摘要目的:比较两个引起诺如病毒暴发流行的GⅡ.17变异株Kawasaki308_2015（2014—2023年）与Romania_2021（2024—2025年）的基因特征差异。方法:对40株来自2024—2025年海南、北京和深圳诺如病毒暴发疫情的GⅡ.17 变异株Romania_2021阳性样本进行核酸提取、基因组扩增及测序。结合GenBank数据库GⅡ.17参考株以及我国2014—2023年流行的GⅡ.17变异株Kawasaki308_2015，利用BEAST等生物信息软件对其完整的主要衣壳蛋白（major capsid protein，VP1）区和依赖于RNA的RNA聚合酶（RNA dependent RNA polymerase，RdRp）区进行系统进化分析，同时利用同源模拟方法，利用线上网站构建三维结构并预测抗原表位。结果:系统进化分析表明，GⅡ.17 毒株VP1区分成了四个进化簇（Cluster A-D），其中Cluster C可以进一步分为亚簇Subcluster C1和Subcluster C2；GⅡ.P17毒株在RdRp区分成了三个进化簇（Cluster Ⅰ-Ⅲ）。30株来自我国2022—2023年GⅡ.17型诺如病毒暴发疫情的毒株在VP1区与我国2014年暴发流行株GZ41621株（GenBank登录号：KR020503）和Cluster D参考株Kawasaki308_2015（GenBank登录号：LC037415）形成一簇，在聚合酶区归属于Cluster Ⅰ；40株来自2024—2025年我国GⅡ.17型诺如病毒暴发疫情毒株与Subcluster C2参考株Romania_2021（GenBank登录号：OP805362）划分一簇，RdRp区均属于Cluster Ⅲ。根据VP1氨基酸位点变异分析，从2013年至2025年共有36个氨基酸位点的变化。与Subcluster C1和Cluster D相比，2024—2025年毒株所在的Subcluster C2在抗原位点A（296，368）、D（395）和G（357）存在4个独特变异，在HBGAs受体结合位点site I有一个独特变异（346）。表位预测发现，本研究获得的2024—2025年GⅡ.17变异株Romania_2021代表株Z119，与先前研究我国2014—2015年暴发流行株GZ41621（线性表位和构象表位各4个）相比分别增加了3个线性表位和2个构象表位。结论:我国2024—2025年检出的GⅡ.17变异株Romania_2021与先前流行的GⅡ.17变异株Kawasaki308_2015分属不同的亚群，潜在抗原表位和受体结合位点出现变异。对不同时期GⅡ.17变异株的进化、氨基酸位点等分析，可以为监测诺如病毒流行趋势、疫苗研发和优化精准诊断技术提供重要支撑。

abstractsObjective:To compare the genetic characteristic differences between two epidemic GⅡ.17 norovirus variants，Kawasaki308_2015（circulated during 2014—2023）and Romania_2021（2024—2025）.Methods:Nucleic acid extraction，genomic amplification and sequencing were performed on 40 positive samples of GⅡ.17 variant Romania_2021 of norovirus outbreak strains collected from Hainan，Beijing and Shenzhen during 2024-2025. Combined with the GⅡ.17 reference strains in the GenBank database and the GⅡ.17 variant Kawasaki308_2015 prevalent in China from 2014 to 2023，bioinformatics software such as BEAST were used to conduct phylogenetic analysis of the complete major capsid protein（VP1）region and polymerase region. Meanwhile，homology modeling was adopted to construct the three-dimensional structure and predict the epitopes via online websites.Results:Phylogenetic analysis revealed that the VP1 region of GⅡ.17 strains was divided into four phylogenetic clusters（Cluster A-D），among which Cluster C could be further classified into Subcluster C1 and Subcluster C2；the GⅡ.P17 strains were divided into three phylogenetic clusters（Cluster Ⅰ-Ⅲ）in the polymerase region；30 strains isolated from GⅡ.17 norovirus outbreaks in China between 2022 and 2023 formed a single cluster in the VP1 region with the strain GZ41621（GenBank accession number：KR020503），which caused outbreaks in China in 2014，and the Cluster D reference strain Kawasaki308_2015（GenBank accession number：LC037415），and they were assigned to Cluster I in the polymerase region. Forty strains from GⅡ.17 norovirus outbreaks in China during 2024—2025 were grouped into the same cluster as the Subcluster C2 reference strain Romania_2021（GenBank accession number：OP805362），and all of them belonged to Cluster Ⅲ in the polymerase region. Analysis of amino acid site variations in VP1 showed that a total of 36 amino acid sites had changed from 2013 to 2025. Compared with Subcluster C1 and Cluster D，the Subcluster C2，to which the 2024—2025 strains belonged，had four unique variations at antigenic sites A（296，368），D（395）and G（357），and 1 unique variation（346）at site I of the HBGA receptor-binding sites. Epitope prediction indicated that the representative strain Z119 of the GⅡ.17 variant Romania_2021 obtained in this study during 2024—2025 had 3 additional linear epitopes and 2 additional conformational epitopes compared with GZ41621（with 4 linear epitopes and 4 conformational epitopes respectively），the epidemic strain causing outbreaks in China during 2014—2015 reported in previous studies.Conclusion:Norovirus GⅡ.17 variant Romania_2021 detected in China during 2024—2025 belongs to a different subcluster from the previously prevalent GⅡ.17 variant Kawasaki308_2015，with variations observed in potential epitopes and receptor-binding sites. Analyzes of the evolution and amino acid sites of GⅡ.17 variants from different periods can provide important support for monitoring norovirus epidemic trends，developing vaccines，and optimizing precise diagnostic technologies.