Eliminating the dication-induced intersample chemical-shift variations for NMR-based biofluid metabonomic analysis

Effects of Sample Dilution on Nuclear Magnetic Resonance-Derived Metabolic Profiles of Human Urine

Traditionally, a relatively big urine volume (e.g., 500 μL) is used in nuclear magnetic resonance (NMR)-based human metabolomics, which is not feasible for studies with limited/precious samples. Although urine may be diluted before conventional high-throughput metabolomics analysis, the comprehensive effect of urine dilution on metabolic profiles is unknown. Here, for the first time, we systematically investigated the effect of urine dilution on 1H NMR metabolic profiles, by evaluating signal detectability, integration, signal-to-noise ratio (SNR), chemical shift (δ) and its variation, and signal overlapping of 47 metabolites in 10 volunteers. We observed significant linear changes along with increased dilution, including decreased integration and SNR, altered δ, decreased intersample variation of δ, and increased separation between overlapped signals, e.g., lactate and threonine, β-d-glucose and an unassigned signal, and histidine and 3-methylhistidine. We further tested the 40% dilution level (i.e., employing 300 μL urine) in an epidemiological study containing 1018 pregnant women from the Tongji-Shuangliu Birth Cohort, showing acceptable detectability and chemical shift variability for most of the 47 metabolites profiled. It indicated that mild (e.g., 40%) dilution of human urine can largely preserve the high-abundance metabolites profiled, reduce intersample chemical shift variations, and increase separations of overlapped signals, which is an improvement of routine sample preparation methods in NMR-based metabolomics and is applicable for studies with limited urine volumes, including large-scale epidemiological studies.

Characterization of triclosan-induced hepatotoxicity and triclocarban-triggered enterotoxicity in mice by multiple omics screening

Triclosan (2,4,4'-trichloro-2'-hydroxydiphenyl ether, TCS) and triclocarban (3,4,4'-trichloro-carbanilide, TCC) are two antimicrobial agents commonly used for personal care products. Previous studies primarily focused on respective harmful effects of TCS and TCC. In terms of their structural similarities and differences, however, the structure-toxicity relationships on health effects of TCS and TCC exposure remain unclear. Herein, global ¹H NMR-based metabolomics was employed to screen the changes of metabolic profiling in various biological matrices including liver, serum, urine, feces and intestine of mice exposed to TCS and TCC at chronic and acute dosages. Metagenomics was also applied to analyze the gut microbiota modulation by TCS and TCC exposure. Targeted MS-based metabolites quantification, histopathological examination and biological assays were subsequently conducted to supply confirmatory information on respective toxicity of TCS and TCC. We found that oral administration of TCS mainly induced significant liver injuries accompanied with inflammation and dysfunction, hepatic steatosis fatty acids and bile acids metabolism disorders; while TCC exposure caused marked intestine injuries leading to striking disruption of colonic morphology, inflammatory status and intestinal barrier integrity, intestinal bile acids metabolism and microbial community. These comparative results provide novel insights into structure-dependent mechanisms of TCS-induced hepatotoxicity and TCC-triggered enterotoxicity in mice.

Simultaneous quantification of 70 elements in biofluids within 5 min using inductively coupled plasma mass spectrometry to reveal elementomic phenotypes of healthy Chinese adults

High-throughput quantification of the composition of all chemical elements (elementome) in biological samples is essential for understanding their diverse functions in large cohort studies. We, here, established an ICP-MS method to simultaneously quantify 70 elements in 50 μL biofluids within 5 min. This validated method had excellent quantification linearity (R² > 0.998), sensitivity (with LOD as low as 1.0 ng/L), precision (CV<15%), accuracy (|RE|<20% except Hg), recovery (80-120%), throughput and coverage with minute samples. The method also showed good applicability to multiple biofluids including human serum, plasma, urine and goat serum samples. By using this method, we furture measured 70 elements in blood plasma samples from 758 Chinese adult participants and established the first reference intervals for the concentration of these elements from 127 healthy adults in this population. This offers a high-throughput quantitative elementomics method to define population elementomic phenotypes and for investigating the diverse biological functions of many elements in multiple biological matrices.

Randomized Controlled-Feeding Study of Dietary Emulsifier Carboxymethylcellulose Reveals Detrimental Impacts on the Gut Microbiota and Metabolome

BACKGROUND & AIMS

Epidemiologic and murine studies suggest that dietary emulsifiers promote development of diseases associated with microbiota dysbiosis. Although the detrimental impact of these compounds on the intestinal microbiota and intestinal health have been demonstrated in animal and in vitro models, impact of these food additives in healthy humans remains poorly characterized.

METHODS

To examine this notion in humans, we performed a double-blind controlled-feeding study of the ubiquitous synthetic emulsifier carboxymethylcellulose (CMC) in which healthy adults consumed only emulsifier-free diets (n = 9) or an identical diet enriched with 15 g per day of CMC (n = 7) for 11 days.

RESULTS

Relative to control subjects, CMC consumption modestly increased postprandial abdominal discomfort and perturbed gut microbiota composition in a way that reduced its diversity. Moreover, CMC-fed subjects exhibited changes in the fecal metabolome, particularly reductions in short-chain fatty acids and free amino acids. Furthermore, we identified 2 subjects consuming CMC who exhibited increased microbiota encroachment into the normally sterile inner mucus layer, a central feature of gut inflammation, as well as stark alterations in microbiota composition.

CONCLUSIONS

These results support the notion that the broad use of CMC in processed foods may be contributing to increased prevalence of an array of chronic inflammatory diseases by altering the gut microbiome and metabolome (ClinicalTrials.gov, number NCT03440229).

Diet standardization reduces intra-individual microbiome variation

The human gut microbiota is highly heterogenous between individuals and also exhibits considerable day-to-day variation within individuals. We hypothesized that diet contributed to such inter- and/or intra-individual variance. Hence, we investigated the extent to which diet normalization impacted microbiota heterogeneity. We leveraged the control arm of our recently reported controlled-feeding study in which nine healthy individuals consumed a standardized additive-free diet for 10 days. Diet normalization did not impact inter-individual differences but reduced the extent of intra-individual day-to-day variation in fecal microbiota composition. Such decreased heterogeneity reflected individual-specific enrichment and depletion of an array of taxa microbiota members and was paralleled by a trend toward reduced intra-individual variance in fecal LPS and flagellin, which, collectively, reflect microbiota's pro-inflammatory potential. Yet, the microbiota of some subjects did not change significantly over the course of the study, suggesting heterogeneity in microbiota resilience to dietary stress or that baseline diets of some subjects were perhaps similar to our study's standardized diet. Collectively, our results indicate that short-term diet heterogeneity contributes to day-to-day intra-individual microbiota composition variance.

