Next Issue
Previous Issue

Table of Contents

Metabolites, Volume 5, Issue 3 (September 2015) , Pages 404-535

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-8
Export citation of selected articles as:
Open AccessReview Achieving Metabolic Flux Analysis for S. cerevisiae at a Genome-Scale: Challenges, Requirements, and Considerations
Metabolites 2015, 5(3), 521-535; https://doi.org/10.3390/metabo5030521
Received: 26 August 2015 / Accepted: 4 September 2015 / Published: 18 September 2015
Cited by 7 | Viewed by 1979 | PDF Full-text (178 KB) | HTML Full-text | XML Full-text
Abstract
Recent advances in 13C-Metabolic flux analysis (13C-MFA) have increased its capability to accurately resolve fluxes using a genome-scale model with narrow confidence intervals without pre-judging the activity or inactivity of alternate metabolic pathways. However, the necessary precautions, computational challenges, and minimum data requirements [...] Read more.
Recent advances in 13C-Metabolic flux analysis (13C-MFA) have increased its capability to accurately resolve fluxes using a genome-scale model with narrow confidence intervals without pre-judging the activity or inactivity of alternate metabolic pathways. However, the necessary precautions, computational challenges, and minimum data requirements for successful analysis remain poorly established. This review aims to establish the necessary guidelines for performing 13C-MFA at the genome-scale for a compartmentalized eukaryotic system such as yeast in terms of model and data requirements, while addressing key issues such as statistical analysis and network complexity. We describe the various approaches used to simplify the genome-scale model in the absence of sufficient experimental flux measurements, the availability and generation of reaction atom mapping information, and the experimental flux and metabolite labeling distribution measurements to ensure statistical validity of the obtained flux distribution. Organism-specific challenges such as the impact of compartmentalization of metabolism, variability of biomass composition, and the cell-cycle dependence of metabolism are discussed. Identification of errors arising from incorrect gene annotation and suggested alternate routes using MFA are also highlighted. Full article
(This article belongs to the Special Issue Metabolic Flux Analysis)
Figures

Figure 1

Open AccessArticle Metabolomic Screening of Tumor Tissue and Serum in Glioma Patients Reveals Diagnostic and Prognostic Information
Metabolites 2015, 5(3), 502-520; https://doi.org/10.3390/metabo5030502
Received: 9 June 2015 / Revised: 20 August 2015 / Accepted: 6 September 2015 / Published: 15 September 2015
Cited by 15 | Viewed by 2343 | PDF Full-text (696 KB) | HTML Full-text | XML Full-text
Abstract
Glioma grading and classification, today based on histological features, is not always easy to interpret and diagnosis partly relies on the personal experience of the neuropathologists. The most important feature of the classification is the aimed correlation between tumor grade and prognosis. However, [...] Read more.
Glioma grading and classification, today based on histological features, is not always easy to interpret and diagnosis partly relies on the personal experience of the neuropathologists. The most important feature of the classification is the aimed correlation between tumor grade and prognosis. However, in the clinical reality, large variations exist in the survival of patients concerning both glioblastomas and low-grade gliomas. Thus, there is a need for biomarkers for a more reliable classification of glioma tumors as well as for prognosis. We analyzed relative metabolite concentrations in serum samples from 96 fasting glioma patients and 81 corresponding tumor samples with different diagnosis (glioblastoma, oligodendroglioma) and grade (World Health Organization (WHO) grade II, III and IV) using gas chromatography-time of flight mass spectrometry (GC-TOFMS). The acquired data was analyzed and evaluated by pattern recognition based on chemometric bioinformatics tools. We detected feature patterns in the metabolomics data in both tumor and serum that distinguished glioblastomas from oligodendrogliomas (ptumor = 2.46 × 10−8, pserum = 1.3 × 10−5) and oligodendroglioma grade II from oligodendroglioma grade III (ptumor = 0.01, pserum = 0.0008). Interestingly, we also found patterns in both tumor and serum with individual metabolite features that were both elevated and decreased in patients that lived long after being diagnosed with glioblastoma compared to those who died shortly after diagnosis (ptumor = 0.006, pserum = 0.004; AUROCCtumor = 0.846 (0.647–1.000), AUROCCserum = 0.958 (0.870–1.000)). Metabolic patterns could also distinguish long and short survival in patients diagnosed with oligodendroglioma (ptumor = 0.01, pserum = 0.001; AUROCCtumor = 1 (1.000–1.000), AUROCCserum = 1 (1.000–1.000)). In summary, we found different metabolic feature patterns in tumor tissue and serum for glioma diagnosis, grade and survival, which indicates that, following further verification, metabolomic profiling of glioma tissue as well as serum may be a valuable tool in the search for latent biomarkers for future characterization of malignant glioma. Full article
(This article belongs to the Special Issue Cancer Metabolomics 2016)
Figures

