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Tomoyoshi Soga - One of the best experts on this subject based on the ideXlab platform.

  • Research Article The Consumption of Bicarbonate-Rich Mineral Water Improves Glycemic Control
    2016
    Co-Authors: Shinnosuke Murakami, Tomoyoshi Soga, Masaru Tomita, Yasuaki Goto, Kyo Ito, Shinya Hayasaka, Shigeo Kurihara, Shinji Fukuda
    Abstract:

    Copyright © 2015 Shinnosuke Murakami et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Hot spring water and natural mineral water have been therapeutically used to prevent or improve various diseases. Specifically, consumption of bicarbonate-rich mineral water (BMW) has been reported to prevent or improve type 2 diabetes (T2D) in humans. However, the molecular mechanisms of the beneficial effects behind mineral water consumption remain unclear. To elucidate the molecular level effects of BMW consumption on glycemic control, blood Metabolome Analysis and fecal microbiome Analysis were applied to the BMW consumption test. During the study, 19 healthy volunteers drank 500mL of commercially available tap water (TW) or BMW daily. TW consumption periods and BMW consumption periods lasted for a week each and this cycle was repeated twice. Biochemical tests indicated that serum glycoalbumin levels, one of the indexes of glycemic controls, decreased significantly after BMW consumption. Metabolome Analysis of blood samples revealed that 19 metabolites including glycolysis-related metabolites and 3 amino acids were significantly different between TW and BMW consumption periods. Additionally

  • Metabolome Analysis based on capillary electrophoresis mass spectrometry
    Trends in Analytical Chemistry, 2014
    Co-Authors: Akiyoshi Hirayama, Masataka Wakayama, Tomoyoshi Soga
    Abstract:

    Abstract Capillary electrophoresis-mass spectrometry (CE-MS) has emerged as a powerful new tool for comprehensive Analysis of charged compounds. In this review, we provide a general description of the application of CE-MS in Metabolome Analysis, including the separation modes of CE, various interfaces and the mass spectrometers used. We also discuss strategies for sample pretreatment, data processing and peak identification, which are important processes in Metabolome Analysis. In addition, we highlight a number of new techniques to improve metabolite extraction, peak resolution and sensitivity. Finally, we provide some general conclusions and future perspectives.

  • capillary electrophoresis mass spectrometry based Metabolome Analysis of serum and saliva from neurodegenerative dementia patients
    Electrophoresis, 2013
    Co-Authors: Mayuko Tsuruoka, Tomoyoshi Soga, Akiyoshi Hirayama, Masahiro Sugimoto, Junko Hara, William R Shankle, Masaru Tomita
    Abstract:

    Despite increasing global prevalence, the precise pathogenesis and terms for objective diagnosis of neurodegenerative dementias remain controversial, and comprehensive understanding of the disease remains lacking. Here, we conducted metabolomic Analysis of serum and saliva obtained from patients with neurodegenerative dementias (n = 10), including Alzheimer's disease, frontotemporal lobe dementia, and Lewy body disease, as well as from age-matched healthy controls (n = 9). Using CE-TOF-MS, six metabolites in serum (β-alanine, creatinine, hydroxyproline, glutamine, iso-citrate, and cytidine) and two in saliva (arginine and tyrosine) were significantly different between dementias and controls. Using multivariate Analysis, serum was confirmed as a more efficient biological fluid for diagnosis compared to saliva; additionally, 45 metabolites in total were identified as candidate markers that could discriminate at least one pair of diagnostic groups from the healthy control group. These metabolites possibly provide an objective method for diagnosing dementia-type by multiphase screening. Moreover, diagnostic-type-dependent differences were observed in several tricarboxylic acid cycle compounds detected in serum, indicating that some pathways in glucose metabolism may be altered in dementia patients. This pilot study revealed novel alterations in metabolomic profiles between various neurodegenerative dementias, which would contribute to etiological investigations.

  • Dynamic simulation and Metabolome Analysis of long-term erythrocyte storage in adenine-guanosine solution.
    PloS one, 2013
    Co-Authors: Taiko Nishino, Tomoyoshi Soga, Akiyoshi Hirayama, Makoto Suematsu, Ayako Yachie-kinoshita, Masaru Tomita
    Abstract:

    Although intraerythrocytic ATP and 2,3-bisphophoglycerate (2,3-BPG) are known as direct indicators of the viability of preserved red blood cells and the efficiency of post-transfusion oxygen delivery, no current blood storage method in practical use has succeeded in maintaining both these metabolites at high levels for long periods. In this study, we constructed a mathematical kinetic model of comprehensive metabolism in red blood cells stored in a recently developed blood storage solution containing adenine and guanosine, which can maintain both ATP and 2,3-BPG. The predicted dynamics of metabolic intermediates in glycolysis, the pentose phosphate pathway, and purine salvage pathway were consistent with time-series Metabolome data measured with capillary electrophoresis time-of-flight mass spectrometry over 5 weeks of storage. From the Analysis of the simulation model, the metabolic roles and fates of the 2 major additives were illustrated: (1) adenine could enlarge the adenylate pool, which maintains constant ATP levels throughout the storage period and leads to production of metabolic waste, including hypoxanthine; (2) adenine also induces the consumption of ribose phosphates, which results in 2,3-BPG reduction, while (3) guanosine is converted to ribose phosphates, which can boost the activity of upper glycolysis and result in the efficient production of ATP and 2,3-BPG. This is the first attempt to clarify the underlying metabolic mechanism for maintaining levels of both ATP and 2,3-BPG in stored red blood cells with in silico Analysis, as well as to analyze the trade-off and the interlock phenomena between the benefits and possible side effects of the storage-solution additives.

