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Review

Potential Therapeutic Mechanism of Traditional Chinese Medicine on Diabetes in Rodents: A Review from an NMR-Based Metabolomics Perspective

by
Yinli Huang
1,†,
Jiahui Lu
2,†,
Qihui Zhao
2,†,
Junli Chen
2,
Wei Dong
1,
Minjie Lin
1 and
Hong Zheng
1,2,*
1
Department of Endocrinology, Pingyang Affiliated Hospital of Wenzhou Medical University, Wenzhou 325400, China
2
School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Molecules 2022, 27(16), 5109; https://doi.org/10.3390/molecules27165109
Submission received: 28 July 2022 / Revised: 5 August 2022 / Accepted: 8 August 2022 / Published: 11 August 2022
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Abstract

:
Traditional Chinese medicine (TCM) has been used to treat diabetes for a long time, but its application has not been widely accepted due to unstandardized product quality and complex pharmacological mechanisms. The modernization of TCM is crucial for its further development, and in recent years the metabolomics technique has largely driven its modernization. This review focuses on the application of NMR-based metabolomics in diabetic therapy using TCM. We identified a series of metabolic pathways that altered significantly after TCM treatment, providing a better understanding of the metabolic mechanisms of TCM for diabetes care.

1. Introduction

Diabetes is a common metabolic disease characterized by hyperglycemia owing to insulin secretion deficiency for type 1 diabetes (T1D) or insulin resistance for type 2 diabetes (T2D), which has become a global health problem [1]. In 2021, approximately 537 million adults between 20 and 79 years of age suffered from diabetes worldwide, and this number is projected to increase to 783 million by 2045 [1]. More than three out of every four diabetic patients were living in low- and middle-income countries. Moreover, diabetes caused 6.7 million deaths in 2021 [1]. Currently, T2D can be treated by a number of different medications such as metformin, sulfonylureas, glinides, thiazolidinediones, DPP-4 inhibitors, GLP-1 receptor agonists and SGLT2 inhibitors. However, there are fewer treatment methods for T1D, so all T1D patients require daily insulin injections to maintain normal blood glucose levels. Therefore, there is an urgent need to discover novel therapeutic strategies, especially for T1D. Traditional Chinese medicine (TCM) is a system of healing that originated thousands of years ago that has also been used to treat diabetes for a long time [2,3,4]. However, several problems including unstandardized product quality and complex pharmacological mechanisms have restricted its wide acceptance and application [5]. Therefore, TCM modernization is crucial for its further development [6]. This review aims to provide the currently available information on potential metabolic mechanisms of TCM on the management and treatment of diabetes for diabetic patients, pharmacologists, drug developers and endocrinologists.

2. Metabolomics as a Powerful Tool for the Modernization of TCM

In recent years, omics technologies have largely driven the modernization of TCM [7]. Metabolomics is the apogee of the omics cascade that attempts to analyze a comprehensive set of metabolites in biological samples and explore changes in metabolic pathways related to genomic and proteomic perturbations [8]. TCM possesses several typical characteristics such as being multi-component, multi-target and multi-pathway, resulting in great difficulty when attempting to explore its pharmacological mechanisms [9]. Notably, metabolomics, especially untargeted metabolomics, can detect a global set of metabolites without bias in living organisms after TCM treatment, which provides the possibility of exploring the metabolic mechanisms of TCM in disease prevention and treatment [10]. Currently, two analytical platforms are mainly employed to acquire metabolomic data, including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy [11]. These techniques have their advantages and disadvantages, as listed in Table 1. For example, the MS-based method has a higher sensitivity and more metabolites can be detected even using a minimal sample size. Moreover, the MS-based method is also a flexible technique, which can couple liquid or gas chromatography to achieve the selection and separation of different metabolites. However, it also has a number of disadvantages including low reproducibility, complex sample preparation, non-recyclable samples, relatively poor quantitative analysis and difficult metabolite identification. The NMR-based method possesses several strengths, such as high reproducibility, simple sample preparation, non-destructive, fast analysis, good quantitative analysis and straightforward identification, although this method cannot analyze non-protonated metabolites. In addition, compared with the MS-based method, NMR analysis needs a larger sample size and has a relatively low sensitivity. Figure 1 shows the typical 1H NMR-based metabolomics profiling obtained from serum, liver and feces samples in healthy mice [12], and the detailed metabolite assignments are listed in Table 2, where a series of metabolites can be identified involving amino acid metabolism, energy metabolism, fatty acid metabolism, ketone body metabolism and others. NMR metabolomics profiling is tissue-specific due to different metabolite compositions. Therefore, different analytical sequences have been developed for NMR analysis. For example, a Carr–Purcell–Meiboom–Gill (CPMG) sequence is usually conducted for serum samples in order to minimize the line-broadening effect of blood macromolecules including proteins and lipids. However, for samples with a high water content such as urine, a standard single-pulse sequence (ZGPR) can be used to reduce the impact of water signals on metabolomics profiling. In addition, there is a greater likelihood of overlapping peaks from multiple metabolites with NMR analysis, resulting in difficult identification and quantification. One way to solve this problem is to perform NMR experiments under higher magnetic fields. Moreover, 2D J-resolved spectroscopy and spectral deconvolution have also been used to address the peak overlap of metabolites.
In this review, we focus on the application of NMR metabolomics in diabetes therapy using TCM, providing a better understanding of the metabolic mechanisms of TCM. Figure 2 illustrates the flowchart of the NMR-based metabolomics method for elucidating the metabolic mechanisms of TCM for diabetes treatment. In brief, diabetic rodent models are treated with TCM after a period of time and then biological samples are collected for NMR-based metabolomics analysis, such as serum, plasma, urine, feces and tissue samples. Metabolomics data are subjected to multivariate and univariate analyses to identify important metabolites that are significantly altered after TCM treatment. Finally, metabolic pathway analysis is performed to elucidate potential therapeutic mechanisms of TCM for diabetes.

