Login Register Cart 0
Generic placeholder image

Current Pharmaceutical Design

Editor-in-Chief

ISSN (Print): 1381-6128
ISSN (Online): 1873-4286

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

miRNAs in SARS-CoV 2: A Spoke in the Wheel of Pathogenesis

Author(s): Rohit Satyam, Tulika Bhardwaj, Sachin Goel, Niraj Kumar Jha*, Saurabh Kumar Jha, Parma Nand, Janne Ruokolainen, Mohammad Amjad Kamal and Kavindra Kumar Kesari

Volume 27, Issue 13, 2021

Published on: 01 October, 2020

Page: [1628 - 1641] Pages: 14

DOI: 10.2174/1381612826999201001200529

Price: $65

Abstract

Introduction: The rapid emergence of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-- CoV-2) has resulted in an increased mortality rate across the globe. However, the underlying mechanism of SARS-CoV-2 altering human immune response is still elusive. The existing literature on miRNA mediated pathogenesis of RNA virus viz. Dengue virus, West Nile virus, etc. raises a suspicion that miRNA encoded by SARS-CoV-2 might facilitate virus replication and regulate the host’s gene expression at the post-transcriptional level.

Methods: We investigated this possibility via computational prediction of putative miRNAs encoded by the SARS-CoV-2 genome using a novel systematic pipeline that predicts putative mature-miRNA and their targeted genes transcripts. To trace down if viral-miRNAs targeted the genes critical to the immune pathway, we assessed whether mature miRNA transcripts exhibit effective hybridization with the 3’UTR region of human gene transcripts. Conversely, we also tried to study human miRNA-mediated viral gene regulation to get insight into the miRNA mediated offense and defense mechanism of virus and its host organisms in toto.

Results: Our analysis led us to shortlist six putative miRNAs that target, majorly, genes related to cell proliferation/ differentiation/signaling, and senescence. Nonetheless, they also target immune-related genes that directly/ indirectly orchestrate immune pathways like TNF (Tumor Necrosis Factor) signaling and Chemokine signaling pathways putatively serving as the nucleus to cytokine storms.

Conclusion: Besides, these six miRNAs were found to be conserved so far across 80 complete genomes of SARS-CoV-2 (NCBI Virus, last assessed 12 April 2020) including Indian strains that are also targeted by 7 human miRNAs and can, therefore, be exploited to develop MicroRNA-Attenuated Vaccines.

Keywords: Cytokine storm, targetome, systems biology, SARS-CoV-2, functional annotation, pathway analysis.

