Abstract

The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automated, inter-laboratory operation. Images were captured for the cytokinesis-block micronucleus (CBMN) assay across three laboratories using methyl methanesulphonate (1.25–5.0 μg/mL) and/or carbendazim (0.8–1.6 μg/mL) exposures to TK6 cells. Human-scored image sets were assembled and used to train and test the classification abilities of the “DeepFlow” neural network in both intra- and inter-laboratory contexts. Harnessing image diversity across laboratories yielded a network able to score unseen data from an entirely new laboratory without any user configuration. Image classification accuracies of 98%, 95%, 82% and 85% were achieved for ‘mononucleates’, ‘binucleates’, ‘mononucleates with MN’ and ‘binucleates with MN’, respectively. Successful classifications of ‘trinucleates’ (90%) and ‘tetranucleates’ (88%) in addition to ‘other or unscorable’ phenotypes (96%) were also achieved. Attempts to classify extremely rare, tri- and tetranucleated cells with micronuclei into their own categories were less successful (≤ 57%). Benchmark dose analyses of human or automatically scored micronucleus frequency data yielded quantitation of the same equipotent concentration regardless of scoring method. We conclude that this automated approach offers significant potential to broaden the practical utility of the CBMN method across industry, research and clinical domains. We share our strategy using openly-accessible frameworks.

Highlights

  • Across industry, government and academic research institutions the in vitro micronucleus test is one of the most widely used bioassays for the identification and quantification of chromosomal damage (Decordier and Kirsch-Volders 2006; Fenech 2000, 2020; Kirsch-Volders et al 2011)

  • In addition to regulatory compound screening, the assay is widely used for more specific research and clinical purposes including compound mode-of-action determinations, tumour radiosensitivity prediction and inter-individual monitoring of lifestyle, occupational and environmental factors including radiation biodosimetry assessments (Decordier and Kirsch-Volders 2006; Fenech 2000, 2020; Kirsch-Volders et al 2011; Wang et al 2019)

  • Cells were seeded at 2 × ­105 cells/mL in 25 ­cm2 flasks (ThermoFisher) and incubated at 37 °C for ~ 1.5 cell cycles (24–30 h) in the presence of Methyl methanesulphonate (MMS) (0/1.25/2.5/5.0 μg/mL concentrations) or carbendazim (0/0.8/1.0/1.6 μg/mL concentrations) delivered using dimethyl sulphoxide (DMSO) as a vehicle, with coexposed cytochalasin-B (#C6762, Sigma) added to a final concentration of 3 μg/mL as a cytokinesis block

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Summary

Introduction

Government and academic research institutions the in vitro micronucleus test is one of the most widely used bioassays for the identification and quantification of chromosomal damage (Decordier and Kirsch-Volders 2006; Fenech 2000, 2020; Kirsch-Volders et al 2011). Because complete nuclear division is required to enable expression of these events, the ‘cytokinesis-block’ version of the assay was developed This method inhibits cell division into daughter entities (cytokinesis) using the microfilament assembly inhibitor cytochalasin-B. The cytokinesis-block micronucleus (CBMN) assay allows scoring of micronucleus events in cells known to have undergone division during the treatment period This avoids misleading results otherwise present due to pre-existing damage, sub-optimal cell culture conditions or from the selection of overly cytotoxic compound concentrations that retard or inhibit cell division and concomitant micronucleus expression (Decordier and Kirsch-Volders 2006; Fenech 2000; KirschVolders et al 2011)

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