| Literature DB >> 33675361 |
Song Zhang1, Kuerbannisha Amahong2, Xiuna Sun2, Xichen Lian2, Jin Liu2, Huaicheng Sun2, Yan Lou3, Feng Zhu2, Yunqing Qiu4.
Abstract
Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a severe and rapidly evolving epidemic. Now, although a few drugs and vaccines have been proved for its treatment and prevention, little systematic comments are made to explain its susceptibility to humans. A few scattered studies used bioinformatics methods to explore the role of microRNA (miRNA) in COVID-19 infection. Combining these timely reports and previous studies about virus and miRNA, we comb through the available clues and seemingly make the perspective reasonable that the COVID-19 cleverly exploits the interplay between the small miRNA and other biomolecules to avoid being effectively recognized and attacked from host immune protection as well to deactivate functional genes that are crucial for immune system. In detail, SARS-CoV-2 can be regarded as a sponge to adsorb host immune-related miRNA, which forces host fall into dysfunction status of immune system. Besides, SARS-CoV-2 encodes its own miRNAs, which can enter host cell and are not perceived by the host's immune system, subsequently targeting host function genes to cause illnesses. Therefore, this article presents a reasonable viewpoint that the miRNA-based interplays between the host and SARS-CoV-2 may be the primary cause that SARS-CoV-2 accesses and attacks the host cells.Entities:
Keywords: COVID-19; immune system; miRNA; virus
Mesh:
Substances:
Year: 2021 PMID: 33675361 PMCID: PMC7989616 DOI: 10.1093/bib/bbab062
Source DB: PubMed Journal: Brief Bioinform ISSN: 1467-5463 Impact factor: 11.622
miRNA knockout during virus infection in mice
| miRNA | Virus | Phenotypes | Reference |
|---|---|---|---|
| miR-155 | WNV | Increased morbidity and mortality after infection with a lethal strain. 100% mortality after infection with a non-lethal strain; Sharp reduction of interleukin (IL)-1β, IL-12, IL-6, IL-15 and GM-CSF abundance during WNV infection | [ |
| HSV-1 | Enhanced resistance to herpetic stromal keratitis; Remarkable reduction of T helper cells type 1 and 17 in number in the ocular lesions and the lymphoid organs during HSV-1 infection; Decreased stromal keratitis lesion severity | [ | |
| HSV-1 | Increased susceptibility to ocular infection with HSV-1; Higher mortality after infection with HSV-1 | [ | |
| NV | No obvious phenotype | [ | |
| JHMV | Increased morbidity and mortality during JHMV infection; Loss of the ability of T cell responses during JHMV infection | [ | |
| MHV-68 | Reduced efficient MHV-68 reactivation | [ | |
| Flu | Faster recovery capability from influenza infection; Low level of inflammation and endoplasmic reticulum stress in lung during influenza infection | [ | |
| CVB3 | Decreased mortality and alleviative viral myocarditis; Reduced abundance of IFN-γ and increased expression IL-4 and IL-13 in heart; Decreased inflammation and CD45(+) leukocytes in heart | [ | |
| miR-17-92 | LMCV | Impaired humoral response during LMCV infection; Reduced virus-specific TFH and Th1 cells during LMCV infection | [ |
| miR-150 | LMCV | Enhanced recall response in memory CD8+ T cells; Accelerated differentiation of memory cells | [ |
| miR-21-5p | HCV | Reduced steatosis during HCV infection | [ |
| miR-22 | LMCV | Maintained platelet in number during LMCV infection; Sharply decreased red blood cells and hemoglobin | [ |
| miR-34a | HIV | Enhanced resistance to HIV; Reduced antiretroviral agents and HIV-Tat protein-induced senescence during HIV infection | [ |
WNV, West Nile virus; HSV-1, Herpes simplex virus 1; NV, norovirus; JHMV, neurotropic JHM strain of mouse hepatitis virus; MHV-68, murine gammaherpesvirus; Flu, influenza; LMCV, lymphocytic choriomeningitis virus.
