1
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Meeussen JVW, Lenstra TL. Time will tell: comparing timescales to gain insight into transcriptional bursting. Trends Genet 2024; 40:160-174. [PMID: 38216391 PMCID: PMC10860890 DOI: 10.1016/j.tig.2023.11.003] [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: 09/13/2023] [Revised: 11/27/2023] [Accepted: 11/27/2023] [Indexed: 01/14/2024]
Abstract
Recent imaging studies have captured the dynamics of regulatory events of transcription inside living cells. These events include transcription factor (TF) DNA binding, chromatin remodeling and modification, enhancer-promoter (E-P) proximity, cluster formation, and preinitiation complex (PIC) assembly. Together, these molecular events culminate in stochastic bursts of RNA synthesis, but their kinetic relationship remains largely unclear. In this review, we compare the timescales of upstream regulatory steps (input) with the kinetics of transcriptional bursting (output) to generate mechanistic models of transcription dynamics in single cells. We highlight open questions and potential technical advances to guide future endeavors toward a quantitative and kinetic understanding of transcription regulation.
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Affiliation(s)
- Joseph V W Meeussen
- Division of Gene Regulation, The Netherlands Cancer Institute, Oncode Institute, Amsterdam 1066CX, The Netherlands
| | - Tineke L Lenstra
- Division of Gene Regulation, The Netherlands Cancer Institute, Oncode Institute, Amsterdam 1066CX, The Netherlands.
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2
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Fu RZ, Cottrell O, Cutillo L, Rowntree A, Zador Z, Wurdak H, Papalopulu N, Marinopoulou E. Identification of genes with oscillatory expression in glioblastoma: the paradigm of SOX2. Sci Rep 2024; 14:2123. [PMID: 38267500 PMCID: PMC10808450 DOI: 10.1038/s41598-024-51340-z] [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: 11/10/2023] [Accepted: 01/03/2024] [Indexed: 01/26/2024] Open
Abstract
Quiescence, a reversible state of cell-cycle arrest, is an important state during both normal development and cancer progression. For example, in glioblastoma (GBM) quiescent glioblastoma stem cells (GSCs) play an important role in re-establishing the tumour, leading to relapse. While most studies have focused on identifying differentially expressed genes between proliferative and quiescent cells as potential drivers of this transition, recent studies have shown the importance of protein oscillations in controlling the exit from quiescence of neural stem cells. Here, we have undertaken a genome-wide bioinformatic inference approach to identify genes whose expression oscillates and which may be good candidates for controlling the transition to and from the quiescent cell state in GBM. Our analysis identified, among others, a list of important transcription regulators as potential oscillators, including the stemness gene SOX2, which we verified to oscillate in quiescent GSCs. These findings expand on the way we think about gene regulation and introduce new candidate genes as key regulators of quiescence.
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Affiliation(s)
- Richard Zhiming Fu
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK
- Geoffrey Jefferson Brain Research Centre, University of Manchester, Manchester, M13 9PL, UK
- Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Care Organisation, Northern Care Alliance NHS Foundation Trust, Salford Royal, Stott Lane, Salford, M6 8HD, UK
| | - Oliver Cottrell
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK
| | - Luisa Cutillo
- School of Mathematics, University of Leeds, Woodhouse, Leeds, LS2 9JT, UK
| | - Andrew Rowntree
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK
| | - Zsolt Zador
- Division of Neurosurgery, Department of Surgery, St. Michael's Hospital, 36 Queen St E, Toronto, ON, M5B 1W8, Canada
- Department of Surgery, McMaster University, 1280 Mains St W, Hamilton, ON, L8S 4L8, Canada
- Center for Discovery in Cancer Research (CDCR), McMaster University, 1280 Main St W, Hamilton, ON, L8S 4L8, Canada
| | - Heiko Wurdak
- Stem Cell and Brain Tumour Group, Leeds Institute of Medical Research at St James's, School of Medicine, University of Leeds, Leeds, LS9 7TF, UK
| | - Nancy Papalopulu
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK.
| | - Elli Marinopoulou
- Division of Developmental Biology and Medicine, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PT, UK.
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3
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Eck E, Moretti B, Schlomann BH, Bragantini J, Lange M, Zhao X, VijayKumar S, Valentin G, Loureiro C, Soroldoni D, Royer LA, Oates AC, Garcia HG. Single-cell transcriptional dynamics in a living vertebrate. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.03.574108. [PMID: 38260569 PMCID: PMC10802376 DOI: 10.1101/2024.01.03.574108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
The ability to quantify transcriptional dynamics in individual cells via live imaging has revolutionized our understanding of gene regulation. However, such measurements are lacking in the context of vertebrate embryos. We addressed this deficit by applying MS2-MCP mRNA labeling to the quantification of transcription in zebrafish, a model vertebrate. We developed a platform of transgenic organisms, light sheet fluorescence microscopy, and optimized image analysis that enables visualization and quantification of MS2 reporters. We used these tools to obtain the first single-cell, real-time measurements of transcriptional dynamics of the segmentation clock. Our measurements challenge the traditional view of smooth clock oscillations and instead suggest a model of discrete transcriptional bursts that are organized in space and time. Together, these results highlight how measuring single-cell transcriptional activity can reveal unexpected features of gene regulation and how this data can fuel the dialogue between theory and experiment.
