Displaying publications 1 - 20 of 171 in total

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  1. van Roekel EH, Trijsburg L, Assi N, Carayol M, Achaintre D, Murphy N, et al.
    Nutrients, 2018 May 22;10(5).
    PMID: 29789452 DOI: 10.3390/nu10050654
    Identifying the metabolites associated with alcohol consumption may provide insights into the metabolic pathways through which alcohol may affect human health. We studied associations of alcohol consumption with circulating concentrations of 123 metabolites among 2974 healthy participants from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Alcohol consumption at recruitment was self-reported through dietary questionnaires. Metabolite concentrations were measured by tandem mass spectrometry (BIOCRATES AbsoluteIDQTM p180 kit). Data were randomly divided into discovery (2/3) and replication (1/3) sets. Multivariable linear regression models were used to evaluate confounder-adjusted associations of alcohol consumption with metabolite concentrations. Metabolites significantly related to alcohol intake in the discovery set (FDR q-value < 0.05) were further tested in the replication set (Bonferroni-corrected p-value < 0.05). Of the 72 metabolites significantly related to alcohol intake in the discovery set, 34 were also significant in the replication analysis, including three acylcarnitines, the amino acid citrulline, four lysophosphatidylcholines, 13 diacylphosphatidylcholines, seven acyl-alkylphosphatidylcholines, and six sphingomyelins. Our results confirmed earlier findings that alcohol consumption was associated with several lipid metabolites, and possibly also with specific acylcarnitines and amino acids. This provides further leads for future research studies aiming at elucidating the mechanisms underlying the effects of alcohol in relation to morbid conditions.
    Matched MeSH terms: Metabolomics/methods
  2. Zuther E, Lee YP, Erban A, Kopka J, Hincha DK
    Adv Exp Med Biol, 2018 10 6;1081:81-98.
    PMID: 30288705 DOI: 10.1007/978-981-13-1244-1_5
    During low-temperature exposure, temperate plant species increase their freezing tolerance in a process termed cold acclimation. The molecular mechanisms involved in cold acclimation have been mostly investigated in Arabidopsis thaliana. In addition, other Brassicaceae species related to A. thaliana have been employed in recent years to study plant stress responses on a phylogenetically broader basis and in some cases with extremophile species with a much higher stress tolerance. In this paper, we briefly summarize cold acclimation responses in A. thaliana and current knowledge about cold acclimation in A. thaliana relatives with special emphasis on Eutrema salsugineum and two closely related Thellungiella species. We then present a transcriptomic and metabolomic analysis of cold acclimation in five A. thaliana and two E. salsugineum accessions that differ widely in their freezing tolerance. Differences in the cold responses of the two species are discussed.
    Matched MeSH terms: Metabolomics
  3. Zolkeflee NKZ, Isamail NA, Maulidiani M, Abdul Hamid NA, Ramli NS, Azlan A, et al.
    Phytochem Anal, 2021 Jan;32(1):69-83.
    PMID: 31953888 DOI: 10.1002/pca.2917
    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.

    Matched MeSH terms: Metabolomics
  4. Zolkeflee NKZ, Wong PL, Maulidiani M, Ramli NS, Azlan A, Abas F
    Planta Med, 2023 Aug;89(9):916-934.
    PMID: 36914160 DOI: 10.1055/a-2053-0950
    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.
    Matched MeSH terms: Metabolomics
  5. Zolkeflee NKZ, Wong PL, Maulidiani M, Ramli NS, Azlan A, Mediani A, et al.
    Biochem Biophys Res Commun, 2024 May 14;708:149778.
    PMID: 38507867 DOI: 10.1016/j.bbrc.2024.149778
    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.
    Matched MeSH terms: Metabolomics/methods
  6. Zailani NNB, Ho PC
    Eur J Drug Metab Pharmacokinet, 2023 Sep;48(5):467-494.
