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1.
Dirk Hartmann 《Biomechanics and modeling in mechanobiology》2010,9(1):1-17
The objective of this article is the derivation of a continuum model for mechanics of red blood cells via multiscale analysis.
On the microscopic level, we consider realistic discrete models in terms of energy functionals defined on networks/lattices.
Using concepts of Γ-convergence, convergence results as well as explicit homogenisation formulae are derived. Based on a characterisation
via energy functionals, appropriate macroscopic stress–strain relationships (constitutive equations) can be determined. Further,
mechanical moduli of the derived macroscopic continuum model are directly related to microscopic moduli. As a test case we
consider optical tweezers experiments, one of the most common experiments to study mechanical properties of cells. Our simulations
of the derived continuum model are based on finite element methods and account explicitly for membrane mechanics and its coupling
with bulk mechanics. Since the discretisation of the continuum model can be chosen freely, rather than it is given by the
topology of the microscopic cytoskeletal network, the approach allows a significant reduction of computational efforts. Our
approach is highly flexible and can be generalised to many other cell models, also including biochemical control. 相似文献
2.
Zaman MH 《Molecular & cellular biomechanics : MCB》2007,4(3):133-141
Tumor metastasis is the leading cause of nearly all cancer related deaths. While several experimental and computational studies have addressed individual stages of the complex metastasis process, a comprehensive systems-biology model that links various stages of metastasis has not been put forth as of yet. In this paper we discuss the formulation and application of such a model that utilizes basic principles of cell biology, physics and mechanics to study the migratory patterns of tumor cells as they move from the parent tumor site to the connective tissue via the basement membrane. The model is first of its kind in capturing the essential early features of metastasis in a single simulation and shows good agreement with recent experimental studies. 相似文献
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Laurace E. Townsend Philip J. Bendick Randal S. Juleff John L. Glover 《In vitro cellular & developmental biology. Animal》1991,27(2):97-99
This research was supported by a grant from the William Beaumont Hospital Research Institute. 相似文献
6.
A model of cell growth dynamics 总被引：3，自引：0，他引：3
F M Williams 《Journal of theoretical biology》1967,15(2):190-207
7.
Gang Liu Amina A Qutub Prakash Vempati Feilim Mac Gabhann Aleksander S Popel 《Theoretical biology & medical modelling》2011,8(1):6
Background
Mathematical modeling of angiogenesis has been gaining momentum as a means to shed new light on the biological complexity underlying blood vessel growth. A variety of computational models have been developed, each focusing on different aspects of the angiogenesis process and occurring at different biological scales, ranging from the molecular to the tissue levels. Integration of models at different scales is a challenging and currently unsolved problem. 相似文献8.
Kuzmic Nikola Moore Thomas Devadas Deepika Young Edmond W. K. 《Biomechanics and modeling in mechanobiology》2019,18(3):717-731
Biomechanics and Modeling in Mechanobiology - Tumour-induced angiogenesis is a complex biological process that involves growth of new blood vessels within the tumour microenvironment and is an... 相似文献
9.
Microvascular endothelial cells from human neonatal foreskin were grown in vitro until a three-dimensional network of capillary-like structures was formed. All stages of the angiogenic cascade could be observed in this in vitro model, including the formation of an internal lumen. The microscopy focused on morphology, formation of an internal lumen, role of the extracellular matrix, polarity of the cells, and the time-course of the angiogenic cascade. Bright-field microscopy revealed cells arranged circularly side by side and the internal lumen of capillary-like structures was verified by electron microscopy. Immunolabeling revealed a peritubular localization of collagen IV. Reporter gene expression after the formation of capillary-like structures was marginally higher than control expression, but clearly lower than the expression of cells at the stage of proliferation. Highest transfection efficiencies were obtained using vectors with the CMV promoter and the long fragment of the Ets-1 promoter. This is a first study of transfection efficiencies mapped for stages of in vitro angiogenesis. We describe here the morphological features of a long-term in vitro model of angiogenesis of human microvascular endothelial cells that could be used for transfection studies, without the provision of an extracellular matrix substrate. The cells self-create their own extracellular matrix to proliferate and form a three-dimensional network of capillary-like structures with an internal lumen. 相似文献
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Cell spreading is a critical component of numerous physiological phenomena including cancer metastasis, embryonic development, and mitosis. We have previously illustrated that cellular blebs appear after abrupt cell-substrate detachment and play a critical role in regulating membrane tension; however, the dynamics of bleb-substrate interactions during spreading remains unclear. Here we explore the role of blebs during endothelial cell spreading using chemical and osmotic modifications to either induce or inhibit bleb formation. We track cell-substrate dynamics as well as individual blebs using surface sensitive microscopic techniques. Blebbing cells (both control and chemically induced) exhibit increased lag times prior to fast growth. Interestingly, lamellae appear later for blebbing compared to non-blebbing cells, and in all cases, lamellae signal the start of fast spreading. Our results indicate that cellular blebs play a key role in the early stage of cell spreading, first by controling the initial cell adhesion and then by presenting a dynamic inhibition of cell spreading until a lamella appears and fast spreading ensues. 相似文献
12.
Cell migration underlies tissue formation, maintenance, and regeneration as well as pathological conditions such as cancer invasion. Structural and molecular determinants of both tissue environment and cell behavior define whether cells migrate individually (through amoeboid or mesenchymal modes) or collectively. Using a multiparameter tuning model, we describe how dimension, density, stiffness, and orientation of the extracellular matrix together with cell determinants—including cell–cell and cell–matrix adhesion, cytoskeletal polarity and stiffness, and pericellular proteolysis—interdependently control migration mode and efficiency. Motile cells integrate variable inputs to adjust interactions among themselves and with the matrix to dictate the migration mode. The tuning model provides a matrix of parameters that control cell movement as an adaptive and interconvertible process with relevance to different physiological and pathological contexts.
