Biology subjects

Plewczynski, D.

Publications and source records attributed to Plewczynski, D..

31 records · Page 2Linked to original sources

bioRxiv2022

Inferring CTCF insulators and anchored loops across human tissues and cell types

CCCTC-binding factor (CTCF) is a transcription regulator which is involved in many cellular processes. How CTCF recognizes DNA sequence to exert chromosome barrier or enhancer blocking effects remains to be fully interrogated. Despite many computational tools were developed to predict CTCF-mediated loops qualitatively or quantitatively, few could specially evaluate the regulatory potential of DNA sequence at CTCF binding sites (CBSs) and how it affects chromatin loop formation. Here, we developed a deep learning model, DeepAnchor, to precisely characterize the binding patterns for different types of CBSs. By incorporating base-wise genomic/epigenomic features, we revealed distinct chromatin and sequence features for CTCF-mediated insulation and looping at a high resolution, such as two sequence motifs flanking the core CTCF motif at loop-associated CBSs. Besides, we leveraged the predicted anchor score to optimize the loop extrusion model and achieved the best performance in predicting CTCF-anchored loops. We established a compendium of context-specific CTCF-anchored loops across 52 human tissue/cell types and found that genomic disruption of CTCF-anchored loops may represent a general causal mechanism of disease pathogenesis. These computational models, together with the established resource, could facilitate the mechanistic research on how the CTCF-mediated cis-regulatory elements (CREs) shapes context-specific gene regulation in cell development and disease progression.

bioinformatics↗

bioRxiv2022

MCIBox: A Toolkit for Single-molecule Multi-way Chromatin Interaction Visualization and Micro-Domains Identification

The emerging ligation-free three-dimensional (3D) genome mapping technologies can identify multiplex chromatin interactions with single-molecule precision. These technologies offer new insight into high-dimensional chromatin organization and gene regulation, but also introduce new challenges in data visualization and analysis. To overcome these challenges, we developed MCIBox, a toolkit for Multi-way Chromatin Interaction (MCI) analysis, including a visualization tool and a platform for identifying micro-domains with clustered single-molecule chromatin complexes. MCIBox is based on various clustering algorithms integrated with dimensionality reduction methods that can display multiplex chromatin interactions at single-molecule level, allowing users to explore chromatin extrusion patterns and super-enhancers regulation modes in transcription, and to identify single-molecule chromatin complexes that are clustered into micro-domains. Furthermore, MCIBox incorporates a two-dimensional kernel density estimation algorithm to identify micro-domains boundaries automatically. These micro-domains were stratified with distinctive signatures of transcription activity and contained different cell cycle associated genes. MCIBox could potentially distinguish the specificity of single-molecule chromatin interaction patterns in various phases of a cell cycle or cell types.

genomics↗

bioRxiv2022

Multi-scale phase separation by explosive percolation with single chromatin loop resolution

The 2m-long human DNA is tightly intertwined into the cell nucleus of the size of 10m. The DNA packing is explained by folding of chromatin fiber. This folding leads to the formation of such hierarchical structures as: chromosomal territories, compartments; densely packed genomic regions known as Chromatin Contact Domains (CCDs), and loops. We propose models of dynamical genome folding into hierarchical components in human lymphoblastoid, stem cell, and fibroblast cell lines. Our models are based on explosive percolation theory. The chromosomes are modeled as graphs where CTCF chromatin loops are represented as edges. The folding trajectory is simulated by gradually introducing loops to the graph following various edge addition strategies that are based on topological network properties, chromatin loop frequencies, compartmentalization, or epigenomic features. Finally, we propose the genome folding model - a biophysical pseudo-time process guided by a single scalar order parameter. The parameter is calculated by Linear Discriminant Analysis. We simulate the loop formation by using Loop Extrusion Model (LEM) while adding them to the system. The chromatin phase separation, where fiber folds into topological domains and compartments, is observed when the critical number of contacts is reached. We also observe that 80% of the loops are needed for chromatin fiber to condense in 3D space, and this is constant through various cell lines. Overall, our in-silico model integrates the high-throughput 3D genome interaction experimental data with the novel theoretical concept of phase separation, which allows us to model event-based time dynamics of chromatin loop formation and folding trajectories.

