A tripartite mode of action approach for investigating the impact of aneugens on tubulin polymerization

Mode-of-action analysis of the effects induced by nicotine in the in vitro micronucleus assay

Nicotine's genotoxic potential has been extensively studied in vitro. While the results of mammalian cell-based studies have inferred that it can potentially damage chromosomes, in general and with few exceptions, adverse DNA effects have been observed primarily at supraphysiological concentrations in nonregulatory assays that provide little information on its mode-of-action (MoA). In this study, a modern-day regulatory genotoxicity assessment was conducted using a flow cytometry-based in vitro micronucleus (MN) assay, Good Laboratory Practice study conditions, Chinese hamster ovary cells of known provenance, and acceptance/evaluation criteria from the current OECD Test Guideline 487. Nicotine concentrations up to 3.95 mM had no effect on background levels of DNA damage; however, concentrations above the point-of-departure range of 3.94-4.54 mM induced increases in MN and hypodiploid nuclei, indicating a possible aneugenicity hazard. Follow-up experiments designed to elucidate nicotine's MoA revealed cellular vacuolization, accompanying distortions in microtubules, inhibition of tubulin polymerization, centromere-positive DNA, and multinucleate cells at MN-inducing concentrations. Vacuoles likely originated from acidic cellular compartments (e.g., lysosomes). Remarkably, genotoxicity was suppressed by chemicals that raised the luminal pH of these organelles. Other endpoints (e.g., changes in phosphorylated histones) measured in the study cast doubt on the biological relevance of this apparent genotoxicity. In addition, three major nicotine metabolites, including cotinine, had no MN effects but nornicotine induced a nicotine-like profile. It is possible that nicotine's lysosomotropic properties drive the genotoxicity observed in vitro; however, the potency and mechanistic insights revealed here indicate that it is likely of minimal physiological relevance for nicotine consumers. Environ. Mol. Mutagen. 2019. © 2019 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.

Aneugen Molecular Mechanism Assay: Proof-of-Concept With 27 Reference Chemicals

A tiered bioassay and data analysis scheme is described for elucidating the most common molecular targets responsible for chemical-induced in vitro aneugenicity: tubulin destabilization, tubulin stabilization, and inhibition of mitotic kinase(s). To evaluate this strategy, TK6 cells were first exposed to each of 27 presumed aneugens over a range of concentrations. After 4 and 24 h of treatment, γH2AX, p53, phospho-histone H3 (p-H3), and polyploidization biomarkers were evaluated using the MultiFlow DNA Damage Assay Kit. The assay identified 27 of 27 chemicals as genotoxic, with 25 exhibiting aneugenic signatures, 1 aneugenic and clastogenic, and 1 clastogenic. Subsequently, a newly described follow-up assay was employed to investigate the aneugenic agents' molecular targets. For these experiments, TK6 cells were exposed to each of 26 chemicals in the presence of 488 Taxol. After 4 h, cells were lysed and the liberated nuclei and mitotic chromosomes were stained with a nucleic acid dye and labeled with fluorescent antibodies against p-H3 and Ki-67. Flow cytometric analyses revealed that alterations to 488 Taxol-associated fluorescence were only observed with tubulin binders-increases in the case of tubulin stabilizers, decreases with destabilizers. Mitotic kinase inhibitors with known Aurora kinase B inhibiting activity were the only aneugens that dramatically decreased the ratio of p-H3-positive to Ki-67-positive nuclei. Unsupervised hierarchical clustering based on 488 Taxol fluorescence and p-H3: Ki-67 ratios clearly distinguished compounds with these disparate molecular mechanisms. Furthermore, a classification algorithm based on an artificial neural network was found to effectively predict molecular target, as leave-one-out cross-validation resulted in 25/26 agreement with a priori expectations. These results are encouraging, as they suggest that an adequate number of training set chemicals, in conjunction with a machine learning algorithm based on 488 Taxol, p-H3, and Ki-67 responses, can reliably elucidate the most commonly encountered aneugenic molecular targets.

Differentiation of Aneugens and Clastogens in the In Vitro Micronucleus Test by Kinetochore Scoring Using Automated Image Analysis

The in vitro micronucleus test according to OECD Test Guideline 487 (TG 487) is widely used to investigate the genotoxic potential of drugs. Besides the identification of in vitro genotoxicants, the assay can be complemented with kinetochore staining for the differentiation between clastogens and aneugens. This differentiation constitutes a major contribution to risk assessment as especially aneugens show a threshold response. Thus, a novel method for automated MN plus kinetochore (k+) scoring by image analysis was developed based on the OECD TG 487. Compound-induced increases in MN frequency can be detected using the cytokinesis-block (cytochalasin B) method in V79 cells after 24 h in a 96-well format. Nuclei, MN, and kinetochores were labeled with nuclear counterstain and anti-kinetochore antibodies, respectively, to score MN in binuclear or multinuclear cells and to differentiate compound-induced MN by the presence of kinetochores. First, a reference data set was created by manual scoring using two clastogens and aneugens. After developing the automated scoring process, a set of 14 reference genotoxicants were studied. The automated image analysis yielded the expected results: 5/5 clastogens and 6/6 aneugens (sensitivity: 100%) as well as 3/3 non-genotoxicants (specificity: 100%) were correctly identified. Further, a threshold was determined for identifying aneugens. Based on the data for our internally characterized reference compounds, unknown compounds that induce ≥53.8% k+ MN are classified as aneugens. The current data demonstrate excellent specificity and sensitivity and the methodology is superior to manual microscopic analysis in terms of speed and throughput as well as the absence of human bias. Environ. Mol. Mutagen. 60:227-242, 2019. © 2018 Wiley Periodicals, Inc.