The Role of Network Architecture in Collagen Mechanics.
Biophys J
; 114(11): 2665-2678, 2018 06 05.
Article
en En
| MEDLINE
| ID: mdl-29874616
Collagen forms fibrous networks that reinforce tissues and provide an extracellular matrix for cells. These networks exhibit remarkable strain-stiffening properties that tailor the mechanical functions of tissues and regulate cell behavior. Recent models explain this nonlinear behavior as an intrinsic feature of disordered networks of stiff fibers. Here, we experimentally validate this theoretical framework by measuring the elastic properties of collagen networks over a wide range of self-assembly conditions. We show that the model allows us to quantitatively relate both the linear and nonlinear elastic behavior of collagen networks to their underlying architecture. Specifically, we identify the local coordination number (or connectivity) ãzã as a key architectural parameter that governs the elastic response of collagen. The network elastic response reveals that ãzã decreases from 3.5 to 3 as the polymerization temperature is raised from 26 to 37°C while being weakly dependent on concentration. We furthermore infer a Young's modulus of 1.1 MPa for the collagen fibrils from the linear modulus. Scanning electron microscopy confirms that ãzã is between three and four but is unable to detect the subtle changes in ãzã with polymerization conditions that rheology is sensitive to. Finally, we show that, consistent with the model, the initial stress-stiffening response of collagen networks is controlled by the negative normal stress that builds up under shear. Our work provides a predictive framework to facilitate future studies of the regulatory effect of extracellular matrix molecules on collagen mechanics. Moreover, our findings can aid mechanobiological studies of wound healing, fibrosis, and cancer metastasis, which require collagen matrices with tunable mechanical properties.
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Estrés Mecánico
/
Colágeno
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Biophys J
Año:
2018
Tipo del documento:
Article
País de afiliación:
Países Bajos