Details of Award
NERC Reference : NE/M01939X/1
Developing the Ecotoxicological - Predictive - Information - Connectivity Map (EPIC-map)
Fellowship Award
- Fellow:
- Dr P Antczak, University of Liverpool, Institute of Integrative Biology
- Grant held at:
- University of Liverpool, Institute of Integrative Biology
- Science Area:
- Atmospheric
- Earth
- Freshwater
- Marine
- Terrestrial
- Overall Classification:
- Panel C
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Global Change
- Natural Resource Management
- Pollution and Waste
- Science Topics:
- Omics
- Ecotoxicology
- Environmental risk assessment
- Bioinformatics
- Bioinform. for transcriptomics
- Biological database dev.
- Regulatory Networks (bioinf.)
- Abstract:
- A fundamental challenge within the environmental sciences is to establish the relationship between exposure to a chemical stressor, its molecular effect and the resulting adverse outcome. Particularly in risk assessment it is desired to identify or predict the adverse outcome before its manifestation. To this effect, computational (predictive) biology aims at developing techniques and methodologies to identify molecular pathways and physiological endpoints that can be directly linked to the adverse outcome. The Environmental Protection Agency (US EPA) following a White House Mandate in 2003 has placed computational predictive ecotoxicology at the centre of their R&D strategy and since then has been heavily investing into this technology. In the UK, the NERC has also recognised the importance of a computational approach to integrating multi-level complex datasets by establishing the Environmental Omics Synthesis (EOS) initiative and by including Systems Biology as one of the core research priorities. An essential part of the these programs is the adverse outcome pathway (AOP) framework, developed by G. Ankley et al at the US EPA.This was designed to link available knowledge on key events in a logical chain of events, from the molecular initiating event to organism molecular and physiology response and leading up to and including the adverse outcome. The resulting pathways could then be interrogated and used to support risk assessment and environmental monitoring. As the number of AOPs increase more robust predictions can be made on the effect a novel compound may have on a given organism. At the core of the AOPs is the reconstruction of molecular pathways leading to adverse outcomes. This requires extensive and highly complex datasets allowing for an unbiased approach. The underpinning computational tools required to develop an AOP from such data should therefore be able to 1) reconstruct the underlying regulatory network, 2) link the molecular response to the adverse outcome, 3) link structural features of compounds to molecular response, and 4) provide an interpretive output for AOP and hypothesis generation. Finally, the results developed from a set of known compounds forms the basis for deriving predictions on the potential molecular effect of novel chemicals on a given organism. This project proposal addresses this important need by developing the necessary computational framework in collaboration with the US EPA which directly integrates with their FY2015-17 research plan to develop and validate computational (eco)toxicology techniques to integrate and eventually transition away from traditional assays. To achieve its goals the project will start by integrating various publicly available databases with a purpose built standardized dataset of 200 compounds into a single database. Links between the genes and compounds will form the basis of the networking approach, while the standardized dataset will be used for identification purposes and predictive modelling. To interrogate the database the project will utilize a number of tools currently used by many computational biologists and in addition incorporate a set of predictive modelling approaches. This will allow any bench user to identify compounds linked to their molecular response, gene-gene-chemical-adverse outcome networks for AOP development and hypothetical prediction of molecular effect of yet untested compounds via chemical structure. This will provide a basis for risk assessors such as the US EPA, UK Environmental Agency or European Commission Joint Research Center and many other high level and academic organisations to develop hypotheses on the potential risk and effects a chemical may have on an organism.
- NERC Reference:
- NE/M01939X/1
- Grant Stage:
- Completed
- Scheme:
- Research Fellowship
- Grant Status:
- Closed
- Programme:
- Omics Fellowships
This fellowship award has a total value of £521,288
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DI - Staff | DA - Estate Costs | DI - T&S | DA - Other Directly Allocated |
|---|---|---|---|---|---|
| £76,659 | £148,553 | £208,278 | £57,909 | £23,360 | £6,530 |
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