Correlative and quantitative 1H NMR-based metabolomics reveals specific metabolic pathway disturbances in diabetic rats

3D superstructure based metabolite profiling for glaucoma diagnosis

Metabolome analysis has gained widespread application in disease diagnosis owing to its ability to provide comprehensive information, including disease phenotypes. In this study, we utilized 3D superstructures fabricated through evaporation-induced microprinting to analyze the metabolome for glaucoma diagnosis. 3D superstructures offer the following advantages: high hotspot density per unit volume of the structure extending from two to three dimensions, excellent signal repeatability due to the reproducibility and defect tolerance of 3D printing, and high thermal stability due to the PVP-enclosed capsule form. Leveraging the superior optical properties of the 3D superstructure, we aimed to classify patients with glaucoma. The signal obtained from the 3D superstructure was employed in a Deep Neural Network (DNN) classification model to accurately classify glaucoma patients. The sensitivity and specificity of the model were determined as 92.05% and 93.51%, respectively. Additionally, the fabrication of 3D superstructures can be performed at any stage, significantly reducing measurement time. Furthermore, their thermal stability allows for the analysis of smaller samples. One notable advantage of 3D superstructures is their versatility in accommodating different target materials. Consequently, they can be utilized for a wide range of metabolic analyses and disease diagnoses.

Salbutamol ameliorates skeletal muscle wasting and inflammatory markers in streptozotocin (STZ)-induced diabetic rats

Diabetes accelerates muscle atrophy, leading to the deterioration of skeletal muscles. This study aimed to assess the potential of the β2-adrenoceptor agonist, salbutamol (SLB), to alleviate muscle atrophy in streptozotocin (STZ)-induced diabetic rats. Male Sprague Dawley rats were randomized into four groups (n=6): control, SLB, STZ (55 mg/kg, single i.p.), and STZ + SLB (6 mg/kg, orally for 4 weeks). After the final SLB dose, animals underwent tests to evaluate muscle strength and coordination, including forelimb grip strength, wire-hanging, actophotometer, rotarod, and footprint assessments. Rats were then sacrificed, and serum and gastrocnemius (GN) muscles were collected for further analysis. Serum evaluations included proinflammatory markers (tumor necrosis factor α, interleukin-1β, interleukin-6), muscle markers (creatine kinase, myostatin), testosterone, and lipidemic markers. Muscle oxidative stress (malonaldehyde, protein carbonyl), antioxidants (glutathione, catalase, superoxide dismutase), and histology were also performed. Additionally, 1H nuclear magnetic resonance serum profiling was conducted. SLB notably enhanced muscle grip strength, coordination, and antioxidant levels, while reduced proinflammatory markers and oxidative stress in STZ-induced diabetic rats. Reduced serum muscle biomarkers, increased testosterone, restored lipidemic levels, and improved muscle cellular architecture indicated SLB's positive effect on muscle condition in diabetic rats. Metabolomics profiling revealed that the STZ group significantly increased the phenylalanine-to-tyrosine ratio (PTR), lactate-to-pyruvate ratio (LPR), acetate, succinate, isobutyrate, and histidine. SLB administration restored these perturbed serum metabolites in the STZ-induced diabetic group. In conclusion, salbutamol significantly protected against skeletal muscle wasting in STZ-induced diabetic rats.

Integrating (Nutri-)Metabolomics into the One Health Tendency-The Key for Personalized Medicine Advancement

Metabolomics is an advanced technology, still under development, with multiple research applications, especially in the field of health. Individual metabolic profiles, the functionality of the body, as well as its interaction with the environment, can be established using this technology. The body's response to various external factors, including the food consumed and the nutrients it contains, has increased researchers' interest in nutrimetabolomics. Establishing correlations between diet and the occurrence of various diseases, or even the development of personalized nutrition plans, could contribute to advances in precision medicine. The interdependence between humans, animals, and the environment is of particular importance today, with the dramatic emergence and spread of zoonotic diseases, food, water and soil contamination, and the degradation of resources and habitats. All these events have led to an increase in risk factors for functional diseases, burdening global health. Thus, this study aimed to highlight the importance of metabolomics, and, in particular, nutrimetabolomics, as a technical solution for a holistic, collaborative, and precise approach for the advancement of the One Health strategy.

Qualitative and Quantitative Mass Spectrometry in Salivary Metabolomics and Proteomics

The metabolomics and proteomics analysis of saliva, an excellent biofluid that is a rich source of biological compounds, allows for the safe and frequent screening of drugs, their metabolites, and molecular biomarkers of various diseases. One of the most frequently used analytical methods in saliva analysis is liquid chromatography coupled with mass spectrometry (LC-MS) and tandem mass spectrometry. The low ionisation efficiency of some compounds and a complex matrix makes their identification by MS difficult. Furthermore, quantitative analysis by LC-MS frequently cannot be performed without isotopically labelled standards, which usually have to be specially synthesised. This review presented reports on qualitative and quantitative approaches in salivary metabolomics and proteomics. The purpose of this manuscript was to present the challenges, advances, and future prospects of mass spectrometry, both in the analysis of salivary metabolites and proteins. The presented review should appeal to those interested in the recent advances and trends in qualitative and quantitative mass spectrometry in salivary metabolomics and proteomics, which may facilitate a diagnostic accuracy, the evaluation of treatment efficacy, the early diagnosis of disease, and a forensic investigation of some unapproved drugs for any medical or dietary administration.

Differences in meat quality between Angus cattle and Xinjiang brown cattle in association with gut microbiota and its lipid metabolism

Gut microbiota plays important roles in mediating fat metabolic events in humans and animals. However, the differences of meat quality traits related to the lipid metabolism (MQT-LM) in association with gut microbiota involving in lipid metabolism have not been well explored between Angus cattle (AG) and Xinjiang brown cattle (BC). Ten heads of 18-month-old uncastrated male AG and BC (5 in each group) raised under the identical conditions were selected to test MQT-LM, i.e., the backfat thickness (BFT), the intramuscular fat (IMF) content, the intramuscular adipocyte areas (IAA), the eye muscle area (EMA), the muscle fiber sectional area (MFSA) and the muscle shear force after sacrifice. The gut microbiota composition and structure with its metabolic function were analyzed by means of metagenomics and metabolomics with rectal feces. The correlation of MQT-LM with the gut microbiota and its metabolites was analyzed. In comparison with AG, BC had significant lower EMA, IMF content and IAA but higher BFT and MFSA. Chao1 and ACE indexes of α-diversity were lower. β-diversity between AG and BC were significantly different. The relative abundance of Bacteroidetes, Prevotella and Blautia and Prevotella copri, Blautia wexlerae, and Ruminococcus gnavus was lower. The lipid metabolism related metabolites, i.e., succinate, oxoglutaric acid, L-aspartic acid and L-glutamic acid were lower, while GABA, L-asparagine and fumaric acid were higher. IMF was positively correlated with Prevotella copri, Blautia wexlerae and Ruminococcus gnavus, and the metabolites succinate, oxoglutaric acid, L-aspartic acid and L-glutamic acid, while negatively with GABA, L-asparagine and fumaric acid. BFT was negatively correlated with Blautia wexlerae and the metabolites succinate, L-aspartic acid and L-glutamic acid, while positively with GABA, L-asparagine and fumaric acid. Prevotella Copri, Blautia wexlerae, and Ruminococcus gnavus was all positively correlated with succinate, oxoglutaric acid, while negatively with L-asparagine and fumaric acid. In conclusion, Prevotella copri, Prevotella intermedia, Blautia wexlerae, and Ruminococcus gnavus may serve as the potential differentiated bacterial species in association with MQT-LM via their metabolites of oxoglutaric acid, succinate, fumaric acid, L-aspartic acid, L-asparagine, L-glutamic acid and GABA between BC and AG.

Fine optimization of a dissolution dynamic nuclear polarization experimental setting for 13C NMR of metabolic samples

NMR-based analysis of metabolite mixtures provides crucial information on biological systems but mostly relies on 1D 1 H experiments for maximizing sensitivity. However, strong peak overlap of 1 H spectra often is a limitation for the analysis of inherently complex biological mixtures. Dissolution dynamic nuclear polarization (d-DNP) improves NMR sensitivity by several orders of magnitude, which enables 13 C NMR-based analysis of metabolites at natural abundance. We have recently demonstrated the successful introduction of d-DNP into a full untargeted metabolomics workflow applied to the study of plant metabolism. Here we describe the systematic optimization of d-DNP experimental settings for experiments at natural 13 C abundance and show how the resolution, sensitivity, and ultimately the number of detectable signals improve as a result. We have systematically optimized the parameters involved (in a semi-automated prototype d-DNP system, from sample preparation to signal detection, aiming at providing an optimization guide for potential users of such a system, who may not be experts in instrumental development). The optimization procedure makes it possible to detect previously inaccessible protonated 13 C signals of metabolites at natural abundance with at least 4 times improved line shape and a high repeatability compared to a previously reported d-DNP-enhanced untargeted metabolomic study. This extends the application scope of hyperpolarized 13 C NMR at natural abundance and paves the way to a more general use of DNP-hyperpolarized NMR in metabolomics studies.

Rapid quantitative 1H–13C two-dimensional NMR with high precision

Two dimensional (2D) ¹H–¹³C heteronuclear single-quantum correlation (HSQC) spectroscopy has recently been proposed for quantitative determination of typical linear low density polyethylene (LLDPE) with high accuracy. It requires highly precise measurement to achieve further reliable quantification. In this context, this paper aims at determining conditions that allow the achievement of high precision. On the basis of the optimized parameters, two time-saving strategies, nonuniform sampling (NUS) and band-selective HSQC are evaluated on model polyolefins in terms of repeatability. Precision better than 0.3% and 5% for ethylene content (E mol%) and 1-hexene content (H mol%) of the model poly(ethylene-co-1-hexene)s are obtained with 50% NUS or band-selective HSQC. Moreover, dramatic precision enhancements can be achieved with the combination of band-selective HSQC and 50% NUS, in which repeatabilities better than 0.15% and 2.5% for E mol% and H mol% are observed. The experiment times are reduced to about 0.5 h. These methods open important perspectives for rapid, precise and accurate quantitative analysis of complex polymers.

Precision better than 2.5% can be achieved with the combination of band-selective HSQC and 50% NUS in 0.5 h.

Urinary metabolites of type 2 diabetes rats fed with palm oil-enriched high fat diet

High fat diet (HFD) is one of the risk factors of obesity and diabetes. Recommended diet regimen for diabetes is difficult to abide by especially for HFD as it adds flavour to the taste buds. In this study, palm oil-enriched HFD and normal diet were fed to nicotinamide-induced type 2 diabetes rats, respectively for six weeks. Additionally, metformin, a common drug used to treat diabetes was given to rats under treatment groups. We evaluated the change of urinary metabolites of diabetes rats fed with palm oil-enriched HFD, and also after metformin treatment. Rats were divided into six-groups with different feeding diets, disease condition and with or without metformin treatment. Rats’ urine were collected at the end of six weeks feeding program and subjected to 1H-NMR and multivariate data analysis to evaluate their metabolite profiles. At the early phase of diabetes, metabolites changes in diabetic rats were associated with the disease itself. Our data showed that continuous consumption of HFD altered various metabolic pathways of diabetic rats and caused detrimental effects to the rats. On the other hand, metformin treatment combined with normal diet lessened the physiological impacts caused by diabetes condition.

Mothers' cafeteria diet induced sex-specific changes in fat content, metabolic profiles, and inflammation outcomes in rat offspring

“Western diet” containing high concentrations of sugar and fat consumed during pregnancy contributes to development of obesity and diabetes type 2 in offspring. To mimic effects of this diet in animals, a cafeteria (CAF) diet is used. We hypothesized that CAF diet given to rats before, and during pregnancy and lactation differently influences fat content, metabolic and inflammation profiles in offspring. Females were exposed to CAF or control diets before pregnancy, during pregnancy and lactation. At postnatal day 25 (PND 25), body composition, fat contents were measured, and blood was collected for assessment of metabolic and inflammation profiles. We have found that CAF diet lead to sex-specific alterations in offspring. At PND25, CAF offspring had: (1) higher percentage of fat content, and were lighter; (2) sex-specific differences in levels of glucose; (3) higher levels of interleukin 6 (IL-6), interleukin-10 (IL-10) and tumor necrosis factor (TNF-α); (4) sex-specific differences in concentration of IL-6 and TNF-α, with an increase in CAF females; (5) higher level of IL-10 in both sexes, with a more pronounced increase in females. We concluded that maternal CAF diet affects fat content, metabolic profiles, and inflammation parameters in offspring. Above effects are sex-specific, with female offspring being more susceptible to the diet.

Revealing hypoglycemic and hypolipidemic mechanism of Xiaokeyinshui extract combination on streptozotocin-induced diabetic mice in high sucrose/high fat diet by metabolomics and lipidomics

Type 2 diabetic mellitus (T2DM), often accompanied by disorders of glucose and lipid metabolism, has troubled hundreds of millions of people. Xiaokeyinshui extract combination (XEC), derived from traditional Chinese medicines formula, has exerted hypoglycemic effects against T2DM. However, its mechanism of metabolic level is still unclear. In this study, a T2DM mice model, induced by a high sucrose/high fat diet combined with low-dose streptozotocin (STZ) injections, was adopted. The biochemical index was determined and a combination of metabolomics and lipidomics analyses of plasma were performed. The results showed that XEC increased secretion of insulin and level of HDL-C, decreased levels of FBG, HbA1c, TC, TG, LDL-C and repaired islet structure in diabetic mice. In addition, the metabolic profiles of plasma were analyzed and 54 potential biomarkers were screened out, mainly including carbohydrates, lipids and amino acids. These potential biomarkers were found to be correlated with the following pathways: galactose metabolism, fructose and mannose metabolism, TCA cycle, arachidonic acid metabolism, glycerolipid metabolism, glycerophospholipid metabolism, sphingolipid metabolism and amino acid metabolism. In conclusion, we speculated that carbohydrate metabolism, lipid metabolism and amino acid metabolism played roles in the therapeutic mechanisms of XEC on T2DM.

