PubMed
Looking into living cell systems: Planar waveguide microfluidic NMR detector for in vitro metabolomics of tumor spheroids.
Looking into living cell systems: Planar waveguide microfluidic NMR detector for in vitro metabolomics of tumor spheroids.
Anal Chem. 2015 Jun 29;
Authors: Kalfe A, Telfah A, Lambert J, Hergenroeder R
Abstract
The complex cell metabolism and its link to oncogenic signaling pathways have received huge interest within the last years. But the lack of advanced analytical tools for the investigation of living cell metabolism is still a challenge to be faced. Therefore, we designed and fabricated a novel miniaturized microslot NMR detector with on-board heater integrated with a microfluidic device as NMR sample holder. For the first time, a tumor spheroid of 500 µm diameter and consisting of 9000 cells has been studied non-invasively and online for 24 hours. The dynamic process of production and degradation of 23 intra- and extracellular metabolites were monitored. Remarkably high concentrations of lactate and alanine were observed being an indicator for a shift from oxidative to glycolytic metabolism. In summary, this methodical development has proven to be a successful analytical tool for the elucidation of cellular functions and their corresponding biochemical pathways. Additionally, the planar geometry of the microslot NMR detector allows the hyphenation with versatile lab-on-a chip (LOC) technology. This opens a new window for metabolomics studies on living cells and can be implemented into new application fields in biotechnology and life sciences.
PMID: 26121119 [PubMed - as supplied by publisher]
New insights and biomarkers for Type 1 Diabetes: Review for Scandinavian Journal of Immunology.
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New insights and biomarkers for Type 1 Diabetes: Review for Scandinavian Journal of Immunology.
Scand J Immunol. 2015 Jun 28;
Authors: Heinonen MT, Moulder R, Lahesmaa R
Abstract
The increasing incidence of type 1 diabetes observed in the past 60 years has spawned massive efforts in multiple research fields to elucidate the etiology of this disease. While GWAS studies provide a good genetic basis for the current knowledge, it is clear that environmental triggers and their influence in disease prevalence and origin are is highly important. The realization of disease heterogeneity has created a requirement for better biomarkers to complement the known autoantibody markers and to more successfully predict the severity and onset time of the disease. Such biomarkers would be needed both for prevention as well as for monitoring disease activity and response to preventive and therapeutic measures. Systematic holistic approaches concentrating on the triggering molecular mechanisms, pancreatic beta cells, immune response as well as the influence of diet and environment are necessary to understand the disease pathogenesis and find a cure. The current genomic knowledge is being broadened with accompanying studies in epigenetics and transcriptomic regulation, metabolomics, proteomics and lipidomics, covering the whole system from beta cells, the profile and cellular balance of the infiltrating lymphocytes to gut microbiota and viral infections. Here we highlight interesting recent findings in type 1 diabetes research. This article is protected by copyright. All rights reserved.
PMID: 26119046 [PubMed - as supplied by publisher]
Metabolome progression during early gut microbial colonization of gnotobiotic mice.
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Metabolome progression during early gut microbial colonization of gnotobiotic mice.
Sci Rep. 2015;5:11589
Authors: Marcobal A, Yusufaly T, Higginbottom S, Snyder M, Sonnenburg JL, Mias GI
Abstract
The microbiome has been implicated directly in host health, especially host metabolic processes and development of immune responses. These are particularly important in infants where the gut first begins being colonized, and such processes may be modeled in mice. In this investigation we follow longitudinally the urine metabolome of ex-germ-free mice, which are colonized with two bacterial species, Bacteroides thetaiotaomicron and Bifidobacterium longum. High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series analysis to urine metabolomics data. Results demonstrate both gradual and punctuated changes in metabolite production and that early colonization events profoundly impact the nature of small molecules circulating in the host. The identified small molecules are implicated in amino acid and carbohydrate metabolic processes, and offer insights into the dynamic changes occurring during the colonization process, using high-throughput longitudinal methodology.
PMID: 26118551 [PubMed - in process]
[UPLC/Q-TOF MS and NMR plant metabolomics approach in studying the effect of growth year on the quality of Polygala tenuifolia].
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[UPLC/Q-TOF MS and NMR plant metabolomics approach in studying the effect of growth year on the quality of Polygala tenuifolia].
