Literature DB >> 33691108

Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

Maria Virginia Ruiz Cuevas1, Marie-Pierre Hardy2, Jaroslav Hollý3, Éric Bonneil2, Chantal Durette2, Mathieu Courcelles2, Joël Lanoix2, Caroline Côté2, Louis M Staudt4, Sébastien Lemieux1, Pierre Thibault5, Claude Perreault6, Jonathan W Yewdell7.   

Abstract

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.
Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  computational biology; defective ribosomal products; major histocompatibility complex; mass spectrometry; non-canonical translation; peptides; protein isoforms; proteomic methods; ribosome profiling

Mesh:

Substances:

Year:  2021        PMID: 33691108      PMCID: PMC8040094          DOI: 10.1016/j.celrep.2021.108815

Source DB:  PubMed          Journal:  Cell Rep            Impact factor:   9.423


  83 in total

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Journal:  Mol Cell Proteomics       Date:  2019-06       Impact factor: 5.911

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Authors:  T N Bullock; L C Eisenlohr
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8.  Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling.

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Review 10.  Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship.

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Journal:  Genome Res       Date:  2018-04-06       Impact factor: 9.043

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8.  Profiling SARS-CoV-2 HLA-I peptidome reveals T cell epitopes from out-of-frame ORFs.

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Journal:  Cell       Date:  2021-06-03       Impact factor: 66.850

9.  Is the Immunopeptidome Getting Darker?: A Commentary on the Discussion around Mishto et al., 2019.

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Journal:  Front Immunol       Date:  2021-07-13       Impact factor: 7.561

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