miRNAs regulate the clinical targets of SARS-CoV-2 in TTD
| Target | miRNA | Description | Reference |
|---|---|---|---|
| DHODH | miR-502 | MiR-502 directly regulates DHODH through binding to the position 245 to 251 in 3′-UTR of its mRNA in colon cancer cells. | [ |
| VCP | miR-129-5p | MiR-129-5p downregulates the expression of VCP by binding to two sites located at its 3′-UTR in hepatocellular carcinoma cells. | [ |
| AGTR1 | miR-410 | MiR-410 suppresses the expression level of AGTR1 by two binding sites in the 3′-UTR of AGTR1 mRNA in pancreatic cancer. | [ |
| TMEM97 | miR-152-3p | MiR-152-3p downregulates TMEM97 through interacting with 3′-UTR of TMEM97 mRNA in prostate cancer. | [ |
| OPRS1 | miR-297 | MiR-297 regulates Sig-1R expression via directly targeting its 3′-UTR during cardiomyocyte hypertrophy. | [ |
| MRC1 | miR-27a-3p | MiR-27a can mediate the process of phagocytosis by regulating CD206 expression on monocytes. | [ |
| mTOR | miR-99a | MiR-99 inhibits the expression of mTOR by targeting its 3′-UTR in a post-transcriptional manner in esophageal squamous cell carcinoma. | [ |
| JAK-2 | miR-124 | MiR-124 reduces the expression of JAK2 via binding to its UTR in non-small-cell lung carcinoma cells. | [ |
| IMPDH2 | miR-34a-5p | MiR-34a can target and downregulate IMPDH2 by binding to its exon 7 of IMPDH2. | [ |
| IMPDH1 | miR-19a-3p | MiR-19a could reduce gene expression of IMPDH1 through targeting its 3′-UTR in breast cancer. | [ |
| CSK2 | miR-1228-3p | MiR-1228* can target 3′-UTR of CK2A2 and inhibit its expression in gastric cancer. | [ |
| BRD2 | miR-143-3p | MiR-143-3p directly targets BRD2 by binding to its 3′-UTR in gastric cancer. | [ |
| BAR | miR-19a-3p | MiR-19a suppresses ADRB1 expression by directly interacting with its 3′-UTR. | [ |
| JAK-1 | miR-299-3p | MiR-299-3p targets 3′-UTR of JAK1 mRNA and inhibits its expression. | [ |
| IL6R | miR-451a | MiR-451can negatively regulate IL6R by interacting with 3′-UTR in IL6R mRNA in umbilical vein endothelial cells. | [ |
| IL1R1 | miR-21 | MiR-21 negatively regulates the IL1R1 at the level of translation through binding to 3′-UTR of L1R1. | [ |
| IL6 | miR-665 | MiR-665 interacts and downregulates IL6 by targeting its 3′-UTR in adipose-derived stem cells. | [ |
| GAK | miR-206 | MiR-206 downregulates GAK via target 3′-UTR of its mRNA in renal cell cancer. | [ |
| VEGF | miR-125 | MiR-125 inhibits the expression of VEGF through interacting with 3′-UTR of VEGF mRNA in the colorectal cancer cells. | [ |
| IFNG | miR-16-5p | MiR-15b regulates IFNG through binding to the sites at IFNG’s 3′-UTR in natural killer cells. | [ |
| TLR6 | miR-494-3p | MiR-494-3p remarkably downregulates the level of TLR6 through targeting its 3′-UTR. | [ |
| TLR2 | miR-344b-1-3p | MiR-344b-1-3p targets and downregulates TLR2 by interaction with the site of TLR2 3′-UTR. | [ |
| PIK3CG | miR-1976 | MiR-1976 interacts with PIK3CG and reduces PIK3CG expression through binding the site at PIK3CG 3′-UTR in triple-negative breast cancer. | [ |
| PIK3CD | miR-30a | MiR-30a downregulates the expression of PIK3CD via directly binding to the 3′-UTR of PIK3CD mRNA in colorectal carcinoma. | [ |