3. Potential Metabolic Mechanisms of TCM on Diabetes Care

A systematic search of the PubMed, SCOPUS and Web of Science databases was conducted for relevant studies from 2012 to 2022. Different possible combinations of the following search terms were used: “traditional Chinese medicine”, “Chinese medicine”, “TCM”, “diabetes”, “diabetic”, “nuclear magnetic spectroscopy”, “NMR”, “metabolomic”, “metabonomic” and “metabolic”. We independently searched the literature to minimize bias and firstly screened studies according to titles and abstracts. Inclusion and exclusion criteria were discussed and defined for literature selection. The following inclusion criteria were used: Firstly, studies should be related to diabetes, NMR-based metabolomic analysis, TCM treatment and rodents. Secondly, studies need to measure a specific metabolite level and compare the metabolic differences in diabetes with and without TCM treatment. The exclusion criteria included drug structure analysis, in vitro studies, biomarker discovery or pathological studies. Moreover, reviews, meta-analyses, abstracts and case reports were also excluded. The detailed procedure of literature selection is illustrated in Figure 3, and the information of 25references included in this review are listed in Table 3, of which there are 17 references on T2D and 8 references on T1D. In animal studies, T1D models were developed by streptozotocin or alloxan induction, but lacked non-obese diabetic (NOD) mouse models. Several T2D animal models were used including high-fat diet-fed and low-dose streptozotocin-treated models, KKay mice and Zucker diabetic rats, whereas the use of db/db mice as a widely used preclinical model of T2D also needs to be considered for future studies.
Subsequently, metabolic pathway analysis was carried out on the basis of the metabolites included in this review by the MetaboAnalyst 5.0 [38]. The result of pathway analysis was presented according to −log (p) values from the pathway enrichment analysis and pathway impact values from the pathway topology analysis. A metabolic pathway with high values of these two parameters was identified as the important pathway in the response to TCM treatment, as shown in Figure 4.

3.1. Amino Acid Metabolism

Amino acid metabolism has been reported to play a key role in insulin secretion and thereby affect the onset and development of diabetes [39]. In this review, most studies reported a reduced amino acid metabolism in diabetic rodents, including glycine, serine and threonine metabolism (Figure 5), alanine, aspartate and glutamate metabolism (Figure 6) and arginine and proline metabolism (Figure 7). We found that the changes in these amino acids might be associated with the regulation of insulin signaling. For example, Wang-Sattler et al. revealed that a lower glycine level could be a predictor for impaired glucose tolerance and T2D [40]. Glycine can increase insulin sensitivity by suppressing oxidative stress in sucrose-fed rats [41]. In addition, serine/threonine phosphorylation plays an essential role in the regulation of pancreatic β-cell growth/survival and insulin signaling [42,43]. Brennan et al. revealed that alanine increased insulin secretion via the physiological regulation of β-cell electrical activity [44]. Alanine can oxidize to glutamate in β-cells [44], and glutamate serves as an intracellular messenger in the regulation of insulin secretion in response to glucose [45]. In a supplementation trial, glutamate has also been evidenced to improve glucose metabolism by increasing insulin secretion in healthy males [46]. Moreover, Gheni et al. elucidated that glutamate derived from the malate-aspartate shuttle is a key signal between glucose metabolism and cAMP action in incretin-induced insulin secretion [47]. Monti et al. conducted a human intervention study for 18 months and found that arginine supplementation significantly increased regression to normal glucose tolerance, although there was no significant effect on the incidence of diabetes [48]. In addition, arginine has also been reported to perform an essential role in pancreatic β-cell functional integrity [49] and improve insulin sensitivity [50]. In this review, we found that the metabolism of these aminoacids was up-regulated after TCM treatment in most studies, suggesting that TCM may improve insulin action and glycemic control via the regulation of amino acid metabolism.

