Identifcation of differentially expressed long non-coding RNAs in CD4+ T cells response to latent tuberculosis infection

Differential Expression of lncRNAs in HIV Patients with TB and HIV-TB with Anti-Retroviral Treatment

Tuberculosis (TB) is the leading cause of death among people with HIV-1 infection. To improve the diagnosis and treatment of HIV-TB patients, it is important to understand the mechanisms underlying these conditions. Here, we used an integrated genomics approach to analyze and determine the lncRNAs that are dysregulated in HIV-TB patients and HIV-TB patients undergoing anti-retroviral therapy (ART) using a dataset available in the public domain. The analyses focused on the portion of the genome transcribed into non-coding transcripts, which historically have been poorly studied and received less focus. This revealed that Mtb infection in HIV prominently up-regulates the expression of long non-coding RNA (lncRNA) genes DAAM2-AS1, COL4A2-AS1, LINC00599, AC008592.1, and CLRN1-AS1 and down-regulates the expression of lncRNAs AC111000.4, AC100803.3, AC016168.2, AC245100.7, and LINC02073. It also revealed that ART down-regulates the expression of some lncRNA genes (COL4A2-AS1, AC079210.1, MFA-AS1, and LINC01993) that are highly up-regulated in HIV-TB patients. Furthermore, the interrogation of the genomic regions that are associated with regulated lncRNAs showed enrichment for biological processes linked to immune pathways in TB-infected conditions. However, intriguingly, TB patients treated with ART showed completely opposite and non-overlapping pathways. Our findings suggest that lncRNAs could be used to identify critical diagnostic, prognostic, and treatment targets for HIV-TB patients.

Construction of ceRNA regulatory networks for active pulmonary tuberculosis

Delayed diagnosis in patients with pulmonary tuberculosis (PTB) often leads to serious public health problems. High throughput sequencing was used to determine the expression levels of lncRNAs, mRNAs, and miRNAs in the lesions and adjacent health lung tissues of patients with PTB. Their differential expression profiles between the two groups were compared, and 146 DElncRs, 447 DEmRs, and 29 DEmiRs were obtained between lesions and adjacent health tissues in patients with PTB. Enrichment analysis for mRNAs showed that they were mainly involved in Th1, Th2, and Th17 cell differentiation. The lncRNAs, mRNAs with target relationship with miRNAs were predicted respectively, and correlation analysis was performed. The ceRNA regulatory network was obtained by comparing with the differentially expressed transcripts (DElncRs, DEmRs, DEmiRs), then 2 lncRNAs mediated ceRNA networks were established. The expression of genes within the network was verified by quantitative real-time PCR (qRT-PCR). Flow cytometric analysis revealed that the proportion of Th1 cells and Th17 cells was lower in PTB than in controls, while the proportion of Th2 cells increased. Our results provide rich transcriptome data for a deeper investigation of PTB. The ceRNA regulatory network we obtained may be instructive for the diagnosis and treatment of PTB.

ncRNAs: an unexplored cellular defense mechanism in leprosy

Leprosy is an infectious disease primarily caused by the obligate intracellular parasite Mycobacterium leprae. Although it has been considered eradicated in many countries, leprosy continues to be a health issue in developing nations. Besides the social stigma associated with it, individuals affected by leprosy may experience nerve damage leading to physical disabilities if the disease is not properly treated or early diagnosed. Leprosy is recognized as a complex disease wherein socioenvironmental factors, immune response, and host genetics interact to contribute to its development. Recently, a new field of study called epigenetics has emerged, revealing that the immune response and other mechanisms related to infectious diseases can be influenced by noncoding RNAs. This review aims to summarize the significant advancements concerning non-coding RNAs in leprosy, discussing the key perspectives on this novel approach to comprehending the pathophysiology of the disease and identifying molecular markers. In our view, investigations on non-coding RNAs in leprosy hold promise and warrant increased attention from researches in this field.

Pathogenic mycoplasmas of humans regulate the long noncoding RNAs in epithelial cells

Non-coding RNAs (ncRNAs), specifically long ncRNAs (lncRNAs), regulate cellular processes by affecting gene expression at the transcriptional, post-transcriptional, and epigenetic levels. Emerging evidence indicates that pathogenic microbes dysregulate the expression of host lncRNAs to suppress cellular defense mechanisms and promote survival. To understand whether the pathogenic human mycoplasmas dysregulate host lncRNAs, we infected HeLa cells with Mycoplasma genitalium (Mg) and Mycoplasma penumoniae (Mp) and assessed the expression of lncRNAs by directional RNA-seq analysis. HeLa cells infected with these species showed up-and-down regulation of lncRNAs expression, indicating that both species can modulate host lncRNAs. However, the number of upregulated (200 for Mg and 112 for Mp) and downregulated lncRNAs (30 for Mg and 62 for Mp) differ widely between these two species. GREAT analysis of the noncoding regions associated with differentially expressed lncRNAs showed that Mg and Mp regulate a discrete set of lncRNA plausibly related to transcription, metabolism, and inflammation. Further, signaling network analysis of the differentially regulated lncRNAs exhibited diverse pathways such as neurodegeneration, NOD-like receptor signaling, MAPK signaling, p53 signaling, and PI3K signaling, suggesting that both species primarily target signaling mechanisms. Overall, the study's results suggest that Mg and Mp modulate lncRNAs to promote their survival within the host but in distinct manners.

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.

Functions of exosomal non-coding RNAs to the infection with Mycobacterium tuberculosis

Tuberculosis (TB) is a major infectious disease induced by Mycobacterium tuberculosis (M. tb) which causes the world's dominant fatal bacterial contagious disease. Increasing studies have indicated that exosomes may be a novel option for the diagnosis and treatment of TB. Exosomes are nanovesicles (30-150 nm) containing lipids, proteins and non-coding RNAs (ncRNAs) released from various cells, and can transfer their cargos and communicate between cells. Furthermore, exosomal ncRNAs exhibit diagnosis potential in bacterial infections, including TB. Additionally, differential exosomal ncRNAs regulate the physiological and pathological functions of M. tb-infected cells and act as diagnostic markers for TB. This current review explored the potential biological roles and the diagnostic application prospects of exosomal ncRNAs, and included recent information on their pathogenic and therapeutic functions in TB.