Figure 1

Open AccessArticle Integrating Multiple Analytical Datasets to Compare Metabolite Profiles of Mouse Colonic-Cecal Contents and Feces
Metabolites 2015, 5(3), 489-501; https://doi.org/10.3390/metabo5030489
Received: 28 July 2015 / Revised: 25 August 2015 / Accepted: 6 September 2015 / Published: 11 September 2015
Cited by 4 | Viewed by 1908 | PDF Full-text (1079 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The pattern of metabolites produced by the gut microbiome comprises a phenotype indicative of the means by which that microbiome affects the gut. We characterized that phenotype in mice by conducting metabolomic analyses of the colonic-cecal contents, comparing that to the metabolite patterns [...] Read more.
The pattern of metabolites produced by the gut microbiome comprises a phenotype indicative of the means by which that microbiome affects the gut. We characterized that phenotype in mice by conducting metabolomic analyses of the colonic-cecal contents, comparing that to the metabolite patterns of feces in order to determine the suitability of fecal specimens as proxies for assessing the metabolic impact of the gut microbiome. We detected a total of 270 low molecular weight metabolites in colonic-cecal contents and feces by gas chromatograph, time-of-flight mass spectrometry (GC-TOF) and ultra-high performance liquid chromatography, quadrapole time-of-flight mass spectrometry (UPLC-Q-TOF). Of that number, 251 (93%) were present in both types of specimen, representing almost all known biochemical pathways related to the amino acid, carbohydrate, energy, lipid, membrane transport, nucleotide, genetic information processing, and cancer-related metabolism. A total of 115 metabolites differed significantly in relative abundance between both colonic-cecal contents and feces. These data comprise the first characterization of relationships among metabolites present in the colonic-cecal contents and feces in a healthy mouse model, and shows that feces can be a useful proxy for assessing the pattern of metabolites to which the colonic mucosum is exposed. Full article
Figures

Figure 1

Open AccessArticle Identifying the Tautomeric Form of a Deoxyguanosine-Estrogen Quinone Intermediate
Metabolites 2015, 5(3), 475-488; https://doi.org/10.3390/metabo5030475
Received: 11 June 2015 / Revised: 3 September 2015 / Accepted: 6 September 2015 / Published: 10 September 2015
Cited by 1 | Viewed by 1680 | PDF Full-text (759 KB) | HTML Full-text | XML Full-text
Abstract
Mechanistic insights into the reaction of an estrogen o-quinone with deoxyguanosine has been further investigated using high level density functional calculations in addition to the use of 4-hyroxycatecholestrone (4-OHE1) regioselectivity labeled with deuterium at the C1-position. Calculations using the M06-2X [...] Read more.
Mechanistic insights into the reaction of an estrogen o-quinone with deoxyguanosine has been further investigated using high level density functional calculations in addition to the use of 4-hyroxycatecholestrone (4-OHE1) regioselectivity labeled with deuterium at the C1-position. Calculations using the M06-2X functional with large basis sets indicate the tautomeric form of an estrogen-DNA adduct present when glycosidic bonds cleavage occurs is comprised of an aromatic A ring structure. This tautomeric form was further verified by use of deuterium labelling of the catechol precursor use to form the estrogen o-quinone. Regioselective deuterium labelling at the C1-position of the estrogen A ring allows discrimination between two tautomeric forms of a reaction intermediate either of which could be present during glycosidic bond cleavage. HPLC-MS analysis indicates a reactive intermediate with a m/z of 552.22 consistent with a tautomeric form containing no deuterium. This intermediate is consistent with a reaction mechanism that involves: (1) proton assisted Michael addition; (2) re-aromatization of the estrogen A ring; and (3) glycosidic bond cleavage to form the known estrogen-DNA adduct, 4-OHE1-1-N7Gua. Full article
Figures

