705 research outputs found

    Mechanical and Systems Biology of Cancer

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    Mechanics and biochemical signaling are both often deregulated in cancer, leading to cancer cell phenotypes that exhibit increased invasiveness, proliferation, and survival. The dynamics and interactions of cytoskeletal components control basic mechanical properties, such as cell tension, stiffness, and engagement with the extracellular environment, which can lead to extracellular matrix remodeling. Intracellular mechanics can alter signaling and transcription factors, impacting cell decision making. Additionally, signaling from soluble and mechanical factors in the extracellular environment, such as substrate stiffness and ligand density, can modulate cytoskeletal dynamics. Computational models closely integrated with experimental support, incorporating cancer-specific parameters, can provide quantitative assessments and serve as predictive tools toward dissecting the feedback between signaling and mechanics and across multiple scales and domains in tumor progression.Comment: 18 pages, 3 figure

    Coupling of cytoplasm and adhesion dynamics determines cell polarization and locomotion

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    Observations of single epidermal cells on flat adhesive substrates have revealed two distinct morphological and functional states, namely a non-migrating symmetric unpolarized state and a migrating asymmetric polarized state. These states are characterized by different spatial distributions and dynamics of important biochemical cell components: F-actin and myosin-II form the contractile part of the cytoskeleton, and integrin receptors in the plasma membrane connect F-actin filaments to the substratum. In this way, focal adhesion complexes are assembled, which determine cytoskeletal force transduction and subsequent cell locomotion. So far, physical models have reduced this phenomenon either to gradients in regulatory control molecules or to different mechanics of the actin filament system in different regions of the cell. Here we offer an alternative and self-organizational model incorporating polymerization, pushing and sliding of filaments, as well as formation of adhesion sites and their force dependent kinetics. All these phenomena can be combined into a non-linearly coupled system of hyperbolic, parabolic and elliptic differential equations. Aim of this article is to show how relatively simple relations for the small-scale mechanics and kinetics of participating molecules may reproduce the emergent behavior of polarization and migration on the large-scale cell level.Comment: v2 (updates from proof): add TOC, clarify Fig. 4, fix several typo

    Cell Migration within 3D Microenvironments: an Integrative Perspective from the Membrane to the Nucleus

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    La migración celular es fundamental para la vida y el desarrollo. Desafortunadamente, la movilidad celular también está asociada con algunas de las principales causas de morbilidad y mortalidad, incluidos los trastornos inmunitarios, esqueléticos y cardiovasculares, así como la metástasis del cáncer. Las células dependen en su capacidad para percibir y responder a estímulos externos en muchos procesos fisiológicos y patológicos (p. ej., desarrollo embrionario, angiogénesis, reparación de tejidos y progresión tumoral). El objetivo global de esta tesis doctoral fue investigar la respuesta migratoria de células individuales a señales bioquímicas y biofísicas. En particular, el enfoque de esta investigación se centró en los mecanismos que permiten a las células percibir e internalizar señales bioquímicas y biofísicas y la influencia de estos estímulos en la respuesta migratoria de las células individuales.El primer estudio tuvo como objetivo establecer una metodología para facilitar la integración de estudios teóricos con datos experimentales. Al minimizar la intervención del usuario, el sistema propuesto basado en técnicas de optimización Bayesiana gestionó de manera eficiente la calibración de los modelos in silico, que de otro modo sería tediosa y propensa a errores. Posteriormente, se construyó un modelo in silico para investigar cómo los estímulos bioquímicos y biofísicos influyen en el movimiento celular en tres dimensiones. Este modelo computacional integró algunos de los principales actores que permiten a las células percibir y responder a señales externas, que pueden actuar a diferentes escalas e interactuar entre sí. Los resultados mostraron, por un lado, que las células cambian su comportamiento migratorio en función de la pendiente de los gradientes químicos y la concentración absoluta de factores químicos (por ejemplo, factores de crecimiento) a su alrededor. Por otro lado, estos resultados revelaron que la respuesta migratoria de las células a la rigidez y densidad de la matriz depende de su fenotipo. En general, la tesis destaca la dependencia de la migración celular tridimensional al fenotipo de las células (es decir, el tamaño de su núcleo, la deformabilidad del mismo) y las propiedades del microambiente circundante (por ejemplo, el perfil químico, la rigidez de la matriz, el confinamiento).Cell migration is fundamental for life and development. Unfortunately, cell motility is also associated with some of the leading causes of morbidity and mortality, including immune, skeletal, and cardiovascular disorders as well as cancer metastasis. Cells rely on their ability to perceive and respond to external stimuli in many physiological and pathological processes (e.g., embryonic development, angiogenesis, tissue repair, and tumor progression). The global objective of this doctoral thesis was to investigate the migratory response of individual cells to biochemical and biophysical cues. In particular, the focus of this research was on the mechanisms enabling cells to perceive and internalize biochemical and biophysical cues and the influence of these stimuli on the migratory response of individual cells. The first study aimed at establishing a methodology to facilitate the integration of theoretical studies with experimental data. By minimizing user intervention, the proposed framework based on Bayesian optimization techniques efficiently handled the otherwise tedious and error-prone calibration of in silico models. Afterward, an in silico model was built to investigate how biochemical and biophysical stimuli influence three-dimensional cell motion. This computational model integrated some of the main actors enabling cells to probe and respond to external cues, which may act at different scales and interact with each other. The results showed, on the one hand, that cells change their migratory behavior based on the slope of chemical gradients and the absolute concentration of chemical factors (e.g., growth factors) around them. On the other hand, these results revealed that cells’ migratory response to matrix stiffness and density depends on their phenotype. Overall, this thesis highlights the dependence of three-dimensional cell migration on both cells’ phenotype (i.e., nucleus size, deformability) and the properties of the surrounding microenvironment (e.g., chemical profile, matrix rigidity, confinement).<br /

