Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.

Autoimmune diseases, often triggered by infection, affect ~5% of the worldwide population. Rheumatoid Arthritis (RA)-a painful condition characterized by the chronic inflammation of joints-comprises up to 20% of known autoimmune pathologies, with the tendency of increasing prevalence. Molecular mimi...

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Autores principales:	Jelena Repac, Marija Mandić, Tanja Lunić, Bojan Božić, Biljana Božić Nedeljković
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a0c34fe05bae46f08330c8585e687cde
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spelling	oai:doaj.org-article:a0c34fe05bae46f08330c8585e687cde2021-12-02T20:09:50ZMining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.1932-620310.1371/journal.pone.0253918https://doaj.org/article/a0c34fe05bae46f08330c8585e687cde2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0253918https://doaj.org/toc/1932-6203Autoimmune diseases, often triggered by infection, affect ~5% of the worldwide population. Rheumatoid Arthritis (RA)-a painful condition characterized by the chronic inflammation of joints-comprises up to 20% of known autoimmune pathologies, with the tendency of increasing prevalence. Molecular mimicry is recognized as the leading mechanism underlying infection-mediated autoimmunity, which assumes sequence similarity between microbial and self-peptides driving the activation of autoreactive lymphocytes. T lymphocytes are leading immune cells in the RA-development. Therefore, deeper understanding of the capacity of microorganisms (both pathogens and commensals) to trigger autoreactive T cells is needed, calling for more systematic approaches. In the present study, we address this problem through a comprehensive immunoinformatics analysis of experimentally determined RA-related T cell epitopes against the proteomes of Bacteria, Fungi, and Viruses, to identify the scope of organisms providing homologous antigenic peptide determinants. By this, initial homology screening was complemented with de novo T cell epitope prediction and another round of homology search, to enable: i) the confirmation of homologous microbial peptides as T cell epitopes based on the predicted binding affinity to RA-related HLA polymorphisms; ii) sequence similarity inference for top de novo T cell epitope predictions to the RA-related autoantigens to reveal the robustness of RA-triggering capacity for identified (micro/myco)organisms. Our study reveals a much larger repertoire of candidate RA-triggering organisms, than previously recognized, providing insights into the underestimated role of Fungi in autoimmunity and the possibility of a more direct involvement of bacterial commensals in RA-pathology. Finally, our study pinpoints Endoplasmic reticulum chaperone BiP as the most potent (most likely mimicked) RA-related autoantigen, opening an avenue for identifying the most potent autoantigens in a variety of different autoimmune pathologies, with possible implications in the design of next-generation therapeutics aiming to induce self-tolerance by affecting highly reactive autoantigens.Jelena RepacMarija MandićTanja LunićBojan BožićBiljana Božić NedeljkovićPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0253918 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jelena Repac Marija Mandić Tanja Lunić Bojan Božić Biljana Božić Nedeljković Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.
description	Autoimmune diseases, often triggered by infection, affect ~5% of the worldwide population. Rheumatoid Arthritis (RA)-a painful condition characterized by the chronic inflammation of joints-comprises up to 20% of known autoimmune pathologies, with the tendency of increasing prevalence. Molecular mimicry is recognized as the leading mechanism underlying infection-mediated autoimmunity, which assumes sequence similarity between microbial and self-peptides driving the activation of autoreactive lymphocytes. T lymphocytes are leading immune cells in the RA-development. Therefore, deeper understanding of the capacity of microorganisms (both pathogens and commensals) to trigger autoreactive T cells is needed, calling for more systematic approaches. In the present study, we address this problem through a comprehensive immunoinformatics analysis of experimentally determined RA-related T cell epitopes against the proteomes of Bacteria, Fungi, and Viruses, to identify the scope of organisms providing homologous antigenic peptide determinants. By this, initial homology screening was complemented with de novo T cell epitope prediction and another round of homology search, to enable: i) the confirmation of homologous microbial peptides as T cell epitopes based on the predicted binding affinity to RA-related HLA polymorphisms; ii) sequence similarity inference for top de novo T cell epitope predictions to the RA-related autoantigens to reveal the robustness of RA-triggering capacity for identified (micro/myco)organisms. Our study reveals a much larger repertoire of candidate RA-triggering organisms, than previously recognized, providing insights into the underestimated role of Fungi in autoimmunity and the possibility of a more direct involvement of bacterial commensals in RA-pathology. Finally, our study pinpoints Endoplasmic reticulum chaperone BiP as the most potent (most likely mimicked) RA-related autoantigen, opening an avenue for identifying the most potent autoantigens in a variety of different autoimmune pathologies, with possible implications in the design of next-generation therapeutics aiming to induce self-tolerance by affecting highly reactive autoantigens.
format	article
author	Jelena Repac Marija Mandić Tanja Lunić Bojan Božić Biljana Božić Nedeljković
author_facet	Jelena Repac Marija Mandić Tanja Lunić Bojan Božić Biljana Božić Nedeljković
author_sort	Jelena Repac
title	Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.
title_short	Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.
title_full	Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.
title_fullStr	Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.
title_full_unstemmed	Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.
title_sort	mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-a systematic immunoinformatics analysis of t cell epitopes.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a0c34fe05bae46f08330c8585e687cde
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Mining the capacity of human-associated microorganisms to trigger rheumatoid arthritis-A systematic immunoinformatics analysis of T cell epitopes.

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