Differentiation among spotted fever group rickettsiae species by analysis of restriction fragment length polymorphism of PCR-amplified DNA

Author:

Eremeeva M1,Yu X1,Raoult D1

Affiliation:

1. Unité des Rickettsies, Faculté de Médecine, Centre National de la Recherche Scientifique EP J0054, Marseille, France.

Abstract

Restriction fragment length polymorphism (RFLP) analysis of PCR-amplified genes was used to study spotted fever group (SFG) rickettsiae, extending the previous work of Regnery et al. (R.L. Regnery, C.L. Spruill, and B.D. Plikaytis, J. Bacteriol. 173:1576-1589, 1991). Twenty-six strains of SFG rickettsia were studied, including several recognized species which have never been studied (R. parkeri, R. helvetica, and R. japonica) as well as strains which are not currently classified. Two previously used primer pairs derived from the R. prowazekii citrate syntase gene and the R. rickettsii 190-kDa protein antigen gene were studied, as were primer pairs obtained from the R. rickettsii 120-kDa protein antigen gene. By using three amplifications and three enzyme digestions, it was possible to differentiate between almost all of the known SFG rickettsia species and to differentiate between several strains of the R. conorii complex. Two human pathogens, "R. africae" and the Israeli tick typhus rickettsia, were first separated by using BG-12 pair primer amplification and then RsaI restriction endonuclease digestion. The proposed simplified model of identification may be useful in studying the geographical distributions of SFG rickettsiae.

Publisher

American Society for Microbiology

Subject

Microbiology (medical)

Cited by 125 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3