State-Space-Based Framework for Predicting Microbial Interaction Variability in Wastewater Treatment Plants,Environmental Science & Technology

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State-Space-Based Framework for Predicting Microbial Interaction Variability in Wastewater Treatment Plants
Environmental Science & Technology ( IF 10.8 ) Pub Date : 2022-08-09 , DOI: 10.1021/acs.est.2c02844
Zhong Yu _{1,

2} , Yue Huang ₃ , Zhihao Gan _{1,

2} , Yabing Meng _{1,

2} , Fangang Meng _{1,

2}

Affiliation

Substantial attempts have been made to control microbial communities for environmental integrity, biosystem performance, and human health. However, it is difficult to manipulate microbial communities in practice due to the varying and nonlinear nature of interspecific interaction networks. Here, we develop a manifold-based framework to investigate the patterns of microbial interaction variability in wastewater treatment plants using manifold geometric properties and design a simple control strategy to manipulate the microbes in nonlinear communities. We validate our framework using the readily available and nonsequential microbiome profiles of wastewater treatment plants. Our results show that some microbes in the activated sludge and anammox communities display deterministic rival or cooperative relationships and constitute a stable subnetwork within the whole nonlinear community network. We further use a simulation to demonstrate that these microbes can be used to drive a microbe in a target direction regardless of the community dynamics. Overall, our framework can provide a time-efficient solution to select effective control inputs for reliable manipulation in varying microbial networks, opening up new possibilities across a range of biological fields, including wastewater treatment plants.

中文翻译：

用于预测废水处理厂中微生物相互作用变异性的基于状态空间的框架

为了环境完整性、生物系统性能和人类健康，已经进行了大量尝试来控制微生物群落。然而，由于种间相互作用网络的变化和非线性性质，在实践中很难操纵微生物群落。在这里，我们开发了一个基于流形的框架，以使用多种几何特性研究污水处理厂中微生物相互作用的变异模式，并设计一种简单的控制策略来操纵非线性群落中的微生物。我们使用废水处理厂现成的和非连续的微生物组谱来验证我们的框架。我们的研究结果表明，活性污泥和厌氧氨氧化群落中的一些微生物表现出确定性的竞争或合作关系，并在整个非线性群落网络中构成了一个稳定的子网络。我们进一步使用模拟来证明这些微生物可用于将微生物驱动到目标方向，而不管群落动态如何。总体而言，我们的框架可以提供一种省时的解决方案，以选择有效的控制输入，以在不同的微生物网络中进行可靠的操作，从而为包括废水处理厂在内的一系列生物领域开辟新的可能性。

更新日期：2022-08-09

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