The immunoregulatory landscape of human tuberculosis granulomas

New Atomic Mass Tags for Enhanced Multiplexing Capability of Multiplexed Ion Beam Imaging Time-of-Flight (MIBI-TOF) Analysis

Antibodies conjugated to metal chelating polymers are routinely used in high-dimensional multiplexed single cell mass spectrometric imaging techniques, such as immunohistochemistry-based multiplexed ion beam imaging by time-of-flight (MIBI-TOF) mass spectrometry, imaging mass cytometry (IMC), and flow cytometry-based CyTOF. However, successful multiplexed capability of these techniques is heavily dependent on the stability of the metal-chelates used. Chelate stability is governed by the ionic radius of the metal used, which in some cases can fall below or exceed the optimal range for commercially available DTPA-based polymers. In this study, we have developed and optimized macrocyclic chelators for metals with relatively small (i.e., Ga) or large (i.e., Tl) atomic radii. In agreement with previously published studies, we observed NOTA to be a suitable chelator for Ga, whereas DOTA was found to be an ideal chelator for Tl and larger lanthanides, such as La, Ce, and Pr. DOTA and DTPA chelator dendrimers were synthesized and conjugated to primary antibodies that were subsequently used for tissue staining. Antibodies conjugated with the DOTA-dendrimer were more stable and exhibited more specific staining than those modified with the corresponding DTPA-dendrimer. With these new chelates, we incorporated seven new reporter channels into a highly multiplexed MIBI-TOF imaging study containing 44 protein epitope markers on various tissues. To the best of our knowledge, this is the largest multiplexed panel used to date for MIBI-TOF applications.

Multi-omic landscape of human gliomas from diagnosis to treatment and recurrence

Gliomas are among the most lethal cancers, with limited treatment options. To uncover hallmarks of therapeutic escape and tumor microenvironment (TME) evolution, we applied spatial proteomics, transcriptomics, and glycomics to 670 lesions from 310 adult and pediatric patients. Single-cell analysis shows high B7H3+ tumor cell prevalence in glioblastoma (GBM) and pleomorphic xanthoastrocytoma (PXA), while most gliomas, including pediatric cases, express targetable tumor antigens in less than 50% of tumor cells, potentially explaining trial failures. Longitudinal samples of isocitrate dehydrogenase (IDH)-mutant gliomas reveal recurrence driven by tumor-immune spatial reorganization, shifting from T-cell and vasculature-associated myeloid cell-enriched niches to microglia and CD206+ macrophage-dominated tumors. Multi-omic integration identified N-glycosylation as the best classifier of grade, while the immune transcriptome best predicted GBM survival. Provided as a community resource, this study opens new avenues for glioma targeting, classification, outcome prediction, and a baseline of TME composition across all stages.

Proapoptotic Bcl-2 inhibitor as potential host directed therapy for pulmonary tuberculosis

Mycobacterium tuberculosis establishes within host cells by inducing anti-apoptotic Bcl-2 family proteins, triggering necrosis, inflammation, and fibrosis. Here, we demonstrate that navitoclax, an orally bioavailable, small-molecule Bcl-2 inhibitor, significantly improves pulmonary tuberculosis (TB) treatments as a host-directed therapy. Addition of navitoclax to standard TB treatments at human equipotent dosing in mouse models of TB, inhibits Bcl-2 expression, leading to improved bacterial clearance, reduced tissue necrosis, fibrosis and decreased extrapulmonary bacterial dissemination. Using immunohistochemistry and flow cytometry, we show that navitoclax induces apoptosis in several immune cells, including CD68+ and CD11b+ cells. Finally, positron emission tomography (PET) in live animals using clinically translatable biomarkers for apoptosis (18F-ICMT-11) and fibrosis (18F-FAPI-74), demonstrates that navitoclax significantly increases apoptosis and reduces fibrosis in pulmonary tissues, which are confirmed in postmortem analysis. Our studies suggest that proapoptotic drugs such as navitoclax can potentially improve pulmonary TB treatments, reduce lung damage / fibrosis and may be protective against post-TB lung disease.

Microenvironments of tuberculous granuloma: advances and opportunities for therapy

The hallmark tissue lesions of tuberculosis (TB) are granulomas. These multicellular structures exhibit varying degrees of cellular complexity, are dynamic, and show considerable diversity within and between hosts. Categorization based on gross pathologic features, particularly caseation and necrosis, was historically coined prior to the identification of mycobacteria as the causative agent of TB. More recently, granuloma zonation based on immune cell composition, metabolite abundance, and physical characteristics has gained attention. With the advent of single-cell analyses, distinct microenvironments and cellular ecosystems within TB granulomas have been identified. We summarize the architecture of TB granulomas and highlight their cellular heterogeneity, including cell niches as well as physical factors such as oxygen gradients that modulate lesion fate. We discuss opportunities for therapy, highlighting new models and the power of in silico modeling to unravel granuloma features and trajectories. Understanding the relevance of the granuloma microenvironment to disease pathophysiology will facilitate the development of more effective interventions, such as host-directed therapies for TB.

Timing matters in macrophage/CD4+ T cell interactions: an agent-based model comparing Mycobacterium tuberculosis host-pathogen interactions between latently infected and naïve individuals

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a significant health challenge. Clinical manifestations of TB exist across a spectrum with a majority of infected individuals remaining asymptomatic, commonly referred to as latent TB infection (LTBI). In vitro models have demonstrated that cells from individuals with LTBI can better control Mtb growth and form granuloma-like structures more quickly, compared to cells from uninfected (Mtb-naïve) individuals. These in vitro results agree with animal and clinical evidence that LTBI protects, to some degree, against reinfection. However, the mechanisms by which LTBI might offer protection against reinfection remain unclear, and quantifying the relative contributions of multiple control mechanisms is challenging using experimental methods alone. To complement in vitro models, we have developed an in silico agent-based model to help elucidate host responses that might contribute to protection against reinfection. Our simulations indicate that earlier contact between macrophages and CD4+ T cells leads to LTBI simulations having more activated CD4+ T cells and, in turn, more activated infected macrophages, all of which contribute to a decreased bacterial load early on. Our simulations also demonstrate that granuloma-like structures support this early macrophage activation in LTBI simulations. We find that differences between LTBI and Mtb-naïve simulations are driven by TNFα and IFNγ-associated mechanisms as well as macrophage phagocytosis and killing mechanisms. Together, our simulations show how important the timing of the first interactions between innate and adaptive immune cells is, how this impacts infection progression, and why cells from LTBI individuals might be faster to respond to reinfection.IMPORTANCETuberculosis (TB) remains a significant global health challenge, with millions of new infections and deaths annually. Despite extensive research, the mechanisms by which latent TB infection (LTBI) confers protection against reinfection remain unclear. In this study, we developed an in silico agent-based model to simulate early immune responses to Mycobacterium tuberculosis infection based on experimental in vitro infection of human donor cells. Our simulations reveal that early interactions between macrophages and CD4+ T cells, driven by TNFα and IFNγ, are critical for bacterial control and granuloma formation in LTBI. These findings offer new insights into the immune processes involved in TB, which could inform the development of targeted vaccines and host-directed therapies. By integrating experimental data with computational predictions, our research provides a robust framework for understanding TB immunity and guiding future interventions to mitigate the global TB burden.

CD4 T cell dysfunction is associated with bacterial recrudescence during chronic tuberculosis

While most people contain Mycobacterium tuberculosis infection, some individuals develop active disease, usually within two years of infection. Why immunity fails after initially controlling infection is unknown. C57BL/6 mice control Mycobacterium tuberculosis for up to a year but ultimately succumb to disease. We hypothesize that the development of CD4 T cell dysfunction permits bacterial recrudescence. We developed a reductionist model to assess antigen-specific T cells during chronic infection and found evidence of CD4 T cell senescence and exhaustion. In C57BL/6 mice, CD4 T cells upregulate coinhibitory receptors and lose effector cytokine production. Single cell RNAseq shows that only a small number of CD4 T cells in the lungs of chronically infected mice are polyfunctional. While the origin and causal relationship between T-cell dysfunction and recrudescence remains uncertain, we propose T cell dysfunction leads to a feed-forward loop that causes increased bacillary numbers, greater T cell dysfunction, and progressive disease.