    PMID: 37495930 DOI: 10.1007/s13318-023-00846-4
    This review provides an overview on the current applications of dried blood spots (DBS) as matrices for therapeutic drug (TDM) and drug or disease response monitoring (DRM). Compared with conventional methods using plasma/serum, DBS offers several advantages, including minimally invasiveness, a small blood volume requirement, reduced biohazardous risk, and improved sample stability. Numerous assays utilising DBS for TDM have been reported in the literature over the past decade, covering a wide range of therapeutic drugs. Several factors can affect the accuracy and reliability of the DBS sampling method, including haematocrit (HCT), blood volume, sampling paper and chromatographic effects. It is crucial to evaluate the correlation between DBS concentrations and conventional plasma/serum concentrations, as the latter has traditionally been used for clinical decision. The feasibility of using DBS sampling method as an option for home-based TDM is also discussed. Furthermore, DBS has also been used as a matrix for monitoring the drug or disease responses (DRM) through various approaches such as genotyping, viral load measurement, assessment of inflammatory factors, and more recently, metabolic profiling. Although this research is still in the development stage, advancements in technology are expected to lead to the identification of surrogate biomarkers for drug treatment in DBS and a better understanding of the correlation between DBS drug levels and drug responses. This will make DBS a valuable matrix for TDM and DRM, facilitating the achievement of pharmacokinetic and pharmacodynamic correlations and enabling personalised therapy.
    Matched MeSH terms: Metabolomics
  7. Yusof HM, Ab-Rahim S, Suddin LS, Saman MSA, Mazlan M
    Malays J Med Sci, 2018 Sep;25(5):16-34.
    PMID: 30914860 MyJurnal DOI: 10.21315/mjms2018.25.5.3
    Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Early diagnosis and accurate staging of the disease is vital to improve the prognosis. Metabolomics has been used to identify changes in metabolite profiles in the different stages of cancer in order to introduce new non-invasive molecular tools for staging. In this systematic review, we aim to identify the common metabolite changes in human biological samples and the dominant metabolic pathways associated with CRC progression. A broad systematic search was carried out from selected databases. Four reviewers screened and reviewed the titles, abstracts, and full-text articles according to the inclusion and exclusion criteria. Quality assessment was conducted on the eight articles which met the criteria. Data showed that the metabolites involved with redox status, energy metabolism and intermediates of amino acids, choline and nucleotides metabolism were the most affected during CRC progression. However, there were differences in the levels of individual metabolites detected between the studies, and this might be due to the study population, sample preparation, analytical platforms used and statistical tools. In conclusion, this systematic review highlights the changes in metabolites from early to late stages of CRC. Moreover, biomarkers for prognosis are important to reduce CRC-related mortality.
    Matched MeSH terms: Metabolomics
  8. Yong WK, Sim KS, Poong SW, Wei D, Phang SM, Lim PE
    3 Biotech, 2019 Aug;9(8):315.
    PMID: 31406637 DOI: 10.1007/s13205-019-1848-8
    An ecologically important tropical freshwater microalga, Scenedesmus quadricauda, was exposed to Ni toxicity under two temperature regimes, 25 and 35 °C to investigate the interactive effects of warming and different Ni concentrations (0.1, 1.0 and 10.0 ppm). The stress responses were assessed from the growth, photosynthesis, reactive oxygen species (ROS) generation and metabolomics aspects to understand the effects at both the physiological and biochemical levels. The results showed that the cell densities of the cultures were higher at 35 °C compared to 25 °C, but decreased with increasing Ni concentrations at 35 °C. In terms of photosynthetic efficiency, the maximum quantum yield of photosystem II (Fv/Fm) of S. quadricauda remained consistent across different conditions. Nickel concentration at 10.0 ppm affected the maximum rate of relative electron transport (rETRm) and saturation irradiance for electron transport (Ek) in photosynthesis. At 25 °C, the increase of non-photochemical quenching (NPQ) values in cells exposed to 10.0 ppm Ni might indicate the onset of thermal dissipation process as a self-protection mechanism against Ni toxicity. The combination of warming and Ni toxicity induced a strong oxidative stress response in the cells. The ROS level increased significantly by 40% after exposure to 10.0 ppm of Ni at 35 °C. The amount of Ni accumulated in the biomass was higher at 25 °C compared to 35 °C. Based on the metabolic profile, temperature contributed the most significant differentiation among the samples compared to Ni treatment and the interaction between the two factors. Amino acids, sugars and organic acids were significantly regulated by the combined factors to restore homeostasis. The most affected pathways include sulphur, amino acids, and nitrogen metabolisms. Overall, the results suggest that the inhibitory effect of Ni was lower at 35 °C compared to 25 °C probably due to lower metal uptake and primary metabolism restructuring. The ability of S. quadricauda to accumulate substantial amount of Ni and thrive at 35 °C suggests the potential use of this strain for phycoremediation and outdoor wastewater treatment.
