Long non-coding RNAs ENST00000429730.1 and MSTRG.93125.4 are associated with metabolic activity in tuberculosis lesions of sputum-negative tuberculosis patients

Advances of Long Non-Coding RNAs as Potential Biomarkers for Tuberculosis: New Hope for Diagnosis?

Tuberculosis (TB), one of the top ten causes of death globally induced by the infection of Mycobacterium tuberculosis (Mtb), remains a grave public health issue worldwide. With almost one-third of the world's population getting infected by Mtb, between 5% and 10% of these infected individuals are predicted to develop active TB disease, which would not only result in severe tissue damage and necrosis, but also pose serious threats to human life. However, the exact molecular mechanisms underlying the pathogenesis and immunology of TB remain unclear, which significantly restricts the effective control of TB epidemics. Despite significant advances in current detection technologies and treatments for TB, there are still no appropriate solutions that are suitable for simultaneous, early, rapid, and accurate screening of TB. Various cellular events can perturb the development and progression of TB, which are always associated with several specific molecular signaling events controlled by dysregulated gene expression patterns. Long non-coding RNAs (lncRNAs), a kind of non-coding RNA (ncRNA) with a transcript of more than 200 nucleotides in length in eukaryotic cells, have been found to regulate the expression of protein-coding genes that are involved in some critical signaling events, such as inflammatory, pathological, and immunological responses. Increasing evidence has claimed that lncRNAs might directly influence the susceptibility to TB, as well as the development and progression of TB. Therefore, lncRNAs have been widely expected to serve as promising molecular biomarkers and therapeutic targets for TB. In this review, we summarized the functions of lncRNAs and their regulatory roles in the development and progression of TB. More importantly, we widely discussed the potential of lncRNAs to act as TB biomarkers, which would offer new possibilities in novel diagnostic strategy exploration and benefit the control of the TB epidemic.

Long Non-coding RNAs in Tuberculosis: From Immunity to Biomarkers

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is the leading lethal infectious disease with 1.3 million deaths in 2020. Despite significant advances have been made in detection techniques and therapeutic approaches for tuberculosis, no suitable diagnostic tools are available for early and precise screening. Many studies have reported that Long non-coding RNAs (lncRNAs) play a regulatory role in gene expression in the host immune response against Mtb. Dysregulation of lncRNAs expression patterns associated with immunoregulatory pathways arose in mycobacterial infection. Meanwhile, host-induced lncRNAs regulate antibacterial processes such as apoptosis and autophagy to limit bacterial proliferation. In this review, we try to summarize the latest reports on how dysregulated expressed lncRNAs influence host immune response in tuberculosis infection. We also discuss their potential clinical prospects for tuberculosis diagnosis and development as molecular biomarkers.

Identification of Key CircRNAs Related to Pulmonary Tuberculosis Based on Bioinformatics Analysis

Pulmonary tuberculosis (TB) is a chronic infectious disease that is caused by respiratory infections, principally Mycobacterium tuberculosis. Increasingly, studies have shown that circular (circ)RNAs play regulatory roles in different diseases through different mechanisms. However, their roles and potential regulatory mechanisms in pulmonary TB remain unclear. In this study, we analyzed circRNA sequencing data from adjacent normal and diseased tissues from pulmonary TB patients and analyzed the differentially expressed genes. We then constructed machine learning models and used single-factor analysis to identify hub circRNAs. We downloaded the pulmonary TB micro (mi)RNA (GSE29190) and mRNA (GSE83456) gene expression datasets from the Gene Expression Omnibus database and performed differential expression analysis to determine the differentially expressed miRNAs and mRNAs. We also constructed a circRNA–miRNA–mRNA interaction network using Cytoscape. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were used to predict the biological functions of the identified RNAs and determine hub genes. Then, the STRING database and cytoHubba were used to construct protein-protein interaction networks. The results showed 125 differentially expressed circRNAs in the adjacent normal and diseased tissues of pulmonary TB patients. Among them, we identified three hub genes associated with the development of pulmonary TB: hsa_circ_0007919 (upregulated), hsa_circ_0002419 (downregulated), and hsa_circ_0005521 (downregulated). Through further screening, we determined 16 mRNAs of potential downstream genes for hsa-miR-409-5p and hsa_circ_0005521 and established an interaction network. This network may have important roles in the occurrence and development of pulmonary TB. We constructed a model with 100% prediction accuracy by machine learning and single-factor analysis. We constructed a protein-protein interaction network among the top 50 hub mRNAs, with FBXW7 scoring the highest and SOCS3 the second highest. These results may provide a new reference for the identification of candidate markers for the early diagnosis and treatment of pulmonary TB.

