Implementation of Zebrafish Ontologies for Toxicology Screening

Frontiers in Toxicology

Pamela Lein¹  Stephanie Padilla²  Bianca Yaghoobi²  Dante Perone³  Rafael Miñana Prieto⁴  Arantza Muriana⁵  Celia Quevedo⁶  David Reif⁷  Evelyn Stinckens⁸  Lisa Truong⁹  Colette Vom Berg⁹  J. C. Achenbach^1,10  Melissa A. Haendel^1,11  Anne E. Thessen^1,11  Nils Klüver^1,12  Skylar Marvel^1,13  Kristen Ryan^1,13  J. Erik Mylroie^1,14  Lucia Vergauwen^1,14  Antonio Planchart^1,14  Kimberly Hayward^1,14  Connor Leong^1,15  Jon Hamm^1,15  Jessica Legradi^1,16  Mitch Wilbanks^1,17  Sarah Könemann^1,17  Stephan Fischer^1,18 

[1] Health, Vrije Universiteit Amsterdam, Amsterdam, Netherlands;0Environmental Laboratory, US Army Engineer Research and Development Center, Vicksburg, MS, United States;1Center for Computational Toxicology and Exposure, Biomolecular and Computational Toxicology Division, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States;2Center for Human Health and the Environment, and Center for Environmental and Health Effects of PFAS, Biological Sciences, NC State University, Raleigh, NC, United States;3ZeClinics SL, Badalona, Spain;4Biobide USA, Cambridge, MA, United States;5Biobide, Donostia-San Sebastian, Spain;6Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Durham, NC, United States;7Zebrafishlab, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium;Aquatic and Crop Resource Development Research Center, National Research Council of Canada, Halifax, NS, Canada;Center for Health AI, University of Colorado Anschutz Medical Campus, Aurora, CO, United States;Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany;Department of Biological Sciences, Bioinformatics Research Center, North Carolina State University, Raleigh, NC, United States;Department of Environmental and Molecular Toxicology and the Sinnhuber Aquatic Research Laboratory, Oregon State University, Corvallis, OR, United States;Department of Molecular Biosciences, University of California, Davis, Davis, CA, United States;;Environment &Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology (Eawag), Dübendorf, Switzerland;aQuaTox-Solutions Ltd, Wallisellen, Switzerland;

关键词: phenotype;    ontology;    annotation;    Danio rerio;    zebrafish;    endpoint;   

DOI  :  10.3389/ftox.2022.817999

来源: DOAJ

【 摘 要 】

Toxicological evaluation of chemicals using early-life stage zebrafish (Danio rerio) involves the observation and recording of altered phenotypes. Substantial variability has been observed among researchers in phenotypes reported from similar studies, as well as a lack of consistent data annotation, indicating a need for both terminological and data harmonization. When examined from a data science perspective, many of these apparent differences can be parsed into the same or similar endpoints whose measurements differ only in time, methodology, or nomenclature. Ontological knowledge structures can be leveraged to integrate diverse data sets across terminologies, scales, and modalities. Building on this premise, the National Toxicology Program’s Systematic Evaluation of the Application of Zebrafish in Toxicology undertook a collaborative exercise to evaluate how the application of standardized phenotype terminology improved data consistency. To accomplish this, zebrafish researchers were asked to assess images of zebrafish larvae for morphological malformations in two surveys. In the first survey, researchers were asked to annotate observed malformations using their own terminology. In the second survey, researchers were asked to annotate the images from a list of terms and definitions from the Zebrafish Phenotype Ontology. Analysis of the results suggested that the use of ontology terms increased consistency and decreased ambiguity, but a larger study is needed to confirm. We conclude that utilizing a common data standard will not only reduce the heterogeneity of reported terms but increases agreement and repeatability between different laboratories. Thus, we advocate for the development of a zebrafish phenotype atlas to help laboratories create interoperable, computable data.

【 授权许可】

Unknown