The immunoregulatory landscape of human tuberculosis granulomas

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.

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.

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.

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.

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.

Therapeutic Modulation of Arginase with nor-NOHA Alters Immune Responses in Experimental Mouse Models of Pulmonary Tuberculosis including in the Setting of Human Immunodeficiency Virus (HIV) Co-Infection

L-arginine metabolism is strongly linked with immunity to mycobacteria, primarily through the antimicrobial activity of nitric oxide (NO). The potential to modulate tuberculosis (TB) outcomes through interventions that target L-arginine pathways are limited by an incomplete understanding of mechanisms and inadequate in vivo modeling. These gaps in knowledge are compounded for HIV and Mtb co-infections, where activation of arginase-1 due to HIV infection may promote survival and replication of both Mtb and HIV. We utilized in vitro and in vivo systems to determine how arginase inhibition using Nω-hydroxy-nor-L-arginine (nor-NOHA) alters L-arginine pathway metabolism relative to immune responses and disease outcomes following Mtb infection. Treatment with nor-NOHA polarized murine macrophages (RAW 264.7) towards M1 phenotype, increased NO, and reduced Mtb in RAW macrophages. In Balb/c mice, nor-NOHA reduced pulmonary arginase and increased the antimicrobial metabolite spermine in association with a trend towards reduced Mtb CFU in lung. In humanized immune system (HIS) mice, HIV infection increased plasma arginase and heightened the pulmonary arginase response to Mtb. Treatment with nor-NOHA increased cytokine responses to Mtb and Mtb/HIV in lung tissue but did not significantly alter bacterial burden or viral load. Our results suggest that L-arginine pathway modulators may have potential as host-directed therapies to augment antibiotics in TB chemotherapy.

Automated classification of cellular expression in multiplexed imaging data with Nimbus

Multiplexed imaging offers a powerful approach to characterize the spatial topography of tissues in both health and disease. To analyze such data, the specific combination of markers that are present in each cell must be enumerated to enable accurate phenotyping, a process that often relies on unsupervised clustering. We constructed the Pan-Multiplex (Pan-M) dataset containing 197 million distinct annotations of marker expression across 15 different cell types. We used Pan-M to create Nimbus, a deep learning model to predict marker positivity from multiplexed image data. Nimbus is a pre-trained model that uses the underlying images to classify marker expression across distinct cell types, from different tissues, acquired using different microscope platforms, without requiring any retraining. We demonstrate that Nimbus predictions capture the underlying staining patterns of the full diversity of markers present in Pan-M. We then show how Nimbus predictions can be integrated with downstream clustering algorithms to robustly identify cell subtypes in image data. We have open-sourced Nimbus and Pan-M to enable community use at https://github.com/angelolab/Nimbus-Inference.

Humoral pathways of innate immune regulation in granuloma formation

The humoral arm of mammalian innate immunity regulates several molecular mechanisms involved in resistance to pathogens, inflammation, and tissue repair. Recent studies highlight the crucial role played by humoral mediators in granulomatous inflammation. However the molecular mechanisms linking the function of these soluble molecules to the initiation and maintenance of granulomas remain elusive. We propose that humoral innate immunity coordinates fundamental physiological processes in macrophages which, in turn, initiate activation and transformation events that enable granuloma formation. We discuss the involvement of humoral mediators in processes such as immune activation, phagocytosis, metabolism, and tissue remodeling, and how these can dictate macrophage functionality during granuloma formation. These advances present opportunities for discovering novel disease factors and developing targeted, more effective treatments for granulomatous diseases.

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

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

The function of CD36 in Mycobacterium tuberculosis infection

CD36 is a scavenger receptor that has been reported to function as a signaling receptor that responds to pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) and could integrate metabolic pathways and cell signaling through its dual functions. Thereby influencing activation to regulate the immune response and immune cell differentiation. Recent studies have revealed that CD36 plays critical roles in the process of lipid metabolism, inflammatory response and immune process caused by Mycobacterium tuberculosis infection. This review will comprehensively investigate CD36's functions in lipid uptake and processing, inflammatory response, immune response and therapeutic targets and biomarkers in the infection process of M. tuberculosis. The study also raised outstanding issues in this field to designate future directions.

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

Spatial patterns of cells and other biological elements drive both 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 patterns that differ from random assortment. For sets of images, rankings reflect patterns that differ across sample groups (e.g., genotypes, treatments, timepoints, etc.). Further tools then thoroughly 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 use SPACE to detect new patterns across varied datasets, including tumors and tuberculosis granulomas.

A novel humanized mouse model for HIV and tuberculosis co-infection studies

Background

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), continues to be a major public health problem worldwide. The human immunodeficiency virus (HIV) is another equally important life-threatening pathogen. HIV infection decreases CD4+ T cell levels markedly increasing Mtb co-infections. An appropriate animal model for HIV/Mtb co-infection that can recapitulate the diversity of the immune response in humans during co-infection would facilitate basic and translational research in HIV/Mtb infections. Herein, we describe a novel humanized mouse model.

Methods

The irradiated NSG-SGM3 mice were transplanted with human CD34+ hematopoietic stem cells, and the humanization was monitored by staining various immune cell markers for flow cytometry. They were challenged with HIV and/or Mtb, and the CD4+ T cell depletion and HIV viral load were monitored over time. Before necropsy, the live mice were subjected to pulmonary function test and CT scan, and after sacrifice, the lung and spleen homogenates were used to determine Mtb load (CFU) and cytokine/chemokine levels by multiplex assay, and lung sections were analyzed for histopathology. The mouse sera were subjected to metabolomics analysis.

Results

Our humanized NSG-SGM3 mice were able to engraft human CD34+ stem cells, which then differentiated into a full-lineage of human immune cell subsets. After co-infection with HIV and Mtb, these mice showed decrease in CD4+ T cell counts overtime and elevated HIV load in the sera, similar to the infection pattern of humans. Additionally, Mtb caused infections in both lungs and spleen, and induced granulomatous lesions in the lungs. Distinct metabolomic profiles were also observed in the tissues from different mouse groups after co-infections.

