1
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Paul S, Adetunji J, Hong T. Widespread biochemical reaction networks enable Turing patterns without imposed feedback. Nat Commun 2024; 15:8380. [PMID: 39333132 PMCID: PMC11436923 DOI: 10.1038/s41467-024-52591-0] [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: 02/12/2024] [Accepted: 09/11/2024] [Indexed: 09/29/2024] Open
Abstract
Understanding self-organized pattern formation is fundamental to biology. In 1952, Alan Turing proposed a pattern-enabling mechanism in reaction-diffusion systems containing chemical species later conceptualized as activators and inhibitors that are involved in feedback loops. However, identifying pattern-enabling regulatory systems with the concept of feedback loops has been a long-standing challenge. To date, very few pattern-enabling circuits have been discovered experimentally. This is in stark contrast to ubiquitous periodic patterns and symmetry in biology. In this work, we systematically study Turing patterns in 23 elementary biochemical networks without assigning any activator or inhibitor. These mass action models describe post-synthesis interactions applicable to most proteins and RNAs in multicellular organisms. Strikingly, we find ten simple reaction networks capable of generating Turing patterns. While these network models are consistent with Turing's theory mathematically, there is no apparent connection between them and commonly used activator-feedback intuition. Instead, we identify a unifying network motif that enables Turing patterns via regulated degradation pathways with flexible diffusion rate constants of individual molecules. Our work reveals widespread biochemical systems for pattern formation, and it provides an alternative approach to tackle the challenge of identifying pattern-enabling biological systems.
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Affiliation(s)
- Shibashis Paul
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Knoxville, TN, 37916, USA
- Department of Biological Sciences, The University of Texas at Dallas, Richardson, TX, 75080, USA
| | - Joy Adetunji
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Knoxville, TN, 37916, USA
| | - Tian Hong
- Department of Biological Sciences, The University of Texas at Dallas, Richardson, TX, 75080, USA.
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2
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Yap XL, Chen JA. Elucidation of how the Mir-23-27-24 cluster regulates development and aging. Exp Mol Med 2024; 56:1263-1271. [PMID: 38871817 PMCID: PMC11263685 DOI: 10.1038/s12276-024-01266-3] [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: 03/05/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 06/15/2024] Open
Abstract
MicroRNAs (miRNAs) are pivotal regulators of gene expression and are involved in biological processes spanning from early developmental stages to the intricate process of aging. Extensive research has underscored the fundamental role of miRNAs in orchestrating eukaryotic development, with disruptions in miRNA biogenesis resulting in early lethality. Moreover, perturbations in miRNA function have been implicated in the aging process, particularly in model organisms such as nematodes and flies. miRNAs tend to be clustered in vertebrate genomes, finely modulating an array of biological pathways through clustering within a single transcript. Although extensive research of their developmental roles has been conducted, the potential implications of miRNA clusters in regulating aging remain largely unclear. In this review, we use the Mir-23-27-24 cluster as a paradigm, shedding light on the nuanced physiological functions of miRNA clusters during embryonic development and exploring their potential involvement in the aging process. Moreover, we advocate further research into the intricate interplay among miRNA clusters, particularly the Mir-23-27-24 cluster, in shaping the regulatory landscape of aging.
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Affiliation(s)
- Xin Le Yap
- Molecular and Cell Biology, Taiwan International Graduate Program, Academia Sinica and Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan
| | - Jun-An Chen
- Molecular and Cell Biology, Taiwan International Graduate Program, Academia Sinica and Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan.
- Institute of Molecular Biology, Academia Sinica, Taipei, Taiwan.
- Neuroscience Program of Academia Sinica, Academia Sinica, Taipei, Taiwan.
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3
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Xue G, Zhang X, Li W, Zhang L, Zhang Z, Zhou X, Zhang D, Zhang L, Li Z. A logic-incorporated gene regulatory network deciphers principles in cell fate decisions. eLife 2024; 12:RP88742. [PMID: 38652107 PMCID: PMC11037919 DOI: 10.7554/elife.88742] [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] [Indexed: 04/25/2024] Open
Abstract
Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.
