ABSTRACT. A matched case-control study of infectious salmon anaemia (ISA) risk factors in Norwegian salmonid sea sites was performed in 1993. The distribution of potential exposure factors associated with the site management and location was compared in 2 paired groups of sea sites, one group comprising 37 ISA-positive sites and the other 37 1SA-negative sites. The risk of ISA was found to be significantly associated with the location of the site. Location within 5 km from a salmonid slaughterhouse gave an ISA odds ratio of 13.0 compared to location further away. The risk of infection increased by 8.0 if the site was situated closer than 5 km to another ISA-positive site as compared to the risk when the site was more than 5 km away. Disinfecting the waste water from the slaughtering and processing plants seemed to prevent transmission of ISA. The density of fish markets for sea-caught fish was higher in the vicinity of cases than of controls. The risk of ISA was associated with the number of hatcheries delivering smolt to the sea sites, and the risk increased if the hatcheries were located outside the site's home county. The overall results from the present study indlcate that 1SA is mainly transmitted from infected salmonid sources to clean sites through sea water Further disease control measures should concentrate on minimising the risk of transmission through sea water by shortening the time period between the diagnosis of ISA and the elimination of posltive sites, and should work towards the establishment of 5 km as a minimum distance between sea sites In addition, decontamination systenls must be systematically introduced into the fish processing industry. The implementation of good sanitary practices by fish farmers may also reduce the nsk of ISA.KEY WORDS: Epidemiology Disease -Risk factors . Infectious salmon anaemia INTRODUCTIONThe first case of infectious salmon anaemia (ISA) was diagnosed in Atlantic salmon parr Salmo salar L. in a hatchery on the west coast of Norway in 1984(Thorud 1991. In this outbreak, which lasted for several months, fish mortality in the hatchery reached approximately 80%. The affected parr were kept in smolt tanks where the fresh water was mixed with raw sea water, but afterwards no naturally occurring cases were registered in fry or smolt prior to seawater transfer until 1995. The most serious problems associated with the diagnosis of ISA in the farmed population of Atlantic salmon were registered in sea farms. The mortality associated with ISA in sea farms varies considerably from insignificant to moderate.In 1995 the causal virus of ISA was isolated from cultured cells in the laboratory (Dannevig et al. 1995). Prior to this confirmation of the viral aetiology, the results from several studies indicated that the disease was transmissible (Thorud 1991, Dannevig et al. 1994, Vagsholm et al. 1994). The virus is not yet fully classified, although it seems to be an orthomyxo-like RNAvirus (S. Mjaaland pers, comm.).Since the first appearance of ISA in 1984, the disease has been co...

We suggest that a single HPR-deleted genotype of ISAV has spread between salmon farms in the North-cluster. Furthermore, we find that HPR0/F (Q(266)) genotypes are frequently present in farmed populations of Atlantic salmon. From this, we anticipate a population dynamics of ISAV portrayed by low virulent genotypes occasionally transitioning into virulent genotypes, causing solitary outbreaks or local epidemics through local transmission.

BackgroundConstraint-based modeling is a widely used and powerful methodology to assess the metabolic phenotypes and capabilities of an organism. The starting point and cornerstone of all such modeling is a genome-scale metabolic network reconstruction. The creation, further development, and application of such networks is a growing field of research thanks to a plethora of readily accessible computational tools. While the majority of studies are focused on single-species analyses, typically of a microbe, the computational study of communities of organisms is gaining attention. Similarly, reconstructions that are unified for a multi-cellular organism have gained in popularity. Consequently, the rapid generation of genome-scale metabolic reconstructed networks is crucial. While multiple web-based or stand-alone tools are available for automated network reconstruction, there is, however, currently no publicly available tool that allows the swift assembly of draft reconstructions of community metabolic networks and consolidated metabolic networks for a specified list of organisms.ResultsHere, we present AutoKEGGRec, an automated tool that creates first draft metabolic network reconstructions of single organisms, community reconstructions based on a list of organisms, and finally a consolidated reconstruction for a list of organisms or strains. AutoKEGGRec is developed in Matlab and works seamlessly with the COBRA Toolbox v3, and it is based on only using the KEGG database as external input. The generated first draft reconstructions are stored in SBML files and consist of all reactions for a KEGG organism ID and corresponding linked genes. This provides a comprehensive starting point for further refinement and curation using the host of COBRA toolbox functions or other preferred tools. Through the data structures created, the tool also facilitates a comparative analysis of metabolic content in any given number of organisms present in the KEGG database.ConclusionAutoKEGGRec provides a first step in a metabolic network reconstruction process, filling a gap for tools creating community and consolidated metabolic networks. Based only on KEGG data as external input, the generated reconstructions consist of data with a directly traceable foundation and pedigree. With AutoKEGGRec, this kind of modeling is made accessible to a wider part of the genome-scale metabolic analysis community.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2472-z) contains supplementary material, which is available to authorized users.

ABSTRACT. The Tana river in northern Norway, the most productive salmon river in Europe, is free of Gyrodactylus salaris. Currently there is one salmon farm in operation on the Tana fjord. Because of the strong association between stocking of rivers with salmon and infestations with G. salaris there is national and international concern that the existing farm might lead to the introduction of the parasite to the Tana river. In response to these concerns a quantitative analysis of the nsk of introduction of G. salaris to the Tana river was undertaken. A scenario tree, the Monte Carlo simulation model and results of the sirnulations including sensitimty analyses are presented and discussed. Results show that the probabhty of introduction of G. salaris to the Tana river via transfer of smolt to the existing salmon farm is extremely low primarily due to the low probability that the transferred smolt become infested. The total risk was very sensitive to changes in the s h t y of the water at the sea site.

Genome-scale metabolic modeling is an important tool in the study of metabolism by enhancing the collation of knowledge, interpretation of data, and prediction of metabolic capabilities. A frequent assumption in the use of genome-scale models is that the in vivo organism is evolved for optimal growth, where growth is represented by flux through a biomass objective function (BOF). While the specific composition of the BOF is crucial, its formulation is often inherited from similar organisms due to the experimental challenges associated with its proper determination. A cell’s macro-molecular composition is not fixed and it responds to changes in environmental conditions. As a consequence, initiatives for the high-fidelity determination of cellular biomass composition have been launched. Thus, there is a need for a mathematical and computational framework capable of using multiple measurements of cellular biomass composition in different environments. Here, we propose two different computational approaches for directly addressing this challenge: Biomass Trade-off Weighting (BTW) and Higher-dimensional-plane InterPolation (HIP). In lieu of experimental data on biomass composition-variation in response to changing nutrient environment, we assess the properties of BTW and HIP using three hypothetical, yet biologically plausible, BOFs for the Escherichia coli genome-scale metabolic model iML1515. We find that the BTW and HIP formulations have a significant impact on model performance and phenotypes. Furthermore, the BTW method generates larger growth rates in all environments when compared to HIP. Using acetate secretion and the respiratory quotient as proxies for phenotypic changes, we find marked differences between the methods as HIP generates BOFs more similar to a reference BOF than BTW. We conclude that the presented methods constitute a conceptual step in developing genome-scale metabolic modelling approaches capable of addressing the inherent dependence of cellular biomass composition on nutrient environments.