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Mapping and manipulating the M. tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network

ABSTRACT: Expression data from transcription factor over expression experiments (Abstract from paper will be appended after publication)

ORGANISM(S): Mycobacterium tuberculosis H37Rv

PROVIDER: GSE59086 | GEO | 2014/07/04

SECONDARY ACCESSION(S): PRJNA254351

REPOSITORIES: GEO

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Project description: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.

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Mapping and manipulating the M. tuberculosis transcriptome using a transcription factor overexpression-derived regulatory network

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