Albert Alonso, Julius B. Kirkegaard, Robert G. Endres
Single-cell organisms and various cell types use a range of motility modes when following a chemical gradient, but it is unclear which mode is best suited for different gradients. Here, we model directional decision-making in chemotactic amoeboid cells as a stimulus-dependent actin recruitment contest. Pseudopods extending from the cell body compete for a finite actin pool to push the cell in their direction until one pseudopod wins and determines the direction of movement. Our minimal model provides a quantitative understanding of the strategies cells use to reach the physical limit of accurate chemotaxis, aligning with data without explicit gradient sensing or cellular memory for persistence. To generalize our model, we employ reinforcement learning optimization to study the effect of pseudopod suppression, a simple but effective cellular algorithm by which cells can suppress possible directions of movement. Different pseudopod-based chemotaxis strategies emerge naturally depending on the environment and its dynamics. For instance, in static gradients, cells can react faster at the cost of pseudopod accuracy, which is particularly useful in noisy, shallow gradients where it paradoxically increases chemotactic accuracy. In contrast, in dynamics gradients, cells form textit{de novo} pseudopods. Overall, our work demonstrates mechanical intelligence for high chemotaxis performance with minimal cellular regulation.
{"title":"Persistent pseudopod splitting is an effective chemotaxis strategy in shallow gradients","authors":"Albert Alonso, Julius B. Kirkegaard, Robert G. Endres","doi":"arxiv-2409.09342","DOIUrl":"https://doi.org/arxiv-2409.09342","url":null,"abstract":"Single-cell organisms and various cell types use a range of motility modes\u0000when following a chemical gradient, but it is unclear which mode is best suited\u0000for different gradients. Here, we model directional decision-making in\u0000chemotactic amoeboid cells as a stimulus-dependent actin recruitment contest.\u0000Pseudopods extending from the cell body compete for a finite actin pool to push\u0000the cell in their direction until one pseudopod wins and determines the\u0000direction of movement. Our minimal model provides a quantitative understanding\u0000of the strategies cells use to reach the physical limit of accurate chemotaxis,\u0000aligning with data without explicit gradient sensing or cellular memory for\u0000persistence. To generalize our model, we employ reinforcement learning\u0000optimization to study the effect of pseudopod suppression, a simple but\u0000effective cellular algorithm by which cells can suppress possible directions of\u0000movement. Different pseudopod-based chemotaxis strategies emerge naturally\u0000depending on the environment and its dynamics. For instance, in static\u0000gradients, cells can react faster at the cost of pseudopod accuracy, which is\u0000particularly useful in noisy, shallow gradients where it paradoxically\u0000increases chemotactic accuracy. In contrast, in dynamics gradients, cells form\u0000textit{de novo} pseudopods. Overall, our work demonstrates mechanical\u0000intelligence for high chemotaxis performance with minimal cellular regulation.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Olenka Jain, Brato Chakrabarti, Reza Farhadifar, Elizabeth R. Gavis, Michael J. Shelley, Stanislav Y. Shvartsman
This work probes the role of cell geometry in orienting self-organized fluid flows in the late stage Drosophila oocyte. Recent theoretical work has shown that a model, which relies only on hydrodynamic interactions of flexible, cortically anchored microtubules (MTs) and the mechanical loads from molecular motors moving upon them, is sufficient to generate observed flows. While the emergence of flows has been studied in spheres, oocytes change shape during streaming and it was unclear how robust these flows are to the geometry of the cell. Here we use biophysical theory and computational analysis to investigate the role of geometry and find that the axis of rotation is set by the shape of the domain and that the flow is robust to biologically relevant perturbations of the domain shape. Using live imaging and 3D flow reconstruction, we test the predictions of the theory/simulation, finding consistency between the model and live experiments, further demonstrating a geometric dependence on flow direction in late-stage Drosophila oocytes.
