Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism

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Christopher M. Shymansky

2017-05-01

Full Text Available 13C metabolic flux analysis (13C MFA is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant of 13C MFA known as 2-Scale 13C metabolic flux analysis (2S-13C MFA. In this study, all strains have the galactose metabolism deactivated (gal1Δ background so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments

Non-stationary (13)C-metabolic flux ratio analysis.

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Hörl, Manuel; Schnidder, Julian; Sauer, Uwe; Zamboni, Nicola

2013-12-01

(13)C-metabolic flux analysis ((13)C-MFA) has become a key method for metabolic engineering and systems biology. In the most common methodology, fluxes are calculated by global isotopomer balancing and iterative fitting to stationary (13)C-labeling data. This approach requires a closed carbon balance, long-lasting metabolic steady state, and the detection of (13)C-patterns in a large number of metabolites. These restrictions mostly reduced the application of (13)C-MFA to the central carbon metabolism of well-studied model organisms grown in minimal media with a single carbon source. Here we introduce non-stationary (13)C-metabolic flux ratio analysis as a novel method for (13)C-MFA to allow estimating local, relative fluxes from ultra-short (13)C-labeling experiments and without the need for global isotopomer balancing. The approach relies on the acquisition of non-stationary (13)C-labeling data exclusively for metabolites in the proximity of a node of converging fluxes and a local parameter estimation with a system of ordinary differential equations. We developed a generalized workflow that takes into account reaction types and the availability of mass spectrometric data on molecular ions or fragments for data processing, modeling, parameter and error estimation. We demonstrated the approach by analyzing three key nodes of converging fluxes in central metabolism of Bacillus subtilis. We obtained flux estimates that are in agreement with published results obtained from steady state experiments, but reduced the duration of the necessary (13)C-labeling experiment to less than a minute. These results show that our strategy enables to formally estimate relative pathway fluxes on extremely short time scale, neglecting cellular carbon balancing. Hence this approach paves the road to targeted (13)C-MFA in dynamic systems with multiple carbon sources and towards rich media. © 2013 Wiley Periodicals, Inc.

Metabolic Flux Analysis of Shewanella spp. Reveals Evolutionary Robustness in Central Carbon Metabolism

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Tang, Yinjie J.; Martin, Hector Garcia; Dehal, Paramvir S.; Deutschbauer, Adam; Llora, Xavier; Meadows, Adam; Arkin, Adam; Keasling, Jay D.

2009-08-19

Shewanella spp. are a group of facultative anaerobic bacteria widely distributed in marine and fresh-water environments. In this study, we profiled the central metabolic fluxes of eight recently sequenced Shewanella species grown under the same condition in minimal med-ium with [3-13C] lactate. Although the tested Shewanella species had slightly different growth rates (0.23-0.29 h31) and produced different amounts of acetate and pyruvate during early exponential growth (pseudo-steady state), the relative intracellular metabolic flux distributions were remarkably similar. This result indicates that Shewanella species share similar regulation in regard to central carbon metabolic fluxes under steady growth conditions: the maintenance of metabolic robustness is not only evident in a single species under genetic perturbations (Fischer and Sauer, 2005; Nat Genet 37(6):636-640), but also observed through evolutionary related microbial species. This remarkable conservation of relative flux profiles through phylogenetic differences prompts us to introduce the concept of metabotype as an alternative scheme to classify microbial fluxomics. On the other hand, Shewanella spp. display flexibility in the relative flux profiles when switching their metabolism from consuming lactate to consuming pyruvate and acetate.

Mapping cancer cell metabolism with 13 C flux analysis: Recent progress and future challenges

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Casey Scott Duckwall

2013-01-01

Full Text Available The reprogramming of energy metabolism is emerging as an important molecular hallmark of cancer cells. Recent discoveries linking specific metabolic alterations to cancer development have strengthened the idea that altered metabolism is more than a side effect of malignant transformation, but may in fact be a functional driver of tumor growth and progression in some cancers. As a result, dysregulated metabolic pathways have become attractive targets for cancer therapeutics. This review highlights the application of 13 C metabolic flux analysis (MFA to map the flow of carbon through intracellular biochemical pathways of cancer cells. We summarize several recent applications of MFA that have identified novel biosynthetic pathways involved in cancer cell proliferation and shed light on the role of specific oncogenes in regulating these pathways. Through such studies, it has become apparent that the metabolic phenotypes of cancer cells are not as homogeneous as once thought, but instead depend strongly on the molecular alterations and environmental factors at play in each case.

Genetic and environmental relationships of metabolic and weight phenotypes to metabolic syndrome and diabetes: the healthy twin study.

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Song, Yun-Mi; Sung, Joohon; Lee, Kayoung

2015-02-01

We aimed to examine the relationships, including genetic and environmental correlations, between metabolic and weight phenotypes and factors related to diabetes and metabolic syndrome. Participants of the Healthy Twin Study without diabetes (n=2687; 895 monozygotic and 204 dizygotic twins, and 1588 nontwin family members; mean age, 42.5±13.1 years) were stratified according to body mass index (BMI) (metabolic syndrome categories at baseline. The metabolic traits, namely diabetes and metabolic syndrome, metabolic syndrome components, glycated hemoglobin (HbA1c) level, and homeostasis model assessment of insulin resistance (HOMA-IR), were assessed after 2.5±2.1 years. In a multivariate-adjusted model, those who had metabolic syndrome or overweight phenotypes at baseline were more likely to have higher HbA1C and HOMA-IR levels and abnormal metabolic syndrome components at follow-up as compared to the metabolically healthy normal weight subgroup. The incidence of diabetes was 4.4-fold higher in the metabolically unhealthy but normal weight individuals and 3.3-fold higher in the metabolically unhealthy and overweight individuals as compared with the metabolically healthy normal weight individuals. The heritability of the metabolic syndrome/weight phenotypes was 0.40±0.03. Significant genetic and environmental correlations were observed between the metabolic syndrome/weight phenotypes at baseline and the metabolic traits at follow-up, except for incident diabetes, which only had a significant common genetic sharing with the baseline phenotypes. The genetic and environmental relationships between the metabolic and weight phenotypes at baseline and the metabolic traits at follow-up suggest pleiotropic genetic mechanisms and the crucial role of lifestyle and behavioral factors.

Fluxomics - connecting 'omics analysis and phenotypes.

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Winter, Gal; Krömer, Jens O

2013-07-01

In our modern 'omics era, metabolic flux analysis (fluxomics) represents the physiological counterpart of its siblings transcriptomics, proteomics and metabolomics. Fluxomics integrates in vivo measurements of metabolic fluxes with stoichiometric network models to allow the determination of absolute flux through large networks of the central carbon metabolism. There are many approaches to implement fluxomics including flux balance analysis (FBA), (13) C fluxomics and (13) C-constrained FBA as well as many experimental settings for flux measurement including dynamic, stationary and semi-stationary. Here we outline the principles of the different approaches and their relative advantages. We demonstrate the unique contribution of flux analysis for phenotype elucidation using a thoroughly studied metabolic reaction as a case study, the microbial aerobic/anaerobic shift, highlighting the importance of flux analysis as a single layer of data as well as interlaced in multi-omics studies. © 2012 John Wiley & Sons Ltd and Society for Applied Microbiology.

1H NMR spectroscopy-based interventional metabolic phenotyping

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Lauridsen, Michael B; Bliddal, Henning; Christensen, Robin

2010-01-01

1H NMR spectroscopy-based metabolic phenotyping was used to identify biomarkers in the plasma of patients with rheumatoid arthritis (RA). Forty-seven patients with RA (23 with active disease at baseline and 24 in remission) and 51 healthy subjects were evaluated during a one-year follow-up with a......1H NMR spectroscopy-based metabolic phenotyping was used to identify biomarkers in the plasma of patients with rheumatoid arthritis (RA). Forty-seven patients with RA (23 with active disease at baseline and 24 in remission) and 51 healthy subjects were evaluated during a one-year follow......-up with assessments of disease activity (DAS-28) and 1H NMR spectroscopy of plasma samples. Discriminant analysis provided evidence that the metabolic profiles predicted disease severity. Cholesterol, lactate, acetylated glycoprotein, and lipid signatures were found to be candidate biomarkers for disease severity.......0007). However, after 31 days of optimized therapy, the two patient groups were not significantly different (P=0.91). The metabolic profiles of both groups of RA patients were different from the healthy subjects. 1H NMR-based metabolic phenotyping of plasma samples in patients with RA is well suited...

Sample size calculation in metabolic phenotyping studies.

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Billoir, Elise; Navratil, Vincent; Blaise, Benjamin J

2015-09-01

The number of samples needed to identify significant effects is a key question in biomedical studies, with consequences on experimental designs, costs and potential discoveries. In metabolic phenotyping studies, sample size determination remains a complex step. This is due particularly to the multiple hypothesis-testing framework and the top-down hypothesis-free approach, with no a priori known metabolic target. Until now, there was no standard procedure available to address this purpose. In this review, we discuss sample size estimation procedures for metabolic phenotyping studies. We release an automated implementation of the Data-driven Sample size Determination (DSD) algorithm for MATLAB and GNU Octave. Original research concerning DSD was published elsewhere. DSD allows the determination of an optimized sample size in metabolic phenotyping studies. The procedure uses analytical data only from a small pilot cohort to generate an expanded data set. The statistical recoupling of variables procedure is used to identify metabolic variables, and their intensity distributions are estimated by Kernel smoothing or log-normal density fitting. Statistically significant metabolic variations are evaluated using the Benjamini-Yekutieli correction and processed for data sets of various sizes. Optimal sample size determination is achieved in a context of biomarker discovery (at least one statistically significant variation) or metabolic exploration (a maximum of statistically significant variations). DSD toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) for Kernel and log-normal estimates, and in GNU Octave for log-normal estimates (Kernel density estimates are not robust enough in GNU octave). It is available at http://www.prabi.fr/redmine/projects/dsd/repository, with a tutorial at http://www.prabi.fr/redmine/projects/dsd/wiki. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Constraining Genome-Scale Models to Represent the Bow Tie Structure of Metabolism for 13C Metabolic Flux Analysis

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Tyler W. H. Backman

2018-01-01

Full Text Available Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1 systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2 automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.

Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii.

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Nanette R Boyle

Full Text Available Despite the wealth of knowledge available for C. reinhardtii, the central metabolic fluxes of growth on acetate have not yet been determined. In this study, 13C-metabolic flux analysis (13C-MFA was used to determine and quantify the metabolic pathways of primary metabolism in C. reinhardtii cells grown under heterotrophic conditions with acetate as the sole carbon source. Isotopic labeling patterns of compartment specific biomass derived metabolites were used to calculate the fluxes. It was found that acetate is ligated with coenzyme A in the three subcellular compartments (cytosol, mitochondria and plastid included in the model. Two citrate synthases were found to potentially be involved in acetyl-coA metabolism; one localized in the mitochondria and the other acting outside the mitochondria. Labeling patterns demonstrate that Acetyl-coA synthesized in the plastid is directly incorporated in synthesis of fatty acids. Despite having a complete TCA cycle in the mitochondria, it was also found that a majority of the malate flux is shuttled to the cytosol and plastid where it is converted to oxaloacetate providing reducing equivalents to these compartments. When compared to predictions by flux balance analysis, fluxes measured with 13C-MFA were found to be suboptimal with respect to biomass yield; C. reinhardtii sacrifices biomass yield to produce ATP and reducing equivalents.

Constraining genome-scale models to represent the bow tie structure of metabolism for 13C metabolic flux analysis

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Backman, Tyler W.H.; Ando, David; Singh, Jahnavi

2018-01-01

for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13C MFA or 2S- 13C MFA, as well as provide for a substantially lower set of flux bounds......Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13C Metabolic Flux Analysis (13C MFA) and Two-Scale 13C Metabolic Flux Analysis (2S-13C MFA) are two techniques used...

Reduced TCA flux in diabetic myotubes: A governing influence on the diabetic phenotype?

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Gaster, Michael

2009-01-01

The diabetic phenotype is complex, requiring elucidation of key initiating defects. It is unknown whether the reduced tricarboxylic acid cycle (TCA) flux in skeletal muscle of obese and obese type 2 diabetic (T2D) subjects is of primary origin. Acetate oxidation (measurement of TCA-flux) was sign......The diabetic phenotype is complex, requiring elucidation of key initiating defects. It is unknown whether the reduced tricarboxylic acid cycle (TCA) flux in skeletal muscle of obese and obese type 2 diabetic (T2D) subjects is of primary origin. Acetate oxidation (measurement of TCA...

Body Temperature Measurements for Metabolic Phenotyping in Mice

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Meyer, Carola W.; Ootsuka, Youichirou; Romanovsky, Andrej A.

2017-01-01

Endothermic organisms rely on tightly balanced energy budgets to maintain a regulated body temperature and body mass. Metabolic phenotyping of mice, therefore, often includes the recording of body temperature. Thermometry in mice is conducted at various sites, using various devices and measurement practices, ranging from single-time probing to continuous temperature imaging. Whilst there is broad agreement that body temperature data is of value, procedural considerations of body temperature measurements in the context of metabolic phenotyping are missing. Here, we provide an overview of the various methods currently available for gathering body temperature data from mice. We explore the scope and limitations of thermometry in mice, with the hope of assisting researchers in the selection of appropriate approaches, and conditions, for comprehensive mouse phenotypic analyses. PMID:28824441

NIH Mouse Metabolic Phenotyping Centers: the power of centralized phenotyping.

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Laughlin, Maren R; Lloyd, K C Kent; Cline, Gary W; Wasserman, David H

2012-10-01

The Mouse Metabolic Phenotyping Centers (MMPCs) were founded in 2001 by the National Institutes of Health (NIH) to advance biomedical research by providing the scientific community with standardized, high-quality phenotyping services for mouse models of diabetes, obesity, and their complications. The intent is to allow researchers to take optimum advantage of the many new mouse models produced in labs and in high-throughput public efforts. The six MMPCs are located at universities around the country and perform complex metabolic tests in intact mice and hormone and analyte assays in tissues on a fee-for-service basis. Testing is subsidized by the NIH in order to reduce the barriers for mouse researchers. Although data derived from these tests belong to the researcher submitting mice or tissues, these data are archived after publication in a public database run by the MMPC Coordinating and Bioinformatics Unit. It is hoped that data from experiments performed in many mouse models of metabolic diseases, using standard protocols, will be useful in understanding the nature of these complex disorders. The current areas of expertise include energy balance and body composition, insulin action and secretion, whole-body and tissue carbohydrate and lipid metabolism, cardiovascular and renal function, and metabolic pathway kinetics. In addition to providing services, the MMPC staff provides expertise and advice to researchers, and works to develop and refine test protocols to best meet the community's needs in light of current scientific developments. Test technology is disseminated by publications and through annual courses.

Metabolic Phenotyping of Diet and Dietary Intake.

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Brignardello, J; Holmes, E; Garcia-Perez, I

Nutrition provides the building blocks for growth, repair, and maintenance of the body and is key to maintaining health. Exposure to fast foods, mass production of dietary components, and wider importation of goods have challenged the balance between diet and health in recent decades, and both scientists and clinicians struggle to characterize the relationship between this changing dietary landscape and human metabolism with its consequent impact on health. Metabolic phenotyping of foods, using high-density data-generating technologies to profile the biochemical composition of foods, meals, and human samples (pre- and postfood intake), can be used to map the complex interaction between the diet and human metabolism and also to assess food quality and safety. Here, we outline some of the techniques currently used for metabolic phenotyping and describe key applications in the food sciences, ending with a broad outlook at some of the newer technologies in the field with a view to exploring their potential to address some of the critical challenges in nutritional science. © 2017 Elsevier Inc. All rights reserved.

Nature and Nurture: What Determines Tumor Metabolic Phenotypes?

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Mayers, Jared R; Vander Heiden, Matthew G

2017-06-15

Understanding the genetic basis of cancer has led to therapies that target driver mutations and has helped match patients with more personalized drugs. Oncogenic mutations influence tumor metabolism, but other tumor characteristics can also contribute to their metabolic phenotypes. Comparison of isogenic lung and pancreas tumor models suggests that use of some metabolic pathways is defined by lineage rather than by driver mutation. Lung tumors catabolize circulating branched chain amino acids (BCAA) to extract nitrogen for nonessential amino acid and nucleotide synthesis, whereas pancreatic cancer obtains amino acids from catabolism of extracellular protein. These differences in amino acid metabolism translate into distinct pathway dependencies, as genetic disruption of the enzymes responsible for utilization of BCAA nitrogen limits the growth of lung tumors, but not pancreatic tumors. These data argue that some cancer metabolic phenotypes are defined by cancer tissue-of-origin and environment and that these features constrain the influence of genetic mutations on metabolism. A better understanding of the factors defining tumor nutrient utilization could be exploited to help improve cancer therapy. Cancer Res; 77(12); 3131-4. ©2017 AACR . ©2017 American Association for Cancer Research.

MicrobesFlux: a web platform for drafting metabolic models from the KEGG database

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Feng Xueyang

2012-08-01

Full Text Available Abstract Background Concurrent with the efforts currently underway in mapping microbial genomes using high-throughput sequencing methods, systems biologists are building metabolic models to characterize and predict cell metabolisms. One of the key steps in building a metabolic model is using multiple databases to collect and assemble essential information about genome-annotations and the architecture of the metabolic network for a specific organism. To speed up metabolic model development for a large number of microorganisms, we need a user-friendly platform to construct metabolic networks and to perform constraint-based flux balance analysis based on genome databases and experimental results. Results We have developed a semi-automatic, web-based platform (MicrobesFlux for generating and reconstructing metabolic models for annotated microorganisms. MicrobesFlux is able to automatically download the metabolic network (including enzymatic reactions and metabolites of ~1,200 species from the KEGG database (Kyoto Encyclopedia of Genes and Genomes and then convert it to a metabolic model draft. The platform also provides diverse customized tools, such as gene knockouts and the introduction of heterologous pathways, for users to reconstruct the model network. The reconstructed metabolic network can be formulated to a constraint-based flux model to predict and analyze the carbon fluxes in microbial metabolisms. The simulation results can be exported in the SBML format (The Systems Biology Markup Language. Furthermore, we also demonstrated the platform functionalities by developing an FBA model (including 229 reactions for a recent annotated bioethanol producer, Thermoanaerobacter sp. strain X514, to predict its biomass growth and ethanol production. Conclusion MicrobesFlux is an installation-free and open-source platform that enables biologists without prior programming knowledge to develop metabolic models for annotated microorganisms in the KEGG

Reduced TCA flux in diabetic myotubes: A governing influence on the diabetic phenotype?

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Gaster, Michael

2009-10-02

The diabetic phenotype is complex, requiring elucidation of key initiating defects. It is unknown whether the reduced tricarboxylic acid cycle (TCA) flux in skeletal muscle of obese and obese type 2 diabetic (T2D) subjects is of primary origin. Acetate oxidation (measurement of TCA-flux) was significantly reduced in primary myotube cultures established from T2D versus lean subjects. Acetate oxidation was acutely stimulated by insulin and respiratory uncoupling. Inhibition of TCA flux in lean myotubes by malonate was followed by a measured decline in; acetate oxidation, complete palmitate oxidation, lipid uptake, glycogen synthesis, ATP content and increased glucose uptake, while glucose oxidation was unaffected. Acute TCA inhibition did not induce insulin resistance. Thus the reduced TCA cycle flux in T2D skeletal muscle may be of primary origin. The diabetic phenotype of increased basal glucose uptake and glucose oxidation, the reduced complete lipid oxidation and increased respiratory quotient, are likely to be adaptive responses to the reduced TCA cycle flux.

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis.

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Morales, Yeimy; Bosque, Gabriel; Vehí, Josep; Picó, Jesús; Llaneras, Francisco

2016-07-11

Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios. Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples. The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production.

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Caroline Colijn

2009-08-01

Full Text Available Metabolism is central to cell physiology, and metabolic disturbances play a role in numerous disease states. Despite its importance, the ability to study metabolism at a global scale using genomic technologies is limited. In principle, complete genome sequences describe the range of metabolic reactions that are possible for an organism, but cannot quantitatively describe the behaviour of these reactions. We present a novel method for modeling metabolic states using whole cell measurements of gene expression. Our method, which we call E-Flux (as a combination of flux and expression, extends the technique of Flux Balance Analysis by modeling maximum flux constraints as a function of measured gene expression. In contrast to previous methods for metabolically interpreting gene expression data, E-Flux utilizes a model of the underlying metabolic network to directly predict changes in metabolic flux capacity. We applied E-Flux to Mycobacterium tuberculosis, the bacterium that causes tuberculosis (TB. Key components of mycobacterial cell walls are mycolic acids which are targets for several first-line TB drugs. We used E-Flux to predict the impact of 75 different drugs, drug combinations, and nutrient conditions on mycolic acid biosynthesis capacity in M. tuberculosis, using a public compendium of over 400 expression arrays. We tested our method using a model of mycolic acid biosynthesis as well as on a genome-scale model of M. tuberculosis metabolism. Our method correctly predicts seven of the eight known fatty acid inhibitors in this compendium and makes accurate predictions regarding the specificity of these compounds for fatty acid biosynthesis. Our method also predicts a number of additional potential modulators of TB mycolic acid biosynthesis. E-Flux thus provides a promising new approach for algorithmically predicting metabolic state from gene expression data.

Identification of genetic elements in metabolism by high-throughput mouse phenotyping

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Rozman, Jan; Rathkolb, Birgit; Oestereicher, Manuela A.

2018-01-01

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic da...

Analysis on endocrine and metabolic features of different phenotypes of polycystic ovary syndrome patients.

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Li, Feng; Yao, Li; Wu, Hong; Cao, Shihong

2016-09-01

To discuss the manifestations of endocrine and metabolism for polycystic ovary syndrome patients with different phenotype. This study selected 226 cases of Rotterdam Standard diagnosed polycystic ovary syndrome patients in People's Hospital of Zhengzhou from October 2013 to February 2015. The control group was the 100 cases of non hyperandrogen menstrual women as the control group. Polycystic ovary syndrome included 4 phenotype: /or anovulatio (O) combined with hyperandrogenism (H) and polycystic ovary morphology (P), phenotype of O and P, phenotype of H and P, and phenotype of O and P. All patients were detected for the clinical endocrine and metabolism related parameters. The phenotype of O and P occupied 55.8%, it had significant difference on the comparison between control group and the luteinizing hormone (LH) and luteinizing hormone/follicle stimulating hormone (LH/FSH) of phenotype of O, H and P, phenotype of O and H and phenotype of O and P; the testosterone (T) of phenotype of O,H and P and phenotype of O and H was apparently higher than phenotype of O and P and control group; The total cholesterol (TC) and triglyceride (TG) in phenotype of O, H and P was greatly higher than phenotype of O and P and control group. The phenotype of O and P was the most common phenotype in PCOS patients. It was same for the clinical endocrine and metabolism of two classic characteristics in PCOS. Compared to other PCOS phenotype, the metabolism in phenotype of O and P was lower. The phenotype classification of PCOS patients could better guide clinical individualized treatment in patients with PCOS.

SUMOFLUX: A Generalized Method for Targeted 13C Metabolic Flux Ratio Analysis

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Kogadeeva, Maria

2016-01-01

Metabolic fluxes are a cornerstone of cellular physiology that emerge from a complex interplay of enzymes, carriers, and nutrients. The experimental assessment of in vivo intracellular fluxes using stable isotopic tracers is essential if we are to understand metabolic function and regulation. Flux estimation based on 13C or 2H labeling relies on complex simulation and iterative fitting; processes that necessitate a level of expertise that ordinarily preclude the non-expert user. To overcome this, we have developed SUMOFLUX, a methodology that is broadly applicable to the targeted analysis of 13C-metabolic fluxes. By combining surrogate modeling and machine learning, we trained a predictor to specialize in estimating flux ratios from measurable 13C-data. SUMOFLUX targets specific flux features individually, which makes it fast, user-friendly, applicable to experimental design and robust in terms of experimental noise and exchange flux magnitude. Collectively, we predict that SUMOFLUX's properties realistically pave the way to high-throughput flux analyses. PMID:27626798

Pool size measurements facilitate the determination of fluxes at branching points in nonstationary metabolic flux analysis: The case of Arabidopsis thaliana

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Robert eHeise

2015-06-01

Full Text Available Pool size measurements are important for the estimation of absolute intracellular fluxes in particular scenarios based on data from heavy carbon isotope experiments. Recently, steady-state fluxes estimates were obtained for central carbon metabolism in an intact illuminated rosette of Arabidopsis thaliana grown photoautotrophically (Szecowka et al., 2013; Heise et al., 2014. Fluxes were estimated therein by integrating mass-spectrometric data of the dynamics of the unlabeled metabolic fraction, data on metabolic pool sizes, partitioning of metabolic pools between cellular compartments and estimates of photosynthetically inactive pools, with a simplified model of plant central carbon metabolism. However, the fluxes were determined by treating the pool sizes as fixed parameters. Here we investigated whether and, if so, to what extent the treatment of pool sizes as parameters to be optimized in three scenarios may affect the flux estimates. The results are discussed in terms of benchmark values for canonical pathways and reactions, including starch and sucrose synthesis as well as the ribulose-1,5-bisphosphate carboxylation and oxygenation reactions. In addition, we discuss pathways emerging from a divergent branch point for which pool sizes are required for flux estimation, irrespective of the computational approach used for the simulation of the observable labelling pattern. Therefore, our findings indicate the necessity for development of techniques for accurate pool size measurements to improve the quality of flux estimates from nonstationary flux estimates in intact plant cells in the absence of alternative flux measurements.

Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.

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Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S

2013-05-01

Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiobjective flux balancing using the NISE method for metabolic network analysis.

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Oh, Young-Gyun; Lee, Dong-Yup; Lee, Sang Yup; Park, Sunwon

2009-01-01

Flux balance analysis (FBA) is well acknowledged as an analysis tool of metabolic networks in the framework of metabolic engineering. However, FBA has a limitation for solving a multiobjective optimization problem which considers multiple conflicting objectives. In this study, we propose a novel multiobjective flux balance analysis method, which adapts the noninferior set estimation (NISE) method (Solanki et al., 1993) for multiobjective linear programming (MOLP) problems. NISE method can generate an approximation of the Pareto curve for conflicting objectives without redundant iterations of single objective optimization. Furthermore, the flux distributions at each Pareto optimal solution can be obtained for understanding the internal flux changes in the metabolic network. The functionality of this approach is shown by applying it to a genome-scale in silico model of E. coli. Multiple objectives for the poly(3-hydroxybutyrate) [P(3HB)] production are considered simultaneously, and relationships among them are identified. The Pareto curve for maximizing succinic acid production vs. maximizing biomass production is used for the in silico analysis of various combinatorial knockout strains. This proposed method accelerates the strain improvement in the metabolic engineering by reducing computation time of obtaining the Pareto curve and analysis time of flux distribution at each Pareto optimal solution. (c) 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009.

Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit.

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Colombié, Sophie; Nazaret, Christine; Bénard, Camille; Biais, Benoît; Mengin, Virginie; Solé, Marion; Fouillen, Laëtitia; Dieuaide-Noubhani, Martine; Mazat, Jean-Pierre; Beauvoit, Bertrand; Gibon, Yves

2015-01-01

Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co-factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulated metabolites in the pericarp, determined at each stage, were fitted in order to calculate, by derivation, the corresponding external fluxes. They were used as constraints to solve the model by minimizing the internal fluxes. The distribution of the calculated fluxes of central metabolism were then analysed and compared with known metabolic behaviours. For instance, the partition of the main metabolic pathways (glycolysis, pentose phosphate pathway, etc.) was relevant throughout fruit development. We also predicted a valid import of carbon and nitrogen by the fruit, as well as a consistent CO2 release. Interestingly, the energetic balance indicates that excess ATP is dissipated just before the onset of ripening, supporting the concept of the climacteric crisis. Finally, the apparent contradiction between calculated fluxes with low values compared with measured enzyme capacities suggest a complex reprogramming of the metabolic machinery during fruit development. With a powerful set of experimental data and an accurate definition of the metabolic system, this work provides important insight into the metabolic and physiological requirements of the developing tomato fruits. © 2014 The Authors The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

Phenotypic and metabolic traits of commercial Saccharomyces cerevisiae yeasts.

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Barbosa, Catarina; Lage, Patrícia; Vilela, Alice; Mendes-Faia, Arlete; Mendes-Ferreira, Ana

2014-01-01

Currently, pursuing yeast strains that display both a high potential fitness for alcoholic fermentation and a favorable impact on quality is a major goal in the alcoholic beverage industry. This considerable industrial interest has led to many studies characterizing the phenotypic and metabolic traits of commercial yeast populations. In this study, 20 Saccharomyces cerevisiae strains from different geographical origins exhibited high phenotypic diversity when their response to nine biotechnologically relevant conditions was examined. Next, the fermentation fitness and metabolic traits of eight selected strains with a unique phenotypic profile were evaluated in a high-sugar synthetic medium under two nitrogen regimes. Although the strains exhibited significant differences in nitrogen requirements and utilization rates, a direct relationship between nitrogen consumption, specific growth rate, cell biomass, cell viability, acetic acid and glycerol formation was only observed under high-nitrogen conditions. In contrast, the strains produced more succinic acid under the low-nitrogen regime, and a direct relationship with the final cell biomass was established. Glucose and fructose utilization patterns depended on both yeast strain and nitrogen availability. For low-nitrogen fermentation, three strains did not fully degrade the fructose. This study validates phenotypic and metabolic diversity among commercial wine yeasts and contributes new findings on the relationship between nitrogen availability, yeast cell growth and sugar utilization. We suggest that measuring nitrogen during the stationary growth phase is important because yeast cells fermentative activity is not exclusively related to population size, as previously assumed, but it is also related to the quantity of nitrogen consumed during this growth phase.

Host Genotype and Gut Microbiome Modulate Insulin Secretion and Diet-Induced Metabolic Phenotypes.

Science.gov (United States)

Kreznar, Julia H; Keller, Mark P; Traeger, Lindsay L; Rabaglia, Mary E; Schueler, Kathryn L; Stapleton, Donald S; Zhao, Wen; Vivas, Eugenio I; Yandell, Brian S; Broman, Aimee Teo; Hagenbuch, Bruno; Attie, Alan D; Rey, Federico E

2017-02-14

Genetic variation drives phenotypic diversity and influences the predisposition to metabolic disease. Here, we characterize the metabolic phenotypes of eight genetically distinct inbred mouse strains in response to a high-fat/high-sucrose diet. We found significant variation in diabetes-related phenotypes and gut microbiota composition among the different mouse strains in response to the dietary challenge and identified taxa associated with these traits. Follow-up microbiota transplant experiments showed that altering the composition of the gut microbiota modifies strain-specific susceptibility to diet-induced metabolic disease. Animals harboring microbial communities with enhanced capacity for processing dietary sugars and for generating hydrophobic bile acids showed increased susceptibility to metabolic disease. Notably, differences in glucose-stimulated insulin secretion between different mouse strains were partially recapitulated via gut microbiota transfer. Our results suggest that the gut microbiome contributes to the genetic and phenotypic diversity observed among mouse strains and provide a link between the gut microbiome and insulin secretion. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Rumen microbial communities influence metabolic phenotypes in lambs

DEFF Research Database (Denmark)

Morgavi, Diego P.; Rahahao-Paris, Estelle; Popova, Milka

2015-01-01

and the metabolic phenotype of lambs for identifying host-microbe associations and potential biomarkers of digestive functions. Twin lambs, separated in two groups after birth were exposed to practices (isolation and gavage with rumen fluid with protozoa or protozoa-depleted) that differentially restricted...

Maintenance metabolism and carbon fluxes in Bacillus species

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Decasper Seraina

2008-06-01

Full Text Available Abstract Background Selection of an appropriate host organism is crucial for the economic success of biotechnological processes. A generally important selection criterion is a low maintenance energy metabolism to reduce non-productive consumption of substrate. We here investigated, whether various bacilli that are closely related to Bacillus subtilis are potential riboflavin production hosts with low maintenance metabolism. Results While B. subtilis exhibited indeed the highest maintenance energy coefficient, B. licheniformis and B. amyloliquefaciens exhibited only statistically insignificantly reduced maintenance metabolism. Both B. pumilus and B. subtilis (natto exhibited irregular growth patterns under glucose limitation such that the maintenance metabolism could not be determined. The sole exception with significantly reduced maintenance energy requirements was the B. licheniformis strain T380B. The frequently used spo0A mutation significantly increased the maintenance metabolism of B. subtilis. At the level of 13C-detected intracellular fluxes, all investigated bacilli exhibited a significant flux through the pentose phosphate pathway, a prerequisite for efficient riboflavin production. Different from all other species, B. subtilis featured high respiratory tricarboxylic acid cycle fluxes in batch and chemostat cultures. In particular under glucose-limited conditions, this led to significant excess formation of NADPH of B. subtilis, while anabolic consumption was rather balanced with catabolic NADPH formation in the other bacilli. Conclusion Despite its successful commercial production of riboflavin, B. subtilis does not seem to be the optimal cell factory from a bioenergetic point of view. The best choice of the investigated strains is the sporulation-deficient B. licheniformis T380B strain. Beside a low maintenance energy coefficient, this strain grows robustly under different conditions and exhibits only moderate acetate overflow, hence

Study of AMPK-Regulated Metabolic Fluxes in Neurons Using the Seahorse XFe Analyzer.

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Marinangeli, Claudia; Kluza, Jérome; Marchetti, Philippe; Buée, Luc; Vingtdeux, Valérie

2018-01-01

AMP-activated protein kinase (AMPK) is the intracellular master energy sensor and metabolic regulator. AMPK is involved in cell energy homeostasis through the regulation of glycolytic flux and mitochondrial biogenesis. Interestingly, metabolic dysfunctions and AMPK deregulations are observed in many neurodegenerative diseases, including Alzheimer's. While these deregulations could play a key role in the development of these diseases, the study of metabolic fluxes has remained quite challenging and time-consuming. In this chapter, we describe the Seahorse XFe respirometry assay as a fundamental experimental tool to investigate the role of AMPK in controlling and modulating cell metabolic fluxes in living and intact differentiated primary neurons. The Seahorse XFe respirometry assay allows the real-time monitoring of glycolytic flux and mitochondrial respiration from different kind of cells, tissues, and isolated mitochondria. Here, we specify a protocol optimized for primary neuronal cells using several energy substrates such as glucose, pyruvate, lactate, glutamine, and ketone bodies. Nevertheless, this protocol can easily be adapted to monitor metabolic fluxes from other types of cells, tissues, or isolated mitochondria by taking into account the notes proposed for each key step of this assay.

Dynamic metabolic flux analysis using B-splines to study the effects of temperature shift on CHO cell metabolism

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Verónica S. Martínez

2015-12-01

Full Text Available Metabolic flux analysis (MFA is widely used to estimate intracellular fluxes. Conventional MFA, however, is limited to continuous cultures and the mid-exponential growth phase of batch cultures. Dynamic MFA (DMFA has emerged to characterize time-resolved metabolic fluxes for the entire culture period. Here, the linear DMFA approach was extended using B-spline fitting (B-DMFA to estimate mass balanced fluxes. Smoother fits were achieved using reduced number of knots and parameters. Additionally, computation time was greatly reduced using a new heuristic algorithm for knot placement. B-DMFA revealed that Chinese hamster ovary cells shifted from 37 °C to 32 °C maintained a constant IgG volume-specific productivity, whereas the productivity for the controls peaked during mid-exponential growth phase and declined afterward. The observed 42% increase in product titer at 32 °C was explained by a prolonged cell growth with high cell viability, a larger cell volume and a more stable volume-specific productivity. Keywords: Dynamic, Metabolism, Flux analysis, CHO cells, Temperature shift, B-spline curve fitting

Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions

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Edwards Jeremy S

2000-07-01

Full Text Available Abstract Background Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silico representations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA. FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information. Results Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coli using FBA and examined the optimal utilization of the E. coli metabolic pathways as a function of environmental variables. We have used an in silico analysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system essential for aerobic growth of E. coli on glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi-, zwf, and pta- mutant strains were examined in more detail by mapping the capabilities of these in silico isogenic strains. Conclusions We found that computational models of E. coli metabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silica results lead to a further understanding of the complex genotype-phenotype relation. Supplementary information: http://gcrg.ucsd.edu/supplementary_data/DeletionAnalysis/main.htm

The role of metabolism in modulating CO2 fluxes in boreal lakes

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Bogard, Matthew J.; del Giorgio, Paul A.

2016-10-01

Lake CO2 emissions are increasingly recognized as an important component of the global CO2 cycle, yet the origin of these emissions is not clear, as specific contributions from metabolism and in-lake cycling, versus external inputs, are not well defined. To assess the coupling of lake metabolism with CO2 concentrations and fluxes, we estimated steady state ratios of gross primary production to respiration (GPP:R) and rates of net ecosystem production (NEP = GPP-R) from surface water O2 dynamics (concentration and stable isotopes) in 187 boreal lakes spanning long environmental gradients. Our findings suggest that internal metabolism plays a dominant role in regulating CO2 fluxes in most lakes, but this pattern only emerges when examined at a resolution that accounts for the vastly differing relationships between lake metabolism and CO2 fluxes. Fluxes of CO2 exceeded those from NEP in over half the lakes, but unexpectedly, these effects were most common and typically largest in a subset ( 30% of total) of net autotrophic lakes that nevertheless emitted CO2. Equally surprising, we found no environmental characteristics that distinguished this category from the more common net heterotrophic, CO2 outgassing lakes. Excess CO2 fluxes relative to NEP were best predicted by catchment structure and hydrologic properties, and we infer from a combination of methods that both catchment inputs and internal anaerobic processes may have contributed this excess CO2. Together, our findings show that the link between lake metabolism and CO2 fluxes is often strong but can vary widely across the boreal biome, having important implications for catchment-wide C budgets.

Hydrogen production and metabolic flux analysis of metabolically engineered Escherichia coli strains

Energy Technology Data Exchange (ETDEWEB)

Kim, Seohyoung; Seol, Eunhee; Park, Sunghoon [Department of Chemical and Biochemical Engineering, Pusan National University, Busan 609-735 (Korea); Oh, You-Kwan [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-543 (Korea); Wang, G.Y. [Department of Oceanography, University of Hawaii at Manoa Honolulu, HI 96822 (United States)

2009-09-15

Escherichia coli can produce H{sub 2} from glucose via formate hydrogen lyase (FHL). In order to improve the H{sub 2} production rate and yield, metabolically engineered E. coli strains, which included pathway alterations in their H{sub 2} production and central carbon metabolism, were developed and characterized by batch experiments and metabolic flux analysis. Deletion of hycA, a negative regulator for FHL, resulted in twofold increase of FHL activity. Deletion of two uptake hydrogenases (1 (hya) and hydrogenase 2 (hyb)) increased H{sub 2} production yield from 1.20 mol/mol glucose to 1.48 mol/mol glucose. Deletion of lactate dehydrogenase (ldhA) and fumarate reductase (frdAB) further improved the H{sub 2} yield; 1.80 mol/mol glucose under high H{sub 2} pressure or 2.11 mol/mol glucose under reduced H{sub 2} pressure. Several batch experiments at varying concentrations of glucose (2.5-10 g/L) and yeast extract (0.3 or 3.0 g/L) were conducted for the strain containing all these genetic alternations, and their carbon and energy balances were analyzed. The metabolic flux analysis revealed that deletion of ldhA and frdAB directed most of the carbons from glucose to the glycolytic pathway leading to H{sub 2} production by FHL, not to the pentose phosphate pathway. (author)

Genetic and Environmental Regulation on Longitudinal Change of Metabolic Phenotypes in Danish and Chinese Adult Twins

DEFF Research Database (Denmark)

Li, Shuxia; Kyvik, Kirsten Ohm; Pang, Zengchang

2016-01-01

OBJECTIVE: The rate of change in metabolic phenotypes can be highly indicative of metabolic disorders and disorder-related modifications. We analyzed data from longitudinal twin studies on multiple metabolic phenotypes in Danish and Chinese twins representing two populations of distinct ethnic...... pairs traced for about 7 years with a mean baseline age of 39.5 years (range: 23-64). The classical twin models were fitted to the longitudinal change in each phenotype (Δphenotype) to estimate the genetic and environmental contributions to the variation in Δphenotype. RESULTS: Moderate to high...... contributions by the unique environment were estimated for all phenotypes in both Danish (from 0.51 for low density lipoprotein cholesterol up to 0.72 for triglycerides) and Chinese (from 0.41 for triglycerides up to 0.73 for diastolic blood pressure) twins; low to moderate genetic components were estimated...

Lansoprazole Is Associated with Worsening Asthma Control in Children with the CYP2C19 Poor Metabolizer Phenotype.

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Lang, Jason E; Holbrook, Janet T; Mougey, Edward B; Wei, Christine Y; Wise, Robert A; Teague, W Gerald; Lima, John J

2015-06-01

Gastric acid blockade in children with asymptomatic acid reflux has not improved asthma control in published studies. There is substantial population variability regarding metabolism of and response to proton pump inhibitors based on metabolizer phenotype. How metabolizer phenotype affects asthma responses to acid blockage is not known. To determine how metabolizer phenotype based on genetic analysis of CYP2C19 affects asthma control among children treated with a proton pump inhibitor. Asthma control as measured by the Asthma Control Questionnaire (ACQ) and other questionnaires from a 6-month clinical trial of lansoprazole in children with asthma was analyzed for associations with surrogates of lansoprazole exposure (based on treatment assignment and metabolizer phenotype). Groups included placebo-treated children; lansoprazole-treated extensive metabolizers (EMs); and lansoprazole-treated poor metabolizers (PMs). Metabolizer phenotypes were based on CYP2C19 haplotypes. Carriers of the CYP2C19*2, *3, *8, *9, or *10 allele were PMs; carriers of two wild-type alleles were extensive metabolizers (EMs). Asthma control through most of the treatment period was unaffected by lansoprazole exposure or metabolizer phenotype. At 6 months, PMs displayed significantly worsened asthma control compared with EMs (+0.16 vs. -0.13; P = 0.02) and placebo-treated children (+0.16 vs. -0.23; P lansoprazole-treated PMs. Children with the PM phenotype developed worse asthma control after 6 months of lansoprazole treatment for poorly controlled asthma. Increased exposure to proton pump inhibitor may worsen asthma control by altering responses to respiratory infections. Clinical trial registered with www.clinicaltrials.gov (NCT00604851).

Metabolic flux analysis of Cyanothece sp. ATCC 51142 under mixotrophic conditions.

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Alagesan, Swathi; Gaudana, Sandeep B; Sinha, Avinash; Wangikar, Pramod P

2013-11-01

Cyanobacteria are a group of photosynthetic prokaryotes capable of utilizing solar energy to fix atmospheric carbon dioxide to biomass. Despite several "proof of principle" studies, low product yield is an impediment in commercialization of cyanobacteria-derived biofuels. Estimation of intracellular reaction rates by (13)C metabolic flux analysis ((13)C-MFA) would be a step toward enhancing biofuel yield via metabolic engineering. We report (13)C-MFA for Cyanothece sp. ATCC 51142, a unicellular nitrogen-fixing cyanobacterium, known for enhanced hydrogen yield under mixotrophic conditions. Rates of reactions in the central carbon metabolism under nitrogen-fixing and -non-fixing conditions were estimated by monitoring the competitive incorporation of (12)C and (13)C from unlabeled CO2 and uniformly labeled glycerol, respectively, into terminal metabolites such as amino acids. The observed labeling patterns suggest mixotrophic growth under both the conditions, with a larger fraction of unlabeled carbon in nitrate-sufficient cultures asserting a greater contribution of carbon fixation by photosynthesis and an anaplerotic pathway. Indeed, flux analysis complements the higher growth observed under nitrate-sufficient conditions. On the other hand, the flux through the oxidative pentose phosphate pathway and tricarboxylic acid cycle was greater in nitrate-deficient conditions, possibly to supply the precursors and reducing equivalents needed for nitrogen fixation. In addition, an enhanced flux through fructose-6-phosphate phosphoketolase possibly suggests the organism's preferred mode under nitrogen-fixing conditions. The (13)C-MFA results complement the reported predictions by flux balance analysis and provide quantitative insight into the organism's distinct metabolic features under nitrogen-fixing and -non-fixing conditions.

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis.

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Lee, Jessica J Y; Gottlieb, Michael M; Lever, Jake; Jones, Steven J M; Blau, Nenad; van Karnebeek, Clara D M; Wasserman, Wyeth W

2018-05-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze phenotypes. Such methods have allowed phenotypic data to be widely used in medical applications, from assisting clinical diagnoses to prioritizing genomic diagnoses. To channel the benefits of phenomics into the field of inborn errors of metabolism (IEM), we have recently launched IEMbase, an expert-curated knowledgebase of IEM and their disease-characterizing phenotypes. While our efforts with IEMbase have realized benefits, taking full advantage of phenomics requires a comprehensive curation of IEM phenotypes in core phenomics projects, which is dependent upon contributions from the IEM clinical and research community. Here, we assess the inclusion of IEM biochemical phenotypes in a core phenomics project, the Human Phenotype Ontology. We then demonstrate the utility of biochemical phenotypes using a text-based phenomics method to predict gene-disease relationships, showing that the prediction of IEM genes is significantly better using biochemical rather than clinical profiles. The findings herein provide a motivating goal for the IEM community to expand the computationally accessible descriptions of biochemical phenotypes associated with IEM in phenomics resources.

Synergizing metabolic flux analysis and nucleotide sugar metabolism to understand the control of glycosylation of recombinant protein in CHO cells

LENUS (Irish Health Repository)

Burleigh, Susan C

2011-10-18

Abstract Background The glycosylation of recombinant proteins can be altered by a range of parameters including cellular metabolism, metabolic flux and the efficiency of the glycosylation process. We present an experimental set-up that allows determination of these key processes associated with the control of N-linked glycosylation of recombinant proteins. Results Chinese hamster ovary cells (CHO) were cultivated in shake flasks at 0 mM glutamine and displayed a reduced growth rate, glucose metabolism and a slower decrease in pH, when compared to other glutamine-supplemented cultures. The N-linked glycosylation of recombinant human chorionic gonadotrophin (HCG) was also altered under these conditions; the sialylation, fucosylation and antennarity decreased, while the proportion of neutral structures increased. A continuous culture set-up was subsequently used to understand the control of HCG glycosylation in the presence of varied glutamine concentrations; when glycolytic flux was reduced in the absence of glutamine, the glycosylation changes that were observed in shake flask culture were similarly detected. The intracellular content of UDP-GlcNAc was also reduced, which correlated with a decrease in sialylation and antennarity of the N-linked glycans attached to HCG. Conclusions The use of metabolic flux analysis illustrated a case of steady state multiplicity, where use of the same operating conditions at each steady state resulted in altered flux through glycolysis and the TCA cycle. This study clearly demonstrated that the control of glycoprotein microheterogeneity may be examined by use of a continuous culture system, metabolic flux analysis and assay of intracellular nucleotides. This system advances our knowledge of the relationship between metabolic flux and the glycosylation of biotherapeutics in CHO cells and will be of benefit to the bioprocessing industry.

Applications of computational modeling in metabolic engineering of yeast.

Science.gov (United States)

Kerkhoven, Eduard J; Lahtvee, Petri-Jaan; Nielsen, Jens

2015-02-01

Generally, a microorganism's phenotype can be described by its pattern of metabolic fluxes. Although fluxes cannot be measured directly, inference of fluxes is well established. In biotechnology the aim is often to increase the capacity of specific fluxes. For this, metabolic engineering methods have been developed and applied extensively. Many of these rely on balancing of intracellular metabolites, redox, and energy fluxes, using genome-scale models (GEMs) that in combination with appropriate objective functions and constraints can be used to predict potential gene targets for obtaining a preferred flux distribution. These methods point to strategies for altering gene expression; however, fluxes are often controlled by post-transcriptional events. Moreover, GEMs are usually not taking into account metabolic regulation, thermodynamics and enzyme kinetics. To facilitate metabolic engineering, tools from synthetic biology have emerged, enabling integration and assembly of naturally nonexistent, but well-characterized components into a living organism. To describe these systems kinetic models are often used and to integrate these systems with the standard metabolic engineering approach, it is necessary to expand the modeling of metabolism to consider kinetics of individual processes. This review will give an overview about models available for metabolic engineering of yeast and discusses their applications. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.

13C metabolic flux analysis: optimal design of isotopic labeling experiments.

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Antoniewicz, Maciek R

2013-12-01

Measuring fluxes by 13C metabolic flux analysis (13C-MFA) has become a key activity in chemical and pharmaceutical biotechnology. Optimal design of isotopic labeling experiments is of central importance to 13C-MFA as it determines the precision with which fluxes can be estimated. Traditional methods for selecting isotopic tracers and labeling measurements did not fully utilize the power of 13C-MFA. Recently, new approaches were developed for optimal design of isotopic labeling experiments based on parallel labeling experiments and algorithms for rational selection of tracers. In addition, advanced isotopic labeling measurements were developed based on tandem mass spectrometry. Combined, these approaches can dramatically improve the quality of 13C-MFA results with important applications in metabolic engineering and biotechnology. Copyright © 2013 Elsevier Ltd. All rights reserved.

Metabolic-flux analysis of hydrogen production pathway in Citrobacter amalonaticus Y19

Energy Technology Data Exchange (ETDEWEB)

Oh, You-Kwan; Kim, Mi-Sun [Bioenergy Research Center, Korea Institute of Energy Research, Daejeon 305-343 (Korea); Kim, Heung-Joo; Park, Sunghoon [Department of Chemical and Biochemical Engineering and Institute for Environmental Technology and Industry, Pusan National University, Busan 609-735 (Korea); Ryu, Dewey D.Y. [Biochemical Engineering Program, Department of Chemical Engineering and Material Science, University of California, Davis, CA 95616 (United States)

2008-03-15

For the newly isolated chemoheterotrophic bacterium Citrobacter amalonaticus Y19, anaerobic glucose metabolism and hydrogen (H{sub 2}) production pathway were studied using batch cultivation and an in silico metabolic-flux analysis. Batch cultivation was conducted under varying initial glucose concentration between 1.5 and 9.5 g/L with quantitative measurement of major metabolites to obtain accurate carbon material balance. The metabolic flux of Y19 was analyzed using a metabolic-pathway model which was constructed from 81 biochemical reactions. The linear optimization program MetaFluxNet was employed for the analysis. When the specific growth rate of cells was chosen as an objective function, the model described the batch culture characteristics of Ci. amalonaticus Y19 reasonably well. When the specific H{sub 2} production rate was selected as an objective function, on the other hand, the achievable maximal H{sub 2} production yield (8.7molH{sub 2}/mol glucose) and the metabolic pathway enabling the high H{sub 2} yield were identified. The pathway involved non-native NAD(P)-linked hydrogenase and H{sub 2} production from NAD(P)H which were supplied at a high rate from glucose degradation through the pentose phosphate pathway. (author)

iMS2Flux – a high–throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis

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Poskar C Hart

2012-11-01

Full Text Available Abstract Background Metabolic flux analysis has become an established method in systems biology and functional genomics. The most common approach for determining intracellular metabolic fluxes is to utilize mass spectrometry in combination with stable isotope labeling experiments. However, before the mass spectrometric data can be used it has to be corrected for biases caused by naturally occurring stable isotopes, by the analytical technique(s employed, or by the biological sample itself. Finally the MS data and the labeling information it contains have to be assembled into a data format usable by flux analysis software (of which several dedicated packages exist. Currently the processing of mass spectrometric data is time-consuming and error-prone requiring peak by peak cut-and-paste analysis and manual curation. In order to facilitate high-throughput metabolic flux analysis, the automation of multiple steps in the analytical workflow is necessary. Results Here we describe iMS2Flux, software developed to automate, standardize and connect the data flow between mass spectrometric measurements and flux analysis programs. This tool streamlines the transfer of data from extraction via correction tools to 13C-Flux software by processing MS data from stable isotope labeling experiments. It allows the correction of large and heterogeneous MS datasets for the presence of naturally occurring stable isotopes, initial biomass and several mass spectrometry effects. Before and after data correction, several checks can be performed to ensure accurate data. The corrected data may be returned in a variety of formats including those used by metabolic flux analysis software such as 13CFLUX, OpenFLUX and 13CFLUX2. Conclusion iMS2Flux is a versatile, easy to use tool for the automated processing of mass spectrometric data containing isotope labeling information. It represents the core framework for a standardized workflow and data processing. Due to its flexibility

Co-regulation of metabolic genes is better explained by flux coupling than by network distance.

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Richard A Notebaart

2008-01-01

Full Text Available To what extent can modes of gene regulation be explained by systems-level properties of metabolic networks? Prior studies on co-regulation of metabolic genes have mainly focused on graph-theoretical features of metabolic networks and demonstrated a decreasing level of co-expression with increasing network distance, a naïve, but widely used, topological index. Others have suggested that static graph representations can poorly capture dynamic functional associations, e.g., in the form of dependence of metabolic fluxes across genes in the network. Here, we systematically tested the relative importance of metabolic flux coupling and network position on gene co-regulation, using a genome-scale metabolic model of Escherichia coli. After validating the computational method with empirical data on flux correlations, we confirm that genes coupled by their enzymatic fluxes not only show similar expression patterns, but also share transcriptional regulators and frequently reside in the same operon. In contrast, we demonstrate that network distance per se has relatively minor influence on gene co-regulation. Moreover, the type of flux coupling can explain refined properties of the regulatory network that are ignored by simple graph-theoretical indices. Our results underline the importance of studying functional states of cellular networks to define physiologically relevant associations between genes and should stimulate future developments of novel functional genomic tools.

