Understanding how emerging influenza viruses recognize host cells is critical in evaluating their zoonotic potential, pathogenicity, and transmissibility between humans. The surface of the influenza virus is covered with hemagglutinin (HA) proteins that can form multiple interactions with sialic acid-terminated glycans on the host cell surface. This multivalent binding affects the selectivity of the virus in ways that cannot be predicted from the individual receptor–ligand interactions alone. Here, we show that the intrinsic structural and energetic differences between the interactions of avian- or human-type receptors with influenza HA translate from individual site affinity and orientation through receptor length and density on the surface into virus avidity and specificity. We introduce a method to measure virus avidity using receptor density gradients. We found that influenza viruses attached stably to a surface at receptor densities that correspond to a minimum number of approximately 8 HA–glycan interactions, but more interactions were required if the receptors were short and human-type. Thus, the avidity and specificity of influenza viruses for a host cell depend not on the sialic acid linkage alone but on a combination of linkage and the length and density of receptors on the cell surface. Our findings suggest that threshold receptor densities play a key role in virus tropism, which is a predicting factor for both their virulence and zoonotic potential.
The neuraminidase on the surface of influenza viruses make the virus a receptor-cleaving molecular walker, similar to molecular spiders.
The influenza A virus (IAV) interacts with the glycocalyx of host cells through its surface proteins hemagglutinin (HA) and neuraminidase (NA). Quantitative biophysical measurements of these interactions may help to understand these interactions at the molecular level with the long-term aim to predict influenza infectivity and answer other biological questions. We developed a method, called multivalent affinity profiling (MAP), to measure virus binding profiles on receptor density gradients to determine the threshold receptor density, which is a quantitative measure of virus avidity toward a receptor. Here, we show that imaging of IAVs on receptor density gradients allows the direct visualization and efficient assessment of their superselective binding. We show how the multivalent binding of IAVs can be quantitatively assessed using MAP if the receptor density gradients are prepared around the threshold receptor density without crowding at the higher densities. The threshold receptor density increases strongly with increasing flow rate, showing that the superselective binding of IAV is influenced by shear force. This method of visualization and quantitative assessment of superselective binding allows not only comparative studies of IAV−receptor interactions, but also more fundamental studies of how superselectivity arises and is influenced by experimental conditions.
Biosensors and other biological platform technologies require the functionalization of their surface with receptors to enhance affinity and selectivity. Control over the functionalization density is required to tune the platform’s properties. Streptavidin (SAv) monolayers are widely used to immobilize biotinylated proteins, receptors, and DNA. The SAv density on a surface can be varied easily, but the predictability is dependent on the method by which the SAv is immobilized. In this study we show a method to quantitatively predict the SAv coverage on biotinylated surfaces. The method is validated by measuring the SAv coverage on supported lipid bilayers with a range of biotin contents and two different main phase lipids and by using quartz crystal microbalance and localized surface plasmon resonance. We explore a predictive model of the biotin-dependent SAv coverage without any fit parameters. Model and data allow to predict the SAv coverage based on the biotin coverage, in both the low- and high-density regimes. This is of special importance in applications with multivalent binding where control over surface receptor density is required, but a direct measurement is not possible.
Microfluidic devices are widely used for the sensing of small quantities of analytes. In these applications, the measurement can be easily perturbed by loss of analyte due to binding of the analyte outside the sensing area. We studied the binding of small molecules and nanoparticles up to 400 nm in a state‐of‐the‐art sensing platform – receptor gradients on supported lipid bilayers (SLBs) – in a microfluidic device over time. Biotin‐streptavidin was used as the model interaction motif for specific binding and a biotin‐modified dye, which can bind to the streptavidin on the SLB, as a small‐molecule model analyte. We used finite element simulations to show that the time‐dependent binding of analytes in the sensing area depends strongly on the extent of the nonspecific binding of the vesicles, used in a preceding step to make the SLB platform, outside of the sensing area (e. g., in the tubing). At sufficiently high flow rates, proteins and nanoparticles were only partially depleted by nonspecifically adsorbed lipids, and no delayed onset of binding was observed, because of their lower diffusion coefficients. As a practical solution, a flow cell with two inlets was used to avoid the presence of nonspecifically adsorbed receptors in the sample inlet, which allowed us to decouple the formation of the sensor layer on the surface from the subsequent sensing event. We found that in the absence of lipids adsorbed to the tubing, the nonspecific binding of dye molecules was negligible.
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