Jian Tajbakhsh

Automated quantification of DNA demethylation effects in cells via 3D mapping of nuclear signatures and population homogeneity assessment

Todays advanced microscopic imaging applies to the preclinical stages of drug discovery that employ high‐throughput and high‐content three‐dimensional (3D) analysis of cells to more efficiently screen candidate compounds. Drug efficacy can be assessed by measuring response homogeneity to treatment within a cell population. In this study, topologically quantified nuclear patterns of methylated cytosine and global nuclear DNA are utilized as signatures of cellular response to the treatment of cultured cells with the demethylating anti‐cancer agents: 5‐azacytidine (5‐AZA) and octreotide (OCT). Mouse pituitary folliculostellate TtT‐GF cells treated with 5‐AZA and OCT for 48 hours, and untreated populations, were studied by immunofluorescence with a specific antibody against 5‐methylcytosine (MeC), and 4,6‐diamidino‐2‐phenylindole (DAPI) for delineation of methylated sites and global DNA in nuclei (n = 163). Cell images were processed utilizing an automated 3D analysis software that we developed by combining seeded watershed segmentation to extract nuclear shells with measurements of Kullback‐Leiblers (K‐L) divergence to analyze cell population homogeneity in the relative nuclear distribution patterns of MeC versus DAPI stained sites. Each cell was assigned to one of the four classes: similar, likely similar, unlikely similar, and dissimilar. Evaluation of the different cell groups revealed a significantly higher number of cells with similar or likely similar MeC/DAPI patterns among untreated cells (approximately 100%), 5‐AZA‐treated cells (90%), and a lower degree of same type of cells (64%) in the OCT‐treated population. The latter group contained (28%) of unlikely similar or dissimilar (7%) cells. Our approach was successful in the assessment of cellular behavior relevant to the biological impact of the applied drugs, i.e., the reorganization of MeC/DAPI distribution by demethylation. In a comparison with other metrics, K‐L divergence has proven to be a more valuable and robust tool for categorization of individual cells within a population, with potential applications in epigenetic drug screening.

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

BackgroundThe spatial organization of the genome is being evaluated as a novel indicator of toxicity in conjunction with drug-induced global DNA hypomethylation and concurrent chromatin reorganization. 3D quantitative DNA methylation imaging (3D-qDMI) was applied as a cell-by-cell high-throughput approach to investigate this matter by assessing genome topology through represented immunofluorescent nuclear distribution patterns of 5-methylcytosine (MeC) and global DNA (4,6-diamidino-2-phenylindole = DAPI) in labeled nuclei.MethodsDifferential progression of global DNA hypomethylation was studied by comparatively dosing zebularine (ZEB) and 5-azacytidine (AZA). Treated and untreated (control) human prostate and liver cancer cells were subjected to confocal scanning microscopy and dedicated 3D image analysis for the following features: differential nuclear MeC/DAPI load and codistribution patterns, cell similarity based on these patterns, and corresponding differences in the topology of low-intensity MeC (LIM) and low in intensity DAPI (LID) sites.ResultsBoth agents generated a high fraction of similar MeC phenotypes across applied concentrations. ZEB exerted similar effects at 10–100-fold higher drug concentrations than its AZA analogue: concentration-dependent progression of global cytosine demethylation, validated by measuring differential MeC levels in repeat sequences using MethyLight, and the concurrent increase in nuclear LIM densities correlated with cellular growth reduction and cytotoxicity.Conclusions3D-qDMI demonstrated the capability of quantitating dose-dependent drug-induced spatial progression of DNA demethylation in cell nuclei, independent from interphase cell-cycle stages and in conjunction with cytotoxicity. The results support the notion of DNA methylation topology being considered as a potential indicator of causal impacts on chromatin distribution with a conceivable application in epigenetic drug toxicology.

Measuring topology of low-intensity DNA methylation sites for high-throughput assessment of epigenetic drug-induced effects in cancer cells.