Open in a separate windowAmoeboid migration commonly refers to the movement of rounded or ellipsoid cells that lack mature focal adhesions and stress fibers (Friedl et al., 2001; Lämmermann and Sixt, 2009). There are two subtypes of amoeboid movement. The first is the rounded, blebby migration of cells that do not adhere or pull on substrate but rather use a propulsive, pushing migration mode (Fackler and Grosse, 2008; Sanz-Moreno and Marshall, 2009). The second occurs in slightly more elongated amoeboid cells that generate actin-rich filopodia at the leading edge that engage in poorly defined, weak adhesive interaction with the substrate (Fig. 1; Yoshida and Soldati, 2006; Smith et al., 2007). In a special case of amoeboid movement, terminally matured nonadhesive dendritic cells produce dynamic actin-rich dendrites, instead of blebs, at their leading edge that cause these cell to become entangled with the ECM substrate during migration (Gunzer et al., 1997; Lämmermann et al., 2008). Individual cells with high levels of attachment and cytoskeletal contractility develop mesenchymal migration, which involves focalized cell–matrix interactions and movement in a fibroblast-like manner (Kaye et al., 1971; Maaser et al., 1999; Grinnell, 2008). The migration of individual cells that transiently form and resolve cell–cell contacts while moving along a common track is termed chain migration or cell streaming (Davis and Trinkaus, 1981; Teddy and Kulesa, 2004). Finally, the maintenance of stringent cell–cell adhesions can lead to partial or complete silencing of migration activity in cells inside a group yet supports cytoskeletal activity at outward edges or at basal cell–substrate contacts. The resulting collective migration occurs in the form of multicellular tubes, strands, irregularly shaped masses, or sheets (Vaughan and Trinkaus, 1966; Friedl et al., 1995; Farooqui and Fenteany, 2005).Most migration modes, although they can be observed in (mostly experimental) 2D environments, occur in vivo in the context of 3D tissue environments (Even-Ram and Yamada, 2005). Conversely, in vivo, some migration modes are dedicated exclusively to 2D environments. Epithelial keratocytes and keratinocytes migrate across flat 2D substrate using rapid spread-out cell gliding (Keren et al., 2008) that, if cell–cell junctions between the cells remain intact, form a collectively migrating 2D cell sheet (Vaughan and Trinkaus, 1966; Farooqui and Fenteany, 2005). In different cell types, these modes of migration are associated with different efficiencies yielding varying migration speeds, such as the fast migratory scanning of single leukocytes, the relatively slow invasive migration of fibroblasts into provisorial wound matrix, or, at the slowest end, the collective migration during organ formation (Friedl et al., 1998b).Single-cell and collective migration modes serve mutually exclusive purposes during morphogenesis, tissue regeneration, and in pathological conditions. Collective cell migration is essential in building, shaping, and remodeling complex tissues and tissue compartments, such as epithelia, ducts, glands, and vessels, but also contributes to cancer progression by local invasion (Alexander et al., 2008; Friedl and Gilmour, 2009). In contrast, single-cell migration allows cells either to cover local distances and integrate into tissues, such as neural crest cell migration, or to move from one location in the body to another and fulfill effector functions, such as immune cell trafficking (Friedl, 2004; Teddy and Kulesa, 2004; Lämmermann and Sixt, 2009). The latter process is recapitulated during cancer metastasis to distant sites (Thiery, 2002). Although not all molecular determinants of each migration mode are fully understood, some key parameters have been identified as “checkpoints” to either maintain a given migration type, or, by an increase or decrease of activity, initiate transitions.
Introduction
Cell migration is a complex and heterogeneous process executed by all nucleated cell types at a given time window of their development. For most cells, including epithelial, stromal, and neuronal cells, migration phases are confined to morphogenesis and cease with terminal differentiation toward intact tissue to become reactivated only for tissue regeneration or neoplastic processes. For other cell types, such as leukocytes, migration is integral to their function and maintained throughout their life span. Some cell types migrate only in the context of a defined substrate, such as epithelial cells moving along a basement membrane but not through interstitial tissues, whereas other cell types, including leukocytes, are versatile, as they interact with and migrate within virtually any substrate present in the body. Thus, although the same basic process is executed (i.e., cell translocation along or through tissue structures), each cell type exerts migration in different contexts using distinct molecular repertoires and extracellular guidance cues. We here summarize extra- and intracellular molecular parameters that regulate cell migration and integrate them into a parameter “matrix” to better classify how cell migration modes are being both achieved and modulated.The modes of cell migration
The mode of cell migration was originally classified based on the morphology of migration patterns. This terminology was then extended to include molecular parameters, such as cytoskeletal organization, the type of cell–matrix interaction and force generation, and the modification of the tissue structure imposed by migrating cells (Friedl et al., 1998b; Thiery, 2002; Friedl, 2004; Lämmermann and Sixt, 2009; Sanz-Moreno and Marshall, 2009). As main categories, cell move either individually (amoeboid or mesenchymal) or collectively (the migration of cohesive multicellular units; Fig. 1 and Friedl, 2004). Although these terms are arguably arbitrary and the molecular discrimination between the certain modes is incomplete, they help to simplify and categorize an otherwise diffuse literature and allow dissection of the molecular machineries underlying each mode.Open in a separate windowFigure 1.Cell morphologies, migration modes, and transitions. The nomenclature of interstitial migration modes is based on typical cell morphology (rounded or spindle-shaped) and pattern (individual, loosely connected, or collective). Each migration mode is governed by a set of molecular mechanisms (see details in Fig. 2), the regulation of which can change the style of migration. Most widely studied examples for alterations of migration mode are the mesenchymal-to-amoeboid transition or the collective-to-individual transition. The thick gray arrows indicate the direction of migration.Table I.
