Controlled Self-assembly of Stem Cell Aggregates Instructs Pluripotency and Lineage Bias. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Xie, Angela; Binder, Bernard; Khalil, Andrew; Schmitt, Samantha; Johnson, Hunter; Zacharias, Nicholas; Murphy, William
• Is Part Of: Scientific reports. Volume 7:Issue 1(2017)
• Page Start: 1
• Page End: 15
• Publication Date: 2017-12
• Subjects: Natural history -- Research -- Periodicals; Biology -- Research -- Periodicals; Physical sciences -- Research -- Periodicals; Earth sciences -- Research -- Periodicals; Environmental sciences -- Research -- Periodicals; 502.85
• DOI: 10.1038/s41598-017-14325-9
• Languages: English
• ISSNs: 2045-2322

Abstract

Abstract 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.