Metabolomic approach to key metabolites characterizing postmortem aged loin muscle of Japanese Black (Wagyu) cattle.
Skeletal muscle metabolites such as amino acids, peptides, nucleotide-related products, fatty acids, and sugars contribute to meat quality as flavor components. Postmortem protein degradation generates free amino acids and peptides in the muscles of cattle . These compounds contribute to the development of meat flavor in beef by Maillard reaction in cooked foods, one of the most important molecular events for flavor formation, which occurs primarily between amino acids and reducing monosaccharides . In pork, inosine 5'-monophosphate (IMP), ribose, and glucose increase "meaty" aroma, while IMP, ribose, and glucose 6-phosphate increase "roasted" aroma .
Meanwhile, nucleotide triphosphates such as adenosine triphosphate (ATP) and guanosine triphosphate (GTP) are broken down during postmortem meat aging, generating taste-associated products including IMP and guanosine monophosphate (GMP) . Moreover, lactic acid accumulation caused by glycolysis results in a decline in muscle pH . This indirectly affects water-holding capacity, color, and tenderness of meat through protein denaturation and protease inactivation. Thus, most of the low-molecular-weight water-soluble metabolites present in skeletal muscle are generated, and some of these are further converted to meat flavor components during meat aging and cooking processes. Despite the importance of these water-soluble compounds in meat, metabolomic changes by which these metabolites are generated in beef have been poorly explored.
A comprehensive understanding of the changes that occur in postmortem muscle metabolites could provide key information on how to control the generation of key compounds for development of meat quality. Metabolomic approaches to beef cattle have been applied to exploration of metabolites related to sensory characteristics and beef flavor [6,7], differences in cattle feeding systems , and the storage conditions of minced beef  using liquid chromatography-mass spectrometry (LC-MS), gas chromatography (GC)-MS, and headspace solid phase microextraction-GC/MS methodologies. A metabolomic study on postmortem beef aging, using reversephase high-performance (HP) LC-MS-based metabolomics, has revealed involvement of metabolites including acyl carnitines and amino acids in beef color stability and lipid oxidation during postmortem aging . The HPLC-MS-based technique has the advantage of detecting semipolar metabolites but not polar metabolites such as ATP and organic acids, due to the higher retention on less charged compounds rather than charged compounds. Another metabolomic study of beef aging using nuclear magnetic resonance (NMR) spectroscopy obtained a total of 25 annotated metabolites in Japanese Black (JB; a Japanese Wagyu breed) cattle, and demonstrated that NMR-based metabolomics can evaluate multiple parameters related to the beef-quality attributes of this breed .
In pork analysis, capillary electrophoresis time-of-flight MS (CE-TOFMS) was previously employed for the analysis of changes in the metabolomic profiles of porcine muscles during postmortem aging, revealing the relevant pathways that generate metabolites associated with pork quality, including the postmortem energy metabolism and protein degradation pathways . The results demonstrated the efficacy of CE-TOFMS technique for such studies based on its broader coverage and the identification of water-soluble, charged metabolites.
JB cattle are well known for their genetically superior intramuscular fat depot, which makes beef tender and gives JB beef the high marbling score that is so prized. In the present study, to explore the key metabolites and pathways in postmortem beef aging, changes in profiles of water-soluble metabolites during postmortem aging of JB beef were comprehensively analyzed for the first time. The CE-TOFMS technique was used for the analysis of water-soluble charged metabolites including free amino acids, organic acids, and short-chain peptides in the lean portion of JB cattle Longissimus thoracis (LT) muscle.
MATERIALS AND METHODS
Animals and muscle samples
The animals were cared for as outlined in the Guide for the Care and Use of Experimental Animals (Animal Care Committee of the NARO Institute of Livestock and Grassland Science [NILGS]), and this committee approved the study (approval number 1611C010). All efforts were made to minimize suffering of the animals. A portion of the LT muscles at the 8th to 9th thoracic vertebrae was dissected from three JB steers aged 28 months (632 to 739 kg) at 30 min after slaughter at the slaughter house of the NILGS. After intramuscular fat was carefully removed from the muscle samples, several pieces of small lean-muscle were picked up from four or five locations in the core part (approx. 2-cm diameter) of each LT muscle at time 0 postmortem. To minimize the deterioration of metabolites, mincing of the muscle samples was avoided. After overnight hanging of the carcasses at 2[degrees]C, the remaining LT muscles were excised out, and lean muscle samples were taken from the LT muscles at 24 h (1 d); then, after continuous storage of the LT muscles at 2[degrees]C, further muscle pieces were picked up at 336 h (14 d) postmortem. The mean values of the crude fat, protein, and moisture contents of the LT muscle block samples were 365.3 mg/g (36.5%), 141.7 mg/g (14.2%), and 476.7 mg/g (47.7%), respectively. After collection from the carcasses, intramuscular fat was manually removed from the muscle tissues. All the subsequent small pieces of lean muscle were collected and frozen in liquid nitrogen and thereafter stored at -80[degrees]C until use. Muscle pH was measured according to the method described previously .
Sample preparation for CE-TOFMS
The frozen muscle pieces (46.3 to 90.0 mg) were immediately plunged into a solution (50% acetonitrile, 10 [micro]M Internal Standard Solution 1 [Human Metabolome Technologies, Tsuruoka, Japan]) at 0[degrees]C and homogenized twice at 1,500 rpm for 120 s. The samples were then centrifuged at 2,300xg for 5 min at 4[degrees]C. The upper layer solution was centrifugally filtered through a Millipore 5-kDa cutoff membrane. The filtrate was lyophilized, suspended in Milli-Q water and analyzed by CETOFMS.
Instrumentation and conditions of CE-TOFMS
CE-TOFMS was carried out using an Agilent CE Capillary Electrophoresis System equipped with an Agilent 6210 Timeof-Flight mass spectrometer, Agilent 1100 isocratic HPLC pump, Agilent G1603A CE-MS adapter kit, and Agilent G1607A CE-ESI-MS sprayer kit (Agilent Technologies, Waldbronn, Germany). The analytic conditions were the same as those used in a previous study . The spectrometer was scanned from m/z 50 to 1,000.
