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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-8778386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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