Genotoxicity induced by metal oxide nanoparticles: a weight of evidence study and effect of particle surface and electronic properties

Abstract

The genetic toxicology of nanomaterials is a crucial toxicology issue and one of the least investigated topics. Substantially, the genotoxicity of metal oxide nanomaterials’ data is resulting from in vitro comet assay. Current contributions to the genotoxicity data assessed by the comet assay provide a case-by-case evaluation of different types of metal oxides. The existing inconsistency in the literature regarding the genotoxicity testing data requires intelligent assessment strategies, such as weight of evidence evaluation. Two main tasks were performed in the present study. First, the genotoxicity data from comet assay for 16 noncoated metal oxide nanomaterials with different core composition were collected. An evaluation criterion was applied to establish which of these individual lines of evidence were of sufficient quality and what weight could have been given to them in inferring genotoxic results. The collected data were surveyed on (1) minimum necessary characterization points for nanomaterials and (2) principals of correct comet assay testing for nanomaterials. Second, in this study the genotoxicity effect of metal oxide nanomaterials was investigated by quantitative nanostructure–activity relationship approach. A set of quantum-chemical descriptors was developed for all investigated metal oxide nanomaterials. A classification model based on decision tree was developed for the investigated dataset. Thus, three descriptors were identified as the most responsible factors for genotoxicity effect: heat of formation, molecular weight, and surface area of the oxide cluster based on the conductor-like screening model. Conclusively, the proposed genotoxicity assessment strategy is useful to prioritize the study of the nanomaterials for further risk assessment evaluations.

Keywords:

• Genotoxicity
• nanomaterials
• metal oxide
• comet
• quantitative structure–activity relationship

Acknowledgements

The authors thank the support from the NSF CREST Interdisciplinary Nanotoxicity Center NSF-CREST – grant #HRD-1547754; NSF-EPSCoR Award number: 362492–190200-01\NSFEPS-0903787. The authors also thank the Extreme Science and Engineering Discovery Environment (XSEDE) for the award allocations (TG-DMR110088 and CHE140005) and Mississippi Center for Supercomputer Research (Oxford, MS) for a generous allotment of computer time. BR gratefully acknowledges support from the North Dakota State University (Start Up grant) and support from National Science Foundation under ND EPSCoR Award #IIA-1355466 and the State of North Dakota. AGB is grateful for access to the initial literature analysis carried which was funded via the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement number 309837 (NanoPUZZLES project).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 309837 (NanoPUZZLES project) and the EC project PeptiCAPS (project reference: 686141).