PubMed

Related Articles Rapid in situ (13)C tracing of sucrose utilization in Arabidopsis sink and source leaves. Plant Methods. 2017;13:87 Authors: Dethloff F, Orf I, Kopka J Abstract BACKGROUND: Conventional metabolomics approaches face the problem of hidden metabolic phenotypes where only fluxes are altered but pool sizes stay constant. Metabolic flux experiments are used to detect such hidden flux phenotypes. These experiments are, however, time consuming, may be cost intensive, and involve specialists for modeling. We fill the gap between conventional metabolomics and flux modeling. We present rapid stable isotope tracing assays and analysis strategies of (13)C labeling data. For this purpose, we combine the conventional metabolomics approach that detects significant relative changes of metabolite pool sizes with analyses of differential utilization of (13)C labeled carbon. As a test case, we use uniformly labeled (13)C-sucrose. RESULTS: We present petiole and hypocotyl feeding assays for the rapid in situ feeding (≤ 4 h) of isotopically labeled metabolic precursor to whole Arabidopsis thaliana rosettes. The assays are assessed by conventional gas chromatography-mass spectrometry based metabolite profiling that was extended by joined differential analysis of (13)C-labeled sub-pools and of (13)C enrichment of metabolites relative to the enrichment of (13)C-sucrose within each sample. We apply these analyses to the sink to source transition continuum of leaves from single A. thaliana rosettes and characterize the associated relative changes of metabolite pools, as well as previously hidden changes of sucrose-derived carbon partitioning. We compared the contribution of sucrose as a carbon source in predominantly sink to predominantly source leaves and identified a set of primary metabolites with differential carbon utilization during sink to source transition. CONCLUSION: The presented feeding assays and data evaluation strategies represent a rapid and easy-to-use tool box for enhanced metabolomics studies that combine differential pool size analysis with screening for differential carbon utilization from defined stable isotope labeled metabolic precursors. PMID: 29075313 [PubMed]

Related Articles Phenolic Profiling for Traceability of Vanilla ×tahitensis. Front Plant Sci. 2017;8:1746 Authors: Busconi M, Lucini L, Soffritti G, Bernardi J, Bernardo L, Brunschwig C, Lepers-Andrzejewski S, Raharivelomanana P, Fernandez JA Abstract Vanilla is a flavoring recovered from the cured beans of the orchid genus Vanilla. Vanilla ×tahitensis is traditionally cultivated on the islands of French Polynesia, where vanilla vines were first introduced during the nineteenth century and, since the 1960s, have been introduced to other Pacific countries such as Papua New Guinea (PNG), cultivated and sold as "Tahitian vanilla," although both sensory properties and aspect are different. From an economic point of view, it is important to ensure V. ×tahitensis traceability and to guarantee that the marketed product is part of the future protected designation of the origin "Tahitian vanilla" (PDO), currently in progress in French Polynesia. The application of metabolomics, allowing the detection and simultaneous analysis of hundreds or thousands of metabolites from different matrices, has recently gained high interest in food traceability. Here, metabolomics analysis of phenolic compounds profiles was successfully applied for the first time to V. ×tahitensis to deepen our knowledge of vanilla metabolome, focusing on phenolics compounds, for traceability purposes. Phenolics were screened through a quadrupole-time-of-flight mass spectrometer coupled to a UHPLC liquid chromatography system, and 260 different compounds were clearly evidenced and subjected to different statistical analysis in order to enable the discrimination of the samples based on their origin. Eighty-eight and twenty three compounds, with a prevalence of flavonoids, resulted to be highly discriminant through ANOVA and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) respectively. Volcano plot analysis and pairwise comparisons were carried out to determine those compounds, mainly responsible for the differences among samples as a consequence of either origin or cultivar. The samples from PNG were clearly different from the Tahitian samples that were further divided in two different groups based on the different phenolic patterns. Among the 260 compounds, metabolomics analysis enabled the detection of previously unreported phenolics in vanilla (such as flavonoids, lignans, stilbenes and other polyphenols). PMID: 29075276 [PubMed]

