Revealing metabolic and biochemical variations via 1H NMR metabolomics in streptozotocin-nicotinamide-induced diabetic rats treated with metformin

The increasing prevalence of lean diabetes has prompted the generation of animal models that mimic metabolic disease in humans. This study aimed to determine the optimum streptozotocin-nicotinamide (STZ-NA) dosage ratio to elicit lean diabetic features in a rat model. It also used a proton nuclear magnetic resonance (1H NMR) urinary metabolomics approach to identify the metabolic effect of metformin treatment on this novel rat model. Three different STZ-NA dosage regimens (by body weight: Group A: 110 mg/kg NA and 45 mg/kg STZ; Group B: 180 mg/kg NA and 65 mg/kg STZ and Group C: 120 mg/kg NA and 60 mg/kg STZ) were administered to Sprague-Dawley rats along with oral metformin. Group A diabetic rats (A-DC) showed favorable serum biochemical analyses and a more positive response toward oral metformin administration relative to the other STZ-NA dosage ratio groups. Orthogonal partial least squares-discriminant analysis (OPLS-DA) revealed that glucose, citrate, pyruvate, hippurate, and methylnicotinamide differentiating the OPLS-DA of A-MTF rats (Group A diabetic rats treated with metformin) and A-DC model rats. Subsequent metabolic pathway analyses revealed that metformin treatment was associated with improvement in dysfunctions caused by STZ-NA induction, including carbohydrate metabolism, cofactor metabolism, and vitamin and amino acid metabolism. In conclusion, our results identify the best STZ-NA dosage ratio for a rat model to exhibit lean type 2 diabetic features with optimum sensitivity to metformin treatment. The data presented here could be informative to improve our understanding of non-obese diabetes in humans through the identification of possible activated metabolic pathways in the STZ-NA-induced diabetic rats model.

Phytoconstituents of Endiandra kingiana; antidiabetic effects and molecular docking studies on alpha-amylase and alpha-glucosidase

Phytochemical investigation on the bark of E. kingiana plant afforded ten compounds, including six polyketides namely kingianin A 1, kingianin B 2, kingianin E 3, kingianin F 4, kingianin K 5 and kingianin L 6, three endiandric acids; kingianic acid A 7, tsangibeilin B 8 and endiandric acid M 9, and one sesquiterpene; daibuoxide 10. All compounds were separated as racemic mixture by recycling high-performance liquid chromatography (RHPLC), except for daibuoxide. Their structures were elucidated by detailed spectroscopic and comparative literature data analysis. This is the first report on the presence of the sesquiterpene; daibuoxide in Endiandra genus. In vitro enzymatic bio-evaluation of the isolated compounds against α-amylase and α-glucosidase showed that 4 demonstrated the best α-amylase and α-glucosidase inhibitory activity with IC50 values of 181.54 ± 6.27 µg/mL and 237.87 ± 0.07 µg/mL, respectively. In addition, molecular docking analysis confirmed the α-amylase and α-glucosidase inhibitory activities demonstrated by 4.

Multivariate modelling analysis for prediction of glycidyl esters and 3-monochloropropane-1,2-diol (3-MCPD) formation in periodically heated palm oil

Palm oil is a vegetable oil that is widely used for cooking and deep-frying because of its affordability. However, repeatedly heated palm oil is also prone to oxidation due to its significant content of unsaturated fatty acids and other chemical toxicants such as glycidyl esters and 3-monochloropropane-1,2-diol (3-MCPD). Initially, the physicochemical properties such as colour, viscosity, peroxide, p-anisidine and total oxidation (TOTOX) of periodically heated palm oil were investigated. Chemical profiling and fingerprinting of six different brands of palm cooking oil during heating cycles between 90 and 360 min were conducted using Fourier transform infrared (FTIR) and 1H Nuclear Magnetic Resonance (NMR) metabolomics. In addition, the multivariate analysis was employed to evaluate the 1H NMR spectroscopic pattern of repeatedly heated palm oil with the corresponding physicochemical properties. The FTIR metabolomics showed significant different of the chemical fingerprinting subjected to heating duration, which in agreement with the result of 1H NMR metabolomics. Partial least squares (PLS) model revealed that most of the physicochemical properties of periodically heated palm oil are positively correlated (R2 values of 0.98-0.99) to their spectroscopic pattern. Based on the findings, the color of the oils darkened with increased heating time. The peroxide value (PV), p-anisidine value (p-AnV), and total oxidation (TOTOX) values increased significantly due to degradation of unsaturated compounds and oxidation products formed. We identified targeted metabolites (probable carcinogens) such as 3-monochloropropane-1,2-diol (3-MCPD) and glycidyl ester (GE), indicating the conversion of 3-MCPD to GE in repeatedly heated oils based on PCA and OPLSDA models. Our correlation analysis of NMR and physicochemical properties has shown that the conversion of 3-MCPD to GE was significantly increased from 180 to 360 min cooking time. The combination spectroscopic techniques with physicochemical properties are a reliable and robust methods to evaluate the characteristics, stability and chemical's structure changes of periodically heated palm oil, which may contribute to probable carcinogens development. This study has proven that combination of NMR and physicochemical analysis may predict the formation of the probable carcinogens of heated cooking oil over time which emphasizing the need to avoid certain heating cycles to mitigate formation of probable carcinogens during cooking process.