Reconstruction and flux analysis of coupling between metabolic pathways of astrocytes and neurons: application to cerebral hypoxia

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Akιn Ata

2007-12-01

Full Text Available Abstract Background It is a daunting task to identify all the metabolic pathways of brain energy metabolism and develop a dynamic simulation environment that will cover a time scale ranging from seconds to hours. To simplify this task and make it more practicable, we undertook stoichiometric modeling of brain energy metabolism with the major aim of including the main interacting pathways in and between astrocytes and neurons. Model The constructed model includes central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, lipid metabolism, reactive oxygen species (ROS detoxification, amino acid metabolism (synthesis and catabolism, the well-known glutamate-glutamine cycle, other coupling reactions between astrocytes and neurons, and neurotransmitter metabolism. This is, to our knowledge, the most comprehensive attempt at stoichiometric modeling of brain metabolism to date in terms of its coverage of a wide range of metabolic pathways. We then attempted to model the basal physiological behaviour and hypoxic behaviour of the brain cells where astrocytes and neurons are tightly coupled. Results The reconstructed stoichiometric reaction model included 217 reactions (184 internal, 33 exchange and 216 metabolites (183 internal, 33 external distributed in and between astrocytes and neurons. Flux balance analysis (FBA techniques were applied to the reconstructed model to elucidate the underlying cellular principles of neuron-astrocyte coupling. Simulation of resting conditions under the constraints of maximization of glutamate/glutamine/GABA cycle fluxes between the two cell types with subsequent minimization of Euclidean norm of fluxes resulted in a flux distribution in accordance with literature-based findings. As a further validation of our model, the effect of oxygen deprivation (hypoxia on fluxes was simulated using an FBA-derivative approach, known as minimization of metabolic adjustment (MOMA. The results show the power of the

THE RELEVANCE OF METABOLIC PHENOTYPES OF OBESITY IN CHILDHOOD AND ADOLESCENCE

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S. I. Malyavskaya

2015-01-01

Full Text Available Rationale: The study  on  specifics of metabolic phenotypes of obesity in children and adolescents seems be highly relevant for a comprehensive assessment  of causal and  pathophysiological  roles of obesity in the  atherogenesis. Aim: To identify particulars of metabolic  phenotypes of obesity in the  population of the  school children in the  city of Arkhangelsk. Materials and methods: We examined 102 patients aged from 10 to 15 years with obesity, abdominal type (boys, 44.6%, girls, 55.4%. According to the results of a comprehensive clinical and laboratory assessments, the patients  were divided  into  the  group  of metabolically  healthy obese   (children  and  adolescents  with  obesity, but without any metabolic abnormalities and the group of metabolically unhealthy obese (having at least 1 metabolic abnormality. The list of metabolic abnormalities  included  high triglyceride levels, low levels of high density lipoprotein  cholesterol (HDL-C, high blood pressure, impaired fasting glucose, increased  C-reactive protein  levels. Results: The  group  comparison   showed  that  the  mean levels  of  all studied   parameters  of  pro-atherogenic  metabolic  abnormalities  were significantly higher  in the  patients  with  metabolically  active obesity (the mean triglyceride levels in the groups of metabolically active and metabolically healthy obesity were 1.31 vs 0.74 mmol/L, glucose levels, 4.92  vs 4.54  mmol/L,  C-reactive protein,  3.15  vs 2.30 mg/mL, systolic and diastolic blood pressure, 118.97 vs 110.23 mmHg and 72.90 vs 68.58 mmHg, respectively; p < 0.001, with the  exclusion of the   mean level of anti-atherogenic HDL-C, which was lower (1.27 vs 1.49 mmol/L; p < 0.001. Also, in addition to abdominal obesity, 21.43% of school children with metabolically active obesity had ≥ 2 atherogenic factors, as well as some pro-inflammatory abnormalities (C-reactive protein levels were

Primary Metabolic Pathways and Metabolic Flux Analysis

DEFF Research Database (Denmark)

Villadsen, John

2015-01-01

his chapter introduces the metabolic flux analysis (MFA) or stoichiometry-based MFA, and describes the quantitative basis for MFA. It discusses the catabolic pathways in which free energy is produced to drive the cell-building anabolic pathways. An overview of these primary pathways provides...... the reader who is primarily trained in the engineering sciences with atleast a preliminary introduction to biochemistry and also shows how carbon is drained off the catabolic pathways to provide precursors for cell mass building and sometimes for important industrial products. The primary pathways...... to be examined in the following are: glycolysis, primarily by the EMP pathway, but other glycolytic pathways is also mentioned; fermentative pathways in which the redox generated in the glycolytic reactions are consumed; reactions in the tricarboxylic acid (TCA) cycle, which produce biomass precursors and redox...

Metabolic flux profiling of recombinant protein secreting Pichia pastoris growing on glucose:methanol mixtures

Science.gov (United States)

2012-01-01

Background The methylotrophic yeast Pichia pastoris has emerged as one of the most promising yeast hosts for the production of heterologous proteins. Mixed feeds of methanol and a multicarbon source instead of methanol as sole carbon source have been shown to improve product productivities and alleviate metabolic burden derived from protein production. Nevertheless, systematic quantitative studies on the relationships between the central metabolism and recombinant protein production in P. pastoris are still rather limited, particularly when growing this yeast on mixed carbon sources, thus hampering future metabolic network engineering strategies for improved protein production. Results The metabolic flux distribution in the central metabolism of P. pastoris growing on a mixed feed of glucose and methanol was analyzed by Metabolic Flux Analysis (MFA) using 13C-NMR-derived constraints. For this purpose, we defined new flux ratios for methanol assimilation pathways in P. pastoris cells growing on glucose:methanol mixtures. By using this experimental approach, the metabolic burden caused by the overexpression and secretion of a Rhizopus oryzae lipase (Rol) in P. pastoris was further analyzed. This protein has been previously shown to trigger the unfolded protein response in P. pastoris. A series of 13C-tracer experiments were performed on aerobic chemostat cultivations with a control and two different Rol producing strains growing at a dilution rate of 0.09 h−1 using a glucose:methanol 80:20 (w/w) mix as carbon source. The MFA performed in this study reveals a significant redistristribution of carbon fluxes in the central carbon metabolism when comparing the two recombinant strains vs the control strain, reflected in increased glycolytic, TCA cycle and NADH regeneration fluxes, as well as higher methanol dissimilation rates. Conclusions Overall, a further 13C-based MFA development to characterise the central metabolism of methylotrophic yeasts when growing on mixed

Metabolic flux profiling of recombinant protein secreting Pichia pastoris growing on glucose:methanol mixtures

Directory of Open Access Journals (Sweden)

Jordà Joel

2012-05-01

Full Text Available Abstract Background The methylotrophic yeast Pichia pastoris has emerged as one of the most promising yeast hosts for the production of heterologous proteins. Mixed feeds of methanol and a multicarbon source instead of methanol as sole carbon source have been shown to improve product productivities and alleviate metabolic burden derived from protein production. Nevertheless, systematic quantitative studies on the relationships between the central metabolism and recombinant protein production in P. pastoris are still rather limited, particularly when growing this yeast on mixed carbon sources, thus hampering future metabolic network engineering strategies for improved protein production. Results The metabolic flux distribution in the central metabolism of P. pastoris growing on a mixed feed of glucose and methanol was analyzed by Metabolic Flux Analysis (MFA using 13C-NMR-derived constraints. For this purpose, we defined new flux ratios for methanol assimilation pathways in P. pastoris cells growing on glucose:methanol mixtures. By using this experimental approach, the metabolic burden caused by the overexpression and secretion of a Rhizopus oryzae lipase (Rol in P. pastoris was further analyzed. This protein has been previously shown to trigger the unfolded protein response in P. pastoris. A series of 13C-tracer experiments were performed on aerobic chemostat cultivations with a control and two different Rol producing strains growing at a dilution rate of 0.09 h−1 using a glucose:methanol 80:20 (w/w mix as carbon source. The MFA performed in this study reveals a significant redistristribution of carbon fluxes in the central carbon metabolism when comparing the two recombinant strains vs the control strain, reflected in increased glycolytic, TCA cycle and NADH regeneration fluxes, as well as higher methanol dissimilation rates. Conclusions Overall, a further 13C-based MFA development to characterise the central metabolism of methylotrophic

Metabolite-balancing techniques vs. 13C tracer experiments to determine metabolic fluxes in hybridoma cells.

Science.gov (United States)

Bonarius, H P; Timmerarends, B; de Gooijer, C D; Tramper, J

The estimation of intracellular fluxes of mammalian cells using only mass balances of the relevant metabolites is not possible because the set of linear equations defined by these mass balances is underdetermined. In order to quantify fluxes in cyclic pathways the mass balance equations can be complemented with several constraints: (1) the mass balances of co-metabolites, such as ATP or NAD(P)H, (2) linear objective functions, (3) flux data obtained by isotopic-tracer experiments. Here, these three methods are compared for the analysis of fluxes in the primary metabolism of continuously cultured hybridoma cells. The significance of different theoretical constraints and different objective functions is discussed after comparing their resulting flux distributions to the fluxes determined using 13CO2 and 13C-lactate measurements of 1 - 13C-glucose-fed hybridoma cells. Metabolic fluxes estimated using the objective functions "maximize ATP" and "maximize NADH" are relatively similar to the experimentally determined fluxes. This is consistent with the observation that cancer cells, such as hybridomas, are metabolically hyperactive, and produce ATP and NADH regardless of the need for these cofactors. Copyright 1998 John Wiley & Sons, Inc.

13C Metabolic Flux Analysis for systematic metabolic engineering of S. cerevisiae for overproduction of fatty acids.

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Amit Ghosh

2016-10-01

Full Text Available Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here we used flux-based modeling approaches to improve yields of fatty acids in S. cerevisiae. We combined 13C labeling data with comprehensive genome-scale models to shed light onto microbial metabolism and improve metabolic engineering efforts. We concentrated on studying the balance of acetyl-CoA, a precursor metabolite for the biosynthesis of fatty acids. A genome-wide acetyl-CoA balance study showed ATP citrate lyase from Y. lipolytica as a robust source of cytoplasmic acetyl-CoA and malate synthase as a desirable target for down-regulation in terms of acetyl-CoA consumption. These genetic modifications were applied to S. cerevisiae WRY2, a strain that is capable of producing 460 mg L of free fatty acids. With the addition of ATP citrate lyase and down-regulation of malate synthase the engineered strain produced 26 per cent more free fatty acids. Further increases in free fatty acid production of 33 per cent were obtained by knocking out the cytoplasmic glycerol-3-phosphate dehydrogenase, which flux analysis had shown was competing for carbon flux upstream with the carbon flux through the acetyl-CoA production pathway in the cytoplasm. In total, the genetic interventions applied in this work increased fatty acid production by 70 per cent.

Assessment of metabolic phenotypic variability in children’s urine using 1H NMR spectroscopy

Science.gov (United States)

Maitre, Léa; Lau, Chung-Ho E.; Vizcaino, Esther; Robinson, Oliver; Casas, Maribel; Siskos, Alexandros P.; Want, Elizabeth J.; Athersuch, Toby; Slama, Remy; Vrijheid, Martine; Keun, Hector C.; Coen, Muireann

2017-04-01

The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8-9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.

Regulation of flux through metabolic cycles

International Nuclear Information System (INIS)

Walsh, K.

1984-01-01

The branchpoint of the tricarboxylic acid and glyoxylate shunt was characterized in the intact organism by a multidimensional approach. Theory and methodology were developed to determine velocities for the net flow of carbon through the major steps of acetate metabolism in E. coli. Rates were assigned based on the 13 C-NMR spectrum of intracellular glutamate, measured rates of substrate incorporation into end products, the constituent composition of E. coli and a series of conservation equations which described the system at steady state. The in vivo fluxes through the branchpoint of the tricarboxylic acid and glyoxylate cycles were compared to rates calculated from the kinetic constants of the branchpoint enzymes and the intracellular concentrations of their substrates. These studies elucidated the role of isocitrate dehydrogenase phosphorylation in the Krebs cycle and led to the development of a generalized mathematical description of the sensitivity of branchpoints to regulatory control. This theoretical analysis was termed the branchpoint effect and it describes conditions which result in large changes in the flux through an enzyme even though that enzyme is not subject to direct regulatory control. The theoretical and experimental characterization of this system provided a framework to study the effects of enzyme overproduction and underproduction on metabolic processes in the cell. An in vivo method was developed to determine the extent to which an enzyme catalyzes a rate-controlling reaction. The enzyme chosen for this study was citrate synthase

Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain.

NARCIS (Netherlands)

Gavai, Anand K.; Supandi, Farahaniza; Hettling, Hannes; Murell, Paul; Leunissen, Jack A.M.; van Beek, Johannes H.G.M.

2015-01-01

Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the

Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain

NARCIS (Netherlands)

Gavai, A.K.; Supandi, F.; Hettling, H.; Murrell, P.; Leunissen, J.A.M.; Beek, van J.H.G.M.

2015-01-01

Predicting the distribution of metabolic fluxes in biochemical networks is of major interest in systems biology. Several databases provide metabolic reconstructions for different organisms. Software to analyze flux distributions exists, among others for the proprietary MATLAB environment. Given the

Differential Bees Flux Balance Analysis with OptKnock for in silico microbial strains optimization.

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Yee Wen Choon

Full Text Available Microbial strains optimization for the overproduction of desired phenotype has been a popular topic in recent years. The strains can be optimized through several techniques in the field of genetic engineering. Gene knockout is a genetic engineering technique that can engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, the complexities of the metabolic networks have made the process to identify the effects of genetic modification on the desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to the combinatorial problem in obtaining optimal gene deletion strategy. Basically, the size of a genome-scale metabolic model is usually large. As the size of the problem increases, the computation time increases exponentially. In this paper, we propose Differential Bees Flux Balance Analysis (DBFBA with OptKnock to identify optimal gene knockout strategies for maximizing the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by improving the performance of a hybrid of Bees Algorithm and Flux Balance Analysis (BAFBA by hybridizing Differential Evolution (DE algorithm into neighborhood searching strategy of BAFBA. In addition, DBFBA is integrated with OptKnock to validate the results for improving the reliability the work. Through several experiments conducted on Escherichia coli, Bacillus subtilis, and Clostridium thermocellum as the model organisms, DBFBA has shown a better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes compared to the methods used in previous works.

Metabolic phenotype in the mouse model of osteogenesis imperfecta.

Science.gov (United States)

Boraschi-Diaz, Iris; Tauer, Josephine T; El-Rifai, Omar; Guillemette, Delphine; Lefebvre, Geneviève; Rauch, Frank; Ferron, Mathieu; Komarova, Svetlana V

2017-09-01

Osteogenesis imperfecta (OI) is the most common heritable bone fragility disorder, usually caused by dominant mutations in genes coding for collagen type I alpha chains, COL1A1 or COL1A2 Osteocalcin (OCN) is now recognized as a bone-derived regulator of insulin secretion and sensitivity and glucose homeostasis. Since OI is associated with increased rates of bone formation and resorption, we hypothesized that the levels of undercarboxylated OCN are increased in OI. The objective of this study was to determine changes in OCN and to elucidate the metabolic phenotype in the Col1a1 Jrt/+ mouse, a model of dominant OI caused by a Col1a1 mutation. Circulating levels of undercarboxylated OCN were higher in 4-week-old OI mice and normal by 8 weeks of age. Young OI animals exhibited a sex-dependent metabolic phenotype, including increased insulin levels in males, improved glucose tolerance in females, lower levels of random glucose and low adiposity in both sexes. The rates of O 2 consumption and CO 2 production, as well as energy expenditure assessed using indirect calorimetry were significantly increased in OI animals of both sexes, whereas respiratory exchange ratio was significantly higher in OI males only. Although OI mice have significant physical impairment that may contribute to metabolic differences, we specifically accounted for movement and compared OI and WT animals during the periods of similar activity levels. Taken together, our data strongly suggest that OI animals have alterations in whole body energy metabolism that are consistent with the action of undercarboxylated osteocalcin. © 2017 Society for Endocrinology.

Targeting the latest hallmark of cancer: another attempt at 'magic bullet' drugs targeting cancers' metabolic phenotype.

Science.gov (United States)

Cuperlovic-Culf, M; Culf, A S; Touaibia, M; Lefort, N

2012-10-01

The metabolism of tumors is remarkably different from the metabolism of corresponding normal cells and tissues. Metabolic alterations are initiated by oncogenes and are required for malignant transformation, allowing cancer cells to resist some cell death signals while producing energy and fulfilling their biosynthetic needs with limiting resources. The distinct metabolic phenotype of cancers provides an interesting avenue for treatment, potentially with minimal side effects. As many cancers show similar metabolic characteristics, drugs targeting the cancer metabolic phenotype are, perhaps optimistically, expected to be 'magic bullet' treatments. Over the last few years there have been a number of potential drugs developed to specifically target cancer metabolism. Several of these drugs are currently in clinical and preclinical trials. This review outlines examples of drugs developed for different targets of significance to cancer metabolism, with a focus on small molecule leads, chemical biology and clinical results for these drugs.

Changes in muscle cell metabolism and mechanotransduction are associated with myopathic phenotype in a mouse model of collagen VI deficiency.

Directory of Open Access Journals (Sweden)

Sara De Palma

Full Text Available This study identifies metabolic and protein phenotypic alterations in gastrocnemius, tibialis anterior and diaphragm muscles of Col6a1(-/- mice, a model of human collagen VI myopathies. All three muscles of Col6a1(-/- mice show some common changes in proteins involved in metabolism, resulting in decreased glycolysis and in changes of the TCA cycle fluxes. These changes lead to a different fate of α-ketoglutarate, with production of anabolic substrates in gastrocnemius and tibialis anterior, and with lipotoxicity in diaphragm. The metabolic changes are associated with changes of proteins involved in mechanotransduction at the myotendineous junction/costameric/sarcomeric level (TN-C, FAK, ROCK1, troponin I fast and in energy metabolism (aldolase, enolase 3, triose phosphate isomerase, creatine kinase, adenylate kinase 1, parvalbumin, IDH1 and FASN. Together, these change may explain Ca(2+ deregulation, impaired force development, increased muscle-relaxation-time and fiber damage found in the mouse model as well as in patients. The severity of these changes differs in the three muscles (gastrocnemius

The prevalence of metabolic disorders in various phenotypes of polycystic ovary syndrome: a community based study in Southwest of Iran.

Science.gov (United States)

Tehrani, Fahimeh Ramezani; Rashidi, Homeira; Khomami, Mahnaz Bahri; Tohidi, Maryam; Azizi, Fereidoun

2014-09-16

Polycystic ovary syndrome (PCOS) is a common endocrinopathy, associated with metabolic abnormalities. Metabolic features of various phenotypes of this syndrome are still debatable. The aim of present study hence was to evaluate the metabolic and hormonal features of PCOS phenotypes in comparison to a group of healthy control. A total of 646 reproductive-aged women were randomly selected using the stratified, multistage probability cluster sampling method. The subjects were divided into five phenotypes: A (oligo/anovulation + hyperandrogenism + polycystic ovaries), B (oligo/anovulation + hyperandrogenism), C (hyperandrogenism + polycystic ovaries) and D (oligo/anovulation + polycystic ovaries). Hormonal and metabolic profiles and the prevalence of metabolic syndrome among these groups were compared using ANCOVA adjusted for age and body mass index. Among women with PCOS (n = 85), those of groups A and C had higher serum levels of insulin and homeostatic model assessment for insulin resistance (HOMA-IR), compared to PCOS women of group D. Serum concentrations of cholesterol, low density lipoprotein, triglycerides and glucose in group A were higher than in other phenotypes, whereas the metabolic syndrome was more prevalent among group B. Women who had all three components of the syndrome showed the highest level of metabolic disturbances indicating that metabolic screening of the severest phenotype of PCOS may be necessary.

A Novel Methodology to Estimate Metabolic Flux Distributions in Constraint-Based Models

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Francesco Alessandro Massucci

2013-09-01

Full Text Available Quite generally, constraint-based metabolic flux analysis describes the space of viable flux configurations for a metabolic network as a high-dimensional polytope defined by the linear constraints that enforce the balancing of production and consumption fluxes for each chemical species in the system. In some cases, the complexity of the solution space can be reduced by performing an additional optimization, while in other cases, knowing the range of variability of fluxes over the polytope provides a sufficient characterization of the allowed configurations. There are cases, however, in which the thorough information encoded in the individual distributions of viable fluxes over the polytope is required. Obtaining such distributions is known to be a highly challenging computational task when the dimensionality of the polytope is sufficiently large, and the problem of developing cost-effective ad hoc algorithms has recently seen a major surge of interest. Here, we propose a method that allows us to perform the required computation heuristically in a time scaling linearly with the number of reactions in the network, overcoming some limitations of similar techniques employed in recent years. As a case study, we apply it to the analysis of the human red blood cell metabolic network, whose solution space can be sampled by different exact techniques, like Hit-and-Run Monte Carlo (scaling roughly like the third power of the system size. Remarkably accurate estimates for the true distributions of viable reaction fluxes are obtained, suggesting that, although further improvements are desirable, our method enhances our ability to analyze the space of allowed configurations for large biochemical reaction networks.

Anthropometric, clinical, and metabolic comparisons of the four Rotterdam PCOS phenotypes: A prospective study of PCOS women.

Science.gov (United States)

Kar, Sujata

2013-07-01

1. To study the distribution of various Rotterdam classified phenotypes of polycystic ovarian syndrome (PCOS) women, in our population. 2. To compare the four phenotypes with respect to anthropometric, clinical, and metabolic parameters. 3. To report the prevalence of insulin resistance (IR) and metabolic syndrome in these women. Private practice, Prospective cross-sectional comparative study. Women attending gynecology outpatient with the primary complains of irregular menses and/or infertility were evaluated. Each of them underwent detailed clinical examination, transvaginal sonography, and biochemical and hormonal assays. Four hundred and ten women with a clinical diagnosis of PCOS based on Rotterdam criteria were included in the study. The four phenotypes were 1) PCO complete, that is oligo/anovulation (O) + polycystic ovaries (P) + hyperandrogenism (H) 2) P + O, 3) P + H, and 4) O + H. All women were also evaluated for metabolic syndrome (American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI), modified Adult Treatment Panel (ATP) III 2005 guidelines) and IR (homeostatic model assessment-IR (HOMA-IR)). Statistical Package for Social Sciences (SPSS) version 18. Largest group was PCOS complete (65.6%) followed by P + O (22.2%); H + O (11.2%); and P + H (0.9%). Overall prevalence of metabolic syndrome was 35.07%. Hyperandrogenic phenotyptes; H + O (50%) and P + H + O (37.04%), had significantly higher prevalence of metabolic syndrome than normoandrogenic P + O phenotype (10%) (P ≤ 0.001). Body mass index (BMI) ≥ 25 (P = 0.0004; odds ratio (OR) = 3.07 (1.6574-5.7108, 95% CI)), waist circumference (WC) ≥ 80 cm (P = 0.001; OR = 3.68 (1.6807-8.0737, 95% CI)) and family history of diabetes (P = 0.019; OR 1.82 (1.1008-3.0194, 95% CI)), were strongly associated with the presence of metabolic syndrome. The overall prevalence of IR in PCOS women was 30.44% (HOMA-IR cutoff ≥ 3.8) and 34.94% (HOMA-IR cutoff ≥ 3.5). The prevalence of

FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses.

Science.gov (United States)

Desai, Trunil S; Srivastava, Shireesh

2018-01-01

13 C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13 C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13 C-MFA software that works in various operating systems will enable more researchers to perform 13 C-MFA and to further modify and develop the package.

Invariability of Central Metabolic Flux Distribution in Shewanella oneidensis MR-1 Under Environmental or Genetic Perturbations

Energy Technology Data Exchange (ETDEWEB)

Tang, Yinjie; Martin, Hector Garcia; Deutschbauer, Adam; Feng, Xueyang; Huang, Rick; Llora, Xavier; Arkin, Adam; Keasling, Jay D.

2009-04-21

An environmentally important bacterium with versatile respiration, Shewanella oneidensis MR-1, displayed significantly different growth rates under three culture conditions: minimal medium (doubling time {approx} 3 hrs), salt stressed minimal medium (doubling time {approx} 6 hrs), and minimal medium with amino acid supplementation (doubling time {approx}1.5 hrs). {sup 13}C-based metabolic flux analysis indicated that fluxes of central metabolic reactions remained relatively constant under the three growth conditions, which is in stark contrast to the reported significant changes in the transcript and metabolite profiles under various growth conditions. Furthermore, ten transposon mutants of S. oneidensis MR-1 were randomly chosen from a transposon library and their flux distributions through central metabolic pathways were revealed to be identical, even though such mutational processes altered the secondary metabolism, for example, glycine and C1 (5,10-Me-THF) metabolism.

Metabolic flux ratio analysis and cell staining suggest the existence of C4 photosynthesis in Phaeodactylum tricornutum.

Science.gov (United States)

Huang, A; Liu, L; Zhao, P; Yang, C; Wang, G C

2016-03-01

Mechanisms for carbon fixation via photosynthesis in the diatom Phaeodactylum tricornutum Bohlin were studied recently but there remains a long-standing debate concerning the occurrence of C4 photosynthesis in this species. A thorough investigation of carbon metabolism and the evidence for C4 photosynthesis based on organelle partitioning was needed. In this study, we identified the flux ratios between C3 and C4 compounds in P. tricornutum using (13)C-labelling metabolic flux ratio analysis, and stained cells with various cell-permeant fluorescent probes to investigate the likely organelle partitioning required for single-cell C4 photosynthesis. Metabolic flux ratio analysis indicated the C3/C4 exchange ratios were high. Cell staining indicated organelle partitioning required for single-cell C4 photosynthesis might exist in P. tricornutum. The results of (13)C-labelling metabolic flux ratio analysis and cell staining suggest single-cell C4 photosynthesis exists in P. tricornutum. This study provides insights into photosynthesis patterns of P. tricornutum and the evidence for C4 photosynthesis based on (13)C-labelling metabolic flux ratio analysis and organelle partitioning. © 2015 The Society for Applied Microbiology.

Development of Computational Tools for Metabolic Model Curation, Flux Elucidation and Strain Design

Energy Technology Data Exchange (ETDEWEB)

Maranas, Costas D

2012-05-21

An overarching goal of the Department of Energy mission is the efficient deployment and engineering of microbial and plant systems to enable biomass conversion in pursuit of high energy density liquid biofuels. This has spurred the pace at which new organisms are sequenced and annotated. This torrent of genomic information has opened the door to understanding metabolism in not just skeletal pathways and a handful of microorganisms but for truly genome-scale reconstructions derived for hundreds of microbes and plants. Understanding and redirecting metabolism is crucial because metabolic fluxes are unique descriptors of cellular physiology that directly assess the current cellular state and quantify the effect of genetic engineering interventions. At the same time, however, trying to keep pace with the rate of genomic data generation has ushered in a number of modeling and computational challenges related to (i) the automated assembly, testing and correction of genome-scale metabolic models, (ii) metabolic flux elucidation using labeled isotopes, and (iii) comprehensive identification of engineering interventions leading to the desired metabolism redirection.

The association between metabolic health, obesity phenotype and the risk of breast cancer.

Science.gov (United States)

Park, Yong-Moon Mark; White, Alexandra J; Nichols, Hazel B; O'Brien, Katie M; Weinberg, Clarice R; Sandler, Dale P

2017-06-15

Beyond the current emphasis on body mass index (BMI), it is unknown whether breast cancer risk differs between metabolically healthy and unhealthy normal weight or overweight/obese women. The Sister Study is a nationwide prospective cohort study. Data came from 50,884 cohort participants aged 35 to 74 years enrolled from 2003 through 2009. Cox proportional hazards models were used to estimate multivariable adjusted hazard ratios (HR) and 95% confidence intervals (CIs) for breast cancer risk. Metabolic abnormalities considered included: high waist circumference (≥88 cm); elevated blood pressure (≥130/85 mm Hg or antihypertensive medication); previously diagnosed diabetes or antidiabetic drug treatment; and cholesterol-lowering medication use. During follow-up (mean, 6.4 years), 1,388 invasive breast cancers were diagnosed at least 1 year after enrollment. Compared to women with BMI women with a BMI women with a BMI ≥25 kg/m 2 and no metabolic abnormalities (metabolically healthy overweight/obese phenotype) (HR = 1.24, 95% CI: 0.99-1.55). Furthermore, risk of postmenopausal breast cancer was consistently elevated in women with normal BMI and central obesity (normal weight central obesity phenotype) regardless of the criterion used to define central obesity, with HR for waist circumference ≥88 cm, waist circumference ≥80 cm, and waist-hip ratio ≥0.85 of 1.58, 95% CI: 1.02-2.46; 1.38, 95% CI: 1.09-1.75; and 1.38, 95% CI: 1.02-1.85, respectively. There was an inverse association between premenopausal breast cancer and metabolically healthy overweight/obese phenotype (HR = 0.71, 95% CI: 0.52-0.97). Our findings suggest that postmenopausal women who are metabolically unhealthy or have central adiposity may be at increased risk for breast cancer despite normal BMI. © 2017 UICC.

Metabolic Phenotype Characterization of Botrytis cinerea, the Causal Agent of Gray Mold

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Han-Cheng Wang

2018-03-01

Full Text Available Botrytis cinerea, which causes gray mold, is an important pathogen in four important economic crops, tomato, tobacco, cucumber and strawberry, in China and worldwide. Metabolic phenomics data on B. cinerea isolates from these four crops were characterized and compared for 950 phenotypes with a BIOLOG Phenotype MicroArray (PM. The results showed that the metabolic fingerprints of the four B. cinerea isolates were similar to each other with minimal differences. B. cinerea isolates all metabolized more than 17% of the tested carbon sources, 63% of the amino acid nitrogen substrates, 80% of the peptide nitrogen substrates, 93% of the phosphorus substrates, and 97% of the sulfur substrates. Carbon substrates of organic acids and carbohydrates, and nitrogen substrates of amino acids and peptides were the significant utilization patterns for B. cinerea. Each B. cinerea isolate contained 94 biosynthetic pathways. These isolates showed a large range of adaptabilities and were still able to metabolize substrates in the presence of the osmolytes, including up to 6% potassium chloride, 10% sodium chloride, 5% sodium sulfate, 6% sodium formate, 20% ethylene glycol, and 3% urea. These isolates all showed active metabolism in environments with pH values from 3.5 to 8.5 and exhibited decarboxylase activities. These characterizations provide a theoretical basis for the study of B. cinerea in biochemistry and metabolic phenomics and provide valuable clues to finding potential new ways to manage gray mold.

Assessing glycolytic flux alterations resulting from genetic perturbations in E. coli using a biosensor

DEFF Research Database (Denmark)

Lehning, Christina Eva; Siedler, Solvej; Ellabaan, Mostafa M Hashim

2017-01-01

validated the glycolytic flux dependency of the biosensor in a range of different carbon sources in six different E. coli strains and during mevalonate production. Furthermore, we studied the flux-altering effects of genome-wide single gene knock-outs in E. coli in a multiplex FlowSeq experiment. From...... a library consisting of 2126 knock-out mutants, we identified 3 mutants with high-flux and 95 mutants with low-flux phenotypes that did not have severe growth defects. This approach can improve our understanding of glycolytic flux regulation improving metabolic models and engineering efforts....

A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient

Directory of Open Access Journals (Sweden)

Picó Jesús

2007-10-01

Full Text Available Abstract Background An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry. Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i sometimes it cannot be used because there is a lack of measurable fluxes, and ii the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties. Results We propose a procedure to estimate the evolution of the metabolic fluxes that is structured as follows: 1 measure the concentrations of extracellular species and biomass, 2 convert this data to measured fluxes and 3 estimate the non-measured fluxes using the Flux Spectrum Approach, a variant of Metabolic Flux Analysis that overcomes the difficulties mentioned above without assuming optimal behaviour. We apply the procedure to a real problem taken from the literature: estimate the metabolic fluxes during a cultivation of CHO cells in batch mode. We show that it provides a reliable and rich estimation of the non-measured fluxes, thanks to considering measurements uncertainty and reversibility constraints. We also demonstrate that this procedure can estimate the non-measured fluxes even when there is a lack of measurable species. In addition, it offers a new method to deal with inconsistency. Conclusion This work introduces a procedure to estimate time-varying metabolic fluxes that copes with the insufficiency of

Secular change in 13 metabolic phenotypes: A Chinese longitudinal twin study

DEFF Research Database (Denmark)

Li, Shuxia; Pang, Zengchang; Zhang, Dongfeng

in prospective investigations. Based on Chinese twin data collected from Danish-Chinese collaboration research, we perform twin modeling on 13 metabolic phenotypes (total cholesterol; triglyceride; high density lipoprotein (HDL); low density lipoprotein (LDL); urine acid (UA); glucose; weight; body mass index...... fitted to the secular changes in each of the 13 phenotypes with best fitting model selected based on model performance. Age and sex were included as covariates in the models to adjust for their effects on secular trend. Results: Variations in secular change in 3 lipids (total cholesterol; triglyceride...

Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

International Nuclear Information System (INIS)

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R.; Jijakli, Kenan; Salehi-Ashtiani, Kourosh

2014-01-01

Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

Microalgal Metabolic Network Model Refinement through High-Throughput Functional Metabolic Profiling

Energy Technology Data Exchange (ETDEWEB)

Chaiboonchoe, Amphun; Dohai, Bushra Saeed; Cai, Hong; Nelson, David R. [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Jijakli, Kenan [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates); Engineering Division, Biofinery, Manhattan, KS (United States); Salehi-Ashtiani, Kourosh, E-mail: ksa3@nyu.edu [Division of Science and Math, New York University Abu Dhabi, Abu Dhabi (United Arab Emirates); Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi Institute, Abu Dhabi (United Arab Emirates)

2014-12-10

Metabolic modeling provides the means to define metabolic processes at a systems level; however, genome-scale metabolic models often remain incomplete in their description of metabolic networks and may include reactions that are experimentally unverified. This shortcoming is exacerbated in reconstructed models of newly isolated algal species, as there may be little to no biochemical evidence available for the metabolism of such isolates. The phenotype microarray (PM) technology (Biolog, Hayward, CA, USA) provides an efficient, high-throughput method to functionally define cellular metabolic activities in response to a large array of entry metabolites. The platform can experimentally verify many of the unverified reactions in a network model as well as identify missing or new reactions in the reconstructed metabolic model. The PM technology has been used for metabolic phenotyping of non-photosynthetic bacteria and fungi, but it has not been reported for the phenotyping of microalgae. Here, we introduce the use of PM assays in a systematic way to the study of microalgae, applying it specifically to the green microalgal model species Chlamydomonas reinhardtii. The results obtained in this study validate a number of existing annotated metabolic reactions and identify a number of novel and unexpected metabolites. The obtained information was used to expand and refine the existing COBRA-based C. reinhardtii metabolic network model iRC1080. Over 254 reactions were added to the network, and the effects of these additions on flux distribution within the network are described. The novel reactions include the support of metabolism by a number of d-amino acids, l-dipeptides, and l-tripeptides as nitrogen sources, as well as support of cellular respiration by cysteamine-S-phosphate as a phosphorus source. The protocol developed here can be used as a foundation to functionally profile other microalgae such as known microalgae mutants and novel isolates.

Isotopically nonstationary metabolic flux analysis (INST-MFA) of photosynthesis and photorespiration in plants

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Photorespiration is a central component of photosynthesis; however to better understand its role it should be viewed in the context of an integrated metabolic network rather than a series of individual reactions that operate independently. Isotopically nonstationary 13C metabolic flux analysis (INST...

Anthropometric, clinical, and metabolic comparisons of the four Rotterdam PCOS phenotypes: A prospective study of PCOS women

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Sujata Kar

2013-01-01

Full Text Available Aims: 1. To study the distribution of various Rotterdam classified phenotypes of polycystic ovarian syndrome (PCOS women, in our population. 2. To compare the four phenotypes with respect to anthropometric, clinical, and metabolic parameters. 3. To report the prevalence of insulin resistance (IR and metabolic syndrome in these women. Settings and Design: Private practice, Prospective cross-sectional comparative study. Materials and Methods: Women attending gynecology outpatient with the primary complains of irregular menses and/or infertility were evaluated. Each of them underwent detailed clinical examination, transvaginal sonography, and biochemical and hormonal assays. Four hundred and ten women with a clinical diagnosis of PCOS based on Rotterdam criteria were included in the study. The four phenotypes were 1 PCO complete, that is oligo/anovulation (O + polycystic ovaries (P + hyperandrogenism (H 2 P + O, 3 P + H, and 4 O + H. All women were also evaluated for metabolic syndrome (American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI, modified Adult Treatment Panel (ATP III 2005 guidelines and IR (homeostatic model assessment-IR (HOMA-IR. Statistical Analysis: Statistical Package for Social Sciences (SPSS version 18. Results: Largest group was PCOS complete (65.6% followed by P + O (22.2%; H + O (11.2%; and P + H (0.9%. Overall prevalence of metabolic syndrome was 35.07%. Hyperandrogenic phenotyptes; H + O (50% and P + H + O (37.04%, had significantly higher prevalence of metabolic syndrome than normoandrogenic P + O phenotype (10% (P ≤ 0.001. Body mass index (BMI ≥ 25 (P = 0.0004; odds ratio (OR = 3.07 (1.6574-5.7108, 95% CI, waist circumference (WC ≥ 80 cm (P = 0.001; OR = 3.68 (1.6807-8.0737, 95% CI and family history of diabetes (P = 0.019; OR 1.82 (1.1008-3.0194, 95% CI, were strongly associated with the presence of metabolic syndrome. The overall prevalence of IR in PCOS women was 30.44% (HOMA-IR cutoff �

Differential association between sarcopenia and metabolic phenotype in Korean young and older adults with and without obesity.

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Hwang, You-Cheol; Cho, In-Jin; Jeong, In-Kyung; Ahn, Kyu Jeung; Chung, Ho Yeon

2017-01-01

To determine whether sarcopenia was associated with metabolic phenotype in subjects with and without obesity. A total of 6,021 participants (2,592 men, 3,429 women) aged 30 to 93 years were assessed using data from the 2009 Korea National Health and Nutrition Examination Survey. Sarcopenia was defined as appendicular skeletal muscle mass divided by weight (%) that is young adults. Metabolically unhealthy was defined as ≥2 components of metabolic syndrome or the presence of hypertension, diabetes, or cardiovascular disease. Obesity was defined as body mass index ≥25.0 kg/m 2 . Sarcopenia was associated with a metabolically unhealthy phenotype in nonobese men independent of age, smoking, regular physical activity, daily energy intake, total body fat, fasting insulin, non-HDL cholesterol, white blood cell count, ferritin level, and 25(OH) vitamin D level (OR per 1 SD increment (95% CI) 1.88 (1.28-2.75), P obesity. Sarcopenia was independently associated with a metabolically unhealthy phenotype in nonobese men, but this association was not evident in nonobese women or subjects with obesity. © 2016 The Obesity Society.

Detection of Metabolic Fluxes of O and H Atoms into Intracellular Water in Mammalian Cells

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Kreuzer, Helen W.; Quaroni, Luca; Podlesak, David W.; Zlateva, Theodora; Bollinger, Nikki; McAllister, Aaron; Lott, Michael J.; Hegg, Eric L.

2012-01-01

Metabolic processes result in the release and exchange of H and O atoms from organic material as well as some inorganic salts and gases. These fluxes of H and O atoms into intracellular water result in an isotopic gradient that can be measured experimentally. Using isotope ratio mass spectroscopy, we revealed that slightly over 50% of the H and O atoms in the intracellular water of exponentially-growing cultured Rat-1 fibroblasts were isotopically distinct from growth medium water. We then employed infrared spectromicroscopy to detect in real time the flux of H atoms in these same cells. Importantly, both of these techniques indicate that the H and O fluxes are dependent on metabolic processes; cells that are in lag phase or are quiescent exhibit a much smaller flux. In addition, water extracted from the muscle tissue of rats contained a population of H and O atoms that were isotopically distinct from body water, consistent with the results obtained using the cultured Rat-1 fibroblasts. Together these data demonstrate that metabolic processes produce fluxes of H and O atoms into intracellular water, and that these fluxes can be detected and measured in both cultured mammalian cells and in mammalian tissue. PMID:22848359

Changes in Muscle Metabolism are Associated with Phenotypic Variability in Golden Retriever Muscular Dystrophy




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Nghiem, Peter P.; Bello, Luca; Stoughton, William B.; López, Sara Mata; Vidal, Alexander H.; Hernandez, Briana V.; Hulbert, Katherine N.; Gourley, Taylor R.; Bettis, Amanda K.; Balog-Alvarez, Cynthia J.; Heath-Barnett, Heather; Kornegay, Joe N.

2017-01-01

Duchenne muscular dystrophy (DMD) is an X-chromosome-linked disorder and the most common monogenic disease in people. Affected boys are diagnosed at a young age, become non-ambulatory by their early teens, and succumb to cardiorespiratory failure by their thirties. Despite being a monogenic condition resulting from mutations in the DMD gene, affected boys have noteworthy phenotypic variability. Efforts have identified genetic modifiers that could modify disease progression and be pharmacologic targets. Dogs affected with golden retriever muscular dystrophy (GRMD) have absent dystrophin and demonstrate phenotypic variability at the functional, histopathological, and molecular level. Our laboratory is particularly interested in muscle metabolism changes in dystrophin-deficient muscle. We identified several metabolic alterations, including myofiber type switching from fast (type II) to slow (type I), reduced glycolytic enzyme expression, reduced and morphologically abnormal mitochondria, and differential AMP-kinase phosphorylation (activation) between hypertrophied and wasted muscle. We hypothesize that muscle metabolism changes are, in part, responsible for phenotypic variability in GRMD. Pharmacological therapies aimed at modulating muscle metabolism can be tested in GRMD dogs for efficacy. PMID:28955176

Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non-stationary 13 C metabolic flux analysis.

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Hendry, John I; Prasannan, Charulata; Ma, Fangfang; Möllers, K Benedikt; Jaiswal, Damini; Digmurti, Madhuri; Allen, Doug K; Frigaard, Niels-Ulrik; Dasgupta, Santanu; Wangikar, Pramod P

2017-10-01

Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non-stationary 13 C metabolic flux analysis (INST- 13 C-MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA-I glgA-II) of the model cyanobacterium Synechococcus sp. PCC 7002. During balanced photoautotrophic growth, 10-20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose-1-phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re-routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298-2308. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Impaired TCA cycle flux in mitochondria in skeletal muscle from type 2 diabetic subjects: marker or maker of the diabetic phenotype?

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Gaster, Michael; Nehlin, Jan O; Minet, Ariane D

2012-07-01

The diabetic phenotype is complex, requiring elucidation of key initiating defects. Recent research has shown that diabetic myotubes express a primary reduced tricarboxylic acid (TCA) cycle flux. A reduced TCA cycle flux has also been shown both in insulin resistant offspring of T2D patients and exercising T2D patients in vivo. This review will discuss the latest advances in the understanding of the molecular mechanisms regulating the TCA cycle with focus on possible underlying mechanism which could explain the impaired TCA flux in insulin resistant human skeletal muscle in type 2 diabetes. A reduced TCA is both a marker and a maker of the diabetic phenotype.

Heterosis Is a Systemic Property Emerging From Non-linear Genotype-Phenotype Relationships: Evidence From in Vitro Genetics and Computer Simulations

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Julie B. Fiévet

2018-05-01

Full Text Available Heterosis, the superiority of hybrids over their parents for quantitative traits, represents a crucial issue in plant and animal breeding as well as evolutionary biology. Heterosis has given rise to countless genetic, genomic and molecular studies, but has rarely been investigated from the point of view of systems biology. We hypothesized that heterosis is an emergent property of living systems resulting from frequent concave relationships between genotypic variables and phenotypes, or between different phenotypic levels. We chose the enzyme-flux relationship as a model of the concave genotype-phenotype (GP relationship, and showed that heterosis can be easily created in the laboratory. First, we reconstituted in vitro the upper part of glycolysis. We simulated genetic variability of enzyme activity by varying enzyme concentrations in test tubes. Mixing the content of “parental” tubes resulted in “hybrids,” whose fluxes were compared to the parental fluxes. Frequent heterotic fluxes were observed, under conditions that were determined analytically and confirmed by computer simulation. Second, to test this model in a more realistic situation, we modeled the glycolysis/fermentation network in yeast by considering one input flux, glucose, and two output fluxes, glycerol and acetaldehyde. We simulated genetic variability by randomly drawing parental enzyme concentrations under various conditions, and computed the parental and hybrid fluxes using a system of differential equations. Again we found that a majority of hybrids exhibited positive heterosis for metabolic fluxes. Cases of negative heterosis were due to local convexity between certain enzyme concentrations and fluxes. In both approaches, heterosis was maximized when the parents were phenotypically close and when the distributions of parental enzyme concentrations were contrasted and constrained. These conclusions are not restricted to metabolic systems: they only depend on the

Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

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Sadhukhan, Priyanka P; Raghunathan, Anu

2014-01-01

Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris

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Joel Jordà

2014-05-01

Full Text Available Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol on P. pastoris central carbon metabolism. Higher oxygen uptake and CO2 production rates and slightly reduced biomass yield suggest an increased energy demand for the producing strain. This observation is further confirmed by 13C-based metabolic flux analysis. In particular, the flux through the methanol oxidation pathway and the TCA cycle was increased in the Rol-producing strain compared to the reference strain. Next to changes in the flux distribution, significant variations in intracellular metabolite concentrations were observed. Most notably, the pools of trehalose, which is related to cellular stress response, and xylose, which is linked to methanol assimilation, were significantly increased in the recombinant strain.

Longitudinal Investigation into Genetics in the Conservation of Metabolic Phenotypes in Danish and Chinese Twins

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Li, Shuxia; Kyvik, Kirsten Ohm; Duan, Haiping

2016-01-01

twin study on long-term stability of metabolic phenotypes in Danish and Chinese twins identified a common pattern of high genetic control over phenotype conservation, and at the same time revealed population-specific patterns of genetic and common environmental regulation on the variance as well...

Multi-objective experimental design for (13)C-based metabolic flux analysis.

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Bouvin, Jeroen; Cajot, Simon; D'Huys, Pieter-Jan; Ampofo-Asiama, Jerry; Anné, Jozef; Van Impe, Jan; Geeraerd, Annemie; Bernaerts, Kristel

2015-10-01

(13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi

Metabolic fluxes in the central carbon metabolism of Dinoroseobacter shibae and Phaeobacter gallaeciensis, two members of the marine Roseobacter clade

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Rabus Ralf

2009-09-01

Full Text Available Abstract Background In the present work the central carbon metabolism of Dinoroseobacter shibae and Phaeobacter gallaeciensis was studied at the level of metabolic fluxes. These two strains belong to the marine Roseobacter clade, a dominant bacterial group in various marine habitats, and represent surface-associated, biofilm-forming growth (P. gallaeciensis and symbiotic growth with eukaryotic algae (D. shibae. Based on information from recently sequenced genomes, a rich repertoire of pathways has been identified in the carbon core metabolism of these organisms, but little is known about the actual contribution of the various reactions in vivo. Results Using 13C labelling techniques in specifically designed experiments, it could be shown that glucose-grown cells of D. shibae catabolise the carbon source exclusively via the Entner-Doudoroff pathway, whereas alternative routes of glycolysis and the pentose phosphate pathway are obviously utilised for anabolic purposes only. Enzyme assays confirmed this flux pattern and link the lack of glycolytic flux to the absence of phosphofructokinase activity. The previously suggested formation of phosphoenolpyruvate from pyruvate during mixotrophic CO2 assimilation was found to be inactive under the conditions studied. Moreover, it could be shown that pyruvate carboxylase is involved in CO2 assimilation and that the cyclic respiratory mode of the TCA cycle is utilised. Interestingly, the use of intracellular pathways was highly similar for P. gallaeciensis. Conclusion The present study reveals the first insight into pathway utilisation within the Roseobacter group. Fluxes through major intracellular pathways of the central carbon metabolism, which are closely linked to the various important traits found for the Roseobacter clade, could be determined. The close similarity of fluxes between the two physiologically rather different species might provide the first indication of more general key properties among

Flux-Enabled Exploration of the Role of Sip1 in galactose yeast metabolism

DEFF Research Database (Denmark)

Shymansky, Christopher M.; Wang, George; Baidoo, Edward E. K.

2017-01-01

13C metabolic flux analysis (13C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon kn...

Modeling Lactococcus lactis using a genome-scale flux model

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Nielsen Jens

2005-06-01

Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions1

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Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten

2016-01-01

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244

Metabolic flux rearrangement in the amino acid metabolism reduces ammonia stress in the α1-antitrypsin producing human AGE1.HN cell line.

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Priesnitz, Christian; Niklas, Jens; Rose, Thomas; Sandig, Volker; Heinzle, Elmar

2012-03-01

This study focused on metabolic changes in the neuronal human cell line AGE1.HN upon increased ammonia stress. Batch cultivations of α(1)-antitrypsin (A1AT) producing AGE1.HN cells were carried out in media with initial ammonia concentrations ranging from 0mM to 5mM. Growth, A1AT production, metabolite dynamics and finally metabolic fluxes calculated by metabolite balancing were compared. Growth and A1AT production decreased with increasing ammonia concentration. The maximum A1AT concentration decreased from 0.63g/l to 0.51g/l. Central energy metabolism remained relatively unaffected exhibiting only slightly increased glycolytic flux at high initial ammonia concentration in the medium. However, the amino acid metabolism was significantly changed. Fluxes through transaminases involved in amino acid degradation were reduced concurrently with a reduced uptake of amino acids. On the other hand fluxes through transaminases working in the direction of amino acid synthesis, i.e., alanine and phosphoserine, were increased leading to increased storage of excess nitrogen in extracellular alanine and serine. Glutamate dehydrogenase flux was reversed increasingly fixing free ammonia with increasing ammonia concentration. Urea production additionally observed was associated with arginine uptake by the cells and did not increase at high ammonia stress. It was therefore not used as nitrogen sink to remove excess ammonia. The results indicate that the AGE1.HN cell line can adapt to ammonia concentrations usually present during the cultivation process to a large extent by changing metabolism but with slightly reduced A1AT production and growth. Copyright © 2012 Elsevier Inc. All rights reserved.

Integrating tracer-based metabolomics data and metabolic fluxes in a linear fashion via Elementary Carbon Modes.

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Pey, Jon; Rubio, Angel; Theodoropoulos, Constantinos; Cascante, Marta; Planes, Francisco J

2012-07-01

Constraints-based modeling is an emergent area in Systems Biology that includes an increasing set of methods for the analysis of metabolic networks. In order to refine its predictions, the development of novel methods integrating high-throughput experimental data is currently a key challenge in the field. In this paper, we present a novel set of constraints that integrate tracer-based metabolomics data from Isotope Labeling Experiments and metabolic fluxes in a linear fashion. These constraints are based on Elementary Carbon Modes (ECMs), a recently developed concept that generalizes Elementary Flux Modes at the carbon level. To illustrate the effect of our ECMs-based constraints, a Flux Variability Analysis approach was applied to a previously published metabolic network involving the main pathways in the metabolism of glucose. The addition of our ECMs-based constraints substantially reduced the under-determination resulting from a standard application of Flux Variability Analysis, which shows a clear progress over the state of the art. In addition, our approach is adjusted to deal with combinatorial explosion of ECMs in genome-scale metabolic networks. This extension was applied to infer the maximum biosynthetic capacity of non-essential amino acids in human metabolism. Finally, as linearity is the hallmark of our approach, its importance is discussed at a methodological, computational and theoretical level and illustrated with a practical application in the field of Isotope Labeling Experiments. Copyright © 2012 Elsevier Inc. All rights reserved.

The Composition and Metabolic Phenotype of Neisseria gonorrhoeae Biofilms

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Michael A Apicella

2011-04-01

Full Text Available N. gonorrhoeae has been shown to form biofilms during cervical infection. Thus, biofilm formation may play an important role in the infection of women. The ability of N. gonorrhoeae to form membrane blebs is crucial to biofilm formation. Blebs contain DNA and outer membrane structures, which have been shown to be major constituents of the biofilm matrix. The organism expresses a DNA thermonuclease that is involved in remodeling of the biofilm matrix. Comparison of the transcriptional profiles of gonococcal biofilms and planktonic runoff indicate that genes involved in anaerobic metabolism and oxidative stress tolerance are more highly expressed in biofilm. The expression of aniA, ccp, and norB, which encode nitrite reductase, cytochrome c peroxidase, and nitric oxide reductase respectively, is required for mature biofilm formation over glass and human cervical cells. In addition, anaerobic respiration occurs in the substratum of gonococcal biofilms and disruption of the norB gene required for anaerobic respiration, results in a severe biofilm attenuation phenotype. It has been demonstrated that accumulation of nitric oxide (NO contributes to the phenotype of a norB mutant and can retard biofilm formation. However, NO can also enhance biofilm formation, and this is largely dependent on the concentration and donation rate or steady state kinetics of NO. The majority of the genes involved in gonococcal oxidative stress tolerance are also required for normal biofilm formation, as mutations in the following genes result in attenuated biofilm formation over cervical cells and/or glass: oxyR, gor, prx, mntABC, trxB, and estD. Overall, biofilm formation appears to be an adaptation for coping with the environmental stresses present in the female genitourinary tract. Therefore, this review will discuss the studies, which describe the composition and metabolic phenotype of gonococcal biofilms.

Prevalence and clinical characteristics of metabolically healthy obese individuals and other obese/non-obese metabolic phenotypes in a working population: results from the Icaria study

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Albert Goday

2016-04-01

Full Text Available Abstract Background Metabolically healthy obese (MHO phenotype may present with distinct characteristics compared with those with a metabolically unhealthy obese phenotype. Epidemiologic data on the distribution of these conditions in the working population are lacking. We aimed to evaluate the prevalence and clinical characteristics of MHO and other obese/non-obese metabolic phenotypes in a working population. Methods Cross-sectional analysis of all subjects who had undergone a medical examination with Ibermutuamur Prevention Society from May 2004 to December 2007. Participants were classified into 5 categories according to their body mass index (BMI; within each of these categories, participants were further classified as metabolically healthy (MH or metabolically unhealthy (MUH according to the modified NCEP-ATPIII criteria. A logistic regression analysis was performed to evaluate some clinically relevant factors associated with a MH status. Results In the overall population, the prevalence of the MHO phenotype was 8.6 %. The proportions of MH individuals in the overweight and obese categories were: 87.1 % (overweight and 55.5 % (obese I-III [58.8, 40.0, and 38.7 % of the obese I, II, and III categories, respectively]. When the overweight and obese categories were considered, compared with individuals who were MUH, those who were MH tended to be younger and more likely to be female or participate in physical exercise; they were also less likely to smoke, or to be a heavy drinker. In the underweight and normal weight categories, compared with individuals who were MH, those who were MUH were more likely to be older, male, manual (blue collar workers, smokers and heavy drinkers. Among participants in the MUH, normal weight group, the proportion of individuals with a sedentary lifestyle was higher relative to those in the MH, normal weight group. The factors more strongly associated with the MUH phenotype were BMI and age, followed by the

The Protein Cost of Metabolic Fluxes: Prediction from Enzymatic Rate Laws and Cost Minimization.

