performing these analyses, in both deterministic and stochastic settings, and propose novel techniques to handle problems encountered during these types of analyses.

Microenvironments in Tuberculous Granulomas Are Delineated by Distinct Populations of Macrophage Subsets and Expression of Nitric Oxide Synthase and Arginase Isoforms

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.

Tumor Necrosis Factor Blockade in Chronic Murine Tuberculosis Enhances Granulomatous Inflammation and Disorganizes Granulomas in the Lungs

ABSTRACT Tumor necrosis factor (TNF) is a prototypic proinflammatory cytokine that contributes significantly to the development of immunopathology in various disease states. A complication of TNF blockade therapy, which is used increasingly for the treatment of chronic inflammatory diseases, is the reactivation of latent tuberculosis. This study used a low-dose aerogenic model of murine tuberculosis to analyze the effect of TNF neutralization on disease progression in mice with chronic tuberculous infections. Histological, immunohistochemical, and flow cytometric analyses of Mycobacterium tuberculosis-infected lung tissues revealed that the neutralization of TNF results in marked disorganization of the tuberculous granuloma, as demonstrated by the dissolution of the previously described B-cell-macrophage unit in granulomatous tissues as well as by increased inflammatory cell infiltration. Quantitative gene expression studies using laser capture microdissected granulomatous lung tissues revealed that TNF blockade in mice chronically infected with M. tuberculosis leads to the enhanced expression of specific proinflammatory molecules. Collectively, these studies have provided evidence suggesting that in the chronic phase of M. tuberculosis infection, TNF is essential for maintaining the structure of the tuberculous granuloma and may regulate the granulomatous response by exerting an anti-inflammatory effect through modulation of the expression of proinflammatory mediators.

Multiscale computational modeling reveals a critical role for TNF-α receptor 1 dynamics in tuberculosis granuloma formation

Multiple immune factors control host responses to Mycobacterium tuberculosis infection, including the formation of granulomas, which are aggregates of immune cells whose function may reflect success or failure of the host to contain infection. One such factor is TNF-α. TNF-α has been experimentally characterized to have the following activities in M. tuberculosis infection: macrophage activation, apoptosis, and chemokine and cytokine production. Availability of TNF-α within a granuloma has been proposed to play a critical role in immunity to M. tuberculosis. However, in vivo measurement of a TNF-α concentration gradient and activities within a granuloma are not experimentally feasible. Further, processes that control TNF-α concentration and activities in a granuloma remain unknown. We developed a multiscale computational model that includes molecular, cellular, and tissue scale events that occur during granuloma formation and maintenance in lung. We use our model to identify processes that regulate TNF-α concentration and cellular behaviors and thus influence the outcome of infection within a granuloma. Our model predicts that TNF-αR1 internalization kinetics play a critical role in infection control within a granuloma, controlling whether there is clearance of bacteria, excessive inflammation, containment of bacteria within a stable granuloma, or uncontrolled growth of bacteria. Our results suggest that there is an interplay between TNF-α and bacterial levels in a granuloma that is controlled by the combined effects of both molecular and cellular scale processes. Finally, our model elucidates processes involved in immunity to M. tuberculosis that may be new targets for therapy.

Dendritic Cell Trafficking and Antigen Presentation in the Human Immune Response to Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) is an extraordinarily successful human pathogen, one of the major causes of death by infectious disease worldwide. A key issue for the study of tuberculosis is to understand why individuals infected with Mtb experience different clinical outcomes. To better understand the dynamics of Mtb infection and immunity, we coupled nonhuman primate experiments with a mathematical model we previously developed that qualitatively and quantitatively captures important processes of cellular priming and activation. These processes occur between the lung and the nearest draining lymph node where the key cells mediating this process are the dendritic cells (DC). The nonhuman primate experiments consist of bacteria and cell numbers from tissues of 17 adult cynomolgus macaques (Macaca fascicularis) that were infected with Mtb strain Erdman (∼25 CFU/animal via bronchoscope). The main result of this work is that delays in either DC migration to the draining lymph node or T cell trafficking to the site of infection can alter the outcome of Mtb infection, defining progression to primary disease or latent infection and reactivated tuberculosis. Our results also support the idea that the development of a new generation of treatment against Mtb should optimally elicit a fast DC turnover at the site of infection, as well as strong activation of DCs for maximal Ag presentation and production of key cytokines. This will induce the most protective T cell response.

Variability in Tuberculosis Granuloma T Cell Responses Exists, but a Balance of Pro- and Anti-inflammatory Cytokines Is Associated with Sterilization

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.

Differences in reactivation of tuberculosis induced from anti-TNF treatments are based on bioavailability in granulomatous tissue.

