Software-assisted serum metabolite quantification using NMR

Human Pancreatic Islets React to Glucolipotoxicity by Secreting Pyruvate and Citrate

Progressive decline in pancreatic beta-cell function is central to the pathogenesis of type 2 diabetes (T2D). Here, we explore the relationship between the beta cell and its nutritional environment, asking how an excess of energy substrate leads to altered energy production and subsequent insulin secretion. Alterations in intracellular metabolic homeostasis are key markers of islets with T2D, but changes in cellular metabolite exchanges with their environment remain unknown. We answered this question using nuclear magnetic resonance-based quantitative metabolomics and evaluated the consumption or secretion of 31 extracellular metabolites from healthy and T2D human islets. Islets were also cultured under high levels of glucose and/or palmitate to induce gluco-, lipo-, and glucolipotoxicity. Biochemical analyses revealed drastic alterations in the pyruvate and citrate pathways, which appear to be associated with mitochondrial oxoglutarate dehydrogenase (OGDH) downregulation. We repeated these manipulations on the rat insulinoma-derived beta-pancreatic cell line (INS-1E). Our results highlight an OGDH downregulation with a clear effect on the pyruvate and citrate pathways. However, citrate is directed to lipogenesis in the INS-1E cells instead of being secreted as in human islets. Our results demonstrate the ability of metabolomic approaches performed on culture media to easily discriminate T2D from healthy and functional islets.

Warburg-associated acidification represses lactic fermentation independently of lactate, contribution from real-time NMR on cell-free systems

Lactate accumulation and acidification in tumours are a cancer hallmark associated with the Warburg effect. Lactic acidosis correlates with cancer malignancy, and the benefit it offers to tumours has been the subject of numerous hypotheses. Strikingly, lactic acidosis enhances cancer cell survival to environmental glucose depletion by repressing high-rate glycolysis and lactic fermentation, and promoting an oxidative metabolism involving reactivated respiration. We used real-time NMR to evaluate how cytosolic lactate accumulation up to 40 mM and acidification up to pH 6.5 individually impact glucose consumption, lactate production and pyruvate evolution in isolated cytosols. We used a reductive cell-free system (CFS) to specifically study cytosolic metabolism independently of other Warburg-regulatory mechanisms found in the cell. We assessed the impact of lactate and acidification on the Warburg metabolism of cancer cytosols, and whether this effect extended to different cytosolic phenotypes of lactic fermentation and cancer. We observed that moderate acidification, independently of lactate concentration, drastically reduces the glucose consumption rate and halts lactate production in different lactic fermentation phenotypes. In parallel, for Warburg-type CFS lactate supplementation induces pyruvate accumulation at control pH, and can maintain a higher cytosolic pyruvate pool at low pH. Altogether, we demonstrate that intracellular acidification accounts for the direct repression of lactic fermentation by the Warburg-associated lactic acidosis.

NMR metabolite quantification of a synthetic urine sample: an inter-laboratory comparison of processing workflows

INTRODUCTION

Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling.

OBJECTIVES

An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision.

METHODS

A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool.

RESULTS

For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables.

CONCLUSION

External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools.

Quantitative plasma profiling by 1H NMR-based metabolomics: impact of sample treatment

Introduction: There is evidence that sample treatment of blood-based biosamples may affect integral signals in nuclear magnetic resonance-based metabolomics. The presence of macromolecules in plasma/serum samples makes investigating low-molecular-weight metabolites challenging. It is particularly relevant in the targeted approach, in which absolute concentrations of selected metabolites are often quantified based on the area of integral signals. Since there are a few treatments of plasma/serum samples for quantitative analysis without a universally accepted method, this topic remains of interest for future research. Methods: In this work, targeted metabolomic profiling of 43 metabolites was performed on pooled plasma to compare four methodologies consisting of Carr-Purcell-Meiboom-Gill (CPMG) editing, ultrafiltration, protein precipitation with methanol, and glycerophospholipid solid-phase extraction (g-SPE) for phospholipid removal; prior to NMR metabolomics analysis. The effect of the sample treatments on the metabolite concentrations was evaluated using a permutation test of multiclass and pairwise Fisher scores. Results: Results showed that methanol precipitation and ultrafiltration had a higher number of metabolites with coefficient of variation (CV) values above 20%. G-SPE and CPMG editing demonstrated better precision for most of the metabolites analyzed. However, differential quantification performance between procedures were metabolite-dependent. For example, pairwise comparisons showed that methanol precipitation and CPMG editing were suitable for quantifying citrate, while g-SPE showed better results for 2-hydroxybutyrate and tryptophan. Discussion: There are alterations in the absolute concentration of various metabolites that are dependent on the procedure. Considering these alterations is essential before proceeding with the quantification of treatment-sensitive metabolites in biological samples for improving biomarker discovery and biological interpretations. The study demonstrated that g-SPE and CPMG editing are effective methods for removing proteins and phospholipids from plasma samples for quantitative NMR analysis of metabolites. However, careful consideration should be given to the specific metabolites of interest and their susceptibility to the sample treatment procedures. These findings contribute to the development of optimized sample preparation protocols for metabolomics studies using NMR spectroscopy.

