How pathogens affect the marine habitat use and migration of sea trout (Salmo trutta) in two Norwegian fjord systems

Developing molecular classifiers to detect environmental stressors, smolt stages and morbidity in coho salmon, Oncorhynchus kisutch

Aquatic species are increasingly confronted with environmental stressors because of climate change. Although molecular technologies have advanced our understanding of how organisms respond to stressors in laboratory settings, the ability to detect physiological responses to specific stressors under complex field conditions remains underdeveloped. This research applied multi-stressor challenge trials on coho salmon, employing the "Salmon Fit-Chips" genomic tool and a random forest-based classification model to develop classifiers predictive for chronic thermal and hypoxic stress, as well as salinity acclimation, smolt stage and morbidity status. The study also examined how smolts and de-smolts (smolts not having entered SW during the smolt window) responded transcriptionally to exposure to saltwater. Using RF classifiers optimized with 4 to 12 biomarkers, we identified transcriptional signatures that accurately predicted the presence of each stressor and physiological state, achieving prediction accuracy rates between 86.8 % and 100 %, regardless of other background stressors present. Stressor recovery time was established by placing fish back into non-stressor conditions after stress exposure, providing important context to stressor detections in field applications. Recovery from thermal and hypoxic stress requires about 3 and 2 days, respectively, with >3 days needed for re-acclimation to freshwater for seawater acclimated fish. The study also found non-additive (synergistic) effects of multiple stressors on mortality risk. Importantly, osmotic stress associated with de-smolts was the most important predictor of mortality. In saltwater, de-smolts exposed to salinity, high temperature, and hypoxia experienced a 9-fold increase in mortality compared to those only exposed to saltwater, suggesting a synergistic response to multiple stressors. These findings suggest that delays in hatchery releases to support release of larger fish need to be carefully scrutinized to ensure fish are not being released as de-smolts, which are highly susceptible to additional climate-induced stressors like rising temperatures and reduced dissolved oxygen levels in the marine environment.

A novel high-throughput qPCR chip for solving co-infections in RAS farmed rainbow trout

Recirculating aquaculture systems (RAS) have become more attractive due to reduced water consumption and effluent discharge. However, intensification of production increases the risk of introducing pathogens at farming sites. The emergence of uncultivable pathogens and RAS pathobiome diversity shifts the traditional disease paradigm from "one pathogen, one disease" to complex multiple-pathogen disease cases. Piscine orthoreovirus genotype 3 (PRV-3) is an excellent example, as it is capable of inducing anemia and heart pathology resembling heart and skeletal muscle inflammation under experimental conditions, and is associated with increased mortality in association with other pathogens in the field. The aim of this study was to develop a method for detection of multiple pathogens and putative pathogens, as co-infections are common in aquaculture. To do this, in the pilot study, we mapped the pathobiome of RAS-farmed rainbow trout (Oncorhynchus mykiss) (commercial RAS, farm A) using both standard diagnostic methods and metabarcording (16S rRNA) to investigate the gill microbiome. During this study, we observed infections with multiple pathogens, and detected two putative gill pathogens Candidatus Branchiomonas cysticola and Candidatus Piscichlamydia salmonis, both of which have been linked with complex gill disease in Atlantic salmon (Salmo salar). Based on the pilot study, we developed and tested a high throughput qPCR (HT-qPCR) chip targeting 22 viral and bacterial pathogens and putative pathogens, followed by a surveillance of a fish cohort in a commercial RAS farm during production (farm B). Co-infection with PRV-3 and Ca. B. cysticola combined with stress inducing management practices may explain the severe disease outbreak observed (37% mortality). The time course study sets the base for a future screening scheme for disease prediction and addresses limitations of the method when testing environmental DNA/RNA.

Effects of tag type and surgery on migration of Atlantic salmon (Salmo salar) smolts

