Displaying publications 1 - 20 of 59 in total

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  1. Windows Scanning Multiomics: Integrated Metabolomics and Proteomics
    Shi J, Zhao J, Zhang Y, Wang Y, Tan CP, Xu YJ, et al.
    Anal Chem, 2023 Dec 26;95(51):18793-18802.
    PMID: 38095040 DOI: 10.1021/acs.analchem.3c03785
    Metabolomics and proteomics offer significant advantages in understanding biological mechanisms at two hierarchical levels. However, conventional single omics analysis faces challenges due to the high demand for specimens and the complexity of intrinsic associations. To obtain comprehensive and accurate system biological information, we developed a multiomics analytical method called Windows Scanning Multiomics (WSM). In this method, we performed simultaneous extraction of metabolites and proteins from the same sample, resulting in a 10% increase in the coverage of the identified biomolecules. Both metabolomics and proteomics analyses were conducted by using ultrahigh-performance liquid chromatography mass spectrometry (UPLC-MS), eliminating the need for instrument conversions. Additionally, we designed an R-based program (WSM.R) to integrate mathematical and biological correlations between metabolites and proteins into a correlation network. The network created from simultaneously extracted biomolecules was more focused and comprehensive compared to those from separate extractions. Notably, we excluded six pairs of false-positive relationships between metabolites and proteins in the network established using simultaneously extracted biomolecules. In conclusion, this study introduces a novel approach for multiomics analysis and data processing that greatly aids in bioinformation mining from multiomics results. This method is poised to play an indispensable role in systems biology research.
    Matched MeSH terms: Metabolomics/methods
  2. iMSEA: A Novel Metabolite Set Enrichment Analysis Strategy to Decipher Drug Interactions
    Wang Y, Liu X, Dong L, Cheng KK, Lin C, Wang X, et al.
    Anal Chem, 2023 Apr 18;95(15):6203-6211.
    PMID: 37023366 DOI: 10.1021/acs.analchem.2c04603
    Drug combinations are commonly used to treat various diseases to achieve synergistic therapeutic effects or to alleviate drug resistance. Nevertheless, some drug combinations might lead to adverse effects, and thus, it is crucial to explore the mechanisms of drug interactions before clinical treatment. Generally, drug interactions have been studied using nonclinical pharmacokinetics, toxicology, and pharmacology. Here, we propose a complementary strategy based on metabolomics, which we call interaction metabolite set enrichment analysis, or iMSEA, to decipher drug interactions. First, a digraph-based heterogeneous network model was constructed to model the biological metabolic network based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Second, treatment-specific influences on all detected metabolites were calculated and propagated across the whole network model. Third, pathway activity was defined and enriched to quantify the influence of each treatment on the predefined functional metabolite sets, i.e., metabolic pathways. Finally, drug interactions were identified by comparing the pathway activity enriched by the drug combination treatments and the single drug treatments. A data set consisting of hepatocellular carcinoma (HCC) cells that were treated with oxaliplatin (OXA) and/or vitamin C (VC) was used to illustrate the effectiveness of the iMSEA strategy for evaluation of drug interactions. Performance evaluation using synthetic noise data was also performed to evaluate sensitivities and parameter settings for the iMSEA strategy. The iMSEA strategy highlighted synergistic effects of combined OXA and VC treatments including the alterations in the glycerophospholipid metabolism pathway and glycine, serine, and threonine metabolism pathway. This work provides an alternative method to reveal the mechanisms of drug combinations from the viewpoint of metabolomics.
    Matched MeSH terms: Metabolomics/methods
  3. Fulltext NMF-Based Approach for Missing Values Imputation of Mass Spectrometry Metabolomics Data
    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*
  4. NMR metabolomics for evaluating passage number and harvesting effects on mammalian cell metabolome
    Abdul-Hamid NA, Abas F, Maulidiani M, Ismail IS, Tham CL, Swarup S, et al.
    Anal Biochem, 2019 07 01;576:20-32.
    PMID: 30970239 DOI: 10.1016/j.ab.2019.04.001
    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.
    Matched MeSH terms: Metabolomics/methods*
  5. Recent insights on the significance of transcriptomic and metabolomic analysis of male factor infertility
    Lee LK, Foo KY
    Clin Biochem, 2014 Jul;47(10-11):973-82.
