Utilizing Pork Exudate Metabolomics to Reveal the Impact of Aging on Meat Quality

A non-destructive predictive model for estimating the freshness/spoilage of packaged chicken meat using changes in drip metabolites

This study investigates the possibility of utilizing drip as a non-destructive method for assessing the freshness and spoilage of chicken meat. The quality parameters [pH, volatile base nitrogen (VBN), and total aerobic bacterial counts (TAB)] of chicken meat were evaluated over a 13-day storage period in vacuum packaging at 4 °C. Simultaneously, the metabolites in the chicken meat and its drip were measured by nuclear magnetic resonance. Correlation (Pearson's and Spearman's rank) and pathway analyses were conducted to select the metabolites for model training. Binary logistic regression (model 1 and model 2) and multiple linear regression models (model 3-1 and model 3-2) were trained using selected metabolites, and their performance was evaluated using receiver operating characteristic (ROC) curves. As a result, the chicken meat was spoiled after 7 days of storage, exceeding 20 mg/100 g VBN and 5.7 log CFU/g TAB. The correlation analysis identified one organic acid, eight free amino acids, and five nucleic acids as highly correlated with chicken meat and its drip during storage. Pathway analysis revealed tyrosine and purine metabolism as metabolic pathways highly correlated with spoilage. Based on these findings, specific metabolites were selected for model training: ATP, glutamine, hypoxanthine, IMP, tyrosine, and tyramine. To predict the freshness and spoilage of chicken meat, model 1, trained using tyramine, ATP, tyrosine, and IMP from chicken meat, achieved a 99.9 % accuracy and had an ROC value of 0.884 when validated using drip metabolites. This model 1 was improved by training with tyramine and IMP from both chicken meat and its drip (model 2), which increased the ROC value for drip metabolites from 0.884 to 0.997. Finally, selected two metabolites (tyramine and IMP) can predict TAB and VBN quantitatively through models 3-1 and 3-2, respectively. Therefore, the model developed using metabolic changes in drip demonstrated the capability to non-destructively predict the freshness and spoilage of chicken meat at 4 °C. To make generic predictions, it is necessary to expand the model's applicability to various conditions, such as different temperatures, and validate its performance across multiple chicken batches.

Dietary supplementation with quercetin: an ideal approach for improving meat quality and oxidative stability of broiler chickens

This study aimed to improve the eating quality of yellow-feathered broiler chicks by feeding them corn-soybean meal diets supplemented with 250, 500, and 1,000 mg/kg quercetin. we examined the impact of varying doses of dietary quercetin on the sensory quality of chicken breast meat as well as on the antioxidant enzymes, antioxidant-related signaling molecules, structure and thermal stability of myofibrillar protein (MPs), and microstructure of myogenic fibers in the meat during 24 h of postslaughter aging. Additionally, we investigated the potential correlations among antioxidant capacity, MP structure, and meat quality parameters. The results indicated that dietary supplementations with 500 and 1,000 mg/kg quercetin improved the physicochemical properties and eating quality of yellow-feathered broiler chicken breast meat during 12 to 24 h postslaughter. Additionally, quercetin improved the postslaughter oxidative stress status and reduced protein and lipid oxidation levels. It also increased hydrogen bonding interactions and α-helix content during 6 to 12 h postslaughter and decreased β-sheet content during 12 to 24 h postslaughter in chicken breast MP. This resulted in improved postslaughter MP structure and thermal stability. The correlation results indicated that the enhancement of antioxidant capacity and MP structure enhanced the physicochemical and edible qualities of yellow-feathered broiler chicken breast meat. In conclusion, the current findings suggest that dietary supplementation with quercetin is an ideal approach for improving the eating quality of chicken meat, thereby broadening our understanding of theoretical and technological applications for improving the quality of chicken.

