Metabolic profiling of cervical tubercular lymphadenitis tissues by proton HR-MAS NMR spectroscopy

Proton metabolic profiling of incisional biopsied cervical lymph node tissue specimens of 109 patients suffering from tubercular (CTBL) and non-specific (NSCLA) lymphadenitis were analyzed by high resolution magic angle spinning (HR-MAS) NMR spectroscopy. In the present study, 40 endogenous metabolites namely, myo-inositol (m-Ins), branched chain amino acids (BCAA), glutamate, serine, taurine (Tau) aromatic amino acids, choline (Cho) containing compounds and glucose were characterized. To the best of our knowledge, this is the first report on metabolic profiling of cervical tubercular lymph node tissues using HR-MAS NMR spectroscopy. The principal component analysis revealed a clear discrimination between CTBL and NSCLA tissues. Increase in the concentration of mobile poly unsaturated fatty acids, BCAA, Cho, Tau, glycine and a decrease in the concentration of lactate, phosphocholine and m-Ins was observed in CTBL cases. The partial least square discriminant analysis (PLS-DA) with R ² = 0.95 and Q ² = 0.92 provided >98 % of correct classification between the two groups. A PLS-DA training set model of 75 % (CTBL = 54, NSCLA = 27) of the subjects when subjected for prediction of 25 % cases (CTBL = 18, NSCLA = 10) as an unknown dataset provided more than 98 % of diagnostic accuracy in their respective histological categories. The receiver operator characteristic curve was generated from PLS-DA factor-1 projected an area under the curve of 0.962. The metabolic profile obtained from HR-MAS NMR spectroscopy may be used as surrogate markers in vivo MRS for differentiating between CTBL and NSCLA cases non-invasively.     

Influence of ethanol concentration of extraction solvent on metabolite profiling for Salviae Miltiorrhizae Radix et Rhizoma extract by 1H NMR spectroscopy and multivariate data analysis

Salviae Miltiorrhizae Radix et Rhizoma (Danshen in China) and its related preparations are widely used in clinical practice due to its high medicinal value. In recent years, ¹H NMR technology has made great progress and demonstrated its unique advantages in the field of botanical metabolomics. In this study, ¹H NMR-based metabolomics was used to investigate the dissolution of various metabolites in Danshen as a function of ethanol concentration. ¹H NMR spectroscopy of Danshen extract identified 28 metabolites including 6 sugars, 11 amino acids, 3 organic acids, 4 salvianolic acids, and 4 tanshinones. Multivariate statistical analysis was used to classify and compare various Danshen extracts. PCA and HCA were used to obtain a global overview of the similarity in the samples and two-class OPLS-DA models were established for identifying characteristic metabolites. Then, ¹H-qNMR method was used to estimate the concentration of 22 metabolites, which is helpful to further describe the changes in metabolite ratios of various Danshen extracts. The result of this study laid the foundation for further biological activity research, and also provided an important reference for subsequent process research and quality control of Danshen related preparations.     

Quantitative analysis of metabolite concentrations in human urine samples using 13C{1H} NMR spectroscopy

Targeted profiling is a library-based method of using mathematically modeled reference spectra for quantification of metabolite concentrations in NMR mixture analysis. Metabolomics studies of biofluids, such as urine, represent a highly complex problem in this area, and for this reason targeted profiling of ¹H NMR spectra can be hampered. A number of the issues relating to ¹H NMR spectroscopy can be overcome using ¹³C{¹H} NMR spectroscopy. In this work, a ¹³C{¹H} NMR database was created using Chenomx NMR Suite, incorporating 120 metabolites. The ¹³C{¹H} NMR database was standardized through the analysis of a series of metabolite solutions containing varying concentrations of 19 distinct metabolites, where the metabolite concentrations were varied across a range of values including biological ranges. Subsequently, the NMR spectra of urine samples were collected using ¹³C{¹H} NMR spectroscopy and profiled using the ¹³C{¹H} NMR library. In total, about 30 metabolites were conclusively identified and quantified in the urine samples using ¹³C{¹H} NMR targeted profiling. The proton decoupling and larger spectral window provided easier identification and more accurate quantification for specific classes of metabolites, such as sugars and amino acids with overlap in the aliphatic region of the ¹H NMR spectrum. We discuss potential application areas in which ¹³C{¹H} NMR targeted profiling may be superior to ¹H NMR targeted profiling.     