Metabolic Alterations in Streptozotocin-nicotinamide-induced Diabetic Rats Treated with Muntingia calabura Extract via 1H-NMR-based Metabolomics

Diabetes mellitus (DM) is a metabolic endocrine disorder caused by decreased insulin concentration or poor insulin response. Muntingia calabura (MC) has been used traditionally to reduce blood glucose levels. This study aims to support the traditional claim of MC as a functional food and blood-glucose-lowering regimen. The antidiabetic potential of MC is tested on a streptozotocin-nicotinamide (STZ-NA)-induced diabetic rat model by using the ¹H-NMR-based metabolomic approach. Serum biochemical analyses reveal that treatment with 250 mg/kg body weight (bw) standardized freeze-dried (FD) 50% ethanolic MC extract (MCE 250) shows favorable serum creatinine (37.77 ± 3.53 µM), urea (5.98 ± 0.84 mM) and glucose (7.36 ± 0.57 mM) lowering capacity, which was comparable to the standard drug, metformin. The clear separation between diabetic control (DC) and normal group in principal component analysis indicates the successful induction of diabetes in the STZ-NA-induced type 2 diabetic rat model. A total of nine biomarkers, including allantoin, glucose, methylnicotinamide, lactate, hippurate, creatine, dimethylamine, citrate and pyruvate are identified in rats' urinary profile, discriminating DC and normal groups through orthogonal partial least squares-discriminant analysis. Induction of diabetes by STZ-NA is due to alteration in the tricarboxylic acid (TCA) cycle, gluconeogenesis pathway, pyruvate metabolism and nicotinate and nicotinamide metabolism. Oral treatment with MCE 250 in STZ-NA-induced diabetic rats shows improvement in the altered carbohydrate metabolism, cofactor and vitamin metabolic pathway, as well as purine and homocysteine metabolism.

Overcoming Methicillin-Resistance Staphylococcus aureus (MRSA) Using Antimicrobial Peptides-Silver Nanoparticles

Antibiotics are regarded as a miracle in the medical field as it prevents disease caused by pathogenic bacteria. Since the discovery of penicillin, antibiotics have become the foundation for modern medical discoveries. However, bacteria soon became resistant to antibiotics, which puts a burden on the healthcare system. Methicillin-resistant Staphylococcus aureus (MRSA) has become one of the most prominent antibiotic-resistant bacteria in the world since 1961. MRSA primarily developed resistance to beta-lactamases antibiotics and can be easily spread in the healthcare system. Thus, alternatives to combat MRSA are urgently required. Antimicrobial peptides (AMPs), an innate host immune agent and silver nanoparticles (AgNPs), are gaining interest as alternative treatments against MRSA. Both agents have broad-spectrum properties which are suitable candidates for controlling MRSA. Although both agents can exhibit antimicrobial effects independently, the combination of both can be synergistic and complementary to each other to exhibit stronger antimicrobial activity. The combination of AMPs and AgNPs also reduces their own weaknesses as their own, which can be developed as a potential agent to combat antibiotic resistance especially towards MRSA. Thus, this review aims to discuss the potential of antimicrobial peptides and silver nanoparticles towards controlling MRSA pathogen growth.

A Preliminary Nuclear Magnetic Resonance Metabolomics Study Identifies Metabolites that Could Serve as Diagnostic Markers of Major Depressive Disorder

BACKGROUND

The evaluation of metabolites that are directly involved in the physiological process, few steps short of phenotypical manifestation, remains vital for unravelling the biological moieties involved in the development of the (MDD) and in predicting its treatment outcome.

METHODOLOGY

Eight (8) urine and serum samples each obtained from consenting healthy controls (HC), twenty-five (25) urine and serum samples each from first episode treatment naïve MDD (TNMDD) patients, and twenty (22) urine and serum samples each s from treatment naïve MDD patients 2 weeks after SSRI treatment (TWMDD) were analysed for metabolites using proton nuclear magnetic resonance (1HNMR) spectroscopy. The evaluation of patients' samples was carried out using Partial Least Squares Discriminant Analysis (PLS-DA) and Orthogonal Partial Least Square- Discriminant Analysis (OPLSDA) models.

RESULTS

In the serum, decreased levels of lactate, glucose, glutamine, creatinine, acetate, valine, alanine, and fatty acid and an increased level of acetone and choline in TNMDD or TWMDD irrespective of whether an OPLSDA or PLSDA evaluation was used were identified. A test for statistical validations of these models was successful.

CONCLUSION

Only some changes in serum metabolite levels between HC and TNMDD identified in this study have potential values in the diagnosis of MDD. These changes included decreased levels of lactate, glutamine, creatinine, valine, alanine, and fatty acid, as well as an increased level of acetone and choline in TNMDD. The diagnostic value of these changes in metabolites was maintained in samples from TWMDD patients, thus reaffirming the diagnostic nature of these metabolites for MDD.