    Matched MeSH terms: Metabolomics
  9. Yap, Ivan K.S.
    MyJurnal
    Metabonomics can be used to quantitatively measure dynamic biochemical responses of living organisms to physiological or pathological stimuli. A range of analytical tools such as high-resolution nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) combined with multivariate statistical analysis can be employed to create comprehensive metabolic signatures of biological samples including urine, plasma, faecal water and tissue extracts. These metabolic signatures can reflect the physiological or pathological condition of the organism and indicate imbalances in the homeostatic regulation of tissues and extracellular fluids. This technology has been employed in a diverse range of application areas including investigation of disease mechanisms, diagnosis/prognosis of pathologies, nutritional interventions and drug toxicity. Metabolic profiling is becoming increasingly important in identifying biomarkers of disease progression and drug intervention, and can provide additional information to support or aid the interpretation of genomic and proteomic data. With the new generation of postgenomic technologies, the paradigm in many biological fields has shifted to either top down systems biology approaches, aiming to achieve a general understanding of the global and integrated response of an organism or to bottom up modelling of specific pathways and networks using a priori knowledge based on mining large bodies of literature. Whilst metabolic profiling lends itself to either approach, using it in an exploratory and hypothesis generating capacity clearly allows new mechanisms to be uncovered.
    Matched MeSH terms: Metabolomics
  10. Yap TW, Leow AH, Azmi AN, Callahan DL, Perez-Perez GI, Loke MF, et al.
    Front Microbiol, 2017;8:536.
    PMID: 28424674 DOI: 10.3389/fmicb.2017.00536
    Background:Helicobacter pylori colonizes the gastric mucosa of more than half of the world's population. There is increasing evidence H. pylori protects against the development of obesity and childhood asthma/allergies in which the development of these diseases coincide with transient dysbiosis. However, the mechanism underlying the association of H. pylori eradication with human metabolic and immunological disorders is not well-established. In this study, we aimed to investigate the local and systemic effects of H. pylori eradication through untargeted fecal lipidomics and plasma metabolomics approaches by liquid chromatography mass spectrometry (LC-MS). Results: Our study revealed that eradication of H. pylori eradication (i.e., loss of H. pylori and/or H. pylori eradication therapy) changed many global metabolite/lipid features, with the majority being down-regulated. Our findings primarily show that H. pylori eradication affects the host energy and lipid metabolism which may eventually lead to the development of metabolic disorders. Conclusion: These predictive metabolic signatures of metabolic and immunological disorders following H. pylori eradication can provide insights into dynamic local and systemic metabolism related to H. pylori eradication in modulating human health.
    Matched MeSH terms: Metabolomics
  11. Yap IK, Kho MT, Lim SH, Ismail NH, Yam WK, Chong CW
    Mol Biosyst, 2015 Jan;11(1):297-306.
