DI-UMONS : Dépôt institutionnel de l’université de Mons

Recherche transversale
(titres de publication, de périodique et noms de colloque inclus)
2016-02-26 - Article/Dans un journal avec peer-review - Anglais - 8 page(s)

Lantoine Joséphine , Grevesse Thomas, Villers Agnès , Delhaye Geoffrey, Versaevel Marie, Mohammed Danahe , Bruyere Céline , Alaimo Laura , Lacour Stéphanie, Ris Laurence , Gabriele Sylvain , "Matrix stiffness modulates formation and activity of neuronal networks of controlled architectures" in Biomaterials, 89, 14-24

  • Edition : Butterworth Heinemann, Oxford (United Kingdom)
  • Codes CREF : Physico-chimie générale (DI1320), Biophysique (DI3113)
  • Unités de recherche UMONS : Laboratoire Interfaces et Fluides complexes (S885)
  • Instituts UMONS : Institut des Biosciences (Biosciences)
Texte intégral :

Abstract(s) :

(Anglais) The ability to construct easily in vitro networks of primary neurons organized with imposed topologies is required for neural tissue engineering as well as for the development of neuronal interfaces with desirable characteristics. However, accumulating evidence suggests that the mechanical properties of the culture matrix can modulate important neuronal functions such as growth, extension, branching and activity. Here we designed robust and reproducible laminin-polylysine grid micropatterns on cell culture substrates that have similar biochemical properties but a 100-fold difference in Young's modulus to investigate the role of the matrix rigidity on the formation and activity of cortical neuronal networks. We found that cell bodies of primary cortical neurons gradually accumulate in circular islands, whereas axonal extensions spread on linear tracks to connect circular islands. Our findings indicate that migration of cortical neurons is enhanced on soft substrates, leading to a faster formation of neuronal networks. Furthermore, the pre-synaptic density was two times higher on stiff substrates and consistently the number of action potentials and miniature synaptic currents was enhanced on stiff substrates. Taken together, our results provide compelling evidence to indicate that matrix stiffness is a key parameter to modulate the growth dynamics, synaptic density and electrophysiological activity of cortical neuronal networks, thus providing useful information on scaffold design for neural tissue engineering.