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About this Research Topic

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Background

Human pluripotent stem cells (PSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), can self-renew indefinitely, and differentiate into any cell type in the body. Intensive research in the past two decades that exploited the properties of PSCs has opened up new frontiers of basic and translational biomedical research. Human PSCs have enabled the modeling of disease pathogenesis in the human context, and have helped to illuminate mechanisms of monogenic disease, complex disease, cancer, and, most recently, emerging infectious disease such as COVID-19. Lately, the striking ability of PSCs to self-organize has engendered three-dimension (3D) models of human development (e.g., blastoids, gastruloids, assembloids, and organoids), which have hitherto remained a black box to mechanistic studies. Genome editing technology, whose development has intertwined with that of PSCs, has become an integral and synergistic component of PSC-based models by providing, for examples, isogenic controls, lineage tracing reporters, and genome-wide genetic screens. Human PSC models aided by genome editing technologies and single-cell OMICs analysis (scRNA-seq, scATAC-seq, CUT&TAG, spatial transcriptomics, etc.) promise to deliver unprecedented insights into human development and disease pathogenesis, which serve as the basis for future precision therapies.

Many challenges remain to be addressed before the full potentials of human PSC models can be realized. This Research Topic is aimed at identifying and tackling some of the roadblocks to the use of stem cell-based models in basic and translational research. For example, the 2D and 3D stem cell models generally suffer from low differentiation efficiency and high experimental variability. There is an urgent need for best practice guidelines and evaluation standards to ensure reproducibility of results obtained from different models. Advances in bioengineering methods for monitoring and controlling cellular environments (pCO2, pO2, pH, substrate stiffness, and hydrodynamic forces) are expected to improve cellular differentiation and reproducibility. Such new methods will go hand in hand with mechanistic studies aimed at understanding the sources of experimental variability (e.g., inter-variability among iPSC lines derived from different donors and intra-variability among iPSC clones derived from the same donor) and together they can help to standardize differentiation protocols for future clinical translation. The recent revelation of various untended genotoxic effects of genome editing tools has implications in the interpretation of experimental findings and the safety of genome edited stem cells in the clinic. New methods and mechanistic studies aimed at characterizing and understanding the side effects of genome editing (e.g., on-target large deletions and complex rearrangements, chromosomal loss, and off-target effects), respectively, will be of broad interest to the field. Exciting research advances at the above-mentioned fronts will undoubtedly improve the translational values of stem cell models.

We welcome contributions, from Original Research to Review Articles, that cover advances (not limited to) the following areas:
• Effects of culture environmental factors (gases, pH, and mechanical factors) on the differentiation, maturation, and survival of 2D and 3D stem cell models;
• Method to monitor and evaluate 2D and 3D stem cell models;
• Methods to control culture environments or to improve cellular performance by engineering stem cell models;
• Heterogeneity, variability, and reproducibility of 2D and 3D stem cell models;
• Methods to characterize unintended genotoxic effects of genome editing tools;
• Development of new stem cell-based models of early human development and diseases;
• High-throughput sequencing and computational approaches to study human development and disease.



Dr. Ying Gu is employed by BGI-Research, all other Topic Editors declare no conflicts of interest.

Research Topic Research topic image

Keywords: stem cells models, 2D stem cell models, 3D stem cell models, pluripotent stem cells

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