Displaying publications 21 - 40 of 171 in total

Abstract:
Sort:
  1. Windarsih A, Bakar NKA, Dachriyanus, Yuliana ND, Riswanto FDO, Rohman A
    Molecules, 2023 Aug 09;28(16).
    PMID: 37630216 DOI: 10.3390/molecules28165964
    Beef sausage (BS) is one of the most favored meat products due to its nutrition and good taste. However, for economic purposes, BS is often adulterated with pork by unethical players. Pork consumption is strictly prohibited for religions including Islam and Judaism. Therefore, advanced detection methods are highly required to warrant the halal authenticity of BS. This research aimed to develop a liquid chromatography-high-resolution mass spectrometry (LC-HRMS) method to determine the halal authenticity of BS using an untargeted metabolomics approach. LC-HRMS was capable of detecting various metabolites in BS and BS containing pork. The presence of pork in BS could be differentiated using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) with high accuracy. PLS-DA perfectly classified authentic BS and BS containing pork in all concentration levels of pork with R2X = (0.821), R2Y(= 0.984), and Q2 = (0.795). The level of pork in BS was successfully predicted through partial least squares (PLS) and orthogonal PLS (OPLS) chemometrics. Both models gave high R2 (>0.99) actual and predicted values as well as few errors, indicating good accuracy and precision. Identification of discriminating metabolites' potential as biomarker candidates through variable importance for projections (VIP) value revealed metabolites of 2-arachidonyl-sn-glycero-3-phosphoethanolamine, 3-hydroxyoctanoylcarnitine, 8Z,11Z,14Z-eicosatrienoic acid, D-(+)-galactose, oleamide, 3-hydroxyhexadecanoylcarnitine, arachidonic acid, and α-eleostearic acid as good indicators to detect pork. It can be concluded that LC-HRMS metabolomics combined with PCA, PLS-DA, PLS, and OPLS was successfully used to detect pork adulteration in beef sausages. The results imply that LC-HRMS untargeted metabolomics in combination with chemometrics is a promising alternative as an analytical technique to detect pork in sausage products. Further analysis of larger samples is required to warrant the reproducibility.
    Matched MeSH terms: Metabolomics
  2. Windarsih A, Bakar NKA, Rohman A, Erwanto Y
    Anal Sci, 2024 Mar;40(3):385-397.
    PMID: 38095741 DOI: 10.1007/s44211-023-00470-x
    Due to the different price and high quality, halal meat such as beef can be adulterated with non-halal meat with low price to get an economical price. The objective of this research was to develop an analytical method for halal authentication testing of beef meatballs (BM) from dog meat (DM) using a non-targeted metabolomics approach employing liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics. The differentiation of authentic BM from that adulterated with DM was successfully performed using partial least square-discriminant analysis (PLS-DA) with high accuracy (R2X = 0.980, and R2Y = 0.980) and good predictivity (Q2 = 0.517). In addition, partial least square (PLS) and orthogonal PLS (OPLS) were successfully used to predict the DM added (% w/w) in BM with high accuracy (R2 > 0.990). A number of metabolites, potential for biomarker candidates, were identified to differentiate BM and that adulterated with DM. It showed that the combination of a non-targeted LC-HRMS Orbitrap metabolomics and chemometrics could detect up to 0.1% w/w of DM adulteration. The developed method was successfully applied for analysis of commercial meatball samples (n = 28). Moreover, pathway analysis revealed that beta-alanine, histidine, and ether lipid metabolism were significantly affected by dog meat adulteration. In summary, this developed method has great potential to be developed and used as an alternative method for analysis of non-halal meats in halal meat products.
    Matched MeSH terms: Metabolomics
  3. 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
  4. Wei J, Ren W, Wang L, Liu M, Tian X, Ding G, et al.
    J Sci Food Agric, 2020 Dec;100(15):5627-5636.
    PMID: 32712996 DOI: 10.1002/jsfa.10690
    BACKGROUND: Serofluid dish, a traditional Chinese fermented food, possesses unique flavors and health beneficial effects. These properties are likely due to the sophisticated metabolic networks during fermentation, which are mainly driven by microbiota. However, the exact roles of metabolic pathways and the microbial community during this process remain equivocal.

