Controlled Self-assembly of Stem Cell Aggregates Instructs Pluripotency and Lineage Bias

Stem cell-derived organoids and other 3D microtissues offer enormous potential as models for drug screening, disease modeling, and regenerative medicine. Formation of stem/progenitor cell aggregates is common in biomanufacturing processes and critical to many organoid approaches. However, reproducib...

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Veröffentlicht in:Scientific reports 2017-10, Vol.7 (1), p.14070-15, Article 14070
Hauptverfasser: Xie, Angela W., Binder, Bernard Y. K., Khalil, Andrew S., Schmitt, Samantha K., Johnson, Hunter J., Zacharias, Nicholas A., Murphy, William L.
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Sprache:eng
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Zusammenfassung:Stem cell-derived organoids and other 3D microtissues offer enormous potential as models for drug screening, disease modeling, and regenerative medicine. Formation of stem/progenitor cell aggregates is common in biomanufacturing processes and critical to many organoid approaches. However, reproducibility of current protocols is limited by reliance on poorly controlled processes (e.g., spontaneous aggregation). Little is known about the effects of aggregation parameters on cell behavior, which may have implications for the production of cell aggregates and organoids. Here we introduce a bioengineered platform of labile substrate arrays that enable simple, scalable generation of cell aggregates via a controllable 2D-to-3D “self-assembly”. As a proof-of-concept, we show that labile substrates generate size- and shape-controlled embryoid bodies (EBs) and can be easily modified to control EB self-assembly kinetics. We show that aggregation method instructs EB lineage bias, with faster aggregation promoting pluripotency loss and ectoderm, and slower aggregation favoring mesoderm and endoderm. We also find that aggregation kinetics of EBs markedly influence EB structure, with slower kinetics resulting in increased EB porosity and growth factor signaling. Our findings suggest that controlling internal structure of cell aggregates by modifying aggregation kinetics is a potential strategy for improving 3D microtissue models for research and translational applications.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-017-14325-9