    Control of Mechanotransduction by Molecular Clutch Dynamics

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    By considering the molecular and mechanical properties of actin filaments, myosin motors, adaptor proteins, and integrins/cadherins, the molecular clutch model can quantitatively predict cell response to internal and external mechanical factors. These factors include cell contractility, matrix rigidity, and the density, nature, and distribution of matrix ligands, and affect cell response largely by controlling the rate of force loading in specific molecules. Due to its dynamic nature, clutch-mediated mechanosensing requires force application to at least two molecular mechanosensors in series, with differential response to force. The type of cell responses involved so far in clutch-mediated mechanosensing include cytoskeletal dynamics, the growth of cell adhesions, the nuclear localization of transcriptional regulators, and cell migration. The linkage of cells to their microenvironment is mediated by a series of bonds that dynamically engage and disengage, in what has been conceptualized as the molecular clutch model. Whereas this model has long been employed to describe actin cytoskeleton and cell migration dynamics, it has recently been proposed to also explain mechanotransduction (i.e., the process by which cells convert mechanical signals from their environment into biochemical signals). Here we review the current understanding on how cell dynamics and mechanotransduction are driven by molecular clutch dynamics and its master regulator, the force loading rate. Throughout this Review, we place a specific emphasis on the quantitative prediction of cell response enabled by combined experimental and theoretical approaches.This work was supported by the Spanish Ministry of Economy and Competitiveness (BFU2015-65074-P to X.T. and BFU2016-79916-P to P.R.-C.), the European Commission (H2020-FETPROACT-01-2016-731957 to X.T. and P.R.-C.), the Generalitat de Catalunya (2014-SGR-927), the European Research Council (CoG-616480 to X.T.), and Obra Social “La Caixa”. A.E.-A was supported by a Juan de la Cierva Fellowship (Spanish Ministry of Economy and Competitiveness, IJCI2014-19156)

    Dynamic Modeling of Cell Migration and Spreading Behaviors on Fibronectin Coated Planar Substrates and Micropatterned Geometries

