Diagnostic value of microRNA-155 in active tuberculosis: A systematic review and meta-analysis

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Mouse Models for Mycobacterium tuberculosis Pathogenesis: Show and Do Not Tell

Science has been taking profit from animal models since the first translational experiments back in ancient Greece. From there, and across all history, several remarkable findings have been obtained using animal models. One of the most popular models, especially for research in infectious diseases, is the mouse. Regarding research in tuberculosis, the mouse has provided useful information about host and bacterial traits related to susceptibility to the infection. The effect of aging, sexual dimorphisms, the route of infection, genetic differences between mice lineages and unbalanced immunity scenarios upon Mycobacterium tuberculosis infection and tuberculosis development has helped, helps and will help biomedical researchers in the design of new tools for diagnosis, treatment and prevention of tuberculosis, despite various discrepancies and the lack of deep study in some areas of these traits.

The diagnostic value of combined detection of microRNA-155, TNF-α and IL-37 for active pulmonary tuberculosis in the elderly

OBJECTIVE

To identify a panel of potential biomarkers consisting of microRNA-155 (miR-155), tumor necrosis factor-alpha (TNF-α), interleukin-37 (IL-37) for the diagnosis of active pulmonary tuberculosis (PTB) infection in elderly patients.

METHODS

The serum expression of miR-155 and TNF-α in patients was measured by RT-qPCR, and the serum IL-37 level was determined by ELISA. The correlation between their expression and the features of active PTB patients was also analyzed. The AUCs of miR-155, TNF-α and IL-37 in diagnosing active PTB was calculated according to the ROC curves. The sensitivity, specificity and Youden's index of the three biomarkers alone or in combination for the active PTB diagnosis in the elderly were assessed.

RESULTS

miR-155, TNF-α, and IL-37 were overexpressed in the sera of elderly patients with active PTB. miR-155, TNF-α and IL-37 serum levels were enhanced in the elderly patients with pulmonary and extrapulmonary TB relative to those with PTB only, and in patients with active TB infection in both lungs compared to those with unilateral lung infection. The AUCs of miR-155, TNF-α and IL-37 for the diagnosis of active PTB were 0.7920, 0.8734 and 0.7398, respectively. The combination of these three improved the sensitivity of the diagnosis (84.78%).

CONCLUSION

miR-155, TNF-α and IL-37 were overexpressed in elderly patients with active PTB. The combined detection of serum miR-155/TNF-α/IL-37 expression has potential to serve as a diagnostic tool for active PTB in the elderly.

Diagnostic value of Long non-coding Ribonucleic Acid non-coding activated by Deoxyribonucleic Acid damage in pulmonary tuberculosis and its regulatory role in Mycobacterium tuberculosis infection of macrophages

Pulmonary tuberculosis (PTB) infection is a chronic inflammatory response caused by Mycobacterium tuberculosis (Mtb). The purpose of this study was to confirm the value of Long non-coding RNA (LncRNA) non-coding activated by DNA damage (NORAD) in the diagnosis of PTB and to explore its mechanism in Mtb-infected macrophages. NORAD serum levels were estimated by qRT-PCR in 90 PTB patients and 85 healthy individuals. ROC curves were employed to assess the diagnostic value of NORAD for PTB. Human and murine macrophages were infected with Mtb strain H37Rv. CCK-8 and ELISA detected macrophages viability and inflammatory cytokine secretion. A dual-luciferase reporter assay was performed to analyze the targeting relationship between NORAD and microRNA (miR)-618. NORAD was significantly elevated in patients with PTB, and its positivity was correlated with inflammatory cytokines IL-1 β (r = 0.854), TNF-α (r = 0.617), IL-6 (r = 0.585). With an AUC of 0.918, and sensitivity and specificity of 80.0% and 89.4%, respectively, NORAD remarkedly identified PTB patients from healthy individuals. Furthermore, Mtb infection significantly increased NORAD levels in THP-1 and RAW264.7 and increased their viability and inflammation (P <0.001). However, this increased effect was weakened by reduced NORAD. Dual-luciferase reporter assay confirmed that miR-618 in macrophages was a target miRNA for NORAD and can be negatively regulated by it. Moreover, elevated miR-618 suppressed macrophage viability and inflammation in Mtb infection. NORAD is a potential diagnostic biomarker for PTB and is involved in Mtb infected macrophage activity and inflammation by targeting miR-618. This article is protected by copyright. All rights reserved.