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Tao Y, Ghagre A, Molter CW, Clouvel A, Al Rahbani J, Brown CM, Nowrouzezahrai D, Ehrlicher AJ. Inferring cellular contractile forces and work using deep morphology traction microscopy. Biophys J 2024:S0006-3495(24)00479-X. [PMID: 39033326 DOI: 10.1016/j.bpj.2024.07.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 05/02/2024] [Accepted: 07/17/2024] [Indexed: 07/23/2024] Open
Abstract
Traction-force microscopy (TFM) has emerged as a widely used standard methodology to measure cell-generated traction forces and determine their role in regulating cell behavior. While TFM platforms have enabled many discoveries, their implementation remains limited due to complex experimental procedures, specialized substrates, and the ill-posed inverse problem whereby low-magnitude high-frequency noise in the displacement field severely contaminates the resulting traction measurements. Here, we introduce deep morphology traction microscopy (DeepMorphoTM), a deep-learning alternative to conventional TFM approaches. DeepMorphoTM first infers cell-induced substrate displacement solely from a sequence of cell shapes and subsequently computes cellular traction forces, thus avoiding the requirement of a specialized fiduciarily marked deformable substrate or force-free reference image. Rather, this technique drastically simplifies the overall experimental methodology, imaging, and analysis needed to conduct cell-contractility measurements. We demonstrate that DeepMorphoTM quantitatively matches conventional TFM results while offering stability against the biological variability in cell contractility for a given cell shape. Without high-frequency noise in the inferred displacement, DeepMorphoTM also resolves the ill-posedness of traction computation, increasing the consistency and accuracy of traction analysis. We demonstrate the accurate extrapolation across several cell types and substrate materials, suggesting robustness of the methodology. Accordingly, we present DeepMorphoTM as a capable yet simpler alternative to conventional TFM for characterizing cellular contractility in two dimensions.
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Affiliation(s)
- Yuanyuan Tao
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada; Department of Electrical and Computer Engineering, McGill University, Montreal, Quebec, Canada
| | - Ajinkya Ghagre
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
| | - Clayton W Molter
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
| | - Anna Clouvel
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada
| | - Jalal Al Rahbani
- Department of Physiology, McGill University, Montreal, Quebec, Canada
| | - Claire M Brown
- Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec, Canada; Department of Physiology, McGill University, Montreal, Quebec, Canada; Advanced BioImaging Facility (ABIF), McGill University, Montreal, Quebec, Canada
| | - Derek Nowrouzezahrai
- Department of Electrical and Computer Engineering, McGill University, Montreal, Quebec, Canada
| | - Allen J Ehrlicher
- Department of Bioengineering, McGill University, Montreal, Quebec, Canada; Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec, Canada; Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada; Department of Mechanical Engineering, McGill University, Montreal, Quebec, Canada; Rosalind and Morris Goodman Cancer Research Institute, McGill University, Montreal, Quebec, Canada; Centre for Structural Biology, McGill University, Montreal, Quebec, Canada.
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2
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Banerjee T, Matsuoka S, Biswas D, Miao Y, Pal DS, Kamimura Y, Ueda M, Devreotes PN, Iglesias PA. A dynamic partitioning mechanism polarizes membrane protein distribution. Nat Commun 2023; 14:7909. [PMID: 38036511 PMCID: PMC10689845 DOI: 10.1038/s41467-023-43615-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 11/14/2023] [Indexed: 12/02/2023] Open
Abstract
The plasma membrane is widely regarded as the hub of the numerous signal transduction activities. Yet, the fundamental biophysical mechanisms that spatiotemporally compartmentalize different classes of membrane proteins remain unclear. Using multimodal live-cell imaging, here we first show that several lipid-anchored membrane proteins are consistently depleted from the membrane regions where the Ras/PI3K/Akt/F-actin network is activated. The dynamic polarization of these proteins does not depend upon the F-actin-based cytoskeletal structures, recurring shuttling between membrane and cytosol, or directed vesicular trafficking. Photoconversion microscopy and single-molecule measurements demonstrate that these lipid-anchored molecules have substantially dissimilar diffusion profiles in different regions of the membrane which enable their selective segregation. When these diffusion coefficients are incorporated into an excitable network-based stochastic reaction-diffusion model, simulations reveal that the altered affinity mediated selective partitioning is sufficient to drive familiar propagating wave patterns. Furthermore, normally uniform integral and lipid-anchored membrane proteins partition successfully when membrane domain-specific peptides are optogenetically recruited to them. We propose "dynamic partitioning" as a new mechanism that can account for large-scale compartmentalization of a wide array of lipid-anchored and integral membrane proteins during various physiological processes where membrane polarizes.
