Teleost fish scales form distinct growth rings deposited in proportion to somatic growth in length, and are routinely used in fish ageing and growth analyses. Extraction of incremental growth data from scales is labour intensive. We present a fully automated method to retrieve this data from fish scale images using Convolutional Neural Networks (CNNs). Our pipeline of two CNNs automatically detects the centre of the scale and individual growth rings (circuli) along multiple radial transect emanating from the centre. The focus detector was trained on 725 scale images and achieved an average precision of 99%; the circuli detector was trained on 40 678 circuli annotations and achieved an average precision of 95.1%. Circuli detections were made with less confidence in the freshwater zone of the scale image where the growth bands are most narrowly spaced. However, the performance of the circuli detector was similar to that of another human labeller, highlighting the inherent ambiguity of the labelling process. The system predicts the location of scale growth rings rapidly and with high accuracy, enabling the calculation of spacings and thereby growth inferences from salmon scales. The success of our method suggests its potential for expansion to other species.

Fish scale microchemistry can be used to make life-history inferences, although ecological studies examining scale composition are relatively rare. Salmon scales have an external layer of calcium phosphate hydroxyl apatite (HAP). The structure, hardness, and calcium content of this layer have been shown to vary within and between species. This variation may lead to misinterpretation of trace element profiles. This study uses backscatter scanning electron microscopy with electron dispersive spectrometry to compare scales from salmon populations and to present a more detailed analysis of scale HAP than was previously available. Our findings extend the range of salmon populations for which HAP Ca is available and confirm previous findings that the HAP Ca is relatively invariable within this species.

BACKGROUND: Developing an alternative and benign method for DNA extraction is imperative due to the high cost and potential harms associated with conventional techniques. Investigation of Ionic liquid (IL) as a solvent for DNA storage and stability revealed the ability of IL to assist DNA processes. IL-based aqueous biphasic system emerges as a comprehensive extraction platform capitalizing on the task-specificity of ILs and the wide applicability of ABS for biomolecule extractions. Therefore, it is beneficial to optimize an IL-based ABS specifically for DNA extraction, taking into account the fundamental interactions between the IL and DNA.
RESULTS: The primary objective was to design ABS consisting of Ammonium based ILs, and Potassium phosphate buffer as the salting-out agent for the partitioning of salmon sperm DNA. The analysis focused on optimizing biocompatible anions for the extraction. Moreover, the stability of the DNA in the IL rich phases was analysed to validate the method. The proposed process was then employed for extracting plasmid DNA from bacteria, demonstrating results comparable to those obtained with a commercially available kit. Further validation using agarose gel electrophoresis and transformation of the extracted DNA into E.coli were conducted, producing promising outcomes. Although there is room for improvement in terms of recovery of DNA and reusability of ABS, the described approach is comparable with the conventional one while being cost-effective, and showcases a noticeable and convincing link to eco-friendly processes.
CONCLUSIONS: There is limited literature on IL-based ABS for DNA extraction, and the existing studies predominantly concentrate on systems derived from Cholinium ILs. However, their high hydrophilicity limits the choice of the second-phase forming component to polymers for the formation of ABS. Ammonium ILs efficiently form biphasic systems with various available salting-out agents, and biocompatible anions are introduced to mitigate the toxicity of the ILs.

The canonical view of DNA methylation, a pivotal epigenetic regulation mechanism in eukaryotes, dictates its role as a suppressor of gene activity, particularly within promoter regions. However, this view is being challenged as it is becoming increasingly evident that the connection between DNA methylation and gene expression varies depending on the genomic location and is therefore more complex than initially thought. We examined DNA methylation levels in the gut epithelium of Atlantic salmon (Salmo salar) using whole-genome bisulfite sequencing, which we correlated with gene expression data from RNA sequencing of the same gut tissue sample (RNA-seq). Assuming epigenetic signals might be pronounced between distinctive phenotypes, we compared large and small fish, finding 22 significant associations between 22 differentially methylated regions and 21 genes. We did not detect significant methylation differences between large and small fish. However, we observed a consistent signal of methylation levels around the transcription start sites (TSS), being negatively correlated with the expression levels of those genes. We found both negative and positive associations of methylation levels with gene expression further upstream or downstream of the TSS, revealing a more unpredictable pattern. The 21 genes showing significant methylation-expression correlations were involved in biological processes related to salmon health, such as growth and immune responses. Deciphering how DNA methylation affects the expression of such genes holds great potential for future applications. For instance, our results suggest the importance of genomic context in targeting epigenetic modifications to improve the welfare of aquaculture species like Atlantic salmon.

