Tracking and Predicting Human Somatic Cell Reprogramming Using Nuclear Characteristics.
Tracking and Predicting Human Somatic Cell Reprogramming Using Nuclear Characteristics.
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DOI：
10.1016/j.bpj.2019.10.014
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发表时间：
2019-10
影响因子：
3.4
通讯作者：
Kaivalya Molugu;Ty Harkness;Jared Carlson-Stevermer;Ryan Prestil;Nicole J. Piscopo;Stephanie K Seymour;G. Knight;R. Ashton;Krishanu Saha
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文献类型：
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作者：
Kaivalya Molugu;Ty Harkness;Jared Carlson-Stevermer;Ryan Prestil;Nicole J. Piscopo;Stephanie K Seymour;G. Knight;R. Ashton;Krishanu Saha
将人类体细胞重编程为诱导多能干细胞（iPSC）为疾病建模，毒理学，细胞治疗和再生医学提供了宝贵的资源。然而，重编程过程可能是随机和低效的，除了完全重编程的iPSC之外，还产生许多部分重编程的中间体和非重编程的细胞。在重编程期间鉴定、评估和富集iPSC的许多工作依赖于固定、破坏或单一化细胞培养物的方法，从而破坏每个细胞的微环境。在这里，我们开发了一种微图案化的基底，可以对数百个正在进行重编程的细胞亚群进行动态活细胞显微镜检查，同时保留细胞微环境中的许多生物物理和生物化学线索。在这种基质上，我们能够在对来自健康供体的皮肤活检和抽血的人体细胞进行重编程的过程中，观察并物理地将细胞限制在离散的岛屿中。使用高含量分析，我们确定了八个核特征的组合，这些特征可用于生成计算模型，以预测重编程的进展，并将部分重编程的细胞与完全重编程的细胞区分开来。这种使用微图案化基底原位跟踪重编程的方法可以帮助生物制造治疗相关的iPSC，并用于阐明伴随人类细胞命运转变的多尺度细胞变化（细胞-细胞相互作用以及亚细胞变化）。
Reprogramming of human somatic cells to induced pluripotent stem cells (iPSCs) generates valuable resources for disease modeling, toxicology, cell therapy, and regenerative medicine. However, the reprogramming process can be stochastic and inefficient, creating many partially reprogrammed intermediates and non-reprogrammed cells in addition to fully reprogrammed iPSCs. Much of the work to identify, evaluate, and enrich for iPSCs during reprogramming relies on methods that fix, destroy, or singularize cell cultures, thereby disrupting each cell's microenvironment. Here, we develop a micropatterned substrate that allows for dynamic live-cell microscopy of hundreds of cell subpopulations undergoing reprogramming while preserving many of the biophysical and biochemical cues within the cells' microenvironment. On this substrate, we were able to both watch and physically confine cells into discrete islands during the reprogramming of human somatic cells from skin biopsies and blood draws obtained from healthy donors. Using high-content analysis, we identified a combination of eight nuclear characteristics that can be used to generate a computational model to predict the progression of reprogramming and distinguish partially reprogrammed cells from those that are fully reprogrammed. This approach to track reprogramming in situ using micropatterned substrates could aid in biomanufacturing of therapeutically relevant iPSCs and be used to elucidate multiscale cellular changes (cell-cell interactions as well as subcellular changes) that accompany human cell fate transitions.