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

Publication ,  Journal Article
Jung, JP; Moyano, JV; Collier, JH
Published in: Integrative biology : quantitative biosciences from nano to macro
March 2011

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.

Duke Scholars

Published In

Integrative biology : quantitative biosciences from nano to macro

DOI

EISSN

1757-9708

ISSN

1757-9694

Publication Date

March 2011

Volume

3

Issue

3

Start / End Page

185 / 196

Related Subject Headings

  • Tissue Scaffolds
  • Rheology
  • Platelet Endothelial Cell Adhesion Molecule-1
  • Peptides
  • Peptide Fragments
  • Oligopeptides
  • Microscopy, Electron, Transmission
  • Ligands
  • Least-Squares Analysis
  • Laminin
 

Citation

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Jung, J. P., Moyano, J. V., & Collier, J. H. (2011). Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices. Integrative Biology : Quantitative Biosciences from Nano to Macro, 3(3), 185–196. https://doi.org/10.1039/c0ib00112k
Jung, Jangwook P., José V. Moyano, and Joel H. Collier. “Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices.Integrative Biology : Quantitative Biosciences from Nano to Macro 3, no. 3 (March 2011): 185–96. https://doi.org/10.1039/c0ib00112k.
Jung JP, Moyano JV, Collier JH. Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices. Integrative biology : quantitative biosciences from nano to macro. 2011 Mar;3(3):185–96.
Jung, Jangwook P., et al. “Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices.Integrative Biology : Quantitative Biosciences from Nano to Macro, vol. 3, no. 3, Mar. 2011, pp. 185–96. Epmc, doi:10.1039/c0ib00112k.
Jung JP, Moyano JV, Collier JH. Multifactorial optimization of endothelial cell growth using modular synthetic extracellular matrices. Integrative biology : quantitative biosciences from nano to macro. 2011 Mar;3(3):185–196.
Journal cover image

Published In

Integrative biology : quantitative biosciences from nano to macro

DOI

EISSN

1757-9708

ISSN

1757-9694

Publication Date

March 2011

Volume

3

Issue

3

Start / End Page

185 / 196

Related Subject Headings

  • Tissue Scaffolds
  • Rheology
  • Platelet Endothelial Cell Adhesion Molecule-1
  • Peptides
  • Peptide Fragments
  • Oligopeptides
  • Microscopy, Electron, Transmission
  • Ligands
  • Least-Squares Analysis
  • Laminin