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Computational Prediction of Bacteriophage Host Ranges

Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and...

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Detalles Bibliográficos
Autores principales: Versoza, Cyril J., Pfeifer, Susanne P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778386/
https://www.ncbi.nlm.nih.gov/pubmed/35056598
http://dx.doi.org/10.3390/microorganisms10010149
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author Versoza, Cyril J.
Pfeifer, Susanne P.
author_facet Versoza, Cyril J.
Pfeifer, Susanne P.
author_sort Versoza, Cyril J.
collection PubMed
description Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and strains a bacteriophage is able to infect. Although experimental explorations of host ranges remain the gold standard, such investigations are inherently limited to a small number of viruses and bacteria amendable to cultivation. Here, we review recently developed bioinformatic tools that offer a promising and high-throughput alternative by computationally predicting the putative host ranges of bacteriophages, including those challenging to grow in laboratory environments.
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spelling pubmed-87783862022-01-22 Computational Prediction of Bacteriophage Host Ranges Versoza, Cyril J. Pfeifer, Susanne P. Microorganisms Review Increased antibiotic resistance has prompted the development of bacteriophage agents for a multitude of applications in agriculture, biotechnology, and medicine. A key factor in the choice of agents for these applications is the host range of a bacteriophage, i.e., the bacterial genera, species, and strains a bacteriophage is able to infect. Although experimental explorations of host ranges remain the gold standard, such investigations are inherently limited to a small number of viruses and bacteria amendable to cultivation. Here, we review recently developed bioinformatic tools that offer a promising and high-throughput alternative by computationally predicting the putative host ranges of bacteriophages, including those challenging to grow in laboratory environments. MDPI 2022-01-12 /pmc/articles/PMC8778386/ /pubmed/35056598 http://dx.doi.org/10.3390/microorganisms10010149 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Versoza, Cyril J.
Pfeifer, Susanne P.
Computational Prediction of Bacteriophage Host Ranges
title Computational Prediction of Bacteriophage Host Ranges
title_full Computational Prediction of Bacteriophage Host Ranges
title_fullStr Computational Prediction of Bacteriophage Host Ranges
title_full_unstemmed Computational Prediction of Bacteriophage Host Ranges
title_short Computational Prediction of Bacteriophage Host Ranges
title_sort computational prediction of bacteriophage host ranges
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778386/
https://www.ncbi.nlm.nih.gov/pubmed/35056598
http://dx.doi.org/10.3390/microorganisms10010149
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