3D Culturing of Stem Cells and Progenitors for Reproducible Differentiation and Tissue Engineering

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Generation and control of three dimensional (3D) niche environments in a highly reproducible platform is necessary to optimize tissue engineering with stem cells for translational biomedical applications. The differentiation of human pluripotent stem cells through embryoid body (EB) formation is used to evaluate pluripotency potential in vitro and provides a common precursor for lineage differentiation and organoid formation. Although in the stem cell field the current norm is to allow EBs to spontaneously form by non-templated methods, their formation by different groups is far from uniform and results in EB populations that are often of mixed or inappropriate size and shape dependent on the degree of EB fusion events. Applying tools of nanotechnology we generated lithography-templated arrays coated with polydimethylsiloxane (LTA-PDMS grids) as a seeding platform for human embryonic stem cells (hESCs) as 2D cell clusters or as 3D early aggregates. A lithography-based templating method offers high throughput generation of EBs of controllable shape and size and a means to track 3D aggregate cell formation through time-lapse analysis in this optically clear template. The size of human EBs is critical to differentiation timing and efficiency, which has also been observed with mouse ESCs.  By further combining EB pre-templating with an additional post-patterning step we are able to ensure uniform settling of EBs, an additional parameter that can affect statistical analysis, thus providing a powerful set of tools to evaluate and optimize differentiation factors and gradients using more homogeneously formed EBs. The internal core structure of EBs varies dependent on their size and is revealed by confocal microscopy and serial microtome sectioning. We are applying these tools and lithography-based approaches to optimize in vitro platforms for tumor formation and reprogramming studies in cancer research, in tissue engineering with 3D-initiated lineage progenitors, and in multicellular co-cultures. Our approach offers an exciting new strategy for studying cell aggregates by enabling better monitoring and control of single and multi-cellular 3D environments.