Cytotoxicity and 1H NMR metabolomics analyses of microalgal extracts for synergistic application with Tamoxifen on breast cancer cells with reduced toxicity against Vero cells

This study evaluated the cytotoxic activity of Tamoxifen (TMX), an anti-estrogen drug, with microalgal crude extracts (MCEs) in single and synergistic application (TMX-MCEs) on MCF-7 and 4T1 breast cancer cells, and non-cancerous Vero cells. The MCEs of Nannochloropsis oculata, Tetraselmis suecica and Chlorella sp. from five different solvents (methanol, MET; ethanol, ETH; water, W; chloroform, CHL; and hexane, HEX) were developed. The TMX-MCEs-ETH and W at the 1:2 and 1:3 ratios, attained IC₅₀ of 15.84–29.51 μg/mL against MCF-7; 13.8–31.62 μg/mL against 4T1; and 24.54–85.11 μg/mL against Vero cells. Higher late apoptosis was exhibited against MCF-7 by the TMX-N. oculata-ETH (41.15 %); and by the TMX-T. suecica-ETH (65.69 %) against 4T1 cells. The TMX-T. suecica-ETH also showed higher ADP/ATP ratios, but comparable Caspase activities to control. For Vero cells, overall apoptotic effects were lowered with synergistic application, and only early apoptosis was higher with TMX-T. suecica-ETH but at lower levels (29.84 %). The MCEs-W showed the presence of alanine, oleic acid, linoleic acid, lactic acid, and fumaric acid. Based on Principal Component Analysis (PCA), the spectral signals for polar solvents such as MET and ETH, were found in the same cluster, while the non-polar solvent CHL was with HEX, suggesting similar chemical profiles clustered for the same polarity. The CHL and HEX were more effective with N. oculata and T. suecica which were of the marine origin, while the ETH and MET were more effective with Chlorella sp., which was of the freshwater origin. The synergistic application of microalgal bioactive compounds with TMX can maintain the cytotoxicity against breast cancer cells whilst reducing the toxicity against non-cancerous Vero cells. These findings will benefit the biopharmaceutical, and functional and healthy food industries.

Complementary Analytical Platforms of NMR Spectroscopy and LCMS Analysis in the Metabolite Profiling of Isochrysis galbana

This study was designed to profile the metabolites of Isochrysis galbana, an indigenous and less explored microalgae species. ¹H Nuclear Magnetic Resonance (NMR) spectroscopy and Liquid Chromatography-Mass Spectrometry (LCMS) were used to establish the metabolite profiles of five different extracts of this microalga, which are hexane (Hex), ethyl acetate (EtOAc), absolute ethanol (EtOH), EtOH:water 1:1 (AqE), and 100% water (Aq). Partial least square discriminant analysis (PLS–DA) of the generated profiles revealed that EtOAc and Aq extracts contain a diverse range of metabolites as compared to the other extracts with a total of twenty-one metabolites, comprising carotenoids, polyunsaturated fatty acids, and amino acids, that were putatively identified from the NMR spectra. Meanwhile, thirty-two metabolites were successfully annotated from the LCMS/MS data, ten of which (palmitic acid, oleic acid, α-linolenic acid, arachidic acid, cholesterol, DHA, DPA, fucoxanthin, astaxanthin, and pheophytin) were similar to those present in the NMR profile. Another eleven glycerophospholipids were discovered using MS/MS-based molecular network (MN) platform. The results of this study, besides providing a better understanding of I.galbana’s chemical make-up, will be of importance in exploring this species potential as a feed ingredient in the aquaculture industry.

Perturbations in Amino Acid Metabolism in Reserpine-Treated Zebrafish Brain Detected by 1H Nuclear Magnetic Resonance-Based Metabolomics

Depression is a complex and disabling psychiatric disorder, which is expected to be a leading cause for disability by 2030. According to World Health Organization, about 350 million people are suffering with mental health disorders around the globe, especially depression. However, the mechanisms involved in stress-induced depression have not been fully elucidated. In this study, a stress-like state was pharmacologically induced in zebrafish using reserpine, a drug widely used to mediate depression in experimental animal models. Zebrafish received single intraperitoneal (i.p.) injections of 20, 40, and 80 mg/kg body weight reserpine doses and were subjected to open-field test at 2, 24, 48, 72, and 96 h after the treatment. Along with observed changes in behavior and measurement of cortisol levels, the fish were further examined for perturbations in their brain metabolites by ¹H nuclear magnetic resonance (NMR)-based metabolomics. We found a significant increase in freezing duration, whereas total distance travelled was decreased 24 h after single intraperitoneal injection of reserpine. Cortisol level was also found to be higher after 48 h of reserpine treatment. The ¹H NMR data showed that the levels of metabolites such as glutamate, glutamine, histamine, valine, leucine and histidine, lactate, l-fucose, betaine and γ-amino butyric acid (GABA), β-hydroxyisovalerate, and glutathione were significantly decreased in the reserpine-treated group. This study provided some insights into the molecular nature of stress that could contribute toward a better understanding of depression disorder.