Multiomic analysis identifies suppressive myeloid cell populations in human TB granulomas

Tuberculosis (TB) remains a major global health challenge, particularly in the context of multidrug-resistant (MDR) Mycobacterium tuberculosis (Mtb). Host-directed therapies (HDTs) have been proposed as adjunctive therapy to enhance immune control of infection. Recently, one such HDT, pharmacologic modulation of myeloid-derived suppressor cells (MDSCs), has been proposed to treat MDR-TB. While MDSCs have been well characterized in cancer, their role in TB pathogenesis remains unclear. To investigate whether MDSCs or other myeloid suppressor populations contribute to TB granuloma microenvironments (GME), we performed spatial transcriptional profiling and single-cell immunophenotyping on eighty-four granulomas in lung specimens from three individuals with active disease. Granulomas were histologically classified based on H&E staining, and transcriptional signatures were compared across regions of interest (ROIs) at different states of granuloma maturation. Our analysis revealed that immune suppression within granuloma was not primarily driven by classical MDSCs but rather by multiple myeloid cell subsets, including dendritic cells expressing indoleamine 2,3 dioxygenase-1 expressing (IDO1+ DCs). IDO1+ DCs were the most frequently observed suppressive myeloid cells, particularly in cellular regions, and their spatial proximity to activated T cells suggested localized immunosuppression. Importantly, granulomas at different stages contained distinct proportions of suppressor myeloid cells, with necrotic and cellular regions showing different myeloid phenotypes that may influence granuloma progression. Gene set enrichment analysis (GSEA) further indicated that elevated IDO1 expression was associated with a complex immune response that balanced suppressive signaling, immune activation, and cellular metabolism. These findings suggest that classical MDSCs, as defined in tumor microenvironments, likely play a minor role in TB, whereas IDO1+ DCs may be key regulators of immune suppression in granulomas influencing local Mtb control in infected lung. A deeper understanding of the role of IDO1+ suppressive myeloid cells in TB granulomas is essential to assessing their potential as therapeutic targets in TB treatment.

Profiling immune cell tissue niches in the spatial -omics era

Immune responses require complex, spatially coordinated interactions between immune cells and their tissue environment. For decades, we have imaged tissue sections to visualize a limited number of immune-related macromolecules in situ, functioning as surrogates for cell types or processes of interest. However, this inevitably provides a limited snapshot of the tissue's immune landscape. Recent developments in high-throughput spatial -omics technologies, particularly spatial transcriptomics, and its application to human samples has facilitated a more comprehensive understanding of tissue immunity by mapping fine-grained immune cell states to their precise tissue location while providing contextual information about their immediate cellular and tissue environment. These data provide opportunities to investigate mechanisms underlying the spatial distribution of immune cells and its functional implications, including the identification of immune niches, although the criteria used to define this term have been inconsistent. Here, we review recent technological and analytic advances in multiparameter spatial profiling, focusing on how these methods have generated new insights in translational immunology. We propose a 3-step framework for the definition and characterization of immune niches, which is powerfully facilitated by new spatial profiling methodologies. Finally, we summarize current approaches to analyze adaptive immune repertoires and lymphocyte clonal expansion in a spatially resolved manner.

Assessing the risk of TB progression: Advances in blood-based biomarker research

This review addresses the significant advancements in the identification of blood-based prognostic biomarkers for tuberculosis (TB), highlighting the importance of early detection to prevent disease progression. The manuscript discusses various biomarker categories, including transcriptomic, proteomic, metabolomic, immune cell-based, cytokine-based, and antibody response-based markers, emphasizing their potential in predicting TB incidence. Despite promising results, practical application is hindered by high costs, technical complexities, and the need for extensive validation across diverse populations. Transcriptomic biomarkers, such as the Risk16 signature, show high sensitivity and specificity, while proteomic and metabolic markers provide insights into protein-level changes and biochemical alterations linked to TB. Immune cell and cytokine markers offer real-time data on the body's response to infection. The manuscript also explores the role of single-nucleotide polymorphisms in TB susceptibility and the challenges of implementing novel RNA signatures as point-of-care tests in low-resource settings. The review concludes that, while significant progress has been made, further research and development are necessary to refine these biomarkers, improve their practical application, and achieve the World Health Organization's TB elimination goals.

The Autoimmune Profiles in the Etiopathogenesis of Granulomatous Lobular Mastitis

OBJECTIVES

Granulomatous lobular mastitis (GLM) is a chronic breast inflammation with low remission and high recurrence. This study aimed to investigate GLM patients' autoimmune profiles and their correlation with GLM etiopathogenesis.

METHODS

Samples from GLM patients and fibroadenoma (FA) controls admitted to Shuguang Hospital between July 2021 and July 2022 were analyzed. Patients (107 GLM, 73 FA) underwent humoral immunity (C3, C4, IgG, IgM, IgE and IgA), cellular immunity (CD3+CD4+ T cells, CD3+CD8+ T cells, regulatory T cells and CD4/CD8 ratio) and cytokines (IL-1β, IL-6, IL-8, IL-10, IL-12 and TNF-α) tests. Immunohistochemical staining (10 GLM, 10 FA normal tissues) detected IL-1β, IL-6, CD86 and CD206, and immunofluorescence (3 GLM, 3 FA normal tissues) evaluated CD86 and CD206 expression. Multivariate analysis was done using logistic regression.

RESULTS

GLM featured granulomas with non-caseation necrosis and inflammatory cell infiltration. GLM patients showed higher C3 (P < 0.001), C4 (P < 0.001), IgE (P < 0.05), IgA (P < 0.05), IL-6 (P < 0.001), and IL-8 levels (P < 0.05). M1 (CD86) and M2 (CD206) macrophage markers were significantly higher in GLM than controls in both immunohistochemical and immunofluorescent staining (P < 0.05). The multivariate logistic regression analysis revealed that reproductive history (OR = 7.011, P < 0.01) and C3 expression level (OR = 5565.570, P < 0.001) were independent factors of GLM.

CONCLUSIONS

The results highlighted the crucial role of elevated M1 and M2 macrophages in GLM inflammation. GLM was associated with reproductive history, C3, C4, IgE, IgA, IL-6, and IL-8, with reproductive history and C3 as independent risks.

Prevention of tuberculosis in cynomolgus macaques by an attenuated Mycobacterium tuberculosis vaccine candidate

The need for novel vaccination strategies to control tuberculosis (TB) is underscored by the limited and variable efficacy of the currently licensed vaccine, Bacille Calmette-Guerin (BCG). SigH is critical for Mycobacterium tuberculosis (Mtb) to mitigate oxidative stress, and in its absence Mtb is unable to scavenge host oxidative/nitrosative bursts. The MtbΔsigH (ΔsigH) isogenic mutant induces signatures of the innate immunity in macrophages and protects rhesus macaques from a lethal Mtb challenge. To understand the immune mechanisms of protection via mucosal vaccination with ΔsigH, we employed the resistant cynomolgus macaque model; and our results show that ΔsigH vaccination significantly protects against lethal Mtb challenge in this species. ΔsigH-vaccinated macaques are devoid of granulomas and instead generate inducible bronchus associated lymphoid structures, and robust antigen-specific CD4+ and CD8+ T cell responses, driven by a hyper-immune, trained immunity-like phenotype in host macrophages with enhanced antigen presentation. Correlates of protection in ΔsigH-vaccinated macaques include gene signatures of T cell activation, IFNG production, including IFN-responsive, activated T cells, concomitant with IFNG production, and suppression of IDO+ Type I IFN-responsive macrophage recruitment. Thus, ΔsigH is a promising lead candidate for further development as an antitubercular vaccine.