Data analysis of CE-TOFMS results
Raw data obtained by CE-TOFMS were processed with MasterHands, as in our previous study . Among all the detected compounds, the compounds annotated in the Human Metabolome Database (ver. 4.0, http://www.hmdb.ca/) or the Kyoto encyclopedia of genes and genomes database (KEGG; http://www.genome.jp/kegg/), a bioinformatics resource, were further analyzed. The relative contents of the annotated compounds over time were determined by comparing the peaks of compounds with the same MS properties in the analysis. To compare the relative contents of the compounds between time points, peak areas were normalized by those of the internal standards (methionine sulfone for cations, (+)-camphor-10-sulfonic acid for anions) and by sample weight. The resultant relative area values but not the absolute contents were further normalized by the content of methylhistidine (MH; sum of 1 MH and 3 MH, 3 MH is a skeletal muscle-specific metabolite ) which is not affected by postmortem aging time in pork (unpublished data). The contents of major metabolites such as glycolytic products, amino acids, and ATP degradation products were determined using commercially available standards. The abundance of each compound used for comparative analysis was set as 0 when the content of the compound was under detection. The annotated compounds were categorized using the KEGG database, to extract the terms that represent molecular metabolic events associated with the categorized compounds. File conversion of raw MS data, peak picking, reduction of noise, and alignment of data for multiple samples were conducted as previously described .
The normalized relative content values were used for the data analyses. Cluster 3.0 (http://bonsai.hgc.jp/~mdehoon/software/ cluster/software.htm) combined with Java TreeView software (https://sourceforge.net/projects/jtreeview/) was used for hierarchical cluster analysis (HCA). The principal component analysis (PCA), analysis of variance (ANOVA), and multiple comparison test were conducted using SAS Excel Add-In 6.1 for Microsoft Office (https://www.sas.com/ja_jp/home.html). For PCA, all the relative values were transformed into Z-scores, to calculate the principal component (PC) scores and loading values.
To assess the significance of differences between the time points for each compound in multiple comparisons, statistical analysis was performed using R 3.5.1 (http://cran.r-project. org), using an R package for the analysis of significant gene expression profile differences over time (maSigPro release 3.7; https://www.bioconductor.org/packages/release/bioc/html/ maSigPro.html). An adjusted p-value (maSigPro P) <0.050, corresponding to a false discovery rate (FDR) <0.10 and p-values <0.05 were considered statistically significant.
Data were also statistically analyzed using one-way ANOVA for each compound. The model included the fixed effects of postmortem storage time and a random effect of the individual animal, considering the factor of storage time to be within-subject. Data were considered significantly different if p<0.05 in a post hoc multiple test using Fishers least significant difference test (LSD) after ANOVA. The pH value was also analyzed by ANOVA, followed by a post hoc multiple test with the LSD.
Quantitative analyses of postmortem changes in metabolites of LT muscle in JB steers by CE-TOFMS
To clarify the metabolic characteristics and factors responsible for metabolic events in the LT muscle at each time point, metabolomic analyses using CE-TOFMS were conducted. In total, 197 compounds were detected in the beef samples, among which 171 compounds (117 cations and 54 anions) were annotated. Other peaks corresponding to a total of 26 compounds were also detected but could not be determined due to a lack of structural information. Among the 171 annotated metabolites, a total of 70 compounds were absolutely quantified using standard compounds (Table 1). Of the 70 compounds, the contents of 31 increased over time, while the contents of 14 decreased (p<0.05); the rest showed no difference between 0 d and 14 d, with or without change at 1 d. Although there were 110 metabolites to be potentially quantified by the present methodology, 40 of those were not detected (data not shown). Charged metabolites associated with glycolytic metabolism and the citric acid cycle (i.e., the tricarboxylic acid cycle) are not easily detected by LC-MS- or GC-MS-based methods , but they were successfully quantified using the present approach.
According to the results regarding the glycolytic pathway, the lactic acid content increased significantly within the first 24 hrs (p = 0.02). In contrast, the fructose 1,6-bisphosphate (F-1,6-dP) content decreased over the first 24 hrs, indicating the progress of glycolysis in the LT muscle in the early postmortem period. On the other hand, ATP degradation, temporary IMP accumulation at 1 d, and the subsequent accumulation of hypoxanthine and inosine progressed in a coordinated manner during aging. Concomitantly, the muscle pH, starting at 6.20 at 1 h postmortem, declined to 5.33 within the first 24 hrs, and thereafter remained at the ultimate pH value (5.36) until 14 d postmortem (Figure 1). The contents of 15 protein constituent amino acids significantly increased in the postmortem period (Table 1; p<0.05).
Characterization of aging beef samples by HCA and PCA
To characterize the muscle samples at each time point using the metabolomic profiles, the resultant profiles were applied to HCA and PCA analyses using all the metabolites detected and annotated. Before the comparison, it was confirmed that the MH content was not significantly affected by aging time (p>0.05 in ANOVA), which indicates its usefulness as an internal standard of postmortem lean muscle content (data not shown). The heatmap resulting from HCA clearly showed that the metabolomic composition of the beef water-soluble compounds was separated into several categories according to the pattern of changes over time (Figure 2). In other words, the samples were grouped by the pattern of postmortem changes in water-soluble compounds detected in the lean portion of JB bee M
The PCA results also showed that the metabolomic profile of the beef could be grouped according to the first two PCs, PC1, and PC2 (Figure 3). The cumulative proportions of PC1, PC2, and PC3 were 40.4%, 20.9%, and 11.9%, respectively. The plot patterns of the beef samples at D0, D1, and D14 revealed a clear association of PC1 with postmortem muscle aging. In particular, the D0 and D14 samples were segregated from each other by PC1, with the intermediate D1 samples as a transient state. ken at 0, 24 h (1 d), and 168 h (14 d) postmortem, respectively.
The loading scores of cysteine-glutathione disulfide (CysGTdS), thiamine, nicotinamide, gluconic acid, Cys, gluconic acid, and hypoxanthine were highly positive for PC1 (Table 2). The DO and D14 samples were plotted in the negative and positive areas of PC1, respectively, indicating that the JB beef samples at day 14 postmortem were characterized by an abundance of the above-mentioned compounds, such as thiamine and Cys-GTdS. In addition, PC1 was negatively attributed to oxidized form of nicotinamide adenine dinucleotide (NAD+), F-1,6-dP, glycerol 3-phosphate, citric acid, malic acid, cytidine triphosphate, GTP, and uridine diphosphate (UDP)-linked compounds, indicating that these compounds were abundant in the muscle at slaughter but later decreased. On the other hand, the beef samples at D1 were grouped and plotted in a negative area of PC2 compared to those at D0 and D14 (Figure 3). The compounds including Gly, urea, betaine, glutathione, and reduced form of nicotinamide adenine dinucleotide (NADH) showed positive loading scores, while compounds such as GMP, uric acid, spermine, uridine monophosphate (UMP), IMP, adenosine monophosphate (AMP), and inosine diphosphate showed negative loading scores for PC2(Table 2).
