PubMed

Environmental chemical burden in metabolic tissues and systemic biological pathways in adolescent bariatric surgery patients: A pilot untargeted metabolomic approach. Environ Int. 2020 Jul 16;143:105957 Authors: Valvi D, Walker DI, Inge T, Bartell SM, Jenkins T, Helmrath M, Ziegler TR, La Merrill MA, Eckel SP, Conti D, Liang Y, Jones DP, McConnell R, Chatzi L Abstract BACKGROUND: Advances in untargeted metabolomic technologies have great potential for insight into adverse metabolic effects underlying exposure to environmental chemicals. However, important challenges need to be addressed, including how biological response corresponds to the environmental chemical burden in different target tissues. AIM: We performed a pilot study using state-of-the-art ultra-high-resolution mass spectrometry (UHRMS) to characterize the burden of lipophilic persistent organic pollutants (POPs) in metabolic tissues and associated alterations in the plasma metabolome. METHODS: We studied 11 adolescents with severe obesity at the time of bariatric surgery. We measured 18 POPs that can act as endocrine and metabolic disruptors (i.e. 2 dioxins, 11 organochlorine compounds [OCs] and 5 polybrominated diphenyl ethers [PBDEs]) in visceral and subcutaneous abdominal adipose tissue (vAT and sAT), and liver samples using gas chromatography with UHRMS. Biological pathways were evaluated by measuring the plasma metabolome using high-resolution metabolomics. Network and pathway enrichment analysis assessed correlations between the tissue-specific burden of three frequently detected POPs (i.e. p,p'-dichlorodiphenyldichloroethene [DDE], hexachlorobenzene [HCB] and PBDE-47) and plasma metabolic pathways. RESULTS: Concentrations of 4 OCs and 3 PBDEs were quantifiable in at least one metabolic tissue for > 80% of participants. All POPs had the highest median concentrations in adipose tissue, especially sAT, except for PBDE-154, which had comparable average concentrations across all tissues. Pathway analysis showed high correlations between tissue-specific POPs and metabolic alterations in pathways of amino acid metabolism, lipid and fatty acid metabolism, and carbohydrate metabolism. CONCLUSIONS: Most of the measured POPs appear to accumulate preferentially in adipose tissue compared to liver. Findings of plasma metabolic pathways potentially associated with tissue-specific POPs concentrations merit further investigation in larger populations. PMID: 32683211 [PubMed - as supplied by publisher]

A review of saponin intervention in metabolic syndrome suggests further study on intestinal microbiota. Pharmacol Res. 2020 Jul 16;:105088 Authors: Luo Z, Xu W, Zhang Y, Di L, Shan J Abstract Metabolic syndrome (MetS) is a series of symptoms including insulin resistance, obesity, dyslipidemia, elevated fasting blood glucose levels, and hepatic steatosis. As a key criterion in MetS, the onset of insulin resistance is related to abnormal levels of circulating free fatty acids and adipokines. It has been discovered in recent years that metabolites and pathogen-associated molecular patterns of intestinal microbiota are also important factors that cause insulin resistance and MetS. Saponins are the main components of many botanicals and traditional Chinese medicines (TCMs), such as ginseng, platycodon, licorice, and alfalfa. They have poor bioavailability, but can be transformed into secondary glycosides and aglycones by intestinal microbiota, further being absorbed. Based on in vivo and in vitro data, we found that saponins and their secondary metabolites have a preventive effect on MetS, and the effective targets are distributed in the intestine and other organs in human body. Intestinal targets involve pancreatic lipase, dietary cholesterol, and intestinal microbiota. Other targets include central appetite, nuclear receptors such as PPAR and LXR, AMPK signaling pathway and adipokines levels, etc. In view of the poor bioavailability of saponins, it is inferred that targets for prototype-saponins to interfere with MetS is mainly located in the intestine, and the activation of other targets may be related to secondary glycosides and aglycones transformed from saponins by intestinal flora. We suggest that the role of intestinal microbiota in saponin intervention in MetS should be further investigated. PMID: 32683035 [PubMed - as supplied by publisher]