{"title":"Geometric Effects in Large Scale Intracellular Flows","authors":"Olenka Jain, Brato Chakrabarti, Reza Farhadifar, Elizabeth R. Gavis, Michael J. Shelley, Stanislav Y. Shvartsman","doi":"arxiv-2409.06763","DOIUrl":"https://doi.org/arxiv-2409.06763","url":null,"abstract":"This work probes the role of cell geometry in orienting self-organized fluid\u0000flows in the late stage Drosophila oocyte. Recent theoretical work has shown\u0000that a model, which relies only on hydrodynamic interactions of flexible,\u0000cortically anchored microtubules (MTs) and the mechanical loads from molecular\u0000motors moving upon them, is sufficient to generate observed flows. While the\u0000emergence of flows has been studied in spheres, oocytes change shape during\u0000streaming and it was unclear how robust these flows are to the geometry of the\u0000cell. Here we use biophysical theory and computational analysis to investigate\u0000the role of geometry and find that the axis of rotation is set by the shape of\u0000the domain and that the flow is robust to biologically relevant perturbations\u0000of the domain shape. Using live imaging and 3D flow reconstruction, we test the\u0000predictions of the theory/simulation, finding consistency between the model and\u0000live experiments, further demonstrating a geometric dependence on flow\u0000direction in late-stage Drosophila oocytes.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We examine the difference in motion ordering between cellular systems with and without information transfer to evaluate the effect of the polar--polar interaction through mutual guiding, which enables cells to inform other cells of their moving directions. We compare this interaction with the polar--nonpolar interaction through cell motion triggered by cellular contact, which cannot provide information on the moving directions. We model these interactions on the basis of the cellular Potts model. We calculate the order parameter of the polar direction in the interactions and examine the cell concentration and surface tension conditions of ordering. The results suggest that the polar--polar interaction through mutual guiding efficiently induces the motion ordering in comparison with the polar-nonpolar interaction for contact triggering, except in cases of weak driving. The results also show that the polar--polar interaction efficiently accelerates the collective motion compared with the polar--nonpolar interaction.
{"title":"Motion Ordering in Cellular Polar-polar and Polar-nonpolar Interactions","authors":"Katsuyoshi Matsushita, Taiko Arakaki, Koichi Fujimoto","doi":"arxiv-2409.05333","DOIUrl":"https://doi.org/arxiv-2409.05333","url":null,"abstract":"We examine the difference in motion ordering between cellular systems with\u0000and without information transfer to evaluate the effect of the polar--polar\u0000interaction through mutual guiding, which enables cells to inform other cells\u0000of their moving directions. We compare this interaction with the\u0000polar--nonpolar interaction through cell motion triggered by cellular contact,\u0000which cannot provide information on the moving directions. We model these\u0000interactions on the basis of the cellular Potts model. We calculate the order\u0000parameter of the polar direction in the interactions and examine the cell\u0000concentration and surface tension conditions of ordering. The results suggest\u0000that the polar--polar interaction through mutual guiding efficiently induces\u0000the motion ordering in comparison with the polar-nonpolar interaction for\u0000contact triggering, except in cases of weak driving. The results also show that\u0000the polar--polar interaction efficiently accelerates the collective motion\u0000compared with the polar--nonpolar interaction.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shubhadeep Sadhukhan, Cristina Martinez-Torres, Samo Penič, Carsten Beta, Aleš Iglič, Nir S Gov
Cell motility is fundamental to many biological processes, and cells exhibit a variety of migration patterns. Many motile cell types follow a universal law that connects their speed and persistency, a property that can originate from the intracellular transport of polarity cues due to the global actin retrograde flow. This mechanism was termed the ``Universal Coupling between cell Speed and Persistency"(UCSP). Here we implemented a simplified version of the UCSP mechanism in a coarse-grained ``minimal-cell" model, which is composed of a three-dimensional vesicle that contains curved active proteins. This model spontaneously forms a lamellipodia-like motile cell shape, which is however sensitive and can depolarize into a non-motile form due to random fluctuations or when interacting with external obstacles. The UCSP implementation introduces long-range inhibition, which stabilizes the motile phenotype. This allows our model to describe the robust polarity observed in cells and explain a large variety of cellular dynamics, such as the relation between cell speed and aspect ratio, cell-barrier scattering, and cellular oscillations in different types of geometric confinements.
