PubMed

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 2019/03/19PubMed 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.

The association of sleep with metabolic pathways and metabolites: evidence from the Dietary Approaches to Stop Hypertension (DASH)-sodium feeding study. Metabolomics. 2019 Mar 16;15(4):48 Authors: Gordon-Dseagu VLZ, Derkach A, Xiao Q, Williams I, Sampson J, Stolzenberg-Solomon RZ Abstract INTRODUCTION: Sleep is increasingly being viewed as an issue of public health concern, yet few epidemiologic studies have explored associations between sleep habits and metabolomic profile. OBJECTIVES: To assess the association between sleep and blood metabolites. METHODS: We examined the association between sleep and 891 fasting plasma metabolites in a subgroup of 106 participants from the Dietary Approaches to Stop Hypertension (DASH)-Sodium feeding trial (1997-1999). We produced two sleep variables to analyze, sleep midpoint (median time between bedtime and waketime) and sleep duration, as well as bedtime and wake time. Metabolites were measured using liquid and gas chromatography, coupled with mass spectrometry. We assessed associations between sleep variables and log transformed metabolites using linear mixed-effects models. We combined the resulting p-values using Fisher's method to calculate associations between sleep and 38 metabolic pathways. RESULTS: Sixteen pathways were associated (p < 0.05) with midpoint. Only the γ-glutamyl amino acid metabolism pathway reached Bonferroni-corrected threshold (0.0013). Eighty-three metabolites were associated with midpoint (FDR < 0.20). Similar associations were found for wake time. Neither bed time nor duration were strongly associated. The top metabolites (pathways given in brackets) associated with sleep were erythrulose (advanced glycation end-product) (positive association) and several γ-glutamyl pathway metabolites, including CMPF (fatty acid, dicarboxylate), isovalerate (valine, leucine and isoleucine and fatty acid metabolism) and HWESASXX (polypeptide) (inverse association). CONCLUSION: Within our study, several metabolites that have previously been linked to inflammation and oxidative stress (processes involved in diseases such as cardiovascular disease and cancer) were found to be associated with sleep. PMID: 30879189 [PubMed - in process]

High-throughput quantitative analysis of phytohormones in sorghum leaf and root tissue by ultra-performance liquid chromatography-mass spectrometry. Anal Bioanal Chem. 2019 Mar 16;: Authors: Sheflin AM, Kirkwood JS, Wolfe LM, Jahn CE, Broeckling CD, Schachtman DP, Prenni JE Abstract Plant development, growth, and adaptation to stress are regulated by phytohormones, which can influence physiology even at low concentrations. Phytohormones are chemically grouped according to both structure and function as auxins, cytokinins, abscisic acid, jasmonates, salicylates, gibberellins, and brassinosteroids, among others. This chemical diversity and requirement for highly sensitive detection in complex matrices create unique challenges for comprehensive phytohormone analysis. Here, we present a robust and efficient quantitative UPLC-MS/MS assay for 17 phytohormones, including jasmonates, salicylates, abscisic acid, gibberellins, cytokinins, and auxins. Using this assay, 12 phytohormones were detected and quantified in sorghum plant tissue without the need for solid phase extraction (SPE) or liquid-liquid extraction. Variation of phytohormone profiles was explored in both root and leaf tissues between three genotypes, harvested at two different developmental time points. The results highlight the importance of tissue type, sampling time, and genetic factors when designing experiments that involve phytohormone analysis of sorghum. This research lays the groundwork for future studies, which can combine phytohormone profiling with other datasets such as transcriptome, soil microbiome, genome, and metabolome data, to provide important functional information about adaptation to stress and other environmental variables. PMID: 30879116 [PubMed - as supplied by publisher]

An untargeted metabolomic strategy based on liquid chromatography-mass spectrometry to study high glucose-induced changes in HK-2 cells. J Chromatogr A. 2019 Mar 06;: Authors: Bernardo-Bermejo S, Sánchez-López E, Castro-Puyana M, Benito S, Lucio-Cazaña FJ, Marina ML Abstract Diabetes mellitus is a major health concern nowadays. It is estimated that 40% of diabetics are affected by diabetic nephropathy, one of the complications derived from high glucose blood levels which can lead to chronic loss of kidney function. It is now clear that the renal proximal tubule plays a critical role in the progression of diabetic nephropathy but research focused on studying the molecular mechanisms involved is still needed. The aim of this work was to develop a liquid chromatography-mass spectrometry platform to carry out, for the first time, the untargeted metabolomic analysis of high glucose-induced changes in cultured human proximal tubular HK-2 cells. In order to find the metabolites which were affected by high glucose and to expand the metabolite coverage, intra- and extracellular fluid from HK-2 cells exposed to high glucose (25 mM), normal glucose (5.5 mM) or osmotic control (5.5 mM glucose +19.5 mM mannitol) were analyzed by two complementary chromatographic modes: hydrophilic interaction and reversed-phase liquid chromatography. Non-supervised principal components analysis showed a good separation among the three groups of samples. Statistically significant variables were chosen for further metabolite identification. Different metabolic pathways were affected mainly those derived from amino acidic, polyol, and nitrogenous bases metabolism. PMID: 30878178 [PubMed - as supplied by publisher]

