Department of Laboratory Medicine and Pathology, University of Minnesota School of Medicine, Minneapolis, Minnesota 55455, United States.
Microbiology, Immunology, and Cancer Biology Graduate Program, University of Minnesota School of Medicine, Minneapolis, Minnesota 55455, United States.
J Am Soc Mass Spectrom. 2024 Nov 6;35(11):2659-2669. doi: 10.1021/jasms.4c00131. Epub 2024 Sep 12.
Serum contains several proteins that are associated with disease-related processes. Mass spectrometry (MS)-based proteomics approaches greatly facilitate serum protein biomarker development. However, the serum proteome complexity presents a technical challenge for the accurate, sensitive, and reproducible quantification of proteins by MS. Thus, efficient sample preparation methods are of critical importance for serum proteome analyses. In this study, we evaluated the technical performance of two serum proteome sample preparation methods using sera from patients with high-grade serous ovarian cancer and patients with benign nongynecological conditions with a goal of providing insight into their compatibility with clinical proteomics workflows. One method entailed the use of immobilized trypsin (SMART Digest Trypsin) with RapiGest SF, an acid-labile surfactant designed to enhance the in-solution enzymatic digestion of proteins. The other method incorporated a commercially available sample preparation kit, iST-BCT, which contains standardized reagents. Significantly higher protein sequence coverage, albeit with lower digestion efficiency, was obtained with the immobilized trypsin + RapiGest SF workflow, whereas the iST-BCT workflow was quicker and had marginally better reproducibility. Protein relative abundance analysis revealed that the serum proteomes clustered primarily by the sample processing workflow and secondarily by disease state. We conducted a time course study to determine whether differences in the relative abundance of diagnostic high-grade serous ovarian cancer serum protein biomarker candidates were biased according to the duration of enzymatic digestion. Our results highlight the importance of optimizing enzymatic digestion kinetics according to the peptide targets of interest while considering the sensitivity of the downstream analytical method utilized in clinical proteomics workflows designed to measure biomarkers.
血清中含有几种与疾病相关过程相关的蛋白质。基于质谱（MS）的蛋白质组学方法极大地促进了血清蛋白质生物标志物的开发。然而，血清蛋白质组的复杂性给 MS 对蛋白质进行准确、灵敏和可重复定量带来了技术挑战。因此，高效的样品制备方法对于血清蛋白质组分析至关重要。在这项研究中，我们评估了两种血清蛋白质组样品制备方法的技术性能，使用了来自高级别浆液性卵巢癌患者和良性非妇科疾病患者的血清，旨在深入了解它们与临床蛋白质组学工作流程的兼容性。一种方法涉及使用固定化胰蛋白酶（SMART Digest Trypsin）与 RapiGest SF，这是一种酸不稳定的表面活性剂，旨在增强蛋白质在溶液中的酶解。另一种方法采用了一种市售的样品制备试剂盒 iST-BCT，其中包含标准化试剂。虽然消化效率较低，但固定化胰蛋白酶+RapiGest SF 工作流程获得了更高的蛋白质序列覆盖率，而 iST-BCT 工作流程更快，重现性略好。蛋白质相对丰度分析表明，血清蛋白质组主要按样品处理工作流程聚类，其次按疾病状态聚类。我们进行了一个时间过程研究，以确定诊断高级别浆液性卵巢癌血清蛋白质生物标志物候选物的相对丰度差异是否根据酶解时间而产生偏差。我们的结果强调了根据感兴趣的肽靶优化酶解动力学的重要性，同时考虑到用于测量生物标志物的临床蛋白质组学工作流程中使用的下游分析方法的灵敏度。
