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Moos PJ, Carey AF, Joseph J, Kialo S, Norrie J, Moyarelce JM, Amof A, Nogua H, Lim AL, Barrows LR. Single Cell Analysis of Peripheral TB-Associated Granulomatous Lymphadenitis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.28.596301. [PMID: 38853908 PMCID: PMC11160601 DOI: 10.1101/2024.05.28.596301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
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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Affiliation(s)
- Philip J. Moos
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, Utah 84112 USA
| | - Allison F. Carey
- Department of Pathology, University of Utah, Salt Lake City, Utah 84112 USA
| | - Jacklyn Joseph
- Coordinator of Pathology Services, Port Moresby General Hospital, Boroko Post, 111, Papua New Guinea
| | - Stephanie Kialo
- Division of Pathology, School of Medicine and Health Sciences, University of Papua New Guinea and Central Public Health Laboratory, Papua New Guinea National Department of Health, PMGH, P.O. Box 5623 Boroko, Papua New Guinea
| | - Joe Norrie
- Division of Pathology, School of Medicine and Health Sciences, University of Papua New Guinea and Central Public Health Laboratory, Papua New Guinea National Department of Health, PMGH, P.O. Box 5623 Boroko, Papua New Guinea
| | - Julie M. Moyarelce
- Division of Pathology, School of Medicine and Health Sciences, University of Papua New Guinea and Central Public Health Laboratory, Papua New Guinea National Department of Health, PMGH, P.O. Box 5623 Boroko, Papua New Guinea
| | - Anthony Amof
- Division of Pathology, School of Medicine and Health Sciences, University of Papua New Guinea and Central Public Health Laboratory, Papua New Guinea National Department of Health, PMGH, P.O. Box 5623 Boroko, Papua New Guinea
| | - Hans Nogua
- Division of Pathology, School of Medicine and Health Sciences, University of Papua New Guinea and Central Public Health Laboratory, Papua New Guinea National Department of Health, PMGH, P.O. Box 5623 Boroko, Papua New Guinea
| | - Albebson L. Lim
- Department of Medicinal Chemistry, University of Utah, Salt Lake City, Utah 84112 USA
| | - Louis R. Barrows
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, Utah 84112 USA
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Zhuang J, Zhu H, Cheng Z, Hu X, Yu X, Li J, Liu H, Tang P, Zhang Y, Xiong X, Deng H. PCSK9, a novel immune and ferroptosis related gene in abdominal aortic aneurysm neck. Sci Rep 2023; 13:6054. [PMID: 37055467 PMCID: PMC10102181 DOI: 10.1038/s41598-023-33287-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 04/11/2023] [Indexed: 04/15/2023] Open
Abstract
The gene expression profile of abdominal aortic aneurysm (AAA) neck is not fully understood. The etiology of AAA is considered to be related to atherosclerosis and the inflammatory response, involving congenital, genetic, metabolic, and other factors. The level of proprotein convertase subtilisin/kexin type 9 (PCSK9) is related to those of cholesterol, oxidized low-density lipoprotein, and triglycerides. PCSK9 inhibitors have significant effects on lowering LDL-cholesterol, reversing atherosclerotic plaques, and reducing the risk of cardiovascular events and have been approved by several lipid-lowering guidelines. This work was aimed to investigate the potential role of PCSK9 in the neck of AAA. We extracted the expression dataset (GSE47472) containing 14 AAA patients and 8 donors and single-cell RNAseq (scRNA-seq) data (GSE164678) of CaCl2-induced (AAA) samples from the Gene Expression Omnibus dataset. Through bioinformatics methods, we found that PCSK9 was up-regulated in the proximal neck of human AAA. In AAA, PCSK9 was mainly expressed in fibroblasts. Additionally, immune check-point PDCD1LG2 was also expressed higher in AAA neck than donor, while CTLA4, PDCD1, and SIGLEC15 were down-regulated in AAA neck. The expression of PCSK was correlated with PDCD1LG2, LAG3, and CTLA4 in AAA neck. Additionally, some ferroptosis-related genes were also down-regulated in AAA neck. PCSK9 was also correlated with ferroptosis-related genes in AAA neck. In conclusion, PCSK9 was highly expressed in AAA neck, and may exert its role through interacting with immune check-points and ferroptosis-related genes.
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Affiliation(s)
- Junli Zhuang
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Hua Zhu
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
- Department of Neurosurgery, The Affiliated Huzhou Hospital, Zhejiang University School of Medicine (Huzhou Central Hospital), NO. 1558 North Sanhuan Road, Huzhou, 313003, Zhejiang, China
- Department of Neurosurgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Ziqi Cheng
- Department of Neurosurgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Xinyao Hu
- Cancer Center, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Xiaohui Yu
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Jie Li
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Huagang Liu
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Peng Tang
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Ying Zhang
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China
| | - Xiaoxing Xiong
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China.