    PMID: 25382376 DOI: 10.1039/c4mb00463a
    Understanding the basal gut bacterial community structure and the host metabolic composition is pivotal for the interpretation of laboratory treatments designed to answer questions pertinent to host-microbe interactions. In this study, we report for the first time the underlying gut microbiota and systemic metabolic composition in BALB/c mice during the acclimatisation period. Our results showed that stress levels were reduced in the first three days of the study when the animals were subjected to repetitive handling daily but the stress levels were increased when handling was carried out at lower frequencies (weekly). We also observed a strong influence of stress on the host metabolism and commensal compositional variability. In addition, temporal biological compartmental variations in the responses were observed. Based on these results, we suggest that consistency in the frequency and duration of laboratory handling is crucial in murine models to minimise the impact of stress levels on the commensal and host metabolism dynamics. Furthermore, caution is advised in consideration of the temporal delay effect when integrating metagenomics and metabonomics data across different biological matrices (i.e. faeces and urine).
    Matched MeSH terms: Metabolomics/methods
  12. Yan D, Wong YF, Whittock SP, Koutoulis A, Shellie RA, Marriott PJ
    Anal Chem, 2018 04 17;90(8):5264-5271.
    PMID: 29575899 DOI: 10.1021/acs.analchem.8b00142
    A novel sequential three-dimensional gas chromatography-high-resolution time-of-flight mass spectrometry (3D GC-accTOFMS) approach for profiling secondary metabolites in complex plant extracts is described. This integrated system incorporates a nonpolar first-dimension (1Dnp) separation step, prior to a microfluidic heart-cut (H/C) of a targeted region(s) to a cryogenic trapping device, directly followed by the rapid reinjection of a trapped solute into a polar second-dimension (2DPEG) column for multidimensional separation (GCnp-GCPEG). For additional separation, the effluent from 2DPEG can then be modulated according to a comprehensive 2D GC process (GC×GC), using an ionic liquid phase as a third-dimension (3DIL) column, to produce a sequential GCnp-GCPEG×GCIL separation. Thus, the unresolved or poorly resolved components, or regions that require further separation, can be precisely selected and rapidly transferred for additional separation on 2D or 3D columns, based on the greater separation realized by these steps. The described integrated system can be used in a number of modes, but one useful approach is to target specific classes of compounds for improved resolution. This is demonstrated through the separation and detection of the oxygenated sesquiterpenes in hop ( Humulus lupulus L.) essential oil and agarwood ( Aquilaria malaccensis) oleoresin. Improved resolution and peak capacity were illustrated through the progressive comparison of the tentatively identified components for GCnp-GCPEG and GCnp-GCPEG×GCIL methods. Relative standard deviations of intraday retentions (1 tR, 2 tR,, and 3 tR) and peak areas of ≤0.01, 0.07, 0.71, and 7.5% were achieved. This analytical approach comprising three GC column selectivities, hyphenated with high-resolution TOFMS detection, should be a valuable adjunct for the improved characterization of complex plant samples, particularly in the area of plant metabolomics.
    Matched MeSH terms: Metabolomics
  13. Xu J, Jiang H, Li J, Cheng KK, Dong J, Chen Z
    PLoS One, 2015;10(4):e0119654.
    PMID: 25849323 DOI: 10.1371/journal.pone.0119654
    Wilson's disease (WD), also known as hepatoleticular degeneration (HLD), is a rare autosomal recessive genetic disorder of copper metabolism, which causes copper to accumulate in body tissues. In this study, rats fed with copper-laden diet are used to render the clinical manifestations of WD, and their copper toxicity-induced organ lesions are studied. To investigate metabolic behaviors of 'decoppering' process, penicillamine (PA) was used for treating copper-laden rats as this chelating agent could eliminate excess copper through the urine. To date, there has been limited metabolomics study on WD, while metabolic impacts of copper accumulation and PA administration have yet to be established.
    Matched MeSH terms: Metabolomics/methods*
  14. Xu J, Wang Y, Xu X, Cheng KK, Raftery D, Dong J
    Molecules, 2021 Sep 24;26(19).
