Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices.

Journal Article

Extracellular matrices (ECMs) are complex materials, containing at least dozens of different macromolecules that are assembled together, thus complicating their optimization towards applications in 3D cell culture or tissue engineering. The natural complexity of ECMs has limited cell-matrix investigations predominantly to experiments where only one matrix component is adjusted at a time, making it difficult to uncover interactions between different matrix components or to efficiently determine optimal matrix compositions for specific desired biological responses. Here we have developed modular synthetic ECMs based on peptide self-assembly whose incorporation of multiple different peptide ligands can be adjusted. The peptides can co-assemble in a wide range of combinations to form hydrogels of uniform morphology and consistent mechanical properties, but with precisely varied mixtures of peptide ligands. The modularity of this system in turn enabled multi-factorial experimental designs for investigating interactions between these ligands and for determining a multi-peptide matrix formulation that maximized endothelial cell growth. In cultures of HUVECs, we observed a previously unknown antagonistic interaction between the laminin-derived peptide YIGSR and RGDS-mediated cell attachment and growth. We also identified an optimized combination of self-assembled peptides bearing the ligands RGDS and IKVAV that led to endothelial cell growth equivalent to that on native full-length fibronectin. Both of these findings would have been challenging to uncover using more traditional one-factor-at-a-time analyses.

Full Text

Duke Authors

Cited Authors

  • Jung, JP; Moyano, JV; Collier, JH

Published Date

  • March 2011

Published In

Volume / Issue

  • 3 / 3

Start / End Page

  • 185 - 196

PubMed ID

  • 21249249

Electronic International Standard Serial Number (EISSN)

  • 1757-9708

International Standard Serial Number (ISSN)

  • 1757-9694

Digital Object Identifier (DOI)

  • 10.1039/c0ib00112k

Language

  • eng