The immunometabolic topography of tuberculosis granulomas governs cellular organization and bacterial control

Despite being heavily infiltrated by immune cells, tuberculosis (TB) granulomas often subvert the host response to Mycobacterium tuberculosis (Mtb) infection and support bacterial persistence. We previously discovered that human TB granulomas are enriched for immunosuppressive factors typically associated with tumor-immune evasion, raising the intriguing possibility that they promote tolerance to infection. In this study, our goal was to identify the prime drivers for establishing this tolerogenic niche and to determine if the magnitude of this response correlates with bacterial persistence. To do this, we conducted a multimodal spatial analysis of 52 granulomas from 16 non-human primates (NHP) who were infected with low dose Mtb for 9-12 weeks. Notably, each granuloma's bacterial burden was individually quantified allowing us to directly ask how granuloma spatial structure and function relate to infection control. We found that a universal feature of TB granulomas was partitioning of the myeloid core into two distinct metabolic environments, one of which is hypoxic. This hypoxic environment associated with pathologic immune cell states, dysfunctional cellular organization of the granuloma, and a near-complete blockade of lymphocyte infiltration that would be required for a successful host response. The extent of these hypoxia-associated features correlated with worsened bacterial burden. We conclude that hypoxia governs immune cell state and organization within granulomas and is a potent driver of subverted immunity during TB.

Building Spatiotemporal Understanding of Mycobacterium tuberculosis-Host Interactions

Heterogeneity during Mycobacterium tuberculosis (Mtb) infection greatly impacts disease outcome and complicates treatment. This heterogeneity encompasses many facets, spanning local differences in the host immune response to Mtb and the environment experienced by the bacterium, to nonuniformity in Mtb replication state. All of these facets are interlinked and each can affect Mtb susceptibility to antibiotic treatment. In-depth spatiotemporal understanding of Mtb-host interactions is thus critical to both fundamental comprehension of Mtb infection biology and for the development of effective therapeutic regimens. Such spatiotemporal understanding dictates the need for analysis at the single bacterium/cell level in the context of intact tissue architecture, which has been a significant technical challenge. Excitingly, innovations in spatial single cell methodology have opened the door to such studies, beginning to illuminate aspects ranging from intergranuloma differences in cellular composition and phenotype, to sublocation differences in Mtb physiology and replication state. In this perspective, we discuss recent studies that demonstrate the potential of these methodological advancements to reveal critical spatiotemporal insight into Mtb-host interactions, and highlight future avenues of research made possible by these advances.

Single-cell transcriptome analysis reveals the dysregulated monocyte state associated with tuberculosis progression

BACKGROUND

In tuberculosis (TB) infection, monocytes play a crucial role in regulating the balance between immune tolerance and immune response through various mechanisms. A deeper understanding of the roles of monocyte subsets in TB immune responses may facilitate the development of novel immunotherapeutic strategies and improve TB prevention and treatment.

METHODS

We retrieved and processed raw single-cell RNA-seq data from SRP247583. Single-cell RNA-seq combined with bioinformatics analysis was employed to investigate the roles of monocytes in TB progression.

RESULTS

Our findings revealed that classical monocytes expressing inflammatory mediators increased as the disease progressed, whereas non-classical monocytes expressing molecules associated with anti-pathogen infection were progressively depleted. Pseudotime analysis delineated the differentiation trajectory of monocytes from classical to intermediate to non-classical subsets. An abnormal differentiation trajectory to non-classical monocytes may represent a key mechanism underlying TB pathogenesis, with CEBPB and CORO1A identified as genes potentially related to TB development. Analysis of key transcription factors in non-classical monocytes indicated that IRF9 was the only downregulated transcription factor with high AUC activity in this subset. The expression of IRF9 exhibited a decreasing trend in both latent TB infection (LTBI) and active TB groups. Furthermore, dysregulation of transcription factor regulatory networks appeared to impair ferroptosis, with ferroptosis-associated genes MEF2C, MICU1, and PRR5 identified as potential targets of IRF9. Through cell communication analysis, we found that interactions between non-classical monocytes and other subpopulations may mediate TB progression, with MIF and LGALS9 highlighted as potential signaling pathways.

CONCLUSION

This study employs bioinformatics analysis in conjunction with single-cell sequencing technology to uncover the crucial role of monocyte subsets in tuberculosis infection.

Spatial Patterning Analysis of Cellular Ensembles (SPACE) finds complex spatial organization at the cell and tissue levels

Spatial patterns of cells and other biological elements drive physiologic and pathologic processes within tissues. While many imaging and transcriptomic methods document tissue organization, discerning these patterns is challenging, especially when they involve multiple elements in complex arrangements. To address this challenge, we present Spatial Patterning Analysis of Cellular Ensembles (SPACE), an R package for analysis of high-plex spatial data. SPACE is compatible with any data collection modality that records values (i.e., categorical cell/structure types or quantitative expression levels) at fixed spatial coordinates (i.e., 2d pixels or 3d voxels). SPACE detects not only broad patterns of co-occurrence but also context-dependent associations, quantitative gradients and orientations, and other organizational complexities. Via a robust information theoretic framework, SPACE explores all possible ensembles of tissue elements-single elements, pairs, triplets, and so on-and ranks the most strongly patterned ensembles. For single images, rankings reflect differences from random assortment. For sets of images, rankings reflect differences across sample groups (e.g., genotypes, treatments, timepoints, etc.). Further tools then characterize the nature of each pattern for intuitive interpretation. We validate SPACE and demonstrate its advantages using murine lymph node images for which ground truth has been defined. We then detect new patterns across varied datasets, including tumors and tuberculosis granulomas.

The correlation between immune profiles and pathological changes in pulmonary tuberculosis granulomas revealed by bioinformatic analysis and experimental validation

Most of Mycobacterium tuberculosis(Mtb) infection result in the formation of granulomas, which are often rich in immune cells, with subsequent clinical symptoms. However, the role of the immune system in the formation of tuberculosis granuloma structures has not been fully revealed. Here we first analyzed single-cell transcriptome and microenvironment spatial characteristics to reveal the contribution of immune cells to granuloma expansion with validation by immunofluorescence. We then integrated published peripheral blood transcriptome data for Mtb-infected patients and healthy controls. Immune cell profiles were deconvoluted and results were validated on a local cohort using flow cytometry. At the same time, an in-depth evaluation of the changes in the population and function of multiple peripheral blood immune cells during tuberculosis infection were conducted to define correlation with granuloma area. Finally, we screened 6 cytokines (IL6, IL8, IL10, IFNγ, TNFα, TGFβ) through machine learning bioinformatics and analyzed their correlation with the size of tuberculosis granuloma. Based on these findings, we confirmed that the dynamic variation in proportion of immune cells in peripheral blood and the levels of cytokine profiles are closely related to the occurrence and development of tuberculosis granuloma. This study provides a theoretical basis for the molecular mechanism of tuberculosis granuloma.

Retrotrans-genomics identifies aberrant THE1B endogenous retrovirus fusion transcripts in the pathogenesis of sarcoidosis

Transposon-like human element 1B (THE1B) originates from ancient retroviral sequences integrated into the primate genome approximately 50 million years ago, now accounting for at least 27,233 copies in the human genome, suggesting their extensive influence on human genomic architecture. Here we report identification of 19 THE1B fusion transcripts through short- and long-read RNA-seq analysis, 15 of which are previously unmapped, showing elevated expression in 16 individuals with sarcoid myopathy (SM), as compared to 400 controls with various other muscle diseases. Analysis of publicly available RNA-seq data indicated a correlation between the reduced expression of eight THE1B fusion transcripts and clinical improvement in individuals with cutaneous sarcoidosis receiving tofacitinib treatment. Single-cell or single-nucleus RNA-seq analyses of sarcoidosis not only confirmed these transcripts but also revealed a novel read-through transcript, SIRPB1-SIRPD, and TREM2.1, predominantly in granuloma-associated macrophages. The expression profiles of THE1B fusion transcripts in tuberculosis (TB) significantly differed from SM in single-cell RNA-seq data, suggesting that the differences between TB's caseous granulomas and sarcoidosis's non-caseous granulomas might be linked to disparate expression patterns of THE1B fusion transcripts. Our retrotrans-genomics approach has not only identified the genomic landscape of sarcoidosis but also provided new insights into its etiology.

