Localizatome:一个蛋白质中应力依赖性亚细胞定位变化的数据库。

IF 3.6 4区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Takahide Matsushima, Yuki Naito, Tomoki Chiba, Ryota Kurimoto, Keiko Itano, Koji Ochiai, Koichi Takahashi, Naoki Goshima, Hiroshi Asahara
{"title":"Localizatome:一个蛋白质中应力依赖性亚细胞定位变化的数据库。","authors":"Takahide Matsushima, Yuki Naito, Tomoki Chiba, Ryota Kurimoto, Keiko Itano, Koji Ochiai, Koichi Takahashi, Naoki Goshima, Hiroshi Asahara","doi":"10.1093/database/baaf028","DOIUrl":null,"url":null,"abstract":"<p><p>Understanding protein subcellular localization and its dynamic changes is crucial for elucidating cellular function and disease mechanisms, particularly under stress conditions, where protein localization changes can modulate cellular responses. Currently available databases provide insights into protein localization under steady-state conditions; however, stress-related dynamic localization changes remain poorly understood. Here, we present the Localizatome, a comprehensive database that captures stress-induced protein localization dynamics in living cells. Using an original high-throughput microscopy system and machine learning algorithms, we analysed the localization patterns of 10 287 fluorescent protein-fused human proteins in HeLa cells before and after exposure to oxidative stress. Our analysis revealed that 1910 proteins exhibited oxidative stress-dependent localization changes, particularly forming distinct foci. Among them, there were stress granule assembly factors and autophagy-related proteins, as well as components of various signalling pathways. Subsequent characterization identified some specific amino acid motifs and intrinsically disordered regions associated with stress-induced protein redistribution. The Localizatome provides open access to these data through a web-based interface, supporting a wide range of studies on cellular stress response and disease mechanisms. Database URL https://localizatome.embrys.jp/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Localizatome: a database for stress-dependent subcellular localization changes in proteins.\",\"authors\":\"Takahide Matsushima, Yuki Naito, Tomoki Chiba, Ryota Kurimoto, Keiko Itano, Koji Ochiai, Koichi Takahashi, Naoki Goshima, Hiroshi Asahara\",\"doi\":\"10.1093/database/baaf028\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Understanding protein subcellular localization and its dynamic changes is crucial for elucidating cellular function and disease mechanisms, particularly under stress conditions, where protein localization changes can modulate cellular responses. Currently available databases provide insights into protein localization under steady-state conditions; however, stress-related dynamic localization changes remain poorly understood. Here, we present the Localizatome, a comprehensive database that captures stress-induced protein localization dynamics in living cells. Using an original high-throughput microscopy system and machine learning algorithms, we analysed the localization patterns of 10 287 fluorescent protein-fused human proteins in HeLa cells before and after exposure to oxidative stress. Our analysis revealed that 1910 proteins exhibited oxidative stress-dependent localization changes, particularly forming distinct foci. Among them, there were stress granule assembly factors and autophagy-related proteins, as well as components of various signalling pathways. Subsequent characterization identified some specific amino acid motifs and intrinsically disordered regions associated with stress-induced protein redistribution. The Localizatome provides open access to these data through a web-based interface, supporting a wide range of studies on cellular stress response and disease mechanisms. Database URL https://localizatome.embrys.jp/.</p>\",\"PeriodicalId\":10923,\"journal\":{\"name\":\"Database: The Journal of Biological Databases and Curation\",\"volume\":\"2025 \",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Database: The Journal of Biological Databases and Curation\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/database/baaf028\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Database: The Journal of Biological Databases and Curation","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/database/baaf028","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

了解蛋白质亚细胞定位及其动态变化对于阐明细胞功能和疾病机制至关重要,特别是在应激条件下,蛋白质定位变化可以调节细胞反应。目前可用的数据库提供了在稳态条件下蛋白质定位的见解;然而,与应力相关的动态局部化变化仍然知之甚少。在这里,我们介绍了Localizatome,一个捕获活细胞中应力诱导的蛋白质定位动态的综合数据库。利用原始的高通量显微镜系统和机器学习算法,我们分析了氧化应激前后HeLa细胞中10 287种荧光蛋白融合的人蛋白的定位模式。我们的分析显示,1910蛋白表现出氧化应激依赖的定位变化,特别是形成不同的焦点。其中包括胁迫颗粒组装因子和自噬相关蛋白,以及各种信号通路的组分。随后的表征确定了一些特定的氨基酸基序和与应力诱导的蛋白质再分配相关的内在紊乱区域。Localizatome通过基于网络的界面提供对这些数据的开放访问,支持对细胞应激反应和疾病机制的广泛研究。数据库URL https://localizatome.embrys.jp/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localizatome: a database for stress-dependent subcellular localization changes in proteins.

Understanding protein subcellular localization and its dynamic changes is crucial for elucidating cellular function and disease mechanisms, particularly under stress conditions, where protein localization changes can modulate cellular responses. Currently available databases provide insights into protein localization under steady-state conditions; however, stress-related dynamic localization changes remain poorly understood. Here, we present the Localizatome, a comprehensive database that captures stress-induced protein localization dynamics in living cells. Using an original high-throughput microscopy system and machine learning algorithms, we analysed the localization patterns of 10 287 fluorescent protein-fused human proteins in HeLa cells before and after exposure to oxidative stress. Our analysis revealed that 1910 proteins exhibited oxidative stress-dependent localization changes, particularly forming distinct foci. Among them, there were stress granule assembly factors and autophagy-related proteins, as well as components of various signalling pathways. Subsequent characterization identified some specific amino acid motifs and intrinsically disordered regions associated with stress-induced protein redistribution. The Localizatome provides open access to these data through a web-based interface, supporting a wide range of studies on cellular stress response and disease mechanisms. Database URL https://localizatome.embrys.jp/.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Database: The Journal of Biological Databases and Curation
Database: The Journal of Biological Databases and Curation MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
9.00
自引率
3.40%
发文量
100
审稿时长
>12 weeks
期刊介绍: Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data. Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信