1H NMR Metabolic Profiling Research Articles

Therapeutic assessment of fractions of Gastrodiae Rhizoma on chronic atrophic gastritis by 1H NMR-based metabolomics

Ethnopharmacological relevanceGastrodiae Rhizoma (GR), a well-known and commonly-used TCM (Traditional Chinese Medicine) for treating headache, dizziness, tetanus, epilepsy, and etc., has been proven to relieve chronic atrophic gastritis (CAG). Due to its complex ingredients, the active fractions responsible for the treatment of CAG remain largely unknown. Aim of the studyTo explore the underlying material and interpret its underlying mechanism, the therapeutic effect of extract from different polar parts of Gastrodiae Rhizoma on autoimmune CAG was studied based on the 1H NMR metabolomics. Materials and methodsThe rat model of CAG was established by autoimmune method. The modeled CAG rats were then treated with 4 polar parts (T1-4 in descending polarity, corresponding to water, n-butanol, ethyl acetate and petroleum ether extracts, respectively) of Gastrodiae Rhizoma for 21 consecutive days. The stomach and serum samples were collected and then subjected to histopathology observation, biochemical measurement (MDA, SOD, GSH, NO, XOD and pepsin), 1H NMR metabolic profiling and multivariate/univariate statistical analysis. ResultsThe results showed that T1 had the best therapeutic effect, T2 the second, and T3 and T4 the poorest with no obvious therapeutic effect, demonstrating that the effective components of Gastrodiae Rhizoma should be compounds of high polarity. T1 achieved good therapeutic effects due to the anti-inflammatory and anti-oxidant activities, and by rectifying the disturbed energy and amino acid metabolism in CAG model. ConclusionThis integrated metabolomics approach proved the validity of the therapeutic effect of extract from different polar parts of Gastrodiae Rhizoma on autoimmune CAG, providing new insights into the underlying mechanisms, and demonstrating the feasibility of metabolomics to evaluate efficacy of herbal drug, which is often difficult by traditional means.

1H NMR Metabolic Profile of Scyphomedusa Rhizostoma pulmo (Scyphozoa, Cnidaria) in Female Gonads and Somatic Tissues: Preliminary Results.

The Mediterranean basin is one of the regions heavily affected by jellyfish bloom phenomena, mainly due to the presence of scyphozoans, such as Rhizostoma pulmo. The jellyfish have few natural predators, and their bodies represent an organic-rich substrate that can support rapid bacterial growth with great impact on the structure of marine food webs. In Asiatic countries, jellyfish are widely studied for their health benefits, but their nutritional and nutraceutical values still remain poorly characterized. In this study, the differences in the 1H NMR spectroscopy metabolic profiles of R. pulmo female gonads and body fractions (including umbrella and oral arms), in different sampling periods, were studied. For each body compartment both lipid and aqueous extracts were characterized and their 1H NMR metabolic profiles subjected to multivariate analysis. From a statistical analysis of the extracts, a higher contents of ω-3 polyunsaturated fatty acids (PUFAs), amino acid and osmolytes (homarine, betaine, taurine) with important roles in marine invertebrates were observed in female gonads, whereas umbrella and oral arms showed similar metabolic profiles. These results support a sustainable exploitation of the jellyfish for the extraction of bioactive compounds useful in nutraceutical, nutricosmetics, and functional food fields.

1H NMR spectroscopy coupled with multivariate analysis was applied to investigate Italian cherry tomatoes metabolic profile

