scholarly journals Organ-Specific Metabolome Deciphering Cell Pathways to Cope with Mercury in Wild Fish (Golden Grey Mullet Chelon auratus)

Animals ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 79
Author(s):  
Giuseppe De Marco ◽  
Fátima Brandão ◽  
Patrícia Pereira ◽  
Mário Pacheco ◽  
Tiziana Cappello
Keyword(s):  
Antioxidant Defense System ◽  
Metabolite Profile ◽  
Proton Nuclear Magnetic Resonance ◽  
Grey Mullet ◽  
Metabolomics Data ◽  
Defensive Strategies ◽  
Fish Organs ◽  
Specific Cytotoxicity ◽  
Organ Specific ◽  
Protective Processes

Metabolomics is a powerful approach in evaluating the health status of organisms in ecotoxicological studies. However, metabolomics data reflect metabolic variations that are attributable to factors intrinsic to the environment and organism, and it is thus crucial to accurately evaluate the metabolome of the tissue/organ examined when it is exposed to no stressor. The metabolomes of the liver and gills of wild golden grey mullet (Chelon auratus) from a reference area were analyzed and compared by proton nuclear magnetic resonance (1H NMR)-based metabolomics. Both organs were characterized by amino acids, carbohydrates, osmolytes, nucleosides and their derivatives, and miscellaneous metabolites. However, similarities and differences were revealed in their metabolite profile and related to organ-specific functions. Taurine was predominant in both organs due to its involvement in osmoregulation in gills, and detoxification and antioxidant protective processes in liver. Environmental exposure to mercury (Hg) triggered multiple and often differential metabolic alterations in fish organs. Disturbances in ion-osmoregulatory processes were highlighted in the gills, whereas differential impairments between fish organs were pointed out in energy-producing metabolic pathways, protein catabolism, membrane stabilization processes, and antioxidant defense system, reflecting the induction of organ-specific adaptive and defensive strategies. Overall, a strict correlation between metabolites and organ-specific functions of fish gills and liver were discerned in this study, as well as organ-specific cytotoxicity mechanisms of Hg in fish.

scholarly journals Extensive Metabolite Profiling in the Unexploited Organs of Black Tiger for Their Potential Valorization in the Pharmaceutical Industry

Life ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 544
Author(s):  
Jianfei Gao ◽  
Kangning Xiong ◽  
Wei Zhou ◽  
Weijie Li
Keyword(s):  
Acid Metabolism ◽  
Metabolite Profile ◽  
Industrial Applications ◽  
Targeted Metabolomics ◽  
Arginine Biosynthesis ◽  
Nutritional Values ◽  
Phenylpropanoid Biosynthesis ◽  
Tyrosine Metabolism ◽  
Organ Specific ◽  
Widely Targeted Metabolomics

Black tiger (Kadsura coccinea (Lem.)) has been reported to hold enormous pharmaceutical potential. The fruit and rhizome of black tiger are highly exploited in the pharmaceutical and other industries. However, the most important organs from the plant such as the leaf and stem are considered biowastes mainly because a comprehensive metabolite profile has not been reported in these organs. Knowledge of the metabolic landscape of the unexploited black tiger organs could help identify and isolate important compounds with pharmaceutical and nutritional values for a better valorization of the species. In this study, we used a widely targeted metabolomics approach to profile the metabolomes of the K. coccinea leaf (KL) and stem (KS) and compared them with the root (KR). We identified 642, 650 and 619 diverse metabolites in KL, KS and KR, respectively. A total of 555 metabolites were mutually detected among the three organs, indicating that the leaf and stem organs may also hold potential for medicinal, nutritional and industrial applications. Most of the differentially accumulated metabolites between organs were enriched in flavone and flavonol biosynthesis, phenylpropanoid biosynthesis, arginine and proline metabolism, arginine biosynthesis, tyrosine metabolism and 2-oxocarboxylic acid metabolism pathways. In addition, several important organ-specific metabolites were detected in K. coccinea. In conclusion, we provide extensive metabolic information to stimulate black tiger leaf and stem valorization in human healthcare and food.

scholarly journals Characterization of antioxidant properties and metabolite profile of Agave atrovirens extracts

2017 ◽  
Author(s):  
Victor Olvera-Garcia ◽  
Ana Belen Granado-Serrano ◽  
Mariona Jove ◽  
Anna Cassanye ◽  
Anaberta Cardador-Martinez ◽  
...  
Keyword(s):  
Oxidative Damage ◽  
Crude Extract ◽  
Antioxidant Properties ◽  
Antioxidant Defense System ◽  
Metabolite Profile ◽  
Antioxidant Response ◽  
Nuclear Extracts ◽  
Antioxidant Response Elements ◽  
Cell Culture Assay ◽  
The One

