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Wyle Y, Lu N, Hepfer J, Sayal R, Martinez T, Wang A. The Role of Biophysical Factors in Organ Development: Insights from Current Organoid Models. Bioengineering (Basel) 2024; 11:619. [PMID: 38927855 PMCID: PMC11200479 DOI: 10.3390/bioengineering11060619] [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: 04/17/2024] [Revised: 05/26/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Biophysical factors play a fundamental role in human embryonic development. Traditional in vitro models of organogenesis focused on the biochemical environment and did not consider the effects of mechanical forces on developing tissue. While most human tissue has a Young's modulus in the low kilopascal range, the standard cell culture substrate, plasma-treated polystyrene, has a Young's modulus of 3 gigapascals, making it 10,000-100,000 times stiffer than native tissues. Modern in vitro approaches attempt to recapitulate the biophysical niche of native organs and have yielded more clinically relevant models of human tissues. Since Clevers' conception of intestinal organoids in 2009, the field has expanded rapidly, generating stem-cell derived structures, which are transcriptionally similar to fetal tissues, for nearly every organ system in the human body. For this reason, we conjecture that organoids will make their first clinical impact in fetal regenerative medicine as the structures generated ex vivo will better match native fetal tissues. Moreover, autologously sourced transplanted tissues would be able to grow with the developing embryo in a dynamic, fetal environment. As organoid technologies evolve, the resultant tissues will approach the structure and function of adult human organs and may help bridge the gap between preclinical drug candidates and clinically approved therapeutics. In this review, we discuss roles of tissue stiffness, viscoelasticity, and shear forces in organ formation and disease development, suggesting that these physical parameters should be further integrated into organoid models to improve their physiological relevance and therapeutic applicability. It also points to the mechanotransductive Hippo-YAP/TAZ signaling pathway as a key player in the interplay between extracellular matrix stiffness, cellular mechanics, and biochemical pathways. We conclude by highlighting how frontiers in physics can be applied to biology, for example, how quantum entanglement may be applied to better predict spontaneous DNA mutations. In the future, contemporary physical theories may be leveraged to better understand seemingly stochastic events during organogenesis.
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Affiliation(s)
- Yofiel Wyle
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
- Institute for Pediatric Regenerative Medicine, Shriners Children’s, Sacramento, CA 95817, USA
| | - Nathan Lu
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Jason Hepfer
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Rahul Sayal
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Taylor Martinez
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Aijun Wang
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
- Institute for Pediatric Regenerative Medicine, Shriners Children’s, Sacramento, CA 95817, USA
- Department of Biomedical Engineering, University of California-Davis, Davis, CA 95616, USA
- Center for Surgical Bioengineering, Department of Surgery, School of Medicine, University of California, Davis, 4625 2nd Ave., Research II, Suite 3005, Sacramento, CA 95817, USA
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Terui R, Berger SE, Sambel LA, Song D, Chistol G. Single-molecule imaging reveals the mechanism of bidirectional replication initiation in metazoa. Cell 2024:S0092-8674(24)00533-6. [PMID: 38866019 DOI: 10.1016/j.cell.2024.05.024] [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: 10/19/2023] [Revised: 03/28/2024] [Accepted: 05/13/2024] [Indexed: 06/14/2024]
Abstract
Metazoan genomes are copied bidirectionally from thousands of replication origins. Replication initiation entails the assembly and activation of two CMG helicases (Cdc45⋅Mcm2-7⋅GINS) at each origin. This requires several replication firing factors (including TopBP1, RecQL4, and DONSON) whose exact roles are still under debate. How two helicases are correctly assembled and activated at each origin is a long-standing question. By visualizing the recruitment of GINS, Cdc45, TopBP1, RecQL4, and DONSON in real time, we uncovered that replication initiation is surprisingly dynamic. First, TopBP1 transiently binds to the origin and dissociates before the start of DNA synthesis. Second, two Cdc45 are recruited together, even though Cdc45 alone cannot dimerize. Next, two copies of DONSON and two GINS simultaneously arrive at the origin, completing the assembly of two CMG helicases. Finally, RecQL4 is recruited to the CMG⋅DONSON⋅DONSON⋅CMG complex and promotes DONSON dissociation and CMG activation via its ATPase activity.
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Affiliation(s)
- Riki Terui
- Chemical and Systems Biology Department, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Scott E Berger
- Biophysics Program, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Larissa A Sambel
- Chemical and Systems Biology Department, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Dan Song
- Chemical and Systems Biology Department, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Gheorghe Chistol
- Chemical and Systems Biology Department, Stanford School of Medicine, Stanford, CA 94305, USA; Biophysics Program, Stanford School of Medicine, Stanford, CA 94305, USA; Cancer Biology Program, Stanford School of Medicine, Stanford, CA 94305, USA; Stanford Cancer Institute, Stanford School of Medicine, Stanford, CA 94305, USA; BioX Interdisciplinary Institute, Stanford School of Medicine, Stanford, CA 94305, USA.
