miRCOVID-19: Potential Targets of Human miRNAs in SARS-CoV-2 for RNA-Based Drug Discovery.
TL;DR: In this article, the authors presented miRCOVID-19, a computational meta-analysis framework identifying the predicted binding sites of human microRNAs along the SARS-CoV-2 RNA genome.
Abstract: Sense-antisense interactions of long and short RNAs in human cells are integral to post-transcriptional gene regulation, in particular that of mRNAs by microRNAs. Many viruses, including severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 (the causative agent of coronavirus disease 2019, COVID-19), have RNA genomes, and interactions between host and viral RNAs, while known to be functional in other viral diseases, have not yet been investigated in COVID-19. To remedy this gap in knowledge, we present miRCOVID-19, a computational meta-analysis framework identifying the predicted binding sites of human microRNAs along the SARS-CoV-2 RNA genome. To highlight the potential relevance of SARS-CoV-2-genome-complementary miRNAs to COVID-19 pathogenesis, we assessed their expression in COVID-19-relevant tissues using public transcriptome data. miRCOVID-19 identified 14 high-confidence mature miRNAs that are highly likely to interact with the SARS-CoV-2 genome and are expressed in diverse respiratory epithelial and immune cell types that are relevant to COVID-19 pathogenesis. As a proof of principle, we have shown that human miR-122, a previously known co-factor of another RNA virus, the hepatitis C virus (HCV) whose genome it binds as a prerequisite for pathogenesis, was predicted to also bind the SARS-CoV-2 RNA genome with high affinity, suggesting the perspective of repurposing anti-HCV RNA-based drugs, such as Miravirsen, to treat COVID-19. Our study is the first to identify all high-confidence binding sites of human miRNAs in the SARS-CoV-2 genome using multiple tools. Our work directly facilitates experimental validation of the reported targets, which would accelerate RNA-based drug discovery for COVID-19 and has the potential to provide new avenues for treating symptomatic COVID-19, and block SARS-CoV-2 replication, in humans.
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TL;DR: In this paper, the authors present the recent discoveries regarding the clinical relevance and biological roles of miRNAs in coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2.
36 citations
TL;DR: In this article , the authors present the recent discoveries regarding the clinical relevance and biological roles of miRNAs in coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2.
36 citations
TL;DR: In this article, the authors provided a summary of the current clinical application of miRNAs for the treatments of patients with COVID-19, and showed that host miRNs play an antiviral role and improve the treatment of patients.
35 citations
TL;DR: In this paper, the authors evaluated the expression of up/downregulated inflammatory miRNAs and their mRNA targets in the serum samples of COVID-19 patients with different grades and during hospitalization from several health centers of Yazd, Tehran, and Zahedan province of Iran from December 20 to March 2, 2021.
Abstract: The aim of this study was to evaluate the expression of four up/down-regulated inflammatory miRNAs and their mRNA targets in the serum samples of COVID-19 patients with different grades. Also, we investigated the relative expression of these miRNAs and mRNAs during hospitalization. In this cross-sectional study, 5 mL of blood sample were taken from COVID-19 patients with different grades and during hospitalization from several health centers of Yazd, Tehran, and Zahedan province of Iran from December 20, 2020 to March 2, 2021. The relative expression of miRNAs and mRNAs was evaluated by q-PCR. We found that the relative expression of hsa-miR-31-3p, hsa-miR-29a-3p, and hsa-miR-126-3p was significantly decreased and the relative expression of their mRNA targets (ZMYM5, COL5A3, and CAMSAP1) was significantly increased with the increase of disease grade. Conversely, the relative expression of hsa-miR-17-3p was significantly increased and its mRNA target (DICER1) was significantly decreased with the increase of disease grade. This pattern was exactly seen during hospitalization of COVID-19 patients who did not respond to treatment. In COVID-19 patients who responded to treatment, the expression of selected miRNAs and their mRNA targets returned to the normal level. A negative significant correlation was seen between (1) the expression of hsa-miR-31-3p and ZMYM5, (2) hsa-miR-29a-3p and COL5A3, (3) hsa-miR-126-3p and CAMSAP1, and (4) hsa-miR-17-3p and DICER1 in COVID-19 patients with any grade (P < 0.05) and during hospitalization. In this study, we gained a more accurate understanding of the expression of up/down-regulated inflammatory miRNAs in the blood of COVID-19 patients. The obtained data may help us in the diagnosis and prognosis of COVID-19. Trial registration: The ethics committee of Zahedan University of Medical Sciences, Zahedan, Iran. (Ethical Code: IR.ZAUMS.REC.1399.316) was registered for this project.