Aberrant expression of long non-coding RNAs in peripheral blood mononuclear cells response to tuberculosis in children

We aimed to identify long non-coding RNAs (lncRNAs) aberrantly expressed in peripheral blood mononuclear cells (PBMCs) triggered by active tuberculosis (ATB), latent tuberculosis infection (LTBI), and healthy controls (HC). We examined lncRNAs expression in PBMCs isolated from children with ATB and LTBI, and from HC using RNA sequencing. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to explore the biological processes and signaling pathways of aberrantly expressed mRNAs. A total of 348 and 205 lncRNAs were differentially expressed in the ATB and LTBI groups, respectively, compared to the HC group. Compared to the LTBI group, 125 lncRNAs were differentially expressed in the ATB group. Compared to the HC group, 2317 mRNAs were differentially expressed in the ATB group, and 1093 mRNAs were differentially expressed in the LTBI group. Compared to the LTBI group, 2328 mRNAs were differentially expressed in the ATB group. The upregulated mRNAs were mainly enriched in neutrophil activation, neutrophil-mediated biological processes, and positive regulation of immune response in tuberculosis (TB), whereas the downregulated mRNAs were enriched in signaling pathways and structural processes, such as the Wnt signaling pathway and rDNA heterochromatin assembly. This is the first study on the differential expression of lncRNAs in PBMCs of children with TB. We identified significant differences in the expression profiles of lncRNAs and mRNAs in the PBMCs of children with ATB, LTBI, and HC, which has important implications for exploring lncRNAs as novel biomarkers for the diagnosis of TB. In addition, further experimental identification and validation of lncRNA roles could help elucidate the underlying mechanisms of Mycobacterium tuberculosis infection in children.

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.

Association Between Genetic Polymorphisms of lncRNA NEAT1 and Pulmonary Tuberculosis Risk, Clinical Manifestations in a Chinese Population

Background

Recent studies have shown that abnormal expression of lncRNA NEAT1 is associated with the progression of pulmonary tuberculosis (PTB). The aim of our study was to analyze the relationship between single nucleotide polymorphisms (SNPs) of NEAT1 gene and susceptibility to PTB.

Methods

Four SNPs (rs2239895, rs3741384, rs3825071, rs512715) in NEAT1 gene were genotyped in 479 patients with PTB and 476 controls by improved multiple ligase detection reaction (iMLDR) in a Chinese population.

Results

We found no significant differences in allele and genotype frequencies of NEAT1 gene rs2239895, rs3741384, rs3825071, rs512715 between PTB patients and controls (all P > 0.05). There was no statistically significant association between genotype frequency distribution of dominant model, as well as recessive model, and genetic susceptibility to PTB patients (all P > 0.05). The TT genotype, T allele frequencies of rs3825071 were significantly increased in sputum smear-positive PTB patients when compared to sputum smear-negative PTB patients (P = 0.010, P = 0.003, respectively). Haplotype analysis shown that NEAT1 haplotype frequency was not associated with PTB susceptibility.

Conclusion

NEAT1 gene polymorphisms were not associated with the risk of PTB in Chinese population, and rs3825071 polymorphism might be related to sputum smear-positive in PTB patients.

Screening of Long Non-coding RNAs Biomarkers for the Diagnosis of Tuberculosis and Preliminary Construction of a Clinical Diagnosis Model

Background

Pathogenic testing for tuberculosis (TB) is not yet sufficient for early and differential clinical diagnosis; thus, we investigated the potential of screening long non-coding RNAs (lncRNAs) from human hosts and using machine learning (ML) algorithms combined with electronic health record (EHR) metrics to construct a diagnostic model.

Methods

A total of 2,759 subjects were included in this study, including 12 in the primary screening cohort [7 TB patients and 5 healthy controls (HCs)] and 2,747 in the selection cohort (798 TB patients, 299 patients with non-TB lung disease, and 1,650 HCs). An Affymetrix HTA2.0 array and qRT-PCR were applied to screen new specific lncRNA markers for TB in individual nucleated cells from host peripheral blood. A ML algorithm was established to combine the patients’ EHR information and lncRNA data via logistic regression models and nomogram visualization to differentiate PTB from suspected patients of the selection cohort.

Results

Two differentially expressed lncRNAs (TCONS_00001838 and n406498) were identified (p < 0.001) in the selection cohort. The optimal model was the “LncRNA + EHR” model, which included the above two lncRNAs and eight EHR parameters (age, hemoglobin, lymphocyte count, gamma interferon release test, weight loss, night sweats, polymorphic changes, and calcified foci on imaging). The best model was visualized by a nomogram and validated, and the accuracy of the “LncRNA + EHR” model was 0.79 (0.75–0.82), with a sensitivity of 0.81 (0.78–0.86), a specificity of 0.73 (0.64–0.79), and an area under the ROC curve (AUC) of 0.86. Furthermore, the nomogram showed good compliance in predicting the risk of TB and a higher net benefit than the “EHR” model for threshold probabilities of 0.2–1.

Conclusion

LncRNAs TCONS_00001838 and n406498 have the potential to become new molecular markers for PTB, and the nomogram of “LncRNA + EHR” model is expected to be effective for the early clinical diagnosis of TB.

Diagnostic significance of long non-coding RNAs expression in tuberculosis patients: A systematic review and meta-analysis

OBJECTIVES

It is crucial to identify effective diagnostic biosignatures of tuberculosis (TB) to optimize its treatment. Herein, we conducted a systematic review to elucidate the diagnostic efficacy of long noncoding RNA (lncRNAs) as TB biomarkers.

METHODS

We searched Medline, Web of Science, Embase, Cochrane Library, CNKI, Wanfang, VIP, and China Biology Medicine disc databases up to February 18, 2020. These studies focusing on lncRNAs as diagnosis markers of TB were collected. STATA 12.0 and Meta-disc1.4 software were used to analyze the data extracted from eligible studies.

RESULTS

We included 8 articles with 1058 TB patients, and 1896 healthy controls in our study. The values of pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.63, 0.86, 4.48, 0.43, and 10.31, respectively. Additionally, we plotted the summary receiver operating characteristic curve to evaluate the diagnostic accuracy, and the area under the curve was 0.80.

CONCLUSION

The present study is the first meta-analysis to assess the diagnostic accuracy of lncRNAs in TB patients. We found that lncRNAs might constitute potential biomarkers for the diagnosis of TB patients. More population-based high-quality research should be conducted to validate the efficacy lncRNAs in TB patients.

