Single Cell Analysis of Peripheral TB-Associated Granulomatous Lymphadenitis

We employed a single cell RNA sequencing (scRNA-seq) approach to describe the cells and communication networks characterizing granulomatous lymph nodes of TB patients. When mapping cells from individual patient samples, we uniformly identify several cell types that characterize granulomas. Whether high or low Mtb burden, overall we find the T cell cluster to be the most abundant. 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 (to gain greater n), we distinguish T, macrophage, dendrocyte and plasma cell subclusters. 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 or positively correlated with NK cell populations. In addition, we discovered that the scRNA-seq pipeline detects Mtb RNA transcripts and associates them with their host cell's transcriptome, thus identifying individual 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. Overall design: Fine needle aspirates from periferal lymphadenopathies were collected from concenting patients arriving at the Port Moresby General Hospital (POMGH) Tuberculosis Clinic, Papua New Guinea, processed to collect the single cells, and fixed and sterilized with MeOH before returning to the University of Utah for processing for single-cell RNA sequencing using the 10X Genomics system.