Figure 1

Open AccessArticle 13C Tracers for Glucose Degrading Pathway Discrimination in Gluconobacter oxydans 621H
Metabolites 2015, 5(3), 455-474; https://doi.org/10.3390/metabo5030455
Received: 10 July 2015 / Revised: 20 August 2015 / Accepted: 24 August 2015 / Published: 2 September 2015
Viewed by 2302 | PDF Full-text (1103 KB) | HTML Full-text | XML Full-text
Abstract
Gluconobacter oxydans 621H is used as an industrial production organism due to its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. With glucose as the carbon source, up to 90% of the initial concentration is oxidized periplasmatically to [...] Read more.
Gluconobacter oxydans 621H is used as an industrial production organism due to its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. With glucose as the carbon source, up to 90% of the initial concentration is oxidized periplasmatically to gluconate and ketogluconates. Growth on glucose is biphasic and intracellular sugar catabolism proceeds via the Entner–Doudoroff pathway (EDP) and the pentose phosphate pathway (PPP). Here we studied the in vivo contributions of the two pathways to glucose catabolism on a microtiter scale. In our approach we applied specifically 13C labeled glucose, whereby a labeling pattern in alanine was generated intracellularly. This method revealed a dynamic growth phase-dependent pathway activity with increased activity of EDP in the first and PPP in the second growth phase, respectively. Evidence for a growth phase-independent decarboxylation-carboxylation cycle around the pyruvate node was obtained from 13C fragmentation patterns of alanine. For the first time, down-scaled microtiter plate cultivation together with 13C-labeled substrate was applied for G. oxydans to elucidate pathway operation, exhibiting reasonable labeling costs and allowing for sufficient replicate experiments. Full article
(This article belongs to the Special Issue Metabolic Flux Analysis)
Figures

Figure 1

Open AccessArticle Temperature Shift Experiments Suggest That Metabolic Impairment and Enhanced Rates of Photorespiration Decrease Organic Acid Levels in Soybean Leaflets Exposed to Supra-Optimal Growth Temperatures
Metabolites 2015, 5(3), 443-454; https://doi.org/10.3390/metabo5030443
Received: 4 June 2015 / Revised: 28 July 2015 / Accepted: 30 July 2015 / Published: 5 August 2015
Cited by 6 | Viewed by 1698 | PDF Full-text (859 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Elevated growth temperatures are known to affect foliar organic acid concentrations in various plant species. In the current study, citrate, malate, malonate, fumarate and succinate decreased 40 to 80% in soybean leaflets when plants were grown continuously in controlled environment chambers at 36/28 [...] Read more.
Elevated growth temperatures are known to affect foliar organic acid concentrations in various plant species. In the current study, citrate, malate, malonate, fumarate and succinate decreased 40 to 80% in soybean leaflets when plants were grown continuously in controlled environment chambers at 36/28 compared to 28/20 °C. Temperature effects on the above mentioned organic acids were partially reversed three days after plants were transferred among optimal and supra-optimal growth temperatures. In addition, CO2 enrichment increased foliar malate, malonate and fumarate concentrations in the supra-optimal temperature treatment, thereby mitigating effects of high temperature on respiratory metabolism. Glycerate, which functions in the photorespiratory pathway, decreased in response to CO2 enrichment at both growth temperatures. The above findings suggested that diminished levels of organic acids in soybean leaflets upon exposure to high growth temperatures were attributable to metabolic impairment and to changes of photorespiratory flux. Leaf development rates differed among temperature and CO2 treatments, which affected foliar organic acid levels. Additionally, we report that large decreases of foliar organic acids in response to elevated growth temperatures were observed in legume species. Full article
(This article belongs to the Special Issue Carbon Metabolism)
Figures

Figure 1

Open AccessArticle Analysis of Metabolomics Datasets with High-Performance Computing and Metabolite Atlases
Metabolites 2015, 5(3), 431-442; https://doi.org/10.3390/metabo5030431
Received: 13 April 2015 / Revised: 7 July 2015 / Accepted: 13 July 2015 / Published: 20 July 2015
Cited by 7 | Viewed by 2976 | PDF Full-text (3088 KB) | HTML Full-text | XML Full-text
Abstract
Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of [...] Read more.
Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. By using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models. Full article
(This article belongs to the Special Issue Bioinformatics and Data Analysis)
Figures

Figure 1

Open AccessArticle A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition
Metabolites 2015, 5(3), 404-430; https://doi.org/10.3390/metabo5030404
Received: 26 February 2015 / Revised: 23 June 2015 / Accepted: 30 June 2015 / Published: 8 July 2015
Cited by 21 | Viewed by 2709 | PDF Full-text (2071 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential [...] Read more.
The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes. Full article
Figures

Figure 1

Metabolites EISSN 2218-1989 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top