High-resolution magic angle spinning 1H NMR analysis of whole cells of Thalassiosira pseudonana (Bacillariophyceae): Broad range analysis of metabolic composition and nutritional value

Chemical composition of the microalga Thalassiosira pseudonana Hasle & Heimdalwas studied with different proton nuclearmagnetic resonance (¹H NMR)techniques, and by comparing NMR spectrafrom extraction samples with a spectrumfrom a sample of whole cells we show thathigh-resolution magic angle spinning (HRMAS) ¹H NMR can be used for broadrange analysis of metabolic composition inmicroalgal whole cells. Signals fromimportant metabolites such aspolyunsaturated fatty acids (PUFAs)eicosapentaenoic (EPA) and docosahexaenoic(DHA) acids were seen in a ¹H NMRspectrum of lipophilic extract, andpossibly also signals from the carotenoidfucoxanthin. In a spectrum of hydrophilicextract we assigned signals to amino acidssuch as glutamine (Gln) and glutamic acid(Glu), carbohydrate and ATP. These findingswere compared to a spectrum of HR MAS¹H NMR analysis of whole cells, whereit was possible to find signals coincidentwith the different metabolites seen inspectra of the extraction samples. Sincethe position of resonance peaks in a NMRspectrum depends on the chemicalsurroundings of each atom at the time ofanalysis some peak shift differencesbetween extract and whole cell samplespectra may occur, but signal shifts werenot significantly different between theanalyses here. In addition, application ofHR MAS highly increased spectral resolutionin the complex whole cell sample. Wetherefore suggest that HR MAS ¹H NMRanalysis is a suitable analysis tool tostudy metabolic composition directly onwhole cells of microalgae, making itpossible to study a broad range ofmetabolites simultaneously without tediousextraction procedures.     

Biochemical characterization of cultivated Cordyceps bassiana mycelia and fruiting bodies by 1H nuclear magnetic resonance spectroscopy

In this study, nuclear magnetic resonance techniques coupled with multivariate data analysis were used for the metabolic profiling of mycelia and fruiting bodies of the entomopathogenic fungi, Cordyceps bassiana according to developmental stages. A direct extraction method using two deuterated solvents of D₂O and CDCl₃ was used to investigate the relative levels of identified metabolites in each extraction condition in the mycelium and fruiting body formation stages. There was a clear separation among mycelia and fruiting bodies with various developmental stages in partial least-squares discriminant analysis (PLS-DA) derived score plots. During the transition from mycelia to fruiting bodies, the major metabolic change observed was the conversion of glucose to mannitol, and beauvericin to phenylalanine and 1-hydroxyisovaleric acid. In the developmental stages of fruiting bodies studied, there was a clear separation between stage 3 and the other stages in PLS-DA derived score plots. Nineteen compounds including 13 amino acids, 2 nucleosides, 3 organic acids, and glucose showed the highest levels in stage 3 fruiting bodies. The flavonoid content in the fruiting bodies showed similar levels during stages 1, 2, and 3, whereas the level at stage 4 was significantly decreased compared to the other stages. Results suggest that the fruiting body of C. bassiana is richer in natural resources at stage 3 compared to the other fruiting body stages due to its high abundance of compounds including total flavonoids. The metabolome information acquired in this study can be useful criteria for the quality control of commercial use of C. bassiana.     