Phytochemical profile and biological activities of Sudanese baobab (Adansonia digitata L.) fruit pulp extract

The present work aimed to investigate the phytochemical profile and biological activities of Sudanese baobab (Adansonia digitata L.) fruit pulp extract. Baobab fruit pulp serves as food, and has been used in traditional medicine in Africa for the treatment of several diseases, and believed to possess many biological activities. The sample of baobab fruit was collected from Blue Nile State in Sudan. The fruit pulp was obtained from baobab pods, sieved, extracted with methanol (80%), and analysed for its antioxidant activity, and alpha-glucosidase and nitric oxide (NO) inhibitory activities. The phytochemical constituents of the pulp were determined by LC-MS and 1H-NMR techniques. The results for antioxidant activity evaluated by DPPH and FRAP for methanolic extract were 232.70 mg Ascorbic Acid Equivalent Antioxidant Capacity (AEAC)/g and 222.28 mmol/g of Fe2+, respectively. Baobab pulp extract showed greater capability in inhibiting the generation of NO from the stimulated RAW264.7 cells at 98.45% inhibition and IC50 of 36.55 µg/mL; and α-glucosidase enzyme activity at 97.94% inhibition and IC50 of 58.59 µg/mL. The LC-MS/MS analysis of the baobab extract showed that 52 compounds were found in the baobab pulp, including 19 flavonoids, ten phenolic acids, four lipids (glycero-3-phosphocholine derivative, 1,2-didodecanoyl-sn-glycero-3-phospho-(1'-sn-glycerol), 1-pentadecanoyl-2-(13Z,16Z-docosadienoyl)-glycero-3-phosphate, and glycero-3-hosphocholine derivative), sugars, organic acid, iridoids, adenosine, scopoletin, and taraxerone. The NMR detected 21 metabolites from baobab pulp extract including carbohydrates, organic acids, vitamin, amino acids, phenolic compounds, alkaloids, and fatty acids. The present work is the first of its kind in comprehensively analysing the Sudanese baobab fruit pulp, combined with qualitative characterisation of chemical components using NMR, LC-MS, α-glucosidase, and NO inhibitors. Baobab fruit pulp contains several beneficial phytochemicals and biological activities, and it has potential positive effect on general human’s health.

Metabolite variations and antioxidant activity of Muntingia calabura leaves in response to different drying methods and ethanol ratios elucidated by NMR-based metabolomics

INTRODUCTION

Muntingia calabura from the Muntingiaceae family has been documented for several medicinal uses. The combinations of drying treatment and extracting solvents for a plant species need to be determined and optimised to ensure that the extracts contain adequate amounts of the bioactive metabolites.

OBJECTIVE

Evaluate the metabolite variations and antioxidant activity among M. calabura leaves subjected to different drying methods and extracted with different ethanol ratios using proton nuclear magnetic resonance (¹ H-NMR)-based metabolomics. Methodology The antioxidant activity of M. calabura leaves dried with three different drying methods and extracted with three different ethanol ratios was determined by using 2,2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) scavenging assays. The metabolites variation among the extracts and correlation with antioxidant activity were analysed by ¹ H-NMR-based metabolomics.

RESULTS

Muntingia calabura leaves extracted with 50% and 100% ethanol from air-drying and freeze-drying methods had the highest total phenolic content and the lowest IC₅₀ value for the DPPH scavenging activity. Meanwhile, oven-dried leaves extracted with 100% ethanol had the lowest IC₅₀ value for the NO scavenging activity. A total of 43 metabolites, including sugars, organic acids, amino acids, phytosterols, phenolics and terpene glycoside were tentatively identified. A noticeable discrimination was observed in the different ethanol ratios by the principal component analysis. The partial least-squares analysis suggested that 32 compounds out of 43 compounds identified were the contributors to the bioactivities.

CONCLUSION

The results established set the preliminary steps towards developing this plant into a high value product for phytomedicinal preparations.

Microalgal metabolites as anti-cancer/anti-oxidant agents reduce cytotoxicity of elevated silver nanoparticle levels against non-cancerous vero cells