Agave spp. is widely analyzed because several functional properties have been described. Some minor bioactive compounds such as polyphenols, saponins and Maillard compounds produced during extraction procedures have been reported to exert antioxidant properties. The objective of this study was to elucidate the antioxidant properties of three different Agave atrovirens extracts in a HepG2 cell culture assay. The three extracts analyzed mostly showed antioxidant properties with an increase in NRF2 content in nuclear extracts. However, a differential response was observed in the reduction of protein oxidative damage in the three extracts analyzed, the crude extract being the one that mainly induced a reduction in oxidative damage. Metabolomic analysis was performed to elucidate the potential molecules responsible for the antioxidant properties, where 2-amino-4-methylphenol could be the main candidate responsible for inducing the transcription of cellular antioxidant response elements. It could be concluded that crude extract of Agave atrovirens may increase the cellular antioxidant defense system, with a reduction in oxidative damage.

scholarly journals Aromatic amino acids play a harmonizing role in prostate cancer: A metabolomics-based cross-sectional study

2021 ◽  
pp. 741-750
Author(s):  
Ziba Akbari ◽  
Roghayeh Taghipour Dijojin ◽  
Zahra Zamani ◽  
Reza Haji Hosseini ◽  
Mohammad Arjmand
Keyword(s):  
Prostate Cancer ◽  
Amino Acids ◽  
Nmr Spectroscopy ◽  
1H Nmr ◽  
1H Nmr Spectroscopy ◽  
Aromatic Amino Acids ◽  
Proton Nuclear Magnetic Resonance ◽  
Least Squares Regression ◽  
Cross Sectional ◽  
Metabolomics Data

Background: Prostate cancer (PCa) is a common health problem worldwide. The rate of this disease is likely to grow by 2021. PCa is a heterogeneous disorder, and various biochemical factors contribute to the development of this disease. The metabolome is the complete set of metabolites in a cell or biological sample and represents the downstream end product of the omics. Hence, to model PCa by computational systems biology, a preliminary metabolomics-based study was used to compare the metabolome profile pattern between healthy and PCa men. Objective: This study was carried out to highlight energy metabolism modification and assist the prognosis and treatment of disease with unique biomarkers. Materials and Methods: In this cross-sectional research, 26 men diagnosed with stage-III PCa and 26 healthy men with normal PSA levels were enrolled. Urine was analyzed with proton nuclear magnetic resonance (1H-NMR) spectroscopy, accompanied by the MetaboAnalyst web-based platform tool for metabolomics data analysis. Partial least squares regression discriminant analysis was applied to clarify the separation between the two groups. Outliers were documented and metabolites determined, followed by identifying biochemical pathways. Results: Our findings reveal that modifications in aromatic amino acid metabolism and some of their metabolites have a high potential for use as urinary PCa biomarkers. Tryptophan metabolism (p < 0.001), tyrosine metabolism (p < 0.001), phenylalanine, tyrosine and tryptophan biosynthesis (p < 0.001), phenylalanine metabolism (p = 0.01), ubiquinone and other terpenoid-quinone biosynthesis (p = 0.19), nitrogen metabolism (p = 0.21), and thiamine metabolism (p = 0.41) with Q2 (0.198) and R2 (0.583) were significantly altered. Conclusion: The discriminated metabolites and their pathways play an essential role in PCa causes and harmony. Key words: Metabolomics, Prostate cancer, Aromatic amino acids, 1H-NMR spectroscopy.

scholarly journals Relationship Between Inflammation and Metabolism in Patients With Newly Presenting Rheumatoid Arthritis

2021 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh Jutley ◽  
Kalvin Sahota ◽  
Ilfita Sahbudin ◽  
Andrew Filer ◽  
Thurayya Arayssi ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Nmr Spectroscopy ◽  
Systemic Inflammation ◽  
Stress Protein ◽  
Metabolite Profile ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Orthogonal Projections ◽  
Metabolomics Data

