Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments

In osteoarthritis (OA), chondrocyte metabolism dysregulation increases relative catabolic activity, which leads to cartilage degradation. To enable the semiquantitative interpretation of the intricate mechanisms of OA progression, we propose a network-based model at the chondrocyte level that incorp...

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Authors: Segarra-Queralt, Maria, Neidlin, Michael, Tío, Laura, Monfort, Jordi, Monllau García, Juan Carlos, González Ballester, Miguel Ángel, 1973-, Alexopoulos, Leonidas G., Piella Fenoy, Gemma, Noailly, Jérôme
Format: article
Status:Published version
Publication Date:2022
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/54483
Online Access:http://hdl.handle.net/10230/54483
http://dx.doi.org/10.1038/s41598-022-07776-2
Access Level:Open access
Keyword:Biochemistry
Computational biology and bioinformatics
Systems biology
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spelling Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environmentsSegarra-Queralt, MariaNeidlin, MichaelTío, LauraMonfort, JordiMonllau García, Juan CarlosGonzález Ballester, Miguel Ángel, 1973-Alexopoulos, Leonidas G.Piella Fenoy, GemmaNoailly, JérômeBiochemistryComputational biology and bioinformaticsSystems biologyIn osteoarthritis (OA), chondrocyte metabolism dysregulation increases relative catabolic activity, which leads to cartilage degradation. To enable the semiquantitative interpretation of the intricate mechanisms of OA progression, we propose a network-based model at the chondrocyte level that incorporates the complex ways in which inflammatory factors affect structural protein and protease expression and nociceptive signals. Understanding such interactions will leverage the identification of new potential therapeutic targets that could improve current pharmacological treatments. Our computational model arises from a combination of knowledge-based and data-driven approaches that includes in-depth analyses of evidence reported in the specialized literature and targeted network enrichment. We achieved a mechanistic network of molecular interactions that represent both biosynthetic, inflammatory and degradative chondrocyte activity. The network is calibrated against experimental data through a genetic algorithm, and 81% of the responses tested have a normalized root squared error lower than 0.15. The model captures chondrocyte-reported behaviors with 95% accuracy, and it correctly predicts the main outcomes of OA treatment based on blood-derived biologics. The proposed methodology allows us to model an optimal regulatory network that controls chondrocyte metabolism based on measurable soluble molecules. Further research should target the incorporation of mechanical signals.Funding was provided by Generalitat de Catalunya (Grant No. 2020 FI_B 00680), European Commission (Grant No. MSCA-2020-ITN-ETN GA: 955735) and Ministerio de Ciencia, Innovación y Universidades (Grant No. HOLOA-DPI2016- 80283-C2-1/2-R).Nature Research202220222022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/54483http://dx.doi.org/10.1038/s41598-022-07776-2reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésSci Rep. 2022 Mar 9;12(1):3856info:eu-repo/grantAgreement/EC/H2020/955735© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10230/544832026-05-29T05:05:01Z
dc.title.none.fl_str_mv Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
title Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
spellingShingle Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
Segarra-Queralt, Maria
Biochemistry
Computational biology and bioinformatics
Systems biology
title_short Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
title_full Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
title_fullStr Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
title_full_unstemmed Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
title_sort Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments
dc.creator.none.fl_str_mv Segarra-Queralt, Maria
Neidlin, Michael
Tío, Laura
Monfort, Jordi
Monllau García, Juan Carlos
González Ballester, Miguel Ángel, 1973-
Alexopoulos, Leonidas G.
Piella Fenoy, Gemma
Noailly, Jérôme
author Segarra-Queralt, Maria
author_facet Segarra-Queralt, Maria
Neidlin, Michael
Tío, Laura
Monfort, Jordi
Monllau García, Juan Carlos
González Ballester, Miguel Ángel, 1973-
Alexopoulos, Leonidas G.
Piella Fenoy, Gemma
Noailly, Jérôme
author_role author
author2 Neidlin, Michael
Tío, Laura
Monfort, Jordi
Monllau García, Juan Carlos
González Ballester, Miguel Ángel, 1973-
Alexopoulos, Leonidas G.
Piella Fenoy, Gemma
Noailly, Jérôme
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Biochemistry
Computational biology and bioinformatics
Systems biology
topic Biochemistry
Computational biology and bioinformatics
Systems biology
description In osteoarthritis (OA), chondrocyte metabolism dysregulation increases relative catabolic activity, which leads to cartilage degradation. To enable the semiquantitative interpretation of the intricate mechanisms of OA progression, we propose a network-based model at the chondrocyte level that incorporates the complex ways in which inflammatory factors affect structural protein and protease expression and nociceptive signals. Understanding such interactions will leverage the identification of new potential therapeutic targets that could improve current pharmacological treatments. Our computational model arises from a combination of knowledge-based and data-driven approaches that includes in-depth analyses of evidence reported in the specialized literature and targeted network enrichment. We achieved a mechanistic network of molecular interactions that represent both biosynthetic, inflammatory and degradative chondrocyte activity. The network is calibrated against experimental data through a genetic algorithm, and 81% of the responses tested have a normalized root squared error lower than 0.15. The model captures chondrocyte-reported behaviors with 95% accuracy, and it correctly predicts the main outcomes of OA treatment based on blood-derived biologics. The proposed methodology allows us to model an optimal regulatory network that controls chondrocyte metabolism based on measurable soluble molecules. Further research should target the incorporation of mechanical signals.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022
2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/54483
http://dx.doi.org/10.1038/s41598-022-07776-2
url http://hdl.handle.net/10230/54483
http://dx.doi.org/10.1038/s41598-022-07776-2
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Sci Rep. 2022 Mar 9;12(1):3856
info:eu-repo/grantAgreement/EC/H2020/955735
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature Research
publisher.none.fl_str_mv Nature Research
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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