1
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Saavedra LA, Mosqueira A, Barrantes FJ. A supervised graph-based deep learning algorithm to detect and quantify clustered particles. NANOSCALE 2024; 16:15308-15318. [PMID: 39082742 DOI: 10.1039/d4nr01944j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/16/2024]
Abstract
Considerable efforts are currently being devoted to characterizing the topography of membrane-embedded proteins using combinations of biophysical and numerical analytical approaches. In this work, we present an end-to-end (i.e., human intervention-independent) algorithm consisting of two concatenated binary Graph Neural Network (GNNs) classifiers with the aim of detecting and quantifying dynamic clustering of particles. As the algorithm only needs simulated data to train the GNNs, it is parameter-independent. The GNN-based algorithm is first tested on datasets based on simulated, albeit biologically realistic data, and validated on actual fluorescence microscopy experimental data. Application of the new GNN method is shown to be faster than other currently used approaches for high-dimensional SMLM datasets, with the additional advantage that it can be implemented on standard desktop computers. Furthermore, GNN models obtained via training procedures are reusable. To the best of our knowledge, this is the first application of GNN-based approaches to the analysis of particle aggregation, with potential applications to the study of nanoscopic particles like the nanoclusters of membrane-associated proteins in live cells.
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Affiliation(s)
- Lucas A Saavedra
- Laboratory of Molecular Neurobiology, Biomedical Research institute (BIOMED), UCA-CONICET, Av. Alicia Moreau de Justo 1600, C1107AFF Buenos Aires, Argentina.
| | - Alejo Mosqueira
- Laboratory of Molecular Neurobiology, Biomedical Research institute (BIOMED), UCA-CONICET, Av. Alicia Moreau de Justo 1600, C1107AFF Buenos Aires, Argentina.
| | - Francisco J Barrantes
- Laboratory of Molecular Neurobiology, Biomedical Research institute (BIOMED), UCA-CONICET, Av. Alicia Moreau de Justo 1600, C1107AFF Buenos Aires, Argentina.
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2
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Pessoa J, Carvalho C. Human RNA Polymerase II Segregates from Genes and Nascent RNA and Transcribes in the Presence of DNA-Bound dCas9. Int J Mol Sci 2024; 25:8411. [PMID: 39125980 PMCID: PMC11312690 DOI: 10.3390/ijms25158411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 07/21/2024] [Accepted: 07/27/2024] [Indexed: 08/12/2024] Open
Abstract
RNA polymerase II (Pol II) dysfunction is frequently implied in human disease. Understanding its functional mechanism is essential for designing innovative therapeutic strategies. To visualize its supra-molecular interactions with genes and nascent RNA, we generated a human cell line carrying ~335 consecutive copies of a recombinant β-globin gene. Confocal microscopy showed that Pol II was not homogeneously concentrated around these identical gene copies. Moreover, Pol II signals partially overlapped with the genes and their nascent RNA, revealing extensive compartmentalization. Using a cell line carrying a single copy of the β-globin gene, we also tested if the binding of catalytically dead CRISPR-associated system 9 (dCas9) to different gene regions affected Pol II transcriptional activity. We assessed Pol II localization and nascent RNA levels using chromatin immunoprecipitation and droplet digital reverse transcription PCR, respectively. Some enrichment of transcriptionally paused Pol II accumulated in the promoter region was detected in a strand-specific way of gRNA binding, and there was no decrease in nascent RNA levels. Pol II preserved its transcriptional activity in the presence of DNA-bound dCas9. Our findings contribute further insight into the complex mechanism of mRNA transcription in human cells.
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Affiliation(s)
- João Pessoa
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina da Universidade de Lisboa, 1649-028 Lisboa, Portugal;
- Department of Medical Sciences and Institute of Biomedicine—iBiMED, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Célia Carvalho
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina da Universidade de Lisboa, 1649-028 Lisboa, Portugal;
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3
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Pradhan SK, Lozoya T, Prorok P, Yuan Y, Lehmkuhl A, Zhang P, Cardoso MC. Developmental Changes in Genome Replication Progression in Pluripotent versus Differentiated Human Cells. Genes (Basel) 2024; 15:305. [PMID: 38540366 PMCID: PMC10969796 DOI: 10.3390/genes15030305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 02/22/2024] [Accepted: 02/23/2024] [Indexed: 06/14/2024] Open
Abstract
DNA replication is a fundamental process ensuring the maintenance of the genome each time cells divide. This is particularly relevant early in development when cells divide profusely, later giving rise to entire organs. Here, we analyze and compare the genome replication progression in human embryonic stem cells, induced pluripotent stem cells, and differentiated cells. Using single-cell microscopic approaches, we map the spatio-temporal genome replication as a function of chromatin marks/compaction level. Furthermore, we mapped the replication timing of subchromosomal tandem repeat regions and interspersed repeat sequence elements. Albeit the majority of these genomic repeats did not change their replication timing from pluripotent to differentiated cells, we found developmental changes in the replication timing of rDNA repeats. Comparing single-cell super-resolution microscopic data with data from genome-wide sequencing approaches showed comparable numbers of replicons and large overlap in origins numbers and genomic location among developmental states with a generally higher origin variability in pluripotent cells. Using ratiometric analysis of incorporated nucleotides normalized per replisome in single cells, we uncovered differences in fork speed throughout the S phase in pluripotent cells but not in somatic cells. Altogether, our data define similarities and differences on the replication program and characteristics in human cells at different developmental states.
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Affiliation(s)
- Sunil Kumar Pradhan
- Cell Biology and Epigenetics, Department of Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany; (S.K.P.); (P.P.)
| | - Teresa Lozoya
- Cell Biology and Epigenetics, Department of Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany; (S.K.P.); (P.P.)
| | - Paulina Prorok
- Cell Biology and Epigenetics, Department of Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany; (S.K.P.); (P.P.)
| | - Yue Yuan
- Center for Tissue Engineering and Stem Cell Research, Guizhou Medical University, Guiyang 550004, China;
| | - Anne Lehmkuhl
- Cell Biology and Epigenetics, Department of Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany; (S.K.P.); (P.P.)
| | - Peng Zhang
- Center for Tissue Engineering and Stem Cell Research, Guizhou Medical University, Guiyang 550004, China;
| | - M. Cristina Cardoso
- Cell Biology and Epigenetics, Department of Biology, Technical University of Darmstadt, 64287 Darmstadt, Germany; (S.K.P.); (P.P.)