Conclusion

The humanized NSG-SGM3 mice are able to recapitulate the pathogenic effects of HIV and Mtb infections and co-infection at the pathological, immunological and metabolism levels and are therefore a reproducible small animal model for studying HIV/Mtb co-infection.

Myeloid cell expression of CD200R is modulated in active TB disease and regulates Mycobacterium tuberculosis infection in a biomimetic model

A robust immune response is required for resistance to pulmonary tuberculosis (TB), the primary disease caused by Mycobacterium tuberculosis (Mtb). However, pharmaceutical inhibition of T cell immune checkpoint molecules can result in the rapid development of active disease in latently infected individuals, indicating the importance of T cell immune regulation. In this study, we investigated the potential role of CD200R during Mtb infection, a key immune checkpoint for myeloid cells. Expression of CD200R was consistently downregulated on CD14+ monocytes in the blood of subjects with active TB compared to healthy controls, suggesting potential modulation of this important anti-inflammatory pathway. In homogenized TB-diseased lung tissue, CD200R expression was highly variable on monocytes and CD11b+HLA-DR+ macrophages but tended to be lowest in the most diseased lung tissue sections. This observation was confirmed by fluorescent microscopy, which showed the expression of CD200R on CD68+ macrophages surrounding TB lung granuloma and found expression levels tended to be lower in macrophages closest to the granuloma core and inversely correlated with lesion size. Antibody blockade of CD200R in a biomimetic 3D granuloma-like tissue culture system led to significantly increased Mtb growth. In addition, Mtb infection in this system reduced gene expression of CD200R. These findings indicate that regulation of myeloid cells via CD200R is likely to play an important part in the immune response to TB and may represent a potential target for novel therapeutic intervention.

CD4-mediated immunity shapes neutrophil-driven tuberculous pathology

Pulmonary Mycobacterium tuberculosis (Mtb) infection results in highly heterogeneous lesions ranging from granulomas with central necrosis to those primarily comprised of alveolitis. While alveolitis has been associated with prior immunity in human post-mortem studies, the drivers of these distinct pathologic outcomes are poorly understood. Here, we show that these divergent lesion structures can be modeled in C3HeB/FeJ mice and are regulated by prior immunity. Using quantitative imaging, scRNAseq, and flow cytometry, we demonstrate that Mtb infection in the absence of prior immunity elicits dysregulated neutrophil recruitment and necrotic granulomas. In contrast, prior immunity induces rapid recruitment and activation of T cells, local macrophage activation, and diminished late neutrophil responses. Depletion studies at distinct infection stages demonstrated that neutrophils are required for early necrosis initiation and necrosis propagation at chronic stages, whereas early CD4 T cell responses prevent neutrophil feedforward circuits and necrosis. Together, these studies reveal fundamental determinants of tuberculosis lesion structure and pathogenesis, which have important implications for new strategies to prevent or treat tuberculosis.

DELVE: feature selection for preserving biological trajectories in single-cell data

Single-cell technologies can measure the expression of thousands of molecular features in individual cells undergoing dynamic biological processes. While examining cells along a computationally-ordered pseudotime trajectory can reveal how changes in gene or protein expression impact cell fate, identifying such dynamic features is challenging due to the inherent noise in single-cell data. Here, we present DELVE, an unsupervised feature selection method for identifying a representative subset of molecular features which robustly recapitulate cellular trajectories. In contrast to previous work, DELVE uses a bottom-up approach to mitigate the effects of confounding sources of variation, and instead models cell states from dynamic gene or protein modules based on core regulatory complexes. Using simulations, single-cell RNA sequencing, and iterative immunofluorescence imaging data in the context of cell cycle and cellular differentiation, we demonstrate how DELVE selects features that better define cell-types and cell-type transitions. DELVE is available as an open-source python package: https://github.com/jranek/delve .

A Novel Humanized Mouse Model for HIV and Tuberculosis Co-infection Studies

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), continues to be a major public health problem worldwide. The human immunodeficiency virus (HIV) is another equally important life-threatening pathogen. Further, co-infections with HIV and Mtb have severe effects in the host, with people infected with HIV being fifteen to twenty-one times more likely to develop active TB. The use of an appropriate animal model for HIV/Mtb co-infection that can recapitulate the diversity of the immune response in humans would be a useful tool for conducting basic and translational research in HIV/Mtb infections. The present study was focused on developing a humanized mouse model for investigations on HIV-Mtb co-infection. Using NSG-SGM3 mice that can engraft human stem cells, our studies showed that they were able to engraft human CD34+ stem cells which then differentiate into a full-lineage of human immune cell subsets. After co-infection with HIV and Mtb, these mice showed decrease in CD4+ T cell counts overtime and elevated HIV load in the sera, similar to the infection pattern of humans. Additionally, Mtb caused infections in both lungs and spleen, and induced the development of granulomatous lesions in the lungs, detected by CT scan and histopathology. Distinct metabolomic profiles were also observed in the tissues from different mouse groups after co-infections. Our results suggest that the humanized NSG-SGM3 mice are able to recapitulate the effects of HIV and Mtb infections and co-infection in the human host at pathological, immunological and metabolism levels, providing a dependable small animal model for studying HIV/Mtb co-infection.

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.

