Daphnia magna and mixture toxicity with nanomaterials – Current status and perspectives in data-driven risk prediction. (April 2022) - Martinez, Diego Stéfani T.; Ellis, Laura-Jayne A.; Da Silva, Gabriela H.; Petry, Romana; Medeiros, Aline M.Z.; Davoudi, Hossein Hayat; Papadiamantis, Anastasios G.; Fazzio, Adalberto; Afantitis, Antreas; Melagraki, Georgia; Lynch, Iseult
Highlights: Chemicals are currently assessed singly with no consideration of potential for combined or synergistic effects. Daphnia is a key model organism to study the impacts of NMs in mixture toxicity. Lack of standardized assays makes comparison of studies on NMs mixture toxicity to Daphnia challenging. NMs-mixture toxicity requires harmonized experimental protocols and new ontologies. FAIR principles and data-driven nano-ecotoxicity modelling of complex mixtures is a promising path forward. Graphical Abstract: ga1 Abstract: The aquatic ecosystem is the final destination of most industrial residues and agrochemicals resulting in organisms being exposed to a complex mixture of contaminants. Nanomaterials (NMs) are being increasingly applied in many technologies and industrial sectors, so there is an increasing concern about the negative impacts of NMs in the environment after their interaction with co-contaminants. Consequently, mixture toxicology has been gaining attention in nanotoxicology recently. Usually, mixture toxicity or combined toxicity is estimated from the individual effects of the chemicals using the mathematical models of concentration addition (CA) or independent action (IA), however these models do not account for metabolic interactions between the chemicals, when they act in related metabolic pathways and molecular targets . As NMs unique physico-chemical properties make them highly reactive with a high surface area for adsorption, those models may not realistically estimate the toxicological effects of mixtures containing NMs. The co-exposition of NMs and other environmental contaminants (e.g., organic pollutants and heavy metals) may cause different mixture effects such as addition, synergism, antagonism, or even other complicated responses, including altered toxicokinetics/toxicodynamics, which vary according to the individual components properties, environmental exposure conditions, and the biological system. Therefore, the large number of factors that may influence the toxicity of a NM and contaminant mixture makes NMs mixture risk assessment a complex task. Daphnia magna are one of the most commonly used model species in nanotoxicology, including in mixture studies. It's advantages include short generation time, small body sizes, ability to produce large populations rapidly, coupled with its completely mapped genome which allows the use of a multitude of omics techniques to understand the stress responses of daphnids to NMs and chemicals. Here, we analyse the toxicological effects of NMs and contaminant mixtures using Daphnia as a model organism, and discuss future perspectives for NMs-mixtures risk assessment focusing on harmonization of methodologies and application of data-driven science in mixture ecotoxicology.