• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

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

用于高通量蛋白质组学的磷酸酪氨酸肽自动富集

Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.

作者信息

Chang Alexis, Leutert Mario, Rodriguez-Mias Ricard A, Villén Judit

机构信息

Department of Genome Sciences, University of Washington, Seattle WA 98195, USA.

出版信息

bioRxiv. 2023 Jan 6:2023.01.05.522335. doi: 10.1101/2023.01.05.522335.

DOI:10.1101/2023.01.05.522335
PMID:36711935
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9881991/
Abstract

Phosphotyrosine (pY) enrichment is critical for expanding fundamental and clinical understanding of cellular signaling by mass spectrometry-based proteomics. However, current pY enrichment methods exhibit a high cost per sample and limited reproducibility due to expensive affinity reagents and manual processing. We present rapid-robotic phosphotyrosine proteomics (R2-pY), which uses a magnetic particle processor and pY superbinders or antibodies. R2-pY handles 96 samples in parallel, requires 2 days to go from cell lysate to mass spectrometry injections, and results in global proteomic, phosphoproteomic and tyrosine specific phosphoproteomic samples. We benchmark the method on HeLa cells stimulated with pervanadate and serum and report over 4000 unique pY sites from 1 mg of peptide input, strong reproducibility between replicates, and phosphopeptide enrichment efficiencies above 99%. R2-pY extends our previously reported R2-P2 proteomic and global phosphoproteomic sample preparation framework, opening the door to large-scale studies of pY signaling in concert with global proteome and phosphoproteome profiling.

摘要

通过基于质谱的蛋白质组学来扩展对细胞信号传导的基础和临床理解,磷酸酪氨酸(pY)富集至关重要。然而,由于昂贵的亲和试剂和手工操作,目前的pY富集方法每个样本成本高昂且重现性有限。我们提出了快速机器人磷酸酪氨酸蛋白质组学(R2-pY)方法,该方法使用磁性颗粒处理器和pY超结合剂或抗体。R2-pY可并行处理96个样本,从细胞裂解物到质谱进样只需2天,并能生成整体蛋白质组、磷酸蛋白质组和酪氨酸特异性磷酸蛋白质组样本。我们在用过氧钒酸盐和血清刺激的HeLa细胞上对该方法进行了基准测试,结果表明,输入1毫克肽可鉴定出4000多个独特的pY位点,重复样本间重现性良好,磷酸肽富集效率超过99%。R2-pY扩展了我们之前报道的R2-P2蛋白质组学和整体磷酸蛋白质组样本制备框架,为与整体蛋白质组和磷酸蛋白质组分析协同进行pY信号传导的大规模研究打开了大门。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/4282f2f4cbb1/nihpp-2023.01.05.522335v1-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/a0473783e430/nihpp-2023.01.05.522335v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/e218c8055b43/nihpp-2023.01.05.522335v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/151540dec7e6/nihpp-2023.01.05.522335v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/e7e81746236d/nihpp-2023.01.05.522335v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/f325267e5bca/nihpp-2023.01.05.522335v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/baf45d6d6265/nihpp-2023.01.05.522335v1-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/4282f2f4cbb1/nihpp-2023.01.05.522335v1-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/a0473783e430/nihpp-2023.01.05.522335v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/e218c8055b43/nihpp-2023.01.05.522335v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/151540dec7e6/nihpp-2023.01.05.522335v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/e7e81746236d/nihpp-2023.01.05.522335v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/f325267e5bca/nihpp-2023.01.05.522335v1-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/baf45d6d6265/nihpp-2023.01.05.522335v1-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b28/9881991/4282f2f4cbb1/nihpp-2023.01.05.522335v1-f0007.jpg

