BACKGROUND
The genus Flavivirus includes a variety of medically important viruses, including dengue virus (DENV) and Zika virus (ZIKV), which are most prevalent in Brazil. Because the clinical profile of patients affected by different DENV serotypes or ZIKV may be similar, the development of new methods that facilitate a rapid and accurate diagnosis is crucial.
OBJECTIVES
The current study aimed to develop an improved reverse transcription-polymerase chain reaction (RT-PCR) protocol for universal detection of flaviviruses by using semi-nested primers that discriminate between DENV serotypes and ZIKV.
METHODS
The bioinformatics workflow adopted for primer design included: (1) alignment of 1,442 flavivirus genome sequences, (2) characterisation of 27 conserved regions, (3) generation of a primer set comprising 77 universal primers, and (4) selection of primer pairs with greatest coverage and specificity. Following primer design, the reaction was validated in vitro. The same approach was applied to the design of primers specific for DENV and ZIKV, using a species-specific sequence database.
FINDINGS
The new assay amplified an 800-806 nt variable region of the NS5 gene and allowed discrimination of virtually all flavivirus species using reference-sequence comparison. The 800-806 nt fragment was validated as a template for a semi-nested multiplex PCR using five additional primers for the detection of DENV and ZIKV. These primers were designed to generate amplicons of different sizes, allowing differentiation of the four serotypes of DENV, and ZIKV using agarose gel electrophoresis.
MAIN CONCLUSIONS
The bioinformatics pipeline allowed efficient primer design, making it possible to identify the best targets within the coding region of the NS5 protein. The multiplex system proved effective in differentiation of DENV1-4 and ZIKV on a 2% agarose gel. The possibility of discriminating DENV serotypes and ZIKV in the same reaction provided a faster result consuming less sample. In addition, this simplified approach ensured the reduction of the cost per analysis.
arbovirus; Flaviviridae; West Nile virus; yellow fever virus