22 citations
TL;DR: Comparison of differential plasma miRNAs and cytokines profiles between COVID-19 and other community-acquired pneumonias (CAP) provides new insights into the etiopathological mechanisms underlying CO VID-19.
Abstract: Coronavirus Disease 2019 (COVID-19) pneumonia is a life-threatening infectious disease, especially for elderly patients with multiple comorbidities. Despite enormous efforts to understand its underlying etiopathogenic mechanisms, most of them remain elusive. In this study, we compared differential plasma miRNAs and cytokines profiles between COVID-19 and other community-acquired pneumonias (CAP). A first screening and subsequent validation assays in an independent cohort of patients revealed a signature of 15 dysregulated miRNAs between COVID-19 and CAP patients. Additionally, multivariate analysis displayed a combination of 4 miRNAs (miR-106b-5p, miR-221-3p, miR-25-3p and miR-30a-5p) that significantly discriminated between both pathologies. Search for targets of these miRNAs, combined with plasma protein measurements, identified a differential cytokine signature between COVID-19 and CAP that included EGFR, CXCL12 and IL-10. Significant differences were also detected in plasma levels of CXCL12, IL-17, TIMP-2 and IL-21R between mild and severe COVID-19 patients. These findings provide new insights into the etiopathological mechanisms underlying COVID-19.
18 citations
References
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TL;DR: A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score.
88,255 citations
TL;DR: A new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format, which allows the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks.
Abstract: Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing webbased methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools
18,858 citations
TL;DR: An update of the miRBase database is described, including the collation and use of deep sequencing data sets to assign levels of confidence to miR base entries, and a high confidence subset of miR Base entries are provided, based on the pattern of mapped reads.
Abstract: We describe an update of the miRBase database (http://www.mirbase.org/), the primary microRNA sequence repository. The latest miRBase release (v20, June 2013) contains 24 521 microRNA loci from 206 species, processed to produce 30 424 mature microRNA products. The rate of deposition of novel microRNAs and the number of researchers involved in their discovery continue to increase, driven largely by small RNA deep sequencing experiments. In the face of these increases, and a range of microRNA annotation methods and criteria, maintaining the quality of the microRNA sequence data set is a significant challenge. Here, we describe recent developments of the miRBase database to address this issue. In particular, we describe the collation and use of deep sequencing data sets to assign levels of confidence to miRBase entries. We now provide a high confidence subset of miRBase entries, based on the pattern of mapped reads. The high confidence microRNA data set is available alongside the complete microRNA collection at http://www.mirbase.org/. We also describe embedding microRNA-specific Wikipedia pages on the miRBase website to encourage the microRNA community to contribute and share textual and functional information.
4,705 citations
TL;DR: This work has mapped reads from short RNA deep-sequencing experiments to microRNAs in miRBase and developed web interfaces to view these mappings, which can be used as a proxy for relative expression levels of microRNA sequences, provide detailed evidence for microRNA annotations and alternative isoforms of mature micro RNAs, and allow us to revisit previous annotations.
Abstract: miRBase is the primary online repository for all microRNA sequences and annotation. The current release (miRBase 16) contains over 15,000 microRNA gene loci in over 140 species, and over 17,000 distinct mature microRNA sequences. Deep-sequencing technologies have delivered a sharp rise in the rate of novel microRNA discovery. We have mapped reads from short RNA deep-sequencing experiments to microRNAs in miRBase and developed web interfaces to view these mappings. The user can view all read data associated with a given microRNA annotation, filter reads by experiment and count, and search for microRNAs by tissue- and stage-specific expression. These data can be used as a proxy for relative expression levels of microRNA sequences, provide detailed evidence for microRNA annotations and alternative isoforms of mature microRNAs, and allow us to revisit previous annotations. miRBase is available online at: http://www.mirbase.org/.
3,618 citations
TL;DR: Using HLA class I and II predicted peptide ‘megapools’, circulating SARS-CoV-2−specific CD8+ and CD4+ T cells were identified in ∼70% and 100% of COVID-19 convalescent patients, respectively, suggesting cross-reactive T cell recognition between circulating ‘common cold’ coronaviruses and SARS.
3,043 citations