    RESULTS: Here, we investigated the microbial dynamics by next-generation sequencing, and outlined a differential non-targeted metabolite profiling in the process of serofluid dish fermentation using the method of hydrophilic interaction liquid chromatography column with ultra-high-performance liquid chromatography-quadruple time-of-flight mass spectrometry. Lactobacillus was the leading genus of bacteria, while Pichia and Issatchenkia were the dominant fungi. They all accumulated during fermentation. In total, 218 differential metabolites were identified, of which organic acids, amino acids, sugar and sugar alcohols, fatty acids, and esters comprised the majority. The constructed metabolic network showed that tricarboxylic acid cycle, urea cycle, sugar metabolism, amino acids metabolism, choline metabolism, and flavonoid metabolism were regulated by the fermentation. Furthermore, correlation analysis revealed that the leading fungi, Pichia and Issatchenkia, were linked to organic acids, amino acid and sugar metabolism, flavonoids, and several other flavor and functional components. Antibacterial tests indicated the antibacterial effect of serofluid soup against Salmonella and Staphylococcus.

    CONCLUSION: This work provides new insights into the complex microbial and metabolic networks during serofluid dish fermentation, and a theoretical basis for the optimization of its industrial production. © 2020 Society of Chemical Industry.

    Matched MeSH terms: Metabolomics
  5. Watanabe M, Roth TL, Bauer SJ, Lane A, Romick-Rosendale LE
    PLoS One, 2016;11(5):e0156318.
    PMID: 27232336 DOI: 10.1371/journal.pone.0156318
    A variety of wildlife species maintained in captivity are susceptible to iron storage disease (ISD), or hemochromatosis, a disease resulting from the deposition of excess iron into insoluble iron clusters in soft tissue. Sumatran rhinoceros (Dicerorhinus sumatrensis) is one of the rhinoceros species that has evolutionarily adapted to a low-iron diet and is susceptible to iron overload. Hemosiderosis is reported at necropsy in many African black and Sumatran rhinoceroses but only a small number of animals reportedly die from hemochromatosis. The underlying cause and reasons for differences in susceptibility to hemochromatosis within the taxon remains unclear. Although serum ferritin concentrations have been useful in monitoring the progression of ISD in many species, there is some question regarding their value in diagnosing hemochromatosis in the Sumatran rhino. To investigate the metabolic changes during the development of hemochromatosis and possibly increase our understanding of its progression and individual susceptibility differences, the serum metabolome from a Sumatran rhinoceros was investigated by nuclear magnetic resonance (NMR)-based metabolomics. The study involved samples from female rhinoceros at the Cincinnati Zoo (n = 3), including two animals that died from liver failure caused by ISD, and the Sungai Dusun Rhinoceros Conservation Centre in Peninsular Malaysia (n = 4). Principal component analysis was performed to visually and statistically compare the metabolic profiles of the healthy animals. The results indicated that significant differences were present between the animals at the zoo and the animals in the conservation center. A comparison of the 43 serum metabolomes of three zoo rhinoceros showed two distinct groupings, healthy (n = 30) and unhealthy (n = 13). A total of eighteen altered metabolites were identified in healthy versus unhealthy samples. Results strongly suggest that NMR-based metabolomics is a valuable tool for animal health monitoring and may provide insight into the progression of this and other insidious diseases.
    Matched MeSH terms: Metabolomics*
  6. Watanabe H, Ng CH, Limviphuvadh V, Suzuki S, Yamada T
    PeerJ, 2020;8:e9579.