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Affiliation(s)
- Tatsat Banerjee
- Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
- Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Satomi Matsuoka
- Laboratory for Cell Signaling Dynamics, RIKEN Center for Biosystems Dynamics Research, Suita, Osaka, Japan
- Laboratory of Single Molecule Biology, Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka, Japan
| | - Debojyoti Biswas
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Yuchuan Miao
- Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
- Department of Biological Chemistry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Dhiman Sankar Pal
- Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Yoichiro Kamimura
- Laboratory for Cell Signaling Dynamics, RIKEN Center for Biosystems Dynamics Research, Suita, Osaka, Japan
| | - Masahiro Ueda
- Laboratory for Cell Signaling Dynamics, RIKEN Center for Biosystems Dynamics Research, Suita, Osaka, Japan
- Laboratory of Single Molecule Biology, Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka, Japan
| | - Peter N Devreotes
- Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
- Department of Biological Chemistry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
| | - Pablo A Iglesias
- Department of Cell Biology and Center for Cell Dynamics, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
- Department of Electrical and Computer Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
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Rashid SA, Dong Y, Ogasawara H, Vierengel M, Essien ME, Salaita K. All-Covalent Nuclease-Resistant and Hydrogel-Tethered DNA Hairpin Probes Map pN Cell Traction Forces. ACS APPLIED MATERIALS & INTERFACES 2023; 15:33362-33372. [PMID: 37409737 PMCID: PMC10360067 DOI: 10.1021/acsami.3c04826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/15/2023] [Indexed: 07/07/2023]
Abstract
Cells sense and respond to the physical properties of their environment through receptor-mediated signaling, a process known as mechanotransduction, which can modulate critical cellular functions such as proliferation, differentiation, and survival. At the molecular level, cell adhesion receptors, such as integrins, transmit piconewton (pN)-scale forces to the extracellular matrix, and the magnitude of the force plays a critical role in cell signaling. The most sensitive approach to measuring integrin forces involves DNA hairpin-based sensors, which are used to quantify and map forces in living cells. Despite the broad use of DNA hairpin sensors to study a variety of mechanotransduction processes, these sensors are typically anchored to rigid glass slides, which are orders of magnitude stiffer than the extracellular matrix and hence modulate native biological responses. Here, we have developed nuclease-resistant DNA hairpin probes that are all covalently tethered to PEG hydrogels to image cell traction forces on physiologically relevant substrate stiffness. Using HeLa cells as a model cell line, we show that the molecular forces transmitted by integrins are highly sensitive to the bulk modulus of the substrate, and cells cultured on the 6 and 13 kPa gels produced a greater number of hairpin unfolding events compared to the 2 kPa substrates. Tension signals are spatially colocalized with pY118-paxillin, confirming focal adhesion-mediated probe opening. Additionally, we found that integrin forces are greater than 5.8 pN but less than 19 pN on 13 kPa gels. This work provides a general strategy to integrate molecular tension probes into hydrogels, which can better mimic in vivo mechanotransduction.
