AE-MS方法中的结构域交换嵌合体揭示了BRI1和SIRK1的受体激酶信号通过它们的相互作用组紧密平衡。

IF 6.1 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Molecular & Cellular Proteomics Pub Date : 2024-10-15 DOI:10.1016/j.mcpro.2024.100857
Lin Xi, Xuna Wu, Jiahui Wang, Zhaoxia Zhang, Mingjie He, Zeeshan Zeeshan, Thorsten Stefan, Waltraud X Schulze
{"title":"AE-MS方法中的结构域交换嵌合体揭示了BRI1和SIRK1的受体激酶信号通过它们的相互作用组紧密平衡。","authors":"Lin Xi, Xuna Wu, Jiahui Wang, Zhaoxia Zhang, Mingjie He, Zeeshan Zeeshan, Thorsten Stefan, Waltraud X Schulze","doi":"10.1016/j.mcpro.2024.100857","DOIUrl":null,"url":null,"abstract":"<p><p>At the plasma membrane, in response to biotic and abiotic cues, specific ligands initiate the formation of receptor kinase heterodimers, which regulate the activities of plasma membrane proteins and initiate signaling cascades to the nucleus. In this study, we utilized affinity enrichment mass spectrometry to investigate the stimulus-dependent interactomes of LRR receptor kinases in response to their respective ligands, with an emphasis on exploring structural influences and potential cross-talk events at the plasma membrane. BRI1 and SIRK1 were chosen as receptor kinases with distinct coreceptor preference. By using interactome characteristic of domain-swap chimera following a gradient boosting learning algorithm trained on SIRK1 and BRI1 interactomes, we attribute contributions of extracellular domain, transmembrane domain, juxtamembrane domain, and kinase domain of respective ligand-binding receptors to their interaction with their coreceptors and substrates. Our results revealed juxtamembrane domain as major structural element defining the specific substrate recruitment for BRI1 and extracellular domain for SIRK1. Furthermore, the learning algorithm enabled us to predict the phenotypic outcomes of chimeric receptors based on different domain combinations, which was verified by dedicated experiments. As a result, our work reveals a tightly controlled balance of signaling cascade activation dependent on ligand-binding receptors domains and the internal ligand status of the plant. Moreover, our study shows the robust utility of machine learning classification as a quantitative metric for studying dynamic interactomes, dissecting the contribution of specific domains and predicting their phenotypic outcome.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"100857"},"PeriodicalIF":6.1000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Receptor Kinase Signaling of BRI1 and SIRK1 Is Tightly Balanced by Their Interactomes as Revealed From Domain-Swap Chimaera in AE-MS Approaches.\",\"authors\":\"Lin Xi, Xuna Wu, Jiahui Wang, Zhaoxia Zhang, Mingjie He, Zeeshan Zeeshan, Thorsten Stefan, Waltraud X Schulze\",\"doi\":\"10.1016/j.mcpro.2024.100857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>At the plasma membrane, in response to biotic and abiotic cues, specific ligands initiate the formation of receptor kinase heterodimers, which regulate the activities of plasma membrane proteins and initiate signaling cascades to the nucleus. In this study, we utilized affinity enrichment mass spectrometry to investigate the stimulus-dependent interactomes of LRR receptor kinases in response to their respective ligands, with an emphasis on exploring structural influences and potential cross-talk events at the plasma membrane. BRI1 and SIRK1 were chosen as receptor kinases with distinct coreceptor preference. By using interactome characteristic of domain-swap chimera following a gradient boosting learning algorithm trained on SIRK1 and BRI1 interactomes, we attribute contributions of extracellular domain, transmembrane domain, juxtamembrane domain, and kinase domain of respective ligand-binding receptors to their interaction with their coreceptors and substrates. Our results revealed juxtamembrane domain as major structural element defining the specific substrate recruitment for BRI1 and extracellular domain for SIRK1. Furthermore, the learning algorithm enabled us to predict the phenotypic outcomes of chimeric receptors based on different domain combinations, which was verified by dedicated experiments. As a result, our work reveals a tightly controlled balance of signaling cascade activation dependent on ligand-binding receptors domains and the internal ligand status of the plant. Moreover, our study shows the robust utility of machine learning classification as a quantitative metric for studying dynamic interactomes, dissecting the contribution of specific domains and predicting their phenotypic outcome.</p>\",\"PeriodicalId\":18712,\"journal\":{\"name\":\"Molecular & Cellular Proteomics\",\"volume\":\" \",\"pages\":\"100857\"},\"PeriodicalIF\":6.1000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular & Cellular Proteomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.mcpro.2024.100857\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOCHEMICAL RESEARCH METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular & Cellular Proteomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.mcpro.2024.100857","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