{"title":"Modelling how lamellipodia-driven cells maintain persistent migration and interact with external barriers","authors":"Shubhadeep Sadhukhan, Cristina Martinez-Torres, Samo Penič, Carsten Beta, Aleš Iglič, Nir S Gov","doi":"arxiv-2409.04772","DOIUrl":"https://doi.org/arxiv-2409.04772","url":null,"abstract":"Cell motility is fundamental to many biological processes, and cells exhibit\u0000a variety of migration patterns. Many motile cell types follow a universal law\u0000that connects their speed and persistency, a property that can originate from\u0000the intracellular transport of polarity cues due to the global actin retrograde\u0000flow. This mechanism was termed the ``Universal Coupling between cell Speed and\u0000Persistency\"(UCSP). Here we implemented a simplified version of the UCSP\u0000mechanism in a coarse-grained ``minimal-cell\" model, which is composed of a\u0000three-dimensional vesicle that contains curved active proteins. This model\u0000spontaneously forms a lamellipodia-like motile cell shape, which is however\u0000sensitive and can depolarize into a non-motile form due to random fluctuations\u0000or when interacting with external obstacles. The UCSP implementation introduces\u0000long-range inhibition, which stabilizes the motile phenotype. This allows our\u0000model to describe the robust polarity observed in cells and explain a large\u0000variety of cellular dynamics, such as the relation between cell speed and\u0000aspect ratio, cell-barrier scattering, and cellular oscillations in different\u0000types of geometric confinements.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For a cell-bulk ODE-PDE model in $mathbb{R}^2$, a hybrid asymptotic-numerical theory is developed to provide a new theoretical and computationally efficient approach for studying how oscillatory dynamics associated with spatially segregated dynamically active ``units" or ``cells" are regulated by a PDE bulk diffusion field that is both produced and absorbed by the entire cell population. The study of oscillator synchronization in a PDE diffusion field was one of the initial aims of Yoshiki Kuramoto's foundational work. For this cell-bulk model, strong localized perturbation theory, as extended to a time-dependent setting, is used to derive a new integro-differential ODE system that characterizes intracellular dynamics in a memory-dependent bulk-diffusion field. For this nonlocal reduced system, a novel fast time-marching scheme, relying in part on the emph{sum-of-exponentials method} to numerically treat convolution integrals, is developed to rapidly and accurately compute numerical solutions to the integro-differential system over long time intervals. For the special case of Sel'kov reaction kinetics, a wide variety of large-scale oscillatory dynamical behavior including phase synchronization, mixed-mode oscillations, and quorum-sensing are illustrated for various ranges of the influx and efflux permeability parameters, the bulk degradation rate and bulk diffusivity, and the specific spatial configuration of cells. Results from our fast algorithm, obtained in under one minute of CPU time on a laptop, are benchmarked against PDE simulations of the cell-bulk model, which are performed with a commercial PDE solver, that have run-times that are orders of magnitude larger.
