- freely available
Live Genomics for Pathogen Monitoring in Public Health
AbstractWhole 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.
- Supplementary File 1:
Supplementary Information (ZIP, 41 KB)
Share & Cite This Article
D'Auria, G.; Schneider, M.V.; Moya, A. Live Genomics for Pathogen Monitoring in Public Health. Pathogens 2014, 3, 93-108.View more citation formats
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.
Notes: Multiple requests from the same IP address are counted as one view.