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Using AI-driven computer vision and high-throughput multiplexed human cell infection assays to dissect intra- and intercellular signalling networks

Importance: Infectious diseases caused by bacteria and viruses are a leading cause of mortality worldwide. The rise of antimicrobial resistance and a dwindling antibiotic development pipeline have prompted the WHO to declare a global emergency.

Antibiotic development is hindered by our limited understanding of the complex processes at the host-pathogen interface. Traditional approaches are labour-intensive and low throughput, often investigating only a small set of proteins, one process, or pathway at a time.

We aim to harness the transformative power of AI-driven computer vision and new multicolour reporter cell libraries to accelerate research, revolutionize our understanding of host-pathogen interactions, and identify new targets for antimicrobial drugs.

Objectives & Methodology:

  1. Cell Engineering: Develop libraries of mammalian cells, bacteria, and viruses tagged with genetic and visual barcodes and reporters for cellular processes, allowing precise identification and measurement of multiple parameters in individual cells upon infection (See Kaufmann et al, 2022; Reicher, 2024; Nemčko et al. 2024)).
  2. High-Content Imaging: Multiplex the barcoded reporter cells, infect with pathogens (initially L. pneumophila and later viruses (See Lockwood et al, 2022)), and use high-content, high-resolution live fluorescence microscopy to capture images of host-pathogen interactions.
  3. AI-Driven Analysis: Implement AI algorithms to analyse the imaging data, identifying changes to organelles and cellular processes, states permissive or non-permissive to infection, and intercellular signaling networks, and to predict targets for new antimicrobials.
  4. Efficacy Testing: Perform proof-of-concept experiments testing the potential of inhibitors for selected targets as new antimicrobials.

Training and Opportunities: Students engaged in this project will acquire a unique, interdisciplinary skill set comprising state-of-the-art biomedical wet-lab research techniques (including genetic engineering and characterization of human cells and pathogens, high-content, high-resolution microscopy) and advanced bioinformatics skills, enabling them to leverage AI to develop cutting-edge drug discovery assays.

Get in touch to learn more about the project!

Click here to access the application form