Yao Xue Xue Bao. 2015 Mar;50(3):340-7
Authors: Xue Y, Li XW, Li ZY, Zeng ZP, Zhang FS, Li AP, Qin XM, Peng B
Abstract
Growth year is one of the important factors for the quality of Polygala tenufolia. In this study, primary metabolites and secondary metabolites were compared in 1, 2 and 3 years old P. tenufolia cultivated in Shaanxi Heyang. The samples were subjected to ultra-high performance liquid chromatography (UPLC)-quadrupole time-of-flight mass spectrometry (Q-TOF MS) and nuclear magnetic resonance (NMR) analysis, and the obtained data were analyzed using principal component analysis (PCA) and other statistical analysis methods. In addition, content and correlation of different metabolites were also calculated. The results showed no significance between main component contents in 2 year-old and 3 year-old P. Tenufolia, but 1 year-old was statistically different. The contents of primary metabolites, such as fructose, sucrose, and choline increased as time goes on, while glycine and raffinose decreased. The contents of secondary metabolites, such as onjisaponin Fg, polygalasaponin XXVIII, polygalasaponin XXXII increased, while polygalaxanthone III and parts of oligosaccharide multi-ester including tenuifoliose A, tenuifoliose C, tenuifoliose C2 and tenuifoliose H decreased with the extension of the growth years. Growth years has important impact on the quality of P. tenuifolia and the existing growing years of commodity P. tenuifolia have its scientific evidence. This study supplied a new method for the quality evaluation of Chinese medicinal materials.
PMID: 26118115 [PubMed - in process]
Evaluation of comprehensive two-dimensional gas chromatography with accurate mass time-of-flight mass spectrometry for the metabolic profiling of plant-fungus interaction in Aquilaria malaccensis.
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Evaluation of comprehensive two-dimensional gas chromatography with accurate mass time-of-flight mass spectrometry for the metabolic profiling of plant-fungus interaction in Aquilaria malaccensis.
J Chromatogr A. 2015 Mar 27;1387:104-15
Authors: Wong YF, Chin ST, Perlmutter P, Marriott PJ
Abstract
To explore the possible obligate interactions between the phytopathogenic fungus and Aquilaria malaccensis which result in generation of a complex array of secondary metabolites, we describe a comprehensive two-dimensional gas chromatography (GC × GC) method, coupled to accurate mass time-of-flight mass spectrometry (TOFMS) for the untargeted and comprehensive metabolic profiling of essential oils from naturally infected A. malaccensis trees. A polar/non-polar column configuration was employed, offering an improved separation pattern of components when compared to other column sets. Four different grades of the oils displayed quite different metabolic patterns, suggesting the evolution of a signalling relationship between the host tree (emergence of various phytoalexins) and fungi (activation of biotransformation). In total, ca. 550 peaks/metabolites were detected, of which tentative identification of 155 of these compounds was reported, representing between 20.1% and 53.0% of the total ion count. These are distributed over the chemical families of monoterpenic and sesquiterpenic hydrocarbons, oxygenated monoterpenes and sesquiterpenes (comprised of ketone, aldehyde, oxide, alcohol, lactone, keto-alcohol and diol), norterpenoids, diterpenoids, short chain glycols, carboxylic acids and others. The large number of metabolites detected, combined with the ease with which they are located in the 2D separation space, emphasises the importance of a comprehensive analytical approach for the phytochemical analysis of plant metabolomes. Furthermore, the potential of this methodology in grading agarwood oils by comparing the obtained metabolic profiles (pattern recognition for unique metabolite chemical families) is discussed. The phytocomplexity of the agarwood oils signified the production of a multitude of plant-fungus mediated secondary metabolites as chemical signals for natural ecological communication. To the best of our knowledge, this is the most complete information available so far about essential oils of A. malaccensis, which represents a valuable extension to available data for advanced studies on microbial-mediated biotransformation of terpenes, and offers promise for potential discovery of unanticipated phytochemicals, and biotechnological exploitation.
PMID: 25704770 [PubMed - indexed for MEDLINE]
Enhancement of antibiotic activity against multidrug-resistant bacteria by the efflux pump inhibitor 3,4-dibromopyrrole-2,5-dione isolated from a Pseudoalteromonas sp.
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Enhancement of antibiotic activity against multidrug-resistant bacteria by the efflux pump inhibitor 3,4-dibromopyrrole-2,5-dione isolated from a Pseudoalteromonas sp.
J Nat Prod. 2015 Mar 27;78(3):402-12
Authors: Whalen KE, Poulson-Ellestad KL, Deering RW, Rowley DC, Mincer TJ
Abstract
Members of the resistance nodulation cell division (RND) of efflux pumps play essential roles in multidrug resistance (MDR) in Gram-negative bacteria. Here, we describe the search for new small molecules from marine microbial extracts to block efflux and thus restore antibiotic susceptibility in MDR bacterial strains. We report the isolation of 3,4-dibromopyrrole-2,5-dione (1), an inhibitor of RND transporters, from Enterobacteriaceae and Pseudomonas aeruginosa, from the marine bacterium Pseudoalteromonas piscicida. 3,4-Dibromopyrrole-2,5-dione decreased the minimum inhibitory concentrations (MICs) of two fluoroquinolones, an aminoglycoside, a macrolide, a beta-lactam, tetracycline, and chloramphenicol between 2- and 16-fold in strains overexpressing three archetype RND transporters (AcrAB-TolC, MexAB-OprM, and MexXY-OprM). 3,4-Dibromopyrrole-2,5-dione also increased the intracellular accumulation of Hoechst 33342 in wild-type but not in transporter-deficient strains and prevented H33342 efflux (IC50 = 0.79 μg/mL or 3 μM), a hallmark of efflux pump inhibitor (EPI) functionality. A metabolomic survey of 36 Pseudoalteromonas isolates mapped the presence of primarily brominated metabolites only within the P. piscicida phylogenetic clade, where a majority of antibiotic activity was also observed, suggesting a link between halogenation and enhanced secondary metabolite biosynthetic potential. In sum, 3,4-dibromopyrrole-2,5-dione is a potent EPI and deserves further attention as an adjuvant to enhance the effectiveness of existing antibiotics.
PMID: 25646964 [PubMed - indexed for MEDLINE]
Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense.
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Genetic variation in the nuclear and organellar genomes modulates stochastic variation in the metabolome, growth, and defense.
PLoS Genet. 2015 Jan;11(1):e1004779
Authors: Joseph B, Corwin JA, Kliebenstein DJ
Abstract
Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype.
PMID: 25569687 [PubMed - indexed for MEDLINE]
Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses.
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Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses.
PLoS Genet. 2015 Jan;11(1):e1004835
Authors: Demirkan A, Henneman P, Verhoeven A, Dharuri H, Amin N, van Klinken JB, Karssen LC, de Vries B, Meissner A, Göraler S, van den Maagdenberg AM, Deelder AM, C 't Hoen PA, van Duijn CM, van Dijk KW
Abstract
Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value = 1.27×10-32), PRODH with proline (P-value = 1.11×10-19), SLC16A9 with carnitine level (P-value = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10-8) and 2p12 locus with valine (P-value = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.
PMID: 25569235 [PubMed - indexed for MEDLINE]
Liver safety assessment: required data elements and best practices for data collection and standardization in clinical trials.
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Liver safety assessment: required data elements and best practices for data collection and standardization in clinical trials.
Drug Saf. 2014 Nov;37 Suppl 1:S19-31
Authors: Avigan MI, Bjornsson ES, Pasanen M, Cooper C, Andrade RJ, Watkins PB, Lewis JH, Merz M
Abstract
A workshop was convened to discuss best practices for the assessment of drug-induced liver injury (DILI) in clinical trials. In a breakout session, workshop attendees discussed necessary data elements and standards for the accurate measurement of DILI risk associated with new therapeutic agents in clinical trials. There was agreement that in order to achieve this goal the systematic acquisition of protocol-specified clinical measures and lab specimens from all study subjects is crucial. In addition, standard DILI terms that address the diverse clinical and pathologic signatures of DILI were considered essential. There was a strong consensus that clinical and lab analyses necessary for the evaluation of cases of acute liver injury should be consistent with the US Food and Drug Administration (FDA) guidance on pre-marketing risk assessment of DILI in clinical trials issued in 2009. A recommendation that liver injury case review and management be guided by clinicians with hepatologic expertise was made. Of note, there was agreement that emerging DILI signals should prompt the systematic collection of candidate pharmacogenomic, proteomic and/or metabonomic biomarkers from all study subjects. The use of emerging standardized clinical terminology, CRFs and graphic tools for data review to enable harmonization across clinical trials was strongly encouraged. Many of the recommendations made in the breakout session are in alignment with those made in the other parallel sessions on methodology to assess clinical liver safety data, causality assessment for suspected DILI, and liver safety assessment in special populations (hepatitis B, C, and oncology trials). Nonetheless, a few outstanding issues remain for future consideration.
PMID: 25352325 [PubMed - indexed for MEDLINE]
Metabolomics Applied to the Pancreatic Islet.
Metabolomics Applied to the Pancreatic Islet.
Arch Biochem Biophys. 2015 Jun 24;
Authors: Gooding JR, Jensen MV, Newgard CB
Abstract
Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to glucose or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes derived from metabolomics studies.
PMID: 26116790 [PubMed - as supplied by publisher]
Metabolomic and transcriptomic insights into how cotton fiber transitions to secondary wall synthesis, represses lignification, and prolongs elongation.
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Metabolomic and transcriptomic insights into how cotton fiber transitions to secondary wall synthesis, represses lignification, and prolongs elongation.
BMC Genomics. 2015;16(1):477
Authors: Tuttle JR, Nah G, Duke MV, Alexander DC, Guan X, Song Q, Chen ZJ, Scheffler BE, Haigler CH
Abstract
BACKGROUND: The morphogenesis of single-celled cotton fiber includes extreme elongation and staged cell wall differentiation. Designing strategies for improving cotton fiber for textiles and other uses relies on uncovering the related regulatory mechanisms. In this research we compared the transcriptomes and metabolomes of two Gossypium genotypes, Gossypium barbadense cv Phytogen 800 and G. hirsutum cv Deltapine 90. When grown in parallel, the two types of fiber developed similarly except for prolonged fiber elongation in the G. barbadense cultivar. The data were collected from isolated fibers between 10 to 28 days post anthesis (DPA) representing: primary wall synthesis to support elongation; transitional cell wall remodeling; and secondary wall cellulose synthesis, which was accompanied by continuing elongation only in G. barbadense fiber.
RESULTS: Of 206 identified fiber metabolites, 205 were held in common between the two genotypes. Approximately 38,000 transcripts were expressed in the fiber of each genotype, and these were mapped to the reference set and interpreted by homology to known genes. The developmental changes in the transcriptomes and the metabolomes were compared within and across genotypes with several novel implications. Transitional cell wall remodeling is a distinct stable developmental stage lasting at least four days (18 to 21 DPA). Expression of selected cell wall related transcripts was similar between genotypes, but cellulose synthase gene expression patterns were more complex than expected. Lignification was transcriptionally repressed in both genotypes. Oxidative stress was lower in the fiber of G. barbadense cv Phytogen 800 as compared to G. hirsutum cv Deltapine 90. Correspondingly, the G. barbadense cultivar had enhanced capacity for management of reactive oxygen species during its prolonged elongation period, as indicated by a 138-fold increase in ascorbate concentration at 28 DPA.
CONCLUSIONS: The parallel data on deep-sequencing transcriptomics and non-targeted metabolomics for two genotypes of single-celled cotton fiber showed that a discrete developmental stage of transitional cell wall remodeling occurs before secondary wall cellulose synthesis begins. The data showed how lignification can be transcriptionally repressed during secondary cell wall synthesis, and they implicated enhanced capacity to manage reactive oxygen species through the ascorbate-glutathione cycle as a positive contributor to fiber length.
PMID: 26116072 [PubMed - as supplied by publisher]
Magnetic resonance spectroscopy of paragangliomas: new insights into in vivo metabolomics.
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Magnetic resonance spectroscopy of paragangliomas: new insights into in vivo metabolomics.
Endocr Relat Cancer. 2015 Jun 26;
Authors: Varoquaux A, Le Fur Y, Imperiale A, Reyre A, Montava M, Fakhry N, Namer IJ, Moulin G, Pacak K, Guye M, Taieb D
Abstract
OBJECTIVE: Paragangliomas (PGLs) can be associated with mutations in genes of the tricarboxylic acid (TCA) cycle. Succinate dehydrogenase mutations (SDHx) are the prime examples of genetically determined TCA cycle defects with accumulation of succinate. Succinate, which acts as an oncometabolite, can be detected by ex-vivo metabolomics approaches. The aim of this study was to evaluate the potential role of proton MR spectroscopy (167 H-MRS) for identifying SDHx-related PGLs in vivo and non-invasively.
METHODS: Eight patients were prospectively evaluated with single voxel 168 H-MRS. MR spectra from 8 tumors (4 SDHx-related PGLs, 2 sporadic PGLs, 1 cervical schwannoma, and 1 cervical neurofibroma) were acquired and interpreted qualitatively.
RESULTS: Compared to other tumors, a succinate resonance peak was detected only in SDHx72 related tumor patients. Spectra quality was considered good in 3 cases, medium in 2 cases, poor in 2 cases, and uninterpretable in the latter case. Smaller lesions had lower spectra quality compared to larger lesions. Jugular PGLs also exihibited a poorer spectra quality compared to other locations.
CONCLUSIONS: 176 H-MRS has always been challenging in terms of its technical requisites. This is even more true for the evaluation of head and neck tumors. However, 177 H-MRS might be added to the classical MR sequences for metabolomic characterization of PGLs. In vivo detection of succinate might guide genetic testing, characterize SDHx variants of unknown significance (in the absence of available tumor sample), and even optimize a selection of appropriate therapies.
PMID: 26115958 [PubMed - as supplied by publisher]
Metabolomics analysis identifies novel plasma biomarkers of cystic fibrosis pulmonary exacerbation.
Metabolomics analysis identifies novel plasma biomarkers of cystic fibrosis pulmonary exacerbation.
Pediatr Pulmonol. 2015 Jun 26;
Authors: Laguna TA, Reilly CS, Williams CB, Welchlin C, Wendt CH
Abstract
BACKGROUND: Cystic fibrosis (CF) lung disease is characterized by infection, inflammation, lung function decline, and intermittent pulmonary exacerbations. However, the link between pulmonary exacerbation and lung disease progression remains unclear. Global metabolomic profiling can provide novel mechanistic insight into a disease process in addition to putative biomarkers for future study. Our objective was to investigate how the plasma metabolomic profile changes between CF pulmonary exacerbation and a clinically well state.
METHODS: Plasma samples and lung function data were collected from 25 CF patients during hospitalization for a pulmonary exacerbation and during quarterly outpatient clinic visits. In collaboration with Metabolon, Inc., the metabolomic profiles of matched pair plasma samples, one during exacerbation and one at a clinic visit, were analyzed using gas and liquid chromatography coupled with mass spectrometry. Compounds were identified by comparison to a library of standards. Mixed effects models that controlled for nutritional status and lung function were used to test for differences and principal components analysis was performed.
RESULTS: Our population had a median age of 27 years (14-39) and had a median FEV1 % predicted of 65% (23-105%). 398 total metabolites were identified and after adjustment for confounders, five metabolites signifying perturbations in nucleotide (hypoxanthine), nucleoside (N4-acetylcytidine), amino acid (N-acetylmethionine), carbohydrate (mannose), and steroid (cortisol) metabolism were identified. Principal components analysis provided good separation between the two clinical phenotypes.
CONCLUSIONS: Our findings provide putative metabolite biomarkers for future study and allow for hypothesis generation about the pathophysiology of CF pulmonary exacerbation. Pediatr Pulmonol. © 2015 Wiley Periodicals, Inc.
PMID: 26115542 [PubMed - as supplied by publisher]
Amino acid analysis using chromatography-mass spectrometry: An inter platform comparison study.
Amino acid analysis using chromatography-mass spectrometry: An inter platform comparison study.
J Pharm Biomed Anal. 2015 Jun 5;114:398-407
Authors: Krumpochova P, Bruyneel B, Molenaar D, Koukou A, Wuhrer M, Niessen WM, Giera M
Abstract
The analysis of amino acids has become a central task in many aspects. While amino acid analysis has traditionally mainly been carried out using either gas chromatography (GC) in combination with flame ionization detection or liquid chromatography (LC) with either post-column derivatization using ninhydrin or pre-column derivatization using o-phthalaldehyde, many of today's analysis platforms are based on chromatography in combination with mass spectrometry (MS). While derivatization is mandatory for the GC-based analysis of amino acids, several LC platforms have emerged, particularly in the dawn of targeted metabolite profiling using hydrophilic interaction liquid chromatography (HILIC) coupled to MS, allowing the analysis of underivatized amino acids. Among the numerous analytical platforms available for amino acid analysis today, we here compare three prominent approaches, being GC-MS and LC-MS after amino acid derivatization using chloroformate and HILIC-MS of underivatized amino acids. We compare and discuss practical issues as well as performance characteristics, e.g., the use of (13)C-labeled internal standards, of the different platforms and present data on their practical implementation in our laboratory. Finally, we compare the real-life applicability of all three platforms for a complex biological sample. While all three platforms are very-well suited for the analysis of complex biological samples they all show advantages and disadvantages for some analytes as discussed in detail in this manuscript.
PMID: 26115383 [PubMed - as supplied by publisher]
Enantioselective Metabolism and Interference on Tryptophan Metabolism of Myclobutanil in Rat Hepatocytes.
Enantioselective Metabolism and Interference on Tryptophan Metabolism of Myclobutanil in Rat Hepatocytes.
Chirality. 2015 Jun 26;
Authors: Wang Y, Qiu J, Zhu W, Wang X, Zhang P, Wang D, Zhou Z
Abstract
Myclobutanil, (RS)-2-(4-chlorophenyl)-2-(1H-1, 2, 4-triazol-1-ylmethyl) hexanenitrile is a widely used triazole fungicide. In this study, enantioselective metabolism and cytotoxicity were investigated in rat hepatocytes by chiral HPLC-MS/MS and the methyl tetrazolium (MTT) assay, respectively. Furthermore, tryptophan metabolism disturbance in rat hepatocytes after myclobutanil exposure was also evaluated by target metabolomics method. The half-life (t1/2) of (+)-myclobutanil was 10.66 h, whereas that for (-)-myclobutanil was 15.07 h. Such results indicated that the metabolic process of myclobutanil in rat hepatocytes was enantioselective with an enrichment of (-)-myclobutanil. For the cytotoxicity research, the calculated EC50 (12h) values for rac-myclobutanil, (+)- and (-)-myclobutanil were 123.65, 150.65 and 152.60 µM, respectively. The results of tryptophan metabolites profiling showed that the levels of kynurenine (KYN) and XA were both up-regulated compared to the control, suggesting the activation effect of the KYN pathway by myclobutanil and its enantiomers which may provide an important insight into its toxicity mechanism. The data presented here could be useful for the environmental hazard assessment of myclobutanil. Chirality 00:000-000, 2015. © 2015 Wiley Periodicals, Inc.
PMID: 26115377 [PubMed - as supplied by publisher]
Metabolomic Analysis of the Skeletal Muscle of Mice Overexpressing PGC-1α.
Metabolomic Analysis of the Skeletal Muscle of Mice Overexpressing PGC-1α.
PLoS One. 2015;10(6):e0129084
Authors: Hatazawa Y, Senoo N, Tadaishi M, Ogawa Y, Ezaki O, Kamei Y, Miura S
Abstract
Peroxisome proliferator-activated receptor (PPAR) γ coactivator 1α (PGC-1α) is a coactivator of various nuclear receptors and other transcription factors whose expression increases in the skeletal muscle during exercise. We have previously made transgenic mice overexpressing PGC-1α in the skeletal muscle (PGC-1α-Tg mice). PGC-1α upregulates the expression of genes associated with red fibers, mitochondrial function, fatty acid oxidation, and branched chain amino acid (BCAA) degradation. However, global analyses of the actual metabolic products have not been investigated. In this study, we conducted metabolomic analysis of the skeletal muscle in PGC-1α-Tg mice by capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry. Principal component analysis and hierarchical cluster analysis showed clearly distinguishable changes in the metabolites between PGC-1α-Tg and wild-type control mice. Changes were observed in metabolite levels of various metabolic pathways such as the TCA cycle, pentose phosphate pathway, nucleotide synthesis, purine nucleotide cycle, and amino acid metabolism, including BCAA and β-alanine. Namely, metabolic products of the TCA cycle increased in PGC-1α-Tg mice, with increased levels of citrate (2.3-fold), succinate (2.2-fold), fumarate (2.8-fold), and malate (2.3-fold) observed. Metabolic products associated with the pentose phosphate pathway and nucleotide biosynthesis also increased in PGC-1α-Tg mice. Meanwhile, BCAA levels decreased (Val, 0.7-fold; Leu, 0.8-fold; and Ile, 0.7-fold), and Glu (3.1-fold) and Asp (2.2-fold) levels increased. Levels of β-alanine and related metabolites were markedly decreased in PGC-1α-Tg mice. Coordinated regulation of the TCA cycle and amino acid metabolism, including BCAA, suggests that PGC-1α plays important roles in energy metabolism. Moreover, our metabolomics data showing the activation of the purine nucleotide pathway, malate-aspartate shuttle, as well as creatine metabolism, which are known to be active during exercise, further suggests that PGC-1α regulates metabolism in exercise. Thus, we demonstrated the roles of PGC-1α in the skeletal muscle at the metabolite level.
PMID: 26114427 [PubMed - as supplied by publisher]
Single cell-type comparative metabolomics of epidermal bladder cells from the halophyte Mesembryanthemum crystallinum.
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Single cell-type comparative metabolomics of epidermal bladder cells from the halophyte Mesembryanthemum crystallinum.
Front Plant Sci. 2015;6:435
Authors: Barkla BJ, Vera-Estrella R
Abstract
One of the remarkable adaptive features of the halophyte Mesembryanthemum crystallinum are the specialized modified trichomes called epidermal bladder cells (EBC) which cover the leaves, stems, and peduncle of the plant. They are present from an early developmental stage but upon salt stress rapidly expand due to the accumulation of water and sodium. This particular plant feature makes it an attractive system for single cell type studies, with recent proteomics and transcriptomics studies of the EBC establishing that these cells are metabolically active and have roles other than sodium sequestration. To continue our investigation into the function of these unusual cells we carried out a comprehensive global analysis of the metabolites present in the EBC extract by gas chromatography Time-of-Flight mass spectrometry (GC-TOF) and identified 194 known and 722 total molecular features. Statistical analysis of the metabolic changes between control and salt-treated samples identified 352 significantly differing metabolites (268 after correction for FDR). Principal components analysis provided an unbiased evaluation of the data variance structure. Biochemical pathway enrichment analysis suggested significant perturbations in 13 biochemical pathways as defined in KEGG. More than 50% of the metabolites that show significant changes in the EBC, can be classified as compatible solutes and include sugars, sugar alcohols, protein and non-protein amino acids, and organic acids, highlighting the need to maintain osmotic homeostasis to balance the accumulation of Na(+) and Cl(-) ions. Overall, the comparison of metabolic changes in salt treated relative to control samples suggests large alterations in M. crystallinum epidermal bladder cells.
PMID: 26113856 [PubMed]
Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.
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Comparative analysis and modeling of the severity of steatohepatitis in DDC-treated mouse strains.
PLoS One. 2014;9(10):e111006
Authors: Pandey V, Sultan M, Kashofer K, Ralser M, Amstislavskiy V, Starmann J, Osprian I, Grimm C, Hache H, Yaspo ML, Sültmann H, Trauner M, Denk H, Zatloukal K, Lehrach H, Wierling C
Abstract
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) has a broad spectrum of disease states ranging from mild steatosis characterized by an abnormal retention of lipids within liver cells to steatohepatitis (NASH) showing fat accumulation, inflammation, ballooning and degradation of hepatocytes, and fibrosis. Ultimately, steatohepatitis can result in liver cirrhosis and hepatocellular carcinoma.
METHODOLOGY AND RESULTS: In this study we have analyzed three different mouse strains, A/J, C57BL/6J, and PWD/PhJ, that show different degrees of steatohepatitis when administered a 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) containing diet. RNA-Seq gene expression analysis, protein analysis and metabolic profiling were applied to identify differentially expressed genes/proteins and perturbed metabolite levels of mouse liver samples upon DDC-treatment. Pathway analysis revealed alteration of arachidonic acid (AA) and S-adenosylmethionine (SAMe) metabolism upon other pathways. To understand metabolic changes of arachidonic acid metabolism in the light of disease expression profiles a kinetic model of this pathway was developed and optimized according to metabolite levels. Subsequently, the model was used to study in silico effects of potential drug targets for steatohepatitis.
CONCLUSIONS: We identified AA/eicosanoid metabolism as highly perturbed in DDC-induced mice using a combination of an experimental and in silico approach. Our analysis of the AA/eicosanoid metabolic pathway suggests that 5-hydroxyeicosatetraenoic acid (5-HETE), 15-hydroxyeicosatetraenoic acid (15-HETE) and prostaglandin D2 (PGD2) are perturbed in DDC mice. We further demonstrate that a dynamic model can be used for qualitative prediction of metabolic changes based on transcriptomics data in a disease-related context. Furthermore, SAMe metabolism was identified as being perturbed due to DDC treatment. Several genes as well as some metabolites of this module show differences between A/J and C57BL/6J on the one hand and PWD/PhJ on the other.
PMID: 25347188 [PubMed - indexed for MEDLINE]
A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk.
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A gas chromatography-mass spectrometry-based metabolomic approach for the characterization of goat milk compared with cow milk.
J Dairy Sci. 2014 Oct;97(10):6057-66
Authors: Scano P, Murgia A, Pirisi FM, Caboni P
Abstract
In this work, the polar metabolite pool of commercial caprine milk was studied by gas chromatography-mass spectrometry and multivariate statistical data analysis. Experimental data were compared with those of cow milk and the discriminant analysis correctly classified milk. By the same means, differences due to heat treatments (UHT or pasteurization) on milk samples were also investigated. Results of the 2 discriminant analyses were combined, with the aim of finding the discriminant metabolites unique for each class and shared by 2 classes. Valine and glycine were specific to goat milk, talose and malic acid to cow milk, and hydroxyglutaric acid to pasteurized samples. Glucose and fructose were shared by cow milk and UHT-treated samples, whereas ribose was shared by pasteurized and goat milk. Other discriminant variables were not attributed to specific metabolites. Furthermore, with the aim to reduce food fraud, the issue of adulteration of caprine milk by addition of cheaper bovine milk has been also addressed. To this goal, mixtures of goat and cow milk were prepared by adding the latter in a range from 0 to 100% (vol/vol) and studied by multivariate regression analysis. The error in the level of cow milk detectable was approximately 5%. These overall results demonstrated that, through the combined approach of gas chromatography-mass spectrometry and multivariate statistical data analysis, we were able to discriminate between milk typologies on the basis of their polar metabolite profiles and to propose a new analytical method to easily discover food fraud and to protect goat milk uniqueness. The use of appropriate visualization tools improved the interpretation of multivariate model results.
PMID: 25108860 [PubMed - indexed for MEDLINE]
Association between the bovine milk metabolome and rennet-induced coagulation properties of milk.
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Association between the bovine milk metabolome and rennet-induced coagulation properties of milk.
J Dairy Sci. 2014 Oct;97(10):6076-84
Authors: Sundekilde UK, Gustavsson F, Poulsen NA, Glantz M, Paulsson M, Larsen LB, Bertram HC
Abstract
The milk metabolomes of 407 individual Swedish Red dairy cows were analyzed by nuclear magnetic resonance spectroscopy as part of the Danish-Swedish Milk Genomics Initiative. By relating these metabolite profiles to total milk protein concentration and rheological measurements of rennet-induced milk coagulation together using multivariate data analysis techniques, we were able to identify several different associations of the milk metabolome to technological properties of milk. Several novel correlations of milk metabolites to protein content and rennet-induced coagulation properties were demonstrated. Metabolites associated with the prediction of total protein content included choline, N-acetyl hexosamines, creatinine, glycerophosphocholine, glutamate, glucose 1-phosphate, galactose 1-phosphate, and orotate. In addition, levels of lactate, acetate, glutamate, creatinine, choline, carnitine, galactose 1-phosphate, and glycerophosphocholine were significantly different when comparing noncoagulating and well-coagulating milks. These findings suggest that the mentioned metabolites are associated with milk protein content and rennet-induced coagulation properties and may act as quality markers for cheese milk.
PMID: 25087032 [PubMed - indexed for MEDLINE]