A different approach to the quantification of human seminal plasma metabolites using high-resolution NMR spectroscopy

In this study, a reliable method was established for the absolute quantification of metabolite concentrations in human seminal plasma using ERETIC2, a quantification tool developed by Bruker based on the PULCON principle. The performance of the ERETIC2 was examined using an AVANCE III HD NMR spectrometer (600 MHz) equipped with a triple inverse 1.7 mm TXI probe in terms of some experimental parameters that may affect the accuracy and precision of the quantitative results. Then, the accuracy, precision, and repeatibility of ERETIC2 were determined using L-asparagine solutions at different concentrations. And it was evaluated by comparing it with the classical internal standard (IS) quantification method. The relative standard deviation (RSD) values for ERETIC2 were calculated in the range of 0.55-1.90% and the minimum recovery value was 99.9%, while the RSD values for the IS method were calculated in the range of 0.88-5.83% and recovery value was minimum 91.0%. Besides, the RSD values of the inter-day precisions for the ERETIC2 and IS methods were obtained to be in the range of 1.25 - 3.03% and 0.97 - 3.46%, respectively. Finally, the concentration values of seminal plasma metabolites were determined using different pulse programs with both methods for samples obtained from normozoospermic control and azoospermic patient groups. The results proved that this quantification method developed using NMR spectroscopy is easy to use in complex sample systems such as biological fluids and is a good alternative to the classical internal standard method in terms of accuracy and sensitivity. In addition, the improvement of the spectral resolution and sensitivity with the microcoil probe technology and the possibility of analyzing with minimum sample quantities has contributed positively to the results of this method.

Glycine Supplementation in Obesity Worsens Glucose Intolerance through Enhanced Liver Gluconeogenesis

Interactions between mitochondria and the endoplasmic reticulum, known as MAMs, are altered in the liver in obesity, which contributes to disruption of the insulin signaling pathway. In addition, the plasma level of glycine is decreased in obesity, and the decrease is strongly correlated with the severity of insulin resistance. Certain nutrients have been shown to regulate MAMs; therefore, we tested whether glycine supplementation could reduce insulin resistance in the liver by promoting MAM integrity. Glycine (5 mM) supported MAM integrity and insulin response in primary rat hepatocytes cultured under control and lipotoxic (palmitate 500 µM) conditions for 18 h. In contrast, in C57 BL/6 JOlaHsd mice (male, 6 weeks old) fed a high-fat, high-sucrose diet (HFHS) for 16 weeks, glycine supplementation (300 mg/kg) in drinking water during the last 6 weeks (HFHS-Gly) did not reverse the deleterious impact of HFHS-feeding on liver MAM integrity. In addition, glycine supplementation worsened fasting glycemia and glycemic response to intraperitoneal pyruvate injection compared to HFHS. The adverse impact of glycine supplementation on hepatic gluconeogenesis was further supported by the higher oxaloacetate/acetyl-CoA ratio in the liver in HFHS-Gly compared to HFHS. Although glycine improves MAM integrity and insulin signaling in the hepatocyte in vitro, no beneficial effect was found on the overall metabolic profile of HFHS-Gly-fed mice.

