NMR-Based Metabolomic Analysis For The Effects Of α-Ketoglutarate Supplementation On C2C12 Myoblasts in Different Energy States

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1. Introduction 

The skeletal muscle is the largest organ in the human body and maintains normal life activities. Prolonged exercise training or pathological processes of diseases induce muscle damage or insufficient muscle energy supply, at this time, restoration of muscle strength and function is particularly important. Various nutritional supplements have been employed to promote skeletal muscle hypertrophy and enhance sports performance [1]. As the intersection of the organic carbon and nitrogen metabolism and simultaneously a critical intermediate in the TCA cycle, α-Ketoglutarate (AKG) has shown pleiotropic effects for improving muscle performance in clinical and animal experiments [2–9]. For example, AKG can reduce intestinal mucosal damage [8] and inflflammation [9], attenuate the development of colorectal cancer [4] and liver fibrosis [5], promote growth [6], and reduce morbidity and delay aging [7]. Previous works have demonstrated that AKG supplementation can alleviate muscle loss by parenteral administration in a trauma model of patients undergoing total hip replacement [2], and promote muscle hypertrophy and protein synthesis through Akt/mTOR signaling pathways [10,11]. In the case of Duchenne muscular dystrophy, AKG supplementation can prevent muscle atrophy and dysfunction through the PHD3/ADRB2-mediated pathway [12]. Our previous work also showed that AKG supplementation can profoundly facilitate the proliferation of C2C12 myoblasts, and alleviate the atrophy of C2C12 myotubes cultured in a no-glucose medium [13]. Given that glucose is the main source of energy to maintain normal physiological functions of skeletal muscle, the effects of AKG supplementation for improving muscle performance are greatly dependent on the glucose level in skeletal muscle. The differences of the AKG-induced effects in skeletal muscle between different energy states are unclear.

AKG participates in the synthesis of amino acids, vitamins, and organic acids and energy metabolism in the body, which involves the conversion of AKG into glutamate by glutamate dehydrogenase, and the subsequent amidation of glutamate with ammonia by glutamine synthetase. AKG provides the energy for cell growth via the TCA cycle and oxidative phosphorylation and promotes cell metabolism and signaling by interacting with its receptor OXGR (a G protein-coupled receptor) on the cell membrane [14,15]. Moreover, AKG can regulate mitochondrial oxidative metabolism and promote the permissive epigenetic state by mediating early embryonic cell state transition and germ cell development [16]. Furthermore, exercise-induced AKG can stimulate its receptor OXGR1 in the adrenal glands to control thermogenesis and the breakdown of triglycerides in adipose tissue and produce beneficial effects on metabolisms [17]. 

However, few studies have been performed to reveal AKG-induced metabolic changes of skeletal muscle in different energy states and the underlying metabolic mechanisms. Recently, metabolomic analysis has been employed to systematically clarify the molecular mechanisms underlying the beneficial effects of nutritional supplementation. Alternations of metabolites acting as the downstream products of gene transcription may reflect overall metabolic changes intuitively. As particularly suitable techniques for quantitatively detecting alterations of metabolite levels in biofluids, tissues, and cells, high-resolution, 1H nuclear magnetic resonance (NMR) spectroscopy has been extensively applied in metabolomic analyses. Signifificantly, NMR-based metabolomic profiling has several advantages such as high reproducibility, quantitative measurement without prejudice, and convenient sample preparation [18,19]. Previously, we performed NMR-based metabolomic analyses for elucidating both the effects of creatine supplementation on C2C12 myoblasts [20], and the effects of alanyl-glutamine supplementation on myoblasts injured by energy deprivation [21]. 

2. Results 

2.1. Proliferation and Differentiation of C2C12 Myoblasts with AKG Supplementation 

C2C12 myoblast cells cultured in a normal growth medium with and without AKG supplementation were grouped as Nor-A and Nor, whereas those in low-glucose growth medium with or without AKG supplementation were grouped as Low-A and Low. Consistent with the previous study [10], Nor-A cells with AKG supplementation at a concentration of 2 mm exhibited a signifificantly enhanced cell viability relative to Nor cells (Figure S1).