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Elad Noor

2016-11-01

Full Text Available Bacterial growth depends crucially on metabolic fluxes, which are limited by the cell's capacity to maintain metabolic enzymes. The necessary enzyme amount per unit flux is a major determinant of metabolic strategies both in evolution and bioengineering. It depends on enzyme parameters (such as kcat and KM constants, but also on metabolite concentrations. Moreover, similar amounts of different enzymes might incur different costs for the cell, depending on enzyme-specific properties such as protein size and half-life. Here, we developed enzyme cost minimization (ECM, a scalable method for computing enzyme amounts that support a given metabolic flux at a minimal protein cost. The complex interplay of enzyme and metabolite concentrations, e.g. through thermodynamic driving forces and enzyme saturation, would make it hard to solve this optimization problem directly. By treating enzyme cost as a function of metabolite levels, we formulated ECM as a numerically tractable, convex optimization problem. Its tiered approach allows for building models at different levels of detail, depending on the amount of available data. Validating our method with measured metabolite and protein levels in E. coli central metabolism, we found typical prediction fold errors of 4.1 and 2.6, respectively, for the two kinds of data. This result from the cost-optimized metabolic state is significantly better than randomly sampled metabolite profiles, supporting the hypothesis that enzyme cost is important for the fitness of E. coli. ECM can be used to predict enzyme levels and protein cost in natural and engineered pathways, and could be a valuable computational tool to assist metabolic engineering projects. Furthermore, it establishes a direct connection between protein cost and thermodynamics, and provides a physically plausible and computationally tractable way to include enzyme kinetics into constraint-based metabolic models, where kinetics have usually been ignored or

Rumen microbial communities influence metabolic phenotypes in lambs

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Diego P. Morgavi

2015-10-01

Full Text Available The rumen microbiota is an essential part of ruminants forging their nutrition and health. Despite its importance, it is not fully understood how various groups of rumen microbes affect host-microbe relationships and functions. The aim of the study was to simultaneously explore the rumen microbiota and the metabolic phenotype of lambs for identifying host-microbe associations and potential biomarkers of digestive functions. Twin lambs, separated in two groups after birth were exposed to practices (isolation and gavage with rumen fluid with protozoa or protozoa-depleted that differentially restricted the acquisition of microbes. Rumen microbiota, fermentation parameters, digestibility and growth were monitored for up to 31 weeks of age. Microbiota assembled in isolation from other ruminants lacked protozoa and had low bacterial and archaeal diversity whereas digestibility was not affected. Exposure to adult sheep microbiota increased bacterial and archaeal diversity independently of protozoa presence. For archaea, Methanomassiliicoccales displaced Methanosphaera. Notwithstanding, protozoa induced differences in functional traits such as digestibility and significantly shaped bacterial community structure, notably Ruminococcaceae and Lachnospiraceae lower up to 6 folds, Prevotellaceae lower by ~40%, and Clostridiaceae and Veillonellaceae higher up to 10 folds compared to microbiota without protozoa. An orthogonal partial least squares-discriminant analysis of urinary metabolome matched differences in microbiota structure. Discriminant metabolites were mainly involved in amino acids and protein metabolic pathways while a negative interaction was observed between methylotrophic methanogens Methanomassiliicoccales and trimethylamine N-oxide. These results stress the influence of gut microbes on animal phenotype and show the potential of metabolomics for monitoring rumen microbial functions.

Genome-Scale Metabolic Model for the Green Alga Chlorella vulgaris UTEX 395 Accurately Predicts Phenotypes under Autotrophic, Heterotrophic, and Mixotrophic Growth Conditions.

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Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten

2016-09-01

The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.

Metabolic Models of Protein Allocation Call for the Kinetome

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Nilsson, Avlant; Nielsen, Jens; Palsson, Bernhard

2017-01-01

The flux of metabolites in the living cell depend on enzyme activities. Recently, many metabolic phenotypes have been explained by computer models that incorporate enzyme activity data. To move further, the scientific community needs to measure the kinetics of all enzymes in a systematic way....

Gene Knockout Identification Using an Extension of Bees Hill Flux Balance Analysis

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Yee Wen Choon

2015-01-01

Full Text Available Microbial strain optimisation for the overproduction of a desired phenotype has been a popular topic in recent years. Gene knockout is a genetic engineering technique that can modify the metabolism of microbial cells to obtain desirable phenotypes. Optimisation algorithms have been developed to identify the effects of gene knockout. However, the complexities of metabolic networks have made the process of identifying the effects of genetic modification on desirable phenotypes challenging. Furthermore, a vast number of reactions in cellular metabolism often lead to a combinatorial problem in obtaining optimal gene knockout. The computational time increases exponentially as the size of the problem increases. This work reports an extension of Bees Hill Flux Balance Analysis (BHFBA to identify optimal gene knockouts to maximise the production yield of desired phenotypes while sustaining the growth rate. This proposed method functions by integrating OptKnock into BHFBA for validating the results automatically. The results show that the extension of BHFBA is suitable, reliable, and applicable in predicting gene knockout. Through several experiments conducted on Escherichia coli, Bacillus subtilis, and Clostridium thermocellum as model organisms, extension of BHFBA has shown better performance in terms of computational time, stability, growth rate, and production yield of desired phenotypes.

Investigating genotype-phenotype relationships in Saccharomyces cerevisiae metabolic network through stoichiometric modeling

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Brochado, Ana Rita

processes. Metabolism is an extensively studied and characterised subcellular system, for which several modeling approaches have been proposed over the last 20 years. Nowadays, stoichiometric modeling of metabolism is done at the genome scale and it has diverse applications, many of them for helping....... This chapter aims at providing the reader with relevant state-of-the-art information concerning Systems Biology, Genome-Scale Metabolic Modeling and Metabolic Engineering. Particular attention is given to the yeast Saccharomyces cerevisiae, the eukaryotic model organism used thought the thesis.......A holistic view of the cell is fundamental for gaining insights into genotype to phenotype relationships. Systems Biology is a discipline within Biology, which uses such holistic approach by focusing on the development and application of tools for studying the structure and dynamics of cellular...

¹³C-based metabolic flux analysis of Saccharomyces cerevisiae with a reduced Crabtree effect.

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Kajihata, Shuichi; Matsuda, Fumio; Yoshimi, Mika; Hayakawa, Kenshi; Furusawa, Chikara; Kanda, Akihisa; Shimizu, Hiroshi

2015-08-01

Saccharomyces cerevisiae shows a Crabtree effect that produces ethanol in a high glucose concentration even under fully aerobic condition. For efficient production of cake yeast or compressed yeast for baking, ethanol by-production is not desired since glucose limited chemostat or fed-batch cultivations are performed to suppress the Crabtree effect. In this study, the (13)C-based metabolic flux analysis ((13)C-MFA) was performed for the S288C derived S. cerevisiae strain to characterize a metabolic state under the reduced Crabtree effect. S. cerevisiae cells were cultured at a low dilution rate (0.1 h(-1)) under the glucose-limited chemostat condition. The estimated metabolic flux distribution showed that the acetyl-CoA in mitochondria was mainly produced from pyruvate by pyruvate dehydrogenase (PDH) reaction and that the level of the metabolic flux through the pentose phosphate pathway was much higher than that of the Embden-Meyerhof-Parnas pathway, which contributes to high biomass yield at low dilution rate by supplying NADPH required for cell growth. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

A comparative study on genetic and environmental influences on metabolic phenotypes in Eastern (Chinese) and Western (Danish) populations

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Li, Shuxia

2015-01-01

the risk of clinic diseases e.g. diabetes, atherosclerosis, stroke and cardiovascular disease. Metabolic phenotypes, similar to most complex traits, can be influenced by both genetic and environmental factors as well as their interplay. Many family and twin studies have demonstrated both genetic...... and environmental factors play important role in the variation of metabolic phenotypes and intra-individual change over time. Although both genetic and environmental factors are involved the development of metabolic disorders, the role of environment should be emphasized as the expression or function of gene can...... be regulated to adapt to existing environmental circumstance. In other words, adaptive evolution in populations under distinct environmental and cultural circumstances could have resulted in varying genetic basis of metabolic factors and development of metabolic disorders or diseases. Thus, it can...

A community-based exercise intervention transitions metabolically abnormal obese adults to a metabolically healthy obese phenotype

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Dalleck, Lance C; Van Guilder, Gary P; Richardson, Tara B; Bredle, Donald L; Janot, Jeffrey M

2014-01-01

Background Lower habitual physical activity and poor cardiorespiratory fitness are common features of the metabolically abnormal obese (MAO) phenotype that contribute to increased cardiovascular disease risk. The aims of the present study were to determine 1) whether community-based exercise training transitions MAO adults to metabolically healthy, and 2) whether the odds of transition to metabolically healthy were larger for obese individuals who performed higher volumes of exercise and/or experienced greater increases in fitness. Methods and results Metabolic syndrome components were measured in 332 adults (190 women, 142 men) before and after a supervised 14-week community-based exercise program designed to reduce cardiometabolic risk factors. Obese (body mass index ≥30 kg · m2) adults with two to four metabolic syndrome components were classified as MAO, whereas those with no or one component were classified as metabolically healthy but obese (MHO). After community exercise, 27/68 (40%) MAO individuals (Pmetabolically healthy, increasing the total number of MHO persons by 73% (from 37 to 64). Compared with the lowest quartiles of relative energy expenditure and change in fitness, participants in the highest quartiles were 11.6 (95% confidence interval: 2.1–65.4; Pexercise transitions MAO adults to metabolically healthy. MAO adults who engaged in higher volumes of exercise and experienced the greatest increase in fitness were significantly more likely to become metabolically healthy. Community exercise may be an effective model for primary prevention of cardiovascular disease. PMID:25120373

Estimation of dynamic flux profiles from metabolic time series data

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Chou I-Chun

2012-07-01

Full Text Available Abstract Background Advances in modern high-throughput techniques of molecular biology have enabled top-down approaches for the estimation of parameter values in metabolic systems, based on time series data. Special among them is the recent method of dynamic flux estimation (DFE, which uses such data not only for parameter estimation but also for the identification of functional forms of the processes governing a metabolic system. DFE furthermore provides diagnostic tools for the evaluation of model validity and of the quality of a model fit beyond residual errors. Unfortunately, DFE works only when the data are more or less complete and the system contains as many independent fluxes as metabolites. These drawbacks may be ameliorated with other types of estimation and information. However, such supplementations incur their own limitations. In particular, assumptions must be made regarding the functional forms of some processes and detailed kinetic information must be available, in addition to the time series data. Results The authors propose here a systematic approach that supplements DFE and overcomes some of its shortcomings. Like DFE, the approach is model-free and requires only minimal assumptions. If sufficient time series data are available, the approach allows the determination of a subset of fluxes that enables the subsequent applicability of DFE to the rest of the flux system. The authors demonstrate the procedure with three artificial pathway systems exhibiting distinct characteristics and with actual data of the trehalose pathway in Saccharomyces cerevisiae. Conclusions The results demonstrate that the proposed method successfully complements DFE under various situations and without a priori assumptions regarding the model representation. The proposed method also permits an examination of whether at all, to what degree, or within what range the available time series data can be validly represented in a particular functional format of

Metabolic flux profiling of MDCK cells during growth and canine adenovirus vector production.

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Carinhas, Nuno; Pais, Daniel A M; Koshkin, Alexey; Fernandes, Paulo; Coroadinha, Ana S; Carrondo, Manuel J T; Alves, Paula M; Teixeira, Ana P

2016-03-23

Canine adenovirus vector type 2 (CAV2) represents an alternative to human adenovirus vectors for certain gene therapy applications, particularly neurodegenerative diseases. However, more efficient production processes, assisted by a greater understanding of the effect of infection on producer cells, are required. Combining [1,2-(13)C]glucose and [U-(13)C]glutamine, we apply for the first time (13)C-Metabolic flux analysis ((13)C-MFA) to study E1-transformed Madin-Darby Canine Kidney (MDCK) cells metabolism during growth and CAV2 production. MDCK cells displayed a marked glycolytic and ammoniagenic metabolism, and (13)C data revealed a large fraction of glutamine-derived labelling in TCA cycle intermediates, emphasizing the role of glutamine anaplerosis. (13)C-MFA demonstrated the importance of pyruvate cycling in balancing glycolytic and TCA cycle activities, as well as occurrence of reductive alphaketoglutarate (AKG) carboxylation. By turn, CAV2 infection significantly upregulated fluxes through most central metabolism, including glycolysis, pentose-phosphate pathway, glutamine anaplerosis and, more prominently, reductive AKG carboxylation and cytosolic acetyl-coenzyme A formation, suggestive of increased lipogenesis. Based on these results, we suggest culture supplementation strategies to stimulate nucleic acid and lipid biosynthesis for improved canine adenoviral vector production.

To be certain about the uncertainty: Bayesian statistics for 13 C metabolic flux analysis.

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Theorell, Axel; Leweke, Samuel; Wiechert, Wolfgang; Nöh, Katharina

2017-11-01

13 C Metabolic Fluxes Analysis ( 13 C MFA) remains to be the most powerful approach to determine intracellular metabolic reaction rates. Decisions on strain engineering and experimentation heavily rely upon the certainty with which these fluxes are estimated. For uncertainty quantification, the vast majority of 13 C MFA studies relies on confidence intervals from the paradigm of Frequentist statistics. However, it is well known that the confidence intervals for a given experimental outcome are not uniquely defined. As a result, confidence intervals produced by different methods can be different, but nevertheless equally valid. This is of high relevance to 13 C MFA, since practitioners regularly use three different approximate approaches for calculating confidence intervals. By means of a computational study with a realistic model of the central carbon metabolism of E. coli, we provide strong evidence that confidence intervals used in the field depend strongly on the technique with which they were calculated and, thus, their use leads to misinterpretation of the flux uncertainty. In order to provide a better alternative to confidence intervals in 13 C MFA, we demonstrate that credible intervals from the paradigm of Bayesian statistics give more reliable flux uncertainty quantifications which can be readily computed with high accuracy using Markov chain Monte Carlo. In addition, the widely applied chi-square test, as a means of testing whether the model reproduces the data, is examined closer. © 2017 Wiley Periodicals, Inc.

Of monkeys and men: A metabolomic analysis of static and dynamic urinary metabolic phenotypes in two species

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Saccenti, E.; Tenori, L.; Verbruggen, P.; Timmerman, M.E.; Bouwman, J.; Greef, J. van der; Luchinat, C.; Smilde, A.K.

2014-01-01

Background: Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the

Of Monkeys and Men: A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

NARCIS (Netherlands)

Saccenti, E.; Tenori, L.; Verbruggen, P.; Timmerman, M.E.; Bouwman, J.; Greef, de J.; Luchinat, C.; Smilde, A.K.

2014-01-01

Background Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the

Of Monkeys and Men : A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

NARCIS (Netherlands)

Saccenti, E.; Tenori, L.; Verbruggen, P.; Timmerman, Marieke; Bouwman, J.; van der Greef, J.; Luchinat, C.; Smilde, Age K.

2014-01-01

Background Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the

Integration of genome-scale metabolic networks into whole-body PBPK models shows phenotype-specific cases of drug-induced metabolic perturbation.

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Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars

2018-01-01

Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.

Arachidonic Acid Metabolism Pathway Is Not Only Dominant in Metabolic Modulation but Associated With Phenotypic Variation After Acute Hypoxia Exposure

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Chang Liu

2018-03-01

Full Text Available Background: The modulation of arachidonic acid (AA metabolism pathway is identified in metabolic alterations after hypoxia exposure, but its biological function is controversial. We aimed at integrating plasma metabolomic and transcriptomic approaches to systematically explore the roles of the AA metabolism pathway in response to acute hypoxia using an acute mountain sickness (AMS model.Methods: Blood samples were obtained from 53 enrolled subjects before and after exposure to high altitude. Ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry and RNA sequencing were separately performed for metabolomic and transcriptomic profiling, respectively. Influential modules comprising essential metabolites and genes were identified by weighted gene co-expression network analysis (WGCNA after integrating metabolic information with phenotypic and transcriptomic datasets, respectively.Results: Enrolled subjects exhibited diverse response manners to hypoxia. Combined with obviously altered heart rate, oxygen saturation, hemoglobin, and Lake Louise Score (LLS, metabolomic profiling detected that 36 metabolites were highly related to clinical features in hypoxia responses, out of which 27 were upregulated and nine were downregulated, and could be mapped to AA metabolism pathway significantly. Integrated analysis of metabolomic and transcriptomic data revealed that these dominant molecules showed remarkable association with genes in gas transport incapacitation and disorders of hemoglobin metabolism pathways, such as ALAS2, HEMGN. After detailed description of AA metabolism pathway, we found that the molecules of 15-d-PGJ2, PGA2, PGE2, 12-O-3-OH-LTB4, LTD4, LTE4 were significantly up-regulated after hypoxia stimuli, and increased in those with poor response manner to hypoxia particularly. Further analysis in another cohort showed that genes in AA metabolism pathway such as PTGES, PTGS1, GGT1, TBAS1 et al. were excessively

Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks

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Brochado, Ana Rita; Andrejev, Sergej; Maranas, Costas D.

2012-01-01

the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results...

(13)C-metabolic flux analysis in S-adenosyl-L-methionine production by Saccharomyces cerevisiae.

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Hayakawa, Kenshi; Kajihata, Shuichi; Matsuda, Fumio; Shimizu, Hiroshi

2015-11-01

S-Adenosyl-L-methionine (SAM) is a major biological methyl group donor, and is used as a nutritional supplement and prescription drug. Yeast is used for the industrial production of SAM owing to its high intracellular SAM concentrations. To determine the regulation mechanisms responsible for such high SAM production, (13)C-metabolic flux analysis ((13)C-MFA) was conducted to compare the flux distributions in the central metabolism between Kyokai no. 6 (high SAM-producing) and S288C (control) strains. (13)C-MFA showed that the levels of tricarboxylic acid (TCA) cycle flux in SAM-overproducing strain were considerably increased compared to those in the S228C strain. Analysis of ATP balance also showed that a larger amount of excess ATP was produced in the Kyokai 6 strain because of increased oxidative phosphorylation. These results suggest that high SAM production in Kyokai 6 strains could be attributed to enhanced ATP regeneration with high TCA cycle fluxes and respiration activity. Thus, maintaining high respiration efficiency during cultivation is important for improving SAM production. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Transgenerational Inheritance of Paternal Neurobehavioral Phenotypes: Stress, Addiction, Ageing and Metabolism.

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Yuan, Ti-Fei; Li, Ang; Sun, Xin; Ouyang, Huan; Campos, Carlos; Rocha, Nuno B F; Arias-Carrión, Oscar; Machado, Sergio; Hou, Gonglin; So, Kwok Fai

2016-11-01

Epigenetic modulation is found to get involved in multiple neurobehavioral processes. It is believed that different types of environmental stimuli could alter the epigenome of the whole brain or related neural circuits, subsequently contributing to the long-lasting neural plasticity of certain behavioral phenotypes. While the maternal influence on the health of offsprings has been long recognized, recent findings highlight an alternative way for neurobehavioral phenotypes to be passed on to the next generation, i.e., through the male germ line. In this review, we focus specifically on the transgenerational modulation induced by environmental stress, drugs of abuse, and other physical or mental changes (e.g., ageing, metabolism, fear) in fathers, and recapitulate the underlying mechanisms potentially mediating the alterations in epigenome or gene expression of offsprings. Together, these findings suggest that the inheritance of phenotypic traits through male germ-line epigenome may represent the unique manner of adaptation during evolution. Hence, more attention should be paid to the paternal health, given its equivalently important role in affecting neurobehaviors of descendants.

Human breath analysis may support the existence of individual metabolic phenotypes.

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Pablo Martinez-Lozano Sinues

Full Text Available The metabolic phenotype varies widely due to external factors such as diet and gut microbiome composition, among others. Despite these temporal fluctuations, urine metabolite profiling studies have suggested that there are highly individual phenotypes that persist over extended periods of time. This hypothesis was tested by analyzing the exhaled breath of a group of subjects during nine days by mass spectrometry. Consistent with previous metabolomic studies based on urine, we conclude that individual signatures of breath composition exist. The confirmation of the existence of stable and specific breathprints may contribute to strengthen the inclusion of breath as a biofluid of choice in metabolomic studies. In addition, the fact that the method is rapid and totally non-invasive, yet individualized profiles can be tracked, makes it an appealing approach.

In vivo urea cycle flux distinguishes and correlates with phenotypic severity in disorders of the urea cycle

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Lee, Brendan; Yu, Hong; Jahoor, Farook; O'Brien, William; Beaudet, Arthur L.; Reeds, Peter

2000-01-01

Urea cycle disorders are a group of inborn errors of hepatic metabolism that result in often life-threatening hyperammonemia and hyperglutaminemia. Clinical and laboratory diagnosis of partial deficiencies during asymptomatic periods is difficult, and correlation of phenotypic severity with either genotype and/or in vitro enzyme activity is often imprecise. We hypothesized that stable isotopically determined in vivo rates of total body urea synthesis and urea cycle-specific nitrogen flux would correlate with both phenotypic severity and carrier status in patients with a variety of different enzymatic deficiencies of the urea cycle. We studied control subjects, patients, and their relatives with different enzymatic deficiencies affecting the urea cycle while consuming a low protein diet. On a separate occasion the subjects either received a higher protein intake or were treated with an alternative route medication sodium phenylacetate/benzoate (Ucephan), or oral arginine supplementation. Total urea synthesis from all nitrogen sources was determined from [18O]urea labeling, and the utilization of peripheral nitrogen was estimated from the relative isotopic enrichments of [15N]urea and [15N]glutamine during i.v. co-infusions of [5-(amide)15N]glutamine and [18O]urea. The ratio of the isotopic enrichments of 15N-urea/15N-glutamine distinguished normal control subjects (ratio = 0.42 ± 0.06) from urea cycle patients with late (0.17 ± 0.03) and neonatal (0.003 ± 0.007) presentations irrespective of enzymatic deficiency. This index of urea cycle activity also distinguished asymptomatic heterozygous carriers of argininosuccinate synthetase deficiency (0.22 ± 0.03), argininosuccinate lyase deficiency (0.35 ± 0.11), and partial ornithine transcarbamylase deficiency (0.26 ± 0.06) from normal controls. Administration of Ucephan lowered, and arginine increased, urea synthesis to the degree predicted from their respective rates of metabolism. The 15N-urea/15N-glutamine ratio

Redistribution of metabolic fluxes in Chlorella protothecoides by variation of media nitrogen concentration

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Saratram Gopalakrishnan

2015-12-01

Full Text Available In this study, the Elementary Metabolite Unit (EMU algorithm was employed to calculate intracellular fluxes for Chlorella protothecoides using previously generated growth and mass spec data. While the flux through glycolysis remained relatively constant, the pentose phosphate pathway (PPP flux increased from 3% to 20% of the glucose uptake during nitrogen-limited growth. The TCA cycle flux decreased from 94% to 38% during nitrogen-limited growth while the flux of acetyl-CoA into lipids increased from 58% to 109% of the glucose uptake, increasing total lipid accumulation. Phosphoenolpyruvate carboxylase (PEPCase activity was higher during nitrogen-sufficient growth. The glyoxylate shunt was found to be partially active in both cases, indicating the nutrient nature has an impact on flux distribution. It was found that the total NADPH supply within the cell remained almost constant under both conditions. In summary, algal cells substantially reorganize their metabolism during the switch from carbon-limited (nitrogen-sufficient to nitrogen-limited (carbon-sufficient growth. Keywords: Microalgae, Biofuels, Chlorella, MFA, EMU algorithm

Growth platform-dependent and -independent phenotypic and metabolic responses of Arabidopsis and its halophytic relative, Eutrema salsugineum, to salt stress.

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Kazachkova, Yana; Batushansky, Albert; Cisneros, Aroldo; Tel-Zur, Noemi; Fait, Aaron; Barak, Simon

2013-07-01

Comparative studies of the stress-tolerant Arabidopsis (Arabidopsis thaliana) halophytic relative, Eutrema salsugineum, have proven a fruitful approach to understanding natural stress tolerance. Here, we performed comparative phenotyping of Arabidopsis and E. salsugineum vegetative development under control and salt-stress conditions, and then compared the metabolic responses of the two species on different growth platforms in a defined leaf developmental stage. Our results reveal both growth platform-dependent and -independent phenotypes and metabolic responses. Leaf emergence was affected in a similar way in both species grown in vitro but the effects observed in Arabidopsis occurred at higher salt concentrations in E. salsugineum. No differences in leaf emergence were observed on soil. A new effect of a salt-mediated reduction in E. salsugineum leaf area was unmasked. On soil, leaf area reduction in E. salsugineum was mainly due to a fall in cell number, whereas both cell number and cell size contributed to the decrease in Arabidopsis leaf area. Common growth platform-independent leaf metabolic signatures such as high raffinose and malate, and low fumarate contents that could reflect core stress tolerance mechanisms, as well as growth platform-dependent metabolic responses were identified. In particular, the in vitro growth platform led to repression of accumulation of many metabolites including sugars, sugar phosphates, and amino acids in E. salsugineum compared with the soil system where these same metabolites accumulated to higher levels in E. salsugineum than in Arabidopsis. The observation that E. salsugineum maintains salt tolerance despite growth platform-specific phenotypes and metabolic responses suggests a considerable degree of phenotypic and metabolic adaptive plasticity in this extremophile.

Effects of drugs in subtoxic concentrations on the metabolic fluxes in human hepatoma cell line Hep G2

International Nuclear Information System (INIS)

Niklas, Jens; Noor, Fozia; Heinzle, Elmar

2009-01-01

Commonly used cytotoxicity assays assess the toxicity of a compound by measuring certain parameters which directly or indirectly correlate to the viability of the cells. However, the effects of a given compound at concentrations considerably below EC 50 values are usually not evaluated. These subtoxic effects are difficult to identify but may eventually cause severe and costly long term problems such as idiosyncratic hepatotoxicity. We determined the toxicity of three hepatotoxic compounds, namely amiodarone, diclofenac and tacrine on the human hepatoma cell line Hep G2 using an online kinetic respiration assay and analysed the effects of subtoxic concentrations of these drugs on the cellular metabolism by using metabolic flux analysis. Several changes in the metabolism could be detected upon exposure to subtoxic concentrations of the test compounds. Upon exposure to diclofenac and tacrine an increase in the TCA-cycle activity was observed which could be a signature of an uncoupling of the oxidative phosphorylation. The results indicate that metabolic flux analysis could serve as an invaluable novel tool for the investigation of the effects of drugs. The described methodology enables tracking the toxicity of compounds dynamically using the respiration assay in a range of concentrations and the metabolic flux analysis permits interesting insights into the changes in the central metabolism of the cell upon exposure to drugs.

The role of inflammatory pathway genetic variation on maternal metabolic phenotypes during pregnancy.

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Margrit Urbanek

Full Text Available Since mediators of inflammation are associated with insulin resistance, and the risk of developing diabetes mellitus and gestational diabetes, we hypothesized that genetic variation in members of the inflammatory gene pathway impact glucose levels and related phenotypes in pregnancy. We evaluated this hypothesis by testing for association between genetic variants in 31 inflammatory pathway genes in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO cohort, a large multiethnic multicenter study designed to address the impact of glycemia less than overt diabetes on pregnancy outcome.Fasting, 1-hour, and 2-hour glucose, fasting and 1-hour C-peptide, and HbA1c levels were measured in blood samples obtained from HAPO participants during an oral glucose tolerance test at 24-32 weeks gestation. We tested for association between 458 SNPs mapping to 31 genes in the inflammatory pathway and metabolic phenotypes in 3836 European ancestry and 1713 Thai pregnant women. The strongest evidence for association was observed with TNF alpha and HbA1c (rs1052248; 0.04% increase per allele C; p-value = 4.4×10(-5, RETN and fasting plasma glucose (rs1423096; 0.7 mg/dl decrease per allele A; p-value = 1.1×10(-4, IL8 and 1 hr plasma glucose (rs2886920; 2.6 mg/dl decrease per allele T; p-value = 1.3×10(-4, ADIPOR2 and fasting C-peptide (rs2041139; 0.55 ug/L decrease per allele A; p-value = 1.4×10(-4, LEPR and 1-hour C-peptide (rs1171278; 0.62 ug/L decrease per allele T; p-value = 2.4×10(-4, and IL6 and 1-hour plasma glucose (rs6954897; -2.29 mg/dl decrease per allele G, p-value = 4.3×10(-4.Based on the genes surveyed in this study the inflammatory pathway is unlikely to have a strong impact on maternal metabolic phenotypes in pregnancy although variation in individual members of the pathway (e.g. RETN, IL8, ADIPOR2, LEPR, IL6, and TNF alpha, may contribute to metabolic phenotypes in pregnant women.

Radiopharmaceuticals for Assessment of Altered Metabolism and Biometal Fluxes in Brain Aging and Alzheimer's Disease with Positron Emission Tomography.

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Xie, Fang; Peng, Fangyu

2017-01-01

Aging is a risk factor for Alzheimer's disease (AD). There are changes of brain metabolism and biometal fluxes due to brain aging, which may play a role in pathogenesis of AD. Positron emission tomography (PET) is a versatile tool for tracking alteration of metabolism and biometal fluxes due to brain aging and AD. Age-dependent changes in cerebral glucose metabolism can be tracked with PET using 2-deoxy-2-[18F]-fluoro-D-glucose (18F-FDG), a radiolabeled glucose analogue, as a radiotracer. Based on different patterns of altered cerebral glucose metabolism, 18F-FDG PET was clinically used for differential diagnosis of AD and Frontotemporal dementia (FTD). There are continued efforts to develop additional radiopharmaceuticals or radiotracers for assessment of age-dependent changes of various metabolic pathways and biometal fluxes due to brain aging and AD with PET. Elucidation of age-dependent changes of brain metabolism and altered biometal fluxes is not only significant for a better mechanistic understanding of brain aging and the pathophysiology of AD, but also significant for identification of new targets for the prevention, early diagnosis, and treatment of AD.

Multiplatform serum metabolic phenotyping combined with pathway mapping to identify biochemical differences in smokers.

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Kaluarachchi, Manuja R; Boulangé, Claire L; Garcia-Perez, Isabel; Lindon, John C; Minet, Emmanuel F

2016-10-01

Determining perturbed biochemical functions associated with tobacco smoking should be helpful for establishing causal relationships between exposure and adverse events. A multiplatform comparison of serum of smokers (n = 55) and never-smokers (n = 57) using nuclear magnetic resonance spectroscopy, UPLC-MS and statistical modeling revealed clustering of the classes, distinguished by metabolic biomarkers. The identified metabolites were subjected to metabolic pathway enrichment, modeling adverse biological events using available databases. Perturbation of metabolites involved in chronic obstructive pulmonary disease, cardiovascular diseases and cancer were identified and discussed. Combining multiplatform metabolic phenotyping with knowledge-based mapping gives mechanistic insights into disease development, which can be applied to next-generation tobacco and nicotine products for comparative risk assessment.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

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Kumari Sonal Choudhary

2016-06-01

Full Text Available Epithelial to mesenchymal transition (EMT is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR, are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E and mesenchymal (EGFR_M networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

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Choudhary, Kumari Sonal; Rohatgi, Neha; Halldorsson, Skarphedinn; Briem, Eirikur; Gudjonsson, Thorarinn; Gudmundsson, Steinn; Rolfsson, Ottar

2016-06-01

Epithelial to mesenchymal transition (EMT) is an important event during development and cancer metastasis. There is limited understanding of the metabolic alterations that give rise to and take place during EMT. Dysregulation of signalling pathways that impact metabolism, including epidermal growth factor receptor (EGFR), are however a hallmark of EMT and metastasis. In this study, we report the investigation into EGFR signalling and metabolic crosstalk of EMT through constraint-based modelling and analysis of the breast epithelial EMT cell model D492 and its mesenchymal counterpart D492M. We built an EGFR signalling network for EMT based on stoichiometric coefficients and constrained the network with gene expression data to build epithelial (EGFR_E) and mesenchymal (EGFR_M) networks. Metabolic alterations arising from differential expression of EGFR genes was derived from a literature review of AKT regulated metabolic genes. Signaling flux differences between EGFR_E and EGFR_M models subsequently allowed metabolism in D492 and D492M cells to be assessed. Higher flux within AKT pathway in the D492 cells compared to D492M suggested higher glycolytic activity in D492 that we confirmed experimentally through measurements of glucose uptake and lactate secretion rates. The signaling genes from the AKT, RAS/MAPK and CaM pathways were predicted to revert D492M to D492 phenotype. Follow-up analysis of EGFR signaling metabolic crosstalk in three additional breast epithelial cell lines highlighted variability in in vitro cell models of EMT. This study shows that the metabolic phenotype may be predicted by in silico analyses of gene expression data of EGFR signaling genes, but this phenomenon is cell-specific and does not follow a simple trend.

Reconstruction of the central carbon metabolism of Aspergillus niger

DEFF Research Database (Denmark)

David, Helga; Åkesson, Mats Fredrik; Nielsen, Jens

2003-01-01

The topology of central carbon metabolism of Aspergillus niger was identified and the metabolic network reconstructed, by integrating genomic, biochemical and physiological information available for this microorganism and other related fungi. The reconstructed network may serve as a valuable...... of metabolic fluxes using metabolite balancing. This framework was employed to perform an in silico characterisation of the phenotypic behaviour of A. niger grown on different carbon sources. The effects on growth of single reaction deletions were assessed and essential biochemical reactions were identified...... for different carbon sources. Furthermore, application of the stoichiometric model for assessing the metabolic capabilities of A. niger to produce metabolites was evaluated by using succinate production as a case study....

The impact of metabolic syndrome and CRP on vascular phenotype in type 2 diabetes mellitus

NARCIS (Netherlands)

Alizadeh Dehnavi, R.; Beishuizen, E.D.; Ree, M.A. van de; Le Cessie, S.; Huisman, M.V.; Kluft, C.; Princen, H.M.G.; Tamsma, J.T.

2008-01-01

Background: The burden of cardiovascular disease in diabetes mellitus type 2 (DM2) patients is variable. We hypothesize that metabolic syndrome (MS) and low-grade systemic inflammation modify the extent of atherosclerosis in DM2. Methods: Vascular phenotype was determined using the following

Metabolic flux analysis during the exponential growth phase of Saccharomyces cerevisiae in wine fermentations.

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Manuel Quirós

Full Text Available As a consequence of the increase in global average temperature, grapes with the adequate phenolic and aromatic maturity tend to be overripe by the time of harvest, resulting in increased sugar concentrations and imbalanced C/N ratios in fermenting musts. This fact sets obvious additional hurdles in the challenge of obtaining wines with reduced alcohols levels, a new trend in consumer demands. It would therefore be interesting to understand Saccharomyces cerevisiae physiology during the fermentation of must with these altered characteristics. The present study aims to determine the distribution of metabolic fluxes during the yeast exponential growth phase, when both carbon and nitrogen sources are in excess, using continuous cultures. Two different sugar concentrations were studied under two different winemaking temperature conditions. Although consumption and production rates for key metabolites were severely affected by the different experimental conditions studied, the general distribution of fluxes in central carbon metabolism was basically conserved in all cases. It was also observed that temperature and sugar concentration exerted a higher effect on the pentose phosphate pathway and glycerol formation than on glycolysis and ethanol production. Additionally, nitrogen uptake, both quantitatively and qualitatively, was strongly influenced by environmental conditions. This work provides the most complete stoichiometric model used for Metabolic Flux Analysis of S. cerevisiae in wine fermentations employed so far, including the synthesis and release of relevant aroma compounds and could be used in the design of optimal nitrogen supplementation of wine fermentations.

Metabolic fuels: regulating fluxes to select mix.

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Weber, Jean-Michel

2011-01-15

Animals must regulate the fluxes of multiple fuels to support changing metabolic rates that result from variation in physiological circumstances. The aim of fuel selection strategies is to exploit the advantages of individual substrates while minimizing the impact of disadvantages. All exercising mammals share a general pattern of fuel selection: at the same %V(O(2,max)) they oxidize the same ratio of lipids to carbohydrates. However, highly aerobic species rely more on intramuscular fuels because energy supply from the circulation is constrained by trans-sarcolemmal transfer. Fuel selection is performed by recruiting different muscles, different fibers within the same muscles or different pathways within the same fibers. Electromyographic analyses show that shivering humans can modulate carbohydrate oxidation either through the selective recruitment of type II fibers within the same muscles or by regulating pathway recruitment within type I fibers. The selection patterns of shivering and exercise are different: at the same %V(O(2,max)), a muscle producing only heat (shivering) or significant movement (exercise) strikes a different balance between lipid and carbohydrate oxidation. Long-distance migrants provide an excellent model to characterize how to increase maximal substrate fluxes. High lipid fluxes are achieved through the coordinated upregulation of mobilization, transport and oxidation by activating enzymes, lipid-solubilizing proteins and membrane transporters. These endurance athletes support record lipolytic rates in adipocytes, use lipoprotein shuttles to accelerate transport and show increased capacity for lipid oxidation in muscle mitochondria. Some migrant birds use dietary omega-3 fatty acids as performance-enhancing agents to boost their ability to process lipids. These dietary fatty acids become incorporated in membrane phospholipids and bind to peroxisome proliferator-activated receptors to activate membrane proteins and modify gene expression.

Role of hormones in cartilage and joint metabolism: understanding an unhealthy metabolic phenotype in osteoarthritis.

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Bay-Jensen, Anne C; Slagboom, Eline; Chen-An, Pingping; Alexandersen, Peter; Qvist, Per; Christiansen, Claus; Meulenbelt, Ingrid; Karsdal, Morten A

2013-05-01

Joint health is affected by local and systemic hormones. It is well accepted that systemic factors regulate the metabolism of joint tissues, and that substantial cross-talk between tissues actively contributes to homeostasis. In the current review, we try to define a subtype of osteoarthritis (OA), metabolic OA, which is dependent on an unhealthy phenotype. Peer-reviewed research articles and reviews were reviewed and summarized. Only literature readily available online, either by download or by purchase order, was included. OA is the most common joint disease and is more common in women after menopause. OA is a disease that affects the whole joint, including cartilage, subchondral bone, synovium, tendons, and muscles. The clinical endpoints of OA are pain and joint space narrowing, which is characterized by cartilage erosion and subchondral sclerosis, suggesting that cartilage is a central tissue of joint health. Thus, the joint, more specifically the cartilage, may be considered a target of endocrine function in addition to the well-described traditional risk factors of disease initiation and progression such as long-term loading of the joint due to obesity. Metabolic syndrome affects a range of tissues and may in part be molecularly described as a dysregulation of cytokines, adipokines, and hormones (e.g., estrogen and thyroid hormone). Consequently, metabolic imbalance may both directly and indirectly influence joint health and cartilage turnover, altering the progression of diseases such as OA. There is substantial evidence for a connection between metabolic health and development of OA. We propose that more focus be directed to understanding this connection to improve the management of menopausal health and associated comorbidities.

Is it the resistance training itself or the combined associated weight loss that improves the metabolic syndrome-related phenotypes in postmenopausal women?

Directory of Open Access Journals (Sweden)

Soyluk O

2015-10-01

Full Text Available Ozlem Soyluk,1 Gulistan Bahat21Division of Endocrinology and Metabolism, Department of Internal Medicine, Istanbul Medical School, Istanbul University, Capa, Istanbul, Turkey; 2Division of Geriatrics, Department of Internal Medicine, Istanbul Medical School, Istanbul University, Capa, Istanbul, TurkeyWe read the article entitled “Resistance training improves isokinetic strength and metabolic syndrome-related phenotypes in postmenopausal women” by Oliveira et al1 with great interest. In the study, the authors examined the effects of 12 weeks of resistance training (RT on metabolic syndrome-related phenotypes in postmenopausal women. They reported that total cholesterol, low-density lipoprotein cholesterol levels, total cholesterol/high-density lipoprotein cholesterol ratio, blood glucose, basal insulin, and homeostatic model assessment of insulin resistance were all significantly reduced with RT (P<0.01. Accordingly, they concluded that a 12-week progressive RT program induces beneficial alterations on metabolic syndrome-related phenotypes in postmenopausal women. View original paper by Oliveira and colleagues.

Cardiovascular and metabolic profiles amongst different polycystic ovary syndrome phenotypes: who is really at risk?

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Daan, Nadine M P; Louwers, Yvonne V; Koster, Maria P H; Eijkemans, Marinus J C; de Rijke, Yolanda B; Lentjes, Eef W G; Fauser, Bart C J M; Laven, Joop S E

2014-11-01

To study the cardiometabolic profile characteristics and compare the prevalence of cardiovascular (CV) risk factors between women with different polycystic ovary syndrome (PCOS) phenotypes. A cross-sectional multicenter study analyzing 2,288 well phenotyped women with PCOS. Specialized reproductive outpatient clinic. Women of reproductive age (18-45 years) diagnosed with PCOS. Women suspected of oligo- or anovulation underwent a standardized screening consisting of a systematic medical and reproductive history taking, anthropometric measurements, and transvaginal ultrasonography followed by an extensive endocrinologic/metabolic evaluation. Differences in cardiometabolic profile characteristics and CV risk factor prevalence between women with different PCOS phenotypes, i.e., obesity/overweight, hypertension, insulin resistance, dyslipidemia, and metabolic syndrome. Women with hyperandrogenic PCOS (n=1,219; 53.3% of total) presented with a worse cardiometabolic profile and a higher prevalence of CV risk factors, such as obesity and overweight, insulin resistance, and metabolic syndrome, compared with women with nonhyperandrogenic PCOS. In women with nonhyperandrogenic PCOS overweight/obesity (28.5%) and dyslipidemia (low-density lipoprotein cholesterol≥3.0 mmol/L; 52.2%) were highly prevalent. Women with hyperandrogenic PCOS have a worse cardiometabolic profile and higher prevalence of CV risk factors compared with women with nonhyperandrogenic PCOS. However, all women with PCOS should be screened for the presence of CV risk factors, since the frequently found derangements at a young age imply an elevated risk for the development of CV disease later in life. Copyright © 2014 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Analysis of Metabolic Pathways and Fluxes in a Newly Discovered Thermophilic and Ethanol-Tolerant Geobacillus Strain

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Tang, Yinjie J.; Sapra, Rajat; Joyner, Dominique; Hazen, Terry C.; Myers, Samuel; Reichmuth, David; Blanch, Harvey; Keasling, Jay D.

2009-01-20

A recently discovered thermophilic bacterium, Geobacillus thermoglucosidasius M10EXG, ferments a range of C5 (e.g., xylose) and C6 sugars (e.g., glucose) and istolerant to high ethanol concentrations (10percent, v/v). We have investigated the central metabolism of this bacterium using both in vitro enzyme assays and 13C-based flux analysis to provide insights into the physiological properties of this extremophile and explore its metabolism for bio-ethanol or other bioprocess applications. Our findings show that glucose metabolism in G. thermoglucosidasius M10EXG proceeds via glycolysis, the pentose phosphate pathway, and the TCA cycle; the Entner?Doudoroff pathway and transhydrogenase activity were not detected. Anaplerotic reactions (including the glyoxylate shunt, pyruvate carboxylase, and phosphoenolpyruvate carboxykinase) were active, but fluxes through those pathways could not be accuratelydetermined using amino acid labeling. When growth conditions were switched from aerobic to micro-aerobic conditions, fluxes (based on a normalized glucose uptake rate of 100 units (g DCW)-1 h-1) through the TCA cycle and oxidative pentose phosphate pathway were reduced from 64+-3 to 25+-2 and from 30+-2 to 19+-2, respectively. The carbon flux under micro-aerobic growth was directed formate. Under fully anerobic conditions, G. thermoglucosidasius M10EXG used a mixed acid fermentation process and exhibited a maximum ethanol yield of 0.38+-0.07 mol mol-1 glucose. In silico flux balance modeling demonstrates that lactate and acetate production from G. thermoglucosidasius M10EXG reduces the maximum ethanol yieldby approximately threefold, thus indicating that both pathways should be modified to maximize ethanol production.

The nutritional status of Methanosarcina acetivorans regulates glycogen metabolism and gluconeogenesis and glycolysis fluxes.

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Santiago-Martínez, Michel Geovanni; Encalada, Rusely; Lira-Silva, Elizabeth; Pineda, Erika; Gallardo-Pérez, Juan Carlos; Reyes-García, Marco Antonio; Saavedra, Emma; Moreno-Sánchez, Rafael; Marín-Hernández, Alvaro; Jasso-Chávez, Ricardo

2016-05-01

Gluconeogenesis is an essential pathway in methanogens because they are unable to use exogenous hexoses as carbon source for cell growth. With the aim of understanding the regulatory mechanisms of central carbon metabolism in Methanosarcina acetivorans, the present study investigated gene expression, the activities and metabolic regulation of key enzymes, metabolite contents and fluxes of gluconeogenesis, as well as glycolysis and glycogen synthesis/degradation pathways. Cells were grown with methanol as a carbon source. Key enzymes were kinetically characterized at physiological pH/temperature. Active consumption of methanol during exponential cell growth correlated with significant methanogenesis, gluconeogenic flux and steady glycogen synthesis. After methanol exhaustion, cells reached the stationary growth phase, which correlated with the rise in glycogen consumption and glycolytic flux, decreased methanogenesis, negligible acetate production and an absence of gluconeogenesis. Elevated activities of carbon monoxide dehydrogenase/acetyl-CoA synthetase complex and pyruvate: ferredoxin oxidoreductase suggested the generation of acetyl-CoA and pyruvate for glycogen synthesis. In the early stationary growth phase, the transcript contents and activities of pyruvate phosphate dikinase, fructose 1,6-bisphosphatase and glycogen synthase decreased, whereas those of glycogen phosphorylase, ADP-phosphofructokinase and pyruvate kinase increased. Therefore, glycogen and gluconeogenic metabolites were synthesized when an external carbon source was provided. Once such a carbon source became depleted, glycolysis and methanogenesis fed by glycogen degradation provided the ATP supply. Weak inhibition of key enzymes by metabolites suggested that the pathways evaluated were mainly transcriptionally regulated. Because glycogen metabolism and glycolysis/gluconeogenesis are not present in all methanogens, the overall data suggest that glycogen storage might represent an environmental

Excess Metabolic and Cardiovascular Risk is not Manifested in all Phenotypes of Polycystic Ovary Syndrome: Implications for Diagnosis and Treatment.

Science.gov (United States)

Daskalopoulos, Georgios; Karkanaki, Artemis; Piouka, Athanasia; Prapas, Nikolaos; Panidis, Dimitrios; Gkeleris, Paraschos; Athyros, Vasilios G

2015-01-01

To assess the potential differences in the metabolic and cardiovascular disease (CVD) risk between the distinct phenotypes of the Polycystic Ovary Syndrome (PCOS) according to the Rotterdam definition regardless of body mass index (BMI). The study included 300 women; 240 women with PCOS, according to the Rotterdam criteria and 60 controls without PCOS. All women were further subdivided, according to their BMI, into normal-weight and overweight/obese and PCOS women were furthermore subdivided to the 4 phenotypes of the syndrome. A complete hormonal and metabolic profile as well as the levels of high sensitivity C reactive protein (hsCRP) and lipoprotein-associated phospholipase A2 (Lp-PLA2) were measured. Levels of surrogate markers of subclinical atherosclerosis (hsCRP and Lp-PLA2), levels of evaluated CVD risk score using risk engines, and several correlations of CVD risk factors. hsCRP levels were higher but not significantly so in PCOS women compared with controls. In lean PCOS patients, Lp-PLA2 levels were significantly higher, compared with lean controls, mainly in the 2 classic phenotypes. Overweight/obese patients in all 4 phenotypes had significantly higher Lp-PLA2 levels compared with overweight/obese controls. Evaluated CVD risk according to 4 risk engines was not different among phenotypes and between PCOS patients and controls. There were several correlations of risk factors with metabolic syndrome and non-alcoholic fatty liver disease requiring appropriate treatment. Only 2 of 4 Rotterdam phenotypes, identical with those of the classic PCOS definition, have excess cardiometabolic risk. These need to be treated to prevent CVD events.

SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets.

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Navratil, Vincent; Pontoizeau, Clément; Billoir, Elise; Blaise, Benjamin J

2013-05-15

Supervised multivariate statistical analyses are often required to analyze the high-density spectral information in metabolic datasets acquired from complex mixtures in metabolic phenotyping studies. Here we present an implementation of the SRV-Statistical Recoupling of Variables-algorithm as an open-source Matlab and GNU Octave toolbox. SRV allows the identification of similarity between consecutive variables resulting from the high-resolution bucketing. Similar variables are gathered to restore the spectral dependency within the datasets and identify metabolic NMR signals. The correlation and significance of these new NMR variables for a given effect under study can then be measured and represented on a loading plot to allow a visual and efficient identification of candidate biomarkers. Further on, correlations between these candidate biomarkers can be visualized on a two-dimensional pseudospectrum, representing a correlation map, helping to understand the modifications of the underlying metabolic network. SRV toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) and in GNU Octave. It is available free of charge at http://www.prabi.fr/redmine/projects/srv/repository with a tutorial. benjamin.blaise@chu-lyon.fr or vincent.navratil@univ-lyon1.fr.

IsoDesign: a software for optimizing the design of 13C-metabolic flux analysis experiments.

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Millard, Pierre; Sokol, Serguei; Letisse, Fabien; Portais, Jean-Charles

2014-01-01

The growing demand for (13) C-metabolic flux analysis ((13) C-MFA) in the field of metabolic engineering and systems biology is driving the need to rationalize expensive and time-consuming (13) C-labeling experiments. Experimental design is a key step in improving both the number of fluxes that can be calculated from a set of isotopic data and the precision of flux values. We present IsoDesign, a software that enables these parameters to be maximized by optimizing the isotopic composition of the label input. It can be applied to (13) C-MFA investigations using a broad panel of analytical tools (MS, MS/MS, (1) H NMR, (13) C NMR, etc.) individually or in combination. It includes a visualization module to intuitively select the optimal label input depending on the biological question to be addressed. Applications of IsoDesign are described, with an example of the entire (13) C-MFA workflow from the experimental design to the flux map including important practical considerations. IsoDesign makes the experimental design of (13) C-MFA experiments more accessible to a wider biological community. IsoDesign is distributed under an open source license at http://metasys.insa-toulouse.fr/software/isodes/ © 2013 Wiley Periodicals, Inc.

¹³C Metabolic Flux Analysis for Systematic Metabolic Engineering of S. cerevisiae for Overproduction of Fatty Acids

DEFF Research Database (Denmark)

Ghosh, Amit; Ando, David; Gin, Jennifer

2016-01-01

Efficient redirection of microbial metabolism into the abundant production of desired bioproducts remains non-trivial. Here, we used flux-based modeling approaches to improve yields of fatty acids in Saccharomyces cerevisiae. We combined 13C labeling data with comprehensive genome-scale models...

Fat oxidation at rest predicts peak fat oxidation during exercise and metabolic phenotype in overweight men

DEFF Research Database (Denmark)

Rosenkilde, M; Nordby, P; Nielsen, L B

2010-01-01

OBJECTIVE: To elucidate if fat oxidation at rest predicts peak fat oxidation during exercise and/or metabolic phenotype in moderately overweight, sedentary men. DESIGN: Cross-sectional study.Subjects:We measured respiratory exchange ratio (RER) at rest in 44 moderately overweight, normotensive...... the International Diabetes Federation criteria, we found that there was a lower accumulation of metabolic risk factors in L-RER than in H-RER (1.6 vs 3.5, P=0.028), and no subjects in L-RER and four of eight subjects in H-RER had the metabolic syndrome. Resting RER was positively correlated with plasma...... triglycerides (Pexercise was positively correlated with plasma free fatty acid concentration at rest (Pexercise and a healthy metabolic...

Proteomic analysis uncovers a metabolic phenotype in C. elegans after nhr-40 reduction of function

International Nuclear Information System (INIS)

Pohludka, Michal; Simeckova, Katerina; Vohanka, Jaroslav; Yilma, Petr; Novak, Petr; Krause, Michael W.; Kostrouchova, Marta; Kostrouch, Zdenek

2008-01-01

Caenorhabditis elegans has an unexpectedly large number (284) of genes encoding nuclear hormone receptors, most of which are nematode-specific and are of unknown function. We have exploited comparative two-dimensional chromatography of synchronized cultures of wild type C. elegans larvae and a mutant in nhr-40 to determine if proteomic approaches will provide additional insight into gene function. Chromatofocusing, followed by reversed-phase chromatography and mass spectrometry, identified altered chromatographic patterns for a set of proteins, many of which function in muscle and metabolism. Prompted by the proteomic analysis, we find that the penetrance of the developmental phenotypes in the mutant is enhanced at low temperatures and by food restriction. The combination of our phenotypic and proteomic analysis strongly suggests that NHR-40 provides a link between metabolism and muscle development. Our results highlight the utility of comparative two-dimensional chromatography to provide a relatively rapid method to gain insight into gene function

Assessment of energetic costs of AhR activation by β-naphthoflavone in rainbow trout (Oncorhynchus mykiss) hepatocytes using metabolic flux analysis

International Nuclear Information System (INIS)

Nault, Rance; Abdul-Fattah, Hiba; Mironov, Gleb G.; Berezovski, Maxim V.; Moon, Thomas W.

2013-01-01

Exposure to environmental contaminants such as activators of the aryl hydrocarbon receptor (AhR) leads to the induction of defense and detoxification mechanisms. While these mechanisms allow organisms to metabolize and excrete at least some of these environmental contaminants, it has been proposed that these mechanisms lead to significant energetic challenges. This study tests the hypothesis that activation of the AhR by the model agonist β-naphthoflavone (βNF) results in increased energetic costs in rainbow trout (Oncorhynchus mykiss) hepatocytes. To address this hypothesis, we employed traditional biochemical approaches to examine energy allocation and metabolism including the adenylate energy charge (AEC), protein synthesis rates, Na + /K + -ATPase activity, and enzyme activities. Moreover, we have used for the first time in a fish cell preparation, metabolic flux analysis (MFA) an in silico approach for the estimation of intracellular metabolic fluxes. Exposure of trout hepatocytes to 1 μM βNF for 48 h did not alter hepatocyte AEC, protein synthesis, or Na + /K + -ATPase activity but did lead to sparing of glycogen reserves and changes in activities of alanine aminotransferase and citrate synthase suggesting altered metabolism. Conversely, MFA did not identify altered metabolic fluxes, although we do show that the dynamic metabolism of isolated trout hepatocytes poses a significant challenge for this type of approach which should be considered in future studies. - Highlights: • Energetic costs of AhR activation by βNF was examined in rainbow trout hepatocytes. • Metabolic flux analysis was performed on a fish cell preparation for the first time. • Exposure to βNF led to sparing of glycogen reserves and altered enzyme activities. • Adenylate energy charge was maintained despite temporal changes in metabolism

Assessment of energetic costs of AhR activation by β-naphthoflavone in rainbow trout (Oncorhynchus mykiss) hepatocytes using metabolic flux analysis

Energy Technology Data Exchange (ETDEWEB)

Nault, Rance, E-mail: naultran@msu.edu [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Abdul-Fattah, Hiba [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Mironov, Gleb G.; Berezovski, Maxim V. [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Department of Chemistry, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada); Moon, Thomas W. [Ottawa-Carleton Institute of Biology, Department of Biology and Centre for Advanced Research in Environmental Genomics, University of Ottawa, Ottawa, Ontario, K1N 6N5 (Canada)

2013-08-15

Exposure to environmental contaminants such as activators of the aryl hydrocarbon receptor (AhR) leads to the induction of defense and detoxification mechanisms. While these mechanisms allow organisms to metabolize and excrete at least some of these environmental contaminants, it has been proposed that these mechanisms lead to significant energetic challenges. This study tests the hypothesis that activation of the AhR by the model agonist β-naphthoflavone (βNF) results in increased energetic costs in rainbow trout (Oncorhynchus mykiss) hepatocytes. To address this hypothesis, we employed traditional biochemical approaches to examine energy allocation and metabolism including the adenylate energy charge (AEC), protein synthesis rates, Na{sup +}/K{sup +}-ATPase activity, and enzyme activities. Moreover, we have used for the first time in a fish cell preparation, metabolic flux analysis (MFA) an in silico approach for the estimation of intracellular metabolic fluxes. Exposure of trout hepatocytes to 1 μM βNF for 48 h did not alter hepatocyte AEC, protein synthesis, or Na{sup +}/K{sup +}-ATPase activity but did lead to sparing of glycogen reserves and changes in activities of alanine aminotransferase and citrate synthase suggesting altered metabolism. Conversely, MFA did not identify altered metabolic fluxes, although we do show that the dynamic metabolism of isolated trout hepatocytes poses a significant challenge for this type of approach which should be considered in future studies. - Highlights: • Energetic costs of AhR activation by βNF was examined in rainbow trout hepatocytes. • Metabolic flux analysis was performed on a fish cell preparation for the first time. • Exposure to βNF led to sparing of glycogen reserves and altered enzyme activities. • Adenylate energy charge was maintained despite temporal changes in metabolism.

