Comparative study of predicted miRNA between Indonesia and China (Wuhan) SARS-CoV-2: a bioinformatics analysis

Abstract

Background Several reports on the discovery of SARS-CoV-2 mutations and variations in Indonesia COVID-19 cases led to genomic dysregulation with the first pandemic cases in Wuhan, China. MicroRNA (miRNA) plays an important role in this genetic regulation and contributes to the enhancement of viral RNA binding through the host mRNA. Objective This research is aimed to detect miRNA targets of SARS-CoV-2 and examines their role in Indonesia cases against Wuhan cases. Methods SARS-CoV-2 sequences were obtained from GISAID ( https://www.gisaid.org/ ), NCBI ( https://ncbi.nlm.nih.gov ), and National Genomics Data Center ( https://bigd.big.ac.cn/gwh/ ) databases. MiRDB ( https://github.com/gbnegrini/mirdb-custom-target-search ) was used to annotate and predict target human mature miRNAs. For statistical analysis, we utilized a series chi-square test to obtain significant miRNA. DIANA-miRPath v3.0 ( http://www.microrna.gr/miRPathv3 ) analyzed the Gene Ontology of mature miRNAs. Result The statistical results detected five significant miRNAs. Two miRNAs: hsa-miR-4778-5p and hsa-miR-4531 were consistently found in the majority of Wuhan samples, while they were only found in less than half of the Indonesia samples. The other three miRNA, hsa-miR-6844, hsa-miR-627-5p, and hsa-miR-3674, were discovered in most samples in both groups but with a significant difference ratio. Among these five significant miRNA targets, hsa-miR-6844 is the only miRNA that has an association with the ORF1ab gene of SARS-CoV-2. Conclusion The Gene Ontology analysis of five significant miRNA targets indicates a significant role in inflammation and the immune system. The specific detection of host miRNAs in this study shows that there are differences in the characteristics of SARS-CoV-2 between Indonesia and Wuhan. Supplementary Information The online version contains supplementary material available at 10.1007/s13258-021-01119-7.

miRNA expression in COVID-19

“…In addition, a significant difference in the characteristics of SARS-CoV-2 between Indonesia and Wuhan was shown by evaluating the host miRNAs. ( Rahmadi et al, 2021 ) miR-9-5p, miR-218-5p Bioinformatics ACE2 miRNAs regulates SARS-CoV-2 infectivity in human cells through attachment of host miRNAs to the SARS-CoV-2 genome and modulation of the transcripts of viral entry proteins, ACE2 and TMPRSS2, and modulation by their upstream IFN modulators. ( Pierce et al, 2020 ) let-7d-5p, -7e-5p, miR-494-3p, miR-382-3p, miR-181c-5p TMPRSS2 miR-361-5p, miR-410-3p IFN-α miR-23a, miR-29a, -29c, miR-151a, -151b (S), miR-4707-3p (S), miR-298 miR-7851-3p, miR-8075 SARS-CoV-2 ORFs hsa-miR-499a-3p hsa-miR-4532 hsa-miR-6763-3p hsa-miR-26b-5p Bioinformatics ACE2 SNP of microRNAs influence susceptibility to COVID-19 s and response to anti-viral drug by regulating ACE2 expression.…”

MicroRNAs as powerful tool against COVID‐19: Computational perspective

“…Table 1 enlists computational tools used in field of COVID-19 research, their applications, and sources. Rahmadi et al (2021) incorporated a total of 39 Indonesian SARS-CoV 2 samples and 37 samples from Wuhan. Whole dataset was compiled from GISAID, NCBI, and China National Center for Bioinformation.…”

“…Rahmadi et al (2021) incorporated a total of 39 Indonesian SARS‐CoV 2 samples and 37 samples from Wuhan. Whole dataset was compiled from GISAID, NCBI, and China National Center for Bioinformation.…”

Genome mining of potential enzyme from Chelatococcus composti for sustainable production of D-Allulose

“…One of the bacteria that has been discovered to live in geothermal system in Indonesia is Chelatococcus composti. The preliminary biological data mining study based on the Basic Local Alignment Search Tool protein Search (BLAST-p search) of DAEase discovered that the species potentially contained a sequence possessing high sequence similarity with previously characterized DAEases [15,16]. Thus, research was done to study the potential of the novel putative enzyme from Chelatococcus composti to become an enzyme candidate for the industry of sugar mass-production.…”