Eukaryotic cells perform chemotaxis by determining the direction of chemical gradients based on stochastic sensing of concentrations at the cell surface. To examine the efficiency of this process, previous studies have investigated the limit of estimation accuracy for gradients. However, these studies assume that the cell shape and gradient are constant, and do not consider how adaptive regulation of cell shape affects the estimation limit. Dynamics of cell shape during gradient sensing is biologically ubiquitous and can influence the estimation by altering the way the concentration is measured, and cells may strategically regulate their shape to improve estimation accuracy. To address this gap, we investigate the estimation limits in dynamic situations where cells change shape adaptively depending on the sensed signal. We approach this problem by analyzing the stationary solution of the Bayesian nonlinear filtering equation. By applying diffusion approximation to the ligand-receptor binding process and the Laplace method for the posterior expectation under a high signal-to-noise ratio regime, we obtain an analytical expression for the estimation limit. This expression indicates that estimation accuracy can be improved by elongating perpendicular to the estimated direction, which is also confirmed by numerical simulations. Our analysis provides a basis for clarifying the interplay between estimation and control in gradient sensing and sheds light on how cells optimize their shape to enhance chemotactic efficiency.
{"title":"Gradient sensing limit of a cell when controlling the elongating direction","authors":"Kento Nakamura, Tetsuya J. Kobayashi","doi":"arxiv-2405.04810","DOIUrl":"https://doi.org/arxiv-2405.04810","url":null,"abstract":"Eukaryotic cells perform chemotaxis by determining the direction of chemical\u0000gradients based on stochastic sensing of concentrations at the cell surface. To\u0000examine the efficiency of this process, previous studies have investigated the\u0000limit of estimation accuracy for gradients. However, these studies assume that\u0000the cell shape and gradient are constant, and do not consider how adaptive\u0000regulation of cell shape affects the estimation limit. Dynamics of cell shape\u0000during gradient sensing is biologically ubiquitous and can influence the\u0000estimation by altering the way the concentration is measured, and cells may\u0000strategically regulate their shape to improve estimation accuracy. To address\u0000this gap, we investigate the estimation limits in dynamic situations where\u0000cells change shape adaptively depending on the sensed signal. We approach this\u0000problem by analyzing the stationary solution of the Bayesian nonlinear\u0000filtering equation. By applying diffusion approximation to the ligand-receptor\u0000binding process and the Laplace method for the posterior expectation under a\u0000high signal-to-noise ratio regime, we obtain an analytical expression for the\u0000estimation limit. This expression indicates that estimation accuracy can be\u0000improved by elongating perpendicular to the estimated direction, which is also\u0000confirmed by numerical simulations. Our analysis provides a basis for\u0000clarifying the interplay between estimation and control in gradient sensing and\u0000sheds light on how cells optimize their shape to enhance chemotactic\u0000efficiency.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140928972","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}
Neuronal dendrites form densely branched tree architectures through which mitochondria must be distributed to supply the cell's energetic needs. Dendritic mitochondria circulate through the tree, undergoing fusion and fission to form clusters of varying sizes. We present a mathematical model for the distribution of such actively-driven particles in a branched geometry. Our model demonstrates that `balanced' trees (wherein cross-sectional area is conserved across junctions and thicker branches support more bushy subtrees) enable symmetric yet distally enriched particle distributions and promote dispersion into smaller clusters. These results highlight the importance of tree architecture and radius-dependent fusion in governing the distribution of neuronal mitochondria.
{"title":"Clustering and spatial distribution of mitochondria in dendritic trees","authors":"Mario Hidalgo-Soria, Elena F. Koslover","doi":"arxiv-2405.04684","DOIUrl":"https://doi.org/arxiv-2405.04684","url":null,"abstract":"Neuronal dendrites form densely branched tree architectures through which\u0000mitochondria must be distributed to supply the cell's energetic needs.\u0000Dendritic mitochondria circulate through the tree, undergoing fusion and\u0000fission to form clusters of varying sizes. We present a mathematical model for\u0000the distribution of such actively-driven particles in a branched geometry. Our\u0000model demonstrates that `balanced' trees (wherein cross-sectional area is\u0000conserved across junctions and thicker branches support more bushy subtrees)\u0000enable symmetric yet distally enriched particle distributions and promote\u0000dispersion into smaller clusters. These results highlight the importance of\u0000tree architecture and radius-dependent fusion in governing the distribution of\u0000neuronal mitochondria.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140928829","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}
Sumit Sinha, Xin Li, Abdul N Malmi-Kakkada, D. Thirumalai
Local stresses in a tissue, a collective property, regulate cell division and apoptosis. In turn, cell growth and division induce active stresses in the tissue. As a consequence, there is a feedback between cell growth and local stresses. However, how the cell dynamics depend on local stress-dependent cell division and the feedback strength is not fully understood. Here, we probe the consequences of stress-mediated growth and cell division on cell dynamics using agent-based simulations of a two-dimensional growing tissue. We discover a rich dynamical behavior of individual cells, ranging from jamming (mean square displacement, $Delta (t) sim t^{alpha}$ with $alpha$ less than unity), to hyperdiffusion ($alpha > 2$) depending on cell division rate and the strength of the mechanical feedback. Strikingly, $Delta (t)$ is determined by the tissue growth law, which quantifies cell proliferation (number of cells $N(t)$ as a function of time). The growth law ($N(t) sim t^{lambda}$ at long times) is regulated by the critical pressure that controls the strength of the mechanical feedback and the ratio between cell division-apoptosis rates. We show that $lambda sim alpha$, which implies that higher growth rate leads to a greater degree of cell migration. The variations in cell motility are linked to the emergence of highly persistent forces extending over several cell cycle times. Our predictions are testable using cell-tracking imaging techniques.
{"title":"Proliferation-driven mechanical feedback regulates cell dynamics in growing tissues","authors":"Sumit Sinha, Xin Li, Abdul N Malmi-Kakkada, D. Thirumalai","doi":"arxiv-2405.01960","DOIUrl":"https://doi.org/arxiv-2405.01960","url":null,"abstract":"Local stresses in a tissue, a collective property, regulate cell division and\u0000apoptosis. In turn, cell growth and division induce active stresses in the\u0000tissue. As a consequence, there is a feedback between cell growth and local\u0000stresses. However, how the cell dynamics depend on local stress-dependent cell\u0000division and the feedback strength is not fully understood. Here, we probe the\u0000consequences of stress-mediated growth and cell division on cell dynamics using\u0000agent-based simulations of a two-dimensional growing tissue. We discover a rich\u0000dynamical behavior of individual cells, ranging from jamming (mean square\u0000displacement, $Delta (t) sim t^{alpha}$ with $alpha$ less than unity), to\u0000hyperdiffusion ($alpha > 2$) depending on cell division rate and the strength\u0000of the mechanical feedback. Strikingly, $Delta (t)$ is determined by the\u0000tissue growth law, which quantifies cell proliferation (number of cells $N(t)$\u0000as a function of time). The growth law ($N(t) sim t^{lambda}$ at long times)\u0000is regulated by the critical pressure that controls the strength of the\u0000mechanical feedback and the ratio between cell division-apoptosis rates. We\u0000show that $lambda sim alpha$, which implies that higher growth rate leads to\u0000a greater degree of cell migration. The variations in cell motility are linked\u0000to the emergence of highly persistent forces extending over several cell cycle\u0000times. Our predictions are testable using cell-tracking imaging techniques.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140881734","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}
Ummay Mowshome Jahan, Brianna Blevins, Sergiy Minko, Vladimir Reukov
Reactive oxygen species (ROS), which are expressed at high levels in many diseases, can be scavenged by cerium oxide nanoparticles (CeO2NPs). CeO2NPs can cause significant cytotoxicity when administered directly to cells, but this cytotoxicity can be reduced if CeO2NPs can be encapsulated in biocompatible polymers. In this study, CeO2NPs were synthesized using a one-stage process, then purified, characterized, and then encapsulated into an electrospun poly-{epsilon}-caprolactone (PCL) scaffold. The direct administration of CeO2NPs to RAW 264.7 Macrophages resulted in reduced ROS levels but lower cell viability. Conversely, the encapsulation of nanoceria in a PCL scaffold was shown to lower ROS levels and improve cell survival. The study demonstrated an effective technique for encapsulating nanoceria in PCL fiber and confirmed its biocompatibility and efficacy. This system has the potential to be utilized for developing tissue engineering scaffolds, targeted delivery of therapeutic CeO2NPs, wound healing, and other biomedical applications.
