Integrated chromosomal and plasmid sequence analyses reveal diverse modes of carbapenemase gene spread among Klebsiella pneumoniae.
Integrated chromosomal and plasmid sequence analyses reveal diverse modes of carbapenemase gene spread among Klebsiella pneumoniae.
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DOI：
10.1073/pnas.2003407117
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发表时间：
2020-10-06
影响因子：
11.1
通讯作者：
Aanensen DM
中科院分区：
文献类型：
--
作者：
David S;Cohen V;Reuter S;Sheppard AE;Giani T;Parkhill J;European Survey of Carbapenemase-Producing Enterobacteriaceae (EuSCAPE) Working Group;ESCMID Study Group for Epidemiological Markers (ESGEM);Rossolini GM;Feil EJ;Grundmann H;Aanensen DM
在许多临床上重要的细菌中，抗生素抗性基因主要携带在质粒上。它们可以在不同的菌株和物种之间水平传播。然而，目前的监测系统仅跟踪细菌的染色体谱系，导致对耐药性如何从单个医院内传播到跨国界的了解不完整。我们提出了一个综合的，高分辨率的分析染色体和质粒序列使用克雷伯氏肺炎杆菌在欧洲调查期间采样的分离株。我们发现，碳青霉烯酶基因，赋予耐药性的最后一线抗生素，已蔓延在不同的方式，包括通过一个质粒/多个谱系（blaOXA-48样），多个质粒/多个谱系（blaVIM，blaNDM），和多个质粒/一个谱系（blaKPC）。在基因组监测系统和新干预措施的设计中必须考虑这些不同的轨迹。细菌病原体的分子和基因组监测系统目前依赖于跟踪克隆进化谱系。相比之下，质粒通常被排除或用低分辨率技术分析，尽管质粒是许多关键病原体抗生素耐药基因的主要载体。在这里，我们使用了来自欧洲调查的肺炎克雷伯菌分离株（n = 1，717）的长和短读段序列数据的组合，对染色体和质粒多样性进行了整合的大陆范围研究。这揭示了碳青霉烯酶基因所使用的三种截然不同的传播模式，这些模式赋予了对最后一线碳青霉烯类的耐药性。首先，blaOXA-48样基因主要通过单一流行性pOXA-48样质粒传播，该质粒最近出现在临床环境中并迅速传播到许多谱系。第二，blaVIM和blaNDM基因通过许多不同质粒与许多谱系的瞬时关联而传播。第三，blaKPC基因主要通过与一个成功的克隆谱系（ST 258/512）的稳定关联来传播，但在该谱系内的不同质粒之间被动员。我们发现，这些质粒，其中包括pKpQIL样和IncX 3质粒，有一个长期的协会（和共同进化）的谱系，虽然频繁的重组和重排事件之间的复杂阵列的嵌合质粒携带blaKPC。总之，这些结果揭示了抗生素耐药基因在临床环境中的不同轨迹，总结为使用一个质粒/多个谱系，多个质粒/多个谱系，和多个质粒/一个谱系。我们的研究提供了一个框架，急需将质粒数据纳入基因组监测系统，这是更全面了解耐药传播的重要一步。
In many clinically important bacteria, antibiotic resistance genes are primarily carried on plasmids. These can spread horizontally between different strains and species. However, current surveillance systems track chromosomal lineages of bacteria only, leading to an incomplete understanding of how resistance spreads, from within an individual hospital to across country borders. We present an integrated, high-resolution analysis of both chromosome and plasmid sequences using Klebsiella pneumoniae isolates sampled during a European survey. We show that carbapenemase genes, which confer resistance to last-line antibiotics, have spread in diverse ways including via one plasmid/multiple lineages (blaOXA-48-like), multiple plasmids/multiple lineages (blaVIM, blaNDM), and multiple plasmids/one lineage (blaKPC). These different trajectories must be considered in genomic surveillance systems and the design of new interventions. Molecular and genomic surveillance systems for bacterial pathogens currently rely on tracking clonally evolving lineages. By contrast, plasmids are usually excluded or analyzed with low-resolution techniques, despite being the primary vectors of antibiotic resistance genes across many key pathogens. Here, we used a combination of long- and short-read sequence data of Klebsiella pneumoniae isolates (n = 1,717) from a European survey to perform an integrated, continent-wide study of chromosomal and plasmid diversity. This revealed three contrasting modes of dissemination used by carbapenemase genes, which confer resistance to last-line carbapenems. First, blaOXA-48-like genes have spread primarily via the single epidemic pOXA-48–like plasmid, which emerged recently in clinical settings and spread rapidly to numerous lineages. Second, blaVIM and blaNDM genes have spread via transient associations of many diverse plasmids with numerous lineages. Third, blaKPC genes have transmitted predominantly by stable association with one successful clonal lineage (ST258/512) yet have been mobilized among diverse plasmids within this lineage. We show that these plasmids, which include pKpQIL-like and IncX3 plasmids, have a long association (and are coevolving) with the lineage, although frequent recombination and rearrangement events between them have led to a complex array of mosaic plasmids carrying blaKPC. Taken altogether, these results reveal the diverse trajectories of antibiotic resistance genes in clinical settings, summarized as using one plasmid/multiple lineages, multiple plasmids/multiple lineages, and multiple plasmids/one lineage. Our study provides a framework for the much needed incorporation of plasmid data into genomic surveillance systems, an essential step toward a more comprehensive understanding of resistance spread.
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影响因子：
4.9
作者：
Leavitt, Azita;Chmelnitsky, Inna;Navon-Venezia, Shiri
通讯作者：
Navon-Venezia, Shiri
影响因子：
5.2
作者：
Adler, Amos;Khabra, Efrat;Carmeli, Yehuda
通讯作者：
Carmeli, Yehuda
影响因子：
15.9
作者：
Chen, Liang;Mathema, Barun;Chavda, Kalyan D.;DeLeo, Frank R.;Bonomo, Robert A.;Kreiswirth, Barry N.
通讯作者：
Kreiswirth, Barry N.
DOI：
10.1126/science.1182395
发表时间：
2010-01-22
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Harris SR;Feil EJ;Holden MT;Quail MA;Nickerson EK;Chantratita N;Gardete S;Tavares A;Day N;Lindsay JA;Edgeworth JD;de Lencastre H;Parkhill J;Peacock SJ;Bentley SD
通讯作者：
Bentley SD
使用 MinION 纳米孔测序仪解析肠杆菌科中的质粒结构：MinION 和 MinION/Illumina 混合数据组装方法的评估。
影响因子：
3.9
作者：
George S;Pankhurst L;Hubbard A;Votintseva A;Stoesser N;Sheppard AE;Mathers A;Norris R;Navickaite I;Eaton C;Iqbal Z;Crook DW;Phan HTT
通讯作者：
Phan HTT