Dataset Information

Spatial distributions of pericellular stiffness in natural extracellular matrices are dependent on cell-mediated proteolysis and contractility.

ABSTRACT: Bulk tissue stiffness has been correlated with regulation of cellular processes and conversely cells have been shown to remodel their pericellular tissue according to a complex feedback mechanism critical to development, homeostasis, and disease. However, bulk rheological methods mask the dynamics within a heterogeneous fibrous extracellular matrix (ECM) in the region proximal to a cell (pericellular region). Here, we use optical tweezers active microrheology (AMR) to probe the distribution of the complex material response function (?=?'+??, in units of µm/nN) within a type I collagen ECM, a biomaterial commonly used in tissue engineering. We discovered cells both elastically and plastically deformed the pericellular material. ?' is wildly heterogeneous, with 1/?' values spanning three orders of magnitude around a single cell. This was observed in gels having a cell-free 1/?' of approximately 0.5nN/µm. We also found that inhibition of cell contractility instantaneously softens the pericellular space and reduces stiffness heterogeneity, suggesting the system was strain hardened and not only plastically remodeled. The remaining regions of high stiffness suggest cellular remodeling of the surrounding matrix. To test this hypothesis, cells were incubated within the type I collagen gel for 24-h in a media containing a broad-spectrum matrix metalloproteinase (MMP) inhibitor. While pericellular material maintained stiffness asymmetry, stiffness magnitudes were reduced. Dual inhibition demonstrates that the combination of MMP activity and contractility is necessary to establish the pericellular stiffness landscape. This heterogeneity in stiffness suggests the distribution of pericellular stiffness, and not bulk stiffness alone, must be considered in the study of cell-ECM interactions and design of complex biomaterial scaffolds. STATEMENT OF SIGNIFICANCE:Collagen is a fibrous extracellular matrix (ECM) protein widely used to study cell-ECM interactions. Stiffness of ECM has been shown to instruct cells, which can in turn modify their ECM, as has been shown in the study of cancer and regenerative medicine. Here we measure the stiffness of the collagen microenvironment surrounding cells and quantitatively measure the dependence of pericellular stiffness on MMP activity and cytoskeletal contractility. Competent cell-mediated stiffening results in a wildly heterogeneous micromechanical topography, with values spanning orders of magnitude around a single cell. We speculate studies must consider this notable heterogeneity generated by cells when testing theories regarding the role of ECM mechanics in health and disease.

SUBMITTER: Keating M

PROVIDER: S-EPMC5526213 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatial distributions of pericellular stiffness in natural extracellular matrices are dependent on cell-mediated proteolysis and contractility.

Keating M M Kurup A A Alvarez-Elizondo M M Levine A J AJ Botvinick E E

Acta biomaterialia 20170505

Bulk tissue stiffness has been correlated with regulation of cellular processes and conversely cells have been shown to remodel their pericellular tissue according to a complex feedback mechanism critical to development, homeostasis, and disease. However, bulk rheological methods mask the dynamics within a heterogeneous fibrous extracellular matrix (ECM) in the region proximal to a cell (pericellular region). Here, we use optical tweezers active microrheology (AMR) to probe the distribution of t ...[more]

PMID: 28483696

Similar Datasets

Project description:BACKGROUND: Epidemiology and ecology share many fundamental research questions. Here we describe how principal coordinates of neighbor matrices (PCNM), a method from spatial ecology, can be applied to spatial epidemiology. PCNM is based on geographical distances among sites and can be applied to any set of sites providing a good coverage of a study area. In the present study, PCNM eigenvectors corresponding to positive autocorrelation were used as explanatory variables in linear regressions to model incidences of eight most common cancer types in Finnish municipalities (n?=?320). The dataset was provided by the Finnish Cancer Registry and it included altogether 615,839 cases between 1953 and 2010. RESULTS: PCNM resulted in 165 vectors with a positive eigenvalue. The first PCNM vector corresponded to the wavelength of hundreds of kilometers as it contrasted two main subareas so that municipalities located in southwestern Finland had the highest positive site scores and those located in midwestern Finland had the highest negative scores in that vector. Correspondingly, the 165(th) PCNM vector indicated variation mainly between the two small municipalities located in South Finland. The vectors explained 13?-?58% of the spatial variation in cancer incidences. The number of outliers having standardized residual > |3| was very low, one to six per model, and even lower, zero to two per model, according to Chauvenet's criterion. The spatial variation of prostate cancer was best captured (adjusted r (2)?=?0.579). CONCLUSIONS: PCNM can act as a complementary method to causal modeling to achieve a better understanding of the spatial structure of both the response and explanatory variables, and to assess the spatial importance of unmeasured explanatory factors. PCNM vectors can be used as proxies for demographics and causative agents to deal with autocorrelation, multicollinearity, and confounding variables. PCNM may help to extend spatial epidemiology to areas with limited availability of registers, improve cost-effectiveness, and aid in identifying unknown causative agents, and predict future trends in disease distributions and incidences. A large advantage of using PCNM is that it can create statistically valid reflectors of real predictors for disease incidence models with only little resources and background information.

Project description:Membrane ruffling and lamellipodia formation promote the motility of adherent cells in two-dimensional motility assays by mechano-sensing of the microenvironment and initiation of focal adhesions towards their surroundings. Lamellipodium formation is stimulated by small Rho GTPases of the Rac subfamily, since genetic removal of these GTPases abolishes lamellipodium assembly. The relevance of lamellipodial or invadopodial structures for facilitating cellular mechanics and 3D cell motility is still unclear. Here, we hypothesized that Rac1 affects cell mechanics and facilitates 3D invasion. Thus, we explored whether fibroblasts that are genetically deficient for Rac1 (lacking Rac2 and Rac3) harbor altered mechanical properties, such as cellular deformability, intercellular adhesion forces and force exertion, and exhibit alterations in 3D motility. Rac1 knockout and control cells were analyzed for changes in deformability by applying an external force using an optical stretcher. Five Rac1 knockout cell lines were pronouncedly more deformable than Rac1 control cells upon stress application. Using AFM, we found that cell-cell adhesion forces are increased in Rac1 knockout compared to Rac1-expressing fibroblasts. Since mechanical deformability, cell-cell adhesion strength and 3D motility may be functionally connected, we investigated whether increased deformability of Rac1 knockout cells correlates with changes in 3D motility. All five Rac1 knockout clones displayed much lower 3D motility than Rac1-expressing controls. Moreover, force exertion was reduced in Rac1 knockout cells, as assessed by 3D fiber displacement analysis. Interference with cellular stiffness through blocking of actin polymerization by Latrunculin A could not further reduce invasion of Rac1 knockout cells. In contrast, Rac1-expressing controls treated with Latrunculin A were again more deformable and less invasive, suggesting actin polymerization is a major determinant of observed Rac1-dependent effects. Together, we propose that regulation of 3D motility by Rac1 partly involves cellular mechanics such as deformability and exertion of forces.

Dataset Information

Spatial distributions of pericellular stiffness in natural extracellular matrices are dependent on cell-mediated proteolysis and contractility.

Publications

Spatial distributions of pericellular stiffness in natural extracellular matrices are dependent on cell-mediated proteolysis and contractility.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets