An Epidemiological Analysis of SARS-CoV-2 Genomic Sequences from Different Regions of India.
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ABSTRACT:
SUBMITTER: Yadav PD
PROVIDER: S-EPMC8156686 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Family clusters have contributed significantly to the onward spread of SARS-CoV-2. However, the dynamics of viral transmission in this setting remain incompletely understood. We describe the clinical and viral-phylogenetic characteristics of a family cluster of SARS-CoV-2 infections with a high attack rate, and explore how whole-genome sequencing (WGS) can inform outbreak investigations in this context. In this cluster, the first symptomatic case was a 22-month-old infant who developed rhinorrhoea and sneezing 2 days prior to attending a family gathering. Subsequently, seven family members in attendance at this event were diagnosed with SARS-CoV-2 infections, including the infant described. WGS revealed indistinguishable SARS-CoV-2 genomes recovered from the adults at the gathering, which were closely related genetically to B.1 lineage viruses circulating in the local community. However, a divergent viral sub-lineage was recovered from the infant and another child, each harbouring a distinguishing spike substitution (N30S). This suggested that the infant was unlikely to be the primary case, despite displaying symptoms first, and additional analysis of her nasopharyngeal swab revealed a picornavirus co-infection to account for her early symptoms. Our findings demonstrate how WGS can elucidate the transmission dynamics of SARS-CoV-2 infections within household clusters and provide useful information to support outbreak investigations. Additionally, our description of SARS-CoV-2 viral lineages and notable variants circulating in Ireland to date provides an important genomic-epidemiological baseline in the context of vaccine introduction.
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Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the ongoing global COVID-19 pandemic that began in late December 2019. The rapid spread of SARS-CoV-2 is primarily due to person-to-person transmission. To understand the epidemiological traits of SARS-CoV-2 transmission, we conducted phylogenetic analysis on genome sequences from >54K SARS-CoV-2 cases obtained from two public databases. Hierarchical clustering analysis on geographic patterns in the resulting phylogenetic trees revealed a co-expansion tendency of the virus among neighboring countries with diverse sources and transmission routes for SARS-CoV-2. Pairwise sequence similarity analysis demonstrated that SARS-CoV-2 is transmitted locally and evolves during transmission. However, no significant differences were seen among SARS-CoV-2 genomes grouped by host age or sex. Here, our identified epidemiological traits provide information to better prevent transmission of SARS-CoV-2 and to facilitate the development of effective vaccines and therapeutics against the virus.
| S-EPMC8145049 | biostudies-literature
Project description:Accumulation of mutations within the genome is the primary driving force in viral evolution within an endemic setting. This inherent feature often leads to altered virulence, infectivity and transmissibility, and antigenic shifts to escape host immunity, which might compromise the efficacy of vaccines and antiviral drugs. Therefore, we carried out a genome-wide analysis of circulating SARS-CoV-2 strains to detect the emergence of novel co-existing mutations and trace their geographical distribution within India. Comprehensive analysis of whole genome sequences of 837 Indian SARS-CoV-2 strains revealed the occurrence of 33 different mutations, 18 of which were unique to India. Novel mutations were observed in the S glycoprotein (6/33), NSP3 (5/33), RdRp/NSP12 (4/33), NSP2 (2/33), and N (1/33). Non-synonymous mutations were found to be 3.07 times more prevalent than synonymous mutations. We classified the Indian isolates into 22 groups based on their co-existing mutations. Phylogenetic analysis revealed that the representative strains of each group were divided into various sub-clades within their respective clades, based on the presence of unique co-existing mutations. The A2a clade was found to be dominant in India (71.34%), followed by A3 (23.29%) and B (5.36%), but a heterogeneous distribution was observed among various geographical regions. The A2a clade was highly predominant in East India, Western India, and Central India, whereas the A2a and A3 clades were nearly equal in prevalence in South and North India. This study highlights the divergent evolution of SARS-CoV-2 strains and co-circulation of multiple clades in India. Monitoring of the emerging mutations will pave the way for vaccine formulation and the design of antiviral drugs.