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Affiliation(s)
- Gang Xue
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Xiaoyi Zhang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Wanqi Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Lu Zhang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Zongxu Zhang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Xiaolin Zhou
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Di Zhang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
| | - Lei Zhang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
- Beijing International Center for Mathematical Research, Center for Machine Learning Research, Peking UniversityBeijingChina
| | - Zhiyuan Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking UniversityBeijingChina
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4
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Mulas C. Control of cell state transitions by post-transcriptional regulation. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230050. [PMID: 38432322 PMCID: PMC10909504 DOI: 10.1098/rstb.2023.0050] [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: 07/17/2023] [Accepted: 12/19/2023] [Indexed: 03/05/2024] Open
Abstract
Cell state transitions are prevalent in biology, playing a fundamental role in development, homeostasis and repair. Dysregulation of cell state transitions can lead to or occur in a wide range of diseases. In this letter, I explore and highlight the role of post-transcriptional regulatory mechanisms in determining the dynamics of cell state transitions. I propose that regulation of protein levels after transcription provides an under-appreciated regulatory route to obtain fast and sharp transitions between distinct cell states. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.
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Affiliation(s)
- Carla Mulas
- Altos Labs Cambridge Institute of Science, Granta Park, Cambridge, CB21 6GP, UK
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5
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Hsu HC, Hsu SP, Hsu FY, Chang M, Chen JA. LncRNA Litchi is a regulator for harmonizing maturity and resilient functionality in spinal motor neurons. iScience 2024; 27:109207. [PMID: 38433925 PMCID: PMC10906515 DOI: 10.1016/j.isci.2024.109207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/08/2023] [Accepted: 02/07/2024] [Indexed: 03/05/2024] Open
Abstract
Long noncoding RNAs (lncRNAs) play pivotal roles in modulating gene expression during development and disease. Despite their high expression in the central nervous system (CNS), understanding the precise physiological functions of CNS-associated lncRNAs has been challenging, largely due to the in vitro-centric nature of studies in this field. Here, utilizing mouse embryonic stem cell (ESC)-derived motor neurons (MNs), we identified an unexplored MN-specific lncRNA, Litchi (Long Intergenic RNAs in Chat Intron). By employing an "exon-only" deletion strategy in ESCs and a mouse model, we reveal that Litchi deletion profoundly impacts MN dendritic complexity, axonal growth, and altered action potential patterns. Mechanistically, voltage-gated channels and neurite growth-related genes exhibited heightened sensitivity to Litchi deletion. Our Litchi-knockout mouse model displayed compromised motor behaviors and reduced muscle strength, highlighting Litchi's critical role in motor function. This study unveils an underappreciated function of lncRNAs in orchestrating MN maturation and maintaining robust electrophysiological properties.
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Affiliation(s)
- Ho-Chiang Hsu
- Institute of Molecular Biology, Academia Sinica, Taipei 11529, Taiwan
- Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Cheng Kung University and Academia Sinica, Taipei, Taiwan
| | - Sheng-Ping Hsu
- Institute of Molecular Biology, Academia Sinica, Taipei 11529, Taiwan
| | - Fang-Yu Hsu
- Institute of Molecular Biology, Academia Sinica, Taipei 11529, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
| | - Mien Chang
- Institute of Molecular Biology, Academia Sinica, Taipei 11529, Taiwan
| | - Jun-An Chen
- Institute of Molecular Biology, Academia Sinica, Taipei 11529, Taiwan
- Taiwan International Graduate Program in Interdisciplinary Neuroscience, National Cheng Kung University and Academia Sinica, Taipei, Taiwan
- Neuroscience Program of Academia Sinica, Academia Sinica, Taipei, Taiwan
- Genome and Systems Biology Degree Program, Academia Sinica and National Taiwan University, Taipei 10617, Taiwan
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6
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Du R, Flynn MJ, Honsa M, Jungmann R, Elowitz MB. miRNA circuit modules for precise, tunable control of gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.12.583048. [PMID: 38559239 PMCID: PMC10979901 DOI: 10.1101/2024.03.12.583048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The ability to express transgenes at specified levels is critical for understanding cellular behaviors, and for applications in gene and cell therapy. Transfection, viral vectors, and other gene delivery methods produce varying protein expression levels, with limited quantitative control, while targeted knock-in and stable selection are inefficient and slow. Active compensation mechanisms can improve precision, but the need for additional proteins or lack of tunability have prevented their widespread use. Here, we introduce a toolkit of compact, synthetic miRNA-based circuit modules that provide precise, tunable control of transgenes across diverse cell types. These circuits, termed DIMMERs (Dosage-Invariant miRNA-Mediated Expression Regulators) use multivalent miRNA regulatory interactions within an incoherent feed-forward loop architecture to achieve nearly uniform protein expression over more than two orders of magnitude variation in underlying gene dosages or transcription rates. They also allow coarse and fine control of expression, and are portable, functioning across diverse cell types. In addition, a heuristic miRNA design algorithm enables the creation of orthogonal circuit variants that independently control multiple genes in the same cell. These circuits allowed dramatically improved CRISPR imaging, and super-resolution imaging of EGFR receptors with transient transfections. The toolbox provided here should allow precise, tunable, dosage-invariant expression for research, gene therapy, and other biotechnology applications.
