Low Levels of T Cell Exhaustion in Tuberculous Lung Granulomas

Unraveling the role of the immune landscape in tuberculosis granuloma

Despite significant advances in research over the past century, Tuberculosis (TB) remains a formidable global health concern. TB granulomas are organized structures composed of immune cells, that serve as the body's primary defense against the spread of Mycobacterium tuberculosis (Mtb). The immune landscape of TB granulomas involves a complex array of immune cells, including CD4+ and CD8+ T cells, B cells, NK cells, and others, which collectively influence the fate of the granuloma. B cells contribute to the formation of the granuloma's germinal center, while the functional state of T cells-particularly their ability to control infection-dictates whether the granuloma is controlling or proliferative. The intricate interplay between T cells and the dynamic microenvironment of the granuloma plays a pivotal role in determining the outcome of the infection. However, several aspects of the immunological basis of tuberculosis are still unknown. This review delves into the immunological landscape of TB granuloma, focusing on the dynamic cellular interplay within the granuloma and its profound influence on disease pathogenesis.

CD226 identifies effector CD8+ T cells during tuberculosis and costimulates recognition of Mycobacterium tuberculosis-infected macrophages

CD8+ T cells defend against Mycobacterium tuberculosis (Mtb) infection but variably recognize Mtb-infected macrophages. To define how the diversity of lung parenchymal CD8+ T cells changes during chronic infection, cells from C57BL/6J mice infected for 6- and 41-weeks were analyzed by scRNA-seq. We identified an effector lineage, including a cluster that expresses high levels of cytotoxic effectors and cytokines, and dysfunctional lineage that transcriptionally resembles exhausted T cells. The most significant differentially expressed gene between two distinct CD8+ T cell lineages is CD226. Mtb-infected IFNγ-eYFP reporter mice revealed IFNγ production is enriched in CD226+CD8+ T cells, confirming these as functional T cells in vivo. Purified CD226+ but not CD226- CD8+ T cells recognize Mtb-infected macrophages, and CD226 blockade inhibits IFNγ and granzyme B production. Thus, CD226 costimulation is required for efficient CD8+ T cell recognition of Mtb-infected macrophages, and its expression identifies CD8+ T cells that recognize Mtb-infected macrophages.

Disseminated tuberculosis is associated with impaired T cell immunity mediated by non-canonical NF-κB pathway

OBJECTIVES

The mechanism that leads to disseminated tuberculosis in HIV-negative patients is still largely unknown. T cell subsets and signaling pathways that were associated with disseminated tuberculosis were investigated.

METHODS

Single-cell profiling of whole T cells was performed to identify T cell subsets and enriched signaling pathways that were associated with disseminated tuberculosis. Flow cytometric analysis and blocking experiment were used to investigate the findings obtained by transcriptome sequencing.

RESULTS

Patients with disseminated tuberculosis had depleted Th1, Tc1 and Tc17 cell subsets, and IFNG was the most down-regulated gene in both CD4 and CD8 T cells. Gene Ontology analysis showed that non-canonical NF-κB signaling pathway, including NFKB2 and RELB genes, was significantly down-regulated and was probably associated with disseminated tuberculosis. Expression of several TNF superfamily ligands and receptors, such as LTA and TNF genes, were suppressed in patients with disseminated tuberculosis. Blocking of TNF-α and soluble LTα showed that TNF-α was involved in IFN-γ production and LTα influenced TNF-α expression in T cells.

CONCLUSIONS

Impaired T cell IFN-γ response mediated by suppression of TNF and non-canonical NF-κB signaling pathways might be responsible for disseminated tuberculosis.

LILRB1-HLA-G axis defines a checkpoint driving natural killer cell exhaustion in tuberculosis

Chronic infections, including Mycobacterium tuberculosis (Mtb)-caused tuberculosis (TB), can induce host immune exhaustion. However, the key checkpoint molecules involved in this process and the underlying regulatory mechanisms remain largely undefined, which impede the application of checkpoint-based immunotherapy in infectious diseases. Here, through adopting time-of-flight mass cytometry and transcriptional profiling to systematically analyze natural killer (NK) cell surface receptors, we identify leukocyte immunoglobulin like receptor B1 (LILRB1) as a critical checkpoint receptor that defines a TB-associated cell subset (LILRB1+ NK cells) and drives NK cell exhaustion in TB. Mechanistically, Mtb-infected macrophages display high expression of human leukocyte antigen-G (HLA-G), which upregulates and activates LILRB1 on NK cells to impair their functions by inhibiting mitogen-activated protein kinase (MAPK) signaling via tyrosine phosphatases SHP1/2. Furthermore, LILRB1 blockade restores NK cell-dependent anti-Mtb immunity in immuno-humanized mice. Thus, LILRB1-HLA-G axis constitutes a NK cell immune checkpoint in TB and serves as a promising immunotherapy target.

