Antani Jyot D, Ward Timothy, Emonet Thierry, Turner Paul E
Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520.
Center for Phage Biology & Therapy, Yale University, New Haven, CT 06520.
Proc Natl Acad Sci U S A. 2024 Dec 24;121(52):e2410905121. doi: 10.1073/pnas.2410905121. Epub 2024 Dec 19.
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 coculturing 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.
噬菌体,即细菌病毒,在地球生物圈中发挥着关键作用,并且在对抗传染病方面作为治疗和诊断工具具有巨大潜力。噬菌体附着于细菌细胞是这种相互作用的关键起始步骤。经典的用于量化噬菌体附着动力学的测定方法涉及细菌和噬菌体的共培养及计数,这既费力又耗时,因此通量低,并且只能提供基于模型的吸附速率常数的总体估计。在这里,我们利用荧光显微镜和粒子追踪来获取单个病毒粒子与细胞相互作用的轨迹。轨迹持续时间量化了停留时间的异质性,即每个噬菌体与细菌相互作用所花费的时间。平均停留时间与经典测量的吸附速率常数密切相关。我们成功地应用这项技术来量化几种噬菌体的宿主附着动力学,包括那些靶向关键细菌病原体的噬菌体。这种方法应该会使噬菌体生物学领域受益,通过在单病毒分辨率下提供高度定量、无模型的读数,有助于揭示传统测量所遗漏的单病毒现象。由于人工操作的显著减少,我们的方法应该能够针对目标细菌菌株对噬菌体文库进行快速、高通量筛选,以用于治疗或诊断等应用。