Spatial considerations in the resolution of inflammation: elucidating leukocyte interactions via an experimentally-calibrated agent-based model

Bayani, A., Dunster, J.L., Crofts, J.J. ORCID: 0000-0001-7751-9984 and Nelson, M.R. ORCID: 0000-0001-5320-2464, 2020. Spatial considerations in the resolution of inflammation: elucidating leukocyte interactions via an experimentally-calibrated agent-based model. PLOS Computational Biology, 16 (11): e1008413. ISSN 1553-734X

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Abstract

Many common medical conditions (such as cancer, arthritis, chronic obstructive pulmonary disease (COPD), and others) are associated with inflammation, and even more so when combined with the effects of ageing and multimorbidity. While the inflammatory response varies in different tissue types, under disease and in response to therapeutic interventions, it has common interactions that occur between immune cells and inflammatory mediators. Understanding these underlying inflammatory mechanisms is key in progressing treatments and therapies for numerous inflammatory conditions. It is now considered that constituent mechanisms of the inflammatory response can be actively manipulated in order to drive resolution of inflammatory damage; particularly, those mechanisms related to the pro-inflammatory role of neutrophils and the anti-inflammatory role of macrophages. In this article, we describe the assembly of a hybrid mathematical model in which the spatial spread of inflammatory mediators is described through partial differential equations, and immune cells (neutrophils and macrophages) are described individually via an agent-based modelling approach. We pay close attention to how immune cells chemotax toward pro-inflammatory mediators, presenting a model for cell chemotaxis that is calibrated against experimentally observed cell trajectories in healthy and COPD-affected scenarios. We illustrate how variations in key model parameters can drive the switch from resolution of inflammation to chronic outcomes, and show that aberrant neutrophil chemotaxis can move an otherwise healthy outcome to one of chronicity. Finally, we reflect on our results in the context of the on-going hunt for new therapeutic interventions .

Item Type:	Journal article
Publication Title:	PLOS Computational Biology
Creators:	Bayani, A., Dunster, J.L., Crofts, J.J. and Nelson, M.R.
Publisher:	Public Library of Science (PLoS)
Date:	2 November 2020
Volume:	16
Number:	11
ISSN:	1553-734X
Identifiers:	Number Type 10.1371/journal.pcbi.1008413 DOI 1399149 Other
Rights:	© 2020 Bayani et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Divisions:	Schools > School of Science and Technology
Record created by:	Jeremy Silvester
Date Added:	15 Jan 2021 10:44
Last Modified:	31 May 2021 15:07
URI:	https://irep.ntu.ac.uk/id/eprint/42039

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