Long Non-coding Antisense RNA DDIT4-AS1 Regulates Meningitic Escherichia coli-Induced Neuroinflammation by Promoting DDIT4 mRNA Stability

Our previous studies have shown that meningitic Escherichia coli can colonize the brain and cause neuroinflammation. Controlling the balance of inflammatory responses in the host central nervous system is particularly vital. Emerging evidence has shown the important regulatory roles of long non-coding RNAs (lncRNAs) in a wide range of biological and pathological processes. However, whether lncRNAs participate in the regulation of meningitic E. coli-mediated neuroinflammation remains unknown. In the present study, we characterized a cytoplasm-enriched antisense lncRNA DDIT4-AS1, which showed similar concordant expression patterns with its parental mRNA DDIT4 upon E. coli infection. DDIT4-AS1 modulated DDIT4 expression at both mRNA and protein levels. Mechanistically, DDIT4-AS1 promoted the stability of DDIT4 mRNA through RNA duplex formation. DDIT4-AS1 knockdown and DDIT4 knockout both attenuated E. coli-induced NF-κB signaling as well as pro-inflammatory cytokines expression, and DDIT4-AS1 regulated the inflammatory response by targeting DDIT4. In summary, our results show that DDIT4-AS1 promotes E. coli-induced neuroinflammatory responses by enhancing the stability of DDIT4 mRNA through RNA duplex formation, providing potential nucleic acid targets for new therapeutic interventions in the treatment of bacterial meningitis.

Lipidomics revealed the global lipid responses of primary bovine alveolar macrophages to infections of Mycobacterium tuberculosis and Mycobacterium bovis

Mycobacterium tuberculosis (M. tuberculosis (MTB) and M. bovis (MB) of the Mycobacterium tuberculosis complex (MTBC) are the causative agents of the notorious infectious disease tuberculosis (TB) in a range of mammals, including bovine and human. The lipid composition of MTB/MB performed imperative function as invading host macrophage. However, the detailed variations in lipid compositions of MTB and MB were unknown, while the responses relevant to lipid metabolisms in MTB/MB-infected host were also unclear. In the present study, a dual-Lipidomics were used to elucidate the differences in lipid composition of MTB and MB and responses in lipid metabolisms of primary bovine alveolar macrophages infected by MTB/MB. The Lipidomics showed significant differences in lipid composition, especially differences in levels of Glycerophospholipids, Sterol Lipids, Fatty Acyls and Polyketides between these two mycobacterium species. Meanwhile, both MTB and MB could invoke various responses of lipid metabolisms in host macrophages. An infection of MTB mainly induced the increases of Polyketides and Glycerophospholipids in macrophages, whereas an MB infection induced the increases of Glycerophospholipids and Sterol. Furthermore, TAG 13:0-18:5-18:5 of MTB and PC (16:1(9E)/0:0), PI(20:2(11Z,14Z)/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), 4, 6-Decadiyn-1-ol isovalerate and LacCer (d18:1/24:1(15Z)) of MB were identified to cause variations in lipid metabolisms of macrophages, respectively. From these data, we proposed that the differential compositions of lipid compositions in MTB and MB could successfully colonize in macrophage by different mechanisms. MTB could promote the formation of foam cells of macrophage for its colonization and development, while MB mainly suppresses the macrophage autophagy to escape the immune responses of host.

A preliminary analysis of LncRNA biomarkers for schizophrenia

Aim: The aim of this study was to identify the long noncoding RNAs (lncRNAs) associated with schizophrenia (SZ) and the relationships among their expression, antipsychotic efficacy and SZ severity. Method: The diagnostic and predictive value of nine lncRNAs, Gomafu, DISC2, PSZA11, AK096174, AK123097, DB340248, uc011dma.1, ENST00000509804-1 and ENST00000509804-2, was investigated in 48 patients with SZ before and after antipsychotic treatment. Results: Gomafu, AK096174, AK123097, DB340248, uc011dma.1, ENST00000509804-1 and ENST00000509804-2 were individually and collectively associated with, and predictive of, SZ pathogenesis. Moreover, increased expression of plasma AK123097, uc011dma.1 and ENST00000509804-1 levels was reversed after 12 weeks of antipsychotic treatment, which was associated with SZ severity. Conclusion: Seven lncRNAs serve as novel biomarkers for SZ diagnosis and prognosis and three lncRNAs are potential therapeutic targets.

LncRNA-ENST00000421645 promotes T cells to secrete IFN-γ by sponging PCM1 in neurosyphilis

Aim: Neurosyphilis patients exhibited significant expression of long noncoding RNA (lncRNA) in peripheral blood T lymphocytes. In this study, we further clarified the role of lncRNA-ENST00000421645 in the pathogenic mechanism of neurosyphilis. Methods: lncRNA-ENST00000421645 was transfected into Jurkat-E6-1 cells, namely lentivirus (Lv)-1645 cells. RNA pull-down assay, flow cytometry, RT-qPCR, ELISA (Neobioscience Technology Co Ltd, Shenzhen, China) and RNA immunoprecipitation chip assay were used to analyze the function of lncRNA-ENST00000421645. Results: The expression of IFN-γ in Lv-1645 cells was significantly increased compared to that in Jurkat-E6-1 cells stimulated by phorbol-12-myristate-13-acetate (PMA). Then, it was suggested that lncRNA-ENST00000421645 interacts with PCM1 protein. Silencing PCM1 significantly increased the level of IFN-γ in Lv-1645 cells stimulated by PMA. Conclusion: This study revealed that lncRNA-ENST00000421645 mediates the production of IFN-γ by sponging PCM1 protein after PMA stimulation.