  • renal cell carcinoma with a novel germ line mutation in isocitrate dehydrogenase 1 idh1 and its functional study
    Journal of Clinical Oncology, 2013
    Co-Authors: Tatsuya Takayama, Tomoyoshi Soga, Mitsuhiro Kitagawa, Naohisa Takaoka, Naoyuki Sugiyama, Kaori Igarashi, Miki Miyazaki, Takayuki Sugiyama, Fumitake Kai, Seiichiro Ozono
    Abstract:

    e15568 Background: Recently, omics study such as Metabolome Analysis and whole genome sequencing has been applied to various disorders. We predicted the dysfunction of isocitrate dehydrogenase 1 (IDH1) in renal cell carcinoma (RCC) using Metabolome Analysis and identified a novel mutation of IDH1. In addition, we examined its function. Methods: We determined the global-scale Metabolome profiling of human RCC by capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS), and compared the metabolite levels of tumors and paired normal tissues in 10 patients with RCC. We performed the genotyping of IDH1 and von Hippel-Lindau (VHL) gene. We also performed transfection experiments by using Lipofectamine and measured the enzymatic activity of IDH1 in RCC cell lines. All protocols were performed by the Institutional Review Board (IRB) of Hamamatsu University School of Medicine and Keio University. Informed consent was obtained from the patient in accordance with the IRB of Hamamatsu University School o...

Peter J Facchini - One of the best experts on this subject based on the ideXlab platform.

  • Metabolome Analysis of 20 taxonomically related benzylisoquinoline alkaloid producing plants
    BMC Plant Biology, 2015
    Co-Authors: Jillian M Hagel, Donald R Dinsmore, Rupasri Mandal, David S Wishart, Christoph H Borchers, Peter J Facchini
    Abstract:

    Background Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties.

  • Metabolome Analysis of 20 taxonomically related benzylisoquinoline alkaloid producing plants
    BMC Plant Biology, 2015
    Co-Authors: Jillian M Hagel, Donald R Dinsmore, Rupasri Mandal, David S Wishart, Christoph H Borchers, Beomsoo Han, Jun Han, Peter J Facchini
    Abstract:

    Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional 1H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were mined for metabolites putatively corresponding to BIAs. Different alkaloids profiles, including both ubiquitous and potentially rare compounds, were observed. Extensive metabolite profiling combining multiple analytical platforms enabled a more complete picture of overall metabolism occurring in selected plant species. This study represents the first time a metabolomics approach has been applied to most of these species, despite their importance in modern and traditional medicine. Coupled with genomics data, these metabolomics resources serve as a key resource for the investigation of BIA biosynthesis in non-model plant species.

Dietmar Schomburg - One of the best experts on this subject based on the ideXlab platform.

  • mspecs a software tool for the administration and editing of mass spectral libraries in the field of metabolomics
    BMC Bioinformatics, 2009
    Co-Authors: Bernhard Thielen, Stephanie Heinen, Dietmar Schomburg
    Abstract:

    Background Metabolome Analysis with GC/MS has meanwhile been established as one of the "omics" techniques. Compound identification is done by comparison of the MS data with compound libraries. Mass spectral libraries in the field of metabolomics ought to connect the relevant mass traces of the metabolites to other relevant data, e.g. formulas, chemical structures, identification numbers to other databases etc. Since existing solutions are either commercial and therefore only available for certain instruments or not capable of storing such information, there is need to provide a software tool for the management of such data.

  • metabolitedetector comprehensive Analysis tool for targeted and nontargeted gc ms based Metabolome Analysis
    Analytical Chemistry, 2009
    Co-Authors: Karsten Hiller, Jasper Hangebrauk, Christian Jager, Jana Spura, Kerstin Schreiber, Dietmar Schomburg
    Abstract:

    We have developed a new software, MetaboliteDetector, for the efficient and automatic Analysis of GC/MS-based metabolomics data. Starting with raw MS data, the program detects and subsequently identifies potential metabolites. Moreover, a comparative Analysis of a large number of chromatograms can be performed in either a targeted or nontargeted approach. MetaboliteDetector automatically determines appropriate quantification ions and performs an integration of single ion peaks. The Analysis results can directly be visualized with a principal component Analysis. Since the manual input is limited to absolutely necessary parameters, the program is also usable for the Analysis of high-throughput data. However, the intuitive graphical user interface of MetaboliteDetector additionally allows for a detailed examination of a single GC/MS chromatogram including single ion chromatograms, recorded mass spectra, and identified metabolite spectra in combination with the corresponding reference spectra obtained from a ...

