Medizinisches Proteom-Center (MPC) Medical Faculty, Ruhr-University Bochum, Bochum, Germany.
Medical Proteome Analysis, Center for Proteindiagnostics (PRODI) Ruhr-University Bochum, Bochum, Germany.
Methods Mol Biol. 2021;2228:283-292. doi: 10.1007/978-1-0716-1024-4_20.
A label-free approach based on a highly reproducible and stable workflow allows for quantitative proteome analysis . Due to advantages compared to labeling methods, the label-free approach has the potential to measure unlimited samples from clinical specimen monitoring and comparing thousands of proteins. The presented label-free workflow includes a new sample preparation technique depending on automatic annotation and tissue isolation via FTIR-guided laser microdissection, in-solution digestion, LC-MS/MS analyses, data evaluation by means of Proteome Discoverer and Progenesis software, and verification of differential proteins. We successfully applied this workflow in a proteomics study analyzing human cystitis and high-grade urothelial carcinoma tissue regarding the identification of a diagnostic tissue biomarker. The differential analysis of only 1 mm of isolated tissue cells led to 74 significantly differentially abundant proteins.
一种基于高度可重现和稳定工作流程的无标记方法可实现定量蛋白质组分析。与标记方法相比，无标记方法具有测量来自临床标本监测和比较数千种蛋白质的无限样本的潜力。所提出的无标记工作流程包括一种新的样品制备技术，该技术依赖于自动注释和组织分离，通过 FTIR 引导的激光显微切割、溶液内消化、LC-MS/MS 分析、使用 Proteome Discoverer 和 Progenesis 软件进行数据评估，以及对差异蛋白进行验证。我们成功地将此工作流程应用于一项蛋白质组学研究中，该研究分析了人类膀胱炎和高级尿路上皮癌组织，以鉴定诊断性组织生物标志物。仅对 1mm 分离的组织细胞进行差异分析，就导致了 74 种显著差异丰度的蛋白质。
