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Investigating FlowSight® imaging flow cytometry as a platform to assess chemically induced micronuclei using human lymphoblastoid cells in vitro
Mutagenesis, Volume: 33, Issue: 4, Pages: 283 - 289
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Use of imaging flow cytometry to assess induced DNA damage via the cytokinesis block micronucleus (CBMN) assay has thus far been limited to radiation dosimetry in human lymphocytes using high end, ‘ImageStream X’ series imaging cytometers. Its potential to enumerate chemically induced DNA damage usi...
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Use of imaging flow cytometry to assess induced DNA damage via the cytokinesis block micronucleus (CBMN) assay has thus far been limited to radiation dosimetry in human lymphocytes using high end, ‘ImageStream X’ series imaging cytometers. Its potential to enumerate chemically induced DNA damage using in vitro cell lines remains unexplored. In the present manuscript, we investigate the more affordable FlowSight® imaging cytometry platform to assess in vitro micronucleus (MN) induction in the human lymphoblastoid TK6 and metabolically competent MCL-5 cells treated with Methyl Methane Sulfonate (MMS) (0–5 µg/ml), Carbendazim (0–1.6 µg/ml), and Benzo[a]Pyrene (B[a]P) (0–6.3 µg/ml) for a period of 1.5–2 cell-cycles. Cells were fixed, and nuclei and MN were stained using the fluorescent nuclear dye DRAQ5™. Image acquisition was carried out using a 20X objective on a FlowSight® imaging cytometer (Amnis, part of Merck Millipore) equipped with a 488 nm laser. Populations of ∼20000 brightfield cell images, alongside DRAQ5™ stained nuclei/MN were rapidly collected (≤10 min). Single, in-focus cells suitable for scoring were then isolated using the IDEAS® software. An overlay of the brightfield cell outlines and the DRAQ5 nuclear fluorescence was used to facilitate scoring of mono-, bi-, tri-, and tetra-nucleated cells with or without MN events and in context of the cytoplasmic boundary of the parent cell.To establish the potential of the FlowSight® platform, and to establish ‘ground truth’ cell classification for the supervised machine learning based scoring algorithm that represents the next stage of our project, the captured images were scored manually. Alongside, MN frequencies were also derived using the ‘gold standard’ light microscopy and manual scoring. A minimum of 3000 bi-nucleated cells were assessed using both approaches. Using the benchmark dose approach, the comparability of genotoxic potency estimations for the different compounds and cell lines was assessed across the two scoring platforms as highly similar. This study therefore provides essential proof-of-concept that FlowSight® imaging cytometry is capable of reproducing the results of ‘gold standard’ manual scoring by light microscopy. We conclude that, with the right automated scoring algorithm, imaging flow cytometry could revolutionise the reportability and scoring throughput of the CBMN assay.
cell cycle, flow cytometry, alkanesulfonates, benchmarking, cell lines, cell nucleus, cytoplasm, dna damage, dyes, fluorescence, immunoglobulins, thyroid-stimulating, infectious mononucleosis, lasers, lymphocytes, methane, micronucleus, pyrenes, radiometry, software, diagnostic imaging, tetracycline, cytokinesis, gold standard, light microscopy, supervised machine learning, proof of concept studies
College of Engineering