AbstractNuclear magnetic resonance (NMR) spectroscopy, in combination with different chemometric methods, was widely used for metabolomic profiling in the geographical determination of food origin. In the present study, spectra data of cherry tomatoes, collected from Pachino (Sicily) and Sabaudia (Latium), were analyzed by principal component analysis (PCA), k nearest neighbors (kNN), and partial least‐squares discriminant analysis (PLS‐DA) in order to discriminate the samples according to their geographical provenance.The PCA analysis of 1H NMR spectra of Sabaudia cherry tomatoes showed significant differences linked to the production year: phospholipids had higher levels in 2004, but less amounts of polyunsaturated acids and lycopene were observed with respect to the year 2005. Despite the annual differences in 1H NMR metabolic profile of Sabaudia cherry tomatoes, using unsupervised (PCA) and supervised (PLS‐DA, kNN) approaches, the geographical origin differentiation was obtained. In fact, the kNN algorithm correctly classified approximately 84% to 87% of Pachino samples and 77% of Sabaudia ones with recognition ability varied from 82% to 84.4% and prediction ability (CV) of 76.2% and 94.7%. The PC1 component, with 53% of total variance, greatly separated Pachino cherry tomatoes from Sabaudia ones and PLS‐DA model showed a good degree of separation with recognition ability of 100% and prediction ability (CV) of 93% to 100%.PCA and PLS‐DA combined analysis highlighted the most prominent spectral areas that well separated the two groups of samples. So, phytosterols were found discriminating compounds according to PCA and PLS‐DA and differences in aroma components were observed mainly in PCA analysis.

From morphological traits to the food fingerprint of Tropaeolum tuberosum through metabolomics by NMR

The objective of our research was to contrast the resonance techniques on tubers with the more commonly used morphological analyses. With the aims of establishing a classification among ecotypes and food fingerprint of mashua tuber, a multivariable data analysis like principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA), were performed with morphological and metabolomic profiling data. Accordingly, the morphological traits showed a clear separation among most of the studied ecotypes. For a 1H NMR metabolic profiling, at least 35 compounds were identified in tubers. The relative concentration of these compounds was used to perform a PCA and OPLS-DA analysis. A clear separation, according to PC1 = 31.7%, was between TTE_01 & TTE_02 and the ecotypes TTE_06 and TTE_05 with significantly higher concentrations of disaccharides such as maltose and sucrose. Amino acids such as proline and alanine were found and organic acid including succinic, fumaric, formic and acetic acid. In contrast, TTE_05 and TTE_06 ecotypes contained higher concentrations of monosaccharides such as fructose, glucose. Metabolic profile demonstrated to be a more reliable technique than morphological analysis for classification of ecotypes.

Methyljasmonate Elicitation Increases Terpenoid Indole Alkaloid Accumulation in Rhazya stricta Hairy Root Cultures.

Methyl jasmonate is capable of initiating or improving the biosynthesis of secondary metabolites in plants and therefore has opened up a concept for the biosynthesis of valuable constituents. In this study, the effect of different doses of methyl jasmonate (MeJA) elicitation on the accumulation of terpenoid indole alkaloids (TIAs) in the hairy root cultures of the medicinal plant, Rhazya stricta throughout a time course (one-seven days) was investigated. Gas chromatography-mass spectrometry (GC-MS) analyses were carried out for targeted ten major non-polar alkaloids. Furthermore, overall alterations in metabolite contents in elicited and control cultures were investigated applying proton nuclear magnetic resonance (1H NMR) spectroscopy. Methyl jasmonate caused dosage- and time course-dependent significant rise in the accumulation of TIAs as determined by GC-MS. The contents of seven alkaloids including eburenine, quebrachamine, fluorocarpamine, pleiocarpamine, tubotaiwine, tetrahydroalstonine, and ajmalicine increased compared to non-elicited cultures. However, MeJA-elicitation did not induce the accumulation of vincanine, yohimbine (isomer II), and vallesiachotamine. Furthermore, principal component analysis (PCA) of 1H NMR metabolic profiles revealed a discrimination between elicited hairy roots and control cultures with significant increase in total vindoline-type alkaloid content and elevated levels of organic and amino acids. In addition, elicited and control samples had different sugar and fatty acid profiles, suggesting that MeJA also influences the primary metabolism of R. stricta hairy roots. It is evident that methyl jasmonate is applicable for elevating alkaloid accumulation in “hairy root” organ cultures of R. strica.

The Influence of Drying Temperatures on the Metabolic Profiles and Antioxidant Activity of Manilkara zapota Leaves.

