scholarly journals Chromatin folding variability across single-cells results from state degeneracy in phase-separation

2020 ◽  
Author(s):  
Mattia Conte ◽  
Luca Fiorillo ◽  
Simona Bianco ◽  
Andrea M. Chiariello ◽  
Andrea Esposito ◽  
...  
Keyword(s):  
Phase Separation ◽  
Binding Sites ◽  
Spatial Organization ◽  
Single Cells ◽  
3D Structure ◽  
Single Molecules ◽  
Super Resolution ◽  
Time Variability ◽  
Imaging Data ◽  
Contact Patterns

AbstractChromosome spatial organization controls functional interactions between genes and regulators, yet the molecular and physical mechanisms underlying folding at the single DNA molecule level remain to be understood. Here we employ models of polymer physics to investigate the conformations of two 2Mb-wide DNA loci in human HCT116 and IMR90 wild-type and cohesin depleted cells. Model predictions on the 3D structure of single-molecules are consistently validated against super-resolution single-cell imaging data, providing evidence that the architecture of the studied loci is controlled by a thermodynamics mechanism of polymer phase separation whereby chromatin self-assembles in segregated globules. The process is driven by interactions between distinct types of cognate binding sites, correlating each with a different combination of chromatin factors, including CTCF, cohesin and histone marks. The intrinsic thermodynamics degeneracy of conformations results in a broad structural and time variability of single-molecules, reflected in their varying TAD-like contact patterns. Globules breathe in time, inducing stochastic unspecific interactions, yet they produce stable, compact environments where specific contacts become highly favored between regions enriched for cognate binding sites, albeit characterized by weak biochemical affinities. Cohesin depletion tends to reverse globule phase separation into a coil, randomly folded state, resulting in much more variable contacts across single-molecules, hence erasing population-averaged patterns. Overall, globule phase separation appears to be a robust, reversible mechanism of chromatin organization, where stochasticity and specificity coexist.

scholarly journals Super-resolution chromatin tracing reveals domains and cooperative interactions in single cells

Science ◽  
2018 ◽  
Vol 362 (6413) ◽  
pp. eaau1783 ◽  
Author(s):  
Bogdan Bintu ◽  
Leslie J. Mateo ◽  
Jun-Han Su ◽  
Nicholas A. Sinnott-Armstrong ◽  
Mirae Parker ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Single Cells ◽  
Domain Boundary ◽  
Super Resolution ◽  
Chromatin Domain ◽  
Imaging Method ◽  
Imaging Data ◽  
Chromatin Interactions ◽  
Population Average ◽  
Binding Factor

The spatial organization of chromatin is pivotal for regulating genome functions. We report an imaging method for tracing chromatin organization with kilobase- and nanometer-scale resolution, unveiling chromatin conformation across topologically associating domains (TADs) in thousands of individual cells. Our imaging data revealed TAD-like structures with globular conformation and sharp domain boundaries in single cells. The boundaries varied from cell to cell, occurring with nonzero probabilities at all genomic positions but preferentially at CCCTC-binding factor (CTCF)- and cohesin-binding sites. Notably, cohesin depletion, which abolished TADs at the population-average level, did not diminish TAD-like structures in single cells but eliminated preferential domain boundary positions. Moreover, we observed widespread, cooperative, multiway chromatin interactions, which remained after cohesin depletion. These results provide critical insight into the mechanisms underlying chromatin domain and hub formation.

scholarly journals Polymer physics and machine learning reveal a combinatorial code linking chromatin 3D architecture to 1D epigenetics

2021 ◽  
Author(s):  
Andrea Esposito ◽  
Simona Bianco ◽  
Andrea M. Chiariello ◽  
Alex Abraham ◽  
Luca Fiorillo ◽  
...  
Keyword(s):  
Machine Learning ◽  
Binding Sites ◽  
Specific Binding ◽  
3D Structure ◽  
Independent Set ◽  
Polymer Physics ◽  
Binding Domains ◽  
Specific Binding Sites ◽  
Contact Patterns ◽  
3D Architecture

