Displaying publications 1 - 20 of 171 in total

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  1. 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
  2. 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
  3. Fulltext Why metabonomics?
    Yap, Ivan K.S.
    International e-Journal of Science, Medicine & Education, 2011;5(1):17-26.
    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
  4. 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*
  5. Urine NMR Metabolomic Study on Biochemical Activities to Investigate the Effect of P. betle Extract on Obese Rats
    Abdul Ghani ZDF, Ab Rashid AH, Shaari K, Chik Z
    Appl Biochem Biotechnol, 2019 Oct;189(2):690-708.
    PMID: 31111377 DOI: 10.1007/s12010-019-03042-w
    The present studies are to evaluate the ability of PB to induce weight loss and urine metabolite profile of Piper betle L. (PB) leaf extracts using metabolomics approach. Dried PB leaves were extracted with ethanol 70% and the studies were performed in different groups of rats fed with high fat (HFD) and normal diet (ND). Then, fed with the PB extract with 100, 300, and 500 mg/kg and two negative control groups given water (WTR). The body weights were monitored and evaluated. Urine was collected and 1H NMR-based metabolomics approach was used to detect the metabolite changes. Results showed that PB-treated group demonstrated inhibition of body weight gain. The trajectory of urine metabolites showed that PB-treated group gave the different distribution from week 12 to 16 compared with the control groups. In 1H NMR metabolomic approach analysis, the urine metabolites gave the best separation in principle component 1 and 3, with 40.0% and 9.56% of the total variation. Shared and unique structures (SUS) plot model showed that higher concentration PB-treated group was characterized by high level of indole-3-acetate, aspartate, methanol, histidine, and creatine, thus caused an increased the metabolic function and maintaining the body weight of the animals treated.
    Matched MeSH terms: Metabolomics*
  6. Fulltext Urinary metabolomics study on the protective role of Orthosiphon stamineus in Streptozotocin induced diabetes mellitus in rats via (1)H NMR spectroscopy
    Azam AA, Pariyani R, Ismail IS, Ismail A, Khatib A, Abas F, et al.
    BMC Complement Altern Med, 2017 May 25;17(1):278.
    PMID: 28545435 DOI: 10.1186/s12906-017-1777-1
    BACKGROUND: Orthosiphon stamineus (OS) is a herb known in ethnomedicine for treating diabetes mellitus (DM). In this study, a (1)H NMR based urine metabolomics tool has been used for the first time to identify the metabolic protective mechanism of OS in DM using Streptozotocin (STZ) induced experimental model in rats.

    METHODS: Four different solvent extracts of OS, namely aqueous, ethanolic, 50% aqueous ethanolic and methanolic, at a dose of 500 mg/kg body weight (bw) were orally administered for 14 days to diabetic rats induced via intraperitoneal injection of 60 mg/kg bw STZ. NMR metabolomics approach using pattern recognition combined with multivariate statistical analysis was applied in the rat urine to study the resulted metabolic perturbations.

    RESULTS: OS aqueous extract (OSAE) caused a reversal of DM comparable to that of 10 mg/kg bw glibenclamide. A total of 15 urinary metabolites, which levels changed significantly upon treatment were identified as the biomarkers of OSAE in diabetes. A systematic metabolic pathways analysis identified that OSAE contributed to the antidiabetic activity mainly through regulating the tricarboxylic acid cycle, glycolysis/gluconeogenesis, lipid and amino acid metabolism.

    CONCLUSIONS: The results of this study validated the ethnopharmacological use of OS in diabetes and unveiled the biochemical and metabolic mechanisms involved.

    Matched MeSH terms: Metabolomics
  7. Urinary metabolic profiling of cisplatin nephrotoxicity and nephroprotective effects of Orthosiphon stamineus leaves elucidated by 1H NMR spectroscopy
    Pariyani R, Ismail IS, Azam A, Khatib A, Abas F, Shaari K, et al.
    J Pharm Biomed Anal, 2017 Feb 20;135:20-30.
