Use of (Q)SAR genotoxicity predictions and fuzzy multicriteria decision-making for priority ranking of ethoxyquin transformation products

Ethoxyquin (EQ; 6-ethoxy-2,2,4-trimethyl-1,2-dihydroquinoline) has been used as an antioxidant in feed for pets and food-producing animals, including farmed fish such as Atlantic salmon. In Europe, the authorization for use of EQ as a feed additive was suspended, due to knowledge gaps concerning the presence and toxicity of EQ transformation products (TPs). Recent analytical studies focusing on the detection of EQ TPs in farmed Atlantic salmon feed and fillets reported the detection of a total of 27 EQ TPs, comprising both known and previously not described EQ TPs. We devised and applied an in silico workflow to rank these EQ TPs according to their genotoxic potential and their occurrence data in Atlantic salmon feed and fillet. Ames genotoxicity predictions were obtained applying a suite of five (quantitative) structure-activity relationship ((Q)SAR) tools, namely VEGA, TEST, LAZAR, Derek Nexus and Sarah Nexus. (Q)SAR Ames genotoxicity predictions were aggregated using fuzzy analytic hierarchy process (fAHP) multicriteria decision-making (MCDM). A priority ranking of EQ TPs was performed based on combining both fAHP ranked (Q)SAR predictions and analytical occurrence data. The applied workflow prioritized four newly identified EQ TPs for further investigation of genotoxicity. The fAHP-based prioritization strategy described here, can easily be applied to other toxicity endpoints and groups of chemicals for priority ranking of compounds of most concern for subsequent experimental and mechanistic toxicology analyses.

A prospective whole-mixture approach to assess risk of the food and chemical exposome

Many widely used chemicals result in ubiquitous human exposure from multiple sources, including diet. Legislation mainly deals with the toxicological evaluation of single substances owing to a methodological and conceptual lack of alternatives, and does so within defined silos subject to over 40 distinct regulations in the EU alone. Furthermore, much of the research and many of the initiatives concerned with the assessment and evaluation of chemical mixtures and their potential effects on human health rely on retrospective analysis. Here we propose an approach for the prospective identification, assessment and regulation of mixtures relevant to human health. We address two distinct aspects of toxicology-which chemicals actually do occur together, and how potential mixture-related health hazards can be predicted-with an adapted concept of the exposome and large-scale hazard screens. The proactive use of the likelihood of co-exposure, together with the new approach of methods-based testing, may be a timely and feasible way of identifying those substances and mixtures where hazards may have been overlooked and regulatory action is needed. Ideally, we would generate co-exposure patterns for specific consumer groups, depending on lifestyle and dietary habits, to assess the specific risk of identified mixtures.

Evaluation and improvement of QSAR predictions of skin sensitization for pesticides

In vivo skin sensitization assays have to be provided by applicants to the competent authorities in the European Union for the approval of active substances (AS) in pesticides. This study aimed to test the practicability of in silico predictions for AS by freely available (Q)SAR tools to evaluate their use as a time- and cost-effective alternative to animal testing in the context of the 3R concept. Predictions of skin sensitization for 48 selected sensitizing and non-sensitizing AS by the software programs CAESAR, Toxtree, OECD (Q)SAR Toolbox, CASE Ultra, Leadscope and SciQSAR were collected and compared. Different data evaluation methodologies (score definition, mean, weighted mean, threshold score definition) were applied to optimize the predictions. The calculation methods were internally cross-validated and further validated with an additional validation set of 80 AS. Although the presented calculation methodologies are not suitable as a stand-alone method, this study has shown weaknesses and strengths of some prominent (Q)SAR programs and diverse combinatorial options in the prediction of skin sensitization by pesticidal AS. The present study will help to foster discussions on in silico alternatives to animal testing in the pesticide area.