Responses to high-fat challenges varying in fat type in subjects with different metabolic risk phenotypes: a randomized trial.

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Susan J van Dijk

Full Text Available The ability of subjects to respond to nutritional challenges can reflect the flexibility of their biological system. Nutritional challenge tests could be used as an indicator of health status but more knowledge on metabolic and immune responses of different subjects to nutritional challenges is needed. The aim of this study was to compare the responses to high-fat challenges varying in fat type in subjects with different metabolic risk phenotypes.In a cross-over design 42 men (age 50-70 y consumed three high-fat shakes containing saturated fat (SFA, monounsaturated fat (MUFA or n-3 polyunsaturated (PUFA. Men were selected on BMI and health status (lean, obese or obese diabetic and phenotyped with MRI for adipose tissue distribution. Before and 2 and 4 h after shake consumption blood was drawn for measurement of expression of metabolic and inflammation-related genes in peripheral blood mononuclear cells (PBMCs, plasma triglycerides (TAG, glucose, insulin, cytokines and ex vivo PBMC immune response capacity. The MUFA and n-3 PUFA challenge, compared to the SFA challenge, induced higher changes in expression of inflammation genes MCP1 and IL1β in PBMCs. Obese and obese diabetic subjects had different PBMC gene expression and metabolic responses to high-fat challenges compared to lean subjects. The MUFA challenge induced the most pronounced TAG response, mainly in obese and obese diabetic subjects.The PBMC gene expression response and metabolic response to high-fat challenges were affected by fat type and metabolic risk phenotype. Based on our results we suggest using a MUFA challenge to reveal differences in response capacity of subjects.ClinicalTrials.gov NCT00977262.

Using a Genome-Scale Metabolic Network Model to Elucidate the Mechanism of Chloroquine Action in Plasmodium falciparum

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2017-03-22

The transcriptome data of P. falciparum obtained under different stress conditions (e.g., drug exposure, genetic mutation , etc.) contain information...Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p. Proc. Natl. Acad

Relationship of metabolic and endocrine parameters to brain glucose metabolism in older adults: do cognitively-normal older adults have a particular metabolic phenotype?

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Nugent, S; Castellano, C A; Bocti, C; Dionne, I; Fulop, T; Cunnane, S C

2016-02-01

Our primary objective in this study was to quantify whole brain and regional cerebral metabolic rates of glucose (CMRg) in young and older adults in order to determine age-normalized reference CMRg values for healthy older adults with normal cognition for age. Our secondary objectives were to--(i) report a broader range of metabolic and endocrine parameters including body fat composition that could form the basis for the concept of a 'metabolic phenotype' in cognitively normal, older adults, and (ii) to assess whether medications commonly used to control blood lipids, blood pressure or thyroxine affect CMRg values in older adults. Cognition assessed by a battery of tests was normal for age and education in both groups. Compared to the young group (25 years old; n = 34), the older group (72 years old; n = 41) had ~14% lower CMRg (μmol/100 g/min) specifically in the frontal cortex, and 18% lower CMRg in the caudate. Lower grey matter volume and cortical thickness was widespread in the older group. These differences in CMRg, grey matter volume and cortical thickness were present in the absence of any known evidence for prodromal Alzheimer's disease (AD). Percent total body fat was positively correlated with CMRg in many brain regions but only in the older group. Before and after controlling for body fat, HOMA2-IR was significantly positively correlated to CMRg in several brain regions in the older group. These data show that compared to a healthy younger adult, the metabolic phenotype of a cognitively-normal 72 year old person includes similar plasma glucose, insulin, cholesterol, triglycerides and TSH, higher hemoglobin A1c and percent body fat, lower CMRg in the superior frontal cortex and caudate, but the same CMRg in the hippocampus and white matter. Age-normalization of cognitive test results is standard practice and we would suggest that regional CMRg in cognitively healthy older adults should also be age-normalized.

Beneficial Autophagic Activities, Mitochondrial Function, and Metabolic Phenotype Adaptations Promoted by High-Intensity Interval Training in a Rat Model

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Fang-Hui Li

2018-05-01

Full Text Available The effects of high-intensity interval (HIIT and moderate-intensity continuous training (MICT on basal autophagy and mitochondrial function in cardiac and skeletal muscle and plasma metabolic phenotypes have not been clearly characterized. Here, we investigated how 10-weeks HIIT and MICT differentially modify basal autophagy and mitochondrial markers in cardiac and skeletal muscle and conducted an untargeted metabolomics study with proton nuclear magnetic resonance (1H NMR spectroscopy and multivariate statistical analysis of plasma metabolic phenotypes. Male Sprague–Dawley rats were separated into three groups: sedentary control (SED, MICT, and HIIT. Rats underwent evaluation of exercise performance, including exercise tolerance and grip strength, and blood lactate levels were measured immediately after an incremental exercise test. Plasma samples were analyzed by 1H NMR. The expression of autophagy and mitochondrial markers and autophagic flux (LC3II/LC3-I ratio in cardiac, rectus femoris, and soleus muscle were analyzed by western blotting. Time to exhaustion and grip strength increased significantly following HIIT compared with that in both SED and MICT groups. Compared with those in the SED group, blood lactate level, and the expression of SDH, COX-IV, and SIRT3 significantly increased in rectus femoris and soleus muscle of both HIIT and MICT groups. Meanwhile, SDH and COX-IV content of cardiac muscle and COX-IV and SIRT3 content of rectus femoris and soleus muscle increased significantly following HIIT compared with that following MICT. The expression of LC3-II, ATG-3, and Beclin-1 and LC3II/LC3-I ratio were significantly increased only in soleus and cardiac muscle following HIIT. These data indicate that HIIT was more effective for improving physical performance and facilitating cardiac and skeletal muscle adaptations that increase mitochondrial function and basal autophagic activities. Moreover, 1H NMR spectroscopy and multivariate

Beneficial Autophagic Activities, Mitochondrial Function, and Metabolic Phenotype Adaptations Promoted by High-Intensity Interval Training in a Rat Model.

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Li, Fang-Hui; Li, Tao; Ai, Jing-Yi; Sun, Lei; Min, Zhu; Duan, Rui; Zhu, Ling; Liu, Yan-Ying; Liu, Timon Cheng-Yi

2018-01-01

The effects of high-intensity interval (HIIT) and moderate-intensity continuous training (MICT) on basal autophagy and mitochondrial function in cardiac and skeletal muscle and plasma metabolic phenotypes have not been clearly characterized. Here, we investigated how 10-weeks HIIT and MICT differentially modify basal autophagy and mitochondrial markers in cardiac and skeletal muscle and conducted an untargeted metabolomics study with proton nuclear magnetic resonance ( 1 H NMR) spectroscopy and multivariate statistical analysis of plasma metabolic phenotypes. Male Sprague-Dawley rats were separated into three groups: sedentary control (SED), MICT, and HIIT. Rats underwent evaluation of exercise performance, including exercise tolerance and grip strength, and blood lactate levels were measured immediately after an incremental exercise test. Plasma samples were analyzed by 1 H NMR. The expression of autophagy and mitochondrial markers and autophagic flux (LC3II/LC3-I ratio) in cardiac, rectus femoris, and soleus muscle were analyzed by western blotting. Time to exhaustion and grip strength increased significantly following HIIT compared with that in both SED and MICT groups. Compared with those in the SED group, blood lactate level, and the expression of SDH, COX-IV, and SIRT3 significantly increased in rectus femoris and soleus muscle of both HIIT and MICT groups. Meanwhile, SDH and COX-IV content of cardiac muscle and COX-IV and SIRT3 content of rectus femoris and soleus muscle increased significantly following HIIT compared with that following MICT. The expression of LC3-II, ATG-3, and Beclin-1 and LC3II/LC3-I ratio were significantly increased only in soleus and cardiac muscle following HIIT. These data indicate that HIIT was more effective for improving physical performance and facilitating cardiac and skeletal muscle adaptations that increase mitochondrial function and basal autophagic activities. Moreover, 1 H NMR spectroscopy and multivariate statistical

Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

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Navid, Ali; Almaas, Eivind

2007-03-01

The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

Metabolic pathway analysis of Scheffersomyces (Pichia) stipitis: effect of oxygen availability on ethanol synthesis and flux distributions.

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Unrean, Pornkamol; Nguyen, Nhung H A

2012-06-01

Elementary mode analysis (EMA) identifies all possible metabolic states of the cell metabolic network. Investigation of these states can provide a detailed insight into the underlying metabolism in the cell. In this study, the flux states of Scheffersomyces (Pichia) stipitis metabolism were examined. It was shown that increasing oxygen levels led to a decrease of ethanol synthesis. This trend was confirmed by experimental evaluation of S. stipitis in glucose-xylose fermentation. The oxygen transfer rate for an optimal ethanol production was 1.8 mmol/l/h, which gave the ethanol yield of 0.40 g/g and the ethanol productivity of 0.25 g/l/h. For a better understanding of the cell's regulatory mechanism in response to oxygenation levels, EMA was used to examine metabolic flux patterns under different oxygen levels. Up- and downregulation of enzymes in the network during the change of culturing condition from oxygen limitation to oxygen sufficiency were identified. The results indicated the flexibility of S. stipitis metabolism to cope with oxygen availability. In addition, relevant genetic targets towards improved ethanol-producing strains under all oxygenation levels were identified. These targeted genes limited the metabolic functionality of the cell to function according to the most efficient ethanol synthesis pathways. The presented approach is promising and can contribute to the development of culture optimization and strain engineers for improved lignocellulosic ethanol production by S. stipitis.

Squeezing Flux Out of Fat

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Gonzalez-Franquesa, Alba; Patti, Mary-Elizabeth

2018-01-01

Merging transcriptomics or metabolomics data remains insufficient for metabolic flux estimation. Ramirez et al. integrate a genome-scale metabolic model with extracellular flux data to predict and validate metabolic differences between white and brown adipose tissue. This method allows both metab...

Evolutionary programming as a platform for in silico metabolic engineering

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Förster Jochen

2005-12-01

Full Text Available Abstract Background Through genetic engineering it is possible to introduce targeted genetic changes and hereby engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, owing to the complexity of metabolic networks, both in terms of structure and regulation, it is often difficult to predict the effects of genetic modifications on the resulting phenotype. Recently genome-scale metabolic models have been compiled for several different microorganisms where structural and stoichiometric complexity is inherently accounted for. New algorithms are being developed by using genome-scale metabolic models that enable identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem, and it is therefore interesting to develop new faster algorithms. Results In this study we report an evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function. We illustrate the proposed method for two important design parameters in industrial fermentations, one linear and other non-linear, by using a genome-scale model of the yeast Saccharomyces cerevisiae. Potential metabolic engineering targets for improved production of succinic acid, glycerol and vanillin are identified and underlying flux changes for the predicted mutants are discussed. Conclusion We show that evolutionary programming enables solving large gene knockout problems in relatively short computational time. The proposed algorithm also allows the optimization of non-linear objective functions or incorporation of non-linear constraints and additionally provides a family of close to optimal solutions. The identified metabolic engineering strategies suggest that non-intuitive genetic modifications span

Stoichiometric Representation of Gene–Protein–Reaction Associations Leverages Constraint-Based Analysis from Reaction to Gene-Level Phenotype Prediction

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Machado, Daniel; Herrgard, Markus; Rocha, Isabel

2016-01-01

only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene...... design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions...

Flux analysis of central metabolic pathways in Geobactermetallireducens during reduction of solubleFe(III)-NTA

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Tang, Yinjie J.; Chakraborty, Romy; Garcia-Martin, Hector; Chu,Jeannie; Hazen, Terry C.; Keasling, Jay D.

2007-01-01

We analyzed the carbon fluxes in the central metabolism ofGeobacter metallireducens strain GS-15 using 13C isotopomer modeling.Acetate labeled in the 1st or 2nd position was the sole carbon source,and Fe-NTA was the sole terminal electron acceptor. The measured labeledacetate uptake rate was 21 mmol/gdw/h in the exponential growth phase.The resulting isotope labeling pattern of amino acids allowed an accuratedetermination of the in vivo global metabolic reaction rates (fluxes)through the central metabolic pathways using a computational isotopomermodel. The tracer experiments showed that G. metallireducens containedcomplete biosynthesis pathways for essential metabolism, and this strainmight also have an unusual isoleucine biosynthesis route (usingacetyl-CoA and pyruvate as the precursors). The model indicated that over90 percent of the acetate was completely oxidized to CO2 via a completetricarboxylic acid (TCA) cycle while reducing iron. Pyruvate carboxylaseand phosphoenolpyruvate carboxykinase were present under theseconditions, but enzymes in the glyoxylate shunt and malic enzyme wereabsent. Gluconeogenesis and the pentose phosphate pathway were mainlyemployed for biosynthesis and accounted for less than 3 percent of totalcarbon consumption. The model also indicated surprisingly highreversibility in the reaction between oxoglutarate and succinate. Thisstep operates close to the thermodynamic equilibrium possibly becausesuccinate is synthesized via a transferase reaction, and the conversionof oxoglutarate to succinate is a rate limiting step for carbonmetabolism. These findings enable a better understanding of therelationship between genome annotation and extant metabolic pathways inG. metallireducens.

Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction. Reprinted from Biotechnology and Bioengineering, Vol. 41, Pp 633-646 (1993).

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Vallino, J J; Stephanopoulos, G

2000-03-20

The two main contributions of this article are the solidification of Corynebacterium glutamicum biochemistry guided by bioreaction network analysis, and the determination of basal metabolic flux distributions during growth and lysine synthesis. Employed methodology makes use of stoichiometrically based mass balances to determine flux distributions in the C. glutamicum metabolic network. Presented are a brief description of the methodology, a thorough literature review of glutamic acid bacteria biochemistry, and specific results obtained through a combination of fermentation studies and analysis-directed intracellular assays. The latter include the findings of the lack of activity of glyoxylate shunt, and that phosphoenolpyruvate carboxylase (PPC) is the only anaplerotic reaction expressed in C. glutamicum cultivated on glucose minimal media. Network simplifications afforded by the above findings facilitated the determination of metabolic flux distributions under a variety of culture conditions and led to the following conclusions. Both the pentose phosphate pathway and PPC support significant fluxes during growth and lysine overproduction, and that flux partitioning at the glucosa-6-phosphate branch point does not appear to limit lysine synthesis. Copyright 1993 John Wiley & Sons, Inc.

Carbon-flux distribution within Streptomyces coelicolor metabolism: a comparison between the actinorhodin-producing strain M145 and its non-producing derivative M1146.

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Fabien Coze

Full Text Available Metabolic Flux Analysis is now viewed as essential to elucidate the metabolic pattern of cells and to design appropriate genetic engineering strategies to improve strain performance and production processes. Here, we investigated carbon flux distribution in two Streptomyces coelicolor A3 (2 strains: the wild type M145 and its derivative mutant M1146, in which gene clusters encoding the four main antibiotic biosynthetic pathways were deleted. Metabolic Flux Analysis and (13C-labeling allowed us to reconstruct a flux map under steady-state conditions for both strains. The mutant strain M1146 showed a higher growth rate, a higher flux through the pentose phosphate pathway and a higher flux through the anaplerotic phosphoenolpyruvate carboxylase. In that strain, glucose uptake and the flux through the Krebs cycle were lower than in M145. The enhanced flux through the pentose phosphate pathway in M1146 is thought to generate NADPH enough to face higher needs for biomass biosynthesis and other processes. In both strains, the production of NADPH was higher than NADPH needs, suggesting a key role for nicotinamide nucleotide transhydrogenase for redox homeostasis. ATP production is also likely to exceed metabolic ATP needs, indicating that ATP consumption for maintenance is substantial.Our results further suggest a possible competition between actinorhodin and triacylglycerol biosynthetic pathways for their common precursor, acetyl-CoA. These findings may be instrumental in developing new strategies exploiting S. coelicolor as a platform for the production of bio-based products of industrial interest.

Metabolic Flux Analysis in Isotope Labeling Experiments Using the Adjoint Approach.

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Mottelet, Stephane; Gaullier, Gil; Sadaka, Georges

2017-01-01

Comprehension of metabolic pathways is considerably enhanced by metabolic flux analysis (MFA-ILE) in isotope labeling experiments. The balance equations are given by hundreds of algebraic (stationary MFA) or ordinary differential equations (nonstationary MFA), and reducing the number of operations is therefore a crucial part of reducing the computation cost. The main bottleneck for deterministic algorithms is the computation of derivatives, particularly for nonstationary MFA. In this article, we explain how the overall identification process may be speeded up by using the adjoint approach to compute the gradient of the residual sum of squares. The proposed approach shows significant improvements in terms of complexity and computation time when it is compared with the usual (direct) approach. Numerical results are obtained for the central metabolic pathways of Escherichia coli and are validated against reference software in the stationary case. The methods and algorithms described in this paper are included in the sysmetab software package distributed under an Open Source license at http://forge.scilab.org/index.php/p/sysmetab/.

Variation in antibiotic-induced microbial recolonization impacts on the host metabolic phenotypes of rats.

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Swann, Jonathan R; Tuohy, Kieran M; Lindfors, Peter; Brown, Duncan T; Gibson, Glenn R; Wilson, Ian D; Sidaway, James; Nicholson, Jeremy K; Holmes, Elaine

2011-08-05

The interaction between the gut microbiota and their mammalian host is known to have far-reaching consequences with respect to metabolism and health. We investigated the effects of eight days of oral antibiotic exposure (penicillin and streptomycin sulfate) on gut microbial composition and host metabolic phenotype in male Han-Wistar rats (n = 6) compared to matched controls. Early recolonization was assessed in a third group exposed to antibiotics for four days followed by four days recovery (n = 6). Fluorescence in situ hybridization analysis of the intestinal contents collected at eight days showed a significant reduction in all bacterial groups measured (control, 10(10.7) cells/g feces; antibiotic-treated, 10(8.4)). Bacterial suppression reduced the excretion of mammalian-microbial urinary cometabolites including hippurate, phenylpropionic acid, phenylacetylglycine and indoxyl-sulfate whereas taurine, glycine, citrate, 2-oxoglutarate, and fumarate excretion was elevated. While total bacterial counts remained notably lower in the recolonized animals (10(9.1) cells/g faeces) compared to the controls, two cage-dependent subgroups emerged with Lactobacillus/Enterococcus probe counts dominant in one subgroup. This dichotomous profile manifested in the metabolic phenotypes with subgroup differences in tricarboxylic acid cycle metabolites and indoxyl-sulfate excretion. Fecal short chain fatty acids were diminished in all treated animals. Antibiotic treatment induced a profound effect on the microbiome structure, which was reflected in the metabotype. Moreover, the recolonization process was sensitive to the microenvironment, which may impact on understanding downstream consequences of antibiotic consumption in human populations.

Updates to a 13C metabolic flux analysis model for evaluating energy metabolism in cultured cerebellar granule neurons from neonatal rats.

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Jekabsons, Mika B; Gebril, Hoda M; Wang, Yan-Hong; Avula, Bharathi; Khan, Ikhlas A

2017-10-01

A hexose phosphate recycling model previously developed to infer fluxes through the major glucose consuming pathways in cultured cerebellar granule neurons (CGNs) from neonatal rats metabolizing [1,2- 13 C 2 ]glucose was revised by considering reverse flux through the non-oxidative pentose phosphate pathway (PPP) and symmetrical succinate oxidation within the tricarboxylic acid (TCA) cycle. The model adjusts three flux ratios to effect 13 C distribution in the hexose, pentose, and triose phosphate pools, and in TCA cycle malate to minimize the error between predicted and measured 13 C labeling in exported lactate (i.e., unlabeled, single-, double-, and triple-labeled; M, M1, M2, and M3, respectively). Inclusion of reverse non-oxidative PPP flux substantially increased the number of calculations but ultimately had relatively minor effects on the labeling of glycolytic metabolites. From the error-minimized solution in which the predicted M-M3 lactate differed by 0.49% from that measured by liquid chromatography-triple quadrupole mass spectrometry, the neurons exhibited negligible forward non-oxidative PPP flux. Thus, no glucose was used by the pentose cycle despite explicit consideration of hexose phosphate recycling. Mitochondria consumed only 16% of glucose while 45% was exported as lactate by aerobic glycolysis. The remaining 39% of glucose was shunted to pentose phosphates presumably for de novo nucleotide synthesis, but the proportion metabolized through the oxidative PPP vs. the reverse non-oxidative PPP could not be determined. The lactate exported as M1 (2.5%) and M3 (1.2%) was attributed to malic enzyme, which was responsible for 7.8% of pyruvate production (vs. 92.2% by glycolysis). The updated model is more broadly applicable to different cell types by considering bi-directional flux through the non-oxidative PPP. Its application to cultured neurons utilizing glucose as the sole exogenous substrate has demonstrated substantial oxygen-independent glucose

Carbon conversion efficiency and central metabolic fluxes in developing sunflower (Helianthus annuus L.) embryos.

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Alonso, Ana P; Goffman, Fernando D; Ohlrogge, John B; Shachar-Hill, Yair

2007-10-01

The efficiency with which developing sunflower embryos convert substrates into seed storage reserves was determined by labeling embryos with [U-(14)C6]glucose or [U-(14)C5]glutamine and measuring their conversion to CO2, oil, protein and other biomass compounds. The average carbon conversion efficiency was 50%, which contrasts with a value of over 80% previously observed in Brassica napus embryos (Goffman et al., 2005), in which light and the RuBisCO bypass pathway allow more efficient conversion of hexose to oil. Labeling levels after incubating sunflower embryos with [U-(14)C4]malate indicated that some carbon from malate enters the plastidic compartment and contributes to oil synthesis. To test this and to map the underlying pattern of metabolic fluxes, separate experiments were carried out in which embryos were labeled to isotopic steady state using [1-(13)C1]glucose, [2-(13)C1]glucose, or [U-(13)C5]glutamine. The resultant labeling in sugars, starch, fatty acids and amino acids was analyzed by NMR and GC-MS. The fluxes through intermediary metabolism were then quantified by computer-aided modeling. The resulting flux map accounted well for the labeling data, was in good agreement with the observed carbon efficiency, and was further validated by testing for agreement with gas exchange measurements. The map shows that the influx of malate into oil is low and that flux through futile cycles (wasting ATP) is low, which contrasts with the high rates previously determined for growing root tips and heterotrophic cell cultures.

[Improving industrial microbial stress resistance by metabolic engineering: a review].

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Fu, Ruiyan; Li, Yin

2010-09-01

Metabolic engineering is a technologic platform for industrial strain improvement and aims not only at modifying microbial metabolic fluxes, but also improving the physiological performance of industrial microbes. Microbes will meet multiple stresses in industrial processes. Consequently, elicited gene responses might result in a decrease in overall cell fitness and the efficiency of biotransformation. Thus, it is crucial to develop robust and productive microbial strains that can be integrated into industrial-scale bioprocesses. In this review, we focus on the progress of these novel methods and strategies for engineering stress-tolerance phenotypes referring to rational metabolic engineering and inverse metabolic engineering in recent years. In addition, we also address problems existing in this area and future research needs of microbial physiological functionality engineering.

Impact of CYP2C19 phenotypes on escitalopram metabolism and an evaluation of pupillometry as a serotonergic biomarker

DEFF Research Database (Denmark)

Noehr-Jensen, L; Zwisler, S; Larsen, F

2009-01-01

PURPOSE: To investigate the impact of cytochrome P450 2C19 (CYP2C19) phenotypes on escitalopram metabolism and to evaluate pupillometry as a serotonergic biomarker. METHODS: This was a double-blind, crossover design study with single and multiple doses of 10 mg escitalopram and placebo in panels...... of CYP2C19 extensive (EM) and poor metabolisers (PM). Pupillometry was measured by a NeurOptics Pupillometer-PLR. RESULTS: Five PM and eight EM completed the study. The CYP2C19 phenotype significantly affected the metabolism of escitalopram. The area under the time-plasma concentration curve (AUC(0......-24)) was 1.8-fold higher in PM than in EM after both single and multiple doses. Escitalopram treatment did not affect the maximum pupil size, but it did statistically significantly decrease the relative amplitude of the pupil light reflex compared to the placebo; this effect was equal in both phenotype...

(13)C-metabolic flux analysis of lipid accumulation in the oleaginous fungus Mucor circinelloides.

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Zhao, Lina; Zhang, Huaiyuan; Wang, Liping; Chen, Haiqin; Chen, Yong Q; Chen, Wei; Song, Yuanda

2015-12-01

The oleaginous fungus Mucor circinelloides is of industrial interest because it can produce high levels of polyunsaturated fatty acid γ-linolenic acid. M. circinelloides CBS 277.49 is able to accumulate less than 15% of cell dry weight as lipids, while M. circinelloides WJ11 can accumulate lipid up to 36%. In order to better understand the mechanisms behind the differential lipid accumulation in these two strains, tracer experiments with (13)C-glucose were performed with the growth of M. circinelloides and subsequent gas chromatography-mass spectrometric detection of (13)C-patterns in proteinogenic amino acids was carried out to identify the metabolic network topology and estimate intracellular fluxes. Our results showed that the high oleaginous strain WJ11 had higher flux of pentose phosphate pathway and malic enzyme, lower flux in tricarboxylic acid cycle, higher flux in glyoxylate cycle and ATP: citrate lyase, together, it might provide more NADPH and substrate acetyl-CoA for fatty acid synthesis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Flux Balance Analysis Inspired Bioprocess Upgrading for Lycopene Production by a Metabolically Engineered Strain of Yarrowia lipolytica

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Komi Nambou

2015-12-01

Full Text Available Genome-scale metabolic models embody a significant advantage of systems biology since their applications as metabolic flux simulation models enable predictions for the production of industrially-interesting metabolites. The biotechnological production of lycopene from Yarrowia lipolytica is an emerging scope that has not been fully scrutinized, especially for what concerns cultivation conditions of newly generated engineered strains. In this study, by combining flux balance analysis (FBA and Plackett-Burman design, we screened chemicals for lycopene production from a metabolically engineered strain of Y. lipolytica. Lycopene concentrations of 126 and 242 mg/L were achieved correspondingly from the FBA-independent and the FBA-assisted designed media in fed-batch cultivation mode. Transcriptional studies revealed upregulations of heterologous genes in media designed according to FBA, thus implying the efficiency of model predictions. Our study will potentially support upgraded lycopene and other terpenoids production from existing or prospect bioengineered strains of Y. lipolytica and/or closely related yeast species.

Reciprocal Effects on Neurocognitive and Metabolic Phenotypes in Mouse Models of 16p11.2 Deletion and Duplication Syndromes.

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Thomas Arbogast

2016-02-01

Full Text Available The 16p11.2 600 kb BP4-BP5 deletion and duplication syndromes have been associated with developmental delay; autism spectrum disorders; and reciprocal effects on the body mass index, head circumference and brain volumes. Here, we explored these relationships using novel engineered mouse models carrying a deletion (Del/+ or a duplication (Dup/+ of the Sult1a1-Spn region homologous to the human 16p11.2 BP4-BP5 locus. On a C57BL/6N inbred genetic background, Del/+ mice exhibited reduced weight and impaired adipogenesis, hyperactivity, repetitive behaviors, and recognition memory deficits. In contrast, Dup/+ mice showed largely opposite phenotypes. On a F1 C57BL/6N × C3B hybrid genetic background, we also observed alterations in social interaction in the Del/+ and the Dup/+ animals, with other robust phenotypes affecting recognition memory and weight. To explore the dosage effect of the 16p11.2 genes on metabolism, Del/+ and Dup/+ models were challenged with high fat and high sugar diet, which revealed opposite energy imbalance. Transcriptomic analysis revealed that the majority of the genes located in the Sult1a1-Spn region were sensitive to dosage with a major effect on several pathways associated with neurocognitive and metabolic phenotypes. Whereas the behavioral consequence of the 16p11 region genetic dosage was similar in mice and humans with activity and memory alterations, the metabolic defects were opposite: adult Del/+ mice are lean in comparison to the human obese phenotype and the Dup/+ mice are overweight in comparison to the human underweight phenotype. Together, these data indicate that the dosage imbalance at the 16p11.2 locus perturbs the expression of modifiers outside the CNV that can modulate the penetrance, expressivity and direction of effects in both humans and mice.

Community metabolism and air-sea CO[sub 2] fluxes in a coral reef ecosystem (Moorea, French Polynesia)

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Gattuso, J P; Pichon, M; Delesalle, B; Frankignoulle, M [Observatory of European Oceanology (Monaco)

1993-06-01

Community metabolism (primary production, respiration and calcification) and air-sea CO[sub 2] fluxes of the 'Tiahura barrier reef' (Moorea, French Polynesia) were investigated in November and December 1991. Gross production and respiration were respectively 640.2 to 753 and 590.4 to 641.5 mmol (O[sub 2] or CO[sub 2]) m[sup 2] d[sup -1] (7.7 to 9.0 and 7.1 to 7.7 g C m)[sup 2] d[sup -1] and the reef displayed a slightly negative excess (net) production. The contribution of planktonic primary production to reef metabolism was negligible (0.15% of total gross production). Net calcification was positive both during the day and at night; its daily value was 243 mmol CaCO[sub 3] m[sup 2] d[sup -1] (24.3 g CaCO)[sub 3] m[sup -2] d[sup -1]. Reef metabolism decreased seawater total CO[sub 2] by 433.3 mmol m[sup 2] d[sup -1]. The air-sea CO[sub 2] fluxes were close to zero in the ocean but displayed a strong daily pattern at the reef front and the back reef. Fluxes were positive (CO[sub 2] evasion) at night, decreased as irradiance increased and were negative during the day (CO[sub 2] invasion). Integration of the fluxes measured during a 24 h experiment at the back reef showed that the reef was a source of CO[sub 2] to the atmosphere (1.5 mmol m[sup 2] d[sup -1]).

A Novel Letrozole Model Recapitulates Both the Reproductive and Metabolic Phenotypes of Polycystic Ovary Syndrome in Female Mice1

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Kauffman, Alexander S.; Thackray, Varykina G.; Ryan, Genevieve E.; Tolson, Kristen P.; Glidewell-Kenney, Christine A.; Semaan, Sheila J.; Poling, Matthew C.; Iwata, Nahoko; Breen, Kellie M.; Duleba, Antoni J.; Stener-Victorin, Elisabet; Shimasaki, Shunichi; Webster, Nicholas J.; Mellon, Pamela L.

2015-01-01

Polycystic ovary syndrome (PCOS) pathophysiology is poorly understood, due partly to lack of PCOS animal models fully recapitulating this complex disorder. Recently, a PCOS rat model using letrozole (LET), a nonsteroidal aromatase inhibitor, mimicked multiple PCOS phenotypes, including metabolic features absent in other models. Given the advantages of using genetic and transgenic mouse models, we investigated whether LET produces a similar PCOS phenotype in mice. Pubertal female C57BL/6N mice were treated for 5 wk with LET, which resulted in increased serum testosterone and normal diestrus levels of estradiol, similar to the hyperandrogenemia and follicular phase estrogen levels of PCOS women. As in PCOS, ovaries from LET mice were larger, polycystic, and lacked corpora lutea versus controls. Most LET females were acyclic, and all were infertile. LET females displayed elevated serum LH levels and higher Lhb mRNA in the pituitary. In contrast, serum FSH and Fshb were significantly reduced in LET females, demonstrating differential effects on gonadotropins, as in PCOS. Within the ovary, LET females had higher Cyp17, Cyp19, and Fsh receptor mRNA expression. In the hypothalamus, LET females had higher kisspeptin receptor mRNA expression but lower progesterone receptor mRNA levels. LET females also gained more weight than controls, had increased abdominal adiposity and adipocyte size, elevated adipose inflammatory mRNA levels, and impaired glucose tolerance, mirroring the metabolic phenotype in PCOS women. This is the first report of a LET paradigm in mice that recapitulates both reproductive and metabolic PCOS phenotypes and will be useful to genetically probe the PCOS condition. PMID:26203175

Magnetic Resonance Spectroscopic Imaging of Tumor Metabolic Markers for Cancer Diagnosis, Metabolic Phenotyping, and Characterization of Tumor Microenvironment

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Qiuhong He

2004-01-01

Full Text Available Cancer cells display heterogeneous genetic characteristics, depending on the tumor dynamic microenvironment. Abnormal tumor vasculature and poor tissue oxygenation generate a fraction of hypoxic tumor cells that have selective advantages in metastasis and invasion and often resist chemo- and radiation therapies. The genetic alterations acquired by tumors modify their biochemical pathways, which results in abnormal tumor metabolism. An elevation in glycolysis known as the “Warburg effect” and changes in lipid synthesis and oxidation occur. Magnetic resonance spectroscopy (MRS has been used to study tumor metabolism in preclinical animal models and in clinical research on human breast, brain, and prostate cancers. This technique can identify specific genetic and metabolic changes that occur in malignant tumors. Therefore, the metabolic markers, detectable by MRS, not only provide information on biochemical changes but also define different metabolic tumor phenotypes. When combined with the contrast-enhanced Magnetic Resonance Imaging (MRI, which has a high sensitivity for cancer diagnosis, in vivo magnetic resonance spectroscopic imaging (MRSI improves the diagnostic specificity of malignant human cancers and is becoming an important clinical tool for cancer management and care. This article reviews the MRSI techniques as molecular imaging methods to detect and quantify metabolic changes in various tumor tissue types, especially in extracranial tumor tissues that contain high concentrations of fat. MRI/MRSI methods have been used to characterize tumor microenvironments in terms of blood volume and vessel permeability. Measurements of tissue oxygenation and glycolytic rates by MRS also are described to illustrate the capability of the MR technology in probing molecular information non-invasively in tumor tissues and its important potential for studying molecular mechanisms of human cancers in physiological conditions.

Ex vivo hyperpolarized MR spectroscopy on isolated renal tubular cells: A novel technique for cell energy phenotyping.

Science.gov (United States)

Juul, Troels; Palm, Fredrik; Nielsen, Per Mose; Bertelsen, Lotte Bonde; Laustsen, Christoffer

2017-08-01

It has been demonstrated that hyperpolarized 13 C MR is a useful tool to study cultured cells. However, cells in culture can alter phenotype, which raises concerns regarding the in vivo significance of such findings. Here we investigate if metabolic phenotyping using hyperpolarized 13 C MR is suitable for cells isolated from kidney tissue, without prior cell culture. Isolation of tubular cells from freshly excised kidney tissue and treatment with either ouabain or antimycin A was investigated with hyperpolarized MR spectroscopy on a 9.4 Tesla preclinical imaging system. Isolation of tubular cells from less than 2 g of kidney tissue generally resulted in more than 10 million live tubular cells. This amount of cells was enough to yield robust signals from the conversion of 13 C-pyruvate to lactate, bicarbonate and alanine, demonstrating that metabolic flux by means of both anaerobic and aerobic pathways can be quantified using this technique. Ex vivo metabolic phenotyping using hyperpolarized 13 C MR in a preclinical system is a useful technique to study energy metabolism in freshly isolated renal tubular cells. This technique has the potential to advance our understanding of both normal cell physiology as well as pathological processes contributing to kidney disease. Magn Reson Med 78:457-461, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Early metabolic response using FDG PET/CT and molecular phenotypes of breast cancer treated with neoadjuvant chemotherapy

International Nuclear Information System (INIS)

Keam, Bhumsuk; Moon, Woo Kyung; Kim, Tae-You; Park, In Ae; Noh, Dong-Young; Chung, June-Key; Bang, Yung-Jue; Im, Seock-Ah; Koh, Youngil; Han, Sae-Won; Oh, Do-Youn; Cho, Nariya; Kim, Jee Hyun; Han, Wonshik; Kang, Keon Wook

2011-01-01

This study was aimed 1) to investigate the predictive value of FDG PET/CT (fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography) for histopathologic response and 2) to explore the results of FDG PET/CT by molecular phenotypes of breast cancer patients who received neoadjuvant chemotherapy. Seventy-eight stage II or III breast cancer patients who received neoadjuvant docetaxel/doxorubicin chemotherapy were enrolled in this study. FDG PET/CTs were acquired before chemotherapy and after the first cycle of chemotherapy for evaluating early metabolic response. The mean pre- and post-chemotherapy standard uptake value (SUV) were 7.5 and 3.9, respectively. The early metabolic response provided by FDG PET/CT after one cycle of neoadjuvant chemotherapy was correlated with the histopathologic response after completion of neoadjuvant chemotherapy (P = 0.002). Sensitivity and negative predictive value were 85.7% and 95.1%, respectively. The estrogen receptor negative phenotype had a higher pre-chemotherapy SUV (8.6 vs. 6.4, P = 0.047) and percent change in SUV (48% vs. 30%, P = 0.038). In triple negative breast cancer (TNBC), the pre-chemotherapy SUV was higher than in non-TNBC (9.8 vs. 6.4, P = 0.008). The early metabolic response using FDG PET/CT could have a predictive value for the assessment of histopathologic non-response of stage II/III breast cancer treated with neoadjuvant chemotherapy. Our findings suggest that the initial SUV and the decline in SUV differed based on the molecular phenotype. ClinicalTrials.gov: http://www.clinicaltrials.gov/ct2/show/NCT01396655

Strategy of metabolic phenotype modulation in Portunus trituberculatus exposed to low salinity.

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Ye, Yangfang; An, Yanpeng; Li, Ronghua; Mu, Changkao; Wang, Chunlin

2014-04-16

Extreme low salinity influences normal crab growth, morphogenesis, and production. Some individuals of swimming crab Portunus trituberculatus have, however, an inherent ability to adapt to such a salinity fluctuation. This study investigated the dynamic metabolite alterations of two P. trituberculatus strains, namely, a wild one and a screened (low-salinity tolerant) one in response to low-salinity challenge by combined use of NMR spectroscopy and high-throughput data analysis. The dominant metabolites in crab muscle were found to comprise amino acids, sugars, carboxylic acids, betaine, trimethylamine-N-oxide, 2-pyridinemethanol, trigonelline, and nucleotides. These results further showed that the strategy of metabolic modulation of P. trituberculatus after low-salinity stimulus includes osmotic rebalancing, enhanced gluconeogenesis from amino acids, and energy accumulation. These metabolic adaptations were manifested in the accumulation of trimethylamine-N-oxide, ATP, 2-pyridinemethanol, and trigonelline and in the depletion of the amino acid pool as well as in the fluctuation of inosine levels. This lends support to the fact that the low-salinity training accelerates the responses of crabs to low-salinity stress. These findings provide a comprehensive insight into the mechanisms of metabolic modulation in P. trituberculatus in response to low salinity. This work highlights the approach of NMR-based metabonomics in conjunction with multivariate data analysis and univariate data analysis in understanding the strategy of metabolic phenotype modulation against stressors.

Random sampling of elementary flux modes in large-scale metabolic networks.

Science.gov (United States)

Machado, Daniel; Soons, Zita; Patil, Kiran Raosaheb; Ferreira, Eugénio C; Rocha, Isabel

2012-09-15

The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set. Our algorithm is an adaptation of the canonical basis approach, where we add an additional filtering step which, at each iteration, selects a random subset of the new combinations of modes. In order to obtain an unbiased sample, all candidates are assigned the same probability of getting selected. This approach avoids the exponential growth of the number of modes during computation, thus generating a random sample of the complete set of EMs within reasonable time. We generated samples of different sizes for a metabolic network of Escherichia coli, and observed that they preserve several properties of the full EM set. It is also shown that EM sampling can be used for rational strain design. A well distributed sample, that is representative of the complete set of EMs, should be suitable to most EM-based methods for analysis and optimization of metabolic networks. Source code for a cross-platform implementation in Python is freely available at http://code.google.com/p/emsampler. dmachado@deb.uminho.pt Supplementary data are available at Bioinformatics online.

Genealogy profiling through strain improvement by using metabolic network analysis: metabolic flux genealogy of several generations of lysine-producing corynebacteria.

Science.gov (United States)

Wittmann, Christoph; Heinzle, Elmar

2002-12-01

A comprehensive approach of metabolite balancing, (13)C tracer studies, gas chromatography-mass spectrometry, matrix-assisted laser desorption ionization-time of flight mass spectrometry, and isotopomer modeling was applied for comparative metabolic network analysis of a genealogy of five successive generations of lysine-producing Corynebacterium glutamicum. The five strains examined (C. glutamicum ATCC 13032, 13287, 21253, 21526, and 21543) were previously obtained by random mutagenesis and selection. Throughout the genealogy, the lysine yield in batch cultures increased markedly from 1.2 to 24.9% relative to the glucose uptake flux. Strain optimization was accompanied by significant changes in intracellular flux distributions. The relative pentose phosphate pathway (PPP) flux successively increased, clearly corresponding to the product yield. Moreover, the anaplerotic net flux increased almost twofold as a consequence of concerted regulation of C(3) carboxylation and C(4) decarboxylation fluxes to cover the increased demand for lysine formation; thus, the overall increase was a consequence of concerted regulation of C(3) carboxylation and C(4) decarboxylation fluxes. The relative flux through isocitrate dehydrogenase dropped from 82.7% in the wild type to 59.9% in the lysine-producing mutants. In contrast to the NADPH demand, which increased from 109 to 172% due to the increasing lysine yield, the overall NADPH supply remained constant between 185 and 196%, resulting in a decrease in the apparent NADPH excess through strain optimization. Extrapolated to industrial lysine producers, the NADPH supply might become a limiting factor. The relative contributions of PPP and the tricarboxylic acid cycle to NADPH generation changed markedly, indicating that C. glutamicum is able to maintain a constant supply of NADPH under completely different flux conditions. Statistical analysis by a Monte Carlo approach revealed high precision for the estimated fluxes, underlining the

Understanding alternative fluxes/effluxes through comparative metabolic pathway analysis of phylum actinobacteria using a simplified approach.

Science.gov (United States)

Verma, Mansi; Lal, Devi; Saxena, Anjali; Anand, Shailly; Kaur, Jasvinder; Kaur, Jaspreet; Lal, Rup

2013-12-01

Actinobacteria are known for their diverse metabolism and physiology. Some are dreadful human pathogens whereas some constitute the natural flora for human gut. Therefore, the understanding of metabolic pathways is a key feature for targeting the pathogenic bacteria without disturbing the symbiotic ones. A big challenge faced today is multiple drug resistance by Mycobacterium and other pathogens that utilize alternative fluxes/effluxes. With the availability of genome sequence, it is now feasible to conduct the comparative in silico analysis. Here we present a simplified approach to compare metabolic pathways so that the species specific enzyme may be traced and engineered for future therapeutics. The analyses of four key carbohydrate metabolic pathways, i.e., glycolysis, pyruvate metabolism, tri carboxylic acid cycle and pentose phosphate pathway suggest the presence of alternative fluxes. It was found that the upper pathway of glycolysis was highly variable in the actinobacterial genomes whereas lower glycolytic pathway was highly conserved. Likewise, pentose phosphate pathway was well conserved in contradiction to TCA cycle, which was found to be incomplete in majority of actinobacteria. The clustering based on presence and absence of genes of these metabolic pathways clearly revealed that members of different genera shared identical pathways and, therefore, provided an easy method to identify the metabolic similarities/differences between pathogenic and symbiotic organisms. The analyses could identify isoenzymes and some key enzymes that were found to be missing in some pathogenic actinobacteria. The present work defines a simple approach to explore the effluxes in four metabolic pathways within the phylum actinobacteria. The analysis clearly reflects that actinobacteria exhibit diverse routes for metabolizing substrates. The pathway comparison can help in finding the enzymes that can be used as drug targets for pathogens without effecting symbiotic organisms

A Nested Case-Control Study of Metabolically Defined Body Size Phenotypes and Risk of Colorectal Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC.

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Neil Murphy

2016-04-01

Full Text Available Obesity is positively associated with colorectal cancer. Recently, body size subtypes categorised by the prevalence of hyperinsulinaemia have been defined, and metabolically healthy overweight/obese individuals (without hyperinsulinaemia have been suggested to be at lower risk of cardiovascular disease than their metabolically unhealthy (hyperinsulinaemic overweight/obese counterparts. Whether similarly variable relationships exist for metabolically defined body size phenotypes and colorectal cancer risk is unknown.The association of metabolically defined body size phenotypes with colorectal cancer was investigated in a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC study. Metabolic health/body size phenotypes were defined according to hyperinsulinaemia status using serum concentrations of C-peptide, a marker of insulin secretion. A total of 737 incident colorectal cancer cases and 737 matched controls were divided into tertiles based on the distribution of C-peptide concentration amongst the control population, and participants were classified as metabolically healthy if below the first tertile of C-peptide and metabolically unhealthy if above the first tertile. These metabolic health definitions were then combined with body mass index (BMI measurements to create four metabolic health/body size phenotype categories: (1 metabolically healthy/normal weight (BMI < 25 kg/m2, (2 metabolically healthy/overweight (BMI ≥ 25 kg/m2, (3 metabolically unhealthy/normal weight (BMI < 25 kg/m2, and (4 metabolically unhealthy/overweight (BMI ≥ 25 kg/m2. Additionally, in separate models, waist circumference measurements (using the International Diabetes Federation cut-points [≥80 cm for women and ≥94 cm for men] were used (instead of BMI to create the four metabolic health/body size phenotype categories. Statistical tests used in the analysis were all two-sided, and a p-value of <0.05 was

Understanding the adaptive growth strategy of Lactobacillus plantarum by in silico optimisation.

NARCIS (Netherlands)

Teusink, B.; Wiersma, A.; Jacobs, L.; Notebaart, R.A.; Smid, E.J.

2009-01-01

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as

Understanding the Adaptive Growth Strategy of Lactobacillus plantarum by In Silico Optimisation

NARCIS (Netherlands)

Teusink, B.; Wiersma, A.; Jacobs, L.; Notebaart, R.A.; Smid, E.J.

2009-01-01

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as

Metabolic Plasticity of Metastatic Breast Cancer Cells: Adaptation to Changes in the Microenvironment

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Rui V. Simões

2015-08-01

Full Text Available Cancer cells adapt their metabolism during tumorigenesis. We studied two isogenic breast cancer cells lines (highly metastatic 4T1; nonmetastatic 67NR to identify differences in their glucose and glutamine metabolism in response to metabolic and environmental stress. Dynamic magnetic resonance spectroscopy of 13C-isotopomers showed that 4T1 cells have higher glycolytic and tricarboxylic acid (TCA cycle flux than 67NR cells and readily switch between glycolysis and oxidative phosphorylation (OXPHOS in response to different extracellular environments. OXPHOS activity increased with metastatic potential in isogenic cell lines derived from the same primary breast cancer: 4T1 > 4T07 and 168FARN (local micrometastasis only > 67NR. We observed a restricted TCA cycle flux at the succinate dehydrogenase step in 67NR cells (but not in 4T1 cells, leading to succinate accumulation and hindering OXPHOS. In the four isogenic cell lines, environmental stresses modulated succinate dehydrogenase subunit A expression according to metastatic potential. Moreover, glucose-derived lactate production was more glutamine dependent in cell lines with higher metastatic potential. These studies show clear differences in TCA cycle metabolism between 4T1 and 67NR breast cancer cells. They indicate that metastases-forming 4T1 cells are more adept at adjusting their metabolism in response to environmental stress than isogenic, nonmetastatic 67NR cells. We suggest that the metabolic plasticity and adaptability are more important to the metastatic breast cancer phenotype than rapid cell proliferation alone, which could 1 provide a new biomarker for early detection of this phenotype, possibly at the time of diagnosis, and 2 lead to new treatment strategies of metastatic breast cancer by targeting mitochondrial metabolism.

Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

Science.gov (United States)

Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

2016-05-01

We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Phenotypic flexibility of traits related to energy acquisition in mice divergently selected for basal metabolic rate (BMR).

Science.gov (United States)

Ksiazek, Aneta; Czerniecki, Jan; Konarzewski, Marek

2009-03-01

Theoretical considerations suggest that one of the main factors determining phenotypic flexibility of the digestive system is the size (mass) of internal organs. To test this, we used mice from two lines selected for high and low levels of basal metabolic rate (BMR). Mice with higher BMRs also have larger internal organs and higher daily food consumption (C) under non-stressful conditions. We exposed animals from both lines to a sudden cold exposure by transferring them (without prior acclimation) from an ambient temperature of 23 degrees C to 5 degrees C. Cold exposure elicited a twofold increase in C and a 25% reduction of apparent digestive efficiency. For the same body mass-corrected C, small intestine, kidneys, heart and liver of cold-exposed low-BMR mice were smaller than those of the high-BMR line. Therefore, the internal organs of low-BMR animals were burdened with substantially higher metabolic loads (defined as C or digestible food intake per total mass of a particular organ). The mass-specific activity of citrate synthase (CS) in the liver and kidneys (but not heart) was also lower in the low-BMR mice. The magnitude of phenotypic flexibility of internal organ size and CS activity was strictly proportional to the organ mass (in the case of kidneys and liver, also mass-specific CS activity) prior to an increased energy demand. Thus, phenotypic flexibility had additive rather than multiplicative dynamics. Our results also suggest that variation in BMR positively correlates with the magnitude of an immediate spare capacity that fuels the initial response of internal organs to a sudden metabolic stress.

Metabolic flux analysis of the halophilic archaeon Haladaptatus paucihalophilus.

Science.gov (United States)

Liu, Guangxiu; Zhang, Manxiao; Mo, Tianlu; He, Lian; Zhang, Wei; Yu, Yi; Zhang, Qi; Ding, Wei

2015-11-27

This work reports the (13)C-assisted metabolic flux analysis of Haladaptatus paucihalophilus, a halophilic archaeon possessing an intriguing osmoadaption mechanism. We showed that the carbon flow is through the oxidative tricarboxylic acid (TCA) cycle whereas the reductive TCA cycle is not operative in H. paucihalophilus. In addition, both threonine and the citramalate pathways contribute to isoleucine biosynthesis, whereas lysine is synthesized through the diaminopimelate pathway and not through the α-aminoadipate pathway. Unexpected, the labeling patterns of glycine from the cells grown on [1-(13)C]pyruvate and [2-(13)C]pyruvate suggest that, unlike all the organisms investigated so far, in which glycine is produced exclusively from the serine hydroxymethyltransferase (SHMT) pathway, glycine biosynthesis in H. paucihalophilus involves different pathways including SHMT, threonine aldolase (TA) and the reverse reaction of glycine cleavage system (GCS), demonstrating for the first time that other pathways instead of SHMT can also make a significant contribution to the cellular glycine pool. Transcriptional analysis confirmed that both TA and GCS genes were transcribed in H. paucihalophilus, and the transcriptional level is independent of salt concentrations in the culture media. This study expands our understanding of amino acid biosynthesis and provides valuable insights into the metabolism of halophilic archaea. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of phenotypes in heterocyclic aromatic amine (HCA) metabolism-related genes on the association of HCA intake with the risk of colorectal adenomas.

Science.gov (United States)

Barbir, Aline; Linseisen, Jakob; Hermann, Silke; Kaaks, Rudolf; Teucher, Birgit; Eichholzer, Monika; Rohrmann, Sabine

2012-09-01

Heterocyclic aromatic amines (HCA), formed by high-temperature cooking of meat, are well-known risk factors for colorectal cancer (CRC). Enzymes metabolizing HCAs may influence the risk of CRC depending on the enzyme activity level. We aimed to assess effect modification by polymorphisms in the HCA-metabolizing genes on the association of HCA intake with colorectal adenoma (CRA) risk, which are precursors of CRC. A case-control study nested in the EPIC-Heidelberg cohort was conducted. Between 1994 and 2005, 413 adenoma cases were identified and 796 controls were matched to cases. Genotypes were determined and used to predict phenotypes (i.e., enzyme activities). Odds ratios (OR) and corresponding 95 % confidence intervals (CI) were calculated by logistic regression analysis. CRA risk was positively associated with PhIP, MeIQx, and DiMeIQx (p trend = 0.006, 0.022, and 0.045, respectively) intake. SULT1A1 phenotypes modified the effect of MeIQx on CRA risk (p (Interaction) > 0.01) such that the association of MeIQx intake with CRA was stronger for slow than for normal phenotypes. Other modifying effects by phenotypes did not reach statistical significance. HCA intake is positively associated with CRA risk, regardless of phenotypes involved in the metabolizing process. Due to the number of comparisons made in the analysis, the modifying effect of SULT1A1 on the association of HCA intake with CRA risk may be due to chance.

Revealing differences in metabolic flux distributions between a mutant strain and its parent strain Gluconacetobacter xylinus CGMCC 2955.

