Accurate and sensitive interactome profiling using a quantitative protein-fragment complementation assay.

IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS Cell Reports Methods Pub Date : 2024-10-21 DOI:10.1016/j.crmeth.2024.100880
Natalia Lazarewicz, Gaëlle Le Dez, Romina Cerjani, Lunelys Runeshaw, Matthias Meurer, Michael Knop, Robert Wysocki, Gwenaël Rabut
{"title":"Accurate and sensitive interactome profiling using a quantitative protein-fragment complementation assay.","authors":"Natalia Lazarewicz, Gaëlle Le Dez, Romina Cerjani, Lunelys Runeshaw, Matthias Meurer, Michael Knop, Robert Wysocki, Gwenaël Rabut","doi":"10.1016/j.crmeth.2024.100880","DOIUrl":null,"url":null,"abstract":"<p><p>An accurate description of protein-protein interaction (PPI) networks is key to understanding the molecular mechanisms underlying cellular systems. Here, we constructed genome-wide libraries of yeast strains to systematically probe protein-protein interactions using NanoLuc Binary Technology (NanoBiT), a quantitative protein-fragment complementation assay (PCA) based on the NanoLuc luciferase. By investigating an array of well-documented PPIs as well as the interactome of four proteins with varying levels of characterization-including the well-studied nonsense-mediated mRNA decay (NMD) regulator Upf1 and the SCF complex subunits Cdc53 and Met30-we demonstrate that ratiometric NanoBiT measurements enable highly precise and sensitive mapping of PPIs. This work provides a foundation for employing NanoBiT in the assembly of more comprehensive and accurate protein interaction maps as well as in their functional investigation.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Reports Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.crmeth.2024.100880","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

An accurate description of protein-protein interaction (PPI) networks is key to understanding the molecular mechanisms underlying cellular systems. Here, we constructed genome-wide libraries of yeast strains to systematically probe protein-protein interactions using NanoLuc Binary Technology (NanoBiT), a quantitative protein-fragment complementation assay (PCA) based on the NanoLuc luciferase. By investigating an array of well-documented PPIs as well as the interactome of four proteins with varying levels of characterization-including the well-studied nonsense-mediated mRNA decay (NMD) regulator Upf1 and the SCF complex subunits Cdc53 and Met30-we demonstrate that ratiometric NanoBiT measurements enable highly precise and sensitive mapping of PPIs. This work provides a foundation for employing NanoBiT in the assembly of more comprehensive and accurate protein interaction maps as well as in their functional investigation.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用定量蛋白质片段互补测定法进行准确而灵敏的相互作用组分析。
准确描述蛋白质-蛋白质相互作用(PPI)网络是了解细胞系统分子机制的关键。在这里,我们构建了酵母菌株的全基因组文库,利用基于 NanoLuc 荧光素酶的定量蛋白质片段互补测定(PCA)--NanoLuc 二进制技术(NanoBiT)系统地探测蛋白质-蛋白质相互作用。通过研究一系列有据可查的 PPIs 以及四种具有不同表征水平的蛋白质的相互作用组--包括研究得很清楚的无义介导 mRNA 衰减(NMD)调节因子 Upf1 以及 SCF 复合物亚基 Cdc53 和 Met30--我们证明了 NanoBiT 的比率测量能够高度精确和灵敏地绘制 PPIs 图谱。这项工作为利用 NanoBiT 绘制更全面、更精确的蛋白质相互作用图谱及其功能研究奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Cell Reports Methods
Cell Reports Methods Chemistry (General), Biochemistry, Genetics and Molecular Biology (General), Immunology and Microbiology (General)
CiteScore
3.80
自引率
0.00%
发文量
0
审稿时长
111 days
期刊最新文献
Optimized full-spectrum flow cytometry panel for deep immunophenotyping of murine lungs. A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain. Adult zebrafish can learn Morris water maze-like tasks in a two-dimensional virtual reality system. Recovering single-cell expression profiles from spatial transcriptomics with scResolve. Mimicking and analyzing the tumor microenvironment.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1