    PMID: 27987392 DOI: 10.1016/j.jpba.2016.12.010
    Orthosiphon stamineus (OS) is a popular medicinal herb used in traditional Chinese medicine as a diuretic agent and for renal system disorders. This study employed 1H NMR based metabolomics approach to investigate the possible protective activity of OS in cisplatin induced nephrotoxicity owing to its diuretic and antioxidant activities. Aqueous (OSAE) and 50% aqueous ethanolic (OSFE) extracts of OS leaves were orally administered at 400mg/kg BW doses to rats which were then intraperitoneally injected with cisplatin at 5mg/kg BW dose. The 1H NMR profile of the urine samples collected on day 5 after cisplatin administration were analyzed by multivariate pattern recognition techniques, whereby 19 marker metabolites suggestive in the involvement of TCA cycle, disturbed energy metabolism, altered gut microflora and BCAA metabolism pathways were identified. It was observed that OSFE caused significant changes (p<0.05) in the levels of 8 markers namely leucine, acetate, hippurate, lysine, valine, 2-oxoglutarate, 3-HBT and acetoacetate resulting in a moderate ameliorative effect, however, it did not completely protect from nephrotoxicity. OSAE did not demonstrate significant down regulatory effects on any markers, albeit, it potentiated the cisplatin nephrotoxicity by inducing significant increase in glucose, glycine, creatinine, citrate, TMAO, acetate and creatine levels. A Principal Component Analysis (PCA) of the 1H NMR spectra of OS extracts identified that OSFE had higher concentrations of the secondary metabolites such as caffeic acid, chlorogenic acid, protocatechuic acid and orthosiphol, among others. Whereas, OSAE was characterized by higher concentrations of acetate, lactate, succinic acid, valine and phosphatidylcholine. This research denotes the first comprehensive analysis to identify the effects of OS extracts on cisplatin nephrotoxicity.
    Matched MeSH terms: Metabolomics/methods*
  8. Fulltext Understanding Host-Pathogen Interactions in Brassica napus in the Omics Era
    Neik TX, Amas J, Barbetti M, Edwards D, Batley J
    Plants (Basel), 2020 Oct 10;9(10).
    PMID: 33050509 DOI: 10.3390/plants9101336
    Brassica napus (canola/oilseed rape/rapeseed) is an economically important crop, mostly found in temperate and sub-tropical regions, that is cultivated widely for its edible oil. Major diseases of Brassica crops such as Blackleg, Clubroot, Sclerotinia Stem Rot, Downy Mildew, Alternaria Leaf Spot and White Rust have caused significant yield and economic losses in rapeseed-producing countries worldwide, exacerbated by global climate change, and, if not remedied effectively, will threaten global food security. To gain further insights into the host-pathogen interactions in relation to Brassica diseases, it is critical that we review current knowledge in this area and discuss how omics technologies can offer promising results and help to push boundaries in our understanding of the resistance mechanisms. Omics technologies, such as genomics, proteomics, transcriptomics and metabolomics approaches, allow us to understand the host and pathogen, as well as the interaction between the two species at a deeper level. With these integrated data in multi-omics and systems biology, we are able to breed high-quality disease-resistant Brassica crops in a more holistic, targeted and accurate way.
    Matched MeSH terms: Metabolomics
  9. Fulltext UPLC-MS-Based Metabolomics Profiling for α-Glucosidase Inhibiting Property of Parkia speciosa Pods
    Saleh MSM, Jalil J, Mustafa NH, Ramli FF, Asmadi AY, Kamisah Y
    Life (Basel), 2021 Jan 22;11(2).
