A Metabolomic Approach to Beer Characterization.
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ABSTRACT:
SUBMITTER: Cavallini N
PROVIDER: S-EPMC7962951 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A clinoptilolite-rich natural zeolite was tested as a substitute for kieselguhr as a filtering material to eliminate ingredients that cause beer haze formation. Two-grain sizes of micronized natural zeolite were thermally activated to 400 °C, to enhance its adsorption performance and remove the impurities adsorbed in the microporous system of zeolites, followed by their physicochemical characterization. The activated zeolites mixed with four commercial filter aids in different ratios were used for beer filtration at the pilot scale. Most of the physicochemical and sensory characteristics of beers filtered with commercial filter aids and with zeolites were similar. Using zeolite in filtering mixtures significantly reduces the number of microorganisms present in the filtered beer, which can eliminate the necessity of beer sterilization after filtration. The results evidenced that activated natural zeolites, which are cheap materials, are promising candidates as filter aids and can replace kieselguhr without producing any degradation of the beer filtration process.
| S-EPMC10559772 | biostudies-literature
Project description:BACKGROUND: Metabolites are not only the catalytic products of enzymatic reactions but also the active regulators or the ultimate phenotype of metabolic homeostasis in highly complex cellular processes. The modes of regulation at the metabolome level can be revealed by metabolic networks. We investigated the metabolic network between wild-type and 2 mutant (methionine-over accumulation 1 [mto1] and transparent testa4 [tt4]) plants regarding the alteration of metabolite accumulation in Arabidopsis thaliana. RESULTS: In the GC-TOF/MS analysis, we acquired quantitative information regarding over 170 metabolites, which has been analyzed by a novel score (ZMC, z-score of metabolite correlation) describing a characteristic metabolite in terms of correlation. Although the 2 mutants revealed no apparent morphological abnormalities, the overall correlation values in mto1 were much lower than those of the wild-type and tt4 plants, indicating the loss of overall network stability due to the uncontrolled accumulation of methionine. In the tt4 mutant, a new correlation between malate and sinapate was observed although the levels of malate, sinapate, and sinapoylmalate remain unchanged, suggesting an adaptive reconfiguration of the network. Gene-expression correlations presumably responsible for these metabolic networks were determined using the metabolite correlations as clues. CONCLUSION: Two Arabidopsis mutants, mto1 and tt4, exhibited the following changes in entire metabolome networks: the overall loss of metabolic stability (mto1) or the generation of a metabolic network of a backup pathway for the lost physiological functions (tt4). The expansion of metabolite correlation to gene-expression correlation provides detailed insights into the systemic understanding of the plant cellular process regarding metabolome and transcriptome.
| S-EPMC2233643 | biostudies-literature
Project description:The dynamics of the Saccharomyces carlsbergensis brewing yeast transcriptome during a production scale lager beer fermentation. The transcriptome of a lager brewing yeast (Saccharomyces carlsbergensis, syn. of S. pastorianus), was analysed at 12 different time points spanning a production-scale lager beer fermentation. Generally, the average expression rapidly increased and had a maximum value on day 2, then decreased as the sugar got consumed. Especially genes involved in protein and lipid biosynthesis or glycolysis were highly expressed during the beginning of the fermentation. Similarities as well as significant differences in expression profiles could be observed when comparing to a previous transcriptome analysis of a laboratory yeast grown in YPD. The regional distribution of various expression levels on the chromosomes appeared to be random or near-random and no reduction in expression near telomeres was observed. Keywords: time-course
2002-09-09 | GSE79 | GEO