Management of tuberculosis risk, screening and preventive therapy in patients with chronic autoimmune arthritis undergoing biotechnological and targeted immunosuppressive agents

Tuberculosis (TB) is the leading cause of death in the world from an infectious disease. Its etiologic agent, the Mycobacterium tuberculosis (Mtb), is a slow-growing bacterium that has coexisted in humans for thousands of years. According to the World Health Organization, 10.6 million new cases of TB and over 1 million deaths were reported in 2022. It is widely recognized that patients affected by chronic autoimmune arthritis such as rheumatoid arthritis (RA), psoriatic arthritis (PsA), and ankylosing spondylitis (AS) have an increased incidence rate of TB disease compared to the general population. As conceivable, the risk is associated with age ≥65 years and is higher in endemic regions, but immunosuppressive therapy plays a pivotal role. Several systematic reviews have analysed the impact of anti-TNF-α agents on the risk of TB in patients with chronic autoimmune arthritis, as well as for other biologic disease-modifying immunosuppressive anti-rheumatic drugs (bDMARDs) such as rituximab, abatacept, tocilizumab, ustekinumab, and secukinumab. However, the data are less robust compared to those available with TNF-α inhibitors. Conversely, data on anti-IL23 agents and JAK inhibitors (JAK-i), which have been more recently introduced for the treatment of RA and PsA/AS, are limited. TB screening and preventive therapy are recommended in Mtb-infected patients undergoing bDMARDs and targeted synthetic (ts)DMARDs. In this review, we evaluate the current evidence from randomized clinical trials, long-term extension studies, and real-life studies regarding the risk of TB in patients with RA, PsA, and AS treated with bDMARDs and tsDMARDs. According to the current evidence, TNF-α inhibitors carry the greatest risk of TB progression among bDMARDs and tsDMARDs, such as JAK inhibitors and anti-IL-6R agents. The management of TB screening and the updated preventive therapy are reported.

Spatial transcriptomic analysis of HIV and tuberculosis coinfection in a humanized mouse model reveals specific transcription patterns, immune responses and early morphological alteration signaling

Mycobacterium tuberculosis (Mtb) and human immunodeficiency virus (HIV) coinfection is one of the biggest public health concerns worldwide. Both pathogens are adept at modulating immune response and, in the case of Mtb, even inducing structural modification of the affected tissue. The present study aimed at understanding the early phenotypical and functional changes in immune cell infiltration in the affected organ, using a humanized mouse model. The humanized mice were infected with either HIV or Mtb in single infection, or with both pathogens in coinfection. Three weeks after the infection, lung samples were collected, and spatial transcriptomics analysis was performed. This analysis revealed high infiltration of CD4+ T cells in Mtb infection, but not in HIV or coinfection. Coinfected mice also showed a minimal number of NK cells compared to the other groups. In addition to infection status, histological features also influenced the immune cell infiltration pattern in the lungs. Two distinct airway regions with distinct immune cell abundance patterns were detected by spatial transcriptome profiling. A lymphoid cell aggregate detected in coinfection lung exhibited distinct transcript profile. The cellular architecture in the lymphoid cell aggregate did not follow the spatial patterns seen in mature granulomas. However, lymphoid cell aggregates exhibited granuloma gene expression signatures, and pathways associated with reactive oxygen species production, oxidative phosphorylation, and TGFβ and interferon signaling similar to granulomas. This study revealed specific transcription patterns, immune responses and morphological alteration signaling in the early stage of HIV and Mtb infections.

Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition

Immune checkpoint inhibition (ICI) has fundamentally changed cancer treatment. However, only a minority of patients with metastatic triple negative breast cancer (TNBC) benefit from ICI, and the determinants of response remain largely unknown. To better understand the factors influencing patient outcome, we assembled a longitudinal cohort with tissue from multiple timepoints, including primary tumor, pre-treatment metastatic tumor, and on-treatment metastatic tumor from 117 patients treated with ICI (nivolumab) in the phase II TONIC trial. We used highly multiplexed imaging to quantify the subcellular localization of 37 proteins in each tumor. To extract meaningful information from the imaging data, we developed SpaceCat, a computational pipeline that quantifies features from imaging data such as cell density, cell diversity, spatial structure, and functional marker expression. We applied SpaceCat to 678 images from 294 tumors, generating more than 800 distinct features per tumor. Spatial features were more predictive of patient outcome, including features like the degree of mixing between cancer and immune cells, the diversity of the neighboring immune cells surrounding cancer cells, and the degree of T cell infiltration at the tumor border. Non-spatial features, including the ratio between T cell subsets and cancer cells and PD-L1 levels on myeloid cells, were also associated with patient outcome. Surprisingly, we did not identify robust predictors of response in the primary tumors. In contrast, the metastatic tumors had numerous features which predicted response. Some of these features, such as the cellular diversity at the tumor border, were shared across timepoints, but many of the features, such as T cell infiltration at the tumor border, were predictive of response at only a single timepoint. We trained multivariate models on all of the features in the dataset, finding that we could accurately predict patient outcome from the pre-treatment metastatic tumors, with improved performance using the on-treatment tumors. We validated our findings in matched bulk RNA-seq data, finding the most informative features from the on-treatment samples. Our study highlights the importance of profiling sequential tumor biopsies to understand the evolution of the tumor microenvironment, elucidating the temporal and spatial dynamics underlying patient responses and underscoring the need for further research on the prognostic role of metastatic tissue and its utility in stratifying patients for ICI.

CD4 T cell dysfunction is associated with bacterial recrudescence during chronic tuberculosis

While most people contain Mycobacterium tuberculosis infection, some individuals develop active disease, usually within two years of infection. Why immunity fails after initially controlling infection is unknown. C57BL/6 mice control Mycobacterium tuberculosis for up to a year but ultimately succumb to disease. We hypothesize that the development of CD4 T cell dysfunction permits bacterial recrudescence. We developed a reductionist model to assess antigen-specific T cells during chronic infection and found evidence of CD4 T cell senescence and exhaustion. In C57BL/6 mice, CD4 T cells upregulate coinhibitory receptors and lose effector cytokine production. Single cell RNAseq shows that only a small number of CD4 T cells in the lungs of chronically infected mice are polyfunctional. While the origin and causal relationship between T-cell dysfunction and recrudescence remains uncertain, we propose T cell dysfunction leads to a feed-forward loop that causes increased bacillary numbers, greater T cell dysfunction, and progressive disease.

How macrophage heterogeneity affects tuberculosis disease and therapy

Macrophages are the primary host cell type for infection by Mycobacterium tuberculosis in vivo. Macrophages are also key immune effector cells that mediate the control of bacterial growth. However, the specific macrophage phenotypes that are required for optimal immune control of M. tuberculosis infection in vivo remain poorly defined. There are two distinct macrophage lineages in the lung, comprising embryonically derived, tissue-resident alveolar macrophages and recruited, blood monocyte-derived interstitial macrophages. Recent studies have shown that these lineages respond divergently to similar immune environments within the tuberculosis granuloma. Here, we discuss how the differing responses of macrophage lineages might affect the control or progression of tuberculosis disease. We suggest that the ability to reprogramme macrophage responses appropriately, through immunological or chemotherapeutic routes, could help to optimize vaccines and drug regimens for tuberculosis.

SMORE: spatial motifs reveal patterns in cellular architecture of complex tissues

Deciphering the link between tissue architecture and function requires methods to identify and interpret patterns in spatial arrangement of cells. We present SMORE, an approach to detect patterns in sequential arrangements of cells and examine their associated gene expression specializations. Applied to retina, brain, and embryonic tissue maps, SMORE identifies novel spatial motifs, including one that offers a new mechanism of action for type 1b bipolar cells. Structural signatures detected by SMORE also form a basis for classifying tissues. Together, our method provides a new framework for uncovering spatial complexity in tissue organization and offers novel insights into tissue function.

