Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.
Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.
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DOI：
10.1371/journal.pgen.1004766
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发表时间：
2014-12
期刊：
影响因子：
4.5
通讯作者：
de la Cruz F
中科院分区：
文献类型：
--
作者：
Lanza VF;de Toro M;Garcillán-Barcia MP;Mora A;Blanco J;Coque TM;de la Cruz F
细菌全基因组序列（WGS）方法正在迅速取代传统的序列分析方法。许多细菌测序项目集中于移动组的变化，因为宏观进化事件，如获得或失去移动遗传元件，主要是质粒，在适应性进化中起着至关重要的作用。现有的WGS分析方案不能对质粒和主染色体之间的contigs进行排序，从而阻碍了质粒序列的完整分析。我们开发了一种方法（称为质粒星座网络或PLACNET），通过创建连续相互作用的网络来识别，可视化和分析WGS项目中的质粒，从而允许在WGS数据集中进行全面的质粒分析。该方法的工作流程基于三种类型的数据：组装信息（包括支架链接和覆盖率），与参考序列的比较以及质粒诊断序列特征。由此产生的网络由专家分析进行修剪，以消除混淆数据，并在基于细胞壁的图形表示中实现。为了验证PLACNET的敏感性和有效性，我们对大肠杆菌ST131细胞系的质粒进行了分析。ST131是一种全球传播的肠外致病性大肠杆菌（exic）克隆群，由不同的亚系组成，能够通过质粒获得和传播抗生素耐药性和毒力基因。结果表明，该谱系在进化过程中存在质粒通量，为质粒交换提供了广阔的空间。MOBF12/IncF质粒普遍存在，仅在ST131泛基因组中添加了350多个蛋白家族。在我们有限的10个ST131基因组样本中发现了近50%最常见的γ -变形菌质粒群，它们代表了主要的ST131亚谱系。质粒很难在WGS数据集中分析，因为获得的序列是碎片化的。我们开发了一种称为PLACNET的方法，它极大地促进了这种分析。作为一个例子，我们分析了大肠杆菌ST131的质粒，这是一个与人类尿路感染和败血症有关的exic克隆群。该克隆内的相关变异（例如，抗生素耐药性和毒力）通常是由质粒和其他可移动遗传元件的获取和丢失引起的。然而，我们对ST131质粒的了解仅限于少数抗生素抗性质粒和已知质粒群的复制子鉴定。PLACNET分析将ST131中可用于比较基因组学的测序质粒数量从11个增加到50个。ST131质粒看似巨大，约占γ -变形菌主要质粒群的50%。MOBF12/IncF质粒显然是相关遗传信息传播中最活跃的参与者。
Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages. Plasmids are difficult to analyze in WGS datasets, due to the fragmented nature of the obtained sequences. We developed a method, called PLACNET, which greatly facilitates this analysis. As an example, we analyzed the plasmidome of E. coli ST131, an ExPEC clonal group involved in human urinary tract infections and septicemia. Relevant variation within this clone (e.g., antibiotic resistance and virulence) is frequently caused by the acquisition and loss of plasmids and other mobile genetic elements. Nevertheless, our knowledge of the ST131 plasmidome is limited to a few antibiotic resistance plasmids and to identification of replicons from known plasmid groups. PLACNET analysis extends the number of sequenced plasmids in ST131, which can be used for comparative genomics, from 11 to 50. The ST131 plasmidome is seemingly huge, encompassing roughly 50% of the main plasmid groups of γ–proteobacteria. MOBF12/IncF plasmids are apparently the most active players in the dissemination of relevant genetic information.
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DOI：
10.1093/bioinformatics/btp347
发表时间：
2009-08-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Assefa S;Keane TM;Otto TD;Newbold C;Berriman M
通讯作者：
Berriman M
DOI：
10.1128/genomea.00988-13
发表时间：
2013-11-01
期刊：
GENOME ANNOUNCEMENTS
影响因子：
--
作者：
Andersen, Paal S.;Stegger, Marc;Price, Lance B.
通讯作者：
Price, Lance B.
影响因子：
4.9
作者：
Albrechtova, Katerina;Dolejska, Monika;Literak, Ivan
通讯作者：
Literak, Ivan
影响因子：
4.4
作者：
Brown, Celeste J.;Sen, Diya;Top, Eva M.
通讯作者：
Top, Eva M.
影响因子：
5.2
作者：
Baquero F;Tedim AP;Coque TM
通讯作者：
Coque TM