📋 Tender Overview
Predicting The Evolution Of Complex Phage-Host Interactions
Untangling Interactions Of The Smallest, Most Numerous Organisms On Earthbacteriophages (Also Called Phages, Bacteria-Infecting Viruses) Are The Most Numerous, Diverse, And Uninvestigated Group Of Organisms On Earth. Recent Computational And Technological Advances Have Identified An Unprecedented Diversity Of Phages In Different Environments Such As The Human Gut And The Ocean~S Depths. Meanwhile, Understanding The Functions Of All These Phages Is Lagging Far Behind. The Evolutionary Interactions Between Phages And Their Hosts Have Led To An Incredible Variety Of Molecular Mechanisms, Several Of Which Led To Groundbreaking Biotechnological Applications. Given The Critical Role Of Phages In Medicine And Biotechnology, Including As An Alternative To Antibiotics To Combat Specific Bacterial Pests And Pathogens, Understanding What Enables A Phage To Infect A Host Is Critical. The Eu-Funded Diversiphi Project Is Developing And Applying New Computational And Experimental Methods To Better Understand The Evolution Of Phage-Host Interactions.
Funded Under
Excellent Science - European Research Council (Erc)
Total Cost
€ 2 000 000,00
Eu Contribution
€ 2 000 000,00
Coordinated By
Friedrich-Schiller-Universität Jena
Germany
Start Date
1 May 2020
End Date
31 October 2026
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