NMR-based metabolomic analysis of human plasma to examine the effect of exposure to persistent organic pollutants

Persistent organic pollutants (POPs) are lipophilic environmental toxins, and the level of chemicals accumulated in the body through the food chain has been linked to the incidence of diseases such as type 2 diabetes, cardiovascular disease, and cancer. We analyzed the concentration of POPs and circulating metabolites and investigated the associations between the concentration of plasma metabolites and the levels of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) to determine the effect of the accumulation of POPs in human samples. Metabolic profiling of plasma from 276 Korean participants was performed using ¹H nuclear magnetic resonance (NMR) and statistical analyses. The concentrations of PCBs and OCPs in each sample were measured. Correlation analysis and a covariate-adjusted general linear model (GLM) were used to investigate the association of the concentration of POPs with circulating metabolites in human blood samples. We found that four categories of Σ6PCBs and Σ5OCPs based on rank were significantly correlated with 4 and 5 metabolites, respectively, after adjusting for confounding factors, including age, sex, body mass index (BMI), smoking status, alcohol intake, physical activity, triglycerides, and total cholesterol. According to the GLM analyses, 3 metabolites, namely, creatinine, acetate, and formate, among the 4 correlated metabolites were associated with four categories of rank-based Σ6PCBs. On the other hand, the quartiles of the rank-based Σ5OCPs were not associated with any circulating metabolites among the 5 correlated metabolites. Our findings indicate that the metabolites related to short-chain fatty acids and creatine can be useful risk indicators for estimating the effect of PCB exposure.

Absolute Metabolite Quantification Using Pure Shift NMR: Toward Quantitative Metabolic Profiling of Aqueous Biological Samples

Accurate quantification of metabolites by nuclear magnetic resonance (NMR) is of prime importance in the field of health sciences for understanding the metabolic pathways of the investigated system, to address the mechanisms of action of diseases, and improving their diagnosis, treatment, and prognosis. Unfortunately, the absolute quantitative analysis of complex samples is still limited by sensitivity and resolution issues that are intrinsic to this technique. Ultrahigh-resolution pure shift methods have especially shown to be suitable for interpreting mixtures of metabolites in biological samples. Here, we introduce a robust analytical protocol based on the use of a pure shift library of calibration reference spectra to fit the fingerprint of each metabolite of interest and determine its concentration. The approach based on the SAPPHIRE pulse sequence enhanced with a block for solvent suppression has been validated through the results of a series of model mixtures, exhibiting excellent trueness (slope values in the range of 0.93-1.02) and linearity (R² > 0.996) in a total time (a few hours) that is fully compatible with metabolomics studies. Furthermore, we have successfully applied our method to determine the absolute metabolite concentrations in a lymphoma extracellular medium, which improves metabolomic protocols reported to date by providing a quantitative and highly resolved vision of metabolic processes at play.

Two Ways to Achieve the Same Goal-Two Validated Quantitative NMR Strategies for a Low-Abundance Natural Product in Standardized Extracts: The Case of Hepatodamianol in Turnera diffusa

The quantification of low-abundance secondary metabolites in plant extracts is an analytical problem that can be addressed by different analytical platforms, the most common being those based on chromatographic methods coupled to a high-sensitivity detection system. However, in recent years nuclear magnetic resonance (NMR) has become an analytical tool of primary choice for this type of problem because of its reliability, inherent simplicity in sample preparation, reduced analysis time, and low solvent consumption. The versatility of strategies based on quantitative NMR (qNMR), such as internal and external standards and electronic references, among others, and the need to develop validated analytical methods make it essential to compare procedures that must rigorously satisfy the analytical well-established acceptance criteria for method validation. In this work, two qNMR methods were developed for the quantification of hepatodamianol, a bioactive component of T. diffusa. The first method was based on a conventional external standard calibration, and the second one was based on the pulse length-based concentration determination (PULCON) method using the ERETIC2 module as a quantitation tool available in TopSpin software. The results show that both procedures allow the content of the analyte of interest in a complex matrix to be determined in a satisfactory way, under strict analytical criteria. In addition, ERETIC2 offers additional advantages such as a reduction in experimental time, reagent consumption, and waste generated.

