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

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1ß. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.

Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies.

High-throughput single-cell RNA-sequencing (scRNA-seq) methodologies enable characterization of complex biological samples by increasing the number of cells that can be profiled contemporaneously. Nevertheless, these approaches recover less information per cell than low-throughput strategies. To accurately report the expression of key phenotypic features of cells, scRNA-seq platforms are needed that are both high fidelity and high throughput. To address this need, we created Seq-Well S3 ("Second-Strand Synthesis"), a massively parallel scRNA-seq protocol that uses a randomly primed second-strand synthesis to recover complementary DNA (cDNA) molecules that were successfully reverse transcribed but to which a second oligonucleotide handle, necessary for subsequent whole transcriptome amplification, was not appended due to inefficient template switching. Seq-Well S3 increased the efficiency of transcript capture and gene detection compared with that of previous iterations by up to 10- and 5-fold, respectively. We used Seq-Well S3 to chart the transcriptional landscape of five human inflammatory skin diseases, thus providing a resource for the further study of human skin inflammation.

Cell-type deconvolution with immune pathways identifies gene networks of host defense and immunopathology in leprosy.

Transcriptome profiles derived from the site of human disease have led to the identification of genes that contribute to pathogenesis, yet the complex mixture of cell types in these lesions has been an obstacle for defining specific mechanisms. Leprosy provides an outstanding model to study host defense and pathogenesis in a human infectious disease, given its clinical spectrum, which interrelates with the host immunologic and pathologic responses. Here, we investigated gene expression profiles derived from skin lesions for each clinical subtype of leprosy, analyzing gene coexpression modules by cell-type deconvolution. In lesions from tuberculoid leprosy patients, those with the self-limited form of the disease, dendritic cells were linked with MMP12 as part of a tissue remodeling network that contributes to granuloma formation. In lesions from lepromatous leprosy patients, those with disseminated disease, macrophages were linked with a gene network that programs phagocytosis. In erythema nodosum leprosum, neutrophil and endothelial cell gene networks were identified as part of the vasculitis that results in tissue injury. The present integrated computational approach provides a systems approach toward identifying cell-defined functional networks that contribute to host defense and immunopathology at the site of human infectious disease.

CD163 favors Mycobacterium leprae survival and persistence by promoting anti-inflammatory pathways in lepromatous macrophages.

Lepromatous macrophages possess a regulatory phenotype that contributes to the immunosuppression observed in leprosy. CD163, a scavenger receptor that recognizes hemoglobin-haptoglobin complexes, is expressed at higher levels in lepromatous cells, although its functional role in leprosy is not yet established. We herein demonstrate that human lepromatous lesions are microenvironments rich in IDO⁺CD163⁺. Cells isolated from these lesions were CD68⁺IDO⁺CD163⁺ while higher levels of sCD163 in lepromatous sera positively correlated with IL-10 levels and IDO activity. Different Myco-bacterium leprae (ML) concentrations in healthy monocytes likewise revealed a positive correlation between increased concentrations of the mycobacteria and IDO, CD209, and CD163 expression. The regulatory phenotype in ML-stimulated monocytes was accompanied by increased TNF, IL-10, and TGF-ß levels whereas IL-10 blockade reduced ML-induced CD163 expression. The CD163 blockade reduced ML uptake in human monocytes. ML uptake was higher in HEK293 cells transfected with the cDNA for CD163 than in untransfected cells. Simultaneously, increased CD163 expression in lepromatous cells seemed to be dependent on ML uptake, and contributed to augmented iron storage in lepromatous macrophages. Altogether, these results suggest that ML-induced CD163 expression modulates the host cell phenotype to create a favorable environment for myco-bacterial entry and survival.