DiversiPHI SIGNED

Project "DiversiPHI" data sheet

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 Partnership

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 Project objective

What determines if a phage can infect a host? This question arises as we work to understand the ecological roles of the hundreds of thousands of unknown viruses that I and others have discovered around the world. Phages are the most abundant life forms on Earth with important applications in medicine and biotechnology and far-ranging effects on microbial community functioning in all environments. Phage-host interactions (PHI) are an emergent trait that depends on the complex integration of factors like their taxonomic identity, the environment, and phage- and host-encoded proteins. With DiversiPHI, I propose a research program to unravel PHI by 1) measuring, 2) modelling, and 3) experimentally testing these diverse factors to develop a predictive understanding of host-range evolution. I will first measure a range of evolutionary, ecological, and molecular factors contributing to PHI at high resolution using newly developed computational tools that exploit high-throughput datasets from thousands of natural environments around the world. Next, I will apply deep learning to integrate these measurements to simultaneously (i) quantify the relative importance and complex inter-dependencies of the different factors, and (ii) create a unique predictive model of host-range evolution. To complement these in silico predictions, I will develop an experimental evolution setup that tests the effect of the different PHI factors on host-range evolution in vitro. Little is known about the abundant phages and their role in shaping our microbial world. DiversiPHI will vastly elevate this understanding and contribute new fundamental knowledge on how species-species interactions evolve in complex environments. Moreover, I will provide valuable new analysis tools to the community and consolidate my strong international reputation as a pioneering researcher in the cross-disciplinary field encompassing microbial ecology, virology, metagenomics, bioinformatics, and computer learning.