Lipids provide the densest form of energy in marine ecosystems. They are also a solvent and absorption carrier for organic contaminants and thus can be drivers of pollutant bioaccumulation. Among the lipids, certain essential fatty acids and sterols are considered to be important determinants of ecosystem health and stability. Fatty acids and sterols are also susceptible to oxidative damage leading to cytotoxicity and a decrease in membrane fluidity. The physical characteristics of biological membranes can be defended from the influence of changing temperature, pressure, or lipid peroxidation by altering the fatty acid and sterol composition of the lipid bilayer. Marine lipids are also a valuable tool to measure inputs, cycling, and loss of materials. Their heterogeneous nature makes them versatile biomarkers that are widely used in marine trophic studies, often with the help of multivariate statistics, to delineate carbon cycling and transfer of materials. Principal components analysis has a strong following as it permits data reduction and an objective interpretation of results, but several more sophisticated multivariate analyses which are more quantitative are emerging too. Integrating stable isotope and lipid data can facilitate the interpretation of both data sets and can provide a quantitative estimate of transfer across trophic levels.

Determining the lipid content and fatty acid (FA) composition of aquatic organisms has been of major interest in trophic ecology, aquaculture, and nutrition for over half a century. Although protocols for lipid analysis are well-described, their application to aquatic sciences often requires modifications to adapt to field conditions and to sample type. Here, we present the current state of knowledge of methods dedicated to both marine and freshwater lipid analyses, from sampling to data treatment. We review: (i) sample preservation, storage and transport protocols, and their effects on lipids, (ii) lipid extraction, separation of polar and neutral lipids, derivatization, and detection methods, and (iii) available tools for the statistical analysis of FA data. We provide recommendations for best practices in field situations and advocate for protocol standardization and interlaboratory calibration.

Dependence on marine natural resources threatens the sustainability of Atlantic salmon aquaculture. In the present study, Atlantic salmon fed for 14 weeks with an experimental diet based on animal by-products and vegetable oil (ABP) exhibited reduced growth performance compared with others fed a fish meal/fish oil based experimental diet (MAR) and a plant protein/vegetable oil-based experimental diet (VEG). To characterize the molecular changes underlying the differences in growth performance, we conducted a 44 K microarray study of the liver transcriptome of the three dietary groups. The microarray experiment identified 122 differentially expressed features (Rank Products, PFP < 10%). Based on their associated Gene Ontology terms, 46 probes were classified as metabolic and growth-relevant genes, 25 as immune-related, and 12 as related to oxidation-reduction processes. The microarray results were validated by qPCR analysis of 29 microarray-identified transcripts. Diets significantly modulated the transcription of genes involved in carbohydrate metabolism (gck and pfkfb4), cell growth and proliferation (sgk2 and htra1), apoptosis (gadd45b), lipid metabolism (fabp3, idi1, sqs), and immunity (igd, mx, ifit5, and mhcI). Hierarchical clustering and linear correlation analyses were performed to find gene expression patterns among the qPCR-analyzed transcripts, and connections between them and muscle and liver lipid composition. Overall, our results indicate that changes in the liver transcriptome and tissue lipid composition were driven by cholesterol synthesis up-regulation by ABP and VEG diets, and the lower carbohydrate intake in the ABP group. Two of the microarray-identified genes (sgk2 and htra1) might be key to explaining glucose metabolism regulation and the dietary-modulation of the immune system in fish. To evaluate the potential of these genes as predictive biomarkers, we subjected the qPCR data to a stepwise discriminant analysis. Three sets of no more than four genes were found to be able to predict, with high accuracy (67–94%), salmon growth and fatty acid composition. This study provides new findings on the impact of terrestrial animal and plant products on the nutrition and health of farmed Atlantic salmon, and a new method based on gene biomarkers for potentially predicting desired phenotypes, which could help formulate superior feeds for the Atlantic salmon aquaculture industry.