A visualized automatic particle counting strategy for single-cell level telomerase activity quantification

Li, Chen1; Chen, Hui1; Fan, Tingting1; Zhao, Jingru1; Ding, Zheng2,3,4; Lin, Zeyu2,3,4; Sun, Shuqing1; Tan, Chunyan1; Liu, Feng1; Jiang, Hongtao2,3,4; Tan, Ying1

2023-03-01

10.1002/VIW.20220078

VIEW   Impact Factor & Quartile

2688-3988

2688-268X

The accurate evaluation of telomerase activity, a typical cancer biomarker, is vital for early cancer screening. In this study, we developed a dark-field microscopy (DFM) visual single-particle detection scheme to detect telomerase activity based on automatic counting gold nanoparticles (AuNPs). This method started with attaching the telomerase substrate (TS) primer to the magnetic beads (MBs) through streptavidin-biotin interaction. In the presence of telomerase and dNTPs, the TS primer was expanded with (TTAGGG)(n) repeat units to form the telomerase extension product (MBs-telomerase extension product), which could be hybridized with the complementary DNA (cDNA) modified with AuNPs through Au-S bonds (AuNPs-SH-cDNA). After magnetic separation and DNA double-strand unwinding, AuNPs were collected from the supernatant, and the telomerase activity was quantitatively measured by visually counting bright spots based on DFM. This strategy achieved a limit of detection as low as 1 HeLa cell and distinguished telomerase activity among different cell lines, thus verifying its excellent sensitivity and specificity. Further, two common telomerase inhibitors (BIBR1532 and curcumin) were screened with the consistent IC50 values with other methods, respectively. It is worth mentioning that this strategy can clearly identify bladder cancer among various urinary diseases. Consequently, the visualized automatic particle counting strategy is potential as a powerful tool in early and noninvasive diagnosis of bladder cancer.

bladder cancer dark-field microscopy telomerase activity visualized automatic particle counting

ESCI

English

Corresponding

National Key R&DProgram of China, Synthetic BiologyResearch[2019YFA0905900] ; Shenzhen Municipal government[JCYJ20220530142812029]

Science & Technology - Other Topics ; Materials Science

Nanoscience & Nanotechnology ; Materials Science, Biomaterials

WOS:000942741200001

WILEY

Web of Science

1.Tsinghua Univ, Shenzhen Int Grad Sch, State Key Lab Chem Oncogen, Shenzhen, Peoples R China
2.Jinan Univ, Shenzhen Peoples Hosp, Dept Urol, Clin Med Coll 2, Shenzhen, Guangdong, Peoples R China
3.Southern Univ Sci & Technol, Affiliated Hosp 1, Shenzhen, Guangdong, Peoples R China
4.Shenzhen Peoples Hosp, Shenzhen Engn & Technol Ctr Minimally Invas Urol, Shenzhen, Peoples R China

Li, Chen,Chen, Hui,Fan, Tingting,et al. A visualized automatic particle counting strategy for single-cell level telomerase activity quantification[J]. VIEW,2023.

Li, Chen.,Chen, Hui.,Fan, Tingting.,Zhao, Jingru.,Ding, Zheng.,...&Tan, Ying.(2023).A visualized automatic particle counting strategy for single-cell level telomerase activity quantification.VIEW.

Li, Chen,et al."A visualized automatic particle counting strategy for single-cell level telomerase activity quantification".VIEW (2023).