Integrated single-cell transcriptome and T cell receptor profiling reveals defects of T cell exhaustion in pulmonary tuberculosis

Tuberculosis-affected lungs with chronic inflammation harbor abundant immunosuppressive immune cells but the nature of such inflammation is unclear. Dysfunction in T cell exhaustion, while implicated in chronic inflammatory diseases, remains unexplored in tuberculosis. Given that immunotherapy targeting exhaustion checkpoints exacerbates tuberculosis, we speculate that T cell exhaustion is dysfunctional in tuberculosis. Using integrated single-cell RNA sequencing and T cell receptor profiling we reported defects in exhaustion responses within inflamed tuberculosis-affected lungs. Tuberculosis lungs demonstrated significantly reduced levels of exhausted CD8+ T cells and exhibited diminished expression of exhaustion-related transcripts among clonally expanded CD4+ and CD8+ T cells. Additionally, clonal expansion of CD4+ and CD8+ T cells bearing T cell receptors specific for CMV was observed. Expanded CD8+ T cells expressed the cytolytic marker GZMK. Hence, inflamed tuberculosis-affected lungs displayed dysfunction in T cell exhaustion. Our findings likely hold implications for understanding the reactivation of tuberculosis observed in patients undergoing immunotherapy targeting the exhaustion checkpoint.

Use of Individual-Based Mathematical Modelling to Understand More About Antibiotic Resistance Within-Host

To model complex systems, individual-based models (IBMs), sometimes called "agent-based models" (ABMs), describe a simplification of the system through an adequate representation of the elements. IBMs simulate the actions and interaction of discrete individuals/agents within a system in order to discover the pattern of behavior that comes from these interactions. Examples of individuals/agents in biological systems are individual immune cells and bacteria that act independently with their own unique attributes defined by behavioral rules. In IBMs, each of these agents resides in a spatial environment and interactions are guided by predefined rules. These rules are often simple and can be easily implemented. It is expected that following the interaction guided by these rules we will have a better understanding of agent-agent interaction as well as agent-environment interaction. Stochasticity described by probability distributions must be accounted for. Events that seldom occur such as the accumulation of rare mutations can be easily modeled.Thus, IBMs are able to track the behavior of each individual/agent within the model while also obtaining information on the results of their collective behaviors. The influence of impact of one agent with another can be captured, thus allowing a full representation of both direct and indirect causation on the aggregate results. This means that important new insights can be gained and hypotheses tested.

Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations

Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex, interconnected biological systems and discuss critical steps involved in building, analyzing, and applying such models within the discipline of model credibility. We also present our two tools: CaliPro, for calibrating multiscale models (MSMs) to datasets, and tunable resolution, for fine- and coarse-graining sub-models while retaining insights. We include as an example our work simulating infection with Mycobacterium tuberculosis to demonstrate modeling choices and how predictions are made to generate new insights and test interventions. We discuss some of the current challenges of incorporating novel datasets, rigorously training computational biologists, and increasing the reach of MSMs. We also offer several promising future research directions of incorporating within-host dynamics into applications ranging from combinatorial treatment to epidemic response.

Comparative pathology of experimental pulmonary tuberculosis in animal models

Research in human tuberculosis (TB) is limited by the availability of human tissues from patients, which is often altered by therapy and treatment. Thus, the use of animal models is a key tool in increasing our understanding of the pathogenesis, disease progression and preclinical evaluation of new therapies and vaccines. The granuloma is the hallmark lesion of pulmonary tuberculosis, regardless of the species or animal model used. Although animal models may not fully replicate all the histopathological characteristics observed in natural, human TB disease, each one brings its own attributes which enable researchers to answer specific questions regarding TB immunopathogenesis. This review delves into the pulmonary pathology induced by Mycobacterium tuberculosis complex (MTBC) bacteria in different animal models (non-human primates, rodents, guinea pigs, rabbits, cattle, goats, and others) and compares how they relate to the pulmonary disease described in humans. Although the described models have demonstrated some histopathological features in common with human pulmonary TB, these data should be considered carefully in the context of this disease. Further research is necessary to establish the most appropriate model for the study of TB, and to carry out a standard characterisation and score of pulmonary lesions.

Characterization of peripheral cytokine-secreting cells responses in HIV/TB co-infection

Background

Currently the responses of peripheral cytokine-secreting cells in the natural course of human immunodeficiency virus (HIV) and tuberculosis (TB) co-infection haven't been fully elucidated.

Methods

The function of peripheral proinflammatory, regulatory and cytotoxic cytokine-secreting cells were investigated by direct intracellular cytokine staining (ICS) and flow cytometry, additionally, the absolute numbers of different cytokine-secreting cells were measured among patients with HIV/TB co-infection (HT group), and compared them with the healthy controls (HC group), patients with TB (TB group) and patients with HIV infection (HIV group). After one week's anti-TB treatment, the changes of the percentages of cytokine-secreting cells were further evaluated in TB and HT groups.

Results

Totally 26 individuals in the HC group, 51 in the TB group, 26 in the HIV group and 29 in the HT group were enrolled. The HT. HT group exhibited significantly lower absolute numbers of IFN-γ⁺CD4⁺, IFN-γ⁺CD8⁺, TNF-α⁺CD4⁺, IL17A⁺CD4⁺ T cells and TNF-α⁺CD14⁺ monocytes than the TB and HIV groups. Compared with the TB group, the percentages of CD8⁺ T cells secreting IFN-γ and perforin (p=0.010; p=0.043) were significantly lower among the HT group. Compared with the HIV group, the percentages of CD4⁺, CD8⁺ T cells and CD14⁺ monocytes secreting TNF-α (p=0.013; p=0.001; p<0.001) were significantly decreased, and the percentage of CD8⁺ T cells secreting IL-17A (p=0.015) was significantly increased among the HT group. Both the percentages of CD4⁺ T cells secreting TGF-β (p<0.001; p=0.001), and CD4⁺ and CD8⁺ T cells secreting granzyme A (all p<0.001), were significantly higher among the HT group than among the TB group and HIV group. After one week's anti-TB treatment, an increased percentage of CD4⁺ T cells secreting TNF-α (p=0.003) was found in the TB group, and an increased percentage of CD8⁺ T cells secreting TNF-α (p=0.029) was found in the HT group.

Conclusion

Significantly different functional profiles of peripheral proinflammatory, regulatory, and cytotoxic cytokine-secreting cells were observed in the natural course of HIV/TB co-infection compared to TB and HIV infection alone, even though the absolute numbers of those cells were significantly lower in HIV/TB co-infection. TNF-α-secreting CD8⁺ T cells may be a more sensitive marker for early evaluation of anti-TB treatment efficacy in patients with HIV/TB co-infection.

Mycobacterium tuberculosis-Specific CD4 T Cells Expressing Transcription Factors T-Bet or RORγT Associate with Bacterial Control in Granulomas

Despite the extensive research on CD4 T cells within the context of Mycobacterium tuberculosis (Mtb) infections, few studies have focused on identifying and investigating the profile of Mtb-specific T cells within lung granulomas. To facilitate the identification of Mtb-specific CD4 T cells, we identified immunodominant epitopes for two Mtb proteins, namely, Rv1196 and Rv0125, using a Mauritian cynomolgus macaque model of Mtb infection, thereby providing data for the synthesis of MHC class II tetramers. Using tetramers, we identified Mtb-specific cells within different immune compartments, postinfection. We found that granulomas were enriched sites for Mtb-specific cells and that tetramer+ cells had increased frequencies of the activation marker CD69 as well as the transcription factors T-bet and RORγT, compared to tetramer negative cells within the same sample. Our data revealed that while the frequency of Rv1196 tetramer+ cells was positively correlated with the granuloma bacterial burden, the frequency of RORγT or T-bet within tetramer+ cells was inversely correlated with the granuloma bacterial burden, thereby highlighting the importance of having activated, polarized, Mtb-specific cells for the control of Mtb in lung granulomas. IMPORTANCE Tuberculosis, caused by the bacterial pathogen Mycobacterium tuberculosis, kills 1.5 million people each year, despite the existence of effective drugs and a vaccine that is given to infants in most countries. Clearly, we need better vaccines against this disease. However, our understanding of the immune responses that are necessary to prevent tuberculosis is incomplete. This study seeks to understand the functions of T cells that are specific for M. tuberculosis at the site of the disease in the lungs. For this, we developed specialized tools called MHC class II tetramers to identify those T cells that can recognize M. tuberculosis and applied the tools to the study of this infection in nonhuman primate models that mimic human tuberculosis. We demonstrate that M. tuberculosis-specific T cells in lung lesions are associated with control of the bacteria only when those T cells are expressing certain functions, thereby highlighting the importance of combining the identification of specific T cells with functional analyses. Thus, we surmise that these functions of specific T cells are critical to the control of infection and should be considered as a part of the development of vaccines against tuberculosis.

Surveillance of Daughter Micronodule Formation Is a Key Factor for Vaccine Evaluation Using Experimental Infection Models of Tuberculosis in Macaques

Tuberculosis (TB) is still a major worldwide health problem and models using non-human primates (NHP) provide the most relevant approach for vaccine testing. In this study, we analysed CT images collected from cynomolgus and rhesus macaques following exposure to ultra-low dose Mycobacterium tuberculosis (Mtb) aerosols, and monitored them for 16 weeks to evaluate the impact of prior intradermal or inhaled BCG vaccination on the progression of lung disease. All lesions found (2553) were classified according to their size and we subclassified small micronodules (<4.4 mm) as 'isolated', or as 'daughter', when they were in contact with consolidation (described as lesions ≥ 4.5 mm). Our data link the higher capacity to contain Mtb infection in cynomolgus with the reduced incidence of daughter micronodules, thus avoiding the development of consolidated lesions and their consequent enlargement and evolution to cavitation. In the case of rhesus, intradermal vaccination has a higher capacity to reduce the formation of daughter micronodules. This study supports the 'Bubble Model' defined with the C3HBe/FeJ mice and proposes a new method to evaluate outcomes in experimental models of TB in NHP based on CT images, which would fit a future machine learning approach to evaluate new vaccines.