Isolation,Characterization, and Metabolic Profiling of Ceratorhiza hydrophila from the Aquatic Plant Myriophyllum spicatum

The goal of the present study was to investigate the antibacterial properties, enzyme production, and metabolic profiling of a new Ceratorhiza hydrophila strain isolated from the submerged aquatic plant Myriophyllum spicatum. Furthermore, the fungus'' morphological characterization and DNA sequencing have been described. The fungus has been identified and submitted to the GenBank as Ceratorhiza hydrophila isolate EG19 and the fungus ID is {"type":"entrez-nucleotide","attrs":{"text":"MK387081","term_id":"1552064574","term_text":"MK387081"}}MK387081. The enzyme analyses showed its ability to produce protease and cellulase enzymes. According to the CSLI standard, the ethyl acetate extract of C. hydrophila showed intermediate antibacterial activity against Streptococcus pneumonia, Micrococcus luteus, and Staphylococcus aureus. Metabolic profiling has been carried out using 700 MHz NMR spectroscopy. Based on the ¹H and ¹H-¹³C heteronuclear single quantum coherence (HSQC) NMR data and NMR databases, 23 compounds have been identified. The identified metabolites include 31% amino acids, 9% sugars, 9% amines, 4% sugar alcohols, and 4% alkaloids. This is the first report for the metabolic characterization of C. hydrophila, which gave preliminary information about the fungus. It is expected that our findings not only will pave the way to other perspectives in enormous applications using C. hydrophila as a new promising source of antimicrobial agents and essential metabolites, but also it will be valuable in the classification and chemotaxonomy of the species.     

Toward Arabidopsis thaliana hydrophilic metabolome: assessment of extraction methods and quantitative 1H NMR

Our goal was to establish the hydrophilic metabolome of heterotrophic Arabidopsis thaliana cells grown in suspension, a cellular model of plant sink tissues. Water‐soluble metabolites were extracted using four protocols: perchloric acid, boiling ethanol, methanol and methanol/chloroform (M/Chl). They were detected and quantified using ¹H nuclear magnetic resonance (NMR) spectroscopy at 400 MHz. Extraction yields and reproducibility of the extraction methods were investigated. The effects of cell harvest protocol, cell grinding and lyophilization and storage conditions on the measured metabolic profiles were also studied. These quantitative studies demonstrated for the first time that the four extraction protocols commonly used do lead to quite similar molecular compositions as analyzed by ¹H NMR. The M/Chl method proved effective and reliable to prepare series of physiologically significant extracts from plant cells for ¹H NMR analysis. Reproducibility of the detected metabolome was assessed over long periods of time by analyzing a large number of separate extracts prepared from independent cultures. Larger variations in the NMR metabolite profiles could be correlated to changes in physiological parameters of the culture medium. Quantitative resolved ¹H NMR of cell extracts proved to be robust and reliable for routine metabolite profiling of plant cell cultures.     

Magic angle spinning NMR spectroscopic metabolic profiling of gall bladder tissues for differentiating malignant from benign disease

Gall bladder tissue specimens obtained from 112 patients were examined by high resolution magic angle spinning (HR-MAS) NMR spectroscopy. Fifty one metabolites were identified by combination of one and two-dimensional NMR spectra. To our knowledge, this is the first report on metabolic profiling of gall bladder tissues using HR-MAS NMR spectroscopy. Metabolic profiles were evaluated for differentiation between benign Chronic Cholecystitis (CC, n = 66) and xantho-granulomatous cholecystitis (XGC, n = 21) and malignant gall bladder cancer (GBC, n = 25). Increase in choline containing compounds, amino acids, taurine, nucleotides and lactate as common metabolites were observed in malignant tissues whereas lipid content was found low as compared to benign tissues. Principal component analysis obtained from the NMR data showed clear distinction between CC and GBC tissue specimens; however, 27 % of XGC tissues were classified with GBC. The partial least square discriminant analysis (PLS-DA) multivariate analysis between benign (CC, XGC) and malignant (GBC) on the training data set (CC; n = 51, XGC; n = 15, GBC; n = 19 tissues specimens) provided 100 % sensitivity and 94.12 % specificity. This PLS-DA model when executed on the spectra of unknown tissue specimens (CC; n = 15, XGC; n = 6, GBC; n = 6) classified them into the three histological categories with more than 95 % of diagnostic accuracy. Non-invasive in vivo MRS technique may be used in future to differentiate between benign (CC and XGC) and malignant (GBC) gall bladder diseases.     

