Mapping Microbial Community Structure and Function in Enhanced Biological Phosphorus Systems
Lead Research Organisation:
University of Bath
Department Name: Chemical Engineering
Abstract
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.
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.
Organisations
Publications
Nguyen Quang M
(2019)
Global Sensitivity Analysis of Metabolic Models for Phosphorus Accumulating Organisms in Enhanced Biological Phosphorus Removal.
in Frontiers in bioengineering and biotechnology
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/N509589/1 | 01/10/2016 | 30/09/2021 | |||
| 1789661 | Studentship | EP/N509589/1 | 01/10/2016 | 31/03/2020 | Minh Nguyen Quang |
| Description | Publication 1: Accepted for publication in Plos One Enhanced Biological Phosphorus Removal (EBPR) is a technology widely used in wastewater treatment to remove phosphorus and prevent eutrophication. Establishing its operating efficiency and stability is an active research field that has generated almost 3000 publications in the last 40 years. Due to its size, including over 119 review articles, it is an example of a field where it becomes increasingly difficult to manually recognize its key research contributions, especially for non-experts or newcomers. Therefore this work included two distinct but complementary objectives. First, to assemble for the first time a collection of bibliometric techniques into a framework for automating the article selection process when preparing a literature review. Second, to demonstrate it by applying it to the field of EBPR, to produce a high-level review. The research domain of EBPR evolved in two principal 'waves': (1) correlation of operational conditions with process performance, theoretical frameworks for mechanisms and the identity and competition between the responsible organisms; (2) EBPR process intensification, optimization and further justification for the technology. Some topics are in decline, e.g. early developments of theoretical frameworks, metabolism of organisms relevant to EBPR, EBPR combined with MBR, and a number of smaller clusters on the characterization of AS flocs and the attachment of Acinetobacter on natural zeolite. Other topics are emerging, e.g. VFA production from WAS for simultaneous N and P-removal, P-recovery for the circular economy, and aerobic granular sludge for better treatment efficiency and process stability. Although BNR from aquaculture wastes is also an emergent area of research, P-removal was a result of biologically-induced precipitation rather than EBPR. Topics which have had the highest impact include the genetic profiling of microbial communities in EBPR systems, the competition between PAO and GAO, VFA generation and P-recovery from WAS, as well as EBPR using aerobic granules. The framework enabled key contributions in each of the constituent topics to be highlighted in a way that may have otherwise been hidden by conventional citation-based ranking. Further, it reduced the burden of manual input compared to a traditional literature review. Hence, in an era of accelerated production of information and publications, this work contributed to the way that we are able to use computer-aided approaches to curate information and manage knowledge. Publication 2: In indepedent review in Frontiers in Biotechnology and Bioengineering This work conducted an uncertainty and global sensitivity analysis of a metabolic model describing the behaviour of PAO in alternating anaerobic and aerobic conditions for EBPR. The input uncertainty was characterised based on the relative abundance of data in the literature for each input parameter required to initialise the model. The input uncertainty was propagated to the output using the Monte Carlo method. The uncertainty of model predictions varied among the different output variables. Differences in the variance of the mean concentration profiles indicated that concentrations of phosphate in the bulk liquid phase and biomass were the most uncertain, whereas the concentrations of intra-cellular PHV, poly-P and PH2MV were the least uncertain. The global sensitivity analysis was conducted using standard regression coefficients (SRC) and Sobol sensitivity indices. The analysis comprised a total of 39 input parameters: 12 metabolic parameters, 10 kinetic parameters, 6 Arrhenius temperature coefficients and 9 initial conditions, two of which included the prevailing conditions in the EBPR system (T and pH). SRC were found to be an inadequate sensitivity measure for this model due to the low degree of linearity between the input parameters and output variables. Consequently, reduction of model complexity by linearisation of its parts is unfeasible in the general case, and limited to particular subsets of output variables for more specific scenarios with well-defined initial conditions. Differences between first and total-order Sobol indices indicated that the uncertainties in model predictions were mainly due to interaction effects between combinations of input parameters rather than uncertainties in individual ones. The contribution of each of the input parameters on the uncertainty of model predictions varied with the output variable in question. For the prediction of liquid phase concentrations as well as intra-cellular fractions of glycogen and poly-phosphate, the vast majority of the uncertainty could be attributed to a smaller subset of input parameters (64% on average). For the prediction of intra-cellular PHA constituents, the contribution was nearly uniformly distributed among all of the input parameters, indicating a high-degree of interaction. Although the contribution of uncertainty in model predictions could not be isolated to any particular group of inputs (metabolic parameters, kinetic parameters, temperature coefficients, process conditions), the effect of initial fractions of PHV, PH2MV and glycogen ranked consistently among the most influential factors, both in terms of direct as well as total effect, suggesting that the value of these parameters should be carefully measured when applying EBPR metabolic models. This work contributed a step towards more complete understanding of the uncertainties associated with EBPR metabolic model predictions, and how to address these uncertainties on an individual basis given knowledge of the corresponding input uncertainty. Possible approaches and pre-requisite conditions with which to simplify metabolic models for PAO, both structurally via linearisation, as well as by reduction in the number of variables required to initialise the them were illustrated based on the results of the sensitivity analyses. This will translate to improved process monitoring control in the context of facilitating the integration of metabolic models within the wider ASM framework, as well as more informed decision-making in model building and fundamental investigations of organisms relevant to EBPR systems. |
