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

The Role of Rv1476 in Regulating Stress Response and Intracellular Survival of Mycobacterium tuberculosis

The virulence of Mycobacterium tuberculosis (M. tuberculosis) is related to many factors, including intracellular survival, cell wall permeability, and cell envelope proteins. However, the biological function of the M. tuberculosis membrane protein Rv1476 remains unclear. To investigate the potential role played by Rv1476, we constructed an Rv1476 overexpression strain and found that overexpression of Rv1476 enhanced the intracellular survival of M. tuberculosis, while having no impact on the growth rate in vitro. Stress experiments demonstrated that the Rv1476 overexpression strain displayed increased susceptibility to different stresses compared to the wild-type strain. Transcriptome analysis showed that Rv1476 overexpression causes changes in the transcriptome of THP-1 cells, and differential genes are mainly enriched in cell proliferation, fatty acid degradation, cytokine-cytokine receptor interaction, and immune response pathways. Rv1476 overexpression inhibited the expression of some anti-tuberculosis-related genes, such as CCL1, IL15, IL16, ISG15, GBP5, IL23, ATG2A, IFNβ, and CSF3. Altogether, we conclude that Rv1476 may play a critical role for M. tuberculosis in macrophage survival.

Identification of important modules and biomarkers in tuberculosis based on WGCNA

Background

Tuberculosis (TB) is a significant public health concern, particularly in China. Long noncoding RNAs (lncRNAs) can provide abundant pathological information regarding etiology and could include candidate biomarkers for diagnosis of TB. However, data regarding lncRNA expression profiles and specific lncRNAs associated with TB are limited.

Methods

We performed ceRNA-microarray analysis to determine the expression profile of lncRNAs in peripheral blood mononuclear cells (PBMCs). Weighted gene co-expression network analysis (WGCNA) was then conducted to identify the critical module and genes associated with TB. Other bioinformatics analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and co-expression networks, were conducted to explore the function of the critical module. Finally, real-time quantitative polymerase chain reaction (qPCR) was used to validate the candidate biomarkers, and receiver operating characteristic analysis was used to assess the diagnostic performance of the candidate biomarkers.

Results

Based on 8 TB patients and 9 healthy controls (HCs), a total of 1,372 differentially expressed lncRNAs were identified, including 738 upregulated lncRNAs and 634 downregulated lncRNAs. Among all lncRNAs and mRNAs in the microarray, the top 25% lncRNAs (3729) and top 25% mRNAs (2824), which exhibited higher median expression values, were incorporated into the WGCNA. The analysis generated 16 co-expression modules, among which the blue module was highly correlated with TB. GO and KEGG analyses showed that the blue module was significantly enriched in infection and immunity. Subsequently, considering module membership values (>0.85), gene significance values (>0.90) and fold-change value (>2 or < 0.5) as selection criteria, the top 10 upregulated lncRNAs and top 10 downregulated lncRNAs in the blue module were considered as potential biomarkers. The candidates were then validated in an independent validation sample set (31 TB patients and 32 HCs). The expression levels of 8 candidates differed significantly between TB patients and HCs. The lncRNAs ABHD17B (area under the curve [AUC] = 1.000) and ENST00000607464.1 (AUC = 1.000) were the best lncRNAs in distinguishing TB patients from HCs.

Conclusion

This study characterized the lncRNA profiles of TB patients and identified a significant module associated with TB as well as novel potential biomarkers for TB diagnosis.

Host-directed therapy against mycobacterium tuberculosis infections with diabetes mellitus

Tuberculosis (TB) is caused by the bacterial pathogen Mycobacterium tuberculosis (MTB) and is one of the principal reasons for mortality and morbidity worldwide. Currently, recommended anti-tuberculosis drugs include isoniazid, rifampicin, ethambutol, and pyrazinamide. TB treatment is lengthy and inflicted with severe side-effects, including reduced patient compliance with treatment and promotion of drug-resistant strains. TB is also prone to other concomitant diseases such as diabetes and HIV. These drug-resistant and complex co-morbid characteristics increase the complexity of treating MTB. Host-directed therapy (HDT), which effectively eliminates MTB and minimizes inflammatory tissue damage, primarily by targeting the immune system, is currently an attractive complementary approach. The drugs used for HDT are repositioned drugs in actual clinical practice with relative safety and efficacy assurance. HDT is a potentially effective therapeutic intervention for the treatment of MTB and diabetic MTB, and can compensate for the shortcomings of current TB therapies, including the reduction of drug resistance and modulation of immune response. Here, we summarize the state-of-the-art roles and mechanisms of HDT in immune modulation and treatment of MTB, with a special focus on the role of HDT in diabetic MTB, to emphasize the potential of HDT in controlling MTB infection.