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Cheng Zhong

Full Text Available A better understanding of metabolic fluxes is important for manipulating microbial metabolism toward desired end products, or away from undesirable by-products. A mutant strain, Gluconacetobacter xylinus AX2-16, was obtained by combined chemical mutation of the parent strain (G. xylinus CGMCC 2955 using DEC (diethyl sulfate and LiCl. The highest bacterial cellulose production for this mutant was obtained at about 11.75 g/L, which was an increase of 62% compared with that by the parent strain. In contrast, gluconic acid (the main byproduct concentration was only 5.71 g/L for mutant strain, which was 55.7% lower than that of parent strain. Metabolic flux analysis indicated that 40.1% of the carbon source was transformed to bacterial cellulose in mutant strain, compared with 24.2% for parent strain. Only 32.7% and 4.0% of the carbon source were converted into gluconic acid and acetic acid in mutant strain, compared with 58.5% and 9.5% of that in parent strain. In addition, a higher flux of tricarboxylic acid (TCA cycle was obtained in mutant strain (57.0% compared with parent strain (17.0%. It was also indicated from the flux analysis that more ATP was produced in mutant strain from pentose phosphate pathway (PPP and TCA cycle. The enzymatic activity of succinate dehydrogenase (SDH, which is one of the key enzymes in TCA cycle, was 1.65-fold higher in mutant strain than that in parent strain at the end of culture. It was further validated by the measurement of ATPase that 3.53-6.41 fold higher enzymatic activity was obtained from mutant strain compared with parent strain.

Amyloid-beta aggregates cause alterations of astrocytic metabolic phenotype: impact on neuronal viability.

Science.gov (United States)

Allaman, Igor; Gavillet, Mathilde; Bélanger, Mireille; Laroche, Thierry; Viertl, David; Lashuel, Hilal A; Magistretti, Pierre J

2010-03-03

Amyloid-beta (Abeta) peptides play a key role in the pathogenesis of Alzheimer's disease and exert various toxic effects on neurons; however, relatively little is known about their influence on glial cells. Astrocytes play a pivotal role in brain homeostasis, contributing to the regulation of local energy metabolism and oxidative stress defense, two aspects of importance for neuronal viability and function. In the present study, we explored the effects of Abeta peptides on glucose metabolism in cultured astrocytes. Following Abeta(25-35) exposure, we observed an increase in glucose uptake and its various metabolic fates, i.e., glycolysis (coupled to lactate release), tricarboxylic acid cycle, pentose phosphate pathway, and incorporation into glycogen. Abeta increased hydrogen peroxide production as well as glutathione release into the extracellular space without affecting intracellular glutathione content. A causal link between the effects of Abeta on glucose metabolism and its aggregation and internalization into astrocytes through binding to members of the class A scavenger receptor family could be demonstrated. Using astrocyte-neuron cocultures, we observed that the overall modifications of astrocyte metabolism induced by Abeta impair neuronal viability. The effects of the Abeta(25-35) fragment were reproduced by Abeta(1-42) but not by Abeta(1-40). Finally, the phosphoinositide 3-kinase (PI3-kinase) pathway appears to be crucial in these events since both the changes in glucose utilization and the decrease in neuronal viability are prevented by LY294002, a PI3-kinase inhibitor. This set of observations indicates that Abeta aggregation and internalization into astrocytes profoundly alter their metabolic phenotype with deleterious consequences for neuronal viability.

Metabolic flux profiling of MDCK cells during growth and canine adenovirus vector production

OpenAIRE

Nuno Carinhas; Daniel A. M. Pais; Alexey Koshkin; Paulo Fernandes; Ana S. Coroadinha; Manuel J. T. Carrondo; Paula M. Alves; Ana P. Teixeira

2016-01-01

Canine adenovirus vector type 2 (CAV2) represents an alternative to human adenovirus vectors for certain gene therapy applications, particularly neurodegenerative diseases. However, more efficient production processes, assisted by a greater understanding of the effect of infection on producer cells, are required. Combining [1,2-13C]glucose and [U-13C]glutamine, we apply for the first time 13C-Metabolic flux analysis (13C-MFA) to study E1-transformed Madin-Darby Canine Kidney (MDCK) cells meta...

OptFlux: an open-source software platform for in silico metabolic engineering

DEFF Research Database (Denmark)

Rocha, I.; Maia, P.; Evangelista, P.

2010-01-01

to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications. Results: OptFlux is an open-source and modular...... available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community. Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network...

Mouse breast cancer model-dependent changes in metabolic syndrome-associated phenotypes caused by maternal dioxin exposure and dietary fat

Science.gov (United States)

La Merrill, Michele; Baston, David S.; Denison, Michael S.; Birnbaum, Linda S.; Pomp, Daniel; Threadgill, David W.

2009-01-01

Diets high in fat are associated with increased susceptibility to obesity and metabolic syndrome. Increased adipose tissue that is caused by high-fat diets (HFD) results in altered storage of lipophilic toxicants like 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), which may further increase susceptibility to metabolic syndrome. Because both TCDD and HFD are associated with increased breast cancer risk, we examined their effects on metabolic syndrome-associated phenotypes in three mouse models of breast cancer: 7,12-dimethylbenz[a]anthracene (DMBA), Tg(MMTV-Neu)202Mul/J (HER2), and TgN(MMTV-PyMT)634Mul/J (PyMT), all on an FVB/N genetic background. Pregnant mice dosed with 1 μg/kg of TCDD or vehicle on gestational day 12.5 were placed on a HFD or low-fat diet (LFD) at parturition. Body weights, percent body fat, and fasting blood glucose were measured longitudinally, and triglycerides were measured at study termination. On HFD, all cancer models reached the pubertal growth spurt ahead of FVB controls. Among mice fed HFD, the HER2 model had a greater increase in body weight and adipose tissue from puberty through adulthood compared with the PyMT and DMBA models. However, the DMBA model consistently had higher fasting blood glucose levels than the PyMT and HER2 models. TCDD only impacted serum triglycerides in the PyMT model maintained on HFD. Because the estrogenic activity of the HFD was three times lower than that of the LFD, differential dietary estrogenic activities did not drive the observed phenotypic differences. Rather, the HFD-dependent changes were cancer model dependent. These results show that cancer models can have differential effects on metabolic syndrome-associated phenotypes even before cancers arise. PMID:18840765

Cultured gut microbiota from twins discordant for obesity modulate adiposity and metabolic phenotypes in mice

OpenAIRE

Ridaura, Vanessa K.; Faith, Jeremiah J.; Rey, Federico E.; Cheng, Jiye; Duncan, Alexis E.; Kau, Andrew L.; Griffin, Nicholas W.; Lombard, Vincent; Henrissat, Bernard; Bain, James R.; Muehlbauer, Michael J.; Ilkayeva, Olga; Semenkovich, Clay F.; Funai, Katsuhiko; Hayashi, David K.

2013-01-01

The role of specific gut microbes in shaping body composition remains unclear. We transplanted fecal microbiota from adult female twin pairs discordant for obesity into germ-free mice fed low-fat mouse chow, as well as diets representing different levels of saturated fat and fruit and vegetable consumption typical of the USA. Increased total body and fat mass, as well as obesity-associated metabolic phenotypes were transmissible with uncultured fecal communities, and with their corresponding ...

Genome-scale metabolic modeling of Mucor circinelloides and comparative analysis with other oleaginous species.

Science.gov (United States)

Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin

2016-06-01

We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles.

Science.gov (United States)

Kitayama, Tomoya; Kinoshita, Ayako; Sugimoto, Masahiro; Nakayama, Yoichi; Tomita, Masaru

2006-07-17

In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles

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Sugimoto Masahiro

2006-07-01

Full Text Available Abstract Background In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. Results The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. Conclusion The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.

Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

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Eddy J Bautista

Full Text Available Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.

Phenotypic Resistance to Antibiotics

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Jose L. Martinez

2013-04-01

Full Text Available The development of antibiotic resistance is usually associated with genetic changes, either to the acquisition of resistance genes, or to mutations in elements relevant for the activity of the antibiotic. However, in some situations resistance can be achieved without any genetic alteration; this is called phenotypic resistance. Non-inherited resistance is associated to specific processes such as growth in biofilms, a stationary growth phase or persistence. These situations might occur during infection but they are not usually considered in classical susceptibility tests at the clinical microbiology laboratories. Recent work has also shown that the susceptibility to antibiotics is highly dependent on the bacterial metabolism and that global metabolic regulators can modulate this phenotype. This modulation includes situations in which bacteria can be more resistant or more susceptible to antibiotics. Understanding these processes will thus help in establishing novel therapeutic approaches based on the actual susceptibility shown by bacteria during infection, which might differ from that determined in the laboratory. In this review, we discuss different examples of phenotypic resistance and the mechanisms that regulate the crosstalk between bacterial metabolism and the susceptibility to antibiotics. Finally, information on strategies currently under development for diminishing the phenotypic resistance to antibiotics of bacterial pathogens is presented.

Validation of the doubly-labeled water (H3H18O) method for measuring water flux and energy metabolism in tenebrionid beetles

International Nuclear Information System (INIS)

Cooper, P.D.

1981-01-01

Doubly-labeled water (H 3 H 18 O) has been used to determine water flux and energy metabolism in a variety of vertebrates. This study examines the applicability of this technique to arthropods. The theory of the technique depends upon the assumption that doubly-labeled water introduced into the animal's body water equilibrates with water and carbon dioxide by the action of carbonic anhydrase. Tritium ( 3 H) is lost from the animal only with water while oxygen-18 is lost with both water and carbon dioxide. The difference bwtween the rates of loss of the two isotopes is proportional to CO 2 loss rate. Validation of the use of tritiated water for measuring water flux was accomplished by comparing gravimetric measurements of water gain with flux rates determined by loss of tritiated water. At room humidity, an overestimate for influx calculated from labeled water calculations was found, averaging 12 mg H 2 O (g.d) -1 . Comparison of CO 2 loss rate determined isotopically with rates of CO 2 loss determined by standard metabolic rates also yielded overestimates for the isotopic technique, overestimates ranging between 20 and 30%. The relevance of this for studies using labeled water for studying water fluxes and free metabolism of free-ranging arthropods is discussed

Metabolic flux analysis of the hydrogen production potential in Synechocystis sp. PCC6803

Energy Technology Data Exchange (ETDEWEB)

Navarro, E. [Departamento de Lenguajes y Ciencias de la Computacion, Campus de Teatrinos, Universidad de Malaga, 29071 Malaga (Spain); Montagud, A.; Fernandez de Cordoba, P.; Urchueguia, J.F. [Instituto Universitario de Matematica Pura y Aplicada, Universidad Politecnica de Valencia, Camino de Vera 14, 46022 Valencia (Spain)

2009-11-15

Hydrogen is a promising energy vector; however, finding methods to produce it from renewable sources is essential to allow its wide-scale use. In that line, biological hydrogen production, although it is considered as a possible alternative, requires substantial improvements to overcome its present low yields. In that direction, genetic manipulation probably will play a central role and from that point of view metabolic flux analysis (MFA) constitutes an important tool to guide a priori most suitable genetic modifications oriented to a hydrogen yield increase. In this work MFA has been applied to analyze hydrogen photoproduction of Synechocystis sp. PCC6803. Flux analysis was carried out based on literature data and several basic fluxes were estimated in different growing conditions of the system. From this analysis, an upper limit for hydrogen photoproduction has been determined indicating a wide margin for improvement. MFA was also used to find a feasible operating space for hydrogen production, which avoids oxygen inhibition, one of the most important limitations to make hydrogen production cost effective. In addition, a set of biotechnological strategies are proposed that would be consistent with the performed mathematical analysis. (author)

MID Max: LC–MS/MS Method for Measuring the Precursor and Product Mass Isotopomer Distributions of Metabolic Intermediates and Cofactors for Metabolic Flux Analysis Applications

DEFF Research Database (Denmark)

McCloskey, Douglas; Young, Jamey D.; Xu, Sibei

2016-01-01

The analytical challenges to acquire accurate isotopic data of intracellular metabolic intermediates for stationary, nonstationary, and dynamic metabolic flux analysis (MFA) are numerous. This work presents MID Max, a novel LC–MS/MS workflow, acquisition, and isotopomer deconvolution method for MFA...... that takes advantage of additional scan types that maximizes the number of mass isotopomer distributions (MIDs) that can be acquired in a given experiment. The analytical method was found to measure the MIDs of 97 metabolites, corresponding to 74 unique metabolite-fragment pairs (32 precursor spectra and 42...

Hyperandrogenemia predicts metabolic phenotype in polycystic ovary syndrome: the utility of serum androstenedione.

Science.gov (United States)

O'Reilly, Michael W; Taylor, Angela E; Crabtree, Nicola J; Hughes, Beverly A; Capper, Farfia; Crowley, Rachel K; Stewart, Paul M; Tomlinson, Jeremy W; Arlt, Wiebke

2014-03-01

Polycystic ovary syndrome (PCOS) is a triad of anovulation, insulin resistance, and hyperandrogenism. Androgen excess may correlate with metabolic risk and PCOS consensus criteria define androgen excess on the basis of serum T. Here we studied the utility of the androgen precursor serum androstenedione (A) in conjunction with serum T for predicting metabolic dysfunction in PCOS. Eighty-six PCOS patients fulfilling Rotterdam diagnostic consensus criteria and 43 age- and body mass index-matched controls underwent measurement of serum androgens by tandem mass spectrometry and an oral glucose tolerance test with homeostatic model assessment of insulin resistance and insulin sensitivity index calculation. We analyzed 24-hour urine androgen excretion by gas chromatography/mass spectrometry. PCOS patients had higher levels of serum androgens and urinary androgen metabolites than controls (all P PCOS cohort, both serum A and T were positively correlated with the free androgen index (T × 100/SHBG) and total androgen metabolite excretion (all P androgen excretion than NA/NT (P androgen phenotype (NA/NT, 0%; HA/NT, 14%; HA/HT, 25%, P = .03). Simultaneous measurement of serum T and A represents a useful tool for predicting metabolic risk in PCOS women. HA levels are a sensitive indicator of PCOS-related androgen excess.

In vivo metabolic phenotyping of myocardial substrate metabolism in rodents: differential efficacy of metformin and rosiglitazone monotherapy.

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Shoghi, Kooresh I; Finck, Brian N; Schechtman, Kenneth B; Sharp, Terry; Herrero, Pilar; Gropler, Robert J; Welch, Michael J

2009-09-01

Cardiovascular disease is the leading cause of death among diabetic patients, with alteration in myocardial substrate metabolism being a likely contributor. We aimed to assess noninvasively the efficacy of metformin and rosiglitazone monotherapy in normalizing myocardial substrate metabolism in an animal model of type 2 diabetes mellitus. The study used 18 male ZDF rats (fa/fa) with 6 rats in each group: an untreated group; a group treated with metformin (16.6 mg/kg/d), and a group treated with rosiglitazone (4 mg/kg). Each rat was scanned at age 14 weeks (baseline) and subsequently at 19 weeks with small-animal positron emission tomography to estimate myocardial glucose utilization (MGU) and myocardial utilization (MFAU), oxidation (MFAO), and esterification (MFAE). Treatment lasted for 5 weeks after baseline imaging. At week 19, rats were euthanized and hearts were extracted for expression analysis of select genes encoding for GLUT transporters and fatty acid transport and oxidation genes. In addition, echocardiography measurements were obtained at weeks 13 and 18 to characterize cardiac function. Metformin had no significant effect on either MGU or MFAU and MFAO. In contrast, rosiglitazone tended to enhance MGU and significantly reduced MFAU and MFAO. Rosiglitazone-induced increase in glucose uptake correlated significantly with increased expression of GLUT4, whereas diminished MFAO correlated significantly with decreased expression of FATP-1 and MCAD. Finally, changes in fractional shortening as a measure of cardiac function were unchanged throughout the study. Treatment with rosiglitazone enhanced glucose utilization and diminished MFAO, thus reversing the metabolic phenotype of the diabetic heart.

13C based proteinogenic amino acid (PAA) and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP) pathway in response to agitation and temperature related stresses.

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Azizan, Kamalrul Azlan; Ressom, Habtom W; Mendoza, Eduardo R; Baharum, Syarul Nataqain

2017-01-01

Lactococcus lactis subsp. cremoris MG1363 is an important starter culture for dairy fermentation. During industrial fermentations, L. lactis is constantly exposed to stresses that affect the growth and performance of the bacterium. Although the response of L. lactis to several stresses has been described, the adaptation mechanisms at the level of in vivo fluxes have seldom been described. To gain insights into cellular metabolism, 13 C metabolic flux analysis and gas chromatography mass spectrometry (GC-MS) were used to measure the flux ratios of active pathways in the central metabolism of L. lactis when subjected to three conditions varying in temperature (30°C, 37°C) and agitation (with and without agitation at 150 rpm). Collectively, the concentrations of proteinogenic amino acids (PAAs) and free fatty acids (FAAs) were compared, and Pearson correlation analysis ( r ) was calculated to measure the pairwise relationship between PAAs. Branched chain and aromatic amino acids, threonine, serine, lysine and histidine were correlated strongly, suggesting changes in flux regulation in glycolysis, the pentose phosphate (PP) pathway, malic enzyme and anaplerotic reaction catalysed by pyruvate carboxylase (pycA). Flux ratio analysis revealed that glucose was mainly converted by glycolysis, highlighting the stability of L. lactis' central carbon metabolism despite different conditions. Higher flux ratios through oxaloacetate (OAA) from pyruvate (PYR) reaction in all conditions suggested the activation of pyruvate carboxylate (pycA) in L. lactis , in response to acid stress during exponential phase. Subsequently, more significant flux ratio differences were seen through the oxidative and non-oxidative pentose phosphate (PP) pathways, malic enzyme, and serine and C1 metabolism, suggesting NADPH requirements in response to environmental stimuli. These reactions could play an important role in optimization strategies for metabolic engineering in L. lactis . Overall, the

13C based proteinogenic amino acid (PAA and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP pathway in response to agitation and temperature related stresses

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Kamalrul Azlan Azizan

2017-07-01

Full Text Available Lactococcus lactis subsp. cremoris MG1363 is an important starter culture for dairy fermentation. During industrial fermentations, L. lactis is constantly exposed to stresses that affect the growth and performance of the bacterium. Although the response of L. lactis to several stresses has been described, the adaptation mechanisms at the level of in vivo fluxes have seldom been described. To gain insights into cellular metabolism, 13C metabolic flux analysis and gas chromatography mass spectrometry (GC-MS were used to measure the flux ratios of active pathways in the central metabolism of L. lactis when subjected to three conditions varying in temperature (30°C, 37°C and agitation (with and without agitation at 150 rpm. Collectively, the concentrations of proteinogenic amino acids (PAAs and free fatty acids (FAAs were compared, and Pearson correlation analysis (r was calculated to measure the pairwise relationship between PAAs. Branched chain and aromatic amino acids, threonine, serine, lysine and histidine were correlated strongly, suggesting changes in flux regulation in glycolysis, the pentose phosphate (PP pathway, malic enzyme and anaplerotic reaction catalysed by pyruvate carboxylase (pycA. Flux ratio analysis revealed that glucose was mainly converted by glycolysis, highlighting the stability of L. lactis’ central carbon metabolism despite different conditions. Higher flux ratios through oxaloacetate (OAA from pyruvate (PYR reaction in all conditions suggested the activation of pyruvate carboxylate (pycA in L. lactis, in response to acid stress during exponential phase. Subsequently, more significant flux ratio differences were seen through the oxidative and non-oxidative pentose phosphate (PP pathways, malic enzyme, and serine and C1 metabolism, suggesting NADPH requirements in response to environmental stimuli. These reactions could play an important role in optimization strategies for metabolic engineering in L. lactis. Overall

13C based proteinogenic amino acid (PAA) and metabolic flux ratio analysis of Lactococcus lactis reveals changes in pentose phosphate (PP) pathway in response to agitation and temperature related stresses

Science.gov (United States)

2017-01-01

Lactococcus lactis subsp. cremoris MG1363 is an important starter culture for dairy fermentation. During industrial fermentations, L. lactis is constantly exposed to stresses that affect the growth and performance of the bacterium. Although the response of L. lactis to several stresses has been described, the adaptation mechanisms at the level of in vivo fluxes have seldom been described. To gain insights into cellular metabolism, 13C metabolic flux analysis and gas chromatography mass spectrometry (GC-MS) were used to measure the flux ratios of active pathways in the central metabolism of L. lactis when subjected to three conditions varying in temperature (30°C, 37°C) and agitation (with and without agitation at 150 rpm). Collectively, the concentrations of proteinogenic amino acids (PAAs) and free fatty acids (FAAs) were compared, and Pearson correlation analysis (r) was calculated to measure the pairwise relationship between PAAs. Branched chain and aromatic amino acids, threonine, serine, lysine and histidine were correlated strongly, suggesting changes in flux regulation in glycolysis, the pentose phosphate (PP) pathway, malic enzyme and anaplerotic reaction catalysed by pyruvate carboxylase (pycA). Flux ratio analysis revealed that glucose was mainly converted by glycolysis, highlighting the stability of L. lactis’ central carbon metabolism despite different conditions. Higher flux ratios through oxaloacetate (OAA) from pyruvate (PYR) reaction in all conditions suggested the activation of pyruvate carboxylate (pycA) in L. lactis, in response to acid stress during exponential phase. Subsequently, more significant flux ratio differences were seen through the oxidative and non-oxidative pentose phosphate (PP) pathways, malic enzyme, and serine and C1 metabolism, suggesting NADPH requirements in response to environmental stimuli. These reactions could play an important role in optimization strategies for metabolic engineering in L. lactis. Overall, the

(13)C metabolic flux analysis in neurons utilizing a model that accounts for hexose phosphate recycling within the pentose phosphate pathway.

Science.gov (United States)

Gebril, Hoda M; Avula, Bharathi; Wang, Yan-Hong; Khan, Ikhlas A; Jekabsons, Mika B

2016-02-01

Glycolysis, mitochondrial substrate oxidation, and the pentose phosphate pathway (PPP) are critical for neuronal bioenergetics and oxidation-reduction homeostasis, but quantitating their fluxes remains challenging, especially when processes such as hexose phosphate (i.e., glucose/fructose-6-phosphate) recycling in the PPP are considered. A hexose phosphate recycling model was developed which exploited the rates of glucose consumption, lactate production, and mitochondrial respiration to infer fluxes through the major glucose consuming pathways of adherent cerebellar granule neurons by replicating [(13)C]lactate labeling from metabolism of [1,2-(13)C2]glucose. Flux calculations were predicated on a steady-state system with reactions having known stoichiometries and carbon atom transitions. Non-oxidative PPP activity and consequent hexose phosphate recycling, as well as pyruvate production by cytoplasmic malic enzyme, were optimized by the model and found to account for 28 ± 2% and 7.7 ± 0.2% of hexose phosphate and pyruvate labeling, respectively. From the resulting fluxes, 52 ± 6% of glucose was metabolized by glycolysis, compared to 19 ± 2% by the combined oxidative/non-oxidative pentose cycle that allows for hexose phosphate recycling, and 29 ± 8% by the combined oxidative PPP/de novo nucleotide synthesis reactions. By extension, 62 ± 6% of glucose was converted to pyruvate, the metabolism of which resulted in 16 ± 1% of glucose oxidized by mitochondria and 46 ± 6% exported as lactate. The results indicate a surprisingly high proportion of glucose utilized by the pentose cycle and the reactions synthesizing nucleotides, and exported as lactate. While the in vitro conditions to which the neurons were exposed (high glucose, no lactate or other exogenous substrates) limit extrapolating these results to the in vivo state, the approach provides a means of assessing a number of metabolic fluxes within the context of hexose phosphate recycling in the PPP from a

Modeling of Zymomonas mobilis central metabolism for novel metabolic engineering strategies.

Science.gov (United States)

Kalnenieks, Uldis; Pentjuss, Agris; Rutkis, Reinis; Stalidzans, Egils; Fell, David A

2014-01-01

Mathematical modeling of metabolism is essential for rational metabolic engineering. The present work focuses on several types of modeling approach to quantitative understanding of central metabolic network and energetics in the bioethanol-producing bacterium Zymomonas mobilis. Combined use of Flux Balance, Elementary Flux Mode, and thermodynamic analysis of its central metabolism, together with dynamic modeling of the core catabolic pathways, can help to design novel substrate and product pathways by systematically analyzing the solution space for metabolic engineering, and yields insights into the function of metabolic network, hardly achievable without applying modeling tools.

Meta-analysis of melanin-concentrating hormone signaling-deficient mice on behavioral and metabolic phenotypes.

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Kenkichi Takase

Full Text Available The demand for meta-analyses in basic biomedical research has been increasing because the phenotyping of genetically modified mice does not always produce consistent results. Melanin-concentrating hormone (MCH has been reported to be involved in a variety of behaviors that include feeding, body-weight regulation, anxiety, sleep, and reward behavior. However, the reported behavioral and metabolic characteristics of MCH signaling-deficient mice, such as MCH-deficient mice and MCH receptor 1 (MCHR1-deficient mice, are not consistent with each other. In the present study, we performed a meta-analysis of the published data related to MCH-deficient and MCHR1-deficient mice to obtain robust conclusions about the role of MCH signaling. Overall, the meta-analysis revealed that the deletion of MCH signaling enhanced wakefulness, locomotor activity, aggression, and male sexual behavior and that MCH signaling deficiency suppressed non-REM sleep, anxiety, responses to novelty, startle responses, and conditioned place preferences. In contrast to the acute orexigenic effect of MCH, MCH signaling deficiency significantly increased food intake. Overall, the meta-analysis also revealed that the deletion of MCH signaling suppressed the body weight, fat mass, and plasma leptin, while MCH signaling deficiency increased the body temperature, oxygen consumption, heart rate, and mean arterial pressure. The lean phenotype of the MCH signaling-deficient mice was also confirmed in separate meta-analyses that were specific to sex and background strain (i.e., C57BL/6 and 129Sv. MCH signaling deficiency caused a weak anxiolytic effect as assessed with the elevated plus maze and the open field test but also caused a weak anxiogenic effect as assessed with the emergence test. MCH signaling-deficient mice also exhibited increased plasma corticosterone under non-stressed conditions, which suggests enhanced activity of the hypothalamic-pituitary-adrenal axis. To the best of our

Increased OXPHOS activity precedes rise in glycolytic rate in H-RasV12/E1A transformed fibroblasts that develop a Warburg phenotype

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Pluk Helma

2009-07-01

Full Text Available Abstract Background The Warburg phenotype in cancer cells has been long recognized, but there is still limited insight in the consecutive metabolic alterations that characterize its establishment. We obtained better understanding of the coupling between metabolism and malignant transformation by studying mouse embryonic fibroblast-derived cells with loss-of-senescence or H-RasV12/E1A-transformed phenotypes at different stages of oncogenic progression. Results Spontaneous immortalization or induction of senescence-bypass had only marginal effects on metabolic profiles and viability. In contrast, H-RasV12/E1A transformation initially caused a steep increase in oxygen consumption and superoxide production, accompanied by massive cell death. During prolonged culture in vitro, cell growth rate increased gradually, along with tumor forming potential in in vitro anchorage-independent growth assays and in vivo tumor formation assays in immuno-deficient mice. Notably, glucose-to-lactic acid flux increased with passage number, while cellular oxygen consumption decreased. This conversion in metabolic properties was associated with a change in mitochondrial NAD+/NADH redox, indicative of decreased mitochondrial tricarboxic acid cycle and OXPHOS activity. Conclusion The high rate of oxidative metabolism in newly transformed cells is in marked contrast with the high glycolytic rate in cells in the later tumor stage. In our experimental system, with cells growing under ambient oxygen conditions in nutrient-rich media, the shift towards this Warburg phenotype occurred as a step-wise adaptation process associated with augmented tumorigenic capacity and improved survival characteristics of the transformed cells. We hypothesize that early-transformed cells, which potentially serve as founders for new tumor masses may escape therapies aimed at metabolic inhibition of tumors with a fully developed Warburg phenotype.

Annual benthic metabolism and organic carbon fluxes in a semi-enclosed Mediterranean bay dominated by the macroalgae Caulerpa prolifera.

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Sergio eRuiz-Halpern

2014-12-01

Full Text Available Coastal areas play an important role on carbon cycling. Elucidating the dynamics on the production, transport and fate of organic carbon is relevant to gain a better understanding of the role coastal areas play in the global carbon budget. Here, we assess the metabolic status and associated organic carbon fluxes of a semi-enclosed Mediterranean bay supporting a meadow of Caulerpa prolifera. We test whether the EDOC pool is a significant component of the organic carbon pool and associated fluxes in this ecosystem. The Bay of Portocolom was in net metabolic balance on a yearly basis, but heterotrophic during the summer months. Community respiration (CR was positively correlated to C. prolifera biomass, while net community production (NCP had a negative correlation. The benthic compartment represented, on average, 72.6 ± 5.2 % of CR and 86.8 ± 4.5 % of gross primary production (GPP. Dissolved organic carbon (DOC production peaked in summer and was always positive, with the incubations performed in the dark almost doubling the flux of those performed in the light. Exchangeable dissolved organic carbon (EDOC, however, oscillated between production and uptake, being completely recycled within the system and representing around 14% of the DOC flux. The pools of bottom and surface DOC were high for an oligotrophic environment, and were positively correlated to the pool of EDOC. Thus, despite being in metabolic balance, this ecosystem acted as a conduit for organic carbon (OC, as it is able to export OC to adjacent areas derived from allochtonous inputs during heterotrophic conditions. These inputs likely come from groundwater discharge, human activity in the watershed, delivered to the sediments through the high capacity of C. prolifera to remove particles from the water column, and from the air-water exchange of EDOC, demonstrating that these communities are a major contributor to the cycling of OC in coastal embayments.

Propofol Compared to Isoflurane Inhibits Mitochondrial Metabolism in Immature Swine Cerebral Cortex

Energy Technology Data Exchange (ETDEWEB)

Kajimoto, Masaki; Atkinson, D. B.; Ledee, Dolena R.; Kayser, Ernst-Bernhard; Morgan, Phil G.; Sedensky, Margaret M.; Isern, Nancy G.; Des Rosiers, Christine; Portman, Michael A.

2014-01-08

Anesthetics used in infants and children are implicated in development of neurocognitive disorders. Although propofol induces neuroapoptosis in developing brain, the underlying mechanisms require elucidation and may have an energetic basis. We studied substrate utilization in an immature swine model anesthetized with either propofol or isoflurane for 4 hours. Piglets were infused with 13-Carbon labeled glucose and leucine in the common carotid artery in order to assess citric acid cycle (CAC) metabolism in the parietal cortex. The anesthetics produced similar systemic hemodynamics and cerebral oxygen saturation by near-infrared-spectroscopy. Compared to isoflurane, propofol depleted ATP and glycogen stores. Propofol also decreased pools of the CAC intermediates, citrate and α-ketoglutarate, while markedly increasing succinate along with decreasing mitochondrial complex II activity. Propofol also inhibited acetyl-CoA entry into the CAC through pyruvate dehydrogenase, while promoting glycolytic flux with marked accumulation of lactate. Although oxygen supply appeared similar between the anesthetic groups, propofol yielded a metabolic phenotype which resembled a hypoxic state. Propofol impairs substrate flux through the CAC in the immature cerebral cortex. These impairments occurred without systemic metabolic perturbations which typically accompany propofol infusion syndrome. These metabolic abnormalities may play a role in neurotoxity observed with propofol in the vulnerable immature brain.

Metabolic and transcriptional responses of gilthead sea bream (Sparus aurata L.) to environmental stress: New insights in fish mitochondrial phenotyping

NARCIS (Netherlands)

Bermejo-Nogales, A.; Nederlof, M.A.J.; Benedito-Palos, L.; Ballester-Lozano, G.F.; Folkedal, O.; Olsen, R.E.; Sitjà-Bobadilla, A.; Pérez-Sánchez, J.

2014-01-01

The aim of the current study was to phenotype fish metabolism and the transcriptionally-mediated response of hepatic mitochondria of gilthead sea bream to intermittent and repetitive environmental stressors: (i) changes in water temperature (T-ST), (ii) changes in water level and chasing (C-ST) and

Sirtuins as regulators of the yeast metabolic network

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Markus eRalser

2012-03-01

Full Text Available There is growing evidence that the metabolic network is an integral regulator of cellularphysiology. Dynamic changes in metabolite concentrations, metabolic flux, or networktopology act as reporters of biological or environmental signals, and are required for the cellto trigger an appropriate biological reaction. Changes in the metabolic network are recognizedby specific sensory macromolecules and translated into a transcriptional or translationalresponse. The protein family of sirtuins, discovered more than 30 years ago as regulators ofsilent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions ofcaloric restriction. NAD+/NADH interconverting metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved inNAD(H, synthesis provide or deprive NAD+ in close proximity to Sir2. This influence sirtuinactivity, and facilitates a dynamic response of the metabolic network to changes inmetabolism with effects on physiology and aging. The molecular network downstream Sir2,however, is complex. In just two orders, Sir2’s metabolism-related interactions span half ofthe yeast proteome, and are connected with virtually every physiological process. Thus,although it is fundamental to analyze single molecular mechanisms, it is at the same timecrucial to consider this genome-scale complexity when correlating single molecular eventswith phenotypes such as aging, cell growth, or stress resistance.

Enhanced production of resveratrol derivatives in tobacco plants by improving the metabolic flux of intermediates in the phenylpropanoid pathway.

Science.gov (United States)

Jeong, Yu Jeong; An, Chul Han; Woo, Su Gyeong; Park, Ji Hye; Lee, Ki-Won; Lee, Sang-Hoon; Rim, Yeonggil; Jeong, Hyung Jae; Ryu, Young Bae; Kim, Cha Young

2016-09-01

The biosynthesis of flavonoids such as anthocyanin and stilbenes has attracted increasing attention because of their potential health benefits. Anthocyanins and stilbenes share common phenylpropanoid precursor pathways. We previously reported that the overexpression of sweetpotato IbMYB1a induced anthocyanin pigmentation in transgenic tobacco (Nicotiana tabacum) plants. In the present study, transgenic tobacco (Nicotiana tabacum SR1) plants (STS-OX and ROST-OX) expressing the RpSTS gene encoding stilbene synthase from rhubarb (Rheum palmatum L. cv. Jangyeop) and the RpSTS and VrROMT genes encoding resveratrol O-methyltransferase from frost grape (Vitis riparia) were generated under the control of 35S promoter. Phenotypic alterations in floral organs, such as a reduction in floral pigments and male sterility, were observed in STS-OX transgenic tobacco plants. However, we failed to obtain STS-OX and ROST-OX plants with high levels of resveratrol compounds. Therefore, to improve the production of resveratrol derivatives in plants, we cross-pollinated flowers of STS-OX or ROST-OX and IbMYB1a-OX transgenic lines (SM and RSM). Phenotypic changes in vegetative and reproductive development of SM and RSM plants were observed. Furthermore, by HPLC and LC-MS analyses, we found enhanced production of resveratrol derivatives such as piceid, piceid methyl ether, resveratrol methyl ether O-hexoside, and 5-methyl resveratrol-3,4'-O-β-D-diglucopyranoside in SM and RSM cross-pollinated lines. Here, total contents of trans- and cis-piceids ranged from approximately 104-240 µg/g fresh weight in SM (F2). Collectively, we suggest that coexpression of RpSTS and IbMYB1a via cross-pollination can induce enhanced production of resveratrol compounds in plants by increasing metabolic flux into stilbenoid biosynthesis.

Flux analysis of central metabolic pathways in the Fe(III)-reducing organism Geobacter metallireducens via 13C isotopiclabeling

Energy Technology Data Exchange (ETDEWEB)

Tang, Yinjie J.; Chakraborty, Romy; Martin, Hector Garcia; Chu,Jeannie; Hazen, Terry C.; Keasling, Jay D.

2007-08-13

We analyzed the carbon fluxes in the central metabolism ofGeobacter metallireducens strain GS-15 using 13C isotopomer modeling.Acetate labeled in the 1st or 2nd position was the sole carbon source,and Fe-NTA was the sole terminal electron acceptor. The measured labeledacetate uptake rate was 21 mmol/gdw/h in the exponential growth phase.The resulting isotope labeling pattern of amino acids allowed an accuratedetermination of the in vivo global metabolic reaction rates (fluxes)through the central metabolic pathways using a computational isotopomermodel. The model indicated that over 90 percent of the acetate wascompletely oxidized to CO2 via a complete tricarboxylic acid (TCA) cyclewhile reducing iron. Pyruvate carboxylase and phosphoenolpyruvatecarboxykinase were present under these conditions, but enzymes in theglyoxylate shunt and malic enzyme were absent. Gluconeogenesis and thepentose phosphate pathway were mainly employed for biosynthesis andaccounted for less than 3 percent of total carbon consumption. The modelalso indicated surprisingly high reversibility in the reaction betweenoxoglutarate and succinate. This step operates close to the thermodynamicequilibrium possibly because succinate is synthesized via a transferasereaction, and its product, acetyl-CoA, inhibits the conversion ofoxoglutarate to succinate. These findings enable a better understandingof the relationship between genome annotation and extant metabolicpathways in G. metallireducens.

Nutrient fluxes and net metabolism in a coastal lagoon SW peninsula of Baja California, Mexico

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Cervantes Duarte, R.

2016-09-01

Full Text Available Fluxes of nutrients and net metabolism were estimated in coastal lagoon Magdalena Bay using LOICZ biogeochemical model. In situ data were obtained from 14 sites in the lagoon and also from a fixed site in the adjacent ocean area. Intense upwelling (February to July and faint upwelling (August to January were analyzed from monthly time series. The Temperature, nitrite + nitrate, ammonium and phosphate within the lagoon showed significant differences (p<0.05 between the two periods. Salinity (p=0.408 was more homogeneous (no significantly different due to mixing processes. During the intense upwelling period, nutrients increased in and out of the lagoon due to the influence of Transitional Water and Subartic Water transported by the California Current. However, during the faint upwelling, from August to January, the Transition Water and Subtropical Surface Water were predominant. Magdalena Bay showed denitrification processes of throughout the year as it occurred in other semi-arid coastal lagoons. It also showed a net autotrophic metabolism during intense upwelling and heterotrophic metabolism during faint upwelling. Understanding nutrient flows and net metabolism through simple biogeochemical models can provide tools for better management of the coastal zone.

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

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Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

Simple and robust determination of the activity signature of key carbohydrate metabolism enzymes for physiological phenotyping in model and crop plants

Czech Academy of Sciences Publication Activity Database

Jammer, A.; Gapserl, A.; Luschin-Ebengreuth, N.; Heyneke, E.; Chu, H.; Cantero-Navarro, E.; Grosskinsky, D. K.; Albacete, A.; Stabentheiner, E.; Franzaring, J.; Fangmeier, A.; van der Graaff, E.; Roitsch, Thomas

2015-01-01

Roč. 66, č. 18 (2015), s. 5531-5542 ISSN 0022-0957 Institutional support: RVO:67179843 Keywords : Carbohydrate metabolism * dialysis * enzyme activities * kinetic assay * physiological phenotyping * physiological state * protein extraction * signatures Subject RIV: EH - Ecology, Behaviour Impact factor: 5.677, year: 2015

Rhabdomyosarcoma cells show an energy producing anabolic metabolic phenotype compared with primary myocytes

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Higashi Richard M

2008-10-01

Full Text Available Abstract Background The functional status of a cell is expressed in its metabolic activity. We have applied stable isotope tracing methods to determine the differences in metabolic pathways in proliferating Rhabdomysarcoma cells (Rh30 and human primary myocytes in culture. Uniformly 13C-labeled glucose was used as a source molecule to follow the incorporation of 13C into more than 40 marker metabolites using NMR and GC-MS. These include metabolites that report on the activity of glycolysis, Krebs' cycle, pentose phosphate pathway and pyrimidine biosynthesis. Results The Rh30 cells proliferated faster than the myocytes. Major differences in flux through glycolysis were evident from incorporation of label into secreted lactate, which accounts for a substantial fraction of the glucose carbon utilized by the cells. Krebs' cycle activity as determined by 13C isotopomer distributions in glutamate, aspartate, malate and pyrimidine rings was considerably higher in the cancer cells than in the primary myocytes. Large differences were also evident in de novo biosynthesis of riboses in the free nucleotide pools, as well as entry of glucose carbon into the pyrimidine rings in the free nucleotide pool. Specific labeling patterns in these metabolites show the increased importance of anaplerotic reactions in the cancer cells to maintain the high demand for anabolic and energy metabolism compared with the slower growing primary myocytes. Serum-stimulated Rh30 cells showed higher degrees of labeling than serum starved cells, but they retained their characteristic anabolic metabolism profile. The myocytes showed evidence of de novo synthesis of glycogen, which was absent in the Rh30 cells. Conclusion The specific 13C isotopomer patterns showed that the major difference between the transformed and the primary cells is the shift from energy and maintenance metabolism in the myocytes toward increased energy and anabolic metabolism for proliferation in the Rh30 cells

The Relation between Diverse Phenotypes of PCOS with Clinical Manifestations, Anthropometric Indices and Metabolic Characteristics.

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Shahrami, Seyedeh Hajar; Abbasi Ranjbar, Zahra; Milani, Forozan; Kezem-Nejad, Ehsan; Hassanzadeh Rad, Afagh; Dalil Heirat, Seyedeh Fatemeh

2016-02-01

Critical issue regarding to variation of findings based on different phenotypes led investigators to define whether they are distinct features or overlapping ones. Therefore, we aimed to investigate the association between diverse phenotypes of PCOS (Poly Cystic Ovary Syndrome) with clinical manifestations, anthropometric indices, and metabolic characteristics. This was a descriptive cross-sectional study conducted in 15-39 years old women with PCOS referred to infertility clinics in the north part of Iran, Rasht during 2010-2011. Data were gathered through an interview by a form consisted of demographic characteristics, laboratory findings, ovarian volume and anthropometric indices. A total of 214 patients consisted of 161 PCOS (cases) and 53 normal women (controls) participated in this study. The most prevalent phenotype in PCOS population was IM/PCO/HA (54%), followed by IM/HA (28%) and IM/PCO (13%). PCO/HA was present only in 6 PCOS patients (5%). PCOS patients were significantly younger than controls (P=0.07). Results showed that increased ovarian volume were higher in PCOS group in comparison with controls and IM/PCO/HA, and IM/PCO had respectively the largest ovarian volumes. Also, a significant relation was observed based on Cholesterol, 17OHP, LH, TG, 2hpp, and LH/FSH between patients with PCOS and control groups. There were significant differences in demographic, anthropometric, hormonal and ultrasound findings between PCOS and controls. Therefore, it seems that classification of the characteristics of each phenotype could offer an appropriate guide for screening risks of PCOS and may facilitate performing most favorable treatment for these complications.

Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

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Perrin H. Beatty

2016-10-01

Full Text Available A comprehensive understanding of plant metabolism could provide a direct mechanism for improving nitrogen use efficiency (NUE in crops. One of the major barriers to achieving this outcome is our poor understanding of the complex metabolic networks, physiological factors, and signaling mechanisms that affect NUE in agricultural settings. However, an exciting collection of computational and experimental approaches has begun to elucidate whole-plant nitrogen usage and provides an avenue for connecting nitrogen-related phenotypes to genes. Herein, we describe how metabolomics, computational models of metabolism, and flux balance analysis have been harnessed to advance our understanding of plant nitrogen metabolism. We introduce a model describing the complex flow of nitrogen through crops in a real-world agricultural setting and describe how experimental metabolomics data, such as isotope labeling rates and analyses of nutrient uptake, can be used to refine these models. In summary, the metabolomics/computational approach offers an exciting mechanism for understanding NUE that may ultimately lead to more effective crop management and engineered plants with higher yields.

Litter size variation in hypothalamic gene expression determines adult metabolic phenotype in Brandt's voles (Lasiopodomys brandtii.

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Xue-Ying Zhang

Full Text Available Early postnatal environments may have long-term and potentially irreversible consequences on hypothalamic neurons involved in energy homeostasis. Litter size is an important life history trait and negatively correlated with milk intake in small mammals, and thus has been regarded as a naturally varying feature of the early developmental environment. Here we investigated the long-term effects of litter size on metabolic phenotype and hypothalamic neuropeptide mRNA expression involved in the regulation of energy homeostasis, using the offspring reared from large (10-12 and small (3-4 litter sizes, of Brandt's voles (Lasiopodomys brandtii, a rodent species from Inner Mongolia grassland in China.Hypothalamic leptin signaling and neuropeptides were measured by Real-Time PCR. We showed that offspring reared from small litters were heavier at weaning and also in adulthood than offspring from large litters, accompanied by increased food intake during development. There were no significant differences in serum leptin levels or leptin receptor (OB-Rb mRNA in the hypothalamus at weaning or in adulthood, however, hypothalamic suppressor of cytokine signaling 3 (SOCS3 mRNA in adulthood increased in small litters compared to that in large litters. As a result, the agouti-related peptide (AgRP mRNA increased in the offspring from small litters.These findings support our hypothesis that natural litter size has a permanent effect on offspring metabolic phenotype and hypothalamic neuropeptide expression, and suggest central leptin resistance and the resultant increase in AgRP expression may be a fundamental mechanism underlying hyperphagia and the increased risk of overweight in pups of small litters. Thus, we conclude that litter size may be an important and central determinant of metabolic fitness in adulthood.

A flux-sensing mechanism could regulate the switch between respiration and fermentation

NARCIS (Netherlands)

Huberts, Daphne H E W; Niebel, Bastian; Heinemann, Matthias

The yeast Saccharomyces cerevisiae can show different metabolic phenotypes (e.g. fermentation and respiration). Based on data from the literature, we argue that the substrate uptake rate is the core variable in the system that controls the global metabolic phenotype. Consequently the metabolic

Shigella reroutes host cell central metabolism to obtain high-flux nutrient supply for vigorous intracellular growth.

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Kentner, David; Martano, Giuseppe; Callon, Morgane; Chiquet, Petra; Brodmann, Maj; Burton, Olga; Wahlander, Asa; Nanni, Paolo; Delmotte, Nathanaël; Grossmann, Jonas; Limenitakis, Julien; Schlapbach, Ralph; Kiefer, Patrick; Vorholt, Julia A; Hiller, Sebastian; Bumann, Dirk

2014-07-08

Shigella flexneri proliferate in infected human epithelial cells at exceptionally high rates. This vigorous growth has important consequences for rapid progression to life-threatening bloody diarrhea, but the underlying metabolic mechanisms remain poorly understood. Here, we used metabolomics, proteomics, and genetic experiments to determine host and Shigella metabolism during infection in a cell culture model. The data suggest that infected host cells maintain largely normal fluxes through glycolytic pathways, but the entire output of these pathways is captured by Shigella, most likely in the form of pyruvate. This striking strategy provides Shigella with an abundant favorable energy source, while preserving host cell ATP generation, energy charge maintenance, and survival, despite ongoing vigorous exploitation. Shigella uses a simple three-step pathway to metabolize pyruvate at high rates with acetate as an excreted waste product. The crucial role of this pathway for Shigella intracellular growth suggests targets for antimicrobial chemotherapy of this devastating disease.

Metabolic flux analysis of the halophilic archaeon Haladaptatus paucihalophilus

Energy Technology Data Exchange (ETDEWEB)

Liu, Guangxiu; Zhang, Manxiao [Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000 (China); Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000 (China); Mo, Tianlu [Department of Chemistry, Fudan University, Shanghai, 200433 (China); He, Lian [Key Laboratory of Combinatory Biosynthesis and Drug Discovery (Ministry of Education), School of Pharmaceutical Sciences, Wuhan University, Wuhan, 430071 (China); Zhang, Wei [Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000 (China); Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000 (China); Yu, Yi, E-mail: yu_yi@whu.edu.cn [Key Laboratory of Combinatory Biosynthesis and Drug Discovery (Ministry of Education), School of Pharmaceutical Sciences, Wuhan University, Wuhan, 430071 (China); Zhang, Qi, E-mail: qizhang@sioc.ac.cn [Department of Chemistry, Fudan University, Shanghai, 200433 (China); Ding, Wei, E-mail: dingw@lzu.edu.cn [Key Laboratory of Desert and Desertification, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000 (China); Key Laboratory of Extreme Environmental Microbial Resources and Engineering, Gansu Province, Lanzhou, 730000 (China); Department of Chemistry, Fudan University, Shanghai, 200433 (China)

2015-11-27

This work reports the {sup 13}C-assisted metabolic flux analysis of Haladaptatus paucihalophilus, a halophilic archaeon possessing an intriguing osmoadaption mechanism. We showed that the carbon flow is through the oxidative tricarboxylic acid (TCA) cycle whereas the reductive TCA cycle is not operative in H. paucihalophilus. In addition, both threonine and the citramalate pathways contribute to isoleucine biosynthesis, whereas lysine is synthesized through the diaminopimelate pathway and not through the α-aminoadipate pathway. Unexpected, the labeling patterns of glycine from the cells grown on [1-{sup 13}C]pyruvate and [2-{sup 13}C]pyruvate suggest that, unlike all the organisms investigated so far, in which glycine is produced exclusively from the serine hydroxymethyltransferase (SHMT) pathway, glycine biosynthesis in H. paucihalophilus involves different pathways including SHMT, threonine aldolase (TA) and the reverse reaction of glycine cleavage system (GCS), demonstrating for the first time that other pathways instead of SHMT can also make a significant contribution to the cellular glycine pool. Transcriptional analysis confirmed that both TA and GCS genes were transcribed in H. paucihalophilus, and the transcriptional level is independent of salt concentrations in the culture media. This study expands our understanding of amino acid biosynthesis and provides valuable insights into the metabolism of halophilic archaea. - Highlights: • Serine hydroxymethyltransferase, threonine aldolase, and glycine cleavage system all contribute to the glycine pool of H. paucihalophilus. • Threonine and the citramalate pathways contribute equally to the isoleucine biosynthesis in H. paucihalophilus. • Lysine in H. paucihalophilus is synthesized through the diaminopimelate pathway and not through the α-aminoadipate pathway. • Glycine biosynthesis is likely unrelated to the cell osmoadaption mechanism.

Metabolic flux analysis of the halophilic archaeon Haladaptatus paucihalophilus

International Nuclear Information System (INIS)

Liu, Guangxiu; Zhang, Manxiao; Mo, Tianlu; He, Lian; Zhang, Wei; Yu, Yi; Zhang, Qi; Ding, Wei

2015-01-01

This work reports the "1"3C-assisted metabolic flux analysis of Haladaptatus paucihalophilus, a halophilic archaeon possessing an intriguing osmoadaption mechanism. We showed that the carbon flow is through the oxidative tricarboxylic acid (TCA) cycle whereas the reductive TCA cycle is not operative in H. paucihalophilus. In addition, both threonine and the citramalate pathways contribute to isoleucine biosynthesis, whereas lysine is synthesized through the diaminopimelate pathway and not through the α-aminoadipate pathway. Unexpected, the labeling patterns of glycine from the cells grown on [1-"1"3C]pyruvate and [2-"1"3C]pyruvate suggest that, unlike all the organisms investigated so far, in which glycine is produced exclusively from the serine hydroxymethyltransferase (SHMT) pathway, glycine biosynthesis in H. paucihalophilus involves different pathways including SHMT, threonine aldolase (TA) and the reverse reaction of glycine cleavage system (GCS), demonstrating for the first time that other pathways instead of SHMT can also make a significant contribution to the cellular glycine pool. Transcriptional analysis confirmed that both TA and GCS genes were transcribed in H. paucihalophilus, and the transcriptional level is independent of salt concentrations in the culture media. This study expands our understanding of amino acid biosynthesis and provides valuable insights into the metabolism of halophilic archaea. - Highlights: • Serine hydroxymethyltransferase, threonine aldolase, and glycine cleavage system all contribute to the glycine pool of H. paucihalophilus. • Threonine and the citramalate pathways contribute equally to the isoleucine biosynthesis in H. paucihalophilus. • Lysine in H. paucihalophilus is synthesized through the diaminopimelate pathway and not through the α-aminoadipate pathway. • Glycine biosynthesis is likely unrelated to the cell osmoadaption mechanism.

Effect of amino acid supplementation on titer and glycosylation distribution in hybridoma cell cultures-Systems biology-based interpretation using genome-scale metabolic flux balance model and multivariate data analysis.

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Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu

2016-09-01

Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016. © 2016 American Institute of Chemical Engineers.

Control of fluxes in metabolic networks

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Basler, Georg; Nikoloski, Zoran; Larhlimi, Abdelhalim; Barabási, Albert-László; Liu, Yang-Yu

2016-01-01

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism. PMID:27197218

GABAA receptor activity modulating piperine analogs: In vitro metabolic stability, metabolite identification, CYP450 reaction phenotyping, and protein binding.

Science.gov (United States)

Zabela, Volha; Hettich, Timm; Schlotterbeck, Götz; Wimmer, Laurin; Mihovilovic, Marko D; Guillet, Fabrice; Bouaita, Belkacem; Shevchenko, Bénédicte; Hamburger, Matthias; Oufir, Mouhssin

2018-01-01

In a screening of natural products for allosteric modulators of GABA A receptors (γ-aminobutyric acid type A receptor), piperine was identified as a compound targeting a benzodiazepine-independent binding site. Given that piperine is also an activator of TRPV1 (transient receptor potential vanilloid type 1) receptors involved in pain signaling and thermoregulation, a series of piperine analogs were prepared in several cycles of structural optimization, with the aim of separating GABA A and TRPV1 activating properties. We here investigated the metabolism of piperine and selected analogs in view of further cycles of lead optimization. Metabolic stability of the compounds was evaluated by incubation with pooled human liver microsomes, and metabolites were analyzed by UHPLC-Q-TOF-MS. CYP450 isoenzymes involved in metabolism of compounds were identified by reaction phenotyping with Silensomes™. Unbound fraction in whole blood was determined by rapid equilibrium dialysis. Piperine was the metabolically most stable compound. Aliphatic hydroxylation, and N- and O-dealkylation were the major routes of oxidative metabolism. Piperine was exclusively metabolized by CYP1A2, whereas CYP2C9 contributed significantly in the oxidative metabolism of all analogs. Extensive binding to blood constituents was observed for all compounds. Copyright © 2017 Elsevier B.V. All rights reserved.

Genetic and phenotypic analysis of carbohydrate metabolism and transport in Lactobacillus reuteri.

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Zhao, Xin; Gänzle, Michael G

2018-05-02

Lactobacilli derive metabolic energy mainly from carbohydrate fermentation. Homofermentative and heterofermentative lactobacilli exhibit characteristic differences in carbohydrate transport and regulation of metabolism, however, enzymes for carbohydrate transport in heterofermentative lactobacilli are poorly characterized. This study aimed to identify carbohydrate active enzymes in the L. reuteri strains LTH2584, LTH5448, TMW1.656, TMW1.112, 100-23, mlc3, and lpuph by phenotypic analysis and comparative genomics. Sourdough and intestinal isolates of L. reuteri displayed no difference in the number and type of carbohydrate-active enzymes encoded in the genome. Predicted sugar transporters encoded by genomes of L. reuteri strains were secondary carriers and most belong to the major facilitator superfamily. The quantification of gene expression during growth in sourdough and in chemically defined media corresponded to the predicted function of the transporters MalT, ScrT and LacS as carriers for maltose, sucrose, and lactose or raffinose, respectively. The genotype for sugar utilization matched the fermentation profile of 39 sugars for L. reuteri strains, and indicated preference for maltose, sucrose, raffinose and (iso)-malto-oligosaccharides, which are available in sourdough and in the upper intestine of rodents. Pentose utilization in L. reuteri species was strain-specific but independent of the origin or phylogenetic position of isolates. Two glycosyl hydrolases, licheninase (EC 3.2.1.73) and endo-1, 4-β-galactosidase (EC 3.2.1.89) were identified based on conserved domains. In conclusion, the study identified the lack of PTS systems, preference for secondary carriers for carbohydrate transport, and absence of carbon catabolite repression as characteristic features of the carbohydrate metabolism in the heterofermentative L. reuteri. Copyright © 2018 Elsevier B.V. All rights reserved.

