Considerations

  Applications

We have successfully demonstrated that E. Coli can be engineered to detect the presence of Pseudomonas aeruginosa autoinducers. Our project opens up a wide range of possibilities for future iGEM projects and even commercial devices. We hope that one day our work will make it easier to detect and combat P. aeruginosa infections in clinical settings.

In the immediate future, there are several ways to expand upon our project. One goal we were not able to accomplish is to match up the two different quorum sensing receptors with two different reporter genes. This would allow for more detailed information about the progression of a P. aeruginosa infection. In addition, the two separate signals could be used as part of an AND gate to reduce the risk of false positives. Another area that could be expanded upon is mining the large number of other P. aeruginosa genomic promoters that are autoinducer sensitive. We have sent two autoinducer-activated genomic promoters to the registry, but there are literally hundreds more within the genome. Each promoter likely has slightly different properties and sensitivities, so perhaps there are promoters particularly well suited for a detection system. Characterization and analysis of genomic promoters could allow for increased signal strength or decreased response time.

Our eventual goal is to use our constructs as part of a biosensor device which can read fluorescence in a clinical setting. This would allow for rapid analysis of a sample to see if it contains P. aeruginosa. The theoretical design of such a device is depicted below in Figure 1. We have begun construction of a prototype device that will allow us to test the basic functionality of this design.

Figure 1: A schematic design for a device which can detect and quantify the presence of P. aeruginosa. The image on the left is a circuit/schematic view, whereas the one on the right is a side view.

In this design, a blue LED is used to excite any GFP that is produced by our construct when P. Aeruginosa is present in a sample. The orange filter only allows emitted green light to pass through, blocking the original blue light. A photodiode will convert the light it receives from our construct into a measurable current signal, which can be analyzed by a microprocessor to determine if P. Aeruginosa is present and if so, at what concentration.

Physically, our prototype consists of an enclosed box with two compartments. The bottom compartment contains the blue (465 nm) LED light. The upper component contains our sample and a photodiode array. Our sample protrudes into the bottom compartment via a hole so that it receives blue light from the LED. Because the photodiodes are physically separated from the blue LED by a compartment wall, this version can be implemented with or without an orange light filter. The photodiodes can convert the fluorescence of the sample to current and send the data to a microprocessor. Figure 2 shows a picture of our current prototype.

Figure 2: Current prototype. A sample can be inserted in the main compartment, and a hole connects it to the bottom compartment. The bottom compartment contains an LED, which can shine blue light on our sample. A photodiode in the main compartment can convert the fluorescence signal of our sample into an electrical signal.

In designing our prototype, we kept in mind two of our goals for our biosensor: inexpensive and simple. LEDs and photodiodes are readily available inexpensive components and the circuit is not overly complex. Furthermore, the microprocessor will allow for a simple output reading that can be interpreted by anyone, with minimal training required. Thus all the user will have to do is insert the sample into a tube with our construct, place the tube in the device, wait an hour or two, and read the output.

As a proof of concept, we subjected each of our three key component systems to an array of blue LEDs with an orange filter. Figure 3 illustrates the validation of our concept and in turn, its practicality.

Figure 3: Proof of concept demonstration of the binary detection biosensor for PAI-1 via Las, concentration-responsive detection of PAI-2 via Rhl , and concentration-responsive detection of PAI-2 via a novel genomic promoter.

In the long term, this technology offers great potential for a rapid and routine P. aeruginosa detection system. Existing commercial methods require a potential sample to be grown overnight, but our system reported measurable GFP transcription within an hour of induction. This increased speed not only improves patient diagnosis efficiency, it also allows more tests to be run to ensure hospital surfaces are not contaminated. The combination of these two advantages would result in faster detection of P. aeruginosa in the hospital environment and could dramatically lower the incidence of this common nosocomial infection.