COMPARATIVE FLOW CYTOMETRIC ANALYSIS OF DNA-BOUND PCNA AND DNA CONTENT AS ESTIMATORS OF S-PHASE CELLS IN CELL LINES

Ana Salas Bustamante, Marta Alonso Guervós,Juan R. de los Toyos, Frank Dolbeare, and Andrés Sampedro Nuño

Servicio de Proceso de Imágenes y Citometría, Universidad de Oviedo

There is a fraction of PCNA (proliferating cell nuclear antigen), tihgtly bound to DNA, not extractable, which is currently considered as a S-phase marker.

We have explored the feasibility and usefulness of the estimation of S-phase cells after extraction of PCNA from three different cell lines in culture (mouse myeloma Sp 2/0, and human osteogenic sarcoma Saos-2 and colon adenocarcinoma LoVo cells), and from frozen aliquots.

The S-phase fraction of every single batch of cells was estimated by four different ways: Vindelöv's DNA histogram, DNA histogram of methanol-fixed cells, bivariate PCNA/DNA analysis after extraction of DNA-not-bound PCNA and the corresponding DNA histogram.

Bivariate PCNA/DNA flow cytometric analyses were performed using LYSIS II Ver 1.1 software (Becton Dickinson). Total DNA histograms were analysed using CellFit software (Becton Dickinson).

We have not found significant differences on the estimation of the percentage of S-phase cells among the four methods tested, and between fresh and frozen specimens.

Nuclei yield following PCNA extraction was very variable, from 63% to 10% (mean: 26%).

The PCNA extraction protocol is longer, and more costly and cumbersome than the currently used Vindelöv's technique. Evenmore, as nuclei yield is low, this procedure may compromise the recovery of poorly represented, interesting, nuclear subpopulations, such as the aneuploid ones. In conclusion, our view is that the application of PCNA- extraction does not provide any significant improvement on the estimation of the S-phase fraction in relation to standard DNA cell cycle analyses. As already suggested, efforts should be directed to improve the quality of DNA flow cytometric measurements and to the application of optimal cell cycle software programs.