« Previous Next »
[1]
Zhou P, Yang XL, Wang XG, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 2020; 579(7798): 270-3.
[http://dx.doi.org/10.1038/s41586-020-2012-7] [PMID: 32015507]
[2]
World Health Organization. WHO Director-General’s opening remarks at the mission briefing on COVID-19 2020. Available from: Https://Www.Who.Int/Dg/Speeches/Detail/Who-Director-General-s-Opening-Remarks-at-the-Media-Briefing-on-Covid-19---11-Marchhttps://doi.org/11
[3]
Lake MA. What we know so far: COVID-19 current clinical knowledge and research. Clin Med (Lond) 2020; 20(2): 124-7.
[http://dx.doi.org/10.7861/clinmed.2019-coron] [PMID: 32139372]
[4]
Rabi FA, Al Zoubi MS, Kasasbeh GA, Salameh DM, Al-Nasser AD. Sars-cov-2 and coronavirus disease 2019: What we know so far. Pathogens 2020; 9(3): 231.
[http://dx.doi.org/10.3390/pathogens9030231] [PMID: 32245083]
[5]
Fan HH, Wang LQ, Liu WL, et al. Repurposing of clinically approved drugs for treatment of coronavirus disease 2019 in a 2019-novel coronavirus-related coronavirus model. Chin Med J (Engl) 2020; 133(9): 1051-6.
[http://dx.doi.org/10.1097/cm9.0000000000000797] [PMID: 32149769]
[6]
Gordon DE, Jang GM, Bouhaddou M, et al. SARS-CoV-2-Human protein-protein interaction map reveals drug targets and potential drug-repurposing. bioRxiv 2020; 583: 459-68.
[http://dx.doi.org/10.1101/2020.03.22.002386] [PMID: 32511329]
[7]
Kruse RL. Therapeutic strategies in an outbreak scenario to treat the novel coronavirus originating in Wuhan, China. F1000 Res 2020; 9(72): 72.
[http://dx.doi.org/10.12688/f1000research.22211.1] [PMID: 32117569]
[8]
Zhou Y, Hou Y, Shen J, Huang Y, Martin W, Cheng F. Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2. Cell Discov 2020; 6: 14.
[http://dx.doi.org/10.1038/s41421-020-0153-3] [PMID: 32194980]
[9]
Koyama T, Platt D, Parida L. Variant analysis of SARS-CoV-2 genomes. Bull World Health Organ 2020; 98(7): 495-504.
[http://dx.doi.org/10.2471/BLT.20.253591] [PMID: 32742035]
[10]
Pang J, Wang MX, Ang IYH, et al. Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review. J Clin Med 2020; 9(3): 623.
[http://dx.doi.org/10.3390/jcm9030623] [PMID: 32110875]
[11]
Liu J, Cao R, Xu M, et al. Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro. Cell Discov 2020; 6(16): 16.
[http://dx.doi.org/10.1038/s41421-020-0156-0] [PMID: 32194981]
[12]
Singh AK, Singh A, Shaikh A, Singh R, Misra A. Chloroquine and hydroxychloroquine in the treatment of COVID-19 with or without diabetes: A systematic search and a narrative review with a special reference to India and other developing countries. Diabetes Metab Syndr 2020; 14(3): 241-6.
[http://dx.doi.org/10.1016/j.dsx.2020.03.011] [PMID: 32247211]
[13]
Rismanbaf A. Potential treatments for COVID-19; a narrative literature review. Arch Acad Emerg Med 2020; 8(1): e29.
[PMID: 32232214]
[14]
Mehta P, McAuley DF, Brown M, Sanchez E, Tattersall RS, Manson JJ. HLH Across Speciality Collaboration, UK. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet 2020; 395(10229): 1033-4.
[http://dx.doi.org/10.1016/S0140-6736(20)30628-0] [PMID: 32192578]
[15]
Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med 2020; 46(5): 846-8.
[http://dx.doi.org/10.1007/s00134-020-05991-x] [PMID: 32125452]
[16]
Zhang C, Wu Z, Li JW, Zhao H, Wang GQ. Cytokine release syndrome in severe COVID-19: interleukin-6 receptor antagonist tocilizumab may be the key to reduce mortality. Int J Antimicrob Agents 2020; 55(5): 105954.
[http://dx.doi.org/10.1016/j.ijantimicag.2020.105954] [PMID: 32234467]
[17]
O’Brien J, Hayder H, Zayed Y, Peng C. Overview of microRNA biogenesis, mechanisms of actions, and circulation. Front Endocrinol (Lausanne) 2018; 9: 402.
