PubMed

Related Articles Can we trust biomarkers identified using different non-targeted metabolomics platforms? Multi-platform, inter-laboratory comparative metabolomics profiling of lettuce cultivars via UPLC-QTOF-MS. Metabolomics. 2020 Jul 31;16(8):85 Authors: García CJ, Yang X, Huang D, Tomás-Barberán FA Abstract INTRODUCTION: Data analysis during UPLC-MS non-targeted metabolomics introduces variation as different manufacturers use specific algorithms for data treatment and this makes untargeted metabolomics an application for the discovery of new biomarkers with low confidence in the reproducibility of the results under the use of different metabolomics platforms. OBJECTIVES: This study compared the ability of two platforms (Agilent UPLC-ESI-QTOF-MS and Waters UPLC-IMS-QTOF-MS) to identify biomarkers in butterhead and romaine lettuce cultivars. METHODS: Two case studies by different metabolomics platforms: (1) Waters and Agilent datasets processed by the same data pre-processing software (Progenesis QI), and (2) Datasets processed by different data pre-processing software. RESULTS: A higher number of candidate biomarkers shared between sample groups in case 2 (101) than in case 1 (26) was found. Thirteen metabolites were common to both cases. Romaine lettuce was characterised by phenolic compounds including flavonoids, hydroxycinnamate derivatives, and 9-undecenal, while Butterhead showed sesquiterpene lactones and xanthosine. This study demonstrates that high percentages of the most discriminatory entities can be obtained by using the manufacturers' embedded pre-processing software and following the recommended processing data guidelines using commercial software to normalise the data matrix. PMID: 32737683 [PubMed - as supplied by publisher]

Related Articles Contribution of anthocyanin pathways to fruit flesh coloration in pitayas. BMC Plant Biol. 2020 Jul 31;20(1):361 Authors: Fan R, Sun Q, Zeng J, Zhang X Abstract BACKGROUND: Color formation in Hylocereus spp. (pitayas) has been ascribed to the accumulation of betalains. However, several studies have reported the presence of anthocyanins in pitaya fruit and their potential role in color formation has not yet been explored. In this study, we profiled metabolome and transcriptome in fruit of three cultivars with contrasting flesh colors (red, pink and white) to investigate their nutritional quality and the mechanism of color formation involving anthocyanins. RESULTS: Results revealed that pitaya fruit is enriched in amino acid, lipid, carbohydrate, polyphenols, vitamin and other bioactive components with significant variation among the three cultivars. Anthocyanins were detected in the fruit flesh and accumulation levels of Cyanidin 3-glucoside, Cyanidin 3-rutinoside, Delphinidin 3-O-(6-O-malonyl)-beta-glucoside-3-O-beta-glucoside and Delphinidin 3-O-beta-D-glucoside 5-O-(6-coumaroyl-beta-D-glucoside) positively correlated with the reddish coloration. Transcriptome data showed that the white cultivar tends to repress the anthocyanin biosynthetic pathway and divert substrates to other competing pathways. This perfectly contrasted with observations in the red cultivar. The pink cultivar however seems to keep a balance between the anthocyanin biosynthetic pathway and the competing pathways. We identified several active transcription factors of the MYB and bHLH families which can be further investigated as potential regulators of the anthocyanin biosynthetic genes. CONCLUSIONS: Collectively, our results suggest that anthocyanins partly contribute to color formation in pitaya fruit. Future studies aiming at manipulating the biosynthetic pathways of anthocyanins and betalains will better clarify the exact contribution of each pathway in color formation in pitayas. This will facilitate efforts to improve pitaya fruit quality and appeal. PMID: 32736527 [PubMed - as supplied by publisher]

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 2020/08/01PubMed 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.

22 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 2020/07/31PubMed 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 2020/07/30PubMed 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.

27 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 2020/07/29PubMed 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.

82 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 2020/07/28PubMed 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.

82 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 2020/07/28PubMed 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.