Leveraging insights from cancer to improve tuberculosis therapy

Exploring and exploiting the microenvironmental similarities between pulmonary tuberculosis (TB) granulomas and malignant tumors has revealed new strategies for more efficacious host-directed therapies (HDTs). This opinion article discusses a paradigm shift in TB therapeutic development, drawing on critical insights from oncology. We summarize recent efforts to characterize and overcome key shared features between tumors and granulomas, including excessive fibrosis, abnormal angiogenesis, hypoxia and necrosis, and immunosuppression. We provide specific examples of cancer therapy application to TB to overcome these microenvironmental abnormalities, including matrix-targeting therapies, antiangiogenic agents, and immune-stimulatory drugs. Finally, we propose a new framework for combining HDTs with anti-TB agents to maximize therapeutic delivery and efficacy while reducing treatment dosages, duration, and harmful side effects to benefit TB patients.

Immunological roads diverged: mapping tuberculosis outcomes in mice

The journey from phenotypic observation to causal genetic mechanism is a long and challenging road. For pathogens like Mycobacterium tuberculosis (Mtb), which causes tuberculosis (TB), host-pathogen coevolution has spanned millennia, costing millions of human lives. Mammalian models can systematically recapitulate host genetic variation, producing a spectrum of disease outcomes. Leveraging genome sequences and deep phenotyping data from infected mouse genetic reference populations (GRPs), quantitative trait locus (QTL) mapping approaches have successfully identified host genomic regions associated with TB phenotypes. Here, we review the ongoing optimization of QTL mapping study design alongside advances in mouse GRPs. These next-generation resources and approaches have enabled identification of novel host-pathogen interactions governing one of the most prevalent infectious diseases in the world today.

Flexible and robust cell type annotation for highly multiplexed tissue images

Identifying cell types in highly multiplexed images is essential for understanding tissue spatial organization. Current cell type annotation methods often rely on extensive reference images and manual adjustments. In this work, we present a tool, Robust Image-Based Cell Annotator (RIBCA), that enables accurate, automated, unbiased, and fine-grained cell type annotation for images with a wide range of antibody panels, without requiring additional model training or human intervention. Our tool has successfully annotated over 3 million cells, revealing the spatial organization of various cell types across more than 40 different human tissues. It is open-source and features a modular design, allowing for easy extension to additional cell types.

Immunopathology in human tuberculosis

Mycobacterium tuberculosis (M.tb) is a bacterial pathogen that has evolved in humans, and its interactions with the host are complex and best studied in humans. Myriad immune pathways are involved in infection control, granuloma formation, and progression to tuberculosis (TB) disease. Inflammatory cells, such as macrophages, neutrophils, conventional and unconventional T cells, B cells, NK cells, and innate lymphoid cells, interact via cytokines, cell-cell communication, and eicosanoid signaling to contain or eliminate infection but can alternatively mediate pathological changes required for pathogen transmission. Clinical manifestations include pulmonary and extrapulmonary TB, as well as post-TB lung disease. Risk factors for TB progression, in turn, largely relate to immune status and, apart from traditional chemotherapy, interventions primarily target immune mechanisms, highlighting the critical role of immunopathology in TB. Maintaining a balance between effector mechanisms to achieve protective immunity and avoid detrimental inflammation is central to the immunopathogenesis of TB. Many research gaps remain and deserve prioritization to improve our understanding of human TB immunopathogenesis.

Memory stem CD8+T cells in HIV/Mtb mono- and co-infection: characteristics, implications, and clinical significance

Human immunodeficiency Virus (HIV) and Mycobacterium tuberculosis (Mtb) co-infection presents a significant public health challenge worldwide. Comprehensive assessment of the immune response in HIV/Mtb co-infection is complex and challenging. CD8+T cells play a pivotal role in the adaptive immune response to both HIV and Mtb. The differentiation of CD8+T cells follow a hierarchical pattern, with varying degrees of exhaustion throughout the process. Memory stem T cells (TSCM cells) is at the apex of the memory T lymphocyte system, which has recently emerged as a promising target in immunotherapy. In this context, we discuss the alterations of CD8+TSCM cells in HIV/Mtb mono- and co-infection, their implications and clinical significance, and potential for improving immunotherapy.

Understanding the development of tuberculous granulomas: insights into host protection and pathogenesis, a review in humans and animals

Granulomas, organized aggregates of immune cells which form in response to Mycobacterium tuberculosis (Mtb), are characteristic but not exclusive of tuberculosis (TB). Despite existing investigations on TB granulomas, the determinants that differentiate host-protective granulomas from granulomas that contribute to TB pathogenesis are often disputed. Thus, the goal of this narrative review is to help clarify the existing literature on such determinants. We adopt the a priori view that TB granulomas are host-protective organelles and discuss the molecular and cellular determinants that induce protective granulomas and those that promote their failure. While reports about protective TB granulomas and their failure may initially seem contradictory, it is increasingly recognized that either deficiencies or excesses of the molecular and cellular components in TB granuloma formation may be detrimental to the host. More specifically, insufficient or excessive expression/representation of the following components have been reported to skew granulomas toward the less protective phenotype: (i) epithelioid macrophages; (ii) type 1 adaptive immune response; (iii) type 2 adaptive immune response; (iv) tumor necrosis factor; (v) interleukin-12; (vi) interleukin-17; (vii) matrix metalloproteinases; (viii) hypoxia in the TB granulomas; (ix) hypoxia inducible factor-1 alpha; (x) aerobic glycolysis; (xi) indoleamine 2,3-dioxygenase activity; (xii) heme oxygenase-1 activity; (xiii) immune checkpoint; (xiv) leukotriene A4 hydrolase activity; (xv) nuclear-factor-kappa B; and (xvi) transforming growth factor-beta. Rather, more precise and timely coordinated immune responses appear essential for eradication or containment of Mtb infection. Since there are several animal models of infection with Mtb, other species within the Mtb complex, and the surrogate Mycobacterium marinum - whether natural (cattle, elephants) or experimental (zebrafish, mouse, guinea pig, rabbit, mini pig, goat, non-human primate) infections - we also compared the TB granulomatous response and other pathologic lung lesions in various animals infected with one of these mycobacteria with that of human pulmonary TB. Identifying components that dictate the formation of host-protective granulomas and the circumstances that result in their failure can enhance our understanding of the macrocosm of human TB and facilitate the development of novel remedies - whether they be direct therapeutics or indirect interventions - to efficiently eliminate Mtb infection and prevent its pathologic sequelae.

Deciphering lung granulomas in HIV & TB co-infection: unveiling macrophages aggregation with IL6R/STAT3 activation

Tuberculosis (TB) remains a leading cause of mortality among individuals coinfected with HIV, characterized by progressive pulmonary inflammation. Despite TB's hallmark being focal granulomatous lung lesions, our understanding of the histopathological features and regulation of inflammation in HIV & TB coinfection remains incomplete. In this study, we aimed to elucidate these histopathological features through an immunohistochemistry analysis of HIV & TB co-infected and TB patients, revealing marked differences. Notably, HIV & TB granulomas exhibited aggregation of CD68 + macrophage (Mφ), while TB lesions predominantly featured aggregation of CD20+ B cells, highlighting distinct immune responses in coinfection. Spatial transcriptome profiling further elucidated CD68+ Mφ aggregation in HIV & TB, accompanied by activation of IL6 pathway, potentially exacerbating inflammation. Through multiplex immunostaining, we validated two granuloma types in HIV & TB versus three in TB, distinguished by cell architecture. Remarkably, in the two types of HIV & TB granulomas, CD68 + Mφ highly co-expressed IL6R/pSTAT3, contrasting TB granulomas' high IFNGRA/SOCS3 expression, indicating different signaling pathways at play. Thus, activation of IL6 pathway may intensify inflammation in HIV & TB-lungs, while SOCS3-enriched immune microenvironment suppresses IL6-induced over-inflammation in TB. These findings provide crucial insights into HIV & TB granuloma formation, shedding light on potential therapeutic targets, particularly for granulomatous pulmonary under HIV & TB co-infection. Our study emphasizes the importance of a comprehensive understanding of the immunopathogenesis of HIV & TB coinfection and suggests potential avenues for targeting IL6 signaling with SOCS3 activators or anti-IL6R agents to mitigate lung inflammation in HIV & TB coinfected individuals.

