The serum proteome of Atlantic salmon, Salmo salar, during pancreas disease (PD) following infection with salmonid alphavirus subtype 3 (SAV3)

Salmonid alphavirus is the aetological agent of pancreas disease (PD) in marine Atlantic salmon, Salmo salar, and rainbow trout, Oncorhynchus mykiss, with most outbreaks in Norway caused by SAV subtype 3 (SAV3). This atypical alphavirus is transmitted horizontally causing a significant economic impact on the aquaculture industry. This histopathological and proteomic study, using an established cohabitational experimental model, investigated the correlation between tissue damage during PD and a number of serum proteins associated with these pathologies in Atlantic salmon. The proteins were identified by two-dimensional electrophoresis, trypsin digest and peptide MS/MS fingerprinting. A number of humoral components of immunity which may act as biomarkers of the disease were also identified. For example, creatine kinase, enolase and malate dehydrogenase serum concentrations were shown to correlate with pathology during PD. In contrast, hemopexin, transferrin, and apolipoprotein, amongst others, altered during later stages of the disease and did not correlate with tissue pathologies. This approach has given new insight into not only PD but also fish disease as a whole, by characterisation of the protein response to infection, through pathological processes to tissue recovery. Biological significance: Salmonid alphavirus causes pancreas disease (PD) in Atlantic salmon, Salmo salar, and has a major economic impact on the aquaculture industry. A proteomic investigation of the change to the serum proteome during PD has been made with an established experimental model of the disease. Serum proteins were identified by two-dimensional electrophoresis, trypsin digest and peptide MS/MS fingerprinting with 72 protein spots being shown to alter significantly over the 12 week period of the infection. The concentrations of certain proteins in serum such as creatine kinase, enolase and malate dehydrogenase were shown to correlate with tissue pathology while other proteins such as hemopexin, transferrin, and apolipoprotein, altered in concentration during later stages of the disease and did not correlate with tissue pathologies. The protein response to infection may be used to monitor disease progression and enhance understanding of the pathology of PD

Serum enolase: a non-destructive biomarker of white skeletal myopathy during pancreas disease (PD) in Atlantic salmon Salmo salar L.

Diseases which cause skeletal muscle myopathy are some of the most economically damaging diseases in Atlantic salmon, Salmo salar L., aquaculture. Despite this, there are limited means of assessing fish health non-destructively. Previous investigation of the serum proteome of Atlantic salmon, Salmo salar L., during pancreas disease (PD) has identified proteins in serum that have potential as biomarkers of the disease. Amongst these proteins, the enzyme enolase was selected as the most viable for use as a biomarker of muscle myopathy associated with PD. Western blot and immunoassay (ELISA) validated enolase as a biomarker for PD, whilst immunohistochemistry identified white muscle as the source of enolase. Enolase was shown to be a specific marker for white muscle myopathy in salmon, rising in serum concentration significantly correlating with pathological damage to the tissue

Large-scale prion protein genotyping in Canadian caribou populations and potential impact on chronic wasting disease susceptibility

Polymorphisms within the prion protein gene (Prnp) are an intrinsic factor that can modulate chronic wasting disease (CWD) pathogenesis in cervids. Although wild European reindeer (Rangifer tarandus tarandus) were infected with CWD, as yet there have been no reports of the disease in North American caribou (R. tarandus spp.). Previous Prnp genotyping studies on approximately 200 caribou revealed single nucleotide polymorphisms (SNPs) at codons 2 (V/M), 129 (G/S), 138 (S/N), 146 (N/n) and 169 (V/M). The impact of these polymorphisms on CWD transmission is mostly unknown, except for codon 138. Reindeer carrying at least one allele encoding for asparagine (138NN or 138SN) are less susceptible to clinical CWD upon infection by natural routes, with the majority of prions limited to extraneural tissues. We sequenced the Prnp coding region of two caribou subspecies (n = 986) from British Columb

Solving the sample size problem for resource selection functions

Sample size sufficiency is a critical consideration for estimating resource selection functions (RSFs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals urn:x-wiley:2041210X:media:mee313701:mee313701-math-0001 and as many relocations per animal N as possible. These thresholds render many RSF-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. We provide the first comprehensive solution for RSF sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 3 biologically meaningful quantities: habitat selection strength, variation in individual selection and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores and herbivores living in boreal, temperate and tropical forests, montane woodlands, swamps and Arctic tundra). Our analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results demonstrate that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with much fewer than urn:x-wiley:2041210X:media:mee313701:mee313701-math-0002 animals. We identify several critical steps in implementing these equations, including (a) a priori selection of expected model coefficients and (b) regular sampling of background (pseudoabsence) data within a given definition of availability. We discuss possible methods to identify a priori expectations for habitat selection coefficients, effects of scale on RSF estimation and caveats for rare species applications. We argue that these equations should be a mandatory component for all future RSF studies