Prediction of Metabolic Disorders Using NMR-Based Metabolomics: The Shanghai Changfeng Study

A metabolically healthy status, whether obese or not, is a transient stage with the potential to develop into metabolic disorders during the course of life. We investigated the incidence of metabolic disorders in 1078 metabolically healthy Chinese adults from the Shanghai Changfeng Study and looked for metabolites that discriminated the participants who would develop metabolic disorders in the future. Participants were divided into metabolically healthy overweight/obesity (MHO) and metabolically healthy normal weight (MHNW) groups according to their body mass index (BMI) and metabolic status. Their serum metabolomic profile was measured using a ¹H nuclear magnetic resonance spectrometer (¹H-NMR). The prevalence of diabetes, hypertriglyceridemia, hypercholesterolemia and metabolic syndrome was similar between the MHNW and MHO participants at baseline. After a median of 4.2 years of follow-up, more MHO participants became metabolically unhealthy than MHNW participants. However, a subgroup of MHO participants who remained metabolically healthy (MHO → MHO) had a similar prevalence of metabolic disorders as the MHNW participants at the follow-up examination, despite a significant reduction in their serum concentrations of high-density lipoprotein (HDL) and an elevation in valine, leucine, alanine and tyrosine. Further correlation analysis indicated that serum intermediate-density lipoprotein (IDL) and very low-density lipoprotein cholesterol (VLDL-CH) might be involved in the transition from metabolically healthy to unhealthy status and could be valuable to identify the MHNW and MHO with increased metabolic risks.

Improved Automated Quantification Algorithm (AQuA) and Its Application to NMR-Based Metabolomics of EDTA-Containing Plasma

We have recently presented an Automated Quantification Algorithm (AQuA) and demonstrated its utility for rapid and accurate absolute metabolite quantification in ¹H NMR spectra in which positions and line widths of signals were predicted from a constant metabolite spectral library. The AQuA quantifies based on one preselected signal per metabolite and employs library spectra to model interferences from other metabolite signals. However, for some types of spectra, the interspectral deviations of signal positions and line widths can be pronounced; hence, interferences cannot be modeled using a constant spectral library. We here address this issue and present an improved AQuA that handles interspectral deviations. The improved AQuA monitors and characterizes the appearance of specific signals in each spectrum and automatically adjusts the spectral library to model interferences accordingly. The performance of the improved AQuA was tested on a large data set from plasma samples collected using ethylenediaminetetraacetic acid (EDTA) as an anticoagulant (n = 772). These spectra provided a suitable test system for the improved AQuA since EDTA signals (i) vary in intensity, position, and line width between spectra and (ii) interfere with many signals from plasma metabolites targeted for quantification (n = 54). Without the improvement, ca. 20 out of the 54 metabolites would have been overestimated. This included acetylcarnitine and ornithine, which are considered particularly difficult to quantify with ¹H NMR in EDTA-containing plasma. Furthermore, the improved AQuA performed rapidly (<10 s for all spectra). We believe that the improved AQuA provides a basis for automated quantification in other data sets where specific signals show interspectral deviations.

NMR-Based Metabolomics in Cancer Research

Nuclear magnetic resonance (NMR) spectroscopy offers reproducible quantitative analysis and structural identification of metabolites in various complex biological samples, such as biofluids (plasma, serum, and urine), cells, tissue extracts, and even intact organs. Therefore, NMR-based metabolomics, a mainstream metabolomic platform, has been extensively applied in many research fields, including pharmacology, toxicology, pathophysiology, nutritional intervention, disease diagnosis/prognosis, and microbiology. In particular, NMR-based metabolomics has been successfully used for cancer research to investigate cancer metabolism and identify biomarker and therapeutic targets. This chapter highlights the innovations and challenges of NMR-based metabolomics platform and its applications in cancer research.

Auto-hydrolysis of red clover as "green" approach to (iso)flavonoid enriched products

Optimal parameters for the auto-hydrolysis of (iso)flavone glycosides to aglycones in ground Trifolium pratense L. plant material were established as a "green" method for the production of a reproducible red clover extract (RCE). The process utilized 72-h fermentation in DI water at 25 and 37 °C. The aglycones obtained at 25 °C, as determined by UHPLC-UV and quantitative ¹H NMR (qHNMR), increased significantly in the auto-hydrolyzed (ARCE) (6.2-6.7% w/w biochanin A 1, 6.1-9.9% formononetin 2) vs a control ethanol (ERCE) extract (0.24% 1, 0.26% 2). After macerating ARCE with 1:1 (v/v) diethyl ether/hexanes (ARCE-d/h), 1 and 2 increased to 13.1-16.7% and 14.9-18.4% w, respectively, through depletion of fatty components. The final extracts showed chemical profiles similar to that of a previous clinical RCE. Biological standardization revealed that the enriched ARCE-d/h extracts produced the strongest estrogenic activity in ERα positive endometrial cells (Ishikawa cells), followed by the precursor ARCE. The glycoside-rich ERCE showed no estrogenic activity. The estrogenicity of ARCE-d/h was similar to that of the clinical RCE. The lower potency of the ARCE compared to the prior clinical RCE indicated that substantial amounts of fatty acids/matter likely reduce the estrogenicity of crude hydrolyzed preparations. The in vitro dynamic residual complexity of the conversion of biochanin A to genistein was evaluated by LC-MS-MS. The outcomes help advance translational research with red clover and other (iso)flavone-rich botanicals by inspiring the preparation of (iso)flavone aglycone-enriched extracts for the exploration of new in vitro and ex vivo bioactivities that are unachievable with genuine, glycoside-containing extracts.

