4.7 Article

Human Induced Pluripotent Stem Cell-Derived Neural Progenitor Cells Produce Distinct Neural 3D In Vitro Models Depending on Alginate/Gellan Gum/Laminin Hydrogel Blend Properties

期刊

ADVANCED HEALTHCARE MATERIALS
卷 10, 期 16, 页码 -

出版社

WILEY
DOI: 10.1002/adhm.202100131

关键词

alternative methods; bioprinting; brain spheres; extracellular matrix; human induced pluripotent stem cells; neurospheres; spheroids

资金

  1. Center for Advanced Imaging (CAi) at the Heinrich Heine University Dusseldorf
  2. Bayer AG
  3. DFG (FOR2795 Synapses under Stress) [Ro2327/13-1]
  4. Projekt DEAL

向作者/读者索取更多资源

The study introduces two alginate/gellan gum/laminin (ALG/GG/LAM) hydrogel blends for creating 3D neural models using human induced pluripotent stem cells (hiPSCs). The stiffness, stress relaxation of the gel blends, as well as the cell differentiation strategy, were found to influence the development of the 3D models. The embedded hiNPCs differentiated into neurons and astrocytes within the gel blends, showing potential for various applications in disease modeling and substance screenings.
Stable and predictive neural cell culture models are a necessary premise for many research fields. However, conventional 2D models lack 3D cell-material/-cell interactions and hence do not reflect the complexity of the in vivo situation properly. Here two alginate/gellan gum/laminin (ALG/GG/LAM) hydrogel blends are presented for the fabrication of human induced pluripotent stem cell (hiPSC)-based 3D neural models. For hydrogel embedding, hiPSC-derived neural progenitor cells (hiNPCs) are used either directly or after 3D neural pre-differentiation. It is shown that stiffness and stress relaxation of the gel blends, as well as the cell differentiation strategy influence 3D model development. The embedded hiNPCs differentiate into neurons and astrocytes within the gel blends and display spontaneous intracellular calcium signals. Two fit-for-purpose models valuable for i) applications requiring a high degree of complexity, but less throughput, such as disease modeling and long-term exposure studies and ii) higher throughput applications, such as acute exposures or substance screenings are proposed. Due to their wide range of applications, adjustability, and printing capabilities, the ALG/GG/LAM based 3D neural models are of great potential for 3D neural modeling in the future.

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