The cellular architecture of the antimicrobial response network in human leprosy granulomas

Research Techniques Made Simple: Spatial Transcriptomics

Transcriptome profiling of tissues and single cells facilitates interrogation of gene expression changes within diverse biological contexts. However, spatial information is often lost during tissue homogenization or dissociation. Recent advances in transcriptome profiling preserve the in situ spatial contexts of RNA molecules and together comprise a group of techniques known as spatial transcriptomics (ST), enabling localization of cell types and their associated gene expression within intact tissues. In this paper, we review ST methods; summarize data analysis approaches, including integration with single-cell transcriptomics data; and discuss their applications in dermatologic research. These tools offer a promising avenue toward improving our understanding of niche patterning and cell‒cell interactions within heterogeneous tissues that encompass skin homeostasis and disease.

Clinical and translational values of spatial transcriptomics

The combination of spatial transcriptomics (ST) and single cell RNA sequencing (scRNA-seq) acts as a pivotal component to bridge the pathological phenomes of human tissues with molecular alterations, defining in situ intercellular molecular communications and knowledge on spatiotemporal molecular medicine. The present article overviews the development of ST and aims to evaluate clinical and translational values for understanding molecular pathogenesis and uncovering disease-specific biomarkers. We compare the advantages and disadvantages of sequencing- and imaging-based technologies and highlight opportunities and challenges of ST. We also describe the bioinformatics tools necessary on dissecting spatial patterns of gene expression and cellular interactions and the potential applications of ST in human diseases for clinical practice as one of important issues in clinical and translational medicine, including neurology, embryo development, oncology, and inflammation. Thus, clear clinical objectives, designs, optimizations of sampling procedure and protocol, repeatability of ST, as well as simplifications of analysis and interpretation are the key to translate ST from bench to clinic.

Single-cell transcriptomics in human skin research: available technologies, technical considerations, and disease applications

Single‐cell technologies have revolutionized research in the last decade, including for skin biology. Single‐cell RNA sequencing has emerged as a powerful tool allowing the dissection of human disease pathophysiology at unprecedented resolution by assessing cell‐to‐cell variation, facilitating identification of rare cell populations and elucidating cellular heterogeneity. In dermatology, this technology has been widely applied to inflammatory skin disorders, fibrotic skin diseases, wound healing complications and cutaneous neoplasms. Here, we discuss the available technologies and technical considerations of single‐cell RNA sequencing and describe its applications to a broad spectrum of dermatological diseases.

The Tuberculous Granuloma and Preexisting Immunity

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

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

The immune-suppressive landscape in lepromatous leprosy revealed by single-cell RNA sequencing

Lepromatous leprosy (L-LEP), caused by the massive proliferation of Mycobacterium leprae primarily in macrophages, is an ideal disease model for investigating the molecular mechanism of intracellular bacteria evading or modulating host immune response. Here, we performed single-cell RNA sequencing of both skin biopsies and peripheral blood mononuclear cells (PBMCs) of L-LEP patients and healthy controls. In L-LEP lesions, we revealed remarkable upregulation of APOE expression that showed a negative correlation with the major histocompatibility complex II gene HLA-DQB2 and MIF, which encodes a pro-inflammatory and anti-microbial cytokine, in the subset of macrophages exhibiting a high expression level of LIPA. The exhaustion of CD8⁺ T cells featured by the high expression of TIGIT and LAG3 in L-LEP lesions was demonstrated. Moreover, remarkable enhancement of inhibitory immune receptors mediated crosstalk between skin immune cells was observed in L-LEP lesions. For PBMCs, a high expression level of APOE in the HLA-DR^highFBP1^high monocyte subset and the expansion of regulatory T cells were found to be associated with L-LEP. These findings revealed the primary suppressive landscape in the L-LEP patients, providing potential targets for the intervention of intracellular bacteria caused persistent infections.

Progress of the Art of Macrophage Polarization and Different Subtypes in Mycobacterial Infection

Mycobacteriosis, mostly resulting from Mycobacterium tuberculosis (MTb), nontuberculous mycobacteria (NTM), and Mycobacterium leprae (M. leprae), is the long-standing granulomatous disease that ravages several organs including skin, lung, and peripheral nerves, and it has a spectrum of clinical-pathologic features based on the interaction of bacilli and host immune response. Histiocytes in infectious granulomas mainly consist of infected and uninfected macrophages (Mφs), multinucleated giant cells (MGCs), epithelioid cells (ECs), and foam cells (FCs), which are commonly discovered in lesions in patients with mycobacteriosis. Granuloma Mφ polarization or reprogramming is the crucial appearance of the host immune response to pathogen aggression, which gets a command of endocellular microbe persistence. Herein, we recapitulate the current gaps and challenges during Mφ polarization and the different subpopulations of mycobacteriosis.

Spatially Resolved Immunometabolism to Understand Infectious Disease Progression

Infectious diseases, including those of viral, bacterial, fungal, and parasitic origin are often characterized by focal inflammation occurring in one or more distinct tissues. Tissue-specific outcomes of infection are also evident in many infectious diseases, suggesting that the local microenvironment may instruct complex and diverse innate and adaptive cellular responses resulting in locally distinct molecular signatures. In turn, these molecular signatures may both drive and be responsive to local metabolic changes in immune as well as non-immune cells, ultimately shaping the outcome of infection. Given the spatial complexity of immune and inflammatory responses during infection, it is evident that understanding the spatial organization of transcripts, proteins, lipids, and metabolites is pivotal to delineating the underlying regulation of local immunity. Molecular imaging techniques like mass spectrometry imaging and spatially resolved, highly multiplexed immunohistochemistry and transcriptomics can define detailed metabolic signatures at the microenvironmental level. Moreover, a successful complementation of these two imaging techniques would allow multi-omics analyses of inflammatory microenvironments to facilitate understanding of disease pathogenesis and identify novel targets for therapeutic intervention. Here, we describe strategies for downstream data analysis of spatially resolved multi-omics data and, using leishmaniasis as an exemplar, describe how such analysis can be applied in a disease-specific context.