Related Articles Metabolome-based signature of disease pathology in MS. Mult Scler Relat Disord. 2019 Mar 09;31:12-21 Authors: Andersen SL, Briggs FBS, Winnike JH, Natanzon Y, Maichle S, Knagge KJ, Newby LK, Gregory SG Abstract BACKGROUND: Diagnostic delays are common for multiple sclerosis (MS) since diagnosis typically depends on the presentation of nonspecific clinical symptoms together with radiologically-determined central nervous system (CNS) lesions. It is important to reduce diagnostic delays as earlier initiation of disease modifying therapies mitigates long-term disability. Developing a metabolomic blood-based MS biomarker is attractive, but prior efforts have largely focused on specific subsets of metabolite classes or analytical platforms. Thus, there are opportunities to interrogate metabolite profiles using more expansive and comprehensive approaches for developing MS biomarkers and for advancing our understanding of MS pathogenesis. METHODS: To identify putative blood-based MS biomarkers, we comprehensively interrogated the metabolite profiles in 12 non-Hispanic white, non-smoking, male MS cases who were drug naïve for 3 months prior to biospecimen collection and 13 non-Hispanic white, non-smoking male controls who were frequency matched to cases by age and body mass index. We performed untargeted two-dimensional gas chromatography and time-of-flight mass spectrometry (GCxGC-TOFMS) and targeted lipidomic and amino acid analysis on serum. 325 metabolites met quality control and supervised machine learning was used to identify metabolites most informative for MS status. The discrimination potential of these select metabolites were assessed using receiver operator characteristic curves based on logistic models; top candidate metabolites were defined as having area under the curves (AUC) >80%. The associations between whole-genome expression data and the top candidate metabolites were examined, followed by pathway enrichment analyses. Similar associations were examined for 175 putative MS risk variants and the top candidate metabolites. RESULTS: 12 metabolites were determined to be informative for MS status, of which 6 had AUCs >80%: pyroglutamate, laurate, acylcarnitine C14:1, N-methylmaleimide, and 2 phosphatidylcholines (PC ae 40:5, PC ae 42:5). These metabolites participate in glutathione metabolism, fatty acid metabolism/oxidation, cellular membrane composition, and transient receptor potential channel signaling. Pathway analyses based on the gene expression association for each metabolite suggested enrichment for pathways associated with apoptosis and mitochondrial dysfunction. Interestingly, the predominant MS genetic risk allele HLA-DRB1×15:01 was associated with one of the 6 top metabolites. CONCLUSION: Our analysis represents the most comprehensive description of metabolic changes associated with MS in serum, to date, with the inclusion of genomic and genetic information. We identified atypical metabolic processes that differed between MS patients and controls, which may enable the development of biological targets for diagnosis and treatment. PMID: 30877925 [PubMed - as supplied by publisher]

Related Articles Mitochondria in precision medicine; linking bioenergetics and metabolomics in platelets. Redox Biol. 2019 Mar 10;22:101165 Authors: Chacko BK, Smith MR, Johnson MS, Benavides G, Culp ML, Pilli J, Shiva S, Uppal K, Go YM, Jones DP, Darley-Usmar VM Abstract Mitochondria possess reserve bioenergetic capacity, supporting protection and resilience in the face of disease. Approaches are limited to understand factors that impact mitochondrial functional reserve in humans. We applied the mitochondrial stress test (MST) to platelets from healthy subjects and found correlations between energetic parameters and mitochondrial function. These parameters were not correlated with mitochondrial complex I-IV activities, however, suggesting that other factors affect mitochondrial bioenergetics and metabolism. Platelets from African American patients with sickle cell disease also differed from controls, further showing that other factors impact mitochondrial bioenergetics and metabolism. To test for correlations of platelet metabolites with energetic parameters, we performed an integrated analysis of metabolomics and MST parameters. Subsets of metabolites, including fatty acids and xenobiotics correlated with mitochondrial parameters. The results establish platelets as a platform to integrate bioenergetics and metabolism for analysis of mitochondrial function in precision medicine. PMID: 30877854 [PubMed - as supplied by publisher]

