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Review

Advances in viral disease diagnostic and molecular epidemiological technologies

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Pages 367-381 | Published online: 09 Jan 2014
 

Abstract

The early and rapid detection and characterization of specific nucleic acids of medico–veterinary pathogens have proven invaluable for diagnostic purposes. The integration of amplification and signal detection systems, including online real-time devices, have increased speed and sensitivity and greatly facilitated the quantification of target nucleic acids. They have also allowed for sequence characterization using melting or hybridization curves. The newer-generation molecular diagnostic technologies offer, hitherto, unparalleled detection and discrimination methodologies, which are vital for the positive detection and identification of pathogenic agents, as well as the effects of the pathogens on the production of antibodies. The development phase of the novel technologies entails a thorough understanding of accurate diagnosis and discrimination of present and emerging diseases. The development of novel technologies can only be successful if they are transferred and used in the field with a sustainable quality-assured application to allow for the optimal detection and effective control of diseases. The aim of these new tools is to detect the presence of a pathogen agent before the onset of disease. This manuscript focuses mainly on the experiences of two World Organisation for Animal Health collaborating centers in context to molecular diagnosis and molecular epidemiology of transboundary and endemic animal diseases of viral origin, food safety and zoonoses.

Acknowledgements

The authors would like to thank all their colleagues and, in particular, for their critical reading, figures and photographs: Anne-Lie Blomström (SLU, Sweden),; Lihong Liu (SLU),; Mikhayil Hakhverdyan (SVA, Sweden),; Carmelo Volpe (Smiths Detection, UK),; and István Kiss (SVA), critical reading. Thanks also to Cor Schoen (PRI-WUR, Netherlands) for providing the photographs for, as well as technical information on the BioTrove OpenArray system. We also gratefully acknowledge the contribution of our partners and funding agencies in the LAB-ON-SITE project of the EC (SSPECT-2004-513645), EPIZONE Network of Excellence (FP6-2004-Food-3-A-016236), DG Research of the EC, the OIE and SLU “Excellensbidrag”.

Financial & competing interests disclosure

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

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