    PMID: 34641330 DOI: 10.3390/molecules26195787
    In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors. Although a number of methodologies have been applied to handle NAs, NA imputation remains a challenging problem. Here, we propose a non-negative matrix factorization (NMF)-based method for NA imputation in MS-based metabolomics data, which makes use of both global and local information of the data. The proposed method was compared with three commonly used methods: k-nearest neighbors (kNN), random forest (RF), and outlier-robust (ORI) missing values imputation. These methods were evaluated from the perspectives of accuracy of imputation, retrieval of data structures, and rank of imputation superiority. The experimental results showed that the NMF-based method is well-adapted to various cases of data missingness and the presence of outliers in MS-based metabolic profiles. It outperformed kNN and ORI and showed results comparable with the RF method. Furthermore, the NMF method is more robust and less susceptible to outliers as compared with the RF method. The proposed NMF-based scheme may serve as an alternative NA imputation method which may facilitate biological interpretations of metabolomics data.
    Matched MeSH terms: Metabolomics/methods*
  15. Xu J, Cheng KK, Yang Z, Wang C, Shen G, Wang Y, et al.
    PMID: 26170882 DOI: 10.1155/2015/801691
    Gastric mucosal lesion (GML) is a common gastrointestinal disorder with multiple pathogenic mechanisms in clinical practice. In traditional Chinese medicine (TCM), electroacupuncture (EA) treatment has been proven as an effective therapy for GML, although the underlying healing mechanism is not yet clear. Here, we used proton nuclear magnetic resonance- ((1)H NMR-) based metabolomic method to investigate the metabolic perturbation induced by GML and the therapeutic effect of EA treatment on stomach meridian (SM) acupoints. Clear metabolic differences were observed between GML and control groups, and related metabolic pathways were discussed by means of online metabolic network analysis toolbox. By comparing the endogenous metabolites from GML and GML-SM groups, the disturbed pathways were partly recovered towards healthy state via EA treated on SM acupoints. Further comparison of the metabolic variations induced by EA stimulated on SM and the control gallbladder meridian (GM) acupoints showed a quite similar metabolite composition except for increased phenylacetylglycine, 3,4-dihydroxymandelate, and meta-hydroxyphenylacetate and decreased N-methylnicotinamide in urine from rats with EA treated on SM acupoints. The current study showed the potential application of metabolomics in providing further insight into the molecular mechanism of acupuncture.
    Matched MeSH terms: Metabolomics
  16. Wong PL, Ramli NS, Tan CP, Azlan A, Abas F
    Phytochem Anal, 2021 Sep;32(5):685-697.
    PMID: 33295100 DOI: 10.1002/pca.3015
    INTRODUCTION: Ardisia elliptica Thunb. (Primulaceae) is a medicinal herb that is traditionally used for the treatment of fever, diarrhoea, measles and herpes. However, there is limited information regarding the correlation of its phytoconstituents with the bioactivity. Optimisation of solvent extraction is vital for maximising retention of bioactive molecules.

    OBJECTIVE: This study investigated the metabolite variations in A. elliptica leaves and the correlation with antioxidant activities.

    METHODOLOGY: Total phenolic content (TPC), 2,2-diphenyl-1-picrylhydrazyl (DPPH) and nitric oxide (NO) radicals scavenging assays were performed on A. elliptica leaves extracted with four different ethanol ratios (0%, 50%, 70% and absolute ethanol). The correlation of metabolites with antioxidant activities was evaluated using a nuclear magnetic resonance (NMR)-based metabolomics approach.

    RESULTS: The results showed that the 50% and 70% ethanolic extracts retained the highest TPC, and the 70% ethanolic extract was the most active, exhibiting half maximal inhibitory concentration (IC50 ) values of 10.18 ± 0.83 and 43.05 ± 1.69 μg/mL, respectively, in both radical scavenging assays. A total of 46 metabolites were tentatively identified, including flavonoids, benzoquinones, triterpenes and phenolic derivatives. The 50% and 70% ethanolic extracts showed similarities in metabolites content and were well discriminated from water and absolute ethanol extracts in a principal component analysis (PCA) model. Moreover, 31 metabolites were found to contribute significantly to the differentiation and antioxidant activity.

