Materials Characterization & Preparation Center, Southern University of Science and Technology, Shenzhen 518055, China.
Department of Urology and Center of Urology, The First Affiliated Hospital of Xiamen University, Xiamen 361003, China.
J Proteomics. 2018 Mar 1;174:9-16. doi: 10.1016/j.jprot.2017.12.014. Epub 2017 Dec 24.
Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery.
Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application, because the usage of small sample amounts makes blood testing much less invasive, the fully integrated sample preparation by the SISPROT technology greatly improve sample preparation throughput and reproducibility, and the scan feature of DIA method provides a way to convert nonrenewable clinical specimens into permanent digital proteome maps which could be easily reanalyzed.
基于质谱(MS)的血清蛋白质组分析由于其蛋白质丰度的高度复杂性和动态范围而极具挑战性。开发高通量和准确的血清蛋白质组分析方法,能够分析大样本量,对于生物标志物的发现是非常迫切的。在此,我们报告了一种从 1μL 血清中快速准确进行蛋白质组分析的简化工作流程。该工作流程结合了一种用于高度敏感和可重现样品制备的集成技术和一种新的基于数据非依赖性采集(DIA)的 MS 方法。与标准的数据依赖性采集(DDA)方法相比,优化的 DIA 方法使检测到的肽和蛋白质数量增加了一倍,且重现性更好。无需蛋白质免疫耗竭和预分级,单次运行 DIA 分析可在 50 分钟的梯度时间内定量分析超过 300 种蛋白质。定量的蛋白质跨越五个数量级的丰度范围,包含超过 50 个 FDA 批准的疾病标志物。该工作流程允许我们每天分析 20 个血清样本,每个样本可鉴定约 358 个蛋白质组。对肾细胞癌(RCC)血清样本的概念验证研究证实了该工作流程用于大规模血清蛋白质组分析和疾病相关生物标志物发现的可行性。
血清或血浆是临床蛋白质组学研究的主要标本,但由于其高度复杂性,分析极具挑战性。过去,为了最大限度地提高蛋白质鉴定数量,已经做了很多血清蛋白质组学的工作,而很少关注高通量和重现性。在此,我们建立了一种快速、稳健且高重现性的基于 DIA 的工作流程,用于从 1μL 血清中进行简化的血清蛋白质组分析。该工作流程不需要蛋白质耗尽和预分级,同时仍能准确检测与疾病相关的蛋白质。该工作流程在临床应用中很有前景,因为使用小样本量使血液检测的侵入性大大降低,SISPROT 技术的完全集成样品制备极大地提高了样品制备的通量和重现性,并且 DIA 方法的扫描功能为将不可再生的临床标本转化为易于重新分析的永久数字蛋白质组图谱提供了一种方法。