Automated optimization of endoderm differentiation on chip†
Abstract
Human induced pluripotent stem cells (hiPSCs) can serve as an unlimited source to rebuild organotypic tissues in vitro. Successful engineering of functional cell types and complex organ structures outside the human body requires knowledge of the chemical, temporal, and spatial microenvironment of their in vivo counterparts. Despite an increased understanding of mouse and human embryonic development, screening approaches are still required for the optimization of stem cell differentiation protocols to gain more functional mature cell types. The liver, lung, pancreas, and digestive tract originate from the endoderm germ layer. Optimization and specification of the earliest differentiation step, which is the definitive endoderm (DE), is of central importance for generating cell types of these organs because off-target cell types will propagate during month-long cultivation steps and reduce yields. Here, we developed a microfluidic large-scale integration (mLSI) chip platform for combined automated three-dimensional (3D) cell culturing and high-throughput imaging to investigate anterior/posterior patterns occurring during hiPSC differentiation into DE cells. Integration of 3D cell cultures with a diameter of 150 μm was achieved using a U-shaped pneumatic membrane valve, which was geometrically optimized and fluidically characterized. Upon parallelization of 32 fluidically individually addressable cell culture unit cells with a total of 128 3D cell cultures, complex and long-term DE differentiation protocols could be automated. Real-time bright-field imaging was used to analyze cell growth during DE differentiation, and immunofluorescence imaging on optically cleared 3D cell cultures was used to determine the DE differentiation yield. By systematically alternating transforming growth factor β (TGF-β) and WNT signaling agonist concentrations and temporal stimulation, we showed that even under similar DE differentiation yields, there were patterning differences in the 3D cell cultures, indicating possible differentiation differences between established DE protocols. The automated mLSI chip platform with the general analytical workflow for 3D stem cell cultures offers the optimization of in vitro generation of various cell types for cell replacement therapies.