PMID- 36796644
OWN - NLM
STAT- MEDLINE
DCOM- 20230425
LR  - 20230502
IS  - 1535-9484 (Electronic)
IS  - 1535-9476 (Print)
IS  - 1535-9476 (Linking)
VI  - 22
IP  - 4
DP  - 2023 Apr
TI  - Benchmarking Bioinformatics Pipelines in Data-Independent Acquisition Mass 
      Spectrometry for Immunopeptidomics.
PG  - 100515
LID - S1535-9476(23)00024-5 [pii]
LID - 10.1016/j.mcpro.2023.100515 [doi]
LID - 100515
AB  - Immunopeptidomes are the peptide repertoires bound by the molecules encoded by 
      the major histocompatibility complex [human leukocyte antigen (HLA) in humans]. 
      These HLA-peptide complexes are presented on the cell surface for immune T-cell 
      recognition. Immunopeptidomics denotes the utilization of tandem mass 
      spectrometry to identify and quantify peptides bound to HLA molecules. 
      Data-independent acquisition (DIA) has emerged as a powerful strategy for 
      quantitative proteomics and deep proteome-wide identification; however, DIA 
      application to immunopeptidomics analyses has so far seen limited use. Further, 
      of the many DIA data processing tools currently available, there is no consensus 
      in the immunopeptidomics community on the most appropriate pipeline(s) for 
      in-depth and accurate HLA peptide identification. Herein, we benchmarked four 
      commonly used spectral library-based DIA pipelines developed for proteomics 
      applications (Skyline, Spectronaut, DIA-NN, and PEAKS) for their ability to 
      perform immunopeptidome quantification. We validated and assessed the capability 
      of each tool to identify and quantify HLA-bound peptides. Generally, DIA-NN and 
      PEAKS provided higher immunopeptidome coverage with more reproducible results. 
      Skyline and Spectronaut conferred more accurate peptide identification with lower 
      experimental false-positive rates. All tools demonstrated reasonable correlations 
      in quantifying precursors of HLA-bound peptides. Our benchmarking study suggests 
      a combined strategy of applying at least two complementary DIA software tools to 
      achieve the greatest degree of confidence and in-depth coverage of 
      immunopeptidome data.
CI  - Copyright (c) 2023 The Authors. Published by Elsevier Inc. All rights reserved.
FAU - Shahbazy, Mohammad
AU  - Shahbazy M
AD  - Infection and Immunity Program, Biomedicine Discovery Institute, Monash 
      University, Clayton, Victoria, Australia; Department of Biochemistry and 
      Molecular Biology, Monash University, Clayton, Victoria, Australia.
FAU - Ramarathinam, Sri H
AU  - Ramarathinam SH
AD  - Infection and Immunity Program, Biomedicine Discovery Institute, Monash 
      University, Clayton, Victoria, Australia; Department of Biochemistry and 
      Molecular Biology, Monash University, Clayton, Victoria, Australia.
FAU - Illing, Patricia T
AU  - Illing PT
AD  - Infection and Immunity Program, Biomedicine Discovery Institute, Monash 
      University, Clayton, Victoria, Australia; Department of Biochemistry and 
      Molecular Biology, Monash University, Clayton, Victoria, Australia.
FAU - Jappe, Emma C
AU  - Jappe EC
AD  - Evaxion Biotech, Copenhagen, Denmark.
FAU - Faridi, Pouya
AU  - Faridi P
AD  - Department of Medicine, School of Clinical Sciences, Monash University, Clayton, 
      Victoria, Australia. Electronic address: pouya.faridi@monash.edu.
FAU - Croft, Nathan P
AU  - Croft NP
AD  - Infection and Immunity Program, Biomedicine Discovery Institute, Monash 
      University, Clayton, Victoria, Australia; Department of Biochemistry and 
      Molecular Biology, Monash University, Clayton, Victoria, Australia. Electronic 
      address: nathan.croft@monash.edu.
FAU - Purcell, Anthony W
AU  - Purcell AW
AD  - Infection and Immunity Program, Biomedicine Discovery Institute, Monash 
      University, Clayton, Victoria, Australia; Department of Biochemistry and 
      Molecular Biology, Monash University, Clayton, Victoria, Australia. Electronic 
      address: anthony.purcell@monash.edu.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20230214
PL  - United States
TA  - Mol Cell Proteomics
JT  - Molecular & cellular proteomics : MCP
JID - 101125647
RN  - 0 (Peptides)
RN  - 0 (Histocompatibility Antigens Class I)
RN  - 0 (Histocompatibility Antigens Class II)
SB  - IM
MH  - Humans
MH  - *Benchmarking
MH  - *Peptides/analysis
MH  - Histocompatibility Antigens Class I/metabolism
MH  - Proteomics/methods
MH  - Tandem Mass Spectrometry
MH  - Histocompatibility Antigens Class II
PMC - PMC10060114
OTO - NOTNLM
OT  - DIA
OT  - HLA-bound peptides
OT  - immunopeptidomics
OT  - mass spectrometry
OT  - software tools benchmark
OT  - spectral library
COIS- Conflict of interest A. W. P. is a scientific advisor for Bioinformatics 
      Solutions Inc (the provider of PEAKS software). There are no other conflicts of 
      interest declared by the authors.
EDAT- 2023/02/17 06:00
MHDA- 2023/04/25 06:42
PMCR- 2023/02/14
CRDT- 2023/02/16 19:27
PHST- 2022/09/17 00:00 [received]
PHST- 2023/01/26 00:00 [revised]
PHST- 2023/02/06 00:00 [accepted]
PHST- 2023/04/25 06:42 [medline]
PHST- 2023/02/17 06:00 [pubmed]
PHST- 2023/02/16 19:27 [entrez]
PHST- 2023/02/14 00:00 [pmc-release]
AID - S1535-9476(23)00024-5 [pii]
AID - 100515 [pii]
AID - 10.1016/j.mcpro.2023.100515 [doi]
PST - ppublish
SO  - Mol Cell Proteomics. 2023 Apr;22(4):100515. doi: 10.1016/j.mcpro.2023.100515. 
      Epub 2023 Feb 14.