Salmon backbones make up about 10 % of the total fish weight and contain valuable proteins, collagen and lipids that can be used for marine ingredients production. Gelatine is derived from the collagen fraction and this study evaluated how different fractionation and extraction procedures can affect the yield and composition of extracted gelatine. Fractionation by mild thermal treatment of backbones (10 min in 40-42 °C) leads to structural changes of muscle, which improves separation of meat from bones and gives better yield of de-muscled backbone fractionation compared to mechanical meat removal. The highest yield of the gelatine (9.3 ± 0.3g dry gelatine from 100g de-muscled backbone dry material) was obtained from mechanically de-muscled backbones. De-muscled backbones were pre-treated with alkaline (0.04 N NaOH) followed by EDTA and 10 % ethanol for de-calcification and lipid extraction, respectively. Gelatine from pretreated backbones was extracted with 60 °C water. The amount of gelatine amino acids (sum of hydroxyproline, proline and glycine) was 43.4 ± 0.2 % of all amino acids in the gelatine. Extracted backbone gelatines showed film-forming ability. Gelatine films were obtained by casting procedure. Resulted salmon backbone 6 % gelatine and 30 % sorbitol films showed properties (e.g. water vapour permeability, colour difference, transparency value) similar to films obtained with commercial gelatine, indicating the capability of the extracted gelatines for its valorisation as edible coatings or bio-based film layers in packaging.

Lipid oxidation in air-fried seafood poses a risk to human health. However, the effect of a prooxidant environment on lipid oxidation in seafood at different air frying (AF) temperatures remains unknown. An integrated machine learning (ML) - guided REIMS and lipidomics method was applied to explore lipid profiles, lipid oxidation, and lipid metabolic pathways of salmons under different AF temperatures (140, 160, 180, and 200 °C). A significant difference in the lipidomic fingerprinting of air-dried salmon at different temperatures was shown by the main ML methods (neural networks, support vector machines, ensemble learning, and naïve bayes). In total, 773 differential expression metabolites (DEMs) were identified, including glycerophospholipids (GPs), glycerides (GLs), and sphingolipids. A total of 34 DEMs with p values <0.05 and variable importance of projection values >1.0 were analyzed, belonging to linoleic acid metabolism, GL metabolism, and GP metabolism pathways. Correlation network analysis revealed that some characteristic DEMs (phosphatidylcholine, lyso-phosphatidylcholine, triglycerides, fatty acids, and phosphatidylethanolamine) were highly correlated with lipid oxidation. In addition, variations of volatile compounds, color values, texture characteristics, and thiobarbituric acid-reactive substance values were analyzed to corroborate the oxidation characteristics.

Current prophylactic and disease control measures in aquaculture highlight the need of alternative strategies to prevent disease and reduce antibiotic use. Mucus covered mucosal surfaces are the first barriers pathogens encounter. Mucus, which is mainly composed of highly glycosylated mucins, has the potential to contribute to disease prevention if we can strengthen this barrier. Therefore, aim of this study was to develop and characterize fish in vitro mucosal surface models based on commercially available cell lines that are functionally relevant for studies on mucin regulation and host-pathogen interactions. The rainbow trout (Oncorhynchus mykiss) gill epithelial cell line RTgill-W1 and the embryonic cell line from Chinook salmon (Oncorhynchus tshawytscha) CHSE-214 were grown on polycarbonate membrane inserts and chemically treated to differentiate the cells into mucus producing cells. RTGill-W1 and CHSE-214 formed an adherent layer at two weeks post-confluence, which further responded to treatment with the γ-secretase inhibitor DAPT and prolonged culture by increasing the mucin production. Mucins were metabolically labelled with N-azidoacetylgalactosamine 6 h post addition to the in vitro membranes. The level of incorporated label was relatively similar between membranes based on RTgill-W1, while larger interindividual variation was observed among the CHSE in vitro membranes. Furthermore, O-glycomics of RTgill-W1 cell lysates identified three sialylated O-glycans, namely Galβ1-3(NeuAcα2-6)GalNAcol, NeuAcα-Galβ1-3GalNAcol and NeuAcα-Galβ1-3(NeuAcα2-6)GalNAcol, resembling the glycosylation present in rainbow trout gill mucin. These glycans were also present in CHSE-214. Additionally, we demonstrated binding of the fish pathogen A. salmonicida to RTgill-W1 and CHSE-214 cell lysates. Thus, these models have similarities to in vivo mucosal surfaces and can be used to investigate the effect of pathogens and modulatory components on mucin production.

