Université Evangélique en Afrique, Molecular Biology Laboratory, Bukavu, Democratic Republic of the Congo.
International Livestock Research Institute (ILRI), Nairobi, Kenya.
Int J Infect Dis. 2022 Sep;122:136-143. doi: 10.1016/j.ijid.2022.05.041. Epub 2022 May 20.
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.
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.
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.
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.
我们使用 SARS-CoV-2 的全基因组测序来鉴定在刚果民主共和国流行的变异株,并获得有助于诊断、改善治疗和一般大流行控制策略的分子信息。
使用 Oxford Nanopore 平台对总共 74 个 SARS-CoV-2 分离株进行测序。处理生成的读数以获得共识基因组序列。使用 Pangolin 谱系注释命名法对具有 80%以上基因组覆盖率的序列进行变异调用、系统发育分析和分类。
基于 Pangolin 分类的系统发育分析将南基伍的序列聚类为七个谱系(A.23.1、B.1.1.6、B.1.214、B.1.617.2、B.1.351、C.16 和 P.1)。Delta(B.1.617.2)变异株最为优势,导致了第三波疫情的爆发。基于武汉参考基因组,我们的分离株与武汉参考株比对时,共检测到 289 个不同的突变,包括 141 个错义突变、123 个同义突变和 25 个插入/缺失。这些点突变大多位于 SARS-CoV-2 基因组的编码序列中,包括刺突蛋白、ORF1ab、ORF3 和核衣壳蛋白基因。最常见的突变是 D614G(1841A>G),在 61 个序列中观察到,其次是 L4715L(14143C>T),在 60 个序列中发现。
我们的研究结果突显了 SARS-CoV-2 通过不同来源多次传入南基伍,并随后在该省传播变异株。这些结果强调了及时监测遗传变异及其对疾病严重程度的影响的重要性。这项工作为使用基因组监测作为未来全球大流行管理和控制的工具奠定了基础。