BackgroundSystemic inflammation in rheumatoid arthritis (RA) is associated with metabolic changes. We used nuclear magnetic resonance (NMR) spectroscopy–based metabolomics to assess the relationship between an objective measure of systemic inflammation [C-reactive protein (CRP)] and both the serum and urinary metabolome in patients with newly presenting RA.MethodsSerum (n=126) and urine (n=83) samples were collected at initial presentation from disease modifying anti-rheumatic drug naïve RA patients for metabolomic profile assessment using 1-dimensional 1H-NMR spectroscopy. Metabolomics data were analysed using partial least square regression (PLS-R) and orthogonal projections to latent structure discriminant analysis (OPLS-DA) with cross validation.ResultsUsing PLS-R analysis, a relationship between the level of inflammation, as assessed by CRP, and the serum (p=0.001) and urinary (p&lt;0.001) metabolome was detectable. Likewise, following categorisation of CRP into tertiles, patients in the lowest CRP tertile and the highest CRP tertile were statistically discriminated using OPLS-DA analysis of both serum (p=0.033) and urinary (p&lt;0.001) metabolome. The most highly weighted metabolites for these models included glucose, amino acids, lactate, and citrate. These findings suggest increased glycolysis, perturbation in the citrate cycle, oxidative stress, protein catabolism and increased urea cycle activity are key characteristics of newly presenting RA patients with elevated CRP.ConclusionsThis study consolidates our understanding of a previously identified relationship between serum metabolite profile and inflammation and provides novel evidence that there is a relationship between urinary metabolite profile and inflammation as measured by CRP. Identification of these metabolic perturbations provides insights into the pathogenesis of RA and may help in the identification of therapeutic targets.

scholarly journals Metabolic profile changes in serum of migraine patients detected using 1H-NMR spectroscopy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Aster V. E. Harder ◽  
Lisanne S. Vijfhuizen ◽  
Peter Henneman ◽  
Ko Willems van Dijk ◽  
Cornelia M. van Duijn ◽  
...  
Keyword(s):  
Nmr Spectroscopy ◽  
Acid Metabolism ◽  
Metabolite Profile ◽  
Proton Nuclear Magnetic Resonance ◽  
Metabolic Profiles ◽  
Serum Samples ◽  
Brain Disorder ◽  
Diagnostic Biomarkers ◽  
H Nmr ◽  
Profile Changes

Abstract Background Migraine is a common brain disorder but reliable diagnostic biomarkers in blood are still lacking. Our aim was to identify, using proton nuclear magnetic resonance (1H-NMR) spectroscopy, metabolites in serum that are associated with lifetime and active migraine by comparing metabolic profiles of patients and controls. Methods Fasting serum samples from 313 migraine patients and 1512 controls from the Erasmus Rucphen Family (ERF) study were available for 1H-NMR spectroscopy. Data was analysed using elastic net regression analysis. Results A total of 100 signals representing 49 different metabolites were detected in 289 cases (of which 150 active migraine patients) and 1360 controls. We were able to identify profiles consisting of 6 metabolites predictive for lifetime migraine status and 22 metabolites predictive for active migraine status. We estimated with subsequent regression models that after correction for age, sex, BMI and smoking, the association with the metabolite profile in active migraine remained. Several of the metabolites in this profile are involved in lipid, glucose and amino acid metabolism. Conclusion This study indicates that metabolic profiles, based on serum concentrations of several metabolites, including lipids, amino acids and metabolites of glucose metabolism, can distinguish active migraine patients from controls.

scholarly journals Comprehensive Metabolic Profiling Reveals a Lipid-Rich Fingerprint of Free Thyroxine Far Beyond Classic Parameters

2018 ◽  
Vol 103 (5) ◽  
pp. 2050-2060 ◽  
Author(s):  
Thomas Lange ◽  
Kathrin Budde ◽  
Georg Homuth ◽  
Gabi Kastenmüller ◽  
Anna Artati ◽  
...  
Keyword(s):  
Thyroid Hormones ◽  
Density Lipoprotein ◽  
Free Thyroxine ◽  
Proton Nuclear Magnetic Resonance ◽  
Plasma Metabolites ◽  
Resonance Spectroscopy ◽  
Phenotypic Characteristics ◽  
Metabolomics Data ◽  
Thyroid State ◽  
Lipid Species