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Affiliation(s)
- Rongrong Du
- Howard Hughes Medical Institute and Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Michael J. Flynn
- Howard Hughes Medical Institute and Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Monique Honsa
- Max Planck Institute of Biochemistry, Martinsried, Germany; Faculty of Physics, Ludwig Maximilian University, Munich, Germany
| | - Ralf Jungmann
- Max Planck Institute of Biochemistry, Martinsried, Germany; Faculty of Physics, Ludwig Maximilian University, Munich, Germany
| | - Michael B. Elowitz
- Howard Hughes Medical Institute and Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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7
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Adhikary R, Roy A, Jolly MK, Das D. Effects of microRNA-mediated negative feedback on gene expression noise. Biophys J 2023; 122:4220-4240. [PMID: 37803829 PMCID: PMC10645566 DOI: 10.1016/j.bpj.2023.09.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 07/19/2023] [Accepted: 09/28/2023] [Indexed: 10/08/2023] Open
Abstract
MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression post-transcriptionally in eukaryotes by binding with target mRNAs and preventing translation. miRNA-mediated feedback motifs are ubiquitous in various genetic networks that control cellular decision making. A key question is how such a feedback mechanism may affect gene expression noise. To answer this, we have developed a mathematical model to study the effects of a miRNA-dependent negative-feedback loop on mean expression and noise in target mRNAs. Combining analytics and simulations, we show the existence of an expression threshold demarcating repressed and expressed regimes in agreement with earlier studies. The steady-state mRNA distributions are bimodal near the threshold, where copy numbers of mRNAs and miRNAs exhibit enhanced anticorrelated fluctuations. Moreover, variation of negative-feedback strength shifts the threshold locations and modulates the noise profiles. Notably, the miRNA-mRNA binding affinity and feedback strength collectively shape the bimodality. We also compare our model with a direct auto-repression motif, where a gene produces its own repressor. Auto-repression fails to produce bimodal mRNA distributions as found in miRNA-based indirect repression, suggesting the crucial role of miRNAs in creating phenotypic diversity. Together, we demonstrate how miRNA-dependent negative feedback modifies the expression threshold and leads to a broader parameter regime of bimodality compared to the no-feedback case.
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Affiliation(s)
- Raunak Adhikary
- Department of Biological Sciences, Indian Institute of Science Education And Research Kolkata Mohanpur, Nadia, West Bengal, India
| | - Arnab Roy
- Department of Biological Sciences, Indian Institute of Science Education And Research Kolkata Mohanpur, Nadia, West Bengal, India
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bengaluru, India
| | - Dipjyoti Das
- Department of Biological Sciences, Indian Institute of Science Education And Research Kolkata Mohanpur, Nadia, West Bengal, India.
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8
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Bocci F, Jia D, Nie Q, Jolly MK, Onuchic J. Theoretical and computational tools to model multistable gene regulatory networks. REPORTS ON PROGRESS IN PHYSICS. PHYSICAL SOCIETY (GREAT BRITAIN) 2023; 86:10.1088/1361-6633/acec88. [PMID: 37531952 PMCID: PMC10521208 DOI: 10.1088/1361-6633/acec88] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 08/02/2023] [Indexed: 08/04/2023]
Abstract
The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.