Therapeutic Effectiveness of Gardenia jasminoides on Type 2 Diabetic Rats: Mass Spectrometry-Based Metabolomics Approach

Gardenia jasminoides fruits, a kind of traditional Chinese medicine (TCM), have shown prospects in the prevention of diabetes and its complications. However, due to their chemical diversity and multiple biological targets, the effective mechanism remains largely unknown. In this study, mass spectrometry-based metabolomics was applied to uncover the underlying therapeutic mechanism of G. jasminoides on type 2 diabetes (T2D) and its clinical complications. We established a T2D rat model using high-fat diet and identified 45 urinary endogenous metabolites as potential diagnostic biomarkers for T2D rats. After treatment with G. jasminoides, pathologic symptoms of T2D rats were significantly improved and some of the diagnostic biomarkers were significantly regulated. Bioinformatics analysis demonstrated that these therapeutic biomarkers were involved in bile acid biosynthesis, amino acid metabolism, vitamin B metabolism, taurine metabolism, etc., which indicated potential therapeutic mechanisms of G. jasminoides on T2D and its complications.

Detection of Early Disease Risk Factors Associated with Metabolic Syndrome: A New Era with the NMR Metabolomics Assessment

The metabolic syndrome is a multifactorial disease developed due to accumulation and chronification of several risk factors associated with disrupted metabolism. The early detection of the biomarkers by NMR spectroscopy could be helpful to prevent multifactorial diseases. The exposure of each risk factor can be detected by traditional molecular markers but the current biomarkers have not been enough precise to detect the primary stages of disease. Thus, there is a need to obtain novel molecular markers of pre-disease stages. A promising source of new molecular markers are metabolomics standing out the research of biomarkers in NMR approaches. An increasing number of nutritionists integrate metabolomics into their study design, making nutrimetabolomics one of the most promising avenues for improving personalized nutrition. This review highlight the major five risk factors associated with metabolic syndrome and related diseases including carbohydrate dysfunction, dyslipidemia, oxidative stress, inflammation, and gut microbiota dysbiosis. Together, it is proposed a profile of metabolites of each risk factor obtained from NMR approaches to target them using personalized nutrition, which will improve the quality of life for these patients.

Study on Hypoglycemic Effect of the Drug Pair of Astragalus Radix and Dioscoreae Rhizoma in T2DM Rats by Network Pharmacology and Metabonomics

Type 2 diabetes mellitus (T2DM) is a metabolic disease accompanied by a series of diseases such as diabetic nephropathy. The drug pair (HS) of Astragalus Radix (HQ) and Dioscoreae Rhizoma (SY) was designed by Dr. Shi Jinmo to improve the treatment of T2DM. However, the exact mechanism involved requires further clarification. In this work, 1H-NMR-based metabonomics and network pharmacology were adopted. Metabolic profiling indicated that the metabolic perturbation was reduced after HS treatment. The results found 21 biomarkers. According to the network pharmacology, we found that the regulation of T2DM was primarily associated with 18 active compounds in HS. These active compounds mainly had an effect on 135 targets. Subsequently, combining network pharmacology and metabonomics, we found four target proteins, which indicated that HS has potential hypoglycemic effects through regulating monoamine oxidases B (MAOB), acetyl-CoA carboxylase 1 (ACACA), carbonic anhydrase 2 (CA2), and catalase (CAT). In conclusion, the result showed that these four targets might be the most relevant targets for the treatment of T2DM with HS. This study clarified the mechanism of HS in the treatment of T2DM and also confirmed the feasibility of combining metabonomics and network pharmacology to study the mechanisms of traditional Chinese medicine (TCM). In the future, this approach may be a potentially powerful tool to discovery active components of traditional Chinese medicines and elucidate their mechanisms.

Metabolomics for Investigating Physiological and Pathophysiological Processes

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites from cells, organs, tissues, or biofluids. The rapid growth in metabolomics is leading to a renewed interest in metabolism and the role that small molecule metabolites play in many biological processes. As a result, traditional views of metabolites as being simply the "bricks and mortar" of cells or just the fuel for cellular energetics are being upended. Indeed, metabolites appear to have much more varied and far more important roles as signaling molecules, immune modulators, endogenous toxins, and environmental sensors. This review explores how metabolomics is yielding important new insights into a number of important biological and physiological processes. In particular, a major focus is on illustrating how metabolomics and discoveries made through metabolomics are improving our understanding of both normal physiology and the pathophysiology of many diseases. These discoveries are yielding new insights into how metabolites influence organ function, immune function, nutrient sensing, and gut physiology. Collectively, this work is leading to a much more unified and system-wide perspective of biology wherein metabolites, proteins, and genes are understood to interact synergistically to modify the actions and functions of organelles, organs, and organisms.

Application of 1H-NMR Metabolomics for the Discovery of Blood Plasma Biomarkers of a Mediterranean Diet

The Mediterranean diet (MD) is a dietary pattern well-known for its benefits in disease prevention. Monitoring adherence to the MD could be improved by discovery of novel dietary biomarkers. The MEDiterranean Diet in Northern Ireland (MEDDINI) intervention study monitored the adherence of participants to the MD for up to 12 months. This investigation aimed to profile plasma metabolites, correlating each against the MD score of participants (n = 58). Based on an established 14-point scale MD score, subjects were classified into two groups (“low” and “high”). ¹H-Nuclear Magnetic Resonance (¹H-NMR) metabolomic analysis found that citric acid was the most significant metabolite (p = 5.99 × 10⁻⁴*; q = 0.03), differing between ‘low’ and ‘high’. Furthermore, five additional metabolites significantly differed (p < 0.05; q < 0.35) between the two groups. Discriminatory metabolites included: citric acid, pyruvic acid, betaine, mannose, acetic acid and myo-inositol. Additionally, the top five most influential metabolites in multivariate models were also citric acid, pyruvic acid, betaine, mannose and myo-inositol. Metabolites significantly correlated with the consumption of certain food types. For example, citric acid positively correlated fruit, fruit juice and vegetable constituents of the diet, and negatively correlated with sweet foods alone or when combined with carbonated drinks. Citric acid was the best performing biomarker and this was enhanced by paired ratio with pyruvic acid. The present study demonstrates the utility of metabolomic profiling for effectively assessing adherence to MD and the discovery of novel dietary biomarkers.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

Changes in hepatic metabolic profile during the evolution of STZ-induced diabetic rats via an 1H NMR-based metabonomic investigation

Background: The present study aimed to explore the changes in the hepatic metabolic profile during the evolution of diabetes mellitus (DM) and verify the key metabolic pathways. Methods: Liver samples were collected from diabetic rats induced by streptozotocin (STZ) and rats in the control group at 1, 5, and 9 weeks after STZ administration. Proton nuclear magnetic resonance spectroscopy (¹H NMR)-based metabolomics was used to examine the metabolic changes during the evolution of DM, and partial least squares-discriminate analysis (PLS-DA) was performed to identify the key metabolites. Results: We identified 40 metabolites in the ¹H NMR spectra, and 11 metabolites were further selected by PLS-DA model. The levels of α-glucose and β-glucose, which are two energy-related metabolites, gradually increased over time in the DM rats, and were significantly greater than those of the control rats at the three-time points. The levels of choline, betaine, and methionine decreased in the DM livers, indicating that the protective function in response to liver injury may be undermined by hyperglycemia. The levels of the other amino acids (leucine, alanine, glycine, tyrosine, and phenylalanine) were significantly less than those of the control group during DM development. Conclusions: Our results suggested that the hepatic metabolic pathways of glucose, choline-betaine-methionine, and amino acids were disturbed during the evolution of diabetes, and that choline-betaine-methionine metabolism may play a key role.

