Surface enhanced Raman spectroscopy based immunosensor for ultrasensitive and selective detection of wild type p53 and mutant p53R175H

多路复用 化学 突变体 表面增强拉曼光谱 生物传感器 胶体金 拉曼光谱 生物结合 检出限 抗原 纳米颗粒 纳米技术 分子生物学 拉曼散射 色谱法 组合化学 生物化学 基因 材料科学 生物 生物信息学 物理 遗传学 光学
作者
Anna Rita Bizzarri,Ilaria Moscetti,Salvatore Cannistraro
出处
期刊:Analytica Chimica Acta [Elsevier BV]
卷期号:1029: 86-96 被引量:30
标识
DOI:10.1016/j.aca.2018.04.049
摘要

p53 is a powerful transcription factor playing a pivotal role in the prevention of cancer development and in maintaining genome integrity. This oncosuppressor is found to be functionally inactivated by mutations in many human tumors. Accordingly, wild type p53 and its oncogenic mutants represent valuable cancer biomarkers for diagnostic and prognostic purposes. We developed a highly sensitive biosensor, based on Surface Enhanced Raman Spectroscopy, for detection of wild type p53 and of p53R175H, which is one of the most frequent tumor-associated mutants of p53. Our approach combines the huge Raman signal enhancement, mainly arising from the plasmonic resonance effect on molecules close to gold nanoparticles, with the antigen-antibody biorecognition specificity. By following the enhanced signal of a specific Raman marker, intrinsic to the nanoparticle-antibody bioconjugation, we were able to push the antigen detection level down to the attomolar range in buffer and to the femtomolar range in spiked human serum. The method demonstrated a high reproducibility and a remarkable selectivity in discriminating between wild type p53 and p53R175H mutant, in both buffer and serum. A calibration plot was built and validated by ELISA for a reliable quantification of p53. These findings entitle our SERS-based immunosensor as a powerful and reliable tool for a non-invasive screening in human serum targeting p53 network. The approach could be easily extended to ultrasensitive detection of other markers of general interest, with feasible implementations into multiplex assays, functioning as lab-on-chip devices for several applications.

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