    PMID: 33499128 DOI: 10.3390/life11020078
    Parkia speciosa is a food plant that grows indigenously in Southeast Asia. A great deal of interest has been paid to this plant due to its traditional uses in the treatment of several diseases. The pods contain many beneficial secondary metabolites with potential applications in medicine and cosmetics. However, studies on their phytochemical properties are still lacking. Therefore, the present study was undertaken to profile the bioactive compounds of P. speciosa pods collected from six different regions of Malaysia through ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) and α-glucosidase inhibitory potential. This study applied metabolomics to elucidate the differences between P. speciosa populations found naturally in the different locations and to characterize potential α-glucosidase inhibitors from P. speciosa pods. P. speciosa collected from different regions of Malaysia showed good α-glucosidase inhibitory activity, with a median inhibitory concentration (IC50) of 0.45-0.76 μg/mL. The samples from the northern and northeastern parts of Peninsular Malaysia showed the highest activity. Using UHPLC-QTOF-MS/MS analysis, 25 metabolites were identified in the pods of P. speciosa. The findings unveiled that the pods of P. speciosa collected from different locations exhibit different levels of α-glucosidase inhibitory activity. The pods are a natural source of potent antidiabetic bioactive compounds.
    Matched MeSH terms: Metabolomics
  10. Fulltext Tocotrienol-Rich Fraction of Palm Oil Improves Behavioral Impairments and Regulates Metabolic Pathways in AβPP/PS1 Mice
    Durani LW, Hamezah HS, Ibrahim NF, Yanagisawa D, Nasaruddin ML, Mori M, et al.
    J Alzheimers Dis, 2018;64(1):249-267.
    PMID: 29889072 DOI: 10.3233/JAD-170880
    We have recently shown that the tocotrienol-rich fraction (TRF) of palm oil, a mixture of vitamin E analogs, improves amyloid pathology in vitro and in vivo. However, precise mechanisms remain unknown. In this study, we examined the effects of long-term (10 months) TRF treatment on behavioral impairments and brain metabolites in (15 months old) AβPP/PS1 double transgenic (Tg) Alzheimer's disease (AD) mice. The open field test, Morris water maze, and novel object recognition tasks revealed improved exploratory activity, spatial learning, and recognition memory, respectively, in TRF-treated Tg mice. Brain metabolite profiling of wild-type and Tg mice treated with and without TRF was performed using ultrahigh performance liquid chromatography (UHPLC) coupled to high-resolution accurate mass (HRAM)-orbitrap tandem mass spectrometry (MS/MS). Metabolic pathway analysis found perturbed metabolic pathways that linked to AD. TRF treatment partly ameliorated metabolic perturbations in Tg mouse hippocampus. The mechanism of this pre-emptive activity may occur via modulation of metabolic pathways dependent on Aβ interaction or independent of Aβ interaction.
    Matched MeSH terms: Metabolomics/methods
  11. Fulltext The methanolic extract of Garcinia atroviridis (MeGa) reduces body weight and food intake, and improves lipid profiles by altering the lipid metabolism: a rat model
    Lim WF, Nasir SM, Teh LK, James RJ, Izhar MHM, Salleh MZ
    Turk J Biol, 2020;44(6):437-448.
    PMID: 33402870 DOI: 10.3906/biy-2005-2
    Garcinia species are widely used for their slimming effects via increased fat burning and suppression of satiety. However, scientific evidence for the biological effects of Garcinia atroviridis (GA) is lacking. We investigated the phytochemical composition, safety profiles, and antioxidant and antiobesity effects of methanolic extracts of Garcinia atroviridis (MeGa) in obese female rats. Repeated dose toxicity studies were conducted according to the OECD guidelines. Upon sacrifice, haematological, biochemical, lipid profile, and serum-based metabolomics analyses were performed to evaluate metabolic expression changes and their related pathways. MeGa contains several phytochemical groups and GA fruit acids. MeGa was found to be nontoxic in both male and female rats with an oral lethal dose (LD50) of 2000 mg/kg. After 9 weeks of treatment, MeGa-treated obese rats had lower weight gain and better lipid profiles (cholesterol and triglyceride), which correlated with the altered metabolic pathways involved in the metabolism of lipid (glycerophospholipid) and biosynthesis of unsaturated fatty acid. In addition, MeGa caused differential metabolism pathways of arachidonic acid and tryptophan that affect the inflammatory response and suppression of appetite. We concluded that MeGa is safe, and its slimming effects are due to the differential metabolism of lipids.
