Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails

ABSTRACT New therapies are necessary to combat increasingly antibiotic-resistant bacterial pathogens. We have developed a technology platform of computational, molecular biology, and microbiology tools which together enable on-demand production of phages that target virtually any given bacterial iso...

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Autores principales:	Catherine M. Mageeney, Anupama Sinha, Richard A. Mosesso, Douglas L. Medlin, Britney Y. Lau, Alecia B. Rokes, Todd W. Lane, Steven S. Branda, Kelly P. Williams
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2020
Materias:	Pseudomonas aeruginosa bioinformatics phage therapy Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/80713451e65d4d25823da5413ce5152f
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spelling	oai:doaj.org-article:80713451e65d4d25823da5413ce5152f2021-12-02T19:47:38ZComputational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails10.1128/mSystems.00659-202379-5077https://doaj.org/article/80713451e65d4d25823da5413ce5152f2020-08-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00659-20https://doaj.org/toc/2379-5077ABSTRACT New therapies are necessary to combat increasingly antibiotic-resistant bacterial pathogens. We have developed a technology platform of computational, molecular biology, and microbiology tools which together enable on-demand production of phages that target virtually any given bacterial isolate. Two complementary computational tools that identify and precisely map prophages and other integrative genetic elements in bacterial genomes are used to identify prophage-laden bacteria that are close relatives of the target strain. Phage genomes are engineered to disable lysogeny, through use of long amplicon PCR and Gibson assembly. Finally, the engineered phage genomes are introduced into host bacteria for phage production. As an initial demonstration, we used this approach to produce a phage cocktail against the opportunistic pathogen Pseudomonas aeruginosa PAO1. Two prophage-laden P. aeruginosa strains closely related to PAO1 were identified, ATCC 39324 and ATCC 27853. Deep sequencing revealed that mitomycin C treatment of these strains induced seven phages that grow on P. aeruginosa PAO1. The most diverse five phages were engineered for nonlysogeny by deleting the integrase gene (int), which is readily identifiable and typically conveniently located at one end of the prophage. The Δint phages, individually and in cocktails, killed P. aeruginosa PAO1 in liquid culture as well as in a waxworm (Galleria mellonella) model of infection. IMPORTANCE The antibiotic resistance crisis has led to renewed interest in phage therapy as an alternative means of treating infection. However, conventional methods for isolating pathogen-specific phage are slow, labor-intensive, and frequently unsuccessful. We have demonstrated that computationally identified prophages carried by near-neighbor bacteria can serve as starting material for production of engineered phages that kill the target pathogen. Our approach and technology platform offer new opportunity for rapid development of phage therapies against most, if not all, bacterial pathogens, a foundational advance for use of phage in treating infectious disease.Catherine M. MageeneyAnupama SinhaRichard A. MosessoDouglas L. MedlinBritney Y. LauAlecia B. RokesTodd W. LaneSteven S. BrandaKelly P. WilliamsAmerican Society for MicrobiologyarticlePseudomonas aeruginosabioinformaticsphage therapyMicrobiologyQR1-502ENmSystems, Vol 5, Iss 4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Pseudomonas aeruginosa bioinformatics phage therapy Microbiology QR1-502
spellingShingle	Pseudomonas aeruginosa bioinformatics phage therapy Microbiology QR1-502 Catherine M. Mageeney Anupama Sinha Richard A. Mosesso Douglas L. Medlin Britney Y. Lau Alecia B. Rokes Todd W. Lane Steven S. Branda Kelly P. Williams Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails
description	ABSTRACT New therapies are necessary to combat increasingly antibiotic-resistant bacterial pathogens. We have developed a technology platform of computational, molecular biology, and microbiology tools which together enable on-demand production of phages that target virtually any given bacterial isolate. Two complementary computational tools that identify and precisely map prophages and other integrative genetic elements in bacterial genomes are used to identify prophage-laden bacteria that are close relatives of the target strain. Phage genomes are engineered to disable lysogeny, through use of long amplicon PCR and Gibson assembly. Finally, the engineered phage genomes are introduced into host bacteria for phage production. As an initial demonstration, we used this approach to produce a phage cocktail against the opportunistic pathogen Pseudomonas aeruginosa PAO1. Two prophage-laden P. aeruginosa strains closely related to PAO1 were identified, ATCC 39324 and ATCC 27853. Deep sequencing revealed that mitomycin C treatment of these strains induced seven phages that grow on P. aeruginosa PAO1. The most diverse five phages were engineered for nonlysogeny by deleting the integrase gene (int), which is readily identifiable and typically conveniently located at one end of the prophage. The Δint phages, individually and in cocktails, killed P. aeruginosa PAO1 in liquid culture as well as in a waxworm (Galleria mellonella) model of infection. IMPORTANCE The antibiotic resistance crisis has led to renewed interest in phage therapy as an alternative means of treating infection. However, conventional methods for isolating pathogen-specific phage are slow, labor-intensive, and frequently unsuccessful. We have demonstrated that computationally identified prophages carried by near-neighbor bacteria can serve as starting material for production of engineered phages that kill the target pathogen. Our approach and technology platform offer new opportunity for rapid development of phage therapies against most, if not all, bacterial pathogens, a foundational advance for use of phage in treating infectious disease.
format	article
author	Catherine M. Mageeney Anupama Sinha Richard A. Mosesso Douglas L. Medlin Britney Y. Lau Alecia B. Rokes Todd W. Lane Steven S. Branda Kelly P. Williams
author_facet	Catherine M. Mageeney Anupama Sinha Richard A. Mosesso Douglas L. Medlin Britney Y. Lau Alecia B. Rokes Todd W. Lane Steven S. Branda Kelly P. Williams
author_sort	Catherine M. Mageeney
title	Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails
title_short	Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails
title_full	Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails
title_fullStr	Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails
title_full_unstemmed	Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails
title_sort	computational basis for on-demand production of diversified therapeutic phage cocktails
publisher	American Society for Microbiology
publishDate	2020
url	https://doaj.org/article/80713451e65d4d25823da5413ce5152f
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Computational Basis for On-Demand Production of Diversified Therapeutic Phage Cocktails

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