Immune cell interactions in tuberculosis

Despite having been identified as the organism that causes tuberculosis in 1882, Mycobacterium tuberculosis has managed to still evade our understanding of the protective immune response against it, defying the development of an effective vaccine. Technology and novel experimental models have revealed much new knowledge, particularly with respect to the heterogeneity of the bacillus and the host response. This review focuses on certain immunological elements that have recently yielded exciting data and highlights the importance of taking a holistic approach to understanding the interaction of M. tuberculosis with the many host cells that contribute to the development of protective immunity.

T cell transcription factor expression evolves over time in granulomas from Mycobacterium tuberculosis-infected cynomolgus macaques

Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), is a global health concern, yearly resulting in 10 million new cases of active TB. Immunologic investigation of lung granulomas is essential for understanding host control of bacterial replication. Here, we identify and compare the pathological, cellular, and functional differences in granulomas at 4, 12, and 20 weeks post-infection in Chinese cynomolgus macaques. Original granulomas differ in transcription-factor expression within adaptive lymphocytes, with those at 12 weeks showing higher frequencies of CD8⁺T-bet⁺ T cells, while CD4⁺T-bet⁺ T cells increase at 20 weeks post-infection. The appearance of T-bet⁺ adaptive T cells at 12 and 20 weeks is coincident with a reduction in bacterial burden, suggesting their critical role in Mtb control. This study highlights the evolution of T cell responses within lung granulomas, suggesting that vaccines promoting the development and migration of T-bet⁺ T cells would enhance mycobacterial control.

Grant et al. investigate the pathological, cellular, and functional differences in TB lung granulomas from macaques. The data reveal that most T cells at early time points have low frequencies of transcription factor expression, while T cells at later time points have increased expression of T-bet and a reduction in bacterial burden.

Multimodal profiling of lung granulomas in macaques reveals cellular correlates of tuberculosis control

Mycobacterium tuberculosis lung infection results in a complex multicellular structure: the granuloma. In some granulomas, immune activity promotes bacterial clearance, but in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal positron emission tomography and computed tomography imaging, single-cell RNA sequencing, and measures of bacterial clearance. Bacterial persistence occurred in granulomas enriched for mast, endothelial, fibroblast, and plasma cells, signaling amongst themselves via type 2 immunity and wound-healing pathways. Granulomas that drove bacterial control were characterized by cellular ecosystems enriched for type 1-type 17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks involving diverse cell populations. Granulomas that arose later in infection displayed functional characteristics of restrictive granulomas and were more capable of killing Mtb. Our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB.

The Tuberculous Granuloma and Preexisting Immunity

Pulmonary granulomas are widely considered the epicenters of the immune response to Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB). Recent animal studies have revealed factors that either promote or restrict TB immunity within granulomas. These models, however, typically ignore the impact of preexisting immunity on cellular organization and function, an important consideration because most TB probably occurs through reinfection of previously exposed individuals. Human postmortem research from the pre-antibiotic era showed that infections in Mtb-naïve individuals (primary TB) versus those with prior Mtb exposure (postprimary TB) have distinct pathologic features. We review recent animal findings in TB granuloma biology, which largely reflect primary TB. We also discuss our current understanding of postprimary TB lesions, about which much less is known. Many knowledge gaps remain, particularly regarding how preexisting immunity shapes granuloma structure and local immune responses at Mtb infection sites.

Expected final online publication date for the Annual Review of Immunology, Volume 40 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The immunoregulatory landscape of human tuberculosis granulomas

Tuberculosis (TB) in humans is characterized by formation of immune-rich granulomas in infected tissues, the architecture and composition of which are thought to affect disease outcome. However, our understanding of the spatial relationships that control human granulomas is limited. Here, we used multiplexed ion beam imaging by time of flight (MIBI-TOF) to image 37 proteins in tissues from patients with active TB. We constructed a comprehensive atlas that maps 19 cell subsets across 8 spatial microenvironments. This atlas shows an IFN-γ-depleted microenvironment enriched for TGF-β, regulatory T cells and IDO1⁺ PD-L1⁺ myeloid cells. In a further transcriptomic meta-analysis of peripheral blood from patients with TB, immunoregulatory trends mirror those identified by granuloma imaging. Notably, PD-L1 expression is associated with progression to active TB and treatment response. These data indicate that in TB granulomas, there are local spatially coordinated immunoregulatory programs with systemic manifestations that define active TB.