In the present study, the leaves of Manilkara zapota (L.) P. Royen (Sapotaceae), an evergreen tree recognized for its medicinal properties in Southern Mexico, were used as a model to study the effect of different drying temperatures on its metabolic profile and therefore, its antioxidant potential. For this purpose, a methanol extraction of leaves dried at room temperature (25 °C) or by heat convection (50, 75 and 100 °C) were compared in terms of drying efficiency, yield of extraction, total phenol content, 1H-NMR metabolic profile, and DPPH antioxidant activity. The drying curves enabled the fact to be uncovered that drying efficiency improves with increase of temperature, as does the level of total phenols and antioxidant activity. A metabolomics approach using principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) of the corresponding 1H-NMR profiles allowed the impact of the drying temperature on their metabolic profile to be documented and also, caffeic acid and epicatechin as main secondary metabolites contributing to the antioxidant activity of M. zapota to be identified.

1H NMR Metabolic Profile to Discriminate Pasture Based Alpine Asiago PDO Cheeses.

Simple SummaryNowadays, alpine cheese from grazing dairy herds has a premium market value because consumers perceive its higher degree of healthiness and sustainability. The authenticity of pasture-based cheese should be safeguarded from local hay-based milk analogues. The study aimed at assessing the reliability of proton nuclear magnetic resonance (1H NMR) to discriminate pasture-based alpine Asiago PDO cheeses of different ripening time from similar hay-based samples processed in the same dairy plant. Cheeses were produced from raw milk collected from grazing or hay-fed alpine dairy herds and they were ripened for 2 (Pressato), 4 (Allevo_4), and 6 (Allevo_6) months. Samples of the cheeses were submitted to wet chemistry and nuclear magnetic resonance analysis. The outcomes of the 1H NMR spectroscopy were used in a multivariate discriminant procedure. Choline, 2,3-butanediol, lysine, and tyrosine and some residual sugar-like compounds were water-soluble biomarkers of cows’ feeding system. However, the application of 1H NMR based metabolomics was an effective fingerprinting method to correctly identify only cheese samples with the shortest ripening period. The classification of more aged cheese samples according to the cows’ feeding system was less accurate likely due to the chemical and biochemical changes induced by a prolonged maturation process.The study was carried out in an alpine area of North-Eastern Italy to assess the reliability of proton nuclear magnetic resonance 1H NMR to fingerprint and discriminate Asiago PDO cheeses processed in the same dairy plant from upland pasture-based milk or from upland hay-based milk. Six experimental types of Asiago cheese were made from raw milk considering 2 cows’ feeding systems (pasture- vs. hay-based milk) and 3 ripening times (2 months, Pressato vs. 4 months, Allevo_4 vs. 6 months, Allevo_6). Samples (n = 55) were submitted to chemical analysis and to 1H NMR coupled with multivariate canonical discriminant analysis. Choline, 2,3-butanediol, lysine, tyrosine, and some signals of sugar-like compounds were suggested as the main water-soluble metabolites useful to discriminate cheese according to cows’ feeding system. A wider pool of polar biomarkers explained the variation due to ripening time. The validation procedure based on a predictive set suggested that 1H NMR based metabolomics was an effective fingerprinting tool to identify pasture-based cheese samples with the shortest ripening period (Pressato). The classification to the actual feeding system of more aged cheese samples was less accurate likely due to their chemical and biochemical changes induced by a prolonged maturation process.

Influence of herd diet on the metabolome of Maasdam cheeses.