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Terui R, Berger S, Sambel L, Song D, Chistol G. Single-Molecule Imaging Reveals the Mechanism of Bidirectional Replication Initiation in Metazoa. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.28.587265. [PMID: 38585807 PMCID: PMC10996697 DOI: 10.1101/2024.03.28.587265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Metazoan genomes are copied bidirectionally from thousands of replication origins. Replication initiation entails the assembly and activation of two CMG (Cdc45•Mcm2-7•GINS) helicases at each origin. This requires several firing factors (including TopBP1, RecQL4, DONSON) whose exact roles remain unclear. How two helicases are correctly assembled and activated at every single origin is a long-standing question. By visualizing the recruitment of GINS, Cdc45, TopBP1, RecQL4, and DONSON in real time, we uncovered a surprisingly dynamic picture of initiation. Firing factors transiently bind origins but do not travel with replisomes. Two Cdc45 simultaneously arrive at each origin and two GINS are recruited together, even though neither protein can dimerize. The synchronized delivery of two GINS is mediated by DONSON, which acts as a dimerization scaffold. We show that RecQL4 promotes DONSON dissociation and facilitates helicase activation. The high fidelity of bidirectional origin firing can be explained by a Hopfield-style kinetic proofreading mechanism.
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Affiliation(s)
- Riki Terui
- Chemical and Systems Biology, Stanford School of Medicine, Stanford CA94305
| | - Scott Berger
- Biophysics Program, Stanford School of Medicine, Stanford CA94305
| | - Larissa Sambel
- Chemical and Systems Biology, Stanford School of Medicine, Stanford CA94305
| | - Dan Song
- Current Address: Eikon Therapeutics Inc
| | - Gheorghe Chistol
- Chemical and Systems Biology, Stanford School of Medicine, Stanford CA94305
- Biophysics Program, Stanford School of Medicine, Stanford CA94305
- Cancer Biology Program, Stanford School of Medicine, Stanford CA94305
- Stanford Cancer Institute, Stanford School of Medicine, Stanford CA94305
- BioX Interdisciplinary Institute, Stanford School of Medicine, Stanford CA94305
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4
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Andrews SS, Wiley HS, Sauro HM. Design patterns of biological cells. Bioessays 2024; 46:e2300188. [PMID: 38247191 PMCID: PMC10922931 DOI: 10.1002/bies.202300188] [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: 09/30/2023] [Revised: 12/03/2023] [Accepted: 12/14/2023] [Indexed: 01/23/2024]
Abstract
Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.
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Affiliation(s)
- Steven S. Andrews
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - H. Steven Wiley
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA
| | - Herbert M. Sauro
- Department of Bioengineering, University of Washington, Seattle, WA, USA
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Fu Y, Clark F, Nomikou S, Tsirigos A, Lionnet T. Connecting Chromatin Structures to Gene Regulation Using Dynamic Polymer Simulations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.07.566032. [PMID: 37986912 PMCID: PMC10659377 DOI: 10.1101/2023.11.07.566032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The transfer of regulatory information between distal loci on chromatin is thought to involve physical proximity, but key biophysical features of these contacts remain unclear. For instance, it is unknown how close and for how long two loci need to be in order to productively interact. The main challenge is that it is currently impossible to measure chromatin dynamics with high spatiotemporal resolution at scale. Polymer simulations provide an accessible and rigorous way to test biophysical models of chromatin regulation, yet there is a lack of simple and general methods for extracting the values of model parameters. Here we adapt the Nelder-Mead simplex optimization algorithm to select the best polymer model matching a given Hi-C dataset, using the MYC locus as an example. The model's biophysical parameters predict a compartmental rearrangement of the MYC locus in leukemia, which we validate with single-cell measurements. Leveraging trajectories predicted by the model, we find that loci with similar Hi-C contact frequencies can exhibit widely different contact dynamics. Interestingly, the frequency of productive interactions between loci exhibits a non-linear relationship with their Hi-C contact frequency when we enforce a specific capture radius and contact duration. These observations are consistent with recent experimental observations and suggest that the dynamic ensemble of chromatin configurations, rather than average contact matrices, is required to fully predict long-range chromatin interactions.