In vivo kinetics of peripheral cellular immune responses in Mycobacterium avium subspecies paratuberculosis (MAP) infected and vaccinated goats

Mycobacterium avium subspecies paratuberculosis (MAP) is the causative agent of paratuberculosis (ParaTB) also known as Johne's disease (JD) in ruminants, which is characterized by chronic intestinal inflammation. A similar counterpart has been observed in the form of Crohn's disease in humans. The present study is the first trail in goats to understand the peripheral cellular immune responses following experimental MAP infection and vaccination. Fifteen apparently healthy male kids (3-6 months old) of Barbari breed were included in this study. In the experimental study, 5 kids were infected with 'S 5' strain of MAP ("Indian Bison Type"), 5 were vaccinated (Indigenous Vaccine) against MAP infection (Singh et al., 2007) and the remaining 5 kids were uninfected and non-vaccinated controls. Kids were observed for a period of 180 days post exposure (infection and vaccination) and were tested for development of infection. Cellular immune responses (in blood) were recorded post-exposure by three assays. We measured the frequencies of CD4 and CD8T cells, estimated plasma IFNγ and TNα and in the third assay, in vitro cytokine production by peripheral blood mononuclear cells (PBMCs) from vaccinated, infected and controls were examined in response to polyclonal stimulation. The frequencies of peripheral CD4 and CD8T cells were comparable in control, infected and vaccinated animals except around day 49 post-infection where MAP infected animals showed a trend towards significantly reduced frequencies of CD4 T cells compared to apparently healthy controls. Significantly reduced plasma TNFα levels were also observed in infected animals compared to vaccinated animals,during the course of infection. Diminished levels (although non significant) of TNFα were observed in the supernatants from polyclonally stimulated PBMCs at around day 49 post infection. It is conceivable that the diminished cellular immune responses may coincide with an impairment (immune exhaustion) of perhaps antigen-specific CD4T cells that might, in the course of infection, contribute to the progressive nature of caprine paratuberculosis.

Establishment of a Patient-Derived, Magnetic Levitation-Based, Three-Dimensional Spheroid Granuloma Model for Human Tuberculosis

Tuberculous granulomas that develop in response to Mycobacterium tuberculosis (M. tuberculosis) infection are highly dynamic entities shaped by the host immune response and disease kinetics. Within this microenvironment, immune cell recruitment, polarization, and activation are driven not only by coexisting cell types and multicellular interactions but also by M. tuberculosis-mediated changes involving metabolic heterogeneity, epigenetic reprogramming, and rewiring of the transcriptional landscape of host cells. There is an increased appreciation of the in vivo complexity, versatility, and heterogeneity of the cellular compartment that constitutes the tuberculosis (TB) granuloma and the difficulty in translating findings from animal models to human disease. Here, we describe a novel biomimetic in vitro three-dimensional (3D) human lung spheroid granuloma model, resembling early "innate" and "adaptive" stages of the TB granuloma spectrum, and present results of histological architecture, host transcriptional characterization, mycobacteriological features, cytokine profiles, and spatial distribution of key immune cells. A range of manipulations of immune cell populations in these spheroid granulomas will allow the study of host/pathogen pathways involved in the outcome of infection, as well as pharmacological interventions. IMPORTANCE TB is a highly infectious disease, with granulomas as its hallmark. Granulomas play an important role in the control of M. tuberculosis infection and as such are crucial indicators for our understanding of host resistance to TB. Correlates of risk and protection to M. tuberculosis are still elusive, and the granuloma provides the perfect environment in which to study the immune response to infection and broaden our understanding thereof; however, human granulomas are difficult to obtain, and animal models are costly and do not always faithfully mimic human immunity. In fact, most TB research is conducted in vitro on immortalized or primary immune cells and cultured in two dimensions on flat, rigid plastic, which does not reflect in vivo characteristics. We have therefore conceived a 3D, human in vitro spheroid granuloma model which allows researchers to study features of granuloma-forming diseases in a 3D structural environment resembling in vivo granuloma architecture and cellular orientation.

Measurement of leukocyte trafficking kinetics in macaques by serial intravascular staining

Leukocyte trafficking enables detection of pathogens, immune responses, and immune memory. Dysregulation of leukocyte trafficking is often found in disease, highlighting its important role in homeostasis and the immune response. Whereas some of the molecular mechanisms mediating leukocyte trafficking are understood, little is known about the regulation of trafficking, including trafficking kinetics and its impact on immune homeostasis. We developed a method of serial intravascular staining (SIVS) to measure trafficking kinetics in nonhuman primates using infusions of fluorescently labeled antibodies to label circulating leukocytes. Because antibody infusions labeled only leukocytes in the blood, cells were "barcoded" according to their location at the time of each infusion, providing positional histories that could be used to infer trafficking kinetics. We used SIVS and multiparameter flow cytometry to quantitate cellular trafficking into lymphoid tissues of healthy animals at homeostasis and to identify perivascular cells that could be unique to nonlymphoid organs. To investigate how these parameters could be influenced during disease, SIVS was used to quantify lymphocyte trafficking in macaques infected with the bacterial pathogen Mycobacterium tuberculosis and to enumerate intravascular leukocytes in lung granulomas. We showed that whereas most cells in lung granulomas were localized there for more than 24 hours, granulomas were dynamic with a slow continual cellular influx, the rate of which predicted clearance of M. tuberculosis from the granulomas. SIVS, in combination with intracellular staining and multiparametric flow cytometry, is a powerful method to quantify the kinetics of leukocyte trafficking in nonhuman primates in vivo.

