The global COVID-19 pandemic continues due to emerging Severe Acute Respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOC). Here, we performed comprehensive analysis of in-house sequenced SARS-CoV-2 genome mutations dynamics in the patients infected with the VOCs – Delta and Omicron, within Recovered and Mortality patients. Statistical analysis highlighted significant mutations – T4685A, N4992N, and G5063S in RdRp; T19R in NTD spike; K444N and N532H in RBD spike, associated with Delta mortality. Mutations, T19I in NTD spike, Q493R and N440K in the RBD spike were significantly associated with Omicron mortality. We performed molecular docking for possible effect of significant mutations on the binding of Remdesivir. We found that Remdesivir showed less binding efficacy with the mutant Spike protein of both Delta and Omicron mortality compared to recovered patients. This indicates that mortality associated mutations could have a modulatory effect on drug binding which could be associated with disease outcome.
- The mutational landscape of 1567 international travellers and community transmission were characterized across VOCs in India
- Mutations in LD for VOCs demonstrated differentially altered binding affinity and electrostatic interactions of Spike-ACE2.•
- Altered Spike-ACE2 affinity among VOCs predicted sudden takeover of Delta over Alpha and BA.2 over BA.1 in India.
SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher’s test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.
The past 2 years, during which waves of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants swept the globe, have starkly highlighted health disparities across nations. Tegally et al. show how the coordinated efforts of talented African scientists have in a short time made great contributions to pandemic surveillance and data gathering. Their efforts and initiatives have provided early warning that has likely benefited wealthier countries more than their own. Genomic surveillance identified the emergence of the highly transmissible Beta and Omicron variants and now the appearance of Omicron sublineages in Africa. However, it is imperative that technology transfer for diagnostics and vaccines, as well the logistic wherewithal to produce and deploy them, match the data-gathering effort. —CA
We sought to investigate whether SARS-CoV-2 was present, and to perform full-length genomic sequencing, in a 5-year-old male crossbreed dog that presented with flu-like symptoms (including a dry hacking cough and mild dyspnea) and resided in a household with 3 adults that were diagnosed with SARS CoV-2 infection. Next generation sequencing based on MinION technology was performed on amplicons that were generated using a reverse transcriptase real-time polymerase chain reaction (RT-qPCR) of confirmed positive SARS-CoV-2 nasopharyngeal and buccal swabs, as well as a bronchoalveolar lavage with mean qCt value of 36 based on the Nucleocapsid gene. Descriptive comparisons to known sequences in Botswana and internationally were made using mutation profiling analysis and phylogenetic inferences based on maximum likelihood. Samples from the dog’s owners were not available. A near-full length SARS-CoV-2 genome (~90% coverage) was successfully genotyped and classified under clade 20 O and Pango-Lineage AY.43 (Pango v.4.0.6 PLEARN-v1.3; 2022-04-21), which is a sub-lineage of the Delta variant of concern (VOC) (formerly called B.1.617.2, first detected in India). We did not identify novel mutations that may be used to distinguish SARS-CoV-2 isolates from the dog and humans. In addition to S region mutation profiling, we performed phylogenetic analysis using Delta sequences from Botswana (n=1303); expectedly, the sequence isolated from the dog was closely related to the Delta sequences, particularly the AY.43, AY.116, and B.1.617.2 sub-lineages that were reported in Botswana within the same time frame. This is the first documented report of human-associated SARS-CoV-2 infection in a dog in Botswana. Although the direction of transmission remains unknown, this study further affirms the need for monitoring pets during different COVID-19 waves for possible clinically relevant SARS-CoV-2 transmissions between species.
The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants.
The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) variants, respectively1,2,3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron, B.1.1.529) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, which are predicted to influence antibody neutralization and spike function4. Here we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.
Global sequencing and surveillance capacity for SARS-CoV-2 must be strengthened and combined with multidisciplinary studies of infectivity, virulence and immune escape, in order to track the unpredictable evolution of the ongoing COVID-19 pandemic.
In June 2020, the World Health Organization (WHO) SARS-CoV-2 evolution working group was established to track SARS-CoV-2 variants and their specific genetic changes and to monitor viral characteristics and their impact on medical and non-medical countermeasures, including vaccines against COVID-19. In November 2021, this working group transitioned to a formal WHO Technical Advisory Group on Virus Evolution (TAG-VE), with the aim of developing and implementing a global risk-monitoring framework for SARS-CoV-2 variants, based on a multidisciplinary approach that includes in silico, virological, clinical and epidemiological data.
Three lineages (BA.1, BA.2 and BA.3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant of concern predominantly drove South Africa’s fourth Coronavirus Disease 2019 (COVID-19) wave. We have now identified two new lineages, BA.4 and BA.5, responsible for a fifth wave of infections. The spike proteins of BA.4 and BA.5 are identical, and similar to BA.2 except for the addition of 69–70 deletion (present in the Alpha variant and the BA.1 lineage), L452R (present in the Delta variant), F486V and the wild-type amino acid at Q493. The two lineages differ only outside of the spike region. The 69–70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure, on the background of variants not possessing this feature. BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa by the first week of April 2022. Using a multinomial logistic regression model, we estimated growth advantages for BA.4 and BA.5 of 0.08 (95% confidence interval (CI): 0.08–0.09) and 0.10 (95% CI: 0.09–0.11) per day, respectively, over BA.2 in South Africa. The continued discovery of genetically diverse Omicron lineages points to the hypothesis that a discrete reservoir, such as human chronic infections and/or animal hosts, is potentially contributing to further evolution and dispersal of the virus.