Dheda, Keertan; Lenders, Laura; Srivastava, Shashikant; Magombedze, Gesham; Wainwright, Helen; Raj, Prithvi; Bush, Stephen J; Pollara, Gabriele; Steyn, Rachelle; Davids, Malika; +11 more... Pooran, Anil; Pennel, Timothy; Linegar, Anthony; McNerney, Ruth; Moodley, Loven; Pasipanodya, Jotam G; Turner, Carolin T; Noursadeghi, Mahdad; Warren, Robin M; Wakeland, Edward; Gumbo, Tawanda; (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. ISSN 1073-449X DOI: https://doi.org/10.1164/rccm.201807-1361OC
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Abstract
Rationale: There is poor understanding about protective immunity and the pathogenesis of cavitation in patients with tuberculosis.Objectives: To map pathophysiological pathways at anatomically distinct positions within the human tuberculosis cavity.Methods: Biopsies were obtained from eight predetermined locations within lung cavities of patients with multidrug-resistant tuberculosis undergoing therapeutic surgical resection (n = 14) and healthy lung tissue from control subjects without tuberculosis (n = 10). RNA sequencing, immunohistochemistry, and bacterial load determination were performed at each cavity position. Differentially expressed genes were normalized to control subjects without tuberculosis, 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.Measurements and Main Results: The median (range) lung cavity volume on positron emission tomography/computed tomography scans was 50 cm3 (15-389 cm3). RNA sequence reads (31% splice variants) mapped to 19,049 annotated human genes. Multiple proinflammatory pathways were upregulated in the cavity wall, whereas a downregulation "sink" in the central caseum-fluid interface characterized 53% of pathways including neuroendocrine signaling, calcium signaling, triggering receptor expressed on myeloid cells-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 triggering receptor expressed on myeloid cells-1 pathways, and macrophage and neutrophil numbers, had the highest correlation with bacterial burden (r > 0.6), whereas T-helper effector systems did not.Conclusions: These data provide novel insights into host immunity to Mycobacterium tuberculosis-related cavitation. The pathways defined may serve as useful targets for the design of host-directed therapies, and transmission prevention interventions.
Item Type | Article |
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Faculty and Department | Faculty of Infectious and Tropical Diseases > Department of Infection Biology |
PubMed ID | 30694692 |
Elements ID | 132575 |
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Filename: Spatial Network Mapping of Pulmonary Multidrug-Resistant Tuberculosis Cavities Using RNA Sequencing.pdf
Licence: Creative Commons: Attribution 3.0
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