{"title":"Advancing Biomedical Applications: Antioxidant and Biocompatible Cerium Oxide Nanoparticle-Integrated Poly-ε- caprolactone Fibers","authors":"Ummay Mowshome Jahan, Brianna Blevins, Sergiy Minko, Vladimir Reukov","doi":"arxiv-2404.17091","DOIUrl":"https://doi.org/arxiv-2404.17091","url":null,"abstract":"Reactive oxygen species (ROS), which are expressed at high levels in many\u0000diseases, can be scavenged by cerium oxide nanoparticles (CeO2NPs). CeO2NPs can\u0000cause significant cytotoxicity when administered directly to cells, but this\u0000cytotoxicity can be reduced if CeO2NPs can be encapsulated in biocompatible\u0000polymers. In this study, CeO2NPs were synthesized using a one-stage process,\u0000then purified, characterized, and then encapsulated into an electrospun\u0000poly-{epsilon}-caprolactone (PCL) scaffold. The direct administration of\u0000CeO2NPs to RAW 264.7 Macrophages resulted in reduced ROS levels but lower cell\u0000viability. Conversely, the encapsulation of nanoceria in a PCL scaffold was\u0000shown to lower ROS levels and improve cell survival. The study demonstrated an\u0000effective technique for encapsulating nanoceria in PCL fiber and confirmed its\u0000biocompatibility and efficacy. This system has the potential to be utilized for\u0000developing tissue engineering scaffolds, targeted delivery of therapeutic\u0000CeO2NPs, wound healing, and other biomedical applications.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140808830","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}
Chananchida Sang-aram, Robin Browaeys, Ruth Seurinck, Yvan Saeys
Ligand-receptor interactions constitute a fundamental mechanism of cell-cell communication and signaling. NicheNet is a well-established computational tool that infers ligand-receptor interactions that potentially regulate gene expression changes in receiver cell populations. Whereas the original publication delves into the algorithm and validation, this paper describes a best practices workflow cultivated over four years of experience and user feedback. Starting from the input single-cell expression matrix, we describe a "sender-agnostic" approach which considers ligands from the entire microenvironment, and a "sender-focused" approach which only considers ligands from cell populations of interest. As output, users will obtain a list of prioritized ligands and their potential target genes, along with multiple visualizations. In NicheNet v2, we have updated the data sources and implemented a downstream procedure for prioritizing cell-type-specific ligand-receptor pairs. Although a standard NicheNet analysis takes less than 10 minutes to run, users often invest additional time in making decisions about the approach and parameters that best suit their biological question. This paper serves to aid in this decision-making process by describing the most appropriate workflow for common experimental designs like case-control and cell differentiation studies. Finally, in addition to the step-by-step description of the code, we also provide wrapper functions that enable the analysis to be run in one line of code, thus tailoring the workflow to users at all levels of computational proficiency.