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4
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Du M, Stitzinger SH, Spille JH, Cho WK, Lee C, Hijaz M, Quintana A, Cissé II. Direct observation of a condensate effect on super-enhancer controlled gene bursting. Cell 2024; 187:331-344.e17. [PMID: 38194964 DOI: 10.1016/j.cell.2023.12.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 10/29/2023] [Accepted: 12/04/2023] [Indexed: 01/11/2024]
Abstract
Enhancers are distal DNA elements believed to loop and contact promoters to control gene expression. Recently, we found diffraction-sized transcriptional condensates at genes controlled by clusters of enhancers (super-enhancers). However, a direct function of endogenous condensates in controlling gene expression remains elusive. Here, we develop live-cell super-resolution and multi-color 3D-imaging approaches to investigate putative roles of endogenous condensates in the regulation of super-enhancer controlled gene Sox2. In contrast to enhancer distance, we find instead that the condensate's positional dynamics are a better predictor of gene expression. A basal gene bursting occurs when the condensate is far (>1 μm), but burst size and frequency are enhanced when the condensate moves in proximity (<1 μm). Perturbations of cohesin and local DNA elements do not prevent basal bursting but affect the condensate and its burst enhancement. We propose a three-way kissing model whereby the condensate interacts transiently with gene locus and regulatory DNA elements to control gene bursting.
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Affiliation(s)
- Manyu Du
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Simon Hendrik Stitzinger
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Jan-Hendrik Spille
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Won-Ki Cho
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Choongman Lee
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Mohammed Hijaz
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Andrea Quintana
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany
| | - Ibrahim I Cissé
- Department of Biological Physics, Max Planck Institute for Immunobiology and Epigenetics, Freiburg im Breisgau, Baden-Württemberg 79108, Germany.
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5
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Hwang HJ, Park TL, Kim HI, Park Y, Kim G, Song C, Cho WK, Kim YK. YTHDF2 facilitates aggresome formation via UPF1 in an m 6A-independent manner. Nat Commun 2023; 14:6248. [PMID: 37803021 PMCID: PMC10558514 DOI: 10.1038/s41467-023-42015-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 09/27/2023] [Indexed: 10/08/2023] Open
Abstract
YTHDF2 has been extensively studied and typified as an RNA-binding protein that specifically recognizes and destabilizes RNAs harboring N6-methyladenosine (m6A), the most prevalent internal modification found in eukaryotic RNAs. In this study, we unravel the m6A-independent role of YTHDF2 in the formation of an aggresome, where cytoplasmic protein aggregates are selectively sequestered upon failure of protein homeostasis mediated by the ubiquitin-proteasome system. Downregulation of YTHDF2 in HeLa cells reduces the circularity of aggresomes and the rate of movement of misfolded polypeptides, inhibits aggresome formation, and thereby promotes cellular apoptosis. Mechanistically, YTHDF2 is recruited to a misfolded polypeptide-associated complex composed of UPF1, CTIF, eEF1A1, and DCTN1 through its interaction with UPF1. Subsequently, YTHDF2 increases the interaction between the dynein motor protein and the misfolded polypeptide-associated complex, facilitating the diffusion dynamics of the movement of misfolded polypeptides toward aggresomes. Therefore, our data reveal that YTHDF2 is a cellular factor involved in protein quality control.
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Affiliation(s)
- Hyun Jung Hwang
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Tae Lim Park
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Hyeong-In Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Yeonkyoung Park
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Geunhee Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Chiyeol Song
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
| | - Won-Ki Cho
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
| | - Yoon Ki Kim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
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6
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Dall'Agnese A, Platt JM, Zheng MM, Friesen M, Dall'Agnese G, Blaise AM, Spinelli JB, Henninger JE, Tevonian EN, Hannett NM, Lazaris C, Drescher HK, Bartsch LM, Kilgore HR, Jaenisch R, Griffith LG, Cisse II, Jeppesen JF, Lee TI, Young RA. The dynamic clustering of insulin receptor underlies its signaling and is disrupted in insulin resistance. Nat Commun 2022; 13:7522. [PMID: 36473871 PMCID: PMC9727033 DOI: 10.1038/s41467-022-35176-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022] Open
Abstract
Insulin receptor (IR) signaling is central to normal metabolic control and is dysregulated in metabolic diseases such as type 2 diabetes. We report here that IR is incorporated into dynamic clusters at the plasma membrane, in the cytoplasm and in the nucleus of human hepatocytes and adipocytes. Insulin stimulation promotes further incorporation of IR into these dynamic clusters in insulin-sensitive cells but not in insulin-resistant cells, where both IR accumulation and dynamic behavior are reduced. Treatment of insulin-resistant cells with metformin, a first-line drug used to treat type 2 diabetes, can rescue IR accumulation and the dynamic behavior of these clusters. This rescue is associated with metformin's role in reducing reactive oxygen species that interfere with normal dynamics. These results indicate that changes in the physico-mechanical features of IR clusters contribute to insulin resistance and have implications for improved therapeutic approaches.
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Affiliation(s)
| | - Jesse M Platt
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Ming M Zheng
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Max Friesen
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
| | - Giuseppe Dall'Agnese
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
- Department of Medicine, University of Udine, Udine, 33100, Italy
| | - Alyssa M Blaise
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
| | | | | | - Erin N Tevonian
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Nancy M Hannett
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
| | | | - Hannah K Drescher
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Lea M Bartsch
- Division of Gastroenterology, Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Henry R Kilgore
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
| | - Rudolf Jaenisch
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Linda G Griffith
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Center for Gynepathology Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ibrahim I Cisse
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jacob F Jeppesen
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA
- Global Drug Discovery, Novo Nordisk, Copenhagen, Denmark
| | - Tong I Lee
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA.
| | - Richard A Young
- Whitehead Institute for Biomedical Research, Cambridge, MA, 02142, USA.