CYP2C9 Genotype vs. Metabolic Phenotype for Individual Drug Dosing—A Correlation Analysis Using Flurbiprofen as Probe Drug

Science.gov (United States)

Vogl, Silvia; Lutz, Roman W.; Schönfelder, Gilbert; Lutz, Werner K.

2015-01-01

Currently, genotyping of patients for polymorphic enzymes responsible for metabolic elimination is considered a possibility to adjust drug dose levels. For a patient to profit from this procedure, the interindividual differences in drug metabolism within one genotype should be smaller than those between different genotypes. We studied a large cohort of healthy young adults (283 subjects), correlating their CYP2C9 genotype to a simple phenotyping metric, using flurbiprofen as probe drug. Genotyping was conducted for CYP2C9*1, *2, *3. The urinary metabolic ratio MR (concentration of CYP2C9-dependent metabolite divided by concentration of flurbiprofen) determined two hours after flurbiprofen (8.75 mg) administration served as phenotyping metric. Linear statistical models correlating genotype and phenotype provided highly significant allele-specific MR estimates of 0.596 for the wild type allele CYP2C9*1, 0.405 for CYP2C9*2 (68 % of wild type), and 0.113 for CYP2C9*3 (19 % of wild type). If these estimates were used for flurbiprofen dose adjustment, taking 100 % for genotype *1/*1, an average reduction to 84 %, 60 %, 68 %, 43 %, and 19 % would result for genotype *1/*2, *1/*3, *2/*2, *2/*3, and *3/*3, respectively. Due to the large individual variation within genotypes with coefficients of variation ≥ 20 % and supposing the normal distribution, one in three individuals would be out of the average optimum dose by more than 20 %, one in 20 would be 40 % off. Whether this problem also applies to other CYPs and other drugs has to be investigated case by case. Our data for the given example, however, puts the benefit of individual drug dosing to question, if it is exclusively based on genotype. PMID:25775139

CYP2C9 genotype vs. metabolic phenotype for individual drug dosing--a correlation analysis using flurbiprofen as probe drug.

Science.gov (United States)

Vogl, Silvia; Lutz, Roman W; Schönfelder, Gilbert; Lutz, Werner K

2015-01-01

Currently, genotyping of patients for polymorphic enzymes responsible for metabolic elimination is considered a possibility to adjust drug dose levels. For a patient to profit from this procedure, the interindividual differences in drug metabolism within one genotype should be smaller than those between different genotypes. We studied a large cohort of healthy young adults (283 subjects), correlating their CYP2C9 genotype to a simple phenotyping metric, using flurbiprofen as probe drug. Genotyping was conducted for CYP2C9*1, *2, *3. The urinary metabolic ratio MR (concentration of CYP2C9-dependent metabolite divided by concentration of flurbiprofen) determined two hours after flurbiprofen (8.75 mg) administration served as phenotyping metric. Linear statistical models correlating genotype and phenotype provided highly significant allele-specific MR estimates of 0.596 for the wild type allele CYP2C9*1, 0.405 for CYP2C9*2 (68 % of wild type), and 0.113 for CYP2C9*3 (19 % of wild type). If these estimates were used for flurbiprofen dose adjustment, taking 100 % for genotype *1/*1, an average reduction to 84 %, 60 %, 68 %, 43 %, and 19 % would result for genotype *1/*2, *1/*3, *2/*2, *2/*3, and *3/*3, respectively. Due to the large individual variation within genotypes with coefficients of variation ≥ 20 % and supposing the normal distribution, one in three individuals would be out of the average optimum dose by more than 20 %, one in 20 would be 40 % off. Whether this problem also applies to other CYPs and other drugs has to be investigated case by case. Our data for the given example, however, puts the benefit of individual drug dosing to question, if it is exclusively based on genotype.

CYP2C9 genotype vs. metabolic phenotype for individual drug dosing--a correlation analysis using flurbiprofen as probe drug.

Directory of Open Access Journals (Sweden)

Silvia Vogl

Full Text Available Currently, genotyping of patients for polymorphic enzymes responsible for metabolic elimination is considered a possibility to adjust drug dose levels. For a patient to profit from this procedure, the interindividual differences in drug metabolism within one genotype should be smaller than those between different genotypes. We studied a large cohort of healthy young adults (283 subjects, correlating their CYP2C9 genotype to a simple phenotyping metric, using flurbiprofen as probe drug. Genotyping was conducted for CYP2C9*1, *2, *3. The urinary metabolic ratio MR (concentration of CYP2C9-dependent metabolite divided by concentration of flurbiprofen determined two hours after flurbiprofen (8.75 mg administration served as phenotyping metric. Linear statistical models correlating genotype and phenotype provided highly significant allele-specific MR estimates of 0.596 for the wild type allele CYP2C9*1, 0.405 for CYP2C9*2 (68 % of wild type, and 0.113 for CYP2C9*3 (19 % of wild type. If these estimates were used for flurbiprofen dose adjustment, taking 100 % for genotype *1/*1, an average reduction to 84 %, 60 %, 68 %, 43 %, and 19 % would result for genotype *1/*2, *1/*3, *2/*2, *2/*3, and *3/*3, respectively. Due to the large individual variation within genotypes with coefficients of variation ≥ 20 % and supposing the normal distribution, one in three individuals would be out of the average optimum dose by more than 20 %, one in 20 would be 40 % off. Whether this problem also applies to other CYPs and other drugs has to be investigated case by case. Our data for the given example, however, puts the benefit of individual drug dosing to question, if it is exclusively based on genotype.

Rational Design of a Corynebacterium glutamicum Pantothenate Production Strain and Ins Characterization by Metabolic Flux Analysis and Genome-Wide Transcriptional Profiling

Czech Academy of Sciences Publication Activity Database

Hüser, A.T.; Chassagnole, Ch.; Lindley, N.D.; Merkamm, M.; Guyonvarch, A.; Elišáková, Veronika; Pátek, Miroslav; Kalinowski, J.; Brune, I.; Pühler, A.; Tauch, A.

2005-01-01

Roč. 71, č. 6 (2005), s. 3255-3268 ISSN 0099-2240 Institutional research plan: CEZ:AV0Z50200510 Keywords : corynebacterium glutamicum * metabolic flux Subject RIV: EE - Microbiology, Virology Impact factor: 3.818, year: 2005

Differential phenotyping of Brucella species using a newly developed semi-automated metabolic system

Directory of Open Access Journals (Sweden)

Appel Bernd

2010-10-01

Full Text Available Abstract Background A commercial biotyping system (Taxa Profile™, Merlin Diagnostika testing the metabolization of various substrates by bacteria was used to determine if a set of phenotypic features will allow the identification of members of the genus Brucella and their differentiation into species and biovars. Results A total of 191 different amines, amides, amino acids, other organic acids and heterocyclic and aromatic substrates (Taxa Profile™ A, 191 different mono-, di-, tri- and polysaccharides and sugar derivates (Taxa Profile™ C and 95 amino peptidase- and protease-reactions, 76 glycosidase-, phosphatase- and other esterase-reactions, and 17 classic reactions (Taxa Profile™ E were tested with the 23 reference strains representing the currently known species and biovars of Brucella and a collection of 60 field isolates. Based on specific and stable reactions a 96-well "Brucella identification and typing" plate (Micronaut™ was designed and re-tested in 113 Brucella isolates and a couple of closely related bacteria. Brucella species and biovars revealed characteristic metabolic profiles and each strain showed an individual pattern. Due to their typical metabolic profiles a differentiation of Brucella isolates to the species level could be achieved. The separation of B. canis from B. suis bv 3, however, failed. At the biovar level, B. abortus bv 4, 5, 7 and B. suis bv 1-5 could be discriminated with a specificity of 100%. B. melitensis isolates clustered in a very homogenous group and could not be resolved according to their assigned biovars. Conclusions The comprehensive testing of metabolic activity allows cluster analysis within the genus Brucella. The biotyping system developed for the identification of Brucella and differentiation of its species and biovars may replace or at least complement time-consuming tube testing especially in case of atypical strains. An easy to handle identification software facilitates the

Co-factor engineering in lactobacilli: Effects of uncoupled ATPase activity on metabolic fluxes in Lactobacillus (L.) plantarum and L. sakei

DEFF Research Database (Denmark)

Rud, Ida; Solem, Christian; Jensen, Peter Ruhdal

2008-01-01

The hydrolytic F-1-part of the F1F0-ATPase was over-expressed in Lactobacillus (L.) plantarum NC8 and L. sakei Lb790x during fermentation of glucose or ribose, in order to study how changes in the intracellular levels of ATP and ADP affect the metabolic fluxes. The uncoupled ATPase activity...... resulted in a decrease in intracellular energy level (ATP/ADP ratio), biomass yield and growth rate. Interestingly, the glycolytic and ribolytic flux increased in L. plantarum with uncoupled ATPase activity compared to the reference strain by up to 20% and 50%, respectively. The ATP demand was estimated...... to have approximately 80% control on both the glycolytic and ribolytic flux in L. plantarum under these conditions. In contrast, the glycolytic and ribolytic flux decreased in L. sakei with uncoupled ATPase activity. (C) 2008 Elsevier Inc. All rights reserved....

Simple and robust determination of the activity signature of key carbohydrate metabolism enzymes for physiological phenotyping in model and crop plants

DEFF Research Database (Denmark)

Jammer, Alexandra; Gasperl, Anna; Luschin-Ebengreuth, Nora

2015-01-01

The analysis of physiological parameters is important to understand the link between plant phenotypes and their genetic bases, and therefore is needed as an important element in the analysis of model and crop plants. The activities of enzymes involved in primary carbohydrate metabolism have been...... shown to be strongly associated with growth performance, crop yield, and quality, as well as stress responses. A simple, fast, and cost-effective method to determine activities for 13 key enzymes involved in carbohydrate metabolism has been established, mainly based on coupled spectrophotometric kinetic...

Osteosarcopenic Visceral Obesity and Osteosarcopenic Subcutaneous Obesity, Two New Phenotypes of Sarcopenia: Prevalence, Metabolic Profile, and Risk Factors

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Spadaccini, Daniele; Nichetti, Mara; Avanzato, Ilaria; Faliva, Milena Anna

2018-01-01

Background The main criticism of the definition of “osteosarcopenic obesity” (OSO) is the lack of division between subcutaneous and visceral fat. This study describes the prevalence, metabolic profile, and risk factors of two new phenotypes of sarcopenia: osteosarcopenic visceral obesity (OSVAT) and osteosarcopenic subcutaneous obesity (OSSAT). Methods A standardized geriatric assessment was performed by anthropometric and biochemical measures. Dual-energy X-ray absorptiometry (DXA) was used to assess body composition, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), osteoporosis, and sarcopenia. Results A sample of 801 subjects were assessed (247 men; 554 women). The prevalence of osteosarcopenic obesity (OSO) was 6.79%; OSSAT and OSOVAT were, respectively, 2.22% and 4.56%. OSVAT (versus the others) showed a higher level of inflammation (CRP and ESR, p < 0.05), bilirubin (p < 0.05), and risk of fractures (FRAX index over 15%, p < 0.001). Subjects with OSSAT did not show any significant risk factors associated to obesity. Conclusions The osteosarcopenic visceral obesity phenotype (OSVAT) seems to be associated with a higher risk of fractures, inflammation, and a worse metabolic profile. These conditions in OSVAT cohort are associated with an increase of visceral adipose tissue, while patients with OSSAT seem to benefit related to the “obesity paradox”. PMID:29862078

A dynamic metabolic flux analysis of ABE (acetone-butanol-ethanol) fermentation by Clostridium acetobutylicum ATCC 824, with riboflavin as a by-product.

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Zhao, Xinhe; Kasbi, Mayssa; Chen, Jingkui; Peres, Sabine; Jolicoeur, Mario

2017-12-01

The present study reveals that supplementing sodium acetate (NaAc) strongly stimulates riboflavin production in acetone-butanol-ethanol (ABE) fermentation by Clostridium acetobutylicum ATCC 824 with xylose as carbon source. Riboflavin production increased from undetectable concentrations to ∼0.2 g L -1 (0.53 mM) when supplementing 60 mM NaAc. Of interest, solvents production and biomass yield were also promoted with fivefold acetone, 2.6-fold butanol, and 2.4-fold biomass adding NaAc. A kinetic metabolic model, developed to simulate ABE biosystem, with riboflavin production, revealed from a dynamic metabolic flux analysis (dMFA) simultaneous increase of riboflavin (ribA) and GTP (precursor of riboflavin) (PurM) synthesis flux rates under NaAc supplementation. The model includes 23 fluxes, 24 metabolites, and 72 kinetic parameters. It also suggested that NaAc condition has first stimulated the accumulation of intracellular metabolite intermediates during the acidogenic phase, which have then fed the solventogenic phase leading to increased ABE production. In addition, NaAc resulted in higher intracellular levels of NADH during the whole culture. Moreover, lower GTP-to-adenosine phosphates (ATP, ADP, AMP) ratio under NaAc supplemented condition suggests that GTP may have a minor role in the cell energetic metabolism compared to its contribution to riboflavin synthesis. © 2017 Wiley Periodicals, Inc.

Metabolic control over the oxygen consumption flux in intact skeletal muscle: in silico studies.

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Liguzinski, Piotr; Korzeniewski, Bernard

2006-12-01

It has been postulated previously that a direct activation of all oxidative phosphorylation complexes in parallel with the activation of ATP usage and substrate dehydrogenation (the so-called each-step activation) is the main mechanism responsible for adjusting the rate of ATP production by mitochondria to the current energy demand during rest-to-work transition in intact skeletal muscle in vivo. The present in silico study, using a computer model of oxidative phosphorylation developed previously, analyzes the impact of the each-step-activation mechanism on the distribution of control (defined within Metabolic Control Analysis) over the oxygen consumption flux among the components of the bioenergetic system in intact oxidative skeletal muscle at different energy demands. It is demonstrated that in the absence of each-step activation, the oxidative phosphorylation complexes take over from ATP usage most of the control over the respiration rate and oxidative ATP production at higher (but still physiological) energy demands. This leads to a saturation of oxidative phosphorylation, impossibility of a further acceleration of oxidative ATP synthesis, and dramatic drop in the phosphorylation potential. On the other hand, the each-step-activation mechanism allows maintenance of a high degree of the control exerted by ATP usage over the ATP turnover and oxygen consumption flux even at high energy demands and thus enables a potentially very large increase in ATP turnover. It is also shown that low oxygen concentration shifts the metabolic control from ATP usage to cytochrome oxidase and thus limits the oxidative ATP production.

Elucidating the Metabolic Plasticity of Cancer: Mitochondrial Reprogramming and Hybrid Metabolic States

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Dongya Jia

2018-03-01

Full Text Available Aerobic glycolysis, also referred to as the Warburg effect, has been regarded as the dominant metabolic phenotype in cancer cells for a long time. More recently, it has been shown that mitochondria in most tumors are not defective in their ability to carry out oxidative phosphorylation (OXPHOS. Instead, in highly aggressive cancer cells, mitochondrial energy pathways are reprogrammed to meet the challenges of high energy demand, better utilization of available fuels and macromolecular synthesis for rapid cell division and migration. Mitochondrial energy reprogramming is also involved in the regulation of oncogenic pathways via mitochondria-to-nucleus retrograde signaling and post-translational modification of oncoproteins. In addition, neoplastic mitochondria can engage in crosstalk with the tumor microenvironment. For example, signals from cancer-associated fibroblasts can drive tumor mitochondria to utilize OXPHOS, a process known as the reverse Warburg effect. Emerging evidence shows that cancer cells can acquire a hybrid glycolysis/OXPHOS phenotype in which both glycolysis and OXPHOS can be utilized for energy production and biomass synthesis. The hybrid glycolysis/OXPHOS phenotype facilitates metabolic plasticity of cancer cells and may be specifically associated with metastasis and therapy-resistance. Moreover, cancer cells can switch their metabolism phenotypes in response to external stimuli for better survival. Taking into account the metabolic heterogeneity and plasticity of cancer cells, therapies targeting cancer metabolic dependency in principle can be made more effective.

Temporal fluxomics reveals oscillations in TCA cycle flux throughout the mammalian cell cycle.

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Ahn, Eunyong; Kumar, Praveen; Mukha, Dzmitry; Tzur, Amit; Shlomi, Tomer

2017-11-06

Cellular metabolic demands change throughout the cell cycle. Nevertheless, a characterization of how metabolic fluxes adapt to the changing demands throughout the cell cycle is lacking. Here, we developed a temporal-fluxomics approach to derive a comprehensive and quantitative view of alterations in metabolic fluxes throughout the mammalian cell cycle. This is achieved by combining pulse-chase LC-MS-based isotope tracing in synchronized cell populations with computational deconvolution and metabolic flux modeling. We find that TCA cycle fluxes are rewired as cells progress through the cell cycle with complementary oscillations of glucose versus glutamine-derived fluxes: Oxidation of glucose-derived flux peaks in late G1 phase, while oxidative and reductive glutamine metabolism dominates S phase. These complementary flux oscillations maintain a constant production rate of reducing equivalents and oxidative phosphorylation flux throughout the cell cycle. The shift from glucose to glutamine oxidation in S phase plays an important role in cell cycle progression and cell proliferation. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

A genetic screen for increasing metabolic flux in the isoprenoid pathway of Saccharomyces cerevisiae: Isolation of SPT15 mutants using the screen

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M. Wadhwa

2016-12-01

Full Text Available A genetic screen to identify mutants that can increase flux in the isoprenoid pathway of yeast has been lacking. We describe a carotenoid-based visual screen built with the core carotenogenic enzymes from the red yeast Rhodosporidium toruloides. Enzymes from this yeast displayed the required, higher capacity in the carotenoid pathway. The development also included the identification of the metabolic bottlenecks, primarily phytoene dehydrogenase, that was subjected to a directed evolution strategy to yield more active mutants. To further limit phytoene pools, a less efficient version of GGPP synthase was employed. The screen was validated with a known flux increasing gene, tHMG1. New mutants in the TATA binding protein SPT15 were isolated using this screen that increased the yield of carotenoids, and an alternate isoprenoid, α-Farnesene confirming increase in overall flux. The findings indicate the presence of previously unknown links to the isoprenoid pathway that can be uncovered using this screen. Keywords: Metabolic engineering, Carotenoids, Isoprenoids, α-Farnesene, Rhodosporidium toruloides, SPT15

Alternative methods for CYP2D6 phenotyping: comparison of dextromethorphan metabolic ratios from AUC, single point plasma, and urine.

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Chen, Rui; Wang, Haotian; Shi, Jun; Hu, Pei

2016-05-01

CYP2D6 is a high polymorphic enzyme. Determining its phenotype before CYP2D6 substrate treatment can avoid dose-dependent adverse events or therapeutic failures. Alternative phenotyping methods of CYP2D6 were compared to aluate the appropriate and precise time points for phenotyping after single-dose and ultiple-dose of 30-mg controlled-release (CR) dextromethorphan (DM) and to explore the antimodes for potential sampling methods. This was an open-label, single and multiple-dose study. 21 subjects were assigned to receive a single dose of CR DM 30 mg orally, followed by a 3-day washout period prior to oral administration of CR DM 30 mg every 12 hours for 6 days. Metabolic ratios (MRs) from AUC∞ after single dosing and from AUC0-12h at steady state were taken as the gold standard. The correlations of metabolic ratios of DM to dextrorphan (MRDM/DX) values based on different phenotyping methods were assessed. Linear regression formulas were derived to calculate the antimodes for potential sample methods. In the single-dose part of the study statistically significant correlations were found between MRDM/DX from AUC∞ and from serial plasma points from 1 to 30 hours or from urine (all p-values < 0.001). In the multiple-dose part, statistically significant correlations were found between MRDM/DX from AUC0-12h on day 6 and MRDM/DX from serial plasma points from 0 to 36 hours after the last dosing (all p-values < 0.001). Based on reported urinary antimode and linear regression analysis, the antimodes of AUC and plasma points were derived to profile the trend of antimodes as the drug concentrations changed. MRDM/DX from plasma points had good correlations with MRDM/DX from AUC. Plasma points from 1 to 30 hours after single dose of 30-mg CR DM and any plasma point at steady state after multiple doses of CR DM could potentially be used for phenotyping of CYP2D6.

Adverse metabolic phenotype of female offspring exposed to preeclampsia in utero: a characterization of the BPH/5 mouse in postnatal life.

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Sutton, Elizabeth F; Lob, Heinrich E; Song, Jiunn; Xia, YunWei; Butler, Scott; Liu, Chin-Chi; Redman, Leanne M; Sones, Jenny L

2017-04-01

Preeclampsia (PE) is a devastating disorder of pregnancy that classically presents with maternal hypertension and proteinuria after 20 wk of gestation. In addition to being a leading cause of maternal and fetal morbidity/mortality, epidemiological and prospective studies have revealed long-term consequences for both the mother and baby of preeclamptic pregnancies, including chronic hypertension as well as other cardiovascular diseases and metabolic derangements. To better understand the effect of in utero exposure of PE on offspring, we utilized the BPH/5 mouse, a spontaneous model of the maternal and fetal PE syndrome. We hypothesized that young BPH/5 offspring would have altered metabolic and cardiovascular phenotypes. Indeed, BPH/5 growth-restricted offspring showed excess catch-up growth by early adulthood due to hyperphagia and increased white adipose tissue (WAT) accumulation, with inflammation markers isolated to the reproductive WAT depot only. Both excessive WAT accumulation and the inflammatory WAT phenotype were corrected by pair-feeding young BPH/5 female mice. We also found that young BPH/5 female mice showed evidence of leptin resistance. Indeed, chronic hyperleptinemia has been shown to characterize other rodent models of PE; however, the maternal metabolic profile before pregnancy has not been fully understood. Furthermore, we found that these mice show signs of cardiovascular anomalies (hypertension and cardiomegaly) and altered signaling within the reproductive axis in early life. Future studies will involve challenging the physiological metabolic state of BPH/5 mice through pair-feeding to reduce WAT before pregnancy and determining its causal role in adverse pregnancy outcomes. Copyright © 2017 the American Physiological Society.

Individual Differences in the Phenotypic Flexibility of Basal Metabolic Rate in Siberian Hamsters Are Consistent on Short- and Long-Term Timescales.

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Boratyński, Jan S; Jefimow, Małgorzata; Wojciechowski, Michał S

Basal metabolic rate (BMR) correlates with the cost of life in endothermic animals. It usually differs consistently among individuals in a population, but it may be adjusted in response to predictable or unpredictable changes in the environment. The phenotypic flexibility of BMR is considered an adaptation to living in a stochastic environment; however, whether it is also repeatable it is still unexplored. Assuming that variations in phenotypic flexibility are evolutionarily important, we hypothesized that they are consistently different among individuals. We predicted that not only BMR but also its flexibility in response to changes in ambient temperature (T a ) are repeatable on short- and long-term timescales. To examine this, we acclimated Siberian hamsters (Phodopus sungorus) for 100 d to winterlike and then to summerlike conditions, and after each acclimation we exposed them interchangeably to 10° and 28°C for 14 d. The difference in BMR measured after each exposure defined an individual's phenotypic flexibility (ΔBMR). BMR was repeatable within and among seasons. It was also flexible in both seasons, but in winter this flexibility was lower in individuals responding to seasonal changes than in nonresponding ones. When we accounted for individual responsiveness, the repeatability of ΔBMR was significant in winter (τ = 0.48, P = 0.01) and in summer (τ = 0.55, P = 0.005). Finally, the flexibility of BMR in response to changes in T a was also repeatable on a long-term timescale, that is, among seasons (τ = 0.31, P = 0.008). Our results indicate the evolutionary importance of the phenotypic flexibility of energy metabolism and suggest that it may be subject to selection.

Niacin and olive oil promote skewing to the M2 phenotype in bone marrow-derived macrophages of mice with metabolic syndrome.

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Montserrat-de la Paz, Sergio; Naranjo, Maria C; Lopez, Sergio; Abia, Rocio; Muriana, Francisco J G; Bermudez, Beatriz

2016-05-18

Metabolic syndrome (MetS) is associated with obesity, dyslipemia, type 2 diabetes and chronic low-grade inflammation. The aim of this study was to determine the role of high-fat low-cholesterol diets (HFLCDs) rich in SFAs (HFLCD-SFAs), MUFAs (HFLCD-MUFAs) or MUFAs plus omega-3 long-chain PUFAs (HFLCD-PUFAs) on polarisation and inflammatory potential in bone marrow-derived macrophages (BMDMs) from niacin (NA)-treated Lep(ob/ob)LDLR(-/-) mice. Animals fed with HFLCD-SFAs had increased weight and serum triglycerides, and their BMDMs accumulated triglycerides over the animals fed with HFLCD-MUFAs or -PUFAs. Furthermore, BMDMs from animals fed with HFLCD-SFAs were polarised towards the M1 phenotype with functional competence to produce pro-inflammatory cytokines, whereas BMDMs from animals fed with HFLCD-MUFAs or -PUFAs were skewed to the anti-inflammatory M2 phenotype. These findings open opportunities for developing novel nutritional strategies with olive oil as the most important dietary source of MUFAs (notably oleic acid) to prevent development and progression of metabolic complications in the NA-treated MetS.

Estimating biological elementary flux modes that decompose a flux distribution by the minimal branching property

DEFF Research Database (Denmark)

Chan, Siu Hung Joshua; Solem, Christian; Jensen, Peter Ruhdal

2014-01-01

biologically feasible EFMs by considering their graphical properties. A previous study on the transcriptional regulation of metabolic genes found that distinct branches at a branch point metabolite usually belong to distinct metabolic pathways. This suggests an intuitive property of biologically feasible EFMs......, i.e. minimal branching. RESULTS: We developed the concept of minimal branching EFM and derived the minimal branching decomposition (MBD) to decompose flux distributions. Testing in the core Escherichia coli metabolic network indicated that MBD can distinguish branches at branch points and greatly...... knowledge, which facilitates interpretation. Comparison of the methods applied to a complex flux distribution in Lactococcus lactis similarly showed the advantages of MBD. The minimal branching EFM concept underlying MBD should be useful in other applications....

Environmental spread of microbes impacts the development of metabolic phenotypes in mice transplanted with microbial communities from humans

DEFF Research Database (Denmark)

Zhang, Li; Bahl, Martin Iain; Roager, Henrik Munch

2017-01-01

Microbiota transplantation to germ-free animals is a powerful method to study involvement of gut microbes in the aetiology of metabolic syndrome. Owing to large interpersonal variability in gut microbiota, studies with broad coverage of donors are needed to elucidate the establishment of human......, thereby allowing us to explore the extent of microbial spread between cages in a well-controlled environment. Despite high group-wise similarity between obese and control human microbiotas, transplanted mice in the four isolators developed distinct gut bacterial composition and activity, body mass gain......, and insulin resistance. Spread of microbes between cages within isolators interacted with establishment of the transplanted microbiotas in mice, and contributed to the transmission of metabolic phenotypes. Our findings highlight the impact of donor variability and reveal that inter-individual spread...

¹³C metabolic flux analysis identifies an unusual route for pyruvate dissimilation in mycobacteria which requires isocitrate lyase and carbon dioxide fixation.

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Dany J V Beste

2011-07-01

Full Text Available Mycobacterium tuberculosis requires the enzyme isocitrate lyase (ICL for growth and virulence in vivo. The demonstration that M. tuberculosis also requires ICL for survival during nutrient starvation and has a role during steady state growth in a glycerol limited chemostat indicates a function for this enzyme which extends beyond fat metabolism. As isocitrate lyase is a potential drug target elucidating the role of this enzyme is of importance; however, the role of isocitrate lyase has never been investigated at the level of in vivo fluxes. Here we show that deletion of one of the two icl genes impairs the replication of Mycobacterium bovis BCG at slow growth rate in a carbon limited chemostat. In order to further understand the role of isocitrate lyase in the central metabolism of mycobacteria the effect of growth rate on the in vivo fluxes was studied for the first time using ¹³C-metabolic flux analysis (MFA. Tracer experiments were performed with steady state chemostat cultures of BCG or M. tuberculosis supplied with ¹³C labeled glycerol or sodium bicarbonate. Through measurements of the ¹³C isotopomer labeling patterns in protein-derived amino acids and enzymatic activity assays we have identified the activity of a novel pathway for pyruvate dissimilation. We named this the GAS pathway because it utilizes the Glyoxylate shunt and Anapleurotic reactions for oxidation of pyruvate, and Succinyl CoA synthetase for the generation of succinyl CoA combined with a very low flux through the succinate--oxaloacetate segment of the tricarboxylic acid cycle. We confirm that M. tuberculosis can fix carbon from CO₂ into biomass. As the human host is abundant in CO₂ this finding requires further investigation in vivo as CO₂ fixation may provide a point of vulnerability that could be targeted with novel drugs. This study also provides a platform for further studies into the metabolism of M. tuberculosis using ¹³C-MFA.

Label-free identification of macrophage phenotype by fluorescence lifetime imaging microscopy

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Alfonso-García, Alba; Smith, Tim D.; Datta, Rupsa; Luu, Thuy U.; Gratton, Enrico; Potma, Eric O.; Liu, Wendy F.

2016-04-01

Macrophages adopt a variety of phenotypes that are a reflection of the many functions they perform as part of the immune system. In particular, metabolism is a phenotypic trait that differs between classically activated, proinflammatory macrophages, and alternatively activated, prohealing macrophages. Inflammatory macrophages have a metabolism based on glycolysis while alternatively activated macrophages generally rely on oxidative phosphorylation to generate chemical energy. We employ this shift in metabolism as an endogenous marker to identify the phenotype of individual macrophages via live-cell fluorescence lifetime imaging microscopy (FLIM). We demonstrate that polarized macrophages can be readily discriminated with the aid of a phasor approach to FLIM, which provides a fast and model-free method for analyzing fluorescence lifetime images.

Use of microdose phenotyping to individualise dosing of patients.

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Hohmann, Nicolas; Haefeli, Walter E; Mikus, Gerd

2015-09-01

Administering the right amount of the right drug at the right time is a key mission of clinical medicine. This comprises dose adaptation according to a patient's intrinsic and extrinsic factors influencing drug disposition. Several biomarkers are available for dose adaptation; still, prediction of individual drug disposition may be improved. Phenotyping is the quantification of drug metabolism with probe substrates specific to drug-metabolising enzymes. This allows measurement of baseline metabolism and changes after modulation of drug metabolism. This article explores the concept of phenotyping using pharmacologically ineffective microdoses of probe substrates to obtain information on drug metabolism. Several probe drugs such as midazolam for cytochrome P450 3A have already been used, but validation of other microdosed probe drugs, analytical procedures and drug formulations still face some challenges that have to be overcome. Since microdosed probe drugs have no risk of adverse drug reactions or interference with therapy, more widespread use is possible. This allows drug-drug interaction data to be safely obtained during first-in-man studies, enhancing the clinical safety of human healthy volunteers and patients in clinical trials, and, most importantly, allows determination of the drug-metabolising phenotype in severely ill patients. With harmless probe drugs at hand quantifying drug metabolism and adapting the dose accordingly, a phenotyping-based dosing strategy could become reality, offering the possibility of individualised drug therapy with reduced adverse effects and fewer therapeutic failures.

Experimental and analytical variation in human urine in 1H NMR spectroscopy-based metabolic phenotyping studies.

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Maher, Anthony D; Zirah, Séverine F M; Holmes, Elaine; Nicholson, Jeremy K

2007-07-15

1H NMR spectroscopy potentially provides a robust approach for high-throughput metabolic screening of biofluids such as urine and plasma, but sample handling and preparation need careful optimization to ensure that spectra accurately report biological status or disease state. We have investigated the effects of storage temperature and time on the 1H NMR spectral profiles of human urine from two participants, collected three times a day on four different days. These were analyzed using modern chemometric methods. Analytical and preparation variation (tested between -40 degrees C and room temperature) and time of storage (to 24 h) were found to be much less influential than biological variation in sample classification. Statistical total correlation spectroscopy and discriminant function methods were used to identify the specific metabolites that were hypervariable due to preparation and biology. Significant intraindividual variation in metabolite profiles were observed even for urine collected on the same day and after at least 6 h fasting. The effect of long-term storage at different temperatures was also investigated, showing urine is stable if frozen for at least 3 months and that storage at room temperature for long periods (1-3 months) results in a metabolic profile explained by bacterial activity. Presampling (e.g., previous day) intake of food and medicine can also strongly influence the urinary metabolic profiles indicating that collective detailed participant historical meta data are important for interpretation of metabolic phenotypes and for avoiding false biomarker discovery.

Phenotypes and enviromental factors: their influence in PCOS.

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Diamanti-Kandarakis, Evanthia; Christakou, Charikleia; Marinakis, Evangelos

2012-01-01

Polycystic ovary syndrome (PCOS) is a complex syndrome of unclear etiopathogenesis characterized by heterogeneity in phenotypic manifestations. The clinical phenotype of PCOS includes reproductive and hormonal aberrations, namely anovulation and hyperandrogenism, which coexist with metabolic disturbances. Reflecting the crosstalk between the reproductive system and metabolic tissues, obesity not only deteriorates the metabolic profile but also aggravates ovulatory dysfunction and hyperandrogenism. Although the pathogenesis of PCOS remains unclear, the syndrome appears to involve environmental and genetic components. Starting from early life and extending throughout lifecycle, environmental insults may affect susceptible women who finally demonstrate the clinical phenotype of PCOS. Diet emerges as the major environmental determinant of PCOS. Overnutrition leading to obesity is widely recognized to have an aggravating impact, while another detrimental dietary factor may be the high content of food in advanced glycated end products (AGEs). Environmental exposure to industrial products, particularly Bisphenol A (BPA), may also exacerbate the clinical course of PCOS. AGEs and BPA may act as endocrine disruptors in the pathogenesis of the syndrome. PCOS appears to mirror the harmful influence of the modern environment on the reproductive and metabolic balance of inherently predisposed individuals.

Cross-sectional analysis of the effects of age on the hormonal, metabolic, and ultrasonographic features and the prevalence of the different phenotypes of polycystic ovary syndrome.

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Panidis, Dimitrios; Tziomalos, Konstantinos; Macut, Djuro; Delkos, Dimitrios; Betsas, George; Misichronis, Georgios; Katsikis, Ilias

2012-02-01

To assess the effects of age on the hormonal, metabolic, and ultrasonographic features of polycystic ovary syndrome (PCOS). Observational study. University department of obstetrics and gynecology. Patients with PCOS (n = 1,212) and healthy women (n = 254). None. Differences in the hormonal, metabolic, and ultrasonographic features of PCOS between age groups. A progressive decline in circulating androgens was observed with advancing age. Patients 21-30 years old had lower plasma glucose and insulin levels, lower area under the oral glucose tolerance test curve and lower homeostasis model assessment of insulin resistance index, and higher glucose/insulin and quantitative insulin sensitivity check index than patients 31-39 years old. The prevalence of PCOS phenotypes changed with age. More specifically, the distribution of the phenotypes did not differ substantially between patients ≤ 20 years old and patients 21-30 years old. However, a decline in the prevalence of phenotype 1 (characterized by anovulation, hyperandrogenemia, and polycystic ovaries) and an increase in the prevalence of phenotype 4 (characterized by anovulation and polycystic ovaries without hyperandrogenemia) were observed in patients 31-39 years old. In women with PCOS, hyperandrogenemia appears to diminish during reproductive life whereas insulin resistance worsens. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Interaction of storage carbohydrates and other cyclic fluxes with central metabolism: A quantitative approach by non-stationary 13C metabolic flux analysis

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C.A. Suarez-Mendez

2016-12-01

Full Text Available 13C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h−1 are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids, which are rearranged depending on the growth rate. At low growth rates the impact of the storage carbohydrate recycle is relatively more significant than at high growth rates due to a higher concentration of these materials in the cell (up to 560-fold and higher fluxes relative to the glucose uptake rate (up to 16%. Experimental observations suggest that glucose can be exported to the extracellular space, and that its source is related to storage carbohydrates, most likely via the export and subsequent extracellular breakdown of trehalose. This hypothesis is strongly supported by 13C-labeling experimental data, measured extracellular trehalose, and the corresponding flux estimations. Keywords: Non-stationary 13C labeling, Flux estimation, Trehalose, Glycogen, Amino acids

Individualized Hydrocodone Therapy Based on Phenotype, Pharmacogenetics, and Pharmacokinetic Dosing.

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Linares, Oscar A; Fudin, Jeffrey; Daly, Annemarie L; Boston, Raymond C

2015-12-01

(1) To quantify hydrocodone (HC) and hydromorphone (HM) metabolite pharmacokinetics with pharmacogenetics in CYP2D6 ultra-rapid metabolizer (UM), extensive metabolizer (EM), and poor metabolizer (PM) metabolizer phenotypes. (2) To develop an HC phenotype-specific dosing strategy for HC that accounts for HM production using clinical pharmacokinetics integrated with pharmacogenetics for patient safety. In silico clinical trial simulation. Healthy white men and women without comorbidities or history of opioid, or any other drug or nutraceutical use, age 26.3±5.7 years (mean±SD; range, 19 to 36 y) and weight 71.9±16.8 kg (range, 50 to 108 kg). CYP2D6 phenotype-specific HC clinical pharmacokinetic parameter estimates and phenotype-specific percentages of HM formed from HC. PMs had lower indices of HC disposition compared with UMs and EMs. Clearance was reduced by nearly 60% and the t1/2 was increased by about 68% compared with EMs. The canonical order for HC clearance was UM>EM>PM. HC elimination mainly by the liver, represented by ke, was reduced about 70% in PM. However, HC's apparent Vd was not significantly different among UMs, EMs, and PM. The canonical order of predicted plasma HM concentrations was UM>EM>PM. For each of the CYP2D6 phenotypes, the mean predicted HM levels were within HM's therapeutic range, which indicates HC has significant phenotype-dependent pro-drug effects. Our results demonstrate that pharmacogenetics afford clinicians an opportunity to individualize HC dosing, while adding enhanced opportunity to account for its conversion to HM in the body.

Dissolved organic matter and lake metabolism: Biogeochemistry and controls of nutrient flux dynamics to fresh waters. Technical progress report, January 1, 1990--December 31, 1991

Energy Technology Data Exchange (ETDEWEB)

Wetzel, R.G.

1992-12-31

The land-water interface region consists of two major components: the wetland, and the down-gradient adjacent littoral floating-leaved and submersed, macrophyte communities. Because of the importance of very high production and nutrient turnover of attached microbiota, a major emphasis of this investigation was placed upon these biota and their metabolic capacities for assimilation and release of organic compounds and nutrient retention and cycling. Examination of the capacities of wetland littoral communities to regulate fluxes of nutrients and organic compounds often has been limited to input-output analyses. These input-output data are an integral part of these investigations, but most of the research effort concentrated on the biotic and metabolic mechanisms that control fluxes and retention capacities and their effects upon biota in the down-gradient waters. The important regulatory capacities of dissolved organic compounds on enzyme reactivity was examined experimentally and coupled to the wetland-littoral organic carbon flux budgets.

Fast flux module detection using matroid theory.

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Reimers, Arne C; Bruggeman, Frank J; Olivier, Brett G; Stougie, Leen

2015-05-01

Flux balance analysis (FBA) is one of the most often applied methods on genome-scale metabolic networks. Although FBA uniquely determines the optimal yield, the pathway that achieves this is usually not unique. The analysis of the optimal-yield flux space has been an open challenge. Flux variability analysis is only capturing some properties of the flux space, while elementary mode analysis is intractable due to the enormous number of elementary modes. However, it has been found by Kelk et al. (2012) that the space of optimal-yield fluxes decomposes into flux modules. These decompositions allow a much easier but still comprehensive analysis of the optimal-yield flux space. Using the mathematical definition of module introduced by Müller and Bockmayr (2013b), we discovered useful connections to matroid theory, through which efficient algorithms enable us to compute the decomposition into modules in a few seconds for genome-scale networks. Using that every module can be represented by one reaction that represents its function, in this article, we also present a method that uses this decomposition to visualize the interplay of modules. We expect the new method to replace flux variability analysis in the pipelines for metabolic networks.

Characterization of the metabolic phenotype of rapamycin-treated CD8+ T cells with augmented ability to generate long-lasting memory cells.

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Shan He

Full Text Available BACKGROUND: Cellular metabolism plays a critical role in regulating T cell responses and the development of memory T cells with long-term protections. However, the metabolic phenotype of antigen-activated T cells that are responsible for the generation of long-lived memory cells has not been characterized. DESIGN AND METHODS: Using lymphocytic choriomeningitis virus (LCMV peptide gp33-specific CD8(+ T cells derived from T cell receptor transgenic mice, we characterized the metabolic phenotype of proliferating T cells that were activated and expanded in vitro in the presence or absence of rapamycin, and determined the capability of these rapamycin-treated T cells to generate long-lived memory cells in vivo. RESULTS: Antigen-activated CD8(+ T cells treated with rapamycin gave rise to 5-fold more long-lived memory T cells in vivo than untreated control T cells. In contrast to that control T cells only increased glycolysis, rapamycin-treated T cells upregulated both glycolysis and oxidative phosphorylation (OXPHOS. These rapamycin-treated T cells had greater ability than control T cells to survive withdrawal of either glucose or growth factors. Inhibition of OXPHOS by oligomycin significantly reduced the ability of rapamycin-treated T cells to survive growth factor withdrawal. This effect of OXPHOS inhibition was accompanied with mitochondrial hyperpolarization and elevation of reactive oxygen species that are known to be toxic to cells. CONCLUSIONS: Our findings indicate that these rapamycin-treated T cells may represent a unique cell model for identifying nutrients and signals critical to regulating metabolism in both effector and memory T cells, and for the development of new methods to improve the efficacy of adoptive T cell cancer therapy.

Cell-Free Protein Synthesis Enhancement from Real-Time NMR Metabolite Kinetics: Redirecting Energy Fluxes in Hybrid RRL Systems.

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Panthu, Baptiste; Ohlmann, Théophile; Perrier, Johan; Schlattner, Uwe; Jalinot, Pierre; Elena-Herrmann, Bénédicte; Rautureau, Gilles J P

2018-01-19

A counterintuitive cell-free protein synthesis (CFPS) strategy, based on reducing the ribosomal fraction in rabbit reticulocyte lysate (RRL), triggers the development of hybrid systems composed of RRL ribosome-free supernatant complemented with ribosomes from different mammalian cell-types. Hybrid RRL systems maintain translational properties of the original ribosome cell types, and deliver protein expression levels similar to RRL. Here, we show that persistent ribosome-associated metabolic activity consuming ATP is a major obstacle for maximal protein yield. We provide a detailed picture of hybrid CFPS systems energetic metabolism based on real-time nuclear magnetic resonance (NMR) investigation of metabolites kinetics. We demonstrate that protein synthesis capacity has an upper limit at native ribosome concentration and that lower amounts of the ribosomal fraction optimize energy fluxes toward protein translation, consequently increasing CFPS yield. These results provide a rationalized strategy for further mammalian CFPS developments and reveal the potential of real-time NMR metabolism phenotyping for optimization of cell-free protein expression systems.

In vivo 13C MRS in the mouse brain at 14.1 Tesla and metabolic flux quantification under infusion of [1,6-13C2]glucose.

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Lai, Marta; Lanz, Bernard; Poitry-Yamate, Carole; Romero, Jackeline F; Berset, Corina M; Cudalbu, Cristina; Gruetter, Rolf

2017-01-01

In vivo 13 C magnetic resonance spectroscopy (MRS) enables the investigation of cerebral metabolic compartmentation while, e.g. infusing 13 C-labeled glucose. Metabolic flux analysis of 13 C turnover previously yielded quantitative information of glutamate and glutamine metabolism in humans and rats, while the application to in vivo mouse brain remains exceedingly challenging. In the present study, 13 C direct detection at 14.1 T provided highly resolved in vivo spectra of the mouse brain while infusing [1,6- 13 C 2 ]glucose for up to 5 h. 13 C incorporation to glutamate and glutamine C4, C3, and C2 and aspartate C3 were detected dynamically and fitted to a two-compartment model: flux estimation of neuron-glial metabolism included tricarboxylic acid cycle (TCA) flux in astrocytes (V g  = 0.16 ± 0.03 µmol/g/min) and neurons (V TCA n  = 0.56 ± 0.03 µmol/g/min), pyruvate carboxylase activity (V PC  = 0.041 ± 0.003 µmol/g/min) and neurotransmission rate (V NT  = 0.084 ± 0.008 µmol/g/min), resulting in a cerebral metabolic rate of glucose (CMR glc ) of 0.38 ± 0.02 µmol/g/min, in excellent agreement with that determined with concomitant 18 F-fluorodeoxyglucose positron emission tomography ( 18 FDG PET).We conclude that modeling of neuron-glial metabolism in vivo is accessible in the mouse brain from 13 C direct detection with an unprecedented spatial resolution under [1,6- 13 C 2 ]glucose infusion.

Metabolic mechanisms behind the type 2 diabetes susceptible phenotype in low birth weight individuals

DEFF Research Database (Denmark)

Ribel-Madsen, Amalie

Background and aims: Low birth weight (LBW) individuals have an increased risk of developing insulin resistance and type 2 diabetes compared with normal birth weight (NBW) individuals. Accordingly, young, healthy, LBW men of the study population examined in the present plasma metabolome studies...... show impaired hepatic insulin sensitivity and, in contrast to NBW men, develop impaired peripheral insulin sensitivity in response to a 5-day high-fat overfeeding. However, the metabolic mechanisms behind the type 2 diabetes susceptible phenotype in LBW individuals are not clear. Our primary aim...... available for lipogenesis, including the synthesis of lipotoxic lipids such as ceramides and diacylglycerols that impair insulin signalling. In the second study, we demonstrated that LBW men had higher plasma alanine, proline, methionine, citrulline, and total amino acid levels after the HFHC diet compared...

A “Forward Genomics” Approach Links Genotype to Phenotype using Independent Phenotypic Losses among Related Species

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Michael Hiller

2012-10-01

Full Text Available Genotype-phenotype mapping is hampered by countless genomic changes between species. We introduce a computational “forward genomics” strategy that—given only an independently lost phenotype and whole genomes—matches genomic and phenotypic loss patterns to associate specific genomic regions with this phenotype. We conducted genome-wide screens for two metabolic phenotypes. First, our approach correctly matches the inactivated Gulo gene exactly with the species that lost the ability to synthesize vitamin C. Second, we attribute naturally low biliary phospholipid levels in guinea pigs and horses to the inactivated phospholipid transporter Abcb4. Human ABCB4 mutations also result in low phospholipid levels but lead to severe liver disease, suggesting compensatory mechanisms in guinea pig and horse. Our simulation studies, counts of independent changes in existing phenotype surveys, and the forthcoming availability of many new genomes all suggest that forward genomics can be applied to many phenotypes, including those relevant for human evolution and disease.

Thermodynamic principles governing metabolic operation : inference, analysis, and prediction

NARCIS (Netherlands)

Niebel, Bastian

2015-01-01

The principles governing metabolic flux are poorly understood. Because diverse organisms show similar metabolic flux patterns, we hypothesized that fundamental thermodynamic constraints might shape cellular metabolism. We developed a constraint-based model for Saccharomyces cerevisiae that included

Genetic Determinants of Cardio-Metabolic Risk: A Proposed Model for Phenotype Association and Interaction

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Blackett, Piers R; Sanghera, Dharambir K

2012-01-01

This review provides a translational and unifying summary of metabolic syndrome genetics and highlights evidence that genetic studies are starting to unravel and untangle origins of the complex and challenging cluster of disease phenotypes. The associated genes effectively express in the brain, liver, kidney, arterial endothelium, adipocytes, myocytes and β cells. Progression of syndrome traits has been associated with ectopic lipid accumulation in the arterial wall, visceral adipocytes, myocytes, and liver. Thus it follows that the genetics of dyslipidemia, obesity, and non-alcoholic fatty liver (NAFLD) disease are central in triggering progression of the syndrome to overt expression of disease traits, and have become a key focus of interest for early detection and for designing prevention and treatments. To support the “birds’ eye view” approach we provide a road-map depicting commonality and interrelationships between the traits and their genetic and environmental determinants based on known risk factors, metabolic pathways, pharmacological targets, treatment responses, gene networks, pleiotropy, and association with circadian rhythm. Although only a small portion of the known heritability is accounted for and there is insufficient support for clinical application of gene-based prediction models, there is direction and encouraging progress in a rapidly moving field that is beginning to show clinical relevance. PMID:23351585

Prevalence and metabolic characteristics of adrenal androgen excess in hyperandrogenic women with different phenotypes.

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Carmina, E; Lobo, R A

2007-02-01

Serum DHEAS has been found to be elevated in some women with polycystic ovary syndrome (PCOS). We wished to determine whether this prevalence is different in women with androgen excess who have different phenotypes and to correlate these findings with various cardiovascular and metabolic parameters. Two hundred and thirty-eight young hyperandrogenic women categorized into various diagnostic groups were evaluated for elevations in serum DHEAS, testosterone, glucose, insulin, quantitative insulin-sensitivity check index (QUICKI), cholesterol, HDL-C, LDL-C, triglycerides and C-reactive protein (CRP). Data were stratified based on elevations in DHEAS. Serum DHEAS was elevated in 39.5% for the entire group [36.7% in PCOS and 48.3% in idiopathic hyperandrogenism (IHA)]. In classic (C)-PCOS, the prevalence was 39.6% and in ovulatory (OV) PCOS it was 29.1%. These differences were not statistically significant. Women with elevated DHEAS had higher testosterone but lower insulin, higher QUICKI, lower total and LDL-cholesterol and higher HDL-cholesterol, pPCOS. The prevalence of adrenal hyperandrogenism, as determined by elevations in DHEAS, appears to be statistically similar in IHA, C-PCOS and compared to OV-PCOS. Metabolic and cardiovascular parameters were noted to be more favorable in those women who have higher DHEAS levels.

Fatty liver as a risk factor for progression from metabolically healthy to metabolically abnormal in non-overweight individuals.

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Hashimoto, Yoshitaka; Hamaguchi, Masahide; Fukuda, Takuya; Ohbora, Akihiro; Kojima, Takao; Fukui, Michiaki

2017-07-01

Recent studies identified that metabolically abnormal non-obese phenotype is a risk factor for cardiovascular diseases. However, little is known about risk factor for progression from metabolically healthy non-overweight to metabolically abnormal phenotype. We hypothesized that fatty liver had a clinical impact on progression from metabolically healthy non-overweight to metabolically abnormal phenotype. In this retrospective cohort study, 14,093 Japanese (7557 men and 6736 women), who received the health-checkup program from 2004 to 2012, were enrolled. Overweight and obesity were defined as body mass index 23.0-25.0 and ≥25.0 kg/m 2 . Four metabolic factors (impaired fasting glucose, hypertension, hypertriglyceridemia and low high density lipoprotein-cholesterol concentration) were used for definition of metabolically healthy (less than two factors) or metabolically abnormal (two or more). We divided the participants into three groups: metabolically healthy non-overweight (9755 individuals, men/women = 4290/5465), metabolically healthy overweight (2547 individuals, 1800/747) and metabolically healthy obesity (1791 individuals, 1267/524). Fatty liver was diagnosed by ultrasonography. Over the median follow-up period of 5.3 years, 873 metabolically healthy non-overweight, 512 metabolically healthy overweight and 536 metabolically healthy obesity individuals progressed to metabolically abnormal. The adjusted hazard risks of fatty liver on progression were 1.49 (95% confidence interval 1.20-1.83, p = 0.005) in metabolically healthy non-overweight, 1.37 (1.12-1.66, p = 0.002) in metabolically healthy overweight and 1.38 (1.15-1.66, p overweight individuals.

Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis

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Balagurunathan Balaji

2012-02-01

Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome

Saccharomyces cerevisiae metabolism in ecological context

OpenAIRE

Jouhten, Paula; Ponomarova, Olga; González García, Ramón; Patil, Kiran R.

2016-01-01

The architecture and regulation of Saccharomyces cerevisiae metabolic network are among the best studied owing to its widespread use in both basic research and industry. Yet, several recent studies have revealed notable limitations in explaining genotype?metabolic phenotype relations in this yeast, especially when concerning multiple genetic/environmental perturbations. Apparently unexpected genotype?phenotype relations may originate in the evolutionarily shaped cellular operating principles ...

Hyperandrogenemia in polycystic ovary syndrome: exploration of the role of free testosterone and androstenedione in metabolic phenotype.

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Elisabeth Lerchbaum

Full Text Available OBJECTIVE: To evaluate the association between androstenedione, testosterone, and free testosterone and metabolic disturbances in polycystic ovary syndrome. METHODS: We analyzed the association between androstenedione, testosterone, and free testosterone and metabolic parameters in a cross-sectional study including 706 polycystic ovary syndrome and 140 BMI-matched healthy women. Polycystic ovary syndrome women were categorized into 4 groups: normal androstenedione and normal free testosterone (NA/NFT, elevated androstenedione and normal free testosterone (HA/NFT, normal androstenedione and elevated free testosterone (NA/HFT, elevated androstenedione and free testosterone (HA/HFT. RESULTS: Polycystic ovary syndrome women with elevated free testosterone levels (HA/HFT and NA/HFT have an adverse metabolic profile including 2 h glucose, HbA1c, fasting and 2 h insulin, area under the insulin response curve, insulin resistance, insulin sensitivity index (Matsuda, triglycerides, total and high density lipoprotein cholesterol levels compared to NA/NFT (p<0.05 for all age- and BMI-adjusted analyses. In binary logistic regression analysis adjusted for age and BMI, odds ratio for insulin resistance was 2.78 (1.34-5.75, p = 0.006 for polycystic ovary syndrome women with HA/HFT compared to NA/NFT. We found no significantly increased risk of metabolic disorders in polycystic ovary syndrome women with HA/NFT. In multiple linear regression analyses (age- and BMI-adjusted, we found a significant negative association between androstenedione/free testosterone-ratio and area under the insulin response curve, insulin resistance, and total cholesterol/high density lipoprotein cholesterol-ratio and a positive association with Matsuda-index, and high density lipoprotein cholesterol (p<0.05 for all. CONCLUSIONS: Polycystic ovary syndrome women with elevated free testosterone levels but not with isolated androstenedione elevation have an adverse metabolic phenotype

Impact of genetic polymorphisms of SLC2A2, SLC2A5, and KHK on metabolic phenotypes in hypertensive individuals.

