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 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 Network-based method for regions with statistically frequent interchromosomal interactions at single-cell resolution

2020 ◽  
Vol 21 (S14) ◽  
Author(s):  
Chanaka Bulathsinghalage ◽  
Lu Liu
Keyword(s):  
Single Cell ◽  
Computational Methods ◽  
Spatial Organization ◽  
Gene Expression Regulation ◽  
Statistical Tests ◽  
Single Cells ◽  
Search Space ◽  
Computational Method ◽  
Frequency Information ◽  
Chromatin Interactions

Abstract Background Chromosome conformation capture-based methods, especially Hi-C, enable scientists to detect genome-wide chromatin interactions and study the spatial organization of chromatin, which plays important roles in gene expression regulation, DNA replication and repair etc. Thus, developing computational methods to unravel patterns behind the data becomes critical. Existing computational methods focus on intrachromosomal interactions and ignore interchromosomal interactions partly because there is no prior knowledge for interchromosomal interactions and the frequency of interchromosomal interactions is much lower while the search space is much larger. With the development of single-cell technologies, the advent of single-cell Hi-C makes interrogating the spatial structure of chromatin at single-cell resolution possible. It also brings a new type of frequency information, the number of single cells with chromatin interactions between two disjoint chromosome regions. Results Considering the lack of computational methods on interchromosomal interactions and the unsurprisingly frequent intrachromosomal interactions along the diagonal of a chromatin contact map, we propose a computational method dedicated to analyzing interchromosomal interactions of single-cell Hi-C with this new frequency information. To the best of our knowledge, our proposed tool is the first to identify regions with statistically frequent interchromosomal interactions at single-cell resolution. We demonstrate that the tool utilizing networks and binomial statistical tests can identify interesting structural regions through visualization, comparison and enrichment analysis and it also supports different configurations to provide users with flexibility. Conclusions It will be a useful tool for analyzing single-cell Hi-C interchromosomal interactions.

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

Gene insulation. Part II: natural strategies in vertebrates

2010 ◽  
Vol 88 (6) ◽  
pp. 885-898 ◽  
Author(s):  
Michèle Amouyal
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Protein Interactions ◽  
Dna Looping ◽  
Chromatin Domain ◽  
Trna Genes ◽  
Binding Factor ◽  
Genomic Environment ◽  
Nuclear Structures ◽  
Definition Of

The way a gene is insulated from its genomic environment in vertebrates is not basically different from what is observed in yeast and Drosophila (preceding article in this issue). If the formation of a looped chromatin domain, whether generated by attachment to the nuclear matrix or not, has become a classic way to confine an enhancer to a specific genomic domain and to coordinate, sequentially or simultaneously, gene expression in a given program, its role has been extended to new networks of genes or regulators within the same gene. A wider definition of the bases of the chromatin loops (nonchromosomal nuclear structures or genomic interacting elements) is also available. However, whereas insulation in Drosophila is due to a variety of proteins, in vertebrates insulators are still practically limited to CTCF (the CCCTC-binding factor), which appears in all cases to be the linchpin of an architecture that structures the assembly of DNA–protein interactions for gene regulation. As in yeast and Drosophila, the economy of means is the rule and the same unexpected diversion of known transcription elements (active or poised RNA polymerases, TFIIIC elements out of tRNA genes, permanent histone replacement) is observed, with variants peculiar to CTCF. Thus, besides structuring DNA looping, CTCF is a barrier to DNA methylation or interferes with all sorts of transcription processes, such as that generating heterochromatin.

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 High-throughput super-resolution analysis of influenza virus pleomorphism reveals insights into viral spatial organization

2021 ◽  
Author(s):  
Andrew McMahon ◽  
Rebecca Andrews ◽  
Sohail V Ghani ◽  
Thorben Cordes ◽  
Achillefs N Kapanidis ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Organization ◽  
Structural Information ◽  
Virus Assembly ◽  
Super Resolution ◽  
Automated Analysis ◽  
Size Analysis ◽  
Analysis Pipeline ◽  
Single Experiment ◽  
Viral Immunology

