Amplification-Free Attomolar Detection of Short Nucleic Acids with Upconversion Luminescence: Eliminating Nonspecific Binding by Hybridization Complex Transfer

化学 核酸 发光 核酸热力学 核酸定量 生物化学 DNA 基序列 光电子学 物理
作者
Jakub Máčala,Saara Kuusinen,Satu Lahtinen,Hans H. Gorris,Petr Skládal,Zdeněk Farka,Tero Soukka
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:97 (3): 1775-1782
标识
DOI:10.1021/acs.analchem.4c05401
摘要

The anti-Stokes emission of photon upconversion nanoparticles (UCNPs) facilitates their use as labels for ultrasensitive detection in biological samples as infrared excitation does not induce autofluorescence at visible wavelengths. The detection of extremely low-abundance analytes, however, remains challenging as it is impossible to completely avoid nonspecific binding of label conjugates. To overcome this limitation, we developed a novel hybridization complex transfer technique using UCNP labels to detect short nucleic acids directly without target amplification. The assay involves capturing the target-label complexes on an initial solid phase, then using releasing oligonucleotides to specifically elute only the target-UCNP complexes and recapturing them on another solid phase. The nonspecifically adsorbed labels remain on the first solid phase, enabling background-free, ultrasensitive detection. When magnetic microparticles were used as the first solid phase in a sample volume of 120 μL, the assay achieved a limit of detection (LOD) of 310 aM, a 27-fold improvement over the reference assay without transfer. Moreover, the additional target-specific steps introduced in the complex transfer procedure improved the sequence specificity of the complex transfer assay compared with the reference assay. The suitability for clinical analysis was confirmed using spiked plasma samples, resulting in an LOD of 190 aM. By increasing the sample volume to 600 μL and using magnetic preconcentration, the LOD was improved to 46 aM. These results highlight the importance of background elimination in achieving ultralow LODs for the analysis of low-abundance biomarkers.
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