    PMID: 24875852 DOI: 10.1016/j.clinbiochem.2014.05.053
    Infertility is a worldwide reproductive health problem which affects approximately 15% of couples, with male factor infertility dominating nearly 50% of the affected population. The nature of the phenomenon is underscored by a complex array of transcriptomic, proteomic and metabolic differences which interact in unknown ways. Many causes of male factor infertility are still defined as idiopathic, and most diagnosis tends to be more descriptive rather than specific. As such, the emergence of novel transcriptomic and metabolomic studies may hold the key to more accurately diagnose and treat male factor infertility. This paper provides the most recent evidence underlying the role of transcriptomic and metabolomic analysis in the management of male infertility. A summary of the current knowledge and new discovery of noninvasive, highly sensitive and specific biomarkers which allow the expansion of this area is outlined.
    Matched MeSH terms: Metabolomics/methods
  6. Fulltext Discriminative Analysis of Different Grades of Gaharu (Aquilaria malaccensis Lamk.) via ¹H-NMR-Based Metabolomics Using PLS-DA and Random Forests Classification Models
    Ismail SN, Maulidiani M, Akhtar MT, Abas F, Ismail IS, Khatib A, et al.
    Molecules, 2017 Sep 25;22(10).
    PMID: 28946701 DOI: 10.3390/molecules22101612
    Gaharu (agarwood, Aquilaria malaccensis Lamk.) is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using ¹H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA) and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a 'high grade' group (samples A, B and D), characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an 'intermediate grade' group (samples C, F and G), dominated by fatty acid and vanillic acid; and a 'low grade' group (sample E and H), which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that ¹H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents.
    Matched MeSH terms: Metabolomics/methods*
  7. Study on the acute toxicity of sodium taurocholate via zebrafish mortality, behavioral response, and NMR-metabolomics analysis
    Abdulazeez I, Ismail IS, Mohd Faudzi SM, Christianus A, Chong SG
    Drug Chem Toxicol, 2024 Jan;47(1):115-130.
    PMID: 37548163 DOI: 10.1080/01480545.2023.2242005
    Sodium taurocholate (NaT) is a hydrophobic bile salt that exhibits varying toxicity and antimicrobial activity. The accumulation of BSs during their entero-hepatic cycle causes cytotoxicity in the liver and intestine and could also alter the intestinal microbiome leading to various diseases. In this research, the acute toxicity of sodium taurocholate in different concentrations (3000 mg/L, 1500 mg/L, 750 mg/L, 375 mg/L, and 0 mg/L) was investigated on four months old zebrafish by immersion in water for 96 h. The results were determined based on the fish mortality, behavioral response, and NMR metabolomics analysis which revealed LC50 of 1760.32 mg/L and 1050.42 mg/L after 72 and 96 h treatment, respectively. However, the non-lethal NaT concentrations of 750 mg/L and 375 mg/L at 96 h exposure significantly (p ≤ 0.05) decreased the total distance traveled and the activity duration, also caused surface respiration on the zebrafish. Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) revealed that the metabolome of the fish treated with 750 mg/L was discriminated from that of the control by PC1. Major significantly downregulated metabolites by NaT-induction include valine, isoleucine, 2-hydroxyvalerate, glycine, glycerol, choline, glucose, pyruvate, anserine, threonine, carnitine and homoserine. On the contrary, taurine, creatine, lactate, acetate and 3-hydroxybutyrate were upregulated suggesting cellular consumption of lipids, glucose and amino acids for adenosine triphosphate (ATP) generation during immune and inflammatory response. whereby these metabolites were released in the process. In conclusion, the research revealed the toxic effect of NaT and its potential to trigger changes in zebrafish metabolism.
    Matched MeSH terms: Metabolomics/methods
  8. Metabolomic-guided discovery of Alzheimer's disease biomarkers from body fluid
    Enche Ady CNA, Lim SM, Teh LK, Salleh MZ, Chin AV, Tan MP, et al.
    J Neurosci Res, 2017 Oct;95(10):2005-2024.
    PMID: 28301062 DOI: 10.1002/jnr.24048
    The rapid increase in the older population has made age-related diseases like Alzheimer's disease (AD) a global concern. Given that there is still no cure for this neurodegenerative disease, the drastic growth in the number of susceptible individuals represents a major emerging threat to public health. The poor understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and management of this disease. There is a dire need for biomarkers that can facilitate early diagnosis, classification, prognosis, and treatment response. Efforts have been directed toward discovery of reliable and distinctive AD biomarkers but with very little success. With the recent emergence of high-throughput technology that is able to collect and catalogue vast datasets of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers. This review article highlights the potential of using multiple metabolomics platforms as useful means in uncovering AD biomarkers from body fluids. © 2017 Wiley Periodicals, Inc.
