Abstract: The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive viral diagnostic methods. During the last few years we have developed a novel method for fluorescently labelling viruses, which uses a cationic solution to bind short fluorescent DNAs to the surface of virus particles. The labelled viruses can then be easily imaged on a microscope. In this talk I’ll discuss how we have developed this methodology into a diagnostic test that uses machine learning algorithms to distinguish between images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in just a couple of minutes and does not require any lysis, purification or amplification steps. We are able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses, with high accuracy. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic methods.

Biography: Nicole Robb completed a BSc. in Microbiology at Imperial College London before doing a D.Phil at the Sir William Dunn School of Pathology, University of Oxford, where she specialised in the field of influenza virology. In 2011 she joined the Department of Physics at Oxford as a post-doctoral research associate, using single-molecule techniques to study how viruses and bacteria replicate. Nicole was awarded a Royal Society Dorothy Hodgkin Fellowship in 2017, and joined the University of Warwick in 2020, where her group uses fluorescent microscopy techniques to visualise, study and detect RNA viruses at the single-molecule level.