title: Comparison of higher energy collisional dissociation and collision-induced dissociation MS/MS sequencing methods for identification of naturally occurring peptides in human urine.
abstract: OBJECTIVE
  The aim of this study is to determine the best fragmentation method for sequence identification of naturally occurring urinary peptides in the field of clinical proteomics.
  
  
  METHODS
  We used LC-MS/MS analysis of urine samples to determine the analytical performance of higher energy collisional dissociation (HCD), CID with high and low resolution MS/MS for the identification of naturally occurring peptides in the low molecular weight urinary proteome.
  
  
  RESULTS
  HCD and CID high-resolution generated a 22% error rate in peptide sequence identifications. CID low-resolution showed significantly higher error rates (37%). Excluding the error rate (i.e rejection of cysteine-containing peptides), we observed a higher degree of overlap between HCD and CID high resolution for identification of peptide sequences of rank 1 and cross-correlation ≥ 1.9 (262 peptide sequences) compared to CID low (208 peptide sequences with HCD and 192 peptide sequences with CID high). Reproducibility of detected peptides in three out of the five replicates was also higher in HCD and CID high in relation to CID low resolution.
  
  
  CONCLUSIONS
  Our data demonstrated that HCD and CID high-resolution performed with better accuracy and reproducibility than CID low resolution in respect to the identification of naturally occurring urinary peptide sequences.
authors.affiliation: Charite-Universitätsmedizin Berlin, Berlin, Germany.|Mosaiques Diagnostics GmbH, Hanover, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Pejchinovski
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.
authors.forename: Julie
authors.initials: J
authors.lastname: Klein
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.
authors.forename: Adela
authors.initials: A
authors.lastname: Ramírez-Torres
authors.affiliation: Biotechnology Division, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
authors.forename: Vasiliki
authors.initials: V
authors.lastname: Bitsika
authors.affiliation: Biotechnology Division, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
authors.forename: George
authors.initials: G
authors.lastname: Mermelekas
authors.affiliation: Biotechnology Division, Biomedical Research Foundation, Academy of Athens, Athens, Greece.
authors.forename: Antonia
authors.initials: A
authors.lastname: Vlahou
authors.affiliation: Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
authors.forename: William
authors.initials: W
authors.lastname: Mullen
authors.affiliation: Mosaiques Diagnostics GmbH, Hanover, Germany.|Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
authors.forename: Harald
authors.initials: H
authors.lastname: Mischak
authors.affiliation: Universitätsklinikum RWTH Aachen, Institute of Molecular Cardiovascular Research, Aachen, Germany.
authors.forename: Vera
authors.initials: V
authors.lastname: Jankowski
mesh_terms: D000595:Amino Acid Sequence; D006801:Humans; D008969:Molecular Sequence Data; D010446:Peptide Fragments / Q000737:chemistry / Q000652:urine*; D015203:Reproducibility of Results; D020539:Sequence Analysis, Protein; D053719:Tandem Mass Spectrometry; D016482:Urinalysis / Q000379:methods
chemical_list: D010446:Peptide Fragments
keywords: Biomarkers; Clinical proteomics; MS/MS sequencing; Peptide fragments