Effect of wet-aging on meat quality and exudate metabolome changes in different beef muscles

The aim of this study was to evaluate meat quality and changes in the meat exudate metabolome of different beef muscles (5 d postmortem, longissimus lumborum and psoas major muscles) during wet-aging (additional 3, 7, 14, 21, and 28 d of aging). Shear force of meat declined significantly (P < 0.001) with aging, meanwhile, increased myofibril fragmentation index, lipid and protein oxidation with aging were observed (P < 0.01). Psoas major (PM) showed significantly higher (P < 0.05) purge loss, centrifugal loss, and cooking loss, as well as higher tenderness and more severe lipid and protein oxidation (P < 0.01) than longissimus lumborum (LL) during aging. Principal component analysis of the metabolomic profiles revealed distinct clusters according to the period of aging and the type of muscle simultaneously. Overabundant amino acids, peptides, oxidized fatty acids, and hydroxy fatty acids were found in long-term aged meat exudates, and forty metabolites were significantly correlated with meat quality characteristics. Fifty-nine metabolites were significantly affected by muscle type. These results demonstrated the potential possibility of evaluating meat quality using meat exudate metabolomics.

Widely targeted metabolomic analysis reveals the dynamic changes of metabolites during postmortem chilled aging in Mongolian sheep

Postmortem aging is a value-added process for meat. The objective of this study was to evaluate the dynamic changes and metabolic pathways of metabolites in Mongolian sheep during early postmortem chilled aging. Widely targeted metabolomic was used to analyze the metabolites of mutton within five days of chilled aging. A total of 1093 metabolites were identified in Mongolian sheep, covering 16 subclasses. Multivariate statistical analysis showed that 467 metabolites had significant changes during aging, including amino acid and its metabolites, fatty acyl, and glycerophospholipid. In particular, 60 metabolites decreased, while other 407 metabolites increased with aging time. The Kyoto encyclopedia of genes and genomes pathway analysis revealed that protein digestion and absorption, amino acyl-trNA biosynthesis, unsaturated fatty acid biosynthesis, nucleotide metabolism and carbon metabolism were the main enrichment pathways in aging. These findings provide a more comprehensive insight into metabolic profiling and metabolic pathways during chilled aging in mutton.

Proteomic and metabolomic analysis of ageing beef exudate to determine that iron metabolism enhances muscle protein and lipid oxidation

The study aimed to assess differences in proteomic and metabolite profiles in ageing (1, 2, 4, and 6 days at 4 °C) beef exudates and determine their relationship with beef muscle iron metabolism and oxidation. Proteomic and metabolomic analyses identified 877 metabolites and 1957 proteins. The joint analysis identified 24 differential metabolites (DMs) and 56 differentially expressed proteins (DEPs) involved in 15 shared pathways. Ferroptosis was identified as the only iron metabolic pathway, and 4 DMs (l-glutamic acid, arachidonic acid, glutathione and gamma-glutamylcysteine) and 5 DEPs (ferritin, phospholipid hydroperoxide glutathione peroxidase, heme oxygenase 1, major prion protein, and acyl-CoA synthetase long chain family member 4) were involved in iron metabolism by regulating heme and ferritin degradation, Fe2+ and Fe3+ conversion, arachidonic acid oxidation and inactivation of glutathione peroxidase (GPX) 4, leading to increased levels of free iron, ROS, protein and lipid oxidation (P < 0.05). Overall, abnormal iron metabolism during ageing induced oxidative stress in muscle tissue.

Transcriptomic and metabolomic analyses to study the key role by which Ralstonia insidiosa induces Listeria monocytogenes to form suspended aggregates

