Students Developing Portable Device to Quickly Detect Bacterial Infections

The new diagnostic tool, which uses genetically engineered bacteria to detect bacterial infections in blood samples, would lead to more informed decisions that would reduce the number of patients with viral infections being prescribed antibiotics, thus reducing unnecessary treatments and helping to tackle antibiotic resistance.

The device is being developed by the University of Sheffield’s (Sheffield, UK) team of students who participated in this year’s “International Genetically Engineered Machine Competition” – iGEM 2016 (October 27-31; Boston, MA, USA) in the field of synthetic biology. The team consists of students from a range of science, engineering, and medicine disciplines.


They hope the device could be used after GP surgeries to potentially help prevent complications from sepsis, or in walk-in clinics to enable patients with flu-like symptoms to have a small blood sample tested and be promptly told whether they have a bacterial or non-bacterial infection and be treated accordingly.

The tool distinguishes between bacterial and viral infection by detecting levels of the protein lipocalin-2, which is produced in high levels by immune system cells in response to bacterial infections. Bacteria produce siderophores that scavenge iron (as Fe3+) from host blood. In response, the immune system produces lipocalin-2, which sequesters siderophores. Lipocalin-2 levels can increase 5-fold during a bacterial infection. The device detects lipocalin-2 levels using genetically engineered bacteria that report a fluorescent signal inversely correlated to lipocalin-2 levels (via repression of GFP, the fluorescent reporter protein).

Therefore, patient blood with bacterial infection results in a weak GFP signal, in contrast to a strong signal without bacterial infection. The portable device, which includes a shoebox size fluorometer, potentially has the capability of rapidly determining the presence of any bacterial infection.

“Antibiotic resistance is a huge problem and this is why we chose to base our project on it,” said Saylee Jangam, a Sheffield student on the iGEM team, “We may not be able to reverse it, but with our device, we could potentially slow it down. What’s even more interesting is that we are using genetically engineered bacteria to detect the presence of bacterial infections in blood – that’s right – using bacteria to detect bacteria.”

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