[http://dx.doi.org/10.3389/fendo.2018.00402] [PMID: 30123182]
[18]
Roberts APE, Lewis AP, Jopling CL. The role of microRNAs in viral infection. Prog Mol Biol Transl Sci 2011; 102: 101-39.
[http://dx.doi.org/10.1016/B978-0-12-415795-8.00002-7] [PMID: 21846570]
[19]
Sullivan CS, Ganem D. MicroRNAs and viral infection. Mol Cell 2005; 20(1): 3-7.
[http://dx.doi.org/10.1016/j.molcel.2005.09.012] [PMID: 16209940]
[20]
Grundhoff A, Sullivan CS. Virus-encoded microRNAs. Virology 2011; 411(2): 325-43.
[http://dx.doi.org/10.1016/j.virol.2011.01.002] [PMID: 21277611]
[21]
Pfeffer S, Zavolan M, Grässer FA, et al. Identification of virus-encoded microRNAs. Science 2004; 304(5671): 734-6.
[http://dx.doi.org/10.1126/science.1096781] [PMID: 15118162]
[22]
Hussain M, Asgari S. MicroRNA-like viral small RNA from Dengue virus 2 autoregulates its replication in mosquito cells. Proc Natl Acad Sci USA 2014; 111(7): 2746-51.
[http://dx.doi.org/10.1073/pnas.1320123111] [PMID: 24550303]
[23]
Ospina-Bedoya M, Campillo-Pedroza N, Franco-Salazar JP, Gallego-Gómez JC. Computational identification of dengue virus microRNA-like structures and their cellular targets. Bioinform Biol Insights 2014; 8: 169-76.
[http://dx.doi.org/10.4137/BBi.s13649] [PMID: 25210446]
[24]
Hussain M, Torres S, Schnettler E, et al. West Nile virus encodes a microRNA-like small RNA in the 3′ untranslated region which up-regulates GATA4 mRNA and facilitates virus replication in mosquito cells. Nucleic Acids Res 2012; 40(5): 2210-23.
[http://dx.doi.org/10.1093/nar/gkr848] [PMID: 22080551]
[25]
Li X, Fu Z, Liang H, et al. H5N1 influenza virus-specific miRNA-like small RNA increases cytokine production and mouse mortality via targeting poly(rC)-binding protein 2. Cell Res 2018; 28(2): 157-71.
[http://dx.doi.org/10.1038/cr.2018.3] [PMID: 29327729]
[26]
Cullen BR. Viruses and microRNAs. Nat Genet 2006; 38(Suppl.): S25-30.
[http://dx.doi.org/10.1038/ng1793] [PMID: 16736021]
[27]
Yee PTI, Poh CL. Development of novel vaccines against enterovirus-71. Viruses 2015; 8(1): 1.
[http://dx.doi.org/10.3390/v8010001] [PMID: 26729152]
[28]
Grundhoff A, Sullivan CS, Ganem D. A combined computational and microarray-based approach identifies novel microRNAs encoded by human gamma-herpesviruses. RNA 2006; 12(5): 733-50.
[http://dx.doi.org/10.1261/rna.2326106] [PMID: 16540699]
[29]
Grundhoff A. Computational prediction of viral miRNAs. Methods Mol Biol 2011; 721: 143-52.
[http://dx.doi.org/10.1007/978-1-61779-037-9_8] [PMID: 21431683]
[30]
Watanabe Y, Tomita M, Kanai A. Computational methods for microRNA target prediction. Methods Enzymol 2007; 427: 65-86.
[http://dx.doi.org/10.1016/S0076-6879(07)27004-1] [PMID: 17720479]
[31]
Tav C, Tempel S, Poligny L, Tahi F. miRNAFold: a web server for fast miRNA precursor prediction in genomes. Nucleic Acids Res 2016; 44(W1): W181-4.
[http://dx.doi.org/10.1093/nar/gkw459] [PMID: 27242364]
[32]
Liu B, Fang L, Chen J, Liu F, Wang X. miRNA-dis: microRNA precursor identification based on distance structure status pairs. Mol Biosyst 2015; 11(4): 1194-204.
[http://dx.doi.org/10.1039/c5mb00050e] [PMID: 25715848]
[33]
Tran VduT, Tempel S, Zerath B, Zehraoui F, Tahi F. miRBoost: boosting support vector machines for microRNA precursor classification. RNA 2015; 21(5): 775-85.
[http://dx.doi.org/10.1261/rna.043612.113] [PMID: 25795417]
[34]
Gruber AR, Lorenz R, Bernhart SH, Neuböck R, Hofacker IL. The Vienna RNA websuite. Nucleic Acids Res 2008; 36(Web Server issue): W70-4.
[http://dx.doi.org/10.1093/nar/gkn188] [PMID: 18424795]
[35]