Identification of interaction partners using protein aggregation and NMR spectroscopy

The interaction among proteins is one of the most fundamental methods of information transfer in the living system. Many methods have been developed in order to identify the interaction pairs or groups either in vivo or in vitro. The in vitro pulldown/coprecipitation assay directly observes the protein that binds to the target. This method involves electrophoresis, which is a technique of a low resolution as well as a low throughput. As a better alternative, we wish to propose a new method that is based on the NMR spectroscopy. This method utilizes the aggregation of the target protein and the concomitant signal disappearance of the interacting partner. The aggregation is accomplished by the elastin-like polypeptide, which is fused to the target. If a protein binds to this supramolecular complex, its NMR signal then becomes too broadened in order to be observed, which is the basic phenomenon of the NMR spectroscopy. Thus, the protein that loses its signal is the one that binds to the target. A compound that interferes with these types of bindings among the proteins can be identified by observing the reappearance of the protein signals with the simultaneous disappearance of the signals of the compound. This technique will be applied in order to find an interaction pair in the information transfer pathway as well as a compound that disrupts it. This proposed method should be able to work with a mixture of proteins and provide a higher resolution in order to find the binding partner in a higher throughput fashion.

Metabolic profiling of serum and urine in lactating dairy cows affected by subclinical ketosis using proton nuclear magnetic resonance spectroscopy

Ketosis is associated with high milk yield during lactating or insufficient feed intake in lactating dairy cows. However, few studies have been conducted on the metabolomics of ketosis in Korean lactating dairy cows. The present study aimed to investigate the serum and urine metabolites profiling of lactating dairy cows through proton nuclear magnetic resonance (¹H-NMR) spectroscopy and comparing those between healthy (CON) and subclinical ketosis (SCK) groups. Six lactating dairy cows were categorized into CON and SCK groups. All experimental Holstein cows were fed total mixed ration. Serum and urine samples were collected from the jugular vein of the neck and by hand sweeping the perineum, respectively. The metabolites in the serum and urine were determined using ¹H-NMR spectroscopy. Identification and quantification of metabolites was performed by Chenomx NMR Suite 8.4 software. Metabolites statistical analysis was performed by Metaboanalyst version 5.0 program. In the serum, the acetoacetate level was significantly (p < 0.05) higher in the SCK group than in the CON group, and whereas acetate, galactose and pyruvate levels tended to be higher. CON group had significantly (p < 0.05) higher levels of 5-aminolevulinate and betaine. Indole-3-acetate, theophylline, p-cresol, 3-hydroxymandelate, gentisate, N-acetylglucosamine, N-nitrosodimethylamine, xanthine and pyridoxine levels were significantly (p < 0.05) higher in the urine of the SCK group than that in the CON group, which had higher levels of homogentisate, ribose, gluconate, ethylene glycol, maltose, 3-methyl-2-oxovalerate and glycocholate. Some significantly (p < 0.05) different metabolites in the serum and urine were associated with ketosis diseases, inflammation, energy balance and body weight. This study will be contributed useful a future ketosis metabolomics studies in Korea.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

Dietary obesity in mice is associated with lipid deposition and metabolic shifts in the lungs sharing features with the liver

Obesity is associated with both chronic and acute respiratory illnesses, such as asthma, chronic obstructive pulmonary disease (COPD) or increased susceptibility to infectious diseases. Anatomical but also systemic and local metabolic alterations are proposed contributors to the pathophysiology of lung diseases in the context of obesity. To bring perspective to this discussion, we used NMR to compare the obesity-associated metabolomic profiles of the lung with those of the liver, heart, skeletal muscles, kidneys, brain and serum from male C57Bl/6J mice fed with a high-fat and high-sucrose (HFHSD) diet vs. standard (SD) chow for 14 weeks. Our results showed that the lung was the second most affected organ after the liver, and that the two organs shared reduced one-carbon (1C) metabolism and increased lipid accumulation. Altered 1C metabolism was found in all organs and in the serum, but serine levels were increased only in the lung of HFHSD compared to SD. Lastly, tricarboxylic acid (TCA)-derived metabolites were specifically and oppositely regulated in the serum and kidneys but not in other organs. Collectively, our data highlighted that HFHSD induced specific metabolic changes in all organs, the lung being the second most affected organ, the main alterations affecting metabolite concentrations of the 1C pathway and, to a minor extend, TCA. The absolute metabolite quantification performed in this study reveals some metabolic specificities affecting both the liver and the lung, that may reveal common metabolic determinants to the ongoing pathological process.