Analytical Evaluation of Low-Field 31P NMR Spectroscopy for Lipid Analysis

We investigate the potential of ³¹P NMR with simple, maintenance-free benchtop spectrometers to probe phospholipids in complex mixtures. ³¹P NMR-based lipidomics has become an important topic in a wide range of applications in food- and health-sciences, and the continuous improvements of compact, maintenance- and cryogen-free instruments opens new opportunities for NMR routine analyses. A prior milestone is the evaluation of the analytical performance provided by ³¹P NMR at low magnetic field. To address this, we assess the ability of state-of-the-art benchtop NMR spectrometers to detect, identify, and quantify several types of phospholipids in mixtures. Relying on heteronuclear cross-polarization experiments, phospholipids can be detected in 2 h with a limit of detection of 0.5 mM at 1 T and 0.2 mM at 2 T, while the headgroups of phosphatidylcholine (PC), phosphatidyl-ethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), and phosphatidyl-glycerol (PG) can be unambiguously assigned based on 2D ¹H-³¹P total correlated spectroscopy (TOCSY) spectra. Furthermore, two quantitative methods to obtain absolute concentrations are proposed and discussed, and the performance is evaluated regarding precision and accuracy.

In-Vivo NMR Spectroscopy: A Powerful and Complimentary Tool for Understanding Environmental Toxicity

Part review, part perspective, this article examines the applications and potential of in-vivo Nuclear Magnetic Resonance (NMR) for understanding environmental toxicity. In-vivo NMR can be applied in high field NMR spectrometers using either magic angle spinning based approaches, or flow systems. Solution-state NMR in combination with a flow system provides a low stress approach to monitor dissolved metabolites, while magic angle spinning NMR allows the detection of all components (solutions, gels and solids), albeit with additional stress caused by the rapid sample spinning. With in-vivo NMR it is possible to use the same organisms for control and exposure studies (controls are the same organisms prior to exposure inside the NMR). As such individual variability can be reduced while continual data collection over time provides the temporal resolution required to discern complex interconnected response pathways. When multidimensional NMR is combined with isotopic labelling, a wide range of metabolites can be identified in-vivo providing a unique window into the living metabolome that is highly complementary to more traditional metabolomics studies employing extracts, tissues, or biofluids.

Development of a Reverse Phase HPLC Retention Index Model for Nontargeted Metabolomics Using Synthetic Compounds

The MolFind application has been developed as a nontargeted metabolomics chemometric tool to facilitate structure identification when HPLC biofluids analysis reveals a feature of interest. Here synthetic compounds are selected and measured to form the basis of a new, more accurate, HPLC retention index model for use with MolFind. We show that relatively inexpensive synthetic screening compounds with simple structures can be used to develop an artificial neural network model that is successful in making quality predictions for human metabolites. A total of 1955 compounds were obtained and measured for the model. A separate set of 202 human metabolites was used for independent validation. The new ANN model showed improved accuracy over previous models. The model, based on relatively simple compounds, was able to make quality predictions for complex compounds not similar to training data. Independent validation metabolites with feature combinations found in three or more training compounds were predicted with 97% sensitivity while metabolites with feature combinations found in less than three training compounds were predicted with >90% sensitivity. The study describes the method used to select synthetic compounds and new descriptors developed to encode the relationship between lipophilic molecular subgraphs and HPLC retention. Finally, we introduce the QRI (qualitative range of interest) modification of neural network backpropagation learning to generate models simultaneously based on quantitative and qualitative data.

Metabolomics and Lipidomics Study of Mouse Models of Type 1 Diabetes Highlights Divergent Metabolism in Purine and Tryptophan Metabolism Prior to Disease Onset

With the increase in incidence of type 1 diabetes (T1DM), there is an urgent need to understand the early molecular and metabolic alterations that accompany the autoimmune disease. This is not least because in murine models early intervention can prevent the development of disease. We have applied a liquid chromatography (LC-) and gas chromatography (GC-) mass spectrometry (MS) metabolomics and lipidomics analysis of blood plasma and pancreas tissue to follow the progression of disease in three models related to autoimmune diabetes: the nonobese diabetic (NOD) mouse, susceptible to the development of autoimmune diabetes, and the NOD-E (transgenic NOD mice that express the I-E heterodimer of the major histocompatibility complex II) and NOD-severe combined immunodeficiency (SCID) mouse strains, two models protected from the development of diabetes. All three analyses highlighted the metabolic differences between the NOD-SCID mouse and the other two strains, regardless of diabetic status indicating that NOD-SCID mice are poor controls for metabolic changes in NOD mice. By comparing NOD and NOD-E mice, we show the development of T1DM in NOD mice is associated with changes in lipid, purine, and tryptophan metabolism, including an increase in kynurenic acid and a decrease in lysophospholipids, metabolites previously associated with inflammation.

Combined systems pharmacology and fecal metabonomics to study the biomarkers and therapeutic mechanism of type 2 diabetic nephropathy treated with Astragalus and Leech

In our study, systems pharmacology was used to predict the molecular targets of Astragalus and Leech, and explore the therapeutic mechanism of type 2 diabetic nephropathy (T2DN) treated with Astragalus and Leech. Simultaneously, to reveal the systemic metabolic changes and biomarkers associated with T2DN, we performed ¹H NMR-based metabonomics and multivariate analysis to analyze fecal samples obtained from model T2DN rats. In addition, ELISA kits and histopathological studies were used to examine biochemical parameters and kidney tissue, respectively. Striking differences in the Pearson's correlation of 22 biomarkers and 9 biochemical parameters were also observed among control, T2DN and treated rats. Results of systems pharmacology analysis revealed that 9 active compounds (3,9-di-O-methylnissolin; (6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol; hirudin; l-isoleucine; phenylalanine; valine; hirudinoidine A–C) and 9 target proteins (l-serine dehydratase; 3-hydroxyacyl-CoA dehydrogenase; tyrosyl-tRNA synthetase; tryptophanyl-tRNA synthetase; branched-chain amino acid aminotransferase; acetyl-CoA C-acetyltransferase; isovaleryl-CoA dehydrogenase; pyruvate dehydrogenase E1 component alpha subunit; hydroxyacylglutathione hydrolase) of Astragalus and Leech were closely associated with the treatment of T2DN. Using fecal metabonomics analysis, 22 biomarkers were eventually found to be closely associated with the occurrence of T2DN. Combined with systems pharmacology and fecal metabonomics, these biomarkers were found to be mainly associated with 6 pathways, involving amino acid metabolism (leucine, valine, isoleucine, alanine, lysine, glutamate, taurine, phenylalanine, tryptophan); energy metabolism (lactate, succinate, creatinine, α-glucose, glycerol); ketone body and fatty acid metabolism (3-hydroxybutyrate, acetate, n-butyrate, propionate); methylamine metabolism (dimethylamine, trimethylamine); and secondary bile acid metabolism and urea cycle (deoxycholate, citrulline). The underlying mechanisms of action included protection of the liver and kidney, enhancement of insulin sensitivity and antioxidant activity, and improvement of mitochondrial function. To the best of our knowledge, this is the first time that systems pharmacology combined with fecal metabonomics has been used to study T2DN. 6 metabolites (n-butyrate, deoxycholate, propionate, tryptophan, taurine and glycerol) associated with T2DN were newly discovered in fecal samples. These 6 metabolites were mainly derived from the intestinal flora, and related to amino acid metabolism, fatty acid metabolism, and secondary bile acid metabolism. We hope the results of this study could be inspirational and helpful for further exploration of T2DN treatment. Meanwhile, our results highlighted that exploring the biomarkers of T2DN and therapeutic mechanisms of Traditional Chinese Medicine (TCM) formulas on T2DN by combining systems pharmacology and fecal metabonomics methods was a promising strategy.

