Embedded 3D Printing in Self-Healing Annealable Composites for Precise Patterning of Functionally Mature Human Neural Constructs

Janko Kajtez*, Milan Finn Wesseler, Marcella Birtele, Farinaz Riyahi Khorasgani, Daniella Rylander Ottosson, Arto Heiskanen, Tom Kamperman, Jeroen Leijten, Alberto Martínez-Serrano, Niels B. Larsen, Thomas E. Angelini, Malin Parmar, Johan U. Lind, Jenny Emnéus

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Human in vitro models of neural tissue with tunable microenvironment and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing inside granular gels holds great promise as it allows precise patterning of extremely soft tissue constructs. However, granular printing support formulations are restricted to only a handful of materials. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, Authors present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise and programmable patterning of human stem cells and consequent generation mature subtype-specific neurons that extend projections into the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular-like channels. Due to its modularity and versatility, SHAPE biomanufacturing toolbox has potential to be used in applications beyond functional modeling of mechanically sensitive neural constructs.
Original languageEnglish
Article numbere2201392
JournalAdvanced Science
Volume9
Issue number25
Number of pages13
ISSN2198-3844
DOIs
Publication statusPublished - 2022

Keywords

  • Embedded 3D printing
  • Granular gels
  • Microgels
  • Neural stem cells
  • Neural tissue engineering

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