⮝ Full datasets listing
PXD069886
PXD069886 is an original dataset announced via ProteomeXchange.
Dataset Summary
| Title | Enhanced Identifications and Quantification through Retention Time Down-Sampling in Fast-Cycling diagonal-PASEF Methods |
| Description | Data-independent acquisition (DIA) mass spectrometry is essential for comprehensive quantification of proteomes, enabling deeper insights into cellular processes and disease mechanisms. On the timsTOF platform, diagonal-PASEF acquisition methods have recently been introduced to directly and continuously cover the observed diagonal shape of the peptide precursor ion distributions. Diagonal-PASEF has already shown great promise and its adaptation as a routine workflow can be further pushed with improved method development as well as enhanced algorithmic solutions. Here, we conducted a systematic and comprehensive optimization of diagonal-PASEF for 17-minute gradients on the timsTOF HT in conjunction to Spectronaut. We demonstrate that Spectronaut fully supports all tested diagonal-PASEF methods independent of the number of slices or overlaps and with minimal user intervention required. We derive an optimized analysis strategy where we coupled diagonal-PASEF acquisitions to retention time down-sampling by summation (RTsum) and thereby exploit the fast-cycling nature of diagonal-PASEF methods. Through the combination of RTsum with diagonal-PASEF, we demonstrate that this strategy yields higher signal-to-noise ratios while retaining the peak shape for analytes of interest ultimately improving overall number of peptide and protein identifications of diagonal-PASEF. Importantly, combining RTsum with diagonal-PASEF improved overall identifications and quantitative precision when compared to dia-PASEF with variable quadrupole isolation widths and across different input amounts for cell line injections. We also tested the performance of diagonal-PASEF in controlled quantitative experiments where diagonal-PASEF outperformed dia-PASEF in the overall number of retained candidates below 1% or 5% error-rate, quantitative precision and identifications on peptide level and protein level. These data indicate that RTsum demonstrates a positive use case of the high sampling rate of diagonal-PASEF and might therefore be a valuable addition to existing analysis pipelines. Collectively, our findings imply that diagonal-PASEF is developing into a competitive alternative to dia-PASEF and that the data analysis options are making fast progress. |
| HostingRepository | MassIVE |
| AnnounceDate | 2025-12-11 |
| AnnouncementXML | Submission_2025-12-11_11:10:59.899.xml |
| DigitalObjectIdentifier | |
| ReviewLevel | Peer-reviewed dataset |
| DatasetOrigin | Original dataset |
| RepositorySupport | Unsupported dataset by repository |
| PrimarySubmitter | Roland Bruderer |
| SpeciesList | scientific name: Homo sapiens; common name: human; NCBI TaxID: 9606; |
| ModificationList | Oxidation; CarbamidomethylDTT |
| Instrument | timsTOF HT |
Dataset History
| Revision | Datetime | Status | ChangeLog Entry |
|---|---|---|---|
| 0 | 2025-10-24 10:32:30 | ID requested | |
| ⏵ 1 | 2025-12-11 11:11:00 | announced |
Publication List
| Christopher R. Below ? Oliver M. Bernhardt ? Stephanie Kaspar-Schönefeld ? Sander Willems ? Edoardo Coronado ? Ino D. Karemaker ? Bettina Streckenbach ? Monika Pepelnjak ? Luca Räss ? Sandra Schär ? Dennis Trede ? Jonathan R. Krieger ? Tejas Gandhi ? Roland Bruderer ? Lukas Reiter. Enhanced Identifications and Quantification through Retention Time Down-Sampling in Fast-Cycling diagonal-PASEF Methods. Molecular and Cellular Proteomics, Articles in Press101480December 2025. |
Keyword List
| submitter keyword: diagnoal-PASEF, dia-PASEF, DatasetType:Proteomics |
Contact List
| Roland Bruderer | |
|---|---|
| contact affiliation | Biognosys AG |
| contact email | roland.bruderer@biognosys.com |
| lab head | |
| Roland Bruderer | |
| contact affiliation | Biognosys AG |
| contact email | roland.bruderer@biognosys.com |
| dataset submitter | |
Full Dataset Link List
| MassIVE 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://massive-ftp.ucsd.edu/v11/MSV000099586/ |
