Enhancing Mass Spectrometry-Based MHC-I Peptide Identification Through a Targeted Database Search Approach

Prathyusha Konda; J. Patrick Murphy; Morten Nielsen; Shashi Gujar

doi:10.1007/978-1-4939-9597-4_19

Enhancing Mass Spectrometry-Based MHC-I Peptide Identification Through a Targeted Database Search Approach

Prathyusha Konda, J. Patrick Murphy, Morten Nielsen, Shashi Gujar

Medicine

Research output: Chapter in Book/Report/Conference proceeding › Chapter

3 Citations (Scopus)

Abstract

MHC-bound peptide ligands dictate the activation and specificity of CD8+ T- cells-based and thus are important for devising T-cell immunotherapies. In recent times, advances in mass spectrometry (MS) have enabled the precise identification of these peptides, wherein MS/MS spectra are compared against a reference proteome. Unfortunately, matching immunopeptide MS/MS to reference proteome databases is hindered by inflated search spaces attributed to the number of matches that need to be considered due to a lack of enzyme restriction. These large search spaces limit the efficiency with which MHC-I peptides are identified. Here we offer a solution to this problem whereby we describe a targeted database search approach and accompanying tool SpectMHC that is based on a priori predicted MHC-I peptides (Murphy et al., J Proteome Res 16:1806–1816, 2017).

Original language	English
Title of host publication	Methods in Molecular Biology
Publisher	Humana Press Inc.
Pages	301-307
Number of pages	7
DOIs	https://doi.org/10.1007/978-1-4939-9597-4_19
Publication status	Published - 2019

Publication series

Name	Methods in Molecular Biology
Volume	2024
ISSN (Print)	1064-3745
ISSN (Electronic)	1940-6029

Bibliographical note

Funding Information:
We gratefully acknowledge Dr. Stefan Stevanovic, Dr. Dan Kowalewski, and Dr. Heiko Schuster (Department of Immunology, Institute for Cell Biology, University of Tubingen) for helpful discussions in devising the targeted database search approach. We also acknowledge Ms. Youra Kim for her support with editing of this document. We acknowledge financial support from the Canadian Institutes of Health Research (CIHR), Canadian Cancer Society Research Institute (CCSRI), the Beatrice Hunter Cancer Research Institute (BHCRI), and the Dalhousie Medical Research Foundation (DMRF).

Publisher Copyright:
© Springer Science+Business Media, LLC, part of Springer Nature 2019.

ASJC Scopus Subject Areas

Molecular Biology
Genetics

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10.1007/978-1-4939-9597-4_19

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title = "Enhancing Mass Spectrometry-Based MHC-I Peptide Identification Through a Targeted Database Search Approach",

abstract = "MHC-bound peptide ligands dictate the activation and specificity of CD8+ T- cells-based and thus are important for devising T-cell immunotherapies. In recent times, advances in mass spectrometry (MS) have enabled the precise identification of these peptides, wherein MS/MS spectra are compared against a reference proteome. Unfortunately, matching immunopeptide MS/MS to reference proteome databases is hindered by inflated search spaces attributed to the number of matches that need to be considered due to a lack of enzyme restriction. These large search spaces limit the efficiency with which MHC-I peptides are identified. Here we offer a solution to this problem whereby we describe a targeted database search approach and accompanying tool SpectMHC that is based on a priori predicted MHC-I peptides (Murphy et al., J Proteome Res 16:1806–1816, 2017).",

author = "Prathyusha Konda and Murphy, {J. Patrick} and Morten Nielsen and Shashi Gujar",

note = "Funding Information: We gratefully acknowledge Dr. Stefan Stevanovic, Dr. Dan Kowalewski, and Dr. Heiko Schuster (Department of Immunology, Institute for Cell Biology, University of Tubingen) for helpful discussions in devising the targeted database search approach. We also acknowledge Ms. Youra Kim for her support with editing of this document. We acknowledge financial support from the Canadian Institutes of Health Research (CIHR), Canadian Cancer Society Research Institute (CCSRI), the Beatrice Hunter Cancer Research Institute (BHCRI), and the Dalhousie Medical Research Foundation (DMRF). Publisher Copyright: {\textcopyright} Springer Science+Business Media, LLC, part of Springer Nature 2019.",

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AU - Nielsen, Morten

AU - Gujar, Shashi

N1 - Funding Information: We gratefully acknowledge Dr. Stefan Stevanovic, Dr. Dan Kowalewski, and Dr. Heiko Schuster (Department of Immunology, Institute for Cell Biology, University of Tubingen) for helpful discussions in devising the targeted database search approach. We also acknowledge Ms. Youra Kim for her support with editing of this document. We acknowledge financial support from the Canadian Institutes of Health Research (CIHR), Canadian Cancer Society Research Institute (CCSRI), the Beatrice Hunter Cancer Research Institute (BHCRI), and the Dalhousie Medical Research Foundation (DMRF). Publisher Copyright: © Springer Science+Business Media, LLC, part of Springer Nature 2019.

PY - 2019

Y1 - 2019

N2 - MHC-bound peptide ligands dictate the activation and specificity of CD8+ T- cells-based and thus are important for devising T-cell immunotherapies. In recent times, advances in mass spectrometry (MS) have enabled the precise identification of these peptides, wherein MS/MS spectra are compared against a reference proteome. Unfortunately, matching immunopeptide MS/MS to reference proteome databases is hindered by inflated search spaces attributed to the number of matches that need to be considered due to a lack of enzyme restriction. These large search spaces limit the efficiency with which MHC-I peptides are identified. Here we offer a solution to this problem whereby we describe a targeted database search approach and accompanying tool SpectMHC that is based on a priori predicted MHC-I peptides (Murphy et al., J Proteome Res 16:1806–1816, 2017).

AB - MHC-bound peptide ligands dictate the activation and specificity of CD8+ T- cells-based and thus are important for devising T-cell immunotherapies. In recent times, advances in mass spectrometry (MS) have enabled the precise identification of these peptides, wherein MS/MS spectra are compared against a reference proteome. Unfortunately, matching immunopeptide MS/MS to reference proteome databases is hindered by inflated search spaces attributed to the number of matches that need to be considered due to a lack of enzyme restriction. These large search spaces limit the efficiency with which MHC-I peptides are identified. Here we offer a solution to this problem whereby we describe a targeted database search approach and accompanying tool SpectMHC that is based on a priori predicted MHC-I peptides (Murphy et al., J Proteome Res 16:1806–1816, 2017).

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Enhancing Mass Spectrometry-Based MHC-I Peptide Identification Through a Targeted Database Search Approach

Abstract

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