Predictive Temporal Analysis of Functional Microbiomes in UK's Anerobic Digestion Reactors
Lead Research Organisation:
University of Warwick
Department Name: School of Life Sciences
Abstract
The scientific and practical importance of microbial communities (MCs) cannot be overstated. They underpin the biogeochemical cycles of the earth's soil, oceans, and the atmosphere, and provide eco-functions to plants, animals, and humans through the gut and skin. Despite the importance of MCs, our understanding of the structure-function relation and dynamics in these complex systems is highly limited. Contributing to this limitation is the difficulty of defining a clear function of natural MCs and conducting controlled, temporal experiments. In contrast, biotechnological applications of MCs provide excellent model systems that have clear functional parameters and offer controlled environments.
Anaerobic digestion (AD) is a key green-energy technology that makes use of complex MCs for the conversion of organic waste into methane. At the time of writing, there are more than 250 AD reactors with a total capacity of approx. 240,000 kWe in the UK that are fed with organic wastes and run in a controlled manner with regular recording of functional parameters. Here, we will develop the experimental and bioinformatics resources for collecting, sharing, and analyzing high- resolution temporal metagenomics data from MCs of AD reactors. The proposed approach will achieve the most comprehensive, highest-resolution temporal data on MCs available to date.
This data, combined with the developed analysis tools will greatly increase our understanding of the structure-function relation in AD microbiomes. Equally importantly, our approach holds the potential to transform the robustness and productivity of the AD technology in the UK. The same resources and insights will also be transferable to other MCs, such as the soils utilised in precision- farming, or guts of farming animals. We, thus, expect this demonstrative project to result in a self- sustaining, online knowledge base that will equally benefit UK bioeconomy and science.
As such, this proposal is in perfect alignment with the BBSRCs core aim to support enabling basic science. The project's focus fits squarely within BBSRC strategy, which identifies MCs as a priority area. Within the TRDF call, this proposal fits with the enabling of "new approaches to the analysis and interpretation of research data in the biological sciences", "new frameworks for the curation, sharing, and re-use/re-purposing of research data in the biological sciences", and "community approaches to the sharing of research data".
Anaerobic digestion (AD) is a key green-energy technology that makes use of complex MCs for the conversion of organic waste into methane. At the time of writing, there are more than 250 AD reactors with a total capacity of approx. 240,000 kWe in the UK that are fed with organic wastes and run in a controlled manner with regular recording of functional parameters. Here, we will develop the experimental and bioinformatics resources for collecting, sharing, and analyzing high- resolution temporal metagenomics data from MCs of AD reactors. The proposed approach will achieve the most comprehensive, highest-resolution temporal data on MCs available to date.
This data, combined with the developed analysis tools will greatly increase our understanding of the structure-function relation in AD microbiomes. Equally importantly, our approach holds the potential to transform the robustness and productivity of the AD technology in the UK. The same resources and insights will also be transferable to other MCs, such as the soils utilised in precision- farming, or guts of farming animals. We, thus, expect this demonstrative project to result in a self- sustaining, online knowledge base that will equally benefit UK bioeconomy and science.
As such, this proposal is in perfect alignment with the BBSRCs core aim to support enabling basic science. The project's focus fits squarely within BBSRC strategy, which identifies MCs as a priority area. Within the TRDF call, this proposal fits with the enabling of "new approaches to the analysis and interpretation of research data in the biological sciences", "new frameworks for the curation, sharing, and re-use/re-purposing of research data in the biological sciences", and "community approaches to the sharing of research data".
Technical Summary
Despite the importance of microbial communities (MCs), our understanding of the structure-function relation and dynamics in these complex systems is highly limited. Contributing to this limitation is the difficulty of defining a clear function of natural MCs and conducting controlled, temporal experiments. In contrast, biotechnological applications of MCs provide excellent model systems that have clear functional parameters and offer controlled environments.
The proposed research will focus on development of resources for collecting, sharing, and analyzing high- resolution temporal metagenomics data from MCs of AD reactors. In particular, we will achieve the most comprehensive, highest-resolution temporal data on MCs together with operational parameters from AD reactors. We will develop novel bioinformatics tools for analysing such data, and focusing on inferring both individual taxa functions and interactions from temporal microbiome data and then use these to develop predictive models of community dynamics. This models will focus on assembling genomes directly from metagenomics data, and predicting metabolic interaction partners and their metabolites based on temporal 16S rRNA data and metagenome assembled genomes.
