MassIVE MSV000087034

Partial Public PXD024676

A systematic evaluation of semispecific peptide search parameter enables identification of previously undescribed N-terminal peptides and conserved proteolytic processing in cancer cell lines

Description

Background: Liquid chromatography- tandem mass spectrometry (LC-MS/MS) has become the most commonly used technique in explorative proteomic research. A variety of open-source tools for peptide-spectrum matching have become available. Most analyses of explorative MS data are performed using conventional settings, such as fully specific enzymatic constraints. Here we evaluated the impact of the fragment mass tolerance as well as the enzymatic constraints on the performance of three search engines. Methods: The open-source search engines including Myrimatch, xTandem and MSGF+ were evaluated with regard to suitability for semi- and unspecific searches as well as the importance of accurate fragment mass spectra. Applying the most suited parameters we performed a semispecific reanalysis of the published NCI-60 deep proteome data. Results: Semi- and unspecific LC-MS/MS data analyses particularly benefit from accurate fragment mass spectra while this effect is less pronounced for conventional, fully specific peptide-spectrum matching. Search speed differed notably between the three search engines with regard to semi- and non-specific peptide-spectrum matching. Semi-specific reanalysis of NCI-60 proteome data revealed hundreds of previously undescribed N-terminal peptides, including cases of proteolytic processing or likely alternative translation start sites, some of which were ubiquitously present in all cell lines of the reanalyzed panel. Conclusions: Highly accurate MS2 fragment data in combination with modern open-source search algorithms facilitate the confident identification of semispecific peptides from large proteomic datasets. The identification of previously undescribed N-terminal peptides in published studies highlights the potential of future reanalysis and data mining in proteomic datasets. The converted .mzML files as well as the sequence databases for the different biological samples are provided. The analysis results are provided as compressed folders containing the results for multiple searches for each .mzML, e.g. using different enzymatic constraints as well as different fragment mass tolerance settings. The NCI-60 raw data from nine representative cancer cell lines was retrieved from https://www.proteomicsdb.org/proteomicsdb/#projects/35/258 and converted to the open mzML format using msconvert using default settings with an additional "metadataFixer" filter. Here we provide the sequence database file as well as the complete reanalysis as compressed galaxy history files which can be downloaded, extracted and imported on https://usegalaxy.eu. [doi:10.25345/C5D22P] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: Endogenous proteolysis ; Fragment mass tolerance ; NCI-60 reanalysis ; Semispecific peptide search ; Mass spectrometry

Contact

Principal Investigators:
(in alphabetical order)
Oliver Schilling, University of Freiburg, N/A
Submitting User: MatthiasF
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Experimental Design
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Identification Results
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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 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.