Highlighted metabolic pathways and compounds in postmortem LT muscle of JB steers
In addition to absolute quantification of the major metabolites, the relative contents of the annotated compounds were also determined to elucidate the biological events associated with the annotated compounds including those whose standard compound was not available. By evaluating the significance of postmortem changes in the metabolite contents in the global JB muscle metabolome, it would be possible to extract not only the relevant metabolic pathways that were activated in the beef samples during postmortem aging, but also significant metabolites that characterize the aged JB beef. To this end, maSigPro software (a statistical R-based package) was employed to test multiple comparisons against changes in the relative contents of the annotated metabolites of the beef, including the absolutely quantified compounds. Consequently, a total of 89 compounds showing significant increases or decreases during postmortem aging (adjusted p<0.05, FDR<0.10) were extracted, of which the top 50 compounds are shown in Supplementary Table S1. Of those, not only 16 amino acids, but also the contents of 6 dipeptides also increased over the duration (Table 3). In addition to compounds related to the glycolytic pathway (dihydroxyacetone phosphate [DHAP], F-1,6-dP, lactic acid) and purine metabolism (AMP, ATP, GMP, hypoxanthine, IP, etc.), other compounds, including 6-phosphogluconic acid (6PG), sedoheptulose 7-phosphate (S7P), citric acid, fumaric acid, and NAD+, showed changes in their contents in the postmortem period.
Using the KEGG database, all the significantly changed compounds (p<0.05) were assigned to functional pathways representing postmortem aging of the LT muscle. We extracted the pathways in which at least three compounds changed significantly (p<0.05); these included the citric acid cycle, glycerophospholipid metabolism, cysteine metabolism, protein digestion and absorption, nicotinate and nicotinamide metabolism, purine metabolism, pentose phosphate metabolism, and polyamine metabolism pathways (Table 3). It is therefore suggested that these metabolic pathways are prominent in the lean portion of JB beef during postmortem aging.
In addition to the above-mentioned metabolites related to beef quality, changes over time were observed in the contents of key metabolites related to nutrition and beef aging: the relative contents of gluconic acid, gluconolactone, Cys-GTdS and coenzyme precursors including pyridoxamine 5'-phosphate (PMP) and thiamine significantly increased during postmortem aging of the beef (adjusted p<0.05, FDR<0.10; Figure 4). Moreover, the relative contents of 6PG, 5-oxoproline, and N-acetyllysine increased, while that of phosphoribosyl pyrophosphate (PRPP) decreased during beef aging (adjusted p<0.05, FDR<0.10; Supplementary Table S1).
Major metabolic pathways observed during postmortem aging of the LT muscle in JB steers
In the present study, the contents of the metabolites in the lean LT muscle at different stages of postmortem aging were determined. Comparison of the contents of the annotated compounds among the postmortem time points by HCA, PCA, and the multiple comparison test revealed changes in numerous metabolites, including glycolytic products, energy metabolism-related compounds, purine and pyrimidine-related compounds, and amino acids. The pathways related to the glycolysis, purine metabolism, protein degradation, pentose pathway, and nicotinamide metabolism in the KEGG database were extracted as the molecular biological events associated with the significantly changed compounds (p< 0.05) during the postmortem aging of the LT muscle.
To focus on the changes in the lean muscle metabolites, the potential contaminating influence of intramuscular fat was excluded by taking only the lean muscle portion as the samples, which was followed by normalization with MH, the content of which did not differ among the aging time points. As a result, the predicted postmortem biochemical events observed during pork aging , such as increases in amino acids and ATP degradation products, were observed (Table 3). This means that the MH-based CE-TOFMS analysis of the metabolite contents in lean muscle portion of Wagyu cattle was not affected by variation of the intramuscular fat content of the cattle. The observations confirmed that the present muscle samples underwent a typical postmortem aging process , and that postmortem metabolic changes in bovine LT muscle are very similar to those in porcine muscle .
Protein digestion and absorption
During postmortem aging of the LT muscle, 16 free amino acids increased (Table 3), which indicates that the muscle proteins were degraded as demonstrated in the progress of porcine [12,14] and bovine muscle proteolysis [15-17]. This protein degradation process is reemphasized by the elevated contents of several dipeptides such as Glu-Glu (p<0.05), a dipeptide sequence frequently present in troponin-T [15,18] that is easily degraded in postmortem bovine muscles [16,17]. The accumulation of amino acids during postmortem aging was also observed in beef of AngusxSimmental crossbred steers . Taken together, these results suggest that postmortem proteolysis generated free amino acids via the breakdown of muscle proteins to dipeptides after 1 d. It is also likely that endoproteinases such as calpains and aminopeptidases [14,19] played principal roles in the generation of most of the amino acids present after 1 d postmortem. The Asp and Glu thus generated might participate in a series of reactions to provide substrates for the citric acid cycle as glucogenic amino acids in the postmortem muscle .
The progress of muscle proteolysis is expected to contribute to postmortem tenderization in the JB loin beef, as shown in past beef studies . The generation of amino acids and dipeptides also contributes to the improvement of beef flavor. The addition of monosodium glutamate to beef soup enhanced its "salty" or "potato" flavors in a consumer sensory examination . Moreover, some dipeptides such as Glu-Glu are recognized to enhance umami taste of 0.02% IMP , suggesting that these proteolytic products are able to improve taste and flavor of beef.
Citric acid cycle and pyruvate metabolism
Compounds involved in the citric acid cycle and pyruvate metabolism were decreased in the postmortem aging period (adjusted p<0.05, FDR<0.10) (Table 3). Lactic acid is a final product of glycolysis, emphasizing the progress of glycolysis in the postmortem LT muscle. The relative contents of citric acid, fumaric acid, and malic acid in the citric acid cycle decreased (adjusted p<0.05, FDR<0.10), suggesting that these compounds were supplied as a source of carbon chains for maintenance of homeostasis. DHAP may have been generated by the degradation of F-1,6-dP, which would account for the increase in DHAP in this study. DHAP is an important metabolite as a source of triglyceride synthesis and the pentose phosphate pathway , and thus the change in DHAP content might influence multiple metabolic pathways.