Generalized cell phenotyping for spatial proteomics with language-informed vision models

We present a novel approach to cell phenotyping for spatial proteomics that addresses the challenge of generalization across diverse datasets with varying marker panels. Our approach utilizes a transformer with channel-wise attention to create a language-informed vision model; this model's semantic understanding of the underlying marker panel enables it to learn from and adapt to heterogeneous datasets. Leveraging a curated, diverse dataset with cell type labels spanning the literature and the NIH Human BioMolecular Atlas Program (HuBMAP) consortium, our model demonstrates robust performance across various cell types, tissues, and imaging modalities. Comprehensive benchmarking shows superior accuracy and generalizability of our method compared to existing methods. This work significantly advances automated spatial proteomics analysis, offering a generalizable and scalable solution for cell phenotyping that meets the demands of multiplexed imaging data.

Decoding Spatial Tissue Architecture: A Scalable Bayesian Topic Model for Multiplexed Imaging Analysis

Recent progress in multiplexed tissue imaging is advancing the study of tumor microenvironments to enhance our understanding of treatment response and disease progression. Cellular neighborhood analysis is a popular computational approach for these complex image data. Despite its popularity, there are significant challenges, including high computational demands that limit feasibility for large-scale applications and the lack of a principled strategy for integrative analysis across images. This absence hampers the precise and consistent identification of spatial features and tracking of their dynamics over disease progression. To overcome these challenges, we introduce SpatialTopic, a spatial topic model designed to decode high-level spatial architecture across multiplexed tissue images. SpatialTopic integrates both cell type and spatial information within a topic modelling framework, originally developed for natural language processing and adapted for computer vision. Spatial information is incorporated into the flexible design of documents, representing densely overlapping regions in images. We employ an efficient collapsed Gibbs sampling algorithm for model inference. We benchmarked the performance against five state-of-the-art algorithms through various case studies using different single-cell spatial transcriptomic and proteomic imaging platforms across different tissue types. We show that SpatialTopic is highly scalable on large-scale image datasets with millions of cells, along with high precision and interpretability. Our findings demonstrate that SpatialTopic consistently identifies biologically and clinically significant spatial "topics" such as tertiary lymphoid structures (TLSs) and tracks dynamic changes in spatial features over disease progression. Its computational efficiency and broad applicability across various molecular imaging platforms will enhance the analysis of large-scale tissue imaging datasets.

Characteristics of Pulmonary Inflammation in Patients with Different Forms of Active Tuberculosis

Targeted treatment of tuberculosis-associated lung damage requires an understanding of the precise mechanisms of immunopathology. A major obstacle to the longitudinal study of tuberculosis (TB) immunopathogenesis in humans is the lack of serial lung biopsies during disease progression and treatment, which could be used to characterize local immune pathways involved in tissue damage. Understanding of the immunobiology of lung tissue damage in tuberculosis has largely been based on animal models. Our study looked for signs of inflammation in TB patients' lung biopsies. Results were compared between a site of infection and relatively healthy tissue outside the site. The most significant differences in the expression of microRNAs (miRs) and cytokine/chemokines were observed between the non-decayed tuberculoma and the surrounding parenchyma. In addition, these parameters showed almost no differences between the cavitary wall and surrounding tissue. This is an indication that the inflammatory process is more prevalent in fibrotic cavitary tuberculosis (FCT). In FCT subjects, no difference was observed between the cavity wall and the parenchyma in the production of key inflammatory factors such as IL-6, IL-11, IL-17, and IFNγ. This is an indication that the limits of the inflammatory response are broader in FCT. The expression levels of miR-191, miR-193a, miR-222, miR-223, miR-18, miR-155, miR-376c, miR-26a, miR-150, and miR-124 were not significantly different between the cavernous wall and lung tissue in patients with FCT, further confirming the spread of inflammatory and destructive processes beyond the focus of infection.

Single-cell sequencing: Current applications in various tuberculosis specimen types

Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single-cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single-cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single-cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real-world applications of the potential targets identified through single-cell sequencing for diagnostics, therapeutics and the development of effective vaccines.

Phenotypic Heterogeneity in Pathogens

Pathogen diversity within an infected organism has traditionally been explored through the lens of genetic heterogeneity. Hallmark studies have characterized how genetic diversity within pathogen subpopulations contributes to treatment escape and infectious disease progression. However, recent studies have begun to reveal the mechanisms by which phenotypic heterogeneity is established within genetically identical populations of invading pathogens. Furthermore, exciting new work highlights how these phenotypically heterogeneous subpopulations contribute to a pathogen population better equipped to handle the complex and fluctuating environment of a host organism. In this review, we focus on how bacterial pathogens, including Staphylococcus aureus, Salmonella typhimurium, Pseudomonas aeruginosa, and Mycobacterium tuberculosis, establish and maintain phenotypic heterogeneity, and we explore recent work demonstrating causative links between this heterogeneity and infection outcome.

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology

INTRODUCTION

Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immunotherapy. Due to the heterogeneous distribution of PD-L1, post-operative histopathology fails to accurately capture its expression in residual tumors, making intra-operative diagnosis crucial for GBM treatment strategies. However, the current methods for evaluating the expression of PD-L1 are still time-consuming.

OBJECTIVE

To overcome the PD-L1 heterogeneity and enable rapid, accurate, and label-free imaging of PD-L1 expression level in GBM IME at the tissue level.

METHODS

We proposed a novel intra-operative diagnostic method, Machine Learning Cascade (MLC)-based Raman histopathology, which uses a coordinate localization system (CLS), hierarchical clustering analysis (HCA), support vector machine (SVM), and similarity analysis (SA). This method enables visualization of PD-L1 expression in glioma cells, CD8+ T cells, macrophages, and normal cells in addition to the tumor/normal boundary. The study quantified PD-L1 expression levels using the tumor proportion, combined positive, and cellular composition scores (TPS, CPS, and CCS, respectively) based on Raman data. Furthermore, the association between Raman spectral features and biomolecules was examined biochemically.

RESULTS

The entire process from signal collection to visualization could be completed within 30 min. In an orthotopic glioma mouse model, the MLC-based Raman histopathology demonstrated a high average accuracy (0.990) for identifying different cells and exhibited strong concordance with multiplex immunofluorescence (84.31 %) and traditional pathologists' scoring (R2 ≥ 0.9). Moreover, the peak intensities at 837 and 874 cm-1 showed a positive linear correlation with PD-L1 expression level.

CONCLUSIONS

This study introduced a new and extendable diagnostic method to achieve rapid and accurate visualization of PD-L1 expression in GBM IMB at the tissular level, leading to great potential in GBM intraoperative diagnosis for guiding surgery and post-operative immunotherapy.

Pathogenesis of Post-Tuberculosis Lung Disease: Defining Knowledge Gaps and Research Priorities at the Second International Post-Tuberculosis Symposium

Post-tuberculosis (post-TB) lung disease is increasingly recognized as a major contributor to the global burden of chronic lung disease, with recent estimates indicating that over half of TB survivors have impaired lung function after successful completion of TB treatment. However, the pathologic mechanisms that contribute to post-TB lung disease are not well understood, thus limiting the development of therapeutic interventions to improve long-term outcomes after TB. This report summarizes the work of the Pathogenesis and Risk Factors Committee for the Second International Post-Tuberculosis Symposium, which took place in Stellenbosch, South Africa, in April 2023. The committee first identified six areas with high translational potential: 1) tissue matrix destruction, including the role of matrix metalloproteinase dysregulation and neutrophil activity; 2) fibroblasts and profibrotic activity; 3) granuloma fate and cell death pathways; 4) mycobacterial factors, including pathogen burden; 5) animal models; and 6) the impact of key clinical risk factors, including HIV, diabetes, smoking, malnutrition, and alcohol. We share the key findings from a literature review of those areas, highlighting knowledge gaps and areas where further research is needed.

