Hypothesis: Caco-2 cell rotational 3D mechanogenomic turing patterns have clinical implications to colon crypts

Glucocorticoid receptor-mediated Nr1d1 chromatin circadian misalignment in stress-induced irritable bowel syndrome

Stress-elevated glucocorticoids cause circadian disturbances and gut-brain axis (GBA) disorders, including irritable bowel syndrome (IBS). We hypothesized that the glucocorticoid receptor (GR/NR3C1) might cause chromatin circadian misalignment in the colon epithelium. We observed significantly decreased core circadian gene Nr1d1 in water avoidance stressed (WAS) BALB/c colon epithelium, like in IBS patients. WAS decreased GR binding at the Nr1d1 promoter E-box (enhancer box), and GR could suppress Nr1d1 via this site. Stress also altered GR binding at the E-box sites along the Ikzf3-Nr1d1 chromatin and remodeled circadian chromatin 3D structures, including Ikzf3-Nr1d1 super-enhancer, Dbp, and Npas2. Intestinal deletion of Nr3c1 specifically abolished these stress-induced transcriptional alternations relevant to IBS phenotypes in BALB/c mice. GR mediated Ikzf3-Nr1d1 chromatin disease related circadian misalignment in stress-induced IBS animal model. This animal model dataset suggests that regulatory SNPs of human IKZF3-NR1D1 transcription through conserved chromatin looping have translational potential based on the GR-mediated circadian-stress crosstalk.

Hypothesis: Caco-2 cell rotational 3D mechanogenomic turing patterns have clinical implications to colon crypts

Colon crypts are recognized as a mechanical and biochemical Turing patterning model. Colon epithelial Caco-2 cell monolayer demonstrated 2D Turing patterns via force analysis of apical tight junction live cell imaging which illuminated actomyosin meshwork linking the actomyosin network of individual cells. Actomyosin forces act in a mechanobiological manner that alters cell/nucleus/tissue morphology. We observed the rotational motion of the nucleus in Caco-2 cells that appears to be driven by actomyosin during the formation of a differentiated confluent epithelium. Single- to multi-cell ring/torus-shaped genomes were observed prior to complex fractal Turing patterns extending from a rotating torus centre in a spiral pattern consistent with a gene morphogen motif. These features may contribute to the well-described differentiation from stem cells at the crypt base to the luminal colon epithelium along the crypt axis. This observation may be useful to study the role of mechanogenomic processes and the underlying molecular mechanisms as determinants of cellular and tissue architecture in space and time, which is the focal point of the 4D nucleome initiative. Mathematical and bioengineer modelling of gene circuits and cell shapes may provide a powerful algorithm that will contribute to future precision medicine relevant to a number of common medical disorders.

3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification

Quantitative analysis of morphological changes in a cell nucleus is important for the understanding of nuclear architecture and its relationship with pathological conditions such as cancer. However, dimensionality of imaging data, together with a great variability of nuclear shapes, presents challenges for 3D morphological analysis. Thus, there is a compelling need for robust 3D nuclear morphometric techniques to carry out population-wide analysis. We propose a new approach that combines modeling, analysis, and interpretation of morphometric characteristics of cell nuclei and nucleoli in 3D. We used robust surface reconstruction that allows accurate approximation of 3D object boundary. Then, we computed geometric morphological measures characterizing the form of cell nuclei and nucleoli. Using these features, we compared over 450 nuclei with about 1,000 nucleoli of epithelial and mesenchymal prostate cancer cells, as well as 1,000 nuclei with over 2,000 nucleoli from serum-starved and proliferating fibroblast cells. Classification of sets of 9 and 15 cells achieved accuracy of 95.4% and 98%, respectively, for prostate cancer cells, and 95% and 98% for fibroblast cells. To our knowledge, this is the first attempt to combine these methods for 3D nuclear shape modeling and morphometry into a highly parallel pipeline workflow for morphometric analysis of thousands of nuclei and nucleoli in 3D.