Toward an Intensive Longitudinal Understanding of Activated Sludge Bacterial Assembly and Dynamics,Environmental Science & Technology

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Toward an Intensive Longitudinal Understanding of Activated Sludge Bacterial Assembly and Dynamics
Environmental Science & Technology ( IF 10.8 ) Pub Date : 2018-07-11 , DOI: 10.1021/acs.est.7b05579
Xiao-Tao Jiang ₁ , Lin Ye ₁ , Feng Ju ₁ , Yu-Lin Wang ₁ , Tong Zhang ₁

Affiliation

Temporal microbial community studies have broadened our knowledge of the dynamics and correlations among microbes in both natural and artificial engineering systems. Using activated sludge as a model system, we utilized the intensive longitudinal sampling method to identify overlooked diversity and the hidden dynamics of microbes, detect cross-associations among microbes after detrending, and reveal the central microbial dynamics during sludge bulking and foaming. We discovered that the accumulative alpha diversity in activated sludge sampled daily over 392 days could be as high as 14 000 OTUs, and that the bacterial community dynamics followed a gradual succession, drifting away from the initial observed day and displaying a significant time-dependent trend. Cross-associations among bacteria were modulated after removing potential spurious correlations based on autocorrelation in microbial time series. Moreover, clusters of bacteria displaying rapid turnover were discovered during the beginning, ongoing, and fading of sludge bulking and foaming, and their physicochemical parameters are resolved. These identified groups of bacteria and their related environmental factors could potentially supply clues to form hypotheses for treating operational problems, such as sludge bulking and foaming.

中文翻译：

深入了解活性污泥细菌的组装和动力学

时间性微生物群落研究拓宽了我们对自然和人工工程系统中微生物之间的动力学和相关性的认识。以活性污泥为模型系统，我们利用密集的纵向采样方法来识别被忽视的多样性和微生物的隐藏动态，去趋势后检测微生物之间的交叉关联，并揭示污泥膨胀和起泡沫过程中的中心微生物动态。我们发现，在392天之内每天采样的活性污泥中的累积α多样性可能高达14000 OTU，并且细菌群落动态随循序渐进，逐渐偏离了最初观察到的一天，并显示出明显的时间依赖性趋势。在去除微生物时间序列中基于自相关的潜在虚假相关性之后，可以调节细菌之间的交叉关联。此外，在污泥膨胀和起泡的开始，持续和褪色过程中发现了显示快速周转的细菌簇，并解析了它们的理化参数。这些确定的细菌群及其相关的环境因素可能会提供线索，以形成假设来处理操作问题，例如污泥膨胀和起泡。

更新日期：2018-07-12

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