The immune response to Mycobacterium tuberculosis (Mtb) infection is complex. Experimental evidence has revealed that tumor necrosis factor (TNF) plays a major role in host defense against Mtb in both active and latent phases of infection. TNF-neutralizing drugs used to treat inflammatory disorders have been reported to increase the risk of tuberculosis (TB), in accordance with animal studies. The present study takes a computational approach toward characterizing the role of TNF in protection against the tubercle bacillus in both active and latent infection. We extend our previous mathematical models to investigate the roles and production of soluble (sTNF) and transmembrane TNF (tmTNF). We analyze effects of anti-TNF therapy in virtual clinical trials (VCTs) by simulating two of the most commonly used therapies, anti-TNF antibody and TNF receptor fusion, predicting mechanisms that explain observed differences in TB reactivation rates. The major findings from this study are that bioavailability of TNF following anti-TNF therapy is the primary factor for causing reactivation of latent infection and that sTNF—even at very low levels—is essential for control of infection. Using a mathematical model, it is possible to distinguish mechanisms of action of the anti-TNF treatments and gain insights into the role of TNF in TB control and pathology. Our study suggests that a TNF-modulating agent could be developed that could balance the requirement for reduction of inflammation with the necessity to maintain resistance to infection and microbial diseases. Alternatively, the dose and timing of anti-TNF therapy could be modified. Anti-TNF therapy will likely lead to numerous incidents of primary TB if used in areas where exposure is likely.

TNF and IL-10 are major factors in modulation of the phagocytic cell environment in lung and lymph node in tuberculosis: a next-generation two-compartmental model.

Tuberculosis (TB) is one of the earliest recorded human diseases and still one of the deadliest worldwide. Its causative agent is the bacteria Mycobacterium tuberculosis (Mtb). Cytokine-mediated macrophage activation is a necessary step in control of bacterial growth, and early immunologic events in lymph node and lung are crucial to the outcome of infection, although the factors that influence these environments and the immune response are poorly understood. Our goal is to build the next-generation two-compartmental model of the immune response to provide a gateway to more spatial and mechanistic investigations of M. tuberculosis infection in the LN and lung. Crucial immune factors emerge that affect macrophage populations and inflammation, namely TNF-dependent recruitment and apoptosis, and IL-10 levels. Surprisingly, bacterial load plays a less important role than TNF in increasing the population of infected macrophages and inflammation. Using a mathematical model, it is possible to distinguish the effects of pro-inflammatory (TNF) and anti-inflammatory (IL-10) cytokines on the spectrum of phagocyte populations (macrophages and dendritic cells) in the lung and lymph node. Our results suggest that TNF is a major mediator of recruitment of phagocytes to the lungs. In contrast, IL-10 plays a role in balancing the dominant macrophage phenotype in LN and lung.

Intracellular bacillary burden reflects a burst size for Mycobacterium tuberculosis in vivo

We previously reported that Mycobacterium tuberculosis triggers macrophage necrosis in vitro at a threshold intracellular load of ∼25 bacilli. This suggests a model for tuberculosis where bacilli invading lung macrophages at low multiplicity of infection proliferate to burst size and spread to naïve phagocytes for repeated cycles of replication and cytolysis. The current study evaluated that model in vivo, an environment significantly more complex than in vitro culture. In the lungs of mice infected with M. tuberculosis by aerosol we observed three distinct mononuclear leukocyte populations (CD11b− CD11c+/hi, CD11b+/lo CD11clo/−, CD11b+/hi CD11c+/hi) and neutrophils hosting bacilli. Four weeks after aerosol challenge, CD11b+/hi CD11c+/hi mononuclear cells and neutrophils were the predominant hosts for M. tuberculosis while CD11b+/lo CD11clo/− cells assumed that role by ten weeks. Alveolar macrophages (CD11b− CD11c+/hi) were a minority infected cell type at both time points. The burst size model predicts that individual lung phagocytes would harbor a range of bacillary loads with most containing few bacilli, a smaller proportion containing many bacilli, and few or none exceeding a burst size load. Bacterial load per cell was enumerated in lung monocytic cells and neutrophils at time points after aerosol challenge of wild type and interferon-γ null mice. The resulting data fulfilled those predictions, suggesting a median in vivo burst size in the range of 20 to 40 bacilli for monocytic cells. Most heavily burdened monocytic cells were nonviable, with morphological features similar to those observed after high multiplicity challenge in vitro: nuclear condensation without fragmentation and disintegration of cell membranes without apoptotic vesicle formation. Neutrophils had a narrow range and lower peak bacillary burden than monocytic cells and some exhibited cell death with release of extracellular neutrophil traps. Our studies suggest that burst size cytolysis is a major cause of infection-induced mononuclear cell death in tuberculosis.

Macrophage Polarization Drives Granuloma Outcome during Mycobacterium tuberculosis Infection

ABSTRACT 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 for M. tuberculosis infection 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 M1 polarization early during infection and to improve outcome.