Heavy metal pollution has become a major concern globally as it contaminates eco-system, water networks and as finely suspended particles in air. In this study, the effects of elevated silver nanoparticle (AgNPs) levels as a model system of heavy metals, in the presence of microalgal crude extracts (MCEs) at different ratios, were evaluated against the non-cancerous Vero cells, and the cancerous MCF-7 and 4T1 cells. The MCEs were developed from water (W) and ethanol (ETH) as green solvents. The AgNPs-MCEs-W at the 4:1 and 5:1 ratios (v/v) after 48 and 72 h treatment, respectively, showed the IC50 values of 83.17-95.49 and 70.79-91.20 μg/ml on Vero cells, 13.18-28.18 and 12.58-25.7 μg/ml on MCF-7; and 16.21-33.88 and 14.79-26.91 μg/ml on 4T1 cells. In comparison, the AgNPs-MCEs-ETH formulation achieved the IC50 values of 56.23-89.12 and 63.09-91.2 μg/ml on Vero cells, 10.47-19.95 and 13.48-26.61 μg/ml on MCF-7; 14.12-50.11 and 15.13-58.88 μg/ml on 4T1 cells, respectively. After 48 and 72 h treatment, the AgNPs-MCE-CHL at the 4:1 and 5:1 ratios exhibited the IC50 of 51.28-75.85 and 48.97-69.18 μg/ml on Vero cells, and higher cytotoxicity at 10.47-16.98 and 6.19-14.45 μg/ml against MCF-7 cells, and 15.84-31.62 and 12.58-24.54 μg/ml on 4T1 cells, respectively. The AgNPs-MCEs-W and ETH resulted in low apoptotic events in the Vero cells after 24 h, but very high early and late apoptotic events in the cancerous cells. The Liquid Chromatography-Mass Spectrometry-Electrospray Ionization (LC-MS-ESI) metabolite profiling of the MCEs exhibited 64 metabolites in negative ion and 56 metabolites in positive ion mode, belonging to different classes. The microalgal metabolites, principally the anti-oxidative components, could have reduced the toxicity of the AgNPs against Vero cells, whilst retaining the cytotoxicity against the cancerous cells.

Mass Spectrometry-Based Metabolomics Combined with Quantitative Analysis of the Microalgal Diatom (Chaetoceros calcitrans)

Although many metabolomics studies of higher land plant species have been conducted, similar studies of lower nonland plant species, which include microalgae, are still developing. The present study represents an attempt to characterize the metabolic profile of a microalgal diatom Chaetoceros calcitrans, by applying high-resolution mass spectrometry detection, via Q-ExactiveTM Plus Orbitrap mass spectrometry. The results showed that 54 metabolites of various classes were tentatively identified. Experimentally, the chloroform and acetone extracts were clearly distinguished from other solvent extracts in chemometric regression analysis using PLS, showing the differences in the C. calcitrans metabolome between the groups. In addition, specific metabolites were evaluated, which supported the finding of antioxidant and anti-inflammatory activities. This study also provides data on the quantitative analysis of four carotenoids based on the identification results. Therefore, these findings could serve as a reliable tool for identifying and quantifying the metabolome that could reflect the metabolic activities of C. calcitrans.

Acetylcholinesterase and α-glucosidase inhibitory compounds from Callicarpa maingayi

Phytochemical investigation on the soluble fractions of n-hexane and dichloromethane of methanolic leaves extract of the Callicarpa maingayi K. & G. led to the isolation of three triterpenoids [euscaphic acid (1), arjunic acid (2), and ursolic acid (3)] together with two flavones [apigenin (4) and acacetin (5)], two phytosterols [stigmasterol 3-O-β-glycopyranoside (6) and sitosterol 3-O-β-glycopyranoside (7)], and a fatty acid [n-hexacosanoic acid (8)]. Six (6) compounds (1, 2, 3, 4, 5, and 8) are reported for the first time from this species. Their structures were elucidated and identified by extensive NMR techniques, GC-MS and comparison with the previously reported literature. Compound 3 was found to displayed good inhibition against acetylcholinesterase with an IC₅₀ value of 21.5 ± 0.022 μM, while 1 and 2 exhibited pronounced α-glucosidase inhibitory activity with IC₅₀ values of 22.4 ± 0.016 μM and 24.9 ± 0.012 μM, respectively.

Rapid assessment of total MCPD esters in palm-based cooking oil using ATR-FTIR application and chemometric analysis

The technique of Fourier transform infrared spectroscopy is widely used to generate spectral data for use in the detection of food contaminants. Monochloropropanediol (MCPD) is a refining process-induced contaminant that is found in palm-based fats and oils. In this study, a chemometric approach was used to evaluate the relationship between the FTIR spectra and the total MCPD content of a palm-based cooking oil. A total of 156 samples were used to develop partial least squares regression (PLSR), artificial neural network (nnet), average artificial neural network (avNNET), random forest (RF) and cubist models. In addition, a consensus approach was used to generate fusion result consisted from all the model mentioned above. All the models were evaluated based on validation performed using training and testing datasets. In addition, the box plot of coefficient of determination (R²), root mean square error (RMSE), slopes and intercepts by 100 times randomization was also compared. Evaluation of performance based on the testing R² and RMSE suggested that the cubist model predicted total MCPD content with the highest accuracy, followed by the RF, avNNET, nnet and PLSR models. The overfitting tendency was assessed based on differences in R² and RMSE in the training and testing calibrations. The observations showed that the cubist and avNNET models possessed a certain degree of overfitting. However, the accuracy of these models in predicting the total MCPD content was high. Results of the consensus model showed that it slightly improved the accuracy of prediction as well as significantly reduced its uncertainty. The important variables derived from the cubist and RF models suggested that the wavenumbers corresponding to the MCPDs originated from the -CH=CH₂ or CH=CH (990-900 cm^-1) and C-Cl stretch (800-700 cm^-1) regions of the FTIR spectrum data. In short, chemometrics in combination with FTIR analysis especially for the consensus model represent a potential and flexible technique for estimating the total MCPD content of refined vegetable oils.

