In the realm of proteomics, accurate and precise relative protein quantitation is the key to unravel the complex secrets of biological processes. In recent years there has been a shift towards analyzing complex proteomics samples in shorter time to keep up with the increasing demand of sample throughput. Dia-PASEF is an advanced variant of Data-Independent Acquisition (DIA), capitalizing on the additional dimension of separation by trapped ion mobility separation (TIMS). We applied more advanced (py_diAID, vistaScan) window schemes to evaluate their performance on complex proteomics samples analyzed from different amounts in short gradient times.

Tryptic digests of human cell lysate (in-house digest), Saccharomyces cerevisiae (Promega) and E. coli (Waters) were used to evaluate the performance of sophisticated DIA methods (py_diAID and VistaScan) for short gradients. Digests were loaded on a 15cm C18 column (75μm, 1.6μm, Aurora, IonOpticks) using a nanoElute 2 nano HPLC (Bruker) coupled to a timsTOF instrument (Bruker) via a CaptiveSpray source (Bruker) using a 15-min ACN gradient. Data were processed in Spectronaut (v19, Biognosys) using library-free mode (directDIA+™). For direct database identifications from dia-PASEF runs, we used human, E. coli, and yeast Uniprot fasta files. False discovery rate (FDR) was controlled at 1% for peptide and protein group level.

In our study we found that using a variable window-based dia-PASEF method enables measurement of nearly the complete yeast proteome in 15 minutes by identifying more than 4500 protein groups using library-free data processing. 95% of the protein groups were identified and quantified with CV values below 20% from triplicate injections and 83.1% with CV <10%. On average 50,233 peptides were identified with very low variation of ±350 peptides between replicates. From a human protein digest sample, representing a higher complexity proteome, nearly 113,000 stripped peptide sequences from over 8000 protein groups have been identified with comparable reproducibility to the yeast proteome measurements.  Samples mixed in defined ratios (HeLa, yeast, E. coli) were used to evaluate the setup for quantitative proteomics. Within a 15 min gradient we could identify and quantify over 13,000 from 400ng sample, with on average 10 peptides being identified per protein group. Investigation of the quantitative performance showed low median coefficient of variation for the replicate runs at around 5% on protein group level and quantitative accuracy with low standard deviation. Lastly, we investigated performance of the timsTOF platform using further optimized schemes based on VistaScan, a method allowing to scan the quadrupole synchronously with the TIMS ramp during the mobility scan to optimally cover the ion population in the ion-mobility-mass to charge plane.