| Autor: |
Antani JD; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA.; Center for Phage Biology & Therapy, Yale University, New Haven, CT 06520, USA.; Quantitative Biology Institute, Yale University, New Haven, CT 06520, USA., Ward T; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA., Emonet T; Quantitative Biology Institute, Yale University, New Haven, CT 06520, USA.; Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520, USA.; Department of Physics, Yale University, New Haven, CT 06520, USA., Turner PE; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA.; Center for Phage Biology & Therapy, Yale University, New Haven, CT 06520, USA.; Quantitative Biology Institute, Yale University, New Haven, CT 06520, USA.; Program in Microbiology, Yale School of Medicine, New Haven, CT 06520, USA. |
| Abstrakt: |
Phages, viruses of bacteria, play a pivotal role in Earth's biosphere and hold great promise as therapeutic and diagnostic tools in combating infectious diseases. Attachment of phages to bacterial cells is a crucial initial step of the interaction. The classic assay to quantify the dynamics of phage attachment involves co-culturing and enumeration of bacteria and phages, which is laborious, lengthy, hence low-throughput, and only provides ensemble estimates of model-based adsorption rate constants. Here, we utilized fluorescence microscopy and particle tracking to obtain trajectories of individual virus particles interacting with cells. The trajectory durations quantified the heterogeneity in dwell time, the time that each phage spends interacting with a bacterium. The average dwell time strongly correlated with the classically-measured adsorption rate constant. We successfully applied this technique to quantify host-attachment dynamics of several phages including those targeting key bacterial pathogens. This approach should benefit the field of phage biology by providing highly quantitative, model-free readouts at single-virus resolution, helping to uncover single-virus phenomena missed by traditional measurements. Owing to significant reduction in manual effort, our method should enable rapid, high-throughput screening of a phage library against a target bacterial strain for applications such as therapy or diagnosis. |