Spatial transcriptomics and the anatomical pathologist: Molecular meets morphology

In recent years anatomical pathology has been revolutionised by the incorporation of molecular findings into routine diagnostic practice, and in some diseases the presence of specific molecular alterations are now essential for diagnosis. Spatial transcriptomics describes a group of technologies that provide up to transcriptome-wide expression profiling while preserving the spatial origin of the data, with many of these technologies able to provide these data using a single tissue section. Spatial transcriptomics allows expression profiling of highly specific areas within a tissue section potentially to subcellular resolution, and allows correlation of expression data with morphology, tissue type and location relative to other structures. While largely still research laboratory-based, several spatial transcriptomics methods have now achieved compatibility with formalin-fixed paraffin-embedded tissue (FFPE), allowing their use in diagnostic tissue samples, and with further development potentially leading to their incorporation in routine anatomical pathology practice. This mini review provides an overview of spatial transcriptomics methods, with an emphasis on platforms compatible with FFPE tissue, approaches to assess the data and potential applications in anatomical pathology practice.

Spatial proteomics of immune microenvironment in nonalcoholic steatohepatitis-associated hepatocellular carcinoma

BACKGROUND AND AIMS

NASH-HCC is inherently resistant to immune checkpoint blockade, but its tumor immune microenvironment is largely unknown.

APPROACH AND RESULTS

We applied the imaging mass cytometry to construct a spatially resolved single-cell atlas from the formalin-fixed and paraffin-embedded tissue sections from patients with NASH-HCC, virus-HCC (HBV-HCC and HCV-HCC), and healthy donors. Based on 35 biomarkers, over 750,000 individual cells were categorized into 13 distinct cell types, together with the expression of key immune functional markers. Higher infiltration of T cells, myeloid-derived suppressor cell (MDSCs), and tumor-associated macrophages (TAMs) in HCC compared to controls. The distribution of immune cells in NASH-HCC is spatially heterogeneous, enriched at adjacent normal tissues and declined toward tumors. Cell-cell connections analysis revealed the interplay of MDSCs and TAMs with CD8 + T cells in NASH-HCC. In particular, exhausted programmed cell death 1 (PD-1 + )CD8 + T cells connected with programmed cell death-ligand 1 (PD-L1 + )/inducible T cell costimulator (ICOS + ) MDSCs and TAMs in NASH-HCC, but not in viral HCC. In contrast, CD4 + /CD8 + T cells with granzyme B positivity were reduced in NASH-HCC. Tumor cells expressed low PD-L1 and showed few connections with immune cells.

CONCLUSIONS

Our work provides the first detailed spatial map of single-cell phenotypes and multicellular connections in NASH-HCC. We demonstrate that interactions between MDSCs and TAMs with effector T cells underlie immunosuppression in NASH-HCC and are an actionable target.

Temporal and cellular analysis of granuloma development in mycobacterial infected adult zebrafish

Because granulomas are a hallmark of tuberculosis pathogenesis, the study of the dynamic changes in their cellular composition and morphological character can facilitate our understanding of tuberculosis pathogenicity. Adult zebrafish infected with Mycobacterium marinum form granulomas that are similar to the granulomas in human patients with tuberculosis and therefore have been used to study host-mycobacterium interactions. Most studies of zebrafish granulomas, however, have focused on necrotic granulomas, while a systematic description of the different stages of granuloma formation in the zebrafish model is lacking. Here, we characterized the stages of granulomas in M. marinum-infected zebrafish, including early immune cell infiltration, nonnecrotizing granulomas, and necrotizing granulomas, using corresponding samples from patients with pulmonary tuberculosis as references. We combined hematoxylin and eosin staining and in situ hybridization to identify the different immune cell types and follow their spatial distribution in the different stages of granuloma development. The macrophages in zebrafish granulomas were shown to belong to distinct subtypes: epithelioid macrophages, foamy macrophages, and multinucleated giant cells. By defining the developmental stages of zebrafish granulomas and the spatial distribution of the different immune cells they contain, this work provides a reference for future studies of mycobacterial granulomas and their immune microenvironments.

Immune mapping of human tuberculosis and sarcoidosis lung granulomas

Tuberculosis (TB) and sarcoidosis are both granulomatous diseases. Here, we compared the immunological microenvironments of granulomas from TB and sarcoidosis patients using in situ sequencing (ISS) transcriptomic analysis and multiplexed immunolabeling of tissue sections. TB lesions consisted of large necrotic and cellular granulomas, whereas "multifocal" granulomas with macrophages or epitheloid cell core and a T-cell rim were observed in sarcoidosis samples. The necrotic core in TB lesions was surrounded by macrophages and encircled by a dense T-cell layer. Within the T-cell layer, compact B-cell aggregates were observed in most TB samples. These B-cell clusters were vascularized and could contain defined B-/T-cell and macrophage-rich areas. The ISS of 40-60 immune transcripts revealed the enriched expression of transcripts involved in homing or migration to lymph nodes, which formed networks at single-cell distances in lymphoid areas of the TB lesions. Instead, myeloid-annotated regions were enriched in CD68, CD14, ITGAM, ITGAX, and CD4 mRNA. CXCL8 and IL1B mRNA were observed in granulocytic areas in which M. tuberculosis was also detected. In line with ISS data indicating tertiary lymphoid structures, immune labeling of TB sections expressed markers of high endothelial venules, follicular dendritic cells, follicular helper T cells, and lymph-node homing receptors on T cells. Neither ISS nor immunolabeling showed evidence of tertiary lymphoid aggregates in sarcoidosis samples. Together, our finding suggests that despite their heterogeneity, the formation of tertiary immune structures is a common feature in granulomas from TB patients.