{"title":"Synchronized Memory-Dependent Intracellular Oscillations for a Cell-Bulk ODE-PDE Model in $mathbb{R}^2$","authors":"Merlin Pelz, Michael J. Ward","doi":"arxiv-2409.00623","DOIUrl":"https://doi.org/arxiv-2409.00623","url":null,"abstract":"For a cell-bulk ODE-PDE model in $mathbb{R}^2$, a hybrid\u0000asymptotic-numerical theory is developed to provide a new theoretical and\u0000computationally efficient approach for studying how oscillatory dynamics\u0000associated with spatially segregated dynamically active ``units\" or ``cells\"\u0000are regulated by a PDE bulk diffusion field that is both produced and absorbed\u0000by the entire cell population. The study of oscillator synchronization in a PDE\u0000diffusion field was one of the initial aims of Yoshiki Kuramoto's foundational\u0000work. For this cell-bulk model, strong localized perturbation theory, as\u0000extended to a time-dependent setting, is used to derive a new\u0000integro-differential ODE system that characterizes intracellular dynamics in a\u0000memory-dependent bulk-diffusion field. For this nonlocal reduced system, a\u0000novel fast time-marching scheme, relying in part on the\u0000emph{sum-of-exponentials method} to numerically treat convolution integrals,\u0000is developed to rapidly and accurately compute numerical solutions to the\u0000integro-differential system over long time intervals. For the special case of\u0000Sel'kov reaction kinetics, a wide variety of large-scale oscillatory dynamical\u0000behavior including phase synchronization, mixed-mode oscillations, and\u0000quorum-sensing are illustrated for various ranges of the influx and efflux\u0000permeability parameters, the bulk degradation rate and bulk diffusivity, and\u0000the specific spatial configuration of cells. Results from our fast algorithm,\u0000obtained in under one minute of CPU time on a laptop, are benchmarked against\u0000PDE simulations of the cell-bulk model, which are performed with a commercial\u0000PDE solver, that have run-times that are orders of magnitude larger.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Herbert Egger, Kathrin Hellmuth, Nora Philippi, Matthias Schlottbom
Chemotaxis describes the intricate interplay of cellular motion in response to a chemical signal. We here consider the case of slab geometry which models chemotactic motion between two infinite membranes. Like previous works, we are particularly interested in the asymptotic regime of high tumbling rates. We establish local existence and uniqueness of solutions to the kinetic equation and show their convergence towards solutions of a parabolic Keller-Segel model in the asymptotic limit. In addition, we prove convergence rates with respect to the asymptotic parameter under additional regularity assumptions on the problem data. Particular difficulties in our analysis are caused by vanishing velocities in the kinetic model as well as the occurrence of boundary terms.
{"title":"A kinetic chemotaxis model and its diffusion limit in slab geometry","authors":"Herbert Egger, Kathrin Hellmuth, Nora Philippi, Matthias Schlottbom","doi":"arxiv-2408.17243","DOIUrl":"https://doi.org/arxiv-2408.17243","url":null,"abstract":"Chemotaxis describes the intricate interplay of cellular motion in response\u0000to a chemical signal. We here consider the case of slab geometry which models\u0000chemotactic motion between two infinite membranes. Like previous works, we are\u0000particularly interested in the asymptotic regime of high tumbling rates. We\u0000establish local existence and uniqueness of solutions to the kinetic equation\u0000and show their convergence towards solutions of a parabolic Keller-Segel model\u0000in the asymptotic limit. In addition, we prove convergence rates with respect\u0000to the asymptotic parameter under additional regularity assumptions on the\u0000problem data. Particular difficulties in our analysis are caused by vanishing\u0000velocities in the kinetic model as well as the occurrence of boundary terms.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the recently proposed Graph Vertex Model (GVM), cellular rearrangements are implemented as local graph transformations of the cell aggregate, represented by a knowledge graph [1]. This study extends GVM to incorporate cell division, a critical biological process involved in morphogenesis, homeostasis, and disease progression. Like cellular rearrangements, cell division in GVM begins by identifying a subgraph of nodes and links, involved in the division, by matching suitable graph patterns or templates within the full knowledge graph. The matched subgraph is then transformed to incorporate topological changes within the knowledge graph, caused by the division event. Importantly, when this transformation is applied to a polygon in a 2D tiling, it performs the transformation, required to divide a polygon, indicating that the 3D graph transformation is general and applicable also to 2D vertex models. Our extension of GVM enables the study of the dynamics of growing cell aggregates in 3D to offer new insights into developmental processes and cancer growth.
