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 mutan...

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Autores principales:	Rogelio A. Rodriguez-Gonzalez, Chung Yin Leung, Benjamin K. Chan, Paul E. Turner, Joshua S. Weitz
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	antimicrobial agents bacteriophage therapy bacteriophages evolutionary biology mathematical modeling microbial ecology Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/94fae756d70040039afaf6350bf34d6c
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spelling	oai:doaj.org-article:94fae756d70040039afaf6350bf34d6c2021-12-02T18:39:47ZQuantitative Models of Phage-Antibiotic Combination Therapy10.1128/mSystems.00756-192379-5077https://doaj.org/article/94fae756d70040039afaf6350bf34d6c2020-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00756-19https://doaj.org/toc/2379-5077ABSTRACT 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.Rogelio A. Rodriguez-GonzalezChung Yin LeungBenjamin K. ChanPaul E. TurnerJoshua S. WeitzAmerican Society for Microbiologyarticleantimicrobial agentsbacteriophage therapybacteriophagesevolutionary biologymathematical modelingmicrobial ecologyMicrobiologyQR1-502ENmSystems, Vol 5, Iss 1 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	antimicrobial agents bacteriophage therapy bacteriophages evolutionary biology mathematical modeling microbial ecology Microbiology QR1-502
spellingShingle	antimicrobial agents bacteriophage therapy bacteriophages evolutionary biology mathematical modeling microbial ecology Microbiology QR1-502 Rogelio A. Rodriguez-Gonzalez Chung Yin Leung Benjamin K. Chan Paul E. Turner Joshua S. Weitz Quantitative Models of Phage-Antibiotic Combination Therapy
description	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.
format	article
author	Rogelio A. Rodriguez-Gonzalez Chung Yin Leung Benjamin K. Chan Paul E. Turner Joshua S. Weitz
author_facet	Rogelio A. Rodriguez-Gonzalez Chung Yin Leung Benjamin K. Chan Paul E. Turner Joshua S. Weitz
author_sort	Rogelio A. Rodriguez-Gonzalez
title	Quantitative Models of Phage-Antibiotic Combination Therapy
title_short	Quantitative Models of Phage-Antibiotic Combination Therapy
title_full	Quantitative Models of Phage-Antibiotic Combination Therapy
title_fullStr	Quantitative Models of Phage-Antibiotic Combination Therapy
title_full_unstemmed	Quantitative Models of Phage-Antibiotic Combination Therapy
title_sort	quantitative models of phage-antibiotic combination therapy
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/94fae756d70040039afaf6350bf34d6c
work_keys_str_mv	AT rogelioarodriguezgonzalez quantitativemodelsofphageantibioticcombinationtherapy AT chungyinleung quantitativemodelsofphageantibioticcombinationtherapy AT benjaminkchan quantitativemodelsofphageantibioticcombinationtherapy AT pauleturner quantitativemodelsofphageantibioticcombinationtherapy AT joshuasweitz quantitativemodelsofphageantibioticcombinationtherapy
_version_	1718377750680567808

Quantitative Models of Phage-Antibiotic Combination Therapy

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