4.6 Article

Resequencing microarray method for molecular diagnosis of human arboviral diseases

Journal

JOURNAL OF CLINICAL VIROLOGY
Volume 56, Issue 3, Pages 238-243

Publisher

ELSEVIER
DOI: 10.1016/j.jcv.2012.10.022

Keywords

Resequencing microarray; Arboviruses; Diagnosis; Human blood samples

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Funding

  1. Institut Pasteur [246]
  2. E.U. [223498]
  3. Fondation Total-Institut Pasteur
  4. Academie Nationale de Medecine
  5. Institut de Veille Sanitaire (InVS
  6. Saint-Maurice, France)

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Background: Resequencing DNA microarray (RMA) technology uses probes designed to identify a panel of viral sequences. It can be used for detecting emerging viruses by revealing the nucleotide polymorphisms within the target of interest. Objectives/study design: As a new tool for molecular diagnosis of arbovirus infection, high density PathogenID v2.0 RMA (PID2-RMA) was assessed for the detection and genetic analysis of dengue, West Nile, and Chikungunya viruses in spiked blood samples or sera from individuals infected with dengue virus. Viral RNAs extracted from biological samples were retrotranscribed into cDNA and amplified using the Phi 29 polymerase-based method. This amplified cDNA was used for hybridization on PID2-RMA. Results: A good specificity of RMA-based detection was demonstrated using a panel of arboviruses including Dengue, West Nile and Chikungunya viruses. This technology was also efficient for the detection and genetic analysis of the different serotypes of dengue virus in sera of infected patients. Furthermore, the mixing of dengue, West Nile and Chikungunya prototype viruses within a single sample of human blood did not interfere with the sensitivity of PID2-RMA. Conclusions: Our data show that high density PID2-RMA was suitable for the identification of medically important arboviruses. It appears to be particularly adapted to the genetic analysis of dengue, West Nile, and Chikungunya viruses in urgent clinical situations where the rapid identification and characterization of the pathogen is essential. (C) 2012 Elsevier B. V. All rights reserved.

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