Single-Cell Imaging Maps Inflammatory Cell Subsets to Pulmonary Arterial Hypertension Vasculopathy

Rationale: Unraveling immune-driven vascular pathology in pulmonary arterial hypertension (PAH) requires a comprehensive understanding of the immune cell landscape. Although patients with hereditary (H)PAH and bone morphogenetic protein receptor type 2 (BMPR2) mutations have more severe pulmonary vascular pathology, it is not known whether this is related to specific immune cell subsets. Objectives: This study aims to elucidate immune-driven vascular pathology by identifying immune cell subtypes linked to severity of pulmonary arterial lesions in PAH. Methods: We used cutting-edge multiplexed ion beam imaging by time of flight to compare pulmonary arteries (PAs) and adjacent tissue in PAH lungs (idiopathic [I]PAH and HPAH) with unused donor lungs, as controls. Measurements and Main Results: We quantified immune cells' proximity and abundance, focusing on those features linked to vascular pathology, and evaluated their impact on pulmonary arterial smooth muscle cells (SMCs) and endothelial cells. Distinct immune infiltration patterns emerged between PAH subtypes, with intramural involvement independently linked to PA occlusive changes. Notably, we identified monocyte-derived dendritic cells within PA subendothelial and adventitial regions, influencing vascular remodeling by promoting SMC proliferation and suppressing endothelial gene expression across PAH subtypes. In patients with HPAH, pronounced immune dysregulation encircled PA walls, characterized by heightened perivascular inflammation involving T cell immunoglobulin and mucin domain-3 (TIM-3)+ T cells. This correlated with an expanded DC subset expressing indoleamine 2,3-dioxygenase 1, TIM-3, and SAM and HD domain-containing deoxynucleoside triphosphate triphosphohydrolase 1, alongside increased neutrophils, SMCs, and alpha-smooth muscle actin (ACTA2)+ endothelial cells, reinforcing the heightened severity of pulmonary vascular lesions. Conclusions: This study presents the first architectural map of PAH lungs, connecting immune subsets not only with specific PA lesions but also with heightened severity in HPAH compared with IPAH. Our findings emphasize the therapeutic potential of targeting monocyte-derived dendritic cells, neutrophils, cellular interactions, and immune responses to alleviate severe vascular pathology in IPAH and HPAH.

Shift in Tissue-Specific Immune Niches and CD137 Expression in Tuberculoma of Pembrolizumab-Treated Nasopharyngeal Carcinoma Patients

The use of immune checkpoint inhibitors (ICIs) in cancer treatment has shown promise but can also have unintended consequences, such as reactivating latent tuberculosis (TB). To develop treatments that address ICIs-related adverse events, it is essential to understand cellular heterogeneity across healthy and pathological tissues. We performed cross-tissue multiplexed staining analysis on samples from two patients with TB reactivation during pembrolizumab treatment for metastatic nasopharyngeal carcinoma. CD8+ T cells, rather than CD4+ T cells, accumulated preferentially in the tuberculoma and were associated with increased production of IFNγ and expression of CD137. Additionally, CD137 enrichment played a role in the spatial organization of the tuberculoma, with specific interaction limited to spatial proximal cells between IFNγ+ CD137+ CD8+ T cells and IL12+ CD137+ type-1 macrophages. This unique feature was not observed in non-tumoral or tumoral tissues. Our analysis of public transcriptomic datasets supported the notion that this cellular interaction was more prominent in patients with durable ICI responses compared to those with non-ICI-related TB. We suggest that shifts towards CD137-rich immune niches are correlated with both off-target immune-related adverse events and anti-tumor efficacy. Targeting the tumor microenvironment through conditional activation of anti-CD137 signaling in combination with ICIs can modulate the reactivity of T cells and macrophages for localized tumor killing without the potential off-target immune-related risks associated with ICIs alone.

Immune mechanisms of granuloma formation in sarcoidosis and tuberculosis

Sarcoidosis is a complex immune-mediated disease characterized by clusters of immune cells called granulomas. Despite major steps in understanding the cause of this disease, many questions remain. In this Review, we perform a mechanistic interrogation of the immune activities that contribute to granuloma formation in sarcoidosis and compare these processes with its closest mimic, tuberculosis, highlighting shared and divergent immune activities. We examine how Mycobacterium tuberculosis is sensed by the immune system; how the granuloma is initiated, formed, and perpetuated in tuberculosis compared with sarcoidosis; and the role of major innate and adaptive immune cells in shaping these processes. Finally, we draw these findings together around several recent high-resolution studies of the granuloma in situ that utilized the latest advances in single-cell technology combined with spatial methods to analyze plausible disease mechanisms. We conclude with an overall view of granuloma formation in sarcoidosis.

Advances in cellular and tissue-based imaging techniques for sarcoid granulomas

Sarcoidosis embodies a complex inflammatory disorder spanning multiple systems, with its origin remaining elusive. It manifests as the infiltration of inflammatory cells that coalesce into distinctive noncaseous granulomas within afflicted organs. Unraveling this disease necessitates the utilization of cellular or tissue-based imaging methods to both visualize and characterize the biochemistry of these sarcoid granulomas. Although hematoxylin and eosin stain, standard in routine use alongside cytological stains have found utility in diagnosis within clinical contexts, special stains such as Masson's trichrome, reticulin, methenamine silver, and Ziehl-Neelsen provide additional varied perspectives of sarcoid granuloma imaging. Immunohistochemistry aids in pinpointing specific proteins and gene expressions further characterizing these granulomas. Finally, recent advances in spatial transcriptomics promise to divulge profound insights into their spatial orientation and three-dimensional (3-D) molecular mapping. This review focuses on a range of preexisting imaging methods employed for visualizing sarcoid granulomas at the cellular level while also exploring the potential of the latest cutting-edge approaches like spatial transcriptomics and matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI), with the overarching goal of shedding light on the trajectory of sarcoidosis research.

A Case of Multi-Organ Tuberculosis Misdiagnosed as Lung Cancer and a Literature Review

Background

Tuberculosis (TB) is a very common and easily diagnosed as a malignancy. However, studies have described the difference between TB and lung cancer. Single-organ TB and lung cancer are often easily distinguished clinically. Atypical systemic hematogenous disseminated TB (HDTB) is uncommon, including rare cases involving multiple organs such as cervical lymph nodes, pleura, liver, and lung TB simultaneously, which are more confusing and easily misdiagnosed in clinical practice.

