3-D DNA methylation phenotypes correlate with cytotoxicity levels in prostate and liver cancer cell models

Experimental Cell Research

Stefanovski

Tang

et al. 2015

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Cell-surface markers and transcription factors are being used in the assessment of stem cell fate and therapeutic safety, but display significant variability in stem cell cultures. We assessed nuclear patterns of 5-hydroxymethylcytosine (5hmC, associated with pluripotency), a second important epigenetic mark, and its combination with 5-methylcytosine (5mC, associated with differentiation), also in comparison to more established markers of pluripotency (Oct-4) and endodermal differentiation (FoxA2, Sox17) in mouse embryonic stem cells (mESC) over a ten-day differentiation course in vitro: by means of confocal and super-resolution imaging together with high-content analysis, an essential tool in single-cell screening. In summary: 1) We did not measure any significant correlation of putative markers with global 5mC or 5hmC. 2) While average Oct-4 levels stagnated on a cell-population base (0.015 lnIU per day), Sox17 and FoxA2 increased 22-fold and 3-fold faster, respectively (Sox17:0.343 lnIU/day; FoxA2: 0.046 lnIU/day). In comparison, DNA global methylation levels increased 4-fold faster (0.068 lnIU/day), and global hydroxymethylation declined at 0.046 lnIU/day, both with a better explanation of the temporal profile. 3) This progression was concomitant with the occurrence of distinct nuclear codistribution patterns that represented a heterogeneous spectrum of states in differentiation; converging to three major coexisting 5mC/5hmC phenotypes by day 10: 5hmC+/5mC−, 5hmC+/5mC+, and 5hmC−/5mC+ cells. 4) Using optical nanoscopy we could delineate the respective topologies of 5mC/5hmC colocalization in subregions of nuclear DNA: in the majority of 5hmC+/5mC+ cells 5hmC and 5mC predominantly occupied mutually exclusive territories resembling euchromatic and heterochromatic regions, respectively. Simultaneously, in a smaller subset of cells we observed a tighter colocalization of the two cytosine variants, presumably delineating chromatin domains in remodeling. We conclude that 1) 5mC emerges as the most differential marker in our model system. 2) However, the combined enrollment of the two DNA modifications provided higher-definition screening and lead to the identification of cell subpopulations based on differential 5hmC/5mC phenotypes corresponding to different 5hmC/5mC ratios. The results encourage: a) assessing the regenerative potential of early-endodermal cells enriched for the three DNA methylation/hydroxymethylation categories, and b) exploring the universality of this type of epigenetic phenotyping across other lineage-specific differentiations.

Section: Methodsmentioning

confidence: 99%

Dynamic heterogeneity of DNA methylation and hydroxymethylation in embryonic stem cell populations captured by single-cell 3D high-content analysis

Experimental Cell Research

Stefanovski

Tang

et al. 2015

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“…Published methods for their analysis are scarce. Our work is based on 3-D image data from an epigenetic drug evaluation study [28, 29] used to design and test a new nuclear segmentation procedure. Since some of the existing tools may not always perform well we implemented 3-D radial symmetries to pinpoint nuclear regions of interest and to address the problem of nuclear segmentation in highly confluent and phenotype-dense image stacks.…”

Section: Discussionmentioning

confidence: 99%

“…Image data was repurposed from an imaging-based high-content screening project [28, 29] to characterize the potency of DNA methylation inhibitors in cancer cell lines. The material consisted of treated and untreated DU145 human prostate carcinoma cells, and HuH-7 liver carcinoma cells.…”

Section: Methodsmentioning

confidence: 99%

“…27 DAPI stacks that were generated on average from 35 slides (Tab.1) and represent a high variability of nuclear staining patterns and cell confluencies (Fig.1) were selected from a large set of pre-existing image data to test the proposed methodology. More details related to specimens, drug treatment schedules, staining protocol and imaging can be found in [28, 29]. Stacks were divided into three groups: low confluency with up to 40 nuclei per stack, moderate confluency (41-65 nuclei) and high confluency (73-190 nuclei).…”

Section: Methodsmentioning

confidence: 99%

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Rapid 3-D delineation of cell nuclei for high-content screening platforms

Gertych

Computers in Biology and Medicine

et al. 2016

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High-resolution three-dimensional (3-D) microscopy combined with multiplexing of fluorescent labels allows high-content analysis of large numbers of cell nuclei. The full automation of 3-D screening platforms necessitates image processing algorithms that can accurately and robustly delineate nuclei in images with little to no human intervention. Imaging-based high-content screening was originally developed as a powerful tool for drug discovery. However, cell confluency, complexity of nuclear staining as well as poor contrast between nuclei and background result in slow and unreliable 3-D image processing and therefore negatively affect the performance of studying a drug response. Here, we propose a new method, 3D-RSD, to delineate nuclei by means of 3-D radial symmetries and test it on high-resolution image data of human cancer cells treated by drugs. The nuclei detection performance was evaluated by means of manually generated ground truth from 2351 nuclei (27 confocal stacks). When compared to three other nuclei segmentation methods, 3D-RSD possessed a better true positive rate of 83.3% and F-score of 0.895+/-0.045 (p- value=0.047). Altogether, 3D-RSD is a method with a very good overall segmentation performance. Furthermore, implementation of radial symmetries offers good processing speed, and makes 3D-RSD less sensitive to staining patterns. In particular the 3D-RSG method performs well in cell lines, which are often used in imaging-based HCS platforms and are afflicted by nuclear crowding and overlaps that hinder feature extraction.

“…Applications of this technology have been utilized in the evaluation of demethylating effects of epigenetic drugs and the progression of human and mouse embryonic stem cells in early differentiation [19–24]. In here, we report on using 3D-qDMI to probe the utility of MeC-related chromatin texture features (MeC phenotypes) in characterizing cells based on their proliferative capacity, i.e.…”

Section: Introductionmentioning

confidence: 99%

Nuclear DNA Methylation and Chromatin Condensation Phenotypes Are Distinct Between Normally Proliferating/Aging, Rapidly Growing/Immortal, and Senescent Cells

Gertych

2013

Oncotarget

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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.