Displaying publications 21 - 40 of 172 in total

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  1. Fulltext Detection of Pork in Beef Meatballs Using LC-HRMS Based Untargeted Metabolomics and Chemometrics for Halal Authentication
    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
  2. Fulltext Microbial Contributions for Rice Production: From Conventional Crop Management to the Use of 'Omics' Technologies
    Doni F, Suhaimi NSM, Mispan MS, Fathurrahman F, Marzuki BM, Kusmoro J, et al.
    Int J Mol Sci, 2022 Jan 10;23(2).
    PMID: 35054923 DOI: 10.3390/ijms23020737
    Rice, the main staple food for about half of the world's population, has had the growth of its production stagnate in the last two decades. One of the ways to further improve rice production is to enhance the associations between rice plants and the microbiome that exists around, on, and inside the plant. This article reviews recent developments in understanding how microorganisms exert positive influences on plant growth, production, and health, focusing particularly on rice. A variety of microbial species and taxa reside in the rhizosphere and the phyllosphere of plants and also have multiple roles as symbiotic endophytes while living within plant tissues and even cells. They alter the morphology of host plants, enhance their growth, health, and yield, and reduce their vulnerability to biotic and abiotic stresses. The findings of both agronomic and molecular analysis show ways in which microorganisms regulate the growth, physiological traits, and molecular signaling within rice plants. However, many significant scientific questions remain to be resolved. Advancements in high-throughput multi-omics technologies can be used to elucidate mechanisms involved in microbial-rice plant associations. Prospectively, the use of microbial inoculants and associated approaches offers some new, cost-effective, and more eco-friendly practices for increasing rice production.
    Matched MeSH terms: Metabolomics/methods
  3. Rapid characterisation of xanthine oxidase inhibitors from the flowers of Chrysanthemum morifolium Ramat. Using metabolomics approach
    Loh KE, Chin YS, Safinar Ismail I, Tan HY
    Phytochem Anal, 2022 Jan;33(1):12-22.
    PMID: 34000756 DOI: 10.1002/pca.3057
    INTRODUCTION: Hyperuricemia is the key risk factor for gout, in which the elevated uric acid is attributed to the oxidation of hypoxanthine and xanthine to uric acid by xanthine oxidase (XO). Adverse effects of the current treatments lead to an urgent need for safer and more effective alternative from natural resources.

    OBJECTIVE: To compare the metabolite profile of Chrysanthemum morifolium flower fraction with that of its detannified fraction in relation to XO inhibitory activity using a rapid and effective metabolomics approach.

    METHODS: Proton nuclear magnetic resonance (1 H-NMR)-based metabolomics approach coupled with multivariate data analysis was utilised to characterise the XO inhibitors related to the antioxidant properties, total phenolic, and total flavonoid contents of the C. morifolium dried flowers.

    RESULTS: The highest XO inhibitory activity, 1,1-diphenyl-2-picryl hydrazyl (DPPH) radical scavenging activity, total phenolic and flavonoid content with strong positive correlation between them were observed in the ethyl acetate (EtOAc) fraction. Detannified EtOAc showed higher XO inhibitory activity than non-detannified EtOAc fraction. A total of 17 metabolites were tentatively identified, of which three namely kaempferol, 4-hydroxybenzoic acid and apigenin, could be suggested to be responsible for the strong XO inhibitory activity. Additive interaction between 4-hydroxybenzoic acid and apigenin (or kaempferol) in XO inhibition was demonstrated in the interaction assay conducted.

    CONCLUSION: Chrysanthemum morifolium dried flower-part could be further explored as a natural XO inhibitor for its anti-hyperuricemic potential. Metabolomics approach served as an effective classification of plant metabolites responsible for XO inhibitory activity, and demonstrated that multiple active compounds can work additively in giving combined inhibitory effects.