Long non-coding RNA expression in PBMCs of patients with active pulmonary tuberculosis

Purpose

Mycobacterium tuberculosis (Mtb) infection is the primary cause of the chronic infectious illness tuberculosis (TB). Long non-coding RNAs (lncRNAs) are functional RNA molecules that cannot be translated into proteins and play a crucial role in regulating the immune system's innate and adaptive responses. It has been demonstrated that the dysregulation of lncRNA expression is associated with various human diseases. However, the mechanism underlying the involvement of so many lncRNAs in the immune response to TB infection remains unclear. The objective of our current study was to identify a number of significantly differentially expressed lncRNAs in peripheral blood mononuclear cells (PBMCs) from TB patients and to select the most indicative lncRNAs as potential biomarkers for active pulmonary tuberculosis.

Methods

Microarray analysis was performed to determine the lncRNA and mRNA expression profiles in TB patients using a case-control model. The differentially expressed lncRNAs were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to investigate potential roles and pathways associated with the pathogenesis of TB infection, and to screen lncRNAs specifically linked to TB infection. Using real-time fluorescence quantitative PCR (QRT-PCR), specific lncRNAs were identified in TB patients and latent infections.

Results

Our findings revealed that various signaling pathways were differentially expressed in TB-infected individuals, suggesting a potential role for lncRNAs in the immunological responses driven by TB infection. This study provides crucial guidelines for future functional research. Upregulated lncRNAs were mainly enriched in Neutrophil extracellular trap formation and Chemokine signaling pathways, while downregulated lncRNAs were enriched in Neuroactive ligand-receptor interaction and Cushing syndrome in TB PBMCs. Furthermore, we found that lnc-XPNPEP1-5, lnc-CASKIN2-2, lnc-HSPA13-6, lnc-CLIC5-1, and LINC02502 were significantly downregulated in TB-infected patients, while LINC00528, lnc-SLC45A4-3, and LINC00926 were significantly upregulated in TB patients and latent infections. These eight lncRNAs, identified as novel biological marker candidates for diagnosing TB infection, were validated by real-time fluorescence quantitative PCR (QRT-PCR).

Conclusion

The abnormally expressed lncRNAs identified in this research may provide crucial information for understanding the pathophysiological characteristics of TB patients and the dysfunction of PBMCs. Our findings reveal potential targets for early TB diagnosis and therapy, as well as offer new insights into the mechanisms underlying TB infection.

Comparative proteome analysis revealed the differences in response to both Mycobacterium tuberculosis and Mycobacterium bovis infection of bovine alveolar macrophages

Tuberculosis (TB), attributed to the Mycobacterium tuberculosis complex, is one of the most serious zoonotic diseases worldwide. Nevertheless, the host mechanisms preferentially leveraged by Mycobacterium remain unclear. After infection, both Mycobacterium tuberculosis (MTB) and Mycobacterium bovis (MB) bacteria exhibit intimate interactions with host alveolar macrophages; however, the specific mechanisms underlying these macrophage responses remain ambiguous. In our study, we performed a comparative proteomic analysis of bovine alveolar macrophages (BAMs) infected with MTB or MB to elucidate the differential responses of BAMs to each pathogen at the protein level. Our findings revealed heightened TB infection susceptibility of BAMs that had been previously infected with MTB or MB. Moreover, we observed that both types of mycobacteria triggered significant changes in BAM energy metabolism. A variety of proteins and signalling pathways associated with autophagy and inflammation-related progression were highly activated in BAMs following MB infection. Additionally, proteins linked to energy metabolism were highly expressed in BAMs following MTB infection. In summary, we propose that BAMs may resist MTB and MB infections via different mechanisms. Our findings provide critical insights into TB pathogenesis, unveiling potential biomarkers to facilitate more effective TB treatment strategies. Additionally, our data lend support to the hypothesis that MTB may be transmitted via cross-species infection.

