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2023—2024年衢州市新型冠状病毒Omicron变异株分子流行病学特征分析

Molecular epidemiological characterization of SARS-CoV-2 Omicron variants in Quzhou, 2023–2024

  • 摘要:
    目的 了解2023—2024年浙江省衢州市新冠病毒(SARS-CoV-2)Omicron变异株流行趋势及刺突蛋白(S)变异进化规律。
    方法 收集2023年1月—2024年9月衢州市各新冠病毒变异监测哨点和流感监测哨点医院送检的新冠病毒感染者鼻咽拭子、痰液等呼吸道样本;采用纳米孔测序技术对收集的267份呼吸道样本进行新冠病毒全基因组测序。运用Pangolin v4.3和Nextclade v3.13.1在线分析平台进行基因分型,并获取氨基酸变异等信息;通过 TBtools-Ⅱ v2.222 绘制S蛋白关键结构域的氨基酸变异热图,利用VarEPS系统评估氨基酸变异对病毒适应性的影响。
    结果 共获得246条新冠病毒全基因组有效序列,均为Omicron变异株,可分为10个进化分支,总体呈BA.5-XBB-BA.2谱系进行顺序更替,其中JN.1及其亚分支占比最高(42.28%,104/246),与系统发育分析结果一致。不同年龄组的新冠病毒基因型分布差异有统计学意义(P<0.001)。氨基酸变异分析显示,S蛋白氨基酸变异最为频繁,其变异位点数随时间逐步增加,并存在氨基酸更替/插入/缺失变异,其中JN.1和XDV.1及其亚分支S蛋白氨基酸突变频率更高,并在关键结构域新增多个变异位点(K356T、R403K、N450D、N481K、E544K、A570V、P621S等)。评估显示,S蛋白多个氨基酸变异位点(R346T、S371F、S373P、T376A、D405N、R408S、K417N、G446S、F456L、Y505H等)可在一定程度上降低S蛋白与中和抗体的结合稳定性。
    结论 2023—2024年衢州地区以Omicron变异株为优势变异株,其基因型呈现多样性,对S蛋白的氨基酸变异监测与分析,有助于及时了解新冠病毒的进化特征,为新冠病毒变异株的流行风险评估及疫情防控提供理论依据。

     

    Abstract:
    Objective To understand the epidemiological trends of SARS-CoV-2 Omicron variants and evolutionary variations of the spike protein in Quzhou city of Zhejiang province from 2023 to 2024.
    Methods Respiratory specimens (including nasopharyngeal swabs and sputum specimens) were collected from COVID-19 cases at sentinel surveillance sites for SARS-CoV-2 variants and influenza in Quzhou between January 2023 and September 2024. The whole genome sequences of SARS-CoV-2 from 267 cases were obtained by nanopore sequencing. The genotypes and amino acid variations were analyzed through Pangolin v4.3 and Nextclade v3.13.1 platforms. Heatmaps of amino acid mutations in the key domains of the spike protein were generated by TBtools-Ⅱ v2.222, while the impact of amino acid mutations on viral adaptability was assessed by the VarEPS system.
    Results All the 246 sequences were Omicron variants of SARS-CoV-2, showing the turnover of BA.5-XBB-BA.2 lineages. These variants were classified into ten sub-lineages, with JN.1 and its sub-lineages showing the highest prevalence (42.28%, 104/246). This classification was consistent with the results of the phylogenetic analysis. The distribution of SARS-CoV-2 genotypes across different age groups showed differences (P < 0.001). Amino acid mutation analysis revealed frequent mutations in the spike protein, with the number of mutation sites gradually increasing over time and involving substitutions, insertions, and deletions. JN.1, XDV.1, and their sub-lineages exhibited higher mutation frequency in the spike protein, accumulating novel mutations (K356T, R403K, N450D, N481K, E544K, A570V, P621S, etc.) in key domains. Functional assessments indicated that multiple spike protein mutations (R346T, S371F, S373P, T376A, D405N, R408S, K417N, G446S, F456L, Y505H, etc.) may reduce the binding stability between the spike protein with neutralizing antibodies.
    Conclusion The Omicron variants were the predominant circulating variants in Quzhou during 2023–2024, exhibiting diverse genotypes. Monitoring and analyzing amino acid mutations in the spike protein facilitate timely understanding of the evolutionary characteristics of SARS-CoV-2, providing a theoretical basis for risk assessment of COVID-19 variant prevalence and the implementation of epidemic prevention and control measures.

     

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