Chemical-induced premature chromosome condensation (PCC) is an alternative biodosimetry method to the gold-standard dicentric analysis for ionizing radiation. However, existing literature shows great variations in the experimental protocols which, together with the different scoring criteria applied in individual studies, result in large discrepancies in the coefficients of the calibration curves. The current study is based on an extensive review of the peer-reviewed literature on the chemical-induced ring PCC (rPCC) assay for high-dose exposure. For the first time, a simplified yet effective protocol was developed and tested in an attempt to reduce the scoring time and to increase the accuracy of dose estimation. Briefly, the protein phosphatase inhibitor, calyculin A, was selected over okadaic acid for higher efficiency. Colcemid block was omitted and only G2-PCC cells were scored. Strict scoring criteria for total rings and hollow rings only were described to minimize the uncertainty resulting from scoring ring-like artefacts. It was found that ring aberrations followed a Poisson distribution and the dose-effect relationship favored a linear fit with an α value of 0.0499 ± 0.0028 Gy–1 for total rings and 0.0361 ± 0.0031 Gy–1 for hollow rings only. The calibration curves constructed by scoring ring aberrations were directly compared between the simplified calyculin A-induced PCC protocol and that of the cell fusion-induced PCC for high-dose exposure to gamma rays. The technical practicalities of these two methods were also compared; and our blind validation tests showed that both assays were feasible for high-dose γ-ray exposure assessment even when only hollow rings in 100 PCC spreads were scored.
A Simplified Calyculin A-Induced Premature Chromosome Condensation (PCC) Protocol for the Biodosimetric Analysis of High-Dose Exposure to Gamma Radiation
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Mingzhu Sun, Jayne Moquet, Stephen Barnard, David Lloyd, Elizabeth Ainsbury; A Simplified Calyculin A-Induced Premature Chromosome Condensation (PCC) Protocol for the Biodosimetric Analysis of High-Dose Exposure to Gamma Radiation. Radiat Res 1 June 2020; 193 (6): 560–568. doi: https://doi.org/10.1667/RR15538.1
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