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Boltzmann energy-based image analysis demonstrates that extracellular domain size differences explain protein segregation at immune synapses

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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. ISSN 1553-7358

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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1002076

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

Volume:

Vol.7

Number:

No.8

Page Range:

e1002076

Identification Number:

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)

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