Emerging investigators series: microbial communities in full-scale drinking water distribution systems - a meta-analysis
Emerging investigators series: microbial communities in full-scale drinking water distribution systems - a meta-analysis
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DOI：
10.1039/c6ew00030d
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发表时间：
2016-01-01
影响因子：
5
通讯作者：
Pinto, Ameet J.
中科院分区：
文献类型：
--
作者：
Bautista-de los Santos, Quyen M.;Schroeder, Joanna L.;Pinto, Ameet J.
在这项研究中，我们共同分析了所有可用的16 S rRNA基因测序研究，从散装饮用水样品在全面的饮用水分配系统。与预期一致，我们发现变形菌，特别是α-和β-变形菌，占主导地位的饮用水细菌群落的研究和存在/不存在或消毒剂残留类型的起源无关。无消毒剂残留系统中的微生物群落比保持消毒剂残留的系统中的微生物群落更多样化。此外，我们发现消毒剂类别组内细菌的平均相对丰度和发生率之间存在正相关。关键细菌属（如军团菌、分枝杆菌、假单胞菌）的相对丰度和发生率受是否存在消毒剂残留物和所用消毒剂残留物类型的影响。同样，我们发现广泛分布的细菌属，从生态和过程的角度来看（如硝化，捕食）的利益。通过估计潜在污染属对已发表的饮用水数据集的贡献，我们建议在饮用水研究中包括阴性对照的常规测序。最后，我们测试了使用16 S rRNA基因数据预测饮用水群落代谢潜力的实用性，并建议反对这种做法。虽然现有数据集的数据异质性是我们荟萃分析中的一个主要混杂因素，但我们建议，在这个时刻，标准化样品处理方案以解决这个问题的努力可能不是饮用水微生物生态学领域的最佳选择。相反，我们建议标准化数据和元数据报告，首先是公开所有测序数据，并共享样本，以支持未来在饮用水系统/研究中进行比较分析的努力。
In this study, we co-analyze all available 16S rRNA gene sequencing studies from bulk drinking water samples in full-scale drinking water distribution systems. Consistent with expectations, we find that Proteobacteria, particularly Alpha-and Betaproteobacteria, dominate drinking water bacterial communities irrespective of origin of study and presence/absence of or disinfectant residual type. Microbial communities in disinfectant residual free systems are more diverse than in those that maintain a disinfectant residual. Further, we find positive associations between mean relative abundance and occurrence of bacteria within a disinfectant category group. The relative abundance and occurrence of key bacterial genera (e.g. Legionella, Mycobacterium, Pseudomonas) is influenced by the presence/absence of a disinfectant residual and the type of disinfectant residual used. Similarly, we find widespread distribution of bacterial genera that are of interest from both an ecological and process perspectives (e.g. nitrification, predation). By estimating the contribution of potential contaminating genera to published drinking water datasets, we recommend that routine sequencing of negative controls be included in drinking water studies. Finally, we test the utility of predicting the metabolic potential of drinking water communities using 16S rRNA gene data and recommend against this practice. Though data heterogeneity across available datasets is a major confounding factor in our meta-analysis, we recommend that efforts to standardize sample processing protocols to address it may not be optimal for the drinking water microbial ecology field at this juncture. Rather, we recommend standardizing data and meta-data reporting, starting with making all sequencing data publicly available, and sample sharing as means of supporting future efforts for comparative analyses across drinking water systems/studies.