Gram-negative bacteria are becoming a major threat to global health due to their ability to resist multiple antibiotics, making infections difficult to treat. This alarming situation has prompted the National Institutes of Health (NIH) to award $3.96 million to Vincent Tam, a professor at the University of Houston College of Pharmacy, to develop more effective combination therapies against these superbugs.
Innovative Approach to Beat Superbugs
Professor Vincent Tam’s research focuses on designing new combination therapies to overcome the antibiotic defenses of gram-negative bacteria. With this grant, Tam will develop a state-of-the-art monitoring device and data-processing algorithm to guide the creation of these therapies. His goal is to outsmart the bacteria’s resistance mechanisms by identifying drug combinations that can effectively break through their defenses.
Growing Threat in Hospitals
Gram-negative bacterial infections are on the rise, especially in hospital settings, where patients are vulnerable to severe illnesses like urinary tract infections, pneumonia, bloodstream infections, wound or surgical infections, and even meningitis. These bacteria are particularly challenging to treat because they are encased in a tough outer capsule that protects them from the body’s immune response. This capsule prevents white blood cells from destroying the bacteria, making infections persistent and difficult to clear.
Furthermore, when these bacteria are killed, they release toxins from their outer membrane, potentially triggering severe inflammation, fever, or septic shock. “Our research aims to provide clinicians with guidance on selecting effective combination therapies without needing detailed knowledge of the bacteria’s resistance mechanisms,” said Tam.
Research Plan and Goals
Tam’s research will start by identifying effective antibiotic combinations against three highly resistant gram-negative strains: Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae. He will then validate his findings using a mathematical model that predicts clinical outcomes, ensuring that the combinations are not only theoretically effective but also work in real-world settings.
The model-based system Tam is developing has the potential to extend beyond these bacteria. “This approach is not limited to specific antibiotic-bacteria combinations,” he explained. “It could be adapted for other antimicrobials like antifungals and antiretrovirals, and for different pathogens such as Neisseria gonorrhoeae, Candida auris, and even HIV.”
Collaborative Effort
The project is a collaborative effort involving experts from different institutions. At the University of Houston, Professor Michael Nikolaou from the Department of Chemical and Biomolecular Engineering will serve as a co-investigator. Additional support comes from William Musick at Houston Methodist Hospital and Truc Cecilia Tran at the Houston Methodist Research Institute.
With the NIH’s support, this research could pave the way for more effective treatment strategies, potentially saving lives by overcoming the challenges posed by multidrug-resistant gram-negative bacteria.
Related topics:
- French Researchers Develop MassiveFold: A Faster, More Efficient Protein Structure Prediction Tool
- Study Investigates Genetic Factors Linked to Alzheimer’s Disease Using Cerebrospinal Fluid Proteins
- Study on Stem Cell Treatment for Limbal Stem Cell Deficiency Shows Positive Results