Scaling Phage-Bacteria Interaction Contexts: From Pairwise Mechanisms to Community Dynamics

Bacteriophages (phages), viruses that parasitize bacteria, hold tremendous potential as antimicrobial agents, microbiome modulators, and industrial biocontrol tools; yet clinical and environmental applications remain frustratingly inconsistent. Decades of research on isolated phage-bacteria pairs have revealed fundamental mechanisms governing infection specificity, coevolutionary arms races, and resistance trade-offs. These foundational studies, however, do not help predict outcomes when phages encounter multi-species assemblages characteristic of natural ecosystems. In this review, we integrate recent advances examining how interaction complexity shapes phage efficacy across four scales, gradually from simple phage-bacteria pairs to phage-bacterial communities. At every scale, emergent properties arise from complex interactions. Dissecting these dynamics requires technologies that can track multiple lineages simultaneously. DNA barcoding, which inserts unique genetic identifiers into bacterial and phage genomes, offers a promising solution. While barcoding all members in a synthetic community is unrealistic, we propose that even foundational reference sets of barcoded phage-bacteria pairs would enable systematic investigation of resistance evolution, competitive interactions, and functional outcomes in realistic contexts. Bridging laboratory insights and field performance demands integrating genetic engineering, high-throughput tracking, functional profiling, and predictive modeling into a coordinated research framework.