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一种用于评估 Xenorhabdus 属(γ-变形菌)与昆虫病原斯氏线虫共生细菌的进化关系的多基因方法。

A multigene approach for assessing evolutionary relationships of Xenorhabdus spp. (gamma-Proteobacteria), the bacterial symbionts of entomopathogenic Steinernema nematodes.

机构信息

Department of Entomology, University of Arizona, Tucson, AZ 85721-0036, USA.

出版信息

J Invertebr Pathol. 2010 Jun;104(2):67-74. doi: 10.1016/j.jip.2010.01.005. Epub 2010 Jan 25.

Abstract

Xenorhabdus spp., are gram-negative bacterial symbionts of entomopathogenic nematodes in the genus Steinernema. A specialized and intimate relationship exists between nematode and bacteria, affecting many of their life history traits, such as nutrition, dispersal, host-finding, foraging and defense from biotic and abiotic factors. Xenorhabdus currently comprises more than 20 species isolated from Steinernema spp. with diverse host range, host foraging behavior, reproductive modes and environmental tolerance. Xenorhabdus phylogenies have historically been based on 16s rDNA sequence analyses, and only recently has data from housekeeping genes been employed. The prevalence of lateral gene transfer among bacteria calls for a wider perspective when considering their phylogeny. With the increasing number of Xenorhabdus species and strains, various perspectives need to be considered for investigating the evolutionary history of these nematode bacterial symbionts, In this study, we reconstruct the evolutionary histories of 30 species of Xenorhabdus considering the traditional 16s rDNA gene region as well as the housekeeping genes recA and serC. Datasets were analyzed individually and then combined, using a variety of phylogenetic criteria.

摘要

寡毛属菌(Xenorhabdus spp.)是斯氏线虫属(Steinernema)昆虫病原线虫的革兰氏阴性共生细菌。线虫和细菌之间存在着一种特殊而紧密的关系,影响着它们的许多生活史特征,如营养、传播、宿主寻找、觅食以及对生物和非生物因素的防御。寡毛属菌目前包含了 20 多种从斯氏线虫属中分离出来的物种,具有不同的宿主范围、宿主觅食行为、繁殖方式和环境耐受性。寡毛属菌的系统发育历史以前基于 16s rDNA 序列分析,直到最近才开始使用管家基因的数据。由于细菌之间存在广泛的基因横向转移,因此在考虑它们的系统发育时需要更广阔的视角。随着寡毛属菌物种和菌株数量的增加,需要从多个角度来研究这些线虫共生细菌的进化历史。在这项研究中,我们考虑了传统的 16s rDNA 基因区域以及管家基因 recA 和 serC,重建了 30 种寡毛属菌的进化历史。我们分别分析了数据集,然后使用多种系统发育标准对其进行了组合。

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