- Department of Neurosurgery, The Affiliated Huzhou Hospital, Zhejiang University School of Medicine (Huzhou Central Hospital), NO. 1558 North Sanhuan Road, Huzhou, 313003, Zhejiang, China.
- Department of Neurosurgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China.
| | - Hongping Deng
- Department of Vascular Surgery, Renmin Hospital of Wuhan University, NO. 99 Zhang Zhidong Road, Wuchang District, Wuhan, 430060, China.
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Duan K, Ma Y, Tan J, Miao Y, Zhang Q. Identification of genetic molecular markers and immune infiltration characteristics of Alzheimer's disease through weighted gene co-expression network analysis. Front Neurol 2022; 13:947781. [PMID: 36071897 PMCID: PMC9441600 DOI: 10.3389/fneur.2022.947781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 07/19/2022] [Indexed: 11/23/2022] Open
Abstract
Background Alzheimer's disease (AD) is a progressive neurodegenerative disease that leads to cognitive impairment and memory loss. Currently, the pathogenesis and underlying causative genes of AD remain unclear, and there exists no effective treatment for this disease. This study explored AD-related diagnostic and therapeutic biomarkers from the perspective of immune infiltration by analyzing public data from the NCBI Gene Expression Omnibus database. Method In this study, weighted gene co-expression network analysis (WGCNA) was conducted to identify modules and hub genes contributing to AD development. A protein–protein interaction network was constructed when the genes in the modules were enriched and examined by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, a gene network was established using topological WGCNA, from which five hub genes were selected. Logistic regression analysis and receiver operating characteristic curve analysis were performed to explore the clinical value of genes in AD diagnosis. The genes in the core module intersected with the hub genes, and four intersection genes (ATP2A2, ATP6V1D, CAP2, and SYNJ1) were selected. These four genes were enriched by gene set enrichment analysis (GSEA). Finally, an immune infiltration analysis was performed. Results The GO/KEGG analysis suggested that genes in the core module played a role in the differentiation and growth of neural cells and in the transmission of neurotransmitters. The GSEA of core genes showed that these four genes were mainly enriched in immune/infection pathways (e.g., cholera infection and Helicobacter pylori infection pathways) and other metabolic pathways. An investigation of immune infiltration characteristics revealed that activated mast cells, regulatory T cells, plasma cells, neutrophils, T follicular helper cells, CD8 T cells, resting memory CD4 T cells, and M1 macrophages were the core immune cells contributing to AD progression. qRT-PCR analysis showed that the ATP6V1D is upregulated in AD. Conclusion The results of enrichment and immuno-osmotic analyses indicated that immune pathways and immune cells played an important role in the occurrence and development of AD. The selected key genes were used as biomarkers related to the pathogenesis of AD to further explore the pathways and cells, which provided new perspectives on therapeutic targets in AD.
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Affiliation(s)
- KeFei Duan
- Department of Geriatrics, Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuan Ma
- Department of Geriatrics, Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Jin Tan
- Department of Geriatrics, Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China
| | - Yuyang Miao
- Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Qiang Zhang
- Department of Geriatrics, Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China
- *Correspondence: Qiang Zhang
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Kathamuthu GR, Sridhar R, Baskaran D, Babu S. Dominant expansion of CD4+, CD8+ T and NK cells expressing Th1/Tc1/Type 1 cytokines in culture-positive lymph node tuberculosis. PLoS One 2022; 17:e0269109. [PMID: 35617254 PMCID: PMC9135291 DOI: 10.1371/journal.pone.0269109] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 05/15/2022] [Indexed: 01/11/2023] Open
Abstract
Lymph node culture-positive tuberculosis (LNTB+) is associated with increased mycobacterial antigen-induced pro-inflammatory cytokine production compared to LN culture-negative tuberculosis (LNTB-). However, the frequencies of CD4+, CD8+ T cells and NK cells expressing Th1/Tc1/Type 1 (IFNγ, TNFα, IL-2), Th17/Tc17/Type 17 (IL-17A, IL-17F, IL-22) cytokines and cytotoxic (perforin [PFN], granzyme [GZE] B, CD107a) markers in LNTB+ and LNTB- individuals are not known. Thus, we have studied the unstimulated (UNS) and mycobacterial antigen-induced frequencies of CD4+, CD8+ T and NK cells expressing Th1, Th17 cytokines and cytotoxic markers using flow cytometry. The frequencies of CD4+, CD8+ T and NK cells expressing cytokines and cytotoxic markers were not significantly different between LNTB+ and LNTB- individuals in UNS condition. In contrast, upon Mtb antigen stimulation, LNTB+ individuals are associated with significantly increased frequencies of CD4+ T cells (PPD [IFNγ, TNFα], ESAT-6 PP [IFNγ, TNFα], CFP-10 PP [IFNγ, TNFα, IL-2]), CD8+ T cells (PPD [IFNγ], ESAT-6 PP [IFNγ], CFP-10 PP [TNFα]) and NK cells (PPD [IFNγ, TNFα], ESAT-6 PP [IFNγ, TNFα], CFP-10 PP [TNFα]) expressing Th1/Tc1/Type 1, but not Th17/Tc17/Type 17 cytokines and cytotoxic markers compared to LNTB- individuals. LNTB+ individuals did not show any significant alterations in the frequencies of CD4+, CD8+ T cells and NK cells expressing cytokines and cytotoxic markers compared to LNTB- individuals upon HIV Gag PP and P/I antigen stimulation. Increased frequencies of CD4+, CD8+ T and NK cells expressing Th1/Tc1/Type 1 cytokines among the LNTB+ group indicates that the presence of mycobacteria plays a dominant role in the activation of key correlates of immune protection or induces higher immunopathology.