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Affiliation(s)
- Elizabeth Eck
- Biophysics Graduate Group, University of California at Berkeley, Berkeley, USA
| | - Bruno Moretti
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Chan Zuckerberg Biohub – San Francisco, San Francisco, CA, USA
| | - Brandon H. Schlomann
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | | | - Merlin Lange
- Chan Zuckerberg Biohub – San Francisco, San Francisco, CA, USA
| | - Xiang Zhao
- Chan Zuckerberg Biohub – San Francisco, San Francisco, CA, USA
| | | | | | | | | | - Loïc A. Royer
- Chan Zuckerberg Biohub – San Francisco, San Francisco, CA, USA
| | - Andrew C. Oates
- Institute of Bioengineering, EPFL; Lausanne, CH
- Department of Cell and Developmental Biology, UCL; London, UK
- The Francis Crick Institute; London, UK
| | - Hernan G. Garcia
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Department of Physics, University of California, Berkeley, CA, USA
- Institute for Quantitative Biosciences-QB3, University of California, Berkeley, CA, USA
- Chan Zuckerberg Biohub – San Francisco, San Francisco, CA, USA
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4
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Ben-Oz BM, Machour FE, Nicola M, Argoetti A, Polyak G, Hanna R, Kleifeld O, Mandel-Gutfreund Y, Ayoub N. A dual role of RBM42 in modulating splicing and translation of CDKN1A/p21 during DNA damage response. Nat Commun 2023; 14:7628. [PMID: 37993446 PMCID: PMC10665399 DOI: 10.1038/s41467-023-43495-6] [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: 06/07/2022] [Accepted: 11/10/2023] [Indexed: 11/24/2023] Open
Abstract
p53-mediated cell cycle arrest during DNA damage is dependent on the induction of p21 protein, encoded by the CDKN1A gene. p21 inhibits cyclin-dependent kinases required for cell cycle progression to guarantee accurate repair of DNA lesions. Hence, fine-tuning of p21 levels is crucial to preserve genomic stability. Currently, the multilayered regulation of p21 levels during DNA damage is not fully understood. Herein, we identify the human RNA binding motif protein 42 (RBM42) as a regulator of p21 levels during DNA damage. Genome-wide transcriptome and interactome analysis reveals that RBM42 alters the expression of p53-regulated genes during DNA damage. Specifically, we demonstrate that RBM42 facilitates CDKN1A splicing by counteracting the splicing inhibitory effect of RBM4 protein. Unexpectedly, we also show that RBM42, underpins translation of various splicing targets, including CDKN1A. Concordantly, transcriptome-wide mapping of RBM42-RNA interactions using eCLIP further substantiates the dual function of RBM42 in regulating splicing and translation of its target genes, including CDKN1A. Collectively, our data show that RBM42 couples splicing and translation machineries to fine-tune gene expression during DNA damage response.
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Affiliation(s)
- Bella M Ben-Oz
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Feras E Machour
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Marian Nicola
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Amir Argoetti
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Galia Polyak
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Rawad Hanna
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Oded Kleifeld
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Yael Mandel-Gutfreund
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel
| | - Nabieh Ayoub
- Department of Biology, Technion - Israel Institute of Technology, Haifa, 3200003, Israel.
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5
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Wu R, Zhou B, Wang W, Liu F. Regulatory Mechanisms for Transcriptional Bursting Revealed by an Event-Based Model. RESEARCH (WASHINGTON, D.C.) 2023; 6:0253. [PMID: 39290237 PMCID: PMC11407585 DOI: 10.34133/research.0253] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/01/2023] [Indexed: 09/19/2024]
Abstract
Gene transcription often occurs in discrete bursts, and it can be difficult to deduce the underlying regulatory mechanisms for transcriptional bursting with limited experimental data. Here, we categorize numerous states of single eukaryotic genes and identify 6 essential transcriptional events, each comprising a series of state transitions; transcriptional bursting is characterized as a sequence of 4 events, capable of being organized in various configurations, in addition to the beginning and ending events. By associating transcriptional kinetics with mean durations and recurrence probabilities of the events, we unravel how transcriptional bursting is modulated by various regulators including transcription factors. Through analytical derivation and numerical simulation, this study reveals key state transitions contributing to transcriptional sensitivity and specificity, typical characteristics of burst profiles, global constraints on intrinsic transcriptional noise, major regulatory modes in individual genes and across the genome, and requirements for fast gene induction upon stimulation. It is illustrated how biochemical reactions on different time scales are modulated to separately shape the durations and ordering of the events. Our results suggest that transcriptional patterns are essentially controlled by a shared set of transcriptional events occurring under specific promoter architectures and regulatory modes, the number of which is actually limited.
