Proteomics

Dataset Information

94

Plasmodium falciparum schizont phosphoproteome


ABSTRACT: Plasmodium falciparum schizont proteins were extracted using SDS, digested with trypsin and phosphopeptides were enriched using IMAC. Phosphopeptides were analysed using either decision tree or data dependent neutral loss triggered ETD acquisition. All raw MS data files were processed and converted into MGF file format using Proteome Discoverer 1.1 (Thermo Scientific). A precursor filter of 600-10000 Da and a non-fragment filter were applied to ETD spectra to remove un-reacted precursor peaks, charge reduced precursor peaks, neutral losses from charge reduced precursors and FT Overtones using default settings. All ion trap spectra with less than 15 fragmentation peaks were removed and a signal to noise filter of 3 was applied to all spectra. All datasets were searched using Mascot v2.2 (Matrix Science) against a combined Human (IPI, 2010) and Plasmodium falciparum (GeneDB) sequence database (79,637 sequences) using the following search parameters: trypsin with a maximum of 3 missed cleavages, 10 ppm for MS mass tolerance, 0.5 Da for MS/MS mass tolerance, with Acetyl (Protein N-term), Oxidation (M), Deamidated (NQ), Carbamidomethyl (C) and Phospho ST set as variable modifications. ETD spectra were searched using c, z and y ion series and CID data was searched using b and y ion series.  All searches used Mascot’s automated decoy database searching.

INSTRUMENT(S): LTQ Orbitrap Velos, instrument model

ORGANISM(S): Plasmodium Falciparum (isolate 3d7)

SUBMITTER: Mark Collins  

PROVIDER: PXD000070 | Pride | 2014-04-24

REPOSITORIES: Pride

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Publications

Confident and sensitive phosphoproteomics using combinations of collision induced dissociation and electron transfer dissociation.

Collins Mark O MO   Wright James C JC   Jones Matthew M   Rayner Julian C JC   Choudhary Jyoti S JS  

Journal of proteomics 20140321


We present a workflow using an ETD-optimised version of Mascot Percolator and a modified version of SLoMo (turbo-SLoMo) for analysis of phosphoproteomic data. We have benchmarked this against several database searching algorithms and phosphorylation site localisation tools and show that it offers highly sensitive and confident phosphopeptide identification and site assignment with PSM-level statistics, enabling rigorous comparison of data acquisition methods. We analysed the Plasmodium falciparu  ...[more]

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