1. Terminal deoxynucleotidyl transferase (TdT) based template-free signal amplification for the detection of exosomes in MUC1-positive cells.
- Author
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Fu W, Yang K, Wu M, and Wang Y
- Subjects
- Humans, Metal Nanoparticles chemistry, Gold chemistry, A549 Cells, Colorimetry methods, Limit of Detection, Cell Line, Tumor, Biosensing Techniques methods, Tetraspanin 30 metabolism, Tetraspanin 30 analysis, Biomarkers, Tumor metabolism, Sensitivity and Specificity, Exosomes metabolism, Mucin-1 metabolism, Mucin-1 analysis, DNA Nucleotidylexotransferase metabolism, Aptamers, Nucleotide
- Abstract
The Mucin1 (MUC1) protein, involved in cytoprotective and signaling pathways, is abnormally elevated in various cancers, making it a key cancer indicator. Exosomes, which reflect the status of their originating cells, offer potential for cancer diagnosis. Thus, developing a method to detect MUC1-positive exosomes is crucial for the early diagnosis of certain cancers. In this study, we developed a highly sensitive, specific, and simple UV-visible signal amplification method to detect MUC1-positive exosomes using terminal deoxynucleotidyl transferase (TdT). Initially, exosomes were captured on magnetic beads using a CD63 aptamer(apt). The Primer-AuNPs-MUC1 apt complex which we synthesized by low pH loading method was then attached MUC1 proteins on the surface of the exosomes to create a sandwich structure. TdT catalyzed the extension of Biotin-dATP at the 3' end of the primer, introducing multiple biotin sites into the sandwich structure. These sites subsequently bound multiple streptavidin-horseradish peroxidase (streptavidin-HRP), which catalyzed the oxidative color change of the substrate, which can be detected by colorimetric method. This method can detect A549 exosomes in the range of 1.4E+6 to 4.2E+8 particles/mL and shows high specificity for cell lines with different MUC1 expression. Additionally, it successfully distinguished cholangiocarcinoma (CCA) patients (n=11) from healthy individuals (n=7) in clinical serum assays, demonstrating good performance in real sample detection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)
- Published
- 2025
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