ICP-MS and fluorescence dual-mode detection of ZIKV-RNA based on quantum dot labeling with hybridization chain
Tianran Zhang1, Chao Huang2, Yanni Jiao3
1Shandong Academy of Preventive Medicine, Shandong Center for Food Safety Risk Assessment, Shandong Center for Disease Control and Prevention, Jinan, 250000, People's Republic of China; Department of Physical and Chemical Inspection, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250000, People's Republic of China; Yantai Center for Disease Control and Prevention, Yantai, 264000, People's Republic of China.
Abstract:
The detection of Zika virus (ZIKV) is of great significance to human life and health. Herein, we presented an ICP-MS and fluorescent dual-mode sensor for quantitative analysis of Zika virus RNA fragments (ZIKV-RNA), which employed quantum dots (QDs) as signal tags and combined with hybridization chain reaction (HCR). The dual-mode sensor realized cross-checking of the analysis results and improved the assay accuracy. Firstly, the single-stranded DNA (ssDNA) was anchored on the surface of magnetic beads (MBs). Afterward, HCR was conducted with probe DNA-CdSe quantum dots conjugates (pDNA-QDs) and link DNA (lDNA), producing the MBs-ssDNA-[pDNA-QDs-lDNA]n conjugates. In the presence of target ZIKV-RNA, a strand displacement reaction occurred, leading to the dissociation of the [pDNA-QDs-lDNA]n labels from the conjugates into the solution. Finally, the signal intensity was detected using ICP-MS and fluorescence analysis, with achieved limits of detection of 131 pM and 152 pM, respectively. The inter-assay RSD values of fluorescence and ICP-MS were 3.94 % and 4.26 % at 10 nM level, respectively, showing that the method had good precision. This method showed high selectivity and was applied to the analysis of biological fluids. There was no significant difference between the results of ICP-MS modes and fluorescence mode. This method offers a new strategy for sensitivity analysis of ZIKV-RNA and exhibits promise in clinical applications for diagnosis.