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Affiliation(s)
- Renjie Wu
- National Laboratory of Solid State Microstructures, Department of Physics, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, P. R. China
| | - Bangyan Zhou
- National Laboratory of Solid State Microstructures, Department of Physics, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, P. R. China
| | - Wei Wang
- National Laboratory of Solid State Microstructures, Department of Physics, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, P. R. China
- Institute for Brain Sciences, Nanjing University, Nanjing 210093, P. R. China
| | - Feng Liu
- National Laboratory of Solid State Microstructures, Department of Physics, and Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, P. R. China
- Institute for Brain Sciences, Nanjing University, Nanjing 210093, P. R. China
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6
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Maeda Y, Isomura A, Masaki T, Kageyama R. Differential cell-cycle control by oscillatory versus sustained Hes1 expression via p21. Cell Rep 2023; 42:112520. [PMID: 37200191 DOI: 10.1016/j.celrep.2023.112520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 01/06/2023] [Accepted: 05/02/2023] [Indexed: 05/20/2023] Open
Abstract
Oscillatory Hes1 expression activates cell proliferation, while high and sustained Hes1 expression induces quiescence, but the mechanism by which Hes1 differentially controls cell proliferation depending on its expression dynamics is unclear. Here, we show that oscillatory Hes1 expression down-regulates the expression of the cyclin-dependent kinase inhibitor p21 (Cdkn1a), which delays cell-cycle progression, and thereby activates the proliferation of mouse neural stem cells (NSCs). By contrast, sustained Hes1 overexpression up-regulates p21 expression and inhibits NSC proliferation, although it initially down-regulates p21 expression. Compared with Hes1 oscillation, sustained Hes1 overexpression represses Dusp7, a phosphatase for phosphorylated Erk (p-Erk), and increases the levels of p-Erk, which can up-regulate p21 expression. These results indicate that p21 expression is directly repressed by oscillatory Hes1 expression, but indirectly up-regulated by sustained Hes1 overexpression, suggesting that depending on its expression dynamics, Hes1 differentially controls NSC proliferation via p21.
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Affiliation(s)
- Yuki Maeda
- RIKEN Center for Brain Science, Wako 351-0198, Japan; Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan
| | - Akihiro Isomura
- Institute for Life and Medical Sciences, Kyoto University, Kyoto 606-8507, Japan; Institute for Integrated Cell-Material Sciences, Kyoto University, Kyoto 606-8501, Japan; Japan Science and Technology Agency, PRESTO, Saitama 332-0012, Japan
| | - Taimu Masaki
- RIKEN Center for Brain Science, Wako 351-0198, Japan
| | - Ryoichiro Kageyama
- RIKEN Center for Brain Science, Wako 351-0198, Japan; Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan; Graduate School of Medicine, Kyoto University, Kyoto 606-8501, Japan.
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7
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Tran AP, Tralie CJ, Reyes J, Moosmüller C, Belkhatir Z, Kevrekidis IG, Levine AJ, Deasy JO, Tannenbaum AR. Long-term p21 and p53 dynamics regulate the frequency of mitosis events and cell cycle arrest following radiation damage. Cell Death Differ 2023; 30:660-672. [PMID: 36182991 PMCID: PMC9984379 DOI: 10.1038/s41418-022-01069-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 09/12/2022] [Accepted: 09/14/2022] [Indexed: 11/07/2022] Open
Abstract
Radiation exposure of healthy cells can halt cell cycle temporarily or permanently. In this work, we analyze the time evolution of p21 and p53 from two single cell datasets of retinal pigment epithelial cells exposed to several levels of radiation, and in particular, the effect of radiation on cell cycle arrest. Employing various quantification methods from signal processing, we show how p21 levels, and to a lesser extent p53 levels, dictate whether the cells are arrested in their cell cycle and how frequently these mitosis events are likely to occur. We observed that single cells exposed to the same dose of DNA damage exhibit heterogeneity in cellular outcomes and that the frequency of cell division is a more accurate monitor of cell damage rather than just radiation level. Finally, we show how heterogeneity in DNA damage signaling is manifested early in the response to radiation exposure level and has potential to predict long-term fate.
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Affiliation(s)
- Anh Phong Tran
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christopher J Tralie
- Department of Mathematics and Computer Science, Ursinus College, Collegeville, PA, USA
| | - José Reyes
- Cancer Biology and Genetics Program and Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Caroline Moosmüller
- Department of Mathematics, University of California, San Diego, La Jolla, CA, USA
| | - Zehor Belkhatir
- School of Engineering and Sustainable Development, De Montfort University, Leicester, UK
| | - Ioannis G Kevrekidis
- Department of Chemical and Biological Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Arnold J Levine
- Simons Center for Systems Biology, Institute for Advanced Study, Princeton, NJ, USA
| | - Joseph O Deasy
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Allen R Tannenbaum
- Departments of Computer Science and Applied Mathematics & Statistics, Stony Brook University, Stony Brook, NY, USA.
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8
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Wang P, Wang HY, Gao XJ, Zhu HX, Zhang XP, Liu F, Wang W. Encoding and Decoding of p53 Dynamics in Cellular Response to Stresses. Cells 2023; 12:cells12030490. [PMID: 36766831 PMCID: PMC9914463 DOI: 10.3390/cells12030490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 01/20/2023] [Accepted: 01/29/2023] [Indexed: 02/05/2023] Open
Abstract
In the cellular response to stresses, the tumor suppressor p53 is activated to maintain genomic integrity and fidelity. As a transcription factor, p53 exhibits rich dynamics to allow for discrimination of the type and intensity of stresses and to direct the selective activation of target genes involved in different processes including cell cycle arrest and apoptosis. In this review, we focused on how stresses are encoded into p53 dynamics and how the dynamics are decoded into cellular outcomes. Theoretical modeling may provide a global view of signaling in the p53 network by coupling the encoding and decoding processes. We discussed the significance of modeling in revealing the mechanisms of the transition between p53 dynamic modes. Moreover, we shed light on the crosstalk between the p53 network and other signaling networks. This review may advance the understanding of operating principles of the p53 signaling network comprehensively and provide insights into p53 dynamics-based cancer therapy.
