Related Experiment Video For Aptamer
Updated: Oct 6, 2025

Harnessing the DNA Dye-triggered Side Population Phenotype to Detect and Purify Cancer Stem Cells from Biological Samples
Published on: May 10, 2017
Translating cancer exosomes detection into the color change of phenol red based on target-responsive DNA
Xianjuan Shen1, Siyi Wang1, Qian Lu1
1Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, 226001, China.
Abstract:
Emerging evidence indicates that exosomes can be used as a potential biomarker for monitoring diseases, including cancer. However, enhancing the sensing performance in terms of convenience and sensitivity remains an urgent demand for exosomes detection. In this study, a pH-sensitive colorimetric biosensing strategy was developed for exosomes detection by integrating stimuli-responsive DNA microcapsules and acetylcholinesterase to produce acetic acid. The constructed DNA microcapsules consisted of DNA shells crosslinked by anti-CD63 aptamers and loaded with acetylcholinesterase. With exosomes addition, an energetically stabilized aptamer-CD63 compound was produced and microcapsules dissociated due to the reaction of surface protein CD63 of exosomes and aptamer of CD63, resulting in the release of encapsulated AChE. Through a simple centrifugation separation, unreacted DNA microcapsules were removed and the supernatant containing released acetylcholinesterase collected, which was then used for colorimetric exosomes detection through the ability of acetylcholinesterase to hydrolyze acetylcholine to release acetic acid. The resulting decreased solution pH was detected with phenol red indicator, with the sharp color transition conveniently by naked eye. Exosomes quantification was also achieved using the solution's absorption intensity ratio of 558 vs. 432 nm. The linear range was from 2.0 × 103 to 5.0 × 105 particles/μL, and the limit of detection and limit of quantification were 1.2 × 103 particles/μL and 2.2 × 103 particles/μL, respectively. In addition, this proposed strategy for exosomes detection showed a relative standard deviation of 3.1% and high recovery efficiency (>94%), exhibiting a bright application future in exsomes analysis.