We will also develop an operation model that will set a pathway towards converting this research platform into a self-sustaining enterprise that will monitor and analyse all AD reactors in the UK.
The proposed research will focus on development of resources for collecting, sharing, and analyzing high- resolution temporal metagenomics data from MCs of AD reactors. In particular, we will achieve the most comprehensive, highest-resolution temporal data on MCs together with operational parameters from AD reactors. We will develop novel bioinformatics tools for analysing such data, and focusing on inferring both individual taxa functions and interactions from temporal microbiome data and then use these to develop predictive models of community dynamics. This models will focus on assembling genomes directly from metagenomics data, and predicting metabolic interaction partners and their metabolites based on temporal 16S rRNA data and metagenome assembled genomes.
We will also develop an operation model that will set a pathway towards converting this research platform into a self-sustaining enterprise that will monitor and analyse all AD reactors in the UK.
Planned Impact
The proposed research will generate the most comprehensive, high time-resolution metagenomics data on functionally well-described microbial communities of Anaerobic Digestion (AD) reactors. This data, combined with the developed analysis tools will greatly increase our understanding of the structure-function relation in AD microbiomes. Equally importantly, our approach holds the potential to transform the robustness and productivity of the AD technology in the UK. The same resources and insights will also be transferable to other MCs, such as the soils utilised in precision- farming, or guts of farming animals. We, thus, expect this demonstrative project to result in a self- sustaining, online knowledge base that will equally benefit UK bioeconomy and science.
AD is identified as a promising green-energy biotechnology that converts organic waste into energy-rich methane gas. The recent report on low carbon energy by the Department of Energy and Climate Change (DECC), states that the government aims to achieve about 0.3-0.4 GW of power from Anaerobic Digestion by 2020. Achieving such a target will require increased uptake of AD by end-users and improved understanding of the AD process. By analysing the microbial communities underpinning AD, this research will help develop the UK AD industry. In particular, monitoring microbial communities from many AD reactors through time and developing bioinformatics tools to convert this data into predictive models of reactor performance and stability will help this research to increase the efficiency and robustness of AD. This science will thus impact the government's goal towards achieving a more energy secure and environmentally friendly future where we use and manage resources more efficiently, prevent waste, and recycle or convert under-utilised wastes into high value products. The latter goal is expected to particularly contribute to the growth of the UK's bioeconomy as stated in the "BIS Building A High Value Bioeconomy" report.
More broadly, the proposed research will contribute to the UK's ability to scientifically lead the emerging research field of engineering MCs, linking up academic strengths in bioinformatics, synthetic biology, engineering, and microbial ecology. The outcome of this proposal will be novel bioinformatics tools for predicting interacting species from complex, temporal MC data and identification of possible "early warning" indicators for loss of stability. The remit of these tools can be extended to the study of other well- defined MCs, such as the soils utilised in precision-farming, or guts of farming animals.
AD is identified as a promising green-energy biotechnology that converts organic waste into energy-rich methane gas. The recent report on low carbon energy by the Department of Energy and Climate Change (DECC), states that the government aims to achieve about 0.3-0.4 GW of power from Anaerobic Digestion by 2020. Achieving such a target will require increased uptake of AD by end-users and improved understanding of the AD process. By analysing the microbial communities underpinning AD, this research will help develop the UK AD industry. In particular, monitoring microbial communities from many AD reactors through time and developing bioinformatics tools to convert this data into predictive models of reactor performance and stability will help this research to increase the efficiency and robustness of AD. This science will thus impact the government's goal towards achieving a more energy secure and environmentally friendly future where we use and manage resources more efficiently, prevent waste, and recycle or convert under-utilised wastes into high value products. The latter goal is expected to particularly contribute to the growth of the UK's bioeconomy as stated in the "BIS Building A High Value Bioeconomy" report.
More broadly, the proposed research will contribute to the UK's ability to scientifically lead the emerging research field of engineering MCs, linking up academic strengths in bioinformatics, synthetic biology, engineering, and microbial ecology. The outcome of this proposal will be novel bioinformatics tools for predicting interacting species from complex, temporal MC data and identification of possible "early warning" indicators for loss of stability. The remit of these tools can be extended to the study of other well- defined MCs, such as the soils utilised in precision-farming, or guts of farming animals.