Ralstonia insidiosa can survive in a wide range of aqueous environments, including food processing areas, and is harmful to humans. It can induce Listeria monocytogenes to form suspended aggregates, resulting from the co-aggregation of two bacteria, which allows for more persistent survival and increases the risk of L. monocytogenes contamination. In our study, different groups of aggregates were analyzed and compared using Illumina RNA sequencing technology. These included R. insidiosa under normal and barren nutrient conditions and in the presence or absence of L. monocytogenes as a way to screen for differentially expressed genes (DEGs) in the process of aggregate formation. In addition, sterile supernatants of R. insidiosa were analyzed under different nutrient conditions using metabolomics to investigate the effect of nutrient-poor conditions on metabolite production by R. insidiosa. We also undertook a combined analysis of transcriptome and metabolome data to further investigate the induction effect of R. insidiosa on L. monocytogenes in a barren environment. The results of the functional annotation analysis on the surface of DEGs and qPCR showed that under nutrient-poor conditions, the acdx, puuE, and acs genes of R. insidiosa were significantly upregulated in biosynthetic processes such as carbon metabolism, metabolic pathways, and biosynthesis of secondary metabolites, with Log2FC reaching 4.39, 3.96, and 3.95 respectively. In contrast, the Log2FC of cydA, cyoB, and rpsJ in oxidative phosphorylation and ribosomal pathways reached 3.74, 3.87, and 4.25, respectively. Thirty-one key components were identified while screening for differential metabolites, which mainly included amino acids and their metabolites, enriched to the pathways of biosynthesis of amino acids, phenylalanine metabolism, and methionine metabolism. Of these, aminomalonic acid and Proximicin B were the special components of R. insidiosa that were metabolized under nutrient-poor conditions.

Using untargeted metabolomics and volatile aroma compounds to predict expert sensory descriptors and consumer liking of beef loin steaks varying in quality grade, aging time, and degree of doneness

Precursors to flavor are important to its development, yet little is known about the intrinsic products of metabolism that influence flavor. Our objective was to use untargeted metabolomics and volatile aroma compounds to predict expert and consumer sensory traits. USDA Select and upper 2/3 Choice beef strip loins were wet aged for 10 or 20 d and then cut into steaks, vacuum-packaged, and frozen. Steaks were cooked to 63 °C, 71 °C, or 80 °C end-point internal steak temperature. USDA Choice steaks had more intense beef flavor identity, brown, roasted, fat-like, salty, sweet, sour, umami, buttery, and overall sweet flavors compared to USDA Select steaks (P < 0.05). Steaks cooked to 80 °C had more intense beef identity, brown, roasted, and umami flavors than steaks cooked to a lower degree of doneness. Steaks cooked to either 63 °C or 71 °C had more intense bloody, metallic, and sour flavors and were juicier, more tender, and had less connective tissue than steaks cooked to a higher degree of doneness. Volatile aroma compounds increased (P < 0.05) in Choice steaks aged for 20 d, while cooking steaks to 80 increased aldehydes, ketones, and pyrazines. Raw steaks had 69 small-molecule metabolomic compounds shared across all four quality grade x aging combinations, and discriminant analysis correctly categorized (P < 0.05) these metabolites. Metabolites and volatiles can be used to predict (r2 > 0.85) expert and consumer sensory panel descriptors and liking.

Proteomics and metabolomics profiling of meat exudate to determine the impact of postmortem aging on oxidative stability of beef muscles

The objective of this study was to characterize the major proteomes and metabolites in beef exudate and determine their relationship to color and oxidative quality of beef muscles. Beef loin (LD) and tenderloin (PM) muscles were cut into sections, individually vacuum-packaged, and aged for 9, 16 and 23 days at 2 °C. Following aging, beef exudates were collected and analyzed for both proteomics and metabolomics profiles. Proteome analysis indicated clustering by muscle types, while metabolomics profiling further clustered the samples based on the aging periods. The PM exudate had a greater concentration of oxidative enzymes, while the LD exudate contained more glycolytic enzymes. Greater lipid, nucleotide, carnitine and glucoside metabolites were observed in LD and 23d exudates. HSP70 and laminin proteins, together with glucosides metabolites, were correlated to muscle oxidative stability. The results indicated that meat exudate could be a viable analytical matrix to determine changes in quality attributes of meat with aging.

Insight from untargeted metabolomics: Revealing the potential marker compounds changes in refrigerated pork based on random forests machine learning algorithm

Data on changes in non-volatile components and metabolic pathways during pork storage were inadequately investigated. Herein, an untargeted metabolomics coupled with random forests machine learning algorithm was proposed to identify the potential marker compounds and their effects on non-volatile production during pork storage by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS/MS). A total of 873 differential metabolites were identified based on analysis of variance (ANOVA). Bioinformatics analysis shows that the key metabolic pathways for protein degradation and amino acid transport are amino acid metabolism and nucleotide metabolism. Finally, 40 potential marker compounds were screened using the random forest regression model, innovatively proposing the key role of pentose-related metabolism in pork spoilage. Multiple linear regression analysis revealed that d-xylose, xanthine, and pyruvaldehyde could be key marker compounds related to the freshness of refrigerated pork. Therefore, this study could provide new ideas for the identification of marker compounds in refrigerated pork.

