Lying in Wait: Modeling the Control of Bacterial Infections via Antibiotic-Induced Proviruses

Abstract

Most bacteria and archaea are infected by latent viruses that change their physiology and responses to environmental stress. We use a population model of the bacterium-phage relationship to examine the role that latent phage play in the bacterial population over time in response to antibiotic treatment. We demonstrate that the stress induced by antibiotic administration, even if bacteria are resistant to killing by antibiotics, is sufficient to control the infection under certain conditions. This work expands the breadth of understanding of phage-antibiotic synergy to include both temperate and chronic viruses persisting in their latent form in bacterial populations. IMPORTANCE Antibiotic resistance is a growing concern for management of common bacterial infections. Here, we show that antibiotics can be effective at subinhibitory levels when bacteria carry latent phage. Our findings suggest that specific treatment strategies based on the identification of latent viruses in individual bacterial strains may be an effective personalized medicine approach to antibiotic stewardship.

Filamentous Bacteriophages and the Competitive Interaction between Pseudomonas aeruginosa Strains under Antibiotic Treatment: a Modeling Study

“…In turn, these properties can affect the physiological state of bacteria, and phage production ( 62 ). In addition, following previous modeling efforts ( 38 , 63 ), we assumed that bacterial growth can be described by a simple logistic model, a hypothesis that, although realistic, still needs to be validated through empirical studies. Also, we did not include the dynamics of colonization from different localized lung sections that could lead to more complicated source-sink dynamics of the strain types or competition-colonization trade-offs.…”

“…We choose to model bacterial growth directly with a logistic equation rather than a Gompertz equation or a mechanistic approach with nutrients, as it only requires estimating the maximum growth rate and carrying capacity. This model and its variants are used regularly to describe bacterial growth ( 38 , 63 , 66 , 67 ). We thus model the per-capita replication rate Φ( B tot ) as a decreasing logistic function of the total bacterial concentration in the local biofilm B tot : where r max is the absolute maximum replication rate, K is the bacterial density at which the per-capita reproductive rate Φ( B tot ) is equal to zero, and θ is the reduction in the per‐capita replication rate caused by the metabolic cost of phage production in Pf+ bacterial strains only (θ is equal to zero for Pf− strains).…”

“…In this study, we use a mathematical model to investigate how antibiotic sequestration by phages impacts the competitive dynamics of Pf+ and Pf− strains of Pa . Building up on previous modeling studies and experimental results ( 18 , 38 , 44 ), our model assumes that Pf− P. aeruginosa exhibits logistic growth in the absence of antibiotics, that phage production has a metabolic cost causing lower growth of Pf+ Pa with respect to Pf− Pa , and yet, that under antibiotic treatment, both Pf+ Pa ’s lower growth and antibiotic sequestration by the phage biofilm might decrease antibiotic impact on Pf+ Pa and provide a competitive advantage with respect to Pf− Pa . We analyzed these hypotheses under alternative assumptions on direct or indirect interaction between Pf+ and Pf− strains of Pa and a realistic range of model parameters according to the results of in vitro experiments, clinical studies, and published literature and explore implications for disease treatment ( Fig.…”

Phage-antibiotic synergy inhibited by temperate and chronic virus competition

“…Bacteria like P. aeruginosa are known to form biofilms at high densities, which effectively saturates the infection rate [14]. Previous studies have used a Hollings Type II functional response to model the infection rate, and the results are not qualitatively different [52]. However, a more sophisticated model would include biofilm formation in the infection assumptions.…”

The Impact of Pf Bacteriophages on the Fitness ofPseudomonas aeruginosa; A Mathematical Modeling Approach

“…Understanding the forces that influence the progression of these infections is critical for developing effective clinical treatments. Mathematical models can yield important insights into these dynamics (10)(11)(12)(13)(14)(15).…”