 Identifying the Rules of Engagement Enabling Leukocyte Rolling, Activation, and AdhesionJonathan Tang and C Anthony Hunt PLOS Computational Biology, 2010, vol. 6, issue 2, 1-15 Abstract: The LFA-1 integrin plays a pivotal role in sustained leukocyte adhesion to the endothelial surface, which is a precondition for leukocyte recruitment into inflammation sites. Strong correlative evidence implicates LFA-1 clustering as being essential for sustained adhesion, and it may also facilitate rebinding events with its ligand ICAM-1. We cannot challenge those hypotheses directly because it is infeasible to measure either process during leukocyte adhesion following rolling. The alternative approach undertaken was to challenge the hypothesized mechanisms by experimenting on validated, working counterparts: simulations in which diffusible, LFA1 objects on the surfaces of quasi-autonomous leukocytes interact with simulated, diffusible, ICAM1 objects on endothelial surfaces during simulated adhesion following rolling. We used object-oriented, agent-based methods to build and execute multi-level, multi-attribute analogues of leukocytes and endothelial surfaces. Validation was achieved across different experimental conditions, in vitro, ex vivo, and in vivo, at both the individual cell and population levels. Because those mechanisms exhibit all of the characteristics of biological mechanisms, they can stand as a concrete, working theory about detailed events occurring at the leukocyte–surface interface during leukocyte rolling and adhesion experiments. We challenged mechanistic hypotheses by conducting experiments in which the consequences of multiple mechanistic events were tracked. We quantified rebinding events between individual components under different conditions, and the role of LFA1 clustering in sustaining leukocyte–surface adhesion and in improving adhesion efficiency. Early during simulations ICAM1 rebinding (to LFA1) but not LFA1 rebinding (to ICAM1) was enhanced by clustering. Later, clustering caused both types of rebinding events to increase. We discovered that clustering was not necessary to achieve adhesion as long as LFA1 and ICAM1 object densities were above a critical level. Importantly, at low densities LFA1 clustering enabled improved efficiency: adhesion exhibited measurable, cell level positive cooperativity.Author Summary: To gain access to sites of inflammation, leukocytes must first adhere to the blood vessel wall using integrin molecules. It has been hypothesized that integrin clustering is essential for sustaining adhesion prior to transmigration into the inflamed tissue. We cannot challenge such hypotheses directly because it is infeasible to measure molecular level events during the leukocyte adhesion process. At best correlative relationships have been made. The alternative approach undertaken was to experimentally challenge the hypothesized mechanisms in silico. We used object-oriented, software engineering methods to build and execute multi-level, multi-attribute analogues of leukocytes and binding surfaces. The simulated leukocytes contained diffusible objects (representing integrins) on their surface that were allowed to interact with binding partners on simulated endothelial surfaces. Validation was achieved across different experimental conditions, in vitro, ex vivo, and in vivo, at both the individual cell and population levels. Consequently, the finalized virtual mechanisms stand as a concrete, working theory about detailed events occurring at the leukocyte-surface interface during adhesion. We challenged mechanistic hypotheses by conducting experiments in which the consequences of multiple mechanistic events were tracked. We discovered that integrin clustering was not necessary to achieve adhesion as long as integrin and binding partner object densities were above a critical level. Importantly, at low densities integrin clustering enabled adhesion that exhibited measurable, cell level positive cooperativity. Date: 2010 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1000681 DOI: 10.1371/journal.pcbi.1000681 Access Statistics for this article More articles in PLOS Computational Biology from Public Library of Science |
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