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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7
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Barrantes FJ. Fluorescence microscopy imaging of a neurotransmitter receptor and its cell membrane lipid milieu. Front Mol Biosci 2022; 9:1014659. [PMID: 36518846 PMCID: PMC9743973 DOI: 10.3389/fmolb.2022.1014659] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/01/2022] [Indexed: 05/02/2024] Open
Abstract
Hampered by the diffraction phenomenon, as expressed in 1873 by Abbe, applications of optical microscopy to image biological structures were for a long time limited to resolutions above the ∼200 nm barrier and restricted to the observation of stained specimens. The introduction of fluorescence was a game changer, and since its inception it became the gold standard technique in biological microscopy. The plasma membrane is a tenuous envelope of 4 nm-10 nm in thickness surrounding the cell. Because of its highly versatile spectroscopic properties and availability of suitable instrumentation, fluorescence techniques epitomize the current approach to study this delicate structure and its molecular constituents. The wide spectral range covered by fluorescence, intimately linked to the availability of appropriate intrinsic and extrinsic probes, provides the ability to dissect membrane constituents at the molecular scale in the spatial domain. In addition, the time resolution capabilities of fluorescence methods provide complementary high precision for studying the behavior of membrane molecules in the time domain. This review illustrates the value of various fluorescence techniques to extract information on the topography and motion of plasma membrane receptors. To this end I resort to a paradigmatic membrane-bound neurotransmitter receptor, the nicotinic acetylcholine receptor (nAChR). The structural and dynamic picture emerging from studies of this prototypic pentameric ligand-gated ion channel can be extrapolated not only to other members of this superfamily of ion channels but to other membrane-bound proteins. I also briefly discuss the various emerging techniques in the field of biomembrane labeling with new organic chemistry strategies oriented to applications in fluorescence nanoscopy, the form of fluorescence microscopy that is expanding the depth and scope of interrogation of membrane-associated phenomena.
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Affiliation(s)
- Francisco J. Barrantes
- Biomedical Research Institute (BIOMED), Catholic University of Argentina (UCA)–National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
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8
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Wang H, Li B, Zuo L, Wang B, Yan Y, Tian K, Zhou R, Wang C, Chen X, Jiang Y, Zheng H, Qin F, Zhang B, Yu Y, Liu CP, Xu Y, Gao J, Qi Z, Deng W, Ji X. The transcriptional coactivator RUVBL2 regulates Pol II clustering with diverse transcription factors. Nat Commun 2022; 13:5703. [PMID: 36171202 PMCID: PMC9519968 DOI: 10.1038/s41467-022-33433-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 09/16/2022] [Indexed: 11/10/2022] Open
Abstract
RNA polymerase II (Pol II) apparatuses are compartmentalized into transcriptional clusters. Whether protein factors control these clusters remains unknown. In this study, we find that the ATPase-associated with diverse cellular activities (AAA + ) ATPase RUVBL2 co-occupies promoters with Pol II and various transcription factors. RUVBL2 interacts with unphosphorylated Pol II in chromatin to promote RPB1 carboxy-terminal domain (CTD) clustering and transcription initiation. Rapid depletion of RUVBL2 leads to a decrease in the number of Pol II clusters and inhibits nascent RNA synthesis, and tethering RUVBL2 to an active promoter enhances Pol II clustering at the promoter. We also identify target genes that are directly linked to the RUVBL2-Pol II axis. Many of these genes are hallmarks of cancers and encode proteins with diverse cellular functions. Our results demonstrate an emerging activity for RUVBL2 in regulating Pol II cluster formation in the nucleus. RNA polymerase II (Pol II) transcription factories play a central role in gene expression and 3D chromatin organization. Here, the authors demonstrate that RUVBL2 directly regulates Pol II clustering at active gene promoters.
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Affiliation(s)
- Hui Wang
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.,Department of Pathogenic Biology, Chengdu Medical College, Chengdu, 610500, China
| | - Boyuan Li
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Linyu Zuo
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Bo Wang
- Biomedical Pioneering Innovation Center (BIOPIC), Academy for Advanced Interdisciplinary Studies, Beijing Advanced Innovation Center for Genomics (ICG), Peking-Tsinghua Center for Life Sciences (CLS), School of Life Sciences, Peking University, Beijing, 100871, China
| | - Yan Yan
- Institute for TCM-X; MOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist (Beijing National Research Center for Information Science and Technology); Department of Automation, Tsinghua University, Beijing, 100084, China.,Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China
| | - Kai Tian
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Rong Zhou
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Chenlu Wang
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Xizi Chen
- Fudan University Shanghai Cancer Center, Institutes of Biomedical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Yongpeng Jiang
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Haonan Zheng
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
| | - Fangfei Qin
- Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, College of Chemistry and Molecular Engineering, Peking University, Beijing, 100871, China
| | - Bin Zhang
- Departments of Pathology and Laboratory Medicine, and Pediatrics, University of Rochester Medical Center, 601 Elmwood Ave, Box 608, Rochester, NY, 14642, USA
| | - Yang Yu
- Key Laboratory of RNA Biology, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chao-Pei Liu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yanhui Xu
- Fudan University Shanghai Cancer Center, Institutes of Biomedical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Juntao Gao
- Institute for TCM-X; MOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist (Beijing National Research Center for Information Science and Technology); Department of Automation, Tsinghua University, Beijing, 100084, China.,Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China
| | - Zhi Qi
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Wulan Deng
- Biomedical Pioneering Innovation Center (BIOPIC), Academy for Advanced Interdisciplinary Studies, Beijing Advanced Innovation Center for Genomics (ICG), Peking-Tsinghua Center for Life Sciences (CLS), School of Life Sciences, Peking University, Beijing, 100871, China
| | - Xiong Ji
- Key Laboratory of Cell Proliferation and Differentiation of the Ministry of Education, School of Life Sciences, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
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9
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Hijacking of transcriptional condensates by endogenous retroviruses. Nat Genet 2022; 54:1238-1247. [PMID: 35864192 PMCID: PMC9355880 DOI: 10.1038/s41588-022-01132-w] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 05/26/2022] [Indexed: 12/20/2022]
Abstract
Most endogenous retroviruses (ERVs) in mammals are incapable of retrotransposition; therefore, why ERV derepression is associated with lethality during early development has been a mystery. Here, we report that rapid and selective degradation of the heterochromatin adapter protein TRIM28 triggers dissociation of transcriptional condensates from loci encoding super-enhancer (SE)-driven pluripotency genes and their association with transcribed ERV loci in murine embryonic stem cells. Knockdown of ERV RNAs or forced expression of SE-enriched transcription factors rescued condensate localization at SEs in TRIM28-degraded cells. In a biochemical reconstitution system, ERV RNA facilitated partitioning of RNA polymerase II and the Mediator coactivator into phase-separated droplets. In TRIM28 knockout mouse embryos, single-cell RNA-seq analysis revealed specific depletion of pluripotent lineages. We propose that coding and noncoding nascent RNAs, including those produced by retrotransposons, may facilitate ‘hijacking’ of transcriptional condensates in various developmental and disease contexts. TRIM28 depletion in embryonic stem cells disconnects transcriptional condensates from super-enhancers, which is rescued by knockdown of endogenous retroviruses.
