Long non-coding RNA GAS5 inhibited hepatitis C virus replication by binding viral NS3 protein

RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence

RNA-protein interactions (RPIs) have critical roles in numerous fundamental biological processes, such as post-transcriptional gene regulation, viral assembly, cellular defence and protein synthesis. As the number of available RNA-protein binding experimental data has increased rapidly due to high-throughput sequencing methods, it is now possible to measure and understand RNA-protein interactions by computational methods. In this study, we integrate a sequence-based derived kernel with regularized least squares to perform prediction. The derived kernel exploits the contextual information around an amino acid or a nucleic acid as well as the repetitive conserved motif information. We propose a novel machine learning method, called RPiRLS to predict the interaction between any RNA and protein of known sequences. For the RPiRLS classifier, each protein sequence comprises up to 20 diverse amino acids but for the RPiRLS-7G classifier, each protein sequence is represented by using 7-letter reduced alphabets based on their physiochemical properties. We evaluated both methods on a number of benchmark data sets and compared their performances with two newly developed and state-of-the-art methods, RPI-Pred and IPMiner. On the non-redundant benchmark test sets extracted from the PRIDB, the RPiRLS method outperformed RPI-Pred and IPMiner in terms of accuracy, specificity and sensitivity. Further, RPiRLS achieved an accuracy of 92% on the prediction of lncRNA-protein interactions. The proposed method can also be extended to construct RNA-protein interaction networks. The RPiRLS web server is freely available at http://bmc.med.stu.edu.cn/RPiRLS.

Analyses of long non-coding RNAs and mRNA profiling through RNA sequencing of MDBK cells at different stages of bovine viral diarrhea virus infection

BACKGROUND

Bovine viral diarrhea virus (BVDV) infection is a dynamic and complex process that leads to significant economic losses in the dairy and cattle industries. However, our understanding of the protective and pathological mechanism underlying host infection is limited.

METHODS

To determine whether BVDV regulates specific activities of the host cell, the expression of long non-coding RNA (lncRNA) during BVDV NADL infection was studied by deep sequencing.

RESULTS

A total of 1236 lncRNA transcripts and 3261 mRNA transcripts were differentially regulated at 2h, 6h, and 18h post-infection. The lncRNAs shared same characteristics with other mammals in terms of exon length, number, expression level, and conservation. The Gene Ontology (GO) enrichment and KEGG pathway analyses showed that lncRNAs regulate immune reaction during BVDV infection. Thirteen differentially expressed genes in 18 hpi were selected and independently validated by reverse-transcription qPCR.

CONCLUSIONS

The present study is the first to provide insights into the biological connection of lncRNAs and BVDV, which can be further explored for the development of antiviral prevention strategies and in understanding persistent infection between viral and host components.

TINCR expression is associated with unfavorable prognosis in patients with hepatocellular carcinoma

Emerging evidence are accumulating that long noncoding RNAs (lncRNAs) have recently been identified to participate in various cellular processes. Terminal differentiation induced ncRNA (TINCR) is a newly identified lncRNA with its functional roles not fully elucidated in human malignancy. The current study aims to identify the clinical significance of TINCR in prognosis and malignant progression of hepatocellular carcinoma (HCC). TINCR expression in HCC specimens at various stages of tumorigenesis were measured by quantitative real-time RT PCR (qRT-PCR). The matched para-carcinoma tissues were used as controls. The associations of TINCR with clinicopathological characteristics, disease-free survival (DFS) and overall survival (OS) of patients were further evaluated. Results revealed that high TINCR expression was significantly correlated with tumor size (P=0.005), tumor differentiation status (P=0.017), TNM stage (P=0.010), and vascular invasion (P=0.004). Moreover, Kaplan-Meier analysis demonstrated that TINCR was correlated to both DFS and OS in HCC cohorts. Patients with high TINCR expression tended to have worse prognosis. Multivariate Cox regression analysis indicated that TINCR was an independent poor prognostic indicator for DFS (HR =1.32, 95% CI: 1.00-1.57, P=0.000) and OS (HR =1.57, 95% CI: 1.30-1.86, P=0.004) in HCC. TINCR was demonstrated as a direct target of miR-137 and miR-133a, and was suppressed by miR-137/miR-133a These results provide the first evidence that the expression of TINCR in HCC may play an oncogenic role in HCC differentiation, invasion, and metastasis. miR-137/miR-133a-TINCR pathway may serve as a promising target for tumor recurrence and prognosis of patients with HCC.

Roles of LncRNAs in Viral Infections

Many proteins and signaling pathways participate in anti-viral host responses. Long non-coding RNAs (lncRNAs), a subset of non-coding RNAs greater than 200 nucleotides in length, have been recently described as critical regulators in viral infections. Accumulating research indicates that lncRNAs are important in the development and progression of infectious diseases. LncRNAs are not only involved in anti-viral responses, but in many different virus-host interactions, some of which may be beneficial to the virus. Here we review the current knowledge regarding host and viral lncRNAs and their roles in viral infections. In addition, the potential of using lncRNAs as diagnostic biomarkers is discussed.

Exosomal MicroRNAs Derived From Umbilical Mesenchymal Stem Cells Inhibit Hepatitis C Virus Infection

: Hepatitis C virus (HCV) is a significant global public health problem, causing more than 350,000 deaths every year. Although the development of direct-acting antivirals has improved the sustained virological response rate in HCV patients, novel anti-HCV agents with higher efficacy as well as better tolerance and cheaper production costs are still urgently needed. Cell-based therapy, especially its unique and strong paracrine ability to transfer information to other cells via extracellular vesicles such as exosomes, has become one of the most popular therapeutic methods in recent years. In our study, exosomes secreted from umbilical mesenchymal stem cells (uMSCs), which are widely used in regenerative medicine, inhibited HCV infection in vitro, especially viral replication, with low cell toxicity. Our analysis revealed that microRNAs (miRNAs) from uMSC-derived exosomes (uMSC-Exo) had their unique expression profiles, and these functional miRNAs, mainly represented by let-7f, miR-145, miR-199a, and miR-221 released from uMSC-Exo, largely contributed to the suppression of HCV RNA replication. These four miRNAs possessed binding sites in HCV RNA as demonstrated by the target prediction algorithm. In addition, uMSC-Exo therapy showed synergistic effect when combined with U.S. Food and Drug Administration-approved interferon-α or telaprevir, enhancing their anti-HCV ability and thus improving the clinical significance of these regenerative substances for future application as optimal adjuvants of anti-HCV therapy.

SIGNIFICANCE

This work reported, for the first time, the identification of stem cell-derived exosomes of antiviral activity. Umbilical mesenchymal stem cell-secreted exosomes inhibited hepatitis C virus infection through transporting a mixture of microRNAs complementing the viral genomes to the host cells. This finding provides insights and prospects for physiologically secreted substances for antiviral therapy.