3.2. Energy Metabolism

In this review, decreases in pyruvate metabolism (Figure 8) and the TCA cycle (Figure 9) in diabetic rodents were reported by most studies, which confirm that mitochondrial dysfunction occurs in diabetes. Mitochondrial damage has been associated with pancreatic β-cell dysfunction and insulin resistance, resulting in the abnormal glucose metabolism of diabetes [51,52,53,54]. However, notably, treatment with TCM can up-regulate these two metabolic pathways in diabetic rodents, suggesting that TCM may alleviate the mitochondrial dysfunction induced by diabetes. Moreover, glucose as a main source for energy production can also be converted to pyruvate, and then pyruvate oxidized to CO2 and H2O via the tricarboxylic acid cycle (TCA cycle). Therefore, increased energy metabolism boosts glucose depletion, which might be a possible mechanism of the glucose-lowering effect of TCM treatment.

3.3. Synthesis and Degradation of Ketone Bodies

We also identified significant changes in the synthesis and degradation of ketone bodies in response to TCM treatment (Figure 4). Ketone bodies are derived from fatty acid metabolism and mostly generated in the liver as an alternative source of energy [55]. Their homeostasis is maintained by the balance of synthesis (ketogenesis) and degradation (ketolysis) of ketone bodies. Ketogenesis is the process of converting fatty acids into two major ketonebodies, acetoacetate and β-hydroxybutyrate [56]. However, changes in acetoacetate and β-hydroxybutyrate in diabetic rodents after TCM treatment were inconsistent based on the current findings using NMR metabolomics (Figure 10). The levels of ketone bodies can also be regulated by insulin; for example, an elevated insulin level promotes ketone body clearance by increasing their catabolic pathway in extrahepatic tissues [57]. Thus, enhanced ketone body production was observed in diabetes patients owing to insulin insufficiency or resistance [58]. Notably, the level of acetone in the urine and serum was significantly reduced in diabetic rodents but increased after TCM treatment in all studies included in this review (Figure 10), suggesting an enhanced ketone body degradation since acetone is produced via the decarboxylation of acetoacetate [56]. Nevertheless, the causal relationship between ketone body degradation and insulin signaling after TCM treatment still needs further confirmation.

3.4. Taurine and Hypotaurine Metabolism

Metabolic pathway analysis suggested that taurine and hypotaurine metabolism was affected after TCM treatment (Figure 4).Taurine has been reported to restore insulin secretion and exert an antidiabetic effect [59,60,61].In this review, the level of taurine in the urine was increased in diabetic rodents but reduced after TCM treatment in most studies, as shown in Figure 11.However, the level of taurine was decreased in the livers of diabetic rodents and increased by the administration of TCM such as Dendrobium officinale water extract [20] and the Qijian mixture [26], which could be beneficial to improve insulin signaling in the liver [62]. Carneiro et al. revealed that taurine facilitated glucose homeostasis by regulating the expression of genes for glucose-stimulated insulin secretion [63]. Additionally, taurine can also affect the electrogenic response and calcium homeostasis in β-cells and then result in insulin secretion [64]. Although the current findings on taurine metabolism are inconsistent, we speculate that an increased taurine level after TCM treatment should have a positive effect on diabetes therapy.