Exploration of metabolite profiles in the biofluids of dairy cows by proton nuclear magnetic resonance analysis

Studies that screen for metabolites produced in ruminants are actively underway. We aimed to evaluate the metabolic profiles of five biofluids (ruminal fluid, serum, milk, urine, and feces) in dairy cow by using proton nuclear magnetic resonance (1H-NMR) and provide a list of metabolites in each biofluid for the benefit of future research. We analyzed the metabolites in five biofluids from lactating cows using proton nuclear magnetic resonance imaging; 96, 73, 88, 118, and 128 metabolites were identified in the five biofluids, respectively. In addition, 8, 6, 9, and 17 metabolites were unique to ruminal fluid, serum, milk, and urine, respectively. The metabolites present at high concentrations were: acetate, propionate, and butyrate in ruminal fluid; lactate, glucose, and acetate in serum; and lactose, guanidoacetate, and glucitol in milk. In addition, the following metabolites were present at high concentrations: hippurate, urea, and trimethylamine N-oxide in urine and acetate, propionate, and butyrate in feces. The score plots of the principal component analysis did not show clear distinctions among the five biofluid samples. The purpose of this study was to verify the ability of our metabolomics approaches to identify metabolites in the biofluids of dairy cows.

Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications

Nuclear Magnetic Resonance (NMR) spectroscopy is a quantitative analytical tool commonly utilized for metabolomics analysis. Quantitative NMR (qNMR) is a field of NMR spectroscopy dedicated to the measurement of analytes through signal intensity and its linear relationship with analyte concentration. Metabolomics-based NMR exploits this quantitative relationship to identify and measure biomarkers within complex biological samples such as serum, plasma, and urine. In this review of quantitative NMR-based metabolomics, the advancements and limitations of current techniques for metabolite quantification will be evaluated as well as the applications of qNMR in biomedical metabolomics. While qNMR is limited by sensitivity and dynamic range, the simple method development, minimal sample derivatization, and the simultaneous qualitative and quantitative information provide a unique landscape for biomedical metabolomics, which is not available to other techniques. Furthermore, the non-destructive nature of NMR-based metabolomics allows for multidimensional analysis of biomarkers that facilitates unambiguous assignment and quantification of metabolites in complex biofluids.

Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures

Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.

Use of Nanovesicles from Orange Juice to Reverse Diet-Induced Gut Modifications in Diet-Induced Obese Mice

We have determined whether orange juice-derived nanovesicles (ONVs) could be used for the treatment of obesity-associated intestinal complications. ONVs were characterized by lipidomic, metabolomic, electron microscopy. In vitro, intestinal barriers (IBs = Caco-2+HT-29-MTX) were treated with ONVs and co-cultured with adipocytes to monitor IB fat release. In vivo, obesity was induced with a high-fat, high-sucrose diet (HFHSD mice) for 12 weeks. Then, half of HFHSD mice were gavaged with ONVs. One-month ONV treatment did not modify HFHSD-induced insulin resistance but reversed diet-induced gut modifications. In the jejunum, ONVs increased villi size, reduced triglyceride content, and modulated mRNA levels of genes involved in immune response (tumor necrosis factor [TNF]-α and interleukin [IL]-1β), barrier permeability (CLDN1, OCLN, ZO1), fat absorption, and chylomicron release. ONVs targeted microsomal triglyceride transfer protein (MTP) and angiopoietin-like protein-4 (ANGPTL4), two therapeutic targets to reduce plasma lipids and inflammation in gastrointestinal diseases. Interestingly, ONV treatment did not aggravate liver steatosis, as MTP mRNA was increased in the liver. Therefore, ONVs protected both intestine and the liver from fat overload associated with the HFHSD. As ONVs concentrated amino acids and bioactive lipids versus orange juice, which are deficient in obese patients, the use of ONVs as a dietary supplement could bring physiological relevant compounds in the jejunum to accelerate the restoration of intestinal functions during weight loss in obese patients.