Project description:A moderate alcohol consumption is demonstrated to exert a protective action in terms of cardiovascular risk. Although this property seems not to be beverage-specific, the various composition of alcoholic compounds could mediate peculiar effects in vivo. The aim of this study was to evaluate potential beer-mediated effects on the cardiovascular health in humans, using a meta-analytic approach (trial registration number: CRD42018118387). The literature search, comprising all English articles published until November, 30th 2019 in EMBASE, PubMed and Cochrane database included all controlled clinical trials evaluating the cardiovascular effects of beer assumption compared to alcohol-free beer, water, abstinence or placebo. Both sexes and all beer preparations were considered eligible. Outcome parameters were those entering in the cardiovascular risk charts and those related to endothelial dysfunction. Twenty-six trials were included in the analysis. Total cholesterol was significantly higher in beer drinkers compared to controls (14 studies, 3.52 mg/dL, 1.71-5.32 mg/dL). Similar increased levels were observed in high-density lipoprotein (HDL) cholesterol (18 studies, 3.63 mg/dL, 2.00-5.26 mg/dL) and in apolipoprotein A1 (5 studies, 0.16 mg/dL, 0.11-0.21 mg/dL), while no differences were detected in low density lipoprotein (LDL) cholesterol (12 studies, -2.85 mg/dL, -5.96-0.26 mg/dL) and triglycerides (14 studies, 0.40 mg/dL, -5.00-5.80 mg/dL) levels. Flow mediated dilation (FMD) resulted significantly higher in beer-consumers compared to controls (4 studies, 0.65%, 0.07-1.23%), while blood pressure and other biochemical markers of inflammation did not differ. In conclusion, the specific beer effect on human cardiovascular health was meta-analysed for the first time, highlighting an improvement of the vascular elasticity, detected by the increase of FMD (after acute intake), and of the lipid profile with a significant increase of HDL and apolipoprotein A1 serum levels. Although the long-term effects of beer consumption are not still understood, a beneficial effect of beer on endothelial function should be supposed.
| S-EPMC7269243 | biostudies-literature
Project description:Diagnosis of ovarian cancer is difficult due to the lack of clinical symptoms and effective screening algorithms. In this study, we aim to develop models for ovarian cancer diagnosis by detecting metabolites in urine and plasma samples. Ultra-high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in positive ion mode was used for metabolome quantification in 235 urine samples and 331 plasma samples. Then, Urine and plasma metabolomic profiles were analyzed by univariate and multivariate statistics. Four groups of samples: normal control, benign, borderline and malignant ovarian tumors were enrolled in this study. A total of 1330 features and 1302 features were detected from urine and plasma samples respectively. Based on two urine putative metabolites, five plasma putative metabolites and five urine putative metabolites, three models for distinguishing normal-ovarian tumors, benign-malignant (borderline + malignant) and borderline-malignant ovarian tumors were developed respectively. The AUC (Area Under Curve) values were 0.987, 0876 and 0.943 in discovery set and 0.984, 0.896 and 0.836 in validation set for three models. Specially, the diagnostic model based on 5 plasma putative metabolites had better early-stage diagnosis performance than CA125 alone. The AUC values of the model were 0.847 and 0.988 in discovery and validation set respectively. Our results showed that normal and ovarian tumors have unique metabolic signature in urine and plasma samples, which shed light on the ovarian cancer diagnosis and classification.
| S-EPMC7761955 | biostudies-literature
Project description:BackgroundUsing human humoral metabolomic profiling, we can discover the diagnostic biomarkers and pathogenesis of disease. The specific characterization of atrial fibrillation (AF) subtypes with metabolomics may facilitate effective and targeted treatment, especially in early stages.ObjectivesBy investigating disturbed metabolic pathways, we could evaluate the diagnostic value of biomarkers based on metabolomics for different types of AF.MethodsA cohort of 363 patients was enrolled and divided into a discovery and validation set. Patients underwent an electrocardiogram (ECG) for suspected AF. Groups were divided as follows: healthy individuals (Control), suspected AF (Sus-AF), first diagnosed AF (Fir-AF), paroxysmal AF (Par-AF), persistent AF (Per-AF), and AF causing a cardiogenic ischemic stroke (Car-AF). Serum metabolomic profiles were determined by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS). Metabolomic variables were analyzed with clinical information to identify relevant diagnostic biomarkers.ResultsThe metabolic disorders were characterized by 16 cross-comparisons. We focused on comparing all of the types of AF (All-AFs) plus Car-AF vs. Control, All-AFs vs. Car-AF, Par-AF vs. Control, and Par-AF vs. Per-AF. Then, 117 and 94 metabolites were identified by GC/MS and LC-QTOF-MS, respectively. The essential altered metabolic pathways during AF progression included D-glutamine and D-glutamate metabolism, glycerophospholipid metabolism, etc. For differential diagnosis, the area under the curve (AUC) of specific metabolomic biomarkers ranged from 0.8237 to 0.9890 during the discovery phase, and the predictive values in the validation cohort were 78.8-90.2%.ConclusionsSerum metabolomics is a powerful way to identify metabolic disturbances. Differences in small-molecule metabolites may serve as biomarkers for AF onset, progression, and differential diagnosis.
