Nuclear DNA methylation and chromatin condensation phenotypes are distinct between normally proliferating/aging, rapidly growing/immortal, and senescent cells

正常增殖/衰老细胞、快速生长/永生细胞和衰老细胞之间的核 DNA 甲基化和染色质凝聚表型存在差异

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作者:Jin Ho Oh, Arkadiusz Gertych, Jian Tajbakhsh

Abstract

This study reports on probing the utility of in situ chromatin texture features such as nuclear DNA methylation and chromatin condensation patterns - visualized by fluorescent staining and evaluated by dedicated three-dimensional (3D) quantitative and high-throughput cell-by-cell image analysis - in assessing the proliferative capacity, i.e. growth behavior of cells: to provide a more dynamic picture of a cell population with potential implications in basic science, cancer diagnostics/prognostics and therapeutic drug development. Two types of primary cells and four different cancer cell lines were propagated and subjected to cell-counting, flow cytometry, confocal imaging, and 3D image analysis at various points in culture. Additionally a subset of primary and cancer cells was accelerated into senescence by oxidative stress. DNA methylation and chromatin condensation levels decreased with declining doubling times when primary cells aged in culture with the lowest levels reached at the stage of proliferative senescence. In comparison, immortal cancer cells with constant but higher doubling times mostly displayed lower and constant levels of the two in situ-derived features. However, stress-induced senescent primary and cancer cells showed similar levels of these features compared with primary cells that had reached natural growth arrest. With regards to global DNA methylation and chromatin condensation levels, aggressively growing cancer cells seem to take an intermediate level between normally proliferating and senescent cells. Thus, normal cells apparently reach cancer-cell equivalent stages of the two parameters at some point in aging, which might challenge phenotypic distinction between these two types of cells. Companion high-resolution molecular profiling could provide information on possible underlying differences that would explain benign versus malign cell growth behaviors.

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