Genetic Variant of SARS-CoV-2 Isolates in Indonesia: Spike Glycoprotein Gene

Molecular epidemiology and genetic characterization of SARS-CoV-2 in Kuwait: A descriptive study

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been fatal to human health, affecting almost the entire world. Here we reported, for the first time, characterization of the genetic variants of SARS-CoV-2 circulating in Kuwait to understand their genetic diversity and monitor the accumulation of mutations over time. This study randomly enrolled 209 COVID-19 patients whose nasopharyngeal swabs were positive for SARS-CoV-2 between February 2020 and June 2021 using RT-PCR. The whole genomes of SARS-CoV-2 from the nasopharyngeal swabs were sequenced using the Oxford Nanopore sequencing technology following the ARTIC network protocol. Whole-genome sequencing has identified different clades/sub-clades circulating in Kuwait, mimicking the virus’s global spread. Clade 20A was dominant from February 2020 until January 2021, and then clade 20I (Alpha, V1) emerged and dominated. In June 2021, the number of cases infected with clades 21I, 21A, and 21 J (Delta) increased and dominated. We detected several known clade-defining missense and synonymous mutations and other missense mutations in the genes encoding important viral proteins, including ORF1a, S, ORF3a, ORF8 regions and a novel mutation in the N region. ORF1ab region harbored more mutations and deletions (n = 62, 49.2%) compared to the other 12 gene regions, and the most prevalent missense mutations were P314L (97%) in ORF1b and D614G (97%) in the S glycoprotein regions. Detecting and analyzing mutations and monitoring the evolution of SARS-CoV-2 over time is essential to help better understand the spread of various clades/strains of SARS-CoV-2 and their implications for pathogenesis. In addition, knowledge of the circulating variants and genome sequence variability of SARS-CoV-2 may potentially influence the development of vaccines and antiviral drugs to control the COVID-19 pandemic.

Community-level SARS-CoV-2 sequence diversity revealed by wastewater sampling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for causing the COVID-19 pandemic, can be detected in untreated wastewater. Wastewater surveillance of SARS-CoV-2 complements clinical data by offering earlier community-level detection, removing underlying factors such as access to healthcare, sampling asymptomatic patients, and reaching a greater population. Here, we compare 24-hour composite samples from the influents of two different wastewater treatment plants (WWTPs) in South Carolina, USA: Columbia and Rock Hill. The sampling intervals span the months of July 2020 and January 2021, which cover the first and second waves of elevated SARS-CoV-2 transmission and COVID-19 clinical cases in these regions. We identify four signature mutations in the surface glycoprotein (spike) gene that are associated with the following variants of interest or concern, VOI or VOC (listed in parenthesis): S477N (B.1.526, Iota), T478K (B.1.617.2, Delta), D614G (present in all VOC as of May 2021), and H655Y (P.1, Gamma). The N501Y mutation, which is associated with three variants of concern, was identified in samples from July 2020, but not detected in January 2021 samples. Comparison of mutations identified in viral sequence databases such as NCBI Virus and GISAID indicated that wastewater sampling detected mutations that were present in South Carolina, but not reflected in the clinical data deposited into databases.

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

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.

Characterization of SARS-CoV-2 different variants and related morbidity and mortality: a systematic review

INTRODUCTION

Coronavirus Disease-2019 (SARS-CoV-2) started its devastating trajectory into a global pandemic in Wuhan, China, in December 2019. Ever since, several variants of SARS-CoV-2 have been identified. In the present review, we aimed to characterize the different variants of SARS-CoV-2 and explore the related morbidity and mortality.

METHODS

A systematic review including the current evidence related to different variants of SARS-CoV-2 and the related morbidity and mortality was conducted through a systematic search utilizing the keywords in the online databases including Scopus, PubMed, Web of Science, and Science Direct; we retrieved all related papers and reports published in English from December 2019 to September 2020.

RESULTS

A review of identified articles has shown three main genomic variants, including type A, type B, and type C. we also identified three clades including S, V, and G. Studies have demonstrated that the C14408T and A23403G alterations in the Nsp12 and S proteins are the most prominent alterations in the world, leading to life-threatening mutations.The spike D614G amino acid change has become the most common variant since December 2019. From missense mutations found from Gujarat SARS-CoV-2 genomes, C28854T, deleterious mutation in the nucleocapsid (N) gene was significantly associated with patients' mortality. The other significant deleterious variant (G25563T) is found in patients located in Orf3a and has a potential role in viral pathogenesis.

CONCLUSION

Overall, researchers identified several SARS-CoV-2 variants changing clinical manifestations and increasing the transmissibility, morbidity, and mortality of COVID-19. This should be considered in current practice and interventions to combat the pandemic and prevent related morbidity and mortality.

The Identification of the SARS-CoV-2 Whole Genome: Nine Cases Among Patients in Banten Province, Indonesia

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the strain of virus that causes coronavirus disease 2019 (COVID-19), the respiratory illness responsible for the current pandemic. Viral genome sequencing has been widely applied during outbreaks to study the relatedness of this virus to other viruses, its transmission mode, pace, evolution and geographical spread, and also its adaptation to human hosts. To date, more than 90,000 SARS-CoV-2 genome sequences have been uploaded to the GISAID database. The availability of sequencing data along with clinical and geographical data may be useful for epidemiological investigations. In this study, we aimed to analyse the genetic background of SARS-CoV-2 from patients in Indonesia by whole genome sequencing. We examined nine samples from COVID-19 patients with RT-PCR cycle threshold (Ct) of less than 25 using ARTIC Network protocols for Oxford Nanopore’s Gridi On sequencer. The analytical methods were based on the ARTIC multiplex PCR sequencing protocol for COVID-19. In this study, we found that several genetic variants within the nine COVID-19 patient samples. We identified a mutation at position 614 P323L mutation in the ORF1ab gene often found in our severe patient samples. The number of SNPs and their location within the SARS-CoV-2 genome seems to vary. This diversity might be responsible for the virulence of the virus and its clinical manifestation.