| Exploitation Route | We provided insights into the evolution of a multi-disciplinary area of research, detected its emerging areas and outlined the key events throughout its development. With increasing rates of scientific publication and information dissemination, we contributed a step in the direction of systematic and automated curation of knowledge repositories. As the programs and scripts used to carry-out the work were included in the supplementary materials, other researchers may apply the techniques developed or described in our publication to analyse databases of interest without the need for specialist knowledge in the field of bilbliometrics. We have also assessed the uncertainty associated with input parameters to metabolic models for the study of competition between bacterial species relevant to the operation of EBPR systems, as well as how the input uncertainty affects the quality of model predictions. This will be of use to both researchers as well as practitioners to use the models for more accurate process design. Directions for model simplification were outlined, so as to make the models more practical within the context of process monitoring and control, where real-time predictions will be required at minimal computational cost. Finally, our analysis included a compilation of all input parameter ranges reported in the scientific literature into a centralised dataset, which will aid in future research into the fundamental understanding of EBPR kinetic processes. |
| Sectors | Environment |
| Title | Compartmentalised Metabolic Model for organisms relevant to EBPR |
| Description | Mathematical models for the anaerobic, aerobic and anoxic metabolisms of Candidatus Accumulibacter phosphatis, Candidatus Competibacter phosphatis and Defluvicoccus-related organisms, combining previously observed reaction mechanisms under the availability of different electron acceptors, including sequential use of substrates in Accumulibacter during cell maintenance but excluding alternative metabolic pathways. Model was implemented in Python version 3. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | Allows simulation of microbial competition subject to multi-parametric perturbations, including different temperatures, organic loading rates, carbon source composition, pH, etc. Model was implemented using the approach of object oriented programming (OOP), such that simulations can be initialised with specific organisms and under specific conditions (anaerobic/aerobic/anoxic phases) with no adjustment to the underlying code. |
| Title | Compilation of Metabolic and Stoichiometric parameters for Phosphorus Accumulating and Glycogen Accumulating Organisms in EBPR |
| Description | Database of experimentally measured or otherwise estimated values for parameters required to initialise metabolic models for phosphorus accumulating organisms (PAO) and glycogen accumulating organisms (GAO) in EBPR, including kinetic parameters (half-saturation constants, maximum rates of reaction), Arrhenius temperature coefficients, metabolic parameters (efficiency of oxidative phosphorylation, cell maintenance coefficients) and stoichiometry. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | Typically, any study involving the use of metabolic models to predict the behaviour of organisms relevant to EBPR requires a lab-scale reactor(s) enriched with the organism(s) of interest so that the parameters required to initialise the models may be obtained (via calibration to match batch test concentration profiles). This compilation of data from all previous experimental studies in the literature systematic comparison and analysis of different metabolic models to test EBPR performance under a variety of operating conditions, rather than those specific to any given experiment. |
| URL | https://www.frontiersin.org/articles/10.3389/fbioe.2019.00234/full#supplementary-material |
| Description | 10th IWA Symposium on Modelling and Integrated Assessment |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | An forum to present, discuss and exchange methodologies with respect to a variety of water-related problems, within an interdisciplinary framework that relies heavily on the use of different types of models, with a particular focus on systems modelling and control, decision support, life cycle analysis and integrated assessment. |
| Year(s) Of Engagement Activity | 2019 |
| URL | https://www.watermatex2019.org/ |
| Description | 18th UK Young Water Professionals Conference |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Multi-day international conference. Delivered flash presentation, guided a group discussion on the contents and attended a poster session. Took on various duties as part of the organising committee, e.g. directing attendees to the various sessions, guided and chaired group discussions, led activites at a workshop, took notes on the various events and relayed the summaries of keynote presentations at the closing ceremony. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://iwa-network.org/events/18th-uk-iwa-young-water-professional-conference-a-water-world-without... |
| Description | 1st Symposium on Microbiological Methods for Waste & Water Resource Recovery |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | A two day international conference on a specialist topic, bringing together engineers and microbiologists with the aim of integrating and/or standardising microbiological methods into environmental bio-process design and operation. Delivered a flash presentation. Networked with other attendees and looked for opportunities for collaborating on sharing of data relevant to my work and applying the outcomes of this research project outside of academia. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://pure.tudelft.nl/portal/en/activities/1st-symposium-on-microbiological-methods-for-waste-and-... |
| Description | GW4 Water Security Alliance Workshop. |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Postgraduate students |
| Results and Impact | All-day conference between water research centres from the universities of Bath, Bristol, Cardiff and Exeter. The event brought together researchers from a variety of disciplines, working to address topics spanning climate change, water scarcity and resource management, flood risk and policy, to highlight key challenges and explore opportunities for collaboration through keynote presentations, group discussions and workshops. |
| Year(s) Of Engagement Activity | 2016 |
| Description | UK-SEA Research Engagement Day |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Postgraduate students |
| Results and Impact | Gave a 10 minute presentation of the research project at a networking event for UK and South East Asian early-career researchers, comprising approximately 20 attendees from a variety of academic disciplines from research institutions all across the UK. Individuals presentations were followed-up with discussions to explore ways to combine different research methodologies to address different facets of the problems, namely how social science may be used, complement and implement policy conclusions derived from mathematical modelling of technical problems. |
| Year(s) Of Engagement Activity | 2019 |