Details of Award
NERC Reference : NE/X000192/1
PROTECT: Predicting teleost fish species' sensitivity at molecular initiating events
Grant Award
- Principal Investigator:
- Professor NR Bury, University of Southampton, Sch of Ocean and Earth Science
- Co-Investigator:
- Dr M Khushi, Brunel University London, Computer Science
- Grant held at:
- University of Southampton, Sch of Ocean and Earth Science
- Science Area:
- Freshwater
- Marine
- Overall Classification:
- Panel C
- ENRIs:
- Biodiversity
- Environmental Risks and Hazards
- Pollution and Waste
- Science Topics:
- Cell culture systems
- Endocrine disruption
- Environmental risk assessment
- Fish
- Toxicity testing
- Ecotoxicology
- Pollution
- Ecotoxicity
- Bioinformatic Sequence anal.
- Bioinform. Function Prediction
- Genotype to Phenotype
- Bioinformatics
- Pollutants
- Environmental Informatics
- Predictive biology
- Research approaches
- Abstract:
- We are losing biodiversity at an alarming rate, so much so that we are now in a 6th mass extinction event. The reasons for this are varied and include habitat loss, climate change and chemical pollution. Restoration of habitats has the potential to increase biodiversity, but a positive outcome will be limited if chemical pollution is not tackled and remains at a level that is detrimental to wildlife. To guide policy on where to prioritise resources for beneficial pollution mitigation and habitat restoration strategies, it is necessary to identify those species that are the most sensitive to a pollutant and are under threat of extinction. Chemicals exert their toxicity via interacting with proteins, termed the molecular initiating event. If the organism is unable to respond to this toxic insult, then the individual's health may be impacted, leading to effects at a population level. Understanding the factors that determine how a chemical interacts at the molecular initiating event is a key component for predictive toxicology at the individual species level. Mutations can alter a protein's structure and function. We know that single mutations in human genes can alter protein function and lead to disease. With millions of species, thousands of proteins and thousands of chemicals released into the environment it is not surprising that there is a large range of species sensitivities to pollutants. Species sensitivity distribution curves confirm this and show these large differences can occur between closely related species. Species sensitivity is derived from toxicity tests. There is recognition that it is unethical to continue killing organisms, and there is a push to find alternative strategies such as in vitro methods (data derived without the use of animals) and in-silico approaches (the use of computer programmes) to generate the data necessary to set standards to protect all species, a novel approach called New Approach Methodology. Global initiatives to sequence the genomes of many species has the potential to revolutionise predictive toxicology without further toxicity testing. The genomic resource allows us to identify protein mutations between species. However, not all mutations alter protein function, some are neutral and thus additional functional data is required to identify if changes in proteins involved in the molecular initiating event account for an individual species sensitivity. The aim of the project is to develop a computer-based approach to predict individual species sensitivity by focusing on fish stress receptors, called the corticosteroid receptors which comprise the glucocorticoid and mineralocorticoid receptors. This is because: 1. There are assays available to assess receptor functionality and thus the sensitivity of the molecular initiating event to man-made chemicals. 2. There is evidence of differences in the sensitivity of the receptors to steroids in a few species, but not others. 3. There is a suite of computer-based tools to identity the key sequence motifs in receptors that confer sensitivity to a chemical. 4. Altered corticosteroid receptors' function is detrimental to health and man-made corticosteroids are a growing environmental concern. The project will generate functional information on the interaction of 9 natural and man-made steroids with 53 corticosteroid receptors proteins from 18 fish species representing 14 orders. This information will be used to classify the receptors into those that are hypo or hypersensitive to corticosteroids and interact with another class of steroids progestins. This functional data along with computational analysis will be used to identify common amino acid sequences that classify receptor type. The deliverable of the project will be the ability to identify fish species that are sensitive to man-made corticosteroids, other corticosteroid endocrine disrupting chemicals, progestins and stress based on receptor amino acid sequence alone.
- NERC Reference:
- NE/X000192/1
- Grant Stage:
- Awaiting Event/Action
- Scheme:
- Standard Grant FEC
- Grant Status:
- Active
- Programme:
- Standard Grant
This grant award has a total value of £287,640
FDAB - Financial Details (Award breakdown by headings)
| DI - Other Costs | Indirect - Indirect Costs | DA - Investigators | DA - Estate Costs | DI - Staff | DI - T&S |
|---|---|---|---|---|---|
| £74,717 | £89,553 | £23,216 | £20,161 | £75,944 | £4,049 |
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