Dataset Information

Synchro-PASEF slices peptide precursors enabling specific fragment extraction and interference removal in data independent acquisition

ABSTRACT: Data independent acquisition methods have become increasingly popular in mass spectrometry (MS)-based proteomics because they enable parallel and continuous acquisition of fragment spectra. However, these advantages come with the challenge of correctly reconstructing the precursor-fragment relationship in these highly multiplexed spectra for reliable identification and quantification. Here we introduce a scan mode for the combination of trapped ion mobility spectrometry (TIMS) with parallel accumulation – serial fragmentation (PASEF) that naturally and continuously follows the ion cloud in ion mobility and peptide mass dimensions as opposed to the step functions we employed before. Termed synchro-PASEF, it increases fragment yield several fold at sub-second cycle times. The quadrupole selection window moves synchronously through the mass and ion mobility range, deconvoluting the DIA spectra and defining precursor-quadrupole relationships. In this process, the quadrupole slices through the peptide precursors, which separates fragment ion signals of each precursor into adjacent synchro-PASEF scans. This precisely defines precursor – fragment relationship in ion mobility and mass dimensions. Importantly, the two parts of the fragment ion transitions in synchro-PASEF provide a further dimension of specificity via a lock and key mechanism. This is especially advantageous for quantification, where signals from interfering precursors in the dia selection window only affect the top or bottom part of the fragment ion, allowing them to be filtered out. In this paper, we establish the defining features of synchro-PASEF and explore its potential for proteomics analyses.

INSTRUMENT(S): timsTOF Pro 2

ORGANISM(S): Homo Sapiens (human) Bos Taurus (bovine) Oryctolagus Cuniculus (rabbit) Candida Albicans (yeast)

SUBMITTER: Mario Oroshi

LAB HEAD: Matthias Mann

PROVIDER: PXD037766 | Pride | 2023-03-10

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20220923_TIMS03_PaSk_SA_4prot_200fmol_Evo05_3min_IM0713_classical_SyS_4MS_wCE_S4-G3_1_32594.d.zip	Other
	20220923_TIMS03_PaSk_SA_4prot_200fmol_Evo05_6min_IM0713_classical_SyS_4MS_wCE_S4-G4_1_32595.d.zip	Other
	20220923_TIMS03_PaSk_SA_4prot_Evo05_11min_IM0713_classical_SyS_4MS_wCE_S2-C3_1_32343.d.zip	Other
	20220923_TIMS03_PaSk_SA_4prot_Evo05_21min_IM0713_classical_SyS_4MS_wCE_S2-C8_1_32384.d.zip	Other
	20220923_TIMS03_PaSk_SA_4prot_Evo05_21min_IM0713_ddaPASEF_wCE_S2-A8_1_32382.d.zip	Other

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Publications

Synchro-PASEF Allows Precursor-Specific Fragment Ion Extraction and Interference Removal in Data-Independent Acquisition.

Skowronek Patricia P Krohs Florian F Lubeck Markus M Wallmann Georg G Itang Ericka C M ECM Koval Polina P Wahle Maria M Thielert Marvin M Meier Florian F Willems Sander S Raether Oliver O Mann Matthias M

Molecular & cellular proteomics : MCP 20221222 2

Data-independent acquisition (DIA) methods have become increasingly popular in mass spectrometry-based proteomics because they enable continuous acquisition of fragment spectra for all precursors simultaneously. However, these advantages come with the challenge of correctly reconstructing the precursor-fragment relationships in these highly convoluted spectra for reliable identification and quantification. Here, we introduce a scan mode for the combination of trapped ion mobility spectrometry wi ...[more]

PMID: 36566012

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Project description:Although current mass spectrometry (MS)-based proteomics identifies and quantifies thousands of proteins and (modified) peptides, only a minority of them are subjected to in-depth downstream analysis. With the advent of automated processing workflows, biologically or clinically important results within a study are rarely validated by visualization of the underlying raw information. Although several tools for this are in principle available, they are often not integrated into the overall analysis nor readily extendable with new approaches. To remedy this, we developed AlphaViz, an open-source Python package to superimpose output from common analysis workflows on the raw data for quick and easy visualization and validation of protein and peptide identifications. AlphaViz takes advantage of recent breakthroughs in the deep learning-assisted prediction of experimental peptide properties to allow manual assessment of the expected and measured peptide result deviation. We focused on the visualization of the 4-dimensional data cuboid provided by Bruker TimsTOF instruments, where the ion mobility dimension, besides intensity and retention time, can be predicted and used for verification. We illustrate how AlphaViz can quickly validate or invalidate peptide identifications regardless of the score given to them by automated workflows. Furthermore, we provide a â€˜predict modeâ€™ that can locate peptides present in the raw data but not reported by the search engine. This is illustrated with dilution series and the recovery of missing values from experimental replicates. Applied to phosphoproteomics of the EGF-signaling pathway, we show how key signaling nodes can be validated to enhance confidence for downstream interpretation or follow-up experiments. AlphaViz follows accepted standards for open-source software development, including extensive documentation, testing and continuous integration. It features an easy-to-install graphical user interface for end-users and a modular Python package for bioinformaticians. We hope that AlphaViz can help to make validation of critical proteomics results a standard feature in MS-based proteomics.