Different migration modes and selected determinants| Migration mode | Cell types | ECM determinants | Cell determinants | Related transitions | References |
| Single | |||||
| Amoeboid, blebby | Zebrafish macrophage, some stem cells | Poorly adhesive; soft embryonic connective tissue; obligate 3D | Asymmetric bleb-rich cortical actomyosin cytoskeleton, low polarity; low migration speed (below 1 µm/min) | Blebby-to-pseudopodal transitions | Blaser et al., 2006; Yoshida and Soldati, 2006 |
| Amoeboid, pseudopodal | Leukocytes, including dendritic cells; Dictyostelium discoideum | Loose primordial or mature connective tissue; 2D or 3D | Poorly adhesive, no formation of focal adhesions; Rac-driven anterior protrusion with counterbalance by Rho/ROCK in other cell parts; relatively rapid migration (10 µm/min) | Amoeboid-to-mesenchymal transition | Yoshida and Soldati, 2006; Lämmermann et al., 2008 |
| Mesenchymal | Fibroblasts, neural crest cells, sarcoma cells, dedifferentiated cancer cells of different origin | Loose or dense primordial or mature connective tissue; usually associated with fibrin or collagen remodeling | Moderately to highly adhesive; focal interactions with ECM; high contractility; high anterior Rac activity counterbalanced by Rho in other cell parts; slow migration (0.1–1 µm/min) | Mesenchymal-to-amoeboid transition; mesenchymal-to-epithelial/collective transition | Wolf et al., 2003a, 2007; Grinnell, 2008; Paňková et al., 2009; Thiery, 2002 |
| Multicellular | |||||
| Chain migration, cell streaming | Neural crest cells, fibroblasts | Joint ECM tracks? | Individual cells with temporary tiplike cell-cell contacts | Migration arrest and integration into terminal tissue | Davis and Trinkaus, 1981; Kulesa and Fraser, 2000 |
| Collective | Dictyostelium at slug stage, lateral line (zebrafish), border cells (Drosophila egg chamber), sprouting vessels, many epithelial and other cancer types | Any 2D and 3D ECM environment, resulting in cohesive sheets or 3D strands, tubes, clusters or amorphous masses | Intact and stable cell–cell adhesions; coordination of multicellular leading edge protrusion and rear retraction; cell–cell communication during migration | Collective-to-single cell transitions (epithelial/collective-to-mesenchymal; collective-to-amoeboid) | Hegerfeldt et al., 2002; Thiery, 2002; Alexander et al., 2008; Friedl and Gilmour, 2009 |
| Keratocyte-like | Keratinocytes | Obligate 2D surface or tissue | Persistent gliding-type migration of spread-out cells with broad continuous leading lamella cadherin-based cell–cell junctions | Not known | Keren et al., 2008 |
Determinants of cell migration
The common process underlying all migration modes of nucleated mammalian cells is polarized actomyosin-driven shape change of the cell body (Lauffenburger and Horwitz, 1996; Ridley et al., 2003; Keren et al., 2008). This basic program is regulated and “shaped” by several distinct yet interdependent physical and molecular parameters of the tissue and the cell itself that together determine how a cell migrates (Fig. 2). The extracellular environment strongly impacts migration type and efficiency by providing ECM ligands of different macromolecular and structural organization, which includes dimension, density, stiffness, and orientation. In response to environmental determinants, the actomyosin cytoskeleton adapts in a dynamic manner and generates different geometries in space and time, ranging from flat and spread out to roundish, elongated, or multipolar shapes (Grinnell, 2008; Keren et al., 2008). To transmit actomyosin-driven forces to surrounding tissue structures, the cell either develops actin-polymerization–driven protrusions that bind to adhesion sites of the tissue through adhesion receptors (Yamada et al., 2003), or it utilizes poorly adhesive intercalation and propulsion (Paluch et al., 2006a). In both cases, subsequent to leading edge protrusion, actomyosin contraction leads to retraction of the cell rear and translocation of the cell body (Paluch et al., 2006a; Lämmermann and Sixt, 2009). The cyclic repetition of protrusion, interaction with the extracellular environment, and retraction of the cell rear result in cell movement that, depending on the molecular repertoire of the cell, yields distinct migratory modes (Lauffenburger and Horwitz, 1996; Friedl and Wolf, 2009). Additional parameters impacting the type and efficiency of cell migration are the availability of surface proteases that remodel the surrounding tissue (Wolf and Friedl, 2009), and whether the cells retain stringent, loose, or no cell–cell junctions (Friedl and Gilmour, 2009).Open in a separate windowFigure 2.The tuning model of cell migration. An integrated multiscale model to combine multiple interdependent parameters that impact migration mode. Each parameter is experimentally testable individually; however, in most cases they are interconnected with others (see text for details). Approximated parameter profiles of selected migration modes are indicated (colored lines). Modulation by increasing or decreasing the magnitude of any parameter may impact the resulting migration mode as well as the input strength of coregulated parameters. The format of the tuning model mimics the popular display of a graphic equalizer, which is integral to modern media display programs (e.g., Windows Media Player or QuickTime); the graphic interface serves to adjust the intensity of different wavelengths of the phono output independently to modify the sound profile.ECM determinants
The ECM provides a structural and molecular frame for the moving cell body and thereby impacts the mode and efficiency of cell migration.ECM dimension.
Extracellular tissue structures encountered by migrating cells are either flat 2D sheets or 3D tissue networks. Cell migration across 2D surfaces occurs during reepithelialization of wounds or the scanning of leukocytes along the inner blood vessel wall or inner epithelial surfaces (Farooqui and Fenteany, 2005). Hallmarks of 2D migration are the requirement of unilateral adhesion to the substrate, which provides stable-enough but transient attachment; a flattened, spread-out cell morphology guided by a leading lamellipod; and, due to the flat geometry of the substrate, a largely barrier-free migration (Ridley et al., 2003; Farooqui and Fenteany, 2005; Keren et al., 2008; Vitorino and Meyer, 2008). In contrast, when cells move through 3D interstitial tissue consisting of a network of interwoven collagen fibers, which impose space limitations against the moving cell body, their morphology undergoes characteristic changes. First, spread-out morphology is abandoned in favor of a spindle-like shape; second, instead of lamellipodia formation, with its unilateral polarization to the underlying substrate, leading edge protrusion occurs by formation of thin tiplike cylindrical pseudopodia that orient in three dimensions; and third, the cell either deforms its shape to accommodate small tissue gaps or executes remodeling of the ECM structure by pericellular proteolysis (Maaser et al., 1999; Wolf et al., 2003a; Jiang and Grinnell, 2005).ECM density and gap size.