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10
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Na Z, Dai X, Zheng SJ, Bryant CJ, Loh KH, Su H, Luo Y, Buhagiar AF, Cao X, Baserga SJ, Chen S, Slavoff SA. Mapping subcellular localizations of unannotated microproteins and alternative proteins with MicroID. Mol Cell 2022; 82:2900-2911.e7. [PMID: 35905735 PMCID: PMC9662605 DOI: 10.1016/j.molcel.2022.06.035] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 04/08/2022] [Accepted: 06/29/2022] [Indexed: 11/15/2022]
Abstract
Proteogenomic identification of translated small open reading frames has revealed thousands of previously unannotated, largely uncharacterized microproteins, or polypeptides of less than 100 amino acids, and alternative proteins (alt-proteins) that are co-encoded with canonical proteins and are often larger. The subcellular localizations of microproteins and alt-proteins are generally unknown but can have significant implications for their functions. Proximity biotinylation is an attractive approach to define the protein composition of subcellular compartments in cells and in animals. Here, we developed a high-throughput technology to map unannotated microproteins and alt-proteins to subcellular localizations by proximity biotinylation with TurboID (MicroID). More than 150 microproteins and alt-proteins are associated with subnuclear organelles. One alt-protein, alt-LAMA3, localizes to the nucleolus and functions in pre-rRNA transcription. We applied MicroID in a mouse model, validating expression of a conserved nuclear microprotein, and establishing MicroID for discovery of microproteins and alt-proteins in vivo.
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Affiliation(s)
- Zhenkun Na
- Department of Chemistry, Yale University, New Haven, CT 06520, USA; Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT 06516, USA
| | - Xiaoyun Dai
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA; Systems Biology Institute, Yale University, West Haven, CT 06516, USA
| | - Shu-Jian Zheng
- Department of Chemistry, Yale University, New Haven, CT 06520, USA; Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT 06516, USA
| | - Carson J Bryant
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06529, USA
| | - Ken H Loh
- Laboratory of Molecular Genetics, Howard Hughes Medical Institute, The Rockefeller University, New York, NY 10065, USA
| | - Haomiao Su
- Department of Chemistry, Yale University, New Haven, CT 06520, USA; Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT 06516, USA
| | - Yang Luo
- Department of Chemistry, Yale University, New Haven, CT 06520, USA; Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT 06516, USA
| | - Amber F Buhagiar
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06529, USA
| | - Xiongwen Cao
- Department of Chemistry, Yale University, New Haven, CT 06520, USA; Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT 06516, USA
| | - Susan J Baserga
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06529, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA; Department of Therapeutic Radiology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Sidi Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06520, USA; Systems Biology Institute, Yale University, West Haven, CT 06516, USA
| | - Sarah A Slavoff
- Department of Chemistry, Yale University, New Haven, CT 06520, USA; Institute of Biomolecular Design and Discovery, Yale University, West Haven, CT 06516, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06529, USA.
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11
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Gormal RS, Meunier FA. Nanoscale organization of the pre-synapse: Tracking the neurotransmitter release machinery. Curr Opin Neurobiol 2022; 75:102576. [PMID: 35716557 DOI: 10.1016/j.conb.2022.102576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/02/2022] [Accepted: 05/11/2022] [Indexed: 11/18/2022]
Abstract
Chemical communication is underpinned by the fusion of neurotransmitter-containing synaptic vesicles with the plasma membrane at active zones. With the advent of super-resolution microscopy, the door is now opened to unravel the dynamic remodeling of synapses underpinning learning and memory. Imaging proteins with conventional light microscopy cannot provide submicron information vital to determining the nanoscale organization of the synapse. We will first review the current super-resolution microscopy techniques available to investigate the localization and movement of synaptic proteins and how they have been applied to visualize the synapse. We discuss the new techniques and analytical approaches have provided comprehensive insights into synaptic organization in various model systems. Finally, this review provides a brief update on how these super-resolution techniques and analyses have opened the way to a much greater understanding of the synapse, the fusion and compensatory endocytosis machinery.
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Affiliation(s)
- Rachel S Gormal
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia. https://twitter.com/rachelgormal
| | - Frédéric A Meunier
- Clem Jones Centre for Ageing Dementia Research, Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, 4072, Australia.
