bioRxivMicrobiologyPreprint
The dual nature of bacteriophage: growth-dependent predation and generalised transduction of antimicrobial resistance
Q. J. Leclerc, J. Wildfire, A. Gupta, J. A. Lindsay, G. M. Knight
Abstract
Bacteriophage ("phage") are both predators and evolutionary drivers for bacteria, notably contributing to the spread of antimicrobial resistance (AMR) genes by generalised transduction. Our current understanding of the dual nature of this relationship is limited. We used an interdisciplinary approach to quantify how these interacting dynamics can lead to the evolution of multi-drug resistant bacteria. We co-cultured two strains of Methicillin-resistant Staphylococcus aureus, each harbouring a different antibiotic resistance gene, with 80 generalized transducing phage. After a growth phase of 8h, bacteria and phage surprisingly coexisted at a stable equilibrium in our culture, the level of which was dependent on the starting concentration of phage. We detected double-resistant bacteria as early as 7h, indicating that transduction of AMR genes had occurred. We developed multiple mathematical models of the bacteria and phage relationship, and found that phage-bacteria dynamics were best captured by a model in which the phage burst size decreases as the bacteria population reaches stationary phase, and where phage predation is frequency-dependent. We estimated that one in every 108 new phage generated was a transducing phage carrying an AMR gene, and that double-resistant bacteria were always predominantly generated by transduction rather than by growth. Our results suggest a shift in how we understand and model phage-bacteria dynamics. Although rates of generalised transduction could be interpreted as too rare to be significant, they are sufficient to consistently lead to the evolution of multi-drug resistant bacteria. Currently, the potential of phage to contribute to the growing burden of AMR is likely underestimated.
- organism: bacteria (other)
- research focus: host-pathogen & immune response
- approach: statistical model
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