Integrated proteomic and metabolomic applications in aquatic animal nutrition research

Understanding dietary factors is paramount in the development of feed for aquatic animals. Classic approaches are based on growth trials, investigating growth performance, feed utilization, body composition, and specific biochemical pathways. Proteomics and metabolomics offer potential to expand our understanding of dietary factors on a broader scale. Two growth trials were conducted and proteomic and metabolomic analysis were used to evaluate dietary cholesterol and lecithin supplementation to soybean meal-based diets in juvenile Pacific white shrimp (Litopenaeus vannamei), and dietary methionine deficiency in zebrafish (Danio rerio), respectively. Lack of dietary supplementation of cholesterol, lecithin, or both in soybean meal-based diets had no significant effects on weight gain, feed efficiency, or survival of Pacific white shrimp. Proteomic and metabolomic analysis collectively indicated that only a small subset of metabolic networks, majorly amino acid metabolism, were affected by lack of dietary supplementation of cholesterol, lecithin or both. However, these altered metabolic networks potentially reduced the capability of antioxidant response, osmoregulation, and metamorphosis, which possibly impairs shrimp health in the long term. Another important finding in the first study is that cholesterol biosynthesis possibly existed in Pacific white shrimp as shown by the catabolism of leucine. In the second study, dietary methionine deficiency significantly reduced weight gain and feed efficiency of zebrafish, but had no significant effect on feed intake of zebrafish. Methionine deficiency-induced liver injury was observed. Impaired lipid transportation and oxidative stress were documented by histological, proteomic and metabolomic analysis. Using proteomic and metabolic approaches expands our understanding of dietary inputs, but faces challenges including identification of proteins and metabolites, and extraction of biological information from proteomic and metabolic data