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Combining Confocal and Atomic Force Microscopy to Quantify Single-Virus Binding to Mammalian Cell Surfaces

Nature Protocols(2017)

Department of Biosystems Science and Engineering

Cited 58|Views21
Abstract
Over the past five years, atomic force microscopy (AFM)-based approaches have evolved into a powerful multiparametric tool set capable of imaging the surfaces of biological samples ranging from single receptors to membranes and tissues. One of these approaches, force-distance curve-based AFM (FD-based AFM), uses a probing tip functionalized with a ligand to image living cells at high-resolution and simultaneously localize and characterize specific ligand-receptor binding events. Analyzing data from FD-based AFM experiments using appropriate probabilistic models allows quantification of the kinetic and thermodynamic parameters that describe the free-energy landscape of the ligand-receptor bond. We have recently developed an FD-based AFM approach to quantify the binding events of single enveloped viruses to surface receptors of living animal cells while simultaneously observing them by fluorescence microscopy. This approach has provided insights into the early stages of the interaction between a virus and a cell. Applied to a model virus, we probed the specific interaction with cells expressing viral cognate receptors and measured the affinity of the interaction. Furthermore, we observed that the virus rapidly established specific multivalent interactions and found that each bond formed in sequence strengthened the attachment of the virus to the cell. Here we describe detailed procedures for probing the specific interactions of viruses with living cells; these procedures cover tip preparation, cell sample preparation, step-by-step FD-based AFM imaging and data analysis. Experienced microscopists should be able to master the entire set of protocols in 1 month.
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Key words
Atomic force microscopy,Confocal microscopy,Nanoscale biophysics,Virus–host interactions,Life Sciences,general,Biological Techniques,Analytical Chemistry,Microarrays,Computational Biology/Bioinformatics,Organic Chemistry
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