Jun Wang, Yang Li, Yisheng Wang, Guoli Wang, Chenyang Zhao, Ying Zhang, Haojie Lu
{"title":"Comparison of Protein Solubilization and Normalization Methods for Proteomics Analysis of Extracellular Vesicles from Urine.","authors":"Jun Wang, Yang Li, Yisheng Wang, Guoli Wang, Chenyang Zhao, Ying Zhang, Haojie Lu","doi":"10.1021/acs.jproteome.4c01085","DOIUrl":null,"url":null,"abstract":"<p><p>Extracellular vesicles (EVs) play a vital role in numerous biological processes. Proteomic research of EVs is crucial for understanding their functions and potential therapeutic implications. Despite many sample preparation protocols for mass spectrometry-based proteomics of EVs being described, the variability in protein extraction across different protocols has not been extensively investigated. Moreover, given the inherent heterogeneity of EVs, it is vital to conduct a thorough evaluation of normalization methods. Here, we present a comprehensive comparison of three widely used lysis agents─sodium dodecyl sulfate (SDS), urea, and sodium deoxycholate (SDC)─for protein extraction from EVs. We also assess the impact of different normalization strategies on protein quantification, which is crucial for ensuring reliable results. Our results show that method-dependent differences in protein recovery were observed, particularly for membrane-associated proteins. We also find that common normalization strategies, such as urine creatinine and EV markers, did not significantly stabilize protein quantification, indicating that these methods are not universally applicable as normalization standards. Our work thereby provides a reference for the selection of MS sample preparation and normalization strategies for a given EV proteomics project.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.4c01085","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
Abstract
Extracellular vesicles (EVs) play a vital role in numerous biological processes. Proteomic research of EVs is crucial for understanding their functions and potential therapeutic implications. Despite many sample preparation protocols for mass spectrometry-based proteomics of EVs being described, the variability in protein extraction across different protocols has not been extensively investigated. Moreover, given the inherent heterogeneity of EVs, it is vital to conduct a thorough evaluation of normalization methods. Here, we present a comprehensive comparison of three widely used lysis agents─sodium dodecyl sulfate (SDS), urea, and sodium deoxycholate (SDC)─for protein extraction from EVs. We also assess the impact of different normalization strategies on protein quantification, which is crucial for ensuring reliable results. Our results show that method-dependent differences in protein recovery were observed, particularly for membrane-associated proteins. We also find that common normalization strategies, such as urine creatinine and EV markers, did not significantly stabilize protein quantification, indicating that these methods are not universally applicable as normalization standards. Our work thereby provides a reference for the selection of MS sample preparation and normalization strategies for a given EV proteomics project.
期刊介绍:
Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".