Engineering synthetic phages to optimize bacterial killing in phage therapy

Background: Bacteriophage therapy, using viruses that infect and kill bacterial cells, is the emerging hope to fight the antimicrobial resistance crisis. However, the use of natural phages provides several challenges that could be overcome by using synthetic phages, which can be optimized for clinical use. A crucial function of phages as antimicrobials is their lysing of bacterial cells, but a key distinguishing feature of phages relative to chemotherapeutic antimicrobials is that their killing efficacy depends upon the production of phage lysis proteins by using bacterial cell functions.

As such, the efficacy of killing is likely to critically depend upon the cellular state, which is affected by extracellular conditions. Optimizing the design of lysis systems will be crucial to engineer effective phage therapy.

We will build on ongoing work in the Igler lab, which has found a diverse set of lysis 'clock' proteins (holins or pinholins), which determine the timing of cell lysis, and is investigating the molecular mechanisms of these diverse systems. In this project, we will make use of this diversity to engineer synthetic phages that carry 'optimal' and reliable lysis systems.

Objectives: The aim of the project is to improve the engineering of synthetic phages as new healthcare technologies by optimizing the systems that phages use to kill bacterial cells. The objectives are: To engineer synthetic phages with diverse lysis systems To predict which lysis systems or combinations of lysis systems optimize killing of bacterial pathogens

To increase phage efficacy in host-relevant environments through lysis system optimization

Approach: This project will combine mathematical modelling, machine learning, phage engineering via synthetic genomics and phage infection experiments in a multidisciplinary approach to advance the design and engineering of synthetic phages that are effective under clinical conditions. We will build upon tools in the Cai lab for computer-assisted design to build synthetic phages that infect the priority pathogen Pseudomonas aeruginosa.

In this well-defined genomic background, we will be able to study the impact of lysis systems on phage infection efficacy across host-relevant environments. Mathematical modelling and machine learning tools will be used to understand and extend experimental observations as well as to predict optimal design of lysis systems (or combinations of lysis systems).

Project outcomes: Synthetic engineering of phages is a crucial step in realizing effective, commercializable phage therapy. This project will use understanding of natural diversity in phage traits to optimize the design and engineering of synthetic phages. Investigating the impact of phage lysis systems across environmental conditions will lead to the development of more reliable and effective healthcare technologies and new design strategies.

Supervisor collaboration: The interplay between theoretical modelling, synthetic biology, and laboratory experiments constitutes a crucial part of the project that will enable more targeted optimization of synthetic phages, but necessitates interdisciplinary collaboration. Brockhurst and Cai are leading experts in microbial evolution and synthetic genomics, respectively.

The mathematical modelling expertise and training will be provided by Igler and will be an excellent opportunity for her to build her supervision skills, mentored by experienced senior colleagues. The proposed project will build new cross-faculty collaborations and translate the fundamental phage biology research of Brockhurst/Igler into applied engineering biology solutions.

Multidisciplinary training: This project will provide multidisciplinary training in synthetic genomics and engineering (PC, CI), experimental microbiology (MB, CI, PC), ecology and evolution (MB, CI) and mathematical modelling and machine learning (CI). The student will gain a broad