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

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.

Automated summary

In this study, a dark-field microscopy visual single-particle detection scheme was developed to accurately evaluate telomerase activity. The method involved the attachment of telomerase substrate primer to magnetic beads, which were then hybridized with complementary DNA modified with gold nanoparticles. The telomerase activity was quantitatively measured by visually counting bright spots based on dark-field microscopy. This strategy showed excellent sensitivity and specificity and has the potential to be a powerful tool in early and noninvasive diagnosis of bladder cancer.