Therefore, the AKG concentration of 2 mm was used in the experiments for assessing AKG-induced changes in the proliferation and differentiation of myoblasts. Compared with Nor cells, Low cells showed a profoundly declined proliferation rate due to energy deficiency (Figure 1A). Even though AKG supplementation did not cause signifificantly different morphology of myoblasts in the two energy states, it not only enhanced the proliferation rate of Low cells cultured in a low-glucose medium but also enhanced that of Nor cells cultured in a normal medium in accordance with previous studies [10,12]. Cell numbers per a given area were counted for the four groups of myoblasts (n = 4 for the group): Nor, 563.8 ± 10.4; Nor-A, 624.0 ± 10.8; Low, 493.8 ± 14.5; LowA, 547.0 ± 11.7 (Figure 1B). It is worth noting that Low-A cells did not display statistically different cell numbers from Nor cells, indicating that AKG supplementation could recover cell numbers for the myoblasts under low-glucose culture conditions (Figure 1B).

Figure 1, Proliferation and differentiation abilities of C2C12 myoblasts under the conditions of normal culture and low. glucose culture. (A) Myoblasts morphologies. (B) Cell numbers corresponding to panel A (n = 4). (C) Cell viabilities relative to Nor cells analyzed by MTS cell proliferation assay (n = 5). (D) MyoD1 expressions in myoblasts analyzed by western blot. The anti-GAPDH antibody was used to standardize the amount of protein in each lane. (E) Statistical analysis corresponding to the panels (D) (n = 4). * p < 0.05,** p < 0.01, *** p < 0.001, **** p < 0.0001.

In addition, the MTS assay was performed to quantitatively compare the proliferation rates of the four groups of cells (Figure 1C). Low cells had a distinctly decreased proliferation rate compared with Nor cells, indicating that the low-glucose medium disfavored the proliferation of cells. Significantly, AKG supplementation enhanced the proliferation rates of Nor-A and Low-A cells relative to Nor and Low cells, respectively. Note that Low-A cells showed a proliferation ability lower than Nor cells, implying that AKG supplementation only partially restored the proliferation of cells cultured in a low-glucose medium

.The expression of the myogenic differentiation 1 (MyoD1) protein is usually used to characterize the differentiation ability of cells. We, thus, quantitatively compared the expressions of MyoD1 between the four groups of cells (Figure 1D). Low cells showed a profoundly declined differentiation ability compared with Nor cells. Significantly, AKGsupplementation up-regulated differentiation abilities of cells cultured both in normal medium and in low-glucose medium, as indicated by about a 30% increase of MyoD1expression in Nor-A and Low-A cells. Notably, Low-A cells did not display statistically significantly different MyoD1 expression from Nor cells, implying the high efficiency of AKG supplementation for restoring the differentiation ability of cells cultured in an alow-glucose medium.

Furthermore, we analyzed myotube differentiation abilities for the four groups of C2C12 myoblasts. Myotubes were formed through the fusion of myoblasts cultured in normal and low-glucose differentiation media with or without AKG supplementationFigure S3). Morphologies of the C2C12 myotubes showed that the low-glucose culture impaired the myotube differentiation ability of cells, and AKG supplementation could promote myotube differentiation of myoblasts cultured both in a normal medium and in an ow-glucose medium.

2.2. NMR Spectra ofAqueous Extracts of C2C12 Myoblasts

Typical 850 MHz 1H NMR spectra were recorded on aqueous extracts derived from the Nor, Nor-A, Low, and Low-A groups of C2C12 myoblasts (Figure 2A). A total of34 metabolites were assigned and summarized in Table S1. The resonance assignments of the metabolites were confirmed by using 2D 1H-13C HSOC and 1H-H TOCSY spectra(Figures S4 and S5). The visual inspection of the NMR spectra indicated that culturing myoblasts with AKG supplementation resulted in significant accumulations of intracellularAKG in Nor-A and Low-A cells (Figure 2B).