Metabolic analysis of elicited cell suspension cultures of Cannabis sativa L. by 1H-NMR spectroscopy

Cannabis sativa L. plants produce a diverse array of secondary metabolites. Cannabis cell cultures were treated with jasmonic acid (JA) and pectin as elicitors to evaluate their effect on metabolism from two cell lines using NMR spectroscopy and multivariate data analysis. According to principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA), the chloroform extract of the pectin-treated cultures were more different than control and JA-treated cultures; but in the methanol/water extract the metabolome of the JA-treated cells showed clear differences with control and pectin-treated cultures. Tyrosol, an antioxidant metabolite, was detected in cannabis cell cultures. The tyrosol content increased after eliciting with JA.     

Bioactive compounds from sclerotia extract of Poria cocos that control adipocyte and osteoblast differentiation

Poria cocos Wolf confers edible sclerotia also known as ‘Indian bread’ in North America, that have been used for the treatment of various diseases in Asian countries. As part of our ongoing aim to identify biologically new metabolites from Korean edible mushrooms, we investigated the ethanol (EtOH) extract of the sclerotia of P. cocos by applying a comparative LC/MS- and bioassay-based analysis approach, since the EtOH extract reciprocally regulated adipocyte and osteoblast differentiation in mouse mesenchymal stem cells (MSCs). Bioassay-based analysis of the EtOH extract led to the successful isolation of two sterols, ergosterol peroxide (1) and 9,11-dehydroergosterol peroxide (2); three diterpenes, dehydroabietic acid (3), 7-oxocallitrisic acid, (4) and pimaric acid (5); and two triterpenes, dehydroeburicoic acid monoacetate (6) and eburicoic acid acetate (7) from the active hexane-soluble fraction. The isolated compounds (1–7) were examined for their effects on the regulation of MSC differentiation. The two sterols (1 and 2) were able to suppress MSC differentiation toward adipocytes. In contrast, the three diterpenes (3–5) showed activity to promote osteogenic differentiation of MSC. These findings demonstrate that the EtOH extract of P. cocos sclerotia is worth consideration as a new potential source of bioactive compounds effective in the treatment of osteoporosis in the elderly, since the extract contains sterols that inhibit adipogenic differentiation as well as diterpenes that promote osteogenic differentiation from MSCs.     

Global metabolomics characterization of bacteria: pre-analytical treatments and profiling

Pre-analytical treatments of bacteria are crucial steps in bacterial metabolomics studies. In order to achieve reliable samples that can best represent the global metabolic profile in vivo both qualitatively and quantitatively, many sample treatment procedures have been developed. The use of different methods makes it difficult to compare the results among different groups. In this work, E. coli samples were tested by using NMR spectroscopy. Both liquid N₂ and cold methanol quenching procedures reduce the cell membrane integrity and cause metabolites leakage. However, liquid N₂ quenching affected the cell viability and the NMR metabolites’ profile less than cold methanol procedure. Samples obtained by metabolite extraction were significantly superior over cell suspensions and cell lysates, with a higher number of detectable metabolites. Methanol/chloroform extraction proved most efficient at extraction of intracellular metabolites from both qualitative and quantitative points of view. Finally, standard operating procedures of bacterial sample treatments for NMR metabolomics study are presented.     

Bioactivity-guided isolation of anti-inflammatory triterpenoids from the sclerotia of Poria cocos using LPS-stimulated Raw264.7 cells