| IL8 | miR-203 | MiR-203 can directly target 3′-UTR of IL8 and reduce the expression of IL8 in nasopharyngeal carcinoma. | [ |
| CCR5 | miR-455-5p | MiR-455-5p negatively regulates CCR5 by binding to the 3′-UTR of CCR5 mRNA in the prostate cancer cells. | [ |
| CAPN2/CAPNS1 | miR-223 | MiR-223 targets CAPN2 by binding to the 3′-UTR of CAPN2. | [ |
| CAPN1/CAPNS1 | miR-124-3p | MiR-124-3p inhibits the expression of CAPN1 in the human neural cell line. | [ |
| BTK | miR-346 | Mir-346 inhibits BKT by targeting binding to its 3′-UTR. | [ |
| ACE2 | Let-7b | Let-7b downregulates ACE2 through directly targeting the coding sequence of ACE2. | [ |
| ANG-2 | miR-125b-5p | MiR-125b reduces the expression level of ANGP2 through binding to the 3′-UTR of Angpt2 mRNA. | [ |
| TLR3 | miR-146a | MiR-146a negatively regulates TLR3 via binding to its 3′-UTR during coxsackievirus B infection. | [ |
| BSG | miR-22-3p | MiR-22 represses the level of BASI through directly targeting its 3′-UTR in breast cancer. | [ |
| TNF | miR-17-5p | MiR-17 can decrease TNFA expression via binding to TNFA 3′-UTR in the leukemia cells. | [ |
| RIPK1 | miR-24-3p | MiR24-3p suppresses RIPK1 expression through binding to its 3′-UTR during myocardial ischemia/reperfusion injury. | [ |
| PTGES2 | miR-146a | MiR-146a negatively regulates PTGES-2 via binding to its 3′-UTR in bone marrow stem cells. | [ |
| TBK1 | miR-199a | MiR-199a suppresses the expression level of TBK1 by targeting 3′-UTR of TBK1 in | [ |
| ABCC1 | miR-7-5p | MiR-7-5p downregulates ABCC1 expression by binding to its 3′-UTR in hepatocellular carcinoma. | [ |
| MARK2 | miR-190a-5p | MiR-190a targets PAR-1 and reduce its expression through binding to its 3′-UTR in breast cancer. | [ |
| LOX | miR-200b-3p | MiR-200 suppresses LOX expression by binding to 3′-UTR of LOX mRNA in breast cancer. | [ |
| LH2 | miR-26b-5p | MiR-26b-5p downregulates PLOD2 through binding to 3′-UTR of PLOD2 in bladder cancer. | [ |
| LDH | miR-200c | MiR-200c directly binds to 3′-UTR of LDHA and inhibits LDHA expression in non-small cell lung cancer. | [ |
| LARP1 | miR-374a | MiR-374a negatively regulates LARP1 by the binding site in the 3′-UTR of LARP1 mRNA in non-small cell lung carcinoma cells. | [ |
| IL10 | miR-106a-5p | MiR-106a directly binds 3′-UTR of IL-10 mRNA and downregulates its expression. | [ |
| IL1B | miR-21-5p | MiR-21-5p inhibits IL1B expression by binding the 3′-UTR of IL1B in estrogen receptor-positive breast carcinoma cell. | [ |
| HDAC2 | miR-500a-5p | MiR-500a-5p directly regulates the expression of HDAC2 by binding to HDAC2 3′-UTR in colorectal cancer. | [ |
| DNMT1 | miR-152 | MiR-152 can decrease the expression of DNMT1 by binding to the 3′-UTR of its transcript in the bladder cancer cells. | [ |
| CUL2 | miR-154-5p | MiR-154-5p targets and inhibit CUL2 by binding to the 3′-UTR of CUL2 in cervical cancer. | [ |
| CSNK2A2 | miR-1228-3p | MiR-1228* directly binds to 3′-UTR of CK2A2 mRNA and inhibits its expression in gastric cancer cell. | [ |
| BRD4 | miR-200a | MiR-200a negatively regulates BRD4 expression by binding to the BRD4 3′-UTR in the prostate cancer cells. | [ |