Related Articles 5H-benzo[h]thiazolo[2,3-b]quinazolines ameliorate NDEA-induced hepatocellular carcinogenesis in rats through IL-6 downregulation along with oxidative and metabolic stress reduction. Drug Des Devel Ther. 2017;11:2981-2995 Authors: Keshari AK, Singh AK, Kumar U, Raj V, Rai A, Kumar P, Kumar D, Maity B, Nath S, Prakash A, Saha S Abstract 5H-benzo[h]thiazolo[2,3-b]quinazoline scaffold is known to have an antitumor effect on certain types of malignancies; however, its effect on hepatocellular carcinoma (HCC) remains unclear. Previously, we reported p-toluenesulfonic acid-promoted syntheses, molecular modeling and in vitro antitumor activity of 5H-benzo[h]thiazolo[2,3-b]quinazoline against human hepatoma (Hep-G2) cells where compounds 4A and 6A were found to be potent inhibitors among the series. In continuation to our previous effort to develop novel therapeutic strategies for HCC treatment, here we investigated the in vivo antitumor activity and the mechanism underlying the effects of 4A and 6A in N-nitrosodiethylamine (NDEA)-induced HCC using male Wistar rats. NDEA was administered weekly intraperitoneally at a dose of 100 mg/kg for 6 weeks. Various physiological and morphological changes, oxidative parameters, liver marker enzymes and cytokines were assessed to evaluate the antitumor effect of 4A and 6A. In addition, proton nuclear magnetic resonance-based serum metabolomics were performed to analyze the effects of 4A and 6A against HCC-induced metabolic alterations. Significant tumor incidences with an imbalance in carcinogen metabolizing enzymes and cellular redox status were observed in carcinogenic rats. Tumor inhibitory effects of 4A and 6A were noted by histopathology and biochemical profiles in NDEA-induced hepatic cancer. Compounds 4A and 6A had a potential role in normalizing the elevated levels of inflammatory mediators such as interleukin-1β (IL-1β), IL-2, IL-6 and IL-10. At molecular level, the real-time quantitative reverse-transcribed polymerase chain reaction analysis revealed that 4A and 6A attenuated the IL-6 gene overexpression in hepatic cancer. Further, orthogonal partial least squares discriminant analysis scores plot demonstrated a significant separation of 4A and 6A-treated groups from carcinogen control group. Both the compounds have potential to restore the imbalanced metabolites due to HCC, signifying promising hepatoprotective activities. All these findings suggested that 4A and 6A could be potential drug candidates to treat HCC. PMID: 29075102 [PubMed - in process]

Related Articles Conversion of PRPS hexamer to monomer by AMPK-mediated phosphorylation inhibits nucleotide synthesis in response to energy stress. Cancer Discov. 2017 Oct 26;: Authors: Qian X, Li X, Tan L, Lee JH, Xia Y, Cai Q, Zheng Y, Wang H, Lorenzi PL, Lu Z Abstract Tumors override energy stress to grow. However, how nucleotide synthesis is regulated under energy stress is unclear. We demonstrate here that glucose deprivation or hypoxia results in the AMPK-mediated phosphorylation of phosphoribosyl pyrophosphate synthetase (PRPS) 1 S180 and PRPS2 S183, leading to conversion of PRPS hexamers to monomers and thereby inhibiting PRPS1/2 activity, nucleotide synthesis, and nicotinamide adenine dinucleotide (NAD) production. Knock-in of non-phosphorylatable PRPS1/2 mutants, which have uninhibited activity, in brain tumor cells under energy stress exhausts cellular ATP and NADPH and increases ROS levels, thereby promoting cell apoptosis. The expression of those mutants inhibits brain tumor formation and enhances the inhibitory effect of the glycolysis inhibitor 2-deoxy-D-glucose on tumor growth. Our findings highlight the significance of recalibrating tumor cell metabolism by fine tuning nucleotide and NAD synthesis in tumor growth. PMID: 29074724 [PubMed - as supplied by publisher]

Related Articles Lysosomal metabolomics reveals V-ATPase and mTOR-dependent regulation of amino acid efflux from lysosomes. Science. 2017 Oct 26;: Authors: Abu-Remaileh M, Wyant GA, Kim C, Laqtom NN, Abbasi M, Chan SH, Freinkman E, Sabatini DM Abstract The lysosome degrades and recycles macromolecules, signals to the cytosol and nucleus, and is implicated in many diseases. Here, we describe a method for the rapid isolation of mammalian lysosomes and use it to quantitatively profile lysosomal metabolites under various cell states. Under nutrient replete conditions, many lysosomal amino acids are in rapid exchange with those in the cytosol. Loss of lysosomal acidification through inhibition of the vacuolar H+ATPase (V-ATPase) increased the luminal concentrations of most metabolites but had no effect on those of the majority of essential amino acids. Instead, nutrient starvation regulates the lysosomal concentrations of these amino acids, an effect we traced to regulation of the mTOR pathway. Inhibition of mTOR strongly reduced the lysosomal efflux of most essential amino acids, converting the lysosome into a cellular depot for them. These results reveal the dynamic nature of lysosomal metabolites and that V-ATPase- and mTOR-dependent mechanisms exist for controlling lysosomal amino acid efflux. PMID: 29074583 [PubMed - as supplied by publisher]

