Mathematical models disentangle the role of IL-10 feedbacks in human monocytes upon proinflammatory activation.

NF-κB computational biology computer modeling cytokine endotoxin human monocytes inflammation interleukin 10 lipopolysaccharide mathematical modeling ordinary differential equations signal transduction systems biology tumor necrosis factor

Journal

The Journal of biological chemistry
ISSN: 1083-351X
Titre abrégé: J Biol Chem
Pays: United States
ID NLM: 2985121R

Informations de publication

Date de publication:
Oct 2023
Historique:
received: 24 03 2023
revised: 16 08 2023
accepted: 24 08 2023
pubmed: 4 9 2023
medline: 4 9 2023
entrez: 3 9 2023
Statut: ppublish

Résumé

Inflammation is one of the vital mechanisms through which the immune system responds to harmful stimuli. During inflammation, proinflammatory and anti-inflammatory cytokines interplay to orchestrate fine-tuned and dynamic immune responses. The cytokine interplay governs switches in the inflammatory response and dictates the propagation and development of the inflammatory response. Molecular pathways underlying the interplay are complex, and time-resolved monitoring of mediators and cytokines is necessary as a basis to study them in detail. Our understanding can be advanced by mathematical models that enable to analyze the system of interactions and their dynamical interplay in detail. We, therefore, used a mathematical modeling approach to study the interplay between prominent proinflammatory and anti-inflammatory cytokines with a focus on tumor necrosis factor and interleukin 10 (IL-10) in lipopolysaccharide-primed primary human monocytes. Relevant time-resolved data were generated by experimentally adding or blocking IL-10 at different time points. The model was successfully trained and could predict independent validation data and was further used to perform simulations to disentangle the role of IL-10 feedbacks during an acute inflammatory event. We used the insight to obtain a reduced predictive model including only the necessary IL-10-mediated feedbacks. Finally, the validated reduced model was used to predict early IL-10-tumor necrosis factor switches in the inflammatory response. Overall, we gained detailed insights into fine-tuning of inflammatory responses in human monocytes and present a model for further use in studying the complex and dynamic process of cytokine-regulated acute inflammation.

Identifiants

pubmed: 37660912
pii: S0021-9258(23)02233-0
doi: 10.1016/j.jbc.2023.105205
pmc: PMC10556785
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

105205

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article.

Auteurs

Niloofar Nikaein (N)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden. Electronic address: X-HiDE@oru.se.

Kedeye Tuerxun (K)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden.

Gunnar Cedersund (G)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden; Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.

Daniel Eklund (D)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden.

Robert Kruse (R)

Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Department of Clinical Research Laboratory, Örebro University, Örebro, Sweden.

Eva Särndahl (E)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden.

Eewa Nånberg (E)

Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden; Faculty of Medicine and Health, School of Health Sciences, Örebro University, Örebro, Sweden.

Antje Thonig (A)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden.

Dirk Repsilber (D)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden.

Alexander Persson (A)

Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden; Faculty of Medicine and Health, Inflammatory Response and Infection Susceptibility Centre (iRiSC), Örebro University, Örebro, Sweden.

Elin Nyman (E)

Department of Biomedical Engineering, Linköping University, Linköping, Sweden. Electronic address: elin.nyman@liu.se.

Classifications MeSH