4. Conclusions and Perspectives

This review has focused mostly on NMR metabolomics and provides a panoramic view of the metabolic responses to diabetic treatment using TCM. Treatment with TCM up-regulates energy metabolism, amino acid metabolism, ketone body degradation and taurine metabolism and then increases insulin secretion and reduces blood glucose levels (Figure 12). However, the relevant studies are still inadequate to make a final conclusion. Moreover, the real knowledge for a complex biological system needs to integrate genes, proteins and metabolites, suggesting that a multi-omics analysis could be one of the avenues to explore in the future. In this review, most studies focused on analyses of biofluids, such as urine and serum, but we suggest that attention should also be paid to metabolic changes in organs and tissues in order to explore potential mechanisms underlying the treatment of diabetic complications using TCM. Notably, the fecal metabolome also needs to be paid more attention in order to explore the role of gut microbiota in diabetes therapy via TCM treatment [65].
Thus far, the clinical studies of TCM in diabetes have mostly focused on glycemic control, but with no metabolomics investigations. Thus, metabolic pathways affected by TCM treatment in rodents still need to be validated in human intervention studies in order to uncover potential pharmacological mechanisms of TCM for its clinical translational application. We also recommend using a multi-omics analysis for elucidating whether these metabolic changes have a causative role in diabetes therapy. Such metabolomics information could then be used to evaluate TCM interventions and discover new targets for diabetic treatment. Relative to T2D, there are fewer therapeutic methods for T1D, but there are few TCM studies on T1D. We appeal for the need to discover novel therapeutic strategies for T1D patients from TCM in the future.

Author Contributions

Y.H., J.L., Q.Z., J.C., W.D. and M.L. contributed to the literature search and selection; H.Z., Y.H., J.L. and Q.Z. contributed to the result’s interpretation and writing. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Medical and Health Science and Technology Project of Zhejiang Province (No.: 2022KY1215).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare that they have no conflict of interest.