    Matched MeSH terms: Metabolomics
  12. The effects of polyphenols-rich tropical fruit juice on cognitive function and metabolomics profile - a randomized controlled trial in middle-aged women
    Rosli H, Shahar S, Rajab NF, Che Din N, Haron H
    Nutr Neurosci, 2021 Mar 05.
    PMID: 33666540 DOI: 10.1080/1028415X.2021.1880312
    Objectives: Polyphenols, particularly anthocyanins, have received attention in improving health issues during old age, including decline in cognitive function and other health parameters. We aimed to determine the effects of polyphenols-rich tropical fruit TP 3-in-1™ juice towards improving cognitive function, oxidative stress and metabolomics profiles among middle-aged women.Methods: This clinical trial involved 31 subjects with signs of poor cognitive function, as assessed using the Rey Auditory Verbal Learning Test (RAVLT). They were randomized to receive either TP 3-in-1™ juice (n = 16) or placebo (n = 15). Study subjects consumed 500 ml of beverages for three times per day, three days per week, for a period of ten weeks. Juice supplementation provided 9135 mg GAE of total phenolic content and 194.1 mg cyanidin-3-glucoside of total anthocyanin monomer.Results: There was a significant interaction effects on RAVLT immediate recall (p 
    Matched MeSH terms: Metabolomics
  13. The effects of high-fat diet and metformin on urinary metabolites in diabetes and prediabetes rat models
    Lee YF, Sim XY, Teh YH, Ismail MN, Greimel P, Murugaiyah V, et al.
    Biotechnol Appl Biochem, 2021 Oct;68(5):1014-1026.
    PMID: 32931602 DOI: 10.1002/bab.2021
    High-fat diet (HFD) interferes with the dietary plan of patients with type 2 diabetes mellitus (T2DM). However, many diabetes patients consume food with higher fat content for a better taste bud experience. In this study, we examined the effect of HFD on rats at the early onset of diabetes and prediabetes by supplementing their feed with palm olein oil to provide a fat content representing 39% of total calorie intake. Urinary profile generated from liquid chromatography-mass spectrometry analysis was used to construct the orthogonal partial least squares discriminant analysis (OPLS-DA) score plots. The data provide insights into the physiological state of an organism. Healthy rats fed with normal chow (NC) and HFD cannot be distinguished by their urinary metabolite profiles, whereas diabetic and prediabetic rats showed a clear separation in OPLS-DA profile between the two diets, indicating a change in their physiological state. Metformin treatment altered the metabolomics profiles of diabetic rats and lowered their blood sugar levels. For prediabetic rats, metformin treatment on both NC- and HFD-fed rats not only reduced their blood sugar levels to normal but also altered the urinary metabolite profile to be more like healthy rats. The use of metformin is therefore beneficial at the prediabetes stage.
    Matched MeSH terms: Metabolomics
  14. The differential metabolite profiles of acute lymphoblastic leukaemic patients treated with 6-mercaptopurine using untargeted metabolomics approach
    Bannur Z, Teh LK, Hennesy T, Rosli WR, Mohamad N, Nasir A, et al.
    Clin Biochem, 2014 Apr;47(6):427-31.
    PMID: 24582698 DOI: 10.1016/j.clinbiochem.2014.02.013
    Acute lymphoblastic leukaemia (ALL) has posed challenges to the clinician due to variable patients' responses and late diagnosis. With the advance in metabolomics, early detection and personalised treatment are possible.
    Matched MeSH terms: Metabolomics/methods*
  15. Fulltext The anti-neuroinflammatory effects of Clinacanthus nutans leaf extract on metabolism elucidated through 1H NMR in correlation with cytokines microarray
    Ahmad Azam A, Ismail IS, Kumari Y, Shaikh MF, Abas F, Shaari K
    PLoS One, 2020;15(9):e0238503.