Towards efficient immunotherapy for bacterial infection

The emergence of multiantibiotic-resistant bacteria, often referred to as superbugs, is leading to infections that are increasingly difficult to treat. Further, bacteria have evolved mechanisms by which they subvert the immune response, meaning that even antibiotic-sensitive bacteria can persist through antibiotic therapy. For these reasons, a broad range of viable therapeutic alternatives or conjunctions to traditional antimicrobial therapy are urgently required to reduce the burden of disease threatened by antibiotic resistance. Immunotherapy has emerged as a leading treatment option in cancer, and researchers are now attempting to apply this to infectious disease. This review summarizes and discusses the recent advances in the field and highlights current and future perspectives of using immunotherapies to treat bacterial infections.

Pre-existing Simian Immunodeficiency Virus Infection Increases Expression of T Cell Markers Associated with Activation during Early Mycobacterium tuberculosis Coinfection and Impairs TNF Responses in Granulomas

Tuberculosis (TB) is the leading infectious cause of death among people living with HIV. People living with HIV are more susceptible to contracting Mycobacterium tuberculosis and often have worsened TB disease. Understanding the immunologic defects caused by HIV and the consequences it has on M. tuberculosis coinfection is critical in combating this global health epidemic. We previously showed in a model of SIV and M. tuberculosis coinfection in Mauritian cynomolgus macaques (MCM) that SIV/M. tuberculosis-coinfected MCM had rapidly progressive TB. We hypothesized that pre-existing SIV infection impairs early T cell responses to M. tuberculosis infection. We infected MCM with SIVmac239, followed by coinfection with M. tuberculosis Erdman 6 mo later. Although similar, TB progression was observed in both SIV⁺ and SIV-naive animals at 6 wk post-M. tuberculosis infection; longitudinal sampling of the blood (PBMC) and airways (bronchoalveolar lavage) revealed a significant reduction in circulating CD4⁺ T cells and an influx of CD8⁺ T cells in airways of SIV⁺ animals. At sites of M. tuberculosis infection (i.e., granulomas), SIV/M. tuberculosis-coinfected animals had a higher proportion of CD4⁺ and CD8⁺ T cells expressing PD-1 and TIGIT. In addition, there were fewer TNF-producing CD4⁺ T cells in granulomas of SIV/M. tuberculosis-coinfected animals. Taken together, we show that concurrent SIV infection alters T cell phenotypes in granulomas during the early stages of TB disease. As it is critical to establish control of M. tuberculosis replication soon postinfection, these phenotypic changes may distinguish the immune dysfunction that arises from pre-existing SIV infection, which promotes TB progression.

Biomechanics of T Cell Dysfunctions in Chronic Diseases

Understanding the mechanisms behind T cell dysfunctions during chronic diseases is critical in developing effective immunotherapies. As demonstrated by several animal models and human studies, T cell dysfunctions are induced during chronic diseases, spanning from infections to cancer. Although factors governing the onset and the extent of the functional impairment of T cells can differ during infections and cancer, most dysfunctional phenotypes share common phenotypic traits in their immune receptor and biophysical landscape. Through the latest developments in biophysical techniques applied to explore cell membrane and receptor-ligand dynamics, we are able to dissect and gain further insights into the driving mechanisms behind T cell dysfunctions. These insights may prove useful in developing immunotherapies aimed at reinvigorating our immune system to fight off infections and malignancies more effectively. The recent success with checkpoint inhibitors in treating cancer opens new avenues to develop more effective, targeted immunotherapies. Here, we highlight the studies focused on the transformation of the biophysical landscape during infections and cancer, and how T cell biomechanics shaped the immunopathology associated with chronic diseases.

Spatial Organization and Recruitment of Non-Specific T Cells May Limit T Cell-Macrophage Interactions Within Mycobacterium tuberculosis Granulomas

Tuberculosis (TB) is a worldwide health problem; successful interventions such as vaccines and treatment require a 2better understanding of the immune response to infection with Mycobacterium tuberculosis (Mtb). In many infectious diseases, pathogen-specific T cells that are recruited to infection sites are highly responsive and clear infection. Yet in the case of infection with Mtb, most individuals are unable to clear infection leading to either an asymptomatically controlled latent infection (the majority) or active disease (roughly 5%-10% of infections). The hallmark of Mtb infection is the recruitment of immune cells to lungs leading to development of multiple lung granulomas. Non-human primate models of TB indicate that on average <10% of T cells within granulomas are Mtb-responsive in terms of cytokine production. The reason for this reduced responsiveness is unknown and it may be at the core of why humans typically are unable to clear Mtb infection. There are a number of hypotheses as to why this reduced responsiveness may occur, including T cell exhaustion, direct downregulation of antigen presentation by Mtb within infected macrophages, the spatial organization of the granuloma itself, and/or recruitment of non-Mtb-specific T cells to lungs. We use a systems biology approach pairing data and modeling to dissect three of these hypotheses. We find that the structural organization of granulomas as well as recruitment of non-specific T cells likely contribute to reduced responsiveness.

