Computer detection of the rapid diffusion of fluorescent membrane fusion markers in images observed with video microscopy

Identifying virus-cell fusion in two-channel fluorescence microscopy image sequences based on a layered probabilistic approach

The entry process of virus particles into cells is decisive for infection. In this work, we investigate fusion of virus particles with the cell membrane via time-lapse fluorescence microscopy. To automatically identify fusion for single particles based on their intensity over time, we have developed a layered probabilistic approach. The approach decomposes the action of a single particle into three abstractions: the intensity over time, the underlying temporal intensity model, as well as a high level behavior. Each abstraction corresponds to a layer and these layers are represented via stochastic hybrid systems and hidden Markov models. We use a maxbelief strategy to efficiently combine both representations. To compute estimates for the abstractions we use a hybrid particle filter and the Viterbi algorithm. Based on synthetic image sequences, we characterize the performance of the approach as a function of the image noise. We also characterize the performance as a function of the tracking error. We have also successfully applied the approach to real image sequences displaying pseudotyped HIV-1 particles in contact with host cells and compared the experimental results with ground truth obtained by manual analysis.

Single event recording shows that docking onto receptor alters the kinetics of membrane fusion mediated by influenza hemagglutinin

The initial steps of membrane fusion, receptor binding and membrane destabilization, are mediated by the envelope glycoprotein hemagglutinin of influenza virus. Interaction between these functions was determined from the time course of individual virion fusions to a planar membrane with and without receptor. With receptor, fusion was described by a Poisson process. In the absence of receptor, the time course was more complicated and could not be described with exponential rate constants. The conversion of a non-Markovian process into a simple Markov chain is direct evidence that receptor binding fundamentally alters the route of fusion.