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Affiliation(s)
- Federico Bocci
- The NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
- Department of Mathematics, University of California, Irvine, CA 92697, USA
| | - Dongya Jia
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
| | - Qing Nie
- The NSF-Simons Center for Multiscale Cell Fate Research, University of California, Irvine, CA 92697, USA
- Department of Mathematics, University of California, Irvine, CA 92697, USA
| | - Mohit Kumar Jolly
- Centre for BioSystems Science and Engineering, Indian Institute of Science, Bangalore 560012, India
| | - José Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
- Department of Physics and Astronomy, Rice University, Houston, TX 77005, USA
- Department of Chemistry, Rice University, Houston, TX 77005, USA
- Department of Biosciences, Rice University, Houston, TX 77005, USA
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9
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Fedoseyeva VB, Novosadova EV, Nenasheva VV, Novosadova LV, Grivennikov IA, Tarantul VZ. Transcription of HOX Genes Is Significantly Increased during Neuronal Differentiation of iPSCs Derived from Patients with Parkinson's Disease. J Dev Biol 2023; 11:23. [PMID: 37367477 DOI: 10.3390/jdb11020023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 05/10/2023] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
Parkinson's disease (PD) is the most serious movement disorder, but the actual cause of this disease is still unknown. Induced pluripotent stem cell-derived neural cultures from PD patients carry the potential for experimental modeling of underlying molecular events. We analyzed the RNA-seq data of iPSC-derived neural precursor cells (NPCs) and terminally differentiated neurons (TDNs) from healthy donors (HD) and PD patients with mutations in PARK2 published previously. The high level of transcription of HOX family protein-coding genes and lncRNA transcribed from the HOX clusters was revealed in the neural cultures from PD patients, while in HD NPCs and TDNs, the majority of these genes were not expressed or slightly transcribed. The results of this analysis were generally confirmed by qPCR. The HOX paralogs in the 3' clusters were activated more strongly than the genes of the 5' cluster. The abnormal activation of the HOX gene program upon neuronal differentiation in the cells of PD patients raises the possibility that the abnormal expression of these key regulators of neuronal development impacts PD pathology. Further research is needed to investigate this hypothesis.
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Affiliation(s)
- Viya B Fedoseyeva
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow 123182, Russia
| | - Ekaterina V Novosadova
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow 123182, Russia
| | - Valentina V Nenasheva
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow 123182, Russia
| | - Lyudmila V Novosadova
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow 123182, Russia
| | - Igor A Grivennikov
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow 123182, Russia
| | - Vyacheslav Z Tarantul
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow 123182, Russia
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10
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Vand-Rajabpour F, Savage M, Belote RL, Judson-Torres RL. Critical Considerations for Investigating MicroRNAs during Tumorigenesis: A Case Study in Conceptual and Contextual Nuances of miR-211-5p in Melanoma. EPIGENOMES 2023; 7:9. [PMID: 37218870 PMCID: PMC10204420 DOI: 10.3390/epigenomes7020009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/11/2023] [Accepted: 04/13/2023] [Indexed: 05/24/2023] Open
Abstract
MicroRNAs are non-coding RNAs fundamental to metazoan development and disease. Although the aberrant regulation of microRNAs during mammalian tumorigenesis is well established, investigations into the contributions of individual microRNAs are wrought with conflicting observations. The underlying cause of these inconsistencies is often attributed to context-specific functions of microRNAs. We propose that consideration of both context-specific factors, as well as underappreciated fundamental concepts of microRNA biology, will permit a more harmonious interpretation of ostensibly diverging data. We discuss the theory that the biological function of microRNAs is to confer robustness to specific cell states. Through this lens, we then consider the role of miR-211-5p in melanoma progression. Using literature review and meta-analyses, we demonstrate how a deep understating of domain-specific contexts is critical for moving toward a concordant understanding of miR-211-5p and other microRNAs in cancer biology.
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Affiliation(s)
- Fatemeh Vand-Rajabpour
- Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, P.O. Box 14155-6447, Tehran 14176-13151, Iran
| | - Meghan Savage
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
| | - Rachel L. Belote
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Robert L. Judson-Torres
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
- Department of Dermatology, University of Utah, Salt Lake City, UT 84112, USA
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11
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Clauss B, Lu M. A quantitative evaluation of topological motifs and their coupling in gene circuit state distributions. iScience 2023; 26:106029. [PMID: 36824273 PMCID: PMC9941213 DOI: 10.1016/j.isci.2023.106029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 12/19/2022] [Accepted: 01/17/2023] [Indexed: 01/24/2023] Open
Abstract
One of the major challenges in biology is to understand how gene interactions collaborate to determine overall functions of biological systems. Here, we present a new computational framework that enables systematic, high-throughput, and quantitative evaluation of how small transcriptional regulatory circuit motifs, and their coupling, contribute to functions of a dynamical biological system. We illustrate how this approach can be applied to identify four-node gene circuits, circuit motifs, and motif coupling responsible for various gene expression state distributions, including those derived from single-cell RNA sequencing data. We also identify seven major classes of four-node circuits from clustering analysis of state distributions. The method is applied to establish phenomenological models of gene circuits driving human neuron differentiation, revealing important biologically relevant regulatory interactions. Our study will shed light on a better understanding of gene regulatory mechanisms in creating and maintaining cellular states.
