摘要
目的使用多位点可变数目串联重复序列分析方法对四川省鼠疫耶尔森菌进行基因分型研究,为四川省鼠疫防控提供科学依据。方法选用14+12分级分型方案对四川省历年分离的132株鼠疫菌进行PCR扩增并计算重复拷贝数,通过Bio Numerics对各位点重复数进行聚类分析。结果四川省青海田鼠鼠疫自然疫源地菌株可被分为5个群9个基因型,再分型将占比最高的基因群分为3个亚群24个亚型;喜马拉雅旱獭鼠疫自然疫源地菌株可被分为4个群14个基因型,再分型将占比最高的基因群分为3个亚群18个亚型。喜马拉雅旱獭鼠疫自然疫源地中,甘孜州德格县鼠疫菌株VNTR与其他4处自然疫源地差异较大,但基因型相对保守。仅利用14个位点不能满足四川省鼠疫菌株分型需求,需结合12个位点再分型以提高分辨率或直接使用26个位点一并进行分析。结论本次实验所获得的MLVA型与四川省鼠疫菌株生态型以及自然疫源地的空间分布吻合较好,存在明显的地区聚集性,利用其构建的数据库将对该省未来的鼠疫菌株进化及溯源研究提供技术支持。
Objective The Multiple-Locus Variable-Number Tandem Repeat Analysis(MLVA)was used to study the genotyping of Yersinia pestis in Sichuan Province,which provides a scientific basis for the prevention and control of plague in Sichuan Province.Methods The genotypes of 132 Yersinia pestis strainsisolated in Sichuan Province were analyzed by14+12 VNTRs,and the data were processed with BioNumerics software.Results The strains of Microtus fuscusnatural plague foci were divided into 5 groups with 9 genotypes,and were subdivided into 3 subgroups with 24 subtypes.The strains ofMarmaotahimalayananatural plague foci were divided into 5 groups with14 genotypes,and were subdivided into 3 subgroups with 18 subtypes.Among the natural plague foci ofMarmaotahimalayana,the VNTRs of Dege County were quite different from the others,and the genotype was relatively conservative.It is necessary to use 14+12 VNTRswhen genotyping the strains in Sichuan Province.In addition,if only a limited number of strains need to be genotyped,it would be more convenient to determine the polymorphism of all 26 VNTRs simultaneously.Conclusion The results were consistent with traditional ecological classification,and the clustering analysis showed good relationship between the genotypes of Yersinia pestis and geographic location.The database constructed using MLVA will provide technical support for the mutation research and traceability of Yersinia pestis in Sichuan Province.
作者
李文博
祁腾
曾林子
廖虹瑜
梁莹
杨军
何树森
杨小蓉
周兴余
LI Wen-bo;QI Teng;ZENG Lin-zi;LIAO Hong-yu;LIANG Ying;YANG Jun;HE Shu-sen;YANG Xiao-rong;ZHOU Xing-yu(Sichuan Center for Disease Control and Prevention,Chengdu 610041,China)
出处
《中国地方病防治》
CAS
2021年第1期7-10,共4页
Chinese Journal of Control of Endemic Diseases
基金
国家科技重大专项(2018ZX10714002-003-008)
四川省卫健委课题(19PJ109)。
