PXD041118-1
PXD041118 is an original dataset announced via ProteomeXchange.
Dataset Summary
| Title | A One-pot Analytical Pipeline for Efficient and Sensitive Proteomic Analysis of Extracellular Vesicles |
| Description | Detection of extracellular vesicles (EVs) cargoes from biofluids has drawn more attention in the field of translational and clinical medicine. EV proteomics is particularly a promising tool in discovering potential biomarkers for disease diagnosis, monitoring, and therapeutics. However, the current workflow of mass spectrometry-based EV proteome analysis is not well compatible with clinical settings due to inefficient EV isolation methods and tedious sample preparation processes. To further implement highly efficient EV proteome analysis, this study established a one-pot analytical pipeline based on a robust EV isolation approach, EV total recovery and purification (EVtrap), to detect urinary EV proteome in a rapid and sensitive manner. By incorporating solvent-driven protein capture and on-bead digestion, the one-pot EV proteomics pipeline avoided any sample transfer step and largely reduced the complexity of the peptide preparation process for bottom-up proteomic analysis. Moreover, a shorter digestion time was practicable in this novel pipeline, which enables a whole EV proteome analysis to be completed within one day. In comparison with the more time-consuming conventional workflow, the one-pot pipeline was able to obtain a higher peptide yield and identify similar numbers of unique EV proteins in 1 mL of urine. Finally, we applied the one-pot pipeline to monitor potential biomarkers in urinary EVs of bladder cancer patients. A total of 2,774 proteins and ~20,000 peptides were identified in 53 urine samples using a 15-min gradient direct data-independent acquisition (directDIA). Several known bladder cancer-associated protein markers were successfully identified and showed significantly higher abundance in patient-derived EVs. Taken altogether, our novel one-pot analytical pipeline demonstrated its potential for routine and robust EV proteomics in biomedical applications. |
| HostingRepository | jPOST |
| AnnounceDate | 2023-07-24 |
| AnnouncementXML | Submission_2023-07-24_19:11:20.496.xml |
| DigitalObjectIdentifier | |
| ReviewLevel | Non peer-reviewed dataset |
| DatasetOrigin | Original dataset |
| RepositorySupport | Unsupported dataset by repository |
| PrimarySubmitter | Marco Hadisurya |
| SpeciesList | scientific name: Homo sapiens (Human); NCBI TaxID: 9606; |
| ModificationList | S-carboxamidomethyl-L-cysteine; L-methionine sulfoxide |
| Instrument | Q Exactive |
Dataset History
| Revision | Datetime | Status | ChangeLog Entry |
|---|---|---|---|
| 0 | 2023-03-26 22:48:20 | ID requested | |
| ⏵ 1 | 2023-07-24 19:11:20 | announced |
Publication List
| Dataset with its publication pending |
Keyword List
| submitter keyword: extracellular vesicles, proteomics, urine, EVtrap, bladder cancer |
Contact List
| W. Andy Tao | |
|---|---|
| lab head | |
| Marco Hadisurya | |
| contact affiliation | Purdue University |
| dataset submitter | |
Full Dataset Link List
| jPOST dataset URI |
| Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.jpostdb.org/JPST002105/ |
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