The objective of this study was to investigate, by a metabolomic approach, the effects of chilled ageing conditioning at 4°C in lamb longissimus dorsi (LD) muscles on water-soluble flavour precursors. The results showed that the content of nucleotide degradation products significantly increased (
Lambs are important meat-producing animals worldwide [
Metabonomics is defined as the study of the endogenous metabolites present in an organism and the changes that occur in these compounds [
Although many studies have reported changes in flavour precursors during the postmortem aging, most reports determine flavour precursors mainly by the traditional chromatography method to evaluate the influence of aging on flavour precursors during the postmortem ageing [
A total of 8 LD muscles (c.1.5 kg each) obtained from approximately 6-month-old Tan sheep were bought from a commercial meat company (Yanchi, Yinchuan, China). The samples were vacuum-packed and transferred in portable coolers (4°C) to the laboratory. The samples were stored at 4°C and a relative humidity of 80% in polystyrene trays sealed with polyethylene films for 8 days. Sampling consisted of cutting a 20 cm × 20 cm slice from the whole LD using an alcohol-sterilized knife on day 0, 4, and 8. Samples (
The experimental protocols for sample derivation followed our previously published work with minor modifications [
Samples were analyzed by GC × GC-TOF/MS based on the reports of Peng et al. [
Data on GCxGC-TOF/MS were transferred into the SIMCA software package (14.0, Umetrics, Umeå, Sweden). Principle component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) were performed to visualize the metabolic differences among three groups. The Hotelling’s T2 region is shown as an ellipse in score plots of the models, which defines the 95% confidence interval of the modelled variation. Variable importance in the projection (VIP) ranks the overall contribution of each variable to the OPLS-DA model, and the variables with “VIP > 1.00” and “
Differential metabolites from GC × GC-TOF/MS were further validated by searching the online databases including the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the
The effect of ageing on flavour precursors was analysed by ANOVA using SPSS 19.0 statistical software (SPSS Inc., Chicago, IL, USA.).
The Chroma TOF4.3X software (LECO) and LECO-Fiehn Rtx5 database were used to analyze the data. For all group samples, the missing value of the original data was simulated by filling half of the minimum value and noise removal was used by an interquartile range to filter data. The data were normalized to the total peak area of each sample and multiplied by 10000, and the peaks from the same metabolite were combined. The datasets consisted of 102 variables obtained from GC × GC-TOF/MS analyses after applying the above-described quality assurance criteria.
These datasets were used to build PCA and OPLS-DA in order to visualize group trends during meat chilled ageing. The PCA score plot (Figures
PCA, corresponding validation plots of OPLS-DA, and OPLS-DA score plots derived from the GC × GC-TOF/MS between day 0 and day 4 and day 4 and day 8 during chilled ageing. Day 0: triangles; day 4: circles; day 8: squares.
All the samples in the score plots of PCA and OPLS-DA were inside the 95% Hotelling T2 ellipse. Clear separation and discrimination indicated that the OPLS-DA model can be used to identify the difference between groups.
The reproducible ionization method used for GC × GC-TOF/MS qualitative identification of compounds is less complicated due to the availability of universal mass spectral libraries. Based on the NIST 11 database and Fiehn metabolomics library, the majority of the peaks were endogenous metabolites and some of these peaks may be attributed to the derivatives of byproducts. After screening with “VIP > 1.00,” “
Identification of significantly different metabolites in lamb samples using GC × GC-TOF/.
