Department of Laboratory Medicine, Lund, Division of Occupational and Environmental Medicine, Lund University, SE-221 85 Lund, Sweden.
J Proteome Res. 2013 Jan 4;12(1):234-47. doi: 10.1021/pr300802g. Epub 2012 Dec 14.
Proteomic-based studies of nasal lavage fluid (NLF) may identify molecular pathways associated with disease pathology and new biomarker candidates of upper airway diseases. However, most studies have used rather tedious untargeted MS techniques. Selected reaction monitoring (SRM) is a sensitive and specific technique that can be used with high throughput. In this study, we developed a semiquantitative SRM-based method targeting 244 NLF proteins. The protein set was identified through a literature study in combination with untargeted LC-MS/MS analyses of trypsin-digested NLF samples. The SRM assays were designed using MS/MS data either downloaded from a proteomic data repository or experimentally obtained. Each protein is represented by one to five peptides, resulting in 708 SRM assays. Three to four transitions per assay were used to ensure analyte specificity. The majority (69%) of the assays showed good within-day precision (coefficient of variation ≤ 20%). The accuracy of the method was evaluated by analyzing four samples prepared with varying amounts of four proteins. Peptide and protein ratios were in good agreement with expected ratios. In conclusion, a high throughput screening method for relative quantification of 244 NLF proteins was developed. The method should be of general use in any proteomic study of the upper airways.
基于蛋白质组学的鼻洗液（NLF）研究可能会确定与疾病病理相关的分子途径，并发现上呼吸道疾病的新生物标志物候选物。然而，大多数研究都使用了相当繁琐的非靶向 MS 技术。选择反应监测（SRM）是一种敏感且特异性的技术，可用于高通量分析。在本研究中，我们开发了一种针对 244 种 NLF 蛋白的半定量 SRM 方法。该蛋白组是通过文献研究与胰蛋白酶消化的 NLF 样本的非靶向 LC-MS/MS 分析相结合来鉴定的。SRM 分析是使用从蛋白质组学数据存储库下载的 MS/MS 数据或通过实验获得的数据来设计的。每个蛋白质由一个到五个肽代表，共产生 708 个 SRM 分析。每个分析使用三到四个跃迁以确保分析物的特异性。大多数（69％）分析的日内精密度良好（变异系数≤20％）。通过分析用四种蛋白质的不同量制备的四个样品来评估方法的准确性。肽和蛋白质的比率与预期的比率非常吻合。总之，开发了一种用于相对定量分析 244 种 NLF 蛋白的高通量筛选方法。该方法应可普遍用于上呼吸道的任何蛋白质组学研究。
