Nano-QTTR development for interspecies aquatic toxicity of silver nanoparticles between daphnia and fish

Limited studies of quantitative toxicity-toxicity relationship (QTTR) modeling have been conducted to predict interspecies toxicity of engineered nanomaterials (ENMs) between aquatic test species. A meta-analysis of 66 publications providing acute toxicity data of silver nanoparticles (AgNPs) to daphnia and fish was performed, and the toxicity data, physicochemical properties, and experimental conditions were collected and curated. Based on Euclidean distance (ED) grouping, a meaningful correlation of logarithmic lethal concentrations between daphnia and fish was derived for bare (R-bare(2) = 0.47) and coated AgNPs (R-coated(2) = 0.48) when a distance of 10 was applied. The correlation of coated AgNPs was improved (R-coated( )2= 0.55) by the inclusion of descriptors of the coating materials. The correlations were further improved by R-bare (2)= 0.57 and R-coated(2) = 0.81 after additionally considering particle size only, and by R-bare(2) = 0.59 and R-coated(2) = 0.92 after considering particle size and zeta potential simultaneously. The developed ED-based nano-QTTR model demonstrated that inclusion of the coating material descriptors and physicochemical properties improved the goodness-of-fit to predict interspecies aquatic toxicity of AgNPs between daphnia and fish. This study provides insight for future in silico research on QTTR model development in ENM toxicology.

Automated summary

Limited studies have been conducted to predict interspecies toxicity of engineered nanomaterials, particularly focusing on silver nanoparticles. A meta-analysis of acute toxicity data of AgNPs to daphnia and fish showed meaningful correlations when considering coating material descriptors and physicochemical properties. The inclusion of these factors improved the goodness-of-fit in predicting aquatic toxicity between species, providing insight for future in silico research.