{"title":"Unraveling cell-cell communication with NicheNet by inferring active ligands from transcriptomics data","authors":"Chananchida Sang-aram, Robin Browaeys, Ruth Seurinck, Yvan Saeys","doi":"arxiv-2404.16358","DOIUrl":"https://doi.org/arxiv-2404.16358","url":null,"abstract":"Ligand-receptor interactions constitute a fundamental mechanism of cell-cell\u0000communication and signaling. NicheNet is a well-established computational tool\u0000that infers ligand-receptor interactions that potentially regulate gene\u0000expression changes in receiver cell populations. Whereas the original\u0000publication delves into the algorithm and validation, this paper describes a\u0000best practices workflow cultivated over four years of experience and user\u0000feedback. Starting from the input single-cell expression matrix, we describe a\u0000\"sender-agnostic\" approach which considers ligands from the entire\u0000microenvironment, and a \"sender-focused\" approach which only considers ligands\u0000from cell populations of interest. As output, users will obtain a list of\u0000prioritized ligands and their potential target genes, along with multiple\u0000visualizations. In NicheNet v2, we have updated the data sources and\u0000implemented a downstream procedure for prioritizing cell-type-specific\u0000ligand-receptor pairs. Although a standard NicheNet analysis takes less than 10\u0000minutes to run, users often invest additional time in making decisions about\u0000the approach and parameters that best suit their biological question. This\u0000paper serves to aid in this decision-making process by describing the most\u0000appropriate workflow for common experimental designs like case-control and cell\u0000differentiation studies. Finally, in addition to the step-by-step description\u0000of the code, we also provide wrapper functions that enable the analysis to be\u0000run in one line of code, thus tailoring the workflow to users at all levels of\u0000computational proficiency.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800023","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}
Tumor cell migration within the microenvironment is a crucial aspect for cancer progression and, in this context, hypoxia has a significant role. An inadequate oxygen supply acts as an environmental stressor inducing migratory bias and phenotypic changes. In this paper, we propose a novel multi-scale mathematical model to analyze the pivotal role of Snail protein expression in the cellular responses to hypoxia. Starting from the description of single-cell dynamics driven by the Snail protein, we construct the corresponding kinetic transport equation that describes the evolution of the cell distribution. Subsequently, we employ proper scaling arguments to formally derive the equations for the statistical moments of the cell distribution, which govern the macroscopic tumor dynamics. Numerical simulations of the model are performed in various scenarios with biological relevance to provide insights into the role of the multiple tactic terms, the impact of Snail expression on cell proliferation, and the emergence of hypoxia-induced migration patterns. Moreover, quantitative comparison with experimental data shows the model's reliability in measuring the impact of Snail transcription on cell migratory potential. Through our findings, we shed light on the potential of our mathematical framework in advancing the understanding of the biological mechanisms driving tumor progression.
{"title":"Multi-scale modeling of Snail-mediated response to hypoxia in tumor progression","authors":"Giulia Chiari, Martina Conte, Marcello Delitala","doi":"arxiv-2404.16769","DOIUrl":"https://doi.org/arxiv-2404.16769","url":null,"abstract":"Tumor cell migration within the microenvironment is a crucial aspect for\u0000cancer progression and, in this context, hypoxia has a significant role. An\u0000inadequate oxygen supply acts as an environmental stressor inducing migratory\u0000bias and phenotypic changes. In this paper, we propose a novel multi-scale\u0000mathematical model to analyze the pivotal role of Snail protein expression in\u0000the cellular responses to hypoxia. Starting from the description of single-cell\u0000dynamics driven by the Snail protein, we construct the corresponding kinetic\u0000transport equation that describes the evolution of the cell distribution.\u0000Subsequently, we employ proper scaling arguments to formally derive the\u0000equations for the statistical moments of the cell distribution, which govern\u0000the macroscopic tumor dynamics. Numerical simulations of the model are\u0000performed in various scenarios with biological relevance to provide insights\u0000into the role of the multiple tactic terms, the impact of Snail expression on\u0000cell proliferation, and the emergence of hypoxia-induced migration patterns.\u0000Moreover, quantitative comparison with experimental data shows the model's\u0000reliability in measuring the impact of Snail transcription on cell migratory\u0000potential. Through our findings, we shed light on the potential of our\u0000mathematical framework in advancing the understanding of the biological\u0000mechanisms driving tumor progression.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799985","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}
Praveen Sahu, Ignacio G. Camarillo, Pragatheiswar Giri, Raji Sundararajan
In this research, we investigated the efficacy of Metformin, the most commonly administered type-2 diabetes drug for triple negative breast cancer (TNBC) treatment, due to its various anticancer properties. It is a plant-based bio-compound, synthesized as a novel biguanide, called dimethyl biguanide or metformin. One of the ways it operates is by hindering electron transport chain-complex I, in mitochondria, which causes a drop-in energy (ATP) generation. This eventually builds energetic stress and a decline in energy. Therefore, the natural cellular processes and proliferating tumor cells are obstructed. Here, we used electroporation, where, the MDA-MB-231, human TNBC cells were subjected to high intensity, short-duration electrical pulses (EP) in the presence of Metformin. The cell viability results indicate lower cell viability of 43.45% as compared to 85.20% with drug alone at 5mM concentration. This indicates that Metformin, the most common diabetes drug could also be explored for cancer treatment.
