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Biological adhesion between cells is critical for development of multicellular organisms and for the function of the adaptive immune system of vertebrates. A gap in understanding of adhesion systems arises from the difficulty of collecting quantitative data on the molecular interactions underlying adhesion, which is typically studied by population statistics such as percent adhesion in the presence of empirically defined forces to separate less adherent cells. Supported lipid bilayers formed on glass surfaces offer a useful model system in which to explore some basic features of molecular interactions in adhesive contacts. We have exploited the lateral mobility of molecules in the supported planar bilayers and fluorescence microscopy to develop a system for measurement of two-dimensional affinities and kinetic rates in contact areas. Affinity measurements are based on a modified Scatchard analysis. Measurements of kinetic rates are based on fluorescence photobleaching after recovery at the level of the entire contact area. This has been coupled to a reaction-diffusion equation that allows calculation of on- and off-rates. We have found that mixtures of ligands in supported planar bilayers can effectively activate T lymphocytes and simultaneously allow monitoring of the immunological synapse. Recent studies in planar bilayers have provided additional insights into organization principles of cell-cell interfaces. Perennial problems in understanding cell-cell communication are yielding to quantitative measurements based on planar bilayers in areas of ligand driven receptor clustering and the role of the actin cytoskeleton in immune cell activation. A major goal for the field is determining quantitative rules involved in signaling complex formation.

Original publication

DOI

10.1016/j.jsb.2009.05.007

Type

Journal article

Journal

J Struct Biol

Publication Date

10/2009

Volume

168

Pages

152 - 160

Keywords

Animals, Cell Adhesion, Humans, Immune System, Immunological Synapses, Lipid Bilayers, Lymphocyte Activation, Models, Biological