1 H-NMR metabolomics for evaluating the protective effect of Clinacanthus nutans (Burm. f) Lindau water extract against nitric oxide production in LPS-IFN-γ activated RAW 264.7 macrophages

INTRODUCTION

Clinacanthus nutans, a small shrub that is native to Southeast Asia, is commonly used in traditional herbal medicine and as a food source. Its anti-inflammation properties is influenced by the metabolites composition, which can be determined by different binary extraction solvent ratio and extraction methods used during plant post-harvesting stage.

OBJECTIVE

Evaluate the relationship between the chemical composition of C. nutans and its anti-inflammatory properties using nuclear magnetic resonance (NMR) metabolomics approach.

METHODOLOGY

The anti-inflammatory effect of C. nutans air-dried leaves extracted using five different binary extraction solvent ratio and two extraction methods was determined based on their nitric oxide (NO) inhibition effect in lipopolysaccharide-interferon-gamma (LPS-IFN-γ) activated RAW 264.7 macrophages. The relationship between extract bioactivity and metabolite profiles and quantifications were established using ¹ H-NMR metabolomics and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The possible metabolite biosynthesis pathway was constructed to further strengthen the findings.

RESULTS

Water and sonication prepared air-dried leaves possessed the highest NO inhibition activity (IC₅₀  = 190.43 ± 12.26 μg/mL, P < 0.05). A total of 56 metabolites were tentatively identified using ¹ H-NMR metabolomics. A partial least square (PLS) biplot suggested that sulphur containing glucoside, sulphur containing compounds, phytosterols, triterpenoids, flavones and some organic and amino acids were among the potential NO inhibitors. LC-MS/MS targeted quantification further supported sonicated water extract was among the extract that possessed the most abundant C-glycosyl flavones.

CONCLUSION

The present study may serve as a preliminary reference for the selection of optimum extract in further C. nutans in vivo anti-inflammatory study.

Hematological, Biochemical, Histopathological and ¹H-NMR Metabolomics Application in Acute Toxicity Evaluation of Clinacanthus nutans Water Leaf Extract

The present study aims for the first time to provide the in vivo acute toxicological profile of the highest dose of Clinacanthus nutans (Burm. f.) Lindau water leaf extract according to the Organization for economic co-operation and development (OECD) 423 guidelines through conventional toxicity and advanced proton nuclear magnetic resonance (¹H-NMR) serum and urinary metabolomics evaluation methods. A single dose of 5000 mg/kg bw of C. nutans water extract was administered to Sprague Dawley rats, and they were observed for 14 days. Conventional toxicity evaluation methods (physical observation, body and organ weight, food and water consumption, hematology, biochemical testing and histopathological analysis) suggested no abnormal toxicity signs. Serum ¹H-NMR metabolome revealed no significant metabolic difference between untreated and treated groups. Urinary ¹H-NMR analysis, on the other hand, revealed alteration in carbohydrate metabolism, energy metabolism and amino acid metabolism in extract-treated rats after 2 h of extract administration, but the metabolic expression collected after 24 h and at Day 5, Day 10 and Day 15 indicated that the extract-treated rats did not accumulate any toxicity biomarkers. Importantly, the outcomes further suggest that single oral administration of up to 5000 mg/kg bw of C. nutans water leaf extract is safe for consumption.

Classification of Raw Stingless Bee Honeys by Bee Species Origins Using the NMR- and LC-MS-Based Metabolomics Approach

The official standard for quality control of honey is currently based on physicochemical properties. However, this method is time-consuming, cost intensive, and does not lead to information on the originality of honey. This study aims to classify raw stingless bee honeys by bee species origins as a potential classifier using the NMR-LCMS-based metabolomics approach. Raw stingless bee honeys were analysed and classified by bee species origins using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and an ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) in combination with chemometrics tools. The honey samples were able to be classified into three different groups based on the bee species origins of Heterotrigona itama, Geniotrigona thoracica, and Tetrigona apicalis. d-Fructofuranose (H. itama honey), β-d-Glucose, d-Xylose, α-d-Glucose (G. thoracica honey), and l-Lactic acid, Acetic acid, l-Alanine (T. apicalis honey) ident d-Fructofuranose identified via ¹H-NMR data and the diagnostic ions of UHPLC-QTOF MS were characterized as the discriminant metabolites or putative chemical markers. It could be suggested that the quality of honey in terms of originality and purity can be rapidly determined using the classification technique by bee species origins via the ¹H-NMR- and UHPLC-QTOF MS-based metabolomics approach.

