Coevolutionary phage training leads to greater bacterial suppression and delays the evolution of phage resistance.
Joshua M BorinSarit AvraniJeffrey E BarrickKatherine L PetrieJustin R MeyerPublished in: Proceedings of the National Academy of Sciences of the United States of America (2021)
The evolution of antibiotic-resistant bacteria threatens to become the leading cause of worldwide mortality. This crisis has renewed interest in the practice of phage therapy. Yet, bacteria's capacity to evolve resistance may debilitate this therapy as well. To combat the evolution of phage resistance and improve treatment outcomes, many suggest leveraging phages' ability to counter resistance by evolving phages on target hosts before using them in therapy (phage training). We found that in vitro, λtrn, a phage trained for 28 d, suppressed bacteria ∼1,000-fold for three to eight times longer than its untrained ancestor. Prolonged suppression was due to a delay in the evolution of resistance caused by several factors. Mutations that confer resistance to λtrn are ∼100× less common, and while the target bacterium can evolve complete resistance to the untrained phage in a single step, multiple mutations are required to evolve complete resistance to λtrn. Mutations that confer resistance to λtrn are more costly than mutations for untrained phage resistance. Furthermore, when resistance does evolve, λtrn is better able to suppress these forms of resistance. One way that λtrn improved was through recombination with a gene in a defunct prophage in the host genome, which doubled phage fitness. This transfer of information from the host genome is an unexpected but highly efficient mode of training phage. Lastly, we found that many other independently trained λ phages were able to suppress bacterial populations, supporting the important role training could play during phage therapeutic development.
Keyphrases
- pseudomonas aeruginosa
- healthcare
- primary care
- cardiovascular disease
- public health
- gene expression
- physical activity
- mesenchymal stem cells
- type diabetes
- body composition
- resistance training
- oxidative stress
- transcription factor
- cystic fibrosis
- risk factors
- dna methylation
- social media
- quality improvement
- virtual reality