Identification of Potential Biomarkers in the Cervicovaginal Fluid by Metabolic Profiling for Preterm Birth

During pregnancy, dysbiosis in the vaginal microbiota directly affects the metabolic profiles, which might impact preterm birth (PTB). In this study, we performed cervicovaginal fluid (CVF) metabolic profiling using nuclear magnetic resonance (NMR) spectroscopy and identified the metabolic markers for predicting PTB. In this nested case-control study, 43 South Korean pregnant women with PTB (n = 22), and term birth (TB; n = 21) were enrolled with their demographic profiles, and CVF samples were collected by vaginal swabs. The PTB group had two subgroups based on post-CVF sampling birth: PTB less than (PTB < 7 d) and more than 7 days (PTB ≥ 7 d). We observed significant differences in the gestational age at birth (GAB), cervical length (CL), and neonatal birth weight among the groups. The principal component analysis (PCA), and partial least square discriminant analysis (PLS-DA) scatter plot showed the separation between the PTB < 7 d group, and the TB group. Out of 28 identified metabolites, acetone, ethanol, ethylene glycol, formate, glycolate, isopropanol, methanol, and trimethylamine N-oxide (TMAO) were significantly increased in the PTB group compared with the TB group. The ROC curve analysis revealed that the acetone, ethylene glycol, formate, glycolate, isopropanol, methanol, and TMAO had the best predictive values for PTB. Additionally, the correlation analysis of these metabolites showed a strong negative correlation with GAB and CL. These metabolites could be beneficial markers for the clinical application of PTB prediction.

Accurate estimation of diffusion coefficient for molecular identification in a complex background

To eliminate the effects of complex background signals and to enhance the accuracy of the diffusion coefficient measurement, derivative NMR spectroscopy with negligible loss of the spectral quality is introduced based on the customized Savitzky-Golay method and used to construct diffusion-ordered NMR spectroscopy (DOSY). The criterion of the method was established by simulations. The application of this method on mouse urine and serum showed that the accuracy and precision of diffusion coefficient measurements in a complex background were improved to enhance the identification of molecules. Graphical abstract Diffusion-ordered NMR spectroscopy is a powerful tool for analyzing complex mixtures. To improve the accuracy of diffusion coefficient measurement, the magnitude of complex derivative spectra is introduced as a post-processing method to eliminate the effects of background signals, broad signals, or distorted baseline. And thus, accurate estimate of the diffusion coefficient is ensured to enhance the molecule identification.

Differential Effects of Typical Korean Versus American-Style Diets on Gut Microbial Composition and Metabolic Profile in Healthy Overweight Koreans: A Randomized Crossover Trial

The Westernized diet has been associated with the pathogenesis of metabolic diseases, whereas a Korean diet has been reported to exert beneficial effects on health in several studies. However, the effects of Western and Korean diets on the gut microbiome and host metabolome are unclear. To examine the diet-specific effects on microbiome and metabolome, we conducted a randomized crossover clinical trial of typical Korean diet (TKD), typical American diet (TAD), and recommended American diet (RAD). The trial involved a 4-week consumption of an experimental diet followed by a 2-week interval before diet crossover. 16S rRNA sequencing analysis identified 16, 10, and 14 differential bacteria genera specific to TKD, RAD, and TAD, respectively. The Firmucutes-Bacteroidetes ratio was increased by TKD. Nuclear magnetic resonance metabolome profiling revealed that TKD enriched branched chain amino acid metabolism, whereas ketone body metabolism was evident in RAD and TAD. Microbiome and metabolome responses to the experimental diets varied with individual enterotypes. These findings provide evidence that the gut microbiome and host metabolome rapidly respond to different cultural diets. The findings will inform clarification of the diet-related communication networks of the gut microbiome and host metabolome in humans.

