Towards Early Prediction of Human iPSC Reprogramming Success

This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenerative cell therapies.The minuscule success rate of iPSC-reprogramming of around $0.01$ to $0.1$ makes it labor-intensive, time-consuming, and exorbitantly expensive to generate a stable iPSC line. Since that requires culturing of millions of cells and intense biological scrutiny of multiple clones to identify a single optimal clone. The ability to reliably predict which cells are likely to establish as an optimal iPSC line at an early stage of pluripotency would therefore be ground-breaking in rendering this a practical and cost-effective approach to personalized medicine. Temporal information about changes in cellular appearance over time is crucial for predicting its future growth outcomes. In order to generate this data, we first performed continuous time-lapse imaging of iPSCs in culture using an ultra-high resolution microscope. We then annotated the locations and identities of cells in late-stage images where reliable manual identification is possible. Next, we propagated these labels backwards in time using a semi-automated tracking system to obtain labels for early stages of growth. Finally, we used this data to train deep neural networks to perform automatic cell segmentation and classification. Our code and data are available at https://github.com/abhineet123/ipsc_prediction.Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:01

Suspension culture improves iPSC expansion and pluripotency phenotype

Abstract Background Induced pluripotent stem cells (iPSCs) offer potential to revolutionize regenerative medicine as a renewable source for islets, dopaminergic neurons, retinal cells, and cardiomyocytes. However, translation of these regenerative cell therapies requires cost-efficient mass manufacturing of high-quality human iPSCs. This study presents an improved three-dimensional Vertical-Wheel® bioreactor (3D suspension) cell expansion protocol with comparison to a two-dimensional (2D planar) protocol. Methods Sendai virus transfection of human peripheral blood mononuclear cells was used to establish mycoplasma and virus free iPSC lines without common genetic duplications or deletions. iPSCs were then expanded under 2D planar and 3D suspension culture conditions. We comparatively evaluated cell expansion capacity, genetic integrity, pluripotency phenotype, and in vitro and in vivo pluripotency potential of iPSCs. Results Expansion of iPSCs using Vertical-Wheel® bioreactors achieved 93.8-fold (IQR 30.2) growth compared to 19.1 (IQR 4.0) in 2D (p  25). 2D-cultured cells displayed a primed pluripotency phenotype, which transitioned to naïve after 3D-culture. Both 2D and 3D cells were capable of trilineage differentiation and following teratoma, 2D-expanded cells generated predominantly solid teratomas, while 3D-expanded cells produced more mature and predominantly cystic teratomas with lower Ki67+ expression within teratomas (3D: 16.7% [IQR 3.2%] vs.. 2D: 45.3% [IQR 3.0%], p = 0.002) in keeping with a naïve phenotype. Conclusion This study demonstrates nearly 100-fold iPSC expansion over 5-days using our 3D suspension culture protocol in Vertical-Wheel® bioreactors, the largest cell growth reported to date. 3D expanded cells showed enhanced in vitro and in vivo pluripotency phenotype that may support more efficient scale-up strategies and safer clinical implementation