NMR-based metabonomics reveals relationship between pre-slaughter exercise stress, the plasma metabolite profile at time of slaughter, and water-holding capacity in pigs

Effects of recovery from short-term heat stress exposure on feed intake, plasma amino acid profiles, and metabolites in growing pigs

Heat stress (HS) damages health and decreases performance variables in pigs, and if severe enough, causes mortality. However, metabolic changes under HS and recovery following HS are poorly understood. Therefore, this study was aimed to expose the essential mechanisms by which growing pigs respond to HS and the temporal pattern of plasma concentrations (PC) of amino acids (AAs) and metabolites. Crossbred male growing pigs were penned separately and allowed to adapt to thermal-neutral (TN) conditions (20°C and 80% relative humidity; TN[-1D]). On the first day, all pigs were exposed to HS for 24 h (36°C and 60% relative humidity), then to TN conditions for 5 days (TN[2D] to TN[5D]). All pigs had ad libitum access to water and 3 kg feed twice daily. Rectal temperature (RT) and feed intake (FI) were determined daily. HS pigs had higher RT (40.72°C) and lower (50%) FI than TN(-1D) pigs (p < 0.01). The PC of indispensable (threonine, valine, and methionine) and dispensable (cysteine and tyrosine) AAs were higher (p < 0.05) in HS than TN(-1D) pigs and remained increased during recovery time. Nonprotein α-aminobutyric acid and β-alanine concentrations were higher (p < 0.05) in HS than TN(-1D) pigs. The metabolite concentration of creatinine was higher (p < 0.01) under HS treatment than other treatments, but that of alanine and leucine remained increased (p < 0.05) through 5 d of recovery. In summary, some major differences were found in plasma AA profiles and metabolites between HS- and TN-condition pigs. This indicates that the HS pigs were forced to alter their metabolism, and these results provide information about mechanisms of acute HS responses relative to the recovery time.

Effect of myoglobin, hemin, and ferric iron on quality of chicken breast meat

OBJECTIVE

The objective was to evaluate the impact of different forms of iron including myoglobin, hemin, and ferric chloride on the quality of chicken breast meat.

METHODS

Chicken breast muscles were subjected to 1, 2, 3 mg/mL of FeCl3, myoglobin and hemin treatment respectively, and the production of reactive oxygen species (ROS) and malondialdehyde, meat color, tenderness, water holding capacity and morphology of meat was evaluated.

RESULTS

Hemin was found to produce more ROS and induce greater extent of lipid oxidation than myoglobin and ferric chloride. However, it showed that hemin could significantly increase the redness and decrease the lightness of the muscle. Hemin was also shown to be prominent in improving water holding capacity of meat, maintaining a relatively higher level of the immobilized water from low-field nuclear magnetic resonance measurements. Morphology observation by hematoxylin-eosin staining further confirmed the results that hemin preserved the integrity of the muscle.

CONCLUSION

The results indicated that hemin may have economic benefit for the industry based on its advantage in improving water holding capacity and quality of meat.

The application of 1H NMR to explore the taste difference caused by taste-active metabolites of different Chinese sauce-stewed beef

In this study, we developed a method for the quantification of taste-active metabolites of Chinese commercial sauce-stewed beef by using 1H NMR spectroscopy coupled with multivariate data analysis. This method was applied to analyze the taste difference which caused by taste-active metabolites of different Chinese sauce-stewed beef. Beef samples demonstrated to consist of 25 metabolites, including amino acids, sugars, organic acids, nucleic aides, and their derivatives. PC1 and PC2 explained a total of 85.1 and 13.1% of variables, respectively. Metabolites such as isoleucine, histidine, glutamate, pyroglutamate, sucrose, lactate, creatine, carnitine, and creatinine were kept at a higher levels compared with other metabolites in the four products. Sensory evaluation was also done to help analyze the taste difference. This microcosmic approach of using high-resolution NMR spectrometry to analyze beef products has rarely been reported. This work established a feasible method to distinguish the taste difference of different Chinese sauce-stewed beef.

Integrative Analysis of Metabolomic and Transcriptomic Profiles Uncovers Biological Pathways of Feed Efficiency in Pigs

Feed efficiency (FE) is an economically important trait. Thus, reliable predictors would help to reduce the production cost and provide sustainability to the pig industry. We carried out metabolome-transcriptome integration analysis on 40 purebred Duroc and Landrace uncastrated male pigs to identify potential gene-metabolite interactions and explore the molecular mechanisms underlying FE. To this end, we applied untargeted metabolomics and RNA-seq approaches to the same animals. After data quality control, we used a linear model approach to integrate the data and find significant differently correlated gene-metabolite pairs separately for the breeds (Duroc and Landrace) and FE groups (low and high FE) followed by a pathway over-representation analysis. We identified 21 and 12 significant gene-metabolite pairs for each group. The valine-leucine-isoleucine biosynthesis/degradation and arginine-proline metabolism pathways were associated with unique metabolites. The unique genes obtained from significant metabolite-gene pairs were associated with sphingolipid catabolism, multicellular organismal process, cGMP, and purine metabolic processes. While some of the genes and metabolites identified were known for their association with FE, others are novel and provide new avenues for further research. Further validation of genes, metabolites, and gene-metabolite interactions in larger cohorts will elucidate the regulatory mechanisms and pathways underlying FE.