Publications
Benoit G
(2024)
High-quality metagenome assembly from long accurate reads with metaMDBG.
in Nature biotechnology
Raguideau S
(2021)
Novel microbial syntrophies identified by longitudinal metagenomics
Quince C
(2021)
STRONG: metagenomics strain resolution on assembly graphs.
in Genome biology
Title | sLola Project Film |
Description | A short film describing the sLola project 'Engineering Synthetic Microbial Communities for Biomethane Production'. Filming took place at all participating institutes in order to capture the work being done on AD minimal communities, community mixing and evolution, cold-adapted communities and reactor design. The film was tailored for use with a wide audience including future collaborators, funders, industry members, academics and students. The film is still at the editing stage, we will post the URL as soon as we can. |
Type Of Art | Film/Video/Animation |
Year Produced | 2018 |
Impact | None |
Description | 1. We have collected the largest temporal dataset from Anaerobic Digestion reactors to date, capturing both the dynamics of the microbial populations (16S sequencing and Metagenomic data) and operational data (pH, temperature, gas etc). 2. We have found the microbial communities to be highly dynamic and uniquely rich in structure compared with some other complex microbial communities. 3. We have found that you can use the temporal dynamics of the microbial population to predict Reactor performance and that this is more reliable than simply measuring the composition of the input feedstock. 4. We are developing mathematical models to explain and predict Reactor performance, focusing on combining the microbial population data with the Reactor operational data in order to understand how the microbial species interact and effect Reactor performance and importantly how to improve Reactor performance and stability. |
Exploitation Route | Improved understanding of the role of the microbial communities in the AD process will allow Industry users of AD technology to operate there Reactors to produce increased levels of methane (i.e increased performance) whilst maintaining Reactor stability. In addition, this project has created the most comprehensive, high-resolution temporal dataset on microbial communities to date, which will allow key open questions on microbial communities to be addressed and opportunities for exploitation identified. |
Sectors | Aerospace Defence and Marine Agriculture Food and Drink Energy Environment |
URL | http://anaerodynamics.com/ |
Description | BBSRC AD Network BIV |
Amount | £10,000 (GBP) |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Department | Anaerobic Digestion Network (AD Network) |
Sector | Academic/University |
Country | United Kingdom |
Start | 03/2017 |
End | 07/2017 |
Description | BBSRC AD Network POC |
Amount | £59,970 (GBP) |
Funding ID | POC2016012 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Department | Anaerobic Digestion Network (AD Network) |
Sector | Academic/University |
Country | United Kingdom |
Start | 08/2017 |
End | 02/2018 |
Description | BBSRC Impact Acceleration Account (IAA) |
Amount | £149,790 (GBP) |
Funding ID | BB/S506783/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 05/2018 |
End | 03/2021 |
Description | Interdisciplinary Discovery Science |
Amount | £42,065 (GBP) |
Organisation | Natural Environment Research Council |
Sector | Public |
Country | United Kingdom |
Start | 12/2022 |
End | 03/2023 |
Title | Additional file 2 of STRONG: metagenomics strain resolution on assembly graphs |
Description | Additional file 2 Genomes used in the synthetic communities (Additional file 1: Tables S1 and S2). |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_STRONG_metagenomics_strain... |
Title | Additional file 2 of STRONG: metagenomics strain resolution on assembly graphs |
Description | Additional file 2 Genomes used in the synthetic communities (Additional file 1: Tables S1 and S2). |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_STRONG_metagenomics_strain... |
Title | MetQy |
Description | MetQy is a R package to ease interfacing with the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to query metabolic functions of genes and genomes |
Type Of Material | Computer model/algorithm |
Year Produced | 2017 |
Provided To Others? | Yes |
Impact | None to report |
URL | https://academic.oup.com/bioinformatics/article/34/23/4134/5033387 |
Title | Micodymora |
Description | Micodymora is a python package allowing to simulate Ordinary Differential Equations (ODE) models of microbial population dynamics, while providing gas/liquid transfer and acide/base equilibria as additional features |
Type Of Material | Computer model/algorithm |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | None as yet |
URL | https://github.com/OSS-Lab/micodymora |