Case Presentation

A HIV-negative 56-year-old male was hospitalized for chest disease with main symptoms of chest tightness, chest pain, fatigue, anorexia, and weight loss. Heart rate 109 times/min, the computed tomography (CT) scans of the neck, chest, and abdomen revealed multiple nodules in the right pleura, right pleural encapsulated effusion, and limited, incomplete expansion of the middle and lower lobes of the right lung, enlarged lymph nodes in the right hilar and mediastinal and diaphragm groups, and multiple slightly low-density nodules in the liver, bone destruction in the 2nd thoracic vertebra, raising the possibility of multiple liver metastases of right lung cancer and malignant pleural fluid. The lymph nodes in the neck, mediastinum, abdomen, and pelvis were enlarged bilaterally. After comprehensive analysis, the patient was diagnosed with atypical systemic HDTB. After three months of conventional anti-TB treatment, the patient refused our hospital follow-up, and his symptoms improved significantly during the telephone follow-up.

Conclusion

Most previous TB misdiagnoses involved a single organ, and this case enriches the clinical experience of diagnosing atypical HDTB. We encourage clinicians to establish a dynamic diagnostic and therapeutic mindset, emphasizing the value of biopsy and pathology.

CD4+ T cells are homeostatic regulators during Mtb reinfection

Immunological priming - either in the context of prior infection or vaccination - elicits protective responses against subsequent Mycobacterium tuberculosis (Mtb) infection. However, the changes that occur in the lung cellular milieu post-primary Mtb infection and their contributions to protection upon reinfection remain poorly understood. Here, using clinical and microbiological endpoints in a non-human primate reinfection model, we demonstrate that prior Mtb infection elicits a long-lasting protective response against subsequent Mtb exposure and that the depletion of CD4+ T cells prior to Mtb rechallenge significantly abrogates this protection. Leveraging microbiologic, PET-CT, flow cytometric, and single-cell RNA-seq data from primary infection, reinfection, and reinfection-CD4+ T cell depleted granulomas, we identify differential cellular and microbial features of control. The data collectively demonstrate that the presence of CD4+ T cells in the setting of reinfection results in a reduced inflammatory lung milieu characterized by reprogrammed CD8+ T cell activity, reduced neutrophilia, and blunted type-1 immune signaling among myeloid cells, mitigating Mtb disease severity. These results open avenues for developing vaccines and therapeutics that not only target CD4+ and CD8+ T cells, but also modulate innate immune cells to limit Mtb disease.

Inflammatory immune profiles associated with disease severity in pulmonary tuberculosis patients with moderate to severe clinical TB or anemia

Background

Immune control of Mycobacterium tuberculosis (Mtb) infection is largely influenced by the extensive disease heterogeneity that is typical for tuberculosis (TB). In this study, the peripheral inflammatory immune profile of different sub-groups of pulmonary TB patients was explored based on clinical disease severity, anemia of chronic disease, or the radiological extent of lung disease.

Methods

Plasma samples were obtained from n=107 patients with active pulmonary TB at the time of diagnosis and after start of standard chemotherapy. A composite clinical TB symptoms score, blood hemoglobin status and chest X-ray imaging were used to sub-group TB patients into 1.) mild and moderate-severe clinical TB, 2.) anemic and non-anemic TB, or 3.) limited and extensive lung involvement. Plasma levels of biomarkers associated with inflammation pathways were assessed using a Bio-Plex Magpix 37-multiplex assay. In parallel, Th1/Th2 cytokines were quantified with a 27-multiplex in matched plasma and cell culture supernatants from whole blood stimulated with M. tuberculosis-antigens using the QuantiFERON-TB Gold assay.

Results

Clinical TB disease severity correlated with low blood hemoglobin levels and anemia but not with radiological findings in this study cohort. Multiplex protein analyses revealed that distinct clusters of inflammation markers and cytokines separated the different TB disease sub-groups with variable efficacy. Several top-ranked markers overlapped, while other markers were unique with regards to their importance to differentiate the TB disease severity groups. A distinct immune response profile defined by elevated levels of BAFF, LIGHT, sTNF-R1 and 2, IP-10, osteopontin, chitinase-3-like protein 1, and IFNα2 and IL-8, were most effective in separating TB patients with different clinical disease severity and were also promising candidates for treatment monitoring. TB patients with mild disease displayed immune polarization towards mixed Th1/Th2 responses, while pro-inflammatory and B cell stimulating cytokines as well as immunomodulatory mediators predominated in moderate-severe TB disease and anemia of TB.

Conclusions

Our data demonstrated that clinical disease severity in TB is associated with anemia and distinct inflammatory immune profiles. These results contribute to the understanding of immunopathology in pulmonary TB and define top-ranked inflammatory mediators as biomarkers of disease severity and treatment prognosis.

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.

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 RNAs and proteins 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. Our results demonstrate (1) the feasibility of imputing single-cell abundance levels for many proteins using machine learning to overcome the technical constraints of multiplex tissue imaging and (2) how including cellular spatial information can substantially enhance imputation results.

The Causal Impact of the Gut Microbiota on Respiratory Tuberculosis Susceptibility

INTRODUCTION

Recent cross-sectional research has demonstrated a substantial link between tuberculosis (TB) and gut microbiota. Nevertheless, the causal impact of the gut microbiota on TB susceptibility in humans remains unknown.

METHODS

The Mendelian randomization (MR) method was utilized for investigating the causality between them. The main method used for MR analysis was the inverse variance weighted (IVW) test, with the MR-Egger, weighted median, weighted mode, and simple median methods serving as supplements. And several sensitivity tests were carried out to validate the MR findings.

RESULTS

The IVW outcomes suggested that three bacterial traits exhibited associations with susceptibility to respiratory TB after Bonferroni correction, namely Lachnospiraceae UCG010 (odds ratio [OR] 1.73, 95% confidence interval [CI] 1.17-2.55, P = 0.005), Eubacterium (brachy group) (OR 1.33, 95% CI 1.07-1.65, P = 0.009), and Ruminococcaceae UCG005 (OR 0.71, 95% CI 0.52-0.98, P = 0.034). Sensitivity analyses demonstrated that horizontal pleiotropy and heterogeneity were absent, thereby guaranteeing the reliability of the results.

