Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Appl Environ Microbiol. 2011 Oct;77(20):7195-206. doi: 10.1128/AEM.00665-11. Epub 2011 Aug 26.
We synthesized population structure data from three studies that assessed the fine-scale distribution of Vibrionaceae among temporally and spatially distinct environmental categories in coastal seawater and animals. All studies used a dynamic model (AdaptML) to identify phylogenetically cohesive and ecologically distinct bacterial populations and their predicted habitats without relying on a predefined genetic cutoff or relationships to previously named species. Across the three studies, populations were highly overlapping, displaying similar phylogenetic characteristics (identity and diversity), and were predominantly congruent with taxonomic Vibrio species previously characterized as genotypic clusters by multilocus sequence analysis (MLSA). The environmental fidelity of these populations appears high, with 9 out of 12 reproducibly associating with the same predicted (micro)habitats when similar environmental categories were sampled. Overall, this meta-analysis provides information on the habitat predictability and structure of previously described species, demonstrating that MLSA-based taxonomy can, at least in some cases, serve to approximate ecologically cohesive populations.
我们综合了三项研究的种群结构数据,这些研究评估了在沿海海水和动物中不同时间和空间的环境类别中弧菌类的精细分布。所有研究都使用动态模型(AdaptML)来识别具有系统发育一致性和生态独特性的细菌种群及其预测的栖息地,而无需依赖预先定义的遗传截止值或与先前命名的物种的关系。在这三项研究中,种群高度重叠,显示出相似的系统发育特征(同一性和多样性),并且主要与先前通过多位点序列分析(MLSA)鉴定为基因型聚类的分类学弧菌物种一致。这些种群的环境保真度似乎很高,在类似环境类别采样时,12 个中有 9 个可重现地与相同的预测(微)栖息地相关联。总体而言,这项荟萃分析提供了有关先前描述的物种的栖息地可预测性和结构的信息,表明基于 MLSA 的分类法至少在某些情况下可以近似于具有生态一致性的种群。