The Role of microRNAs and Long Non-Coding RNAs in the Regulation of the Immune Response to Mycobacterium tuberculosis Infection

Non-coding RNAs have emerged as critical regulators of the immune response to infection. MicroRNAs (miRNAs) are small non-coding RNAs which regulate host defense mechanisms against viruses, bacteria and fungi. They are involved in the delicate interplay between Mycobacterium tuberculosis, the causative agent of tuberculosis (TB), and its host, which dictates the course of infection. Differential expression of miRNAs upon infection with M. tuberculosis, regulates host signaling pathways linked to inflammation, autophagy, apoptosis and polarization of macrophages. Experimental evidence suggests that virulent M. tuberculosis often utilize host miRNAs to promote pathogenicity by restricting host-mediated antibacterial signaling pathways. At the same time, host- induced miRNAs augment antibacterial processes such as autophagy, to limit bacterial proliferation. Targeting miRNAs is an emerging option for host-directed therapies. Recent studies have explored the role of long non-coding RNA (lncRNAs) in the regulation of the host response to mycobacterial infection. Among other functions, lncRNAs interact with chromatin remodelers to regulate gene expression and also function as miRNA sponges. In this review we attempt to summarize recent literature on how miRNAs and lncRNAs are differentially expressed during the course of M. tuberculosis infection, and how they influence the outcome of infection. We also discuss the potential use of non-coding RNAs as biomarkers of active and latent tuberculosis. Comprehensive understanding of the role of these non-coding RNAs is the first step towards developing RNA-based therapeutics and diagnostic tools for the treatment of TB.

Use of RNA Sequencing to Perform Comprehensive Analysis of Long Noncoding RNA Expression Profiles in Macrophages Infected with Trichosporon asahii

Trichosporon asahii (T. asahii) is a clinically important opportunistic pathogenic fungus capable of causing systemic lethal infection in immunosuppressive and immunodeficient hosts. However, the mechanism of the host immune response upon T. asahii infection has not been elucidated. Recent evidence has shown that long noncoding RNAs (lncRNAs) play key roles in regulating the immune response to resist microbial infections. In this study, we analyzed the expression profiles of lncRNAs at 12 and 24 h post-infection (hpi) in THP-1 cells infected with T. asahii using RNA sequencing (RNA-Seq). A total of 64 and 160 lncRNAs displayed significant differentially expressed (DE) at 12 h and 24 hpi, respectively. Among these lncRNAs, 18 lncRNAs were continuous DE at two time points. The DE of eight candidate lncRNAs were verified by real time quantitative polymerase chain reaction (RT-qPCR). Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed to analyze the cis-target genes of 18 DE lncRNAs. The results showed that they were enriched in signaling pathways related to the host immune response, indicating that these lncRNAs might play important roles in fungi-host interactions. Finally, we explored the function of lncRNA NEAT1 and found that the expression of TNF-α and IL-1β declined after NEAT1 knockdown in T. asahii-infected THP-1 cells. To our knowledge, this is the first report of a expression analysis of lncRNAs in macrophages infected with T. asahii. Our study helps to elucidate the role of lncRNAs in the host immune response to early infection by T. asahii.

Identification of differentially expressed lncRNAs as potential plasma biomarkers for active tuberculosis

BACKGROUND

Tuberculosis, one of the deadliest infectious diseases worldwide, is difficult to diagnose. As long noncoding RNAs (lncRNAs) were demonstrated to be promising biomarkers, we aimed to identify lncRNAs in plasma as potential biomarkers for tuberculosis.

METHODS

We analyzed a GEO dataset (GSE94907) to identify the differential lncRNAs in serum exosomes between active tuberculosis (ATB) patients and healthy controls. To search for promising candidates that can be used for tuberculosis diagnosis, we excluded low-abundance lncRNAs using a cutoff value of FPKM >5. Four lncRNAs were selected for validation using real-time quantitative PCR in 69 ATB patients and 69 healthy individuals. A receiver operating characteristic (ROC) curve was constructed to evaluate the diagnostic value of these lncRNAs for ATB.

RESULTS

Integrated analysis of the GEO dataset and NONCODE database identified nine dysregulated lncRNAs in ATB patient serum exosomes. Compared with the heathy controls, NONHSAT101518.2, NONHSAT067134.2, NONHSAT148822.1 and NONHSAT078957.2 were significantly downregulated in ATB patient plasma. ROC curve analysis suggests that these four lncRNAs can discriminate ATB from healthy individuals with high specificity and sensitivity.

CONCLUSION

We identified four differentially expressed lncRNAs in ATB patient plasma that can be used as potential diagnostic biomarkers of ATB.

The role of non-coding RNA on macrophage modification in tuberculosis infection

Tuberculosis (TB), a serious disease caused by Mycobacterium tuberculosis (Mtb), remains the world's top infectious killer. It is well-established that TB can circumvent the host's immune response for long-term survival. Macrophages serve as the major host cells for TB growth and persistence and their altered functions are critical for the response of the host defense against TB exposure (elimination, latency, reactivation, and bacillary dissemination). Noncoding RNAs are crucial posttranscriptional regulators of macrophage discrimination. Therefore, this review highlights the regulatory mechanism underlying the relationship between noncoding RNAs and macrophages in TB infection, which may facilitate the identification of potential therapeutic targets and effective diagnosis biomarkers for TB disease.

Long Noncoding RNA and Predictive Model To Improve Diagnosis of Clinically Diagnosed Pulmonary Tuberculosis

Clinically diagnosed pulmonary tuberculosis (PTB) patients lack microbiological evidence of Mycobacterium tuberculosis, and misdiagnosis or delayed diagnosis often occurs as a consequence. We investigated the potential of long noncoding RNAs (lncRNAs) and corresponding predictive models to diagnose these patients. We enrolled 1,764 subjects, including clinically diagnosed PTB patients, microbiologically confirmed PTB cases, non-TB disease controls, and healthy controls, in three cohorts (screening, selection, and validation).

Clinically diagnosed pulmonary tuberculosis (PTB) patients lack microbiological evidence of Mycobacterium tuberculosis, and misdiagnosis or delayed diagnosis often occurs as a consequence. We investigated the potential of long noncoding RNAs (lncRNAs) and corresponding predictive models to diagnose these patients. We enrolled 1,764 subjects, including clinically diagnosed PTB patients, microbiologically confirmed PTB cases, non-TB disease controls, and healthy controls, in three cohorts (screening, selection, and validation). Candidate lncRNAs differentially expressed in blood samples of the PTB and healthy control groups were identified by microarray and reverse transcription-quantitative PCR (qRT-PCR) in the screening cohort. Logistic regression models were developed using lncRNAs and/or electronic health records (EHRs) from clinically diagnosed PTB patients and non-TB disease controls in the selection cohort. These models were evaluated by area under the concentration-time curve (AUC) and decision curve analyses, and the optimal model was presented as a Web-based nomogram, which was evaluated in the validation cohort. Three differentially expressed lncRNAs (ENST00000497872, n333737, and n335265) were identified. The optimal model (i.e., nomogram) incorporated these three lncRNAs and six EHRs (age, hemoglobin, weight loss, low-grade fever, calcification detected by computed tomography [CT calcification], and interferon gamma release assay for tuberculosis [TB-IGRA]). The nomogram showed an AUC of 0.89, a sensitivity of 0.86, and a specificity of 0.82 in differentiating clinically diagnosed PTB cases from non-TB disease controls of the validation cohort, which demonstrated better discrimination and clinical net benefit than the EHR model. The nomogram also had a discriminative power (AUC, 0.90; sensitivity, 0.85; specificity, 0.81) in identifying microbiologically confirmed PTB patients. lncRNAs and the user-friendly nomogram could facilitate the early identification of PTB cases among suspected patients with negative M. tuberculosis microbiological evidence.