Poria cocos Wolf (Polyporaceae) has been used as a medicinal fungus to treat various diseases since ancient times. This study aimed to investigate the anti-inflammatory chemical constituents of the sclerotia of P. cocos. Based on bioassay-guided fractionation using lipopolysaccharide (LPS)-stimulated Raw264.7 cells, chemical investigation of the EtOH extract of the sclerotia of P. cocos resulted in the isolation and identification of eight compounds including six triterpenoids, namely poricoic acid A (1), 3-O-acetyl-16α-hydroxydehydrotrametenolic acid (2), polyporenic acid C (3), 3β-hydroxylanosta-7,9(11),24-trien-21-oic acid (4), trametenolic acid (5), and dehydroeburicoic acid (6), as well as (−)-pinoresinol (7) and protocatechualdehyde (8). The structures of the isolated compounds were determined by spectroscopic analysis, including ¹H and ¹³C NMR spectra, and LC/MS analysis. The anti-inflammatory activities of the isolates were evaluated by estimating their effect on the production of nitric oxide (NO) and prostaglandin E₂ (PGE₂) in LPS-stimulated Raw264.7 as well as on the expression of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2). Compounds 1–5 inhibited NO production and iNOS expression in LPS-stimulated Raw264.7 cells. Among them, compound 1 exerted the highest anti-inhibitory activity and reduced PGE₂ levels via downregulation of COX-2 protein expression. The findings of this study provide experimental evidence that the sclerotia of P. cocos are a potential source of natural anti-inflammatory agents for use in pharmaceuticals and functional foods. Furthermore, the most active compound 1, seco-lanostane triterpenoid, could be a promising lead compound for the development of novel anti-inflammatory agents.     

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

Background and Aims

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (¹H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although ¹H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors.

Methods and Results

We applied ¹H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses.

Conclusions

Differences in grape-derived metabolites associated with genetic differences alone are a major source of ¹H NMR-based discrimination of wines and ¹H NMR has the capacity to discriminate between very closely related cultivars.

Significance of the Study

The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by ¹H NMR-PCA/PLS and indicates that ¹H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.     

1H-NMR-based metabolomics for cancer targeting and metabolic engineering –A review

Nuclear magnetic resonance (NMR) spectroscopy acts as the best tool that can be used in tissue engineering scaffolds to investigate unknown metabolites. Moreover, metabolomics is a systems approach for examining in vivo and in vitro metabolic profiles, which promises to provide data on cancer metabolic alterations. However, metabolomic profiling allows for the activity of small molecules and metabolic alterations to be measured. Furthermore, metabolic profiling also provides high-spectral resolution, which can then be linked to potential metabolic relationships. An altered metabolism is a hallmark of cancer that can control many malignant properties to drive tumorigenesis. Metabolite targeting and metabolic engineering contribute to carcinogenesis by proliferation, and metabolic differentiation. The resulting the metabolic differences are examined with traditional chemometric methods such as principal component analysis (PCA), and partial least squares-discriminate analysis (PLS-DA). In this review, we examine NMR-based activity metabolomic platforms that can be used to analyze various fluxomics and for multivariant statistical analysis in cancer. We also aim to provide the reader with a basic understanding of NMR spectroscopy, cancer metabolomics, target profiling, chemometrics, and multifunctional tools for metabolomics discrimination, with a focus on metabolic phenotypic diversity for cancer therapeutics.     

A Comprehensive Search of the Primary and Secondary Metabolites and Radical Scavenging Potential of Trillium govanianum Wall. ex D. Don

Trillium govanianum rhizomes are traditionally consumed as a raw powder and decoction for the treatment of health complications. Hence, the present study aimed to investigate whether aqueous and alcoholic extracts of T. govanianum rhizomes under hot and cold extraction conditions have similar or dissimilar chemical, nutrient, and antioxidant profiles. The total phenolics, flavonoids, carbohydrates, proteins, fats, and energy values were estimated in all the conditionally prepared samples. The total phenolics (21.23±1.4 mg GAE/g extract), flavonoids (70.57±3.24 mg RE/g extract) were found higher in hot ethanolic extract (TGHEt), while cold water extract (TGGC) showed higher nutrients including amino acids (10.545±0.219 mg/g) and nucleosides (1.803±0.018 mg/g). The nutrient energy value (2.60 and 2.49 Kcal/g extract) was higher in cold and hot ethanolic extracts. Further, TGHEt scavenged the DPPH^. (IC₅₀; 870±22 μg/mL) and ABTS^.+ (IC₅₀; 80±1.49 μg/mL) effectively and proved its highest antioxidant activity compared to other samples. In LC/MS/MS-based metabolite profiling, twenty-six metabolites (fatty acids, steroidal saponins, triterpene saponins, ecdysteroid hormones) were confirmed with mass fragmentation and literature, while one hundred nine metabolites were identified using the METLIN database. The principal component analysis showed clustering of hot condition extracts while cold extracts were differentially located in quadrants. The heatmaps exhibited the associations and differences between metabolite composition, solvents, and extraction conditions. The identified metabolites speculatively predicted the biosynthesis pathway of T. govanianum. Findings also illustrated that T. govanianum is a source of bioactive nutritional components and saponins. The current metabolite profiling of T. govanianum will help in its agricultural and biotechnological interventions for higher quality produce.     