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Affiliation(s)
- Sk Aysha Rashid
- Department
of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Yixiao Dong
- Department
of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Hiroaki Ogasawara
- Department
of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Maia Vierengel
- Department
of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Mark Edoho Essien
- Department
of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Khalid Salaita
- Department
of Chemistry, Emory University, Atlanta, Georgia 30322, United States
- Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia 30322, United States
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Beta C, Edelstein-Keshet L, Gov N, Yochelis A. From actin waves to mechanism and back: How theory aids biological understanding. eLife 2023; 12:e87181. [PMID: 37428017 DOI: 10.7554/elife.87181] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 06/01/2023] [Indexed: 07/11/2023] Open
Abstract
Actin dynamics in cell motility, division, and phagocytosis is regulated by complex factors with multiple feedback loops, often leading to emergent dynamic patterns in the form of propagating waves of actin polymerization activity that are poorly understood. Many in the actin wave community have attempted to discern the underlying mechanisms using experiments and/or mathematical models and theory. Here, we survey methods and hypotheses for actin waves based on signaling networks, mechano-chemical effects, and transport characteristics, with examples drawn from Dictyostelium discoideum, human neutrophils, Caenorhabditis elegans, and Xenopus laevis oocytes. While experimentalists focus on the details of molecular components, theorists pose a central question of universality: Are there generic, model-independent, underlying principles, or just boundless cell-specific details? We argue that mathematical methods are equally important for understanding the emergence, evolution, and persistence of actin waves and conclude with a few challenges for future studies.
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Affiliation(s)
- Carsten Beta
- Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany
| | | | - Nir Gov
- Department of Chemical and Biological Physics, Weizmann Institute of Science, Rehovot, Israel
| | - Arik Yochelis
- Swiss Institute for Dryland Environmental and Energy Research, Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Midreshet Ben-Gurion, Israel
- Department of Physics, Ben-Gurion University of the Negev, Be'er Sheva, Israel
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Kuang X, Guan G, Tang C, Zhang L. MorphoSim: an efficient and scalable phase-field framework for accurately simulating multicellular morphologies. NPJ Syst Biol Appl 2023; 9:6. [PMID: 36806172 PMCID: PMC9938209 DOI: 10.1038/s41540-023-00265-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Accepted: 01/04/2023] [Indexed: 02/19/2023] Open
Abstract
The phase field model can accurately simulate the evolution of microstructures with complex morphologies, and it has been widely used for cell modeling in the last two decades. However, compared to other cellular models such as the coarse-grained model and the vertex model, its high computational cost caused by three-dimensional spatial discretization hampered its application and scalability, especially for multicellular organisms. Recently, we built a phase field model coupled with in vivo imaging data to accurately reconstruct the embryonic morphogenesis of Caenorhabditis elegans from 1- to 8-cell stages. In this work, we propose an improved phase field model by using the stabilized numerical scheme and modified volume constriction. Then we present a scalable phase-field framework, MorphoSim, which is 100 times more efficient than the previous one and can simulate over 100 mechanically interacting cells. Finally, we demonstrate how MorphoSim can be successfully applied to reproduce the assembly, self-repairing, and dissociation of a synthetic artificial multicellular system - the synNotch system.
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Affiliation(s)
- Xiangyu Kuang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Guoye Guan
- Center for Quantitative Biology, Peking University, Beijing, 100871, China
| | - Chao Tang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China.
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China.
- School of Physics, Peking University, Beijing, 100871, China.
| | - Lei Zhang
- Center for Quantitative Biology, Peking University, Beijing, 100871, China.
- Beijing International Center for Mathematical Research, Peking University, Beijing, 100871, China.
- Center for Machine Learning Research, Peking University, Beijing, 100871, China.
