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Han MH, Issagulova D, Park M. Interplay between epigenome and 3D chromatin structure. BMB Rep 2023; 56:633-644. [PMID: 38052424 PMCID: PMC10761748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 11/28/2023] [Accepted: 12/05/2023] [Indexed: 12/07/2023] Open
Abstract
Epigenetic mechanisms, primarily mediated through histone and DNA modifications, play a pivotal role in orchestrating the functional identity of a cell and its response to environmental cues. Similarly, the spatial arrangement of chromatin within the threedimensional (3D) nucleus has been recognized as a significant factor influencing genomic function. Investigating the relationship between epigenetic regulation and 3D chromatin structure has revealed correlation and causality between these processes, from the global alignment of average chromatin structure with chromatin marks to the nuanced correlations at smaller scales. This review aims to dissect the biological significance and the interplay between the epigenome and 3D chromatin structure, while also exploring the underlying molecular mechanisms. By synthesizing insights from both experimental and modeling perspectives, we seek to provide a comprehensive understanding of cellular functions. [BMB Reports 2023; 56(12): 633-644].
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Affiliation(s)
- Man-Hyuk Han
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Dariya Issagulova
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Minhee Park
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea; Graduate School of Engineering Biology, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141; KAIST Institute for the BioCentury, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141; KAIST Stem Cell Center, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
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2
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Pancaldi V. Network models of chromatin structure. Curr Opin Genet Dev 2023; 80:102051. [PMID: 37245241 DOI: 10.1016/j.gde.2023.102051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/30/2023]
Abstract
Increasing numbers of datasets and experimental assays that capture the organization of chromatin inside the nucleus warrant an effort to develop tools to visualize and analyze these structures. Alongside polymer physics or constraint-based modeling, network theory approaches to describe 3D epigenome organization have gained in popularity. Representing genomic regions as nodes in a network enables visualization of 1D epigenomics datasets in the context of chromatin structure maps, while network theory metrics can be used to describe 3D epigenome organization and dynamics. In this review, we summarize the most salient applications of network theory to the study of chromatin contact maps, demonstrating its potential in revealing epigenomic patterns and relating them to cellular phenotypes.
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Affiliation(s)
- Vera Pancaldi
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France.
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3
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Tan ZW, Toong PJ, Guarnera E, Berezovsky IN. Disrupted chromatin architecture in olfactory sensory neurons: looking for the link from COVID-19 infection to anosmia. Sci Rep 2023; 13:5906. [PMID: 37041182 PMCID: PMC10088727 DOI: 10.1038/s41598-023-32896-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Accepted: 04/04/2023] [Indexed: 04/13/2023] Open
Abstract
We tackle here genomic mechanisms of a rapid onset and recovery from anosmia-a potential diagnostic indicator for early-stage COVID-19 infection. Based on previous observations on how olfactory receptor (OR) gene expression is regulated via chromatin structure in mice, we hypothesized that the disruption of the OR gene expression and, respectively, deficiency of the OR function can be caused by chromatin reorganization taking place upon SARS-CoV-2 infection. We obtained chromatin ensemble reconstructions from COVID-19 patients and control samples using our original computational framework for the whole-genome 3D chromatin ensemble reconstruction. Specifically, we used megabase-scale structural units and effective interactions between them obtained in the Markov State modelling of the Hi-C contact network as an unput in the stochastic embedding procedure of the whole-genome 3D chromatin ensemble reconstruction. We have also developed here a new procedure for analyzing fine structural hierarchy with (sub)TAD-size units in local chromatin regions, which we apply here to parts of chromosomes containing OR genes and corresponding regulatory elements. We observed structural modifications in COVID-19 patients on different levels of chromatin organization, from the alteration of whole genome structure and chromosomal intermingling to reorganization of contacts between chromatin loops at the level of topologically associating domains. While complementary data on known regulatory elements point to potential pathology-associated changes within the overall picture of chromatin alterations, further investigation using additional epigenetic factors mapped on 3D reconstructions with improved resolution will be required for better understanding of anosmia caused by SARS-CoV-2 infection.
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Affiliation(s)
- Zhen Wah Tan
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore
| | - Ping Jing Toong
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore
| | - Enrico Guarnera
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore
- Computational Drug Discovery, EMD Serono Research and Development Institute, Merck KGaA, 45A Middlesex Tpke, Billerica, MA, 01821, USA
| | - Igor N Berezovsky
- Agency for Science, Technology and Research (A*STAR), Bioinformatics Institute (BII), 30 Biopolis Street, Matrix, Singapore, 138671, Republic of Singapore.
- Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore, 117597, Singapore.
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4
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Zimatore G, Tsuchiya M, Hashimoto M, Kasperski A, Giuliani A. Self-organization of whole-gene expression through coordinated chromatin structural transition. BIOPHYSICS REVIEWS 2021; 2:031303. [PMID: 38505632 PMCID: PMC10903504 DOI: 10.1063/5.0058511] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 08/20/2021] [Indexed: 03/21/2024]
Abstract
The human DNA molecule is a 2-m-long polymer collapsed into the micrometer space of the cell nucleus. This simple consideration rules out any "Maxwell demon"-like explanation of regulation in which a single regulatory molecule (e.g., a transcription factor) finds autonomously its way to the particular target gene whose expression must be repressed or enhanced. A gene-by-gene regulation is still more contrasting with the physical reality when in the presence of cell state transitions involving the contemporary expression change of thousands of genes. This state of affair asks for a statistical mechanics inspired approach where specificity arises from a selective unfolding of chromatin driving the rewiring of gene expression pattern. The arising of "expression waves" marking state transitions related to chromatin structural reorganization through self-organized critical control of whole-genome expression will be described in the present paper. We adopt as a model system the gene expression time course of a cancer cell (MCF-7) population exposed to an efficient stimulus causing a state transition in comparison with an ineffective stimulus. The obtained results will be put into the perspective of biological adaptive systems living on the edge of chaos.
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Affiliation(s)
- Giovanna Zimatore
- eCampus University, 22060 Novedrate, Como, Italy and CNR-IMM Bologna, Italy
| | - Masa Tsuchiya
- SEIKO Life Science Laboratory, SEIKO Research Institute for Education, Osaka 540-659, Japan
| | - Midori Hashimoto
- Japan Fisheries Research and Education Agency, Kanagawa 236-8648, Japan
| | - Andrzej Kasperski
- Institute of Biological Sciences, Department of Biotechnology, University of Zielona Góra, ul. Szafrana 1, 65-516 Zielona Góra, Poland
| | - Alessandro Giuliani
- Environment and Health Department, Istituto Superiore di Sanitá, 00161 Rome, Italy
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5
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Guarnera E, Tan ZW, Berezovsky IN. Three-dimensional chromatin ensemble reconstruction via stochastic embedding. Structure 2021; 29:622-634.e3. [PMID: 33567266 DOI: 10.1016/j.str.2021.01.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 11/17/2020] [Accepted: 01/13/2021] [Indexed: 01/04/2023]
Abstract
We propose a comprehensive method for reconstructing the whole-genome chromatin ensemble from the Hi-C data. The procedure starts from Markov state modeling (MSM), delineating the structural hierarchy of chromatin organization with partitioning and effective interactions archetypal for corresponding levels of hierarchy. The stochastic embedding procedure introduced in this work provides the 3D ensemble reconstruction, using effective interactions obtained by the MSM as the input. As a result, we obtain the structural ensemble of a genome, allowing one to model the functional and the cell-type variability in the chromatin structure. The whole-genome reconstructions performed on the human B lymphoblastoid (GM12878) and lung fibroblast (IMR90) Hi-C data unravel distinctions in their morphologies and in the spatial arrangement of intermingling chromosomal territories, paving the way to studies of chromatin dynamics, developmental changes, and conformational transitions taking place in normal cells and during potential pathological developments.
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Affiliation(s)
- Enrico Guarnera
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A(∗)STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Zhen Wah Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A(∗)STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore
| | - Igor N Berezovsky
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A(∗)STAR), 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore; Department of Biological Sciences (DBS), National University of Singapore (NUS), 8 Medical Drive, Singapore 117597, Singapore.