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Affiliation(s)
- Ping Wang
- Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China
- Key Laboratory of High Performance Scientific Computation, School of Science, Xihua University, Chengdu 610039, China
| | - Hang-Yu Wang
- Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China
| | - Xing-Jie Gao
- Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China
| | - Hua-Xia Zhu
- Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China
| | - Xiao-Peng Zhang
- Kuang Yaming Honors School, Nanjing University, Nanjing 210023, China
- Institute of Brain Sciences, Nanjing University, Nanjing 210093, China
- Correspondence: (X.-P.Z.); (W.W.)
| | - Feng Liu
- Institute of Brain Sciences, Nanjing University, Nanjing 210093, China
- National Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
- Department of Physics, Nanjing University, Nanjing 210093, China
| | - Wei Wang
- Institute of Brain Sciences, Nanjing University, Nanjing 210093, China
- National Laboratory of Solid State Microstructure, Nanjing University, Nanjing 210093, China
- Department of Physics, Nanjing University, Nanjing 210093, China
- Correspondence: (X.-P.Z.); (W.W.)
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9
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Xiong L, Garfinkel A. A common pathway to cancer: Oncogenic mutations abolish p53 oscillations. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2022; 174:28-40. [PMID: 35752348 DOI: 10.1016/j.pbiomolbio.2022.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 06/13/2022] [Accepted: 06/20/2022] [Indexed: 06/15/2023]
Abstract
The tumor suppressor p53 oscillates in response to DNA double-strand breaks, a behavior that has been suggested to be essential to its anti-cancer function. Nearly all human cancers have genetic alterations in the p53 pathway; a number of these alterations have been shown to be oncogenic by experiment. These alterations include somatic mutations and copy number variations as well as germline polymorphisms. Intriguingly, they exhibit a mixed pattern of interactions in tumors, such as co-occurrence, mutual exclusivity, and paradoxically, mutual antagonism. Using a differential equation model of p53-Mdm2 dynamics, we employ Hopf bifurcation analysis to show that these alterations have a common mode of action, to abolish the oscillatory competence of p53, thereby, we suggest, impairing its tumor suppressive function. In this analysis, diverse genetic alterations, widely associated with human cancers clinically, have a unified mechanistic explanation of their role in oncogenesis.
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Affiliation(s)
- Lingyun Xiong
- Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90007 USA; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, 90007, USA; Ludwig Institute for Cancer Research, University of Oxford, Oxford, OX3 7DQ, UK
| | - Alan Garfinkel
- Departments of Medicine (Cardiology) and Integrative Biology and Physiology, University of California, Los Angeles, CA, 90095, USA; Newton-Abraham Visiting Professor (2019-2020), Lincoln College and Department of Computer Science, University of Oxford, Oxford, OX1 3DR, UK.
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10
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Gupta A, Martin-Rufino JD, Jones TR, Subramanian V, Qiu X, Grody EI, Bloemendal A, Weng C, Niu SY, Min KH, Mehta A, Zhang K, Siraj L, Al' Khafaji A, Sankaran VG, Raychaudhuri S, Cleary B, Grossman S, Lander ES. Inferring gene regulation from stochastic transcriptional variation across single cells at steady state. Proc Natl Acad Sci U S A 2022; 119:e2207392119. [PMID: 35969771 PMCID: PMC9407670 DOI: 10.1073/pnas.2207392119] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 07/20/2022] [Indexed: 12/24/2022] Open
Abstract
Regulatory relationships between transcription factors (TFs) and their target genes lie at the heart of cellular identity and function; however, uncovering these relationships is often labor-intensive and requires perturbations. Here, we propose a principled framework to systematically infer gene regulation for all TFs simultaneously in cells at steady state by leveraging the intrinsic variation in the transcriptional abundance across single cells. Through modeling and simulations, we characterize how transcriptional bursts of a TF gene are propagated to its target genes, including the expected ranges of time delay and magnitude of maximum covariation. We distinguish these temporal trends from the time-invariant covariation arising from cell states, and we delineate the experimental and technical requirements for leveraging these small but meaningful cofluctuations in the presence of measurement noise. While current technology does not yet allow adequate power for definitively detecting regulatory relationships for all TFs simultaneously in cells at steady state, we investigate a small-scale dataset to inform future experimental design. This study supports the potential value of mapping regulatory connections through stochastic variation, and it motivates further technological development to achieve its full potential.