CaliPro: A Calibration Protocol That Utilizes Parameter Density Estimation to Explore Parameter Space and Calibrate Complex Biological Models

Introduction

Mathematical and computational modeling have a long history of uncovering mechanisms and making predictions for biological systems. However, to create a model that can provide relevant quantitative predictions, models must first be calibrated by recapitulating existing biological datasets from that system. Current calibration approaches may not be appropriate for complex biological models because: 1) many attempt to recapitulate only a single aspect of the experimental data (such as a median trend) or 2) Bayesian techniques require specification of parameter priors and likelihoods to experimental data that cannot always be confidently assigned. A new calibration protocol is needed to calibrate complex models when current approaches fall short.

Methods

Herein, we develop CaliPro, an iterative, model-agnostic calibration protocol that utilizes parameter density estimation to refine parameter space and calibrate to temporal biological datasets. An important aspect of CaliPro is the user-defined pass set definition, which specifies how the model might successfully recapitulate experimental data. We define the appropriate settings to use CaliPro.

Results

We illustrate the usefulness of CaliPro through four examples including predator-prey, infectious disease transmission, and immune response models. We show that CaliPro works well for both deterministic, continuous model structures as well as stochastic, discrete models and illustrate that CaliPro can work across diverse calibration goals.

Conclusions

We present CaliPro, a new method for calibrating complex biological models to a range of experimental outcomes. In addition to expediting calibration, CaliPro may be useful in already calibrated parameter spaces to target and isolate specific model behavior for further analysis.

Immunometabolism: new insights and lessons from antigen-directed cellular immune responses

Modulation of immune responses by nutrients is an important area of study in cellular biology and clinical sciences in the context of cancer therapies and anti-pathogen-directed immune responses in health and disease. We review metabolic pathways that influence immune cell function and cellular persistence in chronic infections. We also highlight the role of nutrients in altering the tissue microenvironment with lessons from the tumor microenvironment that shapes the quality and quantity of cellular immune responses. Multiple layers of biological networks, including the nature of nutritional supplements, the genetic background, previous exposures, and gut microbiota status have impact on cellular performance and immune competence against molecularly defined targets. We discuss how immune metabolism determines the differentiation pathway of antigen-specific immune cells and how these insights can be explored to devise better strategies to strengthen anti-pathogen-directed immune responses, while curbing unwanted, non-productive inflammation.

A computational model tracks whole-lung Mycobacterium tuberculosis infection and predicts factors that inhibit dissemination

Mycobacterium tuberculosis (Mtb), the causative infectious agent of tuberculosis (TB), kills more individuals per year than any other infectious agent. Granulomas, the hallmark of Mtb infection, are complex structures that form in lungs, composed of immune cells surrounding bacteria, infected cells, and a caseous necrotic core. While granulomas serve to physically contain and immunologically restrain bacteria growth, some granulomas are unable to control Mtb growth, leading to bacteria and infected cells leaving the granuloma and disseminating, either resulting in additional granuloma formation (local or non-local) or spread to airways or lymph nodes. Dissemination is associated with development of active TB. It is challenging to experimentally address specific mechanisms driving dissemination from TB lung granulomas. Herein, we develop a novel hybrid multi-scale computational model, MultiGran, that tracks Mtb infection within multiple granulomas in an entire lung. MultiGran follows cells, cytokines, and bacterial populations within each lung granuloma throughout the course of infection and is calibrated to multiple non-human primate (NHP) cellular, granuloma, and whole-lung datasets. We show that MultiGran can recapitulate patterns of in vivo local and non-local dissemination, predict likelihood of dissemination, and predict a crucial role for multifunctional CD8+ T cells and macrophage dynamics for preventing dissemination.

Tuberculosis (TB) is caused by infection with Mycobacterium tuberculosis (Mtb) and kills 3 people per minute worldwide. Granulomas, spherical structures composed of immune cells surrounding bacteria, are the hallmark of Mtb infection and sometimes fail to contain the bacteria and disseminate, leading to further granuloma growth within the lung environment. To date, the mechanisms that determine granuloma dissemination events have not been characterized. We present a computational multi-scale model of granuloma formation and dissemination within primate lungs. Our computational model is calibrated to multiple experimental datasets across the cellular, granuloma, and whole-lung scales of non-human primates. We match to both individual granuloma and granuloma-population datasets, predict likelihood of dissemination events, and predict a critical role for multifunctional CD8+ T cells and macrophage-bacteria interactions to prevent infection dissemination.