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Molecules 27 05109 g001 550
Figure 1. NMR-based metabolomics profiling. Typical 600 MHz 1H NMR spectra obtained from (a) serum, (b) liver and (c) feces in healthy mice. Metabolite assignment: 1, 3-hydroxybutyrate; 2, AMP; 3, NAG; 4, α-glucose; 5, β-glucose; 6, phenylalanine; 7, alanine; 8, acetone; 9, pyruvate; 10, choline; 11, LDL/VLDL; 12, butyrate; 13, glycine; 14, glycerol; 15, glutamate; 16, glutamine; 17, glutathione; 18, succinate; 19, creatine; 20, methanol; 21, methylhistidine; 22, formate; 23, lysine; 24, tyrosine; 25, leucine; 26, uracil; 27, citrate; 28, taurine; 29, glucose/amino acid region; 30, lactate; 31, aspartate; 32, valine; 33, fumarate; 34, acetate; 35, isoleucine; 36, histidine; 37, tryptophan. Amplification: ×2, 2 times; ×4, 4 times; ×8, 8 times.
Figure 1. NMR-based metabolomics profiling. Typical 600 MHz 1H NMR spectra obtained from (a) serum, (b) liver and (c) feces in healthy mice. Metabolite assignment: 1, 3-hydroxybutyrate; 2, AMP; 3, NAG; 4, α-glucose; 5, β-glucose; 6, phenylalanine; 7, alanine; 8, acetone; 9, pyruvate; 10, choline; 11, LDL/VLDL; 12, butyrate; 13, glycine; 14, glycerol; 15, glutamate; 16, glutamine; 17, glutathione; 18, succinate; 19, creatine; 20, methanol; 21, methylhistidine; 22, formate; 23, lysine; 24, tyrosine; 25, leucine; 26, uracil; 27, citrate; 28, taurine; 29, glucose/amino acid region; 30, lactate; 31, aspartate; 32, valine; 33, fumarate; 34, acetate; 35, isoleucine; 36, histidine; 37, tryptophan. Amplification: ×2, 2 times; ×4, 4 times; ×8, 8 times.
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Figure 2. Flowchart depicting NMR-based metabolomics method to elucidate metabolic mechanisms of traditional Chinese medicine for the treatment of diseases.
Figure 2. Flowchart depicting NMR-based metabolomics method to elucidate metabolic mechanisms of traditional Chinese medicine for the treatment of diseases.
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Figure 3. Flowchart of literature search and selection.
Figure 3. Flowchart of literature search and selection.
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Figure 4. Metabolic pathway analysis based on differentiated metabolites from NMR metabolomics studies on diabetic treatment using traditional Chinese medicine.
Figure 4. Metabolic pathway analysis based on differentiated metabolites from NMR metabolomics studies on diabetic treatment using traditional Chinese medicine.
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Figure 5. The effect of traditional Chinese medicine onglycine, serine and threonine metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00037, glycine; C00065, serine; C00078, tryptophan; C00114, choline; C00188, threonine; C00213, sarcosine; C00263, homoserine; C00300, creatine; C00719, betaine; C01026, dimethylglycine.
Figure 5. The effect of traditional Chinese medicine onglycine, serine and threonine metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00037, glycine; C00065, serine; C00078, tryptophan; C00114, choline; C00188, threonine; C00213, sarcosine; C00263, homoserine; C00300, creatine; C00719, betaine; C01026, dimethylglycine.
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Figure 6. The effect of traditional Chinese medicine on alanine, aspartate and glutamate metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00025, glutamate; C00026, 2-oxoglutarate; C00041, alanine; C00042, succinate; C00064, glutamine; C00122, fumarate.
Figure 6. The effect of traditional Chinese medicine on alanine, aspartate and glutamate metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00025, glutamate; C00026, 2-oxoglutarate; C00041, alanine; C00042, succinate; C00064, glutamine; C00122, fumarate.
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Figure 7. The effect of traditional Chinese medicine on arginine and proline metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00025, glutamate; C00062, arginine; C00064, glutamine; C00086, urea; C00122, fumarate; C00148, proline; C00213, sarcosine; C00300, creatine; C00791, creatinine.
Figure 7. The effect of traditional Chinese medicine on arginine and proline metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00025, glutamate; C00062, arginine; C00064, glutamine; C00086, urea; C00122, fumarate; C00148, proline; C00213, sarcosine; C00300, creatine; C00791, creatinine.