Pentose phosphate pathway, nicotinate and nicotinamide metabolism
It is possible that the decrease in DHAP content influences changes in the contents of pentose phosphate pathway metabolites such as S7P and ribulose 5-phosphate (Ru5P). In fact, the S7P and Ru5P contents significantly increased (adjusted p<0.05, FDR<0.10) (Table 3). On the other hand, NADPH was not detected in this study. DHAP is made by coupling reactions with the pentose phosphate pathway as an energy source for synthesis of fatty acid and cholesterol . Although the reason why neither NADPH nor NADP+ was detected remains unclear, previously those compounds were successfully detected by CE-TOFMS in pork . There might be a specific difference between beef and pork in the role of NADPH/ NADP+ in energy metabolism. Another energy-supplying compound, NADH, was detected, but its content did not change. In contrast, the NAD+ content decreased, possibly due to degradation to nicotinamide, the content of which increased during the aging period. The changes in the ratio of NADH/NAD+ were very similar to those in pork .
This is the first study to report increases in choline and CDP-choline during postmortem aging of beef. Both choline and CDP-choline are nutritionally essential components as methyl-group donors in food materials, similarly to eggs . These metabolites are categorized as part of glycerophospholipid metabolism, and such changes could reflect a shift of the metabolism toward a supply of energy source compounds in glycolytic metabolism where the final product is ATP. It is likely that the increases in choline and CDP-choline were linked with a metabolic shift toward G3P generation via DHAP by degradation of phosphatidyl choline, a plasma membrane component. Likewise, an increase in ethanolamine (data not shown) and its phosphate was also observed, possibly due to degradation of phosphatidyl ethanolamine, another component of the plasma membrane.
A series of changes in metabolites associated with purine metabolism were also observed. This indicates that there was a dynamic change in the nucleotide metabolite profile over time during postmortem aging. Thus, ATP was degraded into xanthine or hypoxanthine via IMP or inosine generation, and GTP was degraded into GMP and guanosine in parallel during the aging process, resulting in increased contents of uric acid and PRPP. The 5'-ribonucleotides, AMP, IMP, and GMP, are all important in meat flavor perception, as they have umami taste characteristics  as well as an enhancing effect on umami taste. IMP and hypoxanthine are especially associated with meaty and bitter flavors in pork, respectively . Thus, the catabolic reactions of purine metabolism contribute to the accumulation of taste-related compounds such as IMP in beef after appropriate aging periods.
Characteristic compounds in postmortem aging of LT muscle in JB steers
During postmortem aging of beef in the present study, we clearly observed significant changes in metabolites that have the potential to influence human health. Some of these compounds, namely Cys-GTdS, nicotinamide, thiamine, and gluconic acid, have highly positive PC1 loading values, indicating that they are characteristic of postmortem aging of beef.
Gluconic acid and the precursor gluconolactone can promote growth of intestinal Bifidobacterium, since oral administration of gluconate increases the number of fecal Bifidobacteria, resulting in increased defecation frequency in humans . The polyamines spermidine and putrescine were also detected in the present study. Changes in those polyamines during postmortem beef aging have not been reported previously. Spermidine also has a role of promoting microbiota growth in the intestine and thereby delaying senescence in mice . Spermidine is a final compound in Gln degradation via ornithine and putrescine , which seemed to progress in postmortem LT muscle in the present study. Thiamine and PMP are well known as precursors of vitamins B2 and B6, respectively, which are essential nutrients for humans, as is nicotinamide . The increases in the metabolites discussed above (i.e., choline, gluconate, polyamines, and vitamins) during the aging process may enhance the functional value of the beef.
In addition, according to the PCA loading analysis, thiamine is one of the most characteristic metabolites to show the extent of postmortem aging of the LT muscle, which has also been confirmed in porcine muscles [29,30]. Recently we hypothesized that thiamine may be generated by sequential dephosphorylation steps starting from thiamine triphosphate (ThTP) via thiamine diphosphate (ThDP) in the postmortem porcine muscles . As thiamine is more absolvable than ThDP in intestinal epithelial cells , an increase in thiamine in aged beef may be beneficial for human health. Interestingly, neither ThTP nor ThDP was detected in the LT muscle during aging, even when using the same methodology as in the previous pork study. This difference might be due to the interspecies difference in metabolism, as suggested by the different contents of ThTP found in bovine and porcine muscles . The mechanism of postmortem thiamine accumulation in bovine muscle requires further investigation.
Several other compounds have been shown to be characteristic of the postmortem aging of beef. PCA loading analysis showed higher contributions of Cys-GTdS (Figure 4) and hypoxanthine in the aged beef. In beef from Angus crossbred steers, the contents of acylcarnitines (butyryl-, pivaloyl-, hexanoyl-, octanoyl-, decanoyl-, and propionylcarnitines) were temporarily elevated during the aging period . In the present study, butyryl-, malonyl-, isovaleryl-, and octanoylcarnitines were detected, but only butyrylcarnitine increased in the postmortem LT muscle (p<0.05, data not shown). The difference in detected compounds between the two studies might have been due to the different breeds of cattle studied, rather than the different detection methods used.
Several potential limitations should be mentioned. In the present study, we only used three steers, which is a minimal number for experiments. Moreover, there was a variation of body weight among the tested steers, and the impact of body weight on postmortem metabolite generation remains unknown. Nevertheless, our finding of significant changes in metabolite contents agreed with the results of past studies of postmortem meat aging, especially in regard to ATP degradation and the generation of amino acids and peptides. This suggests that the overall tendency of metabolomic changes observed in the three steers in this study would not contradict that observed in studies using larger numbers of animals, although further analyses are necessary to confirm those results.
In the postmortem aging process in the LT muscle of JB steer, glycolysis, the citric acid cycle, the pentose phosphate pathway, protein digestion, amino acid generation, and purine metabolism were highlighted as the characteristic biochemical events. The accumulation of products in those pathways, such as IMP, R5P, and Glu, is expected to contribute to the improvement of the quality traits of aged beef. In addition, thiamine, choline, and Cys-GTdS could be useful as biomarkers of aged beef. Due to the accumulation of some of nutritional ingredients, the aging of beef may increase its value as a food and may contribute to human health.
CONFLICT OF INTEREST
We certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.
We thank the personnel at the cattle house of the Livestock Research Support Center of the NARO Institute of Livestock and Grassland Science for their support, especially Mr. K. Inoue and Mr. K. Kajitani, who skillfully prepared beef cuts. We also thank Dr. H. Shingu and Mr. M. Hayashi at Division of Animal Metabolism and Nutrition for their rearing management of the cattle, and Mrs. C. Shindo and Mrs. M. Ichimura for their technical supports. This research was partly supported by the Japan Society for the Promotion of Science (JSPS KAKENHI JP15K07775 to SM).