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Affiliation(s)
- Gokul Raj Kathamuthu
- National Institutes of Health-NIRT-International Center for Excellence in Research, Chennai, India
- National Institute for Research in Tuberculosis (NIRT), Chennai, India
- * E-mail:
| | | | - Dhanaraj Baskaran
- National Institute for Research in Tuberculosis (NIRT), Chennai, India
| | - Subash Babu
- National Institutes of Health-NIRT-International Center for Excellence in Research, Chennai, India
- Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, United States of America
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Zhou H, Lu H, Sun L, Wang Z, Zheng M, Hang Z, Zhang D, Tan R, Gu M. Diagnostic Biomarkers and Immune Infiltration in Patients With T Cell-Mediated Rejection After Kidney Transplantation. Front Immunol 2022; 12:774321. [PMID: 35058922 PMCID: PMC8764245 DOI: 10.3389/fimmu.2021.774321] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 12/15/2021] [Indexed: 11/25/2022] Open
Abstract
T cell-mediated rejection (TCMR) is an important rejection type in kidney transplantation, characterized by T cells and macrophages infiltration. The application of bioinformatic analysis in genomic research has been widely used. In the present study, Microarray data was analyzed to identify the potential diagnostic markers of TCMR in kidney transplantation. Cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) was performed to determine the distribution of immune cell infiltration in the pathology. Totally 129 upregulated differently expressed genes (DEGs) and 378 downregulated DEGs were identified. The GO and KEGG results demonstrated that DEGs were mainly associated with pathways and diseases involved in immune response. The intersection of the two algorithms (PPI network and LASSO) contains three overlapping genes (CXCR6, CXCL13 and FCGR1A). After verification in GSE69677, only CXCR6 and CXCL13 were selected. Immune cells Infiltration analysis demonstrated that CXCR6 and CXCL13 were positively correlated with gamma delta T cells (p < 0.001), CD4+ memory activated T cells (p < 0.001), CD8+ T cells (p < 0.001) and M1 macrophages (p = 0.006), and negatively correlated with M2 macrophages (p < 0.001) and regulatory T cells (p < 0.001). Immunohistochemical staining and image analysis confirmed the overexpression of CXCR6 and CXCL13 in human allograft TCMR samples. CXCR6 and CXCL13 could be diagnostic biomarkers of TCMR and potential targets for immunotherapy in patients with TCMR.
