Litcius/Paper detail

Highly parallelized human embryonic stem cell differentiation to cardiac mesoderm in nanoliter chambers on a microfluidic chip

Anke R. Vollertsen, Simone A. ten Den, Verena Schwach, Albert van den Berg, Robert Passier, Andries D. van der Meer, Mathieu Odijk

2021Biomedical Microdevices13 citationsDOIOpen Access PDF

Abstract

Abstract Human stem cell-derived cells and tissues hold considerable potential for applications in regenerative medicine, disease modeling and drug discovery. The generation, culture and differentiation of stem cells in low-volume, automated and parallelized microfluidic chips hold great promise to accelerate the research in this domain. Here, we show that we can differentiate human embryonic stem cells (hESCs) to early cardiac mesodermal cells in microfluidic chambers that have a volume of only 30 nanoliters, using discontinuous medium perfusion. 64 of these chambers were parallelized on a chip which contained integrated valves to spatiotemporally isolate the chambers and automate cell culture medium exchanges. To confirm cell pluripotency, we tracked hESC proliferation and immunostained the cells for pluripotency markers SOX2 and OCT3/4. During differentiation, we investigated the effect of different medium perfusion frequencies on cell reorganization and the expression of the early cardiac mesoderm reporter MESP1 mCherry by live-cell imaging. Our study demonstrates that microfluidic technology can be used to automatically culture, differentiate and study hESC in very low-volume culture chambers even without continuous medium perfusion. This result is an important step towards further automation and parallelization in stem cell technology.

Topics & Concepts

Embryonic stem cellSOX2Cell biologyStem cellMesodermMicrofluidicsCellular differentiationBiologyInduced pluripotent stem cellRegenerative medicineCell cultureBiomedical engineeringNanotechnologyMaterials scienceGeneticsMedicineGene3D Printing in Biomedical ResearchPluripotent Stem Cells ResearchNeuroscience and Neural Engineering