    PMID: 32821539 DOI: 10.7717/peerj.9579
    Coffee beans derived from feces of the civet cat are used to brew coffee known as kopi luwak (the Indonesian words for coffee and palm civet, respectively), which is one of the most expensive coffees in the world owing to its limited supply and strong market demand. Recent metabolomics studies have revealed that kopi luwak metabolites differ from metabolites found in other coffee beans. To produce kopi luwak, coffee beans are first eaten by civet cats. It has been proposed that fermentation inside the civet cat digestive tract may contribute to the distinctively smooth flavor of kopi luwak, but the biological basis has not been determined. Therefore, we characterized the microbiome of civet cat feces using 16S rRNA gene sequences to determine the bacterial taxa that may influence fermentation processes related to kopi luwak. Moreover, we compared this fecal microbiome with that of 14 other animals, revealing that Gluconobacter is a genus that is, uniquely found in feces of the civet cat. We also found that Gluconobacter species have a large number of cell motility genes, which may encode flagellar proteins allowing colonization of the civet gut. In addition, genes encoding enzymes involved in the metabolism of hydrogen sulfide and sulfur-containing amino acids were over-represented in Gluconobacter. These genes may contribute to the fermentation of coffee beans in the digestive tract of civet cats.
    Matched MeSH terms: Metabolomics
  7. 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
  8. 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
  9. Wang J, Tao C, Xu G, Ling J, Tong J, Goh BH, et al.
    Mol Omics, 2023 Dec 04;19(10):769-786.
    PMID: 37498608 DOI: 10.1039/d3mo00029j
    Chinese herbal medicine (CHM) exhibits a broad spectrum of clinical applications and demonstrates favorable therapeutic efficacy. Nonetheless, elucidating the underlying mechanism of action (MOA) of CHM in disease treatment remains a formidable task due to its inherent characteristics of multi-level, multi-linked, and multi-dimensional non-linear synergistic actions. In recent years, the concept of a Quality marker (Q-marker) proposed by Liu et al. has significantly contributed to the monitoring and evaluation of CHM products, thereby fostering the advancement of CHM research. Within this study, a Q-marker screening strategy for CHM formulas has been introduced, particularly emphasising efficacy and biological activities, integrating absorption, distribution, metabolism, and excretion (ADME) studies, systems biology, and experimental verification. As an illustrative case, the Q-marker screening of Qianghuo Shengshi decoction (QHSSD) for treating rheumatoid arthritis (RA) has been conducted. Consequently, from a pool of 159 compounds within QHSSD, five Q-markers exhibiting significant in vitro anti-inflammatory effects have been identified. These Q-markers encompass notopterol, isoliquiritin, imperatorin, cimifugin, and glycyrrhizic acid. Furthermore, by employing an integrated analysis of network pharmacology and metabolomics, several instructive insights into pharmacological mechanisms have been gleaned. This includes the identification of key targets and pathways through which QHSSD exerts its crucial roles in the treatment of RA. Notably, the inhibitory effect of QHSSD on AKT1 and MAPK3 activation has been validated through western blot analysis, underscoring its potential to mitigate RA-related inflammatory responses. In summary, this research demonstrates the proposed strategy's feasibility and provides a practical reference model for the systematic investigation of CHM formulas.
    Matched MeSH terms: Metabolomics
  10. Veeramohan R, Azizan KA, Aizat WM, Goh HH, Mansor SM, Yusof NSM, et al.
    Data Brief, 2018 Jun;18:1212-1216.
    PMID: 29900296 DOI: 10.1016/j.dib.2018.04.001
    Mitragyna speciosa is a psychoactive plant known as "ketum" in Malaysia and "kratom" in Thailand. This plant is distinctly known to produce two important alkaloids, namely mitragynine (MG) and 7-hydroxymitragynine (7-OH-MG) that can bind to opioid receptors [1]. MG was reported to exhibit antidepressant properties in animal studies [2]. These compounds were also proposed to have the potential to replace opioid analgesics with much lower risks of side effects [3]. To date, there are only over 40 metabolites identified in M. speciosa [4,5]. To obtain a more complete profile of secondary metabolites in ketum, we performed metabolomics study using mature leaves of the green M. speciosa variety. The leaf samples were extracted using methanol prior to liquid chromatography-electrospray ionization-time of flight-mass spectrometry (LC-ESI-TOF-MS) analysis. This data can be useful to for the identification of unknown metabolites that are associated with alkaloid biosynthesis pathway in M. speciosa.
    Matched MeSH terms: Metabolomics
  11. Veeramohan R, Zamani AI, Azizan KA, Goh HH, Aizat WM, Razak MFA, et al.
    PLoS One, 2023;18(3):e0283147.
