A systems mechanobiology model to predict cardiac reprogramming outcomes on different biomaterials

Biomaterials. 2018 Oct:181:280-292. doi: 10.1016/j.biomaterials.2018.07.036. Epub 2018 Jul 28.


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.

Keywords: Heart regeneration; Mechanotransduction; Reprogramming; Systems biology.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Biocompatible Materials / pharmacology*
  • Calcium / metabolism
  • Cells, Cultured
  • Cellular Reprogramming / drug effects
  • Dimethylpolysiloxanes / chemistry
  • Extracellular Matrix / chemistry
  • Mechanotransduction, Cellular / drug effects
  • Mice
  • Systems Biology / methods*


  • Biocompatible Materials
  • Dimethylpolysiloxanes
  • baysilon
  • Calcium