PhD Projects » ESR 7: Generation of datasets for phage-bacterial interactions in complex communities and mutational spectra analysis following exposure to selective pressure

Host institution:
University of Zurich (UZH), Switzerland
Local supervisor:
Dr. Shawna E. McCallin (UZH)
Local co-supervisor:
Prof. Dr. Niko Beerenwinkel (ETH Zurich)
Project partner:
ESR 14
Work packages:
WP 1.1 Virus identification
WP 1.2 Host prediction
WP 1.5 Virus products

Bacteriophages are the most abundant organisms on Earth, making it difficult to select which ones have the potential for therapeutic or other commercial applications. Current methods rely on non-iterative in vitro elaboration for product development, requiring >6 months per phage product.

In the current project, we aim to generate input data from experiments to build deep learning algorithms that will guide and support phage product development by

  • revealing which phages compete best under which specific conditions and combinations,
  • identifying mutations important for phage activity and survival under environmental conditions (pH, temperature), and
  • demonstrating the population effects of phage infection in complex community structures.

Our group specialises in the AI-prediction of phage-host interactions in two-components systems (phage, bacteria, lysis/no lysis). In this project, we will use a top-down approach to characterise the resulting community composition and mutational spectra from in vitro assays and/or clinical samples to measure: 1. competition between multiple phages; 2. phage-interaction in complex communities to simulate microbiome and polymicrobial infection settings; and 3. exposition of phage to multiple environmental conditions using genomic re-sequencing and/or cycling temperature capillary electrophoresis (CTCE) to identify regions of mutations associated with specific stimuli.