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Susumu Muroya (1),*, Mika Oe (1), Koichi Ojima (1), and Akira Watanabe (2)
* Corresponding Author: Susumu Muroya Tel: +81-29-838-8686, Fax: +81-29-838-8686, E-mail: email@example.com
(1) Muscle Biology Research Unit, Animal Products Research Division, NARO Institute of Livestock and Grassland Science, Tsukuba, Ibaraki 305-0901, Japan
(2) NARO Tohoku Agricultural Research Center, Morioka, Iwate 020-0198, Japan
Submitted Aug 31, 2018; Revised Oct 25, 2018; Accepted Dec 20, 2018
Caption: Figure 1. Postmortem pH decline in Longissimus thoracis muscle of Japanese Black steers. Different letters (a, b) indicate significant differences among time points (p<a.001). Error bars indicate standard error (n = 3).
Caption: Figure 2. Heatmap result of hierarchical clustering analysis of metabolomic changes during postmortem aging in Longissimus thoracis muscle of Japanese Black steers. Three cattle samples were allocated to each group at a specific time point (day 0: D0, day 1: D1, day 14: D14). The row displays the metabolite and the column represents the sample. Metabolites with relatively low contents are displayed in green, while metabolites with relatively high contents are displayed in red. The brightness of each color corresponds to the magnitude of the difference when compared with the average value.
Caption: Figure 3. Principal component analysis of Longissimus thoracis muscle of Japanese Black steers by metabolomic changes during postmortem aging. The plots of open square (D0), gray triangle (D1), and closed circle (D14) indicate LT samples taken at 0,24 h (1 d), and 168 h (14 d) postmortem, respectively.
Caption: Figure 4. Postmortem changes in relative contents of metabolites in Longissimus thoracis muscle of Japanese Black steers. The relative content contents (vertical axis) were normalized using a method described in Materials and Methods. The horizontal axis indicates postmortem time (day 0: D0, day 1: D1, day 14: D14). Error bars indicate standard error (n = 3). Different letters (a, b, c) indicate significant differences among time points (p<0.05) in post hoc least significant difference test after analysis of variance (p = 0.05 for pyridoxamine 5'-phosphate; p = 0.07 for CDP-choline; p<0.05 for the other compounds).
Table 1. Changes in the contents of compounds during post-mortem Japanese Black beef aging DO Compound Mean (nmol/g) SE 3-Hydroxybutyric acid 136.6 22.8 6-Phosphogluconic acid 0 -- (a) ADP 53.5 2.1 Ala 2,295.2 380.1 AMP 0 -- Arg 334.5 35.7 (a) Asn 111.5 5.8 (a) Asp 44.1 9.3 ATP 6,534.6 451.5 (b) Betaine 1,712.7 69.7 Carnosine 12,381.8 1,028.1 Choline 35.6 1.9 (a) Citric acid 113.7 9.4 (b) Citrulline 84.7 26.3 Creatine 21,093.9 1,605.9 Creatinine 479.6 10.7 (a) CTP 46.6 1.5 (b) Cys 1.6 0.8 (a) Cytidine 2.4 0.7 (a) Dihydroxyacetone phosphate 801.1 113.7 (b) Fructose 1,6-diphosphate 168.8 33.2 (b) Fructose 6-phosphate 2,343.4 188.8 Fumaric acid 166.4 41.5 GABA 19.4 2.9 Gln 3,613.6 530.1 Glu 312.4 68.0 (a) Gluconic acid 0 -- Glucose 1-phosphate 598.9 57.3 Glucose 6-phosphate 10,707.5 825.7 Glutathione (GSH) 696.7 77.9 Glutathione (GSSG)_divalent 91.5 9.7 (b) Gly 1,083.4 15.7 Glycerol 3-phosphate 4,032.4 715.9 (b) GMP 0 -- (a) GTP 171.5 9.1 (b) Guanosine 0 -- (a) His 152.1 19.0 (a) Hydroxyproline 45.2 3.6 Hypoxanthine 9.9 2.3 (a) Ile 177.8 17.9 (a) IMP 78.4 39.2 (a) Inosine 4.5 2.5 (a) Lactic acid 43,827.0 6,652.1 (a) Leu 263.3 25.7 (a) Lys 341.3 36.0 (a) Malic acid 802.1 138.4 (b) Met 44.0 4.1 (a) NAD+ 550.5 59.7 (c) Ornithine 84.6 4.8 Phe 113.2 10.8 (a) Pro 267.4 17.8 PRPP 24.0 0.8 (b) Putrescine 9.9 0.9 (a) Pyruvic acid 0 -- Ribose 5-phosphate 0 --(a) Ribulose 5-phosphate 34.9 8.9 (a) S-Adenosylmethionine 8.5 2.3 (a) Sedoheptulose 7-phosphate 0 --(a) Ser 290.0 17.1 (a) Spermidine 1.6 0.1 (a) Spermine 0 -- Succinic acid 1,250.1 374.2 Thr 202.5 9.8 (a) Trp 38.5 3.8 (a) Tyr 89.8 8.2 (a) UMP 0.0 --(a) Uridine 14.1 2.3 (a) UTP 124.5 10.3 (b) Val 362.7 31.3 (a) [beta]-Ala 119.8 34.9 D1 Compound Mean (nmol/g) SE 3-Hydroxybutyric acid 211.3 30.7 6-Phosphogluconic acid 19.1 0 (a) ADP 35.2 9.9 Ala 2,427.6 246.5 AMP 99.1 39.8 Arg 405.7 11.7 (a) Asn 114.6 5.6 (a) Asp 13.1 13.1 ATP 21.1 7.0 (a) Betaine 1,611.4 214.4 Carnosine 1,2587.4 1,069.8 Choline 58.4 13.3 (a) Citric acid 43.3 10.5 (a) Citrulline 86.0 17.3 Creatine 23,799.2 