Automated production of nerve repair constructs containing endothelial cell tube-like structures

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Abstract
Engineered neural tissue (EngNT) is a stabilised aligned cellular hydrogel that offers a potential alternative to the nerve autograft for the treatment of severe peripheral nerve injury. This work aimed to automate the production of EngNT, to improve the feasibility of scalable manufacture for clinical translation. Endothelial cells were used as the cellular component of the EngNT, with the formation of endothelial cell tube-like structures mimicking the polarised vascular structures formed early on in the natural regenerative process. Gel aspiration-ejection for the production of EngNT was automated by integrating a syringe pump with a robotic positioning system, using software coded in Python to control both devices. Having established the production method and tested mechanical properties, the EngNT containing human umbilical vein endothelial cells (EngNT-HUVEC) was characterised in terms of viability and alignment, compatibility with neurite outgrowth from rat dorsal root ganglion neurons and formation of endothelial cell networks in vitro. EngNT-HUVEC manufactured using the automated system contained viable and aligned endothelial cells, which developed into a network of multinucleated endothelial cell tube-like structures inside the constructs and an outer layer of endothelialisation. The EngNT-HUVEC constructs were made in various sizes within minutes. Constructs provided support and guidance to regenerating neurites in vitro. This work automated the formation of EngNT, facilitating high throughput manufacture at scale. The formation of endothelial cell tube-like structures within stabilised hydrogels provides an engineered tissue with potential for use in nerve repair.
Funding Information
  • Biotechnology and Biological Sciences Research Council (BB/T008709/1)
  • Canada Foundation for Innovation (38822)
  • Fonds de Recherche du Québec-Nature et Technologies du Québec (254631)
  • Natural Sciences and Engineering Research Council of Canada (RGPIN-2022-04364)

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