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6
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Madrid-Mencía M, Raineri E, Cao TBN, Pancaldi V. Using GARDEN-NET and ChAseR to explore human haematopoietic 3D chromatin interaction networks. Nucleic Acids Res 2020; 48:4066-4080. [PMID: 32182345 PMCID: PMC7192625 DOI: 10.1093/nar/gkaa159] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 02/21/2020] [Accepted: 03/02/2020] [Indexed: 12/31/2022] Open
Abstract
We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks, exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology properties. We demonstrate the approach using published epigenomic and chromatin structure datasets in haematopoietic cells, including a collection of gene expression, DNA methylation and histone modifications data in primary healthy myeloid cells from hundreds of individuals. These datasets allow us to test the robustness of chromatin assortativity, which highlights which epigenomic features, alone or in combination, are more strongly associated with 3D genome architecture. We find evidence for genomic regions with specific histone modifications, DNA methylation, and gene expression levels to be forming preferential contacts in 3D nuclear space, to a different extent depending on the cell type and lineage. Finally, we examine replication timing data and find it to be the genomic feature most strongly associated with overall 3D chromatin organization at multiple scales, consistent with previous results from the literature.
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Affiliation(s)
- Miguel Madrid-Mencía
- Centre de Recherches en Cancérologie de Toulouse (CRCT), INSERM U1037, Toulouse 31037, France.,Université Paul Sabatier III, Toulouse 31400, Toulouse, France.,Barcelona Supercomputing Center, Barcelona 08034, Spain
| | - Emanuele Raineri
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Barcelona 08028, Spain
| | - Tran Bich Ngoc Cao
- Pharmacological, Medical and Agronomical Biotechnology Department, University of Science and Technology of Hanoi, 100000, Vietnam
| | - Vera Pancaldi
- Centre de Recherches en Cancérologie de Toulouse (CRCT), INSERM U1037, Toulouse 31037, France.,Université Paul Sabatier III, Toulouse 31400, Toulouse, France.,Barcelona Supercomputing Center, Barcelona 08034, Spain
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7
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Zhang S, Chen F, Bahar I. Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation. Nucleic Acids Res 2020; 48:1131-1145. [PMID: 31828312 PMCID: PMC7026660 DOI: 10.1093/nar/gkz1102] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Revised: 11/01/2019] [Accepted: 11/22/2019] [Indexed: 12/19/2022] Open
Abstract
Advances in chromosome conformation capture techniques as well as computational characterization of genomic loci structural dynamics open new opportunities for exploring the mechanistic aspects of genome-scale differences across different cell types. We examined here the dynamic basis of variabilities between different cell types by investigating their chromatin mobility profiles inferred from Hi-C data using an elastic network model representation of the chromatin. Our comparative analysis of sixteen cell lines reveals close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations emerge in the detailed spatial mobilities of genomic loci. Closer examination reveals that the differences in spatial dynamics mainly originate from the difference in the frequencies of their intrinsically accessible modes of motion. Thus, even though the chromosomes of different types of cells have access to similar modes of collective movements, not all modes are deployed by all cells, such that the effective mobilities and cross-correlations of genomic loci are cell-type-specific. Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation.
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Affiliation(s)
- She Zhang
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Fangyuan Chen
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.,School of Medicine, Tsinghua University, Beijing 100084, China
| | - Ivet Bahar
- Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
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Nussinov R, Tsai CJ, Shehu A, Jang H. Computational Structural Biology: Successes, Future Directions, and Challenges. Molecules 2019; 24:molecules24030637. [PMID: 30759724 PMCID: PMC6384756 DOI: 10.3390/molecules24030637] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 02/05/2019] [Accepted: 02/10/2019] [Indexed: 02/06/2023] Open
Abstract
Computational biology has made powerful advances. Among these, trends in human health have been uncovered through heterogeneous 'big data' integration, and disease-associated genes were identified and classified. Along a different front, the dynamic organization of chromatin is being elucidated to gain insight into the fundamental question of genome regulation. Powerful conformational sampling methods have also been developed to yield a detailed molecular view of cellular processes. when combining these methods with the advancements in the modeling of supramolecular assemblies, including those at the membrane, we are finally able to get a glimpse into how cells' actions are regulated. Perhaps most intriguingly, a major thrust is on to decipher the mystery of how the brain is coded. Here, we aim to provide a broad, yet concise, sketch of modern aspects of computational biology, with a special focus on computational structural biology. We attempt to forecast the areas that computational structural biology will embrace in the future and the challenges that it may face. We skirt details, highlight successes, note failures, and map directions.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
- Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
| | - Amarda Shehu
- Departments of Computer Science, Department of Bioengineering, and School of Systems Biology, George Mason University, Fairfax, VA 22030, USA.
| | - Hyunbum Jang
- Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA.
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