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MyPhuong T Le

Full Text Available In the past few decades, consumption of added sugars has increased dramatically. Studies have linked high sugar intake with increased risk for a number of diseases. Importantly, fructose, a component of sugar, has been linked with the development of features of metabolic syndrome. This study determined if single nucleotide polymorphisms in genes involved in fructose transport (solute carrier family 2 facilitated glucose transporter, member 2 (SLC2A2 and solute carrier family 2 facilitated glucose/fructose transporter, member 5 (SLC2A5 and metabolism (ketohexokinase (KHK affect inter-individual variability in metabolic phenotypes, such as increased serum uric acid levels.The influence of SLC2A2, SLC2A5, and KHK SNPs on metabolic phenotypes was tested in 237 European Americans and 167 African Americans from the Pharmacogenomic Evaluation and Antihypertensive Responses (PEAR study. Using baseline untreated fasting data, associations were considered significant if p≤0.005. These SNPs were then evaluated for potential replication (p≤0.05 using data from the Genetic Epidemiology of Responses to Antihypertensives (GERA studies.SLC2A5 rs5438 was associated with an increase in serum uric acid in European American males. However, we were unable to replicate the association in GERA. The minor allele of SLC2A2 rs8192675 showed an association with lower high-density lipoproteins in European Americans (A/A: 51.0 mg/dL, A/G: 47.0 mg/dL, G/G: 41.5 mg/dL, p = 0.0034 in PEAR. The association between rs8192675 and lower high-density lipoproteins was replicated in the combined European American GERA study samples (A/A: 47.6 mg/dL, A/G: 48.6 mg/dL, G/G: 41.9 mg/dL, p = 0.0315.The association between SLC2A2 rs8192675 and high-density lipoproteins suggests the polymorphism may play a role in influencing high-density lipoproteins and thus metabolic risk of cardiovascular disease.

Exploration of Energy Metabolism in the Mouse Using Indirect Calorimetry: Measurement of Daily Energy Expenditure (DEE) and Basal Metabolic Rate (BMR).

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Meyer, Carola W; Reitmeir, Peter; Tschöp, Matthias H

2015-09-01

Current comprehensive mouse metabolic phenotyping involves studying energy balance in cohorts of mice via indirect calorimetry, which determines heat release from changes in respiratory air composition. Here, we describe the measurement of daily energy expenditure (DEE) and basal metabolic rate (BMR) in mice. These well-defined metabolic descriptors serve as meaningful first-line read-outs for metabolic phenotyping and should be reported when exploring energy expenditure in mice. For further guidance, the issue of appropriate sample sizes and the frequency of sampling of metabolic measurements is also discussed. Copyright © 2015 John Wiley & Sons, Inc.

Interaction of storage carbohydrates and other cyclic fluxes with central metabolism: A quantitative approach by non-stationary 13C metabolic flux analysis.

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Suarez-Mendez, C A; Hanemaaijer, M; Ten Pierick, Angela; Wolters, J C; Heijnen, J J; Wahl, S A

2016-12-01

13 C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h -1 ) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are rearranged depending on the growth rate. At low growth rates the impact of the storage carbohydrate recycle is relatively more significant than at high growth rates due to a higher concentration of these materials in the cell (up to 560-fold) and higher fluxes relative to the glucose uptake rate (up to 16%). Experimental observations suggest that glucose can be exported to the extracellular space, and that its source is related to storage carbohydrates, most likely via the export and subsequent extracellular breakdown of trehalose. This hypothesis is strongly supported by 13 C-labeling experimental data, measured extracellular trehalose, and the corresponding flux estimations.

Maneuvering in the Complex Path from Genotype to Phenotype

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Strohman, Richard

2002-04-01

Human disease phenotypes are controlled not only by genes but by lawful self-organizing networks that display system-wide dynamics. These networks range from metabolic pathways to signaling pathways that regulate hormone action. When perturbed, networks alter their output of matter and energy which, depending on the environmental context, can produce either a pathological or a normal phenotype. Study of the dynamics of these networks by approaches such as metabolic control analysis may provide new insights into the pathogenesis and treatment of complex diseases.

Interaction of storage carbohydrates and other cyclic fluxes with central metabolism : A quantitative approach by non-stationary 13C metabolic flux analysis

NARCIS (Netherlands)

Suarez-Mendez, C. A.; Hanemaaijer, M.; ten Pierick, Angela; Wolters, J. C.; Heijnen, J.J.; Wahl, S. A.

2016-01-01

13C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h-1) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are

Testicular Metabolic Reprogramming in Neonatal Streptozotocin-Induced Type 2 Diabetic Rats Impairs Glycolytic Flux and Promotes Glycogen Synthesis

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Rato, L.; Alves, M. G.; Dias, T. R.; Cavaco, J. E.; Oliveira, Pedro F.

2015-01-01

Defects in testicular metabolism are directly implicated with male infertility, but most of the mechanisms associated with type 2 diabetes- (T2DM) induced male infertility remain unknown. We aimed to evaluate the effects of T2DM on testicular glucose metabolism by using a neonatal-streptozotocin- (n-STZ) T2DM animal model. Plasma and testicular hormonal levels were evaluated using specific kits. mRNA and protein expression levels were assessed by real-time PCR and Western Blot, respectively. Testicular metabolic profile was assessed by 1H-NMR spectroscopy. T2DM rats showed increased glycemic levels, impaired glucose tolerance and hyperinsulinemia. Both testicular and serum testosterone levels were decreased, whereas those of 17β-estradiol were not altered. Testicular glycolytic flux was not favored in testicles of T2DM rats, since, despite the increased expression of both glucose transporters 1 and 3 and the enzyme phosphofructokinase 1, lactate dehydrogenase activity was severely decreased contributing to lower testicular lactate content. However, T2DM enhanced testicular glycogen accumulation, by modulating the availability of the precursors for its synthesis. T2DM also affected the reproductive sperm parameters. Taken together these results indicate that T2DM is able to reprogram testicular metabolism by enhancing alternative metabolic pathways, particularly glycogen synthesis, and such alterations are associated with impaired sperm parameters. PMID:26064993

Cross-sectional surveillance study to phenotype lorry drivers’ sedentary behaviours, physical activity and cardio-metabolic health

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Varela-Mato, Veronica; O’Shea, Orlagh; King, James A; Yates, Thomas; Stensel, David J; Biddle, Stuart JH; Nimmo, Myra A; Clemes, Stacy A

2017-01-01

Objectives Elevated risk factors for a number of chronic diseases have been identified in lorry drivers. Unhealthy lifestyle behaviours such as a lack of physical activity (PA) and high levels of sedentary behaviour (sitting) likely contribute to this elevated risk. This study behaviourally phenotyped UK lorry drivers’ sedentary and non-sedentary behaviours during workdays and non-workdays and examined markers of drivers cardio-metabolic health. Setting A transport company from the East Midlands, UK. Participants A sample of 159 male heavy goods vehicle drivers (91% white European; (median (range)) age: 50 (24, 67) years) completed the health assessments. 87 (age: 50.0 (25.0, 65.0); body mass index (BMI): 27.7 (19.6, 43.4) kg/m2) provided objective information on sedentary and non-sedentary time. Outcomes Participants self-reported their sociodemographic information. Primary outcomes: sedentary behaviour and PA, assessed over 7 days using an activPAL3 inclinometer. Cardio-metabolic markers included: blood pressure (BP), heart rate, waist circumference (WC), hip circumference, body composition and fasted capillary blood glucose, triglycerides, high-density lipopreotein cholesterol, low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) levels. These cardio-metabolic markers were treated as secondary outcomes. Results Lorry drivers presented an unhealthy cardio-metabolic health profile (median (IQR) systolic BP: 129 (108.5, 164) mm Hg; diastolic BP: 81 (63, 104) mm Hg; BMI: 29 (20, 47) kg/m2; WC: 102 (77.5, 146.5) cm; LDL-C: 3 (1, 6) mmol/L; TC: 4.9 (3, 7.5) mmol/L). 84% were overweight or obese, 43% had type 2 diabetes or prediabetes and 34% had the metabolic syndrome. The subsample of lorry drivers with objective postural data (n=87) accumulated 13 hours/day and 8 hours/day of sedentary behaviour on workdays and non-workdays (pdrivers accrued 12 min/day on workdays and 6 min/day on non-workdays of moderate-to-vigorous PA (MVPA). Conclusion

Central carbon metabolism influences cellulase production in Bacillus licheniformis.

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Wang, J; Liu, S; Li, Y; Wang, H; Xiao, S; Li, C; Liu, B

2018-01-01

Bacillus licheniformis that can produce cellulase including endo glucanase and glucosidase is an important industrial microbe for cellulose degradation. The purpose of this research was to assess the effect of endo glucanase gene bglC and glucosidase gene bglH on the central metabolic flux in B. licheniformis. bglC and bglH were knocked out using homologous recombination method, respectively, and the corresponding knockout strains were obtained for 13 C metabolic flux analysis. A significant change was observed in metabolic fluxes after 13 C metabolic flux ratio analysis. In both of the knockout strains, the increased fluxes of the pentose phosphate pathway and malic enzyme reaction enabled an elevated supply of NADPH which provided enough reducing power for the in vivo synthesis reactions. The fluxes through tricarboxylic acid cycle and anaplerotic reactions increased fast in the two knockout strains, which meant more energy generated. The changed fluxes in central carbon metabolism provided a holistic view of the physiological status in B. licheniformis and possible targets for further strain engineering. Cellulase is very important in the field of agriculture and bioenergy because of its degrading effect on cellulosic biomass. This study presented the effect of central carbon metabolism on cellulase production in Bacillus licheniformis. The study also provided a holistic view of the physiological status in B. licheniformis. The shifted metabolism provided a quantitative evaluation of the biosynthesis of cellulase and a priority ranked target list for further strain engineering. © 2017 The Society for Applied Microbiology.

"Metabolic staging" after major trauma - a guide for clinical decision making?

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Moore Ernest E

2010-06-01

Full Text Available Abstract Metabolic changes after major trauma have a complex underlying pathophysiology. The early posttraumatic stress response is associated with a state of hyperinflammation, with increased oxygen consumption and energy expenditure. This hypercatabolic state must be recognized early and mandates an early nutritional management strategy. A proactive concept of early enteral "immunonutrition" in severely injured patients, is aimed at counterbalancing the negative aspects of hyperinflammation and hypercatabolism in order to reduce the risk of late complications, including infections and posttraumatic organ failure. Recently, the concept of "metabolic staging" has been advocated, which takes into account the distinct inflammatory phases and metabolic phenotypes after major trauma, including the "ischemia/reperfusion phenotype", the "leukocytic phenotype", and the "angiogenic phenotype". The potential clinical impact of metabolic staging, and of an appropriately adapted "metabolic control" and nutritional support, remains to be determined.

Producing Acetic Acid of Acetobacter pasteurianus by Fermentation Characteristics and Metabolic Flux Analysis.

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Wu, Xuefeng; Yao, Hongli; Liu, Qing; Zheng, Zhi; Cao, Lili; Mu, Dongdong; Wang, Hualin; Jiang, Shaotong; Li, Xingjiang

2018-03-19

The acetic acid bacterium Acetobacter pasteurianus plays an important role in acetic acid fermentation, which involves oxidation of ethanol to acetic acid through the ethanol respiratory chain under specific conditions. In order to obtain more suitable bacteria for the acetic acid industry, A. pasteurianus JST-S screened in this laboratory was compared with A. pasteurianus CICC 20001, a current industrial strain in China, to determine optimal fermentation parameters under different environmental stresses. The maximum total acid content of A. pasteurianus JST-S was 57.14 ± 1.09 g/L, whereas that of A. pasteurianus CICC 20001 reached 48.24 ± 1.15 g/L in a 15-L stir stank. Metabolic flux analysis was also performed to compare the reaction byproducts. Our findings revealed the potential value of the strain in improvement of industrial vinegar fermentation.

Regulation of adipose branched-chain amino acid catabolism enzyme expression and cross-adipose amino acid flux in human obesity

Science.gov (United States)

Lackey, Denise E.; Lynch, Christopher J.; Olson, Kristine C.; Mostaedi, Rouzbeh; Ali, Mohamed; Smith, William H.; Karpe, Fredrik; Humphreys, Sandy; Bedinger, Daniel H.; Dunn, Tamara N.; Thomas, Anthony P.; Oort, Pieter J.; Kieffer, Dorothy A.; Amin, Rajesh; Bettaieb, Ahmed; Haj, Fawaz G.; Permana, Paska; Anthony, Tracy G.

2013-01-01

Elevated blood branched-chain amino acids (BCAA) are often associated with insulin resistance and type 2 diabetes, which might result from a reduced cellular utilization and/or incomplete BCAA oxidation. White adipose tissue (WAT) has become appreciated as a potential player in whole body BCAA metabolism. We tested if expression of the mitochondrial BCAA oxidation checkpoint, branched-chain α-ketoacid dehydrogenase (BCKD) complex, is reduced in obese WAT and regulated by metabolic signals. WAT BCKD protein (E1α subunit) was significantly reduced by 35–50% in various obesity models (fa/fa rats, db/db mice, diet-induced obese mice), and BCKD component transcripts significantly lower in subcutaneous (SC) adipocytes from obese vs. lean Pima Indians. Treatment of 3T3-L1 adipocytes or mice with peroxisome proliferator-activated receptor-γ agonists increased WAT BCAA catabolism enzyme mRNAs, whereas the nonmetabolizable glucose analog 2-deoxy-d-glucose had the opposite effect. The results support the hypothesis that suboptimal insulin action and/or perturbed metabolic signals in WAT, as would be seen with insulin resistance/type 2 diabetes, could impair WAT BCAA utilization. However, cross-tissue flux studies comparing lean vs. insulin-sensitive or insulin-resistant obese subjects revealed an unexpected negligible uptake of BCAA from human abdominal SC WAT. This suggests that SC WAT may not be an important contributor to blood BCAA phenotypes associated with insulin resistance in the overnight-fasted state. mRNA abundances for BCAA catabolic enzymes were markedly reduced in omental (but not SC) WAT of obese persons with metabolic syndrome compared with weight-matched healthy obese subjects, raising the possibility that visceral WAT contributes to the BCAA metabolic phenotype of metabolically compromised individuals. PMID:23512805

From genomes to in silico cells via metabolic networks

DEFF Research Database (Denmark)

Borodina, Irina; Nielsen, Jens

2005-01-01

Genome-scale metabolic models are the focal point of systems biology as they allow the collection of various data types in a form suitable for mathematical analysis. High-quality metabolic networks and metabolic networks with incorporated regulation have been successfully used for the analysis...... of phenotypes from phenotypic arrays and in gene-deletion studies. They have also been used for gene expression analysis guided by metabolic network structure, leading to the identification of commonly regulated genes. Thus, genome-scale metabolic modeling currently stands out as one of the most promising...

Metabolic profiles to define the genome: can we hear the phenotypes?

OpenAIRE

Griffin, Julian L

2004-01-01

There is an increased reliance on genetically modified organisms as a functional genomic tool to elucidate the role of genes and their protein products. Despite this, many models do not express the expected phenotype thought to be associated with the gene or protein. There is thus an increased need to further define the phenotype resultant from a genetic modification to understand how the transcriptional or proteomic network may conspire to alter the expected phenotype. This is best typified ...

Genome-scale modeling for metabolic engineering.

Science.gov (United States)

Simeonidis, Evangelos; Price, Nathan D

2015-03-01

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

Beaver-mediated lateral hydrologic connectivity, fluvial carbon and nutrient flux, and aquatic ecosystem metabolism

Science.gov (United States)

Wegener, Pam; Covino, Tim; Wohl, Ellen

2017-06-01

River networks that drain mountain landscapes alternate between narrow and wide valley segments. Within the wide segments, beaver activity can facilitate the development and maintenance of complex, multithread planform. Because the narrow segments have limited ability to retain water, carbon, and nutrients, the wide, multithread segments are likely important locations of retention. We evaluated hydrologic dynamics, nutrient flux, and aquatic ecosystem metabolism along two adjacent segments of a river network in the Rocky Mountains, Colorado: (1) a wide, multithread segment with beaver activity; and, (2) an adjacent (directly upstream) narrow, single-thread segment without beaver activity. We used a mass balance approach to determine the water, carbon, and nutrient source-sink behavior of each river segment across a range of flows. While the single-thread segment was consistently a source of water, carbon, and nitrogen, the beaver impacted multithread segment exhibited variable source-sink dynamics as a function of flow. Specifically, the multithread segment was a sink for water, carbon, and nutrients during high flows, and subsequently became a source as flows decreased. Shifts in river-floodplain hydrologic connectivity across flows related to higher and more variable aquatic ecosystem metabolism rates along the multithread relative to the single-thread segment. Our data suggest that beaver activity in wide valleys can create a physically complex hydrologic environment that can enhance hydrologic and biogeochemical buffering, and promote high rates of aquatic ecosystem metabolism. Given the widespread removal of beaver, determining the cumulative effects of these changes is a critical next step in restoring function in altered river networks.

Computational Flux Balance Analysis Predicts that Stimulation of Energy Metabolism in Astrocytes and their Metabolic Interactions with Neurons Depend on Uptake of K+ Rather than Glutamate.

Science.gov (United States)

DiNuzzo, Mauro; Giove, Federico; Maraviglia, Bruno; Mangia, Silvia

2017-01-01

Brain activity involves essential functional and metabolic interactions between neurons and astrocytes. The importance of astrocytic functions to neuronal signaling is supported by many experiments reporting high rates of energy consumption and oxidative metabolism in these glial cells. In the brain, almost all energy is consumed by the Na + /K + ATPase, which hydrolyzes 1 ATP to move 3 Na + outside and 2 K + inside the cells. Astrocytes are commonly thought to be primarily involved in transmitter glutamate cycling, a mechanism that however only accounts for few % of brain energy utilization. In order to examine the participation of astrocytic energy metabolism in brain ion homeostasis, here we attempted to devise a simple stoichiometric relation linking glutamatergic neurotransmission to Na + and K + ionic currents. To this end, we took into account ion pumps and voltage/ligand-gated channels using the stoichiometry derived from available energy budget for neocortical signaling and incorporated this stoichiometric relation into a computational metabolic model of neuron-astrocyte interactions. We aimed at reproducing the experimental observations about rates of metabolic pathways obtained by 13 C-NMR spectroscopy in rodent brain. When simulated data matched experiments as well as biophysical calculations, the stoichiometry for voltage/ligand-gated Na + and K + fluxes generated by neuronal activity was close to a 1:1 relationship, and specifically 63/58 Na + /K + ions per glutamate released. We found that astrocytes are stimulated by the extracellular K + exiting neurons in excess of the 3/2 Na + /K + ratio underlying Na + /K + ATPase-catalyzed reaction. Analysis of correlations between neuronal and astrocytic processes indicated that astrocytic K + uptake, but not astrocytic Na + -coupled glutamate uptake, is instrumental for the establishment of neuron-astrocytic metabolic partnership. Our results emphasize the importance of K + in stimulating the activation of

Metabolic Reprogramming During Multidrug Resistance in Leukemias

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Raphael Silveira Vidal

2018-04-01

Full Text Available Cancer outcome has improved since introduction of target therapy. However, treatment success is still impaired by the same drug resistance mechanism of classical chemotherapy, known as multidrug resistance (MDR phenotype. This phenotype promotes resistance to drugs with different structures and mechanism of action. Recent reports have shown that resistance acquisition is coupled to metabolic reprogramming. High-gene expression, increase of active transport, and conservation of redox status are one of the few examples that increase energy and substrate demands. It is not clear if the role of this metabolic shift in the MDR phenotype is related to its maintenance or to its induction. Apart from the nature of this relation, the metabolism may represent a new target to avoid or to block the mechanism that has been impairing treatment success. In this mini-review, we discuss the relation between metabolism and MDR resistance focusing on the multiple non-metabolic functions that enzymes of the glycolytic pathway are known to display, with emphasis with the diverse activities of glyceraldehyde-3-phosphate dehydrogenase.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

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Kim Hyun

2011-12-01

Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

Science.gov (United States)

Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

[Hypertriglyceridemic waist phenotype: associated factors and comparison with other cardiovascular and metabolic risk indicators in the ELSA-Brasil study].

Science.gov (United States)

Freitas, Roberta Souza; Fonseca, Maria de Jesus Mendes da; Schmidt, Maria Inês; Molina, Maria Del Carmen Bisi; Almeida, Maria da Conceição Chagas de

2018-03-29

This study's objectives were to estimate the prevalence of hypertriglyceridemic waist (HTW) phenotype in participants in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), identify associated risk factors, and compare with other cardiovascular and metabolic risk indicators. This was a cross-sectional study with baseline data from a cohort of public employees. HTW is defined as the simultaneous presence of increased waist circumference (WC) (≥ 80cm for women, ≥ 90cm for men according to the International Diabetes Federation - IDF; and ≥ 88cm for women, ≥ 102cm for men according to the U.S. National Cholesterol Education Program - NCEP) and hypertriglyceridemia. Associations between independent variables and HTW were tested with multivariate logistic regression models. HTW was also compared to other cardiovascular and metabolic risk indicators by means of correlation tests, kappa index, sensitivity, and specificity. After exclusions, 12,811 participants were analyzed. Prevalence of HTW ranged from 24.7% (IDF) to 13.3% (NCEP). HTW was associated with age, excessive alcohol consumption, former smoking, low HDL, non-high HDL, and increased C-reactive protein, independently of gender or the criterion used to define HTW. HTW was associated with cardiovascular risk indicators, especially metabolic syndrome. The high prevalence of HTW and its association with cardiovascular risk indicators, especially metabolic syndrome, supports its use as a cardiometabolic risk screening tool in clinical practice.

The Influence of CYP2D6 Phenotype on the Pharmacokinetic Profile of Atomoxetine in Caucasian Healthy Subjects

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Todor Ioana

2017-06-01

Full Text Available Objective: To analyze a potential phenotypic variation within the studied group based on the pharmacokinetic profile of atomoxetine and its active metabolite, and to further investigate the impact of CYP2D6 phenotype on atomoxetine pharmacokinetics. Methods: The study was conducted as an open-label, non-randomized clinical trial which included 43 Caucasian healthy volunteers. Each subject received a single oral dose of atomoxetine 25 mg. Subsequently, atomoxetine and 4-hydroxyatomoxetine-O-glucuronide (glucuronidated active metabolite plasma concentrations were determined and a noncompartmental method was used to calculate the pharmacokinetic parameters of both compounds. Further on, the CYP2D6 metabolic phenotype was assessed using the area under the curve (AUC metabolic ratio (atomoxetine/ 4-hydroxyatomoxetine-O-glucuronide and specific statistical tests (Lilliefors (Kolgomorov-Smirnov and Anderson-Darling test. The phenotypic differences in atomoxetine disposition were identified based on the pharmacokinetic profile of the parent drug and its metabolite. Results: The statistical analysis revealed that the AUC metabolic ratio data set did not follow a normal distribution. As a result, two different phenotypes were identified, respectively the poor metabolizer (PM group which included 3 individuals and the extensive metabolizer (EM group which comprised the remaining 40 subjects. Also, it was demonstrated that the metabolic phenotype significantly influenced atomoxetine pharmacokinetics, as PMs presented a 4.5-fold higher exposure to the parent drug and a 3.2-fold lower exposure to its metabolite in comparison to EMs. Conclusions: The pharmacokinetic and statistical analysis emphasized the existence of 2 metabolic phenotypes: EMs and PMs. Furthermore, it was proved that the interphenotype variability had a marked influence on atomoxetine pharmacokinetic profile.

Cyanobacterial carbon metabolism: Fluxome plasticity and oxygen dependence: Cyanobacterial Carbon Metabolism

Energy Technology Data Exchange (ETDEWEB)

Wan, Ni [Washington Univ., St. Louis, MO (United States); DeLorenzo, Drew M. [Washington Univ., St. Louis, MO (United States); He, Lian [Washington Univ., St. Louis, MO (United States); You, Le [Washington Univ., St. Louis, MO (United States); Immethun, Cheryl M. [Washington Univ., St. Louis, MO (United States); Wang, George [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Baidoo, Edward E. K. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Hollinshead, Whitney [Washington Univ., St. Louis, MO (United States); Keasling, Jay D. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Technical Univ. of Denmark, Lyngby (Denmark); Moon, Tae Seok [Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis Missouri 63130; Tang, Yinjie J. [Washington Univ., St. Louis, MO (United States)

2017-03-30

Synechocystis sp. strain PCC 6803 has been widely used as a photo-biorefinery chassis. Based on its genome annotation, this species contains a complete TCA cycle, an Embden-Meyerhof-Parnas pathway (EMPP), an oxidative pentose phosphate pathway (OPPP), and an Entner–Doudoroff pathway (EDP). To evaluate how Synechocystis 6803 catabolizes glucose under heterotrophic conditions, we performed ¹³C metabolic flux analysis, metabolite pool size analysis, gene knockouts, and heterologous expressions. The results revealed a cyclic mode of flux through the OPPP. Small, but non-zero, fluxes were observed through the TCA cycle and the malic shunt. Independent knockouts of 6-phosphogluconate dehydrogenase (gnd) and malic enzyme (me) corroborated these results, as neither mutant could grow under dark heterotrophic conditions. Our data also indicate that Synechocystis 6803 metabolism relies upon oxidative phosphorylation to generate ATP from NADPH under dark or insufficient light conditions. The pool sizes of intermediates in the TCA cycle, particularly acetyl-CoA, were found to be several fold lower in Synechocystis 6803 (compared to E. coli metabolite pool sizes), while its sugar phosphate intermediates were several-fold higher. Moreover, negligible flux was detected through the native, or heterologous, EDP in the wild type or Δgnd strains under heterotrophic conditions. Comparing photoautotrophic, photomixotrophic, and heterotrophic conditions, the Calvin cycle, OPPP, and EMPP in Synechocystis 6803 possess the ability to regulate their fluxes under various growth conditions (plastic), whereas its TCA cycle always maintains at low levels (rigid). This work also demonstrates how genetic profiles do not always reflect actual metabolic flux through native or heterologous pathways. Biotechnol. Bioeng. 2017;114: 1593–1602. © 2017 Wiley Periodicals, Inc.

Cross-sectional surveillance study to phenotype lorry drivers' sedentary behaviours, physical activity and cardio-metabolic health.

Science.gov (United States)

Varela-Mato, Veronica; O'Shea, Orlagh; King, James A; Yates, Thomas; Stensel, David J; Biddle, Stuart Jh; Nimmo, Myra A; Clemes, Stacy A

2017-06-21

Elevated risk factors for a number of chronic diseases have been identified in lorry drivers. Unhealthy lifestyle behaviours such as a lack of physical activity (PA) and high levels of sedentary behaviour (sitting) likely contribute to this elevated risk. This study behaviourally phenotyped UK lorry drivers' sedentary and non-sedentary behaviours during workdays and non-workdays and examined markers of drivers cardio-metabolic health. A transport company from the East Midlands, UK. A sample of 159 male heavy goods vehicle drivers (91% white European; (median (range)) age: 50 (24, 67) years) completed the health assessments. 87 (age: 50.0 (25.0, 65.0); body mass index (BMI): 27.7 (19.6, 43.4) kg/m 2 ) provided objective information on sedentary and non-sedentary time. Participants self-reported their sociodemographic information. Primary outcomes: sedentary behaviour and PA, assessed over 7 days using an activPAL3 inclinometer. Cardio-metabolic markers included: blood pressure (BP), heart rate, waist circumference (WC), hip circumference, body composition and fasted capillary blood glucose, triglycerides, high-density lipopreotein cholesterol, low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC) levels. These cardio-metabolic markers were treated as secondary outcomes. Lorry drivers presented an unhealthy cardio-metabolic health profile (median (IQR) systolic BP: 129 (108.5, 164) mm Hg; diastolic BP: 81 (63, 104) mm Hg; BMI: 29 (20, 47) kg/m 2 ; WC: 102 (77.5, 146.5) cm; LDL-C: 3 (1, 6) mmol/L; TC: 4.9 (3, 7.5) mmol/L). 84% were overweight or obese, 43% had type 2 diabetes or prediabetes and 34% had the metabolic syndrome. The subsample of lorry drivers with objective postural data (n=87) accumulated 13 hours/day and 8 hours/day of sedentary behaviour on workdays and non-workdays (pdrivers accrued 12 min/day on workdays and 6 min/day on non-workdays of moderate-to-vigorous PA (MVPA). Lorry drivers demonstrate a high-risk cardio-metabolic

A holistic view of dietary carbohydrate utilization in lobster: digestion, postprandial nutrient flux, and metabolism.

Science.gov (United States)

Rodríguez-Viera, Leandro; Perera, Erick; Casuso, Antonio; Perdomo-Morales, Rolando; Gutierrez, Odilia; Scull, Idania; Carrillo, Olimpia; Martos-Sitcha, Juan A; García-Galano, Tsai; Mancera, Juan Miguel

2014-01-01

Crustaceans exhibit a remarkable variation in their feeding habits and food type, but most knowledge on carbohydrate digestion and utilization in this group has come from research on few species. The aim of this study was to make an integrative analysis of dietary carbohydrate utilization in the spiny lobster Panulirus argus. We used complementary methodologies such as different assessments of digestibility, activity measurements of digestive and metabolic enzymes, and post-feeding flux of nutrients and metabolites. Several carbohydrates were well digested by the lobster, but maize starch was less digestible than all other starches studied, and its inclusion in diet affected protein digestibility. Most intense hydrolysis of carbohydrates in the gastric chamber of lobster occurred between 2-6 h after ingestion and afterwards free glucose increased in hemolymph. The inclusion of wheat in diet produced a slow clearance of glucose from the gastric fluid and a gradual increase in hemolymph glucose. More intense hydrolysis of protein in the gastric chamber occurred 6-12 h after ingestion and then amino acids tended to increase in hemolymph. Triglyceride concentration in hemolymph rose earlier in wheat-fed lobsters than in lobsters fed other carbohydrates, but it decreased the most 24 h later. Analyses of metabolite levels and activities of different metabolic enzymes revealed that intermolt lobsters had a low capacity to store and use glycogen, although it was slightly higher in wheat-fed lobsters. Lobsters fed maize and rice diets increased amino acid catabolism, while wheat-fed lobsters exhibited higher utilization of fatty acids. Multivariate analysis confirmed that the type of carbohydrate ingested had a profound effect on overall metabolism. Although we found no evidence of a protein-sparing effect of dietary carbohydrate, differences in the kinetics of their digestion and absorption impacted lobster metabolism determining the fate of other nutrients.

A holistic view of dietary carbohydrate utilization in lobster: digestion, postprandial nutrient flux, and metabolism.

Directory of Open Access Journals (Sweden)

Leandro Rodríguez-Viera

Full Text Available Crustaceans exhibit a remarkable variation in their feeding habits and food type, but most knowledge on carbohydrate digestion and utilization in this group has come from research on few species. The aim of this study was to make an integrative analysis of dietary carbohydrate utilization in the spiny lobster Panulirus argus. We used complementary methodologies such as different assessments of digestibility, activity measurements of digestive and metabolic enzymes, and post-feeding flux of nutrients and metabolites. Several carbohydrates were well digested by the lobster, but maize starch was less digestible than all other starches studied, and its inclusion in diet affected protein digestibility. Most intense hydrolysis of carbohydrates in the gastric chamber of lobster occurred between 2-6 h after ingestion and afterwards free glucose increased in hemolymph. The inclusion of wheat in diet produced a slow clearance of glucose from the gastric fluid and a gradual increase in hemolymph glucose. More intense hydrolysis of protein in the gastric chamber occurred 6-12 h after ingestion and then amino acids tended to increase in hemolymph. Triglyceride concentration in hemolymph rose earlier in wheat-fed lobsters than in lobsters fed other carbohydrates, but it decreased the most 24 h later. Analyses of metabolite levels and activities of different metabolic enzymes revealed that intermolt lobsters had a low capacity to store and use glycogen, although it was slightly higher in wheat-fed lobsters. Lobsters fed maize and rice diets increased amino acid catabolism, while wheat-fed lobsters exhibited higher utilization of fatty acids. Multivariate analysis confirmed that the type of carbohydrate ingested had a profound effect on overall metabolism. Although we found no evidence of a protein-sparing effect of dietary carbohydrate, differences in the kinetics of their digestion and absorption impacted lobster metabolism determining the fate of other

Applications of computational modeling in metabolic engineering of yeast

DEFF Research Database (Denmark)

Kerkhoven, Eduard J.; Lahtvee, Petri-Jaan; Nielsen, Jens

2015-01-01

a preferred flux distribution. These methods point to strategies for altering gene expression; however, fluxes are often controlled by post-transcriptional events. Moreover, GEMs are usually not taking into account metabolic regulation, thermodynamics and enzyme kinetics. To facilitate metabolic engineering......, it is necessary to expand the modeling of metabolism to consider kinetics of individual processes. This review will give an overview about models available for metabolic engineering of yeast and discusses their applications....

Prenatal Metformin Exposure in Mice Programs the Metabolic Phenotype of the Offspring during a High Fat Diet at Adulthood

Science.gov (United States)

Salomäki, Henriikka; Vähätalo, Laura H.; Laurila, Kirsti; Jäppinen, Norma T.; Penttinen, Anna-Maija; Ailanen, Liisa; Ilyasizadeh, Juan; Pesonen, Ullamari; Koulu, Markku

2013-01-01

Aims The antidiabetic drug metformin is currently used prior and during pregnancy for polycystic ovary syndrome, as well as during gestational diabetes mellitus. We investigated the effects of prenatal metformin exposure on the metabolic phenotype of the offspring during adulthood in mice. Methods Metformin (300 mg/kg) or vehicle was administered orally to dams on regular diet from the embryonic day E0.5 to E17.5. Gene expression profiles in liver and brain were analysed from 4-day old offspring by microarray. Body weight development and several metabolic parameters of offspring were monitored both during regular diet (RD-phase) and high fat diet (HFD-phase). At the end of the study, two doses of metformin or vehicle were given acutely to mice at the age of 20 weeks, and Insig-1 and GLUT4 mRNA expressions in liver and fat tissue were analysed using qRT-PCR. Results Metformin exposed fetuses were lighter at E18.5. There was no effect of metformin on the maternal body weight development or food intake. Metformin exposed offspring gained more body weight and mesenteric fat during the HFD-phase. The male offspring also had impaired glucose tolerance and elevated fasting glucose during the HFD-phase. Moreover, the expression of GLUT4 mRNA was down-regulated in epididymal fat in male offspring prenatally exposed to metformin. Based on the microarray and subsequent qRT-PCR analyses, the expression of Insig-1 was changed in the liver of neonatal mice exposed to metformin prenatally. Furthermore, metformin up-regulated the expression of Insig-1 later in development. Gene set enrichment analysis based on preliminary microarray data identified several differentially enriched pathways both in control and metformin exposed mice. Conclusions The present study shows that prenatal metformin exposure causes long-term programming effects on the metabolic phenotype during high fat diet in mice. This should be taken into consideration when using metformin as a therapeutic agent during

Prenatal metformin exposure in mice programs the metabolic phenotype of the offspring during a high fat diet at adulthood.

Directory of Open Access Journals (Sweden)

Henriikka Salomäki

Full Text Available AIMS: The antidiabetic drug metformin is currently used prior and during pregnancy for polycystic ovary syndrome, as well as during gestational diabetes mellitus. We investigated the effects of prenatal metformin exposure on the metabolic phenotype of the offspring during adulthood in mice. METHODS: Metformin (300 mg/kg or vehicle was administered orally to dams on regular diet from the embryonic day E0.5 to E17.5. Gene expression profiles in liver and brain were analysed from 4-day old offspring by microarray. Body weight development and several metabolic parameters of offspring were monitored both during regular diet (RD-phase and high fat diet (HFD-phase. At the end of the study, two doses of metformin or vehicle were given acutely to mice at the age of 20 weeks, and Insig-1 and GLUT4 mRNA expressions in liver and fat tissue were analysed using qRT-PCR. RESULTS: Metformin exposed fetuses were lighter at E18.5. There was no effect of metformin on the maternal body weight development or food intake. Metformin exposed offspring gained more body weight and mesenteric fat during the HFD-phase. The male offspring also had impaired glucose tolerance and elevated fasting glucose during the HFD-phase. Moreover, the expression of GLUT4 mRNA was down-regulated in epididymal fat in male offspring prenatally exposed to metformin. Based on the microarray and subsequent qRT-PCR analyses, the expression of Insig-1 was changed in the liver of neonatal mice exposed to metformin prenatally. Furthermore, metformin up-regulated the expression of Insig-1 later in development. Gene set enrichment analysis based on preliminary microarray data identified several differentially enriched pathways both in control and metformin exposed mice. CONCLUSIONS: The present study shows that prenatal metformin exposure causes long-term programming effects on the metabolic phenotype during high fat diet in mice. This should be taken into consideration when using metformin as a

Impaired TCA cycle flux in mitochondria in skeletal muscle from type 2 diabetic subjects

DEFF Research Database (Denmark)

Gaster, Michael; Nehlin, Jan O; Minet, Ariane D

2012-01-01

The diabetic phenotype is complex, requiring elucidation of key initiating defects. Recent research has shown that diabetic myotubes express a primary reduced tricarboxylic acid (TCA) cycle flux. A reduced TCA cycle flux has also been shown both in insulin resistant offspring of T2D patients...... and exercising T2D patients in vivo. This review will discuss the latest advances in the understanding of the molecular mechanisms regulating the TCA cycle with focus on possible underlying mechanism which could explain the impaired TCA flux in insulin resistant human skeletal muscle in type 2 diabetes....... A reduced TCA is both a marker and a maker of the diabetic phenotype....

Metabolic phenotyping of various tea (Camellia sinensis L.) cultivars and understanding of their intrinsic metabolism.

Science.gov (United States)

Ji, Hyang-Gi; Lee, Yeong-Ran; Lee, Min-Seuk; Hwang, Kyeong Hwan; Kim, Eun-Hee; Park, Jun Seong; Hong, Young-Shick

2017-10-15

Recently, we selected three tea (Camellia sinensis) cultivars that are rich in taste, epigallocatechin-3-O-gallate (EGCG) and epigallocatechin-3-O-(3-O-methyl)-gallate (EGCG3″Me) and then cultivated them through asexual propagation by cutting in the same region. In the present study, proton nuclear magnetic resonance ( 1 H NMR)-based metabolomics was applied to characterize the metabotype and to understand the metabolic mechanism of these tea cultivars including wild type tea. Of the tea leaf metabolite variations, reverse associations of amino acid metabolism with catechin compound metabolism were found in the rich-taste, and EGCG- and EGCG3″Me-rich tea cultivars. Indeed, the metabolism of individual catechin compounds in the EGCG3″Me-rich cultivar differed from those of other tea cultivars. The current study highlights the distinct metabolism of various tea cultivars newly selected for cultivation and the important role of metabolomics in understanding the metabolic mechanism. Thus, comprehensive metabotyping is a useful method to assess and then develop a new plant cultivar. Copyright © 2017 Elsevier Ltd. All rights reserved.

Construction and completion of flux balance models from pathway databases.

Science.gov (United States)

Latendresse, Mario; Krummenacker, Markus; Trupp, Miles; Karp, Peter D

2012-02-01

Flux balance analysis (FBA) is a well-known technique for genome-scale modeling of metabolic flux. Typically, an FBA formulation requires the accurate specification of four sets: biochemical reactions, biomass metabolites, nutrients and secreted metabolites. The development of FBA models can be time consuming and tedious because of the difficulty in assembling completely accurate descriptions of these sets, and in identifying errors in the composition of these sets. For example, the presence of a single non-producible metabolite in the biomass will make the entire model infeasible. Other difficulties in FBA modeling are that model distributions, and predicted fluxes, can be cryptic and difficult to understand. We present a multiple gap-filling method to accelerate the development of FBA models using a new tool, called MetaFlux, based on mixed integer linear programming (MILP). The method suggests corrections to the sets of reactions, biomass metabolites, nutrients and secretions. The method generates FBA models directly from Pathway/Genome Databases. Thus, FBA models developed in this framework are easily queried and visualized using the Pathway Tools software. Predicted fluxes are more easily comprehended by visualizing them on diagrams of individual metabolic pathways or of metabolic maps. MetaFlux can also remove redundant high-flux loops, solve FBA models once they are generated and model the effects of gene knockouts. MetaFlux has been validated through construction of FBA models for Escherichia coli and Homo sapiens. Pathway Tools with MetaFlux is freely available to academic users, and for a fee to commercial users. Download from: biocyc.org/download.shtml. mario.latendresse@sri.com Supplementary data are available at Bioinformatics online.

The role of metabolism in bacterial persistence

Directory of Open Access Journals (Sweden)

Stephanie M. Amato

2014-03-01

Full Text Available Bacterial persisters are phenotypic variants with extraordinary tolerances toward antibiotics. Persister survival has been attributed to inhibition of essential cell functions during antibiotic stress, followed by reversal of the process and resumption of growth upon removal of the antibiotic. Metabolism plays a critical role in this process, since it participates in the entry, maintenance, and exit from the persister phenotype. Here, we review the experimental evidence that demonstrates the importance of metabolism to persistence, highlight the successes and potential for targeting metabolism in the search for anti-persister therapies, and discuss the current methods and challenges to understand persister physiology.

Metabolic heterogeneity in clonal microbial populations.

Science.gov (United States)

Takhaveev, Vakil; Heinemann, Matthias

2018-02-21

In the past decades, numerous instances of phenotypic diversity were observed in clonal microbial populations, particularly, on the gene expression level. Much less is, however, known about phenotypic differences that occur on the level of metabolism. This is likely explained by the fact that experimental tools probing metabolism of single cells are still at an early stage of development. Here, we review recent exciting discoveries that point out different causes for metabolic heterogeneity within clonal microbial populations. These causes range from ecological factors and cell-inherent dynamics in constant environments to molecular noise in gene expression that propagates into metabolism. Furthermore, we provide an overview of current methods to quantify the levels of metabolites and biomass components in single cells. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Temporal expression-based analysis of metabolism.

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Sara B Collins

Full Text Available Metabolic flux is frequently rerouted through cellular metabolism in response to dynamic changes in the intra- and extra-cellular environment. Capturing the mechanisms underlying these metabolic transitions in quantitative and predictive models is a prominent challenge in systems biology. Progress in this regard has been made by integrating high-throughput gene expression data into genome-scale stoichiometric models of metabolism. Here, we extend previous approaches to perform a Temporal Expression-based Analysis of Metabolism (TEAM. We apply TEAM to understanding the complex metabolic dynamics of the respiratorily versatile bacterium Shewanella oneidensis grown under aerobic, lactate-limited conditions. TEAM predicts temporal metabolic flux distributions using time-series gene expression data. Increased predictive power is achieved by supplementing these data with a large reference compendium of gene expression, which allows us to take into account the unique character of the distribution of expression of each individual gene. We further propose a straightforward method for studying the sensitivity of TEAM to changes in its fundamental free threshold parameter θ, and reveal that discrete zones of distinct metabolic behavior arise as this parameter is changed. By comparing the qualitative characteristics of these zones to additional experimental data, we are able to constrain the range of θ to a small, well-defined interval. In parallel, the sensitivity analysis reveals the inherently difficult nature of dynamic metabolic flux modeling: small errors early in the simulation propagate to relatively large changes later in the simulation. We expect that handling such "history-dependent" sensitivities will be a major challenge in the future development of dynamic metabolic-modeling techniques.

Antiandrogen Treatment Ameliorates Reproductive and Metabolic Phenotypes in the Letrozole-Induced Mouse Model of PCOS.

Science.gov (United States)

Ryan, Genevieve E; Malik, Shaddy; Mellon, Pamela L

2018-04-01

Polycystic ovary syndrome (PCOS), the most common endocrinopathy in women of reproductive age, is characterized by hyperandrogenism, anovulation, and polycystic ovaries. Although its etiology is unknown, excess androgens are thought to be a critical factor driving the pathology of PCOS. We previously demonstrated that continuous exposure to the aromatase inhibitor letrozole (LET) in mice produces many hallmarks of PCOS, including elevated testosterone (T) and luteinizing hormone, anovulation, and obesity. In the current study, we sought to determine whether androgen receptor (AR) actions are responsible for any of the phenotypes observed in LET mice. C57BL/6 female mice were subcutaneously implanted with LET or placebo control and subsequently treated with the nonsteroidal AR antagonist flutamide or vehicle control. Flutamide treatment in LET females reversed elevated T levels and restored ovarian expression of Cyp17a1 (critical for androgen synthesis) to normal levels. Pituitary expression of Lhb was decreased in LET females that received flutamide treatment, with no changes in expression of Fshb or Gnrhr. Flutamide treatment also restored estrous cycling and reduced the number of ovarian cyst-like follicles in LET females. Furthermore, body weight and adipocyte size were decreased in flutamide-treated LET females. Altogether, our findings provide strong evidence that AR signaling is responsible for many key reproductive and metabolic PCOS phenotypes and further establish the LET mouse model as an important tool for the study of androgen excess.

Second Law of Thermodynamics Applied to Metabolic Networks

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Nigam, R.; Liang, S.

2003-01-01

We present a simple algorithm based on linear programming, that combines Kirchoff's flux and potential laws and applies them to metabolic networks to predict thermodynamically feasible reaction fluxes. These law's represent mass conservation and energy feasibility that are widely used in electrical circuit analysis. Formulating the Kirchoff's potential law around a reaction loop in terms of the null space of the stoichiometric matrix leads to a simple representation of the law of entropy that can be readily incorporated into the traditional flux balance analysis without resorting to non-linear optimization. Our technique is new as it can easily check the fluxes got by applying flux balance analysis for thermodynamic feasibility and modify them if they are infeasible so that they satisfy the law of entropy. We illustrate our method by applying it to the network dealing with the central metabolism of Escherichia coli. Due to its simplicity this algorithm will be useful in studying large scale complex metabolic networks in the cell of different organisms.

Debrisoquine phenotype and the pharmacokinetics and beta-2 receptor pharmacodynamics of metoprolol and its enantiomers

NARCIS (Netherlands)

Jonkers, R. E.; Koopmans, R. P.; Portier, E. J.; van Boxtel, C. J.

1991-01-01

The metabolism of the cardioselective beta-blocker metoprolol is under genetic control of the debrisoquine/sparteine type. The two metabolic phenotypes, extensive (EM) and poor metabolizers (PM), show different stereoselective metabolism, resulting in apparently higher beta-1 adrenoceptor

The Key to Acetate: Metabolic Fluxes of Acetic Acid Bacteria under Cocoa Pulp Fermentation-Simulating Conditions

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Adler, Philipp; Frey, Lasse Jannis; Berger, Antje; Bolten, Christoph Josef; Hansen, Carl Erik

2014-01-01

Acetic acid bacteria (AAB) play an important role during cocoa fermentation, as their main product, acetate, is a major driver for the development of the desired cocoa flavors. Here, we investigated the specialized metabolism of these bacteria under cocoa pulp fermentation-simulating conditions. A carefully designed combination of parallel 13C isotope labeling experiments allowed the elucidation of intracellular fluxes in the complex environment of cocoa pulp, when lactate and ethanol were included as primary substrates among undefined ingredients. We demonstrate that AAB exhibit a functionally separated metabolism during coconsumption of two-carbon and three-carbon substrates. Acetate is almost exclusively derived from ethanol, while lactate serves for the formation of acetoin and biomass building blocks. Although this is suboptimal for cellular energetics, this allows maximized growth and conversion rates. The functional separation results from a lack of phosphoenolpyruvate carboxykinase and malic enzymes, typically present in bacteria to interconnect metabolism. In fact, gluconeogenesis is driven by pyruvate phosphate dikinase. Consequently, a balanced ratio of lactate and ethanol is important for the optimum performance of AAB. As lactate and ethanol are individually supplied by lactic acid bacteria and yeasts during the initial phase of cocoa fermentation, respectively, this underlines the importance of a well-balanced microbial consortium for a successful fermentation process. Indeed, AAB performed the best and produced the largest amounts of acetate in mixed culture experiments when lactic acid bacteria and yeasts were both present. PMID:24837393

Plant phenomics and the need for physiological phenotyping across scales to narrow the genotype-to-phenotype knowledge gap

DEFF Research Database (Denmark)

Grosskinsky, Dominik Kilian; Svensgaard, Jesper; Christensen, Svend

2015-01-01

Plants are affected by complex genome×environment×management interactions which determine phenotypic plasticity as a result of the variability of genetic components. Whereas great advances have been made in the cost-efficient and high-throughput analyses of genetic information and non-invasive ph......Plants are affected by complex genome×environment×management interactions which determine phenotypic plasticity as a result of the variability of genetic components. Whereas great advances have been made in the cost-efficient and high-throughput analyses of genetic information and non......-invasive phenotyping, the large-scale analyses of the underlying physiological mechanisms lag behind. The external phenotype is determined by the sum of the complex interactions of metabolic pathways and intracellular regulatory networks that is reflected in an internal, physiological, and biochemical phenotype......, ultimately enabling the in silico assessment of responses under defined environments with advanced crop models. This will allow generation of robust physiological predictors also for complex traits to bridge the knowledge gap between genotype and phenotype for applications in breeding, precision farming...

MCT1 and MCT4 expression and lactate flux activity increase during white and brown adipogenesis and impact adipocyte metabolism

DEFF Research Database (Denmark)

Petersen, Charlotte; Nielsen, Mette D.; Andersen, Elise S.

2017-01-01

RNA and protein levels of the lactate-H+ transporter MCT1 and the Na+,HCO3 - cotransporter NBCe1 were upregulated in mouse interscapular brown and inguinal white adipose tissue upon cold induction of thermogenesis and browning. MCT1, MCT4, and NBCe1 were furthermore strongly upregulated at the mRNA and protein...... level upon differentiation of cultured pre-adipocytes. Adipocyte differentiation was accompanied by increased plasma membrane lactate flux capacity, which was reduced by MCT inhibition and by MCT1 knockdown. Finally, in differentiated brown adipocytes, glycolysis (assessed as ECAR), and after...... noradrenergic stimulation also oxidative metabolism (OCR), was decreased by MCT inhibition. We suggest that upregulation of MCT1- and MCT4-mediated lactate flux capacity and NBCe1-mediated HCO3 -/pH homeostasis are important for the physiological function of mature adipocytes....

Oxygen-enriched fermentation of sodium gluconate by Aspergillus niger and its impact on intracellular metabolic flux distributions.

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Shen, Yuting; Tian, Xiwei; Zhao, Wei; Hang, Haifeng; Chu, Ju

2018-01-01

Different concentrations of oxygen-enriched air were utilized for sodium gluconate (SG) fermentation by Aspergillus niger. The fermentation time shortened from 20 to 15.5 h due to the increase of volumetric oxygen transfer coefficient (K L a) and the formation of more dispersed mycelia when inlet oxygen concentration ascended from 21 to 32%. According to metabolic flux analysis, during the growth phase, extracellular glucose for SG synthesis accounted for 79.0 and 85.3% with air and oxygen-enriched air (25%), respectively, whereas the proportions were 89.4 and 93.0% in the stationary phase. Intracellular glucose consumption decreased in oxygen-enriched fermentation, as cell respiration was more high-efficiently performed. Metabolic profiling indicated that most intermediates in TCA cycle and EMP pathway had smaller pool sizes in oxygen-enriched fermentations. Moreover, the main by-product of citric acid dramatically decreased from 1.36 to 0.34 g L -1 in oxygen-enriched fermentation. And the sodium gluconate yield increased from 0.856 to 0.903 mol mol -1 .

Software applications for flux balance analysis.

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Lakshmanan, Meiyappan; Koh, Geoffrey; Chung, Bevan K S; Lee, Dong-Yup

2014-01-01

Flux balance analysis (FBA) is a widely used computational method for characterizing and engineering intrinsic cellular metabolism. The increasing number of its successful applications and growing popularity are possibly attributable to the availability of specific software tools for FBA. Each tool has its unique features and limitations with respect to operational environment, user-interface and supported analysis algorithms. Presented herein is an in-depth evaluation of currently available FBA applications, focusing mainly on usability, functionality, graphical representation and inter-operability. Overall, most of the applications are able to perform basic features of model creation and FBA simulation. COBRA toolbox, OptFlux and FASIMU are versatile to support advanced in silico algorithms to identify environmental and genetic targets for strain design. SurreyFBA, WEbcoli, Acorn, FAME, GEMSiRV and MetaFluxNet are the distinct tools which provide the user friendly interfaces in model handling. In terms of software architecture, FBA-SimVis and OptFlux have the flexible environments as they enable the plug-in/add-on feature to aid prospective functional extensions. Notably, an increasing trend towards the implementation of more tailored e-services such as central model repository and assistance to collaborative efforts was observed among the web-based applications with the help of advanced web-technologies. Furthermore, most recent applications such as the Model SEED, FAME, MetaFlux and MicrobesFlux have even included several routines to facilitate the reconstruction of genome-scale metabolic models. Finally, a brief discussion on the future directions of FBA applications was made for the benefit of potential tool developers.

Energetics of glucose metabolism: a phenomenological approach to metabolic network modeling.

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Diederichs, Frank

2010-08-12

A new formalism to describe metabolic fluxes as well as membrane transport processes was developed. The new flux equations are comparable to other phenomenological laws. Michaelis-Menten like expressions, as well as flux equations of nonequilibrium thermodynamics, can be regarded as special cases of these new equations. For metabolic network modeling, variable conductances and driving forces are required to enable pathway control and to allow a rapid response to perturbations. When applied to oxidative phosphorylation, results of simulations show that whole oxidative phosphorylation cannot be described as a two-flux-system according to nonequilibrium thermodynamics, although all coupled reactions per se fulfill the equations of this theory. Simulations show that activation of ATP-coupled load reactions plus glucose oxidation is brought about by an increase of only two different conductances: a [Ca(2+)] dependent increase of cytosolic load conductances, and an increase of phosphofructokinase conductance by [AMP], which in turn becomes increased through [ADP] generation by those load reactions. In ventricular myocytes, this feedback mechanism is sufficient to increase cellular power output and O(2) consumption several fold, without any appreciable impairment of energetic parameters. Glucose oxidation proceeds near maximal power output, since transformed input and output conductances are nearly equal, yielding an efficiency of about 0.5. This conductance matching is fulfilled also by glucose oxidation of β-cells. But, as a price for the metabolic mechanism of glucose recognition, β-cells have only a limited capability to increase their power output.

