Quantitative Models of Phage-Antibiotic Combination Therapy

Abstract

The spread of multidrug-resistant (MDR) bacteria is a global public health crisis. Bacteriophage therapy (or "phage therapy") constitutes a potential alternative approach to treat MDR infections. However, the effective use of phage therapy may be limited when phage-resistant bacterial mutants evolve and proliferate during treatment. Here, we develop a nonlinear population dynamics model of combination therapy that accounts for the system-level interactions between bacteria, phage, and antibiotics for in vivo application given an immune response against bacteria. We simulate the combination therapy model for two strains of Pseudomonas aeruginosa, one which is phage sensitive (and antibiotic resistant) and one which is antibiotic sensitive (and phage resistant). We find that combination therapy outperforms either phage or antibiotic alone and that therapeutic effectiveness is enhanced given interaction with innate immune responses. Notably, therapeutic success can be achieved even at subinhibitory concentrations of antibiotics, e.g., ciprofloxacin. These in silico findings provide further support to the nascent application of combination therapy to treat MDR bacterial infections, while highlighting the role of innate immunity in shaping therapeutic outcomes.IMPORTANCE This work develops and analyzes a novel model of phage-antibiotic combination therapy, specifically adapted to an in vivo context. The objective is to explore the underlying basis for clinical application of combination therapy utilizing bacteriophage that target antibiotic efflux pumps in Pseudomonas aeruginosa In doing so, the paper addresses three key questions. How robust is combination therapy to variation in the resistance profiles of pathogens? What is the role of immune responses in shaping therapeutic outcomes? What levels of phage and antibiotics are necessary for curative success? As we show, combination therapy outperforms either phage or antibiotic alone, and therapeutic effectiveness is enhanced given interaction with innate immune responses. Notably, therapeutic success can be achieved even at subinhibitory concentrations of antibiotic. These in silico findings provide further support to the nascent application of combination therapy to treat MDR bacterial infections, while highlighting the role of system-level feedbacks in shaping therapeutic outcomes.

Keywords: antimicrobial agents; bacteriophage therapy; bacteriophages; evolutionary biology; mathematical modeling; microbial ecology.

FIG 1

Schematic of the phage-antibiotic combination therapy model. Antibiotic-sensitive bacteria (B_A) and phage-sensitive bacteria (B_P) are targeted by antibiotic (A) and the phage (P), respectively. Host innate immune response interactions (pink arrows) are included in the in vivo model. Innate immunity (I) is activated by the presence of bacteria and attacks both bacterial strains. Furthermore, in model versions accounting for partial resistance (blue arrows), B_A and B_P are targeted by both antibiotic and phage but at quantitatively different levels.

FIG 2

Dynamics of the immunophage therapy model against two different bacterial inocula. We simulate the phage therapy model developed in reference against two infection settings. In the first infection setting (a), a phage-sensitive bacterial inoculum, B_P (orange solid line), is challenged with phage (blue dashed line) inside an immunocompetent host. In the second scenario (b), antibiotic-sensitive bacteria, B_A (green solid line), are challenged with phage in the presence of an active immune response (purple dashed line). The initial bacterial density and the initial phage density are B₀ = 7.4 × 10⁷ CFU/g and P₀ = 7.4 × 10⁸ PFU/g, respectively. For the simulation, we use a heterogeneous mixing model as a functional form of phage infection. The growth rates of B_P and B_A are r_P = 0.75 h⁻¹ and r_A = 0.67 h⁻¹, respectively. Simulation run is 96 h with phage being administered 2 h after the infection. The bacterial carrying capacity is K_C = 10¹⁰ CFU/g.

FIG 3

Outcomes of the phage-antibiotic combination therapy model for two different infection settings. We simulate the combined effects of phage and antibiotics in an immunocompetent host infected with phage-sensitive bacteria (a), B_P (orange solid line). In panel b, the host is infected with antibiotic-sensitive bacteria, B_A (green solid line). The dynamics of the phage (blue dashed line) and innate immunity (purple dashed line) are shown for each infection setting. Initial bacterial density and phage density are B₀ = 7.4 × 10⁷ CFU/g and P₀ = 7.4 × 10⁸ PFU/g, respectively. For the simulation, we use a heterogeneous mixing model as a functional form of phage infection. The simulation run is 96 h (4 days). Antibiotic and phage are administered 2 h after the beginning infection. Ciprofloxacin is maintained at a constant concentration of 0.0350 μg/ml during the simulation. The carrying capacity of the bacteria is K_C = 10¹⁰ CFU/g.

FIG 4

Bacterial dynamics given joint exposure to phage and antibiotic. We simulate bacterial growth for 96 h in exposure to phage (blue dashed line) and antibiotic (data not shown) added 2 h after the beginning of the inoculation. The combination of phage and antibiotic is tested against two different bacterial inocula. The first inoculum consisted of exclusively phage-sensitive bacteria (a to c), B_P (orange solid line). The second inoculum consisted of antibiotic-sensitive bacteria (d to f), B_A (green solid line). Additionally, we test three different models of phage infection, heterogeneous mixing (a and d), phage saturation (b and e), and linear infection (c and f). The initial bacterial density and phage density are B₀ = 7.4 × 10⁷ CFU/g and P₀ = 7.4 × 10⁸ PFU/g, respectively. Ciprofloxacin is maintained at a constant concentration of 2.5× MIC (i.e., 0.0350 μg/ml) during the simulations.

FIG 5

Outcomes of the robustness analysis for different antimicrobial strategies. We simulate the exposure of bacteria to different antimicrobial strategies, such as antibiotic-only (a), antibiotic plus innate immunity (b), phage plus antibiotic (c), and phage-antibiotic combination in the presence of innate immunity (d). The heatmaps show the bacterial density at 96 h postinfection. Colored regions represent bacterial persistence (e.g., orange areas for ∼10⁹ CFU/g and bright yellow areas for ∼10¹⁰ CFU/g), while the white regions represent pathogen clearance. We vary the concentration of ciprofloxacin (MIC = 0.014 μg/ml), ranging from 0.1× MIC (0.0014 μg/ml) to 10× MIC (0.14 μg/ml), and the bacterial composition of the inoculum, ranging from 100% phage-sensitive bacteria (0% B_A) to 100% antibiotic-sensitive bacteria (100% B_A). Initial bacterial density and phage density (c and d) are B₀ = 7.4 × 10⁷ CFU/g and P₀ = 7.4 × 10⁸ PFU/g, respectively. Phage and antibiotic are administered 2 h after the beginning of the infection.