Development of two-photon polymerised scaffolds for optical interrogation and neurite guidance of human iPSC-derived cortical neuronal networks

J A Crowe, A El-Tamer, D Nagel, A V Koroleva, J Madrid-Wolff, O E Olarte, S Sokolovsky, E Estevez-Priego, A-A Ludl, J Soriano, P Loza-Alvarez, B N Chichkov, E J Hill, H R Parri, E U Rafailov

Research output: Contribution to journalArticlepeer-review

Abstract

Recent progress in the field of human induced pluripotent stem cells (iPSCs) has led to the efficient production of human neuronal cell models for in vitro study. This has the potential to enable the understanding of live human cellular and network function which is otherwise not possible. However, a major challenge is the generation of reproducible neural networks together with the ability to interrogate and record at the single cell level. A promising aid is the use of biomaterial scaffolds that would enable the development and guidance of neuronal networks in physiologically relevant architectures and dimensionality. The optimal scaffold material would need to be precisely fabricated with submicron resolution, be optically transparent, and biocompatible. Two-photon polymerisation (2PP) enables precise microfabrication of three-dimensional structures. In this study, we report the identification of two biomaterials that support the growth and differentiation of human iPSC-derived neural progenitors into functional neuronal networks. Furthermore, these materials can be patterned to induce alignment of neuronal processes and enable the optical interrogation of individual cells. 2PP scaffolds with tailored topographies therefore provide an effective method of producing defined in vitro human neural networks for application in influencing neurite guidance and complex network activity.

Original languageEnglish
Pages (from-to)1792-1806
Number of pages15
JournalLab on a Chip
Volume20
Issue number10
Early online date21 Apr 2020
DOIs
Publication statusPublished - 19 May 2020

Bibliographical note

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.
Funding: This project has received funding from the European Union's
Horizon 2020 research and innovation programme under the
grant agreement MESOBRAIN No 713140. EUR and BNC
acknowledge further financial support from the European
Union's Horizon 2020 programme under the grant agreement
SCAFFOLD-NEEDS No. 851734.

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