Biophysical parameters of bacteriophage adsorption to host cells

Bacteriophages (phages), viruses that infect bacteria, represent the most abundant biological entities on Earth. Phages initiate a new infection cycle by binding to specific proteins, polysaccharides, or appendages on host bacterial surfaces- termed phage receptors. While the phage receptors, different for each phage species, are routinely characterized through genetic assays, the dynamics of phage attachment (adsorption) are poorly understood. The classical understanding of phage adsorption is derived from flasks- and plate-based assays, which provide ensemble estimates of the adsorption rate. Characterization of stochastic dynamics of phage-host interactions requires single cell and single phage measurements.

We used fluorescence microscopy to quantify the attachment of individual phages to cells. Through particle tracking, we obtained individual phage trajectories from videos recorded at high spatiotemporal resolution. Tracking phage T4 particles near host Escherichia coli surfaces confirmed that phages reversibly bind to and unbind from host surfaces, as inferred previously through non-microscopic methods. From thousands of trajectories, we obtained histograms of the dwell time, the time that a phage spends near bacterial cells, likely exploring the surface. These histograms do not follow exponential distributions as predicted by the existing theories of phage attachment. We propose an updated model of the biophysics of phage adsorption.

Next, we compared the dwell time distributions for phages attaching to wildtype host cells and cells of multiple strains carrying mutated phage-receptors. As expected, the dwell times of phages interacting with the mutant cell surfaces are significantly lower. Comparisons of the classical adsorption rate to the dwell time distributions revealed a monotonic relationship, allowing us to propose the microscopy assay as a proxy for laborious classical adsorption assays.

These results establish a framework for quantifying the dynamics of the interactions between individual viruses and the host surface. We are currently developing and implementing parameter extraction algorithms to infer quantities such as diffusion coefficients, fractions of bound and unbound subpopulations, as well as binding and unbinding rates.