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Affiliation(s)
- Benjamin Clauss
- Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA,Genetics Program, Graduate School of Biomedical Sciences, Tufts University, Boston, MA 02111, USA,The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Mingyang Lu
- Department of Bioengineering, Northeastern University, Boston, MA 02115, USA,Center for Theoretical Biological Physics, Northeastern University, Boston, MA 02115, USA,Genetics Program, Graduate School of Biomedical Sciences, Tufts University, Boston, MA 02111, USA,The Jackson Laboratory, Bar Harbor, ME 04609, USA,Corresponding author
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12
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Single-cell transcriptomic analysis reveals diversity within mammalian spinal motor neurons. Nat Commun 2023; 14:46. [PMID: 36596814 PMCID: PMC9810664 DOI: 10.1038/s41467-022-35574-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 12/12/2022] [Indexed: 01/05/2023] Open
Abstract
Spinal motor neurons (MNs) integrate sensory stimuli and brain commands to generate movements. In vertebrates, the molecular identities of the cardinal MN types such as those innervating limb versus trunk muscles are well elucidated. Yet the identities of finer subtypes within these cell populations that innervate individual muscle groups remain enigmatic. Here we investigate heterogeneity in mouse MNs using single-cell transcriptomics. Among limb-innervating MNs, we reveal a diverse neuropeptide code for delineating putative motor pool identities. Additionally, we uncover that axial MNs are subdivided into three molecularly distinct subtypes, defined by mediolaterally-biased Satb2, Nr2f2 or Bcl11b expression patterns with different axon guidance signatures. These three subtypes are present in chicken and human embryos, suggesting a conserved axial MN expression pattern across higher vertebrates. Overall, our study provides a molecular resource of spinal MN types and paves the way towards deciphering how neuronal subtypes evolved to accommodate vertebrate motor behaviors.
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13
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Nordick B, Chae-Yeon Park M, Quaranta V, Hong T. Cooperative RNA degradation stabilizes intermediate epithelial-mesenchymal states and supports a phenotypic continuum. iScience 2022; 25:105224. [PMID: 36248730 PMCID: PMC9557027 DOI: 10.1016/j.isci.2022.105224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Revised: 08/21/2022] [Accepted: 09/23/2022] [Indexed: 11/29/2022] Open
Abstract
Multiple intermediate epithelial-mesenchymal transition (EMT) states reflecting hybrid epithelial and mesenchymal phenotypes were observed in physiological and pathological conditions. Previous theoretical models explaining multiple EMT states rely on regulatory loops involving transcriptional feedback, which produce three or four attractors. This is incompatible with the observed continuum-like EMT spectrum. Here, we used mass-action-based models to describe post-transcriptional regulations, finding that cooperative RNA degradation via multiple microRNA binding sites can generate four-attractor systems without transcriptional feedback. Furthermore, the newly identified intermediates-enabling circuits are common in the EMT regulatory network, and they can synergize with transcriptional feedback to support phenotypic continuum. Finally, our model predicted a role of miR-101 in multistate EMT, and we identified evidence from single-cell RNA-sequencing data that support the prediction. Our work reveals a previously unknown role of cooperative RNA degradation and microRNAs in EMT, providing a framework that can bridge the gap between mechanistic models and single-cell experiments.