    CONCLUSION: This study provides information on bioactive compounds in A. elliptica leaves, which is promising as a functional ingredient for food production or for the development of phytomedicinal products.

    Matched MeSH terms: Metabolomics
  17. Wong PL, Zolkeflee NKZ, Ramli NS, Tan CP, Azlan A, Tham CL, et al.
    J Ethnopharmacol, 2024 Jan 10;318(Pt B):117015.
    PMID: 37572932 DOI: 10.1016/j.jep.2023.117015
    ETHNOPHARMACOLOGICAL RELEVANCE: Ardisia elliptica Thunb. (AE) (Primulaceae) is a medicinal plant found in the Malay Peninsula and has been traditionally used to treat diabetes. However, limited studies to date in providing scientific evidence to support the antidiabetic efficacy of this plant by in-vitro and in-vivo models.

    AIM OF THE STUDY: To investigate the anti-hyperglycemic potential of AE through in-vitro enzymatic activities and streptozotocin-nicotinamide (STZ-NA) induced diabetic rat models using proton-nuclear magnetic resonance (1H-NMR)-based metabolomics approach.

    MATERIALS AND METHODS: Anti-α-amylase and anti-α-glucosidase activities of the hydroethanolic extracts of AE were evaluated. The absolute quantification of bioactive constituents, using ultra-high performance liquid chromatography (UHPLC) was performed for the most active extract. Three different dosage levels of the AE extract were orally administered for 4 weeks consecutively in STZ-NA induced diabetic rats. Physical assessments, biochemical analysis, and an untargeted 1H-NMR-based metabolomics analysis of the urine and serum were carried out on the animal model.

    RESULTS: Type 2 diabetes mellitus (T2DM) rat model was successfully developed based on the clear separation observed between the STZ-NA induced diabetic and normal non-diabetic groups. Discriminating biomarkers included glucose, citrate, succinate, allantoin, hippurate, 2-oxoglutarate, and 3-hydroxybutyrate, as determined through an orthogonal partial least squares-discriminant analysis (OPLS-DA) model. A treatment dosage of 250 mg/kg body weight (BW) of standardized 70% ethanolic AE extract mitigated increase in serum glucose, creatinine, and urea levels, providing treatment levels comparable to that obtained using metformin, with flavonoids primarily contribute to the anti-hyperglycemic activities. Urinary metabolomics disclosed that the following disturbed metabolism pathways: the citrate cycle (TCA cycle), butanoate metabolism, glycolysis and gluconeogenesis, pyruvate metabolism, and synthesis and degradation of ketone bodies, were ameliorated after treatment with the standardized AE extract.

    CONCLUSIONS: This study demonstrated the first attempt at revealing the therapeutic effect of oral treatment with 250 mg/kg BW of standardized AE extract on chemically induced T2DM rats. The present study provides scientific evidence supporting the ethnomedicinal use of Ardisia elliptica and further advances the understanding of the fundamental molecular mechanisms affected by this herbal antidote.

    Matched MeSH terms: Metabolomics/methods
  18. Wong EHJ, Ng CG, Goh KL, Vadivelu J, Ho B, Loke MF
    Sci Rep, 2018 01 23;8(1):1409.
    PMID: 29362474 DOI: 10.1038/s41598-018-19697-0
    The biofilm-forming-capability of Helicobacter pylori has been suggested to be among factors influencing treatment outcome. However, H. pylori exhibit strain-to-strain differences in biofilm-forming-capability. Metabolomics enables the inference of spatial and temporal changes of metabolic activities during biofilm formation. Our study seeks to examine the differences in metabolome of low and high biofilm-formers using the metabolomic approach. Eight H. pylori clinical strains with different biofilm-forming-capability were chosen for metabolomic analysis. Bacterial metabolites were extracted using Bligh and Dyer method and analyzed by Liquid Chromatography/Quadrupole Time-of-Flight mass spectrometry. The data was processed and analyzed using the MassHunter Qualitative Analysis and the Mass Profiler Professional programs. Based on global metabolomic profiles, low and high biofilm-formers presented as two distinctly different groups. Interestingly, low-biofilm-formers produced more metabolites than high-biofilm-formers. Further analysis was performed to identify metabolites that differed significantly (p-value 
    Matched MeSH terms: Metabolomics/methods*
  19. Wong C, Ling YS, Wee JLS, Mujahid A, Müller M
    Sci Rep, 2020 12 14;10(1):21861.