The untargeted metabolic profiles of ripened Maasdam cheese samples prepared from milk derived from three herd groups, fed: (1) indoors on total mixed ration (TMR), or outdoors on (2) grass only pasture (GRA) or (3) grass and white clover pasture (CLO) were studied using high resolution nuclear magnetic resonance (1H NMR), high resolution magic angle spinning nuclear magnetic resonance (1H HRMAS NMR) and headspace (HS) gas chromatography mass spectrometry (GC-MS). A total of 31 compounds were identified using 1H NMR and 32 volatile compounds including 7 acids, 5 esters, 4 alcohols, 4 ketones, 4 sulfur compounds, 2 aldehydes, 3 hydrocarbons, 2 terpenes and a lactone were identified using GC-MS in Maasdam cheeses ripened for 97-d. On comparing the 1H NMR metabolic profiles, TMR-derived cheese had higher levels of citrate compared to GRA-derived cheese. The toluene content of cheese was significantly higher in GRA or CLO compared to TMR cheeses and dimethyl sulfide was identified only in CLO-derived cheese samples as detected using HS GC-MS. These compounds are proposed as indicator compounds for Maasdam cheese derived from pasture-fed milk. Clear differences between outdoor or indoor feeding systems in terms of cheese metabolites were detected in the lipid phase, as indicated by principal component analysis (PCA) from 1H HRMAS NMR spectra, although differences based on PCA of all 1H NMR spectra and HS-GC-MS were less clear. Overall, this study presented the metabolite profile and identified specific compounds which may be useful for discriminating between ripened Maasdam cheese and related cheese varieties manufactured from indoor or outdoor herd-feeding systems.

NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome

The variation in the extracellular metabolites of RAW 264.7 cells obtained from different passage numbers (passage 9, 12 and 14) was examined. The impact of different harvesting protocols (trypsinization and scraping) on recovery of intracellular metabolites was then assessed. The similarity and variation in the cell metabolome was investigated using 1H NMR metabolic profiling modeled using multivariate data analysis. The characterization and quantification of metabolites was performed to determine the passage-related and harvesting-dependent effects on impacted metabolic networks. The trypsinized RAW cells from lower passages gave higher intensities of most identified metabolites, including asparagine, serine and tryptophan. Principal component analysis revealed variation between cells from different passages and harvesting methods, as indicated by the formation of clusters in score plot. Analysis of S-plots revealed metabolites that acted as biomarkers in discriminating cells from different passages including acetate, serine, lactate and choline. Meanwhile lactate, glutamine and pyruvate served as biomarkers for differentiating trypsinized and scraped cells. In passage-dependent effects, glycolysis and TCA cycle were influential, whereas glycerophospholipid metabolism was affected by the harvesting method. Overall, it is proposed that typsinized RAW cells from lower passage numbers are more appropriate when conducting experiments related to NMR metabolomics.

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome

BackgroundBoth of the modern medicine and the traditional Chinese medicine classify depressive disorder (DD) and chronic fatigue syndrome (CFS) to one type of disease. Unveiling the association between depressive and the fatigue diseases provides a great opportunity to bridge the modern medicine with the traditional Chinese medicine. MethodsIn this work, 295 general participants were recruited to complete Zung Self-Rating Depression Scales and Chalder Fatigue Scales, and meanwhile, to donate plasma and urine samples for 1H NMR-metabolic profiling. Artificial intelligence methods was used to analysis the underlying association between DD and CFS. Principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyze the metabolic profiles with respect to gender and age. Variable importance in projection and t-test were employed in conjunction with the PLS-DA models to identify the metabolite biomarkers. Considering the asymmetry and complexity of the data, convolutional neural networks (CNN) model, an artificial intelligence method, was built to analyze the data characteristics between each groups. ResultsThe results showed the gender- and age-related differences for the candidate biomarkers of the DD and the CFS diseases, and indicated the same and different biomarkers of the two diseases. PCA analysis for the data characteristics reflected that DD and CFS was separated completely in plasma metabolite. However, DD and CFS was merged into one group. LimitationLack of transcriptomic analysis limits the understanding of the association of the DD and the CFS diseases on gene level. ConclusionThe unmasked candidate biomarkers provide reliable evidence to explore the commonality and differences of the depressive and the fatigue diseases, and thereby, bridge over the traditional Chinese medicine with the modern medicine.