Arginine methylation and respiratory disease

Arginine methylation, a vital post-translational modification, plays a pivotal role in numerous cellular functions such as signal transduction, DNA damage response and repair, regulation of gene transcription, mRNA splicing, and protein interactions. Central to this modification is the role of protein arginine methyltransferases (PRMTs), which have been increasingly recognized for their involvement in the pathogenesis of various respiratory diseases. This review begins with an exploration of the biochemical underpinnings of arginine methylation, shedding light on the intricate molecular regulatory mechanisms governed by PRMTs. It then delves into the impact of arginine methylation and the dysregulation of arginine methyltransferases in diverse pulmonary disorders. Concluding with a focus on the therapeutic potential and recent advancements in PRMT inhibitors, this article aims to offer novel perspectives and therapeutic avenues for the management and treatment of respiratory diseases.

Automated Diagnosis and Phenotyping of Tuberculosis Using Serum Metabolic Fingerprints

Tuberculosis (TB) stands as the second most fatal infectious disease after COVID-19, the effective treatment of which depends on accurate diagnosis and phenotyping. Metabolomics provides valuable insights into the identification of differential metabolites for disease diagnosis and phenotyping. However, TB diagnosis and phenotyping remain great challenges due to the lack of a satisfactory metabolic approach. Here, a metabolomics-based diagnostic method for rapid TB detection is reported. Serum metabolic fingerprints are examined via an automated nanoparticle-enhanced laser desorption/ionization mass spectrometry platform outstanding by its rapid detection speed (measured in seconds), minimal sample consumption (in nanoliters), and cost-effectiveness (approximately $3). A panel of 14 m z-1 features is identified as biomarkers for TB diagnosis and a panel of 4 m z-1 features for TB phenotyping. Based on the acquired biomarkers, TB metabolic models are constructed through advanced machine learning algorithms. The robust metabolic model yields a 97.8% (95% confidence interval (CI), 0.964-0.986) area under the curve (AUC) in TB diagnosis and an 85.7% (95% CI, 0.806-0.891) AUC in phenotyping. In this study, serum metabolic biomarker panels are revealed and develop an accurate metabolic tool with desirable diagnostic performance for TB diagnosis and phenotyping, which may expedite the effective implementation of the end-TB strategy.

Spatial transcriptomic sequencing reveals immune microenvironment features of Mycobacterium tuberculosis granulomas in lung and omentum

Granulomas are a key pathological feature of tuberculosis (TB), characterized by cell heterogeneity, spatial composition, and cellular interactions, which play crucial roles in granuloma progression and host prognosis. This study aims to analyze the transcriptome profiles of cell populations based on their spatial location and to understand the core transcriptome characteristics of granuloma formation and development. Methods In this study, we collected four clinical biopsy samples including Mycobacterium tuberculosis (Mtb) infected lung (MTB-L) and omentum tissues (MTB-O), as well as two lung and omentum biopsies from non-TB patients. The tissues were analyzed by spatial transcriptomics to create a spatial atlas. Utilizing cell enrichment scores and intercellular communication analysis, we investigated the transcriptome signatures of cell populations in various spatial regions and identified genes that may play a decisive role in the formation of pulmonary and omental tuberculosis granulomas. To validate our major findings, an in vitro TB model based on organoid-macrophage co-culture was established. Results Spatial transcriptomics mapped the cell composition and spatial distribution characteristics of tuberculosis granulomas in lung and omental tissues infected with Mtb. The characteristics and evolutionary relationships of major cell populations in granulomas reveal a shift in the immune microenvironment: from a predominance of B cells and fibroblasts in pulmonary granulomas to a predominance of myeloid cells and fibroblasts in omental granulomas. Furthermore, our data identified key differentially expressed genes across cell clusters and regions, showing that upregulation of collagen genes is a common feature of granulomas. Using an organoid-macrophage co-culture model, we demonstrated the notable efficacy of Thrombospondin-1 (THBS1) in reducing protein expression levels related to extracellular matrix remodeling. Conclusion These results provide insights into the pathogenesis and development of tuberculosis, enhancing our understanding of the composition and interactions of tuberculosis granuloma cells from a spatial perspective, and pave the way for novel adjuvant treatments for tuberculosis.

Proapoptotic Bcl-2 inhibitor as host directed therapy for pulmonary tuberculosis

Mycobacterium tuberculosis establishes within host cells by inducing anti-apoptotic Bcl-2 family proteins, triggering necrosis, inflammation, and fibrosis. Here, we demonstrate that navitoclax, an orally bioavailable, small-molecule Bcl-2 inhibitor, significantly improves pulmonary tuberculosis (TB) treatments as a host-directed therapy. Addition of navitoclax to standard TB treatments at human equipotent dosing in mouse models of TB, inhibits Bcl-2 expression, leading to improved bacterial clearance, reduced tissue damage / fibrosis and decreased extrapulmonary bacterial dissemination. Using immunohistochemistry and flow cytometry, we show that navitoclax induces apoptosis in several immune cells, including CD68 + and CD11b + cells. Finally, positron emission tomography (PET) in live animals using novel, clinically translatable biomarkers for apoptosis (18F-ICMT-11) and fibrosis (18F-FAPI-74) demonstrates that navitoclax significantly increases apoptosis and reduces fibrosis in pulmonary tissues, which are confirmed using post-mortem studies. Our studies suggest that proapoptotic drugs such as navitoclax can improve pulmonary TB treatments, and should be evaluated in clinical trials.

Unmasking the hidden impact of viruses on tuberculosis risk

Tuberculosis (TB) is a leading cause of mortality from an infectious disease. In this opinion article, we focus on accumulating scientific evidence indicating that viral infections may contribute to TB progression, possibly allowing novel preventive interventions. Viruses can remodel the mammalian immune system, potentially modulating the risk of reactivating latent microbes such as Mycobacterium tuberculosis (Mtb). Evidence is mixed regarding the impact of emergent viruses such as SARS-CoV-2 on the risk of TB. Therefore, we posit that important knowledge gaps include elucidating which viral families increase TB risk and whether these provide unique or shared immune mechanisms. We also propose potential future research to define the contribution of viruses to TB pathogenesis.

Heterogeneity in immune cell composition is associated with Mycobacterium tuberculosis replication at the granuloma level

The control of bacterial growth is key to the prevention and treatment of tuberculosis (TB). Granulomas represent independent foci of the host immune response that present heterogeneous capacity for control of bacterial growth. At the whole tissue level, B cells and CD4 or CD8 T cells have an established role in immune protection against TB. Immune cells interact within each granuloma response, but the impact of granuloma immune composition on bacterial replication remains unknown. Here we investigate the associations between immune cell composition, including B cell, CD4, and CD8 T cells, and the state of replicating Mycobacterium tuberculosis (Mtb) within the granuloma. A measure of ribosomal RNA synthesis, the RS ratio®, represents a proxy measure of Mtb replication at the whole tissue level. We adapted the RS ratio through use of in situ hybridization, to identify replicating and non-replicating Mtb within each designated granuloma. We applied a regression model to characterize the associations between immune cell populations and the state of Mtb replication within each respective granuloma. In the evaluation of nearly 200 granulomas, we identified heterogeneity in both immune cell composition and proportion of replicating bacteria. We found clear evidence of directional associations between immune cell composition and replicating Mtb. Controlling for vaccination status and endpoint post-infection, granulomas with lower CD4 or higher CD8 cell counts are associated with a higher percent of replicating Mtb. Conversely, changes in B cell proportions were associated with little change in Mtb replication. This study establishes heterogeneity across granulomas, demonstrating that certain immune cell types are differentially associated with control of Mtb replication. These data suggest that evaluation at the granuloma level may be imperative to identifying correlates of immune protection.

