Jalali-Yazdi Farzad, Corbin Jasmine M, Takahashi Terry T, Roberts Richard W
3710 McClintock Avenue, RTH 507, Los Angeles, California 90089-2905, United States.
Anal Chem. 2014 May 20;86(10):4715-22. doi: 10.1021/ac500084d. Epub 2014 May 2.
A major benefit of proteomic and genomic data is the potential for developing thousands of novel diagnostic and analytical tests of cells, tissues, and clinical samples. Monoclonal antibody technologies, phage display and mRNA display, are methods that could be used to generate affinity ligands against each member of the proteome. Increasingly, the challenge is not ligand generation, rather the analysis and affinity rank-ordering of the many ligands generated by these methods. Here, we developed a quantitative method to analyze protein interactions using in vitro translated ligands. In this assay, in vitro translated ligands generate a signal by simultaneously binding to a target immobilized on a magnetic bead and to a sensor surface in a commercial acoustic sensing device. We then normalize the binding of each ligand with its relative translation efficiency in order to rank-order the different ligands. We demonstrate the method with peptides directed against the cancer marker Bcl-xL. Our method has 4- to 10-fold higher sensitivity, using 100-fold less protein and 5-fold less antibody per sample, as compared directly with ELISA. Additionally, all analysis can be conducted in complex mixtures at physiological ionic strength. Lastly, we demonstrate the ability to use peptides as ultrahigh affinity reagents that function in complex matrices, as would be needed in diagnostic applications.
蛋白质组学和基因组学数据的一个主要优势在于,有潜力开发数千种针对细胞、组织和临床样本的新型诊断和分析测试。单克隆抗体技术、噬菌体展示和mRNA展示,是可用于生成针对蛋白质组中每个成员的亲和配体的方法。越来越多的挑战不在于配体的生成,而是对这些方法产生的众多配体进行分析和亲和排序。在此,我们开发了一种使用体外翻译配体分析蛋白质相互作用的定量方法。在该测定中,体外翻译的配体通过同时结合固定在磁珠上的靶标和商业声学传感装置中的传感器表面来产生信号。然后,我们将每个配体的结合与其相对翻译效率进行归一化,以便对不同的配体进行排序。我们用针对癌症标志物Bcl-xL的肽展示了该方法。与ELISA直接相比,我们的方法灵敏度高4至10倍,每个样品使用的蛋白质少100倍,抗体少5倍。此外,所有分析都可以在生理离子强度的复杂混合物中进行。最后,我们展示了使用肽作为在复杂基质中起作用的超高亲和力试剂的能力,这是诊断应用中所需要的。