Comprehensive Genetic Analysis of Tuberculosis and Identification of Candidate Biomarkers

Purpose: The purpose of this study is to use the data in the GEO database to analyze, screen biomarkers that can diagnose tuberculosis, and verification of candidate biomarkers.

Materials and methods: GSE158767 dataset were used to process WGCNA analysis, differential gene analysis, Gene ontology and KEGG analysis, protein-protein network analysis and hub genes analysis. Based on our previous study, the intersect between WGCNA and differential gene analysis could be used as candidate biomarkers. Then, the enzyme-linked immunosorbent assay was used to validate candidate biomarkers, and receiver operating characteristic was used to assess diagnose ability of candidate biomarkers.

Results: A total of 412 differential genes were screened. And we obtained 105 overlapping genes between DEGs and WGCNA. GO and KEGG analysis showed that most of the differential genes were significantly enriched in innate immunity. A total of 15 hub genes were screened, and four of them were verified by Enzyme-linked immunosorbent assay. CCL5 performed well in distinguishing the healthy group from the TB group (AUC = 0.723). And CCL19 performed well in distinguishing the TB group from the ORD groups (AUC = 0.811).

Conclusion: CCL19, C1Qb, CCL5 and HLA-DMB may play important role in tuberculosis, which indicated four genes may become effective biomarkers and could be conveniently used to facilitate the individual tuberculosis diagnosis in Chinese people.

Non-Coding RNAs in the Etiology and Control of Major and Neglected Human Tropical Diseases

Non-coding RNAs (ncRNAs) including microRNAs (miRs) and long non-coding RNAs (lncRNAs) have emerged as key regulators of gene expression in immune cells development and function. Their expression is altered in different physiological and disease conditions, hence making them attractive targets for the understanding of disease etiology and the development of adjunctive control strategies, especially within the current context of mitigated success of control measures deployed to eradicate these diseases. In this review, we summarize our current understanding of the role of ncRNAs in the etiology and control of major human tropical diseases including tuberculosis, HIV/AIDS and malaria, as well as neglected tropical diseases including leishmaniasis, African trypanosomiasis and leprosy. We highlight that several ncRNAs are involved at different stages of development of these diseases, for example miR-26-5p, miR-132-3p, miR-155-5p, miR-29-3p, miR-21-5p, miR-27b-3p, miR-99b-5p, miR-125-5p, miR-146a-5p, miR-223-3p, miR-20b-5p, miR-142-3p, miR-27a-5p, miR-144-5p, miR-889-5p and miR-582-5p in tuberculosis; miR-873, MALAT1, HEAL, LINC01426, LINC00173, NEAT1, NRON, GAS5 and lincRNA-p21 in HIV/AIDS; miR-451a, miR-let-7b and miR-106b in malaria; miR-210, miR-30A-5P, miR-294, miR-721 and lncRNA 7SL RNA in leishmaniasis; and miR-21, miR-181a, miR-146a in leprosy. We further report that several ncRNAs were investigated as diseases biomarkers and a number of them showed good potential for disease diagnosis, including miR-769-5p, miR-320a, miR-22-3p, miR-423-5p, miR-17-5p, miR-20b-5p and lncRNA LOC152742 in tuberculosis; miR-146b-5p, miR-223, miR-150, miR-16, miR-191 and lncRNA NEAT1 in HIV/AIDS; miR-451 and miR-16 in malaria; miR-361-3p, miR-193b, miR-671, lncRNA 7SL in leishmaniasis; miR-101, miR-196b, miR-27b and miR-29c in leprosy. Furthermore, some ncRNAs have emerged as potential therapeutic targets, some of which include lncRNAs NEAT1, NEAT2 and lnr6RNA, 152742 in tuberculosis; MALAT1, HEAL, SAF, lincRNA-p21, NEAT1, GAS5, NRON, LINC00173 in HIV/AIDS; miRNA-146a in malaria. Finally, miR-135 and miR-126 were proposed as potential targets for the development of therapeutic vaccine against leishmaniasis. We also identify and discuss knowledge gaps that warrant for increased research work. These include investigation of the role of ncRNAs in the etiology of African trypanosomiasis and the assessment of the diagnostic potential of ncRNAs for malaria, and African trypanosomiasis. The potential targeting of ncRNAs for adjunctive therapy against tuberculosis, leishmaniasis, African trypanosomiasis and leprosy, as well as their targeting in vaccine development against tuberculosis, HIV/AIDS, malaria, African trypanosomiasis and leprosy are also new avenues to explore.