Related Articles Identification of metabolic markers in patients with type 2 Diabetes Mellitus by Ultrafast gas chromatography coupled to electronic nose. A pilot study. Biomed Chromatogr. 2020 Jul 24;:e4956 Authors: Méndez-Rodríguez KB, Figueroa-Vega N, Ilizaliturri Hernandez CA, Cardona-Alvarado M, Borjas García JA, Kornhauser C, Malacara JM, Flores-Ramírez R, Pérez-Vázquez FJ Abstract Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p<0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice. PMID: 32706910 [PubMed - as supplied by publisher]

Related Articles Bioinformatics-assisted, integrated omics studies on medicinal plants. Brief Bioinform. 2019 Nov 18;: Authors: Ma X, Meng Y, Wang P, Tang Z, Wang H, Xie T Abstract The immense therapeutic and economic values of medicinal plants have attracted increasing attention from the worldwide researchers. It has been recognized that production of the authentic and high-quality herbal drugs became the prerequisite for maintaining the healthy development of the traditional medicine industry. To this end, intensive research efforts have been devoted to the basic studies, in order to pave a way for standardized authentication of the plant materials, and bioengineering of the metabolic pathways in the medicinal plants. In this paper, the recent advances of omics studies on the medicinal plants were summarized from several aspects, including phenomics and taxonomics, genomics, transcriptomics, proteomics and metabolomics. We proposed a multi-omics data-based workflow for medicinal plant research. It was emphasized that integration of the omics data was important for plant authentication and mechanistic studies on plant metabolism. Additionally, the computational tools for proper storage, efficient processing and high-throughput analyses of the omics data have been introduced into the workflow. According to the workflow, authentication of the medicinal plant materials should not only be performed at the phenomics level but also be implemented by genomic and metabolomic marker-based examination. On the other hand, functional genomics studies, transcriptional regulatory networks and protein-protein interactions will contribute greatly for deciphering the secondary metabolic pathways. Finally, we hope that our work could inspire further efforts on the bioinformatics-assisted, integrated omics studies on the medicinal plants. PMID: 32706024 [PubMed - as supplied by publisher]

Related Articles Comparative analysis of metabolites in liver of Muscovy duck at different egg-laying stages using nontargeted UPLC-MS based metabolomics. J Proteome Res. 2020 Jul 23;: Authors: Zhu W, Liu L, Yang W, Wei C, Geng Z, Chen X Abstract Liver plays an important physiological function in the synthesis of yolk materials during egg laying in bird. Liver metabolite profiles of Muscovy ducks at different egg-laying stages from the perspective of nontargeted metabolomics were analyzed in this study. Twelve Muscovy ducks were selected at pre-laying (22wk, TT group), laying (40wk, FT group) and post-laying (60wk, ST group) stages, resulted in thirty-six hepatic metabolite profiles by using ultra-high performance liquid chromatography-electrospray mass spectrometry (UPLC-MS). A total of 324 differential metabolites (156 increased and 168 decreased) in FT as compared to TT (FT/TT) group and 332 differential metabolites (120 increased and 212 decreased) in ST as compared to FT (ST/FT) group were screened out. Metabolic pathways enriched in FT/TT group and ST/FT group were mainly amino acid metabolism, glycerophospholipid metabolism, nucleotide metabolism, and vitamin metabolism. The amino acid metabolism pathways were up-regulated in FT/TT group and down-regulated in ST/FT group (P<0.05). The glutathione and ascorbic acid abundance were down-regulated and the choline abundance was up-regulated during egg laying (P<0.05). The liver provides amino acids, lipids, nucleotides, vitamins, and choline, etc, essential materials for yolk precursor synthesis. The decrease in the abundance of glutathione and ascorbic acid indicate that Muscovy ducks might be in a relatively stable physiological state during egg laying. PMID: 32705871 [PubMed - as supplied by publisher]

Related Articles Research Progress of Metabolomics in Forensic Pathology. Fa Yi Xue Za Zhi. 2020 Jun;36(3):347-353 Authors: Du TS, Mengxi MM, Ye X, Tu CY, Jin KD, Chen SW, Liu NG, Xie JH, Shen YW Abstract Abstract: Metabolomics is an interdisciplinary subject that rose in the post-genomic era, which focuses on quantitative study of the response of living organisms to outside stimulation and pathophysiological changes, as well as multiple dynamic response of the level of in vivo metabolites caused by genetic mutation. It is extensively used in basic research of system biology, materia medica, clinical medicine, etc. In the forensic field, metabolomics mainly focuses on forensic toxicology, but with the generalization of certain techniques, it's foreseeable that metabolomics has a broad research prospect in forensic pathology. This article summarizes the major analysis techniques and methods of metabolomics, describes the research status of metabolomic techniques in the field of forensic pathology application research, including postmortem interval and death cause. Moreover, this article summarizes and discusses the potential applicable areas, in order to provide reference for relative research and application. PMID: 32705848 [PubMed - in process]