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Figure 8. The effect of traditional Chinese medicine on pyruvate metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00033, acetate; C00058, formate; C00149, malate; C00186, lactate; C00583, propylene glycol.
Figure 8. The effect of traditional Chinese medicine on pyruvate metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00033, acetate; C00058, formate; C00149, malate; C00186, lactate; C00583, propylene glycol.
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Figure 9. The effect of traditional Chinese medicine on TCA cycle during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00149, malate; C00042, succinate; C00122, fumarate; C00158, citrate; C00026, 2-oxoglutarate.
Figure 9. The effect of traditional Chinese medicine on TCA cycle during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00149, malate; C00042, succinate; C00122, fumarate; C00158, citrate; C00026, 2-oxoglutarate.
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Figure 10. The effect of traditional Chinese medicine on synthesis and degradation of ketone bodies during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00207, acetone; C00164, acetoacetate; C01089, 3-hydroxybutyrate.
Figure 10. The effect of traditional Chinese medicine on synthesis and degradation of ketone bodies during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00207, acetone; C00164, acetoacetate; C01089, 3-hydroxybutyrate.
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Figure 11. The effect of traditional Chinese medicine on taurine and hypotaurine metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00033, acetate; C00041, alanine; C00245, taurine.
Figure 11. The effect of traditional Chinese medicine on taurine and hypotaurine metabolism during diabetic treatment. Each row in the table represents one study and arrow indicates relative change tendency of metabolite. Red and wathet blue colors indicate the increase and decrease in metabolite level in DM relative to normal controls or in DM after TCM treatment, respectively. DM, diabetes mellitus; T, TCM treatment. Metabolite: C00022, pyruvate; C00033, acetate; C00041, alanine; C00245, taurine.
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Figure 12. Potential metabolic mechanisms of traditional Chinese medicine on diabetic treatment. Up and down arrows indicate increase and decrease after TCM treatment, respectively.
Figure 12. Potential metabolic mechanisms of traditional Chinese medicine on diabetic treatment. Up and down arrows indicate increase and decrease after TCM treatment, respectively.
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Table
Table 1. Summary of the main advantages and disadvantages of nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) in metabolomics.
Table 1. Summary of the main advantages and disadvantages of nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) in metabolomics.
NMRMS
AdvantageHigh reproducibilityHigh sensitivity
Minimal sample preparationMore metabolite detection
Non-destructiveFlexible technique
Good quantitative analysisMinimal sample size
No separation and fast analysis
Good software/database for identification
DisadvantageRelatively low sensitivityLow reproducibility
Larger sample sizeSample derivatization for GC-MS
Cannot detect non-protonated metabolitesSample not recoverable
Relatively poor quantitative analysis
Difficult identification
Table
Table 2. Metabolite assignment in 1H NMR-based metabolomics profiling.
Table 2. Metabolite assignment in 1H NMR-based metabolomics profiling.
No.MetaboliteChemical Shift (ppm) aMetabolic Pathway
13-Hydroxybutyrate1.18(d)Ketone body metabolism
2AMP b6.15(d), 8.26(s), 8.58(s)Energy metabolism
3NAG c2.05(m), 3.75(m)- e
4α-Glucose5.21(d)Energy metabolism
5β-Glucose4.65(d)Energy metabolism
6Phenylalanine7.37(t), 7.45(t)Amino acid metabolism
7Alanine1.48(d)Amino acid metabolism
8Acetone2.37(s)Ketone body metabolism
9Pyruvate2.40(s)Energy metabolism
10Choline3.20(s)Choline metabolism
11LDL/VLDL d0.85(m), 1.25(m)-
12Butyrate0.89(t), 1.55(m)Fatty acid metabolism
13Glycine3.55(s)Amino acid metabolism
14Glycerol3.67(q)Glycerolipid metabolism
15Glutamate2.15(m), 3.75(m)Amino acid metabolism
16Glutamine2.45(m), 3.78(t)Amino acid metabolism
17Glutathione2.15(m)Amino acid metabolism
18Succinate2.39(s)Energy metabolism
19Creatine3.03(s), 3.93(s)Energy metabolism
20Methanol3.35(s)-