HIV-MTB Co-Infection Reduces CD4+ T Cells and Affects Granuloma Integrity

Granuloma is a crucial pathological feature of tuberculosis (TB). The relationship between CD4+ T cells in both peripheral blood and granulomatous tissue, and the integrity of granulomas in Human Immunodeficiency Virus (HIV)-MTB co-infection, remains unexplored. This study collected biopsy specimens from 102 TB patients (53 with HIV-MTB co-infection and 49 only with TB). Hematoxylin and eosin (HE) staining and immunohistochemical staining were performed, followed by microscopic examination of the integrity of tuberculous granulomas. Through statistical analysis of peripheral blood CD4+ T cell counts, tissue CD4+ T cell proportion, and the integrity of granulomas, it was observed that HIV infection leads to poor formation of tuberculous granulomas. Peripheral blood CD4+ T cell counts were positively correlated with granuloma integrity, and there was a similar positive correlation between tissue CD4+ T cell proportions and granuloma integrity. Additionally, a positive correlation was found between peripheral blood CD4+ T cell counts and the proportion of CD4+ T cells in granuloma tissues. Therefore, HIV infection could impact the morphology and structure of tuberculous granulomas, with a reduced proportion of both peripheral blood and tissue CD4+ T lymphocytes.

Imaging the Architecture of Granulomas Induced by Mycobacterium tuberculosis Infection with Single-molecule Fluorescence In Situ Hybridization

Granulomas are an important hallmark of Mycobacterium tuberculosis infection. They are organized and dynamic structures created when immune cells assemble around the sites of infection in the lungs that locally restrict M. tuberculosis growth and the host's inflammatory responses. The cellular architecture of granulomas is traditionally studied by immunofluorescence labeling of surface markers on the host cells. However, very few Abs are available for model animals used in tuberculosis research, such as nonhuman primates and rabbits, and secreted immunological markers such as cytokines cannot be imaged in situ using Abs. Furthermore, traditional phenotypic surface markers do not provide sufficient resolution for the detection of the many subtypes and differentiation states of immune cells. Using single-molecule fluorescence in situ hybridization (smFISH) and its derivatives, amplified smFISH and iterative smFISH, we developed a platform for imaging mRNAs encoding immune markers in rabbit and macaque tuberculosis granulomas. Multiplexed imaging for several mRNA and protein markers was followed by quantitative measurement of the expression of these markers in single cells. An analysis of the combinatorial expressions of these markers allowed us to classify the cells into several subtypes, and to chart their densities within granulomas. For one mRNA target, hypoxia-inducible factor-1α, we imaged its mRNA and protein in the same cells, demonstrating the specificity of the probes. This method paves the way for defining granular differentiation states and cell subtypes from transcriptomic data, identifying key mRNA markers for these cell subtypes, and then locating the cells in the spatial context of granulomas.

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.

Imputing Single-Cell Protein Abundance in Multiplex Tissue Imaging

Multiplex tissue imaging are a collection of increasingly popular single-cell spatial proteomics and transcriptomics assays for characterizing biological tissues both compositionally and spatially. However, several technical issues limit the utility of multiplex tissue imaging, including the limited number of molecules (proteins and RNAs) that can be assayed, tissue loss, and protein probe failure. In this work, we demonstrate how machine learning methods can address these limitations by imputing protein abundance at the single-cell level using multiplex tissue imaging datasets from a breast cancer cohort. We first compared machine learning methods' strengths and weaknesses for imputing single-cell protein abundance. Machine learning methods used in this work include regularized linear regression, gradient-boosted regression trees, and deep learning autoencoders. We also incorporated cellular spatial information to improve imputation performance. Using machine learning, single-cell protein expression can be imputed with mean absolute error ranging between 0.05-0.3 on a [0,1] scale. Finally, we used imputed data to predict whether single cells were more likely to come from pre-treatment or post-treatment biopsies. Our results demonstrate (1) the feasibility of imputing single-cell abundance levels for many proteins using machine learning; (2) how including cellular spatial information can substantially enhance imputation results; and (3) the use of single-cell protein abundance levels in a use case to demonstrate biological relevance.

Indoleamine-2,3-dioxygenase inhibition improves immunity and is safe for concurrent use with cART during Mtb/SIV coinfection

Chronic immune activation promotes tuberculosis (TB) reactivation in the macaque Mycobacterium tuberculosis (M. tuberculosis)/SIV coinfection model. Initiating combinatorial antiretroviral therapy (cART) early lowers the risk of TB reactivation, but immune activation persists. Studies of host-directed therapeutics (HDTs) that mitigate immune activation are, therefore, required. Indoleamine 2,3, dioxygenase (IDO), a potent immunosuppressor, is one of the most abundantly induced proteins in NHP and human TB granulomas. Inhibition of IDO improves immune responses in the lung, leading to better control of TB, including adjunctive to TB chemotherapy. The IDO inhibitor D-1 methyl tryptophan (D1MT) is, therefore, a bona fide TB HDT candidate. Since HDTs against TB are likely to be deployed in an HIV coinfection setting, we studied the effect of IDO inhibition in M. tuberculosis/SIV coinfection, adjunctive to cART. D1MT is safe in this setting, does not interfere with viral suppression, and improves the quality of CD4+ and CD8+ T cell responses, including reconstitution, activation and M. tuberculosis-specific cytokine production, and access of CD8+ T cells to the lung granulomas; it reduces granuloma size and necrosis, type I IFN expression, and the recruitment of inflammatory IDO+ interstitial macrophages (IMs). Thus, trials evaluating the potential of IDO inhibition as HDT in the setting of cART in M. tuberculosis/HIV coinfected individuals are warranted.

Modeling nontuberculous mycobacterial infections in zebrafish

The incidence of infections due to nontuberculous mycobacteria (NTM) has increased rapidly in recent years, surpassing tuberculosis in developed countries. Due to inherent antimicrobial resistance, NTM infections are particularly difficult to treat with low cure rates. There is an urgent need to understand NTM pathogenesis and to develop novel therapeutic approaches for the treatment of NTM diseases. Zebrafish have emerged as an excellent animal model due to genetic amenability and optical transparency during embryonic development, allowing spatiotemporal visualization of host-pathogen interactions. Furthermore, adult zebrafish possess fully functional innate and adaptive immunity and recapitulate important pathophysiological hallmarks of mycobacterial infection. Here, we report recent breakthroughs in understanding the hallmarks of NTM infections using the zebrafish model.

Single Cell Analysis of Peripheral TB-Associated Granulomatous Lymphadenitis

We successfully employed a single cell RNA sequencing (scRNA-seq) approach to describe the cells and the communication networks characterizing granulomatous lymph nodes of TB patients. When mapping cells from individual patient samples, clustered based on their transcriptome similarities, we uniformly identify several cell types that known to characterize human and non-human primate granulomas. Whether high or low Mtb burden, we find the T cell cluster to be one of the most abundant. Many cells expressing T cell markers are clearly quantifiable within this CD3 expressing cluster. Other cell clusters that are uniformly detected, but that vary dramatically in abundance amongst the individual patient samples, are the B cell, plasma cell and macrophage/dendrocyte and NK cell clusters. When we combine all our scRNA-seq data from our current 23 patients (in order to add power to cell cluster identification in patient samples with fewer cells), we distinguish T, macrophage, dendrocyte and plasma cell subclusters, each with distinct signaling activities. The sizes of these subclusters also varies dramatically amongst the individual patients. In comparing FNA composition we noted trends in which T cell populations and macrophage/dendrocyte populations were negatively correlated with NK cell populations. In addition, we also discovered that the scRNA-seq pipeline, designed for quantification of human cell mRNA, also detects Mtb RNA transcripts and associates them with their host cell's transcriptome, thus identifying individual infected cells. We hypothesize that the number of detected bacterial transcript reads provides a measure of Mtb burden, as does the number of Mtb-infected cells. The number of infected cells also varies dramatically in abundance amongst the patient samples. CellChat analysis identified predominating signaling pathways amongst the cells comprising the various granulomas, including many interactions between stromal or endothelial cells and the other component cells, such as Collagen, FN1 and Laminin,. In addition, other more selective communications pathways, including MIF, MHC-1, MHC-2, APP, CD 22, CD45, and others, are identified as originating or being received by individual immune cell components.