Predicting the acclimatisation of microbial wastewater treatment communities as a function of the environment, random immigration, birth and death

对于一个污水处理厂来说，几十个，也许是几百个不同种类的细菌和原生动物必须聚集在一起，形成一个微生物群落，将废物转化为生物质，二氧化碳或其他一些希望危害较小的物质。一旦形成，微生物群落通常会经历适应过程，以适应环境条件的变化。这是所有生物治疗的一个基本方面，目前我们只能凭经验设计。没有先验的方法来确定反应堆需要多长时间才能获得或失去特定的适应性，从业者通常只有运气和判断。在这个建议中，我们的目标是开发预测acclimitation的数学模型。我们将进行一系列明确的实验，沿着全面的统计分析，以确定环境和随机效应在确定用于处理废水的微生物群落组成中的相对重要性。我们将集中在预测社区组成的变化，将发生在环境温度的系统性变化。这与厌氧系统特别相关，厌氧系统因其低碳足迹而对水工业有吸引力，但对低温非常敏感。已知存在冷适应产甲烷群落，并且原则上它们可用于接种冷适应厌氧反应器。然而，如果这样的反应堆在环境温度下运行，它将在温暖的月份失去其冷适应性。因此，一个理论框架，用于预测在反应器中的驯化率可以被非常广泛地使用。应用范围可能远远超出环境服务行业。同样的概念和数学方法将在所有开放的微生物系统中具有价值，无论它们是工程化的、医学的还是农业的，并且对于在合成生物学的新生领域中设想的工程生物体的应用可能是至关重要的。

For a wastewater treatment plant to work dozens, perhaps hundreds, of different species of bacteria and protozoa must come together to form a microbial community that will transform the waste into biomass, CO2 or some other, hopefully less harmful, substance. Once formed the microbial community will often go through processes of acclimatisation where it adapts to changes in environmental conditions. This is a fundamental aspect of all biological treatment that, at present we can only engineer empirically. There is no a priori method for determining how long it will take for a reactor to acquire or lose a particular adaptation and practitioners are often have little more to go on than luck and judgment. In this proposal we aim to develop mathematical model for predicting acclimitisation. We will conduct a definitive set of experiments along with a comprehensive statistical analysis to ascertain the relative importance of environmental and stochastic effects in determining the composition of microbial communities used to treat wastewater. We will concentrate on the predicting shifts in community composition that will occur in response to systematic changes in ambient temperature. This has particular relevance to anaerobic systems which are attractive to the water industry because of their low carbon foot print, but are very sensitive to low temperatures. Cold adapted methanogenic communities are known to exist and in principle they could be used to seed a cold adapted anaerobic reactor. However, if such a reactor was run at ambient temperatures it would lose its cold adaptation in warmer months. Thus a theoretical framework for predicting the rate of acclimatisation in a reactor could be used very widely. Applications could stretch far beyond the environmental services industry. The same conceptual and mathematical approach will have value in all open microbiological systems be they engineered, medical or agricultural and could be critical to the application of engineered organisms envisaged in the nascent field of synthetic biology.