{"title":"Graph polyhedral divisions in growing cell aggregates","authors":"Urban Železnik, Matej Krajnc, Tanmoy Sarkar","doi":"arxiv-2408.07551","DOIUrl":"https://doi.org/arxiv-2408.07551","url":null,"abstract":"In the recently proposed Graph Vertex Model (GVM), cellular rearrangements\u0000are implemented as local graph transformations of the cell aggregate,\u0000represented by a knowledge graph [1]. This study extends GVM to incorporate\u0000cell division, a critical biological process involved in morphogenesis,\u0000homeostasis, and disease progression. Like cellular rearrangements, cell\u0000division in GVM begins by identifying a subgraph of nodes and links, involved\u0000in the division, by matching suitable graph patterns or templates within the\u0000full knowledge graph. The matched subgraph is then transformed to incorporate\u0000topological changes within the knowledge graph, caused by the division event.\u0000Importantly, when this transformation is applied to a polygon in a 2D tiling,\u0000it performs the transformation, required to divide a polygon, indicating that\u0000the 3D graph transformation is general and applicable also to 2D vertex models.\u0000Our extension of GVM enables the study of the dynamics of growing cell\u0000aggregates in 3D to offer new insights into developmental processes and cancer\u0000growth.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The mechanical properties within living cells play a critical role in the adaptive regulation of their biological functions upon environmental and internal stimuli. While these properties exhibit nonequilibrium dynamics due to the thermal and nonthermal forces that universally coexist in actin-myosin-active proliferative cells, quantifying them within such complex systems remains challenging. Here, we develop a nonequilibrium framework that combines fluorescence correlation spectroscopy (FCS) measurements of intracellular diffusion with nonequilibrium theory to quantitatively analyze cell-specific nonthermal driving forces and cellular adaptability. Our results reveal that intracellular particle diffusion is influenced not only by common thermal forces but also by nonthermal forces generated by approximately 10-100 motor proteins. Furthermore, we derive a physical parameter that quantitatively assesses the sensitivity of intracellular particle responses to these nonthermal forces, showing that systems with more active diffusion exhibit higher response sensitivity. Our work highlights the biological fluctuations arising from multiple interacting elements, advancing the understanding of the complex mechanical properties within living cells.
{"title":"Nonthermal driving forces in cells revealed by nonequilibrium fluctuations","authors":"Yuika Ueda, Shinji Deguchi","doi":"arxiv-2408.06683","DOIUrl":"https://doi.org/arxiv-2408.06683","url":null,"abstract":"The mechanical properties within living cells play a critical role in the\u0000adaptive regulation of their biological functions upon environmental and\u0000internal stimuli. While these properties exhibit nonequilibrium dynamics due to\u0000the thermal and nonthermal forces that universally coexist in\u0000actin-myosin-active proliferative cells, quantifying them within such complex\u0000systems remains challenging. Here, we develop a nonequilibrium framework that\u0000combines fluorescence correlation spectroscopy (FCS) measurements of\u0000intracellular diffusion with nonequilibrium theory to quantitatively analyze\u0000cell-specific nonthermal driving forces and cellular adaptability. Our results\u0000reveal that intracellular particle diffusion is influenced not only by common\u0000thermal forces but also by nonthermal forces generated by approximately 10-100\u0000motor proteins. Furthermore, we derive a physical parameter that quantitatively\u0000assesses the sensitivity of intracellular particle responses to these\u0000nonthermal forces, showing that systems with more active diffusion exhibit\u0000higher response sensitivity. Our work highlights the biological fluctuations\u0000arising from multiple interacting elements, advancing the understanding of the\u0000complex mechanical properties within living cells.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142182181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Cell size varies between different cell types, and between different growth and osmotic conditions. However, the nuclear-to-cell volume ratio (N/C ratio) remains nearly constant. In this paper, we build on existing deterministic models of N/C ratio homeostasis and develop a simplified gene translation model to study the effect of stochasticity on the N/C ratio homeostasis. We solve the corresponding chemical master equation and obtain the mean and variance of the N/C ratio. We also use a Taylor expansion approximation to study the effects of the system size on the fluctuations of the N/C ratio. We then combine the translation model with a cell division model to study the effects of extrinsic noises from cell division on the N/C ratio. Our model demonstrates that the N/C ratio homeostasis is maintained when the stochasticity in cell growth is taken into account, that the N/C ratio is largely determined by the gene fraction of nuclear proteins, and that the fluctuations in the N/C ratio diminish as the system size increases.
