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.

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.

[1]  M. Farman,et al.  Field Resistance to Strobilurin (Q(o)I) Fungicides in Pyricularia grisea Caused by Mutations in the Mitochondrial Cytochrome b Gene. , 2003, Phytopathology.

[2]  Daniel L Villeneuve,et al.  Cross‐species sensitivity to a novel androgen receptor agonist of potential environmental concern, spironolactone , 2013, Environmental toxicology and chemistry.

[3]  P. Traldi,et al.  Efficacy of imidacloprid on dogs and cats with natural infestations of fleas, with special emphasis on flea hypersensitivity. , 2000, Veterinary therapeutics : research in applied veterinary medicine.

[4]  J. Flexas,et al.  The effect of strobilurins on leaf gas exchange, water use efficiency and ABA content in grapevine under field conditions. , 2012, Journal of plant physiology.

[5]  Michele Magrane,et al.  UniProt Knowledgebase: a hub of integrated protein data , 2011, Database J. Biol. Databases Curation.

[6]  Heather A Carlson,et al.  Protein flexibility is an important component of structure-based drug discovery. , 2002, Current pharmaceutical design.

[7]  David S. Goodsell,et al.  AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility , 2009, J. Comput. Chem..

[8]  Andrew J. Crossthwaite,et al.  Mutation of a nicotinic acetylcholine receptor β subunit is associated with resistance to neonicotinoid insecticides in the aphid Myzus persicae , 2011, BMC Neuroscience.

[9]  Mick Hamer,et al.  The strobilurin fungicides. , 2002, Pest management science.

[10]  P. Rougé,et al.  Selectivity of diacylhydrazine insecticides to the predatory bug Orius laevigatus: in vivo and modelling/docking experiments. , 2012, Pest management science.

[11]  M. Rust Advances in the control of Ctenocephalides felis (cat flea) on cats and dogs. , 2005, Trends in parasitology.

[12]  David M. Reif,et al.  Update on EPA's ToxCast program: providing high throughput decision support tools for chemical risk management. , 2012, Chemical research in toxicology.

[13]  Daniel L Villeneuve,et al.  Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment , 2010, Environmental toxicology and chemistry.

[14]  Sharron McEldowney,et al.  Molecular docking: a potential tool to aid ecotoxicity testing in environmental risk assessment of pharmaceuticals. , 2013, Chemosphere.

[15]  B. Wallace,et al.  Association of neonicotinoid insensitivity with a conserved residue in the loop d binding region of the tick nicotinic acetylcholine receptor. , 2012, Biochemistry.

[16]  Dino Moras,et al.  Structural adaptability in the ligand-binding pocket of the ecdysone hormone receptor , 2003, Nature.

[17]  J. Casida,et al.  Structure and diversity of insect nicotinic acetylcholine receptors. , 2001, Pest management science.

[18]  D. Winkler,et al.  The X-ray Structure of a Hemipteran Ecdysone Receptor Ligand-binding Domain , 2005, Journal of Biological Chemistry.

[19]  D. Hollomon,et al.  Occurrence and molecular characterization of strobilurin resistance in cucumber powdery mildew and downy mildew. , 2001, Phytopathology.

[20]  J. Castresana,et al.  Cytochrome b phylogeny and the taxonomy of great apes and mammals. , 2001, Molecular biology and evolution.

[21]  J. Casida,et al.  Selective toxicity of neonicotinoids attributable to specificity of insect and mammalian nicotinic receptors. , 2003, Annual review of entomology.

[22]  H. Balba Review of strobilurin fungicide chemicals , 2007, Journal of environmental science and health. Part. B, Pesticides, food contaminants, and agricultural wastes.

[23]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[24]  C. R. Howell Effect of Seed Quality and Combination Fungicide-Trichoderma spp. Seed Treatments on Pre- and Postemergence Damping-Off in Cotton. , 2007, Phytopathology.

[25]  C. Stoeckert,et al.  OrthoMCL: identification of ortholog groups for eukaryotic genomes. , 2003, Genome research.

[26]  H. Kutsumi [Trends in parasitology]. , 1979, [Hokkaido igaku zasshi] The Hokkaido journal of medical science.

[27]  D. Sattelle,et al.  A hypothesis to account for the selective and diverse actions of neonicotinoid insecticides at their molecular targets, nicotinic acetylcholine receptors: catch and release in hydrogen bond networks , 2007, Invertebrate Neuroscience.

[28]  Dominique Zelus,et al.  Rapid divergence of the ecdysone receptor in Diptera and Lepidoptera suggests coevolution between ECR and USP-RXR. , 2003, Molecular biology and evolution.

[29]  L. Burgoon,et al.  Molecular target sequence similarity as a basis for species extrapolation to assess the ecological risk of chemicals with known modes of action. , 2013, Aquatic toxicology.

[30]  D. Sattelle,et al.  Role of loop D of the α7 nicotinic acetylcholine receptor in its interaction with the insecticide imidacloprid and related neonicotinoids , 2000, British journal of pharmacology.

[31]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[32]  Christian E. V. Storm,et al.  Automatic clustering of orthologs and in-paralogs from pairwise species comparisons. , 2001, Journal of molecular biology.