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Affiliation(s)
- Anika Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115
| | - Jorge D. Martin-Rufino
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115
- Dana-Farber Cancer Institute, Boston, MA 02215
| | | | | | - Xiaojie Qiu
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142
- HHMI, Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | | | - Chen Weng
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115
- Dana-Farber Cancer Institute, Boston, MA 02215
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142
| | | | - Kyung Hoi Min
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139
| | - Arnav Mehta
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Dana-Farber Cancer Institute, Boston, MA 02215
- Department of Medicine, Massachusetts General Hospital, Boston, MA 02114
| | - Kaite Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | - Layla Siraj
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | - Vijay G. Sankaran
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Division of Hematology/Oncology, Boston Children’s Hospital, Boston, MA 02115
- Dana-Farber Cancer Institute, Boston, MA 02215
| | - Soumya Raychaudhuri
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115
- Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA 02115
| | - Brian Cleary
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
| | | | - Eric S. Lander
- Broad Institute of MIT and Harvard, Cambridge, MA 02142
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142
- Department of Systems Biology, Harvard Medical School, Boston, MA 02115
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11
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Unraveling the effect of intra- and intercellular processes on acetaminophen-induced liver injury. NPJ Syst Biol Appl 2022; 8:27. [PMID: 35933513 PMCID: PMC9357019 DOI: 10.1038/s41540-022-00238-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 07/20/2022] [Indexed: 11/09/2022] Open
Abstract
In high dosages, acetaminophen (APAP) can cause severe liver damage, but susceptibility to liver failure varies across individuals and is influenced by factors such as health status. Because APAP-induced liver injury and recovery is regulated by an intricate system of intra- and extracellular molecular signaling, we here aim to quantify the importance of specific modules in determining the outcome after an APAP insult and of potential targets for therapies that mitigate adversity. For this purpose, we integrated hepatocellular acetaminophen metabolism, DNA damage response induction and cell fate into a multiscale mechanistic liver lobule model which involves various cell types, such as hepatocytes, residential Kupffer cells and macrophages. Our model simulations show that zonal differences in metabolism and detoxification efficiency are essential determinants of necrotic damage. Moreover, the extent of senescence, which is regulated by intracellular processes and triggered by extracellular signaling, influences the potential to recover. In silico therapies at early and late time points after APAP insult indicated that prevention of necrotic damage is most beneficial for recovery, whereas interference with regulation of senescence promotes regeneration in a less pronounced way.
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12
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Model-based translation of DNA damage signaling dynamics across cell types. PLoS Comput Biol 2022; 18:e1010264. [PMID: 35802572 PMCID: PMC9269748 DOI: 10.1371/journal.pcbi.1010264] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 05/30/2022] [Indexed: 12/14/2022] Open
Abstract
Interindividual variability in DNA damage response (DDR) dynamics may evoke differences in susceptibility to cancer. However, pathway dynamics are often studied in cell lines as alternative to primary cells, disregarding variability. To compare DDR dynamics in the cell line HepG2 with primary human hepatocytes (PHHs), we developed a HepG2-based computational model that describes the dynamics of DDR regulator p53 and targets MDM2, p21 and BTG2. We used this model to generate simulations of virtual PHHs and compared the results to those for PHH donor samples. Correlations between baseline p53 and p21 or BTG2 mRNA expression in the absence and presence of DNA damage for HepG2-derived virtual samples matched the moderately positive correlations observed for 50 PHH donor samples, but not the negative correlations between p53 and its inhibitor MDM2. Model parameter manipulation that affected p53 or MDM2 dynamics was not sufficient to accurately explain the negative correlation between these genes. Thus, extrapolation from HepG2 to PHH can be done for some DDR elements, yet our analysis also reveals a knowledge gap within p53 pathway regulation, which makes such extrapolation inaccurate for the regulator MDM2. This illustrates the relevance of studying pathway dynamics in addition to gene expression comparisons to allow reliable translation of cellular responses from cell lines to primary cells. Overall, with our approach we show that dynamical modeling can be used to improve our understanding of the sources of interindividual variability of pathway dynamics. Susceptibility to develop cancer varies among people, partially due to differences in genetic background. Ideally, healthy human-derived cells are used to investigate intracellular signaling pathways and their interindividual variability contributing to cancer susceptibility. Because cells from healthy human tissue are difficult to obtain and culture for periods longer than a few days, cell lines are often used as substitute. However, it is unclear to what extent signaling dynamics in cell lines represent dynamics in healthy human tissue. We asked whether we could reproduce interindividual variability in DNA damage response gene expression in a set of 50 human liver cell donors. Therefore, we built a mathematical model that simulates temporal expression dynamics of the DNA damage response in the HepG2 liver cell line upon chemical activation and used the simulations to create virtual donors. Our virtual donors displayed similar relations between genes as the samples from human donors, provided that we adjusted the strength of specific molecular interactions. Thus, our approach can be used to examine the applicability of widely used cell systems to healthy human tissue in terms of their dynamic responses.
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13
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Lu D, Jambhekar A, Lahav G. Louder for longer: Myc amplifies gene expression by extended transcriptional bursting. Cell Rep 2022; 38:110470. [PMID: 35235795 DOI: 10.1016/j.celrep.2022.110470] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Transcription is a complex, dynamic process. Using live single-cell measurements, Patange et al. show, in a recent issue of Cell Reports, that elevated levels of the transcription factor MYC enhance target gene RNA production by increasing the duration but not frequency of transcriptional bursts.
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Affiliation(s)
- Dan Lu
- Department of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA 02115, USA
| | - Ashwini Jambhekar
- Department of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA 02115, USA
| | - Galit Lahav
- Department of Systems Biology, Blavatnik Institute at Harvard Medical School, Boston, MA 02115, USA.
