de Andrade Silva, B. J. | Search bioRxiv

bioRxiv2025

Spatial profiling reveals TREM2+ macrophages as central to Mycobacterium tuberculosis pathogenesis in human pulmonary tuberculosis

Pulmonary tuberculosis (TB) exhibits marked spatial heterogeneity, with alveolar pneumonia and organized granulomas frequently coexisting within the same lung. While granulomas have long dominated conceptual models of TB pathogenesis, the immune programs operating within alveolar TB pneumonia in humans remain incompletely defined. Here, we integrate spatial transcriptomics, single-cell RNA sequencing, high-resolution imaging, and functional assays of human lung biopsies to directly compare alveolar pneumonia with adjacent granulomas from the same individuals. We demonstrate that alveolar TB pneumonia is enriched for TREM2 lipid-laden macrophages characterized by lipid metabolic reprogramming, sparse T-cell infiltration, attenuated antimicrobial gene expression, and abundant Mycobacterium tuberculosis (Mtb) transcripts and antigens. In contrast, neighboring granulomas exhibit organized lymphoid architecture and robust antimicrobial programs. Mechanistically, the mycobacterial virulence lipid phthiocerol dimycocerosate (PDIM) and free mycolic acids induce TREM2 expression and activate TREM2-DAP12 signaling, promoting lipid droplet accumulation, suppressing autophagy, and enhancing intracellular Mtb survival in human macrophages. This immunometabolic state is pharmacologically reversible: 1,25-dihydroxyvitamin D downregulates TREM2, restores autophagy, reduces lipid droplets, and limits bacterial viability. Together, these findings define a spatially localized TREM2 foamy macrophage program within alveolar pneumonia that contrasts sharply with adjacent granulomatous immunity, establishing an niche permissive for bacillary persistence and potentially transmission, as well as identifying a tractable host pathway in human TB pathogenesis.

immunology↗

bioRxiv2019

Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology

The development of high-throughput single-cell RNA-sequencing (scRNA-Seq) methodologies has empowered the characterization of complex biological samples by dramatically increasing the number of constituent cells that can be examined concurrently. Nevertheless, these approaches typically recover substantially less information per-cell as compared to lower-throughput microtiter plate-based strategies. To uncover critical phenotypic differences among cells and effectively link scRNA-Seq observations to legacy datasets, reliable detection of phenotype-defining transcripts - such as transcription factors, affinity receptors, and signaling molecules - by these methods is essential. Here, we describe a substantially improved massively-parallel scRNA-Seq protocol we term Seq-Well S^3 (\"Second-Strand Synthesis\") that increases the efficiency of transcript capture and gene detection by up to 10- and 5-fold, respectively, relative to previous iterations, surpassing best-in-class commercial analogs. We first characterized the performance of Seq-Well S^3 in cell lines and PBMCs, and then examined five different inflammatory skin diseases, illustrative of distinct types of inflammation, to explore the breadth of potential immune and parenchymal cell states. Our work presents an essential methodological advance as well as a valuable resource for studying the cellular and molecular features that inform human skin inflammation.

immunology↗