Influenza A viruses use multivalent sialic acid clusters for cell binding and receptor activation
Fig 3
IAV performs a receptor concentration-driven random walk on the plasma membrane.
Based on our quantitative analysis of the AF distribution on A549 cells, we hypothesize a motion behavior that is driven by the local AF concentration. We simulate this behavior initially as a 2D random walk with free diffusion coefficient Dfree (A). (B) Next, we simulate AF clusters (red circles, r = 100 nm), which would, due to the increased SA concentration, lead to a temporal confinement (Dconf < Dfree). To identify confined regions within the simulated virus trajectories, we establish a confinement probability Iconf. Accordingly, a free diffusing particle shows only fluctuation in of Iconf (D), while the addition of temporal confinement leads to a clear increase that overlaps with stationary phases of the particle as visible in the XY displacement plot (E). We used the confinement probability to analyze experimental virus trajectories in particular the mixed type of trajectories (C) (see also S8 Fig) (C). Iconf shows a clear signature of temporal confinement (F) similar to the model prediction (E). As a further challenge for our model, we performed a subtrajectory analysis, thereby extracting the dwell time, Dconf as well as the area of the respective temporal confinement in our virus trajectories. (G) shows an overlay of the perimeters of the extracted confined regions as well as the average radius (R). From our simulated data, correlation of Dconf with the dwell time shows that a local increase in AF concentration (i.e. decreased diffusion) due to the encounter of an SA nanodomain leads to an increased local dwell time (H, red markers). We observed a similar behavior, when we tested the confinement dwell time in experimental virus trajectories (H, black markers).