Regulatory SNP rs5743417 impairs constitutive expression of human β-defensin 1 and has high frequency in Africans and Afro-Americans

The prediction of regulatory single nucleotide polymorphisms (rSNPs) in proximal promoters of disease-related genes could be a useful tool for personalized medicine in both patient stratification and customized therapy. Using our previously reported method of rSNPs prediction (currently a software called SNPClinic v.1.0) as well as with PredictSNP tool, we performed in silico prediction of regulatory SNPs in the antimicrobial peptide human β-defensin 1 gene in three human cell lines from 1,000 Genomes Project (1kGP), namely A549 (epithelial cell line), HL-60 (neutrophils) and T_H 1 (lymphocytes). These predictions were run in a proximal pseudo-promoter comprising all common alleles on each polymorphic site according to the 1,000 Genomes Project data (1kGP: ALL). Plasmid vectors containing either the major or the minor allele of a putative rSNP rs5743417 (categorized as regulatory by SNPClinic and confirmed by PredictSNP) and a non-rSNP negative control were transfected to lung A549 human epithelial cell line. We assessed functionality of rSNPs by qPCR using the Pfaffl method. In A549 cells, minor allele of the SNP rs5743417 G→A showed a significant reduction in gene expression, diminishing DEFB1 transcription by 33% when compared with the G major allele (p-value = .03). SNP rs5743417 minor allele has high frequency in Gambians (8%, 1kGP population: GWD) and Afro-Americans (3.3%, 1kGP population: ASW). This SNP alters three transcription factors binding sites (TFBSs) comprising SREBP2 (sterols and haematopoietic pathways), CREB1 (cAMP, insulin and TNF pathways) and JUND (apoptosis, senescence and stress pathways) in the proximal promoter of DEFB1. Further in silico analysis reveals that this SNP also overlaps with GS1-24F4.2, a lincRNA gene complementary to the X Kell blood group related 5 (XKR5) mRNA. The potential clinical impact of the altered constitutive expression of DEFB1 caused by rSNP rs5743417 in DEFB1-associated diseases as tuberculosis, COPD, asthma, cystic fibrosis and cancer in African and Afro-American populations deserves further research.

Long Noncoding RNAs in Host-Pathogen Interactions

Long noncoding RNAs (lncRNAs) are key molecules that regulate gene expression in a variety of organisms. LncRNAs can drive different transcriptional and post-transcriptional events that impact cellular functions. Recent studies have identified many lncRNAs associated with immune cell development and activation; however, an understanding of their functional role in host immunity to infection is just emerging. Here, we provide a detailed and updated review of the functional roles of lncRNAs in regulating mammalian immune responses during host-pathogen interactions, because these functions may be either beneficial or detrimental to the host. With increased mechanistic insight into the roles of lncRNAs, it may be possible to design and/or improve lncRNA-based therapies to treat a variety of infectious and inflammatory diseases.

Mycobacterium smegmatis But Not Mycobacterium avium subsp. hominissuis Causes Increased Expression of the Long Non-Coding RNA MEG3 in THP-1-Derived Human Macrophages and Associated Decrease of TGF-β

Pathogenic mycobacteria are able to persist intracellularly in macrophages, whereas non-pathogenic mycobacteria are effectively combated and eliminated after their phagocytosis. It is known that TGF-β plays an important role in this context. Infection with pathogenic mycobacteria such as Mycobacterium tuberculosis or M. avium leads to production of active TGF-β, which blocks the ability of IFN-γ and TNF-α to inhibit intracellular replication. On the other hand, it is known that the long non-coding RNA (lncRNA) maternally expressed 3 (MEG3) is involved in the regulation of TGF-β. In this study, we show how the infection of THP-1-derived human macrophages with the saprophytic M. smegmatis but not with the facultatively pathogenic M. avium subsp. hominissuis leads to increased MEG3 expression. This is associated with the downregulation of DNA methyltransferases (DNMT) 1 and 3b, which are known to regulate MEG3 expression via promoter hypermethylation. Consequently, we observe a significant downregulation of TGF-β in M. smegmatis-infected macrophages but not in M. avium subsp. hominissuis pointing to lncRNAs as novel mediators of host cell response during mycobacterial infections.

Host Transcriptomics as a Tool to Identify Diagnostic and Mechanistic Immune Signatures of Tuberculosis

Tuberculosis (TB) is a major infectious disease worldwide, and is associated with several challenges for control and eradication. First, more accurate diagnostic tools that better represent the spectrum of infection states are required; in particular, identify the latent TB infected individuals with high risk of developing active TB. Second, we need to better understand, from a mechanistic point of view, why the immune system is unsuccessful in some cases for control and elimination of the pathogen. Host transcriptomics is a powerful approach to identify both diagnostic and mechanistic immune signatures of diseases. We have recently reported that optimal study design for these two purposes should be guided by different sets of criteria. Here, based on already published transcriptomics signatures of tuberculosis, we further develop these guidelines and identify additional factors to consider for obtaining diagnostic vs. mechanistic signatures in terms of cohorts, samples, data generation and analysis. Diagnostic studies should aim to identify small disease signatures with high discriminatory power across all affected populations, and against similar pathologies to TB. Specific focus should be made on improving the diagnosis of infected individuals at risk of developing active disease. Conversely, mechanistic studies should focus on tissues biopsies, immune relevant cell subsets, state of the art transcriptomic techniques and bioinformatics tools to understand the biological meaning of identified gene signatures that could facilitate therapeutic interventions. Finally, investigators should ensure their data are made publicly available along with complete annotations to facilitate metadata and cross-study analyses.

