ACROPATH: Artificial Cells for highly sensitive and RObust diagnosis of PATHogen infections

Rapid diagnosis of infectious disease is critical to successful clinical intervention. Identifying the specific pathogen responsible for a patient’s symptoms and determining whether it is susceptible to antibiotics can be labour-intensive and slow. While some well-resourced hospitals can take advantage of rapid PCR-based diagnostics to identify bacterial species, identification of antibiotic-resistance requires isolation and culture of organisms which can take days rather than the hours that might be needed to treat a patient. Similarly, identification of virulent strains typically requires independent identification of individual markers such as toxins in a sample in an independent step to pathogen identification. In this project, we will use an engineering biology approach to develop artificial cells (artCells) which can bind to and identify intact pathogenic bacteria in a sample. Our approach is based upon the generation of artificial transmembrane sensors which will bind to either cell surface proteins or soluble proteins to activate production of a visible response within the artCell which can be detected using commonly available laboratory equipment. Integration of DNA-based AND gates into the artCells will then extend these to enable combined detection of bacteria together with markers of antibiotic resistance. Finally, we will carry out the key steps required to adapt our laboratory-scale technology to enable application in a clinical context addressing issues of production, stability and specificity. This international, interdisciplinary project will take advantage of specific expertise in protein engineering, vesicle production and cell-free transcription/translation to generate the artificial cells. Initially we will optimise four key underpinning technologies: producing vesicles with embedded transmembrane domains; modifying these segments to generate artificial sensors; optimisation of the genetic circuits required for sensing and finally encapsulation of this machinery. These will then be brought together by the team of researchers to generate the final artCells using the optimised approaches. The artCells will be readily adaptable to the detection of multiple pathogens and toxins based on the availability of suitable antigen-binding proteins due to the modular approach to artCell construction. Within the project we will use already available proteins to develop model artCells capable of detecting the pathogenic organism Staphylococcus aureus and combine these with sensors capable of detecting the toxin produced by cholera toxin. Beyond the project, this could be immediately adapted to detection of other pathogens (e.g. C. difficile) by the use of suitable sets of alternative antigen binding proteins. These artCells would then be used in laboratory work-flows to distinguish non-harmful (commensal) and virulent (toxin-producing) strains of a particular pathogen. In the final work package, we will develop a modular approach to assembly of the artCells at a late stage, using this approach we envision that it will be possible to generate panels of artCells with specificity for the same pathogen and different markers of antibiotic resistance to enable rapid identification of candidate therapies for immediate use in the clinic. Critically, this approach will not be dependent upon specific high-cost equipment and, subject to optimisation of product stability, would be potentially applicable in healthcare environments in low and middle-income countries.