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.
[doi:10.25345/C57659V12]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: diagnoal-PASEF ; dia-PASEF ; DatasetType:Proteomics
|
Principal Investigators: (in alphabetical order) |
Roland Bruderer, Biognosys AG, Switzerland |
| Submitting User: | roland_bruderer |
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.
| Number of Files: | |
| Total Size: | |
| Spectra: | |
| Subscribers: | |
| Owner | Reanalyses | |
|---|---|---|
| Experimental Design | ||
|
Conditions:
|
||
|
Biological Replicates:
|
||
|
Technical Replicates:
|
||
| Identification Results | ||
|
Proteins (Human, Remapped):
|
||
|
Proteins (Reported):
|
||
|
Peptides:
|
||
|
Variant Peptides:
|
||
|
PSMs:
|
||
| Quantification Results | ||
|
Differential Proteins:
|
||
|
Quantified Proteins:
|
||
| Browse Dataset Files | |
|
FTP Download Link (click to copy):
|