In our study, systems pharmacology was used to predict the molecular targets of Astragalus and Leech, and explore the therapeutic mechanism of type 2 diabetic nephropathy (T2DN) treated with Astragalus and Leech.

Combined Metabolomic Analysis of Plasma and Urine Reveals AHBA, Tryptophan and Serotonin Metabolism as Potential Risk Factors in Gestational Diabetes Mellitus (GDM)

Gestational diabetes mellitus during pregnancy has severe implications for the health of the mother and the fetus. Therefore, early prediction and an understanding of the physiology are an important part of prenatal care. Metabolite profiling is a long established method for the analysis and prediction of metabolic diseases. Here, we applied untargeted and targeted metabolomic protocols to analyze plasma and urine samples of pregnant women with and without GDM. Univariate and multivariate statistical analyses of metabolomic profiles revealed markers such as 2-hydroxybutanoic acid (AHBA), 3-hydroxybutanoic acid (BHBA), amino acids valine and alanine, the glucose-alanine-cycle, but also plant-derived compounds like sitosterin as different between control and GDM patients. PLS-DA and VIP analysis revealed tryptophan as a strong variable separating control and GDM. As tryptophan is biotransformed to serotonin we hypothesized whether serotonin metabolism might also be altered in GDM. To test this hypothesis we applied a method for the analysis of serotonin, metabolic intermediates and dopamine in urine by stable isotope dilution direct infusion electrospray ionization mass spectrometry (SID-MS). Indeed, serotonin and related metabolites differ significantly between control and GDM patients confirming the involvement of serotonin metabolism in GDM. Clustered correlation coefficient visualization of metabolite correlation networks revealed the different metabolic signatures between control and GDM patients. Eventually, the combination of selected blood plasma and urine sample metabolites improved the AUC prediction accuracy to 0.99. The detected GDM candidate biomarkers and the related systemic metabolic signatures are discussed in their pathophysiological context. Further studies with larger cohorts are necessary to underpin these observations.

Isolated mangiferin and naringenin exert antidiabetic effect via PPARγ/GLUT4 dual agonistic action with strong metabolic regulation

In this study, we isolated two compounds from the leaves of Salacia oblonga (SA1, mangiferin and SA2, naringenin), and their structures were confirmed by infrared spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and mass spectrometry. SA1 and SA2 were orally administered to streptozotocin-induced diabetic rats at 50 and 100 mg/kg daily for 15 days. Blood glucose level, serum lipid profile, oxidative stress parameters, histopathology, docking, molecular parameters, and NMR-based metabolic perturbation studies were performed to investigate the pharmacological activities of SA1 and SA2. Results suggested that both compounds reduced blood glucose level, restored body weight, and normalized lipid concentrations in the serum and oxidative stress biomarkers in the liver and pancreas. In addition, the docking study on several diabetes-associated targets revealed that both compounds had a strong binding affinity towards peroxisome proliferator-activated receptor gamma (PPAR_γ) and glucose transporter type 4 (GLUT4). Further real-time reverse transcription polymerase chain reaction and western blot analyses were performed to confirm the gene and protein expression levels of PPAR_γ and GLUT4 in the pancreatic tissues. Data obtained from the molecular studies showed that both compounds exhibited antidiabetic effects through dual activation of PPAR_γ/GLUT4 signaling pathways. Finally, the NMR-based metabolic studies showed that both compounds normalized the diabetogenic metabolites in the serum. Altogether, we concluded that SA1 and SA2 might be potential antidiabetic lead compounds for future drug development.

Effect of Ipomoea aquatica ethanolic extract in streptozotocin (STZ) induced diabetic rats via1H NMR-based metabolomics approach

BACKGROUND

Ipomoea aquatica (locally known as "kangkung") has previously been reported to have hypoglycemic activities on glucose level in diabetes patients. However, the effect of I. aquatica ethanolic extract on the metabolites in the body has remained unknown.

PURPOSE

This study provides new insights on the changes of endogenous metabolites caused by I. aquatica ethanolic extract and improves the understanding on the therapeutic efficacy and mechanism of I. aquatica ethanolic extract.

METHODS

By using a combination of ¹H nuclear magnetic resonance (NMR) with multivariate analysis (MVDA), the changes of metabolites due to I. aquatica ethanolic extract administration in obese diabetic-induced Sprague Dawley rats (OB+STZ+IA) were identified.

RESULTS

The results suggested 19 potential biomarkers with variable importance projections (VIP) above 0.5, which include creatine/creatinine, glucose, creatinine, citrate, carnitine, 2-oxoglutarate, succinate, hippurate, leucine, 1-methylnicotinamice (MNA), taurine, 3-hydroxybutyrate (3-HB), tryptophan, lysine, trigonelline, allantoin, formiate, acetoacetate (AcAc) and dimethylamine. From the changes in the metabolites, the affected pathways and aspects of metabolism were identified.

CONCLUSION

I. aquatica ethanolic extract increases metabolite levels such as creatinine/creatine, carnitine, MNA, trigonelline, leucine, lysine, 3-HB and decreases metabolite levels, including glucose and tricarboxylic acid (TCA) intermediates. This implies capabilities of I. aquatica ethanolic extract promoting glycolysis, gut microbiota and nicotinate/nicotinamide metabolism, improving the glomerular filtration rate (GFR) and reducing the β-oxidation rate. However, the administration of I. aquatica ethanolic extract has several drawbacks, such as unimproved changes in amino acid metabolism, especially in reducing branched chain amino acid (BCAA) synthesis pathways and lipid metabolism.

