Suppr超能文献

用于单细胞和纳克级样品定量蛋白质组分析的液相色谱和质谱方法

Liquid Chromatographic and Mass Spectrometric Methods for Quantitative Proteomic Analysis from Single-Cell and Nanogram-Level Samples.

作者信息

Wang Yuefan, Woo Jongmin, Sun Zhenyu, Assis Diego, Kirsch Zachary, Willetts Matthew, Albano Matthew, Liu Hongyi, Pienta Kenneth J, Amend Sarah R, Zhang Hui

机构信息

Department of Pathology, Johns Hopkins University, Baltimore, Maryland 21231, United States.

Bruker Scientific, Billerica, Massachusetts 01821, United States.

出版信息

Anal Chem. 2025 Sep 2;97(34):18415-18422. doi: 10.1021/acs.analchem.5c02808. Epub 2025 Jul 25.

Abstract

Liquid chromatography (LC) and mass spectrometry (MS) are two critical components in proteomics. Advances in methods for both LC and MS have significantly enhanced protein identification and quantifications of limited amounts of proteins, particularly at the picogram-to-nanogram level of proteins. In this study, we explored various LC conditions and MS platforms to optimize protein identification and quantification using data-independent acquisition (DIA). Our investigation focused on evaluating the sensitivity for protein identification, reproducibility of quantification, and robustness across multiple models, specifically focused on analyzing proteins at pico- to nanogram levels, with an emphasis on single-cell proteomics. We further applied our approach for the proteomic analysis of HeLa single cells. Overall, we identified and quantified over 6300 proteins at the single-cell level amount of peptides with a coefficient of variation (CV) of less than 20%, and detected up to 5000 proteins from isolated single HeLa cell samples. Finally, we analyzed docetaxel-treated and nontreated PC3 cells to reveal proteome changes at the single-cell level. This study provides a comprehensive technical evaluation for LC-MS methods in protein identification and quantification for analytical applications involving single-cell proteomics from the picogram to nanogram level of proteins.

摘要

液相色谱(LC)和质谱(MS)是蛋白质组学中的两个关键组成部分。LC和MS方法的进展显著提高了蛋白质鉴定和对少量蛋白质的定量能力,特别是在皮克到纳克水平的蛋白质定量方面。在本研究中,我们探索了各种LC条件和MS平台,以利用数据非依赖采集(DIA)优化蛋白质鉴定和定量。我们的研究重点是评估蛋白质鉴定的灵敏度、定量的重现性以及在多个模型中的稳健性,特别关注皮克到纳克水平蛋白质的分析,重点是单细胞蛋白质组学。我们进一步将我们的方法应用于HeLa单细胞的蛋白质组学分析。总体而言,我们在单细胞水平上鉴定和定量了超过6300种蛋白质,肽段的变异系数(CV)小于20%,并从分离的单个HeLa细胞样本中检测到多达5000种蛋白质。最后,我们分析了多西他赛处理和未处理的PC3细胞,以揭示单细胞水平的蛋白质组变化。本研究为LC-MS方法在蛋白质鉴定和定量中的应用提供了全面的技术评估,适用于从皮克到纳克水平蛋白质的单细胞蛋白质组学分析应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6770/12405731/fda4b65194c5/nihms-2101242-f0001.jpg

相似文献

本文引用的文献

2
Harnessing technologies to unravel gastric cancer heterogeneity.利用技术揭示胃癌异质性。
Trends Cancer. 2025 Aug;11(8):753-769. doi: 10.1016/j.trecan.2025.04.011. Epub 2025 May 27.
7
The rise of single-cell proteomics.单细胞蛋白质组学的兴起。
Anal Sci Adv. 2021 Feb 1;2(3-4):84-94. doi: 10.1002/ansa.202000152. eCollection 2021 Apr.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验