3,311.2 Creatinine 678.1 74.4 (b) CTP 0 -- (a) Cys 23.6 6.9 (a) Cytidine 5.2 0.5 (a) Dihydroxyacetone phosphate 0 -- (a) Fructose 1,6-diphosphate 24.3 2.7 (a) Fructose 6-phosphate 3,994.1 854.2 Fumaric acid 35.3 35.3 GABA 21.0 1.8 Gln 3,228.4 177.8 Glu 151.2 17.7 (a) Gluconic acid 27.0 4.6 Glucose 1-phosphate 938.4 239.5 Glucose 6-phosphate 16,657.2 3,995.0 Glutathione (GSH) 711.5 56.7 Glutathione (GSSG)_divalent 44.5 8.9 (a) Gly 1,121.1 164.7 Glycerol 3-phosphate 1,087.3 493.4 (a) GMP 118.2 19.4 (b) GTP 0 -- (a) Guanosine 4.7 1.1 (a) His 151.5 11.3 (a) Hydroxyproline 47.5 8.5 Hypoxanthine 335.0 36.9 (a) Ile 231.0 10.7 (a) IMP 7,574.3 1,402.1 (c) Inosine 543.5 91.7 (b) Lactic acid 115,982.1 15,570.4 (b) Leu 314.7 18.7 (a) Lys 454.2 54.4 (a) Malic acid 329.4 124.6 (a) Met 42.6 2.4 (a) NAD+ 277.9 84.7 (b) Ornithine 91.2 8.6 Phe 138.2 7.8 (a) Pro 275.0 35.1 PRPP 0 --(a) Putrescine 19.5 0.9 (b) Pyruvic acid 182.2 182.2 Ribose 5-phosphate 56.6 8.6 (b) Ribulose 5-phosphate 180.1 6.2 (b) S-Adenosylmethionine 18.6 2.7 (b) Sedoheptulose 7-phosphate 29.9 3.1 (a) Ser 311.8 19.9 (a) Spermidine 22.8 3.3 (b) Spermine 71.8 22.6 Succinic acid 1,071.2 180.6 Thr 219.5 26.4 (a) Trp 45.0 4.9 (a) Tyr 105.7 3.7 (a) UMP 85.6 12.6 (b) Uridine 29.6 4.6 (a) UTP 0 --(a) Val 402.8 28.9 (a) [beta]-Ala 94.8 10.9 D14 ANOVA Compound Mean (nmol/g) SE p-value 3-Hydroxybutyric acid 198.0 29.0 0.069 6-Phosphogluconic acid 75.4 17.7 (b) 0.021 ADP 31.0 4.5 0.119 Ala 2,930.5 241.8 0.283 AMP 47.7 3.5 0.092 Arg 641.4 44.3 (b) 0.013 Asn 208.2 16.0 (b) 0.008 Asp 39.3 3.5 NA ATP 16.4 2.7 (a) <0.001 Betaine 1,560.7 84.1 0.689 Carnosine 11,076.5 1,387.0 0.706 Choline 134.4 17.9 (b) 0.006 Citric acid 0 -- (a) 0.002 Citrulline 79.6 9.8 0.925 Creatine 20,804.1 504.8 0.610 Creatinine 1,019.7 29.5 (c) 0.004 CTP 0 -- (a) <0.001 Cys 107.2 19.0 (b) 0.005 Cytidine 12.0 1.4 (b) 0.006 Dihydroxyacetone phosphate 0 -- (a) 0.001 Fructose 1,6-diphosphate 0 -- (a) 0.004 Fructose 6-phosphate 2,200.8 365.1 0.178 Fumaric acid 115.8 40.2 NA GABA 18.4 2.1 0.804 Gln 4,126.7 707.3 0.278 Glu 776.0 165.1 (b) 0.032 Gluconic acid 77.0 8.8 0.003 Glucose 1-phosphate 427.9 65.0 0.204 Glucose 6-phosphate 8,776.5 1,544.9 0.226 Glutathione (GSH) 707.2 7.4 0.961 Glutathione (GSSG)_divalent 45.1 9.5 (a) <0.001 Gly 1,272.8 62.6 0.537 Glycerol 3-phosphate 90.0 20.9 (a) 0.018 GMP 78.1 6.9 (b) 0.003 GTP 0 -- (a) <0.001 Guanosine 14.1 3.1 (b) 0.007 His 256.4 23.8 (b) 0.029 Hydroxyproline 44.0 7.1 0.898 Hypoxanthine 2,212.6 203.3 (b) <0.001 Ile 512.3 74.8 (b) 0.016 IMP 3,437.7 205.6 (b) 0.006 Inosine 1,109.1 239.5 (c) 0.008 Lactic acid 105,428.9 6,388.3 (b) 0.020 Leu 826.8 132.6 (b) 0.019 Lys 732.6 12.1 (b) 0.006 Malic acid 105.1 28.9 (a) 0.017 Met 323.7 71.0 (b) 0.014 NAD+ 20.2 5.2 (a) 0.004 Ornithine 148.5 38.1 0.196 Phe 419.5 76.2 (b) 0.020 Pro 338.4 26.1 0.212 PRPP 0 --(a) <0.001 Putrescine 19.3 2.4 (b) 0.002 Pyruvic acid 0 -- NA Ribose 5-phosphate 70.0 16.6 (b) 0.031 Ribulose 5-phosphate 215.0 48.6 (b) 0.035 S-Adenosylmethionine 4.0 1.3 (a) 0.008 Sedoheptulose 7-phosphate 308.9 48.4 (b) 0.002 Ser 735.1 94.4 (b) 0.012 Spermidine 20.6 2.8 (b) 0.002 Spermine 31.0 13.3 0.078 Succinic acid 1,953.8 360.0 0.280 Thr 425.9 41.5 (b) 0.018 Trp 84.7 10.1 (b) 0.030 Tyr 348.3 73.4 (b) 0.027 UMP 34.7 7.2 (a) 0.003 Uridine 131.9 11.0 (b) <0.001 UTP 0 --(a) <0.001 Val 760.3 114.8 (b) 0.050 [beta]-Ala 105.5 22.1 0.849 ANOVA, analysis of variance; SE, standard error; ADP, adenosine diphosphate; AMP, adenosine monophosphate; ATP, adenosine triphosphate; CTP, cytidine triphosphate; GABA, [gamma]-aminobutyric acid; GMP, guanosine monophosphate; GTP, guanosine triphosphate; IMP, inosine 5'-monophosphate; PRPP, phosphoribosyl pyrophosphate; UMP, uridine monophosphate; UTP, uridine triphosphate. The compounds are quantified by CE-TOFMS and shown in nmol/g. The contents of compounds under detection are indicated as 0. Compounds that were not detected throughout the experimental duration are not listed. (a-c) Values with different subscript differ between aging time points (p < 0.05). NA, not applicable due to too large variance between the samples. Table 2. Loading values of top 20 compounds for principal component-1 and -2 of Japanese black beef aging analysis (1) PC1 Compound name 0.1184 Cysteine glutathione disulfide 0.1177 Galactosamine/Glucosamine 0.1159 Glucose 6-phosphate 