Whole-genome sequencing of SARS-CoV-2 reveals diverse mutations in circulating Alpha and Delta variants during the first, second, and third waves of COVID-19 in South Kivu, east of the Democratic Republic of the Congo

https://doi.org/10.1016/j.ijid.2022.05.041Get rights and content
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Highlights

  • The Pangolin classification clustered the South Kivu sequences into seven lineages.

  • The Delta variant is responsible for COVID-19 outbreaks during the third wave.

  • D614G is the most frequent mutation observed, followed by L4715L.

  • There are multiple introductions of SARS-CoV-2 and subsequent circulating variants.

ABSTRACT

Objectives

We used whole-genome sequencing of SARS-CoV-2 to identify variants circulating in the Democratic Republic of the Congo and obtain molecular information useful for diagnosis, improving treatment, and general pandemic control strategies.

Methods

A total of 74 SARS-CoV-2 isolates were sequenced using Oxford Nanopore platforms. Generated reads were processed to obtain consensus genome sequences. Sequences with more than 80% genome coverage were used for variant calling, phylogenetic analysis, and classification using Pangolin lineage annotation nomenclature.

Results

Phylogenetic analysis based on Pangolin classification clustered South Kivu sequences into seven lineages (A.23.1, B.1.1.6, B.1.214, B.1.617.2, B.1.351, C.16, and P.1). The Delta (B.1.617.2) variant was the most dominant and responsible for outbreaks during the third wave. Based on the Wuhan reference genome, 289 distinct mutations were detected, including 141 missenses, 123 synonymous, and 25 insertions/deletions when our isolates were mapped to the Wuhan reference strain. Most of these point mutations were located within the coding sequences of the SARS-CoV-2 genome that includes spike, ORF1ab, ORF3, and nucleocapsid protein genes. The most common mutation was D614G (1841A>G) observed in 61 sequences, followed by L4715L (14143 C>T) found in 60 sequences.

Conclusion

Our findings highlight multiple introductions of SARS-CoV-2 into South Kivu through different sources and subsequent circulation of variants in the province. These results emphasize the importance of timely monitoring of genetic variation and its effect on disease severity. This work set a foundation for the use of genomic surveillance as a tool for future global pandemic management and control.

Keywords

COVID-19
Genetic evolution
Pandemic
SARS-CoV-2
South Kivu
Variants

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