• 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

从1000个细胞中定量蛋白质丰度的简单方法。

Simple Method to Quantify Protein Abundances from 1000 Cells.

作者信息

Vitrinel Burcu, Iannitelli Dylan E, Mazzoni Esteban O, Christiaen Lionel, Vogel Christine

机构信息

Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York 10003, United States.

Center for Developmental Genetics, Department of Biology, New York University, New York, New York 10003, United States.

出版信息

ACS Omega. 2020 Jun 19;5(25):15537-15546. doi: 10.1021/acsomega.0c01191. eCollection 2020 Jun 30.

DOI:10.1021/acsomega.0c01191
PMID:32637829
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7331059/
Abstract

The rise of single-cell transcriptomics has created an urgent need for similar approaches that use a minimal number of cells to quantify expression levels of proteins. We integrated and optimized multiple recent developments to establish a proteomics workflow to quantify proteins from as few as 1000 mammalian stem cells. The method uses chemical peptide labeling, does not require specific equipment other than cell lysis tools, and quantifies >2500 proteins with high reproducibility. We validated the method by comparing mouse embryonic stem cells and in vitro differentiated motor neurons. We identify differentially expressed proteins with small fold changes and a dynamic range in abundance similar to that of standard methods. Protein abundance measurements obtained with our protocol compared well to corresponding transcript abundance and to measurements using standard inputs. The protocol is also applicable to other systems, such as fluorescence-activated cell sorting (FACS)-purified cells from the tunicate . Therefore, we offer a straightforward and accurate method to acquire proteomics data from minimal input samples.

摘要

单细胞转录组学的兴起迫切需要类似的方法,即使用最少数量的细胞来定量蛋白质的表达水平。我们整合并优化了多项最新进展,建立了一种蛋白质组学工作流程,以从低至1000个哺乳动物干细胞中定量蛋白质。该方法采用化学肽标记,除细胞裂解工具外无需特定设备,可高度可重复地定量超过2500种蛋白质。我们通过比较小鼠胚胎干细胞和体外分化的运动神经元验证了该方法。我们识别出具有小倍数变化且丰度动态范围与标准方法相似的差异表达蛋白质。用我们的方案获得的蛋白质丰度测量值与相应的转录本丰度以及使用标准输入的测量值相比效果良好。该方案也适用于其他系统,例如来自被囊动物的荧光激活细胞分选(FACS)纯化细胞。因此,我们提供了一种直接且准确的方法,可从极少输入样本中获取蛋白质组学数据。

相似文献

1
Simple Method to Quantify Protein Abundances from 1000 Cells.从1000个细胞中定量蛋白质丰度的简单方法。
ACS Omega. 2020 Jun 19;5(25):15537-15546. doi: 10.1021/acsomega.0c01191. eCollection 2020 Jun 30.
2
High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.通过集成样本制备技术和单次运行数据独立质谱分析实现高通量和高准确度的血清蛋白质组分析。
J Proteomics. 2018 Mar 1;174:9-16. doi: 10.1016/j.jprot.2017.12.014. Epub 2017 Dec 24.
3
Integrated microscale analysis system for targeted liquid chromatography mass spectrometry proteomics on limited amounts of enriched cell populations.基于有限量富集细胞群体的靶向液相色谱-质谱蛋白质组学的集成微尺度分析系统。
Anal Chem. 2013 Nov 19;85(22):10680-5. doi: 10.1021/ac401937c. Epub 2013 Oct 30.
4
Reproducibility of combinatorial peptide ligand libraries for proteome capture evaluated by selected reaction monitoring.通过选择反应监测评估用于蛋白质组捕获的组合肽配体文库的可重复性。
J Proteomics. 2013 Aug 26;89:215-26. doi: 10.1016/j.jprot.2013.05.037. Epub 2013 Jun 7.
5
Translational Metabolomics of Head Injury: Exploring Dysfunctional Cerebral Metabolism with Ex Vivo NMR Spectroscopy-Based Metabolite Quantification头部损伤的转化代谢组学:基于体外核磁共振波谱的代谢物定量分析探索脑代谢功能障碍
6
Estimating Cellular Abundances of Halo-tagged Proteins in Live Mammalian Cells by Flow Cytometry.通过流式细胞术估算活的哺乳动物细胞中卤代标签蛋白的细胞丰度
Bio Protoc. 2020 Feb 20;10(4):e3527. doi: 10.21769/BioProtoc.3527.
7
Markers and methods for cell sorting of human embryonic stem cell-derived neural cell populations.用于人类胚胎干细胞衍生神经细胞群体细胞分选的标志物和方法。
Stem Cells. 2007 Sep;25(9):2257-68. doi: 10.1634/stemcells.2006-0744. Epub 2007 Jun 21.
8
A practical data processing workflow for multi-OMICS projects.一种适用于多组学项目的实用数据处理工作流程。
Biochim Biophys Acta. 2014 Jan;1844(1 Pt A):52-62. doi: 10.1016/j.bbapap.2013.02.029. Epub 2013 Mar 15.
9
Relative and accurate measurement of protein abundance using 15N stable isotope labeling in Arabidopsis (SILIA).利用 15N 稳定同位素标记在拟南芥中(SILIA)进行相对准确的蛋白质丰度测量。
Phytochemistry. 2011 Jul;72(10):1028-39. doi: 10.1016/j.phytochem.2011.01.007. Epub 2011 Feb 19.
10
Analysis and isolation of embryonic mammalian neurons by fluorescence-activated cell sorting.通过荧光激活细胞分选对胚胎哺乳动物神经元进行分析和分离。
J Neurosci. 1986 May;6(5):1492-512. doi: 10.1523/JNEUROSCI.06-05-01492.1986.