    Matched MeSH terms: Metabolomics
  4. 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
  5. Fulltext Application of the Metabolomics Approach in Food Authentication
    Selamat J, Rozani NAA, Murugesu S
    Molecules, 2021 Dec 14;26(24).
    PMID: 34946647 DOI: 10.3390/molecules26247565
    The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.
    Matched MeSH terms: Metabolomics*
  6. Integration of environmental metabolomics and physiological approach for evaluation of saline pollution to rice plant
    Ma NL, Lam SD, Che Lah WA, Ahmad A, Rinklebe J, Sonne C, et al.
    Environ Pollut, 2021 Oct 01;286:117214.
    PMID: 33971466 DOI: 10.1016/j.envpol.2021.117214
    Salinisation of soil is associated with urban pollution, industrial development and rising sea level. Understanding how high salinity is managed at the plant cellular level is vital to increase sustainable farming output. Previous studies focus on plant stress responses under salinity tolerance. Yet, there is limited knowledge about the mechanisms involved from stress state until the recovery state; our research aims to close this gap. By using the most tolerance genotype (SS1-14) and the most susceptible genotype (SS2-18), comparative physiological, metabolome and post-harvest assessments were performed to identify the underlying mechanisms for salinity stress recovery in plant cells. The up-regulation of glutamine, asparagine and malonic acid were found in recovered-tolerant genotype, suggesting a role in the regulation of panicle branching and spikelet formation for survival. Rice could survive up to 150 mM NaCl (∼15 ds/m) with declined of production rate 5-20% ranged from tolerance to susceptible genotype. This show that rice farming may still be viable on the high saline affected area with the right selection of salt-tolerant species, including glycophytes. The salt recovery biomarkers identified in this study and the adaption underlined could be empowered to address salinity problem in rice field.
    Matched MeSH terms: Metabolomics
  7. Identification of potential serum metabolic biomarkers for patient with keratoconus using untargeted metabolomics approach
    Daphne Teh AL, Jayapalan JJ, Loke MF, Wan Abdul Kadir AJ, Subrayan V
    Exp Eye Res, 2021 10;211:108734.
    PMID: 34428458 DOI: 10.1016/j.exer.2021.108734
    This study aimed to investigate the metabolite differences between patients with keratoconus and control subjects and identify potential serum biomarkers for keratoconus using a non-targeted metabolomics approach. Venous blood samples were obtained from patients with keratoconus (n = 20) as well as from age-, gender- and race-matched control subjects (n = 20). Metabolites extracted from serum were separated and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometer. Processing of raw data and analysis of the data files was performed using Agilent Mass Hunter Qualitative software. The identified metabolites were subjected to a principal component and hierarchical cluster analysis. Appropriate statistical tests were used to analyze the metabolomic profiling data. Together, the analysis revealed that the dehydroepiandrosterone sulfate from the steroidal hormone synthesis pathway was significantly upregulated in patients with keratoconus (p 
    Matched MeSH terms: Metabolomics/methods*
  8. 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
  9. Protective effect of isosteviol sodium against LPS-induced multiple organ injury by regulating of glycerophospholipid metabolism and reducing macrophage-driven inflammation
    Wang S, Tan KS, Beng H, Liu F, Huang J, Kuai Y, et al.
    Pharmacol Res, 2021 Oct;172:105781.
    PMID: 34302975 DOI: 10.1016/j.phrs.2021.105781
    Sepsis is a severe inflammatory disorder that can lead to multiple organ injury. Isosteviol sodium (STV-Na) is a terpenoid derived from stevioside that exerts anti-inflammatory, antioxidant and antiapoptotic activities. However, the influence of STV-Na on sepsis remains unknown. Here, we assessed the potential effects of STV-Na on sepsis and multiple organ injury induced by lipopolysaccharide (LPS). We found that STV-Na increased the survival rate of mice treat with LPS, significantly improved the functions of the heart, lung, liver, and kidney, reduced the production of inflammatory cytokines and decreased macrophage infiltration. Moreover, Multiorgan metabolomics analysis demonstrated that glutathione metabolism, purine metabolism, glycerophospholipid metabolism and pantothenate and CoA biosynthesis, were significantly altered by STV-Na. This study provides novel insights into the metabolite changes of multiple organ injury in septic mice, which may help characterize the underlying mechanism and provide an improved understanding of the therapeutic effects of STV-Na on sepsis.
    Matched MeSH terms: Metabolomics
  10. 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*
  11. Metabolomic analysis reveals the valuable bioactive compounds of Ardisia elliptica
    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
  12. Fulltext 1H-NMR-Based Metabolomics: An Integrated Approach for the Detection of the Adulteration in Chicken, Chevon, Beef and Donkey Meat
    Akhtar MT, Samar M, Shami AA, Mumtaz MW, Mukhtar H, Tahir A, et al.
    Molecules, 2021 Jul 30;26(15).
    PMID: 34361796 DOI: 10.3390/molecules26154643
    Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing of high-price meat species with low-quality/-price meat. This work aimed to differentiate different meat samples on the basis of metabolites. The metabolic difference between various meat samples was investigated through Nuclear Magnetic Resonance spectroscopy coupled with multivariate data analysis approaches like principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). In total, 37 metabolites were identified in the gluteal muscle tissues of cow, goat, donkey and chicken using 1H-NMR spectroscopy. PCA was found unable to completely differentiate between meat types, whereas OPLS-DA showed an apparent separation and successfully differentiated samples from all four types of meat. Lactate, creatine, choline, acetate, leucine, isoleucine, valine, formate, carnitine, glutamate, 3-hydroxybutyrate and α-mannose were found as the major discriminating metabolites between white (chicken) and red meat (chevon, beef and donkey). However, inosine, lactate, uracil, carnosine, format, pyruvate, carnitine, creatine and acetate were found responsible for differentiating chevon, beef and donkey meat. The relative quantification of differentiating metabolites was performed using one-way ANOVA and Tukey test. Our results showed that NMR-based metabolomics is a powerful tool for the identification of novel signatures (potential biomarkers) to characterize meats from different sources and could potentially be used for quality control purposes in order to differentiate different meat types.
    Matched MeSH terms: Metabolomics/methods*
  13. Fulltext A metabolomic analysis of thiol response for standard and modified N-acetyl cysteine treatment regimens in patients with acetaminophen overdose
    Dear JW, Ng ML, Bateman DN, Leroy Sivappiragasam P, Choi H, Khoo BBJ, et al.
    Clin Transl Sci, 2021 Jul;14(4):1476-1489.
    PMID: 33742775 DOI: 10.1111/cts.13009
    N-acetylcysteine (NAC) is an antidote to prevent acetaminophen (paracetamol-APAP)-induced acute liver injury (ALI). The 3-bag licensed 20.25 h standard regimen, and a 12 h modified regimen, are used to treat APAP overdose. This study evaluated the redox thiol response and APAP metabolites, in patients with a single APAP overdose treated with either the 20.25 h standard or 12 h modified regimen. We used liquid chromatography tandem mass spectrometry to quantify clinically important oxidative stress biomarkers and APAP metabolites in plasma samples from 45 patients who participated in a randomized controlled trial (SNAP trial). We investigated the time course response of plasma metabolites at predose, 12 h, and 20.25 h post-start of NAC infusion. The results showed that the 12 h modified regimen resulted in a significant elevation of plasma NAC and cysteine concentrations at 12 h post-infusion. We found no significant alteration in the metabolism of APAP, mitochondrial, amino acids, and other thiol biomarkers with the two regimens. We examined APAP and purine metabolism in overdose patients who developed ALI. We showed the major APAP-metabolites and xanthine were significantly higher in patients with ALI. These biomarkers correlated well with alanine aminotransferase activity at admission. Receiver operating characteristic analysis showed that at admission, plasma APAP-metabolites and xanthine concentrations were predictive for ALI. In conclusion, a significantly higher redox thiol response with the modified NAC regimen at 12 h postdose suggests this regimen may produce greater antioxidant efficacy. At baseline, plasma APAP and purine metabolites may be useful biomarkers for early prediction of APAP-induced ALI.
    Matched MeSH terms: Metabolomics
  14. 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
  15. Fulltext Metabolome analysis and chemical profiling of Indonesian royal jellies as the raw material for cosmetic and bio-supplement products
    Sari E, Mahira KF, Patel DN, Chua LS, Pratami DK, Sahlan M
    Heliyon, 2021 May;7(5):e06912.
    PMID: 34013079 DOI: 10.1016/j.heliyon.2021.e06912
    Royal jellies (RJs) possess moisturizing, emulsifying, and stabilizing properties, and several pharmacological activities have also been found to be present, which make them an ideal component for cosmetic and skin care products. However, despite the abundant efficacies, there is a lack of studies that explore the chemical composition of RJ using metabolome analysis. Furthermore, an evaluation of the chemical composition of Indonesian RJs collected from different regions has yet to be carried out. Therefore, the main objective of this study was to identify any differences in the chemical composition of such RJs. Chemical profiling was also carried out to enable more targeted utilization based on the actual compositions. Chemical profiling is also important given the rich Indonesian biodiversity and the high dependence of the RJ compositions on the botanical source. In this research, ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was used as part of an untargeted metabolomics approach. From the chemical profiling, >30 compounds were identified across four RJ samples. The major constituents of the samples were found to be oligosaccharides, fatty acids, and adenosine monophosphate derivatives. Meanwhile, sucrose and planteose were found to be highest in the samples from Banjarnegara and Kediri, whereas dimethyloctanoic acid was found to be unique to the sample from Banjarnegara. It was also discovered that the RJs from Demak and Tuban contained more organic fatty acids and oligosaccharides than the other samples. Although the sample from Demak demonstrated good potential for use in the cosmetic, skin care, and bio-supplement industries, the higher abundance of fatty acids and oligosaccharides in the sample from Tuban indicated that it is perhaps the most suitable RJ for use in this field.
    Matched MeSH terms: Metabolomics
  16. 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
  17. Metabonomics reveals an alleviation of fitness cost in resistant E. coli competing against susceptible E. coli at sub-MIC doxycycline
    Wen X, Cao J, Mi J, Huang J, Liang J, Wang Y, et al.
