Early cellular mechanisms of type I interferon-driven susceptibility to tuberculosis.

Mycobacterium tuberculosis (Mtb) causes 1.6 million deaths annually. Active tuberculosis correlates with a neutrophil-driven type I interferon (IFN) signature, but the cellular mechanisms underlying tuberculosis pathogenesis remain poorly understood. We found that interstitial macrophages (IMs) and plasmacytoid dendritic cells (pDCs) are dominant producers of type I IFN during Mtb infection in mice and non-human primates, and pDCs localize near human Mtb granulomas. Depletion of pDCs reduces Mtb burdens, implicating pDCs in tuberculosis pathogenesis. During IFN-driven disease, we observe abundant DNA-containing neutrophil extracellular traps (NETs) described to activate pDCs. Cell-type-specific disruption of the type I IFN receptor suggests that IFNs act on IMs to inhibit Mtb control. Single-cell RNA sequencing (scRNA-seq) indicates that type I IFN-responsive cells are defective in their response to IFNγ, a cytokine critical for Mtb control. We propose that pDC-derived type I IFNs act on IMs to permit bacterial replication, driving further neutrophil recruitment and active tuberculosis disease.

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.

CD8+ T cell priming that is required for curative intratumorally anchored anti-4-1BB immunotherapy is constrained by Tregs.

Although co-stimulation of T cells with agonist antibodies targeting 4-1BB (CD137) improves antitumor immune responses in preclinical studies, clinical success has been limited by on-target, off-tumor activity. Here, we report the development of a tumor-anchored ɑ4-1BB agonist (ɑ4-1BB-LAIR), which consists of a ɑ4-1BB antibody fused to the collagen-binding protein LAIR. While combination treatment with an antitumor antibody (TA99) shows only modest efficacy, simultaneous depletion of CD4+ T cells boosts cure rates to over 90% of mice. Mechanistically, this synergy depends on ɑCD4 eliminating tumor draining lymph node regulatory T cells, resulting in priming and activation of CD8+ T cells which then infiltrate the tumor microenvironment. The cytotoxic program of these newly primed CD8+ T cells is then supported by the combined effect of TA99 and ɑ4-1BB-LAIR. The combination of TA99 and ɑ4-1BB-LAIR with a clinically approved ɑCTLA-4 antibody known for enhancing T cell priming results in equivalent cure rates, which validates the mechanistic principle, while the addition of ɑCTLA-4 also generates robust immunological memory against secondary tumor rechallenge. Thus, our study establishes the proof of principle for a clinically translatable cancer immunotherapy.

TLR2 is non-redundant in the population and subpopulation responses to Mycobacterium tuberculosis in macrophages and in vivo.

Tuberculosis (TB), caused by the pathogenic bacterium Mycobacterium tuberculosis (Mtb), is a global health threat. Targeting host pathways that modulate protective or harmful components of inflammation has been proposed as a therapeutic strategy that could aid sterilization or mitigate TB-associated permanent tissue damage. In purified form, many Mtb components can activate innate immune pathways. However, knowledge of the pathways that contribute most to the observed response to live Mtb is incomplete, limiting the possibility of precise intervention. We took a systematic, unbiased approach to define the pathways that drive the earliest immune response to Mtb. Using a macrophage model of infection, we compared the bulk transcriptional response to infection with the response to a panel of Mtb-derived putative innate immune ligands. We identified two axes of response: an NF-kB-dependent response similarly elicited by all Mtb pathogen-associated molecular patterns (PAMPs) and a type I interferon axis unique to cells infected with live Mtb. Consistent with growing literature data pointing to TLR2 as a dominant Mtb-associated PAMP, the TLR2 ligand PIM6 most closely approximated the NF-kB-dependent response to the intact bacterium. Quantitatively, the macrophage response to Mtb was slower and weaker than the response to purified PIM6. On a subpopulation level, the TLR2-dependent response was heterogeneously induced, with only a subset of infected cells expressing key inflammatory genes known to contribute to the control of infection. Despite potential redundancies in Mtb ligand/innate immune receptor interactions during in vivo infection, loss of the TLR2/PIM6 interaction impacted the cellular composition of both the innate and adaptive compartments. IMPORTANCE Tuberculosis (TB) is a leading cause of death globally. Drug resistance is outpacing new antibiotic discovery, and even after successful treatment, individuals are often left with permanent lung damage from the negative consequences of inflammation. Targeting host inflammatory pathways has been proposed as an approach that could either improve sterilization or improve post-treatment lung health. However, our understanding of the inflammatory pathways triggered by Mycobacterium tuberculosis (Mtb) in infected cells and lungs is incomplete, in part because of the complex array of potential molecular interactions between bacterium and host. Here, we take an unbiased approach to identify the pathways most central to the host response to Mtb. We examine how individual pathways are triggered differently by purified Mtb products or infection with the live bacterium and consider how these pathways inform the emergence of subpopulation responses in cell culture and in infected mice. Understanding how individual interactions and immune pathways contribute to inflammation in TB opens the door to the possibility of developing precise therapeutic interventions.

