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Title: Effectiveness of CID, HCD, and ETD with FT MS/MS for Degradomic-Peptidomic Analysis: Comparison of Peptide Identification Methods

Abstract

We report on use of an Orbitrap Velos mass spectrometer for comparison of fragmentation methods namely CID-, HCD-, and ETD for FT MS/MS analysis of human blood plasma peptidomic peptides. The peptidomic peptides were able to be identified from CID, HCD, and ETD spectra on specific confidence levels (e.g., 1% false discovery rate) with use of conventional SEQUEST database search software, and the number of identified peptides was increased by ~50% using accurate fragments (e.g., with mass tolerance of 0.05Da) in comparison with traditional moderate accuracy fragments (e.g., with 1 Da mass tolerance) for database search. However, the peptide datasets identified with such decoy search strategy were found to be varied by ~25% in the dataset size and ~20% in the dataset content with type of decoy database and precursor mass tolerances used for database search. CID was evaluated as the largest contributor to the identified peptide datasets, and HCD, and ETD provided ~20% and ~22% respectively additional peptides with accurate fragments for peptide identification, in contrast to ~25% and ~13% respectively with use of moderate accuracy fragments. When long (typically ≥7 amino acids) sequences were used for identification of peptides from the previously published UStags and de novo sequencingmore » methods, HCD was evaluated as the largest contributor, and CID and ETD provided ~26% and ~8% respectively additional peptides from the UStags method and ~26% and ~6% respectively additional peptides from the de novo sequencing method. The peptide datasets identified with the UStags method were little influenced by the decoy database and mass tolerance and 98-99% peptide overlaps could be achieved between these datasets. CID, HCD, and ETD contributed their identifications of various charge state peptides in the m/z range highly overlapped and complementary implementation of CID, HCD, and ETD should be applied to maximize the number of peptides identified. Finally, the investigation presented in this work suggests that selection of fragmentation methods benefits significantly from a careful match with data analysis method applied for identification of peptides and the analysis throughput desired for various purposes of peptidomic-degradomic analysis.« less

Authors:
; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US), Environmental Molecular Sciences Laboratory (EMSL)
Sponsoring Org.:
USDOE
OSTI Identifier:
1025081
Report Number(s):
PNNL-SA-75441
Journal ID: ISSN 1535-3893; 24698; 600306000; TRN: US201120%%265
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Journal Name:
Journal of Proteome Research
Additional Journal Information:
Journal Volume: 10; Journal Issue: 9; Journal ID: ISSN 1535-3893
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 60 APPLIED LIFE SCIENCES; ACCURACY; AMINO ACIDS; BLOOD PLASMA; CHARGE STATES; DATA ANALYSIS; FRAGMENTATION; IMPLEMENTATION; MASS SPECTROMETERS; PEPTIDES; PRECURSOR; SPECTRA; TOLERANCE; Environmental Molecular Sciences Laboratory

Citation Formats

Shen, Yufeng, Tolić, Nikola, Xie, Fang, Zhao, Rui, Purvine, Samuel O., Schepmoes, Athena A., Moore, Ronald, J., Anderson, Gordon A., and Smith, Richard D. Effectiveness of CID, HCD, and ETD with FT MS/MS for Degradomic-Peptidomic Analysis: Comparison of Peptide Identification Methods. United States: N. p., 2011. Web. doi:10.1021/pr200052c.
Shen, Yufeng, Tolić, Nikola, Xie, Fang, Zhao, Rui, Purvine, Samuel O., Schepmoes, Athena A., Moore, Ronald, J., Anderson, Gordon A., & Smith, Richard D. Effectiveness of CID, HCD, and ETD with FT MS/MS for Degradomic-Peptidomic Analysis: Comparison of Peptide Identification Methods. United States. https://doi.org/10.1021/pr200052c
Shen, Yufeng, Tolić, Nikola, Xie, Fang, Zhao, Rui, Purvine, Samuel O., Schepmoes, Athena A., Moore, Ronald, J., Anderson, Gordon A., and Smith, Richard D. Fri . "Effectiveness of CID, HCD, and ETD with FT MS/MS for Degradomic-Peptidomic Analysis: Comparison of Peptide Identification Methods". United States. https://doi.org/10.1021/pr200052c.
@article{osti_1025081,
title = {Effectiveness of CID, HCD, and ETD with FT MS/MS for Degradomic-Peptidomic Analysis: Comparison of Peptide Identification Methods},
author = {Shen, Yufeng and Tolić, Nikola and Xie, Fang and Zhao, Rui and Purvine, Samuel O. and Schepmoes, Athena A. and Moore, Ronald, J. and Anderson, Gordon A. and Smith, Richard D.},
abstractNote = {We report on use of an Orbitrap Velos mass spectrometer for comparison of fragmentation methods namely CID-, HCD-, and ETD for FT MS/MS analysis of human blood plasma peptidomic peptides. The peptidomic peptides were able to be identified from CID, HCD, and ETD spectra on specific confidence levels (e.g., 1% false discovery rate) with use of conventional SEQUEST database search software, and the number of identified peptides was increased by ~50% using accurate fragments (e.g., with mass tolerance of 0.05Da) in comparison with traditional moderate accuracy fragments (e.g., with 1 Da mass tolerance) for database search. However, the peptide datasets identified with such decoy search strategy were found to be varied by ~25% in the dataset size and ~20% in the dataset content with type of decoy database and precursor mass tolerances used for database search. CID was evaluated as the largest contributor to the identified peptide datasets, and HCD, and ETD provided ~20% and ~22% respectively additional peptides with accurate fragments for peptide identification, in contrast to ~25% and ~13% respectively with use of moderate accuracy fragments. When long (typically ≥7 amino acids) sequences were used for identification of peptides from the previously published UStags and de novo sequencing methods, HCD was evaluated as the largest contributor, and CID and ETD provided ~26% and ~8% respectively additional peptides from the UStags method and ~26% and ~6% respectively additional peptides from the de novo sequencing method. The peptide datasets identified with the UStags method were little influenced by the decoy database and mass tolerance and 98-99% peptide overlaps could be achieved between these datasets. CID, HCD, and ETD contributed their identifications of various charge state peptides in the m/z range highly overlapped and complementary implementation of CID, HCD, and ETD should be applied to maximize the number of peptides identified. Finally, the investigation presented in this work suggests that selection of fragmentation methods benefits significantly from a careful match with data analysis method applied for identification of peptides and the analysis throughput desired for various purposes of peptidomic-degradomic analysis.},
doi = {10.1021/pr200052c},
url = {https://www.osti.gov/biblio/1025081}, journal = {Journal of Proteome Research},
issn = {1535-3893},
number = 9,
volume = 10,
place = {United States},
year = {2011},
month = {9}
}