1H NMR and multivariate data analysis of the differences of metabolites in five types of dry-cured hams

In order to distinguish the taste styles of dry-cured hams (Jinhua, Xuanwei, Country, Parma and Bama), we established a ¹H nuclear magnetic resonance spectroscopy method to identify metabolites. Totally, 33 charged metabolites, including amino acids, organic acids, nucleic acids and their derivatives, sugars, alkaloids and others were identified. The abundant glutamate, lysine, alanine, leucine and lactate could be the major contributors of taste. Total variables were explained by PC1 (67.7%) and PC2 (16.0%) which showed that Parma and Xuanwei styles were close to each other (similar amino acids, peptide, organic acids and alkaloids contents). Bama style showed the highest PC1 and amino acids, organic acids and alkaloids contents. Country style was located on the left-most area of PC1 (the lowest amino acids, organic acids and peptide, but the highest sugars contents). Sensory evaluation revealed that Bama ham had the highest overall taste score, followed by Jinhua, Parma, Xuanwei and American Country ham. We concluded that the proportions and combinations of taste components explained the specific taste instead of any single component. These findings provided a better understanding of different metabolomics among hams.

Metabolite Profile Differences between Beef Longissimus and Psoas Muscles during Display

The objective of this research was to compare metabolite profiles between beef longissimus and psoas muscles during display. Beef short loins were collected 3 d postmortem (n = 10). Steaks were cut from each longissimus lumborum (LL) and psoas major (PM) muscle and displayed under retail conditions for 7 d. Surface color, biochemical properties, and metabolites were analyzed during storage. PM decreased in redness (P < 0.05) by d 3 of display compared with LL. There were differences in metabolite concentrations (P < 0.05) between each muscle type at each time point. Sugars, amino acids, tricarboxylic acid cycle intermediates, and glycolytic substrates were detected in both muscles. Glycolytic metabolites such as pyruvic acid, glucose–6–phosphate, and fructose were greater (P < 0.05) in LL than PM at all display times. On d 0, the intensity of pyruvic acid in LL and PM were 142 and 42, respectively. Citric acid and succinic acid were lower on d 0, but were greater (P < 0.05) in LL compared with PM by d 7 of display. Carnitine was lower (P < 0.05) in LL than PM at all display times. On d 7, carnitine level in LL was 4.1 while in PM was 13,500. The results suggest that in addition to muscle-specific differences in mitochondrial and enzyme activities, inherent metabolite differences also may contribute to muscle color stability.

Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein "phosphoglycerate mutase 2" and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.

Different Statistical Approaches to Investigate Porcine Muscle Metabolome Profiles to Highlight New Biomarkers for Pork Quality Assessment

The aim of this study was to elucidate the underlying biochemical processes to identify potential key molecules of meat quality traits drip loss, pH of meat 1 h post-mortem (pH1), pH in meat 24 h post-mortem (pH24) and meat color. An untargeted metabolomics approach detected the profiles of 393 annotated and 1,600 unknown metabolites in 97 Duroc × Pietrain pigs. Despite obvious differences regarding the statistical approaches, the four applied methods, namely correlation analysis, principal component analysis, weighted network analysis (WNA) and random forest regression (RFR), revealed mainly concordant results. Our findings lead to the conclusion that meat quality traits pH1, pH24 and color are strongly influenced by processes of post-mortem energy metabolism like glycolysis and pentose phosphate pathway, whereas drip loss is significantly associated with metabolites of lipid metabolism. In case of drip loss, RFR was the most suitable method to identify reliable biomarkers and to predict the phenotype based on metabolites. On the other hand, WNA provides the best parameters to investigate the metabolite interactions and to clarify the complex molecular background of meat quality traits. In summary, it was possible to attain findings on the interaction of meat quality traits and their underlying biochemical processes. The detected key metabolites might be better indicators of meat quality especially of drip loss than the measured phenotype itself and potentially might be used as bio indicators.

