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Journal article

Mass spectrometry–based identification of MHC-bound peptides for immunopeptidomics

Abstract:
Peptide antigens bound to molecules encoded by the major histocompatibility complex (MHC) and presented on the cell surface form the targets of T lymphocytes. This critical arm of the adaptive immune system facilitates the eradication of pathogen-infected and cancerous cells, as well as the production of antibodies. Methods to identify these peptide antigens are critical to the development of new vaccines, for which the goal is the generation of effective adaptive immune responses and long-lasting immune memory. Here, we describe a robust protocol for the identification of MHC-bound peptides from cell lines and tissues, using nano-ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (nUPLC–MS/MS) and recent improvements in methods for isolation and characterization of these peptides. The protocol starts with the immunoaffinity capture of naturally processed MHC-peptide complexes. The peptides dissociate from the class I human leukocyte antigens (HLAs) upon acid denaturation. This peptide cargo is then extracted and separated into fractions by HPLC, and the peptides in these fractions are identified using nUPLC–MS/MS. With this protocol, several thousand peptides can be identified from a wide variety of cell types, including cancerous and infected cells and those from tissues, with a turnaround time of 2–3 d.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41596-019-0133-y

Authors

More by this author
Role:
Author
ORCID:
0000-0003-0532-8331
More by this author
Role:
Author
ORCID:
0000-0002-2787-1282
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Jenner Institute
Role:
Author
ORCID:
0000-0002-9283-0743


Publisher:
Springer Nature
Journal:
Nature Protocols More from this journal
Volume:
14
Issue:
6
Pages:
1687-1707
Publication date:
2019-05-15
Acceptance date:
2019-01-08
DOI:
EISSN:
1750-2799
ISSN:
1754-2189
Pmid:
31092913


Language:
English
Pubs id:
pubs:1032980
UUID:
uuid:e805f2e4-749a-4204-8238-c292c9179ece
Local pid:
pubs:1032980
Source identifiers:
1032980
Deposit date:
2019-07-18
ARK identifier:

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