In vivo, interstitial tissues greatly vary in structural organization, such as collagen content, fibrillar texture, fiber bundle thickness, and interfiber porosity. In vivo, migration efficiency is optimal at pore diameters that match or range slightly below the diameter of polarized cells. If the tissue gaps exceed the cell size, migration rates decrease (Haston et al., 1982; Harley et al., 2008) because of a loss of most cell–fiber interactions until only very few or even a single fiber remain engaged with the cell body; the latter is termed “1D” migration (Doyle et al., 2009). Conversely, if pores range below the cell diameter, cells slow down and eventually may become trapped due to the physical hindrance (unpublished data; Haston et al., 1982; Harley et al., 2008). In response to extracellular confinement, migrating cells elongate to a spindle-like shape and thereby stretch and reduce their cell diameter, whereas large pore sizes favor cell rounding, a hallmark of amoeboid migration (unpublished data; Fig. 2).The deformability of the cell and its most rigid compartment, the nucleus, is controlled by nuclear lamins A/C, which mechanically stabilize the nuclear membrane and potentially impact the minimum tissue gaps that can be transmigrated (Lammerding et al., 2006; Dahl et al., 2008). Besides shape adaptation, cells that can proteolytically cleave ECM structures counteract physical hindrance by enlarging pores and forming trails of variable caliber so they match their own diameters (Wolf et al., 2007). Thus, the ability of the cell to deform relative to the available space and to remodel tissues through proteolysis determines both the mode and efficiency of migration in 3D ECM.Stiffness.
ECM stiffness (synonymous with rigidity) or elasticity (synonymous with pliability), which can be measured as elastic modulus, depends on molecular properties of the tissue, including collagen content, fiber thickness, and the extent of intrafibrillar cross-links, which define the stability and deformability of the tissue scaffold (Shoulders and Raines, 2009). Cells detect matrix rigidity via integrin-mediated adhesions and downstream mechanosensor protein signaling (i.e., via talin and p130CAS; Giannone and Sheetz, 2006). Increased substrate stiffness reinforces cell protrusions at outward edges so that focal adhesions form and become reinforced by RhoA-mediated actomyosin contraction, ultimately leading to cell spreading, the generation of high-traction force, and elongated cell movement (Peyton et al., 2008; Ulrich et al., 2009). Conversely, soft matrix does not reinforce focal adhesion formation and cytoskeletal contractility; rather, it supports cell rounding (Ulrich et al., 2009). Consequently, matrix rigidity stimulates directed cell migration, similar to chemotaxis, so that cells tend to migrate toward substrate of greater stiffness, a process termed durotaxis (Lo et al., 2000; Li et al., 2005; Isenberg et al., 2009).Orientation.
Connective tissue comprises a range of physical textures, ranging from loose and random to highly aligned structures (Petrie et al., 2009; Wolf et al., 2009). All mobile cells show a tendency to align in parallel along oriented structural discontinuities, such as at interfaces of muscle fibers, blood vessels, or ECM fiber strands and patterns created by the cells themselves (Provenzano et al., 2008; Petrie et al., 2009). Contact guidance along such structures is mediated by mechanosensory integrins that, together with Rho/ROCK-mediated cytoskeletal stiffening, provide directional persistence (Dickinson et al., 1994; Provenzano et al., 2008; Petrie et al., 2009). Although aligned fiber orientation in collagen-rich ECM does not seemingly impact cell shape (Provenzano et al., 2008), it favors multicellular streaming in chainlike patterns in 3D tissue (Friedl and Wolf, 2009) and migration of 2D cell sheets along tissue clefts (unpublished data).In summary, different ECM environments provide an array of interconnected input parameters that modulate cell adhesion and cytoskeletal organization, and directly impact cell shape, guidance, and mode of migration.Cell determinants
Cell–cell adhesion.
A key determinant of how cells move is whether cell–cell junctions are retained or not, resulting in either collective or single-cell migration, respectively (Vitorino and Meyer, 2008; Friedl and Gilmour, 2009). Cell–cell adhesion is mainly mediated by cadherins, including E-cadherin in epithelial cells, VE-cadherin in endothelial cells, and N-cadherin in stromal cells (Ewald et al., 2008; Vitorino and Meyer, 2008; Friedl and Gilmour, 2009). As opposed to individually migrating cells, during collective migration, the rear of the front cell retains intact cell–cell junctions to the successor cell, thereby mechanically holding the cells together and augmenting the efficiency of paracrine cell–cell signaling and multicellular coordination (Fig. 1). Coordinated cycles of protrusion and rear retraction of the front cells as well as of cells inside the group that engage with underlying substrate lead to movement as a multicellular unit (Farooqui and Fenteany, 2005; Blanchard et al., 2009). If cell–cell junctions are intermittent or less stable, multicellular streaming in a loose tail-to-head fashion results in the coordinated but individual migration of many cells through the tissue, with repetitive short-lived contacts between cells that are resolved and reestablished upon further migration (Fig. 1; Teddy and Kulesa, 2004). Lastly, if cell–cell contacts are absent, cells move independently in both speed and direction (Hegerfeldt et al., 2002). Thus, the presence of stable or transient cell–cell junctions, or their absence, determines whether collective translocation, cell streaming, or single-cell migration, respectively, is being generated.Cell–matrix adhesion.