An NMR-based metabolomics study of pork from different crossbreeds and relation to sensory perception

Meat extracts from five different pig crossbreeds including Duroc/Landrace/Yorkshire (DLY), Iberian/Duroc (ID), Iberian/Duroc/Landrace (ILY), Mangalitza/Duroc (MD), and Mangalitza/Landrace/Yorkshire (MLY) were analysed by nuclear magnetic resonance (NMR)-based metabolomics. The results were compared with technological traits and sensory analyses in order to elucidate the potential of NMR-based metabolomics to highlight meat metabolites of importance for technological and sensory attributes of meat. Amino acids including alanine, carnosine, isoleucine, methionine, phenylalanine, and valine, as well as lactate, inosine monophosphate (IMP), inosine, glycerol and choline-containing compounds were found to be significantly affected by crossbreed. The breed-specific differences in the metabolome were ascribed to differences in ante mortem metabolism, differences in the membrane properties and glycolytic potential of muscle fibres and differences in lipolysis and proteolysis. A high content of carnosine in the meat was associated with a low value of many sensory attributes related to meat flavor/taste, while IMP and inosine were in general not correlated with sensory attributes related to meat flavor/taste.

Phenotypic prediction based on metabolomic data for growing pigs from three main European breeds

Predicting phenotypes is a statistical and biotechnical challenge, both in medicine (predicting an illness) and animal breeding (predicting the carcass economical value on a young living animal). High-throughput fine phenotyping is possible using metabolomics, which describes the global metabolic status of an individual, and is the closest to the terminal phenotype. The purpose of this work was to quantify the prediction power of metabolomic profiles for commonly used production phenotypes from a single blood sample from growing pigs. Several statistical approaches were investigated and compared on the basis of cross validation: raw data vs. signal preprocessing (wavelet transformation), with a single-feature selection method. The best results in terms of prediction accuracy were obtained when data were preprocessed using wavelet transformations on the Daubechies basis. The phenotypes related to meat quality were not well predicted because the blood sample was taken some time before slaughter, and slaughter is known to have a strong influence on these traits. By contrast, phenotypes of potential economic interest (e.g., lean meat percentage and ADFI) were well predicted (R(2) = 0.7; P < 0.0001) using metabolomic data.

HRMAS-NMR spectroscopy and multivariate analysis meat characterisation

¹H-High resolution magic angle spinning-nuclear magnetic resonance spectroscopy was employed to gain the metabolic profile of longissimus dorsi and semitendinosus muscles of four different breeds: Chianina, Holstein Friesian, Maremmana and Buffalo. Principal component analysis, partial least squares projection to latent structure - discriminant analysis and orthogonal partial least squares projection to latent structure - discriminant analysis were used to build models capable of discriminating the muscle type according to the breed. Data analysis led to an excellent classification for Buffalo and Chianina, while for Holstein Friesian the separation was lower. In the case of Maremmana the use of intelligent bucketing was necessary due to some resonances shifting allowed improvement of the discrimination ability. Finally, by using the Variable Importance in Projection values the metabolites relevant for the classification were identified.

Assessment of meat quality by NMR--an investigation of pork products originating from different breeds

In the present study, meat obtained from uncommon and novel pig crossings between the rare Iberian and Mangalitza pigs and the more frequent Duroc and Landrace/Yorkshire pigs was characterized by time-domain proton NMR relaxometry and high-resolution proton NMR spectroscopy to elucidate the potential of NMR to assess the meat quality of new-introduced pig breeds. Multivariate data analysis of proton NMR T(2) relaxation curves obtained on fresh meat samples revealed differences in the T(2) relaxation pattern of the different breeds included in the study. Comparison of NMR T(2) relaxation data with gravimetric determination of water-holding capacity (WHC) indicated that this should be ascribed to differences in the WHC of the different meats, and that NMR T(2) relaxation in accordance with previous studies provides unique information about WHC, which may be ascribed to the fact that NMR T(2) relaxation reflects information about intrinsic meat structure. High-resolution proton NMR spectroscopy of freeze exudate and meat extracts also revealed differences in the metabolite profile of the meat between the different breeds studied. The effects of breed on the amount of lactate in the freeze exudate were observed, which could be linked to WHC of the meat. In conclusion, the different NMR techniques applied could provide complementary information about biophysical and biochemical factors of importance for meat quality assessment.

Oxidative stress-induced metabolic changes in mouse C2C12 myotubes studied with high-resolution 13C, 1H, and 31P NMR spectroscopy

In this study, stress in relation to slaughter was investigated in a model system by the use of (13)C, (1)H, and (31)P nuclear magnetic resonance (NMR) spectroscopy for elucidating changes in the metabolites in C2C12 myotubes exposed to H(2)O(2)-induced stress. Oxidative stress resulted in lower levels of several metabolites, mainly amino acids; however, higher levels of alanine were apparent in the (13)C spectra after incubation with [(13)C(1)]glucose. In the (13)C spectra [(13)C(3)]lactate tended to increase after exposure to increasing concentrations of H(2)O(2); conversely, a tendency to lower levels of the unlabeled ((12)C) lactate were identified in the (1)H spectra after stress exposure. These data indicate an increase in de novo synthesis of alanine, concomitant with a release of lactate from the myotubes to the medium at oxidative stress conditions. The changes in the metabolite levels could possibly be useful as markers for meat quality traits.