Tregs constrain CD8+ T cell priming required for curative intratumorally anchored anti-4-1BB immunotherapy.

Although co-stimulation of T cells with agonist antibodies targeting 4-1BB (CD137) improves antitumor immune responses in preclinical studies, clinical development has been hampered by on-target, off-tumor toxicity. Here, we report the development of a tumor-anchored ɑ4-1BB agonist (ɑ4-1BB-LAIR), which consists of an ɑ4-1BB antibody fused to the collagen binding protein LAIR. While combination treatment with an antitumor antibody (TA99) displayed only modest efficacy, simultaneous depletion of CD4+ T cells boosted cure rates to over 90% of mice. We elucidated two mechanisms of action for this synergy: ɑCD4 eliminated tumor draining lymph node Tregs, enhancing priming and activation of CD8+ T cells, and TA99 + ɑ4-1BB-LAIR supported the cytotoxic program of these newly primed CD8+ T cells within the tumor microenvironment. Replacement of ɑCD4 with ɑCTLA-4, a clinically approved antibody that enhances T cell priming, produced equivalent cure rates while additionally generating robust immunological memory against secondary tumor rechallenge.

Protective intravenous BCG vaccination induces enhanced immune signaling in the airways.

Intradermal (ID) Bacillus Calmette-Guérin (BCG) is the most widely administered vaccine in the world. However, ID-BCG fails to achieve the level of protection needed in adults to alter the course of the tuberculosis epidemic. Recent studies in non-human primates have demonstrated high levels of protection against Mycobacterium tuberculosis ( Mtb ) following intravenous (IV) administration of BCG. However, the protective immune features that emerge following IV BCG vaccination remain incompletely defined. Here we used single-cell RNA-sequencing (scRNAseq) to transcriptionally profile 157,114 unstimulated and purified protein derivative (PPD)-stimulated bronchoalveolar lavage (BAL) cells from 29 rhesus macaques immunized with BCG across routes of administration and doses to uncover cell composition-, gene expression-, and biological network-level signatures associated with IV BCG-mediated protection. Our analyses revealed that high-dose IV BCG drove an influx of polyfunctional T cells and macrophages into the airways. These macrophages exhibited a basal activation phenotype even in the absence of PPD-stimulation, defined in part by IFN and TNF-α signaling up to 6 months following BCG immunization. Furthermore, intercellular immune signaling pathways between key myeloid and T cell subsets were enhanced following PPD-stimulation in high-dose IV BCG-vaccinated macaques. High-dose IV BCG also engendered quantitatively and qualitatively stronger transcriptional responses to PPD-stimulation, with a robust Th1-Th17 transcriptional phenotype in T cells, and augmented transcriptional signatures of reactive oxygen species production, hypoxia, and IFN-γ response within alveolar macrophages. Collectively, this work supports that IV BCG immunization creates a unique cellular ecosystem in the airways, which primes and enables local myeloid cells to effectively clear Mtb upon challenge.