Cell adhesions to ECM ligands are predominantly generated by integrins via coupling to cytoskeletal and signaling proteins. The strength and turnover rates of cell attachments to the extracellular environment determine which cell shapes and forces are being generated during migration (Ridley et al., 2003). Distinct cell types use adhesive strength over different magnitudes, ranging from strong adhesion by stromal fibroblasts or myoblasts (Huttenlocher et al., 1996), to moderate adhesion of epithelial and endothelial cells (Zhang et al., 2006; Schober et al., 2007), to weak adhesion forces of rapidly gliding fish keratocytes and crawling leukocytes (Friedl et al., 1998b; Keren et al., 2008; Lämmermann et al., 2008). High integrin expression levels are mandatory for high-attachment forces, but are also associated with relatively slow turnover of adhesion sites (Friedl et al., 1998b; Mc Henry et al., 2008) and, consequently, associated with slow migration (Palecek et al., 1997). As an underlying mechanism, integrins and downstream mechanotransducing adaptors, such as p130CAS, become activated with increased mechanical tension and, in turn, further strengthen focal adhesions and actin stress fiber formation (Tamada et al., 2004; Sawada et al., 2006). Strong cell–substrate adhesions thus promote cell contractility and the formation of elongated spread-out (2D) or spindle-shaped (3D) morphologies in many cell types, including fibroblasts, smooth muscle cells, and neoplastic cells (Lauffenburger and Horwitz, 1996; Friedl et al., 1998b; Maaser et al., 1999; Jiang and Grinnell, 2005).If cell adhesion is reduced to a moderate or low level, such as by interfering with the integrin-talin axis, focal adhesions and stress fibers do not form or do not reach full maturation (Zhang et al., 2008). As a consequence, the cells convert to a less elongated or spread-out morphology, generate smaller lamellipodia and pseudopodia, and transmit limited adhesion strength toward the substrate (Zhang et al., 2008). Rapidly moving lymphocytes and neutrophils that still adhere to ECM and other ligands but do not form focal adhesions or stress fibers constitutively use the pseudopodal amoeboid type of movement (Friedl et al., 1998a; Smith et al., 2007).At the very low end of cell adhesion strength, cells are unable to form unilateral attachments to 2D ECM substrate and thus fail to spread out, form lamellipodia, and move, whereas in a 3D environment, they move by amoeboid blebbing or dendritic intercalation (Haston et al., 1982; Fackler and Grosse, 2008; Lämmermann and Sixt, 2009). Given such low adhesion capability, the mechanisms that generate force in this blebby (or dendritic) amoeboid translocation remain to be shown. Likely, the irregular cell shape maintained by cortical actin provides high cytoskeletal rigidity locally, which allows mechanical intercalation between anterior parts of the cell with the surrounding tissue while the rear part of the cell retracts (Blaser et al., 2006; Paluch et al., 2006a; Lämmermann and Sixt, 2009).Cell protrusion and rounding.
Cell protrusions control leading edge dynamics and the migration mode in at least two distinct ways. First, the protrusion of pseudopodia, filopodia, and lamellipodia that adhere to cell and ECM substrates is directed by the small GTPases Rac and Cdc42 (Nobes and Hall, 1999; Sanz-Moreno and Marshall, 2009). Consequently, high Rac activity conveys leading edge extension, elongated morphology, focal integrin engagement, and mesenchymal migration (Nobes and Hall, 1999; Sahai and Marshall, 2003; Sanz-Moreno et al., 2008). Second, bleb-like protrusions that contain cortical actin filaments are nonadhesive or poorly adhesive but contribute to lateral anchoring (“elbowing”) of the cell to tissue structures during actomyosin-mediated rear retraction (Paluch et al., 2006a,b; Fackler and Grosse, 2008). In most cells, Rac-mediated protrusion of the leading edge is counterbalanced by Rho/ROCK signaling, which controls actomyosin-mediated retraction of the trailing edge. Together, they form a cyclic balance in distinct regions of the cell and contribute, concurrently, to the migration cycle (Ridley et al., 2003; Sanz-Moreno and Marshall, 2009). High Rac activity generates cell elongation and mesenchymal migration, whereas active Rho in the presence of little or no Rac activity supports rounded cell shapes associated with amoeboid pseudopodal or blebbing migration, respectively (Sahai and Marshall, 2003; Sanz-Moreno et al., 2008). Besides inducing cell protrusions, active Rac negatively regulates Rho/ROCK signaling and inhibits cell rounding, whereas active Rho/ROCK limits Rac, which inhibits cell extension and elongation (Sanz-Moreno et al., 2008).The formation and elongation of cell protrusions during migration are further controlled by tubulins. Posttranslational tubulin acetylation supports high microtubule stability and is associated with mesenchymal movement, whereas microtubules composed of deacetylated tubulin are subject to enhanced depolymerization by the microtubule-destabilizing factor stathmin and therefore support a rounded, amoeboid migration mode (Piperno et al., 1987; Belletti et al., 2008; Berton et al., 2009). Whether tubulin stability dictates cell shape by modulating to the balance between Rac and Rho activity or by other mechanisms, such as delivery of cargo or a direct mechanical function, is unknown.Mode of force generation.
The force required to move a cell body forward is generated by two principal and often interdependent physical mechanisms: cell propulsion, which leads to forward pushing of the cell body; or traction force generated by pulling of an ECM substrate. A phase of actin polymerization–driven forward pushing of the plasma membrane is indispensible for leading edge protrusion, so it is included in most migration types (Lauffenburger and Horwitz, 1996). In adhesive cells, pushing then leads to local adhesion, cytoskeletal anchorage, and, in a second phase, focal adhesion maturation and pulling on ECM substrate by actomyosin contraction (Ridley et al., 2003; Zhang et al., 2008). Pulling is proportional to adhesion strength and cytoskeletal contractility, such as in fibroblasts and myoblasts, to generate forces sufficient for substrate contraction (Beningo et al., 2001; Miron-Mendoza et al., 2008). In contrast, if leading edge protrusion is coupled to low adhesion force, amoeboid pseudopodal migration occurs at very low traction force, as in moving neutrophils (Smith et al., 2007; Wang, Y.-L., personal communication). On the very low end of adhesion and force generation, amoeboid blebbing cells tend to lack any attachment to 2D surfaces but rather float and oscillate on the spot (unpublished data; Paluch et al., 2006a). However, if included in a loose 3D ECM, such as a collagen matrix or matrigel, blebby cells that are deficient in pseudopodia or filopodia are still able to connect to the 3D substrate and generate movement, despite negligible attachment forces (Blaser et al., 2006; Sanz-Moreno et al., 2008). Thus, whereas mesenchymal migration depends on alternating pushing/pulling cycles, amoeboid migration is mechanically equally complex and comprises stronger pushing combined with a small or completely absent phase of adhesive pulling of the substrate.Protease functions.
Depending on the deformability of the migrating cell and the size of gaps and trails available in the 3D tissue, cells proteolytically remodel surrounding ECM and generate gaps, a hallmark of mesenchymal migration; otherwise, they move without engaging proteases by filling available spaces with their cell body (Friedl and Wolf, 2003a, 2009). In interstitial tissues, MT1-MMP is rate-limiting for collagen degradation, as it executes pericellular proteolysis of collagen fibers that physically impede the moving cell (Wolf et al., 2007; Sabeh et al., 2009). After cleavage, collagen fibers become displaced and realigned, which generates tubelike matrix gaps and trails of least resistance (Friedl and Wolf, 2008). In collagen-rich interstitial tissue, MT1-MMP is further involved in the remodeling of already existing trails to even larger macrotracks, which then accommodate the collective invasion of multicellular strands (Wolf et al., 2007).In contrast to mesenchymal cells that are usually large, smaller amoeboid leukocytes employ much faster movement that lacks signs of pericellular proteolysis of the 3D interstitial substrate (Friedl and Wolf, 2003a). A mechanism of coping with narrow trails is cell deformation and squeezing through the pores so that extracellular structures imprint into the cell body and form local zones of cell compression (Wolf et al., 2003b). If tissue densities are high, such as in basement membranes or dense connective tissue, inhibition of pericellular proteolysis cannot be compensated by shape change; instead, cell bodies get stuck in narrow pores (Sabeh et al., 2004, 2009). Likewise, if proteolytic macropatterning is prevented by protease inhibition, collective cell invasion is ablated and only individual amoeboid dissemination persists (Wolf et al., 2007). Thus, proteolytic ECM remodeling is obligatory in tissues in which cell caliber and deformability fail to match available gaps and trails.The tuning model
Because of its physical and molecular modularity, cell migration must be viewed as a consequence of a continuum of states that are determined by cell mechanics and signaling events. These cellular properties are integrated by the cell or cell groups in a given tissue environment. The tuning model predicts that several parameters simultaneously control how a cell migrates and that their combined magnitudes impact which migration type a cell adopts (Fig. 2). With the exception of ECM dimension, which is either 2D or 3D, all other parameters are scalar; i.e., they can be absent or at low, intermediate, or high levels. Therefore, these parameters are assumed to be tunable and thereby control the migration mode and efficiency in a continuous rather than a discrete “on” or “off” manner. By increasing or decreasing their input, they “tune” how moving cells polarize and engage with encountered tissue substrate. Because all parameters act concurrently but at a different strength, each parameter profile (Fig. 2, colored lines) then generates a different type of migration. Whereas most molecular studies tend to address isolated parameters, the tuning model integrates several denominators in context and may help to understand cell migration as a multimodal cell function.Each component, although experimentally amenable as an individual parameter, is interdependent and positively or negatively coregulated with other determinants. The density of fibrillar ECM is positively interconnected with stiffness and inversely proportional to pore size, so alterations of either parameter impacts the overall tissue geometry (unpublished data). Accordingly, integrin-mediated cell attachment to a deformable yet rigid substrate, but not to a soft substrate, enhances substrate tension and stiffness, which reinforces Rho-mediated traction force generation (Paszek et al., 2005; Peyton et al., 2008; Ulrich et al., 2009). Likewise, traction force generation requires sufficient adhesion mediated by integrins, some Rac-mediated protrusion, and Rho-mediated cytoskeletal contraction (Rhee and Grinnell, 2006). The physical tissue geometry is interdependent with protease acitivity of the cells; consequently, collective migration in 3D tissue depends on sufficiently high a priori porosity or the cell-mediated proteolytic generation of macrotracks (Wolf et al., 2007). Therefore, alteration of a given parameter has likely consequences for other interconnected determinants.Plasticity: tuning the mode of migration
At a given differentiation state, each cell type preferentially employs a particular “default” migration type, such as leukocytes using amoeboid migration, stromal cells moving by a mesenchymal mode, or epithelial cell sheets moving collectively (Friedl, 2004). However, in recent years, it has become clear that naturally occurring or experimentally induced modifications of either the environment or cell properties may result in striking adaptation reactions that alter the migration mode rather than abrogating migration per se. Because any parameter may become altered in the course of migration—such as the transition from dense to loose connective tissue, modulation of adhesion receptor expression, or the availability of cytoskeletal adaptor proteins due to altered gene expression—each alteration of parameter may prompt such secondary alteration of migration mode.Because cell–cell junctions can form de novo and resolve again, individual and collective migration modes are interconvertible (Friedl and Gilmour, 2009). If multicellular cohesion is weakened by the down-modulation of cell–cell junctions, individual cells detach from the multicellular unit which, dependent on the molecular repertoire and environment encountered, disseminate individually. Epithelial-to-mesenchymal transition is involved in many developmental processes and in invasive cancers, and leads to the delamination of spindle-shaped cells that use integrin-mediated force generation for tissue invasion either as single cells or by multicellular streaming (Thiery, 2002; Carmona-Fontaine et al., 2008). Collective-to-amoeboid transition occurs when the detached individual cells disseminate using amoeboid migration (Hegerfeldt et al., 2002; Wolf et al., 2007). Conversely, if individually moving cells up-regulate cell–cell adhesion molecules, then cell aggregation leads to individual-to-collective transition (Thiery, 2002).A central pathway controlling the interconversion between mesenchymal and rounded, amoeboid migration is the balance between Rac and Rho signaling (Sahai and Marshall, 2003). In many experimental examples, mesenchymal-to-amoeboid transitions depend, directly or indirectly, on pathways that weaken Rac and/or strengthen Rho/ROCK signaling (Sanz-Moreno et al., 2008; Paňková et al., 2009; Sanz-Moreno and Marshall, 2009). Thus, upstream pathways that suppress Rac activity induce this conversion, including the activation of the GTPase-activating protein (GAP) ARHGAP22, which directly inhibits Rac (Sanz-Moreno et al., 2008); inhibition of the Rac-activating guanine nucleotide exchange factor DOCK3/NEDD9 or of the down-stream Rac effector and Rho inhibitor WAVE-II (Sanz-Moreno et al., 2008); interference with Rab5-mediated endocytosis and recycling of Rac to cell protrusions (Palamidessi et al., 2008); and the inhibition of E3 ubiquitin ligase