Figure 2, Average 850 MHz lH nuclear magnetic resonance (NMR) spectra recorded on aqueous extracts derived from the Nor, Nor-A, Low, and Low-A groups of C2C12 myoblasts. (A) Comparison of the average NMR spectra of the four groups. The vertical scales were kept constant in all the lH NMR spectra. The water region (4.7-5.2 ppm) was removed(B) Local amplified regions of a-Ketoglutarate (AKG) peaks. Blue/green/yellow/red line: spectral regions from the Nor/Nor-A/Low/Low-A groups. AKG, a-ketoglutarate; PC, O-phosphocholine; GPC, sn-glycero-3-phosphocholineUDP-glucose, Uridine diphosphate glucose: CTP, sn-glycero-3-phosphocholine; NAD+, nicotinamide adenine dinucleotide AXP adenine mono /di /triphosphate.

2.3. Multivariate Data Analysis for Exploring Cellular Metabolic Profiles

We further performed multivariate data analysis on the NMR spectral data for metabolic profiling of the four groups of C2C12 myoblasts. We first established three unsupervised PCA models with the first two components (PC1, PC2) to overview the grouping trends and reveal metabolic differences between the groups of myoblasts. The ThePCA score plots show that the metabolic profile of cells cultured in a low-glucose medium was distinctly distinguished from that cultured in a normal medium (Figure 3A), and AKCsupplementation significantly changed the metabolic patterns of the cells cultured both in a normal medium and in low-glucose medium (Figure 3B,C). However, the metabolic difference between the Nor-A and Nor groups was larger than that between the Low-A and Low groups, implying that the effects of AKG supplementation on the metabolic profile of myoblasts are greatly dependent on the energy state of cells.

Figure 3. Multivariate analyses for 'HNMR spectra were recorded on aqueous extracts derived from C2C12 myoblasts of the Nor, Nor-A, Low, and Low-A groups. (A-C) PCA scores plots of the Low and Nor groups, the Low-A and Low groups the Nor-A and Nor groups; (D-F) OPIS-DA scores plots of the Low and Nor groups (R2: 0.999, 02: 0.996), the Low-Aand Low groups (R2: 0.918: 02: 0.761), the Nor-A and Nor groups (R2: 0.927: 02: 0.838). The ellipses indicate the 95%confidence limit.

Furthermore, we established three supervised OPLS-DA models to illustrate metabolic separations between the four groups of myoblasts (Figure 3D-F). As expected, the OPLSDA models maximized the metabolic distinctions between the four groups by reserving the correlated orthogonal variable information and filtering out uncorrelated orthogonal variable information. Furthermore, we performed random permutation tests (n = 200) to evaluate the reliabilities of the OPLS-DA models (Figure S6), which indicate the validities of the established OPLS-DA models.

2.4. Identifications of Differential and Important Metabolites

To quantitatively compare metabolite levels between the four groups of C2C12 myoblasts, we calculated the relative levels of the identified metabolites based on their relative integrals (Table S2). Dramatically AKG supplementation increased intracellularAKG levels in the Nor-A and Low-A groups but did not significantly change those in the Nor and Low group. We conducted Student's t-test to identify differential metabolites with a criterion of p < 0.05 (Figure 4). The comparison of Nor vs. Low identified 29 differential metabolites (Figure 4A), including 18 enhanced metabolites (leucine, isoleucine, valine, acetate, glutamate, glutamine, methionine, aspartate, lysine, creatine, PC (O-phosphocholine)taurine, tyrosine, phenylalanine, histidine, NAD+, formate, AXP), and 11 declined Metabo. lites (glutathione, pyroglutamate, phosphocreatine, beta-alanine, GPC, glucose, glycine, acetate, threonine, GTP, UDP-glucose). The comparison of Low-A vs. Low-identified differential metabolites (Figure 4B), including 7 increased metabolites (ethanol, AKGbeta-alanine, PC, taurine, glycine, and GTP) and 3 decreased metabolites (glutamine, lysine and myoinositol). The comparison of Nor-A vs. Nor identified 18 differential metabolites(Figure 4C), including 6 up-regulated metabolites (AKG, pyroglutamate, glutamine, lysine, glucose, lactate), and 12 down-regulated metabolites (alanine, acetate, glutathione methionine, phosphocreatine, PC, myoinositol, glycine, threonine, GTP, UDP-glucose, and AXP). 

