Quantifying and controlling the proteolytic degradation of cell adhesion peptides
Peptides are widely used within biomaterials to improve cell adhesion, incorporate bioactive ligands, and enable cell-mediated degradation of the matrix. While many of the peptides incorporated into biomaterials are intended to be present throughout the life of the material, their stability is not typically quantified during culture. In this work we designed a series of peptide libraries containing four different N-terminal peptide functionalizations and three C-terminal functionalization to better understand how simple modifications can be used to reduce non-specific degradation of peptides. We tested these libraries with three cell types commonly used in biomaterials research, including mesenchymal stem/stromal cells (hMSCs), endothelial cells, and macrophages, and quantified how these cell types non-specifically degraded peptide as a function of terminal amino acid and chemistry. We found that peptides in solution which contained N-terminal amines were almost entirely degraded by 48 hours, irrespective of the terminal amino acid, and that degradation occurred even at high peptide concentrations. Peptides with C-terminal carboxylic acids also had significant degradation when cultured with cells. We found that simple modifications to the termini could significantly reduce or completely abolish non-specific degradation when soluble peptides were added to cells cultured on tissue culture plastic or within hydrogel matrices, and that functionalizations which mimicked peptide conjugations to hydrogel matrices significantly slowed non-specific degradation. We also found that there were minimal differences across cell donors, and that sequences mimicking different peptides commonly-used to functionalized biomaterials all had significant non-specific degradation. Finally, we saw that there was a positive trend between RGD stability and hMSC spreading within hydrogels, indicating that improving the stability of peptides within biomaterial matrices may improve the performance of engineered matrices.