| S-EPMC9393302 | biostudies-literature
Project description:Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply an untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ~2300 molecular features. Principal component analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts.
| S-EPMC3746514 | biostudies-other
Project description:Introduction:Malignant ascites (MA) is a major cause of morbidity that occurs in 37% of ovarian cancer patients. The accumulation of MA in the peritoneal cavity due to cancer results in debilitating symptoms and extremely poor quality of life. There is an urgent unmet need to expand the understanding of MA to design effective treatment strategies, and to improve MA diagnosis. Objective:Our purpose here is to contribute to a better characterization of MA metabolic composition in ovarian cancer. Method:We determined the metabolic composition of ascitic fluids resulting from orthotopic growth of two ovarian cancer cell lines, the mouse ID8-vascular endothelial growth factor (VEGF)-Defb29 cell line and the human OVCAR3 cell line using high-resolution 1H MRS. ID8-VEGF-Defb29 tumors induce large volumes of ascites, while OVCAR3 tumors induce ascites less frequently and at smaller volumes. To better understand the factors driving the metabolic composition of the fluid, we characterized the metabolism of these ovarian cancer cells in culture by analyzing cell lysates and conditioned culture media with 1H NMR. Results:Distinct metabolite patterns were detected in ascitic fluid collected from OVCAR3 and ID8-VEGF-Defb29 tumor bearing mice that were not reflected in the corresponding cell culture or conditioned medium. Conclusion:High-resolution 1H NMR metabolic markers of MA can be used to improve characterization and diagnosis of MA. Metabolic characterization of MA can provide new insights into how MA fluid supports cancer cell growth and resistance to treatment, and has the potential to identify metabolic targeting strategies to reduce or eliminate the formation of MA.
| S-EPMC5804489 | biostudies-other
Project description:Comprehensive characterisation of the proteins in barley flour
2012-03-04 | PRD000575 | Pride
Project description:In a search for biomarkers of health in whale sharks and as exploration of metabolomics as a modern tool for understanding animal physiology, the metabolite composition of serum in six whale sharks (Rhincodon typus) from an aquarium collection was explored using (1)H nuclear magnetic resonance (NMR) spectroscopy and direct analysis in real time (DART) mass spectrometry (MS). Principal components analysis (PCA) of spectral data showed that individual animals could be resolved based on the metabolite composition of their serum and that two unhealthy individuals could be discriminated from the remaining healthy animals. The major difference between healthy and unhealthy individuals was the concentration of homarine, here reported for the first time in an elasmobranch, which was present at substantially lower concentrations in unhealthy whale sharks, suggesting that this metabolite may be a useful biomarker of health status in this species. The function(s) of homarine in sharks remain uncertain but it likely plays a significant role as an osmolyte. The presence of trimethylamine oxide (TMAO), another well-known protective osmolyte of elasmobranchs, at 0.1-0.3 mol L(-1) was also confirmed using both NMR and MS. Twenty-three additional potential biomarkers were identified based on significant differences in the frequency of their occurrence between samples from healthy and unhealthy animals, as detected by DART MS. Overall, NMR and MS provided complementary data that showed that metabolomics is a useful approach for biomarker prospecting in poorly studied species like elasmobranchs.
| S-EPMC3499553 | biostudies-literature