Sex differences in the 1H NMR metabolic profile of serum in cardiovascular risk patients

Personalized diagnosis and risk stratification of cardiovascular diseases would allow optimizing therapeutic strategies and lifestyle changes. Metabolomics is a promising technique for personalized diagnosis and prognosis; however, various physiological parameters, including sex, influence the metabolic profile thus hampering its translation to the clinic. Knowledge of the variation in the metabolic profile associated with sex would facilitate metabolomic translation to the clinic. The objective of the present work was to investigate the possible differences in the metabolic 1H NMR profile associated to sex beyond lipoproteins. 1H NMR spectra from whole serum and methanol deproteinized samples from 39 patients (22 males, 17 females) between 55–70 years old with suspected coronary artery disease that underwent a stress test that was considered negative where included. Deproteinized serum could be used to differentiate sex based on higher levels of lactate and glucose in women. Lipoprotein region was the most variable area of the spectra between individuals, but spectra of whole serum were able to differentiate sex based on lipoproteins. There are sex-related differences in the 1H NMR metabolic profile of individuals with suspected cardiovascular disease beyond lipoproteins. These findings may help the translation of metabolomics to the clinic.

1H NMR metabolic profiling of the cryopreserved spermatozoa of the wild endangered Persian sturgeon (Acipenser persicus) with the use of beta-cyclodextrin as an external cryoprotectant.

Persian sturgeon (Acipenser persicus) is an endangered species and genetic resource banking such as gametes and embryo preservation could be one of the most pursued conservation approaches. In this study, deleterious effects of the traditional cryopreservation technique and the effect of different doses of 2-hydroxypropyl-beta-cyclodextrin (HβCD) on thawed spermatozoa quality (motility duration and percentage) of Persian sturgeon (Acipenser persicus) were investigated from metabolic aspects of view. For cryopreserving, semen was diluted with Tris-HCl (100mM) extenders containing 0, 5, 10, and 15mM of HβCD in a ratio of 1:1 (semen/extenders). Semen-extenders were filled into 0.5-mL straws and were frozen with the vapor of liquid nitrogen, and then immersed into liquid nitrogen. Cryopreserved spermatozoa were thawed in water baths in 15s. Two treatments with the highest and the lowest motility percentages (0 and 10mM of HβCD) were chosen to reveal the extremes of the metabolites change range and were objected to 1H NMR spectroscopy. Univariate (ANOVA) and multivariate (PCA) analysis of the obtained metabolic profiles showed significant changes (P < 0.05) in metabolites. The use of 10mM of HβCD was completely successful in the preservation of creatinine, glucose, guanidoacetate, O-phosphocholine, and N, N-dimethylglycine and probably their corresponding biochemical pathways, but it failed to preserve lactate, carnitine, betain, β-alanin, and trimethylamine N-oxide. It was also partially successful in preserving acetate, creatine, creatine phosphate, and glycine, all suggesting how HβCD can be effective as a cryoprotectant.

Fast nutritional characterization of different pigmented rice grains using a combination of NMR and decision tree analysis

ABSTRACTDifferent rice cultivars contain various metabolites which are closely related with their nutritional and functional effects. In the current study, NMR and chemometrics methods – decision tree analysis (DTA) were applied to explore the chemical characteristics in different rice cultivars. The pigmented rice were completely discriminated from each other, and the key metabolites that mostly contributed to the rice discrimination were explored, including sugars compounds (sucrose, fructose and glucose) and non-sugar compounds (γ-amino butyric acid (GABA), asparagine, citric acid and malic acid) with DTA approach and 1HNMR metabolite fingerprints. The purple rice has the highest concentrations of sucrose, citric acid and asparagine (p < 0.05), but lowest fructose (p < 0.05); red rice has the lowest GABA concentration comparing with the other three groups (p < 0.05). This study implies that DTA method is a powerful tool to discriminate different pigmented rice varieties. Furthermore, it also reveals the crucial nutrients based on 1H-NMR metabolic profiling.

1H NMR metabolic profiling revealed characteristic metabolites in mud crab Scylla paramamosain for different geographical origins

ABSTRACT The geographical origin of mud crab (Scylla paramamosain) has been arousing increasing interest to consumers due to their flavour and market price. In this study, an NMR-based metabolomics method was used to characterize the differences in the chemical composition of muscle samples of mud crabs caught in four different geographical areas of China. The results showed that a statistically significant separation existed between each of the groups of mud crabs in terms of their geographical origins. The major metabolites responsible for differentiation included inosine 5’-monophosphate (IMP), adenosine 5’-monophosphate (AMP), and some amino acids. A gradual increase in the AMP level in conjunction with a declining IMP level was closely associated with the growth latitude of the mud crab, which means that these metabolites could potentially be used to characterize the specific geographic origin of mud crabs. This information might be useful for assessing the quality of mud crabs from different geographical origins.

