Model Developed to Help Predict Efficacy of Antibacterial Phage Therapy – Genetic Engineering & Biotechnology News

Antibiotic resistance represents a major public health challenge, but while bacteriophages— viruses that kill bacteria—could represent a potential weapon for fighting antibiotic-resistant pathogens, there are multiple challenges. Researchers at Inserm, Université Sorbonne Paris Nord, and Université Paris-Cité at the IAME Laboratory, in close collaboration with a team at Institut Pasteur and the Paris Public Hospitals Group, have now developed a model that they say might better predict the efficacy of phage therapy and possibly help to develop more robust clinical trials.
“In this study, we propose a new approach to streamline the clinical development of phage therapy, which otherwise continues to have its limitations,” said co-lead researcher, Jérémie Guedj, PhD, at Inserm. “Our model could be reused to predict the efficacy of any bacteriophage against the bacteria it targets, once a limited number of in vitro and in vivo data are available on its action … Beyond phage therapy, the model could also be used to test anti-infective therapies based on the association between bacteriophages and antibiotics.”
Guedj and colleagues reported on the development of their model in Cell Reports, in a paper titled, “Combination of in vivo phage therapy data with in silico model highlights key parameters for pneumonia treatment efficacy,” in which they concluded, “The use of such a model will rationalize the phage choice, the dose, and the route of administration in order to optimize the efficacy of phage therapy.”
The discovery of antibiotics revolutionized the history of medicine in the 20th century, allowing us to effectively fight bacteria for the first time. However, antibiotic resistance has become a major public health issue in recent decades. Each year, these resistant bacteria are estimated to be responsible for 700,000 deaths worldwide. Yet the discovery of new antibacterial agents has been stagnating for several years. In this context, phage therapy has recently generated renewed interest. “The pronounced slowdown in the discovery of new antibiotics to treat bacterial infections caused by multidrug resistant (MDR) pathogens has revived interest in bacteriophages (phages), viruses infecting bacteria,” the authors wrote.
This therapeutic approach involves the use of bacteriophages that target and destroy pathogenic bacteria, but are unable to infect humans. While the concept has been in existence for a long time, clinical development has been hampered by various limitations. Unlike conventional medicines, bacteriophages are complex biologics, whose action in the body, optimal dose, and most effective route of administration are difficult to study and anticipate. “The clinical (re)development of bacteriophage (phage) therapy to treat antibiotic-resistant infections faces the challenge of understanding the dynamics of phage-bacteria interactions in the in vivo context,” the investigators continued. “A major milestone for the widespread use in human populations is the determination of the optimal dose, route of administration, and treatment duration. This is a particularly complex endeavor for phages, as standard assessments of clinical pharmacology used to determine the processes of administration, distribution, metabolism, and excretion (ADME) of drugs are not adapted to phages.”
In order to remove some of these obstacles, Guedj’s research team at Inserm, in collaboration with the team of Laurent Debarbieux, PhD, at Institut Pasteur, developed a new mathematical model to better define the interactions between bacteriophages and pathogenic Escherichia coli bacteria in animals, and to identify the key parameters that influence the efficacy of phage therapy. “Here, we develop a general strategy coupling in vitro and in vivo experiments with a mathematical model to characterize the interplay between phage and bacteria during pneumonia induced by a pathogenic strain of Escherichia coli,” they wrote.
Various data from in vitro and in vivo experiments were used to construct the model. “… we coupled in vitro and in vivo experiments with mathematical modeling to approach the key parameters of phage-bacteria-host interactions and guide treatment strategies,” the scientists continued. “Unlike previous models that focused on specific aspects of phage-bacteria, phage-host immune system, or bacteria-host immune system interactions, here we aimed to design a synthetic, semi-mechanistic model that could be used to understand the tripartite phage-bacteria-host interactions in vivo.”
In particular, they used the bacteriophages’ infection parameters determined in the laboratory (for example, the duration of the infectious cycle of the bacteria, the number of viruses released when a bacterium is destroyed) and information collected during experiments using a mouse model of lung infection. “To ensure that the model recapitulates kinetics of phage-bacteria interactions during therapy, it was necessary to use, as much as possible, parameters deduced from animal experiments instead of in vitro conditions,” they noted. “For instance, the growth rate of bacteria, infectivity rate, and lysis rate were all deduced from experimental data.”
Some of the animals were infected with a bioluminescent strain of E. coli to monitor the bacteria within the body. Some animals were treated with bacteriophages at different doses, and using different routes of administration. “… dynamic and direct microbiological data were collected from groups of animals that were either (bacterial) uninfected and (phage) treated, infected and untreated, or infected and treated, using different inoculum doses and routes of administration.” The quantities of bacteria and bacteriophages thus measured over time helped to feed the mathematical model and to test which were the most important parameters for effective phage therapy.
Using their model, the scientists showed that the route of administration was an important parameter to consider when it comes to improving the animals’ survival: the more rapidly it brings the bacteriophages into contact with the bacteria, the more it is effective. In the animal model, the phage therapy administered intravenously was therefore less effective in comparison with the intratracheal route because fewer bacteriophages were reaching the lungs. On the other hand, when administered by intratracheal route, the model suggests that the dose of the medication given has little effect on the efficacy of the therapy.
Also of importance, this model incorporates data on the animals’ immune response in the context of phage therapy. The new model confirms and extends the principle that bacteriophages act in synergy with the immune system of infected animals, enabling more effective elimination of pathogenic bacteria.
And as the authors concluded, “… the model developed during this work could be used to predict the efficacy of virtually any phage for which a minimum set of in vitro and in vivo data must be obtained, which will considerably lower the number of experiments needed to validate such a phage during preclinical development. Beyond phage therapy, the model could also be implemented to test combined anti-infectious therapies such as the association of phages with antibiotics.”
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