Related Articles Tribute Roland Douce, 1939-2018. Photosynth Res. 2019 Mar 15;: Authors: Joyard J, Lichtenthaler HK Abstract On November 4, 2018, Roland Douce, Professor Emeritus at the University of Grenoble, France, died at the age of 79. In Grenoble, where he spent most of his scientific career, Roland Douce created a world-renowned school of plant science, studying the structure, functions, and interactions of plant organelles involved in photosynthesis, respiration, and photorespiration. His main achievements concern the chemical and functional characterization of chloroplast envelope membranes, the demonstration of the uniqueness of plant mitochondria, and the integration of metabolism within the plant cell, among manifold activities. Roland Douce devoted his whole life to science and research with passion and enthusiasm: he was a true charismatic leader. PMID: 30877517 [PubMed - as supplied by publisher]

Related Articles Recent developments in metabolomics-based research in understanding transgenic grass metabolism. Metabolomics. 2019 Mar 15;15(4):47 Authors: Boonchaisri S, Rochfort S, Stevenson T, Dias DA Abstract BACKGROUND: Transgenic herbicide-resistant (HR) turfgrass together with its associated, broad spectrum herbicides promise cheap, selective and efficient weed control by excluding infested weeds resulting in turf lawn with high uniformity and aesthetic value. The concept of this "weeding program" initiated from modern biotechnology has been widely implemented in several principal crops including maize, soybean, canola and cotton as early as the 1990s. Transgenic HR turfgrass classified as a genetically modified organism (GMO) has undoubtedly caused public concern with respect to its biosafety and legalities similar to well-established HR crops. Nevertheless, applying metabolomics-based approaches which focuses on the identification of the global metabolic state of a biological system in response to either internal or external stimuli can also provide a comprehensive characterization of transgenic grass metabolism and its involvement in biosecurity and public perception. AIM OF REVIEW: This review summaries the recent applications of metabolomics applied to HR crops to predict the molecular and physiological phenotypes of HR turfgrass species, glyphosate-resistant Kentucky bluegrass (Poa pratensis L.) and glufosinate-resistant creeping bentgrass (Agrotis stonifera L.). Additionally, this review also presents background knowledge with respect to the application of metabolomics, transformation of HR crops and its biosafety concerns, turfgrass botanical knowledge and its economic and aesthetic value. KEY SCIENTIFIC CONCEPTS OF REVIEW: The purpose of this review is to demonstrate the molecular and physiological phenotypes of HR turfgrass based on several lines of evidence primarily derived from metabolomics data applied to HR crops to identify alterations on HR turfgrass metabolism as a result of genetic modification that confers resistant traits. PMID: 30877485 [PubMed - in process]

Related Articles Resolving coral photoacclimation dynamics through coupled photophysiological and metabolomic profiling. J Exp Biol. 2019 Mar 15;: Authors: Lohr KE, Camp EF, Kuzhiumparambil U, Lutz A, Leggat W, Patterson JT, Suggett DJ Abstract Corals continuously adjust to short term variation in light availability on shallow reefs. Long-term light alterations can also occur due to natural and anthropogenic stressors, as well as management interventions such as coral transplantation. Although short term photophysiological responses are relatively well-understood in corals, little information is available regarding photoacclimation dynamics over weeks of altered light availability. We coupled photophysiology and metabolomic profiling to explore changes that accompany longer-term photoacclimation in a key Great Barrier Reef coral species (Acropora muricata). High (HL) and low light (LL) acclimated corals were collected from the reef and reciprocally exposed to high and low light ex situ Rapid light curves using Pulse Amplitude Modulation (PAM) fluorometry revealed photophysiological acclimation of LL to HL and HL to LL shifted corals within 21 days. A subset of colonies sampled at 7 and 21 days for untargeted LC-MS and GC-MS metabolomic profiling revealed metabolic reorganization before acclimation was detected using PAM fluorometry. Metabolomic shifts were more pronounced for LL to HL treated corals than their HL to LL counterparts. Compounds driving metabolomic separation between HL-exposed and LL control colonies included amino acids, organic acids, fatty acids and sterols. Reduced glycerol and campesterol suggest decreased translocation of photosynthetic products from symbiont to host in LL to HL shifted corals, with concurrent increases in fatty acid abundance indicating reliance on stored lipids for energy. We discuss how these data provide novel insight into environmental regulation of metabolism and implications for management strategies that drive rapid changes in light availability. PMID: 30877226 [PubMed - as supplied by publisher]

34 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 2019/03/16PubMed 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.