[33]  Christophe Dessimoz,et al.  Resolving the Ortholog Conjecture: Orthologs Tend to Be Weakly, but Significantly, More Similar in Function than Paralogs , 2012, PLoS Comput. Biol..

[34]  M. Pardal,et al.  Occurrence, fate and effects of azoxystrobin in aquatic ecosystems: a review. , 2013, Environment international.

[35]  Ming-guo Zhou,et al.  Effects of fungicides JS399-19, azoxystrobin, tebuconazloe, and carbendazim on the physiological and biochemical indices and grain yield of winter wheat , 2010 .

[36]  T. Sugiyama,et al.  Molecular Characterization and Diagnosis of QoI Resistance in Cucumber and Eggplant Fungal Pathogens. , 2007, Phytopathology.

[37]  D. Sattelle,et al.  Roles of loop C and the loop B–C interval of the nicotinic receptor α subunit in its selective interactions with imidacloprid in insects , 2004, Neuroscience Letters.

[38]  D. Bertrand,et al.  Nicotinic acetylcholine receptors and nicotinic cholinergic mechanisms of the central nervous system. , 2007, Annual review of pharmacology and toxicology.

[39]  D. Sattelle,et al.  Combined roles of loops C and D in the interactions of a neonicotinoid insecticide imidacloprid with the α4β2 nicotinic acetylcholine receptor , 2009, Neuropharmacology.

[40]  Andrew K. Jones,et al.  Diversity of insect nicotinic acetylcholine receptor subunits. , 2010, Advances in experimental medicine and biology.

[41]  G. R. Carlson,et al.  The chemical and biological properties of methoxyfenozide, a new insecticidal ecdysteroid agonist. , 2001, Pest management science.

[42]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[43]  Alma L. Burlingame,et al.  Atypical nicotinic agonist bound conformations conferring subtype selectivity , 2008, Proceedings of the National Academy of Sciences.

[44]  Richa Agarwala,et al.  COBALT: constraint-based alignment tool for multiple protein sequences , 2007, Bioinform..

[45]  Iris Antes,et al.  DynaDock: A new molecular dynamics‐based algorithm for protein–peptide docking including receptor flexibility , 2010, Proteins.

[46]  D. Sattelle,et al.  Combinatorial mutations in loops D and F strongly influence responses of the α7 nicotinic acetylcholine receptor to imidacloprid , 2003, Brain Research.

[47]  Carlie A. LaLone,et al.  Development of an adverse outcome pathway for acetylcholinesterase inhibition leading to acute mortality , 2014, Environmental toxicology and chemistry.

[48]  G. R. Carlson Tebufenozide: A Novel Caterpillar Control Agent with Unusually High Target Selectivity , 2000 .

[49]  D. Sattelle,et al.  Role in the Selectivity of Neonicotinoids of Insect-Specific Basic Residues in Loop D of the Nicotinic Acetylcholine Receptor Agonist Binding Site , 2006, Molecular Pharmacology.

[50]  H. Sierotzki,et al.  Cytochrome b gene structure and consequences for resistance to Qo inhibitor fungicides in plant pathogens. , 2006, Pest management science.

[51]  Rodrigo Lopez,et al.  Clustal W and Clustal X version 2.0 , 2007, Bioinform..

[52]  T. Ilg,et al.  Structure‐activity relationships of acetylcholine derivatives with Lucilia cuprina nicotinic acetylcholine receptor α1 and α2 subunits in chicken β2 subunit hybrid receptors in comparison with chicken nicotinic acetylcholine receptor α4/β2 , 2013, Insect molecular biology.

[53]  S. Thany Insect nicotinic acetylcholine receptors , 2010 .

[54]  D. Sattelle,et al.  Insect-vertebrate chimeric nicotinic acetylcholine receptors identify a region, loop B to the N-terminus of the Drosophila Dα2 subunit, which contributes to neonicotinoid sensitivity , 2005, Neuroscience Letters.

[55]  Ruben Abagyan,et al.  In Silico Analysis of the Conservation of Human Toxicity and Endocrine Disruption Targets in Aquatic Species , 2014, Environmental science & technology.

[56]  Andrew K. Jones,et al.  The nicotinic acetylcholine receptor gene family of the honey bee, Apis mellifera. , 2006, Genome research.

[57]  Finn Drabløs,et al.  Homology-based modelling of targets for rational drug design. , 2004, Mini reviews in medicinal chemistry.

[58]  Torsten Schwede,et al.  BIOINFORMATICS Bioinformatics Advance Access published November 12, 2005 The SWISS-MODEL Workspace: A web-based environment for protein structure homology modelling , 2022 .

[59]  Peter Jeschke,et al.  Neonicotinoids-from zero to hero in insecticide chemistry. , 2008, Pest management science.

[60]  R. Nauen,et al.  Applied aspects of neonicotinoid uses in crop protection. , 2008, Pest management science.

[61]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[62]  Narmada Thanki,et al.  CDD: a Conserved Domain Database for the functional annotation of proteins , 2010, Nucleic Acids Res..

[63]  D. Lipman,et al.  A genomic perspective on protein families. , 1997, Science.

[64]  K. Christoffersen,et al.  Clonal variation in physiological responses of Daphnia magna to the strobilurin fungicide azoxystrobin , 2009, Environmental toxicology and chemistry.