Figure 4. Relative intensities of differential metabolites were identified from pairwise comparisons between the four groups of C2C12 myoblasts. (A) Low vs. Nor; (B) Low-A vs. Low; (C) Nor-A vs. Nor. * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001.n = 9 for each group. 

Furthermore, we used the OPLS-DA models to identify important metabolites with a criterion of VIP > 1 (Figure 5). Totally, 12, 10, and 10 important metabolites were identified from the OPLS-DA models of Nor-A vs. Nor, Nor vs. Low, Low-A vs. Low.

Figure 5. VIP scores of important metabolites were identified from pairwise comparisons between the four groups of C2C12myoblasts. (A) Low vs. Nor; (B) Low-A vs. Low; (C) Nor-A vs. Nor. Red/ Blue font denotes increased/decreased levels of the metabolite.

The combination of the identified important metabolites and differential metabolites gave characteristic metabolites (Table 1). The pairwise comparisons of Low vs. Nor, Low-A vs. Low, and Nor-A vs. Nor identified 10, 6, and 10 characteristic metabolites, respectively, indicating that the effects of AKG supplementation on myoblasts were closely associated with the energy state of cells.

2.5. Identifification of Signifificantly Altered Metabolic 

Pathways We performed metabolic pathway analysis to identify signifificantly altered metabolic pathways (signifificant pathways) based on the levels of metabolites identified from the pairwise comparisons between the four groups of C1C12 myoblasts (Figure S7; Table 2 and Table S3). The analysis of Nor vs. Low identified 11 signifificant pathways: (1) Alanine, aspartate, and glutamate metabolism; (2) Glycine, serine, and threonine metabolism; (3) Glutathione metabolism; (4) D-Glutamine and D-glutamate metabolism; (5) Starch and sucrose metabolism; (6) beta-Alanine metabolism; (7) Taurine and hypotaurine metabolism; (8) Phenylalanine metabolism; (9) Phenylalanine, tyrosine and tryptophan biosynthesis; (10) Nicotinate and nicotinamide metabolism; (11) Histidine metabolism. This significant pathway were associated with energy metabolism, oxidative stress, and TCA cycle anaplerotic flflux. 

The analysis of Nor-A vs. Nor only identified the first five signifificant pathways 1–5 excluding the other six pathways 6–11. Differently, the analysis of Low-A vs. Low only identified six signifificant pathways: the first four pathways 1–4 shared by the comparisons of Low vs. Nor, Nor-A vs. Nor; two pathways 6–7 shared by the comparison of Low vs. Nor. Note that AKG supplementation did not signifificantly alter pathway 5 (Starch and sucrose metabolism) in cells cultured in a low-glucose medium, but interfered with two other pathways (beta-Alanine metabolism and taurine and hypotaurine metabolism). To visualize AKG-induced changes in characteristic metabolites, we projected these metabolites onto a metabolic map based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Figure 6). KEGG has been extensively used as one of the main data resources to reconstruct metabolic networks and highlights signifificant metabolic pathways. Both the changed characteristic metabolites and signifificantly altered metabolic pathways provide new insights into the molecular mechanisms underlying the effects of AKG supplementation on C2C12 myoblasts.