Integrated transcriptomic and metabolomic analyses of glutamine metabolism genes unveil key players in Oryza sativa (L.) to ameliorate the unique and combined abiotic stress tolerance. Int J Biol Macromol. 2020 Jul 16;: Authors: Muthuramalingam P, Jeyasri R, Selvaraj A, Pandian SK, Ramesh M Abstract Plants can be considered to biosynthesize the specialized metabolites to adapt to various environmental stressors mainly on abiotic stresses (AbS). Among specialized metabolites, glutamine (Gln) is an essential plant metabolite to achieve sustainable plant growth, yield and food security. In this pilot study, swe employed computational metabolomics genome wide association survey (cmGWAS) of Gln metabolite profiling in Oryza sativa, targeting at the identification of abiotic stress responsible (AbSR) - Gln metabolite producing genes (GlnMPG). Identified 5 AbSR-GlnMPG alter the metabolite levels and play a predominant role in delineating the physiological significance of rice. These genes were systematically analysed for their biological features via OryzaCyc. Spatio-temporal and plant hormonal expression pattern of AbSR-GlnMPG was analysed and their differential expression profiling were noted in 48 different tissues and hormones, respectively. Furthermore, comparative ideogram of these genes revealed the chromosomal synteny with C4 grass genomes. Molecular crosstalks of these proteins, unravelled the various metabolic interaction. The systems expression profiling of AbSR-GlnMPG will lead to unravel the metabolite signaling and putative responses in multiple AbS. On the whole, this holistic study provides deeper insights on biomolecular features of AbSR-GlnMPG, which could be analysed further to decipher their functional metabolisms in AbS dynamism. PMID: 32682969 [PubMed - as supplied by publisher]

UPLC-MS metabolomics method provides valuable insights into the effect and underlying mechanisms of Rhizoma Drynariae protecting osteoporosis. J Chromatogr B Analyt Technol Biomed Life Sci. 2020 Jul 11;1152:122262 Authors: Jiang YC, Li YF, Zhou L, Zhang DP Abstract Osteoporosis (OP) is a metabolic bone disease in which that volume of bone tissue per unit volume decrease, which is a common disease disturbing the elderly or postmenopausal women. Rhizoma Drynariae (RD) is a kind of herb widely used in thousands of years of clinical practice in China to tonify kidney and prevent osteoporosis, with reliable curative effect. However, the mechanism of its anti-osteoporosis action is still unclear. This study is dedicated to exploration the therapeutic effect of RD on retinoic acid solution-induced OP model rats based on high-throughput metabolomics technology platform, and reveal its influence on metabolomics level, so as to find effective potential biomarkers and therapeutic targets for diagnosing OP. OP model was established by intragastric administration of retinoic acid solution for 21 days, and then the treatment group was treated by intragastric administration of RD solution for 60 days. Blood samples of all groups were collected and analyzed based on UPLC-MS metabolomics and combined with EZinfo 3.0 data analysis, 32 potential biomarkers were identified, including 22 in ESI+ and 10 in ESI-, these biomarkers are related to 9 metabolic pathways. After treatment with RD solution, 21 biomarkers were obviously regulated, these mainly affected linoleic acid metabolic, glycerophospholipid metabolism and arachidonic acid metabolism pathway. The results show that RD can reduce the risk of OP disease, which may be related to the metabolic pathway mentioned above, and provides the foundation for the administer prophylaxis and treatment of OP with natural products. PMID: 32682315 [PubMed - as supplied by publisher]

Human ARMT1 structure and substrate specificity indicates that it is a DUF89 family damage-control phosphatase. J Struct Biol. 2020 Jul 15;:107576 Authors: Dennis TN, Kenjić N, Kang AS, Lowenson JD, Kirkwood JS, Clarke SG, Jefferson P Perry J Abstract Metabolite damage control is a critical but poorly defined aspect of cellular biochemistry, which likely involves many of the so far functionally uncharacterized protein domain (domains of unknown function; DUFs). We have determined the crystal structure of the human DUF89 protein product of the C6ORF211 gene to 1.85 Å. The crystal structure shows that the protein contains a core α-β-α fold with an active site-bound metal ion and α-helical bundle N-terminal cap, which are both conserved features of subfamily III DUF89 domains. The biochemical activities of the human protein are conserved with those of a previously characterized budding yeast homolog, where an in vitro phosphatase activity is supported by divalent cations that include Co2+, Ni2+, Mn2+ or Mg2+. Full steady-state kinetics parameters of human DUF89 using a standard PNPP phosphatase assay revealed a six times higher catalytic efficiency in presence of Co2+ compared to Mg2+. The human enzyme targets a number of phosphate substrates similar to the budding yeast homolog, while it lacks a previously indicated methyltransferase activity. The highest activity on substrate was observed with fructose-1-phosphate, a potent glycating agent, and thus human DUF89 phosphatase activity may also play a role in limiting the buildup of phospho-glycan species and their related damaged metabolites. PMID: 32682077 [PubMed - as supplied by publisher]