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14
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Lenz G, Onzi GR, Lenz LS, Buss JH, Santos JAF, Begnini KR. The Origins of Phenotypic Heterogeneity in Cancer. Cancer Res 2021; 82:3-11. [PMID: 34785576 DOI: 10.1158/0008-5472.can-21-1940] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 09/14/2021] [Accepted: 11/10/2021] [Indexed: 11/16/2022]
Abstract
Heterogeneity is a pervasive feature of cancer, and understanding the sources and regulatory mechanisms underlying heterogeneity could provide key insights to help improve the diagnosis and treatment of cancer. In this review, we discuss the origin of heterogeneity in the phenotype of individual cancer cells. Genotype-phenotype (G-P) maps are widely used in evolutionary biology to represent the complex interactions of genes and the environment that lead to phenotypes that impact fitness. Here, we present the rationale of an extended G-P (eG-P) map with a cone structure in cancer. The eG-P cone is formed by cells that are similar at the genome layer but gradually increase variability in the epigenome, transcriptome, proteome, metabolome and signalome layers to produce large variability at the phenome layer. Experimental evidence from single-cell -omics analyses supporting the cancer eG-P cone concept is presented, and the impact of epimutations and the interaction of cancer and tumor microenvironmental eG-P cones are integrated with the current understanding of cancer biology. The eG-P cone concept uncovers potential therapeutic strategies to reduce cancer evolution and improve cancer treatment. More methods to study phenotypes in single cells will be key to better understand cancer cell fitness in tumor biology and therapeutics.
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15
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Role of Episamarcandin in Promoting the Apoptosis of Human Colon Cancer HCT116 Cells through the PI3K-Akt Signaling Pathway. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2021; 2021:9663738. [PMID: 34765011 PMCID: PMC8577892 DOI: 10.1155/2021/9663738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 09/09/2021] [Accepted: 09/29/2021] [Indexed: 12/01/2022]
Abstract
This study identifies the active ingredients of Ferula sinkiangensis and investigates the role and mechanism of episamarcandin in colon cancer cells. The silica gel column chromatography was utilized to separate the chemical components of Ferula sinkiangensis. Sephadex LH-20 and semipreparative HPLC were adopted for further separation and purification. The compound episamarcandin showed good anticolon cancer activity among the 13 monomeric compounds obtained. Its effects on the apoptosis, cell cycle, and invasion and migration of colon cancer HCT 116 cells and PI3K-Akt signaling pathway were further investigated. The results showed that, similar to positive control cisplatin, episamarcandin inhibited the proliferation, promoted the apoptosis, arrested cells at G0/G1 phase, and suppressed migration and invasion of HCT 116 cells. A large number of apoptotic HCT 116 cells were observed under a transmission electron microscope. Fluorescence real-time quantitative PCR and western blot analysis showed that episamarcandin increased the expression of PTEN, p53, and Bax and decreased the expression of P-Akt, Akt, mTOR, Bcl-xl, and Bcl-2. Conclusively, episamarcandin may inhibit cell proliferation, migration, and invasion and promote the apoptosis of human colon cancer HCT 116 cells possibly through the PI3K-Akt signaling pathway.
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16
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Wheat JC, Steidl U. Gene expression at a single-molecule level: implications for myelodysplastic syndromes and acute myeloid leukemia. Blood 2021; 138:625-636. [PMID: 34436525 PMCID: PMC8394909 DOI: 10.1182/blood.2019004261] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Accepted: 12/03/2020] [Indexed: 12/11/2022] Open
Abstract
Nongenetic heterogeneity, or gene expression stochasticity, is an important source of variability in biological systems. With the advent and improvement of single molecule resolution technologies, it has been shown that transcription dynamics and resultant transcript number fluctuations generate significant cell-to-cell variability that has important biological effects and may contribute substantially to both tissue homeostasis and disease. In this respect, the pathophysiology of stem cell-derived malignancies such as acute myeloid leukemia and myelodysplastic syndromes, which has historically been studied at the ensemble level, may require reevaluation. To that end, it is our aim in this review to highlight the results of recent single-molecule, biophysical, and systems studies of gene expression dynamics, with the explicit purpose of demonstrating how the insights from these basic science studies may help inform and progress the field of leukemia biology and, ultimately, research into novel therapies.
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Affiliation(s)
- Justin C Wheat
- Albert Einstein College of Medicine - Montefiore Health System, Bronx, NY
| | - Ulrich Steidl
- Albert Einstein College of Medicine - Montefiore Health System, Bronx, NY
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17
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Alamos S, Reimer A, Niyogi KK, Garcia HG. Quantitative imaging of RNA polymerase II activity in plants reveals the single-cell basis of tissue-wide transcriptional dynamics. NATURE PLANTS 2021; 7:1037-1049. [PMID: 34373604 PMCID: PMC8616715 DOI: 10.1038/s41477-021-00976-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 06/22/2021] [Indexed: 05/18/2023]
Abstract
The responses of plants to their environment are often dependent on the spatiotemporal dynamics of transcriptional regulation. While live-imaging tools have been used extensively to quantitatively capture rapid transcriptional dynamics in living animal cells, the lack of implementation of these technologies in plants has limited concomitant quantitative studies in this kingdom. Here, we applied the PP7 and MS2 RNA-labelling technologies for the quantitative imaging of RNA polymerase II activity dynamics in single cells of living plants as they respond to experimental treatments. Using this technology, we counted nascent RNA transcripts in real time in Nicotiana benthamiana (tobacco) and Arabidopsis thaliana. Examination of heat shock reporters revealed that plant tissues respond to external signals by modulating the proportion of cells that switch from an undetectable basal state to a high-transcription state, instead of modulating the rate of transcription across all cells in a graded fashion. This switch-like behaviour, combined with cell-to-cell variability in transcription rate, results in mRNA production variability spanning three orders of magnitude. We determined that cellular heterogeneity stems mainly from stochasticity intrinsic to individual alleles instead of variability in cellular composition. Together, our results demonstrate that it is now possible to quantitatively study the dynamics of transcriptional programs in single cells of living plants.
