Automating High-Throughput Viral Isolation and Characterisation for Phage Therapy

Abstract

With the escalating global threat posed by antimicrobial resistance, there is an urgent need for innovative therapeutic solutions. The treatment of bacterial infection with bacteriophages (phage therapy) is a promising tool in the fight, and the number of phage repositories across the world is increasing. The labour-intensive nature of current manual methods used by phage repositories for isolating, characterizing, and selecting phages contributes to their high cost and challenges in scalability. This thesis looks at the high-throughput automation of these methods, and the development of an open-source, cost-effective pipeline to facilitate the foundation and operation of phage repositories. Here, laboratory automation is achieved using the Opentrons OT-2 liquid handling robot to process environmental and wastewater samples and isolate phages. Subsequently, phages are characterised via their changing morphology in a plaque assay with a novel Python package; Phagecode, which implements an object detection neural network and image analysis techniques to measure plaque features. Finally, plaques with favourable properties for therapeutic use are automatically picked using the OT-2. Testing of this interdisciplinary approach demonstrated success when isolating, characterising, selecting, and picking phages within the Citizen Phage Library, which supports its potential to improve the accessibility of phage therapy.