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Click Chemistry-Based Quantification of Extracellular Matrix Turnover for Drug Screening and Regenerative Medicine
Journal article   Open access   Peer reviewed

Click Chemistry-Based Quantification of Extracellular Matrix Turnover for Drug Screening and Regenerative Medicine

Annie Porter, Songshan Fan, Ying Peng, Mengxi Lv, Yilu Zhou, Abdulaziz Alanazi, Lin Han, Liyun Wang and X. Lucas Lu
Annals of biomedical engineering, Forthcoming
12 May 2026
PMID: 42120803
url
https://doi.org/10.1007/s10439-026-04152-3View
Published, Version of Record (VoR) Open

Abstract

Bioanalytical Chemistry Organocatalysis Proteolysis Mass Spectrometry
Purpose To develop and validate a bioorthogonal labeling approach for quantifying ECM remodeling in living cell and tissue culture systems. Methods Strain-promoted azide-alkyne (SPAAC) reactions, or copper-free click chemistry, were used to fluorescently label newly synthesized glycan and protein matrix components. ECM synthesis and degradation was quantified in cartilage explants, human mesenchymal stem cells, and SKBR3 breast cancer cells under various external stimuli, including inflammation, mechanical stimulus, and drug treatment. Results The click chemistry method reliable quantified ECM turnover across platforms. It detected reduced glycan and protein synthesis after 24-hour inflammatory challenge and enabled longitudinal tracking of ECM degradation in cartilage explants. The technique demonstrated high sensitivity, measuring increased ECM deposition by ~ 10,000 human mesenchymal stem cells in 12-hour intervals and substrate stiffness-dependent synthesis by SKBR3 cells. Additionally, the approach supported osteoarthritis drug screening by identifying compounds that mitigated inflammation-induced ECM degradation. Conclusion Compared to traditional biochemical or histological assays, the click chemistry-based technique provides higher sensitivity, reduced sample requirements, and improved temporal resolution for quantifying ECM turnover. Its versatility enables broad application in tissue engineering, regenerative medicine, disease modeling, and high-throughput drug evaluation.

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