CONCLUSION

This research sheds light on the causal impact of gut microbiota on respiratory tuberculosis susceptibility, improving our knowledge of therapeutic strategies for managing TB.

Single-cell RNA-sequencing reveals heterogeneity and intercellular crosstalk in human tuberculosis lung

Lung inflammation indicated by 18F-labeled fluorodeoxyglucose (FDG) in patients with tuberculosis is associated with disease severity and relapse risk upon treatment completion. We revealed the heterogeneity and intercellular crosstalk in lung tissues with 18F-FDG avidity and adjacent uninvolved tissues from 6 tuberculosis patients by single-cell RNA-sequencing. Tuberculous lungs had an influx of regulatory T cells (Treg), exhausted CD8 T cells, immunosuppressive myeloid cells, conventional DC, plasmacytoid DC, and neutrophils. Immune cells in inflamed lungs showed general up-regulation of ATP synthesis and interferon-mediated signaling. Immunosuppressive myeloid and Treg cells strongly displayed transcriptions of genes related to tuberculosis disease progression. Intensive crosstalk between IL4I1-expressing myeloid cells and Treg cells involving chemokines, costimulatory molecules, and immune checkpoints, some of which are specific in 18F-FDG-avid lungs, were found. Our analysis provides insights into the transcriptomic heterogeneity and cellular crosstalk in pulmonary tuberculosis and guides unveiling cellular and molecular targets for tuberculosis therapy.

The impact of similarity metrics on cell-type clustering in highly multiplexed in situ imaging cytometry data

Motivation

The advent of highly multiplexed in situ imaging cytometry assays has revolutionized the study of cellular systems, offering unparalleled detail in observing cellular activities and characteristics. These assays provide comprehensive insights by concurrently profiling the spatial distribution and molecular features of numerous cells. In navigating this complex data landscape, unsupervised machine learning techniques, particularly clustering algorithms, have become essential tools. They enable the identification and categorization of cell types and subsets based on their molecular characteristics. Despite their widespread adoption, most clustering algorithms in use were initially developed for cell suspension technologies, leading to a potential mismatch in application. There is a critical gap in the systematic evaluation of these methods, particularly in determining the properties that make them optimal for in situ imaging assays. Addressing this gap is vital for ensuring accurate, reliable analyses and fostering advancements in cellular biology research.

Results

In our extensive investigation, we evaluated a range of similarity metrics, which are crucial in determining the relationships between cells during the clustering process. Our findings reveal substantial variations in clustering performance, contingent on the similarity metric employed. These variations underscore the importance of selecting appropriate metrics to ensure accurate cell type and subset identification. In response to these challenges, we introduce FuseSOM, a novel ensemble clustering algorithm that integrates hierarchical multiview learning of similarity metrics with self-organizing maps. Through a rigorous stratified subsampling analysis framework, we demonstrate that FuseSOM outperforms existing best-practice clustering methods specifically tailored for in situ imaging cytometry data. Our work not only provides critical insights into the performance of clustering algorithms in this novel context but also offers a robust solution, paving the way for more accurate and reliable in situ imaging cytometry data analysis.

Availability and implementation

The FuseSOM R package is available on Bioconductor and is available under the GPL-3 license. All the codes for the analysis performed can be found at Github.

High and Low Levels of ABCB1 Expression Are Associated with Two Distinct Gene Signatures in Lung Tissue of Pulmonary TB Patients with High Inflammation Activity

P-glycoprotein (encoded by the ABCB1 gene) has a dual role in regulating inflammation and reducing chemotherapy efficacy in various diseases, but there are few studies focused on pulmonary TB patients. In this study, our objective was to identify a list of genes that correlate with high and low levels of ABCB1 gene expression in the lungs of pulmonary TB patients with different activity of chronic granulomatous inflammation. We compared gene expression in two groups of samples (with moderate and high activity of tuberculomas) to identify their characteristic gene signatures. Gene expression levels were determined using quantitative PCR in samples of perifocal area of granulomas, which were obtained from 65 patients after surgical intervention. Subsequently, two distinct gene signatures associated with high inflammation activity were identified. The first signature demonstrated increased expression of HIF1a, TGM2, IL6, SOCS3, and STAT3, which correlated with high ABCB1 expression. The second signature was characterized by high expression of TNFa and CD163 and low expression of ABCB1. These results provide insight into various inflammatory mechanisms and association with P-gp gene expression in lung tissue of pulmonary TB patients and will be useful in the development of a host-directed therapy approach to improving the effectiveness of anti-TB treatment.

Harnessing computational spatial omics to explore the spatial biology intricacies

Spatially resolved transcriptomics (SRT) has unlocked new dimensions in our understanding of intricate tissue architectures. However, this rapidly expanding field produces a wealth of diverse and voluminous data, necessitating the evolution of sophisticated computational strategies to unravel inherent patterns. Two distinct methodologies, gene spatial pattern recognition (GSPR) and tissue spatial pattern recognition (TSPR), have emerged as vital tools in this process. GSPR methodologies are designed to identify and classify genes exhibiting noteworthy spatial patterns, while TSPR strategies aim to understand intercellular interactions and recognize tissue domains with molecular and spatial coherence. In this review, we provide a comprehensive exploration of SRT, highlighting crucial data modalities and resources that are instrumental for the development of methods and biological insights. We address the complexities and challenges posed by the use of heterogeneous data in developing GSPR and TSPR methodologies and propose an optimal workflow for both. We delve into the latest advancements in GSPR and TSPR, examining their interrelationships. Lastly, we peer into the future, envisaging the potential directions and perspectives in this dynamic field.