摘要

在质膜上,针对生物和非生物线索,特定配体会启动受体激酶异二聚体的形成,从而调节质膜蛋白的活性并启动通向细胞核的信号级联。在这项研究中,我们利用亲和富集质谱法(AE-MS)研究了 LRR 受体激酶对各自配体的刺激依赖性相互作用组,重点是探索质膜上的结构影响和潜在的交叉对话事件。BRI1 和 SIRK1 被选为具有不同核心受体偏好的受体激酶。通过使用SIRK1和BRI1相互作用组训练的梯度提升学习算法,利用结构域交换嵌合体的相互作用组特征,我们确定了各自配体结合受体的胞外结构域、跨膜结构域、并膜结构域和激酶结构域对它们与核心受体和底物相互作用的贡献。我们的研究结果表明,并膜结构域是决定 BRI1 和 SIRK1 特异性底物招募的主要结构元素,而细胞外结构域则是决定 SIRK1 特异性底物招募的主要结构元素。此外,学习算法使我们能够根据不同的结构域组合预测嵌合受体的表型结果,这一点已通过专门的实验得到验证。因此,我们的工作揭示了信号级联激活的严格控制平衡取决于配体结合受体结构域和植物内部配体状态。此外,我们的研究还表明,机器学习分类作为一种定量指标,在研究动态相互作用组、剖析特定结构域的贡献以及预测其表型结果方面具有强大的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Receptor Kinase Signaling of BRI1 and SIRK1 Is Tightly Balanced by Their Interactomes as Revealed From Domain-Swap Chimaera in AE-MS Approaches.

At the plasma membrane, in response to biotic and abiotic cues, specific ligands initiate the formation of receptor kinase heterodimers, which regulate the activities of plasma membrane proteins and initiate signaling cascades to the nucleus. In this study, we utilized affinity enrichment mass spectrometry to investigate the stimulus-dependent interactomes of LRR receptor kinases in response to their respective ligands, with an emphasis on exploring structural influences and potential cross-talk events at the plasma membrane. BRI1 and SIRK1 were chosen as receptor kinases with distinct coreceptor preference. By using interactome characteristic of domain-swap chimera following a gradient boosting learning algorithm trained on SIRK1 and BRI1 interactomes, we attribute contributions of extracellular domain, transmembrane domain, juxtamembrane domain, and kinase domain of respective ligand-binding receptors to their interaction with their coreceptors and substrates. Our results revealed juxtamembrane domain as major structural element defining the specific substrate recruitment for BRI1 and extracellular domain for SIRK1. Furthermore, the learning algorithm enabled us to predict the phenotypic outcomes of chimeric receptors based on different domain combinations, which was verified by dedicated experiments. As a result, our work reveals a tightly controlled balance of signaling cascade activation dependent on ligand-binding receptors domains and the internal ligand status of the plant. Moreover, our study shows the robust utility of machine learning classification as a quantitative metric for studying dynamic interactomes, dissecting the contribution of specific domains and predicting their phenotypic outcome.

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
Molecular & Cellular Proteomics
Molecular & Cellular Proteomics 生物-生化研究方法
CiteScore
11.50
自引率
4.30%
发文量
131
审稿时长
84 days
期刊介绍: The mission of MCP is to foster the development and applications of proteomics in both basic and translational research. MCP will publish manuscripts that report significant new biological or clinical discoveries underpinned by proteomic observations across all kingdoms of life. Manuscripts must define the biological roles played by the proteins investigated or their mechanisms of action. The journal also emphasizes articles that describe innovative new computational methods and technological advancements that will enable future discoveries. Manuscripts describing such approaches do not have to include a solution to a biological problem, but must demonstrate that the technology works as described, is reproducible and is appropriate to uncover yet unknown protein/proteome function or properties using relevant model systems or publicly available data. Scope: -Fundamental studies in biology, including integrative "omics" studies, that provide mechanistic insights -Novel experimental and computational technologies -Proteogenomic data integration and analysis that enable greater understanding of physiology and disease processes -Pathway and network analyses of signaling that focus on the roles of post-translational modifications -Studies of proteome dynamics and quality controls, and their roles in disease -Studies of evolutionary processes effecting proteome dynamics, quality and regulation -Chemical proteomics, including mechanisms of drug action -Proteomics of the immune system and antigen presentation/recognition -Microbiome proteomics, host-microbe and host-pathogen interactions, and their roles in health and disease -Clinical and translational studies of human diseases -Metabolomics to understand functional connections between genes, proteins and phenotypes
期刊最新文献
Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-treated Pancreatic Beta Cells. Gradient-Elution Nanoflow Liquid Chromatography without a Binary Pump: Smoothed Step Gradients Enable Reproducible, Sensitive, and Low-Cost Separations for Single-Cell Proteomics. In-depth analysis of miRNA binding sites reveals the complex response of uterine epithelium to miR-26a-5p and miR-125b-5p during early pregnancy. Bridging the Gap from Proteomics Technology to Clinical Application: Highlights from the 68th Benzon Foundation Symposium. Knockdown proteomics reveals USP7 as a regulator of cell-cell adhesion in colorectal cancer via AJUBA.
×
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