title: Influence of various endogenous and artefact modifications on large-scale proteomics analysis.
abstract: BACKGROUND
  Some large-scale proteomics studies in which strong cation exchange chromatography has been applied are used to determine proteomes and post-translational modification dynamics. Although such datasets favour the characterisation of thousands of modified peptides, e.g., phosphorylated and N-α-acetylated, a large fraction of the acquired spectra remain unexplained by standard proteomics approaches. Thus, advanced data processing allows characterisation of a significant part of these unassigned spectra.
  
  
  METHODS
  Our recent investigation of the N-α-acetylation status of plant proteins gave a dataset of choice to investigate further the in-depth characterisation of peptide modifications using Mascot tools associated with relevant validation processes. Such an approach allows to target frequently occurring modifications such as methionine oxidation, phosphorylation or N-α-acetylation, but also the less usual peptide cationisation. Finally, this dataset offers the unique opportunity to determine the overall influence of some of these modifications on the identification score.
  
  
  RESULTS
  Although methionine oxidation has no influence and tends to favour the characterisation of protein N-terminal peptides, peptide alkalinisation shows an adverse effect on peptide average score. Nevertheless, peptide cationisation appears to favour the characterisation of protein C-terminal peptides with a limited to no direct influence on the identification score. Unexpectedly, our investigation reveals the unfortunate combination of the molecular weight of N-α-acetylation and potassium cation that mimics the mass increment of a phosphorylation group.
  
  
  CONCLUSIONS
  Since these characterisations rely upon computational treatment associated with statistical validation approaches such as 'False discovery rates' calculation or post-translational modification position validation, our investigation highlights the limitation of such treatment which is biased by the initial searched hypotheses.
authors.affiliation: CNRS, ISV, UPR2355, Bâtiment 23A, 1 avenue de la Terrasse, F-91198, Gif-sur-Yvette Cedex, France. willy.bienvenut@isv.cnrs-gif.fr
authors.forename: Willy V
authors.initials: WV
authors.lastname: Bienvenut
authors.forename: David
authors.initials: D
authors.lastname: Sumpton
authors.forename: Sergio
authors.initials: S
authors.lastname: Lilla
authors.forename: Aude
authors.initials: A
authors.lastname: Martinez
authors.forename: Thierry
authors.initials: T
authors.lastname: Meinnel
authors.forename: Carmela
authors.initials: C
authors.lastname: Giglione
mesh_terms: D000595:Amino Acid Sequence; D029681:Arabidopsis Proteins / Q000032:analysis / Q000737:chemistry / Q000378:metabolism; D030562:Databases, Protein; D008715:Methionine / Q000032:analysis / Q000737:chemistry / Q000378:metabolism; D008969:Molecular Sequence Data; D010084:Oxidation-Reduction; D010446:Peptide Fragments / Q000032:analysis* / Q000737:chemistry / Q000378:metabolism; D010766:Phosphorylation; D011499:Protein Processing, Post-Translational; D020543:Proteome / Q000032:analysis* / Q000378:metabolism; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results
chemical_list: D029681:Arabidopsis Proteins; D010446:Peptide Fragments; D020543:Proteome; D008715:Methionine