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Phylogenetic diversity of drinking water bacteria in a distribution system simulator

机译:配电系统模拟器中饮用水细菌的系统发生多样性

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Aims: To characterize the composition of microbial populations in a distribution system simulator (DSS) by direct sequence analysis of 16S rDNA clone libraries. Methods and Results: Bacterial populations were examined in chlorinated distribution water and chloraminated DSS feed and discharge water. Bacterial strains isolated from DSS discharge water on R2A medium were identified using 16S rDNA sequence analysis. The majority of the bacteria identified were α-proteobacteria, ranging from approx. 34% in the DSS discharge water to 94% of the DSS isolates. Species richness estimators Chao1 and ACE (abundance-based coverage estimators) indicated that the chlorinated distribution water sample was representative of the total population diversity, while the chloraminated DSS feed water sample was dominated by Hyphomicrobium sp. sequences. The DSS discharge water contained the greatest diversity of α-, β-, γ-proteobacteria, with 36% of the sequences being operational taxonomic units (OTUs, sequences with >97.0% homology). Conclusions: This work demonstrated the dominance of -proteobacteria in distribution system water under two different disinfectant residuals. The shift from chlorine to monochloramine residual may have played a role in bacterial population dynamics. Significance and Impact of the Study: Accurate identification of bacteria present in treated drinking water is needed in order to better determine the risk of regrowth of potentially pathogenic organisms within distribution systems.
机译:目的:通过对16S rDNA克隆文库进行直接序列分析,表征分布系统模拟器(DSS)中微生物种群的组成。方法和结果:在氯化分布的水和氯化DSS进水和排水中对细菌种群进行了检查。使用16S rDNA序列分析鉴定了从R2A培养基上的DSS排放水中分离出的细菌菌株。鉴定出的大多数细菌是α-蛋白细菌,范围从大约1。 DSS中有34%的水排放到94%的DSS分离物中。物种丰富度估算器Chao1和ACE(基于丰度的覆盖率估算器)表明,氯化分布水样品代表了总种群多样性,而氯化DSS进水样品则以Hyphomicrobium sp占主导地位。序列。 DSS排放水中含有最大的α-,β-,γ-变形杆菌细菌,其中36%的序列为操作分类单位(OTU,同源性> 97.0%的序列)。结论:这项工作证明了在两种不同的消毒剂残留下,proteobacteria在配水系统水中的优势。从氯到一氯胺残留的转变可能在细菌种群动态中起作用。研究的意义和影响:为了更好地确定分配系统中潜在病原性生物的再生风险,需要准确识别经过处理的饮用水中存在的细菌。

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