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 2019/03/15PubMed 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.

17 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 2019/03/14PubMed 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.

16 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 2019/03/13PubMed 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.

16 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 2019/03/13PubMed 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 2019/03/12PubMed 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 2019/03/12PubMed 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.

Correction to: Answering biological questions by analysis of the strawberry metabolome. Metabolomics. 2019 Mar 09;15(3):40 Authors: Haugeneder A, Trinkl J, Härtl K, Hoffmann T, Allwood JW, Schwab W Abstract The article Answering biological questions by analysis of the strawberry metabolome, written by Annika Haugeneder, Johanna Trinkl, Katja Härtl, Thomas Hoffman, James William Allwood and Wilfred Schwab, was originally published electronically on the publisher's internet portal (currently SpringerLink) on 26 OCtober, 2018 without open access. After publication in volume 14. Issue 11, Citation Id 145, with the author(s)' decision to opt for Open Choice the copyright of the article changed on 20 December, 2018 to © The Author(s) [Year] and the article is forthwith distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. PMID: 30852678 [PubMed - in process]

ColocalizR: An open-source application for cell-based high-throughput colocalization analysis. Comput Biol Med. 2019 Mar 02;107:227-234 Authors: Sauvat A, Leduc M, Müller K, Kepp O, Kroemer G Abstract The microscopic assessment of the colocalization of fluorescent signals has been widely used in cell biology. Although imaging techniques have drastically improved over the past decades, the quantification of colocalization by measures such as the Pearson correlation coefficient or Manders overlap coefficient, has not changed. Here, we report the development of an R-based application that allows to (i) automatically segment cells and subcellular compartments, (ii) measure morphology and texture features, and (iii) calculate the degree of colocalization within each cell. Colocalization can thus be studied on a cell-by-cell basis, permitting to perform statistical analyses of cellular populations and subpopulations. ColocalizR has been designed to parallelize tasks, making it applicable to the analysis of large data sets. Its graphical user interface makes it suitable for researchers without specific knowledge in image analysis. Moreover, results can be exported into a wide range of formats rendering post-analysis adaptable to statistical requirements. This application and its source code are freely available at https://github.com/kroemerlab/ColocalizR. PMID: 30852249 [PubMed - as supplied by publisher]

Resveratrol and other dietary polyphenols are inhibitors of estrogen metabolism in human breast cancer cells. J Steroid Biochem Mol Biol. 2019 Mar 06;: Authors: Poschner S, Maier-Salamon A, Thalhammer T, Jäger W Abstract Polyphenols in foods and dietary supplements are commonly used for the prevention and treatment of a variety of malignancies, including breast cancer. However, daily intake by patients with breast cancer is controversial, as these compounds may stimulate cancer growth. Estrogens serve key roles in breast cancer cell proliferation; therefore, understanding the interaction between endogenous steroid hormones and natural dietary polyphenols is essential. Currently, comprehensive knowledge regarding these effects remains limited. The current review summarizes the dose-dependent in vitro and in vivo interactions of resveratrol and other dietary polyphenols with estrogen precursors, active estrogens, catechol estrogens and their respective glucuronidated, sulfated, glutathionated or O-methylated metabolites in estrogen receptor alpha negative (ERα-) and positive (ERα+) breast cancer. Which estrogen-metabolizing enzymes are affected by polyphenols is also reviewed in detail. Furthermore, the impacts of dose and therapy duration on disease development and progression in patients with breast cancer are discussed. The present article is part of a Special Issue titled 'CSR 2018'. PMID: 30851384 [PubMed - as supplied by publisher]

Interoperable and scalable data analysis with microservices: Applications in Metabolomics. Bioinformatics. 2019 Mar 09;: Authors: Emami Khoonsari P, Moreno P, Bergmann S, Burman J, Capuccini M, Carone M, Cascante M, de Atauri P, Foguet C, Gonzalez-Beltran A, Hankemeier T, Haug K, He S, Herman S, Johnson D, Kale N, Larsson A, Neumann S, Peters K, Pireddu L, Rocca-Serra P, Roger P, Rueedi R, Ruttkies C, Sadawi N, Salek RM, Sansone SA, Schober D, Selivanov V, Thévenot EA, van Vliet M, Zanetti G, Steinbeck C, Kultima K, Spjuth O Abstract MOTIVATION: Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator. RESULTS: We developed a virtual research environment which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics, and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. AVAILABILITY AND IMPLEMENTATION: The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the virtual research environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. PMID: 30851093 [PubMed - as supplied by publisher]