Tagging salmon smolts to provide information about the timing of outmigration has been a common approach to monitor phenology and model the risk of encountering stressors. However, the validity of tagging has come under scrutiny because of the sensitivity of this parameter in various management systems. We studied the probability of migration, timing of migration and growth during migration for Atlantic salmon smolts tagged with three different tags in the River Dale, western Norway. Two groups were tagged with passive integrated transponder (PIT) tags via a small ventral nonsurgical incision, either a 12 mm or a new 16 mm PIT tag. Two groups were subjected to surgical implantation of either a dummy acoustic transmitter or a 12 mm PIT tag (a sham surgery). Overall, 71% of the tagged smolts were recaptured at the downstream Wolf trap. Smolts from the sham tagged group were recaptured most frequently (78%) compared to dummy acoustic transmitters and 16 mm PIT tags (both 68%), but the differences were not significant. Results agree with prior assessments that longer smolts migrated earlier, with about half a day earlier migration for each millimetre total length of the smolt, but did not suggest any difference in time of migration among the tag types. Growth in length was evident from release to recapture, with smaller smolts exhibiting greater growth and no effect of tagging treatment. Our findings suggest that inferences about the timing of outmigration for salmon smolts based on acoustic tagging should be made cautiously because of the relationship among tag size, suitable fish size and the timing of a tagged individual's migration.

Transcriptome Responses of Atlantic Salmon (Salmo salar L.) to Viral and Bacterial Pathogens, Inflammation, and Stress

Transcriptomics provides valuable data for functional annotations of genes, the discovery of biomarkers, and quantitative assessment of responses to challenges. Meta-analysis of Nofima’s Atlantic salmon microarray database was performed for the selection of genes that have shown strong and reproducible expression changes. Using data from 127 experiments including 6440 microarrays, four transcription modules (TM) were identified with a total of 902 annotated genes: 161 virus responsive genes – VRG (activated with five viruses and poly I:C), genes that responded to three pathogenic bacteria (523 up and 33 down-regulated genes), inflammation not caused by infections – wounds, melanized foci in skeletal muscle and exposure to PAMP (180 up and 72 down-regulated genes), and stress by exercise, crowding and cortisol implants (33 genes). To assist the selection of gene markers, genes in each TM were ranked according to the scale of expression changes. In terms of functional annotations, association with diseases and stress was unknown or not reflected in public databases for a large part of genes, including several genes with the highest ranks. A set of multifunctional genes was discovered. Cholesterol 25-hydroxylase was present in all TM and 22 genes, including most differentially expressed matrix metalloproteinases 9 and 13 were assigned to three TMs. The meta-analysis has improved understanding of the defense strategies in Atlantic salmon. VRG have demonstrated equal or similar responses to RNA (SAV, IPNV, PRV, and ISAV), and DNA (gill pox) viruses, injection of bacterial DNA (plasmid) and exposure of cells to PAMP (CpG and gardiquimod) and relatively low sensitivity to inflammation and bacteria. Genes of the highest rank show preferential expression in erythrocytes. This group includes multigene families (gig and several trim families) and many paralogs. Of pathogen recognition receptors, only RNA helicases have shown strong expression changes. Most VRG (82%) are effectors with a preponderance of ubiquitin-related genes, GTPases, and genes of nucleotide metabolism. Many VRG have unknown roles. The identification of TMs makes possible quantification of responses and assessment of their interactions. Based on this, we are able to separate pathogen-specific responses from general inflammation and stress.

The use of non-lethal sampling for transcriptomics to assess the physiological status of wild fishes

Fishes respond to different abiotic and biotic stressors through changes in gene expression as a part of an integrated physiological response. Transcriptomics approaches have been used to quantify gene expression patterns as a reductionist approach to understand responses to environmental stressors in animal physiology and have become more commonly used to study wild fishes. We argue that non-lethal sampling for transcriptomics should become the norm for assessing the physiological status of wild fishes, especially when there are conservation implications. Processes at the level of the transcriptome provide a "snapshot" of the cellular conditions at a given time; however, by using a non-lethal sampling protocol, researchers can connect the transcriptome profile with fitness-relevant ecological endpoints such as reproduction, movement patterns and survival. Furthermore, telemetry is a widely used approach in fisheries to understand movement patterns in the wild, and when combined with transcriptional profiling, provides arguably the most powerful use of non-lethal sampling for transcriptomics in wild fishes. In this review, we discuss the different tissues that can be successfully incorporated into non-lethal sampling strategies, which is particularly useful in the context of the emerging field of conservation transcriptomics. We briefly describe different methods for transcriptional profiling in fishes from high-throughput qPCR to whole transcriptome approaches. Further, we discuss strategies and the limitations of using transcriptomics for non-lethally studying fishes. Lastly, as 'omics' technology continues to advance, transcriptomics paired with different omics approaches to study wild fishes will provide insight into the factors that regulate phenotypic variation and the physiological responses to changing environmental conditions in the future.