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

: Wilde, S.; Queisser, N.; Holz, C.; Raschke, M.; Sutter, A.


Environmental and Molecular Mutagenesis 60 (2019), No.3, pp.227-242
ISSN: 0893-6692
ISSN: 1098-2280
Journal Article
Fraunhofer ITEM ()

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.