Metabolite name | RT | Mass | Similarity | VIP |
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FC |
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Nicotinoyl-glycine | 7.28 | 207 | 912 | 1.26 | 0.05 | 1.34 |
Pyruvic acid | 7.46 | 174 | 885 | 1.56 | 0.04 | 0.64 |
Hydroxylamine | 8.29 | 146 | 870 | 1.74 | <0.01 | 1.21 |
3-Hydroxybutyric acid | 8.64 | 117 | 925 | 1.45 | 0.02 | 0.70 |
Glycerol | 9.91 | 205 | 933 | 1.36 | 0.04 | 1.26 |
N-Epsilon-acetyl-L-lysine | 10.13 | 200 | 912 | 1.75 | <0.01 | 0.75 |
Succinic acid | 10.49 | 247 | 899 | 1.80 | <0.01 | 1.49 |
D-Glyceric acid | 10.62 | 189 | 917 | 2.26 | <0.01 | 2.36 |
Methionine | 13.32 | 176 | 797 | 1.30 | 0.04 | 1.49 |
Glucose-1-phosphate | 16.95 | 217 | 900 | 1.26 | 0.05 | 1.20 |
Tyrosine | 17.21 | 226 | 904 | 1.33 | 0.04 | 0.73 |
Citric acid | 17.79 | 273 | 910 | 1.15 | 0.05 | 1.51 |
Hypoxanthine | 18.05 | 265 | 797 | 1.07 | <0.01 | 1.93 |
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22.91 | 265 | 912 | 1.35 | 0.01 | 15.20 |
Fructose-6-phosphate | 24.03 | 459 | 914 | 1.86 | <0.01 | 1.70 |
Inosine | 26.03 | 230 | 913 | 1.40 | 0.04 | 1.36 |
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Lactic acid | 7.40 | 117 | 825 | 1.87 | <0.01 | 0.94 |
Maleamate | 7.89 | 151 | 797 | 1.56 | <0.01 | 0.87 |
Methylmalonic acid | 8.37 | 218 | 721 | 1.86 | <0.01 | 0.86 |
Valine | 9.31 | 144 | 918 | 1.42 | 0.02 | 1.52 |
N-Epsilon-acetyl-L-lysine | 10.13 | 200 | 912 | 1.56 | 0.01 | 0.78 |
Isoleucine | 10.25 | 158 | 908 | 1.41 | 0.03 | 1.56 |
D-Glyceric acid | 10.62 | 189 | 917 | 1.28 | 0.04 | 1.42 |
Threonine | 11.36 | 219 | 904 | 1.38 | 0.03 | 1.33 |
N-Alpha-acetyl-L-ornithine | 12.49 | 154 | 912 | 1.42 | 0.03 | 0.89 |
Aminomalonic acid | 12.54 | 218 | 778 | 1.40 | 0.03 | 1.34 |
Aspartate | 13.21 | 232 | 701 | 1.62 | 0.02 | 1.90 |
Methionine | 13.32 | 176 | 797 | 1.95 | <0.01 | 2.66 |
Phenylalanine | 14.97 | 218 | 702 | 1.53 | 0.02 | 2.03 |
Tyrosine | 17.21 | 226 | 904 | 2.03 | <0.01 | 1.82 |
O-Phosphorylethanolamine | 17.23 | 73 | 766 | 1.59 | 0.01 | 1.28 |
Hypoxanthine | 18.05 | 265 | 797 | 1.44 | 0.03 | 1.14 |
N-Acetyl-beta-D-mannosamine | 21.98 | 202 | 912 | 1.99 | <0.01 | 4.66 |
Inosine | 26.03 | 230 | 913 | 2.14 | <0.01 | 1.51 |
RT = retention time; FC = fold change. The values of FC are mean value of peak area obtained from day 4 group/mean value of peak area obtained from day 0 group, day 8 group/day 4 group, respectively.
Nucleotide degradation compounds produced by ATP breakdown are associated with flavour formation in pork [
Effects of chilled ageing conditioning on water-soluble flavour precursors.
