Current detection methods for CF lung infections

Patients normally attend the CF clinic once every three months, sometimes more if they are undergoing an exacerbation (a period when lung disease worsens). At these visits they undergo lung function tests and submit sputum samples (mucus that is coughed up from the lower airways (Fig 1)) which are cultured on different types of agar plates to detect pathogens present in the sputum (Fig 2). Some of these plates have to be incubated for up to a week, and so patients often don’t get results from their sputum samples for up to two weeks. In Scotland, some clinics cover vast areas, and patients and nurses have to travel long distances and reorganize work just to deliver or give a sputum sample. After discussing with patients and health care professionals, we wanted to give patients more control over their condition by designing a device which would help monitor for lung infections. This would complement the quarterly clinic visits and would not significantly increase the treatment burden already faced by patients. Importantly, we aimed for our device to detect the presence of pathogens much more rapidly than current methods (within 30 minutes).

Some species of bacteria, such as Burkholderia cenocepacia, can be mistaken for others; this is a problem because in clinical centres, patients infected with Burkholderia cenocepacia may be excluded from lung transplant lists¹ because it is so difficult to treat. It is also associated with 'cepacia syndrome' - acute pulmonary deterioration with bacteremia leading to sepsis, which often leads to death within weeks². While PCR can be used to verify if Burkholderia cenocepacia is present, it is costly and can take several days. We wanted to use synthetic biology to build a detector that would minimize risk of misidentification and of pathogenic isolates in CF sputum samples. In optimal conditions, chronic biofilm infections can form within two weeks. An infection or amplification of bacteria may not result in a noticeable exacerbation until bacterial load increases to a level to form a biofilm infection. Once a biofilm develops, eradication with antibiotics is much more difficult as biofilms are inherently resistant to antibiotics³. Earlier detection of these infections could improve the success rate of eradication therapy, maintaining pulmonary function for longer, thus extending quality of life for the patient. We wanted to address this problem by allowing our device to quantify the bacterial load. This knowledge could then be used to inform treatment options and make antibiotic eradication therapy more effective.

• to use synthetic biology in a responsible way, to address unmet clinical needs specified by patients.


• to use synthetic biology to build a range of biological detectors that would sense and respond to the chemical signals PQS and PAI produced by Pseudomonas aeruginosa, BDSF produced by Burkholderia species and DSF produced by Stenotrophomonas maltophilia, at concentrations in which they are found in CF lung sputa. The biological detectors will be housed in Escherichia coli as our chassis.


• to use fluorescent protein production as our output for proof-of-concept, ultimately replacing this with light emission for downstream applications.


• to model the system pathways in order to analyze and optimize the systems used in the biological detectors


• to build an easy to use piece of equipment to house the biological device and quantify light output as a measure of bacterial load. Ultimately allowing patients to monitor change in lung infections from the comfort of their own home.


• to engage stakeholders (health care professionals, CF patients, Medical Technology Developers) to discuss our ideas and to ensure that our products meet the needs of end users.