Biological variation of Vanilla planifolia leaf metabolome

The metabolomic analysis of Vanilla planifolia leaves collected at different developmental stages was carried out using ¹H-nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis in order to evaluate their variation. Ontogenic changes of the metabolome were considered since leaves of different ages were collected at two different times of the day and in two different seasons. Principal component analysis (PCA) and partial least square modeling discriminate analysis (PLS-DA) of ¹H NMR data provided a clear separation according to leaf age, time of the day and season of collection. Young leaves were found to have higher levels of glucose, bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A) and bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-(2-butyl)-tartrate (glucoside B), whereas older leaves had more sucrose, acetic acid, homocitric acid and malic acid. Results obtained from PLS-DA analysis showed that leaves collected in March 2008 had higher levels of glucosides A and B as compared to those collected in August 2007. However, the relative standard deviation (RSD) exhibited by the individual values of glucosides A and B showed that those compounds vary more according to their developmental stage (50%) than to the time of day or the season in which they were collected (19%). Although morphological variations of the V. planifolia accessions were observed, no clear separation of the accessions was determined from the analysis of the NMR spectra. The results obtained in this study, show that this method based on the use of ¹H NMR spectroscopy in combination with multivariate analysis has a great potential for further applications in the study of vanilla leaf metabolome.     

NMR (1H) analysis of crude extracts detects light stress in Beta vulgaris and Spinacia oleracea leaves

In highlight stress conditions, the mechanism of non-photochemical quenching (NPQ) of chlorophyll fluorescence is triggered at the chloroplast level. This process allows thermal quenching of the excessive excitation energy and it is strictly related to the efficiency of the xanthophyll cycle. Nowadays, the utilization of the nuclear magnetic resonance (NMR) spectroscopy provides a powerful complementary way for the identification and quantitative analysis of plant metabolites either in vivo or in tissue extracts. Seeing that the oxidative damage caused by light stress in plants and the consequent involvement of pigments are widely studied, NMR spectroscopy can be utilized to compare crude leaf extract at different levels of light stress, allowing an analysis of these compounds. In this paper, the identification of possible relationships between light stress and ¹H NMR signal variations is discussed. The analysis of the ¹H NMR (1D) spectra of two agronomic species (Spinacia oleracea and Beta vulgaris) exposed to different light intensities is presented. In particular, change in carotenoids and xanthophylls signals are analyzed.     

HIGH‐RESOLUTION MAGIC ANGLE SPINNING NMR ANALYSIS OF WHOLE CELLS OF CHAETOCEROS MUELLERI (BACILLARIOPHYCEAE) AND COMPARISON WITH 13C‐NMR AND DISTORTIONLESS ENHANCEMENT BY POLARIZATION TRANSFER 13C‐NMR ANALYSIS OF LIPOPHILIC EXTRACTS1

Lipid composition in extracted samples of Chaetoceros muelleri Lemmermann was studied with ¹³C‐NMR and distortionless enhancement by polarization transfer (DEPT) ¹³C‐NMR, resulting in well‐resolved ¹³C‐NMR spectra with characteristic resonance signals from carboxylic, olefinic, glyceryl, methylene, and methyl groups. The application of a DEPT pulse sequence aided in the assignment of methylene and methine groups. Resonance signals were compared with literature references, and signal assignment included important unsaturated fatty acids such as eicosapentaenoic and docosahexaenoic and also phospholipids and glycerols. Results from the extracted samples were used to assign resonance signals in a high‐resolution magic angle spinning (HR MAS) DEPT ¹³C spectrum from whole cells of C. muelleri. The NMR analysis on whole cells yielded equally good information on fatty acids and also revealed signals from carbohydrates and amino acids. Broad resonance signals and peak overlapping can be a problem in whole cell analysis, but we found that application of HR MAS gave a well‐resolved spectrum. The chemical shift of metabolites in an NMR spectrum depends on the actual environment of nuclei during analysis, and some differences could therefore be expected between extracted and whole cell samples. The shift differences were small, and assignment from analysis of lipophilic extract could be used to identify peaks in the whole cell spectrum. HR MAS ¹³C‐NMR therefore offers a possibility for broad‐range metabolic profiling directly on whole cells, simultaneously detecting metabolites that are otherwise not detected in the same analytical set up and avoiding tedious extraction procedures.     

