Selection and identification of Singapore grouper iridovirus vaccine candidate antigens using bioinformatics and DNA vaccination.

In this study, we described a rapid and efficient method which integrated the bioinformatic prediction and DNA vaccine technology to identify vaccine candidates against Singapore grouper iridovirus (SGIV). The 162 previously defined open reading frames (ORFs) of SGIV were subjected to extensive sequence similarity searches, as well as motif, cellular location, and domain prediction. Based on our analysis, 13 genes were chosen and cloned into the eukaryotic expression vector pcDNA 3.1. In vitro and in vivo expression of these DNA vaccine constructs was examined in Epinephelus akaara spleen cells (EAGS) and immunized fish by Western blot and RT-PCR analysis, respectively. Three weeks after the second booster, immunized fish were challenged with SGIV and the level of protection and survival was assessed. Fish vaccinated with plasmid DNA encoding viral ORF072, ORF039 and ORF036 (designated as pcDNA-72, pcDNA-39 and pcDNA-36, respectively) exhibited 66.7%, 66.7% and 58.3% relative percent survival rates, respectively, in comparison with the control fish. These three DNA vaccines induced innate immune responses, raising significantly high level of Mx expression relative to the fish vaccinated with the empty plasmid at 3 days post-vaccination. Furthermore, recombinant protein from ORF072 was also used to immunize another set of fish and similar protective effect was obtained. Taken together, our results validated the applicability of bioinformatics in genome mining, resulting in the identification of three protective antigens. The promising results obtained in the present study have prompted further testing to improve the immunogenicity of these potential DNA vaccines.