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Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A web-based tool for addressing the challenges of cross-species extrapolation of chemical toxicity
Citation:
LaLone, C., Dan Villeneuve, H. Helgen, D. Lane, S. Walata, K. Nelson, S. Robinson, J. Swintek, AND G. Ankley. Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A web-based tool for addressing the challenges of cross-species extrapolation of chemical toxicity. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 153(2):228-245, (2016).
Impact/Purpose:
A manuscript that describes the development of a web-based tool, Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS), developed to simplify, streamline, and quantitatively facilitate evaluation of protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. Such analyses can support prioritization of chemicals for further evaluation, selection of appropriate species for testing, extrapolation of empirical toxicity data, and/or assessment of the cross-species relevance of adverse outcome pathways. Two case studies were developed and described to demonstrate application of the SeqAPASS tool; one focused on predictions of pollinator susceptibility to neonicotinoid insecticides, the second on evaluation of cross-species susceptibility to strobilurin fungicides. These analyses illustrate challenges in species extrapolation and demonstrate the broad utility of SeqAPASS for risk-based decision making and research.
Description:
Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitatively assess protein sequence/structural similarity across taxonomic groups as a means to predict relative intrinsic susceptibility. The intent of the tool is to allow for evaluation of any potential protein target, so it is amenable to variable degrees of protein characterization, depending on available information about the chemical/protein interaction and the molecular target itself. To allow for flexibility in the analysis, a layered strategy was adopted for the tool. The first level of the SeqAPASS analysis compares primary amino acid sequences to a query sequence, calculating a metric for sequence similarity (including detection of candidate orthologs), the second level evaluates sequence similarity within selected domains (e.g., ligand-binding domain, DNA binding domain), and the third level of analysis compares individual amino acid residue positions identified as being of importance for protein conformation and/or ligand binding upon chemical perturbation. Each level of the SeqAPASS analysis provides increasing evidence to apply toward rapid, screening-level assessments of probable cross species susceptibility. Such analyses can support prioritization of chemicals for further evaluation, selection of appropriate species for testing, extrapolation of empirical toxicity data, and/or assessment of the cross-species relevance of adverse outcome pathways. Two case studies were developed and described herein to demonstrate application of the SeqAPASS tool; one focused on predictions of pollinator susceptibility to neonicotinoid insecticides, the second on evaluation of cross-species susceptibility to strobilurin fungicides. These analyses illustrate challenges in species extrapolation and demonstrate the broad utility of SeqAPASS for risk-based decision making and research.
