Bacteriophages—viruses that infect bacteria—are locked in an evolutionary arms race with their hosts, but no one can reliably predict how that race plays out when the environment shifts underfoot. This project builds a physical model that maps how phages and bacteria coevolve across different scales, from single molecules to entire bacterial communities. The problem is that current approaches treat these interactions in static, well-mixed lab conditions, which bear little resemblance to the messy, fluctuating environments where bacteria actually live—such as the human gut or a biofilm on a medical implant. Without understanding how spatial structure and changing conditions shape evolution, we cannot harness phages for practical use. If the model works, it could transform how we deploy phages as precision tools. In medicine, it would help predict whether a phage therapy will drive bacteria to evolve resistance—or whether it will succeed. In agriculture and water treatment, it could guide the design of phage cocktails that remain effective over time. The research is fundamental science, but the same kind of quantitative framework that now underpins weather forecasting could one day allow us to forecast microbial evolution in real-world settings.
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This proposal aims at understanding and eventually predicting how phage-host interactions occurring at the molecular and single-cell scale shape and are shaped by the spatio-temporal dynamics of the host. My approach combines mechanistic physical modelling with tunable and reproducible experiments on bacteria and a range of different phages to characterise the direction, robustness and timescale of viral-host coevolution in complex environment that can be heterogeneous in space and changing over time. First, we will develop a comprehensive physical model that maps phage fitness to the multi-dimensional parameter space that describes phage-host interactions, on one side, and host dynamics, on the other, with goal to identify what fitness landscapes are available to a phage-host system. We will test the predictive power of our model by running multiple evolutionary experiments on 5 well-studied phages that span across the complexity of phage biology. Second, we will apply novel gene-editing techniques recently developed in my group and state-of-the-art microfluidic experiments to our library of evolved phages to investigate the effect of specific mutations on the virus-host interactions at the single-cell level and link genotype, phenotype and fitness. The result of these experiments are meant to both validate the model, but also refine the parameterization of the phage-host interactions within the model. Finally, we will apply this experimentally validated framework to predict phage-host coevolution in two complex environments: (i) gut-on-chip devices where phage and bacteria dwell in a mucosal layer and are subject to variable flow and medium conditions, and (ii) phage phi3T in B. subtilis biofilms, different spatial scales spontaneously emerge from the collective behaviour of the cell
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