Metabolite name | Storage days | ||
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0 d | 4 d | 8 d | |
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Inosine | 38.99 ± 13.66a | 53.17 ± 10.97b | 80.03 ± 5.57c |
Hypoxanthine | 5.41 ± 4.22a | 10.43 ± 1.04b | 11.91 ± 1.30b |
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Glucose-1-phosphate | 14.32 ± 2.03a | 17.16 ± 3.08a | 16.95 ± 2.82a |
Fructose-6-phosphate | 4.34 ± 2.17a | 7.38 ± 0.83b | 6.75 ± 2.07b |
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Succinic acid | 1.90 ± 0.63a | 2.83 ± 0.32b | 3.53 ± 0.87c |
3-Hydroxybutyric acid | 10.94 ± 2.94a | 7.61 ± 1.83b | 6.51 ± 1.11b |
Pyruvic acid | 14.82 ± 3.21a | 9.42 ± 5.89b | 6.42 ± 1.92b |
Citric acid | 9.49 ± 3.69a | 14.35 ± 5.12a | 13.71 ± 4.88a |
Lactic acid | 3159.49 ± 94.16a | 3121.1 ± 88.72a | 2918.62 ± 115.28b |
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N-Epsilon-acetyl-L-lysine | 1.69 ± 0.25a | 1.27 ± 0.24b | 0.99 ± 0.12c |
Methionine | 0.87 ± 0.20a | 1.30 ± 0.51a | 3.46 ± 1.69b |
Nicotinoyl-glycine | 27.69 ± 1.77a | 37.11 ± 12.17b | 46.27 ± 3.33c |
Tyrosine | 1.32 ± 0.40a | 0.96 ± 0.23a | 1.74 ± 0.41b |
Aspartate | 0.78 ± 0.36a | 2.54 ± 1.44b | 4.83 ± 2.04c |
Phenylalanine | 2.83 ± 0.61a | 3.50 ± 1.50a | 7.12 ± 3.66b |
Valine | 18.28 ± 2.78a | 21.64 ± 6.27a | 32.96 ± 11.06b |
N-Alpha-acetyl-L-ornithine | 51.36 ± 4.07a | 52.09 ± 5.31a | 46.45 ± 3.56b |
Isoleucine | 10.87 ± 1.82a | 13.85 ± 4.52a | 21.66 ± 8.06b |
Threonine | 5.60 ± 1.43a | 5.71 ± 1.42a | 7.61 ± 1.78b |
The values followed by different superscript letters were significantly different (
The content of fructose-6-phosphate significantly increased (
The contents of 3-hydroxybutiric acid and pyruvic acid significantly decreased from day 0 to day 4 (
Free amino acids (FAAs) play important roles in the formation of volatile aromatics and taste characteristics [
The annotated metabolites in the datasets obtained from GC × GC-TOF/MS were combined into a new data set (34 significantly different metabolites in total, in which there were 16 and 18 metabolites from day 0 to day 4 and day 4 to day 8, respectively). According to the KEGG database, the TCA cycle and biosynthesis of alkaloids derived from histidine and purine were the key metabolic pathways in lamb refrigerated at 4°C from day 0 to day 4, whereas biosynthesis of amino acids was important from day 4 to day 8.
Based on the KEGG maps, three integrated metabolic pathways are associated with each other through several metabolites (Figure
Kyoto Encyclopedia of Genes and Genomes pathways are manually linked together. The map illustrates significantly different metabolites in meat samples between two compared groups and three key metabolic pathways including the TCA cycle, biosynthesis of alkaloids derived from histidine and purine, and biosynthesis of amino acids.
The integrated metabolic pathways contain interactive networks, as well as related metabolites, and provide information during chilled ageing. This information extends beyond metabolic relevance and has effects as demonstrated in the pathways and network analyses applied in the metabolomics analyses [
Chromatography methods were used to investigate the metabolite profiles in lamb longissimus dorsi muscles stored at 4°C for 0, 4, and 8 days to investigate the potential impact of chilled ageing conditioning on water-soluble flavour precursors. Flavour-related metabolites, such as nucleotide degradation products, glycolytic compounds, organic acids, and free amino acids, were evaluated, and three key metabolic pathways were identified during aging. The results showed that flavour precursors were more abundant after completion of the TCA cycle, through the biosynthesis of alkaloids derived from histidine and purine, and through the biosynthesis of amino acids that occurred during the prolonged ageing of chilled lamb. Therefore, the results of this study may provide a strong evidence for further investigations of the effect and mechanism of ageing on the flavour of meat products.
All the data in this article are true and valid, and the authors and affiliated agency allow to disclose them to the public; the primary data used to support the finding of this study are available from the corresponding author or co-first author upon request.
The authors declare that they have no conflicts of interest.
Liqin You performed the experiments, interpreted the results, and drafted the manuscript. Ruiming Luo designed the study.
This study was supported by grants from the Innovation Project of Ningxia University in China (No. ZKZD2017007).