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Affiliation(s)
- Hai Zhou
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hongcheng Lu
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Li Sun
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zijie Wang
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ming Zheng
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Zhou Hang
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Dongliang Zhang
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ruoyun Tan
- Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Min Gu
- Department of Urology, The Second Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Odia T, Malherbe ST, Meier S, Maasdorp E, Kleynhans L, du Plessis N, Loxton AG, Zak DE, Thompson E, Duffy FJ, Kuivaniemi H, Ronacher K, Winter J, Walzl G, Tromp G. The Peripheral Blood Transcriptome Is Correlated With PET Measures of Lung Inflammation During Successful Tuberculosis Treatment. Front Immunol 2021; 11:596173. [PMID: 33643286 PMCID: PMC7902901 DOI: 10.3389/fimmu.2020.596173] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 12/22/2020] [Indexed: 12/13/2022] Open
Abstract
Pulmonary tuberculosis (PTB) is characterized by lung granulomas, inflammation and tissue destruction. Here we used within-subject peripheral blood gene expression over time to correlate with the within-subject lung metabolic activity, as measured by positron emission tomography (PET) to identify biological processes and pathways underlying overall resolution of lung inflammation. We used next-generation RNA sequencing and [18F]FDG PET-CT data, collected at diagnosis, week 4, and week 24, from 75 successfully cured PTB patients, with the [18F]FDG activity as a surrogate for lung inflammation. Our linear mixed-effects models required that for each individual the slope of the line of [18F]FDG data in the outcome and the slope of the peripheral blood transcript expression data correlate, i.e., the slopes of the outcome and explanatory variables had to be similar. Of 10,295 genes that changed as a function of time, we identified 639 genes whose expression profiles correlated with decreasing [18F]FDG uptake levels in the lungs. Gene enrichment over-representation analysis revealed that numerous biological processes were significantly enriched in the 639 genes, including several well known in TB transcriptomics such as platelet degranulation and response to interferon gamma, thus validating our novel approach. Others not previously associated with TB pathobiology included smooth muscle contraction, a set of pathways related to mitochondrial function and cell death, as well as a set of pathways connecting transcription, translation and vesicle formation. We observed up-regulation in genes associated with B cells, and down-regulation in genes associated with platelet activation. We found 254 transcription factor binding sites to be enriched among the 639 gene promoters. In conclusion, we demonstrated that of the 10,295 gene expression changes in peripheral blood, only a subset of 639 genes correlated with inflammation in the lungs, and the enriched pathways provide a description of the biology of resolution of lung inflammation as detectable in peripheral blood. Surprisingly, resolution of PTB inflammation is positively correlated with smooth muscle contraction and, extending our previous observation on mitochondrial genes, shows the presence of mitochondrial stress. We focused on pathway analysis which can enable therapeutic target discovery and potential modulation of the host response to TB.
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Affiliation(s)
- Trust Odia
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,Bioinformatics Unit, South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Stephanus T Malherbe
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
| | - Stuart Meier
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,Bioinformatics Unit, South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Elizna Maasdorp
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,Bioinformatics Unit, South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
| | - Léanie Kleynhans
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
| | - Nelita du Plessis
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
| | - Andre G Loxton
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
| | - Daniel E Zak
- Center for Infectious Disease Research, Seattle, WA, United States
| | - Ethan Thompson
- Center for Infectious Disease Research, Seattle, WA, United States
| | - Fergal J Duffy
- Center for Infectious Disease Research, Seattle, WA, United States.,Seattle Children's Research Institute, Center for Global Infectious Disease Research, Seattle, WA, United States
| | - Helena Kuivaniemi
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa
| | - Katharina Ronacher
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,Translational Research Institute, Mater Research Institute - The University of Queensland, Brisbane, QLD, Australia
| | - Jill Winter
- Catalysis Foundation for Health, San Ramon, CA, United States
| | - Gerhard Walzl
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,Bioinformatics Unit, South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa
| | - Gerard Tromp
- Division of Molecular Biology and Human Genetics, Department of Biomedical Sciences, Stellenbosch University, Cape Town, South Africa.,DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council Centre for Tuberculosis Research, Stellenbosch University, Cape Town, South Africa.,Bioinformatics Unit, South African Tuberculosis Bioinformatics Initiative, Stellenbosch University, Cape Town, South Africa.,Centre for Bioinformatics and Computational Biology, Stellenbosch University, Stellenbosch, South Africa
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Abstract
Lymph nodes, particularly thoracic lymph nodes, are among the most common sites of extrapulmonary tuberculosis (TB). However, Mycobacterium tuberculosis (Mtb) infection in these organs is understudied. Aside from being sites of initiation of the adaptive immune system, lymph nodes also serve as niches of Mtb growth and persistence. Mtb infection results in granuloma formation that disrupts and—if it becomes large enough—replaces the normal architecture of the lymph node that is vital to its function. In preclinical models, successful TB vaccines appear to prevent spread of Mtb from the lungs to the lymph nodes. Reactivation of latent TB can start in the lymph nodes resulting in dissemination of the bacteria to the lungs and other organs. Involvement of the lymph nodes may improve Bacille Calmette-Guerin (BCG) vaccine efficacy. Lastly, drug penetration to the lymph nodes is poor compared to blood, lung tissue, and lung granulomas. Future studies on evaluating the efficacy of vaccines and anti-TB drug treatments should include consideration of the effects on thoracic lymph nodes and not just the lungs.
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Affiliation(s)
- Sharie Keanne C. Ganchua
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Alexander G. White
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Edwin C. Klein
- Division of Laboratory Animal Resources, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - JoAnne L. Flynn
- Department of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- Center for Vaccine Research, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
- * E-mail:
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