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Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome

Human leukocyte antigen (HLA) molecules are cell-surface glycoproteins that present peptide antigens on the cell surface for surveillance by T lymphocytes, which contemporaneously seek signs of disease. Mass spectrometric analysis allows us to identify large numbers of these peptides (the immunopept...

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Autores principales: Scull, Katherine E., Pandey, Kirti, Ramarathinam, Sri H., Purcell, Anthony W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Biochemistry and Molecular Biology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724885/
https://www.ncbi.nlm.nih.gov/pubmed/34509645
http://dx.doi.org/10.1016/j.mcpro.2021.100143
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author Scull, Katherine E.
Pandey, Kirti
Ramarathinam, Sri H.
Purcell, Anthony W.
author_facet Scull, Katherine E.
Pandey, Kirti
Ramarathinam, Sri H.
Purcell, Anthony W.
author_sort Scull, Katherine E.
collection PubMed
description Human leukocyte antigen (HLA) molecules are cell-surface glycoproteins that present peptide antigens on the cell surface for surveillance by T lymphocytes, which contemporaneously seek signs of disease. Mass spectrometric analysis allows us to identify large numbers of these peptides (the immunopeptidome) following affinity purification of solubilized HLA–peptide complexes. However, in recent years, there has been a growing awareness of the “dark side” of the immunopeptidome: unconventional peptide epitopes, including neoepitopes, which elude detection by conventional search methods because their sequences are not present in reference protein databases (DBs). Here, we establish a bioinformatics workflow to aid identification of peptides generated by noncanonical translation of mRNA or by genome variants. The workflow incorporates both standard transcriptomics software and novel computer programs to produce cell line–specific protein DBs based on three-frame translation of the transcriptome. The final protein DB also includes sequences resulting from variants determined by variant calling on the same RNA-Seq data. We then searched our experimental data against both transcriptome-based and standard DBs using PEAKS Studio (Bioinformatics Solutions, Inc). Finally, further novel software helps to compare the various result sets arising for each sample, pinpoint putative genomic origins for unconventional sequences, and highlight potential neoepitopes. We applied the workflow to study the immunopeptidome of the acute myeloid leukemia cell line THP-1, using RNA-Seq and immunopeptidome data. We confidently identified over 14,000 peptides from three replicates of purified HLA peptides derived from THP-1 cells using the conventional UniProt human proteome. Using the transcriptome-based DB generated using our workflow, we recapitulated >85% of these and also identified 1029 unconventional peptides not explained by UniProt, including 16 sequences caused by nonsynonymous variants. Our workflow, which we term “immunopeptidogenomics,” can provide DBs, which include pertinent unconventional sequences and allow neoepitope discovery, without becoming too large to search. Immunopeptidogenomics is a step toward unbiased search approaches that are needed to illuminate the dark side of the immunopeptidome.
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spelling pubmed-87248852022-01-11 Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome Scull, Katherine E. Pandey, Kirti Ramarathinam, Sri H. Purcell, Anthony W. Mol Cell Proteomics Technological Innovation and Resources Human leukocyte antigen (HLA) molecules are cell-surface glycoproteins that present peptide antigens on the cell surface for surveillance by T lymphocytes, which contemporaneously seek signs of disease. Mass spectrometric analysis allows us to identify large numbers of these peptides (the immunopeptidome) following affinity purification of solubilized HLA–peptide complexes. However, in recent years, there has been a growing awareness of the “dark side” of the immunopeptidome: unconventional peptide epitopes, including neoepitopes, which elude detection by conventional search methods because their sequences are not present in reference protein databases (DBs). Here, we establish a bioinformatics workflow to aid identification of peptides generated by noncanonical translation of mRNA or by genome variants. The workflow incorporates both standard transcriptomics software and novel computer programs to produce cell line–specific protein DBs based on three-frame translation of the transcriptome. The final protein DB also includes sequences resulting from variants determined by variant calling on the same RNA-Seq data. We then searched our experimental data against both transcriptome-based and standard DBs using PEAKS Studio (Bioinformatics Solutions, Inc). Finally, further novel software helps to compare the various result sets arising for each sample, pinpoint putative genomic origins for unconventional sequences, and highlight potential neoepitopes. We applied the workflow to study the immunopeptidome of the acute myeloid leukemia cell line THP-1, using RNA-Seq and immunopeptidome data. We confidently identified over 14,000 peptides from three replicates of purified HLA peptides derived from THP-1 cells using the conventional UniProt human proteome. Using the transcriptome-based DB generated using our workflow, we recapitulated >85% of these and also identified 1029 unconventional peptides not explained by UniProt, including 16 sequences caused by nonsynonymous variants. Our workflow, which we term “immunopeptidogenomics,” can provide DBs, which include pertinent unconventional sequences and allow neoepitope discovery, without becoming too large to search. Immunopeptidogenomics is a step toward unbiased search approaches that are needed to illuminate the dark side of the immunopeptidome. American Society for Biochemistry and Molecular Biology 2021-09-10 /pmc/articles/PMC8724885/ /pubmed/34509645 http://dx.doi.org/10.1016/j.mcpro.2021.100143 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Technological Innovation and Resources
Scull, Katherine E.
Pandey, Kirti
Ramarathinam, Sri H.
Purcell, Anthony W.
Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome
title Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome
title_full Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome
title_fullStr Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome
title_full_unstemmed Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome
title_short Immunopeptidogenomics: Harnessing RNA-Seq to Illuminate the Dark Immunopeptidome
title_sort immunopeptidogenomics: harnessing rna-seq to illuminate the dark immunopeptidome
topic Technological Innovation and Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8724885/
https://www.ncbi.nlm.nih.gov/pubmed/34509645
http://dx.doi.org/10.1016/j.mcpro.2021.100143
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