Karathanasis N, Tsamardinos I, Poirazi P. MiRduplexSVM: A high-performing MiRNA-duplex prediction and evaluation methodology. PLoS One 2015; 10(5): e0126151.
[http://dx.doi.org/10.1371/journal.pone.0126151] [PMID: 25961860]
[36]
Monga I, Kumar M. Computational resources for prediction and analysis of functional miRNA and their targetome. Methods Mol Biol 2019; 1912: 215-50.
[http://dx.doi.org/10.1007/978-1-4939-8982-9_9] [PMID: 30635896]
[37]
Ab Mutalib NS, Sulaiman SA, Jamal R. Computational tools for microRNA target prediction. Computational Epigen Dis 2019; 9: 79-105.
[http://dx.doi.org/10.1016/b978-0-12-814513-5.00006-4]
[38]
Enright AJ, John B, Gaul U, Tuschl T, Sander C, Marks DS. MicroRNA targets in Drosophila. Genome Biol 2003; 5(1): R1.
[http://dx.doi.org/10.1186/gb-2003-5-1-r1] [PMID: 14709173]
[39]
Li H, Handsaker B, Wysoker A, et al. 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009; 25(16): 2078-9.
[http://dx.doi.org/10.1093/bioinformatics/btp352] [PMID: 19505943]
[40]
Marín RM, Vanícek J. Efficient use of accessibility in microRNA target prediction. Nucleic Acids Res 2011; 39(1): 19-29.
[http://dx.doi.org/10.1093/nar/gkq768] [PMID: 20805242]
[41]
Kozomara A, Birgaoanu M, Griffiths-Jones S. miRBase: from microRNA sequences to function. Nucleic Acids Res 2019; 47(D1): D155-62.
[http://dx.doi.org/10.1093/nar/gky1141] [PMID: 30423142]
[42]
Biesiada M, Pachulska-Wieczorek K, Adamiak RW, Purzycka KJ. RNAComposer and RNA 3D structure prediction for nanotechnology. Methods 2016; 103: 120-7.
[http://dx.doi.org/10.1016/j.ymeth.2016.03.010] [PMID: 27016145]
[43]
Oliveros JC. VENNY. An interactive tool for comparing lists with Venn Diagrams 2007. Available from: http://bioinfogp.cnb.csic.es/tools/venny/index.html
[44]
Mudunuri U, Che A, Yi M, Stephens RM. bioDBnet: the biological database network. Bioinformatics 2009; 25(4): 555-6.
[http://dx.doi.org/10.1093/bioinformatics/btn654] [PMID: 19129209]
[45]
Mi H, Huang X, Muruganujan A, et al. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res 2017; 45(D1): D183-9.
[http://dx.doi.org/10.1093/nar/gkw1138] [PMID: 27899595]
[46]
Hulsegge I, Kommadath A, Smits MA. Globaltest and GOEAST: two different approaches for Gene Ontology analysis. BMC Proc 2009; 3(10)(Suppl. 4): S10.
[http://dx.doi.org/10.1186/1753-6561-3-s4-s10] [PMID: 19615110]
[47]
Liao Y, Wang J, Jaehnig EJ, Shi Z, Zhang B. WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. Nucleic Acids Res 2019; 47(W1): W199-205.
[http://dx.doi.org/10.1093/nar/gkz401] [PMID: 31114916]
[48]
Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019; 47(D1): D607-13.
[http://dx.doi.org/10.1093/nar/gky1131] [PMID: 30476243]
[49]
Zhou G, Soufan O, Ewald J, Hancock REW, Basu N, Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res 2019; 47(W1): W234-41.
[http://dx.doi.org/10.1093/nar/gkz240] [PMID: 30931480]
[50]
Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 2010; 26(6): 841-2.
[http://dx.doi.org/10.1093/bioinformatics/btq033] [PMID: 20110278]
[51]
Huang Y, Niu B, Gao Y, Fu L, Li W. CD-HIT Suite: a web server for clustering and comparing biological sequences. Bioinformatics 2010; 26(5): 680-2.
[http://dx.doi.org/10.1093/bioinformatics/btq003] [PMID: 20053844]
[52]
He Y, Yang K, Zhang X. Viral microRNAs targeting virus genes promote virus infection in shrimp in vivo. J Virol 2014; 88(2): 1104-12.
[http://dx.doi.org/10.1128/jvi.02455-13] [PMID: 24198431]
[53]
Skalsky RL, Cullen BR. Viruses, microRNAs, and host interactions. Annu Rev Microbiol 2010; 64: 123-41.
[http://dx.doi.org/10.1146/annurev.micro.112408.134243] [PMID: 20477536]
[54]
Watanabe Y, Kishi A, Yachie N, Kanai A, Tomita M. Computational analysis of microRNA-mediated antiviral defense in humans. FEBS Lett 2007; 581(24): 4603-10.
