title: Boltzmann energy-based image analysis demonstrates that extracellular domain size differences explain protein segregation at immune synapses.
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.
authors.affiliation: Systems Biology Centre, University of Warwick, Coventry, United Kingdom. N.J.Burroughs@warwick.ac.uk
authors.forename: Nigel J
authors.initials: NJ
authors.lastname: Burroughs
authors.forename: Karsten
authors.initials: K
authors.lastname: Köhler
authors.forename: Vladimir
authors.initials: V
authors.lastname: Miloserdov
authors.forename: Michael L
authors.initials: ML
authors.lastname: Dustin
authors.forename: P Anton
authors.initials: PA
authors.lastname: van der Merwe
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Davis
mesh_terms: D002450:Cell Communication / Q000502:physiology; D002461:Cell Line, Transformed; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D005110:Extracellular Space / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D054992:Immunological Synapses / Q000737:chemistry / Q000378:metabolism*; D018799:Intercellular Adhesion Molecule-1 / Q000378:metabolism; D007694:Killer Cells, Natural / Q000378:metabolism; D007700:Kinetics; D008565:Membrane Proteins / Q000737:chemistry / Q000378:metabolism; D010316:Particle Size; D010363:Pattern Recognition, Automated; D016012:Poisson Distribution; D017434:Protein Structure, Tertiary; D013601:T-Lymphocytes / Q000378:metabolism; D013816:Thermodynamics
chemical_list: D008565:Membrane Proteins; D018799:Intercellular Adhesion Molecule-1