Characterization of aluminum, aluminum oxide and titanium dioxide nanomaterials using a combination of methods for particle surface and size analysis

The application of appropriate analytical techniques is essential for nanomaterial (NM) characterization. In this study, we compared different analytical techniques for NM analysis. Regarding possible adverse health effects, ionic and particulate NM effects have to be taken into account. As NMs behave quite differently in physiological media, special attention was paid to techniques which are able to determine the biosolubility and complexation behavior of NMs. Representative NMs of similar size were selected: aluminum (Al⁰) and aluminum oxide (Al₂O₃), to compare the behavior of metal and metal oxides. In addition, titanium dioxide (TiO₂) was investigated. Characterization techniques such as dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) were evaluated with respect to their suitability for fast characterization of nanoparticle dispersions regarding a particle's hydrodynamic diameter and size distribution. By application of inductively coupled plasma mass spectrometry in the single particle mode (SP-ICP-MS), individual nanoparticles were quantified and characterized regarding their size. SP-ICP-MS measurements were correlated with the information gained using other characterization techniques, i.e. transmission electron microscopy (TEM) and small angle X-ray scattering (SAXS). The particle surface as an important descriptor of NMs was analyzed by X-ray diffraction (XRD). NM impurities and their co-localization with biomolecules were determined by ion beam microscopy (IBM) and confocal Raman microscopy (CRM). We conclude advantages and disadvantages of the different techniques applied and suggest options for their complementation. Thus, this paper may serve as a practical guide to particle characterization techniques.

The application of appropriate analytical techniques is essential for nanomaterial (NM) characterization.

The nuclear aryl hydocarbon receptor is involved in regulation of DNA repair and cell survival following treatment with ionizing radiation

In the present study, we explored the role of the aryl hydrocarbon receptor (AhR) for γ-H2AX associated DNA repair in response to treatment with ionizing radiation. Ionizing radiation was able to stabilize AhR protein and to induce a nuclear translocation in a similar way as described for exposure to aromatic hydrocarbons. A comparable AhR protein stabilization was obtained by treatment with hydroxyl-nonenal-generated by radiation-induced lipid peroxidation. AhR knockdown resulted in significant radio-sensitization of both A549- and HaCaT cells. Under these conditions an increased amount of residual γ-H2AX foci and a delayed decline of γ-H2AX foci was observed. Knockdown of the co-activator ARNT, which is essential for transcriptional activation of AhR target genes, reduced AhR-dependent CYP1A expression in response to irradiation, but was without effect on the amount of residual γ-H2AX foci. Nuclear AhR was found in complex with γ-H2AX, DNA-PK, ATM and Lamin A. AhR and γ-H2AX form together nuclear foci, which disappear during DNA repair. Presence of nuclear AhR protein is associated with ATM activation and chromatin relaxation indicated by acetylation of histone H3. Taken together, we could show, that beyond the function as a transcription factor the nuclear AhR is involved in the regulation of DNA repair. Reduction of nuclear AhR inhibits DNA-double stand repair and radiosensitizes cells. First hints for its molecular mechanism suggest a role during ATM activation and chromatin relaxation, both essential for DNA repair.

Application of omics data in regulatory toxicology: report of an international BfR expert workshop

Advances in omics techniques and molecular toxicology are necessary to provide new perspectives for regulatory toxicology. By the application of modern molecular techniques, more mechanistic information should be gained to support standard toxicity studies and to contribute to a reduction and refinement of animal experiments required for certain regulatory purposes. The relevance and applicability of data obtained by omics methods to regulatory purposes such as grouping of chemicals, mode of action analysis or classification and labelling needs further improvement, defined validation and cautious expert judgment. Based on the results of an international expert workshop organized 2014 by the Federal Institute for Risk Assessment in Berlin, this paper is aimed to provide a critical overview of the regulatory relevance and reliability of omics methods, basic requirements on data quality and validation, as well as regulatory criteria to decide which effects observed by omics methods should be considered adverse or non-adverse. As a way forward, it was concluded that the inclusion of omics data can facilitate a more flexible approach for regulatory risk assessment and may help to reduce or refine animal testing.