    PMID: 36943850 DOI: 10.1371/journal.pone.0283147
    The fresh leaves of Mitragyna speciosa (Korth.) Havil. have been traditionally consumed for centuries in Southeast Asia for its healing properties. Although the alkaloids of M. speciosa have been studied since the 1920s, comparative and systematic studies of metabolite composition based on different leaf maturity levels are still lacking. This study assessed the secondary metabolite composition in two different leaf stages (young and mature) of M. speciosa, using an untargeted liquid chromatography-electrospray ionisation-time-of-flight-mass spectrometry (LC-ESI-TOF-MS) metabolite profiling. The results revealed 86 putatively annotated metabolite features (RT:m/z value) comprising 63 alkaloids, 10 flavonoids, 6 terpenoids, 3 phenylpropanoids, and 1 of each carboxylic acid, glucoside, phenol, and phenolic aldehyde. The alkaloid features were further categorised into 14 subclasses, i.e., the most abundant class of secondary metabolites identified. As per previous reports, indole alkaloids are the most abundant alkaloid subclass in M. speciosa. The result of multivariate analysis (MVA) using principal component analysis (PCA) showed a clear separation of 92.8% between the young and mature leaf samples, indicating a high variance in metabolite levels between them. Akuammidine, alstonine, tryptamine, and yohimbine were tentatively identified among the many new alkaloids reported in this study, depicting the diverse biological activities of M. speciosa. Besides delving into the knowledge of metabolite distribution in different leaf stages, these findings have extended the current alkaloid repository of M. speciosa for a better understanding of its pharmaceutical potential.
    Matched MeSH terms: Metabolomics
  12. Teh HF, Neoh BK, Hong MP, Low JY, Ng TL, Ithnin N, et al.
    PLoS One, 2013;8(4):e61344.
    PMID: 23593468 DOI: 10.1371/journal.pone.0061344
    To better understand lipid biosynthesis in oil palm mesocarp, in particular the differences in gene regulation leading to and including de novo fatty acid biosynthesis, a multi-platform metabolomics technology was used to profile mesocarp metabolites during six critical stages of fruit development in comparatively high- and low-yielding oil palm populations. Significantly higher amino acid levels preceding lipid biosynthesis and nucleosides during lipid biosynthesis were observed in a higher yielding commercial palm population. Levels of metabolites involved in glycolysis revealed interesting divergence of flux towards glycerol-3-phosphate, while carbon utilization differences in the TCA cycle were proven by an increase in malic acid/citric acid ratio. Apart from insights into the regulation of enhanced lipid production in oil palm, these results provide potentially useful metabolite yield markers and genes of interest for use in breeding programmes.
    Matched MeSH terms: Metabolomics/methods
  13. Tan YH, Lim PE, Beardall J, Poong SW, Phang SM
    Aquat Toxicol, 2019 Dec;217:105349.
    PMID: 31734626 DOI: 10.1016/j.aquatox.2019.105349
    Ocean acidification, due to increased levels of anthropogenic carbon dioxide, is known to affect the physiology and growth of marine phytoplankton, especially in polar regions. However, the effect of acidification or carbonation on cellular metabolism in polar marine phytoplankton still remains an open question. There is some evidence that small chlorophytes may benefit more than other taxa of phytoplankton. To understand further how green polar picoplankton could acclimate to high oceanic CO2, studies were conducted on an Antarctic Chlorella sp. Chlorella sp. maintained its growth rate (∼0.180 d-1), photosynthetic quantum yield (Fv/Fm = ∼0.69) and chlorophyll a (0.145 fg cell-1) and carotenoid (0.06 fg cell-1) contents under high CO2, while maximum rates of electron transport decreased and non-photochemical quenching increased under elevated CO2. GCMS-based metabolomic analysis reveal that this polar Chlorella strain modulated the levels of metabolites associated with energy, amino acid, fatty acid and carbohydrate production, which could favour its survival in an increasingly acidified ocean.
    Matched MeSH terms: Metabolomics
  14. Tan DC, Kassim NK, Ismail IS, Hamid M, Ahamad Bustamam MS
    Biomed Res Int, 2019;2019:7603125.
