New Method Bridging Antibiotic Susceptibility Testing with Species Identification

While the traditional approach of finding novel drug targets and developing treatments still plays an important role in managing AMR, it is clear that the future of AMR research must draw on new and more varied strategies. According to a new publication from one of our students at UAC, advances in diagnostic methods may be part of the solution. 

In a recent paper published in Nature Communications, UAC student Praneeth Karempudi and colleagues describe a novel method for diagnosing bacterial infections. Antibiotic susceptibility testing (AST) is a technique that allows physicians to determine which medications will be most effective against a patient’s bacterial infection. While AST is already employed in clinical settings, current methods require lab technicians to grow bacterial cultures over extended periods in the presence and absence of antibiotics. Because this process is so time consuming, it often leaves physicians in emergency situations with no choice but to prescribe based on their best judgment, so-called empirical treatment. This practice of uninformed medicating is not only less effective, it can also lead to poor clinical outcomes. However, thanks to developments in rapid AST such as those reported by Karempudi et al. a new standard of care may be just around the corner. 

To address the issue of slow diagnostics, the team employs a microfluidic chip which captures individual bacteria from a sample, optically monitoring their growth with and without antibiotics. However, this aspect of the technology is not novel as there are other similar rapid AST methods currently undergoing clinical implementation. Now, this work goes a step further by also including a method for species identification via a process called fluorescent in situ hybridization (FISH). This step involves labeling the bacteria by using fluorescent markers that are species-specific. The labeled bacteria can then be identified by the color of the lable. Combining the data from both steps allows users to determine the response to different antibiotics as well as the species identification including from samples containing multiple pathogen types. This information allows clinical investigators to make well-informed decisions about a patient's treatment.

The group outlined a few improvements which are required before this technology is brought to the clinic, stressing the need to run parallel samples with an antibiotic concentration gradient and the importance of real time data analysis. With these updates in mind, this new approach to resistance testing could become an essential tool in the field of infectious disease. In an era where personalized medicine is increasingly becoming the gold standard, innovations like rapid AST would ensure that patients suffering from infections are not left behind. 

Publication: Kandavalli, V., Karempudi, P., Larsson, J. et al. Rapid antibiotic susceptibility testing and species identification for mixed samples. Nat Commun 13, 6215 (2022). https://doi.org/10.1038/s41467-022-33659-1

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