Gierahn, T. M. | Search bioRxiv

bioRxiv2020

Single-cell profiling of tuberculosis lung granulomas reveals functional lymphocyte signatures of bacterial control

Mycobacterium tuberculosis lung infection results in a complex multicellular structure, the granuloma. In some granulomas, immune activity promotes bacterial clearance; in others, bacteria persist and grow. We identified correlates of bacterial control in cynomolgus macaque lung granulomas by co-registering longitudinal PET-CT imaging, single-cell RNA-sequencing, and measures of bacterial clearance. We find that bacterial persistence occurs in granulomas enriched for mast, endothelial, fibroblast and plasma cells, signaling amongst themselves via Type II immunity and wound healing pathways. In contrast, these interactions are largely absent in granulomas that drive bacterial control, which are often those that form later in the course of infection; these restrictive lesions are characterized by cellular ecosystems enriched for Type1-Type17, stem-like, and cytotoxic T cells engaged in pro-inflammatory signaling networks that involve diverse myeloid and non-immune cell populations. There is also a temporal aspect to bacterial control, in that granulomas that arise later in infection (in the context of an established immune response) share the functional characteristics of restrictive granulomas and are more capable of killing Mtb. Taken together, our results define the complex multicellular ecosystems underlying (lack of) granuloma resolution and highlight host immune targets that can be leveraged to develop new vaccine and therapeutic strategies for TB. One-Sentence SummaryBacterial control in TB lung granulomas correlates with distinct cellular immune microenvironments and time of formation after infection.

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↗