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.

Screening for diagnostic targets in tuberculosis and study on its pathogenic mechanism based on mRNA sequencing technology and miRNA-mRNA-pathway regulatory network

Purpose

Tuberculosis is common infectious diseases, characterized by infectivity, concealment and chronicity, and the early diagnosis is helpful to block the spread of tuberculosis and reduce the resistance of Mycobacterium tuberculosis to anti-tuberculosis drugs. At present, there are obvious limitations in the application of clinical detection methods used for the early diagnosis of tuberculosis. RNA sequencing (RNA-Seq) has become an economical and accurate gene sequencing method for quantifying transcripts and detecting unknown RNA species.

Methods

A peripheral blood mRNA sequencing was used to screen the differentially expressed genes between healthy people and tuberculosis patients. A protein-protein interaction (PPI) network of differentially expressed genes was constructed through Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The potential diagnostic targets of tuberculosis were screened by the calculation of degree, betweenness and closeness in Cytoscape 3.9.1 software. Finally, the functional pathways and the molecular mechanism of tuberculosis were clarified in combination of the prediction results of key gene miRNAs, and by Gene Ontology (GO) enrichment analysis and the Kyoto Encyclopedia Genes and Genomes (KEGG) pathway annotation analysis.

Results

556 Differential genes of tuberculosis were screened out by mRNA sequencing. Six key genes (AKT1, TP53, EGF, ARF1, CD274 and PRKCZ) were screened as the potential diagnostic targets for tuberculosis by analyzing the PPI regulatory network and using three algorithms. Three pathways related to the pathogenesis of tuberculosis were identified by KEGG pathway analysis, and two key miRNAs (has-miR-150-5p and has-miR-25-3p) that might participate in the pathogenesis of tuberculosis were screened out by constructing a miRNA-mRNA pathway regulatory network.

Conclusion

Six key genes and two important miRNAs that could regulate them were screened out by mRNA sequencing. The 6 key genes and 2 important miRNAs may participate in the pathogenesis of infection and invasion of Mycobacterium tuberculosis through herpes simplex virus 1 infection, endocytosis and B cell receptor signaling pathways.

Analysis of the noncoding RNA regulatory networks of H37Rv- and H37Rv△1759c-infected macrophages

Noncoding RNAs regulate the process of Mycobacterium tuberculosis (M. tb) infecting the host, but there is no simultaneous transcriptional information of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) and the global regulatory networks of non-coding RNA. Rv1759c, a virulence factor, is a member of protein family containing the proline-glutamic acid (PE) in M. tb, which can increase M. tb survival. To reveal the noncoding RNA regulatory networks and the effect of Rv1759c on non-coding RNA expression during M. tb infection, we collected samples of H37Rv- and H37Rv△1759c-infected macrophages and explored the full transcriptome expression profile. We found 356 mRNAs, 433 lncRNAs, 168 circRNAs, and 12 miRNAs differentially expressed during H37Rv infection, 356 mRNAs, 433 lncRNAs, 168 circRNAs, and 12 miRNAs differentially expressed during H37Rv△1759c infection. We constructed lncRNA/circRNA-miRNA-mRNA regulatory networks during H37Rv and H37Rv△1759c infection. We demonstrated the role of one of the hubs of the networks, hsa-miR-181b-3p, for H37Rv survival in macrophages. We discovered that the expression changes of 68 mRNAs, 92 lncRNAs, 26 circRNAs, and 3 miRNAs were only related to the deletion of Rv1759c by comparing the transcription profiles of H37Rv and H37Rv△1759c. Here, our study comprehensively characterizes the transcriptional profiles in THP1-derived-macrophages infected with H37Rv and H37Rv△1759c, which provides support and new directions for in-depth exploration of noncoding RNA and PE/PPE family functions during the infection process.