Related Articles International consensus guidelines for phosphoglucomutase 1 deficiency (PGM1-CDG): diagnosis, follow-up and management. J Inherit Metab Dis. 2020 Jul 18;: Authors: Altassan R, Radenkovic S, Edmondson AC, Barone R, Brasil S, Cechova A, Coman D, Donoghue S, Falkenstein K, Ferreira V, Ferreira C, Fiumara A, Francsico R, Freeze H, Grunewald S, Honzik T, Jaeken J, Krasnewich D, Lam C, Lee J, Lefeber D, Marques-da-Silva D, Pascoal C, Quelhas D, Raymond KM, Rymen D, Seroczynska M, Serrano M, Sykut-Cegielska J, Thiel C, Tort F, Vals MA, Videira P, Voermans N, Witters P, Morava E Abstract Phosphoglucomutase 1 (PGM1) deficiency is a rare genetic disorder that affects glycogen metabolism, glycolysis, and protein glycosylation. Previously known as GSD XIV, it was recently reclassified as a congenital disorder of glycosylation, PGM1-CDG. PGM1-CDG usually manifests as a multisystem disease. Most patients present as infants with cleft palate, liver function abnormalities and hypoglycemia, but some patients present in adulthood with isolated muscle involvement. Some patients develop life-threatening cardiomyopathy. Unlike most other CDG, PGM1-CDG has an effective treatment option, D-galactose, which has been shown to improve many of the patients' symptoms. Therefore, early diagnosis and initiation of treatment for PGM1-CDG patients are crucial decisions. In this paper, our group of international experts suggests diagnostic, follow-up and management guidelines for PGM1-CDG. These guidelines are based on the best available evidence-based data and experts' opinions aiming to provide a practical resource for health care providers to facilitate successful diagnosis and optimal management of PGM1-CDG patients. Concise Statement: These international consensus guidelines provide a practical, evidence-based resource for health care providers to facilitate successful diagnosis and optimal management of PGM1-CDG patients. This article is protected by copyright. All rights reserved. PMID: 32681750 [PubMed - as supplied by publisher]

Related Articles Correlation of fecal metabolomics and gut microbiota in mice with endometriosis. Am J Reprod Immunol. 2020 Jul 17;:e13307 Authors: Ni Z, Sun S, Bi Y, Ding J, Cheng W, Yu J, Zhou L, Li M, Yu C Abstract PROBLEM: Endometriosis (EMS) is a chronic inflammatory disease with unclear pathogenesis. Three studies have uncovered the influence of gut microbiota on mice with EMS, but no study has investigated the characteristics of fecal metabolomics to determine some important clues on EMS. This research aims to uncover the interaction between fecal metabolomics and gut microbiota in EMS mice. METHOD OF STUDY: Female C57BL/6J mice were used to construct the EMS model. Nontarget metabolomics was applied to detect the fecal metabolites of EMS mice. The 16s rRNA sequencing was used for clarifying the composition of the gut microbiota. The functional characteristics of gut microbiota were analyzed using the PICRUSt. The receiver operator characteristic curve (ROC) analysis was utilized for determining the potential important differential metabolites, and the Spearman correlation coefficient was applied for expressing the correlation between the important differential metabolites and gut microbiota. RESULTS: A total of 156 named differential metabolites were screened. The diversity and the abundance of gut microbiota in EMS mice decreased. Eleven pathways were involved in the differential metabolites and the functional prediction of gut microbiota, among which the second bile acid biosynthesis and alpha-linolenic acid (ALA) metabolism were significant the enrichment pathways. The increased abundance of chenodeoxycholic and ursodeoxycholic acids and the decreased abundance of ALA and 12,13-EOTrE were found in the feces of EMS mice. CONCLUSIONS: The abnormal fecal metabolites, which are influenced by dysbacteriosis, may be the characteristics of EMS mice and can be the potential important indices to distinguish the disease. PMID: 32681566 [PubMed - as supplied by publisher]