Metabolic Phenotyping of Adipose-Derived Stem Cells Reveals a Unique Signature and Intrinsic Differences between Fat Pads

White adipose tissues are functionally heterogeneous and differently manage the excess of energy supply. While the expansion of subcutaneous adipose tissues (SAT) is protective in obesity, that of visceral adipose tissues (VAT) correlates with the emergence of metabolic diseases. Maintained in fat pads throughout life, adipose stem cells (ASC) are mesenchymal-like stem cells with adipogenesis and multipotent differentiation potential. ASC from distinct fat pads have long been reported to present distinct proliferation and differentiation potentials that are maintained in culture, yet the origins of these intrinsic differences are still unknown. Metabolism is central to stem cell fate decision in line with environmental changes. In this study, we performed high-resolution nuclear magnetic resonance (NMR) metabolomic analyses of ASC culture supernatants in order to characterize their metabolic phenotype in culture. We identified and quantified 29 ASC exometabolites and evaluated their consumption or secretion over 72 h of cell culture. Both ASC used glycolysis and mitochondrial metabolism, as evidenced by the high secretions of lactate and citrate, respectively, but V-ASC mostly used glycolysis. By varying the composition of the cell culture medium, we showed that glutaminolysis, rather than glycolysis, supported the secretion of pyruvate, alanine, and citrate, evidencing a peculiar metabolism in ASC cells. The comparison of the two types of ASC in glutamine-free culture conditions also revealed the role of glutaminolysis in the limitation of pyruvate routing towards the lactate synthesis, in S-ASC but not in V-ASC. Altogether, our results suggest a difference between depots in the capacity of ASC mitochondria to assimilate pyruvate, with probable consequences on their differentiation potential in pathways requiring an increased mitochondrial activity. These results highlight a pivotal role of metabolic mechanisms in the discrimination between ASC and provide new perspectives in the understanding of their functional differences.

Metabolic changes in urine and serum during progression of diabetic kidney disease in a mouse model

Diabetic kidney disease (DKD) involves various pathogenic processes during progression to end stage renal disease, and activated metabolic pathways might be changing based on major pathophysiologic mechanisms as DKD progresses. In this study, nuclear magnetic resonance spectroscopy (NMR)-based metabolic profiling was performed in db/db mice to suggest potential biomarkers for early detection and its progression. We compared concentrations of serum and urinary metabolites between db/m and db/db mice at 8 or 20 weeks of age and investigated whether changes between 8 and 20 weeks in each group were significant. The metabolic profiles demonstrated significantly increased urine levels of glucose and tricarboxylic acid cycle intermediates at both 8 and 20 weeks of age in db/db mice. These intermediates also exhibited strong positive associations with urinary albumin excretion, suggesting that they may be potential biomarkers for early diagnosis. On the contrary, branched chain amino acid and homocysteine-methionine metabolism were activated early in the disease, whereas ketone and fatty acid metabolism were significantly changed in the late phase of the disease. We demonstrated phase-specific alterations in metabolites during progression of DKD. This study provides insights into perturbed mechanisms during evolution of the disease and identifies potential novel biomarkers for DKD.

Use of Hybrid Capillary Tube Apparatus on 400 MHz NMR for Quantitation of Crucial Low-Quantity Metabolites Using aSICCO Signal

Metabolites of new chemical entities can influence safety and efficacy of a molecule and often times need to be quantified in preclinical studies. However, synthetic standards of metabolites are very rarely available in early discovery. Alternate approaches such as biosynthesis need to be explored to generate these metabolites. Assessing the quantity and purity of these small amounts of metabolites with a nondestructive analytical procedure becomes crucial. Quantitative NMR becomes the method of choice for these samples. Recent advances in high-field NMR (>500 MHz) with the use of cryoprobe technology have helped to improve sensitivity for analysis of small microgram quantity of such samples. However, this type of NMR instrumentation is not routinely available in all laboratories. To analyze microgram quantities of metabolites on a routine basis with lower-resolution 400 MHz NMR instrument fitted with a broad band fluorine observe room temperature probe, a novel hybrid capillary tube setup was developed. To quantitate the metabolite in the sample, an artificial signal insertion for calculation of concentration observed (aSICCO) method that introduces an internally calibrated mathematical signal was used after acquiring the NMR spectrum. The linearity of aSICCO signal was established using ibuprofen as a model analyte. The limit of quantification of this procedure was 0.8 mM with 10 K scans that could be improved further with the increase in the number of scans. This procedure was used to quantify three metabolites-phenytoin from fosphenytoin, dextrophan from dextromethorphan, and 4-OH-diclofenac from diclofenac-and is suitable for minibiosynthesis of metabolites from in vitro systems.