Asia Botto, Chiara De Cesari, Noa Ndimurwanko, Francesco Finamore, Francesco Greco, Valentina Cappello, Valentina Casieri, Benoit Immordino, Vincenzo Lionetti, Mauro Gemmi, Ilaria Tonazzini, Elisa Giovannetti, Liam A McDonnell
{"title":"基于细胞介质的高灵敏度细胞外囊泡蛋白质组学的新颖PPT+SEC工作流程","authors":"Asia Botto, Chiara De Cesari, Noa Ndimurwanko, Francesco Finamore, Francesco Greco, Valentina Cappello, Valentina Casieri, Benoit Immordino, Vincenzo Lionetti, Mauro Gemmi, Ilaria Tonazzini, Elisa Giovannetti, Liam A McDonnell","doi":"10.1021/acs.jproteome.5c00082","DOIUrl":null,"url":null,"abstract":"<p><p>Size exclusion chromatography (SEC) is a well-established method for the isolation of extracellular vesicles (EVs), but the large elution volumes necessitate a concentration step prior to proteomics analysis. This concentration step can lead to a significant EV loss. Here we report an EV proteomics approach that enables the isolation of EVs into just 80 μL, which is directly compatible with proteomics analysis without the need for a prior concentration. EVs were characterized by transmission electron microscopy, Western blot, and nanoparticle tracking analysis, all of which confirmed the presence of small EVs. Proteomics analysis of the EVs was performed and benchmarked against those isolated by using an automated UHPLC-SEC platform. The novel workflow identified more proteins and more EV markers, including 96 of the 100 top exosomal proteins from the ExoCarta database, compared to 91 identified using EV samples isolated by UHPLC-SEC. When applied to EVs isolated from pancreatic cancer cell lines, the workflow demonstrated higher sensitivity for previously reported EV markers of pancreatic cancer.</p>","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel PPT+SEC Workflow for High-Sensitivity Extracellular Vesicle Proteomics from Cell Media.\",\"authors\":\"Asia Botto, Chiara De Cesari, Noa Ndimurwanko, Francesco Finamore, Francesco Greco, Valentina Cappello, Valentina Casieri, Benoit Immordino, Vincenzo Lionetti, Mauro Gemmi, Ilaria Tonazzini, Elisa Giovannetti, Liam A McDonnell\",\"doi\":\"10.1021/acs.jproteome.5c00082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Size exclusion chromatography (SEC) is a well-established method for the isolation of extracellular vesicles (EVs), but the large elution volumes necessitate a concentration step prior to proteomics analysis. This concentration step can lead to a significant EV loss. Here we report an EV proteomics approach that enables the isolation of EVs into just 80 μL, which is directly compatible with proteomics analysis without the need for a prior concentration. EVs were characterized by transmission electron microscopy, Western blot, and nanoparticle tracking analysis, all of which confirmed the presence of small EVs. Proteomics analysis of the EVs was performed and benchmarked against those isolated by using an automated UHPLC-SEC platform. The novel workflow identified more proteins and more EV markers, including 96 of the 100 top exosomal proteins from the ExoCarta database, compared to 91 identified using EV samples isolated by UHPLC-SEC. When applied to EVs isolated from pancreatic cancer cell lines, the workflow demonstrated higher sensitivity for previously reported EV markers of pancreatic cancer.</p>\",\"PeriodicalId\":48,\"journal\":{\"name\":\"Journal of Proteome Research\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2025-05-02\",\"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.5c00082\",\"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":"Journal of Proteome Research","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1021/acs.jproteome.5c00082","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}
Novel PPT+SEC Workflow for High-Sensitivity Extracellular Vesicle Proteomics from Cell Media.
Size exclusion chromatography (SEC) is a well-established method for the isolation of extracellular vesicles (EVs), but the large elution volumes necessitate a concentration step prior to proteomics analysis. This concentration step can lead to a significant EV loss. Here we report an EV proteomics approach that enables the isolation of EVs into just 80 μL, which is directly compatible with proteomics analysis without the need for a prior concentration. EVs were characterized by transmission electron microscopy, Western blot, and nanoparticle tracking analysis, all of which confirmed the presence of small EVs. Proteomics analysis of the EVs was performed and benchmarked against those isolated by using an automated UHPLC-SEC platform. The novel workflow identified more proteins and more EV markers, including 96 of the 100 top exosomal proteins from the ExoCarta database, compared to 91 identified using EV samples isolated by UHPLC-SEC. When applied to EVs isolated from pancreatic cancer cell lines, the workflow demonstrated higher sensitivity for previously reported EV markers of pancreatic cancer.
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".