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Competing endogenous RNA network profiling reveals novel host dependency factors required for MERS-CoV propagation.

ABSTRACT: Circular RNAs (circRNAs) are an integral component of the host competitive endogenous RNA (ceRNA) network. These noncoding RNAs are characterized by their unique splicing reactions to form covalently closed loop structures and play important RNA regulatory roles in cells. Recent studies showed that circRNA expressions were perturbed in viral infections and circRNAs might serve as potential antiviral targets. We investigated the host ceRNA network changes and biological relevance of circRNAs in human lung adenocarcinoma epithelial (Calu-3) cells infected with the highly pathogenic Middle East respiratory syndrome coronavirus (MERS-CoV). A total of ≥49337 putative circRNAs were predicted. Among the 7845 genes which generated putative circRNAs, 147 (1.9%) of them each generated ≥30 putative circRNAs and were involved in various biological, cellular, and metabolic processes, including viral infections. Differential expression (DE) analysis showed that the proportion of DE circRNAs significantly (P < 0.001) increased at 24 h-post infection. These DE circRNAs were clustered into 4 groups according to their time-course expression patterns and demonstrated inter-cluster and intra-cluster variations in the predicted functions of their host genes. Our comprehensive circRNA-miRNA-mRNA network identified 7 key DE circRNAs involved in various biological processes upon MERS-CoV infection. Specific siRNA knockdown of two selected DE circRNAs (circFNDC3B and circCNOT1) significantly reduced MERS-CoV load and their target mRNA expression which modulates various biological pathways, including the mitogen-activated protein kinase (MAPK) and ubiquitination pathways. These results provided novel insights into the ceRNA network perturbations, biological relevance of circRNAs, and potential host-targeting antiviral strategies for MERS-CoV infection.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7170352 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a new member of the Betacoronaviridae family, responsible for the recent pandemic outbreak of COVID-19. To start exploring the molecular events that follow host cell infection, we queried VirusCircBase and identified a circular RNA (circRNA) predicted to be synthesized by SARS-CoV-2, circ_3205, which we used to probe: (i) a training cohort comprised of two pools of cells from three nasopharyngeal swabs of SARS-CoV-2 infected (positive) or uninfected (negative, UCs) individuals; (ii) a validation cohort made up of 12 positive and 3 negative samples. The expression of circRNAs, miRNAs and miRNA targets was assayed through real-time PCR. CircRNA-miRNA interactions were predicted by TarpMiR, Analysis of Common Targets for circular RNAs (ACT), and STarMir tools. Enrichment of the biological processes and the list of predicted miRNA targets were retrieved from DIANA miRPath v3.0. Our results showed that the predicted SARS-CoV-2 circ_3205 was expressed only in positive samples and its amount positively correlated with that of SARS-CoV-2 Spike (S) mRNA and the viral load (r values = 0.80952 and 0.84867, Spearman's correlation test, respectively). Human (hsa) miR-298 was predicted to interact with circ_3205 by all three predictive tools. KCNMB4 and PRKCE were predicted as hsa-miR-298 targets. Interestingly, the function of both is correlated with blood coagulation and immune response. KCNMB4 and PRKCE mRNAs were upregulated in positive samples as compared to UCs (6 and 8.1-fold, p values = 0.049 and 0.02, Student's t test, respectively) and their expression positively correlated with that of circ_3205 (r values = 0.6 and 0.25, Spearman's correlation test, respectively). We propose that our results convincingly suggest that circ_3205 is a circRNA synthesized by SARS-CoV-2 upon host cell infection and that it may behave as a competitive endogenous RNA (ceRNA), sponging hsa-miR-298 and contributing to the upregulation of KCNMB4 and PRKCE mRNAs.

Project description:The present study aimed to screen all types of RNAs involved in the development of papillary thyroid carcinoma (PTC). RNA?sequencing data of PTC and normal samples were used for screening differentially expressed (DE) microRNAs (DE?miRNAs), long non?coding RNAs (DE?lncRNAs) and genes (DEGs). Subsequently, lncRNA?miRNA, miRNA?gene (that is, miRNA?mRNA) and gene?gene interaction pairs were extracted and used to construct regulatory networks. Feature genes in the miRNA?mRNA network were identified by topological analysis and recursive feature elimination analysis. A support vector machine (SVM) classifier was built using 15 feature genes, and its classification effect was validated using two microarray data sets that were downloaded from the Gene Expression Omnibus (GEO) database. In addition, Gene Ontology function and Kyoto Encyclopedia Genes and Genomes pathway enrichment analyses were conducted for genes identified in the ceRNA network. A total of 506 samples, including 447 tumor samples and 59 normal samples, were obtained from The Cancer Genome Atlas (TCGA); 16 DE?lncRNAs, 917 DEGs and 30 DE?miRNAs were screened. The miRNA?mRNA regulatory network comprised 353 nodes and 577 interactions. From these data, 15 feature genes with high predictive precision (>95%) were extracted from the network and were used to form an SVM classifier with an accuracy of 96.05% (486/506) for PTC samples downloaded from TCGA, and accuracies of 96.81 and 98.46% for GEO downloaded data sets. The ceRNA regulatory network comprised 596 lines (or interactions) and 365 nodes. Genes in the ceRNA network were significantly enriched in 'neuron development', 'differentiation', 'neuroactive ligand?receptor interaction', 'metabolism of xenobiotics by cytochrome P450', 'drug metabolism' and 'cytokine?cytokine receptor interaction' pathways. Hox transcript antisense RNA, miRNA?206 and kallikrein?related peptidase 10 were nodes in the ceRNA regulatory network of the selected feature gene, and they may serve import roles in the development of PTC.

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Competing endogenous RNA network profiling reveals novel host dependency factors required for MERS-CoV propagation.

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