    PMID: 32925968 DOI: 10.1371/journal.pone.0238503
    Clinacanthus nutans (CN) (Acanthaceae) is well-known for its anti-inflammatory properties among Asian communities; however, there are currently no data specifically focused on the anti-inflammatory effects of CN on the brain tissue. Neuroinflammation is a common consequence of toxin intrusion to any part of the central nervous system (CNS). As an innate immune response, the CNS may react through both protective and/or toxic actions due to the activation of neuron cells producing pro- and/or anti-inflammatory cytokines in the brain. The unresolved activation of the inflammatory cytokines' response is associated with the pathogenesis of neurological disorders. The present study aimed to decipher the metabolic mechanism on the effects of 14 days oral treatment with CN aqueous extract in induced-lipopolysaccharides (LPS) rats through 1H NMR spectroscopic biomarker profiling of the brain tissue and the related cytokines. Based on the principal component analysis (PCA) of the nuclear magnetic resonance (NMR) spectral data, twenty-one metabolites in the brain tissue were profiled as biomarkers for the LPS (10 μL)-induced neuroinflammation following intracerebroventricular injection. Among the twenty-one biomarkers in the neuroinflammed rats, CN treatment of 1000 and 500 mg/kg BW successfully altered lactate, pyruvate, phosphorylcholine, glutamine, and α-ketoglutarate when compared to the negative control. Likewise, statistical isolinear multiple component analysis (SIMCA) showed that treatments by CN and the positive control drug, dextromethorphan (DXM, 5 mg/kg BW), have anti-neuroinflammatory potential. A moderate correlation, in the orthogonal partial least squares (OPLS) regression model, was found between the spectral metabolite profile and the cytokine levels. The current study revealed the existence of high levels of pro-inflammatory cytokines, namely IL-1α, IL-1β, and TNF-α in LPS-induced rats. Both CN dose treatments lowered IL-1β significantly better than DXM Interestingly, DXM and CN treatments both exhibited the upregulation of the anti-inflammatory cytokines IL-2 and 4. However, DXM has an advantage over CN in that the former also increased the expression of IL-10 of anti-inflammatory cytokines. In this study, a metabolomics approach was successfully applied to discover the mechanistic role of CN in controlling the neuroinflammatory conditions through the modulation of complex metabolite interactions in the rat brain.
    Matched MeSH terms: Metabolomics
  16. Fulltext The Effects of 12 Weeks Colostrum Milk Supplementation on the Expression Levels of Pro-Inflammatory Mediators and Metabolic Changes among Older Adults: Findings from the Biomarkers and Untargeted Metabolomic Analysis
    Ooi TC, Ahmad A, Rajab NF, Sharif R
    Nutrients, 2023 Jul 18;15(14).
    PMID: 37513601 DOI: 10.3390/nu15143184
    Senescence is a normal biological process that is accompanied with a series of deteriorations in physiological function. This study aimed to investigate the effects of bovine colostrum milk supplementation on metabolic changes and the expression of various biomarkers on inflammation, antioxidant and oxidative damage, nutrient metabolism, and genomic stability among older adults. Older adults (50-69 years old) who participated in the 12-week randomized, double-blinded, placebo-controlled trial were instructed to consume the IgCo bovine colostrum-enriched skim milk or regular skim milk (placebo) twice daily. Following 12 weeks of intervention, participants in the intervention group had lower expression levels in pro-inflammatory mediators (CRP, IL-6, and TNF-α), with significant (p < 0.05) interaction effects of the group and time observed. However, no significant interaction effect was observed in the vitamin D, telomerase, 8-OHdG, MDA, and SOD activities. UPLC-MS-based untargeted metabolomics analysis revealed that 22 metabolites were upregulated and 11 were downregulated in the intervention group compared to the placebo group. Glycerophospholipid metabolism, along with cysteine and methionine metabolism were identified as the potential metabolic pathways that are associated with bovine colostrum milk consumption. In conclusion, consuming bovine colostrum milk may induce metabolic changes and reduce the expression of various pro-inflammatory mediators, thus improving the immune function in older adults.
    Matched MeSH terms: Metabolomics
  17. 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
  18. Sparse PLS-Based Method for Overlapping Metabolite Set Enrichment Analysis
    Deng L, Ma L, Cheng KK, Xu X, Raftery D, Dong J
    J Proteome Res, 2021 06 04;20(6):3204-3213.