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Affiliation(s)
- Yi Fu
- Institute for Systems Genetics, New York University School of Medicine, New York, NY 10016, USA
| | - Finnegan Clark
- Institute for Systems Genetics, New York University School of Medicine, New York, NY 10016, USA
| | | | - Aristotelis Tsirigos
- Department of Pathology, NYU School of Medicine, New York, NY 10016, USA
- Department of Medicine, Division of Precision Medicine, NYU School of Medicine, New York, NY 10016, USA
- Applied Bioinformatics Laboratories, NYU School of Medicine, New York, NY 10016, USA
| | - Timothee Lionnet
- Institute for Systems Genetics, New York University School of Medicine, New York, NY 10016, USA
- Department of Cell Biology, New York University School of Medicine, New York, NY 10016, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
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Abstract
Cells must tightly regulate their gene expression programs and yet rapidly respond to acute biochemical and biophysical cues within their environment. This information is transmitted to the nucleus through various signaling cascades, culminating in the activation or repression of target genes. Transcription factors (TFs) are key mediators of these signals, binding to specific regulatory elements within chromatin. While live-cell imaging has conclusively proven that TF-chromatin interactions are highly dynamic, how such transient interactions can have long-term impacts on developmental trajectories and disease progression is still largely unclear. In this review, we summarize our current understanding of the dynamic nature of TF functions, starting with a historical overview of early live-cell experiments. We highlight key factors that govern TF dynamics and how TF dynamics, in turn, affect downstream transcriptional bursting. Finally, we conclude with open challenges and emerging technologies that will further our understanding of transcriptional regulation.
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Affiliation(s)
- Kaustubh Wagh
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; , ,
- Department of Physics, University of Maryland, College Park, Maryland, USA;
| | - Diana A Stavreva
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; , ,
| | - Arpita Upadhyaya
- Department of Physics, University of Maryland, College Park, Maryland, USA;
- Institute for Physical Science and Technology, University of Maryland, College Park, Maryland, USA
| | - Gordon L Hager
- Laboratory of Receptor Biology and Gene Expression, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA; , ,
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Midha T, Mallory JD, Kolomeisky AB, Igoshin OA. Synergy among Pausing, Intrinsic Proofreading, and Accessory Proteins Results in Optimal Transcription Speed and Tolerable Accuracy. J Phys Chem Lett 2023; 14:3422-3429. [PMID: 37010247 DOI: 10.1021/acs.jpclett.3c00345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Cleavage of dinucleotides after the misincorporational pauses serves as a proofreading mechanism that increases transcriptional elongation accuracy. The accuracy is further improved by accessory proteins such as GreA and TFIIS. However, it is not clear why RNAP pauses and why cleavage-factor-assisted proofreading is necessary despite transcriptional errors in vitro being of the same order as those in downstream translation. Here, we developed a chemical-kinetic model that incorporates most relevant features of transcriptional proofreading and uncovers how the balance between speed and accuracy is achieved. We found that long pauses are essential for high accuracy, whereas cleavage-factor-stimulated proofreading optimizes speed. Moreover, in comparison to the cleavage of a single nucleotide or three nucleotides, RNAP backtracking and dinucleotide cleavage improve both speed and accuracy. Our results thereby show how the molecular mechanism and the kinetic parameters of the transcriptional process were evolutionarily optimized to achieve maximal speed and tolerable accuracy.
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Affiliation(s)
- Tripti Midha
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005, United States
| | - Joel D Mallory
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005, United States
| | - Anatoly B Kolomeisky
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005, United States
- Department of Chemistry, Rice University, Houston, Texas 77005, United States
- Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas 77005, United States
- Department of Physics and Astronomy, Rice University, Houston, Texas 77005, United States
| | - Oleg A Igoshin
- Center for Theoretical Biological Physics, Rice University, Houston, Texas 77005, United States
- Department of Chemistry, Rice University, Houston, Texas 77005, United States
- Department of Bioengineering, Rice University, Houston, Texas 77005, United States
- Department of Biosciences, Rice University, Houston, Texas 77005, United States
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8
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Çetiner U, Gunawardena J. Reformulating nonequilibrium steady states and generalized Hopfield discrimination. Phys Rev E 2022; 106:064128. [PMID: 36671125 DOI: 10.1103/physreve.106.064128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022]
Abstract
Despite substantial progress in nonequilibrium physics, steady-state (s.s.) probabilities remain intractable to analysis. For a Markov process, s.s. probabilities can be expressed in terms of transition rates using the graph-theoretic matrix-tree theorem (MTT). The MTT reveals that, away from equilibrium, s.s. probabilities become globally dependent on all rates, with expressions growing exponentially in the system size. This overwhelming complexity and lack of thermodynamic interpretation have greatly impeded analysis. Here we show that s.s. probabilities are proportional to the average of exp(-S(P)), where S(P) is the entropy generated along minimal paths P in the graph, and the average is taken over a probability distribution on spanning trees. Assuming Arrhenius rates, this "arboreal" distribution becomes Boltzmann-like, with the energy of a tree being its total edge barrier energy. This reformulation offers a thermodynamic interpretation that smoothly generalizes equilibrium statistical mechanics and reorganizes the expression complexity: the number of distinct minimal-path entropies depends not on graph size but on the entropy production index, a measure of nonequilibrium complexity. We demonstrate the power of this reformulation by extending Hopfield's analysis of discrimination by kinetic proofreading to any graph with index 1. We derive a general formula for the error ratio and use it to show how local energy dissipation can yield optimal discrimination through global synergy.
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Affiliation(s)
- Uğur Çetiner
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Jeremy Gunawardena
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
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