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Affiliation(s)
- Simon Alamos
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA
| | - Armando Reimer
- Biophysics Graduate Group, University of California Berkeley, Berkeley, CA, USA
| | - Krishna K Niyogi
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA.
- Howard Hughes Medical Institute, University of California Berkeley, Berkeley, CA, USA.
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
| | - Hernan G Garcia
- Biophysics Graduate Group, University of California Berkeley, Berkeley, CA, USA.
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA.
- Department of Physics, University of California Berkeley, Berkeley, CA, USA.
- Institute for Quantitative Biosciences-QB3, University of California Berkeley, Berkeley, CA, USA.
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18
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Higgins CE, Tang J, Higgins SP, Gifford CC, Mian BM, Jones DM, Zhang W, Costello A, Conti DJ, Samarakoon R, Higgins PJ. The Genomic Response to TGF-β1 Dictates Failed Repair and Progression of Fibrotic Disease in the Obstructed Kidney. Front Cell Dev Biol 2021; 9:678524. [PMID: 34277620 PMCID: PMC8284093 DOI: 10.3389/fcell.2021.678524] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 06/07/2021] [Indexed: 12/14/2022] Open
Abstract
Tubulointerstitial fibrosis is a common and diagnostic hallmark of a spectrum of chronic renal disorders. While the etiology varies as to the causative nature of the underlying pathology, persistent TGF-β1 signaling drives the relentless progression of renal fibrotic disease. TGF-β1 orchestrates the multifaceted program of kidney fibrogenesis involving proximal tubular dysfunction, failed epithelial recovery or re-differentiation, capillary collapse and subsequent interstitial fibrosis eventually leading to chronic and ultimately end-stage disease. An increasing complement of non-canonical elements function as co-factors in TGF-β1 signaling. p53 is a particularly prominent transcriptional co-regulator of several TGF-β1 fibrotic-response genes by complexing with TGF-β1 receptor-activated SMADs. This cooperative p53/TGF-β1 genomic cluster includes genes involved in cellular proliferative control, survival, apoptosis, senescence, and ECM remodeling. While the molecular basis for this co-dependency remains to be determined, a subset of TGF-β1-regulated genes possess both p53- and SMAD-binding motifs. Increases in p53 expression and phosphorylation, moreover, are evident in various forms of renal injury as well as kidney allograft rejection. Targeted reduction of p53 levels by pharmacologic and genetic approaches attenuates expression of the involved genes and mitigates the fibrotic response confirming a key role for p53 in renal disorders. This review focuses on mechanisms underlying TGF-β1-induced renal fibrosis largely in the context of ureteral obstruction, which mimics the pathophysiology of pediatric unilateral ureteropelvic junction obstruction, and the role of p53 as a transcriptional regulator within the TGF-β1 repertoire of fibrosis-promoting genes.
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Affiliation(s)
- Craig E. Higgins
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - Jiaqi Tang
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - Stephen P. Higgins
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - Cody C. Gifford
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - Badar M. Mian
- The Urological Institute of Northeastern New York, Albany, NY, United States
- Division of Urology, Department of Surgery, Albany Medical College, Albany, NY, United States
| | - David M. Jones
- Department of Pathology and Laboratory Medicine, Albany Medical College, Albany, NY, United States
| | - Wenzheng Zhang
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - Angelica Costello
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - David J. Conti
- Division of Transplantation Surgery, Department of Surgery, Albany Medical College, Albany, NY, United States
| | - Rohan Samarakoon
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
| | - Paul J. Higgins
- Department of Regenerative and Cancer Cell Biology, Albany Medical College, Albany, NY, United States
- The Urological Institute of Northeastern New York, Albany, NY, United States
- Division of Urology, Department of Surgery, Albany Medical College, Albany, NY, United States
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19
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Friedel L, Loewer A. The guardian's choice: how p53 enables context-specific decision-making in individual cells. FEBS J 2021; 289:40-52. [PMID: 33590949 DOI: 10.1111/febs.15767] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 02/03/2021] [Accepted: 02/15/2021] [Indexed: 01/20/2023]
Abstract
p53 plays a central role in defending the genomic integrity of our cells. In response to genotoxic stress, this tumour suppressor orchestrates the expression of hundreds of target genes, which induce a variety of cellular outcomes ranging from damage repair to induction of apoptosis. In this review, we examine how the p53 response is regulated on several levels in individual cells to allow precise and context-specific fate decisions. We discuss that the p53 response is not only controlled by its canonical regulators but also controlled by interconnected signalling pathways that influence the dynamics of p53 accumulation upon damage and modulate its transcriptional activity at target gene promoters. Additionally, we consider how the p53 response is diversified through a variety of mechanisms at the promoter level and beyond to induce context-specific outcomes in individual cells. These layers of regulation allow p53 to react in a stimulus-specific manner and fine-tune its signalling according to the individual needs of a given cell, enabling it to take the right decision on survival or death.