{"title":"Electroporation-mediated Metformin for effective anticancer treatment of triple-negative breast cancer cells","authors":"Praveen Sahu, Ignacio G. Camarillo, Pragatheiswar Giri, Raji Sundararajan","doi":"arxiv-2404.14353","DOIUrl":"https://doi.org/arxiv-2404.14353","url":null,"abstract":"In this research, we investigated the efficacy of Metformin, the most\u0000commonly administered type-2 diabetes drug for triple negative breast cancer\u0000(TNBC) treatment, due to its various anticancer properties. It is a plant-based\u0000bio-compound, synthesized as a novel biguanide, called dimethyl biguanide or\u0000metformin. One of the ways it operates is by hindering electron transport\u0000chain-complex I, in mitochondria, which causes a drop-in energy (ATP)\u0000generation. This eventually builds energetic stress and a decline in energy.\u0000Therefore, the natural cellular processes and proliferating tumor cells are\u0000obstructed. Here, we used electroporation, where, the MDA-MB-231, human TNBC\u0000cells were subjected to high intensity, short-duration electrical pulses (EP)\u0000in the presence of Metformin. The cell viability results indicate lower cell\u0000viability of 43.45% as compared to 85.20% with drug alone at 5mM concentration.\u0000This indicates that Metformin, the most common diabetes drug could also be\u0000explored for cancer treatment.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799984","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}
Daniel Cebrián-Lacasa, Marcin Leda, Andrew B. Goryachev, Lendert Gelens
We explore a biomimetic model that simulates a cell, with the internal cytoplasm represented by a two-dimensional circular domain and the external cortex by a surrounding ring, both modeled using FitzHugh-Nagumo systems. The external ring is dynamically influenced by a pacemaker-driven wave originating from the internal domain, leading to the emergence of three distinct dynamical states based on the varying strengths of coupling. The range of dynamics observed includes phase patterning, the propagation of phase waves, and interactions between traveling and phase waves. A simplified linear model effectively explains the mechanisms behind the variety of phase patterns observed, providing insights into the complex interplay between a cell's internal and external environments.
{"title":"Wave-driven phase wave patterns in a ring of FitzHugh-Nagumo oscillators","authors":"Daniel Cebrián-Lacasa, Marcin Leda, Andrew B. Goryachev, Lendert Gelens","doi":"arxiv-2404.13363","DOIUrl":"https://doi.org/arxiv-2404.13363","url":null,"abstract":"We explore a biomimetic model that simulates a cell, with the internal\u0000cytoplasm represented by a two-dimensional circular domain and the external\u0000cortex by a surrounding ring, both modeled using FitzHugh-Nagumo systems. The\u0000external ring is dynamically influenced by a pacemaker-driven wave originating\u0000from the internal domain, leading to the emergence of three distinct dynamical\u0000states based on the varying strengths of coupling. The range of dynamics\u0000observed includes phase patterning, the propagation of phase waves, and\u0000interactions between traveling and phase waves. A simplified linear model\u0000effectively explains the mechanisms behind the variety of phase patterns\u0000observed, providing insights into the complex interplay between a cell's\u0000internal and external environments.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140800085","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 consider a minimal go-or-grow model of cell invasion, whereby cells can either proliferate, following logistic growth, or move, via linear diffusion, and phenotypic switching between these two states is density-dependent. Formal analysis in the fast switching regime shows that the total cell density in the two-population go-or-grow model can be described in terms of a single reaction-diffusion equation with density-dependent diffusion and proliferation. Using the connection to single-population models, we study travelling wave solutions, showing that the wave speed in the go-or-grow model is always bounded by the wave speed corresponding to the well-known Fisher-KPP equation.