    PMID: 31275982 DOI: 10.1155/2019/7603125
    Paederia foetida L. (Rubiaceae) is a climber which is widely distributed in Asian countries including Malaysia. The plant is traditionally used to treat various diseases including diabetes. This study is to evaluate the enzymatic inhibition activity of Paederia foetida twigs extracts and to identify the metabolites responsible for the bioactivity by gas chromatography-mass spectrometry (GC-MS) metabolomics profiling. Three different twig extracts, namely, hexane (PFH), chloroform (PFC), and methanol (PFM), were submerged for their α-amylase and α-glucosidase inhibition potential in 5 replicates for each. Results obtained from the loading column scatter plot of orthogonal partial least square (OPLS) model revealed the presence of 12 bioactive compounds, namely, dl-α-tocopherol, n-hexadecanoic acid, 2-hexyl-1-decanol, stigmastanol, 2-nonadecanone, cholest-8(14)-en-3-ol, 4,4-dimethyl-, (3β,5α)-, stigmast-4-en-3-one, stigmasterol, 1-ethyl-1-tetradecyloxy-1-silacyclohexane, ɣ-sitosterol, stigmast-7-en-3-ol, (3β,5α,24S)-, and α-monostearin. In silico molecular docking was carried out using the crystal structure α-amylase (PDB ID: 4W93) and α-glucosidase (PDB ID: 3WY1). α-Amylase-n-hexadecanoic acid exhibited the lowest binding energy of -2.28 kcal/mol with two hydrogen bonds residue, namely, LYS178 and TYR174, along with hydrophobic interactions involving PRO140, TRP134, SER132, ASP135, and LYS172. The binding interactions of α-glucosidase-n-hexadecanoic acid complex ligand also showed the lowest binding energy among 5 major compounds with the energy value of -4.04 kcal/mol. The complex consists of one hydrogen bond interacting residue, ARG437, and hydrophobic interactions with ALA444, ASP141, GLN438, GLU432, GLY374, LEU373, LEU433, LYS352, PRO347, THR445, HIS348, and PRO351. The study provides informative data on the potential antidiabetic inhibitors identified in Paederia foetida twigs, indicating the plant has the therapeutic effect properties to manage diabetes.
    Matched MeSH terms: Metabolomics*
  15. Tan CX, Chong GH, Hamzah H, Ghazali HM
    Phytother Res, 2018 Nov;32(11):2264-2274.
    PMID: 30051518 DOI: 10.1002/ptr.6164
    Hypercholesterolemia is a major risk factor for the initiation and development of nonalcoholic fatty liver disease and atherosclerosis. The present study evaluated the hypocholesterolemic effect of virgin avocado oil (VAO) using urinary metabolomic method. Male Sprague-Dawley rats were fed high-cholesterol diet for four weeks to induce hypercholesterolemia. After confirming the establishment of hypercholesterolemia model, the VAO (450 and 900 mg·kg-1 ·day-1 ) and simvastatin (10 mg·kg-1 ·day-1 ) were given orally while maintaining the high-cholesterol diet for another four weeks. Assessment of urinary metabolomics using NMR revealed that VAO treatment could partially recover the metabolism dysfunction induced by hypercholesterolemia mainly via lipid, energy, amino acid, and gut microbiota metabolism.
    Matched MeSH terms: Metabolomics
  16. 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*
  17. Tajidin NE, Shaari K, Maulidiani M, Salleh NS, Ketaren BR, Mohamad M
    Sci Rep, 2019 11 14;9(1):16766.
    PMID: 31727911 DOI: 10.1038/s41598-019-52905-z
    Andrographis paniculata (Burm. F.) Nees. is considered as the herb of the future due to its precious chemical compounds, andrographolide (ANDRO), neoandrographolide (NAG) and 14-deoxyandrographolide (DAG). This study aims to profile the metabolites in young and mature leaf at six different harvest ages using 1HNMR-based metabolomics combined with multivariate data analysis. Principal component analysis (PCA) indicated noticeable and clear discrimination between young and mature leaves. A comparison of the leaves stage indicated that young leaves were separated from mature leaves due to its larger quantity of ANDRO, NAG, DAG, glucose and sucrose. These similar metabolites are also responsible for the PCA separation into five clusters representing the harvest age at 14, 16, 18, 20, 22 weeks of leaves extract. Loading plots revealed that most of the ANDRO and NAG signals were present when the plant reached at the pre-flowering stage or 18 weeks after sowing (WAS). As a conclusion, A. paniculata young leaves at pre-flowering harvest age were found to be richer in ANDRO, NAG and DAG compared to mature leaves while glucose and choline increased with harvest age. Therefore, young leaves of A. paniculata should be harvested at 18 WAS in order to produce superior quality plant extracts for further applications by the herbal, nutraceutical and pharmaceutical industries.