Hepatotoxicity and hepatoprotection of Polygonum multiflorum Thund. as two sides of the same biological coin

Ethnopharmacological relevancePolygonum multiflorum Thund., a well-known and commonly-used TCM (Traditional Chinese Medicine) for treating hypertension, hyperlipidemia, premature graying of hair, and etc., has aroused wide concern for its reported potential liver toxicity. Due to its various active ingredients, the mechanisms underlying the hepatotoxicity of raw Polygonum multiflorum Thund (RPM) remain largely unknown. Aim of the study1H NMR metabolomics was used to study the mechanism of RPM induced hepatotoxicity and disclosed the existence of hepatotoxicity and hepatoprotection conversion during RPM administration in mice. Materials and MethodsThree dosages of RPM were administered by gavage to mice for consecutive 28 days. The serum and liver samples were collected and then subjected for histopathology observation, biochemical measurement and 1H NMR metabolic profiling. ResultsRPM caused oxidative stress and mitochondria dysfunction in mice, resulting in significant disturbance in energy metabolism, amino acid metabolism and pyrimidine metabolism and also inducing inflammatory responses. RPM induced hepatotoxicity in an apparent non-linear manner: the most severe in low dosage group, and to a less extent in medium group according to metabolomics analysis. The attenuation of liver injury in mice livers might result from the therapeutic effects, such as anti-oxidative capacity of RPM components. ConclusionRPM exerted a complicated non-linear manner in healthy recipients, switching between hepatoxicity and hepatoprotection dependent on the dosage and status of the body.

Traceability of "Tuscan PGI" Extra Virgin Olive Oils by ¹H NMR Metabolic Profiles Collection and Analysis.

According to Coldiretti, Italy still continues to hold the European Quality record in extra virgin olive oils with origin designation and protected geographical indication (PDO and PGI). To date, 46 Italian brands are recognized by the European Union: 42 PDO and 4 PGI (Tuscan PGI, Calabria PGI; Tuscia PGI and PGI Sicily). Specific regulations, introduced for these quality marks, include the designation of both the geographical areas and the plant varieties contributing to the composition of the olive oil. However, the PDO and PGI assessment procedures are currently based essentially on farmer declarations. Tuscan PGI extra virgin olive oil is one of the best known Italian trademarks around the world. Tuscan PGI varietal platform is rather wide including 31 specific olive cultivars which should account for at least 95% of the product. On the other hand, while the characteristics of other popular Italian extra virgin olive oils (EVOOs) cultivars from specific geographical areas have been extensively studied (such as those of Coratina based blends from Apulia), little is still known about Tuscan PGI EVOO constituents. In this work, we performed, for the first time, a large-scale analysis of Tuscan PGI monocultivar olive oils by 1H NMR spectroscopy and multivariate statistical analyses (MVA). After genetic characterization of 217 leaf samples from 24 selected geographical areas, distributed all over the Tuscany, a number of 202 micro-milled oil samples including 10 PGI cultivars, was studied. The results of the present work confirmed the need of monocultivar genetically certified EVOO samples for the construction of 1H-NMR-metabolic profiles databases suitable for cultivar and/or geographical origin assessment. Such specific PGI EVOOs databases could be profitably used to justify the high added value of the product and the sustainability of the related supply chain.

Combined magnetic resonance imaging and high resolution spectroscopy approaches to study the fertilization effects on metabolome, morphology and yeast community of wine grape berries, cultivar Nero di Troia

Effects of fertilization practices, mineral (M) and organo-mineral (OM), on molecular composition of Nero di Troia cultivar grape berries was studied using conventional chemical analysis, Magnetic Resonance Imaging (MRI) and 1H NMR spectroscopy on intact berries and extracts, respectively, and through analysis of yeast species developed on grape skins.Plants vegetative status did not differ between the two fertilization practices, whereas some grape juice chemical characteristics differed in fertilized grapes. MRI provided information on grape berries morphology through weighted images depending on spin-spin (T2) and spin-lattice (T1) relaxation times. T1 values were the highest in OM grape berries. 1H NMR metabolic profile, combined with chemometric analysis, evidenced significant differences for some metabolites (valine, leucine, isoleucine, proline, and malic acid). Furthermore, higher frequency of yeasts genus Starmella sp., isolated from OM grape berries contributed to reinforcing the found results on the physiological response of wine grape Nero di Troia to fertilization.