Smurf1, which enzymatically degrades Rho near the leading edge and thereby secures the dominance of Rac in cell protrusions (Sahai et al., 2007). Likewise, inhibition of chemokine-meditated Rac activation favors amoeboid movement in otherwise mesenchymal cells (Gérard et al., 2007). Pathways that activate Rho lead to mesenchymal-to-amoeboid transition, including inhibition of negative Rho regulators (e.g., p90RhoGAP) through an indirect, reactive oxygen species-dependent mechanism (Nimnual et al., 2003) or the activation of Ephrin2A receptor tyrosine kinase signaling, which indirectly activates Rho (Parri et al., 2009).Alteration of adhesion force by modulating integrin function leads to similar plasticity. The transition from amoeboid myeloid precursor cells to adhesive elongated and contractile macrophages is initiated by the up-regulation and activation of β1, β2, and β3 integrins (McNally and Anderson, 2002). Conversely, mesenchymal cells convert to amoeboid movement in experimental 3D matrices after limiting pathways that control focal adhesion formation, including inhibition of β1 integrin–mediated adhesion or of the tyrosine kinase cSrc (Carragher et al., 2006; Zaman et al., 2006). Plasticity imposed by altered tissue architecture occurs when cells transit from a 2D interface into 3D tissue. The initial spread-out or cuboidal 2D phenotype then converts toward a spindle-shaped mesenchymal phenotype with vertical penetration and migration into the 3D matrix (Alt-Holland et al., 2008). Lastly, in loose interstitial tissues with gaps that accommodate the cell body, the inhibition of surface protease activity causes a transition from protease-dependent mesenchymal migration to amoeboid migration involving shape change and squeezing without tissue remodeling (Wolf et al., 2003a, 2007).Thus, alterations of cell–cell and cell–matrix adhesion, cytoskeletal signaling and mechanics, and protease function determine whether and how cells switch between distinct migration modes. These transitions of migration mode are best studied for cancer cells and likely contribute to the metastatic cascade (Friedl and Wolf, 2003b; Sanz-Moreno and Marshall, 2009), yet they are also relevant to cell migration and function in physiological contexts, such as the delamination of cells during morphogenesis and the distribution of stem cells or leukocytes in tissues and organs (Blaser et al., 2006; Lämmermann and Sixt, 2009).Outlook
The multiparameter tuning model integrates observations from many different cell types and experimental models. The model thus may be helpful to understand and experimentally test the adaptability of cell movement and its consequence for tissue formation and remodeling, particularly in morphogenesis and cancer metastasis. The model may further be a useful starting point for computational modeling of cell migration in different contexts. Although the parameters and migration modes discussed here are best established for interstitial migration of cells in fibrillar collagen-rich tissues, they likely fail to sufficiently represent the movement of other cell types and tissue contexts. This may be the case particularly for cells of neural origin that predominantly move along scaffold tracks formed by other cells, rather than ECM, or cell trafficking across basement membrane during transendothelial migration or the early invasion of epithelial cancer. Likewise, complex movements in ductal gland or vessel formation represent special cases with complex topography, such as lumen formation and deposition of a basement membrane, which may require the inclusion of additional modules. Besides integrin-mediated adhesion structures, special cases of cell–substrate interaction include cadherin- or ephrin-based cell–cell junctions that guide cell migration along cell scaffolds, and podosomes and invadopodia that degrade ECM underneath the cell body but not at leading edges. The contribution of these structures to force generation and the mode of migration remain to be established and, potentially, included in the model. Ultimately, although each parameter has its own contribution to how efficiently cells migrate, the model still lacks prioritization; that is, the importance of each input parameter relative to others still remains undefined. Therefore, future wet-laboratory and computational studies will not only have to integrate additional or exclude existing determinants for special migration modes and contexts, but they also should take coregulated synergistic or antagonistic multiparameter modules into account. 相似文献13.
Myoseverin, a new microtubule-binding molecule, acts reversibly on myoblast proliferation without the cytotoxic effects displayed by nonpurine-based microtubule-disrupting molecules, like taxol, vinblastine, nocodazole, and the colchicines. In this study, we examined the effects of myoseverin on in vitro function of endothelial cells and endothelial progenitor cell differentiation in order to explore the possibility for the application of myoseverin as a reversible antiangiogenic agent. Myoseverin potently inhibited proliferation of human umbilical vein endothelial cells (HUVECs) in a dose-dependent manner with an IC50 of approximately 8 microM. When myoseverin was removed after treatment for 3 days, all the cells pretreated at a concentration range of 2.5-80 microM resumed the cell growth. It also inhibited VEGF-induced HUVEC migration dose dependently. When mononuclear cells (MNCs) isolated from human cord blood were cultured on fibronectin-coated plates for 7 days, myoseverin decreased the number of adherent cells in a dose-dependent manner with IC50 of approximately 9 microM. It also suppressed the development of ac-LDL uptake ability as well as the expression of endothelial lineage markers, KDR, CD31, and vWF. Finally, it inhibited formation of HUVECs or ex vivo cultivated EPCs into capillary-like structure on Matri-gel and in vivo angiogenesis on the chick chorioallantoic membrane. Therefore, these results suggest that myoseverin can be effectively used for the inhibition of new vessel growth by inhibiting endothelial cell function and differentiation of progenitor cells. 相似文献
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A major challenge confronting developmental cell biologists is to understand how individual cell behaviors lead to global tissue organization. Taking advantage of an endothelial cell-specific marker and scanning time-lapse microscopy, we have examined the formation of the primary vascular pattern during avian vasculogenesis. Five types of distinguishable endothelial cell motion are observed during formation of a vascular plexus: (1) global tissue deformations that passively convect endothelial cells; (2) vascular drift, a sheet-like medial translocation of the entire vascular plexus; (3) structural rearrangements, such as vascular fusion; (4) individual cell migration along existing endothelial structures; and (5) cell process extension into avascular areas, resulting in new links within the plexus. The last four types of motion are quantified and found to be reduced in the presence of an alphavbeta3 integrin inhibitor. These dynamic cell motility data result in new hypotheses regarding primordial endothelial cell behavior during embryonic vasculogenesis. 相似文献
15.
