Characteristic Metabolic Changes of the Crust from Dry-Aged Beef Using 2D NMR Spectroscopy

Abstract

<jats:p>Two-dimensional quantitative nuclear magnetic resonance (2D qNMR)-based metabolomics was performed to understand characteristic metabolic profiles in different aging regimes (crust from dry-aged beef, inner edible flesh of dry-aged beef, and wet-aged beef striploin) over 4 weeks. Samples were extracted using 0.6 M perchlorate to acquire polar metabolites. Partial least squares-discriminant analysis showed a good cumulative explained variation (R2 = 0.967) and predictive ability (Q2 = 0.935). Metabolites of crust and aged beef (dry- and wet-aged beef) were separated in the first week and showed a completely different aspect in the second week via NMR-based multivariable analyses. Moreover, NMR-based multivariable analyses could be used to distinguish the method, degree, and doneness of beef aging. Among them, the crust showed more unique metabolic changes that accelerated proteolysis (total free amino acids and biogenic amines) and inosine 5′-monophosphate depletion than dry-aged beef and generated specific microbial catabolites (3-indoxyl sulfate) and γ-aminobutyric acid (GABA), while asparagine, glutamine, tryptophan, and glucose in the crust were maintained or decreased. Compared to the crust, dry-aged beef showed similar patterns of biogenic amines, as well as bioactive compounds and GABA, without a decrease in free amino acids and glucose. Based on these results, the crust allows the inner dry-aged beef to be aged similarly to wet-aged beef without microbial effects. Thus, 2D qNMR-based metabolomic techniques could provide complementary information about biochemical factors for beef aging.</jats:p>

Nuclear Magnetic Resonance (NMR)-Based Quantification on Flavor-Active and Bioactive Compounds and Application for Distinguishment of Chicken Breeds

“…Few ranked metabolites such as 2-aminoadipic acid and myo-inositol have rarely been reported in poultry meat. Additionally, metabolites undergo proteolytic enzyme cleavage and nucleotide degradation during the transition from muscle to meat and metabolic concentrations and end products can also change depending on the sex, species, and age ( Jayasena et al, 2014b ; Jung et al, 2013 ; Kim et al, 2020a ; Ryu and Kim, 2005 ), suggesting that further analysis may be necessary to identify critical metabolic properties in these animals. However, despite this, our data were in agreement with those reported in previous studies which suggested that the combination of qNMR and multivariate analysis could elucidate metabolic characteristics of samples in the absence of numerical quantification ( Kim et al., 2020a ; Kim et al, 2020b ; Winning et al, 2008 ).…”

“…Metabolites in the 1D 1 H NMR analysis were quantified using methods described by Kim et al (2019) . Prior to multivariate comparison, peak intensities in the 1 H- 13 C HSQC data were quantified using AMIX (Analysis of MIXtures software v3.9, Bruker Biospin GmbH) according to the methods described by Kim et al (2020a) .…”

“…While metabolomic analyses are generally used to explain changes in the physicochemical properties of various meat products and rely on various chemometric analyses ( Kim et al, 2020a ; Kim et al, 2020b ; Simmler et al, 2014 ), there has been an increase in the number of nuclear magnetic resonance (NMR)-based studies used to evaluate the metabolic profile of these meat samples without evaluating the chemical characteristics of the target metabolites ( Simmler et al, 2014 ). NMR-based analysis combined with multivariate analysis was used to understand and/or to elucidate metabolic changes of meat samples ( Kim et al, 2020a ; Kim et al, 2020b ).…”

“…While metabolomic analyses are generally used to explain changes in the physicochemical properties of various meat products and rely on various chemometric analyses ( Kim et al, 2020a ; Kim et al, 2020b ; Simmler et al, 2014 ), there has been an increase in the number of nuclear magnetic resonance (NMR)-based studies used to evaluate the metabolic profile of these meat samples without evaluating the chemical characteristics of the target metabolites ( Simmler et al, 2014 ). NMR-based analysis combined with multivariate analysis was used to understand and/or to elucidate metabolic changes of meat samples ( Kim et al, 2020a ; Kim et al, 2020b ). Several studies have used NMR-based analysis of meat samples to determine their metabolic profiles, and many of these profiles have been used to differentiate meat samples based on breed, age, geographical origin, and metabolic fingerprint as determined by one-dimensional 1 H NMR (1D 1 H NMR) analysis ( Beauclercq et al, 2016 ; Jung et al, 2010 ; Kodani et al, 2017 ; Straadt et al., 2014 ).…”

“…Several studies have used NMR-based analysis of meat samples to determine their metabolic profiles, and many of these profiles have been used to differentiate meat samples based on breed, age, geographical origin, and metabolic fingerprint as determined by one-dimensional 1 H NMR (1D 1 H NMR) analysis ( Beauclercq et al, 2016 ; Jung et al, 2010 ; Kodani et al, 2017 ; Straadt et al., 2014 ). However, 1D 1 H NMR analysis may not reveal all the differences in the metabolic profiles as there may be chronic overlap in the obtained data ( Kim et al, 2020a ). To overcome this limitation, many studies have opted to include two-dimensional NMR (2D NMR) to solve the issue of overlapping via dimensional expansion ( Kim et al, 2020b ).…”