Project overview
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.
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.
