Real-Time Arms Race in a Chip: Microfluidics-Enabled High-Resolution Mapping of Phage-Host Coevolution Dynamics

Current coevolution studies (e.g., Yu et al. 2024) rely on bulk sequencing, averaging out rare but crucial events. Gantz et al. (2024) highlight microfluidics for ultrahigh-throughput screening but not for dynamic evolution. I propose a microfluidic chip where isolated phage-bacteria pairs in picoliter droplets are monitored in real-time via fluorescence reporters (e.g., phage infection triggers GFP; resistance triggers RFP). Deep sequencing of "winning" droplets at multiple intervals will map evolutionary trajectories at single-cell resolution. This could uncover ephemeral resistance mechanisms (e.g., phase-variable expression) or phage counter-adaptations invisible to bulk methods. Unlike Zahnd et al.'s affinity maturation (2010), which optimizes static properties, this captures process-level evolution. It would provide the first high-resolution map of phage-host "arms races," informing therapy design to pre-empt resistance.

References:

1. Phage-mediated virulence loss and antimicrobial susceptibility in carbapenem-resistant Klebsiella pneumoniae. Yanshuang Yu, Mengzhu Wang, Liuying Ju, Minchun Li, Mengshi Zhao, Hui Deng, Christopher Rensing, Qiu-e Yang, Shungui Zhou (2024). mBio.
2. On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering. Maximilian Gantz, Simon V. Mathis, Friederike E. H. Nintzel, Pietro Liò, F. Hollfelder (2024). Faraday discussions.
3. Computational analysis of off-rate selection experiments to optimize affinity maturation by directed evolution.. Christian Zahnd, Casim A. Sarkar, A. Plückthun (2010). Protein engineering, design & selection : PEDS.