Computational model combined with in vitro experiments to analyse mechanotransduction during mesenchymal stem cell adhesion

Abstract

The shape that stem cells reach at the end of adhesion process influences their differentiation. Rearrangement of cytoskeleton and modification of intracellular tension may activate mechanotransduction pathways controlling cell commitment. In the present study, the mechanical signals involved in cell adhesion were computed in in vitro stem cells of different shapes using a single cell model, the so-called Cytoskeleton Divided Medium (CDM) model. In the CDM model, the filamentous cytoskeleton and nucleoskeleton networks were represented as a mechanical system of multiple tensile and compressive interactions between the nodes of a divided medium. The results showed that intracellular tonus, focal adhesion forces as well as nuclear deformation increased with cell spreading. The cell model was also implemented to simulate the adhesion process of a cell that spreads on protein-coated substrate by emitting filopodia and creating new distant focal adhesion points. As a result, the cell model predicted cytoskeleton reorganisation and reinforcement during cell spreading. The present model quantitatively computed the evolution of certain elements of mechanotransduction and may be a powerful tool for understanding cell mechanobiology and designing biomaterials with specific surface properties to control cell adhesion and differentiation. Keywords:Mesenchymal stem cells; cell adhesion; cell morphology; computational cell adhesion model; cytoskeleton; mechanical forces; mechanotransduction. IntroductionCell adhesion is fundamental in the field of biomaterials. Especially in orthopaedics, it is crucial for prosthesis osseointegration (Lavenus et al., 2010). Osteoblasts need to adhere on the implant to synthesise the bone tissue that is directly connected to it without the intervening soft tissue. Moreover, stem cells, which are recruited to heal the implant interface, adhere on the surface and differentiate depending, among other factors, on their adherent morphology. For instance, stem cells which reach at the end of adhesion round, elongated or branched shapes depending on substrate topography or stiffness, differentiate preferentially into adipocytes, fibroblasts or osteoblasts, respectively (McBeath et al., 2004;Engler et al., 2006). Therefore, biomaterial surface must promote adhesion of stem cells and their differentiation into the desired phenotype so as to synthesise a periprosthetic tissue, ensuring efficient and viable biomaterial integration. Biomaterials that mimic the natural composition of the extracellular matrix have been developed. They are composed of a biological phase or are coated with RGD complex and showed positive effects on cell adhesion (Von der Mark et al., 2010). Topography and surface chemistry, which play a key role in cell adhesion, may be controlled using nanotechnology. This announces the development of new implant surfaces with predictable tissue-integrative properties (Le Guéhennec et al., 2007;Lavenus et al., 2010).Cell adhesion results from the creation of several discrete focal a...

In silico CDM model sheds light on force transmission in cell from focal adhesions to nucleus

“…The present CDM model is an improvement of the previous version (Milan et al, 2013) which only took cell shape into account. The CDM model has undergone extensive modifications for the sake of the present study to be cell-dependent and to act mechanically as the cell does.…”

“…1). Interactions between node species were ruled as a relationship between reaction force and gap (Milan et al, 2013). Two interaction laws, Elastic Wire and Contact, were used.…”

“…5 additional cells were chosen on the stiffer substrate to estimate the possible influence of additional stiffness. For each of the 25 cells, the CDM was forced to strain iteratively on the substrate until it connected the FA sites as described in (Milan et al, 2013); this is referred to as the spreading phase. Since adhesion forces are the signature of the contractile cytoskeleton we here sought to compute the cytoskeleton by taking into account experimentally measured FA forces.…”

“…Stress fibers, actin cortex, microtubules, intermediate filaments and nucleoskeleton were also included in the model with specific mechanical role. The CDM model was used previously to analyze the influence of adherent shape on the mechanical state of the cell (Milan et al, 2013). This led to discriminant results yet still incomplete, because FA tractions were not measured.…”

Modeling the formation of cell-matrix adhesions on a single 3D matrix fiber

“…Another interesting work is developed by Cirit et al [27] where they created a model that analyzes the dynamical interplay between cell protrusion and adhesion at the cells leading edge. Milan et al [28] like a set of particles interacting with each other and generating a discrete force network able to mimic the discrete filament network of the cytoskeleton in the cell. The model was also implemented to simulate how a cell adheres on plain substrate by emitting filopodia.…”