  • a high throughput method for microbial Metabolome Analysis using gas chromatography mass spectrometry
    Analytical Biochemistry, 2007
    Co-Authors: Jana Borner, Sebastian Buchinger, Dietmar Schomburg
    Abstract:

    An analytical high-throughput method based on gas chromatography/mass spectrometry (GC/MS) was developed for fast Metabolome investigation. By parallelization and partial automation the time needed for the preanalytical steps could be reduced. In addition a strong decrease of the relative standard deviation of metabolite concentrations from independent samples on the same microtiter plate from 25 to 13% was achieved. Between different plates the relative standard deviation is comparable to the one observed in standard experiments with shaking flasks. Using a fast GC the time need for the full GC/MS-based Metabolome Analysis could be decreased from 60 to 18 min per run, allowing the measurement of 72 single samples per day and GC/MS machine. In samples of the model organism Corynebacterium glutamicum more than 1000 peaks in the total ion current could be detected in a single fast GC/MS run of which 650 were strong enough to be quantified. Approximately 150 compounds of these were identified using our metabolite MS-library. Correlation Analysis of the concentration vectors of independent wild-type samples raised under the same conditions show very high correlations of 0.99 ± 0.01 (logs). In conclusion this method allows screenings of large mutant libraries for genetically induced metabolic perturbations.

Jillian M Hagel - One of the best experts on this subject based on the ideXlab platform.

  • Metabolome Analysis of 20 taxonomically related benzylisoquinoline alkaloid producing plants
    BMC Plant Biology, 2015
    Co-Authors: Jillian M Hagel, Donald R Dinsmore, Rupasri Mandal, David S Wishart, Christoph H Borchers, Peter J Facchini
    Abstract:

    Background Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties.

  • Metabolome Analysis of 20 taxonomically related benzylisoquinoline alkaloid producing plants
    BMC Plant Biology, 2015
    Co-Authors: Jillian M Hagel, Donald R Dinsmore, Rupasri Mandal, David S Wishart, Christoph H Borchers, Beomsoo Han, Jun Han, Peter J Facchini
    Abstract:

    Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional 1H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were mined for metabolites putatively corresponding to BIAs. Different alkaloids profiles, including both ubiquitous and potentially rare compounds, were observed. Extensive metabolite profiling combining multiple analytical platforms enabled a more complete picture of overall metabolism occurring in selected plant species. This study represents the first time a metabolomics approach has been applied to most of these species, despite their importance in modern and traditional medicine. Coupled with genomics data, these metabolomics resources serve as a key resource for the investigation of BIA biosynthesis in non-model plant species.

Michael Dauner - One of the best experts on this subject based on the ideXlab platform.

  • integrated sampling procedure for Metabolome Analysis
    Biotechnology Progress, 2008
    Co-Authors: Jochen Schaub, Carola Schiesling, Matthias Reuss, Michael Dauner
    Abstract:

    Metabolome Analysis, the Analysis of large sets of intracellular metabolites, has become an important systems Analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of Metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative Analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative Analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures ≤ 95 °C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s -1 and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS Analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady-state metabolite Analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h -1 .

  • integrated sampling procedure for Metabolome Analysis
    Biotechnology Progress, 2008
    Co-Authors: Jochen Schaub, Carola Schiesling, Matthias Reuss, Michael Dauner
    Abstract:

    Metabolome Analysis, the Analysis of large sets of intracellular metabolites, has become an important systems Analysis method in biotechnological and pharmaceutical research. In metabolic engineering, the integration of Metabolome data with fluxome and proteome data into large-scale mathematical models promises to foster rational strategies for strain and cell line improvement. However, the development of reproducible sampling procedures for quantitative Analysis of intracellular metabolite concentrations represents a major challenge, accomplishing (i) fast transfer of sample, (ii) efficient quenching of metabolism, (iii) quantitative metabolite extraction, and (iv) optimum sample conditioning for subsequent quantitative Analysis. In addressing these requirements, we propose an integrated sampling procedure. Simultaneous quenching and quantitative extraction of intracellular metabolites were realized by short-time exposure of cells to temperatures < or =95 degrees C, where intracellular metabolites are released quantitatively. Based on these findings, we combined principles of heat transfer with knowledge on physiology, for example, turnover rates of energy metabolites, to develop an optimized sampling procedure based on a coiled single tube heat exchanger. As a result, this sampling procedure enables reliable and reproducible measurements through (i) the integration of three unit operations into a one unit operation, (ii) the avoidance of any alteration of the sample due to chemical reagents in quenching and extraction, and (iii) automation. A sampling frequency of 5 s(-)(1) and an overall individual sample processing time faster than 30 s allow observing responses of intracellular metabolite concentrations to extracellular stimuli on a subsecond time scale. Recovery and reliability of the unit operations were analyzed. Impact of sample conditioning on subsequent IC-MS Analysis of metabolites was examined as well. The integrated sampling procedure was validated through consistent results from steady-state metabolite Analysis of Escherichia coli cultivated in a chemostat at D = 0.1 h(-)(1).