    PMID: 34002606 DOI: 10.1021/acs.jproteome.1c00064
    Metabolite set enrichment analysis (MSEA) has gained increasing research interest for identification of perturbed metabolic pathways in metabolomics. The method incorporates predefined metabolic pathways information in the analysis where metabolite sets are typically assumed to be mutually exclusive to each other. However, metabolic pathways are known to contain common metabolites and intermediates. This situation, along with limitations in metabolite detection or coverage leads to overlapping, incomplete metabolite sets in pathway analysis. For overlapping metabolite sets, MSEA tends to result in high false positives due to improper weights allocated to the overlapping metabolites. Here, we proposed an extended partial least squares (PLS) model with a new sparse scheme for overlapping metabolite set enrichment analysis, named overlapping group PLS (ogPLS) analysis. The weight vector of the ogPLS model was decomposed into pathway-specific subvectors, and then a group lasso penalty was imposed on these subvectors to achieve a proper weight allocation for the overlapping metabolites. Two strategies were adopted in the proposed ogPLS model to identify the perturbed metabolic pathways. The first strategy involves debiasing regularization, which was used to reduce inequalities amongst the predefined metabolic pathways. The second strategy is stable selection, which was used to rank pathways while avoiding the nuisance problems of model parameter optimization. Both simulated and real-world metabolomic datasets were used to evaluate the proposed method and compare with two other MSEA methods including Global-test and the multiblock PLS (MB-PLS)-based pathway importance in projection (PIP) methods. Using a simulated dataset with known perturbed pathways, the average true discovery rate for the ogPLS method was found to be higher than the Global-test and the MB-PLS-based PIP methods. Analysis with a real-world metabolomics dataset also indicated that the developed method was less prone to select pathways with highly overlapped detected metabolite sets. Compared with the two other methods, the proposed method features higher accuracy, lower false-positive rate, and is more robust when applied to overlapping metabolite set analysis. The developed ogPLS method may serve as an alternative MSEA method to facilitate biological interpretation of metabolomics data for overlapping metabolite sets.
    Matched MeSH terms: Metabolomics
  19. Fulltext Serum Metabolomics Profiling of Commercially Mixed Functional Foods-Effects in Beta-Amyloid Induced Rats Measured Using 1H NMR Spectroscopy
    Rosli NHM, Yahya HM, Ibrahim FW, Shahar S, Ismail IS, Azam AA, et al.
    Nutrients, 2020 Dec 12;12(12).
    PMID: 33322743 DOI: 10.3390/nu12123812
    Functional foods such as pomegranate, dates and honey were shown by various previous studies to individually have a neuroprotective effect, especially in neurodegenerative disease such as Alzheimer's disease (AD). In this novel and original study, an 1H NMR spectroscopy tool was used to identify the metabolic neuroprotective mechanism of commercially mixed functional foods (MFF) consisting of pomegranate, dates and honey, in rats injected with amyloid-beta 1-42 (Aβ-42). Forty-five male albino Wistar rats were randomly divided into five groups: NC (0.9% normal saline treatment + phosphate buffer solution (PBS) solution injection), Abeta (0.9% normal saline treatment + 0.2 µg/µL Aβ-42 injection), MFF (4 mL/kg MFF treatment + PBS solution injection), Abeta-MFF (4 mL/kg MFF treatment + 0.2 µg/µL Aβ-42 injection) and Abeta-NAC (150 mg/kg N-acetylcysteine + 0.2 µg/µL Aβ-42 injection). Based on the results, the MFF and NAC treatment improved the spatial memory and learning using Y-maze. In the metabolic analysis, a total of 12 metabolites were identified, for which levels changed significantly among the treatment groups. Systematic metabolic pathway analysis found that the MFF and NAC treatments provided a neuroprotective effect in Aβ-42 injected rats by improving the acid amino and energy metabolisms. Overall, this finding showed that MFF might serve as a potential neuroprotective functional food for the prevention of AD.
    Matched MeSH terms: Metabolomics/methods
  20. Sequential Hybrid Three-Dimensional Gas Chromatography with Accurate Mass Spectrometry: A Novel Tool for High-Resolution Characterization of Multicomponent Samples
    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
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