Granulocytes subsets and their divergent functions in host resistance to Mycobacterium tuberculosis - a 'tipping-point' model of disease exacerbation

Granulocytes are innate immune effector cells with essential functions in host resistance to bacterial infections. I will discuss emerging evidence that during Mycobacterium tuberculosis infection, counter-intuitively, eosinophils are host-protective while neutrophils are host detrimental. Additionally, I will propose a 'tipping-point' model in which neutrophils are an integral part of a feedforward loop driving tuberculosis disease exacerbation.

Single-Cell Transcriptomics of Mtb/HIV Co-Infection

Tuberculosis (TB) and Human Immunodeficiency Virus (HIV) co-infection continues to pose a significant healthcare burden. HIV co-infection during TB predisposes the host to the reactivation of latent TB infection (LTBI), worsening disease conditions and mortality. There is a lack of biomarkers of LTBI reactivation and/or immune-related transcriptional signatures to distinguish active TB from LTBI and predict TB reactivation upon HIV co-infection. Characterizing individual cells using next-generation sequencing-based technologies has facilitated novel biological discoveries about infectious diseases, including TB and HIV pathogenesis. Compared to the more conventional sequencing techniques that provide a bulk assessment, single-cell RNA sequencing (scRNA-seq) can reveal complex and new cell types and identify more high-resolution cellular heterogeneity. This review will summarize the progress made in defining the immune atlas of TB and HIV infections using scRNA-seq, including host-pathogen interactions, heterogeneity in HIV pathogenesis, and the animal models employed to model disease. This review will also address the tools needed to bridge the gap between disease outcomes in single infection vs. co-infection. Finally, it will elaborate on the translational benefits of single-cell sequencing in TB/HIV diagnosis in humans.

A half-century of research on tuberculosis: Successes and challenges

Great progress has been made over the past half-century, but TB remains a formidable global health problem, particularly in low- and middle-income countries. Understanding the mechanisms of pathogenesis and necessary and sufficient conditions for protection are critical. The need for inexpensive and sensitive point-of-care diagnostic tests for earlier detection of infection and disease, shorter and less-toxic drug regimens for drug-sensitive and -resistant TB, and a more effective vaccine than BCG is immense. New and better tools, greater support for international research, collaborations, and training will be required to dramatically reduce the burden of this devastating disease which still kills 1.6 million people annually.

Animal models for COVID-19 and tuberculosis

Respiratory infections cause tremendous morbidity and mortality worldwide. Amongst these diseases, tuberculosis (TB), a bacterial illness caused by Mycobacterium tuberculosis which often affects the lung, and coronavirus disease 2019 (COVID-19) caused by the Severe Acute Respiratory Syndrome Coronavirus type 2 (SARS-CoV-2), stand out as major drivers of epidemics of global concern. Despite their unrelated etiology and distinct pathology, these infections affect the same vital organ and share immunopathogenesis traits and an imperative demand to model the diseases at their various progression stages and localizations. Due to the clinical spectrum and heterogeneity of both diseases experimental infections were pursued in a variety of animal models. We summarize mammalian models employed in TB and COVID-19 experimental investigations, highlighting the diversity of rodent models and species peculiarities for each infection. We discuss the utility of non-human primates for translational research and emphasize on the benefits of non-conventional experimental models such as livestock. We epitomize advances facilitated by animal models with regard to understanding disease pathophysiology and immune responses. Finally, we highlight research areas necessitating optimized models and advocate that research of pulmonary infectious diseases could benefit from cross-fertilization between studies of apparently unrelated diseases, such as TB and COVID-19.

Computational Methods for Single-Cell Proteomics

Advances in single-cell proteomics technologies have resulted in high-dimensional datasets comprising millions of cells that are capable of answering key questions about biology and disease. The advent of these technologies has prompted the development of computational tools to process and visualize the complex data. In this review, we outline the steps of single-cell and spatial proteomics analysis pipelines. In addition to describing available methods, we highlight benchmarking studies that have identified advantages and pitfalls of the currently available computational toolkits. As these technologies continue to advance, robust analysis tools should be developed in tandem to take full advantage of the potential biological insights provided by these data.

The dawn of spatial omics

Spatial omics has been widely heralded as the new frontier in life sciences. This term encompasses a wide range of techniques that promise to transform many areas of biology and eventually revolutionize pathology by measuring physical tissue structure and molecular characteristics at the same time. Although the field came of age in the past 5 years, it still suffers from some growing pains: barriers to entry, robustness, unclear best practices for experimental design and analysis, and lack of standardization. In this Review, we present a systematic catalog of the different families of spatial omics technologies; highlight their principles, power, and limitations; and give some perspective and suggestions on the biggest challenges that lay ahead in this incredibly powerful-but still hard to navigate-landscape.

Aerosol pulmonary immune engineering

Aerosolization of immunotherapies poses incredible potential for manipulating the local mucosal-specific microenvironment, engaging specialized pulmonary cellular defenders, and accessing mucosal associated lymphoid tissue to redirect systemic adaptive and memory responses. In this review, we breakdown key inhalable immunoengineering strategies for chronic, genetic, and infection-based inflammatory pulmonary disorders, encompassing the historic use of immunomodulatory agents, the transition to biological inspired or derived treatments, and novel approaches of complexing these materials into drug delivery vehicles for enhanced release outcomes. Alongside a brief description of key immune targets, fundamentals of aerosol drug delivery, and preclinical pulmonary models for immune response, we survey recent advances of inhaled immunotherapy platforms, ranging from small molecules and biologics to particulates and cell therapies, as well as prophylactic vaccines. In each section, we address the formulation design constraints for aerosol delivery as well as advantages for each platform in driving desirable immune modifications. Finally, prospects of clinical translation and outlook for inhaled immune engineering are discussed.

Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering

While technologies for multiplexed imaging have provided an unprecedented understanding of tissue composition in health and disease, interpreting this data remains a significant computational challenge. To understand the spatial organization of tissue and how it relates to disease processes, imaging studies typically focus on cell-level phenotypes. However, images can capture biologically important objects that are outside of cells, such as the extracellular matrix. Here, we describe a pipeline, Pixie, that achieves robust and quantitative annotation of pixel-level features using unsupervised clustering and show its application across a variety of biological contexts and multiplexed imaging platforms. Furthermore, current cell phenotyping strategies that rely on unsupervised clustering can be labor intensive and require large amounts of manual cluster adjustments. We demonstrate how pixel clusters that lie within cells can be used to improve cell annotations. We comprehensively evaluate pre-processing steps and parameter choices to optimize clustering performance and quantify the reproducibility of our method. Importantly, Pixie is open source and easily customizable through a user-friendly interface.

Suppressive myeloid cells in SARS-CoV-2 and Mycobacterium tuberculosis co-infection

Epidemiologic data show that both current and previous tuberculosis (TB) increase the risk of in-hospital mortality from coronavirus disease-2019 (COVID-19), and there is a similar trend for poor outcomes from Mycobacterium tuberculosis (Mtb) infection after recent SARS-CoV-2. A shared dysregulation of immunity explains the dual risk posed by co-infection, but the specific mechanisms are being explored. While initial attention focused on T cell immunity, more comprehensive analyses revealed a dysfunctional innate immune response in COVID-19, characterized by reduced numbers of dendritic cells, NK cells and a redistribution of mononuclear phagocytes towards intermediate myeloid subsets. During hyper- or chronic inflammatory processes, activation signals from molecules such as growth factors and alarmins lead to the expansion of an immature population of myeloid cells called myeloid-deprived suppressor cells (MDSC). These cells enter a state of pathological activation, lose their ability to rapidly clear pathogens, and instead become broadly immunosuppressive. MDSC are enriched in the peripheral blood of patients with severe COVID-19; associated with mortality; and with higher levels of inflammatory cytokines. In TB, MDSC have been implicated in loss of control of Mtb in the granuloma and ineffective innate and T cell immunity to the pathogen. Considering that innate immune sensing serves as first line of both anti-bacterial and anti-viral defence mechanisms, we propose MDSC as a crucial mechanism for the adverse clinical trajectories of TB-COVID-19 coinfection.

CellSighter: a neural network to classify cells in highly multiplexed images

Multiplexed imaging enables measurement of multiple proteins in situ, offering an unprecedented opportunity to chart various cell types and states in tissues. However, cell classification, the task of identifying the type of individual cells, remains challenging, labor-intensive, and limiting to throughput. Here, we present CellSighter, a deep-learning based pipeline to accelerate cell classification in multiplexed images. Given a small training set of expert-labeled images, CellSighter outputs the label probabilities for all cells in new images. CellSighter achieves over 80% accuracy for major cell types across imaging platforms, which approaches inter-observer concordance. Ablation studies and simulations show that CellSighter is able to generalize its training data and learn features of protein expression levels, as well as spatial features such as subcellular expression patterns. CellSighter's design reduces overfitting, and it can be trained with only thousands or even hundreds of labeled examples. CellSighter also outputs a prediction confidence, allowing downstream experts control over the results. Altogether, CellSighter drastically reduces hands-on time for cell classification in multiplexed images, while improving accuracy and consistency across datasets.

Blood transcriptional correlates of BCG-induced protection against tuberculosis in rhesus macaques

Blood-based correlates of vaccine-induced protection against tuberculosis (TB) are urgently needed. Here, we analyze the blood transcriptome of rhesus macaques immunized with varying doses of intravenous (i.v.) BCG followed by Mycobacterium tuberculosis (Mtb) challenge. We use high-dose i.v. BCG recipients for "discovery" and validate our findings in low-dose recipients and in an independent cohort of macaques receiving BCG via different routes. We identify seven vaccine-induced gene modules, including an innate module (module 1) enriched for type 1 interferon and RIG-I-like receptor signaling pathways. Module 1 on day 2 post-vaccination highly correlates with lung antigen-responsive CD4 T cells at week 8 and with Mtb and granuloma burden following challenge. Parsimonious signatures within module 1 at day 2 post-vaccination predict protection following challenge with area under the receiver operating characteristic curve (AUROC) ≥0.91. Together, these results indicate that the early innate transcriptional response to i.v. BCG in peripheral blood may provide a robust correlate of protection against TB.

A spatially resolved timeline of the human maternal-fetal interface

Beginning in the first trimester, fetally derived extravillous trophoblasts (EVTs) invade the uterus and remodel its spiral arteries, transforming them into large, dilated blood vessels. Several mechanisms have been proposed to explain how EVTs coordinate with the maternal decidua to promote a tissue microenvironment conducive to spiral artery remodelling (SAR)1-3. However, it remains a matter of debate regarding which immune and stromal cells participate in these interactions and how this evolves with respect to gestational age. Here we used a multiomics approach, combining the strengths of spatial proteomics and transcriptomics, to construct a spatiotemporal atlas of the human maternal-fetal interface in the first half of pregnancy. We used multiplexed ion beam imaging by time-of-flight and a 37-plex antibody panel to analyse around 500,000 cells and 588 arteries within intact decidua from 66 individuals between 6 and 20 weeks of gestation, integrating this dataset with co-registered transcriptomics profiles. Gestational age substantially influenced the frequency of maternal immune and stromal cells, with tolerogenic subsets expressing CD206, CD163, TIM-3, galectin-9 and IDO-1 becoming increasingly enriched and colocalized at later time points. By contrast, SAR progression preferentially correlated with EVT invasion and was transcriptionally defined by 78 gene ontology pathways exhibiting distinct monotonic and biphasic trends. Last, we developed an integrated model of SAR whereby invasion is accompanied by the upregulation of pro-angiogenic, immunoregulatory EVT programmes that promote interactions with the vascular endothelium while avoiding the activation of maternal immune cells.

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

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