January 8, 2019

Blood infections need to be treated fast. This new tool could help.

WEST LAFAYETTE, Ind. — Bloodstream infections are notoriously deadly. Not because they’re untreatable, but because they work fast and are hard to diagnose. To figure out what medication to give patients, doctors need to culture the bacteria or fungi causing the infection, which takes several days.

In an attempt to treat the infection before results of the culture come back, doctors often give patients a drug cocktail, hoping that one of the medications in the bunch will cure the patient. Often, it doesn’t, and sometimes patients are harmed by taking drugs they didn’t need. This practice also contributes to the increasing prevalence of antimicrobial resistance.

Mortality rates are high – bloodstream infections kill more than 600 people each day in the United States. Mohamed Seleem, a professor of microbiology in Purdue University’s College of Veterinary Medicine, is trying to change this with a faster method for diagnosing these infections.

“We created a method that uses a blood sample from patients, and in 20 minutes identifies what kind of infection they have and what antibiotic or antifungal medication we should give them,” Seleem said. “Doing this without giving patients the wrong treatment or creating antimicrobial resistance is really novel.”

Antimicrobial resistance happens when a microorganism is able to stop a medication from working against it. As a result, standard treatments become ineffective, infections persist and continue to spread. Without effective antibiotics, major surgeries and chemotherapy become extremely high-risk.

Seleem’s new diagnostic tool images the infection and identifies it from the rest of the cells and bacteria in the blood. Once he finds the bacterium he’s looking for, he can go inside it and analyze it. The findings were published in the journal Analytical Chemistry.

“Like each person has an individual fingerprint, each bacterium has a single fingerprint that’s specific to that infection,” Seleem said. “We created a library with the fingerprint of each infection, that way, we can quickly identify what kind of infection the patient has.”

The original study considered only a single bacterium. Now, Seleem wants to make the technique more efficient and verify that it works on the six most common bloodstream infections. With help from Ji-Xin Cheng, a professor of biomedical engineering at Boston University, and a $1.7 million grant from the National Institutes of Health, he’s working toward these goals.

“The mortality rate is very high because patients can die from this in a few hours,” he said. “Finding a fast, efficient diagnostic tool is in high demand. We could save a lot of lives.”

Seleem’s research aligns with Purdue's Giant Leaps celebration, which acknowledges the university's global advancements in health, longevity and quality of life as part of Purdue's 150th anniversary. This is one of the four themes of the yearlong celebration's Ideas Festival, designed to showcase Purdue as an intellectual center solving real-world problems.

The technology is patented through the Purdue Research Foundation Office of Technology Commercialization. More information about the technology can be found here

Writer: Kayla Zacharias, 765-494-9318, kzachar@purdue.edu 

Source: Mohamed Seleem, 765-494-0763, mseleem@purdue.edu

Note to Journalists: For a copy of the paper, please contact Kayla Zacharias, Purdue News Service, kzachar@purdue.edu.


Antibiotic Susceptibility Determination within One Cell Cycle at Single-Bacterium Level by Stimulated Raman Metabolic Imaging

Weili Hong, Caroline W. Karanja, Nader S. Abutaleb, Waleed Younis, Xueyong Zhang, Mohamed N. Seleem, and Ji-Xin Cheng

The widespread use of antibiotics has significantly increased the number of resistant bacteria, which has also increased the urgency of rapid bacterial detection and profiling their antibiotic response. Current clinical methods for antibiotic susceptibility testing (AST) rely on culture and require at least 16 to 24 h to conduct. Therefore, there is an urgent need for a rapid method that can test the susceptibility of bacteria in a culture-free manner. Here we demonstrate a rapid AST method by monitoring the glucose metabolic activity of live bacteria at the single-cell level with hyperspectral stimulated Raman scattering (SRS) imaging. Using vancomycin-susceptible and -resistant enterococci E. faecalis as models, we demonstrate that the metabolic uptake of deuterated glucose in a single living bacterium can be quantitatively monitored via hyperspectral SRS imaging. Remarkably, the metabolic activity of susceptible bacteria responds differently to antibiotics from the resistant strain within only 0.5 h from the addition of antibiotics. Therefore, bacterial susceptibility and the minimum inhibitory concentration (MIC) of antibiotics can be determined within one cell cycle. Our metabolic imaging method is applicable to other bacteria species including E. coli, K. Pneumoniae, and S. aureus as well as different antibiotics, regardless of their mechanisms of inhibiting or killing bacteria.


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