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12
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Ide S, Tamura S, Maeshima K. Chromatin behavior in living cells: Lessons from single‐nucleosome imaging and tracking. Bioessays 2022; 44:e2200043. [DOI: 10.1002/bies.202200043] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 04/24/2022] [Accepted: 04/26/2022] [Indexed: 11/05/2022]
Affiliation(s)
- Satoru Ide
- Genome Dynamics Laboratory National Institute of Genetics, ROIS Mishima Shizuoka Japan
- Department of Genetics School of Life Science SOKENDAI Mishima Shizuoka Japan
| | - Sachiko Tamura
- Genome Dynamics Laboratory National Institute of Genetics, ROIS Mishima Shizuoka Japan
| | - Kazuhiro Maeshima
- Genome Dynamics Laboratory National Institute of Genetics, ROIS Mishima Shizuoka Japan
- Department of Genetics School of Life Science SOKENDAI Mishima Shizuoka Japan
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13
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Lee R, Kang MK, Kim YJ, Yang B, Shim H, Kim S, Kim K, Yang CM, Min BG, Jung WJ, Lee EC, Joo JS, Park G, Cho WK, Kim HP. CTCF-mediated chromatin looping provides a topological framework for the formation of phase-separated transcriptional condensates. Nucleic Acids Res 2021; 50:207-226. [PMID: 34931241 PMCID: PMC8855298 DOI: 10.1093/nar/gkab1242] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 11/22/2021] [Accepted: 12/03/2021] [Indexed: 12/31/2022] Open
Abstract
CTCF is crucial to the organization of mammalian genomes into loop structures. According to recent studies, the transcription apparatus is compartmentalized and concentrated at super-enhancers to form phase-separated condensates and drive the expression of cell-identity genes. However, it remains unclear whether and how transcriptional condensates are coupled to higher-order chromatin organization. Here, we show that CTCF is essential for RNA polymerase II (Pol II)-mediated chromatin interactions, which occur as hyperconnected spatial clusters at super-enhancers. We also demonstrate that CTCF clustering, unlike Pol II clustering, is independent of liquid-liquid phase-separation and resistant to perturbation of transcription. Interestingly, clusters of Pol II, BRD4, and MED1 were found to dissolve upon CTCF depletion, but were reinstated upon restoration of CTCF, suggesting a potent instructive function for CTCF in the formation of transcriptional condensates. Overall, we provide evidence suggesting that CTCF-mediated chromatin looping acts as an architectural prerequisite for the assembly of phase-separated transcriptional condensates.
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Affiliation(s)
- Ryanggeun Lee
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.,College of Natural Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Moo-Koo Kang
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Yong-Jin Kim
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Bobae Yang
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Hwanyong Shim
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Sugyung Kim
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Kyungwoo Kim
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Chul Min Yang
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Byeong-Gyu Min
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Woong-Jae Jung
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Eun-Chong Lee
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Jung-Sik Joo
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
| | - Gunhee Park
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Won-Ki Cho
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea.,KI for Health Science and Technology (KIHST), Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Korea
| | - Hyoung-Pyo Kim
- Department of Environmental Medical Biology, Institute of Tropical Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Brain Korea 21 PLUS Project for Medical Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.,Yonsei Genome Center, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea
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14
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Itoh Y, Woods EJ, Minami K, Maeshima K, Collepardo-Guevara R. Liquid-like chromatin in the cell: What can we learn from imaging and computational modeling? Curr Opin Struct Biol 2021; 71:123-135. [PMID: 34303931 DOI: 10.1016/j.sbi.2021.06.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 06/08/2021] [Indexed: 12/23/2022]
Abstract
Chromatin in eukaryotic cells is a negatively charged long polymer consisting of DNA, histones, and various associated proteins. With its highly charged and heterogeneous nature, chromatin structure varies greatly depending on various factors (e.g. chemical modifications and protein enrichment) and the surrounding environment (e.g. cations): from a 10-nm fiber, a folded 30-nm fiber, to chromatin condensates/droplets. Recent advanced imaging has observed that chromatin exhibits a dynamic liquid-like behavior and undergoes structural variations within the cell. Current computational modeling has made it possible to reconstruct the liquid-like chromatin in the cell by dealing with a number of nucleosomes on multiscale levels and has become a powerful technique to inspect the molecular mechanisms giving rise to the observed behavior, which imaging methods cannot do on their own. Based on new findings from both imaging and modeling studies, we discuss the dynamic aspect of chromatin in living cells and its functional relevance.
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Affiliation(s)
- Yuji Itoh
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Esmae J Woods
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge CB3 0HE, UK
| | - Katsuhiko Minami
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan; Department of Genetics, School of Life Science, Sokendai (Graduate University for Advanced Studies), Mishima, Shizuoka 411-8540, Japan
| | - Kazuhiro Maeshima
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan; Department of Genetics, School of Life Science, Sokendai (Graduate University for Advanced Studies), Mishima, Shizuoka 411-8540, Japan.
| | - Rosana Collepardo-Guevara
- Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, J J Thomson Avenue, Cambridge CB3 0HE, UK; Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK; Department of Genetics, University of Cambridge, Cambridge, CB2 3EH, UK.
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15
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Abstract
Genomic information is encoded on long strands of DNA, which are folded into chromatin and stored in a tiny nucleus. Nuclear chromatin is a negatively charged polymer composed of DNA, histones, and various nonhistone proteins. Because of its highly charged nature, chromatin structure varies greatly depending on the surrounding environment (e.g., cations, molecular crowding, etc.). New technologies to capture chromatin in living cells have been developed over the past 10 years. Our view on chromatin organization has drastically shifted from a regular and static one to a more variable and dynamic one. Chromatin forms numerous compact dynamic domains that act as functional units of the genome in higher eukaryotic cells and locally appear liquid-like. By changing DNA accessibility, these domains can govern various functions. Based on new evidences from versatile genomics and advanced imaging studies, we discuss the physical nature of chromatin in the crowded nuclear environment and how it is regulated.
