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Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches
High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4235732/ https://www.ncbi.nlm.nih.gov/pubmed/25437607 http://dx.doi.org/10.3390/pathogens3010036 |
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author | Che, Dongsheng Hasan, Mohammad Shabbir Chen, Bernard |
author_facet | Che, Dongsheng Hasan, Mohammad Shabbir Chen, Bernard |
author_sort | Che, Dongsheng |
collection | PubMed |
description | High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs). PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms. |
format | Online Article Text |
id | pubmed-4235732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-42357322014-11-25 Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches Che, Dongsheng Hasan, Mohammad Shabbir Chen, Bernard Pathogens Review High-throughput sequencing technologies have made it possible to study bacteria through analyzing their genome sequences. For instance, comparative genome sequence analyses can reveal the phenomenon such as gene loss, gene gain, or gene exchange in a genome. By analyzing pathogenic bacterial genomes, we can discover that pathogenic genomic regions in many pathogenic bacteria are horizontally transferred from other bacteria, and these regions are also known as pathogenicity islands (PAIs). PAIs have some detectable properties, such as having different genomic signatures than the rest of the host genomes, and containing mobility genes so that they can be integrated into the host genome. In this review, we will discuss various pathogenicity island-associated features and current computational approaches for the identification of PAIs. Existing pathogenicity island databases and related computational resources will also be discussed, so that researchers may find it to be useful for the studies of bacterial evolution and pathogenicity mechanisms. MDPI 2014-01-13 /pmc/articles/PMC4235732/ /pubmed/25437607 http://dx.doi.org/10.3390/pathogens3010036 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. http://creativecommons.org/licenses/by/3.0/ This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Che, Dongsheng Hasan, Mohammad Shabbir Chen, Bernard Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches |
title | Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches |
title_full | Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches |
title_fullStr | Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches |
title_full_unstemmed | Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches |
title_short | Identifying Pathogenicity Islands in Bacterial Pathogenomics Using Computational Approaches |
title_sort | identifying pathogenicity islands in bacterial pathogenomics using computational approaches |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4235732/ https://www.ncbi.nlm.nih.gov/pubmed/25437607 http://dx.doi.org/10.3390/pathogens3010036 |
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