Oral Presentation 28th Annual Lorne Proteomics Symposium 2023

High-throughput proteomics and phosphoproteomics of rat tissue using microflow Zeno SWATH. (#7)

Erin M Humphries 1 2 , Dylan Xavier 1 , Keith Ashman 3 , Jeremy Potriquet 3 , Peter G Hains 1 , Phil J Robinson 1 2
  1. Children’s Medical Research Institute, Westmead, NSW, Australia
  2. Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
  3. Sciex, Sydney, NSW, Australia

Microflow liquid chromatography-tandem mass spectrometry is a robust analytical tool for the high-throughput detection of peptides in clinical samples. In contrast, nanoflow is commonly used for the in-depth detection of phosphopeptides using long gradients and columns with smaller internal diameters. Here we explore a trap and elute micro-flow set-up for high-throughput proteomic and phosphoproteomic workflows using a Waters UHPLC system coupled to a ZenoTOF 7600 system.

For proteomic workflows, fresh frozen rat tissue from eight organs were analysed in technical replicates using 400 ng loads, a 30-minute gradient, a 5-minute trapping system, and a 50 variable window Zeno SWATH method. The proteomic data was processed using two computational pipelines to compare their performance. Protein identifications from rat brain, kidney, testis, lung, and spleen were similar across the two pipelines, however Fragpipe quantified significantly more proteins from liver (2700 vs 2500), heart (2300 vs 2100), and muscle (2100 vs 1700) than DIA-NN. Of the rat organs, kidney had the highest number of identifications with roughly 32000 precursors and 2900 proteins at 1% FDR using Fragpipe.

For phosphoproteomic workflows, 100 μg of rat tissue was enriched in phosphopeptides via titanium and zirconium IMAC magnetic beads, cleaned by micro-elution solid phase extraction and analysed in Zeno SWATH using a 15-minute or 30-minute gradient. The phosphoproteomic data was again processed using two computational pipelines to compare their performance. Spectronaut directDIA quantified significantly more class I phosphosites than Fragpipe (6608 vs 5764).

Both proteomic data from Fragpipe and phosphoproteomic data from Spectronaut showed distinct clustering of replicates for rat organs using principal component analysis. This indicates that both the proteome and phosphoproteome can distinguish between rat organs based on peptide or phosphosite intensities.

The combined data shows that the trap-elute micro-flow setup on the ZenoTOF 7600 performs well for proteomics, identifying similar numbers of proteins in a 30-minute Zeno SWATH run using a 400 ng load compared to a 90-minute SWATH run with a 2 μg load on a TripleTOF 6600. Future work should focus on optimising the workflow for Zeno SWATH phosphoproteomics to increase identifications.