Epigenetic anti-cancer drugs with demethylating effects have shown to alter genome organization in mammalian cell nuclei. The interest in the development of novel epigenetic drugs has increased the demand for cell-based assays to evaluate drug performance in pre-clinical studies. An imaging-based cytometrical approach that can measure demethylation effects as changes in the spatial nuclear distributions of methylated cytosine and global DNA in cancer cells is introduced in this paper. The cells were studied by immunofluorescence with a specific antibody against 5-methylcytosine (MeC), and 4,6-diamidino-2-phenylindole (DAPI) for delineation of methylated sites and global DNA in nuclei. In the preprocessing step the segmentation of nuclei in three-dimensional images (3-D) is followed by an automated assessment of nuclear DAPI/MeC patterns to exclude dissimilar entities. Next, low-intensity MeC (LIM) and low-intensity DNA (LID) sites of similar nuclei are localized and processed to obtain specific nuclear density profiles. These profiles sampled at half of the total nuclear volume yielded two parameters: LIM(0.5) and LID(0.5). The analysis shows that zebularine and 5-azacytidine-the two tested epigenetic drugs introduce changes in the spatial distribution of low-intensity DNA and MeC signals. LIM(0.5) and LID(0.5) were significantly different (p<0.001) in 5-azacytidine treated (n=660) and zebularine treated (n=496) vs. untreated (n=649) DU145 human prostate cancer cells. In the latter case the LIM sites were predominantly found at the nuclear border, whereas treated populations showed different degrees of increase in LIMs towards the interior nuclear space, in which a large portion of heterochromatin is located. The cell-by-cell evaluation of changes in the spatial reorganization of MeC/DAPI signals revealed that zebularine is a more gentle demethylating agent than 5-azacytidine. Measuring changes in the topology of low-intensity sites can potentially be a valuable component in the high-throughput assessment of demethylation and risk of chromatin reorganization in epigenetic-drug screening tasks.

Characterization of tumor cells and stem cells by differential nuclear methylation imaging

DNA methylation plays a key role in cellular differentiation. Aberrant global methylation patterns are associated with several cancer types, as a result of changes in long-term activation status of up to 50% of genes, including oncogenes and tumor-suppressor genes, which are regulated by methylation and demethylation of promoter region CpG dinucleotides (CpG islands). Furthermore, DNA methylation also occurs in nonisland CpG sites (> 95% of the genome), present once per 80 dinucleotides on average. Nuclear DNA methylation increases during the course of cellular differentiation while cancer cells usually show a net loss in methylation. Given the large dynamic range in DNA methylation load, the methylation pattern of a cell can provide a valuable distinction as to its status during differentiation versus the disease state. By applying immunofluorescence, confocal microscopy and 3D image analysis we assessed the potential of differential nuclear distribution of methylated DNA to be utilized as a biomarker to characterize cells during development and when diseased. There are two major fields that may immediately benefit from this development: (1) the search for factors that contribute to pluripotency and cell fate in human embryonic stem cell expansion and differentiation, and (2) the characterization of tumor cells with regard to their heterogeneity in molecular composition and behavior. We performed topological analysis of the distribution of methylated CpG-sites (MeC) versus heterochromatin. This innovative approach revealed significant differences in colocalization patterns of MeC and heterochromatin-derived signals between undifferentiated and differentiated human embryonic stem cells, as well as untreated AtT20 mouse pituitary tumor cells compared to a subpopulation of these cells treated with 5-azacytidine for 48 hours.

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

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-RSD 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.

Early In Vitro Differentiation of Mouse Definitive Endoderm Is Not Correlated with Progressive Maturation of Nuclear DNA Methylation Patterns