0.1157 Nicotinamide 0.1156 Thiamine 0.1155 S-Adenosylhomocysteine 0.1153 Cys 0.1152 Hypoxanthine 0.1147 Uridine 0.1146 Gluconic acid -0.0947 S-Lactoylglutathione -0.0970 Fructose 1,6-diphosphate -0.1000 Glycerol 3-phosphate -0.1008 UDP-N-acetylgalactosamine/UDP-N-acetylglucosamine -0.1010 Malic acid -0.1041 UDP-glucose/UDP-galactose -0.1041 Citric acid -0.1042 Argininosuccinic acid -0.1111 Trimethylamine N-oxide -0.1121 NAD+ PC2 Compound name 0.1504 N5-Ethylglutamine 0.1461 S-Methylcysteine 0.1427 Malonylcarnitine 0.1414 Gly 0.1384 Terephthalic acid 0.1344 Urea 0.1330 Betaine 0.1302 Glutathione 0.1269 Methylhistidine 0.1224 NADH -0.0766 GMP -0.0814 Uric acid -0.0861 ADP-ribose 0.0984 Spermine -0.1018 Nicotinamide mononucleotide 0.1047 UMP -0.1095 IMP -0.1209 Pyruvic acid -0.1300 AMP -0.1500 IDP NADH, nicotinamide adenine dinucleotide; GMP, guanosine monophosphate; ADP, adenosine diphosphate; UDP, uridine diphosphate; UMP, uridine monophosphate; IMP, inosine 5'-monophosphate; AMP, adenosine monophosphate; IDP, inosine 5'-diphosphate. (1) Compounds with top 20 positive and negative loading values for PC1 and PC2 are listed. Table 3. Representative KEGG metabolic pathways that contain significantly changed metabolites during postmortem aging of Japanese Black Longissimus thoracis muscle (1) Relative content (2) DO KEGG pathway, compounds Mean SE Protein digestion and absorption Asn 146.6 11.6 Asp 62.8 6.2 Cys 0.6 0.3 Cystine 0 -- Glu 444.0 53.4 His 251.0 10.6 Ile 715.3 81.9 Leu 1,229.4 52.1 Lys 502.3 73.5 Met 91.9 3.0 Phe 349.8 17.2 Ser 399.9 30.6 Thr 369.2 28.5 Trp 80.4 6.0 Tyr 182.2 6.2 Val 1,088.8 45.9 (Dipeptides) Ala-Ala 0 -- Glu-Glu 0 -- Gly-Gly 0 -- His-Glu 0 -- Thr-Asp Ser-Glu 0 -- Tyr-Glu 0 -- Glycolytic pathway Dihydroxyacetone phosphate 245.1 16.0 Fructose 1,6-diphosphate 112.9 11.0 Lactic acid 14,121.1 1,212.1 Citric acid cycle Citric acid 91.8 9.9 Fumaric acid 42.9 6.0 Malic acid 563.4 39.4 Pyruvate metabolism Dihydroxyacetone phosphate 245.1 16.0 Lactic acid 14,121.1 1,212.1 Malic acid 563.4 39.4 Pentose phosphate pathway 6-Phosphogluconic acid 0 -- Ribose 5-phosphate 0 -- Ribulose 5-phosphate 15.0 2.2 Sedoheptulose 7-phosphate 0 -- Nicotinate and nicotinamide metabolism Dihydroxyacetone phosphate 245.1 16.0 Fumaric acid 42.9 6.0 NAD+ 221.4 13.8 Nicotinamide 156.8 10.6 Glycerophospholipid metabolism CDP-choline 1.3 1.1 Choline 94.1 6.7 Dihydroxyacetone phosphate 245.1 16.0 Glycerol 3-phosphate 1,560.5 193.1 Purine metabolism AMP 0 -- ADP-ribose 4.6 3.0 ADP 36.8 4.0 ATP 4,888.2 430.3 GMP 0 -- GTP 85.2 11.7 Guanosine 0 -- Hypoxanthine 12.4 1.5 IMP 26.3 9.5 Inosine 3.9 2.5 PRPP 11.3 1.0 Ribose 5-phosphate 0 -- Uric acid 8.1 1.2 Xanthine 0 -- Xanthosine 0 -- Cysteine metabolism Cys 0.6 0.3 Cystine 0 -- Glutathione (GSSG)_divalent 192.9 12.0 Homocysteine 2.8 1.4 Ser 399.9 30.6 Glutathione metabolism 5-Oxoproline 7.8 3.2 Cys 0.6 0.3 Glu 444.0 53.4 Spermidine 2.8 0.1 Relative content (2) D1 KEGG pathway, compounds Mean SE Protein digestion and absorption Asn 125.9 25.0 Asp 10.5 8.5 Cys 29.3 16.9 Cystine 0 -- Glu 201.3 63.6 His 208.7 35.4 Ile 770.9 151.8 Leu 1,234.5 231.2 Lys 524.1 67.4 Met 79.4 22.7 Phe 358.7 67.7 Ser 363.3 77.5 Thr 325.5 52.7 Trp 76.1 10.7 Tyr 182.5 37.9 Val 1,005.1 174.8 (Dipeptides) Ala-Ala 0 -- Glu-Glu 13.1 8.2 Gly-Gly 5.6 2.3 His-Glu 0 -- Thr-Asp Ser-Glu 0 -- Tyr-Glu 2.7 1.7 Glycolytic pathway Dihydroxyacetone phosphate 0 -- Fructose 1,6-diphosphate 6.7 2.8 Lactic acid 30,112.3 3571.4 Citric acid cycle Citric acid 13.7 5.9 Fumaric acid 5.1 4.2 Malic acid 182.8 41.3 Pyruvate metabolism Dihydroxyacetone phosphate 0 -- Lactic acid 30,112.3 3571.4 Malic acid 182.8 41.3 Pentose phosphate pathway 6-Phosphogluconic acid 1.5 1.2 Ribose 5-phosphate 22.6 5.2 Ribulose 5-phosphate 68.2 14.4 Sedoheptulose 7-phosphate 11.8 2.0 Nicotinate and nicotinamide metabolism Dihydroxyacetone phosphate 0 -- Fumaric acid 5.1 4.2 NAD+ 80.9 11.8 Nicotinamide 386.5 76.3 Glycerophospholipid metabolism CDP-choline 7.4 1.8 Choline 122.5 20.8 Dihydroxyacetone phosphate 0 -- Glycerol 3-phosphate 348.0 109.7 Purine metabolism AMP 43.3 6.8 ADP-ribose 9.9 2.2 ADP 17.9 1.8 ATP 11.1 1.0 GMP 43.6 7.4 GTP 0 -- Guanosine 7.7 2.7 Hypoxanthine 396.9 131.0 IMP 2,035.0 155.8 Inosine 742.3 265.3 PRPP 0 -- Ribose 5-phosphate 22.6 5.2 Uric acid 19.0 1.7 Xanthine 57.1 12.4 Xanthosine 2.9 1.4 Cysteine