{"doi":"10.3389/fimmu.2021.658601","title":"Distinguishing Signal From Noise in Immunopeptidome Studies of Limiting-Abundance Biological Samples: Peptides Presented by I-Ab in C57BL/6 Mouse Thymus","abstract":"Antigen presentation by MHC-II proteins in the thymus is central to selection of CD4 T cells, but analysis of the full repertoire of presented peptides responsible for positive and negative selection is complicated by the low abundance of antigen presenting cells. A key challenge in analysis of limiting abundance immunopeptidomes by mass spectrometry is distinguishing true MHC-binding peptides from co-eluting non-specifically bound peptides present in the mixture eluted from immunoaffinity-purified MHC molecules. Herein we tested several approaches to minimize the impact of non-specific background peptides, including analyzing eluates from isotype-control antibody-conjugated beads, considering only peptides present in nested sets, and using predicted binding motif analysis to identify core epitopes. We evaluated these methods using well-understood human cell line samples, and then applied them to analysis of the I-A b presented immunopeptidome of the thymus of C57BL/6 mice, comparing this to the more easily characterized splenic B cell and dendritic cell populations. We identified a total of 3473 unique peptides eluted from the various tissues, using a data dependent acquisition strategy with a false-discovery rate of <1%. The immunopeptidomes presented in thymus as compared to splenic B cells and DCs identified shared and tissue-specific epitopes. A broader length distribution was observed for peptides presented in the thymus as compared to splenic B cells or DCs. Detailed analysis of 61 differentially presented peptides indicated a wider distribution of I-A b binding affinities in thymus as compared to splenic B cells. These results suggest different constraints on antigen processing and presentation pathways in central versus peripheral tissues.","journal":"Frontiers in Immunology","year":2021,"id":179393,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":18,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9439,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":726851,"name":"Mollie Jurewicz","orcid":"0000-0001-8482-3060","position":1,"is_corresponding":false},{"id":618674,"name":"Cristina C. Clement","orcid":"0000-0003-1464-407X","position":2,"is_corresponding":false},{"id":726852,"name":"Liying Lu","orcid":"0000-0003-3234-6455","position":3,"is_corresponding":false},{"id":324164,"name":"Laura Santambrogio","orcid":"0000-0002-4674-7041","position":4,"is_corresponding":false},{"id":659732,"name":"Lawrence J. Stern","orcid":"0000-0001-9870-8557","position":5,"is_corresponding":false},{"id":659727,"name":"Padma P. Nanaware","orcid":"0000-0002-8973-3205","position":0,"is_corresponding":true}],"reference_count":51,"raw_metadata":null,"created_at":"2026-07-18T23:47:48.974996Z","pmid":"33995376","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}