Artificial neural networks enable genome-scale simulations of intracellular signaling.

Mammalian cells adapt their functional state in response to external signals in form of ligands that bind receptors on the cell-surface. Mechanistically, this involves signal-processing through a complex network of molecular interactions that govern transcription factor activity patterns. Computer simulations of the information flow through this network could help predict cellular responses in health and disease. Here we develop a recurrent neural network framework constrained by prior knowledge of the signaling network with ligand-concentrations as input and transcription factor-activity as output. Applied to synthetic data, it predicts unseen test-data (Pearson correlation r = 0.98) and the effects of gene knockouts (r = 0.8). We stimulate macrophages with 59 different ligands, with and without the addition of lipopolysaccharide, and collect transcriptomics data. The framework predicts this data under cross-validation (r = 0.8) and knockout simulations suggest a role for RIPK1 in modulating the lipopolysaccharide response. This work demonstrates the feasibility of genome-scale simulations of intracellular signaling.

JAK inhibition in a patient with a STAT1 gain-of-function variant reveals STAT1 dysregulation as a common feature of aplastic anemia.

BACKGROUND: Idiopathic aplastic anemia is a potentially lethal disease, characterized by T cell-mediated autoimmune attack of bone marrow hematopoietic stem cells. Standard of care therapies (stem cell transplantation or immunosuppression) are effective but associated with a risk of serious toxicities. METHODS: An 18-year-old man presented with aplastic anemia in the context of a germline gain-of-function variant in STAT1. Treatment with the JAK1 inhibitor itacitinib resulted in a rapid resolution of aplastic anemia and a sustained recovery of hematopoiesis. Peripheral blood and bone marrow samples were compared before and after JAK1 inhibitor therapy. FINDINGS: Following therapy, samples showed a decrease in the plasma concentration of interferon-γ, a decrease in PD1-positive exhausted CD8+ T cell population, and a decrease in an interferon responsive myeloid population. Single-cell analysis of chromatin accessibility showed decreased accessibility of STAT1 across CD4+ and CD8+ T cells, as well as CD14+ monocytes. To query whether other cases of aplastic anemia share a similar STAT1-mediated pathophysiology, we examined a cohort of 9 patients with idiopathic aplastic anemia. Bone marrow from six of nine patients also displayed abnormal STAT1 hyper-activation. CONCLUSIONS: These findings raise the possibility that STAT1 hyperactivition defines a subset of idiopathic aplastic anemia patients for whom JAK inhibition may be an efficacious therapy. FUNDING: Funding was provided by the Massachusetts General Hospital Department of Medicine Pathways Program and NIH T32 AI007387. A trial registration is at https://clinicaltrials.gov/ct2/show/NCT03906318.

Uncovering complex molecular networks in host-pathogen interactions using systems biology.

Interactions between pathogens and their hosts can induce complex changes in both host and pathogen states to privilege pathogen survival or host clearance of the pathogen. To determine the consequences of specific host-pathogen interactions, a variety of techniques in microbiology, cell biology, and immunology are available to researchers. Systems biology that enables unbiased measurements of transcriptomes, proteomes, and other biomolecules has become increasingly common in the study of host-pathogen interactions. These approaches can be used to generate novel hypotheses or to characterize the effects of particular perturbations across an entire biomolecular network. With proper experimental design and complementary data analysis tools, high-throughput omics techniques can provide novel insights into the mechanisms that underlie processes from phagocytosis to pathogen immune evasion. Here, we provide an overview of the suite of biochemical approaches for high-throughput analyses of host-pathogen interactions, analytical frameworks for understanding the resulting datasets, and a vision for the future of this exciting field.