Investigation of changes in proteomes of beef exudate and meat quality attributes during wet-aging

This study was performed to evaluate the effects of wet-aging (3, 7, 14, 21, and 28 d at 2 °C) on beef (longissimus lumborum muscles) exudate proteome and meat quality changes. The pH, purge loss, and tenderness of beef increased with aging (P < 0.05), while color and lipid oxidative stabilities decreased, especially when long-term (14 and 21 d) aged meat were repackaged and displayed under retail condition (P < 0.05). Nineteen proteins changed significantly with aging (FDR < 0.05), in which most of them progressively accumulated in exudates over aging periods. Combined with partial least squares discriminant analysis, 16 proteins (including 9 structural proteins, 3 metabolic enzymes, 1 heat shock protein, 2 binding proteins, and KBTBD10 protein) were screened as characteristic proteins that could be used for potential meat quality indication. These findings offered novel insight into the utilization of exudates for meat quality assessment.

Metabolomics Characterize the Differential Metabolic Markers between Bama Xiang Pig and Debao Pig to Identify Pork

The Bama Xiang pig (BM) is a unique pig species in Guangxi Province, China. Compared to other breeds of domestic pig, such as the Debao pig (DB), it is smaller in size, better in meat quality, resistant to rough feeding and strong in stress resistance. These unique advantages of Bama Xiang pigs make them of great edible value and scientific research value. However, the differences in muscle metabolites between Bama Xiang pigs (BM) and Debao pigs (DB) are largely unexplored. Here, we identified 214 differential metabolites between these two pig breeds by LC-MS. Forty-one such metabolites are enriched into metabolic pathways, and these metabolites correspond to 11 metabolic pathways with significant differences. In Bama pigs, the abundance of various metabolites such as creatine, citric acid, L-valine and hypoxanthine is significantly higher than in Debao pigs, while the abundance of other metabolites, such as carnosine, is significantly lower. Among these, we propose six differential metabolites: L-proline, citric acid, ribose 1-phosphate, L-valine, creatine, and L-arginine, as well as four potential differential metabolites (without the KEGG pathway), alanyl-histidine, inosine 2'-phosphate, oleoylcarnitine, and histidinyl hydroxyproline, as features for evaluating the meat quality of Bama pigs and for differentiating pork from Bama pigs and Debao pigs. This study provides a proof-of-concept example of distinguishing pork from different pig breeds at the metabolite level and sheds light on elucidating the biological processes underlying meat quality differences. Our pork metabolites data are also of great value to the genomics breeding community in meat quality improvement.

Proteomics and Metabolomics Profiling of Pork Exudate Reveals Meat Spoilage during Storage

Previous studies have evaluated pork quality by omics methods. However, proteomics coupled with metabolomics to investigate pork freshness by using pork exudates has not been reported. This study determined the changes in the profiles of peptides and metabolites in exudates from pork stored at different temperatures (25, 10, 4, and −2 °C). Multivariate statistical analysis revealed similar changes in profiles in exudates collected from pork stored at −2 and 4 °C, and additional changes following storage at higher temperatures. We identified peptides from 7 proteins and 30 metabolites differing in abundance between fresh and spoiled pork. Significant correlations between pork quality and most of the peptides from these 7 proteins and 30 metabolites were found. The present study provides insight into changes in the peptide and metabolite profiles of exudates from pork during storage at different temperatures, and our analysis suggests that such changes can be used as markers of pork spoilage.

Foodomics: Current and Future Perspectives in Food Analysis

Climate change, an increase in population, and the recent pandemic crisis triggered by SARS-CoV-2 have all contributed to a period of global problems [...].