Tandem mass tag (TMT)-based mass spectrometry (MS) enables deep proteomic profiling of more than 10,000 proteins in complex biological samples but requires up to 100 μg protein in starting materials during a standard analysis. Here, we present a streamlined protocol to quantify more than 9000 proteins with 0.5 μg protein per sample by 16-plex TMT coupled with two-dimensional liquid chromatography and tandem mass spectrometry (LC/LC–MS/MS). In this protocol, we optimized multiple conditions to reduce sample loss, including processing each sample in a single tube to minimize surface adsorption, increasing digestion enzymes to shorten proteolysis and function as carriers, eliminating a desalting step between digestion and TMT labeling, and developing miniaturized basic pH LC for prefractionation. By profiling 16 identical human brain tissue samples of Alzheimer’s disease (AD), vascular dementia (VaD), and non-dementia controls, we directly compared this new microgram-scale protocol to the standard-scale protocol, quantifying 9116 and 10,869 proteins, respectively. Importantly, bioinformatics analysis indicated that the microgram-scale protocol had adequate sensitivity and reproducibility to detect differentially expressed proteins in disease-related pathways. Thus, this newly developed protocol is of general application for deep proteomics analysis of biological and clinical samples at sub-microgram levels.

中文翻译：

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通过串联质谱标签质谱法对微克级蛋白质组进行深度分析

基于串联质谱标签 (TMT) 的质谱 (MS) 可以对复杂生物样品中的 10,000 多种蛋白质进行深度蛋白质组学分析，但在标准分析过程中，起始材料中需要多达 100 μg 的蛋白质。在这里，我们提出了一个简化的协议，通过 16 重 TMT 结合二维液相色谱和串联质谱 (LC/LC-MS/MS) 来量化超过 9000 种蛋白质，每个样品含有 0.5 μg 蛋白质。在该协议中，我们优化了多种条件以减少样品损失，包括在单个管中处理每个样品以最大程度地减少表面吸附，增加消化酶以缩短蛋白水解并充当载体，消除消化和 TMT 标记之间的脱盐步骤，以及开发小型化用于预分馏的碱性 pH LC。通过分析 16 个相同的阿尔茨海默病 (AD)、血管性痴呆 (VaD) 和非痴呆症对照人脑组织样本，我们直接将这种新的微克级方案与标准级方案进行了比较，分别量化了 9116 和 10,869 种蛋白质. 重要的是，生物信息学分析表明，微克级方案具有足够的灵敏度和可重复性来检测疾病相关途径中的差异表达蛋白质。因此，这一新开发的协议普遍适用于亚微克级生物和临床样本的深度蛋白质组学分析。生物信息学分析表明，微克级方案具有足够的灵敏度和可重复性来检测疾病相关途径中的差异表达蛋白质。因此，这一新开发的协议普遍适用于亚微克级生物和临床样本的深度蛋白质组学分析。生物信息学分析表明，微克级方案具有足够的灵敏度和可重复性来检测疾病相关途径中的差异表达蛋白质。因此，这一新开发的协议普遍适用于亚微克级生物和临床样本的深度蛋白质组学分析。