genomics↗

bioRxiv2021

The 3D enhancer network of the developing T cell genome is controlled by SATB1

Mechanisms of tissue-specific gene expression regulation via spatial coordination of gene promoters and distal regulatory elements are still poorly understood. We investigated the 3D genome organization of developing murine T cells and identified SATB1, a tissue-specific genome organizer, enriched at the anchors of promoter-enhancer chromatin loops. We assessed the function of SATB1 in T cell chromatin organization and compared it to the conventional genome organizer CTCF. SATB1 builds a more refined layer of genome organization upon a CTCF scaffold. To understand the regulatory implications of SATB1 loopscape structure, we generated Satb1fl/flCd4-Cre+ (Satb1 cKO) conditional knockout animals which suffered from autoimmunity. We aimed to identify molecular mechanisms responsible for the deregulation of the immune system in Satb1 cKO animals. H3K27ac HiChIP and Hi-C experiments indicated that SATB1 primarily mediates promoter-enhancer loops affecting master regulator genes (such as Bcl6), the T cell receptor locus and adhesion molecule genes, collectively being critical for cell lineage specification and immune system homeostasis. Our findings unravel the function of a tissue-specific factor that controls transcription programs, via spatial chromatin arrangements complementary to the chromatin structure imposed by ubiquitously expressed genome organizers.

molecular biology↗

bioRxiv2021

Potent but transient immunosuppression of T-cells is a general feature of erythroid progenitor cells

CD71+ erythroid cells (CECs) have been recently recognized in both neonates and cancer patients as potent immunoregulatory cells. Here, we show that in mice early-stage CECs expand in anemia, have high levels of arginase 2 (ARG2) and reactive oxygen species (ROS). In the spleens of anemic mice, CECs expansion-induced L-arginine depletion suppresses T-cell responses. In humans with anemia, CECs expand and express ARG1 and ARG2 that suppress T-cells IFN-{gamma} production. Moreover, bone marrow CECs from healthy human donors suppress T-cells proliferation. CECs differentiated from peripheral blood mononuclear cells potently suppress T-cell activation, proliferation, and IFN-{gamma} production in an ARG- and ROS-dependent manner. These effects are the most prominent for early-stage CECs (CD71highCD235adim cells). The suppressive properties disappear during erythroid differentiation as more differentiated CECs and mature erythrocytes lack significant immunoregulatory properties. Our studies provide a novel insight into the role of CECs in the immune response regulation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/427109v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@136fbd8org.highwire.dtl.DTLVardef@d05d00org.highwire.dtl.DTLVardef@189baceorg.highwire.dtl.DTLVardef@1472b2b_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2020

SeqPIP-2020: Sequence based Protein InteractionPrediction Contest

Computational protein-protein interaction (PPI) prediction techniques can contribute greatly in reducing time, cost and false-positive interactions compared to experimental approaches. Sequence is one of the key and primary information of proteins that plays a crucial role in PPI prediction. Several machine learning approaches have been applied to exploit the characteristics of PPI datasets. However, these datasets greatly influence the performance of predicting models. So, care should be taken on both dataset curation as well as design of predictive models. Here, we summarize the results of the SeqPIP competition whose objective was to develop comprehensive PPI predictive models from sequence information with high-quality bias-free interaction datasets. A training set of 2000 positive and 2000 negative interactions with sequences was given to each contestant. The methods were evaluated with three independent high-quality interaction test datasets.

bioinformatics↗

bioRxiv2020

PartSeg, a Tool for Quantitative Feature Extraction From 3D Microscopy Images for Dummies

