CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codo...

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Autores principales:	Tariq Daouda, Maude Dumont-Lagacé, Albert Feghaly, Yahya Benslimane, Rébecca Panes, Mathieu Courcelles, Mohamed Benhammadi, Lea Harrington, Pierre Thibault, François Major, Yoshua Bengio, Étienne Gagnon, Sébastien Lemieux, Claude Perreault
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/7fdeb099d6ae40b49a40010479c9e4ce
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spelling	oai:doaj.org-article:7fdeb099d6ae40b49a40010479c9e4ce2021-12-02T19:57:37ZCAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.1553-734X1553-735810.1371/journal.pcbi.1009482https://doaj.org/article/7fdeb099d6ae40b49a40010479c9e4ce2021-10-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009482https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.Tariq DaoudaMaude Dumont-LagacéAlbert FeghalyYahya BenslimaneRébecca PanesMathieu CourcellesMohamed BenhammadiLea HarringtonPierre ThibaultFrançois MajorYoshua BengioÉtienne GagnonSébastien LemieuxClaude PerreaultPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 10, p e1009482 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Tariq Daouda Maude Dumont-Lagacé Albert Feghaly Yahya Benslimane Rébecca Panes Mathieu Courcelles Mohamed Benhammadi Lea Harrington Pierre Thibault François Major Yoshua Bengio Étienne Gagnon Sébastien Lemieux Claude Perreault CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
description	MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.
format	article
author	Tariq Daouda Maude Dumont-Lagacé Albert Feghaly Yahya Benslimane Rébecca Panes Mathieu Courcelles Mohamed Benhammadi Lea Harrington Pierre Thibault François Major Yoshua Bengio Étienne Gagnon Sébastien Lemieux Claude Perreault
author_facet	Tariq Daouda Maude Dumont-Lagacé Albert Feghaly Yahya Benslimane Rébecca Panes Mathieu Courcelles Mohamed Benhammadi Lea Harrington Pierre Thibault François Major Yoshua Bengio Étienne Gagnon Sébastien Lemieux Claude Perreault
author_sort	Tariq Daouda
title	CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
title_short	CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
title_full	CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
title_fullStr	CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
title_full_unstemmed	CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.
title_sort	camap: artificial neural networks unveil the role of codon arrangement in modulating mhc-i peptides presentation.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/7fdeb099d6ae40b49a40010479c9e4ce
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CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

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