{"title":"Travelling waves in a minimal go-or-grow model of cell invasion","authors":"Carles Falcó, Rebecca M. Crossley, Ruth E. Baker","doi":"arxiv-2404.11251","DOIUrl":"https://doi.org/arxiv-2404.11251","url":null,"abstract":"We consider a minimal go-or-grow model of cell invasion, whereby cells can\u0000either proliferate, following logistic growth, or move, via linear diffusion,\u0000and phenotypic switching between these two states is density-dependent. Formal\u0000analysis in the fast switching regime shows that the total cell density in the\u0000two-population go-or-grow model can be described in terms of a single\u0000reaction-diffusion equation with density-dependent diffusion and proliferation.\u0000Using the connection to single-population models, we study travelling wave\u0000solutions, showing that the wave speed in the go-or-grow model is always\u0000bounded by the wave speed corresponding to the well-known Fisher-KPP equation.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140612822","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}
Shahzeb Raja Noureen, Richard L. Mort, Christian A. Yates
Adhesion between cells plays an important role in many biological processes such as tissue morphogenesis and homeostasis, wound healing and cancer cell metastasis. From a mathematical perspective, adhesion between multiple cell types has been previously analysed using discrete and continuum models including the Cellular Potts models and partial differential equations (PDEs). While these models can represent certain biological situations well, Cellular Potts models can be computationally expensive and continuum models only capture the macroscopic behaviour of a population of cells, ignoring stochasticity and the discrete nature of cell dynamics. Cellular automaton models allow us to address these problems and can be used for a wide variety of biological systems. In this paper, we consider a cellular automaton approach and develop an on-lattice agent-based model (ABM) for cell migration and adhesion in a population composed of two cell types. By deriving and comparing the corresponding PDEs to the ABM, we demonstrate that cell aggregation and cell sorting are not possible in the PDE model. Therefore, we propose a set of stochastic mean equations (SMEs) which better capture the behaviour of the ABM in one and two dimensions.
{"title":"Modelling adhesion in stochastic and mean-field models of cell migration","authors":"Shahzeb Raja Noureen, Richard L. Mort, Christian A. Yates","doi":"arxiv-2404.10120","DOIUrl":"https://doi.org/arxiv-2404.10120","url":null,"abstract":"Adhesion between cells plays an important role in many biological processes\u0000such as tissue morphogenesis and homeostasis, wound healing and cancer cell\u0000metastasis. From a mathematical perspective, adhesion between multiple cell\u0000types has been previously analysed using discrete and continuum models\u0000including the Cellular Potts models and partial differential equations (PDEs).\u0000While these models can represent certain biological situations well, Cellular\u0000Potts models can be computationally expensive and continuum models only capture\u0000the macroscopic behaviour of a population of cells, ignoring stochasticity and\u0000the discrete nature of cell dynamics. Cellular automaton models allow us to\u0000address these problems and can be used for a wide variety of biological\u0000systems. In this paper, we consider a cellular automaton approach and develop\u0000an on-lattice agent-based model (ABM) for cell migration and adhesion in a\u0000population composed of two cell types. By deriving and comparing the\u0000corresponding PDEs to the ABM, we demonstrate that cell aggregation and cell\u0000sorting are not possible in the PDE model. Therefore, we propose a set of\u0000stochastic mean equations (SMEs) which better capture the behaviour of the ABM\u0000in one and two dimensions.","PeriodicalId":501321,"journal":{"name":"arXiv - QuanBio - Cell Behavior","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140612262","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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