Targeted metabolome profiling by dual-probe microdialysis sampling and treatment using Gardenia jasminoides for rats with type 2 diabetes

Diabetes causes a variety of end-stage organ complications, including diabetic nephropathy. Metabolomics offers an approach for characterizing biofluid metabolic changes, but studies focusing on diabetic nephropathy are limited due to the loss of tissue-specific metabolic information. A microdialysis application for the sampling of intact endogenous metabolites has been developed, utilizing two probes simultaneously inserted into the kidney tissues and jugular vein of rats with type 2 diabetes. The comprehensive and quantitative analysis of 20 diagnostic biomarkers closely realated to type 2 diabetes and its complications were performed. Results indicated that amino acid and nucleotide levels were lower in diabetic rats, revealing that the metabolic pathways of amino acid, as well as purine and pyrimidine, were disturbed. Targeted metabolomics using mass spectrometry was performed to find potential therapeutic biomarkers and related metabolic pathways of Gardenia jasminoides (G. jasminoides) for treating diabetes. Results suggested that seven biomarkers in the kidney and five biomarkers in the blood were related to G. jasminoides. In addition, the marked perturbations of pathways were regulated after treatment with G. jasminoides, including amino acid metabolism and purine metabolism. These biomarkers and metabolic pathways provided new understanding for molecular mechanisms of G. jasminoides for treating diabetes and its complications.

Biochemical characterization and 1H NMR based metabolomics revealed Melicope lunu-ankenda leaf extract a potent anti-diabetic agent in rats

BACKGROUND

Type 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by continuous hyperglycemia associated with insulin resistance and /or reduced insulin secretion. There is an emerging trend regarding the use of medicinal plants for the treatment of diabetes mellitus. Melicope lunu-ankenda (ML) is one of the Melicope species belonging to the family Rutaceae. In traditional medicines, its leaves and flowers are known to exhibit prodigious health benefits. The present study aimed at investigating anti-diabetic effect of Melicope lunu-ankenda (ML) leaves extract.

METHODS

In this study, anti-diabetic effect of ML extract is investigated in vivo to evaluate the biochemical changes, potential serum biomarkers and alterations in metabolic pathways pertaining to the treatment of HFD/STZ induced diabetic rats with ML extract using 1H NMR based metabolomics approach. Type 2 diabetic rats were treated with different doses (200 and 400 mg/kg BW) of Melicope lunu-ankenda leaf extract for 8 weeks, and serum samples were examined for clinical biochemistry. The metabolomics study of serum was also carried out using 1H NMR spectroscopy in combination with multivariate data analysis to explore differentiating serum metabolites and altered metabolic pathways.

RESULTS

The ML leaf extract (400 mg/kg BW) treatment significantly increased insulin level and insulin sensitivity of obese diabetic rats, with concomitant decrease in glucose level and insulin resistance. Significant reduction in total triglyceride, cholesterol and low density lipoprotein was also observed after treatment. Interestingly, there was a significant increase in high density lipoprotein of the treated rats. A decrease in renal injury markers and activities of liver enzymes was also observed. Moreover, metabolomics studies clearly demonstrated that, ML extract significantly ameliorated the disturbance in glucose metabolism, tricarboxylic acid cycle, lipid metabolism, and amino acid metabolism.

CONCLUSION

ML leaf extract exhibits potent antidiabetic properties, hence could be a useful and affordable alternative option for the management of T2DM.

Specific patterns of spinal metabolites underlying α-Me-5-HT-evoked pruritus compared with histamine and capsaicin assessed by proton nuclear magnetic resonance spectroscopy

The mechanism behind itching is not well understood. Proton nuclear magnetic resonance (¹H-NMR) spectroscopic analysis of spinal cord extracts provides a quick modality for evaluating the specific metabolic activity of α-Me-5-HT-evoked pruritus mice. In the current study, four groups of young adult male C57Bl/6 mice were investigated; one group treated with saline, while the other groups intradermally injected with α-Me-5-HT (histamine independent pruritogen), histamine (histamine dependent pruritogen) and capsaicin (algogenic substance), respectively. The intradermal microinjection of α-Me-5-HT and histamine resulted in a dramatic increase in the itch behavior. Furthermore, the results of NMR studies of the spinal cord extracts revealed that the metabolites show very different patterns for these different drugs, especially when comparing α-Me-5-HT and capsaicin. All the animals in the groups of α-Me-5-HT and capsaicin were completely separated using the metabolite parameters and principal component analysis. For α-Me-5-HT, the concentrations of glutamate, GABA, glycine and aspartate increased significantly, especially for GABA (increased 17.2%, p=0.008). Furthermore, the concentration of NAA increased, but there was no significant difference (increased 11.3%, p=0.191) compared to capsaicin (decreased 29.1%, p=0.002). Thus the application of magnetic resonance spectroscopy technique, coupled with statistical analysis, could further explain the mechanism behind itching evoked by α-Me-5-HT or other drugs. It can thus improve our understanding of itch pathophysiology and pharmacological therapies which may contribute to itch relief.

Tryptophan and purine metabolites are consistently upregulated in the urinary metabolome of patients diagnosed with gestational diabetes mellitus throughout pregnancy: A longitudinal metabolomics study of Chinese pregnant women part 2

BACKGROUND

Gestational diabetes mellitus (GDM) is a pathological state of glucose intolerance associated with adverse pregnancy outcomes and an increased risk of developing maternal type 2 diabetes later in life. The mechanisms underlying GDM development are not fully understood. We examined the pathophysiology of GDM through comprehensive metabolic profiling of maternal urine, using participants from a longitudinal cohort of normal pregnancies and pregnancies complicated by GDM.

METHODS

Based on ultra-performance liquid chromatography/hybrid quadrupole time-of-flight mass spectrometry, an untargeted metabolomics study was performed to explore the differences in the urinary metabolome of GDM cases and healthy controls over the course of pregnancy. Multilevel statistical approaches were employed to address the complex metabolomic data obtained from a longitudinal cohort.

RESULTS

The results indicated that tryptophan and purine metabolism was associated with GDM. The tryptophan-kynurenine pathway was activated in the GDM subjects before placental hormones or the fetoplacental unit could have produced any physiological effect. Hypoxanthine, xanthine, xanthosine, and 1-methylhypoxanthine were all elevated in the urine metabolome of subjects with GDM. Catabolism of purine nucleosides leads ultimately to the production of uric acid, which discriminated the subjects with GDM from controls.

CONCLUSIONS

The results support the notion that GDM may be a predisposed condition, or prediabetic state, which is manifested during pregnancy. This challenges the conventional view of the pathogenesis of GDM, which assumes placental hormones are the major causes of insulin resistance in GDM.

Longitudinal analysis of hepatic transcriptome and serum metabolome demonstrates altered lipid metabolism following the onset of hyperglycemia in spontaneously diabetic biobreeding rats

Type 1 diabetes is associated with abberations of fat metabolism before and after the clinical onset of disease. It has been hypothesized that the absence of the effect of insulin in the liver contributes to reduced hepatic fat synthesis. We measured hepatic gene expression and serum metabolites before and after the onset of hyperglycemia in a BioBreeding rat model of type 1 diabetes. Functional pathway annotation identified that lipid metabolism was differentially expressed in hyperglycemic rats and that these pathways significantly overlapped with genes regulated by insulin. 17 serum metabolites significantly changed in concentration. All but 2 of the identified metabolites had previously been reported in type 1 diabetes, and carbohydrates were overall the most upregulated class of metabolites. We conclude that lack of insulin in the liver contributes to the changes in fat metabolism observed in type 1 diabetes. Further studies are needed to understand the clinical consequences of a lack of insulin in the liver in patients with type 1 diabetes.

