Literature DB >> 27370413

Editor's Highlight: Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A Web-Based Tool for Addressing the Challenges of Cross-Species Extrapolation of Chemical Toxicity.

Carlie A LaLone1, Daniel L Villeneuve2, David Lyons3, Henry W Helgen4, Serina L Robinson5, Joseph A Swintek6, Travis W Saari6, Gerald T Ankley6.   

Abstract

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; https://seqapass.epa.gov/seqapass/) application 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 while remaining amenable to variable degrees of protein characterization, in the context of available information about the chemical/protein interaction and the molecular target itself. To accommodate this flexibility in the analysis, 3 levels of evaluation were developed. 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 orthologs); the second level evaluates sequence similarity within selected functional domains (eg, ligand-binding domain); and the third level of analysis compares individual amino acid residue positions of importance for protein conformation and/or interaction with the chemical upon binding. Each level of the SeqAPASS analysis provides additional 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. Three case studies are described herein to demonstrate application of the SeqAPASS tool: the first 2 focused on predictions of pollinator susceptibility to molt-accelerating compounds and neonicotinoid insecticides, and the third 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. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

Entities:  

Keywords:  methoxyfenozide; neonicotinoids; pollinator susceptibility; sequence similarity; strobilurins; tebufenozide

Mesh:

Year:  2016        PMID: 27370413     DOI: 10.1093/toxsci/kfw119

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  34 in total

1.  Linking Mitochondrial Dysfunction to Organismal and Population Health in the Context of Environmental Pollutants: Progress and Considerations for Mitochondrial Adverse Outcome Pathways.

Authors:  David A Dreier; Danielle F Mello; Joel N Meyer; Christopher J Martyniuk
Journal:  Environ Toxicol Chem       Date:  2019-08       Impact factor: 3.742

Review 2.  Practical approaches to adverse outcome pathway development and weight-of-evidence evaluation as illustrated by ecotoxicological case studies.

Authors:  Kellie A Fay; Daniel L Villeneuve; Carlie A LaLone; You Song; Knut Erik Tollefsen; Gerald T Ankley
Journal:  Environ Toxicol Chem       Date:  2017-03-31       Impact factor: 3.742

3.  Toward sustainable environmental quality: Priority research questions for Europe.

Authors:  Paul J Van den Brink; Alistair B A Boxall; Lorraine Maltby; Bryan W Brooks; Murray A Rudd; Thomas Backhaus; David Spurgeon; Violaine Verougstraete; Charmaine Ajao; Gerald T Ankley; Sabine E Apitz; Kathryn Arnold; Tomas Brodin; Miguel Cañedo-Argüelles; Jennifer Chapman; Jone Corrales; Marie-Agnès Coutellec; Teresa F Fernandes; Jerker Fick; Alex T Ford; Gemma Giménez Papiol; Ksenia J Groh; Thomas H Hutchinson; Hank Kruger; Jussi V K Kukkonen; Stefania Loutseti; Stuart Marshall; Derek Muir; Manuel E Ortiz-Santaliestra; Kai B Paul; Andreu Rico; Ismael Rodea-Palomares; Jörg Römbke; Tomas Rydberg; Helmut Segner; Mathijs Smit; Cornelis A M van Gestel; Marco Vighi; Inge Werner; Elke I Zimmer; Joke van Wensem
Journal:  Environ Toxicol Chem       Date:  2018-07-19       Impact factor: 3.742

4.  In Silico Site-Directed Mutagenesis Informs Species-Specific Predictions of Chemical Susceptibility Derived From the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) Tool.

Authors:  Jon A Doering; Sehan Lee; Kurt Kristiansen; Linn Evenseth; Mace G Barron; Ingebrigt Sylte; Carlie A LaLone
Journal:  Toxicol Sci       Date:  2018-11-01       Impact factor: 4.849

Review 5.  In vitro to in vivo extrapolation for high throughput prioritization and decision making.

Authors:  Shannon M Bell; Xiaoqing Chang; John F Wambaugh; David G Allen; Mike Bartels; Kim L R Brouwer; Warren M Casey; Neepa Choksi; Stephen S Ferguson; Grazyna Fraczkiewicz; Annie M Jarabek; Alice Ke; Annie Lumen; Scott G Lynn; Alicia Paini; Paul S Price; Caroline Ring; Ted W Simon; Nisha S Sipes; Catherine S Sprankle; Judy Strickland; John Troutman; Barbara A Wetmore; Nicole C Kleinstreuer
Journal:  Toxicol In Vitro       Date:  2017-12-05       Impact factor: 3.500

6.  Sialic acid on avian erythrocytes.

Authors:  Mark D Jankowski; Scott R Glaberman; David B Kimball; Kirsten J Taylor-McCabe; Jeanne M Fair
Journal:  Comp Biochem Physiol B Biochem Mol Biol       Date:  2019-08-30       Impact factor: 2.231

7.  AOP-DB: A database resource for the exploration of Adverse Outcome Pathways through integrated association networks.

Authors:  Maureen E Pittman; Stephen W Edwards; Cataia Ives; Holly M Mortensen
Journal:  Toxicol Appl Pharmacol       Date:  2018-02-14       Impact factor: 4.219

8.  Mixed phylogenetic signal in fish toxicity data across chemical classes.

Authors:  Andrew Hylton; Ylenia Chiari; Isabella Capellini; Mace G Barron; Scott Glaberman
Journal:  Ecol Appl       Date:  2018-04       Impact factor: 4.657

Review 9.  Twenty years of transcriptomics, 17alpha-ethinylestradiol, and fish.

Authors:  Christopher J Martyniuk; April Feswick; Kelly R Munkittrick; David A Dreier; Nancy D Denslow
Journal:  Gen Comp Endocrinol       Date:  2019-11-13       Impact factor: 2.822

10.  Evidence for Cross Species Extrapolation of Mammalian-Based High-Throughput Screening Assay Results.

Authors:  Carlie A LaLone; Daniel L Villeneuve; Jon A Doering; Brett R Blackwell; Thomas R Transue; Cody W Simmons; Joe Swintek; Sigmund J Degitz; Antony J Williams; Gerald T Ankley
Journal:  Environ Sci Technol       Date:  2018-11-13       Impact factor: 9.028

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