The genome organization in pluripotent cells undergoing the first steps of differentiation is highly relevant to the reprogramming process in differentiation. Considering this fact, chromatin texture patterns that identify cells at the very early stage of lineage commitment could serve as valuable tools in the selection of optimal cell phenotypes for regenerative medicine applications. Here we report on the first-time use of high-resolution three-dimensional fluorescence imaging and comprehensive topological cell-by-cell analyses with a novel image-cytometrical approach towards the identification of in situ global nuclear DNA methylation patterns in early endodermal differentiation of mouse ES cells (up to day 6), and the correlations of these patterns with a set of putative markers for pluripotency and endodermal commitment, and the epithelial and mesenchymal character of cells. Utilizing this in vitro cell system as a model for assessing the relationship between differentiation and nuclear DNA methylation patterns, we found that differentiating cell populations display an increasing number of cells with a gain in DNA methylation load: first within their euchromatin, then extending into heterochromatic areas of the nucleus, which also results in significant changes of methylcytosine/global DNA codistribution patterns. We were also able to co-visualize and quantify the concomitant stochastic marker expression on a per-cell basis, for which we did not measure any correlation to methylcytosine loads or distribution patterns. We observe that the progression of global DNA methylation is not correlated with the standard transcription factors associated with endodermal development. Further studies are needed to determine whether the progression of global methylation could represent a useful signature of cellular differentiation. This concept of tracking epigenetic progression may prove useful in the selection of cell phenotypes for future regenerative medicine applications.

Towards expansion of human hair follicle stem cells in vitro

Objectives:  Multipotential human hair follicle stem cells can differentiate into various cell lineages and thus are investigated here as potential autologous sources for regenerative medicine. Towards this end, we have attempted to expand these cells, directly isolated from minimal amounts of hair follicle explants, to numbers more suitable for stem‐cell therapy.

Homogeneity Assessment of Cell Populations for High Content Screening Platforms

The main thrust of this work is to develop a bioinformatics tool for the automated evaluation of cell population homogeneity, which can be implemented on high content screening platforms. For that we employed Kullback-Leibler (K-L) divergence as a measure of similarity of multidimensional DNA codistribution patterns extracted from cell nuclei, and assigned analyzed cells into four categories. The resulting cell population homogeneity is determined as the ratios of cell quantities in the respective similarity categories. We evaluated our approach on human prostate cancer cells treated with an anticancer drug in comparison to untreated cells. A difference in homogeneities measured in these two populations was influenced by strong changes induced into DNA distribution patterns by treatment process vs. the occurrence of naturally more diverse groups of DNA patterns in the naive cells.

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

UNLABELLED 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 10-day differentiation course in vitro: by means of confocal and super-resolution imaging together with 3D 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/day), Sox17 and FoxA2 increased 22-fold and 3-fold faster, respectively (Sox17: 0.343 lnIU/day; FoxA2: 0.046 lnIU/day). In comparison, global DNA 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.

Prostate cancer diagnosis using epigenetic biomarkers, 3D high-content imaging and probabilistic cell-by-cell classifiers

Background Prostate cancer (PCa) management can benefit from novel concepts/biomarkers for reducing the current 20-30% chance of false-negative diagnosis with standard histopathology of biopsied tissue. Method We explored the potential of selected epigenetic markers in combination with validated histopathological markers, 3D high-content imaging, cell-by-cell analysis, and probabilistic classification in generating novel detailed maps of biomarker heterogeneity in patient tissues, and PCa diagnosis. We used consecutive biopsies/radical prostatectomies from five patients for building a database of ∼140,000 analyzed cells across all tissue compartments and for model development; and from five patients and the two well-characterized HPrEpiC primary and LNCaP cancer cell types for model validation. Results Principal component analysis presented highest covariability for the four biomarkers 4′,6-diamidino-2-phenylindole, 5-methylcytosine, 5-hydroxymethylcytosine, and alpha-methylacyl-CoA racemase in the epithelial tissue compartment. The panel also showed best performance in discriminating between normal and cancer-like cells in prostate tissues with a sensitivity and specificity of 85%, correctly classified 87% of HPrEpiC as healthy and 99% of LNCaP cells as cancer-like, identified a majority of aberrant cells within histopathologically benign tissues at baseline diagnosis of patients that were later diagnosed with adenocarcinoma. Using k-nearest neighbor classifier with cells from an initial patient biopsy, the biomarkers were able to predict cancer stage and grade of prostatic tissue that occurred at later prostatectomy with 79% accuracy. Conclusion Our approach showed favorable diagnostic values to identify the portion and pathological category of aberrant cells in a small subset of sampled tissue cells, correlating with the degree of malignancy beyond baseline.