21Methylhistidine7.05(s)Amino acid metabolism
22Formate8.44(s)Fatty acid metabolism
23Lysine1.71(m)Amino acid metabolism
24Tyrosine6.89(d), 7.20(d)Amino acid metabolism
25Leucine0.95(t)Amino acid metabolism
26Uracil5.80(d)Nucleotide metabolism
27Citrate2.55(d)Energy metabolism
28Taurine3.25(t), 3.41(t)Amino acid metabolism
29Glucose/amino acid region3.35–3.92(m)-
30Lactate1.32(d), 4.11(q)Energy metabolism
31Aspartate2.80(d), 3.15(d)Amino acid metabolism
32Valine0.98(d), 1.05(d)Amino acid metabolism
33Fumarate7.11(s)Energy metabolism
34Acetate1.91(s)Fatty acid metabolism
35Isoleucine0.99(d)Amino acid metabolism
36Histidine7.79(s)Amino acid metabolism
37Tryptophan7.34(d)Amino acid metabolism
a s, singlet; d, doublet; t, triplet; q, quartet; m, multiplet; b adenosine monophosphate; c n-acetyl-glycoprotein; d low-density lipoprotein/very low-density lipoprotein; e others.
Table
Table 3. Summary of main metabolic changes after TCM treatment.
Table 3. Summary of main metabolic changes after TCM treatment.
TreatmentDose/TimeModelTypeGlucose
Lowering		SampleMetabolic Change aReference
Zhibai
Dihuang pill		4 g/kg;
30 days		STZ-induced
diabetic
nephropathy rats		T1DYes, but no
significant
difference		Urine
Serum
Kidney		Urine: (↓)3-hydroxybutyrate, lactate
Serum: (↑) creatine, methionine, lactate, pyruvate; (↓) VLDL/LDL, 3-hydroxybutyrate
Kidney: (↑) betaine, choline, glutamate; (↓)glucose, lactate		[13]
Gegen
Qinlian
decoction		8 g/kg;
5 weeks		High-fat
diet/STZ-induced diabetic rats		T2DYesPlasma(↑)lipoprotein, valine, TMAO, dimethylamine, arginine; (↓) choline, glucose, glycerol, taurine, creatine, creatinine, tyrosine[14]
Momordica charantia ethanol extract200 mg/kg;
1 week		STZ-induced
diabetic rats		T1DYesUrine(↑) succinate, creatine, creatinine, urea, phenylacetylglycine; (↓) lactate, glucose[15]
Phyllanthus niruri
ethanol extract		500 mg/kg;
4 weeks		High-fat
diet/STZ-induced diabetic rats		T2DYesUrine
Serum
Urine: (↑) hippurate, formate, fumarate, methylnicotinamide, pyruvate, acetone, phenylacetylglycine, allantoin, alanine, succinate, lactate; (↓) glucose, choline, taurine, creatine
Serum: (↓) glucose, triglyceride, cholesterol, LDL, HDL		[16]
Andrographis paniculata
water extract		200 mg/kg;
4 weeks		High-fat
diet/STZ-induced diabetic rats		T2DYesUrine(↑) lactate, formate, pyruvate, citrate, 2-oxoglutarate, succinate, acetoacetate, 3-hydroxybutyrate, acetate, dimethylglycine, dimethylamine, alanine, allantoin; (↓) glucose, taurine[17]
Centella asiatica ethanol extract300 mg/kg;
4 weeks		High-fat
diet/STZ-induced diabetic rats		T2DYesUrine
Serum
Urine: (↑) pyruvate, lactate, citrate, fumarate, succinate, 2-oxoglutarate, 3-hydoxybutyrate, acetoacetate, acetone, acetate, alanine, hippurate, dimethylamine, creatinine, trimethylamine, allantoin; (↓) glucose
Serum: (↑) lactate, choline, succinate; (↓) glucose		[18]
Genipin,
derived from the fruit of
Gardenia
jasminoides		100 mg/kg;
2 weeks		Alloxan-induced diabetic ratsT1DYesSerum(↑) citrate, succinate, 3-hydroxybutyrate, acetone[19]
Orthosiphon stamineus
aqueous extract		500 mg/kg;
2 weeks		STZ-induced
diabetic rats		T1DYesUrine(↑) hippurate, allantoin, creatinine, glutamate, 3-hydroxybutyrate, pyruvate, citrate; (↓) glucose, taurine, betaine, leucine, acetoacetate[20]
Dendrobium officinale water extract700 mg/kg;
2 weeks		STZ-induced
diabetic mice		T1DYesSerum
Liver		Serum: (↑) citrate, glutamine; (↓) glucose, creatine
Liver: (↑) creatine, alanine, leucine, isoleucine, valine, glutamine, glutathione, taurine, 3-hydroxybutyrate		[21]
Melicopelunu-ankenda leaf ethanol extract400 mg/kg;
8 weeks		High-fat
diet/STZ-induced diabetic rats		T2DYesSerum(↑) lactate, formate, 2-oxoglutarate, succinate, leucine, isoleucine, hippurate; (↓) glucose, acetoacetate, 3-hydroxybutyrate, choline, creatine[22]
Ipomoea aquatic ethanolic
extract		250 mg/kg;
4 weeks		High-fat
diet/STZ-induced diabetic rats		T2DYes, but no significant differenceUrine(↑)creatine, creatinine, hippurate,
leucine, 1-methylnicotinamice, taurine, 3-hydroxybutyrate, lysine, trigonelline, allantoin, formate; (↓) glucose, citrate, carnitine, 2-oxoglutarate, succinate, tryptophan, acetoacetate, dimethylamine		[23]
Genipin, derived from the fruit of
Gardenia
jasminoides		100 mg/kg;
2 weeks		Alloxan-induced diabetic ratsT1DNot mentionedUrine
Kidney		Urine: (↑) isoleucine, glutamate, acetoacetate, hippurate, N-acetyl-glycoprotein, creatinine, methylamine, dimethylglycine; (↓) 2-oxoglutarate, betaine, sarcosine
