Nipping Bacterial Infections in the Bud: New Method Could Accelerate Diagnosis and Treatment

in News
October 3rd, 2013

By Mark Dwortzan

 

Assistant Professor Ahmad S. Khalil (BME) and Professor James J. Collins (BME, MSE, SE) (Photo by Kalman Zabarsky)

Assistant Professor Ahmad S. Khalil (BME) and Professor James J. Collins (BME, MSE, SE) (Photo by Kalman Zabarsky)

Diagnosing and pinpointing the most effective treatment for a bacterial infection can take several days. Patients must wait as clinicians culture bacteria from a sample of the infected site, test its response to different candidate antibiotics, and select the most effective choice. Meanwhile, they’re given broad spectrum antibiotics that could be far less effective, leaving them prone to spreading the infection and generating antibiotic- resistant bacteria.

Now a new diagnostic approach that Assistant Professor Ahmad S. Khalil (BME) and Professor James J. Collins (BME, MSE, SE) are exploring could avoid time-consuming culturing and identify the most suitable antibiotic in just a few hours, leading to rapid treatment and infection containment.

To develop a culture-free diagnostic device for bacterial infections, Khalil and Collins have received a two-year, $260,000 research grant from the Institut Merieux, a for-profit organization in France that advances solutions to combat infectious diseases and cancers. Drawing on work by Collins elucidating how antibiotics kill bacteria and Khalil’s expertise in microfluidics and diagnostic devices, the researchers aim to create a universal diagnostic platform that can quickly assess antibiotic susceptibility for a wide range of bacterial infections.

“Our goal is to be able to perform antibiotic susceptibility testing across a full spectrum of antibiotics on a single chip,” said Khalil, who was recently appointed as an Innovation Career Development Professor. “And to do this as rapidly as possible.”

To launch the study, which is also supported by the Wallace H. Coulter Foundation, the researchers are subjecting samples of the most common bacterial infection, urinary tract infection (UTI), with antibiotics that target UTIs, and determining which antibiotics are most effective. They’re also building prototypes of microfluidic chips they’ll use to automate the process.

“Our two-year goal is a proof-of-principle that demonstrates that our technology works across a range of bacteria and resistance mechanisms,” said Khalil.