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Affiliation(s)
- Kazuhiro Maeshima
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
- Department of Genetics, School of Life Science, Sokendai (Graduate University for Advanced Studies), Mishima, Shizuoka 411-8540, Japan
| | - Shiori Iida
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
- Department of Genetics, School of Life Science, Sokendai (Graduate University for Advanced Studies), Mishima, Shizuoka 411-8540, Japan
| | - Sachiko Tamura
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
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16
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Mylonas C, Lee C, Auld AL, Cisse II, Boyer LA. A dual role for H2A.Z.1 in modulating the dynamics of RNA polymerase II initiation and elongation. Nat Struct Mol Biol 2021; 28:435-442. [PMID: 33972784 DOI: 10.1038/s41594-021-00589-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 04/06/2021] [Indexed: 02/03/2023]
Abstract
RNA polymerase II (RNAPII) pausing immediately downstream of the transcription start site is a critical rate-limiting step for the expression of most metazoan genes. During pause release, RNAPII encounters a highly conserved +1 H2A.Z nucleosome, yet how this histone variant contributes to transcription is poorly understood. Here, using an inducible protein degron system combined with genomic approaches and live cell super-resolution microscopy, we show that H2A.Z.1 modulates RNAPII dynamics across most genes in murine embryonic stem cells. Our quantitative analysis shows that H2A.Z.1 slows the rate of RNAPII pause release and consequently impacts negative elongation factor dynamics as well as nascent transcription. Consequently, H2A.Z.1 also impacts re-loading of the pre-initiation complex components TFIIB and TBP. Altogether, this work provides a critical mechanistic link between H2A.Z.1 and the proper induction of mammalian gene expression programs through the regulation of RNAPII dynamics and pause release.
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Affiliation(s)
- Constantine Mylonas
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Choongman Lee
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alexander L Auld
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ibrahim I Cisse
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Laurie A Boyer
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. .,Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
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17
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Lionnet T, Wu C. Single-molecule tracking of transcription protein dynamics in living cells: seeing is believing, but what are we seeing? Curr Opin Genet Dev 2021; 67:94-102. [PMID: 33422933 DOI: 10.1016/j.gde.2020.12.001] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/24/2020] [Accepted: 12/01/2020] [Indexed: 12/20/2022]
Abstract
A universe of transcription factors (TFs), cofactors, as well as chromatin remodeling and modifying enzymes combine or compete on chromatin to control transcription. Measuring quantitatively how these proteins dynamically interact is required in order to formulate models with predictive ability to elucidate transcription control mechanisms. Single molecule tracking (SMT) provides a powerful tool towards this goal: it is a fluorescence microscopy approach that measures the location and mobility of individual TF molecules, as well as their rates of association with and dissociation from chromatin in the physiological context of the living cell. Here we review SMT principles, and discuss key TF properties uncovered by live-cell SMT, such as fast turnover (seconds), and formation of clusters that locally increase activity.
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Affiliation(s)
- Timothée Lionnet
- Institute for Systems Genetics, Science Building 807, 435 E 30th Street, NYC, NY 10016, USA.
| | - Carl Wu
- Johns Hopkins University, Department of Biology, 3400 N Charles St, Baltimore, MD 21218, USA.
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18
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Henninger JE, Oksuz O, Shrinivas K, Sagi I, LeRoy G, Zheng MM, Andrews JO, Zamudio AV, Lazaris C, Hannett NM, Lee TI, Sharp PA, Cissé II, Chakraborty AK, Young RA. RNA-Mediated Feedback Control of Transcriptional Condensates. Cell 2021; 184:207-225.e24. [PMID: 33333019 PMCID: PMC8128340 DOI: 10.1016/j.cell.2020.11.030] [Citation(s) in RCA: 283] [Impact Index Per Article: 94.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 08/09/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022]
Abstract
Regulation of biological processes typically incorporates mechanisms that initiate and terminate the process and, where understood, these mechanisms often involve feedback control. Regulation of transcription is a fundamental cellular process where the mechanisms involved in initiation have been studied extensively, but those involved in arresting the process are poorly understood. Modeling of the potential roles of RNA in transcriptional control suggested a non-equilibrium feedback control mechanism where low levels of RNA promote condensates formed by electrostatic interactions whereas relatively high levels promote dissolution of these condensates. Evidence from in vitro and in vivo experiments support a model where RNAs produced during early steps in transcription initiation stimulate condensate formation, whereas the burst of RNAs produced during elongation stimulate condensate dissolution. We propose that transcriptional regulation incorporates a feedback mechanism whereby transcribed RNAs initially stimulate but then ultimately arrest the process.
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Affiliation(s)
| | - Ozgur Oksuz
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Krishna Shrinivas
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; NSF-Simons Center for Mathematical & Statistical Analysis of Biology, Harvard University, Cambridge, MA 02138, USA
| | - Ido Sagi
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Gary LeRoy
- Howard Hughes Medical Institute, New York University School of Medicine, New York, NY 10016, USA; Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA
| | - Ming M Zheng
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - J Owen Andrews
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alicia V Zamudio
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Charalampos Lazaris
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nancy M Hannett
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Tong Ihn Lee
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Phillip A Sharp
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ibrahim I Cissé
- Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Arup K Chakraborty
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Physics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Institute of Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Ragon Institute of Massachusetts General Hospital, MIT and Harvard University, Cambridge, MA 02139, USA.
| | - Richard A Young
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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19
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Ide S, Imai R, Ochi H, Maeshima K. Transcriptional suppression of ribosomal DNA with phase separation. SCIENCE ADVANCES 2020; 6:6/42/eabb5953. [PMID: 33055158 PMCID: PMC7556839 DOI: 10.1126/sciadv.abb5953] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Accepted: 08/25/2020] [Indexed: 05/21/2023]
Abstract
The nucleolus is a nuclear body with multiphase liquid droplets for ribosomal RNA (rRNA) transcription. How rRNA transcription is regulated in the droplets remains unclear. Here, using single-molecule tracking of RNA polymerase I (Pol I) and chromatin-bound upstream binding factor (UBF), we reveal suppression of transcription with phase separation. For transcription, active Pol I formed small clusters/condensates that constrained rDNA chromatin in the nucleolus fibrillar center (FC). Treatment with a transcription inhibitor induced Pol I to dissociate from rDNA chromatin and to move like a liquid within the nucleolar cap that transformed from the FC. Expression of a Pol I mutant associated with a craniofacial disorder inhibited transcription by competing with wild-type Pol I clusters and transforming the FC into the nucleolar cap. The cap droplet excluded an initiation factor, ensuring robust silencing. Our findings suggest a mechanism of rRNA transcription suppression via phase separation of intranucleolar molecules governed by Pol I.
