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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.
Bibliographical noteFunding Information:
D.S.T.M. thanks the Sao Paulo Research Foundation (FAPESP) for the visiting research fellowship at GEES/UoB (Proc. No. 18/25140-3 ) and the National Council for Scientific and Technological Development (CNPq) for the research fellowship. I.L., D.S.T.M. and A.A. thank the European Commission Horizon 2020 programme for funding via the NanoCommons (Grant Agreement No. 731032), NanoSolveIT (Grant Agreement No. 814572) and CompSafeNano (Grant Agreement No. 101008099) projects. A.M.Z.M. extend gratitude to the CAPES-USP PrInt programme for the visiting scholarship at GEES/UoB. The authors are grateful to the National Institute for Complex Functional Materials (INCT-Inomat), the National System of Laboratories on Nanotechnologies (SisNANO/MCTI), and the FAPESP-UoB research grant (Proc. No. 19/07058-0 ).
© 2022 The Authors
ASJC Scopus subject areas
- Biomedical Engineering
- Materials Science(all)
- Pharmaceutical Science
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1/09/21 → 31/08/25