Literature DB >> 26946402

Matrix stiffness modulates formation and activity of neuronal networks of controlled architectures.

Joséphine Lantoine1, Thomas Grevesse1, Agnès Villers2, Geoffrey Delhaye1, Camille Mestdagh1, Marie Versaevel1, Danahe Mohammed1, Céline Bruyère1, Laura Alaimo1, Stéphanie P Lacour3, Laurence Ris2, Sylvain Gabriele4.   

Abstract

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.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Matrix stiffness; Mechanotaxis; Micropatterning; Migration; Neuronal networks

Mesh:

Substances:

Year:  2016        PMID: 26946402     DOI: 10.1016/j.biomaterials.2016.02.041

Source DB:  PubMed          Journal:  Biomaterials        ISSN: 0142-9612            Impact factor:   12.479


  16 in total

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