Inducible phospholipid transfer protein deficiency ameliorates atherosclerosis

BACKGROUND AND AIMS

Atherosclerosis progression and regression studies are related to its prevention and treatment. Although we have gained extensive knowledge on germline phospholipid transfer protein (PLTP) deficiency, the effect of inducible PLTP deficiency in atherosclerosis remains unexplored.

METHODS

We generated inducible PLTP (iPLTP)-knockout (KO) mice and measured their plasma lipid levels after feeding a normal chow or a Western-type diet. Adenovirus associated virus-proprotein convertase subtilisin/kexin type 9 (AAV-PCSK9) was used to induce hypercholesterolemia in the mice. Collars were placed around the common carotid arteries, and atherosclerosis progression and regression in the carotid arteries and aortic roots were evaluated.

RESULTS

On a normal chow diet, iPLTP-KO mice exhibited decreased cholesterol, phospholipid, apoA-I, and apoB levels compared with control mice. Furthermore, the overall amount of high-density lipoprotein (HDL) particles was reduced in these mice, but this effect was more profound for larger HDL particles. On a Western-type diet, iPLTP-KO mice again exhibited reduced levels of all tested lipids, even though the basal lipid levels were increased. Additionally, these mice displayed significantly reduced atherosclerotic plaque sizes with increased plaque stability. Importantly, inducible PLTP deficiency significantly ameliorated atherosclerosis by reducing the size of established plaques and the number of macrophages in the plaques without causing lipid accumulation in the liver.

CONCLUSIONS

Induced PLTP deficiency in adult mice reduces plasma total cholesterol and triglycerides, prevents atherosclerosis progression, and promotes atherosclerosis regression. Thus, PLTP inhibition is a promising therapeutic approach for atherosclerosis.

Short-Term Intake of Hesperetin-7-O-Glucoside Affects Fecal Microbiota and Host Metabolic Homeostasis in Mice

Hesperetin-7-O-glucoside (Hes-7-G) is a typical flavonoid monoglucoside isolated from Citri Reticulatae Pericarpium (CRP), which is commonly used as a food adjuvant and exhibits potential biological activities. To explore the interaction between Hes-7-G ingestion and microbiome and host metabolism, here, 16S rRNA gene sequencing was first used to analyze the alteration of fecal microbiome in mice after Hes-7-G intake. Metabolic homeostasis in mice was subsequently investigated using untargeted ¹H NMR-based metabolomics and targeted metabolite profiling. We found that dietary Hes-7-G significantly regulated fecal microbiota and its derived metabolites, including short-chain fatty acids (SCFAs) and tryptophan metabolites (indole and its derivatives), in feces of mice. Regulation of microbiota was further confirmed by the significantly changed urinary hippurate and trimethylamine N-oxide (TMAO), co-metabolites of the microbe and host. We also found that dietary Hes-7-G modulated the host tricarboxylic acid cycle (TCA) involved in energy metabolism. These findings suggested that Hes-7-G exhibits potential beneficial effects for human health.

Blood molecular markers associated with COVID-19 immunopathology and multi-organ damage

COVID-19 is characterized by dysregulated immune responses, metabolic dysfunction and adverse effects on the function of multiple organs. To understand host responses to COVID-19 pathophysiology, we combined transcriptomics, proteomics, and metabolomics to identify molecular markers in peripheral blood and plasma samples of 66 COVID-19-infected patients experiencing a range of disease severities and 17 healthy controls. A large number of expressed genes, proteins, metabolites, and extracellular RNAs (exRNAs) exhibit strong associations with various clinical parameters. Multiple sets of tissue-specific proteins and exRNAs varied significantly in both mild and severe patients suggesting a potential impact on tissue function. Chronic activation of neutrophils, IFN-I signaling, and a high level of inflammatory cytokines were observed in patients with severe disease progression. In contrast, COVID-19-infected patients experiencing milder disease symptoms showed robust T-cell responses. Finally, we identified genes, proteins, and exRNAs as potential biomarkers that might assist in predicting the prognosis of SARS-CoV-2 infection. These data refine our understanding of the pathophysiology and clinical progress of COVID-19.

Quantitative Metabonomic Phenotypes in Different Structures of Mung Bean (Vigna radiata) Seeds and Their Germination-Associated Dynamic Changes

Plant seed germination involving dynamic water uptakes and biochemical changes is essential for preservation of plant germplasm resource and worldwide food supply. To understand the germination-associated compartmental biochemistry changes, we quantitatively analyzed the metabolite composition (metabonome) for embryonic axes, cotyledons, and testae of mung bean (Vigna radiata) seeds in three germination phases using the NMR-based metabonomics approach. We found that three structures of mung bean seeds had distinct metabonomic phenotypes dominated by 53 metabolites including amino acids, carbohydrates, organic acids, choline metabolites, nucleotides/nucleosides, and shikimate-mediated secondary metabolites together with calcium and magnesium cations. During germination, all three seed structures had outstanding but distinct metabonomic changes. Both embryonic axis and cotyledon showed remarkable metabolic changes related to degradation of carbohydrates and proteins, metabolism of amino acids, nucleotides/nucleosides, and choline together with energy metabolism and shikimate-mediated plant secondary metabolism. The metabonomic changes in these two structures were mostly related to multiple functions for biochemical activities in the former and nutrient mobilizations in the latter. In contrast, testa metabonomic changes mainly reflected the metabolite leakages from the other two structures. Phase 1 of germination was featured with degradation of oligosaccharides and proteins and recycling of stored nucleic acids together with anaerobic metabolisms, whereas phase 2 was dominated by energy metabolism, biosynthesis of osmolytes, and plant secondary metabolites. These provided essential metabolic information for understanding the biochemistry associated with early events of seed germination and possible metabolic functions of different seed structures for plant development.

Pursuing Experimental Reproducibility: An Efficient Protocol for the Preparation of Cerebrospinal Fluid Samples for NMR-based Metabolomics and Analysis of Sample Degradation

NMR-based metabolomics investigations of human biofluids offer great potential to uncover new biomarkers. In contrast to protocols for sample collection and biobanking, procedures for sample preparation prior to NMR measurements are still heterogeneous, thus compromising the comparability of the resulting data. Herein, we present results of an investigation of the handling of cerebrospinal fluid (CSF) samples for NMR metabolomics research. Origins of commonly observed problems when conducting NMR experiments on this type of sample are addressed, and suitable experimental conditions in terms of sample preparation and pH control are discussed. Sample stability was assessed by monitoring the degradation of CSF samples by NMR, hereby identifying metabolite candidates, which are potentially affected by sample storage. A protocol was devised yielding consistent spectroscopic data as well as achieving overall sample stability for robust analysis. We present easy to adopt standard operating procedures with the aim to establish a shared sample handling strategy that facilitates and promotes inter-laboratory comparison, and the analysis of sample degradation provides new insights into sample stability.

