RESUMO
We successfully employed a single cell RNA sequencing (scRNA-seq) approach to describe the cells and the communication networks characterizing granulomatous lymph nodes of TB patients. When mapping cells from individual patient samples, clustered based on their transcriptome similarities, we uniformly identify several cell types that known to characterize human and non-human primate granulomas. Whether high or low Mtb burden, we find the T cell cluster to be one of the most abundant. Many cells expressing T cell markers are clearly quantifiable within this CD3 expressing cluster. 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 (in order to add power to cell cluster identification in patient samples with fewer cells), we distinguish T, macrophage, dendrocyte and plasma cell subclusters, each with distinct signaling activities. 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 correlated with NK cell populations. In addition, we also discovered that the scRNA-seq pipeline, designed for quantification of human cell mRNA, also detects Mtb RNA transcripts and associates them with their host cell's transcriptome, thus identifying individual infected cells. We hypothesize that the number of detected bacterial transcript reads provides a measure of Mtb burden, as does the number of Mtb-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, including many interactions between stromal or endothelial cells and the other component cells, such as Collagen, FN1 and Laminin,. In addition, other more selective communications pathways, including MIF, MHC-1, MHC-2, APP, CD 22, CD45, and others, are identified as originating or being received by individual immune cell components.
RESUMO
Mycobacterium tuberculosis (Mtb) remains a global human health threat and a significant cause of human morbidity and mortality. We document here the capture of Mtb transcripts in libraries designed to amplify eukaryotic mRNA. These reads are often considered spurious or nuisance and are rarely investigated. Because of early literature suggesting the possible presence of polyadenylated transcripts in Mtb RNA, we included the H37Rv Mtb reference genome when assembling scRNA seq libraries from fine needle aspirate samples from patients presenting at the TB clinic, Port Moresby General Hospital, Papua New Guinea. We used 10X Genomics single-cell RNA sequencing transcriptomics pipeline, which initiates mRNA amplification with poly-T primers on ~30-micron beads designed to capture, in this case, human mRNA associated with individual cells in the clinical samples. Utilizing the 10X Genomics Cell Ranger tool to align sequencing reads, we consistently detected bacterial small and large ribosomal subunit RNA sequences (rrs and rrl, respectively) and other bacterial gene transcripts in the cell culture and patient samples. We interpret Mtb reads associated with the host cell's unique molecular identifier (UMI) and transcriptome to indicate infection of that individual host cell. The Mtb transcripts detected showed frequent sequence variation from the reference genome, with greater than 90% of the rrs or rrl reads from many clinical samples having at least 1 sequence difference compared to the H37Rv reference genome. The data presented includes only bacterial sequences from patients with TB infections that were confirmed by the hospital pathology lab using acid-fast microscopy and/or GeneXpert analysis. The repeated, non-random nature of the sequence variations detected in Mtb rrs and rrl transcripts from multiple patients, suggests that, even though this appears to be a stochastic process, there is possibly some selective pressure that limits the types and locations of sequence variation allowed. The variation does not appear to be entirely artefactual, and it is hypothesized that it could represent an additional mechanism of adaptation to enhance bacterial fitness against host defenses or chemotherapy.