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Open Access Highly Accessed Research article

Genomic comparative analysis and gene function prediction in infectious diseases: application to the investigation of a meningitis outbreak

Enrico Lavezzo1, Stefano Toppo1, Elisa Franchin12, Barbara Di Camillo3, Francesca Finotello3, Marco Falda1, Riccardo Manganelli12, Giorgio Palù12* and Luisa Barzon12*

Author Affiliations

1 Department of Molecular Medicine, University of Padova, Padova, Italy

2 Regional Reference Laboratory for Infectious Diseases, Microbiology and Virology Unit, Padova University Hospital, Padova, Italy

3 Department of Information Engineering, University of Padova, Padova, Italy

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BMC Infectious Diseases 2013, 13:554  doi:10.1186/1471-2334-13-554

Published: 19 November 2013

Abstract

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.

Keywords:
Neisseria meningitidis; Whole genome sequencing; Next generation sequencing; capsule locus; Comparative genomics; 454 pyrosequencing; Meningitis outbreak; Molecular epidemiology; Gene function prediction