Extrusion 3D bioprinting of functional self-supporting neural constructs using a photoclickable gelatin bioink. (1st July 2022)

• Record Type: Journal Article
• Authors: Yao, Yue; Molotnikov, Andrey; Parkington, Helena C; Meagher, Laurence; Forsythe, John S
• Is Part Of: Biofabrication. Volume 14:Number 3(2022)
• Publication Date: 2022-07-01
• Subjects: bioprinting -- printability -- neural culture -- bioink -- extrusion -- click-chemistry -- gelatin; Biomedical engineering -- Periodicals; Tissue engineering -- Periodicals; Biomedical materials -- Microstructure -- Periodicals; Bioengineering -- Periodicals; 610.28
• DOI: 10.1088/1758-5090/ac6e87
• Languages: English
• ISSNs: 1758-5082

Abstract

Abstract: Many in vitro models of neural physiology utilize neuronal networks established on two-dimensional substrates. Despite the simplicity of these 2D neuronal networks, substrate stiffness may influence cell morphology, network interactions and how neurons communicate and function. With this perspective, three-dimensional (3D) gel encapsulation is a powerful to recapitulating aspects of in vivo features, yet such an approach is often limited in terms of the level of resolution and feature size relevant for modelling aspects of brain architecture. Here, we report 3D bioplotting of rat primary cortical neural cells using a hydrogel system comprising gelatin norbornene (GelNB) and poly (ethylene glycol) dithiol (PEGdiSH). This bioink benefits from a rapid photo-click chemistry, yielding eight-layer crosshatch neural scaffolds and a filament width of 350 µ m. The printability of this system depends on hydrogel concentration, printing temperature, extrusion pressure and speed. These parameters were studied via quantitative comparison between rheology and filament dimensions to determine the optimal printing conditions. Under optimal conditions, cell viability of bioprinted primary cortical neurons at day 1 (68 ± 2%) and at day 7 (68 ± 1%) were comparable to the 2D control group (72 ± 7%). The present study relates material rheology and filament dimensions to generate compliant free-standing neural constructs through bioplotting of low-concentration GelNB-PEGdiSH, which may provide a step forward to study 3D neuronal function and network formation.