METABOLOMICS ANALYSIS OF EFFECTS OF COMMERCIAL SOY-BASED PROTEIN PRODUCTS IN RED DRUM Sciaenops ocellatus

Fabio Casu*, Daniel W. Bearden, Aaron Watson, Justin Yost, John W. Leffler, Gibson T. Gaylord, Frederic T. Barrows, Paul A. Sandifer and Michael R. Denson
 
National Institute of Standards and Technology
Hollings Marine Laboratory
Charleston, SC 29412, USA
fabio.casu@noaa.gov
 

Metabolomics is the study of the pool of endogenous metabolites (low molecular weight molecules) that are present within an organism and is affected by environmental factors as well as diet. Nuclear Magnetic Resonance (NMR) is a powerful analytical spectroscopic technique that is widely used for the identification and quantification of macromolecules and small organic molecules and has particular utility in complex mixtures from biological samples.  NMR-based metabolomic analysis can be used to quantify the effect experimental diets have on fish metabolic profiles. We are using this technique to investigate the changes in biochemistry between fish fed diets with alternative protein sources to traditional fish meal-based diets.

In this study we investigated the metabolic response of different commercial soy-based protein products on red drum (Sciaenops ocellatus) using NMR-based metabolomics to evaluate different tissues (muscle, liver and plasma). Specifically, during a 12-week feeding trial, juvenile red drum were fed four different commercially available soy formulations, containing the same amount of protein, in addition to two control diets: a 60% soybean meal diet and a natural fish meal diet. Individual fish were maintained in an indoor recirculating aquaculture system and were sampled at multiple time points. Tissues (muscle and liver) and plasma were sampled and rapidly snap-frozen in liquid nitrogen to stop metabolic changes from occurring and thus provide an accurate snapshot of specific metabolic states at different time points. The collected NMR spectra are complex in nature and typically contain several hundred signals ("features"), the analysis of which can be simplified by adopting pattern recognition techniques. The use of unbiased multivariate analysis, specifically principal component analysis (PCA) allowed us to identify differences and similarities among the treatment groups. Metabolite identification was based on the use of NMR metabolomics databases, leading us to identify some of the metabolites responsible for differences between treatments. NMR-based metabolomics analysis combined with statistical multivariate analysis is a powerful tool that can be successfully applied to aquaculture. We will report on recent findings from this study.