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    An integrative cell migration model incorporating focal adhesion (FA) dynamics, cytoskeleton and nucleus remodeling, actin motor activity, and lamellipodia protrusion is developed for predicting cell spreading and migration behaviors. This work is motivated by two experimental works: (1) cell migration on 2-D substrates under various fibronectin concentrations and (2) cell spreading on 2-D micropatterned geometries. These works suggest (1) cell migration speed takes a maximum at a particular ligand density (~1140 molecules/µm2) and (2) that strong traction forces at the corners of the patterns may exist due to combined effects exerted by actin stress fibers (SFs). The integrative model of this paper successfully reproduced these experimental results and indicates the mechanism of cell migration and spreading. In this paper, the mechanical structure of the cell is modeled as having two elastic membranes: an outer cell membrane and an inner nuclear membrane. The two elastic membranes are connected by SFs, which are extended from focal adhesions on the cortical surface to the nuclear membrane. In addition, the model also includes ventral SFs bridging two focal adhesions on the cell surface. The cell deforms and gains traction as transmembrane integrins distributed over the outer cell membrane bond to ligands on the ECM surface, activate SFs, and form focal adhesions. The relationship between the cell migration speed and fibronectin concentration agrees with existing experimental data for Chinese hamster ovary (CHO) cell migrations on fibronectin coated surfaces. In addition, the integrated model is validated by showing persistent high stress concentrations at sharp geometrically patterned edges. This model will be used as a predictive model to assist in design and data processing of upcoming microfluidic cell migration assays

    Cooperation of dual modes of cell motility promotes epithelial stress relaxation to accelerate wound healing

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    Collective cell migration in cohesive units is vital for tissue morphogenesis, wound repair, and immune response. While the fundamental driving forces for collective cell motion stem from contractile and protrusive activities of individual cells, it remains unknown how their balance is optimized to maintain tissue cohesiveness and the fluidity for motion. Here we present a cell-based computational model for collective cell migration during wound healing that incorporates mechanochemical coupling of cell motion and adhesion kinetics with stochastic transformation of active motility forces. We show that a balance of protrusive motility and actomyosin contractility is optimized for accelerating the rate of wound repair, which is robust to variations in cell and substrate mechanical properties. This balance underlies rapid collective cell motion during wound healing, resulting from a tradeoff between tension mediated collective cell guidance and active stress relaxation in the tissue

    Unravelling cell migration: defining movement from the cell surface

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    Cell motility is essential for life and development. Unfortunately, cell migration is also linked to several pathological processes, such as cancer metastasis. Cells’ ability to migrate relies on many actors. Cells change their migratory strategy based on their phenotype and the properties of the surrounding microenvironment. Cell migration is, therefore, an extremely complex phenomenon. Researchers have investigated cell motility for more than a century. Recent discoveries have uncovered some of the mysteries associated with the mechanisms involved in cell migration, such as intracellular signaling and cell mechanics. These findings involve different players, including transmembrane receptors, adhesive complexes, cytoskeletal components , the nucleus, and the extracellular matrix. This review aims to give a global overview of our current understanding of cell migration

    Whence Directionality: Guidance Mechanisms in Solitary and Collective Cell Migration

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    As individual cells or groups of cells move through the complex environment of the body, their migration is affected by multiple external cues. Some cues are diffusible signaling molecules, and some are solid biophysical features. How do cells respond appropriately? This perspective discusses the relationship between guidance input and the cellular output, considering effects from classical chemotaxis to contact-dependent guidance. The influences of membrane trafficking and of imposed constraints on directional movement are also considered. New insights regarding guidance and dynamic cell polarity have emerged from examining new cell migration models and from re-examining well known ones with new approaches and new tools

    Plasticity of Cell Migration in Vivo and in Silico

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    Cell migration results from stepwise mechanical and chemical interactions between cells and their extracellular environment. Mechanistic principles that determine single-cell and collective migration modes and their interconversions depend upon the polarization, adhesion, deformability, contractility, and proteolytic ability of cells. Cellular determinants of cell migration respond to extracellular cues, including tissue composition, topography, alignment, and tissue-associated growth factors and cytokines. Both cellular determinants and tissue determinants are interdependent; undergo reciprocal adjustment; and jointly impact cell decision making, navigation, and migration outcome in complex environments. We here review the variability, decision making, and adaptation of cell migration approached by live-cell, in vivo, and in silico strategies, with a focus on cell movements in morphogenesis, repair, immune surveillance, and cancer metastasi
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