Single Cell Analysis of Peripheral TB-Associated Granulomatous Lymphadenitis
Philip J Moos1, Allison F Carey2, Jacklyn Joseph3
1Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, Utah 84112 USA.
Insights
Single cell RNA sequencing reveals diverse immune cell communication networks within tuberculosis granulomas. This approach identifies Mtb-infected cells and quantifies bacterial burden, offering new insights into disease pathogenesis.
Area of Science:
- Immunology
- Genomics
- Infectious Diseases
Background:
- Granulomatous lymph nodes are hallmarks of tuberculosis (TB) infection.
- Understanding the cellular composition and intercellular communication within these granulomas is crucial for developing effective TB therapies.
Purpose of the Study:
- To characterize the cellular landscape and communication networks in granulomatous lymph nodes from TB patients using single-cell RNA sequencing (scRNA-seq).
- To identify Mtb-infected host cells and explore potential biomarkers for bacterial burden.
Main Methods:
- scRNA-seq was performed on granulomatous lymph node samples from 23 TB patients.
- Bioinformatic analyses were used to cluster cells based on transcriptomes and identify cell types.
- CellChat analysis was employed to infer intercellular communication pathways.
- Mtb RNA transcripts were detected and associated with host cell transcriptomes.
Main Results:
- Uniform identification of key granuloma cell types including T cells, B cells, plasma cells, macrophages, dendritic cells, and NK cells.
- Significant variation in the abundance of different cell subclusters and Mtb-infected cells across patient samples.
- Identification of distinct signaling pathways, including stromal/endothelial cell interactions and immune cell-specific communications.
- Correlation between Mtb burden, number of infected cells, and specific immune cell population trends.
Conclusions:
- scRNA-seq provides a powerful tool for dissecting the complex cellular architecture and communication dynamics within TB granulomas.
- The detection of Mtb RNA within host cells offers a novel method for assessing bacterial burden and identifying infected cells.
- Understanding these intricate cellular interactions may reveal new therapeutic targets for TB treatment.
Abstract:
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.
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