Long Non-Coding RNAs in the Regulation of Gene Expression: Physiology and Disease

The identification of RNAs that are not translated into proteins was an important breakthrough, defining the diversity of molecules involved in eukaryotic regulation of gene expression. These non-coding RNAs can be divided into two main classes according to their length: short non-coding RNAs, such as microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). The lncRNAs in association with other molecules can coordinate several physiological processes and their dysfunction may impact in several pathologies, including cancer and infectious diseases. They can control the flux of genetic information, such as chromosome structure modulation, transcription, splicing, messenger RNA (mRNA) stability, mRNA availability, and post-translational modifications. Long non-coding RNAs present interaction domains for DNA, mRNAs, miRNAs, and proteins, depending on both sequence and secondary structure. The advent of new generation sequencing has provided evidences of putative lncRNAs existence; however, the analysis of transcriptomes for their functional characterization remains a challenge. Here, we review some important aspects of lncRNA biology, focusing on their role as regulatory elements in gene expression modulation during physiological and disease processes, with implications in host and pathogens physiology, and their role in immune response modulation.

Long noncoding RNAs as regulators of cancer immunity

Long noncoding RNAs (lncRNAs) are increasingly known to be important in cancer as they directly interact with the cell cycle, proliferation pathways and microbiome balance. Moreover, lncRNAs regulate the immune system: they do not directly encode proteins of innate or adaptive immunity, but regulate immune cell differentiation and function, such as dendritic cell activity, T cell ratio and metabolism. The result of this complex interaction is that lncRNAs regulate cancer processes through a complex multimodal system involving immunity, metabolism and infection. The possible functions of lncRNAs and their roles in the regulation of cancer immunity will be reported and discussed in the present review. Recent studies showed their function as regulators in the tumour microenvironment (TME), epithelial-mesenchymal transition, microbiota, metabolism and immune cell differentiation. However, there is not much knowledge regarding their roles in cancer immunity regulation. Thus, the main aim of this review is to describe lncRNAs that have specifically been associated with immunity, the immune cycle and the TME.

The Expression of lncRNA NEAT1 in Human Tuberculosis and Its Antituberculosis Effect

Increasing evidence suggests that lncRNA is important in innate immune responses. Recent study has demonstrated that lncRNA NEAT1 (which has two subtypes: NEAT1_1 and NEAT1_2) nuclear-enriched abundant transcript 1 (NEAT1) is essential in immune regulation, but the expression and clinical significance in tuberculosis are still unclear. In this work, we aimed to discuss the expression and clinical significance of NEAT1 in tuberculosis patients. Quantitative real-time polymerase chain reaction was performed to detect the expression of NEAT1 (both NEAT1_1 and NEAT1_2) in peripheral blood mononuclear cells (PBMCs) of patients with tuberculosis and healthy controls and analyze the association of NEAT1 with the development, progression, and outcome of tuberculosis. Then NEAT1 was silenced in THP-1 cells using siRNA. The expression of tumor necrosis factor- (TNF-) α and interleukin- (IL-) 6 was detected after Mycobacterium tuberculosis (Mtb) infection, and the change in bactericidal capacity against Mtb was assessed. We demonstrated that the relative expression of NEAT1 (both NEAT1_1 and NEAT1_2) in patients with tuberculosis was higher than that in the control. However, the expression of NEAT1 (both NEAT1_1 and NEAT1_2) in the new case and relapse groups had insignificant differences. The level of NEAT1 (both NEAT1_1 and NEAT1_2) in PBMCs declined gradually with treatment and was restored to the normal level. The expression of NEAT1 (both NEAT1_1 and NEAT1_2) in THP-1 cells increased markedly after Mtb infection. The levels of IL-6 but not TNF-α in Mtb-infected THP-1 cells declined after the NEAT1 (both NEAT1_1 and NEAT1_2) knockout. The survival of Mtb in NEAT1-knockout (both NEAT1_1 and NEAT1_2) THP-1 cells reached its peak 72 h after infection, taking 0 h after Mtb infection as the baseline data; the difference was statistically significant compared with the control. Thus, our results indicate that the expression of NEAT1 increased during Mtb infection, and it might be associated with the outcome of tuberculosis. The decreased expression of NEAT1 might weaken the clearance of intracellular Mtb by macrophages.

Variation in the Untranslated Genome and Susceptibility to Infections

The clinical outcomes of infections are highly variable among individuals and are determined by complex host-pathogen interactions. Genome-wide association studies (GWAS) are powerful tools to unravel common genetic variations that are associated with disease risk and clinical outcomes. However, GWAS has only rarely revealed information on the exact genetic elements and their effects underlying an association because the majority of the hits are within non-coding regions. Some of the variants or the linked polymorphisms are now being discovered to have functional significance, such as regulatory elements in the promoter and enhancer regions or the microRNA binding sites in the 3′untranslated region of the protein-coding genes, which influence transcription, RNA stability, and translation of the protein-coding genes. However, only 3% of the entire transcriptome is protein-coding, signifying that non-coding RNAs represent most of the transcripts. Thus, a large portion of previously identified intergenic GWAS single nucleotide polymorphisms (SNPs) is in the non-coding RNAs. The non-coding RNAs form a large-scale regulatory network across the transcriptome, greatly expanding the complexity of gene regulation. Accumulating evidence also suggests that the “non-coding” genome regions actively regulate the highly dynamic three dimensional (3D) chromatin structures, which are critical for genome function. Epigenetic modulation like DNA methylation and histone modifications further affect chromatin accessibility and gene expression adding another layer of complexity to the functional interpretation of genetic variation associated with disease outcomes. We provide an overview of the current information on the influence of variation in these “untranslated” regions of the human genome on infectious diseases. The focus of this review is infectious disease-associated polymorphisms and gene regulatory mechanisms of pathophysiological relevance.

Identifying differentially expressed long non-coding RNAs in PBMCs in response to the infection of multidrug-resistant tuberculosis

Purpose

The aim of this paper was to identify differentially expressed long non-coding RNAs (lncRNAs) in peripheral blood mononuclear cells (PBMCs) influenced by the infection of multidrug-resistant tuberculosis (MDR-TB).