Rahnella aquatilis causes seafoods to spoil by metabolizing sulfur-containing amino acids and/or proteins, producing H2S in products. The type II secretion system (T2SS) regulates the transport of proteases from the cytoplasm to the surrounding environment and promotes bacterial growth at low temperatures. To prevent premature fish spoilage, new solutions for inhibiting the T2SS of bacteria should be researched. In this study, global transcriptome sequencing was used to analyze the spoilage properties of R. aquatilis KM05. Two of the mapped genes/coding sequences (CDSs) were matched to the T2SS, namely, qspF and gspE, and four of the genes/CDSs, namely, ftsH, rseP, ptrA and pepN, were matched to metalloproteases or peptidases in R. aquatilis KM05. Subinhibitory concentrations of citric (18 µM) and acetic (41 µM) acids caused downregulation of T2SS-related genes (range from - 1.0 to -4.5) and genes involved in the proteolytic activities of bacteria (range from - 0.5 to -4.0). The proteolytic activities of R. aquatilis KM05 in vitro were reduced by an average of 40%. The in situ experiments showed the antimicrobial properties of citric and acetic acids against R. aquatilis KM05; the addition of an acidulant to salmon fillets limited microbial growth. Citric and acetic acids extend the shelf life of fish-based products and prevent food waste.

Salmons are crucial to ecosystems and economic activities like commercial fishing and aquaculture, while also serving as an important source of nutrients, underscoring their ecological significance and the need for sustainable management. To better understand the toxicity and biological interactions between the salmon and industrial chemicals in the aquatic environment, we utilized the ToxValDB database to develop first ever computational toxicity models for six salmon subspecies (covering Atlantic and Pacific salmon) across two genera, employing Quantitative Structure-Activity Relationship (QSAR) and quantitative Read-Across Structure-Activity Relationship (q-RASAR) methods. For three smaller datasets (Oncorhynchus nerka, Oncorhynchus keta, and Oncorhynchus gorbuscha), we created mathematical models using the entire datasets where QSAR models demonstrated superior statistical quality compared to q-RASAR. Conversely, the three larger datasets (Oncorhynchus kisutch, Oncorhynchus tshawytscha, and Salmon salar) were divided into training and test sets, the q-RASAR models yielded better results compared to QSAR models. Mechanistic interpretations of these models revealed that descriptors such as Burden eigenvalues (BCUT), autocorrelation of topological structure (ATSC), and molecular polarizability were significant predictors of toxicity. For instance, higher polarizability and certain topological features were associated with increased toxicity as per the developed models. Statistically superior models for each subspecies were used to predict the aquatic toxicity of 1085 untested organic chemicals for toxicity data gap filling and risk assessment considering the applicability domain (AD). These insights are pivotal for designing safer chemicals and emphasize the need for sustainable management of salmon populations.

Side streams from aquaculture production such as fish sludge poses ample opportunities for biological upcycling, as the sludge contains high amounts of nutrients, energy and valuable biochemicals, making it an ideal food for extractive species. Sludge has been proposed as a feed stock for polychaete production, which in turn can be utilized live in shrimp aquaculture or as an aquafeed ingredient. However, the biosafety of such value chains has not yet been addressed. We conducted an experiment exposing the polychaete Hediste diversicolor to aquaculture sludge spiked with four different fish pathogens (Mycobacterium salmoniphilum, Yersinia ruckeri, Infectious Pancreatic Necrosis (IPN) and Infectious Salmon Anaemia (ISA)) known to cause diseases in Atlantic salmon (Salmo salar L.). Moreover, we assessed whether heavy metals and other potentially hazardous elements present in fish sludge bioaccumulates in the polychaetes. Neither of the bacteria nor viruses could be detected in the polychaetes after 14 days of continuous exposure. Seven of the 15 elements we analysed showed bioaccumulation factors significantly below one, meaning biodilution, while the other eight did not differ from one, meaning no bioaccumulation. None of the elements showed a significant bioaccumulation. Further on, none of the heavy metals found in the polychaetes at the end of our experiment exceeded the EU regulatory maximum levels for fish feed ingredients. The current results suggest that a H. diversicolor can reared on aquaculture sludge, and aquaculture sludge may serve as feed stock for polychaete production without the product exceeding EU regulations for contaminants in animal feed.