MassIVE MSV000094389

Partial Public PXD050922

An accessible workflow for high sensitivity proteomics using Parallel Accumulation - Serial Fragmentation (PASEF)

Description

Deep and accurate proteome analysis is crucial for understanding cellular processes and disease mechanisms, however, it is also challenging to implement in routine settings. In this protocol we combine a robust and accessible chromatographic platform with an equally robust and high-performance mass spectrometric set up, to enable routine yet in-depth proteome coverage for a broad community. This entails tip-based sample preparation and pre-formed gradients combined with trapped ion mobility - quadrupole - time-of-flight mass spectrometry. It enables parallel accumulation - serial fragmentation (PASEF), in which all ions are used but spectra are resolved by ion mobility. Combined with data-independent acquisition (dia-PASEF), it offers high peak sampling rates and near-complete ion coverage. Here we explain how to balance quantitative accuracy, specificity, proteome coverage, and sensitivity by choosing best PASEF and DIA method parameters. The protocol streamlines the liquid chromatography - mass spectrometry setup and enables PASEF method generation and evaluation for varied samples. Our py_diAID tool automatically generates acquisition schemes where isolation windows are optimally positioned on the mass-to-charge and ion mobility plane. Hands-on time is three hours, and simple biological projects can be performed in three days. The implementation shown here allows reproducible quantification of 7,300 proteins in a human cancer cell line in 21 min with quadruplicate single-shot injections and 27,000 phosphosites in 21 min from for phospho-enriched quadruplicates. Synchro-PASEF, a next-generation scan mode, currently offers proteomic depth comparable to that of dia-PASEF. When analyzed with AlphaDIA, it showed superior quantitative reproducibility owing to its drastically reduced cycle times and high sampling efficiency. [doi:10.25345/C54T6FF0H] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: TIMS ; PASEF ; data-independent acquisition ; scan mode ; TOF

Contact

Principal Investigators:
(in alphabetical order)
Matthias Mann, Proteomics and Signal Transduction Max Planck Institute of Biochemistry Am Klopferspitz 18 D-82152 Martinsried, N/A
Submitting User: patricias
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Experimental Design
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Identification Results
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Number of distinct conditions across all analyses (original submission and reanalyses) associated with this dataset.

Distinct condition labels are counted across all files submitted in the "Metadata" category having a "Condition" column in this dataset.

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Number of distinct biological replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct technical replicates across all analyses (original submission and reanalyses) associated with this dataset.

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Originally identified proteins that were automatically remapped by MassIVE to proteins in the SwissProt human reference database.

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Number of distinct protein accessions reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct unmodified peptide sequences reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct peptide sequences (including modified variants or peptidoforms) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Total number of peptide-spectrum matches (i.e. spectrum identifications) reported across all analyses (original submission and reanalyses) associated with this dataset.

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Number of distinct proteins quantified across all analyses (original submission and reanalyses) associated with this dataset.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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Number of distinct proteins found to be differentially abundant in at least one comparison across all analyses (original submission and reanalyses) associated with this dataset.

A protein is differentially abundant if its change in abundance across conditions is found to be statistically significant with an adjusted p-value <= 0.05 and lists no issues associated with statistical tests for differential abundance.

Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

"N/A" means no results of this type were submitted.
This dataset may not contain all raw spectra data as originally deposited in PRIDE. It has been imported to MassIVE for reanalysis purposes, so its spectra data here may consist solely of processed peak lists suitable for reanalysis with most software.