Many viruses form highly pleomorphic particles; in influenza, these particles range from spheres of ~ 100 nm in diameter to filaments of several microns in length. Virion structure is of interest, not only in the context of virus assembly, but also because pleomorphic variations may correlate with infectivity and pathogenicity. Detailed images of virus morphology often rely on electron microscopy, which is generally low throughput and limited in molecular identification. We have used fluorescence super-resolution microscopy combined with a rapid automated analysis pipeline to image many thousands of individual influenza virions, gaining information on their size, morphology and the distribution of membrane-embedded and internal proteins. This large-scale analysis revealed that influenza particles can be reliably characterised by length, that no spatial frequency patterning of the surface glycoproteins occurs, and that RNPs are preferentially located towards filament ends within Archetti bodies. Our analysis pipeline is versatile and can be adapted for use on multiple other pathogens, as demonstrated by its application for the size analysis of SARS-CoV-2. The ability to gain nanoscale structural information from many thousands of viruses in just a single experiment is valuable for the study of virus assembly mechanisms, host cell interactions and viral immunology, and should be able to contribute to the development of viral vaccines, anti-viral strategies and diagnostics.

scholarly journals Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

2019 ◽  
Author(s):  
Hesam Mazidi ◽  
Tianben Ding ◽  
Arye Nehorai ◽  
Matthew D. Lew
Keyword(s):  
Single Molecule ◽  
Computational Models ◽  
Amyloid Fibrils ◽  
Imaging System ◽  
Simulated Data ◽  
Super Resolution ◽  
Ground Truth ◽  
Localization Algorithm ◽  
Reconstruction Algorithms ◽  
Imaging Data

The resolution and accuracy of single-molecule localization micro-scopes (SMLMs) are routinely benchmarked using simulated data, calibration “rulers,” or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of recon-structed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

scholarly journals Using Connectivity to Explain Autism

2019 ◽  
Author(s):  
Jack Adamek ◽  
Yu Luo ◽  
Joshua Ewen
Keyword(s):  
Scientific Explanation ◽  
Causal Explanation ◽  
Autism Spectrum ◽  
Imaging Method ◽  
Imaging Data ◽  
Reverse Engineer ◽  
Physiological Processes ◽  
The Mind ◽  
The Brain

The chapters in this Handbook reveal the breadth of brilliant imaging and analysis techniques designed to fulfill the mandate of cognitive neuroscience: to understand how anatomical structures and physiological processes in the brain cause typical and atypical behavior. Yet merely producing data from the latest imaging method is insufficient to truly achieve this goal. We also need a mental toolbox that contains methods of inference that allow us to derive true scientific explanation from these data. Causal inference is not easy in the human brain, where we are limited primarily to observational data and our methods of experimental perturbation in the service of causal explanation are limited. As a case study, we reverse engineer one of the most influential accounts of a neuropsychiatric disorder that is derived from observational imaging data: the connectivity theories of autism spectrum disorder (ASD). We take readers through an approach of first considering all possible causal paths that are allowed by preliminary imaging-behavioral correlations. By progressively sharpening the specificity of the measures and brain/behavioral constructs, we iteratively chip away at this space of allowable causal paths, like the sculptor chipping away the excess marble to reveal the statue. To assist in this process, we consider how current imaging methods that are lumped together under the rubric of “connectivity” may actually offer a differentiated set of connectivity constructs that can more specifically relate notions of information transmission in the mind to the physiology of the brain.

scholarly journals Microvillar cartography: a super-resolution single-molecule imaging method to map the positions of membrane proteins with respect to cellular surface topography

2020 ◽  
Author(s):  
Shirsendu Ghosh ◽  
Ronen Alon ◽  
Andres Alcover ◽  
Gilad Haran
Keyword(s):  
Cell Surface ◽  
Single Molecule ◽  
Cell Activation ◽  
Super Resolution ◽  
Cell Receptor ◽  
Specific Protein ◽  
Surface Proteins ◽  
Imaging Method ◽  
Protein Distribution ◽  
Membrane Topography

AbstractWe introduce Microvillar Cartography (MC), a method to map proteins on cellular surfaces with respect to the membrane topography. The surfaces of many cells are not smooth, but are rather covered with various protrusions such as microvilli. These protrusions may play key roles in multiple cellular functions, due to their ability to control the distribution of specific protein assemblies on the cell surface. Thus, for example, we have shown that the T-cell receptor and several of its proximal signaling proteins reside on microvilli, while others are excluded from these projections. These results have indicated that microvilli can function as key signaling hubs for the initiation of the immune response. MC has facilitated our observations of particular surface proteins and their specialized distribution on microvillar and non-microvillar compartments. MC combines membrane topography imaging, using variable-angle total internal microscopy, with stochastic localization nanoscopy, which generates deep sub-diffraction maps of protein distribution. Since the method is based on light microscopy, it avoids some of the pitfalls inherent to electron-microscopy-based techniques, such as dehydration, carbon coating and immunogold clustering, and is amenable to future developments involving e.g. live-cell imaging. This Protocol details the procedures we developed for MC, which can be readily adopted to study a broad range of cell surface molecules and dissect their distribution within distinct surface assemblies under multiple cell activation states.

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