引用本文的文献

1
Proteomic Characterization of 1000 Human and Murine Neutrophils Freshly Isolated From Blood and Sites of Sterile Inflammation.从血液和无菌炎症部位新鲜分离的1000个人类和小鼠中性粒细胞的蛋白质组学特征分析
Mol Cell Proteomics. 2024 Nov;23(11):100858. doi: 10.1016/j.mcpro.2024.100858. Epub 2024 Oct 11.
2
Droplet-based proteomics reveals CD36 as a marker for progenitors in mammary basal epithelium.基于液滴的蛋白质组学揭示CD36是乳腺基底上皮祖细胞的标志物。
Cell Rep Methods. 2024 Apr 22;4(4):100741. doi: 10.1016/j.crmeth.2024.100741. Epub 2024 Apr 2.
3
To the proteome and beyond: advances in single-cell omics profiling for plant systems.

本文引用的文献

1
Microscaled proteogenomic methods for precision oncology.微尺度蛋白质基因组学方法在精准肿瘤学中的应用。
Nat Commun. 2020 Jan 27;11(1):532. doi: 10.1038/s41467-020-14381-2.
2
Automated mass spectrometry imaging of over 2000 proteins from tissue sections at 100-μm spatial resolution.利用 100μm 空间分辨率的组织切片,实现 2000 多种蛋白质的自动化质谱成像。
Nat Commun. 2020 Jan 7;11(1):8. doi: 10.1038/s41467-019-13858-z.
3
High-Throughput Single Cell Proteomics Enabled by Multiplex Isobaric Labeling in a Nanodroplet Sample Preparation Platform.
从蛋白质组学到更广阔的领域:植物系统中单细胞组学分析的进展。
Plant Physiol. 2022 Feb 4;188(2):726-737. doi: 10.1093/plphys/kiab429.
4
New horizons in the stormy sea of multimodal single-cell data integration.多模态单细胞数据整合的波涛汹涌的海洋中的新视野。
Mol Cell. 2022 Jan 20;82(2):248-259. doi: 10.1016/j.molcel.2021.12.012.
5
Surfactant-assisted one-pot sample preparation for label-free single-cell proteomics.表面活性剂辅助的无标记单细胞蛋白质组学的一锅法样品制备。
Commun Biol. 2021 Mar 1;4(1):265. doi: 10.1038/s42003-021-01797-9.
6
Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells.用于少量人类细胞靶向蛋白质组学分析的载体辅助一锅法样品制备
J Vis Exp. 2020 Nov 6(165). doi: 10.3791/61797.
基于纳升液滴样品制备平台的多重等压标记实现高通量单细胞蛋白质组学分析。
Anal Chem. 2019 Oct 15;91(20):13119-13127. doi: 10.1021/acs.analchem.9b03349. Epub 2019 Sep 25.
4
A dream of single-cell proteomics.单细胞蛋白质组学之梦。
Nat Methods. 2019 Sep;16(9):809-812. doi: 10.1038/s41592-019-0540-6.
5
A single-cell transcriptional roadmap for cardiopharyngeal fate diversification.心咽命运多样化的单细胞转录图谱。
Nat Cell Biol. 2019 Jun;21(6):674-686. doi: 10.1038/s41556-019-0336-z. Epub 2019 Jun 3.
6
Stem cell-derived cranial and spinal motor neurons reveal proteostatic differences between ALS resistant and sensitive motor neurons.干细胞衍生的颅神经和脊髓运动神经元揭示了肌萎缩侧索硬化症抗性和敏感运动神经元之间的蛋白质稳态差异。
Elife. 2019 Jun 3;8:e44423. doi: 10.7554/eLife.44423.
7
Boosting to Amplify Signal with Isobaric Labeling (BASIL) Strategy for Comprehensive Quantitative Phosphoproteomic Characterization of Small Populations of Cells.利用等压标记(BASIL)策略进行小细胞群体的全面定量磷酸化蛋白质组学分析。
Anal Chem. 2019 May 7;91(9):5794-5801. doi: 10.1021/acs.analchem.9b00024. Epub 2019 Mar 15.
8
Streamlined Protocol for Deep Proteomic Profiling of FAC-sorted Cells and Its Application to Freshly Isolated Murine Immune Cells.流式细胞分选细胞的深度蛋白质组学简化方案及其在新鲜分离的小鼠免疫细胞中的应用。
Mol Cell Proteomics. 2019 May;18(5):995-1009. doi: 10.1074/mcp.RA118.001259. Epub 2019 Feb 21.
9
Evaluation of a Dual Isolation Width Acquisition Method for Isobaric Labeling Ratio Decompression.双隔离宽度采集法对同重标记比解压的评估。
J Proteome Res. 2019 Mar 1;18(3):1433-1440. doi: 10.1021/acs.jproteome.8b00870. Epub 2019 Jan 3.
10
PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools.PANTHER 版本 14:更多基因组、一个新的 PANTHER GO-slim 和富集分析工具的改进。
Nucleic Acids Res. 2019 Jan 8;47(D1):D419-D426. doi: 10.1093/nar/gky1038.