Solvent Extraction and Identification of Active Anticariogenic Metabolites in Piper cubeba L. through ¹H-NMR-Based Metabolomics Approach

The aim of this study was to determine the effects of different solvents for extraction, liquid⁻liquid partition, and concentrations of extracts and fractions of Piper cubeba L. on anticariogenic; antibacterial and anti-inflammatory activity against oral bacteria. Furthermore, ¹H-Nuclear Magnetic Resonance (NMR) coupled with multivariate data analysis (MVDA) was applied to discriminate between the extracts and fractions and examine the metabolites that correlate to the bioactivities. All tested bacteria were susceptible to Piper cubeba L. extracts and fractions. Different solvents extraction, liquid⁻liquid partition and concentrations of extracts and fractions have partially influenced the antibacterial activity. MTT assay showed that P. cubeba L. extracts and fractions were not toxic to RAW 264.7 cells at selected concentrations. Anti-inflammatory activity evaluated by nitric oxide (NO) production in lipopolysaccharide (LPS) stimulated cells showed a reduction in NO production in cells treated with P. cubeba L. extracts and fractions, compared to those without treatment. Twelve putative metabolites have been identified, which are (1) cubebin, (2) yatein, (3) hinokinin, (4) dihydrocubebin, (5) dihydroclusin, (6) cubebinin, (7) magnosalin, (8) p-cymene, (9) piperidine, (10) cubebol, (11) d-germacrene and (12) ledol. Different extraction and liquid⁻liquid partition solvents caused separation in principal component analysis (PCA) models. The partial least squares (PLS) models showed that higher anticariogenic activity was related more to the polar solvents, despite some of the active metabolites also present in the non-polar solvents. Hence, P. cubeba L. extracts and fractions exhibited antibacterial and anti-inflammatory activity and have potential to be developed as the anticariogenic agent.

Metabolite Profiling of the Microalgal Diatom Chaetoceros Calcitrans and Correlation with Antioxidant and Nitric Oxide Inhibitory Activities via ¹H NMR-Based Metabolomics

Microalgae are promising candidate resources from marine ecology for health-improving effects. Metabolite profiling of the microalgal diatom, Chaetoceros calcitrans was conducted by using robust metabolomics tools, namely ¹H nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate data analysis (MVDA). The unsupervised data analysis, using principal component analysis (PCA), resolved the five types of extracts made by solvents ranging from polar to non-polar into five different clusters. Collectively, with various extraction solvents, 11 amino acids, cholesterol, 6 fatty acids, 2 sugars, 1 osmolyte, 6 carotenoids and 2 chlorophyll pigments were identified. The fatty acids and both carotenoid pigments as well as chlorophyll, were observed in the extracts made from medium polar (acetone, chloroform) and non-polar (hexane) solvents. It is suggested that the compounds were the characteristic markers that influenced the separation between the clusters. Based on partial least square (PLS) analysis, fucoxanthin, astaxanthin, violaxanthin, zeaxanthin, canthaxanthin, and lutein displayed strong correlation to 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging and nitric oxide (NO) inhibitory activity. This metabolomics study showed that solvent extractions are one of the main bottlenecks for the maximum recovery of bioactive microalgal compounds and could be a better source of natural antioxidants due to a high value of metabolites.

Metabolite characterization of different palm date varieties and the correlation with their NO inhibitory activity, texture and sweetness

The aim of this study was to examine the variation in metabolite constituents of five commercial varieties of date fruits; Ajwa, Safawi and Ambar which originated from Madinah, the Iranian Bam and Tunisian Deglet Noor. The differences of metabolome were investigated using proton nuclear magnetic resonance (1H NMR) spectroscopy combined with multivariate data analysis (MVDA). Principal Component Analysis (PCA) revealed clear separation between the date varieties. The Tunisian Deglet Noor demonstrated distinct cluster from the rest of the palm date samples based on the metabolite composition as shown by the pattern observed in Hierarchical Clustering Analysis (HCA) and PCA. Deglet Noor exhibited a significant higher level of sucrose (δ 5.40) and fructose (δ 4.16) in comparison with the other four varieties which can be associated with the distinctive sweet taste of this variety. Dates originated from Madinah and Tunisia exhibited a contrast manner in the amount of xylose and moisture content. These two aspects may contribute towards the soft texture of Tunisian dates. All Madinah dates were found to contain phenolic compounds which were well established as great antioxidant and anti-inflammatory agent. Ajwa dates exerted greater effect in inhibiting the generation of nitric oxide (NO) from the stimulated RAW264.7 cells at 95.37% inhibition. Succinic acid was suggested to have the most significant correlation with the trend of NO inhibitory shown by the selected date palm varieties.

1H NMR and antioxidant profiles of polar and non-polar extracts of persimmon (Diospyros kaki L.) - Metabolomics study based on cultivars and origins

Persimmon (Diospyros kaki L.) is one of the most important fruits that has been consumed for its medicinal properties due to the presence of some active metabolites, particularly polyphenols and carotenoids. Previously described methods, including HPLC, were limited in the determination of metabolites in different persimmon varieties. The present study shows the evaluation and the differences among persimmon polar and non-polar extracts by ¹H NMR-based metabolomics approach. The hierarchical clustering analysis (HCA) based on score values of principal component analysis (PCA) model was used to analyze the important compounds in investigated fruits. The ¹H NMR spectrum of persimmon chloroform (CDCl₃) extracts showed different types of compounds as compared to polar methanol-water (CD₃OD-D₂O) ones. Persimmons growing in Israel were clustered different from those growing in Korea with the abundance of phenolic compounds (gallic, caffeic and protocathecuic acids), carotenoids (β-cryptoxanthin, lutein, and zeaxanthin), amino acids (alanine), maltose, uridine, and fatty acids (myristic and palmitoleic acids). Glucose, choline and formic acid were more prominent in persimmon growing in Korea. In CD₃OD-D₂O and CDCl₃ persimmon extracts, 43 metabolites were identified. The metabolic differences were shown as well on the results of bioactivities and antioxidant capacities determined by ABTS, FRAP, CUPRAC and DPPH assays. The presented methods can be widely used for quantitation of multiple compounds in many plant and biological samples especially in vegetables and fruits.

