Detection and quantification of infectious hematopoietic necrosis virus in rainbow trout (Oncorhynchus mykiss) by SYBR Green real-time reverse transcriptase-polymerase chain reaction.

A real-time reverse transcriptase-polymerase chain reaction assay using the fluorogenic dye SYBR Green I was developed for the detection and quantification of infectious hematopoietic necrosis virus (IHNV) infecting rainbow trout (Oncorhynchus mykiss). Using primers designed for the IHNV nucleocapsid (N) and surface glycoprotein (G) genes, virus was detected in liver, kidney, spleen, adipose tissue, and pectoral fin samples from fish challenged in the laboratory via either injection or immersion and in fish collected from the field. The N- and G-gene amplicons provided melting curves with a single peak at 85.5 and 86.5 degrees C, respectively. Among different tissues tested, overall the N-gene was expressed in greater abundance than the G-gene in both laboratory-challenged and field samples. Kidney, liver, and spleen tissues had higher copies of the N- and G-genes compared to adipose tissue and pectoral fin. In samples from IHNV immersion challenge fish, the virus could be detected in the pectoral fin as early as 1 day post-challenge, and the viral load appears to decline by 6 days post-challenge. To evaluate the usefulness of non-invasive tissue sampling for IHNV detection, pectoral fin samples were collected from fish that were either apparently healthy or showing clinical signs of IHNV infection from commercial operations. Among the apparently healthy fish, using SYBR Green real-time RT-PCR the N-gene was detected in 2 out of 24 (8.3%), while the G-gene was detected in 8 of 24 (33%) fish. Among the fish showing clinical signs of IHNV infection, the N-gene was detected in 15 out of 36 (42%), while the G-gene was detected in 24 of 36 (67%) fish tested. Using a viral plaque assay, virus was detected in 4 of 24 (17%) apparently healthy fish and 33 of 36 (92%) fish showing clinical sign of IHNV infection. The higher level of IHNV detection by plaque assay compared to real-time RT-PCR might be due to the presence of more than one isolate in the field samples, and the inability to detect all the IHNV isolates using the current set of primers used in real-time RT-PCR. In conclusion, we developed a real-time RT-PCR assay for the detection and quantification of IHNV by SYBR Green real-time RT-PCR. This study demonstrates the potential of using fin clip as a non-invasive tissue source for detecting IHNV and possibly other viruses infecting salmonids in commercial aquaculture and in the field.

Validation of reference genes for quantitative measurement of immune gene expression in shrimp.

To accurately measure the relative expression of a target gene, mRNA expression data is routinely normalized with reference to an internal control gene. We examined the transcriptional stability of four internal control genes, beta-actin, glyceraldehyde-3 phosphate dehydrogenase (GAPDH), elongation factor1-alpha (EF1-alpha), and 18S ribosomal RNA (18S rRNA) while measuring the mRNA expression of a gene encoding a pattern recognition protein, lipopolysaccharide and glucan binding protein (LGBP) gene, in healthy and white spot syndrome virus (WSSV) infected shrimp (Penaeus stylirostris) before and after (4, 8, 16 and 32 h) challenge using real-time RT-PCR. Here, we describe a method to rank the internal control genes based on a linear regression analysis. This analysis enables us to analyze the multivariate data set, e.g. time course study samples with control and treatment groups. Using the linear regression analysis and the WSSV-challenged time course samples, GAPDH was found to be the most stable internal control gene followed by the genes EF1-alpha, 18S rRNA and beta-actin. Using the program geNorm, GAPDH was also found to be the most stable gene followed by the genes EF1-alpha, beta-actin and 18S rRNA. Using the program NormFinder, the ranking of the internal control genes were in the order of EF1-alpha>GAPDH>18S rRNA>beta-actin. The ability to compare the healthy and WSSV infected samples in parallel by the regression analysis makes this method a very useful approach while identifying the optimal reference gene for gene expression analysis.