Characterization of data analysis methods for information recovery from metabolic 1H NMR spectra using artificial complex mixtures

The assessment of data analysis methods in ¹H NMR based metabolic profiling is hampered owing to a lack of knowledge of the exact sample composition. In this study, an artificial complex mixture design comprising two artificially defined groups designated normal and disease, each containing 30 samples, was implemented using 21 metabolites at concentrations typically found in human urine and having a realistic distribution of inter-metabolite correlations. These artificial mixtures were profiled by ¹H NMR spectroscopy and used to assess data analytical methods in the task of differentiating the two conditions. When metabolites were individually quantified, volcano plots provided an excellent method to track the effect size and significance of the change between conditions. Interestingly, the Welch t test detected a similar set of metabolites changing between classes in both quantified and spectral data, suggesting that differential analysis of ¹H NMR spectra using a false discovery rate correction, taking into account fold changes, is a reliable approach to detect differential metabolites in complex mixture studies. Various multivariate regression methods based on partial least squares (PLS) were applied in discriminant analysis mode. The most reliable methods in quantified and spectral ¹H NMR data were PLS and RPLS linear and logistic regression respectively. A jackknife based strategy for variable selection was assessed on both quantified and spectral data and results indicate that it may be possible to improve on the conventional Orthogonal-PLS methodology in terms of accuracy and sensitivity. A key improvement of our approach consists of objective criteria to select significant signals associated with a condition that provides a confidence level on the discoveries made, which can be implemented in metabolic profiling studies.     

Metabolomic profile in hyperthyroid patients before and after antithyroid drug treatment: Correlation with thyroid hormone and TSH concentration

Hyperthyroidism (HT) is characterized by an intense metabolic impact which affects the lipid, carbohydrate and amino acids metabolism, with increased resting energy expenditure and thermogenesis. Metabolomics is a new comprehensive technique that allows to capture an instant metabolic picture of an organism, reflecting peculiar molecular and pathophysiological states. The aim of the present prospective study was to identify a distinct metabolomic profile in HT patients using ¹H NMR spectroscopy before and after antithyroid drug treatment. This prospective study included 15 patients (10 female, 5 male) who were newly diagnosed hyperthyroidism. A nuclear magnetic resonance (¹H NMR) based analysis was performed on plasma samples from the same patients at diagnosis (HypT₀) and when they achieved euthyroidism (HypT₁). The case groups were compared with a control group of 26 healthy volunteers (C). Multivariate statistical analysis was performed with Partial Least Squares-Discriminant Analysis (PLS-DA). PLS-DA identified a distinct metabolic profile between C and untreated hyperthyroid patients (R²X 0.638, R²Y 0.932, Q² 0.783). Interestingly, a significant difference was also found between C and euthyroid patients after treatment (R²X 0.510, R²Y 0.838, Q² 0.607), while similar cluster emerged comparing HypT₀ vs HypT₁ patients. This study shows that metabolomic profile is deeply influenced by hyperthyroidism and this alteration persists after normalization of thyrotropin (TSH) and free thyroid hormone (FT3, FT4) concentration. This suggests that TSH, FT3 and FT4 assays may not be insufficient to detect long lasting peripheral effects of the thyroid hormones action. Further studies are needed to clarify whether and to what extent the evaluation of metabolomics profile may provide relevant information in the clinical management of hyperthyroidism.