Materials and methods

IncRNA and mRNA expression profiles in PBMCs derived from healthy controls (HCs) and individuals with MDR-TB and drug-sensitive tuberculosis (DS-TB) were analyzed and compared by microarray assay. Six lncRNAs were randomly selected for validation by using real-time quantitative polymerase chain reaction (RT-qPCR). The biological functions and signaling pathways affected by the differentially expressed mRNAs were investigated by using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-based approaches.

Results

Compared with the HC group, 1,429 lncRNAs (983 mRNAs) and 2,040 lncRNAs (1,407 mRNAs) were identified to be deregulated in the MDR-TB group and in the DS-TB group, respectively, and 1,511 lncRNAs and 1,047 mRNAs were identified to be differentially expressed in both MDR-TB and DS-TB groups. Between the three groups, 22 lncRNAs and 38 mRNAs were found deregulated. Most deregulated lncRNAs were from intergenic regions (~55% of the total), natural antisense to protein-coding loci (~32% of the total), or intronic antisense to protein-coding loci (~5% of the total). Significantly enriched signaling pathways regulated by the deregulated mRNAs were mainly associated with natural killer cell-mediated cytotoxicity, antigen processing and presentation, graft-vs-host disease, the transforming growth factor-β signaling pathway, and the Hippo signaling pathway.

Conclusion

This study is the first to report differentially expressed lncRNAs in PBMCs in response to MDR-TB infection. It revealed that some lncRNAs might be associated with regulating host immune response to MDR-TB infection. Further elucidation of the potential of these deregulated lncRNAs in MDR-TB and its reactivation requires further study.

Screening and identification of lncRNAs as potential biomarkers for pulmonary tuberculosis

Pulmonary tuberculosis (TB) is among the diseases with the highest morbidity and mortality worldwide. Effective diagnostic methods for TB are lacking. In this study, we investigated long non-coding RNAs (lncRNAs) in plasma using microarray and the potential diagnostic value of lncRNAs for TB. We found a total of 163 up-regulated lncRNAs and 348 down-regulated lncRNAs. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and coding-noncoding co-expression (CNC) analyses showed that functions of differentially expressed lncRNAs were mainly enriched in the regulation of alpha-beta T cell activation and the T cell receptor signalling pathway. Four differentially expressed lncRNAs, NR_038221 (fold change = 3.79, P < 0.01), NR_003142 (fold change = 1.69, P < 0.05), ENST00000570366 (fold change = 3.04, P < 0.05), and ENST00000422183 (fold change = 2.11, P < 0.001), were verified using RT-qPCR. Among those, NR_038221, NR_003142, and ENST00000570366 were found to be up-regulated, while ENST00000422183 was down-regulated. The value of the area under the curve (AUC) for the diagnostic model consisting of the four lncRNAs was 0.845 (sensitivity = 79.2%, specificity = 75%). We further predicted 85 mRNAs and 404 miRNAs that potentially interact with these lncRNAs. Our study revealed the potential value of lncRNAs as biomarkers for early diagnosis of TB and the underlying mechanisms of these abnormally expressed lncRNAs in the pathogenesis of TB.

Comprehensive analysis of long non-coding RNA and mRNA expression profiles in rheumatoid arthritis

Abnormal expression of long non-coding RNA (lncRNA) has been demonstrated to be involved in a variety of human diseases. However, the role of lncRNA remains largely unknown in rheumatoid arthritis (RA). The present study aimed to investigate whether lncRNA are differentially expressed in RA. Differentially expressed lncRNA and mRNA in peripheral blood mononuclear cells from individuals with RA and healthy controls were detected using a human lncRNA microarray containing 30,586 lncRNA and 26,109 coding transcripts. Several candidate lncRNA and mRNA in 24 paired samples were verified by reverse transcription-quantitative polymerase chain reaction analysis. Bioinformatics analyses (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) were used to evaluate signaling pathways and biological functions influenced by the differentially expressed mRNA. A total of 5,045 lncRNA (upregulated, 2,410; downregulated, 2,635) and 3,289 mRNA (upregulated, 1,403; downregulated, 1,886) were differentially expressed in patients with RA (fold change >2; P<0.05). The majority of abnormal lncRNA were from intergenic spacer regions (42%), natural antisense (19%) and intronic antisense (15%) to protein-coding loci. lncRNA target prediction indicated the presence of 135 potential lncRNA-mRNA target pairs for the 85 aberrant lncRNA and 109 aberrant mRNA. Significantly enriched (P<0.05) signaling pathways based on deregulated mRNA were mostly implicated in bile secretion, T cell receptor signaling pathway and systemic lupus erythematosus. In summary, to the best of our knowledge, the present study executed global expression profiling of lncRNA and mRNA involved in RA for the first time. These results may provide important insights regarding lncRNA in RA pathogenesis and provide potential therapeutic targets.

Significance of genetic polymorphisms in long non-coding RNA AC079767.4 in tuberculosis susceptibility and clinical phenotype in Western Chinese Han population

Recent studies have implicated long non-coding RNA, AC079767.4, as a highly susceptible gene in tuberculosis. The aim of the study was to preliminarily explore the possible association of single nucleotide polymorphisms (SNPs) in AC079767.4 gene with clinical phenotypes and TB susceptibility in Western Chinese Han population. The improved multiplex ligation detection reaction (iMLDR) method was employed to genotype 4 SNPs in AC079767.4 in 554 tuberculosis patients and 561 healthy individuals. In subgroup analysis, only the C allele for rs12477677 was associated with the decreased susceptibility to pulmonary TB with a p-value of 0.026, but p-value was 0.103 after Bonferroni correction. In total samples, haplotype [ACAC], representing four AC079767.4 variants, was found to slightly decrease TB risk (p = 0.045). Furthermore, patients with the CC genotype of rs12477677 were correlated with fewer occurrences of fever (p = 0.016), while patients carrying the T allele were associated with lower levels of ESR in the dominant model of rs1055229 (p = 0.021). For the first time, we reported the potential susceptibility and clinical traits of tuberculosis with lncRNA variants in the Western Han Chinese population. Our data indicate AC079767.4 polymorphisms may potentially act as novel biomarkers for tuberculosis diagnostic and therapeutic purposes.

