Dheda, K;
Lenders, L;
Srivastava, S;
Magombedze, G;
Wainwright, H;
Raj, P;
Bush, SJ;
... Gumbo, T; + view all
(2019)
Spatial Network Mapping of Pulmonary Multidrug-Resistant Tuberculosis Cavities Using RNA Sequencing.
American Journal of Respiratory and Critical Care Medicine
, 200
(3)
pp. 370-380.
10.1164/rccm.201807-1361OC.
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Abstract
RATIONALE: There is poor understanding about protective immunity and the pathogenesis of cavitation in tuberculosis patients. OBJECTIVES: To map pathophysiological pathways at anatomically distinct positions within the human tuberculosis cavity. METHODS: Biopsies were obtained from eight pre-determined locations within lung cavities of multidrug-resistant tuberculosis patients undergoing therapeutic surgical resection (n=14) and healthy lung tissue from non-tuberculosis controls (n=10). RNA sequencing, immunohistochemistry, and bacterial load determination was performed at each cavity position. Differentially expressed genes were normalized to non-tuberculosis controls, and ontologically mapped to identify a spatially compartmentalized pathophysiological map of the cavity. In silico perturbation using a novel distance-dependent dynamical sink model was used to investigate interactions between immune networks and bacterial burden, and to integrate these identified pathways. RESULTS: The median (range) lung cavity volume on PET-CT scans was 50cm3 (15-389cm3). RNA sequence reads (31% splice variants) mapped to 19,049 annotated human genes. Multiple pro-inflammatory pathways were upregulated in the cavity wall, while a downregulation 'sink' in the central caseum-fluid interface characterized 53% of pathways including neuroendocrine signaling, calcium signaling, TREM-1, reactive oxygen and nitrogen species production, retinoic acid-mediated apoptosis, and RIG-I-like receptor signaling. The mathematical model demonstrated that neuroendocrine, protein kinase C-θ, and TREM-1 pathways, as well as macrophage and neutrophil numbers, had the highest correlation with bacterial burden (r>0.6), while T-helper effector systems did not. CONCLUSION: These data provide novel insights into host immunity to drug-resistant Immune Mycobacterium tuberculosis-related cavitation. The pathways defined may serve as useful targets for the design of host-directed therapies, and transmission prevention interventions.
| Type: | Article |
|---|---|
| Title: | Spatial Network Mapping of Pulmonary Multidrug-Resistant Tuberculosis Cavities Using RNA Sequencing |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1164/rccm.201807-1361OC |
| Publisher version: | https://doi.org/10.1164/rccm.201807-1361OC |
| Language: | English |
| Additional information: | This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/ licenses/by/4.0/). |
| Keywords: | TB cavitation, in silico analysis, pulmonary tuberculosis, transcriptomics |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Infection and Immunity |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10067129 |
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