Burroughs, Nigel John, Köhler, Karsten, Miloserdov, Vladimir, Dustin, Michael L., Van der Merwe, P. Anton and Davis, Daniel M. (2011) Boltzmann energy-based image analysis demonstrates that extracellular domain size differences explain protein segregation at immune synapses. PLoS Computational Biology, Vol.7 (No.8). e1002076. doi:10.1371/journal.pcbi.1002076

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Abstract

Immune synapses formed by T and NK cells both show segregation of the integrin ICAM1 from other proteins such as CD2 (T cell) or KIR (NK cell). However, the mechanism by which these proteins segregate remains unclear; one key hypothesis is a redistribution based on protein size. Simulations of this mechanism qualitatively reproduce observed segregation patterns, but only in certain parameter regimes. Verifying that these parameter constraints in fact hold has not been possible to date, this requiring a quantitative coupling of theory to experimental data. Here, we address this challenge, developing a new methodology for analysing and quantifying image data and its integration with biophysical models. Specifically we fit a binding kinetics model to 2 colour fluorescence data for cytoskeleton independent synapses (2 and 3D) and test whether the observed inverse correlation between fluorophores conforms to size dependent exclusion, and further, whether patterned states are predicted when model parameters are estimated on individual synapses. All synapses analysed satisfy these conditions demonstrating that the mechanisms of protein redistribution have identifiable signatures in their spatial patterns. We conclude that energy processes implicit in protein size based segregation can drive the patternation observed in individual synapses, at least for the specific examples tested, such that no additional processes need to be invoked. This implies that biophysical processes within the membrane interface have a crucial impact on cell:cell communication and cell signalling, governing protein interactions and protein aggregation.

Item Type:	Journal Article
Subjects:	Q Science > QP Physiology
Divisions:	Faculty of Science > Mathematics Faculty of Science > Centre for Systems Biology
Library of Congress Subject Headings (LCSH):	T cells -- Mathematical models, Membrane proteins -- Mathematical models, Cell interaction -- Mathematical models
Journal or Publication Title:	PLoS Computational Biology
Publisher:	Public Library of Science
ISSN:	1553-7358
Official Date:	4 August 2011
Dates:	Date Event 4 August 2011 Published
Date of first compliant deposit:	17 December 2015
Volume:	Vol.7
Number:	No.8
Page Range:	e1002076
DOI:	10.1371/journal.pcbi.1002076
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
Funder:	Royal Society (Great Britain), Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Medical Research Council (Great Britain) (MRC), National Institutes of Health (U.S.) (NIH)
Grant number:	BB/D011663/1 (BBSRC), GO500563 (MRC), AI440931 (NIH)

Data sourced from Thomson Reuters' Web of Knowledge

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