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Affiliation(s)
- Satoru Ide
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.
- Department of Genetics, Sokendai (Graduate University for Advanced Studies), Shizuoka 411-8540, Japan
| | - Ryosuke Imai
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
- Department of Genetics, Sokendai (Graduate University for Advanced Studies), Shizuoka 411-8540, Japan
| | - Hiroko Ochi
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
| | - Kazuhiro Maeshima
- Genome Dynamics Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan.
- Department of Genetics, Sokendai (Graduate University for Advanced Studies), Shizuoka 411-8540, Japan
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20
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Maiser A, Dillinger S, Längst G, Schermelleh L, Leonhardt H, Németh A. Super-resolution in situ analysis of active ribosomal DNA chromatin organization in the nucleolus. Sci Rep 2020; 10:7462. [PMID: 32366902 PMCID: PMC7198602 DOI: 10.1038/s41598-020-64589-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Accepted: 04/01/2020] [Indexed: 12/21/2022] Open
Abstract
Ribosomal RNA (rRNA) transcription by RNA polymerase I (Pol I) is the first key step of ribosome biogenesis. While the molecular mechanisms of rRNA transcription regulation have been elucidated in great detail, the functional organization of the multicopy rRNA gene clusters (rDNA) in the nucleolus is less well understood. Here we apply super-resolution 3D structured illumination microscopy (3D-SIM) to investigate the spatial organization of transcriptionally competent active rDNA chromatin at size scales well below the diffraction limit by optical microscopy. We identify active rDNA chromatin units exhibiting uniformly ring-shaped conformations with diameters of ~240 nm in mouse and ~170 nm in human fibroblasts, consistent with rDNA looping. The active rDNA chromatin units are clearly separated from each other and from the surrounding areas of rRNA processing. Simultaneous imaging of all active genes bound by Pol I and the architectural chromatin protein Upstream Binding Transcription Factor (UBF) reveals a random spatial orientation of regular repeats of rDNA coding sequences within the nucleoli. These observations imply rDNA looping and exclude potential formation of systematic spatial assemblies of the well-ordered repetitive arrays of transcription units. Collectively, this study uncovers key features of the 3D organization of active rDNA chromatin units and their nucleolar clusters providing a spatial framework of nucleolar chromatin organization at unprecedented detail.
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Affiliation(s)
- Andreas Maiser
- Department of Biology II, Ludwig-Maximilians-Universität München, München, Germany
| | - Stefan Dillinger
- Department of Biochemistry III, University of Regensburg, Regensburg, Germany
| | - Gernot Längst
- Department of Biochemistry III, University of Regensburg, Regensburg, Germany
| | - Lothar Schermelleh
- Micron Advanced Bioimaging Unit, Department of Biochemistry, University of Oxford, Oxford, UK
| | - Heinrich Leonhardt
- Department of Biology II, Ludwig-Maximilians-Universität München, München, Germany
| | - Attila Németh
- Department of Biochemistry III, University of Regensburg, Regensburg, Germany.
- Institute of Neuropathology, Justus Liebig University, Giessen, Germany.
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21
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Tavakoli M, Jazani S, Sgouralis I, Shafraz OM, Sivasankar S, Donaphon B, Levitus M, Pressé S. Pitching single-focus confocal data analysis one photon at a time with Bayesian nonparametrics. PHYSICAL REVIEW. X 2020; 10:011021. [PMID: 34540355 PMCID: PMC8445401 DOI: 10.1103/physrevx.10.011021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
Fluorescence time traces are used to report on dynamical properties of molecules. The basic unit of information in these traces is the arrival time of individual photons, which carry instantaneous information from the molecule, from which they are emitted, to the detector on timescales as fast as microseconds. Thus, it is theoretically possible to monitor molecular dynamics at such timescales from traces containing only a sufficient number of photon arrivals. In practice, however, traces are stochastic and in order to deduce dynamical information through traditional means-such as fluorescence correlation spectroscopy (FCS) and related techniques-they are collected and temporally autocorrelated over several minutes. So far, it has been impossible to analyze dynamical properties of molecules on timescales approaching data acquisition without collecting long traces under the strong assumption of stationarity of the process under observation or assumptions required for the analytic derivation of a correlation function. To avoid these assumptions, we would otherwise need to estimate the instantaneous number of molecules emitting photons and their positions within the confocal volume. As the number of molecules in a typical experiment is unknown, this problem demands that we abandon the conventional analysis paradigm. Here, we exploit Bayesian nonparametrics that allow us to obtain, in a principled fashion, estimates of the same quantities as FCS but from the direct analysis of traces of photon arrivals that are significantly smaller in size, or total duration, than those required by FCS.