DHODH, dihydroorotate dehydrogenase; VCP, valosin-containing protein p97; AGTR1, type-1 angiotensin II receptor; TMEM97, sigma intracellular receptor 2; OPRS1, opioid receptor sigma 1; MRC1, mannose receptor; mTOR, mammalian target of rapamycin; JAK-2, janus kinase 2; IMPDH2, inosine-5′-monophosphate dehydrogenase 2; IMPDH1, inosine-5′-monophosphate dehydrogenase 1; CSK2, casein kinase II; BRD2, bromodomain-containing protein 2; BAR, beta adrenergic receptor; JAK-1, janus kinase 1; IL6R, interleukin 6; GAK, cyclin G-associated kinase; VEGF, vascular endothelial growth factor; IFNG, interferon gamma; TLR6, toll-like receptor 6; TLR2, toll-like receptor 2; PIK3CG, PI3-kinase gamma; PIK3CD, PI3-kinase delta; IL8, interleukin 8; CAPN2/CAPNS1, calpain-2/calpain small subunit 1 dimer; CAPN1/CAPNS1, calpain-1/calpain small subunit 1 dimer; BTK, bruton tyrosine kinase; ANG-2, angiopoietin-2; TLR3, toll-like receptor 3; BSG, basigin; RIPK1, receptor-interacting protein 1; PTGES2, prostaglandin E synthase 2; TBK1, NF-kappa-B-activating kinase; ABCC1, multidrug resistance-associated protein 1; MARK2, microtubule affinity regulating kinase 2; LOX, lysyl oxidase; LH2, lysyl hydroxylase 2; LDH, L-lactate dehydrogenase; LARP1, La-related protein 1; IL10, interleukin-10; IL1B, interleukin-1 beta; HDAC2, histone deacetylase 2; DNMT1, DNA [cytosine-5]-methyltransferase 1; CUL2, cullin-2; CSNK2A2, casein kinase II alpha prime; BRD4, bromodomain-containing protein 4.
Tools of studies that focus on miRNAs role in COVID-19
| Studies | Contents | Tools | URL | Description of the tool | Reference |
|---|---|---|---|---|---|
| Khan’s study [ | RNA–RNA interactions for viral miRNA-host mRNA and the host miRNA-viral genome | IntaRNA 2.0 |
| An algorithm for prediction of RNA–RNA interaction | [ |
| microRNA.org |
| A database containing knowledge of miRNA target prediction | [ | ||
| psRNATarget |
| A server for analysis of miRNA target | [ | ||
| Identification of host miRNA targets | Funrich |
| A software for functional enrichment analysis (containing information of experimentally validated targets of host miRNAs) | [ | |
| miRTarBase |
| A database containing experimentally validated microRNA-target interaction | [ | ||
| Fulzele’s study [ | Identification of human miRNAs targeting the SARS-CoV-2 genome | miRDB |
| A database for prediction of miRNA targets | [ |
| Bartoszewski’s study [ | Prediction of interaction between host miRNA and coronaviruses | RNA22 v2 |
| A method for miRNA binding sites and their corresponding microRNA/mRNA complexes | [ |
| Tang’s study [ | Identification of host miRNA-mRNA interaction | multimiR |
| A R package for miRNA-target interaction | [ |
| Satyam’s study [ | Prediction of viral miRNA targeted host gene | miRanda v3.3 |
| An algorithm for prediction of miRNA target genes | [ |
| Sardar’s study [ | Resource of antiviral host miRNAs (experimentally verified) and their targets | VIRmiRNA |
| A database containing experimentally validated viral miRNAs and their targets | [ |
| Prediction of host miRNA targeting virus genome | miRanda v3.3 |
| An algorithm for prediction of miRNA target genes | [ | |
| psRNATarget |
| A server for analysis of miRNA target | [ |