The current state of animal models and genomic approaches towards identifying and validating molecular determinants of Mycobacterium tuberculosis infection and tuberculosis disease

Animal models are important in understanding both the pathogenesis of and immunity to tuberculosis (TB). Unfortunately, we are beginning to understand that no animal model perfectly recapitulates the human TB syndrome, which encompasses numerous different stages. Furthermore, Mycobacterium tuberculosis infection is a very heterogeneous event at both the levels of pathogenesis and immunity. This review seeks to establish the current understanding of TB pathogenesis and immunity, as validated in the animal models of TB in active use today. We especially focus on the use of modern genomic approaches in these models to determine the mechanism and the role of specific molecular pathways. Animal models have significantly enhanced our understanding of TB. Incorporation of contemporary technologies such as single cell transcriptomics, high-parameter flow cytometric immune profiling, proteomics, proteomic flow cytometry and immunocytometry into the animal models in use will further enhance our understanding of TB and facilitate the development of treatment and vaccination strategies.

Agent-based models of inflammation in translational systems biology: A decade later

Agent-based modeling is a rule-based, discrete-event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components ("agents") of system. Agent-based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent-based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent-based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent-based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting-edge technologies such as high-performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine Models of Systems Properties and Processes > Mechanistic Models Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Models of Systems Properties and Processes > Organismal Models.

Checkpoint Inhibition and Infectious Diseases: A Good Thing?

The mammalian immune system has evolved the capacity to detect and destroy tumor cells. Tumors utilize multiple strategies to evade host immune surveillance, including the induction of the checkpoint molecules cytotoxic T lymphocyte-associated protein 4 (CTLA-4) and programmed cell death protein 1 (PD-1) to suppress antitumor immunity. Pharmacologic blockade of these molecules with checkpoint inhibitors (CPIs) restores T cell function and prolongs survival in patients with various malignancies. Emerging evidence suggests that the same checkpoint pathways may play a crucial role during infections. Indeed, CPIs appear promising as immunotherapeutic agents in infectious diseases, although their efficacy varies depending on pathogen-, cell-, and organ-specific factors. More research will be necessary to clarify the effects and safety of CPIs on clinically relevant outcomes of human infection.

HIV Infection Is Associated With Downregulation of BTLA Expression on Mycobacterium tuberculosis-Specific CD4 T Cells in Active Tuberculosis Disease

Nearly a quarter of the global population is infected with Mycobacterium tuberculosis (Mtb), with 10 million people developing active tuberculosis (TB) annually. Co-infection with human immunodeficiency virus (HIV) has long been recognized as a significant risk factor for progression to TB disease, yet the mechanisms whereby HIV impairs T cell-mediated control of Mtb infection remain poorly defined. We hypothesized that HIV infection may promote upregulation of inhibitory receptors on Mtb-specific CD4 T cells, a mechanism that has been associated with antigen-specific T cell dysfunction in chronic infections. Using cohorts of HIV-infected and HIV-uninfected individuals with latent Mtb infection (LTBI) and with active TB disease, we stimulated peripheral blood mononuclear cells (PBMC) for 6 hours with Mtb peptide pools and evaluated co-expression profiles of the inhibitory receptors BTLA, CTLA-4, and PD-1 on IFN-γ⁺/TNF-α⁺ Mtb-specific CD4 T cells. Mtb-specific CD4 T cells in all participant groups expressed predominately either one or no inhibitory receptors, unlike cytomegalovirus- and HIV-specific CD4 T cells circulating in the same individuals, which were predominately CTLA-4⁺PD-1⁺. There were no significant differences in inhibitory receptor expression profiles of Mtb-specific CD4 T cells between HIV-uninfected and HIV-infected individuals with LTBI. Surprisingly, BTLA expression, both alone and in combination with CTLA-4 and PD-1, was markedly downregulated on Mtb-specific CD4 T cells in HIV-infected individuals with active TB. Together, these data provide novel evidence that the majority of Mtb-specific CD4 T cells do not co-express multiple inhibitory receptors, regardless of HIV infection status; moreover, they highlight a previously unrecognized role of BTLA expression on Mtb-specific CD4 T cells that could be further explored as a potential biomarker of Mtb infection status, particularly in people living with HIV, the population at greatest risk for development of active TB disease.

The End of the Binary Era: Revisiting the Spectrum of Tuberculosis

Human Mycobacterium tuberculosis infection was thought to result in either active symptomatic tuberculosis (TB) or latent asymptomatic infection. It is now clear that this binary classification is insufficient to describe the myriad of infection outcomes. In active TB, symptomatic disease can be mild to severe, with a range of lung and thoracic lymph node involvement or extrapulmonary manifestations. Most humans control the infection and develop latent TB infection, with differential risks of reactivation to active TB. However, some frequently exposed persons appear to be resistant to infection, whereas others may initially become infected yet subsequently eliminate all bacilli. The immunologic factors influencing these varied outcomes are still not clear, but likely involve a range of different responses. In this article, we review the data supporting the spectrum of M. tuberculosis infection in humans as well as data in nonhuman primates that allow dissection of the immune responses leading to the varied outcomes of infection.