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Pathogens 2014, 3(1), 93-108; doi:10.3390/pathogens3010093
Article

Live Genomics for Pathogen Monitoring in Public Health

1,2,* , 3
 and 1,2,4
Received: 26 September 2013; in revised form: 16 December 2013 / Accepted: 7 January 2014 / Published: 21 January 2014
(This article belongs to the Special Issue Bacterial Pathogenomics: From Technology to Application)
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Abstract: Whole genome analysis based on next generation sequencing (NGS) now represents an affordable framework in public health systems. Robust analytical pipelines of genomic data provides in short laps of time (hours) information about taxonomy, comparative genomics (pan-genome) and single polymorphisms profiles. Pathogenic organisms of interest can be tracked at the genomic level, allowing monitoring at one-time several variables including: epidemiology, pathogenicity, resistance to antibiotics, virulence, persistence factors, mobile elements and adaptation features. Such information can be obtained not only at large spectra, but also at the “local” level, such as in the event of a recurrent or emergency outbreak. This paper reviews the state of the art in infection diagnostics in the context of modern NGS methodologies. We describe how actuation protocols in a public health environment will benefit from a “streaming approach” (pipeline). Such pipeline would NGS data quality assessment, data mining for comparative analysis, searching differential genetic features, such as virulence, resistance persistence factors and mutation profiles (SNPs and InDels) and formatted “comprehensible” results. Such analytical protocols will enable a quick response to the needs of locally circumscribed outbreaks, providing information on the causes of resistance and genetic tracking elements for rapid detection, and monitoring actuations for present and future occurrences.
Keywords: pathogens outbreaks; pan-genome; comparative genomics; bioinformatics; resistance; public health pathogens outbreaks; pan-genome; comparative genomics; bioinformatics; resistance; public health
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

D'Auria, G.; Schneider, M.V.; Moya, A. Live Genomics for Pathogen Monitoring in Public Health. Pathogens 2014, 3, 93-108.

AMA Style

D'Auria G, Schneider MV, Moya A. Live Genomics for Pathogen Monitoring in Public Health. Pathogens. 2014; 3(1):93-108.

Chicago/Turabian Style

D'Auria, Giuseppe; Schneider, Maria V.; Moya, Andrés. 2014. "Live Genomics for Pathogen Monitoring in Public Health." Pathogens 3, no. 1: 93-108.

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