Related Articles Chemical profiling of the human skin surface for malaria vector control via a non-invasive sorptive sampler with GC×GC-TOFMS. Anal Bioanal Chem. 2020 Jul 18;: Authors: Wooding M, Rohwer ER, Naudé Y Abstract Volatile organic compounds (VOCs) and semi-VOCs detected on the human skin surface are of great interest to researchers in the fields of metabolomics, diagnostics, and skin microbiota and in the study of anthropophilic vector mosquitoes. Mosquitoes use chemical cues to find their host, and humans can be ranked for attractiveness to mosquitoes based on their skin chemical profile. Additionally, mosquitoes show a preference to bite certain regions on the human host. In this study, the chemical differences in the skin surface profiles of 20 human volunteers were compared based on inter-human attractiveness to mosquitoes, as well as inter- and intra-human mosquito biting site preference. A passive, non-invasive approach was followed to sample the wrist and ankle skin surface region. An in-house developed polydimethylsiloxane (PDMS) passive sampler was used to concentrate skin VOCs and semi-VOCs prior to thermal desorption directly in the GC inlet with comprehensive gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS). Compounds from a broad range of chemical classes were detected and identified as contributing to the differences in the surface skin chemical profiles. 5-Ethyl-1,2,3,4-tetrahydronaphthalene, 1,1'-oxybisoctane, 2-(dodecyloxy)ethanol, α,α-dimethylbenzene methanol, methyl salicylate, 2,6,10,14-tetramethylhexadecane, 1,2-benzenedicarboxylic acid, bis(2-methylpropyl) ester, 4-methylbenzaldehyde, 2,6-diisopropylnaphthalene, n-hexadecanoic acid, and γ-oxobenzenebutanoic acid ethyl ester were closely associated with individuals who perceived themselves as attractive for mosquitoes. Additionally, biological lead compounds as potential attractants or repellants in vector control strategies were tentatively identified. Results augment current knowledge on human skin chemical profiles and show the potential of using a non-invasive sampling approach to investigate anthropophilic mosquito-host interactions. Graphical abstract. PMID: 32681223 [PubMed - as supplied by publisher]

Related Articles Caution in studying and interpreting the lupus metabolome. Arthritis Res Ther. 2020 Jul 17;22(1):172 Authors: Zhang T, Mohan C Abstract Several metabolomics studies have shed substantial light on the pathophysiological pathways underlying multiple diseases including systemic lupus erythematosus (SLE). This review takes stock of our current understanding of this field. We compare, collate, and investigate the metabolites in SLE patients and healthy volunteers, as gleaned from published metabolomics studies on SLE. In the surveyed primary reports, serum or plasma samples from SLE patients and healthy controls were assayed using mass spectrometry or nuclear magnetic resonance spectroscopy, and metabolites differentiating SLE from controls were identified. Collectively, the circulating metabolome in SLE is characterized by reduced energy substrates from glycolysis, Krebs cycle, fatty acid β oxidation, and glucogenic and ketogenic amino acid metabolism; enhanced activity of the urea cycle; decreased long-chain fatty acids; increased medium-chain and free fatty acids; and augmented peroxidation and inflammation. However, these findings should be interpreted with caution because several of the same metabolic pathways are also significantly influenced by the medications commonly used in SLE patients, common co-morbidities, and other factors including smoking and diet. In particular, whereas the metabolic alterations relating to inflammation, oxidative stress, lipid peroxidation, and glutathione generation do not appear to be steroid-dependent, the other metabolic changes may in part be influenced by steroids. To conclude, metabolomics studies of SLE and other rheumatic diseases ought to factor in the potential contributions of confounders such as medications, co-morbidities, smoking, and diet. PMID: 32680552 [PubMed - as supplied by publisher]

Related Articles Metabolite Profiles of Red and Yellow Watermelon (Citrullus lanatus) Cultivars Using a 1H-NMR Metabolomics Approach. Molecules. 2020 Jul 15;25(14): Authors: Sulaiman F, Ahmad Azam A, Ahamad Bustamam MS, Fakurazi S, Abas F, Lee YX, Ismail AA, Mohd Faudzi SM, Ismail IS Abstract Watermelon, a widely commercialized fruit, is famous for its thirst-quenching property. The broad range of cultivars, which give rise to distinct color and taste, can be attributed to the differences in their chemical profile, especially that of the carotenoids and volatile compounds. In order to understand this distribution properly, water extracts of red and yellow watermelon pulps with predominantly polar metabolites were subjected to proton nuclear magnetic resonance (1H-NMR) analysis. Deuterium oxide (D2O) and deuterated chloroform (CDCl3) solvents were used to capture both polar and non-polar metabolites from the same sample. Thirty-six metabolites, of which six are carotenoids, were identified from the extracts. The clustering of the compounds was determined using unsupervised principal component analysis (PCA) and further grouping was achieved using supervised orthogonal partial least squares discriminant analysis (OPLS-DA). The presence of lycopene, β-carotene, lutein, and prolycopene in the red watermelon plays an important role in its differentiation from the yellow cultivar. A marked difference in metabolite distribution was observed between the NMR solvents used as evidenced from the PCA model. OPLS-DA and relative quantification of the metabolites, on the other hand, helped in uncovering the discriminating metabolites of the red and yellow watermelon cultivars from the same solvent system. PMID: 32679913 [PubMed - as supplied by publisher]

