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Team:Dundee/Implementation/lassoInterface
From 2014.igem.org
Software
Gateway to The Lung Ranger
The L.A.S.S.O. Interface
To simulate how the L.A.S.S.O. could be used in the real world we created a software application to accompany the hardware. The L.A.S.S.O. Interface was developed to show how the results gathered by the L.A.S.S.O. could be automatically sent to the relevant people. The graphical user interface (GUI) was developed in Visual C# to interact with a local SQL Database. The database is composed of four tables, with the following columns:
- Clinic: Stores the details of a clinic
- Medical: Stores the details of a member of medical personnel
- Patient: Stores the details of a cystic fibrosis patient
- Results: Stores the results of patient tests
As shown in the diagram each entry in the Patient and Medical staff member is related to a clinic. This is to allow for the automatic transfer of data when tests are carried out. The Results table then stores the results of each patient test.
The interface allows for the user to log in as either a patient or member of medical staff (Fig 1.), with each being able to carry out different operations. Once a patient is logged in they are presented with a view that shows them the information that is stored about them (excluding their password) and the information about their clinic (Fig 2.). They can proceed from there to take a test. This will require the L.A.S.S.O. hardware to be attached to the computer they are using. The Interface goes through the procedures for a test to be taken, instructing a test plate to be inserted into the L.A.S.S.O. containing just an E. coli sample with no sputum. This allows the L.A.S.S.O. to run a calibration test so it knows how much background light is present. Once the the plate is inserted they begin the test controlled through the Interface and a progress bar informs the user how long the test has left. During the test 10 readings are taken and averaged to get the final voltage level. Once the test has been completed they are informed of the base reading and prompted to enter the actual sample which contains the plate with our engineered E. coli system and the sputum. The user then runs the test again and the same procedure is followed, with every action necessary being prompted through the on-screen instructions built into the Interface. The new reading then has the base reading subtracted from it to give the final sample result. Through the use of calibration of known voltage levels for different bioluminescence levels based on bacterial load the result is obtained. The user, i.e. the patient, is then presented with this information. It is also sent via email to all the medical staff connected to the clinic that the patient attends. This simulates the automatic transfer of data to medical staff, reducing the chance of important information being delayed. The result is then stored in the Results table along with the date, and the patient's information is updated to show that the current date was the last time they took a test.
If a member of medical staff logs in they will see a completely different view. They will view a list of the patients currently attending the clinic they work at. The list shows each patient's name, the last date they took a test and the last time they were reminded to take a test (Fig 3.). The user can then interact with each patient in one of two different ways. The first is double click on the patient's name. This opens up the patient's profile, showing all their information. This includes a graph which details their test results over time. This section of the application simulates the use of an electronic patient record allowing the medical staff easy access to the information they need. The other operation the medical staff can carry out is select a “Remind” button, this sends an email to the patient to take a test so that their bacterial load may be monitored.
This software application is meant to simulate the full service that would be made available in real production. The patient would most likely have control of the L.A.S.S.O. either through an inbuilt screen or smartphone application with the information being stored on a server. The medical staff would then interact with the data through a web portal.
Welcome to Dundee's 2014 Wiki (Site Information)
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 persistence of 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 Site Information in the navigation bar!
Bulletin Board (Policy & Practice)
Come look at the poster explaining how we involved the local and national Cystic Fibrosis community in our project, how we listened to people on the front line of the disease and how they affected our project.
School (Project)
Come in and learn about all the parts that make The Lung Ranger. The lab work that we carried out over the summer is explained here in detail, along with the modelling and implementation.
Library (Log Book)
Read about the experience the team has had over the summer. A week by week description of our work, how we carried out that work and some photos of our time together.
Saloon (iGEM community)
Come on in, take a seat and learn how we have interacted with the larger iGEM community. Who the team are, who helped them and how we helped others.
College of Life Sciences
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