This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: As multidrug antibiotic resistance emerges as a potent public health challenge, medical science has renewed attention on the potential for bacteriophage therapy. Bacteriophages, or phages, are viruses that target, infect and replicate inside bacteria, destroying them in the process.
To help maximize the success rate of this approach, researchers recently modeled the dynamics of bacteriophage therapy to explain particular therapies and optimize the composition of bacteriophage cocktails. "Phage are the most prevalent organisms on the planet," said Alan Perelson, a Los Alamos National Laboratory scientist and co-author of the research. "They exist everywhere bacteria exist.
However, each phage has evolved to narrowly target specific bacteria, and bacteria have evolved various mechanisms of resistance." Phage cocktails—combinations of particular phages for a patient facing a specific bacterial infection—represent a complicated form of personalized medicine. Given the fast and complex dynamics of bacterial responses to phages, it is not typically known why a particular phage therapy succeeded or failed. As described in the journal PLOS Computational Biology, the research team developed a mathematical model that could describe effective phage cocktails and optimize their diversity and timing.
The researchers developed their mathematical model by building on an existing model calibrated with data from phage therapy in a live mouse. The mathematical model was extended to humans and included multiple phages infecting multiple bacterial strains with varying phage resistance. The model was able to predict success based on several key factors.
The bacteria's pretreatment resistance level was critical, as were the diversity of the phage cocktail and the timing of its delivery. Phage therapy is a complicated dynamic in which more infective phages can wipe out more sensitive (i.e., less resistant) bacteria faster. That leaves resistant bacteria to expand, and they can quickly evolve better resistance, mutating to avoid infection by the phage.
The team found that therapy is best served by a diversity of phages, which overwhelm the bacteria's ability to evolve resistance quickly enough. The team also focused on the timing of phage delivery, determining that immediate treatment with the full phage cocktail offered the most success. That creates a high genetic barrier to bacterial resistance, meaning that the bacteria would need to accumulate several genetic changes or mutations to survive the therapy.
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