A tissue-based draft map of the murine MHC class I immunopeptidome

• DOI: 10.1038/sdata.2018.157
• Publication Date: 2018-08-07T13:10:20Z
• Authors: Heiko Schuster; Wenguang Shao; Tobias Weiss; Patrick G.A. Pedr...; Patrick Roth; Michael Weller; David S. Campbell; Eric W. Deutsch; Robert L. Moritz; Oliver Planz; Hans-Georg Rammensee; Ruedi Aebersold; Etienne Caron
• Keywords: Statistics and Probability; Data Descriptor; 610 Medicine & health; Library and Information Sciences; 1710 Information Systems; Mass Spectrometry; Education; Mice; 03 medical and health sciences; 1706 Computer Science Applications; Animals; 1804 Statistics, Probability and Uncertainty; 2613 Statistics and Probability; 0303 health sciences; Histocompatibility Antigens Class I; 10040 Clinic for Neurology; Computer Science Applications; 3. Good health; Mice, Inbred C57BL; Organ Specificity; 3309 Library and Information Sciences; Statistics, Probability and Uncertainty; Peptides; 3304 Education; Information Systems

AbstractThe large array of peptides presented to CD8+ T cells by major histocompatibility complex (MHC) class I molecules is referred to as the MHC class I immunopeptidome. Although the MHC class I immunopeptidome is ubiquitous in mammals and represents a critical component of the immune system, very little is known, in any species, about its composition across most tissues and organs in vivo. We applied mass spectrometry (MS) technologies to draft the first tissue-based atlas of the murine MHC class I immunopeptidome in health. Peptides were extracted from 19 normal tissues from C57BL/6 mice and prepared for MS injections, resulting in a total number of 28,448 high-confidence H2Db/Kb-associated peptides identified and annotated in the atlas. This atlas provides initial qualitative data to explore the tissue-specificity of the immunopeptidome and serves as a guide to identify potential tumor-associated antigens from various cancer models. Our data were shared via PRIDE (PXD008733), SysteMHC Atlas (SYSMHC00018) and SWATH Atlas. We anticipate that this unique dataset will be expanded in the future and will find wide applications in basic and translational immunology.