ABSTRACTThe mammalian genome has a complex 3D organization, serving vital functional purposes, yet it remains largely unknown how the multitude of specific DNA contacts, e.g., between transcribed and regulatory regions, is orchestrated by chromatin organizers, such as Transcription Factors. Here, we implement a method combining machine learning and polymer physics to infer from only Hi-C data the genomic 1D arrangement of the minimal set of binding sites sufficient to recapitulate, through only physics, 3D contact patterns genome-wide in human and mouse cells. The inferred binding sites are validated by their predictions on how chromatin refolds in a set of duplications at the Sox9 locus against available independent cHi-C data, showing that their different phenotypes originate from distinct enhancer hijackings in their 3D structure. Albeit derived from only Hi-C, our binding sites fall in epigenetic classes that well match chromatin states from epigenetic segmentation studies, such as active, poised and repressed states. However, the inferred binding domains have an overlapping, combinatorial organization along chromosomes, missing in epigenetic segmentations, which is required to explain Hi-C contact specificity with high accuracy. In a reverse approach, the epigenetic profile of binding domains provides a code to derive from only epigenetic marks the DNA binding sites and, hence, the 3D architecture, as validated by successful predictions of Hi-C matrices in an independent set of chromosomes. Overall, our results shed light on how complex 3D architectural information is encrypted in 1D epigenetics via the related, combinatorial arrangement of specific binding sites along the genome.

scholarly journals Physical observables to determine the nature of membrane-less cellular sub-compartments

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Mathias L Heltberg ◽  
Judith Miné-Hattab ◽  
Angela Taddei ◽  
Aleksandra M Walczak ◽  
Thierry Mora
Keyword(s):  
Phase Separation ◽  
Liquid Phase ◽  
Binding Site ◽  
Binding Sites ◽  
Spatial Organization ◽  
Liquid Droplet ◽  
Liquid Phase Separation ◽  
Site Model ◽  
Multiple Binding ◽  
Liquid Liquid Phase Separation

The spatial organization of complex biochemical reactions is essential for the regulation of cellular processes. Membrane-less structures called foci containing high concentrations of specific proteins have been reported in a variety of contexts, but the mechanism of their formation is not fully understood. Several competing mechanisms exist that are difficult to distinguish empirically, including liquid-liquid phase separation, and the trapping of molecules by multiple binding sites. Here we propose a theoretical framework and outline observables to differentiate between these scenarios from single molecule tracking experiments. In the binding site model, we derive relations between the distribution of proteins, their diffusion properties, and their radial displacement. We predict that protein search times can be reduced for targets inside a liquid droplet, but not in an aggregate of slowly moving binding sites. We use our results to reject the multiple binding site model for Rad52 foci, and find a picture consistent with a liquid-liquid phase separation. These results are applicable to future experiments and suggest different biological roles for liquid droplet and binding site foci.

scholarly journals Deep learning connects DNA traces to transcription to reveal predictive features beyond enhancer–promoter contact

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Aparna R. Rajpurkar ◽  
Leslie J. Mateo ◽  
Sedona E. Murphy ◽  
Alistair N. Boettiger
Keyword(s):  
Deep Learning ◽  
Structural Information ◽  
Single Cells ◽  
3D Structure ◽  
Super Resolution ◽  
Structural Features ◽  
Complex Data ◽  
Chromatin Architecture ◽  
Complex Data Sets ◽  
A Minor

AbstractChromatin architecture plays an important role in gene regulation. Recent advances in super-resolution microscopy have made it possible to measure chromatin 3D structure and transcription in thousands of single cells. However, leveraging these complex data sets with a computationally unbiased method has been challenging. Here, we present a deep learning-based approach to better understand to what degree chromatin structure relates to transcriptional state of individual cells. Furthermore, we explore methods to “unpack the black box” to determine in an unbiased manner which structural features of chromatin regulation are most important for gene expression state. We apply this approach to an Optical Reconstruction of Chromatin Architecture dataset of the Bithorax gene cluster in Drosophila and show it outperforms previous contact-focused methods in predicting expression state from 3D structure. We find the structural information is distributed across the domain, overlapping and extending beyond domains identified by prior genetic analyses. Individual enhancer-promoter interactions are a minor contributor to predictions of activity.

IR Super-Resolution Microspectroscopy and its Application to Single Cells

2013 ◽  
Vol 14 (2) ◽  
pp. 159-166
Author(s):  
Makoto Sakai ◽  
Keiichi Inoue ◽  
Masaaki Fujii
Keyword(s):  
Single Cells ◽  
Super Resolution

Eliminating Nonspecific Binding Sites for Highly Reliable Immunoassay via Super-resolution Multicolor Fluorescence Colocalization

Nanoscale ◽  
2021 ◽  
Author(s):  
Shenfei Zong ◽  
Yun Liu ◽  
Kuo Yang ◽  
Zhaoyan Yang ◽  
Zhuyuan Wang ◽  
...  
Keyword(s):  
Binding Sites ◽  
Super Resolution ◽  
Specific Adsorption ◽  
Nonspecific Binding ◽  
Nonspecific Adsorption ◽  
Multicolor Fluorescence