    Matched MeSH terms: Metabolomics/methods*
  9. Proteomic and metabolomic study of wax apple (Syzygium samarangense) fruit during ripening process
    Jamil NAM, Rahmad N, Rosli NHM, Al-Obaidi JR
    Electrophoresis, 2018 12;39(23):2954-2964.
    PMID: 30074628 DOI: 10.1002/elps.201800185
    Wax apple is one of the underutilized fruits that is considered a good source of fibers, vitamins, minerals as well as antioxidants. In this study, a comparative analysis of the developments of wax fruit ripening at the proteomic and metabolomic level was reported. 2D electrophoresis coupled with MALDI-TOF/TOF was used to compare the proteome profile from three developmental stages named immature, young, and mature fruits. In general, the protein expression profile and the identified proteins function were discussed for their potential roles in fruit physiological development and ripening processes. The metabolomic investigation was also performed on the same samples using quadrupole LC-MS (LC-QTOF/MS). Roles of some of the differentially expressed proteins and metabolites are discussed in relation to wax apple ripening during the development. This is the first study investigating the changes in the proteins and metabolites in wax apple at different developmental stages. The information obtained from this research will be helpful in developing biomarkers for breeders and help the plant researchers to avoid wax apple cultivation problems such as fruit cracking.
    Matched MeSH terms: Metabolomics/methods*
  10. Immunomodulatory effects of Isochrysis galbana incorporated diet on Oreochromis sp. (red hybrid tilapia) via Sera-1H NMR metabolomics study
    Ahamad Bustamam MS, Pantami HA, Shaari K, Min CC, Mediani A, Ismail IS
    Fish Shellfish Immunol, 2023 Jan;132:108455.
    PMID: 36464078 DOI: 10.1016/j.fsi.2022.108455
    Tilapia is one of the most common fish species that is intensively produced all over the world. However, significant measures at improving aquaculture health must be taken since disease outbreaks are often encountered in the rapidly developing aquaculture industry. Therefore, the objective of the study was designed to evaluate the metabolite changes in tilapia' sera through 1H NMR metabolomics in identifying the potential biomarkers responsible for immunomodulatory effect by the indigenous species of Malaysian microalgae Isochrysis galbana (IG). The results showed that IG-incorporated diet mainly at 5.0% has improved the immune response of innate immunity as observed in serum bactericidal activity (SBA) and serum lysozyme activity (SLA). The orthogonal partial least squares (OPLS) analysis indicated 5 important metabolites significantly upregulated namely as ethanol, lipoprotein, lipid, α-glucose and unsaturated fatty acid (UFA) in the 5.0% IG-incorporated diet compared to control. In conclusion, this study had successfully determined IG in improving aquaculture health through its potential use as an immune modulator. This work also demonstrated the effective use of metabolomics approach in the development of alternative nutritious diet from microalgae species to boost fish health in fulfilling the aquaculture's long-term goals.
    Matched MeSH terms: Metabolomics/methods
  11. Fulltext A Preliminary Nuclear Magnetic Resonance Metabolomics Study Identifies Metabolites that Could Serve as Diagnostic Markers of Major Depressive Disorder
    Badamasi IM, Maulidiani M, Lye MS, Ibrahim N, Shaari K, Stanslas J
    Curr Neuropharmacol, 2022;20(5):965-982.
    PMID: 34126904 DOI: 10.2174/1570159X19666210611095320
    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.

    Matched MeSH terms: Metabolomics/methods
  12. Fulltext A review of the "Omics" approach to biomarkers of oxidative stress in Oryza sativa
    Ma NL, Rahmat Z, Lam SS
    Int J Mol Sci, 2013 Apr 08;14(4):7515-41.
    PMID: 23567269 DOI: 10.3390/ijms14047515
    Physiological and ecological constraints that cause the slow growth and depleted production of crops have raised a major concern in the agriculture industry as they represent a possible threat of short food supply in the future. The key feature that regulates the stress signaling pathway is always related to the reactive oxygen species (ROS). The accumulation of ROS in plant cells would leave traces of biomarkers at the genome, proteome, and metabolome levels, which could be identified with the recent technological breakthrough coupled with improved performance of bioinformatics. This review highlights the recent breakthrough in molecular strategies (comprising transcriptomics, proteomics, and metabolomics) in identifying oxidative stress biomarkers and the arising opportunities and obstacles observed in research on biomarkers in rice. The major issue in incorporating bioinformatics to validate the biomarkers from different omic platforms for the use of rice-breeding programs is also discussed. The development of powerful techniques for identification of oxidative stress-related biomarkers and the integration of data from different disciplines shed light on the oxidative response pathways in plants.
