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Molecular epidemiology of Sars-CoV-2 in Northern South Africa

Wastewater surveillance from January 2021 to May 2022

Bibliographic Data

ID22069796
AuthorsLisa Arrah Mbang Tambe (0000-0003-0462-8674, University of Venda), Phindulo Mathobo (University of Venda), Nontokozo D Matume (0000-0003-3766-5463, University of Venda), Mukhethwa Munzhedzi (0000-0003-1082-0881, University of Venda), Joshua N Edokpayi (0000-0002-2550-3988, University of Venda), Amsha Viraragavan (0000-0002-4282-1371, South African Medical Research Council), Brigitte Glanzmann (0000-0002-8318-919X, South African Medical Research Council), Denis M Tebit (0000-0002-4540-6245), Lufuno Grace Mavhandu-Ramarumo (0000-0001-7585-5036, University of Venda), Renée Street (0000-0002-1983-8968, South African Medical Research Council), Rabia Johnson (0000-0002-6328-0789, South African Medical Research Council), Craig Kinnear (0000-0001-6025-0026, South African Medical Research Council), Pascal Bessong (0000-0003-0561-272X, Center for Global Health, corresponding author), Pascal Obong Bessong
Year2023
Volume11
Pages1309869-1309869
Publication date2023-12-19
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1309869
PMID38174083
OpenAlexW4389954953
LanguageEN
Citations received1
References cited39

Introduction: Wastewater-based genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provides a comprehensive approach to characterize evolutionary patterns and distribution of viral types in a population. This study documents the molecular epidemiology of SARS-CoV-2, in Northern South Africa, from January 2021 to May 2022. Methodology: A total of 487 wastewater samples were collected from the influent of eight wastewater treatment facilities and tested for SARS-CoV-2 RNA using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). SARS-CoV-2 positive samples with genome copies/mL ≥1,500 were subjected to allele-specific genotyping (ASG) targeting the Spike protein; 75 SARS-CoV-2 positive samples were subjected to whole genome sequencing (WGS) on the ATOPlex platform. Variants of concern (VoC) and lineages were assigned using the Nextclade and PangoLIN Software. Concordance for VoC between ASG and WGS analyses was determined. Sequence relationship was determined by phylogenetic analysis. Results: Seventy-five percent (365/487) of the influent samples were positive for SARS-CoV-2 RNA. Delta and Omicron VoC were more predominant at a prevalence of 45 and 32%, respectively, and they were detected as early as January and February 2021, while Beta VoC was least detected at a prevalence of 5%. A total of 11/60 (18%) sequences were assigned lineages and clades only, but not a specific VoC name. Phylogenetic analysis was used to investigate the relationship of these sequences to other study sequences, and further characterize them. Concordance in variant assignment between ASG and WGS was seen in 51.2% of the study sequences. There was more intra-variant diversity among Beta VoC sequences; mutation E484K was absent. Three previously undescribed mutations (A361S, V327I, D427Y) were seen in Delta VoC. Discussion and Conclusion: The detection of Delta and Omicron VoCs in study sites earlier in the outbreak than has been reported in other regions of South Africa highlights the importance of population-based approaches over individual sample-based approaches in genomic surveillance. Inclusion of non-Spike protein targets could improve the specificity of ASG, since all VoCs share similar Spike protein mutations. Finally, continuous molecular epidemiology with the application of sensitive technologies such as next generation sequencing (NGS) is necessary for the documentation of mutations whose implications when further investigated could enhance diagnostics, and vaccine development efforts

Biology · Concordance · Gene · Genome · Genotype · Genotyping · Molecular epidemiology · Phylogenetic tree · Whole genome sequencing · COVID-19 Clinical Research Studies · Medicine · SARS-CoV-2 and COVID-19 Research · SARS-CoV-2 detection and testing · Genetics · Virology

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Unique citing works1
Citations per year0,5
Citation span2024 - 2024 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 1

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