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Affiliation(s)
- Laura Friedel
- Systems Biology of the Stress Response, Department of Biology, Technical University of Darmstadt, Germany
| | - Alexander Loewer
- Systems Biology of the Stress Response, Department of Biology, Technical University of Darmstadt, Germany
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20
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Sammons MA, Nguyen TAT, McDade SS, Fischer M. Tumor suppressor p53: from engaging DNA to target gene regulation. Nucleic Acids Res 2020; 48:8848-8869. [PMID: 32797160 PMCID: PMC7498329 DOI: 10.1093/nar/gkaa666] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2020] [Revised: 07/24/2020] [Accepted: 07/30/2020] [Indexed: 12/13/2022] Open
Abstract
The p53 transcription factor confers its potent tumor suppressor functions primarily through the regulation of a large network of target genes. The recent explosion of next generation sequencing protocols has enabled the study of the p53 gene regulatory network (GRN) and underlying mechanisms at an unprecedented depth and scale, helping us to understand precisely how p53 controls gene regulation. Here, we discuss our current understanding of where and how p53 binds to DNA and chromatin, its pioneer-like role, and how this affects gene regulation. We provide an overview of the p53 GRN and the direct and indirect mechanisms through which p53 affects gene regulation. In particular, we focus on delineating the ubiquitous and cell type-specific network of regulatory elements that p53 engages; reviewing our understanding of how, where, and when p53 binds to DNA and the mechanisms through which these events regulate transcription. Finally, we discuss the evolution of the p53 GRN and how recent work has revealed remarkable differences between vertebrates, which are of particular importance to cancer researchers using mouse models.
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Affiliation(s)
- Morgan A Sammons
- Department of Biological Sciences and The RNA Institute, University at Albany, State University of New York, 1400 Washington Avenue, Albany, NY 12222, USA
| | - Thuy-Ai T Nguyen
- Genome Integrity & Structural Biology Laboratory and Immunity, Inflammation and Disease Laboratory, National Institute of Environmental Health Sciences/National Institutes of Health, 111 TW Alexander Drive, Research Triangle Park, NC 27709, USA
| | - Simon S McDade
- Patrick G Johnston Centre for Cancer Research, Queen's University Belfast, 97 Lisburn Road, Belfast BT9 7AE, UK
| | - Martin Fischer
- Computational Biology Group, Leibniz Institute on Aging – Fritz Lipmann Institute (FLI), Beutenbergstraße 11, 07745 Jena, Germany
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21
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Zambrano S, Loffreda A, Carelli E, Stefanelli G, Colombo F, Bertrand E, Tacchetti C, Agresti A, Bianchi ME, Molina N, Mazza D. First Responders Shape a Prompt and Sharp NF-κB-Mediated Transcriptional Response to TNF-α. iScience 2020; 23:101529. [PMID: 33083759 PMCID: PMC7509218 DOI: 10.1016/j.isci.2020.101529] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 08/05/2020] [Accepted: 09/01/2020] [Indexed: 12/01/2022] Open
Abstract
Nuclear factor (NF)-κB controls the transcriptional response to inflammatory signals by translocating into the nucleus, but we lack a single-cell characterization of the resulting transcription dynamics. Here we show that upon tumor necrosis factor (TNF)-α transcription of NF-κB target genes is heterogeneous in individual cells but results in an average nascent transcription profile that is prompt (i.e., occurs almost immediately) and sharp (i.e., increases and decreases rapidly) compared with NF-κB nuclear localization. Using an NF-κB-controlled MS2 reporter we show that the single-cell nascent transcription is more heterogeneous than NF-κB translocation dynamics, with a fraction of synchronized “first responders” that shape the average transcriptional profile and are more prone to respond to multiple TNF-α stimulations. A mathematical model combining NF-κB-mediated gene activation and a gene refractory state is able to reproduce these features. Our work shows how the expression of target genes induced by transcriptional activators can be heterogeneous across single cells and yet time resolved on average. Nascent transcription upon TNF-α is heterogeneous, with a subset of “first responders” The average nascent transcription is prompt and sharper than NF-κB response First responders do not depend on NF-κB dynamics and respond more to pulsed stimuli A model including NF-κB and a gene refractory state reproduces these observations
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Affiliation(s)
- Samuel Zambrano
- School of Medicine, Vita-Salute San Raffaele University, Milan 20132, Italy.,Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Alessia Loffreda
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Elena Carelli
- Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Giacomo Stefanelli
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Federica Colombo
- Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy.,Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan 20133, Italy
| | - Edouard Bertrand
- Institut de Génétique Moléculaire de Montpellier, CNRS, Montpellier 34293, France
| | - Carlo Tacchetti
- School of Medicine, Vita-Salute San Raffaele University, Milan 20132, Italy.,Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Alessandra Agresti
- Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Marco E Bianchi
- School of Medicine, Vita-Salute San Raffaele University, Milan 20132, Italy.,Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
| | - Nacho Molina
- Institut de Génétique et Biologie Moléculaire Cellulaire, Illkirch-Graffenstaden 67404, France
| | - Davide Mazza
- Experimental Imaging Center, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy
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