How angiogenesis is regulated by local environmental cues is still not fully understood despite its importance to many regenerative events. Although mechanics is known to influence angiogenesis, the specific cellular mechanisms influenced by mechanical loading are poorly understood. This study adopts a lattice-based modelling approach to simulate endothelial cell (EC) migration and proliferation in order to explore how mechanical stretch regulates their behaviour. The approach enables the explicit modelling of ECs and, in particular, their migration/proliferation (specifically, rate and directionality) in response to such mechanical cues. The model was first used to simulate previously reported experiments of EC migration and proliferation in an unloaded environment. Next, three potential effects (increased cell migration, increased cell proliferation and biased cellular migration) of mechanical stretch on EC behaviour were simulated using the model and the observed changes in cell population characteristics were compared to experimental findings. Combinations of these three potential drivers were also investigated. The model demonstrates that only by incorporating all three changes in cellular physiology (increased EC migration, increased EC proliferation and biased EC migration in the direction perpendicular to the applied strain) in response to dynamic loading, it is possible to successfully predict experimental findings. This provides support for the underlying model hypotheses for how mechanics regulates EC behaviour. 相似文献
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Balasubramaniam V Maxey AM Fouty BW Abman SH 《American journal of physiology. Lung cellular and molecular physiology》2006,290(6):L1111-L1116
Growth and development of the lung normally occur in the low oxygen environment of the fetus. The role of this low oxygen environment on fetal lung endothelial cell growth and function is unknown. We hypothesized that low oxygen tension during fetal life enhances pulmonary artery endothelial cell (PAEC) growth and function and that nitric oxide (NO) production modulates fetal PAEC responses to low oxygen tension. To test this hypothesis, we compared the effects of fetal (3%) and room air (RA) oxygen tension on fetal PAEC growth, proliferation, tube formation, and migration in the presence and absence of the NO synthase (NOS) inhibitor N(omega)-nitro-l-arginine (LNA), and an NO donor, S-nitroso-N-acetylpenicillamine (SNAP). Compared with fetal PAEC grown in RA, 3% O(2) increased tube formation by over twofold (P < 0.01). LNA treatment reduced tube formation in 3% O(2) but had no affect on tube formation in RA. Treatment with SNAP increased tube formation during RA exposure to levels observed in 3% O(2). Exposure to 3% O(2) for 48 h attenuated cell number (by 56%), and treatment with LNA reduced PAEC growth by 44% in both RA and 3% O(2). We conclude that low oxygen tension enhances fetal PAEC tube formation and that NO is essential for normal PAEC growth, migration, and tube formation. Furthermore, we conclude that in fetal cells exposed to the relative hyperoxia of RA, 21% O(2), NO overcomes the inhibitory effects of the increased oxygen, allowing normal PAEC angiogenesis and branching. We speculate that NO production maintains intrauterine lung vascular growth and development during exposure to low O(2) in the normal fetus. We further speculate that NO is essential for pulmonary angiogenesis in fetal animal exposed to increased oxygen tension of RA and that impaired endothelial NO production may contribute to the abnormalities of angiogenesis see in infants with bronchopulmonary dysplasia. 相似文献
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Yuan‐Yuan Sun Wen‐Wu Bai Bo Wang Xiao‐Ting Lu Yi‐Fan Xing Wen Cheng Xiao‐Qiong Liu Yu‐Xia Zhao 《Journal of cellular and molecular medicine》2014,18(5):907-918
Cellular therapeutic neovascularization has been successfully performed in clinical trials for patients with ischaemia diseases. Despite the vast knowledge of cardiovascular disease and circadian biology, the role of the circadian clock in regulating angiogenesis in myocardial infarction (MI) remains poorly understood. In this study, we aimed to investigate the role and underlying mechanisms of Period 2 (Per2) in endothelial progenitor cell (EPC) function. Flow cytometry revealed lower circulating EPC proportion in per2−/− than in wild-type (WT) mice. PER2 was abundantly expressed in early EPCs in mice. In vitro, EPCs from per2−/− mice showed impaired proliferation, migration, tube formation and adhesion. Western blot analysis demonstrated inhibited PI3k/Akt/FoxO signalling and reduced C-X-C chemokine receptor type 4 (CXCR4) protein level in EPCs of per2−/− mice. The impaired proliferation was blocked by activated PI3K/Akt/FoxO signalling. Direct interaction of CXCR4 and PER2 was detected in WT EPCs. To further study the effect of per2 on in vivo EPC survival and angiogenesis, we injected saline or DiI-labelled WT or per2−/− EPC intramyocardially into mice with induced MI. Per2−/− reduced the retention of transplanted EPCs in the myocardium, which was associated with significantly reduced DiI expression in the myocardium of MI mice. Decreased angiogenesis in the myocardium of per2−/− EPC-treated mice coincided with decreased LV function and increased infarct size in the myocardium. Per2 may be a key factor in maintaining EPC function in vitro and in therapeutic angiogenesis in vivo. 相似文献
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Frdrique Billy Benjamin Ribba Olivier Saut Hlne Morre-Trouilhet Thierry Colin Didier Bresch Jean-Pierre Boissel Emmanuel Grenier Jean-Pierre Flandrois 《Journal of theoretical biology》2009,260(4):545-562
Tumor angiogenesis is the process by which new blood vessels are formed and enhance the oxygenation and growth of tumors. As angiogenesis is recognized as being a critical event in cancer development, considerable efforts have been made to identify inhibitors of this process. Cytostatic treatments that target the molecular events of the angiogenesis process have been developed, and have met with some success. However, it is usually difficult to preclinically assess the effectiveness of targeted therapies, and apparently promising compounds sometimes fail in clinical trials.We have developed a multiscale mathematical model of angiogenesis and tumor growth. At the molecular level, the model focuses on molecular competition between pro- and anti-angiogenic substances modeled on the basis of pharmacological laws. At the tissue scale, the model uses partial differential equations to describe the spatio-temporal changes in cancer cells during three stages of the cell cycle, as well as those of the endothelial cells that constitute the blood vessel walls.This model is used to qualitatively assess how efficient endostatin gene therapy is. Endostatin is an anti-angiogenic endogenous substance. The gene therapy entails overexpressing endostatin in the tumor and in the surrounding tissue. Simulations show that there is a critical treatment dose below which increasing the duration of treatment leads to a loss of efficacy.This theoretical model may be useful to evaluate the efficacy of therapies targeting angiogenesis, and could therefore contribute to designing prospective clinical trials. 相似文献