    J Hazard Mater, 2021 03 05;405:124215.
    PMID: 33109407 DOI: 10.1016/j.jhazmat.2020.124215
    High concentrations of antibiotics may induce bacterial resistance mutations and further lead to fitness costs by reducing growth of resistant bacteria. However, antibiotic concentrations faced by bacteria are usually low in common environments, which leads to questions about how resistant bacteria with fitness costs regulate metabolism to coexist or compete with susceptible bacteria during sublethal challenge. Our study revealed that a low proportion (< 15%) of resistant bacteria coexisted with susceptible bacteria due to the fitness cost without doxycycline. However, the cost for the resistant strain decreased at a doxycycline concentration of 1 mg/L and even disappeared when the doxycycline concentration was 2 mg/L. Metabonomics analysis revealed that bypass carbon metabolism and biosynthesis of secondary metabolites were the primary metabolic pathways enriching various upregulated metabolites in resistant bacteria without doxycycline. Moreover, the alleviation of fitness cost for resistant bacteria competed with susceptible bacteria at 1 mg/L doxycycline was correlated with the downregulation of the biomarkers pyruvate and pilocarpine. Our study offered new insight into the metabolic mechanisms by which the fitness cost of resistant mutants was reduced at doxycycline concentrations as low as 1 mg/L and identified various potential metabolites to limit the spread of antimicrobial resistance in the environment.
    Matched MeSH terms: Metabolomics
  18. Fulltext Biodiscovery of Potential Antibacterial Diagnostic Metabolites from the Endolichenic Fungus Xylaria venustula Using LC-MS-Based Metabolomics
    Santiago KAA, Edrada-Ebel R, Dela Cruz TEE, Cheow YL, Ting ASY
    Biology (Basel), 2021 Mar 04;10(3).
    PMID: 33806264 DOI: 10.3390/biology10030191
    Three species of the lichen Usnea (U. baileyi (Stirt.) Zahlbr., U. bismolliuscula Zahlbr. and U. pectinata Stirt.) and nine associated endolichenic fungi (ELF) were evaluated using a metabolomics approach. All investigated lichen crude extracts afforded antibacterial activity against Staphylococcus aureus (minimum inhibitory concentration (MIC): 0.0625 mg/mL), but none was observed against Escherichia coli, while the ELF extract Xylaria venustula was found to be the most active against S. aureus (MIC: 2.5 mg/mL) and E. coli (MIC: 5 mg/mL). X. venustula was fractionated and tested for to determine its antibacterial activity. Fractions XvFr1 to 5 displayed bioactivities against both test bacteria. Selected crude extracts and fractions were subjected to metabolomics analyses using high-resolution LC-MS. Multivariate analyses showed the presence of five secondary metabolites unique to bioactive fractions XvFr1 to 3, which were identified as responsible for the antibacterial activity of X. venustula. The p-values of these metabolites were at the margin of significance level, with methyl xylariate C (P_60) being the most significant. However, their high variable importance of projection (VIP) scores (>5) suggest these metabolites are potential diagnostic metabolites for X. venustula for "dual" bioactivity against S. aureus and E. coli. The statistical models also showed the distinctiveness of metabolites produced by lichens and ELF, thus supporting our hypotheses of ELF functionality similar to plant endophytes.
    Matched MeSH terms: Metabolomics
  19. Fulltext Complementary Analytical Platforms of NMR Spectroscopy and LCMS Analysis in the Metabolite Profiling of Isochrysis galbana
    Bustamam MSA, Pantami HA, Azizan A, Shaari K, Min CC, Abas F, et al.
    Mar Drugs, 2021 Mar 02;19(3).
    PMID: 33801258 DOI: 10.3390/md19030139
    This study was designed to profile the metabolites of Isochrysis galbana, an indigenous and less explored microalgae species. 1H Nuclear Magnetic Resonance (NMR) spectroscopy and Liquid Chromatography-Mass Spectrometry (LCMS) were used to establish the metabolite profiles of five different extracts of this microalga, which are hexane (Hex), ethyl acetate (EtOAc), absolute ethanol (EtOH), EtOH:water 1:1 (AqE), and 100% water (Aq). Partial least square discriminant analysis (PLS-DA) of the generated profiles revealed that EtOAc and Aq extracts contain a diverse range of metabolites as compared to the other extracts with a total of twenty-one metabolites, comprising carotenoids, polyunsaturated fatty acids, and amino acids, that were putatively identified from the NMR spectra. Meanwhile, thirty-two metabolites were successfully annotated from the LCMS/MS data, ten of which (palmitic acid, oleic acid, α-linolenic acid, arachidic acid, cholesterol, DHA, DPA, fucoxanthin, astaxanthin, and pheophytin) were similar to those present in the NMR profile. Another eleven glycerophospholipids were discovered using MS/MS-based molecular network (MN) platform. The results of this study, besides providing a better understanding of I.galbana's chemical make-up, will be of importance in exploring this species potential as a feed ingredient in the aquaculture industry.
    Matched MeSH terms: Metabolomics*
  20. Gut Microbial Ecosystem in Parkinson Disease: New Clinicobiological Insights from Multi-Omics
    Tan AH, Chong CW, Lim SY, Yap IKS, Teh CSJ, Loke MF, et al.
    Ann Neurol, 2021 03;89(3):546-559.
    PMID: 33274480 DOI: 10.1002/ana.25982
    OBJECTIVE: Gut microbiome alterations in Parkinson disease (PD) have been reported repeatedly, but their functional relevance remains unclear. Fecal metabolomics, which provide a functional readout of microbial activity, have scarcely been investigated. We investigated fecal microbiome and metabolome alterations in PD, and their clinical relevance.