    PMID: 33318532 DOI: 10.1038/s41598-020-78873-3
    Nepenthes, as the largest family of carnivorous plants, is found with an extensive geographical distribution throughout the Malay Archipelago, specifically in Borneo, Philippines, and Sumatra. Highland species are able to tolerate cold stress and lowland species heat stress. Our current understanding on the adaptation or survival mechanisms acquired by the different Nepenthes species to their climatic conditions at the phytochemical level is, however, limited. In this study, we applied an eco-metabolomics approach to identify temperature stressed individual metabolic fingerprints of four Nepenthes species: the lowlanders N. ampullaria, N. rafflesiana and N. northiana, and the highlander N. minima. We hypothesized that distinct metabolite regulation patterns exist between the Nepenthes species due to their adaptation towards different geographical and altitudinal distribution. Our results revealed not only distinct temperature stress induced metabolite fingerprints for each Nepenthes species, but also shared metabolic response and adaptation strategies. The interspecific responses and adaptation of N. rafflesiana and N. northiana likely reflected their natural habitat niches. Moreover, our study also indicates the potential of lowlanders, especially N. ampullaria and N. rafflesiana, to produce metabolites needed to deal with increased temperatures, offering hope for the plant genus and future adaption in times of changing climate.
    Matched MeSH terms: Metabolomics*
  20. Windarsih A, Riswanto FDO, Bakar NKA, Yuliana ND, Dachriyanus, Rohman A
    Molecules, 2022 Nov 29;27(23).
    PMID: 36500423 DOI: 10.3390/molecules27238325
    Adulteration of high-quality meat products using lower-priced meats, such as pork, is a crucial issue that could harm consumers. The consumption of pork is strictly forbidden in certain religions, such as Islam and Judaism. Therefore, the objective of this research was to develop untargeted metabolomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with chemometrics for analysis of pork in beef meatballs for halal authentication. We investigated the use of non-targeted LC-HRMS as a method to detect such food adulteration. As a proof of concept using six technical replicates of pooled samples from beef and pork meat, we could show that metabolomics using LC-HRMS could be used for high-throughput screening of metabolites in meatballs made from beef and pork. Chemometrics of principal component analysis (PCA) was successfully used to differentiate beef meatballs and pork meatball samples. Partial least square-discriminant analysis (PLS-DA) clearly discriminated between halal and non-halal beef meatball samples with 100% accuracy. Orthogonal projection to latent structures-discriminant analysis (OPLS-DA) perfectly discriminated and classified meatballs made from beef, pork, and a mixture of beef-pork with a good level of fitness (R2X = 0.88, R2Y = 0.71) and good predictivity (Q2 = 0.55). Partial least square (PLS) and orthogonal PLS (OPLS) were successfully applied to predict the concentration of pork present in beef meatballs with high accuracy (R2 = 0.99) and high precision. Thirty-five potential metabolite markers were identified through VIP (variable important for projections) analysis. Metabolites of 1-(1Z-hexadecenyl)-sn-glycero-3-phosphocholine, acetyl-l-carnitine, dl-carnitine, anserine, hypoxanthine, linoleic acid, and prolylleucine had important roles for predicting pork in beef meatballs through S-line plot analysis. It can be concluded that a combination of untargeted metabolomics using LC-HRMS and chemometrics is promising to be developed as a standard analytical method for halal authentication of highly processed meat products.
    Matched MeSH terms: Metabolomics
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