Quantitative Metabonomic Analysis Reveals the Germination-Associated Dynamic and Systemic Biochemical Changes for Mung-Bean (Vigna radiata) Seeds

Seed germination is essential for plant survival, germplasm resource preservation, and worldwide food supplies, although the germination-associated seed biochemical variations are not fully understood. With the NMR-based metabonomics, we quantitatively analyzed the comprehensive metabolite composition (metabonome) of mung-bean (Vigna radiata) seeds at eight time points of germination covering all three phases. We found that mung-bean seed metabonomes were dominated by 63 metabolites including lipids, amino acids, oligo-/monosaccharides, cyclitols, cholines, organic acids, nucleotides/-sides, nicotinates, and the shikimate pathway-mediated secondary metabolites. During germination, metabolic changes included mainly the degradation of proteins and raffinose family oligosaccharides, glycolysis, tricarboxylic acid (TCA) cycle, anaerobic respiration, biosynthesis of osmolytes and antioxidants together with the metabolisms of nucleotides/-sides, nicotinates, and amino acids. Oligosaccharide degradation was the primary energy source for germination, which coupled with the mobilization of starch and protein storages to produce sugars and amino acids for biomaterial and energy generations. Osmotic and redox regulations were prerequisites for seed germination together with mitochondrial reparations and generations to enable TCA cycle. During the postgermination growth stage (phase-3), the use of small molecules including amino acids and saccharides was switched to meet the growth demands of radicle cells. Small metabolites passed freely through seed testa leaking into the culture media during early germination but were reabsorbed by seed cells around the postgermination growth stage. Extra after-ripening accelerated these metabolic processes of seeds in phase-1, especially the biosynthesis of cyclitols, choline, and nicotinates, increasing the germination uniformity in terms of speed and percentage. Germination-resistant seeds were incapable of activating the germination-associated metabolic processes.

Systems Metabolic Alteration in a Semi-Dwarf Rice Mutant Induced by OsCYP96B4 Gene Mutation

Dwarfism and semi-dwarfism are among the most valuable agronomic traits in crop breeding, which were adopted by the “Green Revolution”. Previously, we reported a novel semi-dwarf rice mutant (oscyp96b4) derived from the insertion of a single copy of Dissociator (Ds) transposon into the gene OsCYP96B4. However, the systems metabolic effect of the mutation is not well understood, which is important for understanding the gene function and developing new semi-dwarf mutants. Here, the metabolic phenotypes in the semi-dwarf mutant (M) and ectopic expression (ECE) rice line were compared to the wild-type (WT) rice, by using nuclear magnetic resonance (NMR) metabolomics and quantitative real-time polymerase chain reaction (qRT-PCR). Compared with WT, ECE of the OsCYP96B4 gene resulted in significant increase of γ-aminobutyrate (GABA), glutamine, and alanine, but significant decrease of glutamate, aromatic and branched-chain amino acids, and some other amino acids. The ECE caused significant increase of monosaccharides (glucose, fructose), but significant decrease of disaccharide (sucrose); induced significant changes of metabolites involved in choline metabolism (phosphocholine, ethanolamine) and nucleotide metabolism (adenosine, adenosine monophosphate, uridine). These metabolic profile alterations were accompanied with changes in the gene expression levels of some related enzymes, involved in GABA shunt, glutamate and glutamine metabolism, choline metabolism, sucrose metabolism, glycolysis/gluconeogenesis pathway, tricarboxylic acid (TCA) cycle, nucleotide metabolism, and shikimate-mediated secondary metabolism. The semi-dwarf mutant showed corresponding but less pronounced changes, especially in the gene expression levels. It indicates that OsCYP96B4 gene mutation in rice causes significant alteration in amino acid metabolism, carbohydrate metabolism, nucleotide metabolism, and shikimate-mediated secondary metabolism. The present study will provide essential information for the OsCYP96B4 gene function analysis and may serve as valuable reference data for the development of new semi-dwarf mutants.

A vitamin-C-derived DNA modification catalysed by an algal TET homologue

Methylation of cytosine to 5-methylcytosine (5mC) is a prevalent DNA modification found in many organisms. Sequential oxidation of 5mC by ten-eleven translocation (TET) dioxygenases results in a cascade of additional epigenetic marks and promotes demethylation of DNA in mammals^1,2. However, the enzymatic activity and function of TET homologues in other eukaryotes remains largely unexplored. Here we show that the green alga Chlamydomonas reinhardtii contains a 5mC-modifying enzyme (CMD1) that is a TET homologue and catalyses the conjugation of a glyceryl moiety to the methyl group of 5mC through a carbon-carbon bond, resulting in two stereoisomeric nucleobase products. The catalytic activity of CMD1 requires Fe(II) and the integrity of its binding motif His-X-Asp, which is conserved in Fe-dependent dioxygenases³. However, unlike previously described TET enzymes, which use 2-oxoglutarate as a co-substrate⁴, CMD1 uses L-ascorbic acid (vitamin C) as an essential co-substrate. Vitamin C donates the glyceryl moiety to 5mC with concurrent formation of glyoxylic acid and CO₂. The vitamin-C-derived DNA modification is present in the genome of wild-type C. reinhardtii but at a substantially lower level in a CMD1 mutant strain. The fitness of CMD1 mutant cells during exposure to high light levels is reduced. LHCSR3, a gene that is critical for the protection of C. reinhardtii from photo-oxidative damage under high light conditions, is hypermethylated and downregulated in CMD1 mutant cells compared to wild-type cells, causing a reduced capacity for photoprotective non-photochemical quenching. Our study thus identifies a eukaryotic DNA base modification that is catalysed by a divergent TET homologue and unexpectedly derived from vitamin C, and describes its role as a potential epigenetic mark that may counteract DNA methylation in the regulation of photosynthesis.