Kidney: (↑) creatine; (↓) glycine, betaine		[24]
Zishen
Jiangtang pill		3.0 g/kg;
8 weeks		STZ-induced rats with diabetic
osteoporosis		T1DYesBlood
Urine		Blood: (↑) tryptophan, malate, propylene glycol, xanthosine, fumarate
Urine: (↓) butyrate		[25]
Qijian mixture5.385 g/kg;
8 weeks		Male KKay miceT2DYesLiver KidneyLiver: (↑) glucose, taurine, glycerol; (↓) isoleucine, valine, lactate, alanine, acetate, homoserine, glutarate, 3-hydroxybutyrate, glutamine, glutathione, choline, anserine, niacinamide, xanthine, inosine
Kidney: (↑) phosphocholine, TMAO, myo-inositol, xanthine; (↓) citrate		[26]
Mangiferin (SA1) and naringenin (SA2) from the leaves of
Salacia oblonga		100 mg/kg;
15 days		STZ-induced diabetic ratsT2DYesSerumSA1: (↑) isoleucine, leucine, valine, lactate, alanine, acetate, proline, N-acetyl-glycoprotein, O-acetyl-glycoprotein, acetone, glutamate, glutamine, lipid, creatine, creatinine, malonate, choline, methanol, myo-inositol, serine, gluconate, threonine, allantoin, tyrosine, phenylalanine, histidine; (↓) glucose
SA2: (↑) HDL/LDL, LDL/VLDL, isoleucine, leucine, valine, lactate, alanine, acetate, proline, N-acetyl-glycoprotein, O-acetyl-glycoprotein, acetone, glutamate, glutamine, lipid, creatine, malonate, choline, methanol, myo-inositol, glycerol, serine, gluconate, threonine, allantoin, tyrosine, phenylalanine, histidine; (↓) glucose		[27]
Ganoderma lucidum polysaccharides400 mg/kg;
4 weeks		STZ-induced T2D ratsT2DYesFeces(↓) xanthine, deoxycholic acid, imidazole, n-Heptanoate, Urocanate, valine; (↑) methanol[28]
Rubus suavissimus S. Lee3 g/kg;
6 weeks		STZ-induced T1D ratsT1DYesUrine(↑) creatinine, allantoin, hippurate; (↓) lactate, pyruvate, succinate, 2-oxoglutarate, citrate[29]
Salvia miltiorrhiza and Radix Pueraria lobata herb pair3.15 g/kg;
4 weeks		STZ-induced T2D ratsT2DYesFeces(↑) alanine, succinate, lactate, proline, valine, leucine, glutamate, glucose, isoleucine, α-ketoisovalerate, hypoxanthine; (↓) butyrate[30]
Anthocyanin Extracts from Bilberry and Purple Potato25 and 50 mg/kg;
8 weeks		Zucker diabetic ratsT2DYesPlasma(↓) lactate, lipid, valine, leucine, isoleucine, glutamate[31]
Berberis kansuensis extract0.84 g/kg;
30 days		High-fat diet/STZ-induced diabetic ratsT2DYesSerum(↑) LDL/VLDL, isoleucine, valine, NAG, acetoacetate, glutamate; (↓) betaine, glucose[32]
Astragalus radix and Dioscoreae rhizoma6.3 g/kg;
4 weeks		High-fat diet/STZ-induced diabetic ratsT2DYesSerum(↑) taurine, glycine, glutamine; (↓) lipid, pyruvate, TMAO, glycerol, isoleucine, leucine, valine, glucose, tyrosine, 3-hydroxybutyrate, acetoacetate, succinate, xanthine[33]
Chickpea
extract		3 g/kg;
4 weeks		High-fat diet/STZ-induced diabetic ratsT2DYesCecum(↑) acetate, propionate, butyrate[34]
Acanthopanax sessiliflorus fruits3 mg/kg;
4 weeks		High-fat diet-induced mouse modelT2DNot mentionedLiver(↑) formate, inosine, pyroglutamate, taurine; (↓) alanine, tyrosine[35]
Enteromorpha prolifera polysaccharide450 mg/kg;
12 weeks		High-fat diet-fed hamstersT2DNot mentionedSerum(↑) arginine; (↓) 2-hydroxyisovalerate, 2-oxoglutarate, 3-hydroxybutyrate, 3-hydroxyisobutyrate, betaine, citrate, glucose, lactate[36]
Berberis vernae extract0.84 g/kg;
30 days		High-fat diet/STZ-induced diabetic ratsT2DYesSerum(↑) LDL/VLDL, isoleucine, valine, lipid, NAG, acetoacetate; (↓) TMAO, betaine, glucose[37]
a Metabolic changes after TCM treatment relative to non-treated diabetes.
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Huang, Y.; Lu, J.; Zhao, Q.; Chen, J.; Dong, W.; Lin, M.; Zheng, H. Potential Therapeutic Mechanism of Traditional Chinese Medicine on Diabetes in Rodents: A Review from an NMR-Based Metabolomics Perspective. Molecules 2022, 27, 5109. https://doi.org/10.3390/molecules27165109

AMA Style

Huang Y, Lu J, Zhao Q, Chen J, Dong W, Lin M, Zheng H. Potential Therapeutic Mechanism of Traditional Chinese Medicine on Diabetes in Rodents: A Review from an NMR-Based Metabolomics Perspective. Molecules. 2022; 27(16):5109. https://doi.org/10.3390/molecules27165109

Chicago/Turabian Style

Huang, Yinli, Jiahui Lu, Qihui Zhao, Junli Chen, Wei Dong, Minjie Lin, and Hong Zheng. 2022. "Potential Therapeutic Mechanism of Traditional Chinese Medicine on Diabetes in Rodents: A Review from an NMR-Based Metabolomics Perspective" Molecules 27, no. 16: 5109. https://doi.org/10.3390/molecules27165109

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