    Matched MeSH terms: Metabolomics/methods*
  13. Acclimatisation-induced stress influenced host metabolic and gut microbial composition change
    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
  14. 1H-NMR-based metabolomics to investigate the effects of Phoenix dactylifera seed extracts in LPS-IFN-γ-induced RAW 264.7 cells
    Abdul-Hamid NA, Abas F, Ismail IS, Tham CL, Maulidiani M, Mediani A, et al.
    Food Res Int, 2019 11;125:108565.
    PMID: 31554083 DOI: 10.1016/j.foodres.2019.108565
    Inflammation has been revealed to play a central role in the onset and progression of many illnesses. Nuclear magnetic resonance (NMR) based metabolomics method was adopted to evaluate the effects of Phoenix dactylifera seeds, in particular the Algerian date variety of Deglet on the metabolome of the LPS-IFN-γ-induced RAW 264.7 cells. Variations in the extracellular and intracellular profiles emphasized the differences in the presence of tyrosine, phenylalanine, alanine, proline, asparagine, isocitrate, inosine and lysine. Principal component analysis (PCA) revealed noticeable clustering patterns between the treated and induced RAW cells based on the metabolic profile of the extracellular metabolites. However, the effects of treatment on the intracellular metabolites appears to be less distinct as suggested by the PCA and heatmap analyses. A clear group segregation was observed for the intracellular metabolites from the treated and induced cells based on the orthogonal partial least squares-discriminant analysis (OPLS-DA) score plot. Likewise, 11 of the metabolites in the treated cells were significantly different from those in the induced groups, including amino acids and succinate. The enrichment analysis demonstrated that treatment with Deglet seed extracts interfered with the energy and of amino acids metabolism. Overall, the obtained data reinforced the possible application of Deglet seeds as a functional food with anti-inflammatory properties.
    Matched MeSH terms: Metabolomics/methods*
  15. Fulltext Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly
    Nik Mohd Fakhruddin NNI, Shahar S, Ismail IS, Ahmad Azam A, Rajab NF
    Nutrients, 2020 Sep 23;12(10).
    PMID: 32977370 DOI: 10.3390/nu12102900
    Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (1H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the 1H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson's correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in "taurine and hypotaurine metabolism" and "tryptophan metabolism" in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.
    Matched MeSH terms: Metabolomics/methods*
  16. Complementary NMR- and MS-based metabolomics approaches reveal the correlations of phytochemicals and biological activities in Phyllanthus acidus leaf extracts
    Abd Ghafar SZ, Mediani A, Maulidiani M, Rudiyanto R, Mohd Ghazali H, Ramli NS, et al.
    Food Res Int, 2020 10;136:109312.
    PMID: 32846521 DOI: 10.1016/j.foodres.2020.109312
    Proton nuclear magnetic resonance (1H NMR)- and ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS)-based analytical tools are frequently used in metabolomics studies. These complementary metabolomics platforms were applied to identify and quantify the metabolites in Phyllanthus acidus extracted with different ethanol concentrations. In total, 38 metabolites were tentatively identified by 1H NMR and 39 via UHPLC-MS, including 30 compounds are reported for the first time from this plant. The partial least square analysis (PLS) revealed the metabolites that contributed to α-glucosidase and nitric oxide (NO) inhibitory activities, including kaempferol, quercetin, myricetin, phyllanthusol A, phyllanthusol B, chlorogenic, catechin, cinnamic coumaric, caffeic, quinic, citric, ellagic and malic acids. This study shows the significance of combining 1H NMR- and UHPLC-MS-based metabolomics as the best strategies in identifying metabolites in P. acidus extracts and establishing an extract with potent antioxidant, anti-diabetic, and anti-inflammatory properties.
    Matched MeSH terms: Metabolomics/methods*
  17. Metabolomics and Lipidomics of Ischemic Stroke
    Au A
    Adv Clin Chem, 2018 03 08;85:31-69.
    PMID: 29655461 DOI: 10.1016/bs.acc.2018.02.002
    Ischemic stroke is a sudden loss of brain function due to the reduction of blood flow. Brain tissues cease to function with subsequent activation of the ischemic cascade. Metabolomics and lipidomics are modern disciplines that characterize the metabolites and lipid components of a biological system, respectively. Because the pathogenesis of ischemic stroke is heterogeneous and multifactorial, it is crucial to establish comprehensive metabolomic and lipidomic approaches to elucidate these alterations in this disease. Fortunately, metabolomic and lipidomic studies have the distinct advantages of identifying tissue/mechanism-specific biomarkers, predicting treatment and clinical outcome, and improving our understanding of the pathophysiologic basis of disease states. Therefore, recent applications of these analytical approaches in the early diagnosis of ischemic stroke were discussed. In addition, the emerging roles of metabolomics and lipidomics on ischemic stroke were summarized, in order to gain new insights into the mechanisms underlying ischemic stroke and in the search for novel metabolite biomarkers and their related pathways.
