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Research Article

Validation of JCountPro software for efficient assessment of ionizing radiation-induced foci in human lymphocytes

, , , , &
Pages 766-773 | Received 16 Mar 2016, Accepted 31 Jul 2016, Published online: 20 Sep 2016
 

Abstract

Purpose: Ionizing radiation-induced foci (IRIF) known also as DNA repair foci represent the most sensitive and specific assay for assessing DNA double-strand break (DSB). IRIF are usually visualized and enumerated with the aid of fluorescence microscopy using antibodies to phosphorylated γH2AX and 53BP1. Although several approaches and software packages were developed for quantification of IRIF, not one of them was commonly accepted and inter-laboratory variability in the outputs was reported. In this study, JCountPro software was validated for IRIF enumeration in two independent laboratories.

Materials and methods: Human lymphocytes were γ-irradiated at doses of 0, 2, 5, 10 and 50 cGy. The cells were fixed, permeabilized and IRIF were immunostained using appropriate antibodies. Cell images were acquired with automatic Metafer system. Endogenous and radiation-induced γH2AX and 53BP1 foci were enumerated using JCountPro. This analysis was performed from the same cell galleries by the researchers from two laboratories. Yield of foci was analyzed by either arithmetic mean (AM) value (foci/cell) or principal average (PA) derived from the approximation of foci distribution with Poisson statistics. Statistical analysis was performed using factorial ANOVA.

Results: Enumeration of 53BP1, γH2AX and co-localized 53BP1/γH2AX foci by JCountPro was essentially the same between laboratories. IRIF were detected at all doses and linear dose response was obtained in the studied dose range. PA values from Poisson distribution fitted the data better as compared to AM values and were more powerful and sensitive for IRIF analysis than the AM values. All JCountPro data were confirmed by visual focus enumeration.

Conclusions: We concluded that the JCountPro software was efficient in objectively enumerating IRIF regardless of an individual researcher’s bias and has a potential for usage in clinics and molecular epidemiology.

Acknowledgements

This work was supported by the Structural Funds of EU (Protonbeam, ITMS: 26220220129), the Slovak Research and Development Agency (APVV 0669-10, APVV-15-0250) and the VEGA Grant Agency (2/0106/15, 2/0109/15) of the Slovak Republic.

Disclosure statement

The authors report no conflicts of interest. The authors alone are response for the content and writing of the paper.

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