Related Articles Strategies for Measuring Induction of Fatty Acid Oxidation in Intestinal Stem and Progenitor Cells. Methods Mol Biol. 2020;2171:53-64 Authors: Cheng CW, Yilmaz OH, Mihaylova MM Abstract This protocol describes a multipronged approach that we have created to determine the transcriptional induction of fatty acid oxidation (FAO) genes in Lgr5high intestinal stem cells and a subsequent metabolomics-based approach for assessing fatty acid utilization in the mammalian intestinal crypt. More specifically, we describe methods for crypt isolation followed by a FACS-based purification of stem and progenitor populations and RNA-sequencing analysis. Using this workflow, we can determine both basal gene expression profiles of key metabolic genes as well as corresponding changes in response to altered metabolic states, such as fasting. Subsequently, we describe a complementary metabolomics-based approach that we have developed to assess fatty acid uptake and utilization in the crypt using 13C stable isotope tracing. Combining these approaches, one can gain a better understanding of substrate utilization and the preceding transcriptional changes that accommodate these reactions in physiologic states of low carbohydrate utilization or during overabundance of dietary lipids. PMID: 32705635 [PubMed - in process]

Related Articles A chemical biology approach to identifying molecular pathways associated with aging. Geroscience. 2020 Jul 23;: Authors: Currais A, Huang L, Petrascheck M, Maher P, Schubert D Abstract The understanding of how aging contributes to dementia remains obscure. To address this problem, a chemical biology approach was used employing CAD031, an Alzheimer's disease (AD) drug candidate identified using a discovery platform based upon phenotypic screens that mimic toxicities associated with the aging brain. Since CAD031 has therapeutic efficacy when fed to old symptomatic transgenic AD mice, the chemical biology hypothesis is that it can be used to determine the molecular pathways associated with age-related disease by identifying those that are modified by the compound. Here we show that when CAD031 was fed to rapidly aging SAMP8 mice starting in the last quadrant of their lifespan, it reduced many of the changes in gene, protein, and small molecule expression associated with mitochondrial aging, maintaining mitochondria at the younger molecular phenotype. Network analysis integrating the metabolomics and transcription data followed by mechanistic validation showed that CAD031 targets acetyl-CoA and fatty acid metabolism via the AMPK/ACC1 pathway. Importantly, CAD031 extended the median lifespan of SAMP8 mice by about 30%. These data show that specific alterations in mitochondrial composition and metabolism highly correlate with aging, supporting the use AD drug candidates that limit physiological aging in the brain. PMID: 32705410 [PubMed - as supplied by publisher]

Related Articles NMR metabolomic analysis of bacterial resistance pathways using multivalent quaternary ammonium functionalized macromolecules. Metabolomics. 2020 Jul 23;16(8):82 Authors: Aries ML, Cloninger MJ Abstract INTRODUCTION: Multivalent antimicrobial dendrimers are an exciting new system that is being developed to address the growing problem of drug resistant bacteria. Nuclear Magnetic Resonance (NMR) metabolomics is a quantitative and reproducible method for the determination of bacterial response to environmental stressors and for visualization of perturbations to biochemical pathways. OBJECTIVES: NMR metabolomics is used to elucidate metabolite differences between wild type and antimicrobially mutated Escherichia coli (E. coli) samples. METHODS: Proton (1H) NMR hydrophilic metabolite analysis was conducted on samples of E. coli after 33 growth cycles of a minimum inhibitory challenge to E. coli by poly(amidoamine) dendrimers functionalized with mannose and with C16-DABCO quaternary ammonium endgroups and compared to the metabolic profile of wild type E. coli. RESULTS: The wild type and mutated E. coli samples were separated into distinct sample sets by hierarchical clustering, principal component analysis (PCA) and sparse partial least squares discriminate analysis (sPLS-DA). Metabolite components of membrane fortification and energy related pathways had a significant p value and fold change between the wild type and mutated E. coli. Amino acids commonly associated with membrane fortification from cationic antimicrobials, such as lysine, were found to have a higher concentration in the mutated E. coli than in the wild type E. coli. N-acetylglucosamine, a major component of peptidoglycan synthesis, was found to have a 25-fold higher concentration in the mid log phase of the mutated E. coli than in the mid log phase of the wild type. CONCLUSION: The metabolic profile suggests that E. coli change their peptidoglycan composition in order to garner protection from the highly positively charged and multivalent C16-DABCO and mannose functionalized dendrimer. PMID: 32705355 [PubMed - in process]

Related Articles Milk fat globule size development in the mammary epithelial cell: a potential role for ether phosphatidylethanolamine. Sci Rep. 2020 Jul 23;10(1):12299 Authors: Walter L, Narayana VK, Fry R, Logan A, Tull D, Leury B Abstract Milk fat globule (MFG) size is a milk production trait characteristic to the individual animal and has important effects on the functional and nutritional properties of milk. Although the regulation of MFG size in the mammary epithelial cell is not fully understood, lipid droplet (LD) fusion prior to secretion is believed to play a role. We selected cows that consistently produced milk with predominantly small or large MFGs to compare their lipidomic profiles, with focus on the polar lipid fraction. The polar lipid composition of the monolayer surrounding the LD is believed to either promote or prevent LD fusion. Using a targeted LC-MS/MS approach we studied the relative abundance of 301 detected species and found significant differences between the studied groups. Here we show that the lipidomic profile of milk from small MFG cows is characterised by higher phosphatidylcholine to phosphatidylethanolamine ratios. In contrast, the milk from large MFG cows contained more ether-phosphatidylethanolamine species. This is the first time that a potential role for ether-phosphatidylethanolamine in MFG size development has been suggested. PMID: 32704146 [PubMed - in process]

Related Articles Author Correction: Human DC-SIGN and CD23 do not interact with human IgG. Sci Rep. 2020 Jul 23;10(1):12560 Authors: Temming AR, Dekkers G, van de Bovenkamp FS, Plomp HR, Bentlage AEH, Szittner Z, Derksen NIL, Wuhrer M, Rispens T, Vidarsson G Abstract An amendment to this paper has been published and can be accessed via a link at the top of the paper. PMID: 32703963 [PubMed - in process]

Related Articles Integrated metabolomic and transcriptomic analysis of the anthocyanin regulatory networks in Salvia miltiorrhiza Bge. flowers. BMC Plant Biol. 2020 Jul 23;20(1):349 Authors: Jiang T, Zhang M, Wen C, Xie X, Tian W, Wen S, Lu R, Liu L Abstract BACKGROUND: The objectives of this study were to reveal the anthocyanin biosynthesis metabolic pathway in white and purple flowers of Salvia miltiorrhiza using metabolomics and transcriptomics, to identify different anthocyanin metabolites, and to analyze the differentially expressed genes involved in anthocyanin biosynthesis. RESULTS: We analyzed the metabolomics and transcriptomics data of S. miltiorrhiza flowers. A total of 1994 differentially expressed genes and 84 flavonoid metabolites were identified between the white and purple flowers of S. miltiorrhiza. Integrated analysis of transcriptomics and metabolomics showed that cyanidin 3,5-O-diglucoside, malvidin 3,5-diglucoside, and cyanidin 3-O-galactoside were mainly responsible for the purple flower color of S. miltiorrhiza. A total of 100 unigenes encoding 10 enzymes were identified as candidate genes involved in anthocyanin biosynthesis in S. miltiorrhiza flowers. Low expression of the ANS gene decreased the anthocyanin content but enhanced the accumulation of flavonoids in S. miltiorrhiza flowers. CONCLUSIONS: Our results provide valuable information on the anthocyanin metabolites and the candidate genes involved in the anthocyanin biosynthesis pathways in S. miltiorrhiza. PMID: 32703155 [PubMed - in process]

Related Articles Distinct metabolic signatures of hormone-sensitive and castration-resistant prostate cancer revealed by a 1H NMR-based metabolomics of biopsy tissue. J Proteome Res. 2020 Jul 23;: Authors: Zheng H, Zhu Y, Shao X, Cai A, Dong B, Xue W, Gao H Abstract Tumor metabolic characteristics have been associated with the progression of prostate cancer (PCa), but little information is available regarding the metabolic alterations from hormone-sensitive (HSPC) to castration-resistant PCa (CRPC). In this study, therefore, we investigated the metabolic profiles in prostate tissues from patients with benign prostatic hyperplasia (BPH), HSPC and CRPC using a 1H NMR-based metabolomics approach. The results show that clear separations in metabolic patterns were obtained in prostate tissues among BPH, HSPC and CRPC; however, CRPC may induce metabolic shift toward BPH, mainly involving amino acid metabolism, choline metabolism and the Warburg effect. Based on these metabolic changes, we identified potential biomarker panels for the discrimination between BPH vs. HSPC, BPH vs. CRPC, and HSPC vs. CRPC with the AUC values of 0.995, 0.972 and 0.937, respectively. Collectively, tissue-based metabolomics analysis not only identifies the altered metabolic pathways during PCa progression, but also has potential to help the classification and diagnosis of PCa in clinical practice. PMID: 32702989 [PubMed - as supplied by publisher]

Related Articles Amino acid and lipid metabolism in post-gestational diabetes and progression to type 2 diabetes: A metabolic profiling study. PLoS Med. 2020 05;17(5):e1003112 Authors: Lai M, Liu Y, Ronnett GV, Wu A, Cox BJ, Dai FF, Röst HL, Gunderson EP, Wheeler MB Abstract BACKGROUND: Women with a history of gestational diabetes mellitus (GDM) have a 7-fold higher risk of developing type 2 diabetes (T2D) during midlife and an elevated risk of developing hypertension and cardiovascular disease. Glucose tolerance reclassification after delivery is recommended, but fewer than 40% of women with GDM are tested. Thus, improved risk stratification methods are needed, as is a deeper understanding of the pathology underlying the transition from GDM to T2D. We hypothesize that metabolites during the early postpartum period accurately distinguish risk of progression from GDM to T2D and that metabolite changes signify underlying pathophysiology for future disease development. METHODS AND FINDINGS: The study utilized fasting plasma samples collected from a well-characterized prospective research study of 1,035 women diagnosed with GDM. The cohort included racially/ethnically diverse pregnant women (aged 20-45 years-33% primiparous, 37% biparous, 30% multiparous) who delivered at Kaiser Permanente Northern California hospitals from 2008 to 2011. Participants attended in-person research visits including 2-hour 75-g oral glucose tolerance tests (OGTTs) at study baseline (6-9 weeks postpartum) and annually thereafter for 2 years, and we retrieved diabetes diagnoses from electronic medical records for 8 years. In a nested case-control study design, we collected fasting plasma samples among women without diabetes at baseline (n = 1,010) to measure metabolites among those who later progressed to incident T2D or did not develop T2D (non-T2D). We studied 173 incident T2D cases and 485 controls (pair-matched on BMI, age, and race/ethnicity) to discover metabolites associated with new onset of T2D. Up to 2 years post-baseline, we analyzed samples from 98 T2D cases with 239 controls to reveal T2D-associated metabolic changes. The longitudinal analysis tracked metabolic changes within individuals from baseline to 2 years of follow-up as the trajectory of T2D progression. By building prediction models, we discovered a distinct metabolic signature in the early postpartum period that predicted future T2D with a median discriminating power area under the receiver operating characteristic curve of 0.883 (95% CI 0.820-0.945, p < 0.001). At baseline, the most striking finding was an overall increase in amino acids (AAs) as well as diacyl-glycerophospholipids and a decrease in sphingolipids and acyl-alkyl-glycerophospholipids among women with incident T2D. Pathway analysis revealed up-regulated AA metabolism, arginine/proline metabolism, and branched-chain AA (BCAA) metabolism at baseline. At follow-up after the onset of T2D, up-regulation of AAs and down-regulation of sphingolipids and acyl-alkyl-glycerophospholipids were sustained or strengthened. Notably, longitudinal analyses revealed only 10 metabolites associated with progression to T2D, implicating AA and phospholipid metabolism. A study limitation is that all of the analyses were performed with the same cohort. It would be ideal to validate our findings in an independent longitudinal cohort of women with GDM who had glucose tolerance tested during the early postpartum period. CONCLUSIONS: In this study, we discovered a metabolic signature predicting the transition from GDM to T2D in the early postpartum period that was superior to clinical parameters (fasting plasma glucose, 2-hour plasma glucose). The findings suggest that metabolic dysregulation, particularly AA dysmetabolism, is present years prior to diabetes onset, and is revealed during the early postpartum period, preceding progression to T2D, among women with GDM. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01967030. PMID: 32433647 [PubMed - indexed for MEDLINE]