Elena Galletti

Isolation and Genetic Characterization of Betanodavirus from Wild Marine Fish from the Adriatic Sea

Ciulli, S., Galletti, E., Grodzki, M., Alessi, A., Battilani, M. and Prosperi, S., 2007. Isolation and genetic characterization of Betanodavirus from wild marine fish from the Adriatic Sea. Veterinary Research Communications, 31(Suppl. 1), 221–224

Detection and quantification of Betanodavirus by real time PCR

Betanodavirus infection is now widespread in several fish species worldwide and it causes severe economic losses in European sea bass (Dicentrarchus labrax) farming in Italy. Betanodavirus are small ssRNA non-envelope viruses. Based on phylogenetic analysis of the coat protein gene, Betanodavirus can be classified into four genotypes: SJNNV, TPNNV, BFNNV, RGNNV (Nishizawa et al., 1997). The virus is widespread both in farmed and wild animals (Gagné et al., 2004; Gomez et al., 2004) and it has high resistance to environmental and chemico-physical disinfectant treatment, so control by direct prophylaxis is particularly difficult. Furthermore, fattening-farm is often conducted in sea cages or in extensive brackish ponds with no clear-cut separation between wild and farmed fish (Munday et al., 2002). Despite a recent work (Thiéry et al., 2004) reporting the presence of a SJNNV-like virus in a sole farmed in the Mediterranean, the main genotype widespread in this region and responsible for the outbreaks on sea bass farms is the RGNNV. Unfortunately, there is no vaccine available for this disease, due to a limited knowledge about the pathogenesis of Betanodavirus infection, so control is based on early diagnosis and broodstock control. In this study we set up a new Real Time PCR diagnostic method. This technique was found to be rapid, practical and sensitive. Several Real Time PCR methods have recently been set up to detect numerous pathogens significantly contributing to studies on pathogenesis (Gilad et al., 2004), diagnosis and antiviral activity (Yun et al., 2003).

The use of sscp analisys to evidence genetic variability in the gene coding for immunodominant protein e2 of the BVDV

The use of sscp analisys to evidence genetic variability in the gene coding for immunodominant protein e2 of the BVDV S. Ciulli & E. Galletti & F. De Giorgi & M. Battilani & S. Prosperi Published online: 6 August 2008 # Springer Science + Business Media B.V. 2008

Genetic characterisation of coat protein gene of betanodavirus isolates from different fish species.

Betanodavirus infection is responsible for Viral EncephaloRetinophaty (VER) an emerging diseased, which was described for the first time at the end of the 1980’s (Bellance and Gallet de Saint-Aurin, 1988) and is now present in all continents except Africa (Munday et al., 2002). The fast diffusion of the infection is due both to the large host range of the virus and extensive translocation of stock within and between countries. Betanodavirus are RNA viruses whose genome consists of two molecules: RNA1 encoding for the RNA-dependent RNA-polymerase and RNA2 encoding for the coat protein. According to phylogenetic analysis of the coat protein gene, Betanodavirus can be classified into four genotypes: SJNNV, TPNNV, BFNNV, and RGNNV (Nishizawa et al., 1997). The four genotypes show a different biological behaviour both in vivo and in vitro (Iwamoto et al., 1999; Totland et al., 1999). Genetic and environmental factors both take part in modulation of VER, although their role has not yet been clarified (Munday et al., 2002). The purpose of the present work is to compare genetic characteristics of Betanodavirus isolated from different fish species and from different geographical areas, to better understand the way the disease spreads and the correlation between infections in these species and in these countries.

Analysis of variability and antigenic peptide prediction of E2 BVDV glycoprotein in a mucosal-disease affected animal

Analysis of variability and antigenic peptide prediction of E2 BVDV glycoprotein in a mucosal-disease affected animal S. Ciulli & E. Galletti & M. Battilani & V. Galligione & S. Prosperi Published online: 8 July 2009 # Springer Science + Business Media B.V. 2009