metabolism Cys 29.3 16.9 Cystine 0 -- Glutathione (GSSG)_divalent 73.5 8.2 Homocysteine 4.6 1.9 Ser 363.3 77.5 Glutathione metabolism 5-Oxoproline 21.7 7.2 Cys 29.3 16.9 Glu 201.3 63.6 Spermidine 31.9 3.3 Relative content (2) D14 KEGG pathway, compounds Mean SE Protein digestion and absorption Asn 234.5 18.8 Asp 49.8 3.2 Cys 120.2 69.4 Cystine 2.2 0.3 Glu 971.5 168.3 His 368.2 27.1 Ile 1,757.5 233.9 Leu 3,354.1 483.3 Lys 905.9 30.8 Met 587.9 113.4 Phe 1,124.8 180.6 Ser 872.2 107.5 Thr 666.3 64.9 Trp 152.3 16.2 Tyr 614.9 114.6 Val 1,980.0 272.2 (Dipeptides) Ala-Ala 20.1 4.2 Glu-Glu 75.6 14.2 Gly-Gly 13.7 0.3 His-Glu 5.0 1.6 Thr-Asp Ser-Glu 10.0 1.8 Tyr-Glu 10.6 1.8 Glycolytic pathway Dihydroxyacetone phosphate 0 -- Fructose 1,6-diphosphate 0 -- Lactic acid 29,663.1 2222.0 Citric acid cycle Citric acid 0 -- Fumaric acid 17.2 8.4 Malic acid 65.6 15.8 Pyruvate metabolism Dihydroxyacetone phosphate 0 -- Lactic acid 29,663.1 2222.0 Malic acid 65.6 15.8 Pentose phosphate pathway 6-Phosphogluconic acid 28.0 5.9 Ribose 5-phosphate 29.0 6.2 Ribulose 5-phosphate 83.8 17.1 Sedoheptulose 7-phosphate 127.4 14.8 Nicotinate and nicotinamide metabolism Dihydroxyacetone phosphate 0 -- Fumaric acid 17.2 8.4 NAD+ 4.9 2.3 Nicotinamide 754.0 73.9 Glycerophospholipid metabolism CDP-choline 8.5 0.4 Choline 301.9 27.9 Dihydroxyacetone phosphate 0 -- Glycerol 3-phosphate 30.2 6.2 Purine metabolism AMP 25.6 1.6 ADP-ribose 0 -- ADP 18.0 2.3 ATP 6.8 2.9 GMP 30.3 2.1 GTP 0 -- Guanosine 21.4 4.3 Hypoxanthine 2,466.0 186.9 IMP 1,031.6 64.7 Inosine 1,407.6 276.1 PRPP 0 -- Ribose 5-phosphate 29.0 6.2 Uric acid 10.7 0.4 Xanthine 219.4 22.2 Xanthosine 6.6 0.2 Cysteine metabolism Cys 120.2 69.4 Cystine 2.2 0.3 Glutathione (GSSG)_divalent 81.0 11.3 Homocysteine 14.6 0.6 Ser 872.2 107.5 Glutathione metabolism 5-Oxoproline 67.7 12.0 Cys 120.2 69.4 Glu 971.5 168.3 Spermidine 31.3 3.7 Adjusted Numbers of KEGG pathway, compounds p value metabolites Protein digestion and absorption 16/31 Asn 0.0092 Asp 0.0084 Cys 0.0009 Cystine <0.0001 Glu 0.0067 His 0.0098 Ile 0.0033 Leu 0.0019 Lys 0.0023 Met 0.0010 Phe 0.0018 Ser 0.0029 Thr 0.0032 Trp 0.0028 Tyr 0.0032 Val 0.0090 (Dipeptides) 6/7 Ala-Ala 0.0006 Glu-Glu 0.0012 Gly-Gly 0.0031 His-Glu 0.0047 Thr-Asp Ser-Glu 0.0002 Tyr-Glu 0.0028 Glycolytic pathway 3/12 Dihydroxyacetone phosphate <0.0001 Fructose 1,6-diphosphate 0.0001 Lactic acid 0.0173 Citric acid cycle 3/4 Citric acid 0.0004 Fumaric acid 0.0369 Malic acid 0.0004 Pyruvate metabolism 3/9 Dihydroxyacetone phosphate <0.0001 Lactic acid 0.0173 Malic acid 0.0004 Pentose phosphate pathway 4/9 6-Phosphogluconic acid 0.0008 Ribose 5-phosphate 0.0252 Ribulose 5-phosphate 0.0491 Sedoheptulose 7-phosphate 0.0000 Nicotinate and nicotinamide metabolism 4/15 Dihydroxyacetone phosphate <0.0001 Fumaric acid 0.0369 NAD+ 0.0001 Nicotinamide 0.0025 Glycerophospholipid metabolism 4/10 CDP-choline 0.0003 Choline 0.0314 Dihydroxyacetone phosphate <0.0001 Glycerol 3-phosphate 0.0010 Purine metabolism 15/50 AMP 0.0025 ADP-ribose 0.0057 ADP 0.0133 ATP 0.0001 GMP 0.0031 GTP 0.0005 Guanosine 0.0059 Hypoxanthine <0.0001 IMP 0.0001 Inosine 0.0244 PRPP <0.0001 Ribose 5-phosphate 0.0252 Uric acid 0.0052 Xanthine 0.0001 Xanthosine 0.0076 Cysteine metabolism 5/18 Cys 0.0009 Cystine <0.0001 Glutathione (GSSG)_divalent 0.0011 Homocysteine 0.0009 Ser 0.0029 Glutathione metabolism 4/16 5-Oxoproline 0.0026 Cys 0.0009 Glu 0.0067 Spermidine 0.0014 KEGG, Kyoto encyclopedia of genes and genomes; SE, standard error; AMP, adenosine monophosphate; ADP, adenosine diphosphate; ATP, adenosine triphosphate; GMP, guanosine monophosphate; GTP, guanosine triphosphate; IMP, inosine 5'-monophosphate; PRPP, phosphoribosyl pyrophosphate. (1) Compounds were extracted and listed if their changes were significant during postmortem aging of Japanese Black cattle Longissimus thoracis muscle (adjusted p<0.05, corresponding to false discovery rate <0.1). The relative value of each compound to 3MH is indicated. (2) Numbers of significantly changed compounds/total numbers of the analyzed compounds that belong to the KEGG pathway.
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|Author:||Muroya, Susumu; Oe, Mika; Ojima, Koichi; Watanabe, Akira|
|Publication:||Asian - Australasian Journal of Animal Sciences|
|Date:||Jul 26, 2019|
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