Impacts of seasonal temperatures, ocean warming and marine heatwaves on the nutritional quality of eastern school prawns (Metapenaeus macleayi)

Ocean warming and marine heatwaves significantly alter environmental conditions in marine and estuarine environments. Despite their potential global importance for nutrient security and human health, it is not well understood how thermal impacts could alter the nutritional quality of harvested marine resources. We tested whether short-term experimental exposure to seasonal temperatures, projected ocean-warming temperatures, and marine heatwaves affected the nutritional quality of the eastern school prawn (Metapenaeus macleayi). In addition, we tested whether nutritional quality was affected by the duration of exposure to warm temperatures. We show the nutritional quality of M. macleayi is likely to be resilient to short- (28 d), but not longer-term (56 d) exposure to warming temperatures. The proximate, fatty acid and metabolite compositions of M. macleayi were unchanged after 28 d exposure to simulated ocean warming and marine heatwaves. The ocean-warming scenario did, however, show potential for elevated sulphur, iron and silver levels after 28 d. Decreasing saturation of fatty acids in M. macleayi after 28 d exposure to cooler temperatures indicates homeoviscous adaptation to seasonal changes. We found that 11 % of measured response variables were significantly different between 28 and 56 d when exposed to the same treatment, indicating the duration of exposure time and time of sampling are critical when measuring this species' nutritional response. Further, we found that future acute warming events could reduce harvestable biomass, despite survivors retaining their nutritional quality. Developing a combined knowledge of the variability in seafood nutrient content with shifts in the availability of harvested seafood is crucial for understanding seafood-derived nutrient security in a changing climate.

1H nuclear magnetic resonance-based metabolomics study of serum and pectoralis major for different commercial chicken breeds

This study aimed to characterize the metabolic composition of four types of commercially available chicken breeds [village chicken, colored broiler (Hubbard), broiler (Cobb), and spent layers (Dekalb)] by ¹H NMR coupling and discriminate them using multivariate analysis. Five chickens were collected for each chicken breed based on the marketing age from the respective commercial farms. The orthogonal partial least squares discriminant analysis (OPLS-DA) results showed an obvious separation of local village chickens from the other breeds based on the metabolites present in their serum and meat (pectoralis major). The cumulative values of Q ², R ² X, and R ² Y of the OPLS-DA model for chicken serum were 0.722, 0.877, and 0.841. For the pectoralis major muscle, the cumulative values of Q ², R ² X, and R ² Y of the OPLS-DA model were reported as 0.684, 0.781, and 0.786, respectively. The quality of both OPLS-DA models was accepted by the cumulative values of Q ² ≥ 0.5 and R ² ≥ 0.65. The ¹H NMR result with multivariate analysis has successfully distinguished local village chicken from the other three commercial chicken breeds based on serum and pectoralis major muscle. Nonetheless, colored broiler (Hubbard) was not distinguished from broiler (Cobb) and spent layers (Dekalb) in serum and pectoralis major, respectively. The OPLS-DA assessment in this study identified 19 and 15 potential metabolites for discriminating different chicken breeds in serum and pectoralis major muscle, respectively. Some of the prominent metabolites identified include amino acids (betaine, glycine, glutamine, guanidoacetate, phenylalanine, and valine), nucleotides (IMP and NAD+), organic acids (lactate, malate, and succinate), peptide (anserine), and sugar alcohol (myo-inositol).

Muscle and Serum Metabolomics for Different Chicken Breeds under Commercial Conditions by GC-MS

Globally, village chicken is popular and is known as a premium meat with a higher price. Food fraud can occur by selling other chicken breeds at a premium price in local markets. This study aimed to distinguish local village chicken from other chicken breeds available in the market, namely, colored broiler (Hubbard), broiler (Cobb), and spent laying hen (Dekalb) in pectoralis major and serum under commercial conditions using an untargeted metabolomics approach. Both pectoralis major and serum were analyzed using gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) results distinguished four different chicken breeds into three main groups for pectoralis major and serum. A total of 30 and 40 characteristic metabolites were identified for pectoralis major and serum, respectively. The four chicken breeds were characterized by the abundance of metabolites such as amino acids (L-glutamic acid, L-threonine, L-serine, L-leucine), organic acids (L-lactic acid, succinic acid, 3-hydroxybutyric acid), sugars (D-allose, D-glucose), sugar alcohols (myo-inositol), and fatty acids (linoleic acid). Our results suggest that an untargeted metabolomics approach using GC-MS and PCA could discriminate chicken breeds for pectoralis major and serum under commercial conditions. In this study, village chicken could only be distinguished from colored broiler (Hubbard) by serum samples.