    Matched MeSH terms: Metabolomics/methods*
  18. Stepien M, Keski-Rahkonen P, Kiss A, Robinot N, Duarte-Salles T, Murphy N, et al.
    Int J Cancer, 2021 Feb 01;148(3):609-625.
    PMID: 32734650 DOI: 10.1002/ijc.33236
    Hepatocellular carcinoma (HCC) development entails changes in liver metabolism. Current knowledge on metabolic perturbations in HCC is derived mostly from case-control designs, with sparse information from prospective cohorts. Our objective was to apply comprehensive metabolite profiling to detect metabolites whose serum concentrations are associated with HCC development, using biological samples from within the prospective European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (>520 000 participants), where we identified 129 HCC cases matched 1:1 to controls. We conducted high-resolution untargeted liquid chromatography-mass spectrometry-based metabolomics on serum samples collected at recruitment prior to cancer diagnosis. Multivariable conditional logistic regression was applied controlling for dietary habits, alcohol consumption, smoking, body size, hepatitis infection and liver dysfunction. Corrections for multiple comparisons were applied. Of 9206 molecular features detected, 220 discriminated HCC cases from controls. Detailed feature annotation revealed 92 metabolites associated with HCC risk, of which 14 were unambiguously identified using pure reference standards. Positive HCC-risk associations were observed for N1-acetylspermidine, isatin, p-hydroxyphenyllactic acid, tyrosine, sphingosine, l,l-cyclo(leucylprolyl), glycochenodeoxycholic acid, glycocholic acid and 7-methylguanine. Inverse risk associations were observed for retinol, dehydroepiandrosterone sulfate, glycerophosphocholine, γ-carboxyethyl hydroxychroman and creatine. Discernible differences for these metabolites were observed between cases and controls up to 10 years prior to diagnosis. Our observations highlight the diversity of metabolic perturbations involved in HCC development and replicate previous observations (metabolism of bile acids, amino acids and phospholipids) made in Asian and Scandinavian populations. These findings emphasize the role of metabolic pathways associated with steroid metabolism and immunity and specific dietary and environmental exposures in HCC development.
    Matched MeSH terms: Metabolomics/methods*
  19. 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
  20. Shen G, Huang Y, Dong J, Wang X, Cheng KK, Feng J, et al.
    J Agric Food Chem, 2018 Jan 10;66(1):368-377.
    PMID: 29215281 DOI: 10.1021/acs.jafc.7b03182
    Taurine is indispensable in aquatic diets that are based solely on plant protein, and it promotes growth of many fish species. However, the physiological and metabolome effects of taurine on fish have not been well described. In this study, 1H NMR-based metabolomics approaches were applied to investigate the metabolite variations in Nile tilapia (Oreochromis nilotictus) muscle in order to visualize the metabolic trajectory and reveal the possible mechanisms of metabolic effects of dietary taurine supplementation on tilapia growth. After extraction using aqueous and organic solvents, 19 taurine-induced metabolic changes were evaluated in our study. The metabolic changes were characterized by differences in carbohydrate, amino acid, lipid, and nucleotide contents. The results indicate that taurine supplementation could significantly regulate the physiological state of fish and promote growth and development. These results provide a basis for understanding the mechanism of dietary taurine supplementation in fish feeding. 1H NMR spectroscopy, coupled with multivariate pattern recognition technologies, is an efficient and useful tool to map the fish metabolome and identify metabolic responses to different dietary nutrients in aquaculture.
    Matched MeSH terms: Metabolomics/methods*
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links