An Integrated Approach for Discovering Noncanonical MHC‑I Peptides Encoded by Small Open Reading Frames

MHC-I peptides are a group of important
immunopeptides presented
by major histocompatibility complex (MHC) on the cell surface for
immune recognition. The majority of reported MHC-I peptides are derived
from protein coding sequences, and noncanonical peptides translated
from small open reading frames (sORF) are largely unknown due to the
lack of accurate and sensitive detection methods. Herein we report
an efficient approach that implements complementary bioinformatic
strategies to improve the identification of noncanonical MHC-I peptides.
In a database search strategy, noncanonical immunopeptides mapping
was optimized by combining three complementary pipelines to construct
predicted sORF databases from Ribo-seq data. In a de novo peptide sequencing strategy, MS data search results were filtered
against sORF databases to pin down additional noncanonical immunopeptides.
In total, 308 noncanonical immunopeptides were identified from two
tumor cell lines with selected ones vigorously validated. Our approach
is a handy solution to identify noncanonical MHC peptides with Ribo-seq
and MS data. Meanwhile, the novel noncanonical immunopeptides identified
with this method could shed insights on fundamental immunology as
well as cancer immunotherapies.