    Matched MeSH terms: Metabolomics/methods*
  18. Fulltext Metabolite Profiling of the Microalgal Diatom Chaetoceros Calcitrans and Correlation with Antioxidant and Nitric Oxide Inhibitory Activities via ¹H NMR-Based Metabolomics
    Azizan A, Ahamad Bustamam MS, Maulidiani M, Shaari K, Ismail IS, Nagao N, et al.
    Mar Drugs, 2018 May 07;16(5).
    PMID: 29735927 DOI: 10.3390/md16050154
    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.
    Matched MeSH terms: Metabolomics/methods
  19. Metabolomics, Lipidomics and Pharmacometabolomics of Human Hypertension
    Au A, Cheng KK, Wei LK
    Adv Exp Med Biol, 2017;956:599-613.
    PMID: 27722964 DOI: 10.1007/5584_2016_79
    Hypertension is a common but complex human disease, which can lead to a heart attack, stroke, kidney disease or other complications. Since the pathogenesis of hypertension is heterogeneous and multifactorial, it is crucial to establish a comprehensive metabolomic approach to elucidate the molecular mechanism of hypertension. Although there have been limited metabolomic, lipidomic and pharmacometabolomic studies investigating this disease to date, metabolomic studies on hypertension have provided greater insights into the identification of disease-specific biomarkers, predicting treatment outcome and monitor drug safety and efficacy. Therefore, we discuss recent updates on the applications of metabolomics technology in human hypertension with a focus on metabolic biomarker discovery.
    Matched MeSH terms: Metabolomics/methods*
  20. 1HNMR-Based Discriminatory Analysis of Eurycoma longifolia from Different Locations and Establishing a Profile for Primary Metabolites Identification and Quassinoids Quantification
    Ebrahimi F, Ibrahim B, Teh CH, Murugaiyah V, Lam CK
    Planta Med, 2017 Jan;83(1-02):172-182.
    PMID: 27399233 DOI: 10.1055/s-0042-110857
    Quassinoids, the major secondary metabolites of Eurycoma longifolia roots, improve male fertility. Hence, it is crucial to investigate their quantitative level in E. longifolia extracts. A profile was established to identify the primary metabolites and major quassinoids, and quantify quassinoids using external calibration curves. Furthermore, the metabolic discrimination of E. longifolia roots from different regions was investigated. The (1)H-NMR spectra of the quassinoids, eurycomanone, eurycomanol, 13,21-dihydroeurycomanone, and eurycomanol-2-O-β-D-glycopyranoside were obtained. The (1)H-NMR profiles of E. longifolia root aqueous extracts from Perak (n = 30) were obtained and used to identify primary metabolites and the quassinoids. Selangor, Kedah, Terengganu (n = 5 for each), and Perak samples were checked for metabolic discrimination. Hotelling's T(2) plot was used to check for outliers. Orthogonal partial least-squares discriminant analysis was run to reveal the discriminatory metabolites. Perak samples contained formic, succinic, methylsuccinic, fumaric, lactic, acetic and syringic acids as well as choline, alanine, phenylalanine, tyrosine, α-glucose, eurycomanone, eurycomanol, 13,21-dihydroeurycomanone, and eurycomanol-2-O-β-D-glycopyranoside. The extracts from other locations contained the same metabolites. The limit of quantification values were 1.96 (eurycomanone), 15.62 (eurycomanol), 3.91 (13,21-dihydroeurycomanone), and 31.25 (eurycomanol-2-O-β-D-glycopyranoside) ppm. The Hotelling's T(2) plot revealed no outlier. The orthogonal partial least-squares discriminant analysis model showed that choline, eurycomanol, eurycomanol-2-O-β-D-glycopyranoside, and lactic and succinic acid levels were different among regions. Terengganu and Perak samples contained higher amounts of eurycomanol and eurycomanol-2-O-β-D-glycopyranoside, respectively. The current approach efficiently detected E. longifolia root metabolites, quantified the quassinoids, and discriminated E. longifolia roots from different locations. These findings could be applicable to future research on E. longifolia where the higher content of quassinoids is required.
    Matched MeSH terms: Metabolomics/methods*
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