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Affiliation(s)
- Meysam Tavakoli
- Department of Physics, Indiana University-Purdue University Indianapolis, IN 46202
| | - Sina Jazani
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287
| | - Ioannis Sgouralis
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287
| | - Omer M. Shafraz
- Department of Biomedical Engineering, University of California, Davis, CA 95616
| | - Sanjeevi Sivasankar
- Department of Biomedical Engineering, University of California, Davis, CA 95616
| | - Bryan Donaphon
- Biodesign Institute, Arizona State University, Tempe, AZ 85287
| | - Marcia Levitus
- Center for Biological Physics, Department of Physics, Arizona State University, Tempe, AZ 85287
- Biodesign Institute, Arizona State University, Tempe, AZ 85287 and School of Molecular Sciences, Arizona State University, Tempe, AZ 85287
| | - Steve Pressé
- Corresponding author. ; Website: http://statphysbio.physics.asu.edu
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22
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Mosqueira A, Camino PA, Barrantes FJ. Antibody‐induced crosslinking and cholesterol‐sensitive, anomalous diffusion of nicotinic acetylcholine receptors. J Neurochem 2019; 152:663-674. [DOI: 10.1111/jnc.14905] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 09/27/2019] [Accepted: 10/25/2019] [Indexed: 02/04/2023]
Affiliation(s)
- Alejo Mosqueira
- Laboratory of Molecular Neurobiology Biomedical Research institute (BIOMED) UCA–CONICET Buenos Aires Argentina
| | - Pablo A. Camino
- Laboratory of Molecular Neurobiology Biomedical Research institute (BIOMED) UCA–CONICET Buenos Aires Argentina
| | - Francisco J. Barrantes
- Laboratory of Molecular Neurobiology Biomedical Research institute (BIOMED) UCA–CONICET Buenos Aires Argentina
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23
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Narayanan A, Meriin A, Andrews JO, Spille JH, Sherman MY, Cisse II. A first order phase transition mechanism underlies protein aggregation in mammalian cells. eLife 2019; 8:39695. [PMID: 30716021 PMCID: PMC6361590 DOI: 10.7554/elife.39695] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Accepted: 12/17/2018] [Indexed: 12/15/2022] Open
Abstract
The formation of misfolded protein aggregates is a hallmark of neurodegenerative diseases. The aggregate formation process exhibits an initial lag phase when precursor clusters spontaneously assemble. However, most experimental assays are blind to this lag phase. We develop a quantitative assay based on super-resolution imaging in fixed cells and light sheet imaging of living cells to study the early steps of aggregation in mammalian cells. We find that even under normal growth conditions mammalian cells have precursor clusters. The cluster size distribution is precisely that expected for a so-called super-saturated system in first order phase transition. This means there exists a nucleation barrier, and a critical size above which clusters grow and mature. Homeostasis is maintained through a Szilard model entailing the preferential clearance of super-critical clusters. We uncover a role for a putative chaperone (RuvBL) in this disassembly of large clusters. The results indicate early aggregates behave like condensates. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
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Affiliation(s)
- Arjun Narayanan
- Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
| | - Anatoli Meriin
- Department of Biochemistry, Boston University School of Medicine, Boston, United States
| | - J Owen Andrews
- Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
| | - Jan-Hendrik Spille
- Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
| | | | - Ibrahim I Cisse
- Department of Physics, Massachusetts Institute of Technology, Cambridge, United States
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24
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Cholesterol modulates acetylcholine receptor diffusion by tuning confinement sojourns and nanocluster stability. Sci Rep 2018; 8:11974. [PMID: 30097590 PMCID: PMC6086833 DOI: 10.1038/s41598-018-30384-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Accepted: 07/20/2018] [Indexed: 11/08/2022] Open
Abstract
Translational motion of neurotransmitter receptors is key for determining receptor number at the synapse and hence, synaptic efficacy. We combine live-cell STORM superresolution microscopy of nicotinic acetylcholine receptor (nAChR) with single-particle tracking, mean-squared displacement (MSD), turning angle, ergodicity, and clustering analyses to characterize the lateral motion of individual molecules and their collective behaviour. nAChR diffusion is highly heterogeneous: subdiffusive, Brownian and, less frequently, superdiffusive. At the single-track level, free walks are transiently interrupted by ms-long confinement sojourns occurring in nanodomains of ~36 nm radius. Cholesterol modulates the time and the area spent in confinement. Turning angle analysis reveals anticorrelated steps with time-lag dependence, in good agreement with the permeable fence model. At the ensemble level, nanocluster assembly occurs in second-long bursts separated by periods of cluster disassembly. Thus, millisecond-long confinement sojourns and second-long reversible nanoclustering with similar cholesterol sensitivities affect all trajectories; the proportion of the two regimes determines the resulting macroscopic motional mode and breadth of heterogeneity in the ensemble population.
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25
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Cho WK, Spille JH, Hecht M, Lee C, Li C, Grube V, Cisse II. Mediator and RNA polymerase II clusters associate in transcription-dependent condensates. Science 2018; 361:412-415. [PMID: 29930094 DOI: 10.1126/science.aar4199] [Citation(s) in RCA: 818] [Impact Index Per Article: 136.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 04/17/2018] [Accepted: 06/11/2018] [Indexed: 12/20/2022]
Abstract
Models of gene control have emerged from genetic and biochemical studies, with limited consideration of the spatial organization and dynamics of key components in living cells. We used live-cell superresolution and light-sheet imaging to study the organization and dynamics of the Mediator coactivator and RNA polymerase II (Pol II) directly. Mediator and Pol II each form small transient and large stable clusters in living embryonic stem cells. Mediator and Pol II are colocalized in the stable clusters, which associate with chromatin, have properties of phase-separated condensates, and are sensitive to transcriptional inhibitors. We suggest that large clusters of Mediator, recruited by transcription factors at large or clustered enhancer elements, interact with large Pol II clusters in transcriptional condensates in vivo.
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Affiliation(s)
- Won-Ki Cho
- Department of Physics, MIT, Cambridge, MA 02139, USA
| | | | - Micca Hecht
- Department of Physics, MIT, Cambridge, MA 02139, USA
| | - Choongman Lee
- Department of Physics, MIT, Cambridge, MA 02139, USA
| | - Charles Li
- Department of Biology, MIT, Cambridge, MA 02139, USA.,Whitehead Institute for Biomedical Research, Cambridge, MA 02139, USA
| | - Valentin Grube
- Department of Physics, MIT, Cambridge, MA 02139, USA.,Department of Physics, LMU Munich, Geschwister Scholl Platz 1, 80539 Munich, Germany
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