Bacterial assembly and temporal dynamics in activated sludge of a full-scale municipal wastewater treatment plant
Bacterial assembly and temporal dynamics in activated sludge of a full-scale municipal wastewater treatment plant
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DOI：
10.1038/ismej.2014.162
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发表时间：
2015-03-01
期刊：
影响因子：
11
通讯作者：
Zhang, Tong
中科院分区：
文献类型：
--
作者：
Ju, Feng;Zhang, Tong
了解环境和生物对微生物群落动态的影响在微生物生态学中受到了极大的关注。在这里，利用大的时间序列16S rRNA基因数据，我们表明，在活性污泥的环境重要的城市污水处理厂，5年的时间动态的细菌群落没有显着的季节性演替，但与确定性的组合相一致的分类相关性。生物相互作用是决定细菌群落组装的主要驱动因素，而环境条件（主要是污泥停留时间和无机氮）部分解释了系统发育和数量的差异，并间接影响细菌组装。我们展示了一种基于相关性的统计方法，将细菌关联网络与它们的分类学联系结合起来，以预测全社区的共现和共排除模式。结果表明，虽然分类学上密切相关的细菌往往是积极的共同出现（例如，出于合作关系），负共同排除相关性确定性地观察到分类学上不太相关的物种之间，可能涉及的作用，在确定细菌组装的竞争。总体而言，揭示种与种之间的正、负关系将有助于我们更好地理解未知物种所占据的生态位，并有助于预测它们在生态系统中的生物学功能。
Understanding environmental and biological influences on the dynamics of microbial communities has received great attention in microbial ecology. Here, utilizing large time-series 16S rRNA gene data, we show that in activated sludge of an environmentally important municipal wastewater treatment plant, 5-year temporal dynamics of bacterial community shows no significant seasonal succession, but is consistent with deterministic assemblage by taxonomic relatedness. Biological interactions are dominant drivers in determining the bacterial community assembly, whereas environmental conditions (mainly sludge retention time and inorganic nitrogen) partially explain phylogenetic and quantitative variances and indirectly influence bacterial assembly. We demonstrate a correlation-based statistical method to integrate bacterial association networks with their taxonomic affiliations to predict community-wide co-occurrence and co-exclusion patterns. The results show that although taxonomically closely related bacteria tend to positively co-occur (for example, out of a cooperative relationship), negative co-excluding correlations are deterministically observed between taxonomically less related species, probably implicating roles of competition in determining bacterial assembly. Overall, disclosures of the positive and negative species-species relations will improve our understanding of ecological niches occupied by unknown species and help to predict their biological functions in ecosystems.