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Project description:BackgroundEmergence of the new SARS-CoV-2 variant B.1.1.529 worried health policy makers worldwide due to a large number of mutations in its genomic sequence, especially in the spike protein region. The World Health Organization (WHO) designated this variant as a global variant of concern (VOC), which was named "Omicron." Following Omicron's emergence, a surge of new COVID-19 cases was reported globally, primarily in South Africa.ObjectiveThe aim of this study was to understand whether Omicron had an epidemiological advantage over existing variants.MethodsWe performed an in silico analysis of the complete genomic sequences of Omicron available on the Global Initiative on Sharing Avian Influenza Data (GISAID) database to analyze the functional impact of the mutations present in this variant on virus-host interactions in terms of viral transmissibility, virulence/lethality, and immune escape. In addition, we performed a correlation analysis of the relative proportion of the genomic sequences of specific SARS-CoV-2 variants (in the period from October 1 to November 29, 2021) with matched epidemiological data (new COVID-19 cases and deaths) from South Africa.ResultsCompared with the current list of global VOCs/variants of interest (VOIs), as per the WHO, Omicron bears more sequence variation, specifically in the spike protein and host receptor-binding motif (RBM). Omicron showed the closest nucleotide and protein sequence homology with the Alpha variant for the complete sequence and the RBM. The mutations were found to be primarily condensed in the spike region (n=28-48) of the virus. Further mutational analysis showed enrichment for the mutations decreasing binding affinity to angiotensin-converting enzyme 2 receptor and receptor-binding domain protein expression, and for increasing the propensity of immune escape. An inverse correlation of Omicron with the Delta variant was noted (r=-0.99, P<.001; 95% CI -0.99 to -0.97) in the sequences reported from South Africa postemergence of the new variant, subsequently showing a decrease. There was a steep rise in new COVID-19 cases in parallel with the increase in the proportion of Omicron isolates since the report of the first case (74%-100%). By contrast, the incidence of new deaths did not increase (r=-0.04, P>.05; 95% CI -0.52 to 0.58).ConclusionsIn silico analysis of viral genomic sequences suggests that the Omicron variant has more remarkable immune-escape ability than existing VOCs/VOIs, including Delta, but reduced virulence/lethality than other reported variants. The higher power for immune escape for Omicron was a likely reason for the resurgence in COVID-19 cases and its rapid rise as the globally dominant strain. Being more infectious but less lethal than the existing variants, Omicron could have plausibly led to widespread unnoticed new, repeated, and vaccine breakthrough infections, raising the population-level immunity barrier against the emergence of new lethal variants. The Omicron variant could have thus paved the way for the end of the pandemic.
| S-EPMC9843602 | biostudies-literature
Project description:Molecular surveillance of the drug resistance genes in parasite can be used for monitoring/surveillance of drug resistance in endemic malaria areas. Here we report the prevalence of single nucleotide polymorphisms (SNPs) in dihydrofolate reductase (dhfr) gene in nucleotide sequence of Plasmodium falciparum from different regions in India. We found markedly prevalent mutants evident in P. falciparum infections N51I, C59R, 108N and I164L. Our results indicate that P. falciparum populations in the regions show an increase in the prevalence of polymorphisms, most likely reflecting different selective pressures found in humans and mosquitoes. Molecular surveillance can serve as a useful tool to monitor the prevalence/emergence of resistant genotypes within endemic populations and can serve for determining the efficacy of antimalarial drugs.
| S-EPMC7139110 | biostudies-literature
Project description:Background: In order to understand the molecular epidemiology of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Sri Lanka, since March 2020, we carried out genomic sequencing overlaid on available epidemiological data until April 2021. Methods: Whole genome sequencing was carried out on diagnostic sputum or nasopharyngeal swabs from 373 patients with COVID-19. Molecular clock phylogenetic analysis was undertaken to further explore dominant lineages. Results: The B.1.411 lineage was most prevalent, which was established in Sri Lanka and caused outbreaks throughout the country until March 2021. The estimated time of the most recent common ancestor (tMRCA) of this lineage was June 1, 2020 (with 95% lower and upper bounds March 30 to July 27) suggesting cryptic transmission may have occurred, prior to a large epidemic starting in October 2020. Returning travellers were identified with infections caused by lineage B.1.258, as well as the more transmissible B.1.1.7 lineage, which has replaced B.1.411 to fuel the ongoing large outbreak in the country. Conclusions: The large outbreak that started in early October, is due to spread of a single virus lineage, B.1.411 until the end of March 2021, when B.1.1.7 emerged and became the dominant lineage.
| S-EPMC8483294 | biostudies-literature
Project description:SARS-CoV-2 (CoV) is the etiological agent of the COVID-19 pandemic and evolves to evade both host immune systems and intervention strategies. We divided the CoV genome into 29 constituent regions and applied novel analytical approaches to identify associations between CoV genomic features and epidemiological metadata. Our results show that nonstructural protein 3 (nsp3) and Spike protein (S) have the highest variation and greatest correlation with the viral whole-genome variation. S protein variation is correlated with nsp3, nsp6, and 3'-to-5' exonuclease variation. Country of origin and time since the start of the pandemic were the most influential metadata associated with genomic variation, while host sex and age were the least influential. We define a novel statistic-coherence-and show its utility in identifying geographic regions (populations) with unusually high (many new variants) or low (isolated) viral phylogenetic diversity. Interestingly, at both global and regional scales, we identify geographic locations with high coherence neighboring regions of low coherence; this emphasizes the utility of this metric to inform public health measures for disease spread. Our results provide a direction to prioritize genes associated with outcome predictors (e.g., health, therapeutic, and vaccine outcomes) and to improve DNA tests for predicting disease status.
