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Exploring chromosomal structural heterogeneity across multiple cell lines.

ABSTRACT: Using computer simulations, we generate cell-specific 3D chromosomal structures and compare them to recently published chromatin structures obtained through microscopy. We demonstrate using machine learning and polymer physics simulations that epigenetic information can be used to predict the structural ensembles of multiple human cell lines. Theory predicts that chromosome structures are fluid and can only be described by an ensemble, which is consistent with the observation that chromosomes exhibit no unique fold. Nevertheless, our analysis of both structures from simulation and microscopy reveals that short segments of chromatin make two-state transitions between closed conformations and open dumbbell conformations. Finally, we study the conformational changes associated with the switching of genomic compartments observed in human cell lines. The formation of genomic compartments resembles hydrophobic collapse in protein folding, with the aggregation of denser and predominantly inactive chromatin driving the positioning of active chromatin toward the surface of individual chromosomal territories.

SUBMITTER: Cheng RR

PROVIDER: S-EPMC7593087 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Exploring chromosomal structural heterogeneity across multiple cell lines.

Cheng Ryan R RR Contessoto Vinicius G VG Lieberman Aiden Erez E Wolynes Peter G PG Di Pierro Michele M Onuchic Jose N JN

eLife 20201013

Using computer simulations, we generate cell-specific 3D chromosomal structures and compare them to recently published chromatin structures obtained through microscopy. We demonstrate using machine learning and polymer physics simulations that epigenetic information can be used to predict the structural ensembles of multiple human cell lines. Theory predicts that chromosome structures are fluid and can only be described by an ensemble, which is consistent with the observation that chromosomes ex ...[more]

PMID: 33047670

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Project description:INTRODUCTION:Loss of annulus fibrosus (AF) integrity predisposes to disc herniation and is associated with IVD degeneration. Successful implementation of biomedical intervention therapy requires in-depth knowledge of IVD cell biology. We recently generated unique clonal human nucleus pulposus (NP) cell lines. Recurring functional cellular phenotypes from independent donors provided pivotal evidence for cell heterogeneity in the mature human NP. In this study we aimed to generate and characterize immortal cell lines for the human AF from matched donors. METHODS:Non-degenerate healthy disc material was obtained as surplus surgical material. AF cells were immortalized by simian virus Large T antigen (SV40LTAg) and human telomerase (hTERT) expression. Early passage cells and immortalized cell clones were characterized based on marker gene expression under standardized culturing and in the presence of Transforming Growth factor ? (TGF?). RESULTS:The AF-specific expression signature included COL1A1, COL5A1, COL12A1, SFRP2 and was largely maintained in immortal AF cell lines. Remarkably, TGF? induced rapid 3D sheet formation in a subgroup of AF clones. This phenotype was associated with inherent differences in Procollagen type I processing and maturation, and correlated with differential mRNA expression of Prolyl 4-hydroxylase alpha polypeptide 1 and 3 (P4HA1,3) and Lysyl oxidase (LOX) between clones and differential P4HA3 protein expression between AF cells in histological sections. CONCLUSION:We report for the first time the generation of representative human AF cell lines. Gene expression profile analysis and functional comparison of AF clones revealed variation between immortalized cells and suggests phenotypic heterogeneity in the human AF. Future characterization of AF cellular (sub-)populations aims to combine identification of additional specific AF marker genes and their biological relevance. Ultimately this knowledge will contribute to clinical application of cell-based technology in IVD repair.

Dataset Information

Exploring chromosomal structural heterogeneity across multiple cell lines.

Publications

Exploring chromosomal structural heterogeneity across multiple cell lines.

Similar Datasets

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