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Affiliation(s)
- Benjamin Nordick
- School of Genome Science and Technology, The University of Tennessee, Knoxville, TN 37916, USA
| | - Mary Chae-Yeon Park
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN 37916, USA
| | - Vito Quaranta
- Department of Biochemistry, Vanderbilt University School of Medicine Basic Sciences, Nashville, TN 37232, USA
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN 37916, USA
- National Institute for Mathematical and Biological Synthesis, Knoxville, TN 37916, USA
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14
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Sriram K. A mathematical model captures the role of adenyl cyclase Cyr1 and guanidine exchange factor Ira2 in creating a growth-to-hyphal bistable switch in Candida albicans. FEBS Open Bio 2022; 12:1700-1716. [PMID: 35979612 PMCID: PMC9527597 DOI: 10.1002/2211-5463.13470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 07/29/2022] [Accepted: 08/15/2022] [Indexed: 12/14/2022] Open
Abstract
Recent biochemical experiments have indicated that in Candida albicans, a commensal fungal pathogen, the Ras signaling pathway plays a significant role in the yeast-to-hyphal transition; specifically, two enzymes in this pathway, Adenyl Cyclase Cyr1 and GTPase activating protein Ira2, facilitate this transition, in the presence of energy sensor ATP. However, the precise mechanism by which protein interactions between Ira2 and Cyr1 and the energy sensor ATP result in the yeast-to-hyphal transition and create a switch-like process are unknown. We propose a new set of biochemical reaction steps that captures all the essential interactions between Ira2, Cyr1, and ATP in the Ras pathway. With the help of chemical reaction network theory, we demonstrate that this set of biochemical reaction steps results in bistability. Further, bifurcation analysis of the differential equations based on this set of reaction steps supports the existence of a bistable switch, and this switch may act as a checkpoint mechanism for the promotion of growth-to-hyphal transition in C. albicans.
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Affiliation(s)
- K Sriram
- Department of Computational Biology, Center for Computational BiologyIIIT‐DelhiIndia
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15
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Mazloom AR, Xu H, Reig-Palou J, Vasileva A, Román AC, Mulero-Navarro S, Lemischka IR, Sevilla A. Esrrb Regulates Specific Feed-Forward Loops to Transit From Pluripotency Into Early Stages of Differentiation. Front Cell Dev Biol 2022; 10:820255. [PMID: 35652095 PMCID: PMC9149258 DOI: 10.3389/fcell.2022.820255] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 03/24/2022] [Indexed: 01/15/2023] Open
Abstract
Characterization of pluripotent states, in which cells can both self-renew or differentiate, with the irreversible loss of pluripotency, are important research areas in developmental biology. Although microRNAs (miRNAs) have been shown to play a relevant role in cellular differentiation, the role of miRNAs integrated into gene regulatory networks and its dynamic changes during these early stages of embryonic stem cell (ESC) differentiation remain elusive. Here we describe the dynamic transcriptional regulatory circuitry of stem cells that incorporate protein-coding and miRNA genes based on miRNA array expression and quantitative sequencing of short transcripts upon the downregulation of the Estrogen Related Receptor Beta (Esrrb). The data reveals how Esrrb, a key stem cell transcription factor, regulates a specific stem cell miRNA expression program and integrates dynamic changes of feed-forward loops contributing to the early stages of cell differentiation upon its downregulation. Together these findings provide new insights on the architecture of the combined transcriptional post-transcriptional regulatory network in embryonic stem cells.
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Affiliation(s)
- Amin R. Mazloom
- Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Huilei Xu
- Department of Pharmacology and Systems Therapeutics, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Jaume Reig-Palou
- Department of Cell Biology, Physiology and Immunology, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Ana Vasileva
- Center for Radiological Research, Columbia University, New York, NY, United States
| | - Angel-Carlos Román
- Department of Biochemistry, Molecular Biology and Genetics, University of Extremadura, Badajoz, Spain
| | - Sonia Mulero-Navarro
- Department of Biochemistry, Molecular Biology and Genetics, University of Extremadura, Badajoz, Spain
| | - Ihor R. Lemischka
- Department of Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Ana Sevilla
- Department of Cell Biology, Physiology and Immunology, Faculty of Biology, University of Barcelona, Barcelona, Spain
- Department of Developmental and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Spain
- *Correspondence: Ana Sevilla,
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Nordick B, Yu PY, Liao G, Hong T. Nonmodular oscillator and switch based on RNA decay drive regeneration of multimodal gene expression. Nucleic Acids Res 2022; 50:3693-3708. [PMID: 35380686 PMCID: PMC9023291 DOI: 10.1093/nar/gkac217] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/13/2022] [Accepted: 03/21/2022] [Indexed: 12/15/2022] Open
Abstract
Periodic gene expression dynamics are key to cell and organism physiology. Studies of oscillatory expression have focused on networks with intuitive regulatory negative feedback loops, leaving unknown whether other common biochemical reactions can produce oscillations. Oscillation and noise have been proposed to support mammalian progenitor cells’ capacity to restore heterogenous, multimodal expression from extreme subpopulations, but underlying networks and specific roles of noise remained elusive. We use mass-action-based models to show that regulated RNA degradation involving as few as two RNA species—applicable to nearly half of human protein-coding genes—can generate sustained oscillations without explicit feedback. Diverging oscillation periods synergize with noise to robustly restore cell populations’ bimodal expression on timescales of days. The global bifurcation organizing this divergence relies on an oscillator and bistable switch which cannot be decomposed into two structural modules. Our work reveals surprisingly rich dynamics of post-transcriptional reactions and a potentially widespread mechanism underlying development, tissue regeneration, and cancer cell heterogeneity.