Comparison of partial least squares and random forests for evaluating relationship between phenolics and bioactivities of Neptunia oleracea

BACKGROUND

Neptunia oleracea is a plant consumed as a vegetable and which has been used as a folk remedy for several diseases. Herein, two regression models (partial least squares, PLS; and random forest, RF) in a metabolomics approach were compared and applied to the evaluation of the relationship between phenolics and bioactivities of N. oleracea. In addition, the effects of different extraction conditions on the phenolic constituents were assessed by pattern recognition analysis.

RESULTS

Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.

CONCLUSION

Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.

Metabolite profiling, antioxidant, and α-glucosidase inhibitory activities of germinated rice: nuclear-magnetic-resonance-based metabolomics study

In an attempt to profile the metabolites of three different varieties of germinated rice, specifically black (GBR), red, and white rice, a ¹H-nuclear-magnetic-resonance-based metabolomics approach was conducted. Multivariate data analysis was applied to discriminate between the three different varieties using a partial least squares discriminant analysis (PLS-DA) model. The PLS model was used to evaluate the relationship between chemicals and biological activities of germinated rice. The PLS-DA score plot exhibited a noticeable separation between the three rice varieties into three clusters by PC1 and PC2. The PLS model indicated that α-linolenic acid, γ-oryzanol, α-tocopherol, γ-aminobutyric acid, 3-hydroxybutyric acid, fumaric acid, fatty acids, threonine, tryptophan, and vanillic acid were significantly correlated with the higher bioactivities demonstrated by GBR that was extracted in 100% ethanol. Subsequently, the proposed biosynthetic pathway analysis revealed that the increased quantities of secondary metabolites found in GBR may contribute to its nutritional value and health benefits.

Characterization of Metabolite Profile in Phyllanthus niruri and Correlation with Bioactivity Elucidated by Nuclear Magnetic Resonance Based Metabolomics

Phyllanthus niruri is an important medicinal plant. To standardize the extract and guarantee its maximum benefit, processing methods optimization ought to be amenable and beneficial. Herein, three dried P. niruri samples, air (AD), freeze (FD) and oven (OD), extracted with various ethanol to water ratios (0%, 50%, 70%, 80% and 100%) were evaluated for their metabolite changes using proton nuclear magnetic resonance (¹H-NMR)-based metabolomics approach. The amino acids analysis showed that FD P. niruri exhibited higher content of most amino acids compared to the other dried samples. Based on principal component analysis (PCA), the FD P. niruri extracted with 80% ethanol contained higher amounts of hypophyllanthin and phenolic compounds based on the loading plot. The partial least-square (PLS) results showed that the phytochemicals, including hypophyllanthin, catechin, epicatechin, rutin, quercetin and chlorogenic, caffeic, malic and gallic acids were correlated with antioxidant and α-glucosidase inhibitory activities, which were higher in the FD material extracted with 80% ethanol. This report optimized the effect of drying and ethanol ratios and these findings demonstrate that NMR-based metabolomics was an applicable approach. The FD P. niruri extracted with 80% ethanol can be used as afunctional food ingredient for nutraceutical or in medicinal preparation.

DISCRIMINATION OF DENGUE DISEASE FROM HEALTHY BASED ON THE CHEMOMETRY OF 1H NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY

Dengue is the most important human viral disease transmitted by arthropod vectors and over half of the world's populations live in areas at risk of infection. The severity of the infection depends on the form of the disease, which can be symptomatic or asymptomatic. Currently there is neither specific treatment nor vaccine to tackle this emerging disease. Metabolomics applied in this study, aimed to provide a global snapshot of all small-molecule metabolites in urine as biological sample of choice to more focused studies of metabolism to distinguish between healthy and dengue infected subjects. Fifty-two patients diagnosed with dengue fever at Penang General Hospital and fourty-three healthy individuals were recruited in this study. 1H-nuclear magnetic resonance (NMR) spectroscopy combined with multivariate analysis (MVA) methods such as principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and orthogonal PLS-DA (OPLS-DA) were employed for statistical data exploration. The model score plot results showed that all three MVAs showed very good spatial distributions with clear clusters/grouping between healthy individuals and dengue infected individuals. Also, statistically, the PLS-DA and OPLS-DA models had high reproducibility and predictivity values, > 0.5. In conclusion, this study established the potential of using a combination of 1H NMR spectroscopy and multivariate data analyses in differentiating healthy and non-healthy individuals, based on obtained score plots reflecting the metabolites pertubation, where spectral features contributing most to variation or separation are identified for further analysis.