Abstract Objective Thyroid hormones are ubiquitously involved in human metabolism. However, the precise molecular patterns associated with alterations in thyroid hormones levels remain to be explored in detail. A number of recent studies took great advantage of metabolomics profiling to outline the metabolic actions of thyroid hormones in humans. Methods Among 952 participants in the Study of Health in Pomerania, data on serum free thyroxine (FT4) and thyrotropin and comprehensive nontargeted metabolomics data from plasma and urine samples were available. Linear regression analyses were performed to assess the association between FT4 or thyrotropin and metabolite levels. Results and Conclusion After accounting for major confounders, 106 of 613 plasma metabolites were significantly associated with FT4. The associations in urine were minor (12 of 587). Most of the plasma metabolites consisted of lipid species, and subsequent analysis of highly resolved lipoprotein subclasses measured by proton nuclear magnetic resonance spectroscopy revealed a consistent decrease in several of these species (e.g., phospholipids) and large low-density lipoprotein and small high-density lipoprotein particles. The latter was unique to men. Several polyunsaturated and saturated fatty acids displayed an association with FT4 in women only. A random forest-based variable selection approach using phenotypic characteristics revealed higher alcohol intake in men and an adverse thyroid state and menopause in women as the putative mediating factors. In general, our observations have confirmed the lipolytic and lipogenic effect of thyroid hormones even in the physiological range and revealed different phenotypic characteristics (e.g., lifestyle differences) as possible confounders for sex-specific findings.

scholarly journals Metabolic Age Based on the BBMRI-NL 1 H-NMR Metabolomics Repository as Biomarker of Age-related Disease

2020 ◽  
Vol 13 (5) ◽  
pp. 541-547
Author(s):  
Erik B. van den Akker ◽  
Stella Trompet ◽  
Jurriaan J.H. Barkey Wolf ◽  
Marian Beekman ◽  
H. Eka D. Suchiman ◽  
...  
Keyword(s):  
Biological Age ◽  
Proton Nuclear Magnetic Resonance ◽  
Cardiometabolic Health ◽  
Older Individuals ◽  
Phenotypic Data ◽  
Metabolomics Data ◽  
Holistic View ◽  
Link Type ◽  
Age Related ◽  
Increased Risk

Background: The blood metabolome incorporates cues from the environment and the host’s genetic background, potentially offering a holistic view of an individual’s health status. Methods: We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts. Results: Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual’s biological age. Exploration in independent cohorts demonstrates that being judged older by one’s metabolome, as compared with one’s chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge ( metaboage.researchlumc.nl ) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data . Conclusions: In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.

scholarly journals Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data

2020 ◽  
Vol 23 (3) ◽  
pp. 145-155
Author(s):  
René Pool ◽  
Fiona A. Hagenbeek ◽  
Anne M. Hendriks ◽  
Jenny van Dongen ◽  
Gonneke Willemsen ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Structural Equation ◽  
Biological Tissues ◽  
Proton Nuclear Magnetic Resonance ◽  
Equation Modeling ◽  
Shared Environment ◽  
Familial Resemblance ◽  
Environmental Variance ◽  
Metabolomics Data ◽  
Significant Heritability

AbstractMetabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term ‘metabolomics’ refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.

scholarly journals Metabolomics approach for multibiomarkers determination to investigate dengue virus infection in human patients

2017 ◽  
Vol 64 (2) ◽  
Author(s):  
Nurul Shahfiza ◽  
Hasnah Osman ◽  
Tang Thean Hock ◽  
Abdel-Hamid Zaki Abdel-Hamid
Keyword(s):  
Dengue Infection ◽  
Metabolite Profile ◽  
Partial Least Square ◽  
Least Square ◽  
Proton Nuclear Magnetic Resonance ◽  
Metabolic Disturbances ◽  
Recent Developments ◽  
Diagnostic Technologies ◽  
Essential Insight ◽  
Insight Into

Background: Dengue is one of the major public health problems in the world, affecting more than fifty million cases in tropical and subtropical region every year. The metabolome, as pathophysiological end-points, provide significant understanding of the mechanism and progression of dengue pathogenesis via changes in the metabolite profile of infected patients. Recent developments in diagnostic technologies provide metabolomics for the early detection of infectious diseases. Methods: The mid-stream urine was collected from 96 patients diagnosed with dengue fever at Penang General Hospital (PGH) and 50 healthy volunteers. Urine samples were analyzed with proton nuclear magnetic resonance (1H NMR) spectroscopy, followed by chemometric multivariate analysis. NMR signals highlighted in the orthogonal partial least square-discriminant analysis (OPLSDA) S-plots were selected and identified using Human Metabolome Database (HMDB) and Chenomx Profiler. A highly predictive model was constructed from urine profile of dengue infected patients versus healthy individuals with the total R2Y (cum) value 0.935, and the total Q2Y (cum) value 0.832. Results: Data showed that dengue infection is related to amino acid metabolism, tricarboxylic acid intermediates cycle and β-oxidation of fatty acids. Distinct variations in certain metabolites were recorded in infected patients including amino acids, various organic acids, betaine, valerylglycine, myoinositol and glycine. Conclusion: Metabolomics approach provides essential insight into host metabolic disturbances following dengue infection.

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