Literature DB >> 23094866

Automated phosphopeptide identification using multiple MS/MS fragmentation modes.

Mathias Vandenbogaert1, Véronique Hourdel, Olivia Jardin-Mathé, Jean Bigeard, Ludovic Bonhomme, Véronique Legros, Heribert Hirt, Benno Schwikowski, Delphine Pflieger.   

Abstract

Phosphopeptide identification is still a challenging task because fragmentation spectra obtained by mass spectrometry do not necessarily contain sufficient fragment ions to establish with certainty the underlying amino acid sequence and the precise phosphosite. To improve upon this, it has been suggested to acquire pairs of spectra from every phosphorylated precursor ion using different fragmentation modes, for example CID, ETD, and/or HCD. The development of automated tools for the interpretation of these paired spectra has however, until now, lagged behind. Using phosphopeptide samples analyzed by an LTQ-Orbitrap instrument, we here assess an approach in which, on each selected precursor, a pair of CID spectra, with or without multistage activation (MSA or MS2, respectively), are acquired in the linear ion trap. We applied this approach on phosphopeptide samples of variable proteomic complexity obtained from Arabidopsis thaliana . We present a straightforward computational approach to reconcile sequence and phosphosite identifications provided by the database search engine Mascot on the spectrum pairs, using two simple filtering rules, at the amino acid sequence and phosphosite localization levels. If multiple sequences and/or phosphosites are likely, they are reported in the consensus sequence. Using our program FragMixer, we could assess that on samples of moderate complexity, it was worth combining the two fragmentation schemes on every precursor ion to help efficiently identify amino acid sequences and precisely localize phosphosites. FragMixer can be flexibly configured, independently of the Mascot search parameters, and can be applied to various spectrum pairs, such as MSA/ETD and ETD/HCD, to automatically compare and combine the information provided by these more differing fragmentation modes. The software is openly accessible and can be downloaded from our Web site at http://proteomics.fr/FragMixer.

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Year:  2012        PMID: 23094866     DOI: 10.1021/pr300507j

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  6 in total

Review 1.  Strategies for mass spectrometry-based phosphoproteomics using isobaric tagging.

Authors:  Xinyue Liu; Rose Fields; Devin K Schweppe; Joao A Paulo
Journal:  Expert Rev Proteomics       Date:  2021-10-28       Impact factor: 3.940

2.  Quantitative Phosphoproteomic Analysis Reveals Shared and Specific Targets of Arabidopsis Mitogen-Activated Protein Kinases (MAPKs) MPK3, MPK4, and MPK6.

Authors:  Naganand Rayapuram; Jean Bigeard; Hanna Alhoraibi; Ludovic Bonhomme; Anne-Marie Hesse; Joëlle Vinh; Heribert Hirt; Delphine Pflieger
Journal:  Mol Cell Proteomics       Date:  2017-11-22       Impact factor: 5.911

3.  Using SEQUEST with theoretically complete sequence databases.

Authors:  Rovshan G Sadygov
Journal:  J Am Soc Mass Spectrom       Date:  2015-08-04       Impact factor: 3.109

Review 4.  Ion Activation Methods for Peptides and Proteins.

Authors:  Jennifer S Brodbelt
Journal:  Anal Chem       Date:  2015-12-11       Impact factor: 6.986

Review 5.  Advances in quantitative high-throughput phosphoproteomics with sample multiplexing.

Authors:  Joao A Paulo; Devin K Schweppe
Journal:  Proteomics       Date:  2021-03-30       Impact factor: 3.984

6.  Unambiguous phosphosite localization using electron-transfer/higher-energy collision dissociation (EThcD).

Authors:  Christian K Frese; Houjiang Zhou; Thomas Taus; A F Maarten Altelaar; Karl Mechtler; Albert J R Heck; Shabaz Mohammed
Journal:  J Proteome Res       Date:  2013-02-07       Impact factor: 4.466

  6 in total

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