ZFinfer: A novel chemical-phenotype inference system for zebrafish for filling data gaps in environmental pollutant...

Zebrafish is an effective model organism for toxicological investigations due to their tiny size, quick reproduction, and conserved vertebrate biology. As environmental pollutants continue to increase, it becomes challenging to detect all chemical-related hazards using zebrafish models. In silico models can facilitate prioritizing chemicals prior to further experimental evaluations and providing potential underlying mechanisms. Chemical-phenotype inference system for zebrafish (ZFinfer), an enrichment analysis tool that can predict affected endpoints, was developed by integrating chemical-protein interaction data from the Search Tool for Interacting Chemicals (STITCH) database and gene-phenotype annotation data from the Zebrafish Information Network (ZFIN). Currently, 419,328 chemicals, 23,180 zebrafish proteins, and 3,104 phenotypes for zebrafish were curated and included in the system. ZFinfer has been validated using 777 ToxCast chemicals and 51 priority pollutants from the USEPA. The inference results demonstrated a sensitivity of 0.72 in critical morphological endpoints and a 93 % rediscovery rate for known toxicity records in the ECOTOX knowledgebase. Furthermore, the affected endpoints of 5,195 PFAS chemical exposures were inferred to fill data gaps. ZFinfer could be useful to prioritize chemicals that should be further evaluated and may be applicable in drug discovery and environmental chemical hazard prediction.