Department of Proteomics, KTH-Royal Institute of Technology, Albanova University Center, Stockholm, Sweden.
J Proteomics. 2009 Dec 1;73(2):252-66. doi: 10.1016/j.jprot.2009.09.009. Epub 2009 Sep 23.
In recent years, affinity-based technologies have become important tools for serum profiling to uncover protein expression patterns linked to disease state or therapeutic effects. In this study, we describe a path towards the production of an antibody microarray to allow protein profiling of biotinylated human serum samples with reproducible sensitivity in the picomolar range. With the availability of growing numbers of affinity reagents, protein profiles are to be validated in efficient manners and we describe a cross-platform strategy based on data concordance with a suspension bead array to interrogate the identical set of antibodies with the same cohort of serum samples. Comparative analysis enabled to screen for high-performing antibodies, which were displaying consistent results across the two platforms and targeting known serum components. Moreover, data processing methods such as sample referencing and normalization were evaluated for their effects on inter-platform agreement. Our work suggests that mutual validation of protein expression profiles using alternative microarray platforms holds great potential in becoming an important and valuable component in affinity-based high-throughput proteomic screenings as it allows to narrow down the number of discovered targets prior to orthogonal, uniplexed validation approaches.
近年来,基于亲和力的技术已成为血清分析中揭示与疾病状态或治疗效果相关的蛋白质表达模式的重要工具。在这项研究中,我们描述了一种生产抗体微阵列的方法,该方法可用于对生物素化人血清样本进行蛋白质分析,具有皮摩尔级别的可重现灵敏度。随着越来越多的亲和试剂的出现,需要以有效的方式验证蛋白质图谱,我们描述了一种基于数据一致性的跨平台策略,该策略基于悬浮珠阵列来检测相同的抗体组合与相同的血清样本集。比较分析可筛选出表现一致且针对已知血清成分的高表现抗体。此外,还评估了样品参考和归一化等数据处理方法对平台间一致性的影响。我们的工作表明,使用替代微阵列平台对蛋白质表达谱进行相互验证,在基于亲和力的高通量蛋白质组筛选中具有很大的潜力,因为它可以在进行正交、单重验证方法之前,缩小发现目标的数量。