Mapping Microbial Community Structure and Function in Enhanced Biological Phosphorus Systems

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Enhanced Biological Phosphorus Removal (EBPR) is a variation of the activated sludge technology that in addition to removal of organic matter using a microbial consortium, enacts phosphorus removal from the influent wastewater to prevent eutrophication of the receiving body. Like activated sludge, wastewater treatment plants employing EBPR are known to suffer from poor performance attributed to population imbalances of the functional microorganisms. An understanding of the root causes behind the deteriorated performance, and of the reliable corrective measures have thus far proven themselves elusive.Advances in culture-independent microbiological techniques and metagenomics have stimulated work towards the in situ characterisation of microbial communities in these systems in terms of their diversity, relative abundance of the representative individual phyla, as well as their respective functional ecology. Complementing this work are laboratory-scale studies utilising highly enriched bacterial cultures, as well as surveys of full-scale facilities which correlate the relative abundance of perceived core members of the microbial community of interest in tandem with physiochemical analyses to their respective function. In its current form however, the nature of the available information remains fragmented and, owing to the isolation in which it was produced, inconclusive - not to mention that with regards to understanding the reported instability of the technology, contradictory.In light of this, the overall aim of this PhD project is to develop and deploy statistical models with which to evaluate and unite elements of the (1a) composition of the microbial community, (2a) their respective ecological function and inter-phyla interactions and (3a) process design and operation.The component objectives of this project thus include but are not limited to: (1b) collecting and framing the existing pool of information into a unified working database; (2b) constructing a network model with which to represent, link and evaluate the assembled data; and (3b) investigating and assessing relevant statistical tools such as a self-learning Bayesian statistical models in order to make use of the available evidence to infer the nature of the relationships among different groups within EBPR microbial consortia, their relation to the process configuration and operational parameters and environmental conditions.The ambition of this project is to improve the holistic understanding of the microbial consortia relevant to EBPR. In particular, the potential impact of this project will (1c) enable the formulation of concrete strategies to cultivate the right communities that would ensure consistently satisfactory performance, and therefore compliance, of wastewater treatment facilities employing this technology, (2c) provide the framework for design optimisation of future EBPR processes and (3c) provide the tools to enable systematic identification of knowledge deficiencies, thereby providing a roadmap of key areas of future research.In a broader sense, the proposed tools to be developed in this project could find application in the exploitation of any biological system, answering questions such as: (1d) which are the key parameters to monitor in full-scale treatment and/or production facilities to ensure efficient performance, (2d) what is the (smallest) required sample size of this pool of data, (3d) how can one make use of the data already available, or (4d) how to define crowd-sourcing strategies for better informed decision making.This project will connect the field of water engineering to that of statistics & applied probability, two among the key growth areas as indicated by the EPSRC thematic research portfolio.