[http://dx.doi.org/10.1016/j.febslet.2007.08.049] [PMID: 17825824]
[55]
Fay EJ, Langlois RA. MicroRNA-Attenuated virus vaccines. Noncoding RNA 2018; 4(4): 25.
[http://dx.doi.org/10.3390/ncrna4040025] [PMID: 30279330]
[56]
Perez JT, Pham AM, Lorini MH, Chua MA, Steel J, tenOever BR. MicroRNA-mediated species-specific attenuation of influenza A virus. Nat Biotechnol 2009; 27(6): 572-6.
[http://dx.doi.org/10.1038/nbt.1542] [PMID: 19483680]
[57]
Veksler-Lublinsky I, Shemer-Avni Y, Kedem K, Ziv-Ukelson M. Gene bi-targeting by viral and human miRNAs. BMC Bioinformatics 2010; 11: 249.
[http://dx.doi.org/10.1186/1471-2105-11-249] [PMID: 20465802]
[58]
Chen Y, Wang X. miRDB: an online database for prediction of functional microRNA targets. Nucleic Acids Res 2020; 48(D1): D127-31.
[http://dx.doi.org/10.1093/nar/gkz757] [PMID: 31504780]
[59]
Canna SW, Behrens EM. Making sense of the cytokine storm: a conceptual framework for understanding, diagnosing, and treating hemophagocytic syndromes. Pediatr Clin North Am 2012; 59(2): 329-44.
[http://dx.doi.org/10.1016/j.pcl.2012.03.002] [PMID: 22560573]
[60]
Borish L. Anti-cytokine therapy. Asthma Prevention 2005; 9913(20): 483-504.
[http://dx.doi.org/10.1007/0-306-47664-9_41]
[61]
Xu K, Cai H, Shen Y, et al. Management of coronavirus disease-19 (COVID-19): the Zhejiang experience. Zhejiang Da Xue Xue Bao. Yi Xue Ban = Journal of Zhejiang University. Med Sci 2020; 49(1): 1-10.
[62]
Hamilton JA. Colony-stimulating factors in inflammation and autoimmunity. Nat Rev Immunol 2008; 8(7): 533-44.
[http://dx.doi.org/10.1038/nri2356] [PMID: 18551128]
[63]
Tisoncik JR, Korth MJ, Simmons CP, Farrar J, Martin TR, Katze MG. Into the eye of the cytokine storm. Microbiol Mol Biol Rev 2012; 76(1): 16-32.
[http://dx.doi.org/10.1128/mmbr.05015-11] [PMID: 22390970]
[64]
Lo U, Selvaraj V, Plane JM, Chechneva OV, Otsu K, Deng W. p38α (MAPK14) critically regulates the immunological response and the production of specific cytokines and chemokines in astrocytes. Sci Rep 2014; 4: 7405.
[http://dx.doi.org/10.1038/srep07405] [PMID: 25502009]
[65]
Phan T. Genetic diversity and evolution of SARS-CoV-2. Infect Genet Evol 2020; 81: 104260.
[http://dx.doi.org/10.1016/j.meegid.2020.104260] [PMID: 32092483]
[66]
Tang X, Wu C, Li X, et al. On the origin and continuing evolution of SARS-CoV-2. Natl Sci Rev 2020; 7(6): 1012-23.
[http://dx.doi.org/10.1093/nsr/nwaa036]
[67]
Wrapp D, Wang N, Corbett KS, et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 2020; 367(6483): 1260-3.
[http://dx.doi.org/10.1126/science.aax0902] [PMID: 32075877]
[68]
Chen X, Zhou L, Peng N, et al. MicroRNA-302a suppresses influenza A virus-stimulated interferon regulatory factor-5 expression and cytokine storm induction. J Biol Chem 2017; 292(52): 21291-303.
[http://dx.doi.org/10.1074/jbc.M117.805937] [PMID: 29046356]
[69]
Muema DM, Akilimali NA, Ndumnego OC, et al. Association between the cytokine storm, immune cell dynamics, and viral replicative capacity in hyperacute HIV infection. BMC Med 2020; 18(1): 81.
[http://dx.doi.org/10.1186/s12916-020-01529-6] [PMID: 32209092]
[70]
Scaria V, Hariharan M, Maiti S, Pillai B, Brahmachari SK. Host-virus interaction: A new role for microRNAs. Retrovirology 2006; 3: 68.
[71]
Teng Y, Wang Y, Zhang X, et al. Systematic Genome-wide Screening and Prediction of microRNAs in EBOV During the 2014 Ebolavirus Outbreak. Sci Rep 2015; 5: 9912.
[http://dx.doi.org/10.1038/srep09912] [PMID: 26011078]

Rights & Permissions Print Cite
Article Metrics
81
2
World Health Day
© 2024 Bentham Science Publishers | Privacy Policy