相似文献

1
Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.用于高通量蛋白质组学的磷酸酪氨酸肽自动富集
bioRxiv. 2023 Jan 6:2023.01.05.522335. doi: 10.1101/2023.01.05.522335.
2
Automated Enrichment of Phosphotyrosine Peptides for High-Throughput Proteomics.自动化富集磷酸化酪氨酸肽用于高通量蛋白质组学。
J Proteome Res. 2023 Jun 2;22(6):1868-1880. doi: 10.1021/acs.jproteome.2c00850. Epub 2023 Apr 25.
3
Deep Phosphotyrosine Proteomics by Optimization of Phosphotyrosine Enrichment and MS/MS Parameters.通过优化磷酸酪氨酸富集和串联质谱参数进行深度磷酸酪氨酸蛋白质组学研究
J Proteome Res. 2017 Feb 3;16(2):1077-1086. doi: 10.1021/acs.jproteome.6b00576. Epub 2016 Dec 5.
4
Phosphotyrosine Biased Enrichment of Tryptic Peptides from Cancer Cells by Combining pY-MIP and TiO Affinity Resins.通过将 pY-MIP 和 TiO2 亲和树脂相结合,从癌细胞中进行磷酸酪氨酸偏置的胰蛋白酶肽富集。
Anal Chem. 2017 Nov 7;89(21):11332-11340. doi: 10.1021/acs.analchem.7b02091. Epub 2017 Oct 25.
5
Protein-phosphotyrosine proteome profiling by superbinder-SH2 domain affinity purification mass spectrometry, sSH2-AP-MS.通过超级结合蛋白-SH2结构域亲和纯化质谱法(sSH2-AP-MS)进行蛋白质磷酸酪氨酸蛋白质组分析。
Proteomics. 2017 Mar;17(6). doi: 10.1002/pmic.201600360. Epub 2017 Jan 17.
6
One-Step SH2 Superbinder-Based Approach for Sensitive Analysis of Tyrosine Phosphoproteome.一步法 SH2 超强黏附剂法用于酪氨酸磷酸化蛋白质组的灵敏分析
J Proteome Res. 2019 Apr 5;18(4):1870-1879. doi: 10.1021/acs.jproteome.9b00045. Epub 2019 Mar 25.
7
A Tyrosine Phosphoproteome Analysis Approach Enabled by Selective Dephosphorylation with Protein Tyrosine Phosphatase.通过蛋白酪氨酸磷酸酶选择性去磷酸化实现的酪氨酸磷酸化蛋白质组分析方法。
Anal Chem. 2022 Mar 15;94(10):4155-4164. doi: 10.1021/acs.analchem.1c03704. Epub 2022 Mar 3.
8
Rapid and reproducible single-stage phosphopeptide enrichment of complex peptide mixtures: application to general and phosphotyrosine-specific phosphoproteomics experiments.快速且可重现的单阶段复杂肽混合物磷酸肽富集:在通用和磷酸酪氨酸特异性磷酸蛋白质组学实验中的应用。
Anal Chem. 2011 Oct 15;83(20):7635-44. doi: 10.1021/ac201894j. Epub 2011 Sep 20.
9
Deep Phospho- and Phosphotyrosine Proteomics Identified Active Kinases and Phosphorylation Networks in Colorectal Cancer Cell Lines Resistant to Cetuximab.深度磷酸化和磷酸化酪氨酸蛋白质组学鉴定了对西妥昔单抗耐药的结直肠癌细胞系中的活性激酶和磷酸化网络。
Sci Rep. 2017 Sep 5;7(1):10463. doi: 10.1038/s41598-017-10478-9.
10
Deep phosphotyrosine characterisation of primary murine T cells using broad spectrum optimisation of selective triggering.利用选择性触发的广谱优化对原代小鼠T细胞进行深度磷酸酪氨酸表征。
Proteomics. 2024 Dec;24(23-24):e2400106. doi: 10.1002/pmic.202400106. Epub 2024 Aug 1.

本文引用的文献

1
Engineered SH2 Domains for Targeted Phosphoproteomics.工程化 SH2 结构域用于靶向磷酸蛋白质组学。
ACS Chem Biol. 2022 Jun 17;17(6):1472-1484. doi: 10.1021/acschembio.2c00051. Epub 2022 May 25.
2
Automating UbiFast for High-throughput and Multiplexed Ubiquitin Enrichment.自动化 Ubifast 进行高通量和多重泛素化富集。
Mol Cell Proteomics. 2021;20:100154. doi: 10.1016/j.mcpro.2021.100154. Epub 2021 Sep 27.
3
Tandem Mass Tag Approach Utilizing Pervanadate BOOST Channels Delivers Deeper Quantitative Characterization of the Tyrosine Phosphoproteome.
利用过氧钒酸盐 BOOST 通道的串联质量标签方法可更深入地定量分析酪氨酸磷酸化蛋白质组。
Mol Cell Proteomics. 2020 Apr;19(4):730-743. doi: 10.1074/mcp.TIR119.001865. Epub 2020 Feb 18.
4
R2-P2 rapid-robotic phosphoproteomics enables multidimensional cell signaling studies.R2-P2 快速机器人磷酸化蛋白质组学可实现多维细胞信号研究。
Mol Syst Biol. 2019 Dec;15(12):e9021. doi: 10.15252/msb.20199021.
5
One-Step SH2 Superbinder-Based Approach for Sensitive Analysis of Tyrosine Phosphoproteome.一步法 SH2 超强黏附剂法用于酪氨酸磷酸化蛋白质组的灵敏分析
J Proteome Res. 2019 Apr 5;18(4):1870-1879. doi: 10.1021/acs.jproteome.9b00045. Epub 2019 Mar 25.
6
Using Ubiquitin Binders to Decipher the Ubiquitin Code.利用泛素结合物来破解泛素密码。
Trends Biochem Sci. 2019 Jul;44(7):599-615. doi: 10.1016/j.tibs.2019.01.011. Epub 2019 Feb 25.
7
Engineered SH2 domains with tailored specificities and enhanced affinities for phosphoproteome analysis.工程化的 SH2 结构域,具有定制的特异性和增强的磷酸化蛋白质组分析亲和力。
Protein Sci. 2019 Feb;28(2):403-413. doi: 10.1002/pro.3551. Epub 2018 Dec 24.
8
The PRIDE database and related tools and resources in 2019: improving support for quantification data.PRIDE 数据库及相关工具和资源在 2019 年的进展:提高定量数据支持。
Nucleic Acids Res. 2019 Jan 8;47(D1):D442-D450. doi: 10.1093/nar/gky1106.
9
High-throughput and high-sensitivity phosphoproteomics with the EasyPhos platform.高通量和高灵敏度磷酸化蛋白质组学的 EasyPhos 平台。
Nat Protoc. 2018 Sep;13(9):1897-1916. doi: 10.1038/s41596-018-0014-9.
10
Coral: Clear and Customizable Visualization of Human Kinome Data.珊瑚:人类激酶组数据的清晰可定制可视化。
Cell Syst. 2018 Sep 26;7(3):347-350.e1. doi: 10.1016/j.cels.2018.07.001. Epub 2018 Aug 29.