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Banerjee T, Matsuoka S, Biswas D, Miao Y, Pal DS, Kamimura Y, Ueda M, Devreotes PN, Iglesias PA. A dynamic partitioning mechanism polarizes membrane protein distribution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.03.522496. [PMID: 36712016 PMCID: PMC9881856 DOI: 10.1101/2023.01.03.522496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The plasma membrane is widely regarded as the hub of the signal transduction network activities that drives numerous physiological responses, including cell polarity and migration. Yet, the symmetry breaking process in the membrane, that leads to dynamic compartmentalization of different proteins, remains poorly understood. Using multimodal live-cell imaging, here we first show that multiple endogenous and synthetic lipid-anchored proteins, despite maintaining stable tight association with the inner leaflet of the plasma membrane, were unexpectedly depleted from the membrane domains where the signaling network was spontaneously activated such as in the new protrusions as well as within the propagating ventral waves. Although their asymmetric patterns resembled those of standard peripheral "back" proteins such as PTEN, unlike the latter, these lipidated proteins did not dissociate from the membrane upon global receptor activation. Our experiments not only discounted the possibility of recurrent reversible translocation from membrane to cytosol as it occurs for weakly bound peripheral membrane proteins, but also ruled out the necessity of directed vesicular trafficking and cytoskeletal supramolecular structure-based restrictions in driving these dynamic symmetry breaking events. Selective photoconversion-based protein tracking assays suggested that these asymmetric patterns instead originate from the inherent ability of these membrane proteins to "dynamically partition" into distinct domains within the plane of the membrane. Consistently, single-molecule measurements showed that these lipid-anchored molecules have substantially dissimilar diffusion profiles in different regions of the membrane. When these profiles were incorporated into an excitable network-based stochastic reaction-diffusion model of the system, simulations revealed that our proposed "dynamic partitioning" mechanism is sufficient to give rise to familiar asymmetric propagating wave patterns. Moreover, we demonstrated that normally uniform integral and lipid-anchored membrane proteins in Dictyostelium and mammalian neutrophil cells can be induced to partition spatiotemporally to form polarized patterns, by optogenetically recruiting membrane domain-specific peptides to these proteins. Together, our results indicate "dynamic partitioning" as a new mechanism of plasma membrane organization, that can account for large-scale compartmentalization of a wide array of lipid-anchored and integral membrane proteins in different physiological processes.
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Moldenhawer T, Moreno E, Schindler D, Flemming S, Holschneider M, Huisinga W, Alonso S, Beta C. Spontaneous transitions between amoeboid and keratocyte-like modes of migration. Front Cell Dev Biol 2022; 10:898351. [PMID: 36247011 PMCID: PMC9563996 DOI: 10.3389/fcell.2022.898351] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 07/18/2022] [Indexed: 01/17/2023] Open
Abstract
The motility of adherent eukaryotic cells is driven by the dynamics of the actin cytoskeleton. Despite the common force-generating actin machinery, different cell types often show diverse modes of locomotion that differ in their shape dynamics, speed, and persistence of motion. Recently, experiments in Dictyostelium discoideum have revealed that different motility modes can be induced in this model organism, depending on genetic modifications, developmental conditions, and synthetic changes of intracellular signaling. Here, we report experimental evidence that in a mutated D. discoideum cell line with increased Ras activity, switches between two distinct migratory modes, the amoeboid and fan-shaped type of locomotion, can even spontaneously occur within the same cell. We observed and characterized repeated and reversible switchings between the two modes of locomotion, suggesting that they are distinct behavioral traits that coexist within the same cell. We adapted an established phenomenological motility model that combines a reaction-diffusion system for the intracellular dynamics with a dynamic phase field to account for our experimental findings.
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Affiliation(s)
- Ted Moldenhawer
- Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany
| | - Eduardo Moreno
- Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Daniel Schindler
- Institute of Mathematics, University of Potsdam, Potsdam, Germany
| | - Sven Flemming
- Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany
| | | | - Wilhelm Huisinga
- Institute of Mathematics, University of Potsdam, Potsdam, Germany
| | - Sergio Alonso
- Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Carsten Beta
- Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany
- *Correspondence: Carsten Beta,
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