Disturbed energy and amino acid metabolism with their diagnostic potential in mitral valve disease revealed by untargeted plasma metabolic profiling

INTRODUCTION

Mitral valve disease (MVD), including mitral valve regurgitation (MR) and mitral valve stenosis (MS), is a chronic and progressive cardiac malady. However, the metabolic alterations in MVD is not well-understood till now. The current gold standard diagnostic test, transthoracic echocardiography, has limitations on high-throughput measurement and lacks molecular information for early diagnosis of the disease.

OBJECTIVE

The present study aimed to investigate the biochemical alterations and to explore their diagnostic potential for MVD.

METHODS

Plasma metabolic profile derangements and their diagnostic potential were non-invasively explored in 34 MR and 20 MS patients against their corresponding controls, using high-throughput NMR-based untargeted metabolomics.

RESULTS

Eighteen differential metabolites were identified for MR and MS patients respectively, on the basis of multivariate and univariate data analysis, which were mainly involved in energy metabolism, amino acid metabolism, calcium metabolism and inflammation. These differential metabolites, notably the significantly down-regulated formate and lactate, showed high diagnostic potential for MVD by using Spearman's rank-order correlation analysis and ROC analysis.

CONCLUSIONS

To the best of our knowledge, the present study is the first one that explores the metabolic derangements and their diagnostic values in MVD patients using metabolomics. The findings indicated that metabolic disturbance occurred in MVD patients, with plasma formate and lactate emerged as important candidate biomarkers for MVD.

1H NMR-based metabolomics approach to investigating the renal protective effects of Genipin in diabetic rats

Diabetic nephropathy is one of the various complications of diabetes mellitus, affecting patients for lifetime. Earlier studies have revealed that genipin can not only improve diabetes, but also induce cytotoxicity. Therefore, it is not clear which effect of genipin on kidneys occurs, when it is used in the treatment of diabetes. In the present study, we performed nuclear magnetic resonance (NMR)-based metabolomics analysis of urine and kidney tissue samples obtained from diabetic rats to explore the change of endogenous metabolites associated with diabetes and concomitant kidney disease. Nine significant differential metabolites that were closely related to renal function were screened. They were mainly related to three metabolic pathways: synthesis and degradation of ketone bodies, glycine, serine and threonine metabolism, and butanoate metabolism, which are involved in methylamine metabolism, energy metabolism and amino acid metabolism. In addition, after the intervention of genipin, the metabolic levels of all the metabolites tended to be normal, indicating a protective effect of genipin on kidneys. Our results may be helpful for understanding the antidiabetic effect of genipin.

Berberine Directly Affects the Gut Microbiota to Promote Intestinal Farnesoid X Receptor Activation

Intestinal bacteria play an important role in bile acid metabolism and in the regulation of multiple host metabolic pathways (e.g., lipid and glucose homeostasis) through modulation of intestinal farnesoid X receptor (FXR) activity. Here, we examined the effect of berberine (BBR), a natural plant alkaloid, on intestinal bacteria using in vitro and in vivo models. In vivo, the metabolomic response and changes in mouse intestinal bacterial communities treated with BBR (100 mg/kg) for 5 days were assessed using NMR- and mass spectrometry-based metabolomics coupled with multivariate data analysis. Short-term BBR exposure altered intestinal bacteria by reducing Clostridium cluster XIVa and IV and their bile salt hydrolase (BSH) activity, which resulted in the accumulation of taurocholic acid (TCA). The accumulation of TCA was associated with activation of intestinal FXR, which can mediate bile acid, lipid, and glucose metabolism. In vitro, isolated mouse cecal bacteria were incubated with three doses of BBR (0.1, 1, and 10 mg/ml) for 4 hours in an anaerobic chamber. NMR-based metabolomics combined with flow cytometry was used to evaluate the direct physiologic and metabolic effect of BBR on the bacteria. In vitro, BBR exposure not only altered bacterial physiology but also changed bacterial community composition and function, especially reducing BSH-expressing bacteria like Clostridium spp. These data suggest that BBR directly affects bacteria to alter bile acid metabolism and activate FXR signaling. These data provide new insights into the link between intestinal bacteria, nuclear receptor signaling, and xenobiotics.

Decreased glutathione biosynthesis contributes to EGFR T790M-driven erlotinib resistance in non-small cell lung cancer

Epidermal growth factor receptor (EGFR) inhibitors such as erlotinib are novel effective agents in the treatment of EGFR-driven lung cancer, but their clinical impact is often impaired by acquired drug resistance through the secondary T790M EGFR mutation. To overcome this problem, we analysed the metabonomic differences between two independent pairs of erlotinib-sensitive/resistant cells and discovered that glutathione (GSH) levels were significantly reduced in T790M EGFR cells. We also found that increasing GSH levels in erlotinib-resistant cells re-sensitised them, whereas reducing GSH levels in erlotinib-sensitive cells made them resistant. Decreased transcription of the GSH-synthesising enzymes (GCLC and GSS) due to the inhibition of NRF2 was responsible for low GSH levels in resistant cells that was directly linked to the T790M mutation. T790M EGFR clinical samples also showed decreased expression of these key enzymes; increasing intra-tumoural GSH levels with a small-molecule GST inhibitor re-sensitised resistant tumours to erlotinib in mice. Thus, we identified a new resistance pathway controlled by EGFR T790M and a therapeutic strategy to tackle this problem in the clinic.

NMR Chemical Shift Ranges of Urine Metabolites in Various Organic Solvents

Signal stability is essential for reliable multivariate data analysis. Urine samples show strong variance in signal positions due to inter patient differences. Here we study the exchange of the solvent of a defined urine matrix and how it affects signal and integral stability of the urinary metabolites by NMR spectroscopy. The exchange solvents were methanol, acetonitrile, dimethyl sulfoxide, chloroform, acetone, dichloromethane, and dimethyl formamide. Some of these solvents showed promising results with a single batch of urine. To evaluate further differences between urine samples, various acid, base, and salt solutions were added in a defined way mimicking to some extent inter human differences. Corresponding chemical shift changes were monitored.