Metabolite Variation in Lean and Obese Streptozotocin (STZ)-Induced Diabetic Rats via 1H NMR-Based Metabolomics Approach

Diabetes mellitus (DM) is considered as a complex metabolic disease because it affects the metabolism of glucose and other metabolites. Although many diabetes studies have been conducted in animal models throughout the years, the pathogenesis of this disease, especially between lean diabetes (ND + STZ) and obese diabetes (OB + STZ), is still not fully understood. In this study, the urine from ND + STZ, OB + STZ, lean/control (ND), and OB + STZ rats were collected and compared by using ¹H NMR metabolomics. The results from multivariate data analysis (MVDA) showed that the diabetic groups (ND + STZ and OB + STZ) have similarities and dissimilarities for a certain level of metabolites. Differences between ND + STZ and OB + STZ were particularly noticeable in the synthesis of ketone bodies, branched-chain amino acid (BCAA), and sensitivity towards the oral T2DM diabetes drug metformin. This finding suggests that the ND + STZ group was more similar to the T1DM model and OB + STZ to the T2DM model. In addition, we also managed to identify several pathways and metabolism aspects shared by obese (OB) and OB + STZ. The results from this study are useful in developing drug target-based research as they can increase understanding regarding the cause and effect of DM.

Metabolomics reveals the protective of Dihydromyricetin on glucose homeostasis by enhancing insulin sensitivity

Dihydromyricetin (DMY), an important flavanone found in Ampelopsis grossedentata, possesses antioxidative properties that ameliorate skeletal muscle insulin sensitivity and exert a hepatoprotective effect. However, little is known about the effects of DMY in the context of high-fat diet (HFD)-induced hepatic insulin resistance. Male Sprague-Dawley(SD) rats were fed a HFD(60% fat) supplemented with DMY for 8 weeks. The administration of DMY to the rats with HFD-induced insulin resistance reduces hyperglycemia, plasma levels of insulin, and steatosis in the liver. Furthermore, DMY treatment modulated 24 metabolic pathways, including glucose metabolism, the TCA cycle. DMY significantly enhanced glucose uptake and improved the translocation of glucose transporter 1. The specificity of DMY promoted the phosphorylation of AMP-activated protein kinase (AMPK). In addition, the exposure of HepG2 cells to high glucose concentrations impaired the insulin-stimulated phosphorylation of Akt2 Ser474 and insulin receptor substrate-1 (IRS-1) Ser612, increased GSK-3β phosphorylation, and upregulated G6Pase and PEPCK expression. Collectively, DMY improved glucose-related metabolism while reducing lipid levels in the HFD-fed rats. These data suggest that DMY might be a useful drug for use in type 2 diabetes insulin resistance therapy and for the treatment of hepatic steatosis.

Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles

Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method.

Anti-Diabetic Activity and Metabolic Changes Induced by Andrographis paniculata Plant Extract in Obese Diabetic Rats

Andrographis paniculata is an annual herb and widely cultivated in Southeast Asian countries for its medicinal use. In recent investigations, A. paniculata was found to be effective against Type 1 diabetes mellitus (Type 1 DM). Here, we used a non-genetic out-bred Sprague-Dawley rat model to test the antidiabetic activity of A. paniculata against Type 2 diabetes mellitus (Type 2 DM). Proton Nuclear Magnetic Resonance (¹H-NMR) spectroscopy in combination with multivariate data analyses was used to evaluate the A. paniculata and metformin induced metabolic effects on the obese and obese–diabetic (obdb) rat models. Compared to the normal rats, high levels of creatinine, lactate, and allantoin were found in the urine of obese rats, whereas, obese-diabetic rats were marked by high glucose, choline and taurine levels, and low lactate, formate, creatinine, citrate, 2-oxoglutarate, succinate, dimethylamine, acetoacetate, acetate, allantoin and hippurate levels. Treatment of A. paniculata leaf water extract was found to be quite effective in restoring the disturbed metabolic profile of obdb rats back towards normal conditions. Thisstudy shows the anti-diabetic potential of A. paniculata plant extract and strengthens the idea of using this plant against the diabetes. Further classical genetic methods and state of the art molecular techniques could provide insights into the molecular mechanisms involved in the pathogenesis of diabetes mellitus and anti-diabetic effects of A. paniculata water extract.

Novel insights into development of diabetic bladder disorder provided by metabolomic analysis of the rat nondiabetic and diabetic detrusor and urothelial layer

There are at present no published studies providing a global overview of changes in bladder metabolism resulting from diabetes. Such studies have the potential to provide mechanistic insight into the development of diabetic bladder disorder (DBD). In the present study, we compared the metabolome of detrusor and urothelial layer in a 1-mo streptozotocin-induced rat model of type 1 diabetes with nondiabetic controls. Our studies revealed that diabetes caused both common and differential changes in the detrusor and urothelial layer's metabolome. Diabetes resulted in similar changes in the levels of previously described diabetic markers in both tissues, such as glucose, lactate, 2-hydroxybutyrate, branched-chain amino acid degradation products, bile acids, and 1,5-anhydroglucitol, as well as markers of oxidative stress. In the detrusor (but not the urothelial layer), diabetes caused activation of the pentose-phosphate and polyol pathways, concomitant with a reduction in the TCA cycle and β-oxidation. Changes in detrusor energy-generating pathways resulted in an accumulation of sorbitol that, through generation of advanced glycation end products, is likely to play a central role in the development of DBD. In the diabetic urothelial layer there was decreased flux of glucose via glycolysis and changes in lipid metabolism, particularly prostaglandin synthesis, which also potentially contributes to detrusor dysfunction.

Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach

Type 2 diabetic coronary heart disease (T2DM-CHD) is a kind of serious and complex disease. Great attention has been paid to exploring its mechanism; however, the detailed understanding of T2DM-CHD is still limited. Plasma samples from 15 healthy controls, 13 coronary heart disease (CHD) patients, 15 type 2 diabetes mellitus (T2DM) patients and 28 T2DM-CHD patients were analyzed in this research. The potential biomarkers of CHD and T2DM were detected and screened out by (1)H NMR-based plasma metabolic profiling and multivariate data analysis. About 11 and 12 representative metabolites of CHD and T2DM were identified respectively, mainly including alanine, arginine, proline, glutamine, creatinine and acetate. Then the diagnostic model was further constructed based on the previous metabolites of CHD and T2DM to detect T2DM-CHD with satisfying sensitivity of 92.9%, specificity of 93.3% and accuracy of 93.2%, validating the robustness of (1)H NMR-based plasma metabolic profiling to diagnostic strategy. The results demonstrated that the NMR-based metabolomics approach processed good performance to identify diagnostic plasma biomarkers and most identified metabolites related to T2DM and CHD could be considered as predictors of T2DM-CHD as well as the therapeutic targets for prevention, which provided new insight into diagnosing and forecasting of complex diseases.

