Cystic Fibrosis is a genetic disease that results in the accumulation of thick mucus in the epithelial linings of the entire body, particularly the respiratory tract. Over the course of a patient’s life the mucus-lined lung epithelium becomes repeatedly infected with pathogenic bacteria that stimulate an immune response, leading to inflammation, tissue damage, and ultimately, respiratory failure.

The microflora of the Cystic Fibrosis lung changes over time. In childhood, the major coloniser is Staphylococcus aureus, but as the patient matures other bacterial pathogens infect. The later-dominating pathogens, Pseudomonas aeruginosa and Burkholderia cepacia, are very difficult to eradicate and are associated with chronic decline in lung function. Burkholderia is so infectious, that patients have to be isolated from one another, and can be denied lung transplants due to the difficulty of eradication this bacterium.

It is important, therefore, for medics to monitor and identify the levels of bacteria within the respiratory tract of a Cystic Fibrosis patient. Currently, patients must provide sputum samples and identification of bacteria takes between 72 hours and 2 weeks, by which point the bacteria can be in an antibiotic resistant state.

The Dundee 2014 iGEM project is focused on designing and testing a device that will rapidly and non-invasively identify the bacteria colonising a Cystic Fibrosis patient. Three biosensors will be developed that recognise external signal molecules produced by key bacteria, all of which are known to be in sputum samples of Cystic Fibrosis patients. A quinolone signal (PQS) is produced by Pseudomonas aeruginosa, a Diffusible Signal Factor (DSF) is produced by Stenotrophomonas maltophilia, an organism that is also associated with cystic fibrosis lung infection in adults, and BDSF is a related, but chemically distinct molecule that is produced by Burkholderia cepacia.

By engineering signal recognition and signal transduction proteins from these biological systems the Dundee iGEM team want to produce a portable electronic device that will identify infection outside of the clinic, so that patients do not have to travel great distances, and can be used to help health professionals make informed and rapid decisions on antibiotic treatments.

Read this again by clicking on the board!