Liquid chromatography mass spectrometry methods aim to yield high peptide and protein identifications while retaining quantitative accuracy and precision. To increase the analytical performance of the timsTOF mass spectrometers, researchers have recently proposed diagonal dia-PASEF acquisition methods termed as synchro- or midia-PASEF which attempt to acquire the ion cloud more efficiently (Skowronek, 2023; Distler, 2023). These methods operate by seamlessly and continuously following the observed diagonal shape of the precursor ion density. While such methods promise to cover the observed ion-cloud more efficiently, their utility is currently still hampered by a lack of systematic method evaluation. We therefore set out to optimize the diagonal-PASEF acquisitions on a timsTOF-HT mass spectrometer for different applications.

We first developed an automated Rshiny-based solution that can seamlessly and efficiently compute any diagonal-PASEF method from dda-PASEF or dia-PASEF acquisitions. We show that this tool can build methods with different specifications depending on user-desires on vastly different biological matrices. Next, we optimized the diagonal-PASEF acquisitions in respect to their ion-mobility settings. We infused a HEK-293 sample at 100 ng on a 17-minute analytical gradient on our timsTOF-HT and analyzed the data in Spectronaut 19. We found that the optimal ion-mobility settings yielded up to 10% more protein groups and up to 56% more precursors compared to settings that could have been chosen if no systematic optimization had been conducted. Next, we optimized the overall width of the diagonal-PASEF methods and the number of slices for each diagonal-PASEF method systematically at a loading amount of 10, 100 and 800 ng. The optimal method was found to strongly differ across the tested loadings indicating that diagonal-PASEF strongly benefits from systematic method optimization efforts. The best performing diagonal-PASEF method achieved on average 9% and 2% more protein group identifications against a set of matching dia-PASEF methods at 10 ng and 100 ng of loading specifically while at 800 ng diagonal-PASEF achieved 2% lower protein group identifications against a set of dia-PASEF methods. The experiments indicated that diagonal-PASEF could be a significant extension of the dia-PASEF group of methods.

To test the performance of our optimized method we evaluated the accuracy and candidate recovery in a controlled quantitative experiment using a 4-species mixture in known ratios. Here, we found that the diagonal-PASEF method not only improved the precision by up to 30% but also the accuracy by up to 26% compared to dia-PASEF. This resulted in an increase of the truly differential abundant proteins at 5% error rate by up to 53%.

In conclusion, we show that the improved duty cycle of the diagonal window dia-PASEF methods together with the systematic optimization of the methods holds a significant potential for quantitative DIA proteomics.