Related Articles Metabolomics applied to diabetes - lessons from human population studies. Int J Biochem Cell Biol. 2017 Oct 23;: Authors: Liggi S, Griffin JL Abstract The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism. PMID: 29074437 [PubMed - as supplied by publisher]

Related Articles Data acquisition workflows in liquid chromatography coupled to high resolution mass spectrometry-based metabolomics: Where do we stand? J Chromatogr A. 2017 Oct 18;: Authors: Fenaille F, Barbier Saint-Hilaire P, Rousseau K, Junot C Abstract Typical mass spectrometry (MS) based untargeted metabolomics protocols are tedious as well as time- and sample-consuming. In particular, they often rely on "full-scan-only" analyses using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) from which metabolites of interest are first highlighted, and then tentatively identified by using targeted MS/MS experiments. However, this situation is evolving with the emergence of integrated HRMS based-data acquisition protocols able to perform multi-event acquisitions. Most of these protocols, referring to as data dependent and data independent acquisition (DDA and DIA, respectively), have been initially developed for proteomic applications and have recently demonstrated their applicability to biomedical studies. In this context, the aim of this article is to take stock of the progress made in the field of DDA- and DIA-based protocols, and evaluate their ability to change conventional metabolomic and lipidomic data acquisition workflows, through a review of HRMS instrumentation, DDA and DIA workflows, and also associated informatics tools. PMID: 29074071 [PubMed - as supplied by publisher]

Related Articles Serial-omics characterization of equine urine. PLoS One. 2017;12(10):e0186258 Authors: Yuan M, Breitkopf SB, Asara JM Abstract Horse urine is easily collected and contains molecules readily measurable using mass spectrometry that can be used as biomarkers representative of health, disease or drug tampering. This study aimed at analyzing microliter levels of horse urine to purify, identify and quantify proteins, polar metabolites and non-polar lipids. Urine from a healthy 12 year old quarter horse mare on a diet of grass hay and vitamin/mineral supplements with limited pasture access was collected for serial-omics characterization. The urine was treated with methyl tert-butyl ether (MTBE) and methanol to partition into three distinct layers for protein, non-polar lipid and polar metabolite content from a single liquid-liquid extraction and was repeated two times. Each layer was analyzed by high performance liquid chromatography-high resolution tandem mass spectrometry (LC-MS/MS) to obtain protein sequence and relative protein levels as well as identify and quantify small polar metabolites and lipids. The results show 46 urine proteins, many related to normal kidney function, structural and circulatory proteins as well as 474 small polar metabolites but only 10 lipid molecules. Metabolites were mostly related to urea cycle and ammonia recycling as well as amino acid related pathways, plant diet specific molecules, etc. The few lipids represented triglycerides and phospholipids. These data show a complete mass spectrometry based-omics characterization of equine urine from a single 333 μL mid-stream urine aliquot. These omics data help serve as a baseline for healthy mare urine composition and the analyses can be used to monitor disease progression, health status, monitor drug use, etc. PMID: 29028822 [PubMed - indexed for MEDLINE]

Related Articles Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data. Am J Hum Genet. 2017 Sep 07;101(3):340-352 Authors: He Z, Xu B, Lee S, Ionita-Laza I Abstract Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. PMID: 28844485 [PubMed - indexed for MEDLINE]

Related Articles Aneuploid Cell Survival Relies upon Sphingolipid Homeostasis. Cancer Res. 2017 Oct 01;77(19):5272-5286 Authors: Tang YC, Yuwen H, Wang K, Bruno PM, Bullock K, Deik A, Santaguida S, Trakala M, Pfau SJ, Zhong N, Huang T, Wang L, Clish CB, Hemann MT, Amon A Abstract Aneuploidy, a hallmark of cancer cells, poses an appealing opportunity for cancer treatment and prevention strategies. Using a cell-based screen to identify small molecules that could selectively kill aneuploid cells, we identified the compound N-[2-hydroxy-1-(4-morpholinylmethyl)-2-phenylethyl]-decanamide monohydrochloride (DL-PDMP), an antagonist of UDP-glucose ceramide glucosyltransferase. DL-PDMP selectively inhibited proliferation of aneuploid primary mouse embryonic fibroblasts and aneuploid colorectal cancer cells. Its selective cytotoxic effects were based on further accentuating the elevated levels of ceramide, which characterize aneuploid cells, leading to increased apoptosis. We observed that DL-PDMP could also enhance the cytotoxic effects of paclitaxel, a standard-of-care chemotherapeutic agent that causes aneuploidy, in human colon cancer and mouse lymphoma cells. Our results offer pharmacologic evidence that the aneuploid state in cancer cells can be targeted selectively for therapeutic purposes, or for reducing the toxicity of taxane-based drug regimens. Cancer Res; 77(19); 5272-86. ©2017 AACR. PMID: 28775166 [PubMed - indexed for MEDLINE]

