Suppr超能文献

运用双位点序列分型方案对从希腊水生栖息地分离出的铜绿假单胞菌进行分子特征分析和系统发育分析。

Molecular Characterization and Phylogenetic Analysis of Pseudomonas aeruginosa Isolates Recovered from Greek Aquatic Habitats Implementing the Double-Locus Sequence Typing Scheme.

作者信息

Pappa Olga, Beloukas Apostolos, Vantarakis Apostolos, Mavridou Athena, Kefala Anastasia-Maria, Galanis Alex

机构信息

Central Public Health Laboratory, Hellenic Center for Disease Control and Prevention, Athens, Greece.

Department of Medical Laboratories Technological Educational Institute of Athens, Athens, Greece.

出版信息

Microb Ecol. 2017 Jul;74(1):78-88. doi: 10.1007/s00248-016-0920-8. Epub 2016 Dec 28.

Abstract

The recently described double-locus sequence typing (DLST) scheme implemented to deeply characterize the genetic profiles of 52 resistant environmental Pseudomonas aeruginosa isolates deriving from aquatic habitats of Greece. DLST scheme was able not only to assign an already known allelic profile to the majority of the isolates but also to recognize two new ones (ms217-190, ms217-191) with high discriminatory power. A third locus (oprD) was also used for the molecular typing, which has been found to be fundamental for the phylogenetic analysis of environmental isolates given the resulted increased discrimination between the isolates. Additionally, the circulation of acquired resistant mechanisms in the aquatic habitats according to their genetic profiles was proved to be more extent. Hereby, we suggest that the combination of the DLST to oprD typing can discriminate phenotypically and genetically related environmental P. aeruginosa isolates providing reliable phylogenetic analysis at a local level.

摘要

最近描述的双位点序列分型(DLST)方案用于深入表征来自希腊水生栖息地的52株耐药环境铜绿假单胞菌分离株的基因图谱。DLST方案不仅能够为大多数分离株指定已知的等位基因图谱,还能够识别出两个具有高鉴别力的新图谱(ms217 - 190,ms217 - 191)。还使用了第三个位点(oprD)进行分子分型,鉴于该位点在分离株之间产生了更高的鉴别力,已发现其对环境分离株的系统发育分析至关重要。此外,根据其基因图谱证明,获得性耐药机制在水生栖息地中的传播程度更高。因此,我们建议将DLST与oprD分型相结合,可以区分表型和遗传相关的环境铜绿假单胞菌分离株,在地方层面提供可靠的系统发育分析。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验