Untargeted Metabolic Pathway Analysis as an Effective Strategy to Connect Various Nanoparticle Properties to Nanoparticle-Induced Ecotoxicity

Abstract

Elucidation of the relationships between nanoparticle properties and ecotoxicity is a fundamental issue for environmental applications and risk assessment of nanoparticles. However, effective strategies to connect the various properties of nanoparticles with their ecotoxicity remain largely unavailable. Herein, an untargeted metabolic pathway analysis was employed to investigate the environmental risk posed by 10 typical nanoparticles (AgNPs, CuNPs, FeNPs, ZnONPs, SiO2NPs, TiO2NPs, GO, GOQDs, SWCNTs, and C60) to rice (a staple food for half of the world's population). Downregulation of carbohydrate metabolism and upregulation of amino acid metabolism were the two dominant metabolic effects induced by all tested nanoparticles. Partial least-squares regression analysis indicated that a zerovalent metal and high specific surface area positively contributed to the downregulation of carbohydrate metabolism, indicating strong abiotic stress. In contrast, the carbon type, the presence of a spherical or sheet shape, and the absence of oxygen functional groups in the nanoparticles positively contributed to the upregulation of amino acid metabolism, indicating adaptation to abiotic stress. Moreover, network relationships among five properties of nanoparticles were established for these metabolic pathways. The results of the present study will aid in the understanding and prediction of environmental risks and in the design of environmentally friendly nanoparticles.