Related Articles A distinct plasma lipid signature associated with poor prognosis in castration-resistant prostate cancer. Int J Cancer. 2017 Nov 15;141(10):2112-2120 Authors: Lin HM, Mahon KL, Weir JM, Mundra PA, Spielman C, Briscoe K, Gurney H, Mallesara G, Marx G, Stockler MR, PRIMe Consortium, Parton RG, Hoy AJ, Daly RJ, Meikle PJ, Horvath LG Abstract Lipids are known to influence tumour growth, inflammation and chemoresistance. However, the association of circulating lipids with the clinical outcome of metastatic castration-resistant prostate cancer (CRPC) is unknown. We investigated associations between the plasma lipidome and clinical outcome in CRPC. Lipidomic profiling by liquid chromatography-tandem mass spectrometry was performed on plasma samples from a Phase 1 discovery cohort of 96 CRPC patients. Results were validated in an independent Phase 2 cohort of 63 CRPC patients. Unsupervised analysis of lipidomic profiles (323 lipid species) classified the Phase 1 cohort into two patient subgroups with significant survival differences (HR 2.31, 95% CI 1.44-3.68, p = 0.0005). The levels of 46 lipids were individually prognostic and were predominantly sphingolipids with higher levels associated with poor prognosis. A prognostic three-lipid signature was derived (ceramide d18:1/24:1, sphingomyelin d18:2/16:0, phosphatidylcholine 16:0/16:0) and was also associated with shorter survival in the Phase 2 cohort (HR 4.8, 95% CI 2.06-11.1, p = 0.0003). The signature was an independent prognostic factor when modelled with clinicopathological factors or metabolic characteristics. The association of plasma lipids with CRPC prognosis suggests a possible role of these lipids in disease progression. Further research is required to determine if therapeutic modulation of the levels of these lipids by targeting their metabolic pathways may improve patient outcome. PMID: 28741687 [PubMed - indexed for MEDLINE]

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 2017/10/27PubMed 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 Cellular bioenergetics is impaired in patients with chronic fatigue syndrome. PLoS One. 2017;12(10):e0186802 Authors: Tomas C, Brown A, Strassheim V, Elson J, Newton J, Manning P Abstract Chronic fatigue syndrome (CFS) is a highly debilitating disease of unknown aetiology. Abnormalities in bioenergetic function have been cited as one possible cause for CFS. Preliminary studies were performed to investigate cellular bioenergetic abnormalities in CFS patients. A series of assays were conducted using peripheral blood mononuclear cells (PBMCs) from CFS patients and healthy controls. These experiments investigated cellular patterns in oxidative phosphorylation (OXPHOS) and glycolysis. Results showed consistently lower measures of OXPHOS parameters in PBMCs taken from CFS patients compared with healthy controls. Seven key parameters of OXPHOS were calculated: basal respiration, ATP production, proton leak, maximal respiration, reserve capacity, non-mitochondrial respiration, and coupling efficiency. While many of the parameters differed between the CFS and control cohorts, maximal respiration was determined to be the key parameter in mitochondrial function to differ between CFS and control PBMCs due to the consistency of its impairment in CFS patients found throughout the study (p≤0.003). The lower maximal respiration in CFS PBMCs suggests that when the cells experience physiological stress they are less able to elevate their respiration rate to compensate for the increase in stress and are unable to fulfil cellular energy demands. The metabolic differences discovered highlight the inability of CFS patient PBMCs to fulfil cellular energetic demands both under basal conditions and when mitochondria are stressed during periods of high metabolic demand. PMID: 29065167 [PubMed - in process]

Related Articles How to model temporal changes in non-targeted metabolomics study? A Bayesian multilevel perspective. J Sep Sci. 2017 Oct 24;: Authors: Wiczling P, Daghir-Wojtkowiak E, Yumba Mpanga A, Szczesny D, Kaliszan R, Markuszewski MJ Abstract Analysis of time series data addresses the question on mechanisms underlying normal physiology and its alteration under pathological conditions. However, adding time variable to high-dimension, collinear, noisy data is a challenge in terms of mining and analysis. Here, we used Bayesian multilevel modeling for time series metabolomics in vivo study to model different levels of random effects occurring as a consequence of hierarchical data structure. A multilevel linear model assuming different treatment effects with double exponential prior, considering major sources of variability and robustness to outliers was proposed and tested in terms of performance. The treatment effect for each metabolite was close to zero suggesting small if any effect of cancer on metabolomics profile change. The average difference in 964 signals for all metabolites varied by a factor ranging from 0.8 to 1.25. The inter-rat variability (expressed as a coefficient of variation) ranged from 3-30% across all metabolites with median around 10%, whereas the inter-occasion variability ranged from 0-30% with a median around 5%. Approximately 36% of metabolites contained outlying data points. The complex correlation structure between metabolite signals was revealed. We conclude that kinetics of metabolites can be modeled using tools accepted in pharmacokinetics type of studies. This article is protected by copyright. All rights reserved. PMID: 29064638 [PubMed - as supplied by publisher]

Related Articles Molecular Affinity of Mabolo Extracts to an Octopamine Receptor of a Fruit Fly. Molecules. 2017 Oct 24;22(10): Authors: Dacanay FND, Ladra MCJA, Junio HA, Nellas RB Abstract Essential oils extracted from plants are composed of volatile organic compounds that can affect insect behavior. Identifying the active components of the essential oils to their biochemical target is necessary to design novel biopesticides. In this study, essential oils extracted from Diospyros discolor (Willd.) were analyzed using gas chromatography mass spectroscopy (GC-MS) to create an untargeted metabolite profile. Subsequently, a conformational ensemble of the Drosophila melanogaster octopamine receptor in mushroom bodies (OAMB) was created from a molecular dynamics simulation to resemble a flexible receptor for docking studies. GC-MS analysis revealed the presence of several metabolites, i.e. mostly aromatic esters. Interestingly, these aromatic esters were found to exhibit relatively higher binding affinities to OAMB than the receptor's natural agonist, octopamine. The molecular origin of this observed enhanced affinity is the π -stacking interaction between the aromatic moieties of the residues and ligands. This strategy, computational inspection in tandem with untargeted metabolomics, may provide insights in screening the essential oils as potential OAMB inhibitors. PMID: 29064449 [PubMed - in process]

Related Articles Modelling of Hydrophilic Interaction Liquid Chromatography Stationary Phases Using Chemometric Approaches. Metabolites. 2017 Oct 24;7(4): Authors: Navarro-Reig M, Ortiz-Villanueva E, Tauler R, Jaumot J Abstract Metabolomics is a powerful and widely used approach that aims to screen endogenous small molecules (metabolites) of different families present in biological samples. The large variety of compounds to be determined and their wide diversity of physical and chemical properties have promoted the development of different types of hydrophilic interaction liquid chromatography (HILIC) stationary phases. However, the selection of the most suitable HILIC stationary phase is not straightforward. In this work, four different HILIC stationary phases have been compared to evaluate their potential application for the analysis of a complex mixture of metabolites, a situation similar to that found in non-targeted metabolomics studies. The obtained chromatographic data were analyzed by different chemometric methods to explore the behavior of the considered stationary phases. ANOVA-simultaneous component analysis (ASCA), principal component analysis (PCA) and partial least squares regression (PLS) were used to explore the experimental factors affecting the stationary phase performance, the main similarities and differences among chromatographic conditions used (stationary phase and pH) and the molecular descriptors most useful to understand the behavior of each stationary phase. PMID: 29064436 [PubMed]

Related Articles Long-term stability of human plasma metabolites during storage at -80 °C. J Proteome Res. 2017 Oct 24;: Authors: Haid M, Muschet C, Wahl S, Römisch-Margl W, Prehn C, Möller G, Adamski J Abstract Prolonged storage of biospecimen can lead to artificially altered metabolite concentrations and thus bias data analysis in metabolomics experiments. To elucidate the potential impact of long-term storage on the metabolite profile, a pooled human plasma sample was aliquoted and stored at 80 °C. During a time period of five years, 1012 of the aliquots were measured with the Biocrates AbsoluteIDQ® p180 targeted-metabolomics assay at 193 time points. Modelling the concentration courses over time revealed that 55 out of 111 metabolites remained stable. The statistically significantly changed metabolites showed on average an increase or decrease of +13.7% and -14.5%, respectively. In detail, increased concentration levels were observed for amino acids (mean: +15.4%), the sum of hexoses (+7.9%), butyrylcarnitine (+9.4%), and some phospholipids mostly with chain lengths exceeding 40 carbon atoms (mean: +18.0%). Lipids tended to exhibit decreased concentration levels with the following mean concentration changes: acylcarnitines: 12.1%, lysophosphatidylcholines: -15.1%, diacyl-phosphatidylcholines: -17.0%, acyl-alkyl-phosphatidylcholines: -13.3%, sphingomyelins: -14.8%. We conclude that storage of plasma samples at -80 °C for up to five years can lead to altered concentration levels of amino acids, acylcarnitines, glycerophospholipids, sphingomyelins and the sum of hexoses. These alterations have to be considered when analyzing metabolomics data from long-term epidemiological studies. PMID: 29064256 [PubMed - as supplied by publisher]

Related Articles Validating quantitative untargeted lipidomics across nine liquid chromatography-high-resolution mass spectrometry platforms. Anal Chem. 2017 Oct 24;: Authors: Cajka T, Smilowitz JT, Fiehn O Abstract Liquid chromatography-mass spectrometry (LC-MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted 'best practice' documents, and reports lack harmonization with respect to quantitative data that enable inter-study comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimated absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match and retention times. Quantitative results were highly comparable between the LC-MS platforms tested. Using partial least squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples. PMID: 29064229 [PubMed - as supplied by publisher]

Related Articles Exhaled breath condensate methods adapted from human studies using longitudinal metabolomics for predicting early health alterations in dolphins. Anal Bioanal Chem. 2017 Oct 23;: Authors: Borras E, Aksenov AA, Baird M, Novick B, Schivo M, Zamuruyev KO, Pasamontes A, Parry C, Foutouhi S, Venn-Watson S, Weimer BC, Davis CE Abstract Monitoring health conditions is essential to detect early asymptomatic stages of a disease. To achieve this, blood, urine and breath samples are commonly used as a routine clinical diagnostic. These samples offer the opportunity to detect specific metabolites related to diseases and provide a better understanding of their development. Although blood samples are commonly used routinely to monitor health, the implementation of a relatively noninvasive technique, such as exhaled breath condensate (EBC) analysis, may further benefit the well-being of both humans and other animals. EBC analysis can be used to track possible physical or biochemical alterations caused by common diseases of the bottlenose dolphin (Tursiops truncatus), such as infections or inflammatory-mediated processes. We have used an untargeted metabolomic method with liquid chromatography-mass spectrometry analysis of EBC samples to determine biomarkers related to disease development. In this study, five dolphins under human care were followed up for 1 year. We collected paired blood, physical examination information, and EBC samples. We then statistically correlated this information to predict specific health alterations. Three dolphins provided promising case study information about biomarkers related to cutaneous infections, respiratory infections, dental disease, or hormonal changes (pregnancy). The use of complementary liquid chromatography platforms, with hydrophilic interaction chromatography and reverse-phased columns, allowed us to detect a wide spectrum of EBC biomarker compounds that could be related to these health alterations. Moreover, these two analytical techniques not only provided complementary metabolite information but in both cases they also provided promising diagnostic information for these health conditions. Graphical abstract Collection of the exhaled condensed breath from a bottlenose dolphin from U.S. Navy Marine Mammal Program (MMP). PMID: 29063162 [PubMed - as supplied by publisher]

Related Articles Development of fungal cell factories for the production of secondary metabolites: Linking genomics and metabolism. Synth Syst Biotechnol. 2017 Mar;2(1):5-12 Authors: Nielsen JC, Nielsen J Abstract The genomic era has revolutionized research on secondary metabolites and bioinformatics methods have in recent years revived the antibiotic discovery process after decades with only few new active molecules being identified. New computational tools are driven by genomics and metabolomics analysis, and enables rapid identification of novel secondary metabolites. To translate this increased discovery rate into industrial exploitation, it is necessary to integrate secondary metabolite pathways in the metabolic engineering process. In this review, we will describe the novel advances in discovery of secondary metabolites produced by filamentous fungi, highlight the utilization of genome-scale metabolic models (GEMs) in the design of fungal cell factories for the production of secondary metabolites and review strategies for optimizing secondary metabolite production through the construction of high yielding platform cell factories. PMID: 29062956 [PubMed]