Tumor growth affects the metabonomic phenotypes of multiple mouse non-involved organs in an A549 lung cancer xenograft model

The effects of tumorigenesis and tumor growth on the non-involved organs remain poorly understood although many research efforts have already been made for understanding the metabolic phenotypes of various tumors. To better the situation, we systematically analyzed the metabolic phenotypes of multiple non-involved mouse organ tissues (heart, liver, spleen, lung and kidney) in an A549 lung cancer xenograft model at two different tumor-growth stages using the NMR-based metabonomics approaches. We found that tumor growth caused significant metabonomic changes in multiple non-involved organ tissues involving numerous metabolic pathways, including glycolysis, TCA cycle and metabolisms of amino acids, fatty acids, choline and nucleic acids. Amongst these, the common effects are enhanced glycolysis and nucleoside/nucleotide metabolisms. These findings provided essential biochemistry information about the effects of tumor growth on the non-involved organs.

Correlations of Fecal Metabonomic and Microbiomic Changes Induced by High-fat Diet in the Pre-Obesity State

Obesity resulting from interactions of genetic and environmental factors becomes a serious public health problem worldwide with alterations of the metabolic phenotypes in multiple biological matrices involving multiple metabolic pathways. To understand the contributions of gut microbiota to obesity development, we analyzed dynamic alterations in fecal metabonomic phenotype using NMR and fecal microorganism composition in rats using pyrosequencing technology during the high-fat diet (HFD) feeding for 81 days (pre-obesity state). Integrated analysis of these two phenotypic datasets was further conducted to establish correlations between the altered rat fecal metabonome and gut microbiome. We found that one-week HFD feeding already caused significant changes in rat fecal metabonome and such changes sustained throughout 81-days feeding with the host and gut microbiota co-metabolites clearly featured. We also found that HFD caused outstanding decreases in most fecal metabolites implying enhancement of gut absorptions. We further established comprehensive correlations between the HFD-induced changes in fecal metabonome and fecal microbial composition indicating contributions of gut microbiota in pathogenesis and progression of the HFD-induced obesity. These findings provided essential information about the functions of gut microbiota in pathogenesis of metabolic disorders which could be potentially important for developing obesity prevention and treatment therapies.

Reprogramming of Seed Metabolism Facilitates Pre-harvest Sprouting Resistance of Wheat

Pre-harvest sprouting (PHS) is a worldwide problem for wheat production and transgene antisense-thioredoxin-s (anti-trx-s) facilitates outstanding resistance. To understand the molecular details of PHS resistance, we analyzed the metabonomes of the transgenic and wild-type (control) wheat seeds at various stages using NMR and GC-FID/MS. 60 metabolites were dominant in these seeds including sugars, organic acids, amino acids, choline metabolites and fatty acids. At day-20 post-anthesis, only malate level in transgenic wheat differed significantly from that in controls whereas at day-30 post-anthesis, levels of amino acids and sucrose were significantly different between these two groups. For mature seeds, most metabolites in glycolysis, TCA cycle, choline metabolism, biosynthesis of proteins, nucleotides and fatty acids had significantly lower levels in transgenic seeds than in controls. After 30-days post-harvest ripening, most metabolites in transgenic seeds had higher levels than in controls including amino acids, sugars, organic acids, fatty acids, choline metabolites and NAD⁺. These indicated that anti-trx-s lowered overall metabolic activities of mature seeds eliminating pre-harvest sprouting potential. Post-harvest ripening reactivated the metabolic activities of transgenic seeds to restore their germination vigor. These findings provided essential molecular phenomic information for PHS resistance of anti-trx-s and a credible strategy for future developing PHS resistant crops.

Modelling the acid/base 1H NMR chemical shift limits of metabolites in human urine

INTRODUCTION

Despite the use of buffering agents the ¹H NMR spectra of biofluid samples in metabolic profiling investigations typically suffer from extensive peak frequency shifting between spectra. These chemical shift changes are mainly due to differences in pH and divalent metal ion concentrations between the samples. This frequency shifting results in a correspondence problem: it can be hard to register the same peak as belonging to the same molecule across multiple samples. The problem is especially acute for urine, which can have a wide range of ionic concentrations between different samples.

OBJECTIVES

To investigate the acid, base and metal ion dependent ¹H NMR chemical shift variations and limits of the main metabolites in a complex biological mixture.

METHODS

Urine samples from five different individuals were collected and pooled, and pre-treated with Chelex-100 ion exchange resin. Urine samples were either treated with either HCl or NaOH, or were supplemented with various concentrations of CaCl₂, MgCl₂, NaCl or KCl, and their ¹H NMR spectra were acquired.

RESULTS

Nonlinear fitting was used to derive acid dissociation constants and acid and base chemical shift limits for peaks from 33 identified metabolites. Peak pH titration curves for a further 65 unidentified peaks were also obtained for future reference. Furthermore, the peak variations induced by the main metal ions present in urine, Na⁺, K⁺, Ca²⁺ and Mg²⁺, were also measured.

CONCLUSION

These data will be a valuable resource for ¹H NMR metabolite profiling experiments and for the development of automated metabolite alignment and identification algorithms for ¹H NMR spectra.

A ratiometric NMR pH sensing strategy based on a slow-proton-exchange (SPE) mechanism

Real time and non-invasive detection of pH in live biological systems is crucial for understanding the physiological role of acid-base homeostasis and for detecting pathological conditions associated with pH imbalance. One method to achieve in vivo pH monitoring is NMR. Conventional NMR methods, however, mainly utilize molecular sensors displaying pH-dependent chemical shift changes, which are vulnerable to multiple pH-independent factors. Here, we present a novel ratiometric strategy for sensitive and accurate pH sensing based on a small synthetic molecule, SPE1, which exhibits exceptionally slow proton exchange on the NMR time scale. Each protonation state of the sensor displays distinct NMR signals and the ratio of these signals affords precise pH values. In contrast to standard NMR methods, this ratiometric mechanism is not based on a chemical shift change, and SPE1 binds protons with high selectivity, resulting in accurate measurements. SPE1 was used to measure the pH in a single oocyte as well as in bacterial cultures, demonstrating the versatility of this method and establishing the foundation for broad biological applications.

Recent developments in sample preparation and data pre-treatment in metabonomics research

Metabonomics is a powerful approach for biomarker discovery and an effective tool for pinpointing endpoint metabolic effects of external stimuli, such as pathogens and disease development. Due to its wide applications, metabonomics is required to deal with various biological samples of different properties. Hence sample preparation and corresponding data pre-treatment become important factors in ensuring validity of an investigation. In this review, we summarize some recent developments in metabonomics sample preparation and data-pretreatment procedures.

Dietary Modulation of Gut Microbiota Contributes to Alleviation of Both Genetic and Simple Obesity in Children

Gut microbiota has been implicated as a pivotal contributing factor in diet-related obesity; however, its role in development of disease phenotypes in human genetic obesity such as Prader-Willi syndrome (PWS) remains elusive. In this hospitalized intervention trial with PWS (n = 17) and simple obesity (n = 21) children, a diet rich in non-digestible carbohydrates induced significant weight loss and concomitant structural changes of the gut microbiota together with reduction of serum antigen load and alleviation of inflammation. Co-abundance network analysis of 161 prevalent bacterial draft genomes assembled directly from metagenomic datasets showed relative increase of functional genome groups for acetate production from carbohydrates fermentation. NMR-based metabolomic profiling of urine showed diet-induced overall changes of host metabotypes and identified significantly reduced trimethylamine N-oxide and indoxyl sulfate, host-bacteria co-metabolites known to induce metabolic deteriorations. Specific bacterial genomes that were correlated with urine levels of these detrimental co-metabolites were found to encode enzyme genes for production of their precursors by fermentation of choline or tryptophan in the gut. When transplanted into germ-free mice, the pre-intervention gut microbiota induced higher inflammation and larger adipocytes compared with the post-intervention microbiota from the same volunteer. Our multi-omics-based systems analysis indicates a significant etiological contribution of dysbiotic gut microbiota to both genetic and simple obesity in children, implicating a potentially effective target for alleviation.

RESEARCH IN CONTEXT

Poorly managed diet and genetic mutations are the two primary driving forces behind the devastating epidemic of obesity-related diseases. Lack of understanding of the molecular chain of causation between the driving forces and the disease endpoints retards progress in prevention and treatment of the diseases. We found that children genetically obese with Prader-Willi syndrome shared a similar dysbiosis in their gut microbiota with those having diet-related obesity. A diet rich in non-digestible but fermentable carbohydrates significantly promoted beneficial groups of bacteria and reduced toxin-producers, which contributes to the alleviation of metabolic deteriorations in obesity regardless of the primary driving forces.

Metabonomic Changes Associated with Atherosclerosis Progression for LDLR(-/-) Mice

Atherosclerosis resulting from hyperlipidemia causes many serious cardiovascular diseases. To understand the systems changes associated with pathogenesis and progression of atherosclerosis, we comprehensively analyzed the dynamic metabonomic changes in multiple biological matrices of LDLR(-/-) mice using NMR and GC-FID/MS with gene expression, clinical chemistry, and histopathological data as well. We found that 12 week "Western-type" diet (WD) treatment caused obvious aortic lesions, macrophage infiltration, and collagen level elevation in LDLR(-/-) mice accompanied by up-regulation of inflammatory factors including aortic ICAM-1, MCP-1, iNOS, MMP2, and hepatic TNFα and IL-1β. The WD-induced atherosclerosis progression was accompanied by metabonomic changes in multiple matrices including biofluids (plasma, urine) and (liver, kidney, myocardial) tissues involving multiple metabolic pathways. These included disruption of cholesterol homeostasis, disturbance of biosynthesis of amino acids and proteins, altered gut microbiota functions together with metabolisms of vitamin-B3, choline, purines, and pyrimidines. WD treatment caused down-regulation of SCD1 and promoted oxidative stress reflected by urinary allantoin elevation and decreases in hepatic PUFA-to-MUFA ratio. When switching to normal diet, atherosclerotic LDLR(-/-) mice reprogrammed their metabolisms and reversed the atherosclerosis-associated metabonomic changes to a large extent, although aortic lesions, inflammation parameters, macrophage infiltration, and collagen content were only partially alleviated. We concluded that metabolisms of fatty acids and vitamin-B3 together with gut microbiota played crucially important roles in atherosclerosis development. These findings offered essential biochemistry details of the diet-induced atherosclerosis and demonstrated effectiveness of the integrated metabonomic analysis of multiple biological matrices for understanding the molecular aspects of cardiovascular diseases.

Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review

The metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.

Dynamic analysis of the endogenous metabolites in depressed patients treated with TCM formula Xiaoyaosan using urinary (1)H NMR-based metabolomics

ETHNOPHAMACOLOGICAL RELEVANCE

Xiaoyaosan (XYS), one of the best-known traditional Chinese medicine prescriptions with a long history of use, is composed of Bupleurum chinense DC., Paeonia lactiflora Pall., Poria cocos (Schw.) Wolf, Angelica sinensis (Oliv.) Diels, Zingiber officinale Rosc., Atractylodes macrocephala Koidz., Glycyrrhiza uralensis Fisch., and Mentha haplocalyx Briq. For centuries, XYS has been widely used in China for the treatment of mental disorders such as depression. However, the complicated mechanism underlying the antidepressant activity of XYS is not yet well-understood. This understanding is complicated by the sophisticated pathophysiology of depression and by the complexity of XYS, which has multiple constituents acting on different metabolic pathways. The variations of endogenous metabolites in depressed patients after administration of XYS may help elucidate the anti-depressant effect and mechanism of action of XYS. The aim of this study is to establish the metabolic profile of depressive disorder and to investigate the changes of endogenous metabolites in the depressed patients before and after the treatment of Xiaoyaosan using the dynamic analysis of urine metabolomics profiles based on (1)H NMR.

MATERIALS AND METHODS

Twenty-one depressed patients were recruited from the Traditional Chinese Medicine Department of the First Affiliated Hospital of Shanxi Medical University. Small endogenous metabolites present in urine samples were measured by nuclear magnetic resonance (NMR) and analyzed by multivariate statistical methods. The patients then received XYS treatment for six weeks, after which their Hamilton Depression Scale (HAMD) scores were significantly decreased compared with their baseline scores (p≤0.01). Eight components in urine specimens were identified that enabled discrimination between the pre- and post-XYS-treated samples.

RESULTS

Urinary of creatinine, taurine, 2-oxoglutarate and xanthurenic acid increased significantly after XYS treatment (p≤0.05), while the urinary levels of citrate, lactate, alanine and dimethylamine decreased significantly (p≤0.05) compared with pre-treatment urine samples. These statistically significant perturbations are involved in energy metabolism, gut microbes, tryptophan metabolism and taurine metabolism.

CONCLUSIONS

The symptoms of depression had been improved after 6 weeks׳ treatment of XYS according to evaluation of HAMD scores. The dynamic tendency of the 8 metabolites that changed significantly during the treatment of XYS is consistent with the improvement in symptoms of depression. These metabolites may be used as biomarkers for the diagnosis of depressive disorders or the evaluation of the antidepressant as well as the exploration of the mechanism of depression.

An efficient high throughput metabotyping platform for screening of biomass willows

Future improvement of woody biomass crops such as willow and poplar relies on our ability to select for metabolic traits that sequester more atmospheric carbon into biomass, or into useful products to replace petrochemical streams. We describe the development of metabotyping screens for willow, using combined 1D 1H-NMR-MS. A protocol was developed to overcome 1D 1H-NMR spectral alignment problems caused by variable pH and peak broadening arising from high organic acid levels and metal cations. The outcome was a robust method to allow direct statistical comparison of profiles arising from source (leaf) and sink (stem) tissues allowing data to be normalised to a constant weight of the soluble metabolome. We also describe the analysis of two willow biomass varieties, demonstrating how fingerprints from 1D 1H-NMR-MS vary from the top to the bottom of the plant. Automated extraction of quantitative data of 56 primary and secondary metabolites from 1D 1H-NMR spectra was realised by the construction and application of a Salix metabolite spectral library using the Chenomx software suite. The optimised metabotyping screen in conjunction with automated quantitation will enable high-throughput screening of genetic collections. It also provides genotype and tissue specific data for future modelling of carbon flow in metabolic networks.

Serum and urine metabolomic fingerprinting in diagnostics of inflammatory bowel diseases

AIM: To evaluate the utility of serum and urine metabolomic analysis in diagnosing and monitoring of inflammatory bowel diseases (IBD).

METHODS: Serum and urine samples were collected from 24 patients with ulcerative colitis (UC), 19 patients with the Crohn’s disease (CD) and 17 healthy controls. The activity of UC was assessed with the Simple Clinical Colitis Activity Index, while the activity of CD was determined using the Harvey-Bradshaw Index. The analysis of serum and urine samples was performed using proton nuclear magnetic resonance (NMR) spectroscopy. All spectra were exported to Matlab for preprocessing which resulted in two data matrixes for serum and urine. Prior to the chemometric analysis, both data sets were unit variance scaled. The differences in metabolite fingerprints were assessed using partial least-squares-discriminant analysis (PLS-DA). Receiver operating characteristic curves and area under curves were used to evaluate the quality and prediction performance of the obtained PLS-DA models. Metabolites responsible for separation in models were tested using STATISTICA 10 with the Mann-Whitney-Wilcoxon test and the Student’s t test (α = 0.05).

RESULTS: The comparison between the group of patients with active IBD and the group with IBD in remission provided good PLS-DA models (P value 0.002 for serum and 0.003 for urine). The metabolites that allowed to distinguish these groups were: N-acetylated compounds and phenylalanine (up-regulated in serum), low-density lipoproteins and very low-density lipoproteins (decreased in serum) as well as glycine (increased in urine) and acetoacetate (decreased in urine). The significant differences in metabolomic profiles were also found between the group of patients with active IBD and healthy control subjects providing the PLS-DA models with a very good separation (P value < 0.001 for serum and 0.003 for urine). The metabolites that were found to be the strongest biomarkers included in this case: leucine, isoleucine, 3-hydroxybutyric acid, N-acetylated compounds, acetoacetate, glycine, phenylalanine and lactate (increased in serum), creatine, dimethyl sulfone, histidine, choline and its derivatives (decreased in serum), as well as citrate, hippurate, trigonelline, taurine, succinate and 2-hydroxyisobutyrate (decreased in urine). No clear separation in PLS-DA models was found between CD and UC patients based on the analysis of serum and urine samples, although one metabolite (formate) in univariate statistical analysis was significantly lower in serum of patients with active CD, and two metabolites (alanine and N-acetylated compounds) were significantly higher in serum of patients with CD when comparing jointly patients in the remission and active phase of the diseases. Contrary to the results obtained from the serum samples, the analysis of urine samples allowed to distinguish patients with IBD in remission from healthy control subjects. The metabolites of importance included in this case up-regulated acetoacetate and down-regulated citrate, hippurate, taurine, succinate, glycine, alanine and formate.

CONCLUSION: NMR-based metabolomic fingerprinting of serum and urine has the potential to be a useful tool in distinguishing patients with active IBD from those in remission.

An optimized method for NMR-based plant seed metabolomic analysis with maximized polar metabolite extraction efficiency, signal-to-noise ratio, and chemical shift consistency

An optimized method for NMR-based plant seed metabolomic analysis was established with extraction solvent, cell-breaking method and extract-to-buffer ratio.

Reproducibility of NMR analysis of urine samples: impact of sample preparation, storage conditions, and animal health status

Introduction. Spectroscopic analysis of urine samples from laboratory animals can be used to predict the efficacy and side effects of drugs. This employs methods combining ¹H NMR spectroscopy with quantification of biomarkers or with multivariate data analysis. The most critical steps in data evaluation are analytical reproducibility of NMR data (collection, storage, and processing) and the health status of the animals, which may influence urine pH and osmolarity. Methods. We treated rats with a solvent, a diuretic, or a nephrotoxicant and collected urine samples. Samples were titrated to pH 3 to 9, or salt concentrations increased up to 20-fold. The effects of storage conditions and freeze-thaw cycles were monitored. Selected metabolites and multivariate data analysis were evaluated after ¹H NMR spectroscopy. Results. We showed that variation of pH from 3 to 9 and increases in osmolarity up to 6-fold had no effect on the quantification of the metabolites or on multivariate data analysis. Storage led to changes after 14 days at 4°C or after 12 months at −20°C, independent of sample composition. Multiple freeze-thaw cycles did not affect data analysis. Conclusion. Reproducibility of NMR measurements is not dependent on sample composition under physiological or pathological conditions.