{"title":"Stochastic Gene Expression Model of Nuclear-to-Cell Ratio Homeostasis","authors":"Xuesong Bai, Thomas G. Fai","doi":"arxiv-2407.19066","DOIUrl":"https://doi.org/arxiv-2407.19066","url":null,"abstract":"Cell size varies between different cell types, and between different growth\u0000and osmotic conditions. However, the nuclear-to-cell volume ratio (N/C ratio)\u0000remains nearly constant. In this paper, we build on existing deterministic\u0000models of N/C ratio homeostasis and develop a simplified gene translation model\u0000to study the effect of stochasticity on the N/C ratio homeostasis. We solve the\u0000corresponding chemical master equation and obtain the mean and variance of the\u0000N/C ratio. We also use a Taylor expansion approximation to study the effects of\u0000the system size on the fluctuations of the N/C ratio. We then combine the\u0000translation model with a cell division model to study the effects of extrinsic\u0000noises from cell division on the N/C ratio. Our model demonstrates that the N/C\u0000ratio homeostasis is maintained when the stochasticity in cell growth is taken\u0000into account, that the N/C ratio is largely determined by the gene fraction of\u0000nuclear proteins, and that the fluctuations in the N/C ratio diminish as the\u0000system size increases.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tom Brandstätter, Emily Brieger, David B. Brückner, Georg Ladurner, Joachim Rädler, Chase P. Broedersz
The migration behavior of colliding cells is critically determined by transient contact-interactions. During these interactions, the motility machinery, including the front-rear polarization of the cell, dynamically responds to surface protein-mediated transmission of forces and biochemical signals between cells. While biomolecular details of such contact-interactions are increasingly well understood, it remains unclear what biophysical interaction mechanisms govern the cell-level dynamics of colliding cells and how these mechanisms vary across cell types. Here, we develop a phenomenological theory based on eleven candidate contact-interaction mechanisms coupling cell position, shape, and polarity. Using high-throughput micropattern experiments, we detect which of these phenomenological contact-interactions captures the interaction behaviors of cells. We find that various cell types - ranging from mesenchymal to epithelial cells - are accurately captured by a single model with only two interaction mechanisms: polarity-protrusion coupling and polarity-polarity coupling. The qualitatively different interaction behaviors of distinct cells, as well as cells subject to molecular perturbations of surface protein-mediated signaling, can all be quantitatively captured by varying the strength and sign of the polarity-polarity coupling mechanism. Altogether, our data-driven phenomenological theory of cell-cell interactions reveals polarity-polarity coupling as a versatile and general contact-interaction mechanism, which may underlie diverse collective migration behavior of motile cells.
{"title":"Learning a phenomenological theory for contact-interactions between motile cells from collision experiments","authors":"Tom Brandstätter, Emily Brieger, David B. Brückner, Georg Ladurner, Joachim Rädler, Chase P. Broedersz","doi":"arxiv-2407.17268","DOIUrl":"https://doi.org/arxiv-2407.17268","url":null,"abstract":"The migration behavior of colliding cells is critically determined by\u0000transient contact-interactions. During these interactions, the motility\u0000machinery, including the front-rear polarization of the cell, dynamically\u0000responds to surface protein-mediated transmission of forces and biochemical\u0000signals between cells. While biomolecular details of such contact-interactions\u0000are increasingly well understood, it remains unclear what biophysical\u0000interaction mechanisms govern the cell-level dynamics of colliding cells and\u0000how these mechanisms vary across cell types. Here, we develop a\u0000phenomenological theory based on eleven candidate contact-interaction\u0000mechanisms coupling cell position, shape, and polarity. Using high-throughput\u0000micropattern experiments, we detect which of these phenomenological\u0000contact-interactions captures the interaction behaviors of cells. We find that\u0000various cell types - ranging from mesenchymal to epithelial cells - are\u0000accurately captured by a single model with only two interaction mechanisms:\u0000polarity-protrusion coupling and polarity-polarity coupling. The qualitatively\u0000different interaction behaviors of distinct cells, as well as cells subject to\u0000molecular perturbations of surface protein-mediated signaling, can all be\u0000quantitatively captured by varying the strength and sign of the\u0000polarity-polarity coupling mechanism. Altogether, our data-driven\u0000phenomenological theory of cell-cell interactions reveals polarity-polarity\u0000coupling as a versatile and general contact-interaction mechanism, which may\u0000underlie diverse collective migration behavior of motile cells.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141770806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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