A systems mechanobiology model to predict cardiac reprogramming outcomes on different biomaterials.
A systems mechanobiology model to predict cardiac reprogramming outcomes on different biomaterials.
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DOI：
10.1016/j.biomaterials.2018.07.036
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发表时间：
2018-10
期刊：
影响因子：
14
通讯作者：
Putnam AJ
中科院分区：
文献类型：
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作者：
Kong YP;Rioja AY;Xue X;Sun Y;Fu J;Putnam AJ
在正常发育过程中，细胞外基质（ECM）以机械和生物化学方式调节细胞命运。然而，ECM对谱系重编程的影响是未知的，谱系重编程是细胞的发育周期逆转以获得祖细胞样细胞状态，随后分化成所需细胞表型的过程。使用ECM的材料模拟物，在这里，我们表明，配体身份，配体密度和底物模量调节间接心脏重编程效率，但没有单独与表型结果的预测方式。或者，我们开发了一个数据驱动的模型，使用偏最小二乘回归将短期细胞状态（由对不同材料环境的定量机械敏感反应定义）与表型的长期变化联系起来。该模型通过准确预测不同材料平台上的重编程结果进行了验证。总的来说，这些发现表明了一种快速筛选候选生物材料的方法，这些材料支持高效率的重编程，而无需使细胞经历整个重编程过程。
During normal development, the extracellular matrix (ECM) regulates cell fate mechanically and biochemically. However, the ECM’s influence on lineage reprogramming, a process by which a cell’s developmental cycle is reversed to attain a progenitor-like cell state followed by subsequent differentiation into a desired cell phenotype, is unknown. Using a material mimetic of the ECM, here we show that ligand identity, ligand density, and substrate modulus modulate indirect cardiac reprogramming efficiency, but were not individually correlated with phenotypic outcomes in a predictive manner. Alternatively, we developed a data-driven model using partial least squares regression to relate short-term cell states, defined by quantitative mechanosensitive responses to different material environments, with long-term changes in phenotype. This model was validated by accurately predicting the reprogramming outcomes on a different material platform. Collectively, these findings suggest a means to rapidly screen candidate biomaterials that support reprogramming with high efficiency, without subjecting cells to the entire reprogramming process.
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影响因子：
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作者：
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通讯作者：
Srivastava, Deepak
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通过对心脏转录因子的非肌细胞进行重编程通过重编程。
影响因子：
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作者：
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通讯作者：
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