GSE70257
Identification of a piscine reovirus-related pathogen in Proliferative Darkening Syndrome infected brown trout (Salmo trutta fario) using a next-generation technology detection pipeline
The proliferative darkening syndrome (PDS) is an annually recurring disease that causes species-specific die-off of brown trout (Salmo trutta fario) with a mortality rate of near 100 % in pre-alpine rivers of central Europe. So far the etiology and causation of this disease is still unclear. The objective of this study was to identify the cause of PDS using a next-generation technology detection pipeline. Following the hypothesis that PDS is caused by an infectious agent, brown trout specimens were exposed to water from a heavily affected pre-alpine river with annual occurrence of the disease. Specimens were sampled over the entire time period from potential infection through death. Transcriptomic analysis (microarray) and RT-qPCR of brown trout liver tissue evidenced strong gene expression response of immune-associated genes. Messenger RNA of specimens with synchronous immune expression profiles were ultra-deep sequenced using next-generation sequencing technology (NGS). Bioinformatic processing of generated reads and gap-filling Sanger re-sequencing of the identified pathogen genome revealed strong evidence that a piscine-related reovirus is the causative organism of PDS. The identified pathogen is phylogenetically closely related to the family of piscine reoviruses (PRV) which are considered as the causation of different fish diseases in Atlantic and Pacific salmonid species such as Salmo salar and Onchorhynchus kisutch. This study also highlights that the approach of first screening immune responses along a timeline in order to identify synchronously affected stages in different specimens which subsequently were ultra-deep sequenced is an effective approach in pathogen detection. In particular, the identification of specimens with synchronous molecular immune response patterns combined with NGS sequencing and gap-filling re-sequencing resulted in the successful pathogen detection of PDS. Overall design: Our study design was primarily based on a comparison of brown trout (n=820) exposed to PDS-affected river water and a group exposed to unaffected spring water. The experiment was conducted over a time period of 15 weeks (complete time window from possible first pathogen contact until die-off). Liver tissue from three specimens per group was sampled every day during the whole duration of the experiment and subsequently used for RNA extraction. For pathogen detection and a characterization of the chronology of immune response on mRNA transcriptome level, three different approaches were used: (A) gene expression profiling: Transcriptomic analysis (microarrays) of mRNA from liver tissue was used to monitor the chronology of immune response of individual specimens throughout the whole experiment. This resulted in the identification of immune response candidate genes (IRGs) responding to the infection. RT-qPCRs of IRGs enable sophisticated statistical analysis by using biological and technical replicates to identify specimens with synchronous response pattern; (B) next-generation sequencing and bioinformatics: cDNA from a selection of specimens with synchronous immune response were ultra-deep sequenced on an Illumina HiSeq 2500 next-generation sequencing platform following deep bioinformatics processing. This resulted in identifying the pathogen genetic signal from the comparison between host genome data, the ultra-deep sequencing data of infected specimens and the generated pathogen databases; (C) Sanger re-sequencing and phylogenetic analysis: In order to complete the genetic information of the detected pathogen, primers matching the processed sequence reads were designed for subsequent amplification and Sanger re-sequencing of the gaps in pathogen cDNA. The pathogen was taxonomically and phylogenetically classified by comparing its sequence data with all available pathogen databases. Detailed description of Transcriptomic analysis (microarrays): Sampling at both experimental stations started on May 29, 2008, which was also the day on which the fish were first transferred to their exposure tanks (referred to as 0 day post exposure; d.p.e), and ended on the 5th of September 2008. At the treatment station 3 fish, which showed no external signs of PDS (phenotypically healthy, non-Stage 3 individuals), were sampled each day (always at 2pm), whereas at the control station 3 fish were sampled in 7-day intervals (always at 12 noon). Fish were anaesthetized by a blow to the head and organ tissue of interest (liver, kidney, spleen, gill, muscle, stomach and foregut tissue) were immediately harvested from sacrificed fish, snap-frozen in liquid nitrogen and subsequently stored at -80°C. Livers from the three brown trout that were sampled concurrently from both treatment and control group in 7-day intervals starting 7 d.p.e (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, 84, 91 and 98 d.p.e; n=14) were recruited for the use in the microarray analysis. Microarray analyses were performed using a direct comparison two-channel design in which equimolar amounts of liver sample of one brown trout from both treatment and control group were co-hybridized on the same microarray. For each time point (n=14) microarray co-hybridizations were repeated in triplicate (n=3) and included one dye-swap in order to reduce dye-bias. Thus a total of 42 microarray slides were used in this study (3 biological replicate microarrays x 14 time points = 42 microarrays).