What is the problem/issue being addressed?
Bacteriophages are viruses that infect bacteria, and like all viruses they require their host to replicate. Both phages and their hosts are evolving entities, and the outcome of their co-evolutionary process is an open question that depends on many factors. DiversiPHI aims to understand how these many factors are related and integrated, by asking:
(1) Can a phage evolve to infect a given bacterium?
(2) What phage and host characteristics are important for this ability?
(3) Can phage-host compatibility after short-term evolution be computationally predicted?
To address these questions, we will use complementary computational and experimental approaches. First, we will use big data analysis to measure a range of phage and host factors that may be relevant to the interaction (genetic, functional, and ecological factors). Second, these factors will be combined by using artificial intelligence techniques with the aim of figuring out how and why they are important in the infection process. Third, we will use experimental evolution to test host-range evolution in a laboratory setting.
Why is it important for society?
Bacteriophages have important applications in e.g. medicine and biotechnology, and far-ranging effects on microbial community functioning in all environments. In turn, microbial communities have important roles in human, plant, and animal health and in a range of industrial processes. Thus, it is very important to be able to predict which bacteria might be (more readily) targeted by a certain phage, to understand the impact of phages on different bacteria, and by extension their effect on complex microbial communities. DiversiPHI not only aims to deliver such predictions, but also to shed light on the mechanisms underlying these interactions.
What are the overall objectives?
The objectives of the DiversiPHI project are to:
(1) collect genomic and metagenomic data for a wide range of bacteriophages that are present in public data repositories from a range of different (micro-) biomes;
(2) create computational analysis methods to measure genomic, functional, and ecological features, known as “phage-host interaction” (PHI) factors;
(3) integrate the PHI factors into a phage-host predictor and to compare the prediction accuracy for different training and testing datasets;
(4) identify which PHI factors are important for predicting bacteriophage host-range;
(5) to enhance our understanding of bacteriophage-bacterial co-evolution across biomes.
The outlook of the project is to understand the role of viruses in structuring the microbial biosphere, while generating critical insights and innovative computational tools to further the viral ecology field.
