High-content image-based profiling for evaluating the effect of peptide coating effect on medical devices

Jun 28, 2022, 11:50 AM
Room: S2

Room: S2


Sugiyama, Ayato (Graduate School of Pharmaceutical Sciences, Nagoya University )


"[Introduction] In recent years, biomolecules have been used to functionalize the surface of scaffold materials to support tissue engineering applications. For the functionalized surface for enhancing the cell culture efficiency, peptide coating has been one of the major strategies to provide surface property mimicking the extracellular matrix (ECM). In the past days, the cell adhesion triggered by such surface modification molecules had been mainly understood through the ligand-receptor interactions, such as integrin recognition mechanisms. On the other side, recent mechanobiology studies have revealed that cells are attracted and recognize more varieties of scaffold surface parameters, such as physicochemical properties. Proteoglycan-associated cell interactions are one of such cell-surface interactions. However, compared to the integrin-mediated adhesions, such cell-surface interactions triggered by physicochemical properties have not yet been clarified, since there are too many parameters to investigate. In order to understand the complex combinational effect of physicochemical parameters on the cell adhesion surface, we focused to examine the effect of peptide-coated surfaces, since peptides are functionalization molecules that can be designed in a combinatorial manner. Our research group has successfully obtained several cell-selective adhesion peptides and osteogenesis-promoting peptides by peptide array screening and has been carrying out research on peptide-based materials with high functionality [1,2]. In addition, we have previously reported that amino acids on the surface of materials can change cell adhesion [3]. In this study, we investigated to evaluate the combinatorial effect of peptide and amino acid-coated surfaces by the introduction of high-content image analysis.
[Methods] By combining laboratory automation technology, image processing, and peptide surface modification techniques using DOPA, we developed a new image-based profiling platform to evaluate the delicate differences of cell adhesion profiles. On the multi-well plate, we immobilized RGD peptide with and without the coating of single amino acids (20 variations) and created the surface conditions in which the neighboring physicochemical atmospheres are different with the same RGD coated surface. On such combinatorial property design surfaces, we evaluated the cell adhesion and cell extension rates by fluorescent image processing capturing cytoskeleton responses.
[Results and conclusions] From our data, we found that the surface physicochemical properties created by amino acid coating drastically changed the RGD peptide functionalization effect, and therefore lead us to find the optimum surface property condition to maximize the peptide effect for cell adhesion. Our results suggest that the control of physicochemical property design can empower and stabilize the surface functionalization of cell culture scaffolds.

  1. Kanie, K., et al. Biotech. Bioeng. 109(7), 1808-1816 (2012)
  2. Kanie, K., et al. Materials 9(9), 730 (2016)
  3. Kanie, K., et al. J. Pept. Sci. 17(6), 479-486 (2011)"


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