Analysis of Primary Metabolites in Cabbage (Brassica oleracea var. capitata) Varieties Correlated with Antioxidant Activity and Taste Attributes by Metabolic Profiling

Brassica vegetables, such as cabbage, have many health benefits arising from their antioxidant and anticancer properties. These properties are endowed by the metabolite composition of the plant, and it is therefore important to elucidate the metabolic profile and associated activities in this genus. This study objectively evaluated the characteristics of cabbage varieties using metabolic profiling to identify the primary metabolic components that correlate with antioxidant activity and taste attributes. GC-MS analysis was used to identify the primary metabolites. Antioxidant activity was measured by oxygen radical absorbance capacity (ORAC) and 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) scavenging assays, and an electronic tongue was used to quantitate nine taste attributes. Orthogonal projections to latent structures (OPLS) using SIMCA 14 correlated the metabolite components with the taste and antioxidant characteristics. We identified 4-aminobutyric acid, fructose 1-phosphate, adipic acid, 5-oxoproline, N-acetylglycine, O-phosphoethanolamine, and homovanillic acid as important determinants of DPPH scavenging activity and umami, sourness, acidic bitterness, irritant and saltiness, bitterness, astringency, and richness, respectively. These metabolites represent markers indicating breed differences and contribute to differential cabbage functionality. These studies could be extended to measure additional metabolites, as well as to understand the role of growth conditions on the metabolic profile and health benefits of plants.

Changes in Metabolic Profiles of Yellowtail (Seriola quinqueradiata) Muscle during Cold Storage as a Freshness Evaluation Tool Based on GC-MS Metabolomics

We applied metabolomics to the evaluation of yellowtail muscle as a new freshness evaluation method for fish meat. Metabolites from yellowtail ordinary and dark muscle (DM) stored at 0 °C and 5 °C were subjected to metabolomics for primary metabolites based on gas chromatography-mass spectrometry (GC-MS). For the annotated metabolites, we created statistically significant models for storage time prediction for all storage conditions by orthogonal partial least squares analysis, using storage time as the y-variable. DM is difficult to evaluate using the K value method, the predominant existing freshness evaluation method. However, in the proposed method, the metabolic component profiles of DM changed depending on storage time. Important metabolites determined from variables important for prediction (VIP) values included various metabolites, such as amino acids and sugars, in addition to nucleic-acid-related substances, especially inosine and hypoxanthine. Therefore, metabolomics, which comprehensively analyses different molecular species, has potential as a new freshness evaluation method that can objectively evaluate conditions of stored fish meat.

Taste Evaluation of Yellowtail (Seriola Quinqueradiata) Ordinary and Dark Muscle by Metabolic Profiling

We performed metabolic profiling on yellowtail (Seriola quinqueradiata) muscle to develop an objective taste evaluation method for fish meat. Dark (DM) and ordinary (OM) muscle samples before and after storage were subjected to gas chromatography-mass spectrometry (GC-MS) analysis and taste measurements using an electronic tongue. The metabolites identified by the GC-MS analysis were treated as x variables, and the taste values obtained by the electronic tongue were treated as y variables. The relationships between the metabolites and taste attributes were evaluated by two-way orthogonal projections to latent structures (O2PLS) analysis. The O2PLS analyses were normalized in two ways, unit variance (UV) and pareto (Par) scaling. The O2PLS (UV) analysis produced 3+1+0 models in Autofit and this model was statistically significant with R²Y (0.73) and Q² (0.52) metrics. In particular, significant correlations were found between DM or OM and metabolite intensity and taste attributes, and strong associations were found between “sourness” and lysine, “irritant” and alanine and phenylalanine, “saltiness” and pantothenic acid, and “umami” and creatinine and histidine. The O2PLS (Par) analysis of DM generated significant predictive models for “acidic bitterness,” “irritant,” “saltiness,” “bitterness,” “astringency,” and “richness.” Among these, only “irritant” was affected by storage. This method was thus effective in evaluating the taste of yellowtail muscle.

Metabolic Profiling of Fish Meat by GC-MS Analysis, and Correlations with Taste Attributes Obtained Using an Electronic Tongue

To evaluate the taste of ordinary muscle from white-fleshed fish, we used GC-MS metabolomic analysis to characterise the compounds therein, and correlated the obtained data with taste measurements from an electronic tongue. Prediction models using orthogonal partial least squares were produced for different taste attributes, and the primary metabolic components correlated with the taste attributes were identified. Clear differences were observed in the component profiles for different fish species. Using an electronic tongue, differences in tastes were noted among the fish species in terms of sourness, acidic bitterness, umami and saltiness. The obtained correlations allowed the construction of good taste prediction models, especially for sourness, acidic bitterness and saltiness. Compounds such as phosphoric acid, lactic acid and creatinine were found to be highly correlated with some taste attributes. Phosphoric acid in particular showed the highest variable important for prediction (VIP) scores in many of the taste prediction models, and it is therefore a candidate marker to evaluate the tastes of white-fleshed fish.