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Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak
BACKGROUND: Next generation sequencing (NGS) is being increasingly used for the detection and characterization of pathogens during outbreaks. This technology allows rapid sequencing of pathogen full genomes, useful not only for accurate genotyping and molecular epidemiology, but also for identificat...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4225559/ https://www.ncbi.nlm.nih.gov/pubmed/24252229 http://dx.doi.org/10.1186/1471-2334-13-554 |
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author | Lavezzo, Enrico Toppo, Stefano Franchin, Elisa Di Camillo, Barbara Finotello, Francesca Falda, Marco Manganelli, Riccardo Palù, Giorgio Barzon, Luisa |
author_facet | Lavezzo, Enrico Toppo, Stefano Franchin, Elisa Di Camillo, Barbara Finotello, Francesca Falda, Marco Manganelli, Riccardo Palù, Giorgio Barzon, Luisa |
author_sort | Lavezzo, Enrico |
collection | PubMed |
description | BACKGROUND: Next generation sequencing (NGS) is being increasingly used for the detection and characterization of pathogens during outbreaks. This technology allows rapid sequencing of pathogen full genomes, useful not only for accurate genotyping and molecular epidemiology, but also for identification of drug resistance and virulence traits. METHODS: In this study, an approach based on whole genome sequencing by NGS, comparative genomics, and gene function prediction was set up and retrospectively applied for the investigation of two N. meningitidis serogroup C isolates collected from a cluster of meningococcal disease, characterized by a high fatality rate. RESULTS: According to conventional molecular typing methods, all the isolates had the same typing results and were classified as outbreak isolates within the same N. meningitidis sequence type ST-11, while full genome sequencing demonstrated subtle genetic differences between the isolates. Looking for these specific regions by means of 9 PCR and cycle sequencing assays in other 7 isolates allowed distinguishing outbreak cases from unrelated cases. Comparative genomics and gene function prediction analyses between outbreak isolates and a set of reference N. meningitidis genomes led to the identification of differences in gene content that could be relevant for pathogenesis. Most genetic changes occurred in the capsule locus and were consistent with recombination and horizontal acquisition of a set of genes involved in capsule biosynthesis. CONCLUSIONS: This study showed the added value given by whole genome sequencing by NGS over conventional sequence-based typing methods in the investigation of an outbreak. Routine application of this technology in clinical microbiology will significantly improve methods for molecular epidemiology and surveillance of infectious disease and provide a bulk of data useful to improve our understanding of pathogens biology. |
format | Online Article Text |
id | pubmed-4225559 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42255592014-11-11 Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak Lavezzo, Enrico Toppo, Stefano Franchin, Elisa Di Camillo, Barbara Finotello, Francesca Falda, Marco Manganelli, Riccardo Palù, Giorgio Barzon, Luisa BMC Infect Dis Research Article BACKGROUND: Next generation sequencing (NGS) is being increasingly used for the detection and characterization of pathogens during outbreaks. This technology allows rapid sequencing of pathogen full genomes, useful not only for accurate genotyping and molecular epidemiology, but also for identification of drug resistance and virulence traits. METHODS: In this study, an approach based on whole genome sequencing by NGS, comparative genomics, and gene function prediction was set up and retrospectively applied for the investigation of two N. meningitidis serogroup C isolates collected from a cluster of meningococcal disease, characterized by a high fatality rate. RESULTS: According to conventional molecular typing methods, all the isolates had the same typing results and were classified as outbreak isolates within the same N. meningitidis sequence type ST-11, while full genome sequencing demonstrated subtle genetic differences between the isolates. Looking for these specific regions by means of 9 PCR and cycle sequencing assays in other 7 isolates allowed distinguishing outbreak cases from unrelated cases. Comparative genomics and gene function prediction analyses between outbreak isolates and a set of reference N. meningitidis genomes led to the identification of differences in gene content that could be relevant for pathogenesis. Most genetic changes occurred in the capsule locus and were consistent with recombination and horizontal acquisition of a set of genes involved in capsule biosynthesis. CONCLUSIONS: This study showed the added value given by whole genome sequencing by NGS over conventional sequence-based typing methods in the investigation of an outbreak. Routine application of this technology in clinical microbiology will significantly improve methods for molecular epidemiology and surveillance of infectious disease and provide a bulk of data useful to improve our understanding of pathogens biology. BioMed Central 2013-11-19 /pmc/articles/PMC4225559/ /pubmed/24252229 http://dx.doi.org/10.1186/1471-2334-13-554 Text en Copyright © 2013 Lavezzo et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Lavezzo, Enrico Toppo, Stefano Franchin, Elisa Di Camillo, Barbara Finotello, Francesca Falda, Marco Manganelli, Riccardo Palù, Giorgio Barzon, Luisa Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
title | Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
title_full | Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
title_fullStr | Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
title_full_unstemmed | Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
title_short | Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
title_sort | genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4225559/ https://www.ncbi.nlm.nih.gov/pubmed/24252229 http://dx.doi.org/10.1186/1471-2334-13-554 |
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