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Unlocking the potential of miRNAs in detecting pulmonary tuberculosis: prospects and pitfalls

Published online by Cambridge University Press:  06 December 2024

Rakesh Arya
Affiliation:
Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, South Korea
Surendra Kumar
Affiliation:
Department of Orthopaedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
Joseph M. Vinetz
Affiliation:
Department of Internal Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT, USA
Jong Joo Kim*
Affiliation:
Department of Biotechnology, Yeungnam University, Gyeongsan, Gyeongbuk, South Korea
Reetika Chaurasia*
Affiliation:
Department of Internal Medicine, Section of Infectious Diseases, Yale University School of Medicine, New Haven, CT, USA
*
Corresponding authors: Jong Joo Kim; Email: kimjj@ynu.ac.kr; Reetika Chaurasia; Email: reetika.chaurasia@yale.edu
Corresponding authors: Jong Joo Kim; Email: kimjj@ynu.ac.kr; Reetika Chaurasia; Email: reetika.chaurasia@yale.edu
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Abstract

Tuberculosis (TB) is one of the deadliest infectious diseases globally, ranking as 13th leading cause of mortality and morbidity. According to the Global Tuberculosis Report 2022, TB claimed the lives of 1.6 million people worldwide in 2021. Among the casualties, 1 870 000 individuals with HIV co-infections contributed to 6.7% of the total fatalities, accounting TB as the second most lethal infectious disease following COVID-19. In the quest to identify biomarkers for disease progression and anti-TB therapy, microRNAs (miRNAs) have gained attention due to their precise regulatory role in gene expression in disease stages and their ability to distinguish latent and active TB, enabling the development of early TB prognostic signatures. miRNAs are stable in biological fluids and therefore will be useful for non-invasive and broad sample collection. However, their inherent lack of specificity and experimental variations may lead to false-positive outcomes. These limitations can be overcome by integrating standard protocols with machine learning, presenting a novel tool for TB diagnostics and therapeutics. This review summarizes, discusses and highlights the potential of miRNAs as a biomarker, particularly their differential expression at disease stages. The review assesses the advantages and obstacles associated with miRNA-based diagnostic biomarkers in pulmonary TB and facilitates rapid, point-of-care testing.

Information

Type
Review
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press must be obtained prior to any commercial use and/or adaptation of the article.
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press
Figure 0

Table 1. Differentially expressed miRNAs are involved in the pathogenesis and survival of Mtb

Figure 1

Table 2. Differentially expressed miRNAs found in biofluids of tuberculosis patients in different studies

Figure 2

Figure 1. Schematic representation of miRNA regulation of apoptosis and autophagy in Mtb-infected macrophage. MiR-155 and miR-223 are potential regulators of apoptosis and autophagy in M. tuberculosis. During Mtb infection, acyl carrier protein (AcpM; Rv2244) of Mtb promotes the expression of miR-155, which targets SH2 domain-containing inositol 5-phosphatase-1 (SHIP1) to activate the Akt1/mTOR pathway. The activated Akt1/mTOR signalling pathway inhibits the nuclear translocation of transcription factor EB (TFEB) and reduces the expression of autophagy and lysosomal genes, which is likely to induce antimicrobial defence and improves intracellular mycobacterial survival by inhibiting phagosome–lysosome fusion in macrophages (Ref. 133). MiR-155 can abolish expression of SHIP1, leading to activation of phosphatidylinositol 3-kinase (PI3 K) signalling-mediated inhibition of pro-apoptotic factors including Bad, FOXO-1 and FOXO-3. In addition, miR-155 and miR-223 can also directly target and suppress the expression of FOXO-3 which is not able to induce a variety of apoptotic stimuli and reducing the release of cytochrome c from mitochondria, which in turn inhibits a series of downstream biochemical reactions, mediates caspase inactivation and downregulate the apoptotic process (Ref. 134). MiR-155 is induced by TLR activation which inhibits suppressor of cytokine signaling-1 (SOCS1) and activate signal transducer and activator of transcription-1 (STAT1) to induce the production of pro-inflammatory cytokines such as IL-6, IL-1β and TNF-α (Refs 16, 135). miR-155 and miR-223 also inhibit IL-6 expression which in turn inhibits IFN-γ inducted autophagy in M. tuberculosis-infected macrophages (Refs 136, 137). MiR-155 also inhibits TAB2 which can abrogate the activation of NFκB to induce the activation of autophagy-related genes. Inhibition of TAB2 y miR-155 also leads to the suppression of JNK pathway-related proteins to regulate innate immune responses in macrophages (Refs 16, 137). MiR-155 also targets Ras homologue enriched in brain (Rheb) and mediates the positive regulation of autophagy during Mtb infection (Ref. 63). Adapted from references (Refs 16, 63, 133, 134, 135, 136, 137).

Figure 3

Figure 2. Dysregulated miRNA expression in active TB versus LTBI. The process of Mtb infection starts when bacilli from an active-TB patient are transmitted to a nearby host via aerosol droplets. Localized alveolar macrophages then ingest the Mtb allowing it to enter lung interstitial tissue. T and B cells, neutrophils and other immune system cells are recruited to the site of infection and converge with the infected macrophage to form a granuloma. To ensure its survival, Mtb prompt the release of both pro- and anti-inflammatory cytokines from granuloma, leading to the successful evasion of the host immune response and resulting in the state of latency or the development of active TB disease. Here, red indicates upregulated factors, while green signifies downregulated ones.