Metabolic Characterization of Peripheral Host Responses to Drainage-Resistant Klebsiella pneumoniae Liver Abscesses by Serum 1H-NMR Spectroscopy.

Purpose: To explore the metabolic characterization of host responses to drainage-resistant Klebsiella pneumoniae liver abscesses (DRKPLAs) with serum 1H-nuclear magnetic resonance (NMR) spectroscopy.Materials and Methods: The hospital records of all patients with a diagnosis of a liver abscess between June 2015 and December 2016 were retrieved from an electronic hospital database. Eighty-six patients with Klebsiella pneumoniae (K. pneumoniae) liver abscesses who underwent percutaneous drainage were identified. Twenty patients with confirmed DRKPLAs were studied. Moreover, we identified 20 consecutive patients with drainage-sensitive Klebsiella pneumoniae liver abscesses (DSKPLAs) as controls. Serum samples from the two groups were analyzed with 1H NMR spectroscopy. Partial least squares discriminant analysis (PLS-DA) was used to perform 1H NMR metabolic profiling. Metabolites were identified using the Human Metabolome Database, and pathway analysis was performed with MetaboAnalyst 3.0.Results: The PLS-DA test was able to discriminate between the two groups. Five key metabolites that contributed to their discrimination were identified. Glucose, lactate, and 3-hydroxybutyrate were found to be upregulated in DRKPLAs, whereas glutamine and alanine were downregulated compared with the DSKPLAs. Pathway analysis indicated that amino acid metabolisms were significantly different between the DRKPLAs and the DSKPLAs. The D-glutamine and D-glutamate metabolisms exhibited the greatest influences.Conclusions: The five key metabolites identified in our study may be potential targets for guiding novel therapeutics of DRKPLAs and are worthy of additional investigation.

Protective effects of Polygonum multiflorum on ischemic stroke rat model analysed by 1H NMR metabolic profiling

Stroke is the third most common cause of death in most industrialized countries. Polygonum multiflorum (He-Shou-Wu, HSW) is one of the traditional Chinese medicines with multiple pharmacological activities which is widely used in Chinese recipe. This study aims to explore the protective effect of HSW on ischemic stroke rat model and to elucidate the underlying mechanisms. The mortality rate, neurological deficit, cerebral infarct size, histopathology, immunohistochemistry, biochemical parameters, quantitative real-time polymerase chain reaction and western blotting were used to access the treatment effects of HSW on ischemic stroke. Proton nuclear magnetic resonance (1H NMR) based metabolomics analysis disclosed that HSW could relieve stroke rats suffering from the ischemia/reperfusion injury by ameliorating the disturbed energy and amino acids metabolisms, alleviating the oxidative stress from reactive oxygen species and reducing the inflammation. HSW treatment increased levels of cellular antioxidants that scavenged reactive oxygen species during ischemia-reperfusion via the nuclear erythroid 2-related factor 2 signaling pathway, and exert anti-inflammatory effect by decreasing the levels of inflammatory factors such as cyclooxygenase-2, interleukin-1β, interleukin-6 and tumor necrosis factor-α. The integrated metabolomics approach showed its potential in understanding mechanisms of HSW in relieving ischemic stroke. Further study to develop HSW as an effective therapeutic agent to treat ischemic stroke is warranted.

1H NMR metabolic profiling of gastric cancer patients with lymph node metastasis

IntroductionGastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients.ObjectivesWe performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC.Methods1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n = 40), LNM-negative GC patients (n = 40) and normal controls (n = 40).ResultsThere was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM.ConclusionTo our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC.