Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with different groups of growth-promoting hormones (dexamethasone, prednisolone, oestradiol) based on recorded metabolite profiles. Two methods of NMR analysis were investigated—a Carr–Purcell–Meiboom–Gill (CPMG)-pulse sequence technique and a conventional ¹H NMR method using pre-extracted plasma. Using the CPMG method, 17 distinct metabolites could be identified from the spectra. ¹H NMR analysis of extracted plasma facilitated identification of 23 metabolites—six more than the alternative method and all within the aromatic region. Multivariate statistical analysis of acquired data from both forms of NMR analysis separated the plasma metabolite profiles into distinct sample cluster sets representative of the different animal study groups. Samples from both sets of corticosteroid-treated animals—dexamethasone and prednisolone—were found to be clustered relatively closely and had similar alterations to identified metabolite panels. Distinctive metabolite profiles, different from those observed within plasma from corticosteroid-treated animal plasma, were observed in oestradiol-treated animals and samples from these animals formed a cluster spatially isolated from control animal plasma samples. These findings suggest the potential use of NMR methodologies of plasma metabolite analysis as a high-throughput screening technique to aid detection of growth promoter use.     

稀土对大鼠代谢产物影响的核磁共振研究

以高场核磁共振技术为研究手段,通过分析腹腔注射０．２、２、１０、２０ｍｇ／ｋｇ体重剂量的Ｌａ（ＮＯ３）３后大鼠尿液中代谢物浓度、物种的变化,研究了稀土化合物在动物体内的作用情况,结果表明,稀土的引入使动物肾脏和肝脏都受到一定程度的损伤,并在代谢物中挑选出了合适的ＮＭＲ ｍａｒｋｅｒｓ,其变化可以反映稀土离子作用后大鼠的异常代谢。     

稀土对大鼠尿液成分影响的核磁共振研究

目前,稀土生物效应的研究已进入了分子和细胞水平,但在活体动物内研究稀土的作用情况还不多见。稀土化合物随食物进入动物体内后,会对动物体内的器官、组织、细胞产生一定影响,将导致其体液容量、分布、电解质浓度等方面的变化。现代NMR技术是目前药理毒理学研究的有效手段之一,它具有简便、全面、快捷、非破坏性等优点,可用于对体液样品的检测和研究。本文采用现代核磁共振技术研究了稀土化合物硝酸镧灌胃给药后对Wistar大鼠尿液中代谢产物的影响,为阐明稀土化合物的毒理学机制和稀土的进一步开发利用提供理论依据。     

Metabonomics investigation of human urine after ingestion of green tea with gas chromatography/mass spectrometry, liquid chromatography/mass spectrometry and (1)H NMR spectroscopy

A method using gas chromatography/mass spectrometry (GC/MS), liquid chromatography/mass spectrometry (LC/MS) and (1)H NMR with pattern recognition tools such as principle components analysis (PCA) was used to study the human urinary metabolic profiles after the intake of green tea. From the normalized peak areas obtained from GC/MS and LC/MS and peak heights from (1)H NMR, statistical analyses were used in the identification of potential biomarkers. Metabolic profiling by GC/MS provided a different set of quantitative signatures of metabolites that can be used to characterize the molecular changes in human urine samples. A comparison of normalized metabonomics data for selected metabolites in human urine samples in the presence of potential overlapping peaks after tea ingestion from LC/MS and (1)H NMR showed the reliability of the current approach and method of normalization. The close agreements of LC/MS with (1)H NMR data showed that the effects of ion suppression in LC/MS for early eluting metabolites were not significant. Concurrently, the specificity of detecting the stated metabolites by (1)H NMR and LC/MS was demonstrated. Our data showed that a number of metabolites involved in glucose metabolism, citric acid cycle and amino acid metabolism were affected immediately after the intake of green tea. The proposed approach provided a more comprehensive picture of the metabolic changes after intake of green tea in human urine. The multiple analytical approach together with pattern recognition tools is a useful platform to study metabolic profiles after ingestion of botanicals and medicinal plants.     

NMR spectroscopy evaluation of direct relationship between soils and molecular composition of red wines from Aglianico grapes

¹H NMR spectroscopy was employed to investigate the molecular quality of Aglianico red wines from the Campania region of Italy. The wines were obtained from three different Aglianico vineyards characterized by different microclimatic and pedological properties. In order to reach an objective evaluation of “terroir” influence on wine quality, grapes were subjected to the same winemaking procedures. The careful subtraction of water and ethanol signals from NMR spectra allowed to statistically recognize the metabolites to be employed in multivariate statistical methods: Principal Component Analysis (PCA), Discriminant Analysis (DA) and Hierarchical Clustering Analysis (HCA). The three wines were differentiated from each other by six metabolites: α-hydroxyisobutyrate, lactic acid, succinic acid, glycerol, α-fructose and β-d-glucuronic acid. All multivariate analyses confirmed that the differentiation among the wines were related to micro-climate, and carbonate, clay, and organic matter content of soils. Additionally, the wine discrimination ability of NMR spectroscopy combined with chemometric methods, was proved when commercial Aglianico wines, deriving from different soils, were shown to be statistically different from the studied wines. Our findings indicate that multivariate statistical elaboration of NMR spectra of wines is a fast and accurate method to evaluate the molecular quality of wines, underlining the objective relation with terroir.     

Highly routinely reproducible alignment of 1H NMR spectral peaks of metabolites in huge sets of urines

A method to obtain high reproducibility of (1)H NMR chemical shift of peaks of biofluid metabolites, by simple acidification with HCl is evaluated. Biofluid (1)H NMR analysis is indeed spoiled by a strong chemical shift dependence of metabolite peaks on parameters such as ionic strength, concentration of some earth alkali cations and, mostly, on pH of samples. The resulting chemical shift variations, as large as 0.1 ppm, generate misalignments of homogeneous peaks, artifacts and misinterpretations. Reproducible alignment is essential in (1)H NMR based metabonomics, where peak misalignments prevent even very wide bins (i.e., 0.04 ppm, as elsewhere proposed) from being used to integrate spectral data for multivariate statistical analysis. Here is demonstrated that routine acidification with HCl to 1.2≤pH≤2.0 ensures highly reproducible peak alignment of urine (1)H NMR spectra. In this respect, simple inspection of citrate peaks in the urine can be used to measure pH, as it will be extensively discussed, in that at such low pH they show no dependency on other urine components as reported at higher pH. Under these conditions, in as many as 493 urine samples, in which concentrations of Ca(2+), Mg(2+), K(+), Na(+), Cl(-), phosphate, and creatinine and ionic strength measured by means of well standardized conventional procedures, showed very wide ranges, peaks align within a SD always lower than 0.002 ppm, thus allowing the use of integration bins at least five times narrower than 0.04 ppm.     

Maternal Physiological Variations Induced by Chronic Gestational Hypoxia: 1H NMR-Based Metabolomics Study

Metabolomics have been widely used in pregnancy-related diseases. However, physiological variations induced by chronic hypoxia during pregnancy are not well characterized. We aimed to investigate physiological variations induced by chronic hypoxia during pregnancy. A Sprague–Dawley (SD) pregnant rat model of chronic hypoxia was established. Plasma and urine metabolite profiles at different stages of the pregnancy were detected by ¹H NMR (nuclear magnetic resonance). Multivariate statistical analysis was used to analyze changes in plasma and urine metabolic trajectories at different time-points. We identified hypoxia-induced changes in the levels of 30 metabolites in plasma and 29 metabolites in urine during different stages of pregnancy; the prominently affected metabolites included acetic acid, acetone, choline, citric acid, glutamine, isoleucine, lysine, and serine. Most significant hypoxia-induced changes in plasma and urine sample metabolites were observed on the 11th day of gestation. In summary, chronic hypoxia has a significant effect on pregnant rats, and may cause metabolic disorders involving glucose, lipids, amino acids, and tricarboxylic acid cycle. Metabolomics study of the effect of hypoxia during pregnancy may provide insights into the pathogenesis of obstetric disorders.     

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by ¹H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.     

Highly routinely reproducible alignment of H NMR spectral peaks of metabolites in huge sets of urines

A method to obtain high reproducibility of ¹H NMR chemical shift of peaks of biofluid metabolites, by simple acidification with HCl is evaluated. Biofluid ¹H NMR analysis is indeed spoiled by a strong chemical shift dependence of metabolite peaks on parameters such as ionic strength, concentration of some earth alkali cations and, mostly, on pH of samples. The resulting chemical shift variations, as large as 0.1 ppm, generate misalignments of homogeneous peaks, artifacts and misinterpretations.Reproducible alignment is essential in ¹H NMR based metabonomics, where peak misalignments prevent even very wide bins (i.e., 0.04 ppm, as elsewhere proposed) from being used to integrate spectral data for multivariate statistical analysis. Here is demonstrated that routine acidification with HCl to 1.2 ≤ pH ≤ 2.0 ensures highly reproducible peak alignment of urine ¹H NMR spectra. In this respect, simple inspection of citrate peaks in the urine can be used to measure pH, as it will be extensively discussed, in that at such low pH they show no dependency on other urine components as reported at higher pH. Under these conditions, in as many as 493 urine samples, in which concentrations of Ca²⁺, Mg²⁺, K⁺, Na⁺, Cl⁻, phosphate, and creatinine and ionic strength measured by means of well standardized conventional procedures, showed very wide ranges, peaks align within a SD always lower than 0.002 ppm, thus allowing the use of integration bins at least five times narrower than 0.04 ppm.     

Metabolic trajectory characterisation of xenobiotic-induced hepatotoxic lesions using statistical batch processing of NMR data

Multivariate statistical batch processing (BP) analysis of 1H NMR urine spectra was employed to establish time-dependent metabolic variations in animals treated with the model hepatotoxin, alpha-naphthylisothiocyanate (ANIT). ANIT (100 mg kg(-1)) was administered orally to rats (n = 5) and urine samples were collected from dosed and matching control rats at time-points up to 168 h post-dose. Urine samples were measured via 1H NMR spectroscopy and partial least squares (PLS) based batch processing analysis was used to interpret the spectral data, treating each rat as an individual batch comprising a series of timed urine samples. A model defining the mean urine profile over the 7 day study period was established, together with model confidence limits (+/-3 standard deviation), for the control group. Samples obtained from ANIT treated animals were evaluated using the control model. Time-dependent deviations from the control model were evident in all ANIT treated animals consisting of glycosuria, bile aciduria, an initial decrease in taurine levels followed by taurinuria and a reduction of tricarboxylic acid cycle intermediate excretion. BP provided an efficient means of visualising the biochemical response to ANIT in terms of both inter-animal variation and net variation in metabolite excretion profiles. BP also allowed multivariate statistical limits for normality to be established and provided a template for defining the sequence of time-dependent metabolic consequences of toxicity in NMR based metabonomic studies.     

亚硒酸钠对大鼠代谢产物影响的核磁共振研究

本文采用核磁共振(^1H NMR)技术研究了在最高耐受摄入量条件下补充亚硒酸钠对大鼠尿液代谢产物的影响。结果表明,在大鼠尿液中甲酸、乙酸、乳酸、丙氨酸、琥珀酸、甘氨酸、马尿酸、苯丙氨酸、色氨酸等代谢物谱峰信号显著增强,而柠檬酸、肌酸、尿素、尿甘素和氧化三甲胺(TAMO)的谱峰信号则显著降低。乳酸、柠檬酸和琥珀酸是体内三羧酸循环的中间产物,其代谢异常是能量代谢紊乱的标志;马尿酸、苯丙氨酸、丙氨酸的代谢异常与肾小球的滤过和回收功能有关;乙酸和甘氨酸的代谢异常则是肝功能损伤的标志,组织切片的结果也证明大鼠的肝和肾已经发生损伤,与^1H NMR的结果相一致。采用HPLC检测到补充亚硒酸钠后尿液中8-OHdG(8-hydroxy1-2′-deoxyguansoine)水平显著升高,证明体内氧化损伤的发生。以上结果表明,在最高耐受摄入量条件下补充亚硒酸钠是不安全的,用NMR方法对阐明硒的毒理学分子基础是有效的。     

Metabolic profiling using principal component analysis, discriminant partial least squares, and genetic algorithms

The aim of this study was to evaluate evolutionary variable selection methods in improving the classification of ¹H nuclear magnetic resonance (NMR) metabonomic profiles, and to identify the metabolites that are responsible for the classification. Human plasma, urine, and saliva from a group of 150 healthy male and female subjects were subjected to ¹H NMR-based metabonomic analysis. The ¹H NMR spectra were analyzed using two pattern recognition methods, principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), to identify metabolites responsible for gender differences. The use of genetic algorithms (GA) for variable selection methods was found to enhance the classification performance of the PLS-DA models. The loading plots obtained by PCA and PLS-DA were compared and various metabolites were identified that are responsible for the observed separations. These results demonstrated that our approach is capable of identifying the metabolites that are important for the discrimination of classes of individuals of similar physiological conditions.     

Determination of absolute stereochemistry of natural alicyclic glycosides by 1H NMR spectroscopy without application of chiral reagents--an indication

A study has been made of the 1H NMR spectra of peracetylated beta-glucopyranosides and alpha-arabinopyranosides obtained by reaction of D- and L-glucoses, and L- and D-arabinoses with either (R)- or (S)-2-octanols. The obtained and literature data show that 1H NMR spectra may be used to determine the absolute configuration of the aglycone moieties of some alicyclic glycosides without the need to synthesize derivatives with chiral reagents, as long as the absolute configuration of their monosaccharide moiety is known or vice versa. Spectra of marine steroid glycosides and their acetates containing glycosylated side chains as alicyclic fragments were also examined. It was shown that analysis of 1H NMR spectra for the determination of the absolute configuration is more applicable in the cases when glycosides have the same substitution in the D-ring of the aglycone moiety.     

Analysis of human urine metabolites using SPE and NMR spectroscopy

Nuclear magnetic resonance (NMR) spectroscopic analysis of metabonome/metabolome has widespread applications in biomedical science researches. However, most of NMR resonances for urinary metabolites remain to be fully assigned. In the present study, human urine samples from two healthy volunteers were pre-treated with C18 solid-phase extraction and the resultant 5 sub-fractions were subjected to one- and two-dimensional NMR studies, including 1H J-Resolved, 1H-1H COSY, 1H-1H TOCSY, 1H-13C HSQC, and HMBC 2D NMR. More than 70 low molecular weight metabolites were identified, and complete assignments of 1H and 13C resonances including many complex coupled spin systems were obtained.     

Application of chemometrics to 1H NMR spectroscopic data to investigate a relationship between human serum metabolic profiles and hypertension

The application of chemometric methods to 1H NMR spectroscopic data has been documented for pathophysiological processes. In this study we show the application of 1H NMR-based metabonomics to investigate a relationship between serum metabolic profiles and hypertension. Although hypertension can be defined using blood pressure measurements, the underlying aetiology and metabolic effects are not so readily identified. Serum profiles for patients with low/normal systolic blood pressure (SBP < or = 130 mm Hg; n = 28), borderline SBP (131-149 mm Hg; n = 19) and high SBP (> or = 150 mm Hg; n = 17) were acquired using 1H NMR spectroscopy. Orthogonal signal correction followed by principal components analysis were applied to these NMR data in order to facilitate interpretation, and the resulting chemometric models were validated using Soft Independent Modelling of Class Analogy. Using 1H NMR-based metabonomics, it was possible to distinguish low/ normal SBP serum samples from borderline and high SBP samples. Borderline and high SBP samples, however, were indiscriminate from each other. Our preliminary results showed that there was a relationship between serum metabolic profiles and blood pressure which, in part, was due to lipoprotein particle composition differences between the samples. Furthermore, our results indicated that serum pathology associated with blood pressure is apparent at SBP values > 130 mm Hg, which the WHO and ISH currently define as the limit between normal and high-normal.     

Combining desorption electrospray ionization mass spectrometry and nuclear magnetic resonance for differential metabolomics without sample preparation

Desorption electrospray ionization mass spectrometry (DESI-MS) and nuclear magnetic resonance (NMR) spectroscopy are used to provide data on urine examined without sample preparation to allow differentiation between diseased (lung cancer) and healthy mice. Principal component analysis (PCA) is used to shortlist compounds with potential for biomarker screening which are responsible for significant differences between control urine samples and samples from diseased animals. Similar PCA score plots have been achieved by DESI-MS and NMR, using a subset of common detected metabolites. The common compounds detected by DESI and NMR have the same changes in sign of their concentrations thereby indicating the usefulness of corroborative analytical methods. The effects of different solvents and surfaces on the DESI mass spectra are also evaluated and optimized. Over 80 different metabolites were successfully identified by DESI-MS and tandem mass spectrometry experiments, with no prior sample preparation.     

