Proteomic Identification and Quantification of Secretory Proteins in Human Dermal Fibroblast-Conditioned Medium for Wound Repair and Hair Regeneration

Abstract

Background

Human dermal fibroblasts secrete numerous growth factors and proteins that have been suggested to promote wound repair and hair regeneration.

Methods

Human dermal fibroblast-conditioned medium (DFCM) was prepared, and proteomic analysis was performed. Secretory proteins in DFCM were identified using 1-dimensional sodium dodecyl sulphate-polyacrylamide gel electrophoresis, in-gel trypsin protein digestion, and quantitative liquid chromatography tandem mass spectrometry (LC-MS/MS). Identified proteins were analyzed using bioinformatic methods for the classification and evaluation of protein–protein interactions.

Results

Using LC-MS/MS, 337 proteins were identified in DFCM. Among them, 160 proteins were associated with wound repair, and 57 proteins were associated with hair regeneration. Protein–protein interaction network analysis of 160 DFCM proteins for wound repair at the highest confidence score (0.9) revealed that 110 proteins were grouped into seven distinctive interaction networks. Additionally, protein–protein interaction network analysis of 57 proteins for hair regeneration at the highest confidence score revealed that 29 proteins were grouped into five distinctive interaction networks. The identified DFCM proteins were associated with several pathways for wound repair and hair regeneration, including epidermal growth factor receptor, fibroblast growth factor, integrin, Wnt, cadherin, and transforming growth factor-β signaling pathways.

Conclusion

DFCM contains numerous secretory proteins that comprise groups of protein–protein interaction networks that regulate wound repair and hair regeneration.

Keywords:

• human dermal fibroblast
• dermal fibroblast-conditioned media
• proteomic analysis
• secretory protein
• wound repair
• hair regeneration

Data Sharing Statement

Data supporting the findings of this study are available upon request from the corresponding author. The data are not publicly available because of privacy and ethical restrictions.

Acknowledgments

We would like to thank Dr. Yeol-Gyun Lee, PhD (PROTEINWORKS Co., Ltd., Daejeon, Korea) for assistance in performing proteomic analysis. Keun Jae Ahn was supported by the 2022 Scientific Promotion Program funded by Jeju National University.

Author Contributions

All authors have made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis, and interpretation, or in all these areas; took part in drafting, revising, or critically reviewing the manuscript; gave final approval of the version to be published; agreed on the journal to which the manuscript would be submitted; and agreed to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no conflicts of interest.

Additional information

Funding

There is no funding to report.