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Strategically selecting test species using the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool
Citation:
Doering, J., G. Ankley, B. Blackwell, K. Dean, C. LaLone, S. Poole, AND Dan Villeneuve. Strategically selecting test species using the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool. SETAC North America, Sacramento, CA, November 04 - 08, 2018.
Impact/Purpose:
This is a presentation showing how a computational tool developed by the US EPA, the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool, can be used to strategically select test species towards characterizing species differences in sensitivity to chemicals. Specifically, differences in sensitivity to chemicals can range by a few fold to more than a thousand-fold among species, but toxicity information used in risk assessment is based on only a few model test species which might not accurately represent all species. This presentation shows that SeqAPASS can be used to predict which species are most likely to differ in their sensitivity to chemicals and can be used to strategically select species for further investigation in order to more comprehensively and cost effectively characterize species differences in sensitivity to chemicals. This work supports aims of CSS project 17.01 towards cross-species extrapolation of adverse effects towards guiding more objective ecological risk assessments of native species of ecological and economic importance in the US.
Description:
Chemicals in the environment can affect the health of wildlife. However, different species can have vastly different sensitivities to these chemicals. Results of this study demonstrate a means of selecting test species in a strategic fashion in order to determine the extent of these differences in sensitivity. This information will help ensure regulators have accurate information for the protection of all species and therefore help prevent declines in populations of wildlife.Differences in species sensitivity to chemicals can range from a few fold to more than a hundred- or thousand-fold. However, most toxicity information used in risk assessments is based on a small number of model test species which might not represent the diversity in species sensitivities to chemicals This uncertainty presents a major challenge to accurate ecological risk assessments of chemicals. This uncertainty is particularly true for agonists of the peroxisome proliferator-activated receptor y (PPARy) and other contaminants of emerging concern (CECs) for which species-sensitivity information might only be available for one or a few species and therefore the range in sensitivities among species is unknown. To begin to address this challenge, the U.S. EPA developed the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS). The SeqAPASS tool can rapidly and computationally predicts species-specific chemical susceptibility across phylogenetically diverse species through evaluation of structural similarities and differences in the protein target. Therefore, the study presented here used the SeqAPASS tool to strategically select test species that were most likely to differ in sensitivity to PPARy agonists in order to inform future characterization of species differences in sensitivity to PPARy agonists. A total of 17 amino acid residues in the ligand binding domain (LBD) of PPARy that interact with chemicals were identified from the published literature, along with knowledge of amino acid differences that cause differences in binding affinity. These key amino acids were investigated among sequences of PPARy of 246 phylogenetically diverse species in the NCBI database using SeqAPASS. Of the investigated amino acids, 4 positions had differences across species that were predicted by SeqAPASS to potentially result in differences in binding of chemicals and therefore potentially result in differences in sensitivity among species. Based on this finding, 5 PPARy-types were proposed that could differ in their sensitivity to chemicals, namely Type 1 (mammal), Type 2 (bird, reptile, amphibian, ancient fish), Type 3 (most fish), Type 4 (salmonid), and type 5 (zebrafish). Xenopus (Type 2), fathead minnow (Type 3), rainbow trout (Type 4), and zebrafish (Type 5) were strategically selected for ongoing studies using in vitro and in vivo assays. This study demonstrates how SeqAPASS can be used to computationally predict species most likely to differ in sensitivity to chemicals for the strategic characterization of species differences in sensitivity. The content of this presentation neither constitute nor necessarily reflect US EPA policy.