AUTHOR=Ma Zhiyao , Toledo Marcelo Augusto Szymanskide , Wanek Paul , Elsafi Mabrouk Mohamed H. , Smet Francis , Pulak Rock , Pieske Simon , Piotrowski Tobias , Herfs Werner , Brecher Christian , Schmitt Robert H. , Wagner Wolfgang , Zenke Martin TITLE=Cell Cluster Sorting in Automated Differentiation of Patient-specific Induced Pluripotent Stem Cells Towards Blood Cells JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.755983 DOI=10.3389/fbioe.2022.755983 ISSN=2296-4185 ABSTRACT=

Induced pluripotent stem cells (iPS cells) represent a particularly versatile stem cell type for a large array of applications in biology and medicine. Taking full advantage of iPS cell technology requires high throughput and automated iPS cell culture and differentiation. We present an automated platform for efficient and robust iPS cell culture and differentiation into blood cells. We implemented cell cluster sorting for analysis and sorting of iPS cell clusters in order to establish clonal iPS cell lines with high reproducibility and efficacy. Patient-specific iPS cells were induced to differentiate towards hematopoietic cells via embryoid body (EB) formation. EB size impacts on iPS cell differentiation and we applied cell cluster sorting to obtain EB of defined size for efficient blood cell differentiation. In summary, implementing cell cluster sorting into the workflow of iPS cell cloning, growth and differentiation represent a valuable add-on for standard and automated iPS cell handling.