    METHODS: Two hundred subjects (104 patients, 96 controls) underwent extensive clinical phenotyping. Stool samples were analyzed using 16S rRNA gene sequencing. Fecal metabolomics were performed using two platforms, nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry.

    RESULTS: Fecal microbiome and metabolome composition in PD was significantly different from controls, with the largest effect size seen in NMR-based metabolome. Microbiome and NMR-based metabolome compositional differences remained significant after comprehensive confounder analyses. Differentially abundant fecal metabolite features and predicted functional changes in PD versus controls included bioactive molecules with putative neuroprotective effects (eg, short chain fatty acids [SCFAs], ubiquinones, and salicylate) and other compounds increasingly implicated in neurodegeneration (eg, ceramides, sphingosine, and trimethylamine N-oxide). In the PD group, cognitive impairment, low body mass index (BMI), frailty, constipation, and low physical activity were associated with fecal metabolome compositional differences. Notably, low SCFAs in PD were significantly associated with poorer cognition and low BMI. Lower butyrate levels correlated with worse postural instability-gait disorder scores.

    INTERPRETATION: Gut microbial function is altered in PD, characterized by differentially abundant metabolic features that provide important biological insights into gut-brain pathophysiology. Their clinical relevance further supports a role for microbial metabolites as potential targets for the development of new biomarkers and therapies in PD. ANN NEUROL 2021;89:546-559.

    Matched MeSH terms: Metabolomics*
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