Latent tuberculosis infection (LTBI) is an important part of the spectrum of tuberculosis (TB) that is caused by Mycobacterium tuberculosis. Programmatic management, monitoring and evaluating active TB and LTBI in high risk groups (particularly in those with human immunodeficiency virus (HIV) infection) and providing appropriate treatment are priorities of action as identified in the End TB Strategy.

The pathology of TB, including LTBI, reactivation, progression, and response to chemotherapy, is multi-factorial. It involves both host and bacterial factors that influence host–pathogen interactions. Genetic aspects of the host influence disease susceptibility and progression, especially components of the innate and adaptive immune responses, such as toll-like receptor [TLR] alleles, cytokine expression, and drug metabolism. The risk of TB progression and treatment outcome also depends on the type of infecting organism, including strain lineages and polymorphisms that can affect the expressions of virulence factors, surface glycolipids, and stress responses.

The objective of this Research Topic is to support the scientific community by collecting relevant articles in which high-throughput technologies from human biospecimens and mycobacterial cultures are used to facilitate a better understanding of the factors that affect the risk of TB progression and reactivation in addition to treatment outcome.

The Research Topic welcomes transcriptional profiles of whole blood and sites of diseased fluid (bronchoalveolar lavage) and cells. This topic includes techniques, such as RNA-sequencing (microRNA and messenger RNA), methylomics, metabolomics, cytokine profiling of plasma/serum, and high-dimensional analysis in immune cells for both innate and adaptive immunity and sputum microbiome. Whole-genome sequencing and RNA-seq of bacterial samples of M. tuberculosis clinical isolates will also be collected to determine their role in TB progression.

Manuscripts describing the use of imaging technologies (such as positron emission tomography/computed tomography [PET/CT]) coupled with omics techniques will also be considered.

These multi-omics datasets of host and pathogen for in vitro/animal/clinical cohorts coupled with statistical analysis, data integration, and systems modeling will enable development of a better understanding of factors affecting the risk of TB reactivation and biomarkers for treatment outcomes.

Omics data are often collected individually, while this Research Topic will aim to collect this data uniformly and systematically as a solid ground for use in preclinical to clinical TB research.

The resulting dataset is intended to provide a unique resource to advance the research and understanding of TB in HIV-1-infected individuals.

This Research Topic welcomes contributions in the form of, but not limited to, original research, reviews, and mini reviews with focus on several parameters:

1) Advancing tuberculosis biomarkers for point-of-care tuberculosis diagnostics
2) Biomarkers for point-of-care tuberculosis treatment response
3) Biomarkers for TB in HIV-1-infected and -exposed children and adults
4) Biomarkers to predict TB reactivation
5) Multi-omics (transcriptomics, epigenomics, metabolomics, and proteomics) technology: methods and applications
6) Multi-omics approaches: challenges and opportunities

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Frontiers in Microbiology

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