Title | UK AD Microbiome website |
Description | A project website has been created where all sequencing and metadata is stored and made available for public use: http://anaerodynamics.com. 2022 update, new website created: https://warwick.ac.uk/fac/sci/lifesci/research/osslab/research/past/anaerodynamicsproject |
Type Of Material | Database/Collection of data |
Year Produced | 2016 |
Provided To Others? | Yes |
Impact | None |
URL | http://anaerodynamics.com |
Description | SIAM |
Organisation | Soehngen Institute of Anaerobic Microbiology |
Country | Netherlands |
Sector | Private |
PI Contribution | The sLola research team plus other PDRAs from the Soyer group visited the Netherlands for a research exchange workshop with researchers from the SIAM research program. Research talks and poster presentations were given at the workshop as well as participation in round table discussions on Anaerobic digestion microbiology topics and potentials for future collaboration. |
Collaborator Contribution | The SIAM group hosted the workshop and also gave research talks and poster presentations and participated in round table discussions on Anaerobic digestion microbiology topics and potentials for future collaboration. |
Impact | None to report yet. |
Start Year | 2017 |
Title | Genephene |
Description | A machine learning based tool to infer species functional capabilities from their genomes |
Type Of Technology | Webtool/Application |
Year Produced | 2021 |
Impact | paper published: https://doi.org/10.1101/2021.07.05.451125 |
URL | https://warwick.ac.uk/fac/sci/lifesci/research/osslab/research/past/anaerodynamicsproject |
Title | Metahood |
Description | Pipeline for metagenomic analysis |
Type Of Technology | Webtool/Application |
Year Produced | 2021 |
Impact | Available to use on metagenomic dataset |
URL | https://warwick.ac.uk/fac/sci/lifesci/research/osslab/research/past/anaerodynamicsproject |
Description | AD Monitoring Project Stakeholder Meeting |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | An online meeting was held with key industrial participants of this project. Results of the project were clearly presented together with plans to publish the data. Also discussed were options for applying for future funding with industrial support. |
Year(s) Of Engagement Activity | 2021 |
Description | AD Science meets Industry 2016 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | We hosted a one-day workshop to bring together anaerobic digestion (AD) practitioners and scientists. The event consisted of both science and industry focussed talks, a session from an expert on AD and an open discussion forum. We also launched a new (BBSRC) project on monitoring AD microbiomes, with 10 companies coming forward to take part. In total 68 people attended the meeting, representing 26 companies and 13 academic institutions. |
Year(s) Of Engagement Activity | 2016 |
Description | Isaac Newton Institute Workshop on Microbial communities: current approaches and open challenges |
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 | This is a 4-month residential workshop we have organised at the Isaac Newton Institute. It aimed to assess the state of the microbial communities research field and resulted in significant impact on the development of the field. The 2022 follow on workshop took place over four days and included 20 invited and 25 contributed talks that covered broad and recent topics in microbial community research. |
Year(s) Of Engagement Activity | 2014,2015,2022 |
URL | https://www.newton.ac.uk/event/umc/ |
Description | Monitoring AD Microbiomes September 2017 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | We organised a 1-day workshop to disseminate the results from the AD Monitoring project 'BBSRC POC2016012' (Predictive Temporal Analysis of Functional Microbiomes in UK's Anerobic Digestion Reactors). The event was attended by 35 people, comprising a mix of academics and AD industry members, all with an interest in Anaerobic Digestion microbiology. Many of the industry attendees have been taking park in the AD monitoring project. As well as disseminating and discussing the findings from the AD monitoring project we presented our future plans for the project and made contact with new industry members who would be willing to participate in any future activities. |
Year(s) Of Engagement Activity | 2017 |
Description | Project featured in 'THE UK ANAEROBIC DIGESTION & BIORESOURCES TRADE ASSOCIATION'S Q UARTERly MAGAZINE' August 2018 |
Form Of Engagement Activity | A magazine, newsletter or online publication |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | This project was highlighted in the August 2018 newsletter by ADBA: http://adbioresources.org/uploads/adverts/Updated_FINAL_ISSUE_41_for_WEBSITE.pdf |
Year(s) Of Engagement Activity | 2018 |