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Affiliation(s)
- Benjamin Nordick
- School of Genome Science and Technology, The University of Tennessee, Knoxville, Tennessee 37916, USA
| | - Polly Y Yu
- NSF-Simons Center for Mathematical and Statistical Analysis of Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Guangyuan Liao
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Tennessee 37916, USA
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, Tennessee 37916, USA.,National Institute for Mathematical and Biological Synthesis, Knoxville, Tennessee 37916, USA
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Nordick B, Hong T. Identification, visualization, statistical analysis and mathematical modeling of high-feedback loops in gene regulatory networks. BMC Bioinformatics 2021; 22:481. [PMID: 34607562 PMCID: PMC8489061 DOI: 10.1186/s12859-021-04405-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 09/27/2021] [Indexed: 12/21/2022] Open
Abstract
Background Feedback loops in gene regulatory networks play pivotal roles in governing functional dynamics of cells. Systems approaches demonstrated characteristic dynamical features, including multistability and oscillation, of positive and negative feedback loops. Recent experiments and theories have implicated highly interconnected feedback loops (high-feedback loops) in additional nonintuitive functions, such as controlling cell differentiation rate and multistep cell lineage progression. However, it remains challenging to identify and visualize high-feedback loops in complex gene regulatory networks due to the myriad of ways in which the loops can be combined. Furthermore, it is unclear whether the high-feedback loop structures with these potential functions are widespread in biological systems. Finally, it remains challenging to understand diverse dynamical features, such as high-order multistability and oscillation, generated by individual networks containing high-feedback loops. To address these problems, we developed HiLoop, a toolkit that enables discovery, visualization, and analysis of several types of high-feedback loops in large biological networks. Results HiLoop not only extracts high-feedback structures and visualize them in intuitive ways, but also quantifies the enrichment of overrepresented structures. Through random parameterization of mathematical models derived from target networks, HiLoop presents characteristic features of the underlying systems, including complex multistability and oscillations, in a unifying framework. Using HiLoop, we were able to analyze realistic gene regulatory networks containing dozens to hundreds of genes, and to identify many small high-feedback systems. We found more than a 100 human transcription factors involved in high-feedback loops that were not studied previously. In addition, HiLoop enabled the discovery of an enrichment of high feedback in pathways related to epithelial-mesenchymal transition. Conclusions HiLoop makes the study of complex networks accessible without significant computational demands. It can serve as a hypothesis generator through identification and modeling of high-feedback subnetworks, or as a quantification method for motif enrichment analysis. As an example of discovery, we found that multistep cell lineage progression may be driven by either specific instances of high-feedback loops with sparse appearances, or generally enriched topologies in gene regulatory networks. We expect HiLoop’s usefulness to increase as experimental data of regulatory networks accumulate. Code is freely available for use or extension at https://github.com/BenNordick/HiLoop. Supplementary Information The online version contains supplementary material available at 10.1186/s12859-021-04405-z.
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Affiliation(s)
- Benjamin Nordick
- School of Genome Science and Technology, The University of Tennessee, Knoxville, TN, USA
| | - Tian Hong
- Department of Biochemistry & Cellular and Molecular Biology, The University of Tennessee, Knoxville, TN, USA. .,National Institute for Mathematical and Biological Synthesis, Knoxville, TN, USA.
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