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Project description:BackgroundThe COVID-19 pandemic remains a global public health concern. Advances in sequencing technologies has allowed for high numbers of SARS-CoV-2 whole genome sequence (WGS) data and rapid sharing of sequences through global repositories to enable almost real-time genomic analysis of the pathogen. WGS data has been used previously to group genetically similar viral pathogens to reveal evidence of transmission, including methods that identify distinct clusters on a phylogenetic tree. Identifying clusters of linked cases can aid in the regional surveillance and management of the disease. In this study, we present a novel method for producing stable genomic clusters of SARS-CoV-2 cases, cov2clusters, and compare the accuracy and stability of our approach to previous methods used for phylogenetic clustering using real-world SARS-CoV-2 sequence data obtained from British Columbia, Canada.ResultsWe found that cov2clusters produced more stable clusters than previously used phylogenetic clustering methods when adding sequence data through time, mimicking an increase in sequence data through the pandemic. Our method also showed high accuracy when predicting epidemiologically informed clusters from sequence data.ConclusionsOur new approach allows for the identification of stable clusters of SARS-CoV-2 from WGS data. Producing high-resolution SARS-CoV-2 clusters from sequence data alone can a challenge and, where possible, both genomic and epidemiological data should be used in combination.
| S-EPMC9579665 | biostudies-literature
Project description:Since late 2019, the coronavirus disease 2019 (COVID-19) outbreak, caused by SARS-CoV-2, has rapidly evolved to become a global pandemic. Each country was affected but with a varying number of infected cases and mortality rates. Africa was hit late by the pandemic but the number of cases rose sharply. In this study, we investigated 224 SARS-CoV-2 genome sequences from the Global Initiative on Sharing Avian Influenza Data (GISAID) in the early part of the outbreak, of which 69 were from Africa. We analyzed a total of 550 mutations by comparing them with the reference SARS-CoV-2 sequence from Wuhan. We classified the mutations observed based on country and region, and afterwards analyzed common and unique mutations on the African continent as a whole. Correlation analyses showed that the duo variants ORF1ab/RdRp 4715L and S protein 614G variants, which are strongly linked to fatality rate, were not significantly and positively correlated with fatality rates (r = -0.03757, P = 0.5331 and r = -0.2876, P = 0.6389, respectively), although increased number of cases correlated with number of deaths (r = 0.997, P = 0.0002). Furthermore, most cases in Africa were mainly imported from American and European countries, except one isolate with no mutation and was similar to the original isolate from Wuhan. Moreover, unique mutations specific to countries were identified in the early phase of the outbreak but these mutations were not regional-specific. There were common mutations in all isolates across the continent as well as similar isolate-specific mutations in different regions. Our findings suggest that mutation is rapid in SARS-CoV-2 in Africa and although these mutations spread across the continent, the duo variants could not possibly be the sole cause of COVID-19 deaths in Africa in the early phase of the outbreak.
| S-EPMC8101992 | biostudies-literature
Project description:Background: India first detected SARS-CoV-2, causal agent of COVID-19 in late January 2020, imported from Wuhan, China. From March 2020 onwards, the importation of cases from countries in the rest of the world followed by seeding of local transmission triggered further outbreaks in India. Methods: We used ARTIC protocol-based tiling amplicon sequencing of SARS-CoV-2 (n=104) from different states of India using a combination of MinION and MinIT sequencing from Oxford Nanopore Technology to understand how introduction and local transmission occurred. Results: The analyses revealed multiple introductions of SARS-CoV-2 genomes, including the A2a cluster from Europe and the USA, A3 cluster from Middle East and A4 cluster (haplotype redefined) from Southeast Asia (Indonesia, Thailand and Malaysia) and Central Asia (Kyrgyzstan). The local transmission and persistence of genomes A4, A2a and A3 was also observed in the studied locations. The most prevalent genomes with patterns of variance (confined in a cluster) remain unclassified, and are here proposed as A4-clade based on its divergence within the A cluster. Conclusions: The viral haplotypes may link their persistence to geo-climatic conditions and host response. Multipronged strategies including molecular surveillance based on real-time viral genomic data is of paramount importance for a timely management of the pandemic.
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