α-ketoglutarate is associated with delayed wound healing in diabetes

AIM

A high level of matrix metalloproteinase 9 (MMP-9) is a predictor of poor wound healing in diabetic foot ulcers. In skin keratinocytes, site-specific DNA demethylation plays an important role in MMP-9 expression. Ten-eleven translocation enzyme 2 (TET2) protein, one member of TET family, could rely on α-ketoglutarate (α-KG) as cosubstrate to exhibit catalytic activity of DNA demethylation. Here, we aimed to explore the changes of α-KG and its relationship with MMP-9 and TET2 during diabetic wound healing.

METHODS

Seventy-one cases of patients with diabetic foot ulcers and 53 cases of nondiabetic ulcers were enrolled. Serum, urine and wound fluids were collected for measurement of α-KG levels and MMP-9 expression. Skin tissues were collected for the measurement of TET2 and MMP-9 expression. Clinical parameters were collected, and transcutaneous oxygen pressure (TcPO2) levels of feet were detected.

RESULTS

The levels of α-KG, TET2 and MMP-9 were significantly increased in diabetic wound compared with nondiabetic wound (P = 0·010, 0·016 and 0·025). There was a significant correlation between a low TcPO2 and a high α-KG level of wound fluids (r = -0·395, P = 0·002). Further analysis showed that α-KG concentration had a positive correlation with both haemoglobin A1c (HbA1C) and 2 h postprandial blood glucose (PBG) (r = 0·393, P = 0·005; r = 0·320, P = 0·025, respectively).

CONCLUSIONS

The levels of α-KG, TET2 and MMP-9 were significantly increased in diabetic wound compared with nondiabetic wound. Elevated α-KG was related to local hypoxia ischaemia status and systematic poor glycaemic control.

Combining biochemical with (1)H NMR-based metabolomics approach unravels the antidiabetic activity of genipin and its possible mechanism

Diabetes mellitus is a typical heterogeneous metabolic disorder characterized by abnormal metabolism of carbohydrates, lipids and proteins. Genipin possesses a wide spectrum of biological activities including ameliorating effects on diabetes, but the definite mechanism of this effect remains unknown. To investigate the antidiabetic activities of genipin and explore the biochemical changes of serum endogenous metabolites on diabetic rats induced by alloxan, (1)H NMR spectroscopy coupled with multivariate data analysis was used to. All rats were randomly divided into six groups including negative control (NC) group, diabetic mellitus (DM) group, metformin hydrochloride group, high dose group of genipin, middle dose group of genipin and low dose group of genipin. Diabetes was induced by a single intraperitoneal injection of 120mg/kg body weight of alloxan. Serum samples were collected for the (1)H NMR-based metabolomics and clinical biochemical analysis. Daily oral administration of genipin (25, 50 and 100mg/kg body weight) and metformin hydrochloride (125mg/kg) for two weeks showed beneficial effects on blood glucose level (P<0.01). Significant differences in the metabolic profile as well as the result of biochemical parameters between the diabetic group and the control group were observed. The PLS-DA scores and corresponding loading plots demonstrated that genipin significantly restored the abnormal metabolic state. Detailed analysis of the altered metabolite levels indicated that genipin significantly ameliorated the disturbance in glucose metabolism, tricarboxylic acid cycle, lipid metabolism and amino acid metabolism. Genipin showed the best anti-diabetic effects at a dose of 100mg/kg in rats. This finding indicates that chemical and metabolomic approaches could be powerful tools for the investigation of the biochemical changes in pathological conditions or drug treatment.

Precise and rapid isotopomic analysis by (1)H-(13)C 2D NMR: Application to triacylglycerol matrices

An optimized HSQC sequence was tested and applied to triacylglycerol matrices to determine their isotopic and metabolomic profiles. Spectral aliasing and non-uniform sampling approaches were used to decrease the experimental time and to improve the resolution, respectively. An excellent long-term repeatability of signal integrals was achieved enabling to perform isotopic measurements. Thirty-two commercial vegetable oils were analyzed by this methodology. The results show that this method can be used to classify oil samples according to their geographical and botanical origins.

Metabolic alteration in obese diabetes rats upon treatment with Centella asiatica extract

ETHNOPHARMACOLOGICAL RELEVANCE

'Pegaga' is a traditional Malay remedy for a wide range of complaints. Among the 'pegaga', Centella asiatica has been used as a remedy for diabetes mellitus. Thus, we decided to validate this claim by evaluating the in vivo antidiabetic property of C. asiatica (CA) on T2DM rat model using the holistic (1)H NMR-based metabolomics approach.

METHOD

In this study, an obese diabetic (mimic of T2DM condition) animal model was developed using Sprague-Dawley rats fed with a high-fat diet and induced into diabetic condition by the treatment of a low dose of streptozotocin (STZ). The effect of C. asiatica extract on the experimental animals was followed based on the changes observed in the urinary and serum metabolites, measured by (1)H NMR of urine and blood samples collected over the test period.

RESULTS

A long-term treatment of obese diabetic rats with CA extract could reverse the glucose and lipid levels, as well as the tricarboxylic acid cycle and amino acid metabolic disorders, back towards normal states. Biochemical analysis also showed an increase of insulin production in diabetic rats upon treatment of CA extract.

CONCLUSION

This study has provided evidence that clearly supported the traditional use of CA as a remedy for diabetes. NMR-based metabolomics was successfully applied to show that CA produced both anti-hyperglycemic and anti-hyperlipidemic effects on a rat model. In addition to increasing the insulin secretion, the CA extract also ameliorates the metabolic pathways affected in the induced diabetic rats. This study further revealed the potential usage of CA extract in managing diabetes mellitus and the results of this work may contribute towards the further understanding of the underlying molecular mechanism of this herbal remedy.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

From sample treatment to biomarker discovery: A tutorial for untargeted metabolomics based on GC-(EI)-Q-MS

This tutorial provides a comprehensive description of the GC-MS-based untargeted metabolomics workflow including: ethical approval requirement, sample collection and storage, equipment maintenance and setup, sample treatment, monitoring of analytical variability, data pre-processing including deconvolution by free software such as AMDIS, data processing, statistical analysis and validation, detection of outliers and biological interpretation of the results. For each stage tricks will be suggested, pitfalls will be highlighted and advice will be provided on how to get the best from this methodology and technique. In addition, a step-by-step procedure and an example of our in-house library have been included in the supplementary material to lead the user through the concepts described herein. As a case study, an interesting example from one of our experiments at CEMBIO Research Centre is described, presenting an example of the use of this ready-to use protocol for identification of a metabolite that was not previously included in Fiehn commercial target library.

Suppression of radiation damping for high precision quantitative NMR

True quantitative analysis of concentrated samples by (1)H NMR is made very difficult by Radiation Damping. A novel NMR sequence (inspired by the WET NMR sequence and by Outer Volume Saturation methods) is therefore proposed to suppress this phenomenon by reducing the spatial area and consequently the number of spins contributing to the signal detected. The size of the detected volume can be easily chosen in a large range and line shape distortions are avoided thanks to a uniform signal suppression of the outer volume. Composition of a mixture can as a result be determined with very high accuracy (precision and trueness) at the per mille level whatever the concentrations and without hardware modification.