BackgroundBioimaging techniques offer a robust tool for studying molecular pathways and morphological phenotypes of cell populations subjected to various conditions. As modern high resolution 3D microscopy provides access to an ever-increasing amount of high quality images, there arises a need for their analysis in an automated, unbiased and simple way. Segmentation of structures within cell nucleus, which is the focus of this paper, presents a new layer of complexity in the form of dense packing and significant signal overlap. At the same time the available segmentation tools provide a steep learning curve for new users with limited technical background. This is especially apparent in bulk processing of image sets, which requires the use of some form of programming notation. ResultsIn this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of cell nucleus. PartSeg integrates refined versions of several state-of-the-art algorithms, including a new multi-scale approach for segmentation and quantitative analysis of 3D microscopy images. The features and user-friendly interface of PartSeg were carefully planned with biologists in mind, based on analysis of multiple use cases and difficulties encountered with other tools, to offer ergonomic interface with a minimal entry barrier. Bulk processing in an ad-hoc manner is possible without the need for programmer support. As the size of datasets of interest grows, such bulk processing solutions become essential for proper statistical analysis of results. Advanced users can use PartSeg components as a library within Python data processing and visualisation pipelines, for example within Jupyter notebooks. The tool is extensible so that new functionality and algorithms can be added by the use of plugins. For biologists the utility of PartSeg is presented in several scenarios, showing the quantitative analysis of nuclear structures. ConclusionsIn this paper, we have presented PartSeg which is a tool for precise and verifiable segmentation and reconstruction of 3D microscopy images. PartSeg is optimised for cell nucleus analysis and offers multiscale segmentation algorithms best-suited for this task. PartSeg can also be used for bulk processing of multiple images and its components can be reused in other systems or computational experiments. Contact g.bokota@cent.uw.edu.pl, a.magalska@nencki.edu.pl, d.plewczynski@cent.uw.edu.pl

bioinformatics↗

bioRxiv2020

Ultrastructural Visualization of 3D Chromatin Folding Using Serial Block-Face Scanning Electron Microscopy and In Situ Hybridization (3D-EMISH)

The human genome is extensively folded into 3-dimensional organization, yet the detailed 3D chromatin folding structures have not been fully visualized due to the lack of robust and ultra- resolution imaging capability. Here, we report the development of a novel electron microscopy method that combines serial block-face scanning electron microscopy with in situ hybridization (3D-EMISH) to visualize 3D chromatin folding at targeted genomic regions with ultra-resolution (5x5x30 nm in xyz dimensions, respectively). We applied 3D-EMISH to human lymphoblastoid cells at a 1.7 Mb segment of the genome and visualized a large number of distinctive 3D chromatin folding structures in high ultra-resolution. We further quantitatively characterized the reconstituted chromatin folding structures by identifying sub-domains, and uncovered a high level of heterogeneity in chromatin folding ultrastructures, suggestive of extensive dynamic fluidity in 3D chromatin states.

genomics↗

bioRxiv2019

3dSpAn: an interactive software for 3D segmentation and analysis of dendritic spines

Three dimensional segmentation and analysis of dendritic spines involve two major challenges: 1) how to segment individual spines from the dendrites and 2) how to quantitatively assess the morphology of individual spines. We developed a software named 3dSpAn to address these two issues by implementing our previously published 3D multiscale opening algorithm in shared intensity space and using effective morphological features for individual dendritic spine plasticity analysis. 3dSpAn consists of four modules: Preprocessing and ROI selection, Intensity thresholding and seed selection, Multiscale segmentation and Quantitative morphological feature extraction. We show the results of segmentation and morphological analysis for different observation methods, including in vitro and ex vivo imaging with confocal microscopy, and in vivo samples, using high-resolution two-photon microscopy. The software is freely available, the source code, windows installer, the software manual and video tutorial can be obtained from: https://sites.google.com/view/3dSpAn/.

neuroscience↗

bioRxiv2019

Spring Model - chromatin modeling tool based on OpenMM

Chromatin structures modelling is a rapidly developing field. Parallel to the enormous growth of available experimental data, there is a growing need of building and visualizing 3D structures of nuclei, chromosomes, chromatin domains, and single loops associated with particular genes locus. Here we present a tool for chromatin domain modeling. It is available as a webserver and standalone python script. Our tool is based on molecular mechanics. It uses OpenMM engine for building models. In this method, the user has to provide contacts and will obtain 3D structure that satisfies these contacts. Additional extra parameters allow controlling fibre stiffness, type of initial structure, resolution. There are also options for structure refinement, and modelling in a spherical container. A user may provide contacts using beads indices, or paste interactions in genome coordinates from BEDPE file. After modelling user is able to download the structure in Protein Data Bank (PDB) file format for further analysis.\n\nWe dedicate this tool for all who are interested in chromatin structures. It is suitable for quick visualization of datasets, studying the impact of structural variants (SVs), inspecting the effects of adding and removing particular contacts, measuring features like maximum distances between certain sites (e.g. promotor-enhancer) or local density of chromatin.

genomics↗

bioRxiv2019

Super resolution imaging of a distinct chromatin loop in human lymphoblastoid cells

The three-dimensional genome structure plays a fundamental role in gene regulation and cellular functions. Recent studies in genomics based on sequencing technologies inferred the very basic functional chromatin folding structures of the genome known as chromatin loops, the long-range chromatin interactions that are often mediated by protein factors. To visualize the looping structure of chromatin we applied super-resolution microscopy iPALM to image a specific chromatin loop in GM12878 cells. Totally, we have generated six images of the target chromatin region at the single molecule resolution. To infer the chromatin structures from the captured images, we modeled them as looping conformations using different computational algorithms and then evaluated the models by comparing with Hi-C data to examine the concordance. The results showed a good correlation between the imaging data and sequencing data, suggesting the visualization of higher-order chromatin structures for the very short genomic segments can be realized by microscopic imaging.

molecular biology↗

bioRxiv2018

Spatial Chromatin Architecture Alteration by Structural Variations in Human Genomes at Population Scale

This genome-wide study is focused on the impact of structural variants identified in individuals from 26 human populations onto three-dimensional structures of their genomes. We assess the tendency of structural variants to accumulate in spatially interacting genomic segments and design a high-resolution computational algorithm to model the 3D conformational changes resulted by structural variations. We show that differential gene transcription is closely linked to variation in chromatin interaction networks mediated by RNA polymerase II. We also demonstrate that CTCF-mediated interactions are well conserved across population, but enriched with disease-associated SNPs. Altogether, this study assesses the critical impact of structural variants on the higher order organization of chromatin folding and provides unique insight into the mechanisms regulating gene transcription at the population scale, among which the local arrangement of chromatin loops seems to be the leading one. It is the first insight into the variability of the human 3D genome at the population scale.

genomics↗

bioRxiv2017

Free energy based high-resolution modeling of CTCF-mediated chromatin loops for human genome

A thermodynamic method for computing the stability and dynamics of chromatin loops is proposed. The CTCF-mediated interactions as observed in ChIA-PET experiments for human B-lymphoblastoid cells are evaluated in terms of a polymer model for chain folding physical properties and the experimentally observed frequency of contacts within the chromatin regions. To estimate the optimal free energy and a Boltzmann distribution of suboptimal structures, the approach uses dynamic programming with methods to handle degeneracy and heuristics to compute parallel and antiparallel chain stems and pseudoknots. Moreover, multiple loops mediated by CTCF proteins connected together and forming multimeric islands are simulated using the same model. Based on the thermodynamic properties of those topological three-dimensional structures, we predict the correlation between the relative activity of chromatin loop and the Boltzmann probability, or the minimum free energy, depending also on its genomic length. Segments of chromatin where the structures show a more stable minimum free energy (for a given genomic distance) tend to be inactive, whereas structures that have lower stability in the minimum free energy (with the same genomic distance) tend to be active.

genomics↗