A Long Journey Ahead: Long Non-coding RNAs in Bacterial Infections

Bacterial pathogens have coevolved with their hosts and acquired strategies to circumvent defense mechanisms of host cells. It was shown that bacteria interfere with the expression of mammalian microRNAs to modify immune signaling, autophagy, or the apoptotic machinery. Recently, a new class of regulatory RNAs, long non-coding RNAs (lncRNAs), was reported to have a pivotal role in the regulation of eukaryotic gene expression. A growing body of literature reports on specific involvement of lncRNAs in the host cell response toward bacterial infections. This mini review summarizes recent data that focuses on lncRNA function in host cells during bacterial infection and provides a perspective where future research in this regard may be going.

Deregulated lncRNAs in B Cells from Patients with Active Tuberculosis

Role of lncRNAs in human adaptive immune response to TB infection is largely unexplored. To address this issue, here we characterized lncRNA expression profile in primary human B cell response to TB infection using microarray assay. Several lncRNAs and mRNAs were chosen for RT-qPCR validation. Bioinformatics prediction was applied to delineate function of the deregulated mRNAs. We found that 844 lncRNAs and 597 mRNAs were differentially expressed between B cell samples from individuals with or without TB. KEGG pathway analysis for the deregulated mRNAs indicated a number of pathways, such as TB, TLR signaling pathway and antigen processing and presentation. Moreover, corresponding to the dysregulation of many lncRNAs, we also found that their adjacent protein-coding genes were also deregulated. Functional annotation for the corresponding mRNAs showed that these lncRNAs were mainly associated with TLR signaling, TGF-β signaling. Interestingly, SOCS3, which is a critical negative regulator of cytokine response to TB infection and its nearby lncRNA XLOC_012582, were highly expressed in active TB B cells. Subsequent RT-qPCR results confirmed the changes. Whether upregulated XLOC_012582 causes SOCS3 overexpression and is eventually involved in the context of exacerbations of active TB represents an interesting issue that deserves to be further explored. Taken together, for the first time, we identified a set of deregulated lncRNAs in active TB B cells and their functions were predicted. Such findings provided novel insight into the pathogenesis of TB and further studies should focus on the function and pathogenic mechanisms of the lncRNAs involved in active TB.

Expression profile of lncRNA in human bronchial epithelial cells response to Talaromyces marneffei infection: A microarray analysis

Talaromyces marneffei is an important opportunistic pathogenic fungus capable of causing systemic lethal infection through inhalation of its conidia. However, little is known about the pathogenesis and interactions between Talaromyces marneffei and host. The aim of this study was to identify potential long noncoding RNAs (lncRNAs) and coding genes associated with interactions between airway epithelial cell and Talaromyces marneffei conidia. We carried out a microarray analysis to determine the expression profile of lncRNA and mRNA in human bronchial epithelial cell in response to Talaromyces marneffei infection. Compared to control group, we found that 370 and 149 lncRNAs were up and down regulated, respectively. Meanwhile, the expression level of 269 and 60 mRNAs was increased and decreased, respectively. To understand the potential role of the differentially expressed lncRNAs, we performed functional annotations of the corresponding coding genes using gene ontology and pathway analyses. Our results provide insights into the pathogenesis of early infection by Talaromyces marneffei.

Microarray analysis of long noncoding RNA and mRNA expression profiles in human macrophages infected with Mycobacterium tuberculosis

Macrophages play a crucial role in the control and elimination of invading Mycobacterium tuberculosis (Mtb), and also serve as the major residence for Mtb. However, the interaction between macrophages and Mtb remains to be clearly determined. Although long noncoding RNAs (lncRNAs) have emerged as key regulators in many biological processes, their roles in anti-mycobacterial responses of macrophages remain to be elucidated. Here, we applied microarray analysis to examine lncRNA and mRNA expression profiles in human primary macrophages after 72 h of infection with H37Ra or H37Rv. Our results revealed that many lncRNAs were differentially expressed in macrophages after H37Ra or H37Rv infection, indicating a possible role for lncRNAs in immune responses induced by Mtb infection and providing important cues for further functional studies. Furthermore, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analysis of the differentially expressed mRNAs showed the potential functions and pathways related to the pathogenesis of Mtb infection. Finally, two lncRNAs, MIR3945HG V1 and MIR3945HG V2, were identified as novel candidate diagnostic markers for tuberculosis. Our results provide novel insight into the mechanisms of the pivotal Mtb-macrophage interactions, and reveal potential targets for diagnostics and the treatment of tuberculosis.

Long noncoding RNAs in innate immunity

Long noncoding RNAs (lncRNAs) have been shown to play important roles in immune cell development and immune responses through different mechanisms, such as dosage compensation, imprinting, enhancer function, and transcriptional regulation. Although the functions of most lncRNAs are unclear, some lncRNAs have been found to control transcriptional or post-transcriptional regulation of the innate and adaptive immune responses via new methods of protein–protein interactions or pairing with DNA and RNA. Interestingly, increasing evidence has elucidated the importance of lncRNAs in the interaction between hosts and pathogens. In this review, an overview of the lncRNAs modes of action, as well as the important and diversified roles of lncRNAs in immunity, are provided, and an emerging paradigm of lncRNAs in regulating innate immune responses is highlighted.

miRNA Regulation Network Analysis in Qianliening Capsule Treatment of Benign Prostatic Hyperplasia

Objective. The objective of this study was to evaluate the molecular mechanism by which Qianliening capsule (QC) treats benign prostatic hyperplasia (BPH). Methods. Benign prostatic hyperplasia epithelial cell line BPH-1 was treated with 0, 1.25, 2.5, and 5 mg/mL QC for 48 h, respectively. Evaluation of cell viability and observation of morphologic changes of BPH-1 cell gene expression and miRNA expression profiles were analyzed. Real-time quantitative PCR was used to confirm changes in miRNA and gene expression. GO and KEGG pathway-based approaches were used to investigate biological functions and signaling pathways affected by differentially expressed mRNAs. Results. QC inhibited BPH-1 cell proliferation. Differential expression of 19 upregulated and 2 downregulated miRNAs was observed in QC-treated BPH-1 cells compared to untreated control cells. 107 upregulated and 71 downregulated genes were identified between the two groups. Significantly enriched signaling pathways based on deregulated mRNAs were mainly involved in regulation of cell proliferation, apoptosis, and so on. Additionally, miRNA-mRNA network analysis integrated these miRNAs and genes by outlining interactions of miRNA and related genes. Conclusion. The study was the first report of differentially expressed miRNA and mRNA in QC-treated BPH-1 cells.