29 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/18PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

29 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/18PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/17PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/17PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/16PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

21 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/15PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

25 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/14PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

25 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2020/07/14PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Type 2 Diabetes Metabolic Improvement After Roux-en-Y Gastric Bypass May Include A Compensatory Mechanism That Balances Fatty Acid β and ω Oxidation. JPEN J Parenter Enteral Nutr. 2020 Jul 11;: Authors: Mendonça Machado N, Torrinhas RS, Sala P, Ishida RK, Guarda IFMS, Moura EGH, Sakai P, Santo MA, Linetzky Waitzberg D Abstract BACKGROUND: More than half patients underwent Roux-en-Y gastric bypass (RYGB) can experience type 2 diabetes (T2D) remission, but the systemic and gastrointestinal metabolic mechanisms of this improvement are still elusive. METHODS: Paired samples collected before and 3 months after RYGB from 28 women with obesity and T2D were analyzed by metabolomics with gas chromatography coupled to mass spectrometry. Samples include plasma (n = 56) and biopsies of gastric pouch (n = 18), gastric remnant (n = 10), duodenum (n = 16), jejunum (n = 18) and ileum (n = 18), collected by double-balloon enteroscopy. RESULTS: After RYGB, improvements in body composition, weight-related and glucose homeostasis parameters were observed. Plasma enriched metabolic pathways included arginine and proline metabolism, urea and tricarboxylic acid cycles, gluconeogenesis, malate-aspartate shuttle and carnitine synthesis. In gastrointestinal tissue, we observed alterations of ammonia recycling and carnitine synthesis in gastric pouch, phenylacetate metabolism and trehalose degradation in duodenum and jejunum, ketone bodies in jejunum, and lactose degradation in ileum. Intermediates molecules of the tricarboxylic acid cycle (TCA) were enriched, particularly in plasma, jejunum and ileum. Fluctuations of dicarboxylic acids (DCA) were relevant in several metabolomic tests and metabolite alterations included aminomalonate and fumaric, malic, oxalic and succinic acids. The product/substrate relationship between these molecules and its pathways may reflect a compensatory mechanism to balance metabolism. CONCLUSIONS: RYGB was associated with systemic and GI metabolic reprogramming. DCA alterations links ω and β fatty acid oxidation to homeostatic mechanisms, including TCA cycle improvement. This article is protected by copyright. All rights reserved. PMID: 32654184 [PubMed - as supplied by publisher]

RTExtract: Time-series NMR spectra quantification based on 3D surface ridge tracking. Bioinformatics. 2020 Jul 12;: Authors: Wu Y, Judge MT, Arnold J, Bhandarkar SM, Edison AS Abstract MOTIVATION: Time-series NMR has advanced our knowledge about metabolic dynamics. Before analyzing compounds through modeling or statistical methods, chemical features need to be tracked and quantified. However, because of peak overlap and peak shifting, the available protocols are time consuming at best or even impossible for some regions in NMR spectra. RESULTS: We introduce RTExtract (Ridge Tracking based Extract), a computer vision-based algorithm, to quantify time-series NMR spectra. The NMR spectra of multiple time points were formulated as a 3D surface. Candidate points were first filtered using local curvature and optima, then connected into ridges by a greedy algorithm. Interactive steps were implemented to refine results. Among 173 simulated ridges, 115 can be tracked (RMSD < 0.001). For reproducing previous results, RTExtract took less than two hours instead of ∼48 hours, and two instead of seven parameters need tuning. Multiple regions with overlapping and changing chemical shifts are accurately tracked. AVAILABILITY: Source code is freely available within Metabolomics toolbox GitHub repository (https://github.com/artedison/Edison_Lab_Shared_Metabolomics_UGA/tree/master/metabolomics_toolbox/code/ridge_tracking) and is implemented in MATLAB and R. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. PMID: 32653900 [PubMed - as supplied by publisher]