Characterization of the metabolites of H3B-6545 in vitro and in vivo by using ultra-high performance liquid chromatography combined with electrospray ionization linear ion trap-orbitrap tandem mass spectrometry

H3B-6545 is a selective ERα covalent antagonist, which has been demonstrated to be effective in anti-tumor. To fully understand its mechanism of action, it is necessary to investigate the in vitro and in vivo metabolic profiles. For in vitro metabolism, H3B-6545 (50 μM) was incubated with the hepatocytes of rat and human for 2 h. For in vivo metabolism H3B-6545 was orally administered to rats at a single dose of 10 mg/kg, and plasma, urine and fecal samples were then collected. All samples were analyzed by using ultra-high performance liquid chromatography combined with linear ion trap-orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap-MS) operated in positive ion mode. The structures of the metabolites were elucidated by comparing their MS and MS² spectra with those of parent drug. A total of 11 metabolites, including a GSH adduct, were detected and structurally identified. M2, M7 and M8 were further unambiguously identified by using reference standards. Among these metabolites, M1, M5, M7 and M10 were newly found and reported for the first time. The metabolic pathways of H3B-6545 included deamination (M8 and M9), dealkylation (M2, M3 and M10), N-hydroxylation (M6), hydroxylation (M1 and M4), formation of amide derivatives (M5 and M7) and GSH conjugation (G1).     

Peak alignment of urine NMR spectra using fuzzy warping

Proton nuclear magnetic resonance (1H NMR) spectroscopic analysis of mixtures has been used extensively for a variety of applications ranging from the analysis of plant extracts, wine, and food to the evaluation of toxicity in animals. For example, NMR analysis of urine samples has been used extensively for biomarker discovery and, more simply, for the construction of classification models of toxicity, disease, and biochemical phenotype. However, NMR spectra of complex mixtures typically show unwanted local peak shifts caused by matrix and instrument variability, which must be compensated for prior to statistical analysis and interpretation of the data. One approach is to align the spectral peaks across the data set. An efficient and fast warping algorithm is required as the signals typically contain ca. 32,000-64,000 data points and there can be several thousand spectra in a data set. As demonstrated in our study, the iterative fuzzy warping algorithm fulfills these requirements and can be used on-line for an alignment of the NMR spectra. Correlation coefficients between the aligned and target spectra are used as the evaluation function for the algorithm, and its performance is compared with those of other published warping methods.     

Evaluation of Bioeffects of a Long-term Administering ChangLe on Rat by Proton NMR Method and BIochemical Examination

High resolution ¹H nuclear magnetic resonance (NMR) spectroscopy has been employed to assess long‐term toxicological effects of ChangLe (a kind of rare earth complex applied in agriculture). Male Wistar rats were administrated orally with ChangLe at doses of 0, 0.1, 0.2, 2.0, 10 and 20 mg/kg body weight daily, respectively, for 6 months. Urine was collected at day 30, 60, 90 and serum samples were taken after 6 months. Many low‐molecular weight metabolites were identified by ¹H NMR spectra of rat urine. A decrease in citrate and an increase in ketone bodies, creatinine, DMA, DMG, TMAO, and taurine in the urine of the rats receiving high doses were found by ¹H NMR spectra. These may mean that high‐dosage of ChangLe impairs the specific region of liver and kidney, such as renal tubule and mitochondria. The decrease in citrate and the increase in succinate and α‐ketoglutarate were attributed to a combination of the inhibition of certain citric acid enzymes, renal tubular acidosis and the abnormal fatty acid catabolism. The information of the renal capillary necrosis could be derived from the increase in DMA, DMG and TMAO. The increase in taurine was due to hepatic mitochondria dysfunction. The conclusions were supported by the results of biochemical measurements and enzymatic assay. No obviously toxicological effects on metabolism were found for low‐dosage ChangLe, but further studies on safety of ChangLe applied to agriculture are still required.     

Application of NMR metabolomics to search for human disease biomarkers

Since antiquity, humans have used body fluids like saliva, urine and sweat for the diagnosis of diseases. The amount, color and smell of body fluids are still used in many traditional medical practices to evaluate an illness and make a diagnosis. The development and application of analytical methods for the detailed analysis of body fluids has led to the discovery of numerous disease biomarkers. Recently, mass spectrometry (MS), nuclear magnetic resonance spectroscopy (NMR), and multivariate statistical techniques have been incorporated into a multidisciplinary approach to profile changes in small molecules associated with the onset and progression of human diseases. The goal of these efforts is to identify metabolites that are uniquely correlated with a specific human disease in order to accurately diagnose and treat the malady. In this review we will discuss recent developments in sample preparation, experimental techniques, the identification and quantification of metabolites, and the chemometric tools used to search for biomarkers of human diseases using NMR.