Non-specific adsorption in immunoassays has always been a major problem that affects the reliability of assay results. Despite the emergence of various methods which can reduce nonspecific adsorption, a universal...

scholarly journals A new method for high-resolution imaging of Ku foci to decipher mechanisms of DNA double-strand break repair

2013 ◽  
Vol 202 (3) ◽  
pp. 579-595 ◽  
Author(s):  
Sébastien Britton ◽  
Julia Coates ◽  
Stephen P. Jackson
Keyword(s):  
High Resolution ◽  
Single Molecule ◽  
Anticancer Agents ◽  
Spatial Organization ◽  
System Development ◽  
Super Resolution ◽  
Strand Break ◽  
Resistance Mechanisms ◽  
Original Method ◽  
Immune System Development

DNA double-strand breaks (DSBs) are the most toxic of all genomic insults, and pathways dealing with their signaling and repair are crucial to prevent cancer and for immune system development. Despite intense investigations, our knowledge of these pathways has been technically limited by our inability to detect the main repair factors at DSBs in cells. In this paper, we present an original method that involves a combination of ribonuclease- and detergent-based preextraction with high-resolution microscopy. This method allows direct visualization of previously hidden repair complexes, including the main DSB sensor Ku, at virtually any type of DSB, including those induced by anticancer agents. We demonstrate its broad range of applications by coupling it to laser microirradiation, super-resolution microscopy, and single-molecule counting to investigate the spatial organization and composition of repair factories. Furthermore, we use our method to monitor DNA repair and identify mechanisms of repair pathway choice, and we show its utility in defining cellular sensitivities and resistance mechanisms to anticancer agents.

The 3D Genome Structure of Single Cells

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Tianming Zhou ◽  
Ruochi Zhang ◽  
Jian Ma
Keyword(s):  
Single Cell ◽  
Data Science ◽  
Spatial Organization ◽  
Method Development ◽  
Single Cells ◽  
Genome Structure ◽  
Computational Method ◽  
Publication Date ◽  
3D Genome ◽  
Genome Features

The spatial organization of the genome in the cell nucleus is pivotal to cell function. However, how the 3D genome organization and its dynamics influence cellular phenotypes remains poorly understood. The very recent development of single-cell technologies for probing the 3D genome, especially single-cell Hi-C (scHi-C), has ushered in a new era of unveiling cell-to-cell variability of 3D genome features at an unprecedented resolution. Here, we review recent developments in computational approaches to the analysis of scHi-C, including data processing, dimensionality reduction, imputation for enhancing data quality, and the revealing of 3D genome features at single-cell resolution. While much progress has been made in computational method development to analyze single-cell 3D genomes, substantial future work is needed to improve data interpretation and multimodal data integration, which are critical to reveal fundamental connections between genome structure and function among heterogeneous cell populations in various biological contexts. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 4 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals Elucidating Binding Sites and Affinities of ERα Agonist and Antagonist to Human Alpha-Fetoprotein by in silico Modeling and Point Mutagenesis

2019 ◽  
Author(s):  
Nurbubu T. Moldogazieva ◽  
Daria S. Ostroverkhova ◽  
Nikolai N. Kuzmich ◽  
Vladimir V. Kadochnikov ◽  
Alexander A. Terentiev ◽  
...  
Keyword(s):  
Binding Sites ◽  
In Silico ◽  
Disulfide Bonds ◽  
Electrostatic Interactions ◽  
Molecular Mechanisms ◽  
3D Structure ◽  
Scoring Function ◽  
Alpha Fetoprotein ◽  
Ligand Interaction ◽  
Ligand Interactions

Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting variety of hydrophobic ligands including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth and this can be attributed to its estrogen-binding ability. Despite AFP has long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP-ligand interaction remain obscure. In our study we constructed homology-based 3D model of human AFP (HAFP) with the purpose to perform docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol) and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on ligand docked scoring function, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity sites were located in (i) a tunnel formed within HAFP subdomains IB and IIA and (ii) opposite side of the molecule in a groove originating from cavity formed between domains I and III, while (iii) the third low-affinity site was found at the bottom of the cavity. 100 ns MD simulation allowed studying their geometries and showed that HAFP-estrogen interactions occur due to van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP-antiestrogen binding. MM/GBSA rescoring method estimated binding free energies (ΔGbind) and showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP-ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues along two disulfide bonds, Cys224-Cys270 and Cys269-Cys277 have key roles in both HAFP-estrogen and HAFP-antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein-ligand interactions and anti-cancer therapy strategies based on ER-binding ligands.

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