血液中低丰度蛋白的单纳米颗粒成像传感方法研究

Quantitative analysis of disease related proteins in blood is critical for personal precision medicine. Concentrations of the disease related proteins in blood are usually in the range of aM to pM. Routine clinical assay and quantitative proteomics cannot detect these proteins because the limit of detection is above the protein abundance. Protein sensors developed in research labs are able to detect the disease related proteins at the above level in simple matrix, but fail to detect the proteins in blood. Nonspecific adsorption can produce signal like target protein. This reduces the sensitivity and reproducibility of the sensors, and makes it difficult to use in clinics. The key to achieve quantitative analysis of rare proteins in blood is to distinguish signal origin. In view of this, using Au nanoparticle labeled detection antibody and aptamer of immune complex as probes, the dimer of Au nanoparticles can be formed through twice recognition of target protein. By criterion of the spectrum switching to that of the Au nanoparticle dimer, the signal from nonspecific adsorption can be identified and thus removed. An ultra-sensitive, highly reproducible, and prospectively commercial platform can be established using 3 cancer related low-abundance proteins as models. This paves the way for precision medicine.

准确测量血样中与疾病相关蛋白质的含量是个体化精准医疗的要求。这些蛋白质通常是低丰度蛋白（含量在aM-pM之间）。常规临床方法和定量蛋白质组学的灵敏度低，无法检测到血样中低丰度蛋白。实验室开发的蛋白传感器在简单溶液中满足检测要求。但在血样中，由于非特异性吸附的蛋白可产生与目标蛋白相似的信号，传感器的灵敏度和重现性均大幅下降，难以用于临床检测。因此，构建信号来源的甄别策略是实现血样中低丰度蛋白定量的关键。鉴于此，本项目拟以三种癌症相关的低丰度蛋白为具体对象，通过金纳米颗粒标记的核酸适配体与同样标记的免疫复合物的1:1亲和，形成局域表面等离子体共振耦合的金纳米颗粒二聚体。以金颗粒二聚体与单体在单分子水平上散射光谱的切换为依据，实现目标蛋白与非特异性吸附蛋白的甄别，进而消除非特异性吸附蛋白在定量上的影响。本项目的完成有望构建一个超灵敏、重现性好的血样中低丰度蛋白质的定量平台，为个性化诊疗打下基础。

以单颗粒光谱成像为手段，发展了多种区分目标物诱导生成的纳米颗粒团聚体与游离单个纳米颗粒的方法。在此基础上，开发了三种单种蛋白质均相免疫传感器、一种同时测定两种蛋白质的均相免疫传感器、一种同时测定三种蛋白质的均相免疫传感器、一种测定循环肿瘤DNA的传感器。上述测定蛋白质的传感器一是灵敏度高，比如单组分传感器和三组分同时测定传感器的检测限低至0.2fM；二是操作简单，仅需混合探针与样品即可完成检测。由此可见，开发的蛋白质传感器在常规临床应用上的潜力极大。部分研究成果以第一作者或通讯作者发表在Analytical Chemical、Chemical Communications、ACS Sensors等期刊上（6篇），获批了1项发明专利。