Circulating omentin-1 might be associated with metabolic health status in different phenotypes of body size.

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Alizadeh, Shahab; Mirzaei, Khadijeh; Mohammadi, Chonur; Keshavarz, Seyed Ali; Maghbooli, Zhila

2017-12-01

Adipokines are mediators of body composition and are involved in obesity complications. This study aimed to assess the association of circulating omentin-1, vaspin, and RBP-4 with body composition indices and metabolic health status (MHS) in different phenotypes of body size. A total of 350 subjects were included in the current cross-sectional study. Body composition was measured using a body composition analyzer, and serum concentrations of omentin-1, vaspin, and RBP-4 were assessed by ELISA kits. Circulating omentin-1 was significantly (OR = 1.81, 95% CI: 1.00-1.91, P = 0.01) and marginally (OR = 1.63, 95%CI: 1.00-1.75, P = 0.06) associated with MHS in the overweight and obese subjects, respectively. But no association was seen between omentin-1 and MHS in normal-weight subjects. Serum levels of vaspin and RBP-4 were not correlated with MHS. Furthermore, a significant positive correlation was observed between circulating omentin-1 and body mass index (BMI) as well as fat percentage (P = 0.02) in the MHS group. Serum vaspin concentrations were not related to body composition components in both groups. In addition, in the MHS group, circulating RBP-4 was positively correlated with fat percentage and fat mass (FM) (p body water (TBW) (p < 0.0001). In contrast, in the metabolically unhealthy group, RBP-4 was negatively correlated with fat percentage, FM, and BMI (p < 0.0001) and was positively correlated with FFM and TBW (p < 0.0001). This study showed that circulating levels of omentin-1 are useful predictors of metabolic health status in overweight and obese people.

The association of incident hypertension with metabolic health and obesity status: definition of metabolic health does not matter.

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Kang, Yu Mi; Jung, Chang Hee; Jang, Jung Eun; Hwang, Jenie Yoonoo; Kim, Eun Hee; Park, Joong-Yeol; Kim, Hong-Kyu; Lee, Woo Je

2016-08-01

Metabolically healthy obese (MHO) phenotype refers to obese individuals with a favourable metabolic profile. Its prognostic value remains controversial and may partly depend on differences in how the phenotype is defined. We aimed to investigate whether the MHO phenotype is associated with future development of incident hypertension in a Korean population according to various definitions of metabolic health. The study population comprised 31 033 Koreans without hypertension. Participants were stratified into metabolically healthy nonobese (MHNO), metabolically unhealthy nonobese (MUNO), metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) by body mass index (cut-off value, 25·0 kg/m(2) ) and metabolic health state, using four different definitions: Adult Treatment Panel (ATP)-III, Wildman, Karelis and the homoeostasis model assessment (HOMA) criteria. Over the median follow-up period of 35·0 months (range, 4·5-81·4 months), 4589 of the 31 033 individuals (14·8%) developed incident hypertension. Compared with the MHNO group, the MHO group showed increased association with incident hypertension with multivariate-adjusted odds ratios of 1·56 (95% confidence interval [CI], 1·41-1·72), 1·58 (95% CI 1·42-1·75), 1·52 (95% CI 1·35-1·71) and 1·46 (95% CI 1·33-1·61), when defined by ATP-III, Wildman, Karelis and HOMA criteria, respectively. MUO individuals showed the highest association with the incident hypertension (adjusted odds ratios up to 2·00). MHO subjects showed an approximately 1·5-fold higher association with incident hypertension than their nonobese counterpart regardless of the definition of metabolic health used. Thus, considering both metabolic health and obesity is important for the assessment of potential cardiovascular outcomes. © 2016 John Wiley & Sons Ltd.

Thermodynamics-based Metabolite Sensitivity Analysis in metabolic networks.

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Kiparissides, A; Hatzimanikatis, V

2017-01-01

The increasing availability of large metabolomics datasets enhances the need for computational methodologies that can organize the data in a way that can lead to the inference of meaningful relationships. Knowledge of the metabolic state of a cell and how it responds to various stimuli and extracellular conditions can offer significant insight in the regulatory functions and how to manipulate them. Constraint based methods, such as Flux Balance Analysis (FBA) and Thermodynamics-based flux analysis (TFA), are commonly used to estimate the flow of metabolites through genome-wide metabolic networks, making it possible to identify the ranges of flux values that are consistent with the studied physiological and thermodynamic conditions. However, unless key intracellular fluxes and metabolite concentrations are known, constraint-based models lead to underdetermined problem formulations. This lack of information propagates as uncertainty in the estimation of fluxes and basic reaction properties such as the determination of reaction directionalities. Therefore, knowledge of which metabolites, if measured, would contribute the most to reducing this uncertainty can significantly improve our ability to define the internal state of the cell. In the present work we combine constraint based modeling, Design of Experiments (DoE) and Global Sensitivity Analysis (GSA) into the Thermodynamics-based Metabolite Sensitivity Analysis (TMSA) method. TMSA ranks metabolites comprising a metabolic network based on their ability to constrain the gamut of possible solutions to a limited, thermodynamically consistent set of internal states. TMSA is modular and can be applied to a single reaction, a metabolic pathway or an entire metabolic network. This is, to our knowledge, the first attempt to use metabolic modeling in order to provide a significance ranking of metabolites to guide experimental measurements. Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation.

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Meadows, Adam L; Karnik, Rahi; Lam, Harry; Forestell, Sean; Snedecor, Brad

2010-03-01

We have developed a reactor-scale model of Escherichia coli metabolism and growth in a 1000 L process for the production of a recombinant therapeutic protein. The model consists of two distinct parts: (1) a dynamic, process specific portion that describes the time evolution of 37 process variables of relevance and (2) a flux balance based, 123-reaction metabolic model of E. coli metabolism. This model combines several previously reported modeling approaches including a growth rate-dependent biomass composition, maximum growth rate objective function, and dynamic flux balancing. In addition, we introduce concentration-dependent boundary conditions of transport fluxes, dynamic maintenance demands, and a state-dependent cellular objective. This formulation was able to describe specific runs with high-fidelity over process conditions including rich media, simultaneous acetate and glucose consumption, glucose minimal media, and phosphate depleted media. Furthermore, the model accurately describes the effect of process perturbations--such as glucose overbatching and insufficient aeration--on growth, metabolism, and titer. (c) 2009 Elsevier Inc. All rights reserved.

Computational Platform for Flux Analysis Using 13C-Label Tracing- Phase I SBIR Final Report

Energy Technology Data Exchange (ETDEWEB)

Van Dien, Stephen J.

2005-04-12

Isotopic label tracing is a powerful experimental technique that can be combined with metabolic models to quantify metabolic fluxes in an organism under a particular set of growth conditions. In this work we constructed a genome-scale metabolic model of Methylobacterium extorquens, a facultative methylotroph with potential application in the production of useful chemicals from methanol. A series of labeling experiments were performed using 13C-methanol, and the resulting distribution of labeled carbon in the proteinogenic amino acids was determined by mass spectrometry. Algorithms were developed to analyze this data in context of the metabolic model, yielding flux distributions for wild-type and several engineered strains of M. extorquens. These fluxes were compared to those predicted by model simulation alone, and also integrated with microarray data to give an improved understanding of the metabolic physiology of this organism.

Metabolic Reprogramming Regulates the Proliferative and Inflammatory Phenotype of Adventitial Fibroblasts in Pulmonary Hypertension Through the Transcriptional Corepressor C-Terminal Binding Protein-1.

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Li, Min; Riddle, Suzette; Zhang, Hui; D'Alessandro, Angelo; Flockton, Amanda; Serkova, Natalie J; Hansen, Kirk C; Moldvan, Radu; McKeon, B Alexandre; Frid, Maria; Kumar, Sushil; Li, Hong; Liu, Hongbing; Caánovas, Angela; Medrano, Juan F; Thomas, Milton G; Iloska, Dijana; Plecitá-Hlavatá, Lydie; Ježek, Petr; Pullamsetti, Soni; Fini, Mehdi A; El Kasmi, Karim C; Zhang, QingHong; Stenmark, Kurt R

2016-10-11

Changes in metabolism have been suggested to contribute to the aberrant phenotype of vascular wall cells, including fibroblasts, in pulmonary hypertension (PH). Here, we test the hypothesis that metabolic reprogramming to aerobic glycolysis is a critical adaptation of fibroblasts in the hypertensive vessel wall that drives proliferative and proinflammatory activation through a mechanism involving increased activity of the NADH-sensitive transcriptional corepressor C-terminal binding protein 1 (CtBP1). RNA sequencing, quantitative polymerase chain reaction, 13 C-nuclear magnetic resonance, fluorescence-lifetime imaging, mass spectrometry-based metabolomics, and tracing experiments with U- 13 C-glucose were used to assess glycolytic reprogramming and to measure the NADH/NAD + ratio in bovine and human adventitial fibroblasts and mouse lung tissues. Immunohistochemistry was used to assess CtBP1 expression in the whole-lung tissues. CtBP1 siRNA and the pharmacological inhibitor 4-methylthio-2-oxobutyric acid (MTOB) were used to abrogate CtBP1 activity in cells and hypoxic mice. We found that adventitial fibroblasts from calves with severe hypoxia-induced PH and humans with idiopathic pulmonary arterial hypertension (PH-Fibs) displayed aerobic glycolysis when cultured under normoxia, accompanied by increased free NADH and NADH/NAD + ratios. Expression of the NADH sensor CtBP1 was increased in vivo and in vitro in fibroblasts within the pulmonary adventitia of humans with idiopathic pulmonary arterial hypertension and animals with PH and cultured PH-Fibs, respectively. Decreasing NADH pharmacologically with MTOB or genetically blocking CtBP1 with siRNA upregulated the cyclin-dependent genes (p15 and p21) and proapoptotic regulators (NOXA and PERP), attenuated proliferation, corrected the glycolytic reprogramming phenotype of PH-Fibs, and augmented transcription of the anti-inflammatory gene HMOX1. Chromatin immunoprecipitation analysis demonstrated that CtBP1 directly

Inferring metabolic states in uncharacterized environments using gene-expression measurements.

Directory of Open Access Journals (Sweden)

Sergio Rossell

Full Text Available The large size of metabolic networks entails an overwhelming multiplicity in the possible steady-state flux distributions that are compatible with stoichiometric constraints. This space of possibilities is largest in the frequent situation where the nutrients available to the cells are unknown. These two factors: network size and lack of knowledge of nutrient availability, challenge the identification of the actual metabolic state of living cells among the myriad possibilities. Here we address this challenge by developing a method that integrates gene-expression measurements with genome-scale models of metabolism as a means of inferring metabolic states. Our method explores the space of alternative flux distributions that maximize the agreement between gene expression and metabolic fluxes, and thereby identifies reactions that are likely to be active in the culture from which the gene-expression measurements were taken. These active reactions are used to build environment-specific metabolic models and to predict actual metabolic states. We applied our method to model the metabolic states of Saccharomyces cerevisiae growing in rich media supplemented with either glucose or ethanol as the main energy source. The resulting models comprise about 50% of the reactions in the original model, and predict environment-specific essential genes with high sensitivity. By minimizing the sum of fluxes while forcing our predicted active reactions to carry flux, we predicted the metabolic states of these yeast cultures that are in large agreement with what is known about yeast physiology. Most notably, our method predicts the Crabtree effect in yeast cells growing in excess glucose, a long-known phenomenon that could not have been predicted by traditional constraint-based modeling approaches. Our method is of immediate practical relevance for medical and industrial applications, such as the identification of novel drug targets, and the development of

Global Phenotypic Characterization of Effects of Fluoroquinolone Resistance Selection on the Metabolic Activities and Drug Susceptibilities of Clostridium perfringens Strains

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Miseon Park

2014-01-01

Full Text Available Fluoroquinolone resistance affects toxin production of Clostridium perfringens strains differently. To investigate the effect of fluoroquinolone resistance selection on global changes in metabolic activities and drug susceptibilities, four C. perfringens strains and their norfloxacin-, ciprofloxacin-, and gatifloxacin-resistant mutants were compared in nearly 2000 assays, using phenotype microarray plates. Variations among mutant strains resulting from resistance selection were observed in all aspects of metabolism. Carbon utilization, pH range, osmotic tolerance, and chemical sensitivity of resistant strains were affected differently in the resistant mutants depending on both the bacterial genotype and the fluoroquinolone to which the bacterium was resistant. The susceptibilities to gentamicin and erythromycin of all resistant mutants except one increased, but some resistant strains were less susceptible to amoxicillin, cefoxitin, ceftriaxone, chloramphenicol, and metronidazole than their wild types. Sensitivity to ethidium bromide decreased in some resistant mutants and increased in others. Microarray analysis of two gatifloxacin-resistant mutants showed changes in metabolic activities that were correlated with altered expression of various genes. Both the chemical structures of fluoroquinolones and the genomic makeup of the wild types influenced the changes found in resistant mutants, which may explain some inconsistent reports of the effects of therapeutic use of fluoroquinolones on clinical isolates of bacteria.

Genetic polymorphisms in one-carbon metabolism: associations with CpG island methylator phenotype (CIMP) in colon cancer and the modifying effects of diet.

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Curtin, Karen; Slattery, Martha L; Ulrich, Cornelia M; Bigler, Jeannette; Levin, Theodore R; Wolff, Roger K; Albertsen, Hans; Potter, John D; Samowitz, Wade S

2007-08-01

This study investigated associations between CpG island methylator phenotype (CIMP) colon cancer and genetic polymorphisms relevant to one-carbon metabolism and thus, potentially the provision of methyl groups and risk of colon cancer. Data from a large, population-based case-control study (916 incident colon cancer cases and 1,972 matched controls) were used. Candidate polymorphisms in methylenetetrahydrofolate reductase (MTHFR), thymidylate synthase (TS), transcobalamin II (TCNII), methionine synthase (MTR), reduced folate carrier (RFC), methylenetetrahydrofolate dehydrogenase 1 (MTHFD1), dihydrofolate reductase (DHFR) and alcohol dehydrogenase 3 (ADH3) were evaluated. CIMP- or CIMP+ phenotype was based on five CpG island markers: MINT1, MINT2, MINT31, p16 and MLH1. The influence of specific dietary factors (folate, methionine, vitamin B(12) and alcohol) on these associations was also analyzed. We hypothesized that polymorphisms involved in the provision of methyl groups would be associated with CIMP+ tumors (two or more of five markers methylated), potentially modified by diet. Few associations specific to CIMP+ tumors were observed overall, which does not support the hypothesis that the provision of methyl groups is important in defining a methylator phenotype. However, our data suggest that genetic polymorphisms in MTHFR 1,298A > C, interacting with diet, may be involved in the development of highly CpG-methylated colon cancers. AC and CC genotypes in conjunction with a high-risk dietary pattern (low folate and methionine intake and high alcohol use) were associated with CIMP+ (OR = 2.1, 95% CI = 1.3-3.4 versus AA/high risk; P-interaction = 0.03). These results provide only limited support for a role of polymorphisms in one-carbon metabolism in the etiology of CIMP colon cancer.

In vivo dynamics of galactose metabolism in Saccharomyces cerevisiae: Metabolic fluxes and metabolite levels

DEFF Research Database (Denmark)

Østergaard, Simon; Olsson, Lisbeth; Nielsen, Jens

2001-01-01

The dynamics of galactose metabolism in Saccharomyces cerevisiae was studied by analyzing the metabolic response of the CEN.PK 113-7D wild-type strain when exposed to a galactose pulse during aerobic growth in a galactose-limited steady-state cultivation at a dilution rate of 0.097 h(-1). A fast...

Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance.

Science.gov (United States)

Carey, Maureen A; Papin, Jason A; Guler, Jennifer L

2017-07-19

Malaria remains a major public health burden and resistance has emerged to every antimalarial on the market, including the frontline drug, artemisinin. Our limited understanding of Plasmodium biology hinders the elucidation of resistance mechanisms. In this regard, systems biology approaches can facilitate the integration of existing experimental knowledge and further understanding of these mechanisms. Here, we developed a novel genome-scale metabolic network reconstruction, iPfal17, of the asexual blood-stage P. falciparum parasite to expand our understanding of metabolic changes that support resistance. We identified 11 metabolic tasks to evaluate iPfal17 performance. Flux balance analysis and simulation of gene knockouts and enzyme inhibition predict candidate drug targets unique to resistant parasites. Moreover, integration of clinical parasite transcriptomes into the iPfal17 reconstruction reveals patterns associated with antimalarial resistance. These results predict that artemisinin sensitive and resistant parasites differentially utilize scavenging and biosynthetic pathways for multiple essential metabolites, including folate and polyamines. Our findings are consistent with experimental literature, while generating novel hypotheses about artemisinin resistance and parasite biology. We detect evidence that resistant parasites maintain greater metabolic flexibility, perhaps representing an incomplete transition to the metabolic state most appropriate for nutrient-rich blood. Using this systems biology approach, we identify metabolic shifts that arise with or in support of the resistant phenotype. This perspective allows us to more productively analyze and interpret clinical expression data for the identification of candidate drug targets for the treatment of resistant parasites.

QUANTITATIVE ANALYSIS OF FLUX REGULATION THROUGH HIERARCHICAL REGULATION ANALYSIS

NARCIS (Netherlands)

van Eunen, Karen; Rossell, Sergio; Bouwman, Jildau; Westerhoff, Hans V.; Bakker, Barbara M.; Jameson, D; Verma, M; Westerhoff, HV

2011-01-01

Regulation analysis is a methodology that quantifies to what extent a change in the flux through a metabolic pathway is regulated by either gene expression or metabolism. Two extensions to regulation analysis were developed over the past years: (i) the regulation of V(max) can be dissected into the

Quantitative analysis of flux regulation through hierarchical regulation analysis

NARCIS (Netherlands)

Eunen, K. van; Rossell, S.; Bouwman, J.; Westerhoff, H.V.; Bakker, B.M.

2011-01-01

Regulation analysis is a methodology that quantifies to what extent a change in the flux through a metabolic pathway is regulated by either gene expression or metabolism. Two extensions to regulation analysis were developed over the past years: (i) the regulation of Vmax can be dissected into the

Genetic networks of liver metabolism revealed by integration of metabolic and transcriptional profiling.

Directory of Open Access Journals (Sweden)

Christine T Ferrara

2008-03-01

Full Text Available Although numerous quantitative trait loci (QTL influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptin(ob/ob and the diabetes-susceptible BTBR leptin(ob/ob mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines. We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes.

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

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Heavner Benjamin D

2012-06-01

Full Text Available Abstract Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Additional file 1 Function testYeastModel.m.m. Click here for file Additional file 2 Function model

Human cytochrome P450 2B6 genetic variability in Botswana: a case of haplotype diversity and convergent phenotypes

KAUST Repository

Tawe, Leabaneng

2018-03-14

Identification of inter-individual variability for drug metabolism through cytochrome P450 2B6 (CYP2B6) enzyme is important for understanding the differences in clinical responses to malaria and HIV. This study evaluates the distribution of CYP2B6 alleles, haplotypes and inferred metabolic phenotypes among subjects with different ethnicity in Botswana. A total of 570 subjects were analyzed for CYP2B6 polymorphisms at position 516 G > T (rs3745274), 785 A > G (rs2279343) and 983 T > C (rs28399499). Samples were collected in three districts of Botswana where the population belongs to Bantu (Serowe/Palapye and Chobe) and San-related (Ghanzi) ethnicity. The three districts showed different haplotype composition according to the ethnic background but similar metabolic inferred phenotypes, with 59.12%, 34.56%, 2.10% and 4.21% of the subjects having, respectively, an extensive, intermediate, slow and rapid metabolic profile. The results hint at the possibility of a convergent adaptation of detoxifying metabolic phenotypes despite a different haplotype structure due to the different genetic background. The main implication is that, while there is substantial homogeneity of metabolic inferred phenotypes among the country, the response to drugs metabolized via CYP2B6 could be individually associated to an increased risk of treatment failure and toxicity. These are important facts since Botswana is facing malaria elimination and a very high HIV prevalence.

Human cytochrome P450 2B6 genetic variability in Botswana: a case of haplotype diversity and convergent phenotypes

KAUST Repository

Tawe, Leabaneng; Motshoge, Thato; Ramatlho, Pleasure; Mutukwa, Naledi; Muthoga, Charles Waithaka; Dongho, Ghyslaine Bruna Djeunang; Martinelli, Axel; Peloewetse, Elias; Russo, Gianluca; Quaye, Isaac Kweku; Paganotti, Giacomo Maria

2018-01-01

Identification of inter-individual variability for drug metabolism through cytochrome P450 2B6 (CYP2B6) enzyme is important for understanding the differences in clinical responses to malaria and HIV. This study evaluates the distribution of CYP2B6 alleles, haplotypes and inferred metabolic phenotypes among subjects with different ethnicity in Botswana. A total of 570 subjects were analyzed for CYP2B6 polymorphisms at position 516 G > T (rs3745274), 785 A > G (rs2279343) and 983 T > C (rs28399499). Samples were collected in three districts of Botswana where the population belongs to Bantu (Serowe/Palapye and Chobe) and San-related (Ghanzi) ethnicity. The three districts showed different haplotype composition according to the ethnic background but similar metabolic inferred phenotypes, with 59.12%, 34.56%, 2.10% and 4.21% of the subjects having, respectively, an extensive, intermediate, slow and rapid metabolic profile. The results hint at the possibility of a convergent adaptation of detoxifying metabolic phenotypes despite a different haplotype structure due to the different genetic background. The main implication is that, while there is substantial homogeneity of metabolic inferred phenotypes among the country, the response to drugs metabolized via CYP2B6 could be individually associated to an increased risk of treatment failure and toxicity. These are important facts since Botswana is facing malaria elimination and a very high HIV prevalence.

Forearm metabolism during infusion of adrenaline

DEFF Research Database (Denmark)

Simonsen, L; Stefl, B; Bülow, J

2000-01-01

Human skeletal muscle metabolism is often investigated by measurements of substrate fluxes across the forearm. To evaluate whether the two forearms give the same metabolic information, nine healthy subjects were studied in the fasted state and during infusion of adrenaline. Both arms were...... catheterized in a cubital vein in the retrograde direction. A femoral artery was catheterized for blood sampling, and a femoral vein for infusion of adrenaline. Forearm blood flow was measured by venous occlusion strain-gauge plethysmography. Forearm subcutaneous adipose tissue blood flow was measured...... by the local 133Xe washout method. Metabolic fluxes were calculated as the product of forearm blood flow and a-v differences of metabolite concentrations. After baseline measurements, adrenaline was infused at a rate of 0.3 nmol kg-1 min-1. No difference in the metabolic information obtained in the fasting...

Simulating Serial-Target Antibacterial Drug Synergies Using Flux Balance Analysis

DEFF Research Database (Denmark)

Krueger, Andrew S.; Munck, Christian; Dantas, Gautam

2016-01-01

Flux balance analysis (FBA) is an increasingly useful approach for modeling the behavior of metabolic systems. However, standard FBA modeling of genetic knockouts cannot predict drug combination synergies observed between serial metabolic targets, even though such synergies give rise to some of t...

Metabolic Reprogramming Regulates the Proliferative and Inflammatory Phenotype of Adventitial Fibroblasts in Pulmonary Hypertension Through the Transcriptional Co-Repressor C-terminal Binding Protein-1

Science.gov (United States)

Li, Min; Riddle, Suzette; Zhang, Hui; D’Alessandro, Angelo; Flockton, Amanda; Serkova, Natalie J.; Hansen, Kirk C.; Moldvan, Radu; McKeon, B. Alexandre; Frid, Maria; Kumar, Sushil; Li, Hong; Liu, Hongbing; Cánovas, Angela; Medrano, Juan F.; Thomas, Milton G.; Iloska, Dijana; Plecita-Hlavata, Lydie; Ježek, Petr; Pullamsetti, Soni; Fini, Mehdi A.; El Kasmi, Karim C.; Zhang, Qinghong; Stenmark, Kurt R.

2016-01-01

Background Changes in metabolism have been suggested to contribute to the aberrant phenotype of vascular wall cells including fibroblasts in pulmonary hypertension (PH). Herein, we test the hypothesis that metabolic reprogramming to aerobic glycolysis is a critical adaptation of fibroblasts in the hypertensive vessel wall that drives proliferative and pro-inflammatory activation through a mechanism involving increased activity of the NADH-sensitive transcriptional co-repressor C-terminal binding protein 1 (CtBP1). Methods RNA-Sequencing, qPCR, 13C-NMR, fluorescence-lifetime imaging, mass spectrometry-based metabolomics and tracing experiments with U-13C-glucose were used to assess glycolytic reprogramming and to measure NADH/NAD+ ratio in bovine and human adventitial fibroblasts, and mouse lung tissues. Immunohistochemistry was utilized to assess CtBP1 expression in the whole lung tissues. CtBP1 siRNA and the pharmacologic inhibitor 4-methylthio-2-oxobutyric acid (MTOB) were utilized to abrogate CtBP1 activity in cells and hypoxic mice. Results We found adventitial fibroblasts from calves with severe hypoxia-induced PH and humans with IPAH (PH-Fibs) displayed aerobic glycolysis when cultured under normoxia, accompanied by increased free NADH and NADH/NAD+ ratios. Expression of the NADH sensor CtBP1 was increased in vivo and in vitro in fibroblasts within the pulmonary adventitia of humans with IPAH and animals with PH and cultured PH-Fibs, respectively. Decreasing NADH pharmacologically with MTOB, or genetically blocking CtBP1 using siRNA, upregulated the cyclin-dependent genes (p15 and p21) and pro-apoptotic regulators (NOXA and PERP), attenuated proliferation, corrected the glycolytic reprogramming phenotype of PH-Fibs, and augmented transcription of the anti-inflammatory gene HMOX1. ChIP analysis demonstrated that CtBP1 directly binds the HMOX1 promoter. Treatment of hypoxic mice with MTOB decreased glycolysis and expression of inflammatory genes, attenuated

Diacylglycerol lipase a knockout mice demonstrate metabolic and behavioral phenotypes similar to those of cannabinoid receptor 1 knockout mice

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David R Powell

2015-06-01

Full Text Available After creating >4650 knockouts (KOs of independent mouse genes, we screened them by high-throughput phenotyping and found that cannabinoid receptor 1 (Cnr1 KO mice had the same lean phenotype published by others. We asked if our KOs of DAG lipase a or b (Dagla or Daglb, which catalyze biosynthesis of the endocannabinoid (EC 2-Arachidonoylglycerol (2-AG, or Napepld, which catalyzes biosynthesis of the EC anandamide, shared the lean phenotype of Cnr1 KO mice. We found that Dagla KO mice, but not Daglb or Napepld KO mice, were among the leanest of 3651 chow-fed KO lines screened. In confirmatory studies, chow- or high fat diet-fed Dagla and Cnr1 KO mice were leaner than wild type (WT littermates; when data from multiple cohorts of adult mice were combined, body fat was 47% and 45% lower in Dagla and Cnr1 KO mice, respectively, relative to WT values. In contrast, neither Daglb nor Napepld KO mice were lean. Weanling Dagla KO mice ate less than WT mice and had body weight similar to pair-fed WT mice, and adult Dagla KO mice had normal activity and VO2 levels, similar to Cnr1 KO mice. Our Dagla and Cnr1 KO mice also had low fasting insulin, triglyceride and total cholesterol levels, and after a glucose challenge had normal glucose but very low insulin levels. Dagla and Cnr1 KO mice also showed similar responses to a battery of behavioral tests. These data suggest: 1 the lean phenotype of young Dagla and Cnr1 KO mice is mainly due to hypophagia; 2 in pathways where ECs signal through Cnr1 to regulate food intake and other metabolic and behavioral phenotypes observed in Cnr1 KO mice, Dagla alone provides the 2-AG that serves as the EC signal; and 3 small molecule Dagla inhibitors with a pharmacokinetic profile similar to that of Cnr1 inverse agonists are likely to mirror the ability of these Cnr1 inverse agonists to lower body weight and improve glycemic control in obese patients with type 2 diabetes, but may also induce undesirable neuropsychiatric

Lipid accumulation product as a marker of cardiometabolic susceptibility in women with different phenotypes of polycystic ovary syndrome.

Science.gov (United States)

Božić-Antić, Ivana; Ilić, Dušan; Bjekić-Macut, Jelica; Bogavac, Tamara; Vojnović-Milutinović, Danijela; Kastratovic-Kotlica, Biljana; Milić, Nataša; Stanojlović, Olivera; Andrić, Zoran; Macut, Djuro

2016-12-01

There are limited data on cardiometabolic risk factors and the prevalence of metabolic syndrome (MetS) across the different PCOS phenotypes in Caucasian population. Lipid accumulation product (LAP) is a clinical surrogate marker that could be used for evaluation of MetS in clinical practice. The aim of the study was to analyze metabolic characteristics and the ability of LAP to predict MetS in different PCOS phenotypes. Cross-sectional clinical study analyzing 365 women with PCOS divided into four phenotypes according to the ESHRE/ASRM criteria, and 125 healthy BMI-matched controls. In all subjects, LAP was determined and MetS was diagnosed according to the National Cholesterol Education Program/Adult Treatment Panel III (NCEP-ATP III), the International Diabetes Federation (IDF) and the Joint Interim Statement (JIS) criteria. Logistic regression and ROC curve analyses were used to determine predictors of MetS in each PCOS phenotype. All analyses were performed with age and BMI adjustment. All PCOS phenotypes in comparison to controls had higher prevalence of MetS assessed by NCEP-ATP III criteria, and only classic phenotypes when IDF and JIS criteria were used. All phenotypes had the same prevalence of MetS irrespective of used definition. LAP and exhibited the highest diagnostic accuracy and was an independent predictor of MetS in all phenotypes. LAP is an independent and accurate clinical determinant of MetS in all PCOS phenotypes in our Caucasian population. All PCOS phenotypes, including non-classic ones, are metabolically challenged and with cardiovascular risk, particularly phenotype B. © 2016 European Society of Endocrinology.

Oxygen-limited metabolism in the methanotroph Methylomicrobium buryatense 5GB1C

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Alexey Gilman

2017-10-01

Full Text Available The bacteria that grow on methane aerobically (methanotrophs support populations of non-methanotrophs in the natural environment by excreting methane-derived carbon. One group of excreted compounds are short-chain organic acids, generated in highest abundance when cultures are grown under O2-starvation. We examined this O2-starvation condition in the methanotroph Methylomicrobium buryatense 5GB1. The M. buryatense 5GB1 genome contains homologs for all enzymes necessary for a fermentative metabolism, and we hypothesize that a metabolic switch to fermentation can be induced by low-O2 conditions. Under prolonged O2-starvation in a closed vial, this methanotroph increases the amount of acetate excreted about 10-fold, but the formate, lactate, and succinate excreted do not respond to this culture condition. In bioreactor cultures, the amount of each excreted product is similar across a range of growth rates and limiting substrates, including O2-limitation. A set of mutants were generated in genes predicted to be involved in generating or regulating excretion of these compounds and tested for growth defects, and changes in excretion products. The phenotypes and associated metabolic flux modeling suggested that in M. buryatense 5GB1, formate and acetate are excreted in response to redox imbalance. Our results indicate that even under O2-starvation conditions, M. buryatense 5GB1 maintains a metabolic state representing a combination of fermentation and respiration metabolism.

Developmental Origin of Reproductive and Metabolic Dysfunctions: Androgenic Versus Estrogenic Reprogramming

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Padmanabhan, Vasantha; Veiga-Lopez, Almudena

2013-01-01

Polycystic ovary syndrome (PCOS) is one of the most common fertility disorders, affecting several million women worldwide. Women with PCOS manifest neuroendocrine, ovarian, and metabolic defects. A large number of animal models have evolved to understand the etiology of PCOS. These models provide support for the contributing role of excess steroids during development in programming the PCOS phenotype. However, considerable phenotypic variability is evident across animal models, depending on the quality of the steroid administered and the perinatal time of treatment relative to the developmental trajectory of the fetus/offspring. This review focuses on the reproductive and metabolic phenotypes of the various PCOS animal models that have evolved in the last decade to delineate the relative roles of androgens and estrogens in relation to the timing of exposure in programming the various dysfunctions that are part and parcel of the PCOS phenotype. Furthermore, the review addresses the contributory role of the postnatal metabolic environment in exaggerating the severity of the phenotype, the translational relevance of the various animal models to PCOS, and areas for future research. PMID:21710394

C-13 Tracer experiments and metabolite balancing for metabolic flux analysis

DEFF Research Database (Denmark)

Schmidt, Karsten; Marx, A.; de Graaf, A. A.

1998-01-01

performed independently for a wild-type strain of Aspergillus oryzae producing alpha-amylase. Two different nitrogen sources, NH4+ and NO3-, have been used to investigate the influence of the NADPH requirements on the intracellular flux distribution. The two different approaches to the calculation of fluxes...

Perspective: Evolution and detection of genetic robustness

NARCIS (Netherlands)

Visser, de J.A.G.M.; Hermisson, J.; Wagner, G.P.; Ancel Meyers, L.; Bagheri-Chaichian, H.; Blanchard, J.L.; Chao, L.; Cheverud, J.M.; Elena, S.F.; Fontana, W.; Gibson, G.; Hansen, T.F.; Krakauer, D.; Lewontin, R.C.; Ofria, C.; Rice, S.H.; Dassow, von G.; Wagner, A.; Whitlock, M.C.

2003-01-01

Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms

Construction of a Genome-Scale Metabolic Model of Arthrospira platensis NIES-39 and Metabolic Design for Cyanobacterial Bioproduction.

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Katsunori Yoshikawa

Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.

Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis

NARCIS (Netherlands)

Lee, Jessica J. Y.; Gottlieb, Michael M.; Lever, Jake; Jones, Steven J. M.; Blau, Nenad; van Karnebeek, Clara D. M.; Wasserman, Wyeth W.

2018-01-01

Phenomics is the comprehensive study of phenotypes at every level of biology: from metabolites to organisms. With high throughput technologies increasing the scope of biological discoveries, the field of phenomics has been developing rapid and precise methods to collect, catalog, and analyze

Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model

DEFF Research Database (Denmark)

Olivares Hernandez, Roberto

Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...

Prevalence of Desloratadine Slow-metabolizer Phenotype and Food-dependent Pharmacokinetics of Desloratadine in Healthy Chinese Volunteers.

Science.gov (United States)

Wang, Ting; Zhang, Kun; Li, Tingting; He, Lin; Xie, Huiru; Jiang, Xuehua; Wang, Ling

2015-12-01

Desloratadine, the major active metabolite of loratadine, is a non-sedating long-acting antihistamine that is widely used in the treatment of allergic rhinitis and chronic idiopathic urticaria. This study aimed to investigate the prevalence of desloratadine slow-metabolizer (DSM) phenotype and the effects of food on the pharmacokinetics of desloratadine and its active metabolite 3-OH-desloratadine in healthy Chinese volunteers. A total of 46 healthy Chinese male volunteers were included in this investigation. All subjects received a single dose of a 5-mg desloratadine tablet under fasting or fed conditions and the plasma concentrations of desloratadine and 3-OH-desloratadine were measured by liquid chromatography-tandem mass spectrometry. The pharmacokinetic profiles were analyzed using a non-compartmental method in the Phoenix WinNonlin program. The individuals with a 3-OH-desloratadine-to-desloratadine exposure ratio lower than 10 % or a desloratadine half-life (t 1/2) of ≥50 h were supposed to be DSM. There was only one DSM among the 46 volunteers, with a prevalence of 2.2 %. Moreover, administration in a fed state resulted in 34.07 and 32.06 % decreases in maximum plasma concentration and area under the concentration-time curve from time zero to infinity for desloratadine and 47.26 and 48.46 % for 3-OH-desloratadine compared with those values under fasting conditions. Taken together, these results indicated that the incidence of the DSM phenotype in the Chinese population was low and that food intake could significantly decrease the absorption rate and extent of desloratadine.

Metabolic response of Geobacter sulfurreducens towards electron donor/acceptor variation

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Lovley Derek R

2010-11-01

Full Text Available Abstract Background Geobacter sulfurreducens is capable of coupling the complete oxidation of organic compounds to iron reduction. The metabolic response of G. sulfurreducens towards variations in electron donors (acetate, hydrogen and acceptors (Fe(III, fumarate was investigated via 13C-based metabolic flux analysis. We examined the 13C-labeling patterns of proteinogenic amino acids obtained from G. sulfurreducens cultured with 13C-acetate. Results Using 13C-based metabolic flux analysis, we observed that donor and acceptor variations gave rise to differences in gluconeogenetic initiation, tricarboxylic acid cycle activity, and amino acid biosynthesis pathways. Culturing G. sulfurreducens cells with Fe(III as the electron acceptor and acetate as the electron donor resulted in pyruvate as the primary carbon source for gluconeogenesis. When fumarate was provided as the electron acceptor and acetate as the electron donor, the flux analysis suggested that fumarate served as both an electron acceptor and, in conjunction with acetate, a carbon source. Growth on fumarate and acetate resulted in the initiation of gluconeogenesis by phosphoenolpyruvate carboxykinase and a slightly elevated flux through the oxidative tricarboxylic acid cycle as compared to growth with Fe(III as the electron acceptor. In addition, the direction of net flux between acetyl-CoA and pyruvate was reversed during growth on fumarate relative to Fe(III, while growth in the presence of Fe(III and acetate which provided hydrogen as an electron donor, resulted in decreased flux through the tricarboxylic acid cycle. Conclusions We gained detailed insight into the metabolism of G. sulfurreducens cells under various electron donor/acceptor conditions using 13C-based metabolic flux analysis. Our results can be used for the development of G. sulfurreducens as a chassis for a variety of applications including bioremediation and renewable biofuel production.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

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McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Variations in gut microbiota and fecal metabolic phenotype associated with Fenbendazole and Ivermectin Tablets by 16S rRNA gene sequencing and LC/MS-based metabolomics in Amur tiger.

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He, Fengping; Zhai, Jiancheng; Zhang, Le; Liu, Dan; Ma, Yue; Rong, Ke; Xu, Yanchun; Ma, Jianzhang

2018-05-15

The Amur tiger is one of the most endangered species in the world, and the healthy population of captive Amur tigers assists the recovery of the wild population. Gut microbes have been shown to be important for human disease and health, but little research exists regarding the microbiome of Amur tigers in captivity. In this study, we used an integrated approach of 16S rRNA gene sequencing combined with ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS)-based metabolomics to analyze the effects of Fenbendazole and Ivermectin Tablets on the gut microbiota and fecal metabolic phenotype of the Amur tiger. The relative abundances of the bacterial genera Collinsella, Clostridium XI and Megamonas were decreased, whereas those of Escherichia and Clostridium sensu stricto were increased in experimental Amur tigers compared with those in normal controls. Meanwhile, distinct changes in the fecal metabolic phenotype of the experimental Amur tigers were also found, including lower levels of acrylic acid, acetoacetate and catechol and higher amounts of 5,6-dihydrouracil, adenine hydrochloride hydrate and galactitol. Moreover, the differentially abundant gut microbes were substantially associated with the altered fecal metabolites, especially the bacteria in the Firmicutes and Actinomycetes, which were involved in the metabolism of 5,6-dihydrouracil, 6-phospho-d-gluconate and 1-methylnicotinamide. Our results indicate for the first time that Fenbendazole and Ivermectin Tablets not only disturb the gut microbiota at the abundance level but also alter the metabolic homeostasis of the Amur tiger. Copyright © 2018 Elsevier Inc. All rights reserved.

Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism

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Flamholz, Avi; Reznik, Ed; Liebermeister, Wolfram; Milo, Ron

2014-01-01

In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (ΔrG′). Accordingly, if an enzyme catalyzes a reaction with a ΔrG′ of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As ΔrG′ approaches equilibrium (ΔrG′ = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating

A hybrid approach identifies metabolic signatures of high-producers for chinese hamster ovary clone selection and process optimization.

Science.gov (United States)

Popp, Oliver; Müller, Dirk; Didzus, Katharina; Paul, Wolfgang; Lipsmeier, Florian; Kirchner, Florian; Niklas, Jens; Mauch, Klaus; Beaucamp, Nicola

2016-09-01

In-depth characterization of high-producer cell lines and bioprocesses is vital to ensure robust and consistent production of recombinant therapeutic proteins in high quantity and quality for clinical applications. This requires applying appropriate methods during bioprocess development to enable meaningful characterization of CHO clones and processes. Here, we present a novel hybrid approach for supporting comprehensive characterization of metabolic clone performance. The approach combines metabolite profiling with multivariate data analysis and fluxomics to enable a data-driven mechanistic analysis of key metabolic traits associated with desired cell phenotypes. We applied the methodology to quantify and compare metabolic performance in a set of 10 recombinant CHO-K1 producer clones and a host cell line. The comprehensive characterization enabled us to derive an extended set of clone performance criteria that not only captured growth and product formation, but also incorporated information on intracellular clone physiology and on metabolic changes during the process. These criteria served to establish a quantitative clone ranking and allowed us to identify metabolic differences between high-producing CHO-K1 clones yielding comparably high product titers. Through multivariate data analysis of the combined metabolite and flux data we uncovered common metabolic traits characteristic of high-producer clones in the screening setup. This included high intracellular rates of glutamine synthesis, low cysteine uptake, reduced excretion of aspartate and glutamate, and low intracellular degradation rates of branched-chain amino acids and of histidine. Finally, the above approach was integrated into a workflow that enables standardized high-content selection of CHO producer clones in a high-throughput fashion. In conclusion, the combination of quantitative metabolite profiling, multivariate data analysis, and mechanistic network model simulations can identify metabolic

The Role of Monoaminergic Neurotransmission for Metabolic Control in the Fruit Fly Drosophila Melanogaster

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Yong Li

2017-08-01

Full Text Available Hormones control various metabolic traits comprising fat deposition or starvation resistance. Here we show that two invertebrate neurohormones, octopamine (OA and tyramine (TA as well as their associated receptors, had a major impact on these metabolic traits. Animals devoid of the monoamine OA develop a severe obesity phenotype. Using flies defective in the expression of receptors for OA and TA, we aimed to decipher the contributions of single receptors for these metabolic phenotypes. Whereas those animals impaired in octß1r, octß2r and tar1 share the obesity phenotype of OA-deficient (tβh-deficient animals, the octß1r, octß2r deficient flies showed reduced insulin release, which is opposed to the situation found in tβh-deficient animals. On the other hand, OAMB deficient flies were leaner than controls, implying that the regulation of this phenotype is more complex than anticipated. Other phenotypes seen in tβh-deficient animals, such as the reduced ability to perform complex movements tasks can mainly be attributed to the octß2r. Tissue-specific RNAi experiments revealed a very complex interorgan communication leading to the different metabolic phenotypes observed in OA or OA and TA-deficient flies.

Increased entropy of signal transduction in the cancer metastasis phenotype

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Teschendorff Andrew E

2010-07-01

Full Text Available Abstract Background The statistical study of biological networks has led to important novel biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Results Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis and provide examples of de-novo discoveries of gene modules with known roles in apoptosis, immune-mediated tumour suppression, cell-cycle and tumour invasion. Importantly, we also identify a novel gene module within the insulin growth factor signalling pathway, alteration of which may

Rethinking the evolution of specialization: A model for the evolution of phenotypic heterogeneity.

Science.gov (United States)

Rubin, Ilan N; Doebeli, Michael

2017-12-21

Phenotypic heterogeneity refers to genetically identical individuals that express different phenotypes, even when in the same environment. Traditionally, "bet-hedging" in fluctuating environments is offered as the explanation for the evolution of phenotypic heterogeneity. However, there are an increasing number of examples of microbial populations that display phenotypic heterogeneity in stable environments. Here we present an evolutionary model of phenotypic heterogeneity of microbial metabolism and a resultant theory for the evolution of phenotypic versus genetic specialization. We use two-dimensional adaptive dynamics to track the evolution of the population phenotype distribution of the expression of two metabolic processes with a concave trade-off. Rather than assume a Gaussian phenotype distribution, we use a Beta distribution that is capable of describing genotypes that manifest as individuals with two distinct phenotypes. Doing so, we find that environmental variation is not a necessary condition for the evolution of phenotypic heterogeneity, which can evolve as a form of specialization in a stable environment. There are two competing pressures driving the evolution of specialization: directional selection toward the evolution of phenotypic heterogeneity and disruptive selection toward genetically determined specialists. Because of the lack of a singular point in the two-dimensional adaptive dynamics and the fact that directional selection is a first order process, while disruptive selection is of second order, the evolution of phenotypic heterogeneity dominates and often precludes speciation. We find that branching, and therefore genetic specialization, occurs mainly under two conditions: the presence of a cost to maintaining a high phenotypic variance or when the effect of mutations is large. A cost to high phenotypic variance dampens the strength of selection toward phenotypic heterogeneity and, when sufficiently large, introduces a singular point into

Toxic metabolic syndrome associated with HAART

DEFF Research Database (Denmark)

Haugaard, Steen B

2006-01-01

(HAART) may encounter the HIV-associated lipodystrophy syndrome (HALS), which attenuates patient compliance to this treatment. HALS is characterised by impaired glucose and lipid metabolism and other risk factors for cardiovascular disease. This review depicts the metabolic abnormalities associated...... with HAART by describing the key cell and organ systems that are involved, emphasising the role of insulin resistance. An opinion on the remedies available to treat the metabolic abnormalities and phenotype of HALS is provided....

Gaucher Disease: The Metabolic Defect, Pathophysiology, Phenotypes And Natural History

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Baris, Hagit N.; Cohen, Ian J.; Mistry, Pramod K.

2015-01-01

Gaucher disease (GD), a prototype lysosomal storage disorder, results from inherited deficiency of lysosomal glucocerebrosidase due to biallelic mutations in GBA. The result is widespread accumulation of macrophages engorged with predominantly lysosomal glucocerebroside. A complex multisystem phenotype arises involving the liver, spleen, bone marrow and occasionally the lungs in type 1 Gaucher disease; in neuronopathic fulminant type 2 and chronic type 3 disease there is in addition progressive neurodegenerative disease. Manifestations of Gaucher disease type 1 (GD1) include hepatosplenomegaly, cytopenia, a complex pattern of bone involvement with avascular osteonecrosis (AVN), osteoporosis, fractures and lytic lesions. Enzyme replacement therapy became the standard of care in 1991, and this has transformed the natural history of GD1. This article reviews the clinical phenotypes of GD, diagnosis, pathophysiology and its natural history. A subsequent chapter discusses the treatment options. PMID:25345088

Polycystic ovary syndrome: reviewing diagnosis and management of metabolic disturbances.

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Spritzer, Poli Mara

2014-03-01

Polycystic ovary syndrome (PCOS) is a common condition in women at reproductive age associated with reproductive and metabolic dysfunction. Proposed diagnosed criteria for PCOS include two out of three features: androgen excess, menstrual irregularity, and polycystic ovary appearance on ultrasound (PCO), after other causes of hyperandrogenism and dysovulation are excluded. Based on these diagnostic criteria, the most common phenotypes are the "classic PCOS"--hyperandrogenism and oligomenorrhea, with or without PCO; the "ovulatory phenotype"--hyperandrogenism and PCO in ovulatory women; and the "non-hyperandrogenic phenotype", in which there is oligomenorrhea and PCO, without overt hyperandrogenism. The presence of obesity may exacerbate the metabolic and reproductive disorders associated with the syndrome. In addition, PCOS women present higher risk for type 2 diabetes and higher prevalence of cardiovascular risk factors that seems to be associated with the classic phenotype. The main interventions to minimize cardiovascular and metabolic risks in PCOS are lifestyle changes, pharmacological therapy, and bariatric surgery. Treatment with metformin has been shown to improve insulin sensitivity, lowering blood glucose and androgen levels. These effects are more potent when combined with lifestyle interventions. In conclusion, besides reproductive abnormalities, PCOS has been associated to metabolic comorbidities, most of them linked to obesity. Confounders, such as the lack of standard diagnostic criteria, heterogeneity of the clinical presentation, and presence of obesity, make management of PCOS difficult. Therefore, the approach to metabolic abnormalities should be tailored to the risks and treatment goals of each individual woman.

Quantitative Assessment of Thermodynamic Constraints on the Solution Space of Genome-Scale Metabolic Models

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Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.

2013-01-01

Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272

Fructan biosynthesis and degradation as part of plant metabolism controlling sugar fluxes during durum wheat kernel maturation

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Sara eCimini

2015-02-01

Full Text Available Wheat kernels contain fructans, fructose based oligosaccharides with prebiotic properties, in levels between 2 and 35 weight % depending on the developmental stage of the kernel. To improve knowledge on the metabolic pathways leading to fructan storage and degradation, carbohydrate fluxes occurring during durum wheat kernel development were analyzed. Kernels were collected at various developmental stages and quali-quantitative analysis of carbohydrates (mono- and di-saccharides, fructans, starch was performed, alongside analysis of the activities and gene expression of the enzymes involved in their biosynthesis and hydrolysis. High resolution HPAEC-PAD of fructan contained in durum wheat kernels revealed that fructan content is higher at the beginning of kernel development, when fructans with higher DP, such as bifurcose and 1,1-nystose, were mainly found. The changes in fructan pool observed during kernel maturation might be part of the signaling pathways influencing carbohydrate metabolism and storage in wheat kernels during development. During the first developmental stages fructan accumulation may contribute to make kernels more effective Suc sinks and to participate in osmotic regulation while the observed decrease in their content may mark the transition to later developmental stages, transition that is also orchestrated by changes in redox balance.

Modeling combined schizophrenia-related behavioral and metabolic phenotypes in rodents

NARCIS (Netherlands)

Sarnyai, Zoltán; Jashar, Cassandra; Olivier, Berend

2015-01-01

Schizophrenia is a chronic, debilitating disorder with a complex behavioral and cognitive phenotype underlined by a similarly complex etiology involving an interaction between susceptibility genes and environmental factors during early development. Limited progress has been made in developing novel

Slave nodes and the controllability of metabolic networks

International Nuclear Information System (INIS)

Kim, Dong-Hee; Motter, Adilson E

2009-01-01

Recent work on synthetic rescues has shown that the targeted deletion of specific metabolic genes can often be used to rescue otherwise non-viable mutants. This raises a fundamental biophysical question: to what extent can the whole-cell behavior of a large metabolic network be controlled by constraining the flux of one or more reactions in the network? This touches upon the issue of the number of degrees of freedom contained by one such network. Using the metabolic network of Escherichia coli as a model system, here we address this question theoretically by exploring not only reaction deletions, but also a continuum of all possible reaction expression levels. We show that the behavior of the metabolic network can be largely manipulated by the pinned expression of a single reaction. In particular, a relevant fraction of the metabolic reactions exhibits canalizing interactions, in that the specification of one reaction flux determines cellular growth as well as the fluxes of most other reactions in optimal steady states. The activity of individual reactions can thus be used as surrogates to monitor and possibly control cellular growth and other whole-cell behaviors. In addition to its implications for the study of control processes, our methodology provides a new approach to study how the integrated dynamics of the entire metabolic network emerges from the coordinated behavior of its component parts.

Compartmentation of glycogen metabolism revealed from 13C isotopologue distributions

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Marin de Mas Igor

2011-10-01

Full Text Available Abstract Background Stable isotope tracers are used to assess metabolic flux profiles in living cells. The existing methods of measurement average out the isotopic isomer distribution in metabolites throughout the cell, whereas the knowledge of compartmental organization of analyzed pathways is crucial for the evaluation of true fluxes. That is why we accepted a challenge to create a software tool that allows deciphering the compartmentation of metabolites based on the analysis of average isotopic isomer distribution. Results The software Isodyn, which simulates the dynamics of isotopic isomer distribution in central metabolic pathways, was supplemented by algorithms facilitating the transition between various analyzed metabolic schemes, and by the tools for model discrimination. It simulated 13C isotope distributions in glucose, lactate, glutamate and glycogen, measured by mass spectrometry after incubation of hepatocytes in the presence of only labeled glucose or glucose and lactate together (with label either in glucose or lactate. The simulations assumed either a single intracellular hexose phosphate pool, or also channeling of hexose phosphates resulting in a different isotopic composition of glycogen. Model discrimination test was applied to check the consistency of both models with experimental data. Metabolic flux profiles, evaluated with the accepted model that assumes channeling, revealed the range of changes in metabolic fluxes in liver cells. Conclusions The analysis of compartmentation of metabolic networks based on the measured 13C distribution was included in Isodyn as a routine procedure. The advantage of this implementation is that, being a part of evaluation of metabolic fluxes, it does not require additional experiments to study metabolic compartmentation. The analysis of experimental data revealed that the distribution of measured 13C-labeled glucose metabolites is inconsistent with the idea of perfect mixing of hexose

Carbohydrates digestion and metabolism in the spiny lobster (Panulirus argus): biochemical indication for limited carbohydrate utilization.

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Rodríguez-Viera, Leandro; Perera, Erick; Montero-Alejo, Vivian; Perdomo-Morales, Rolando; García-Galano, Tsai; Martínez-Rodríguez, Gonzalo; Mancera, Juan M

2017-01-01

As other spiny lobsters, Panulirus argus is supposed to use preferentially proteins and lipids in energy metabolism, while carbohydrates are well digested but poorly utilized. The aim of this study was to evaluate the effect of dietary carbohydrate level on digestion and metabolism in the spiny lobster P. argus . We used complementary methodologies such as post-feeding flux of nutrients and metabolites, as well as measurements of α-amylase expression and activity in the digestive tract. Lobsters readily digested and absorbed carbohydrates with a time-course that is dependent on their content in diet. Lobster showed higher levels of free glucose and stored glycogen in different tissues as the inclusion of wheat flour increased. Modifications in intermediary metabolism revealed a decrease in amino acids catabolism coupled with a higher use of free glucose as carbohydrates rise up to 20%. However, this effect seems to be limited by the metabolic capacity of lobsters to use more than 20% of carbohydrates in diets. Lobsters were not able to tightly regulate α-amylase expression according to dietary carbohydrate level but exhibited a marked difference in secretion of this enzyme into the gut. Results are discussed to highlight the limitations to increasing carbohydrate utilization by lobsters. Further growout trials are needed to link the presented metabolic profiles with phenotypic outcomes.

Carbohydrates digestion and metabolism in the spiny lobster (Panulirus argus: biochemical indication for limited carbohydrate utilization

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Leandro Rodríguez-Viera

2017-11-01

Full Text Available As other spiny lobsters, Panulirus argus is supposed to use preferentially proteins and lipids in energy metabolism, while carbohydrates are well digested but poorly utilized. The aim of this study was to evaluate the effect of dietary carbohydrate level on digestion and metabolism in the spiny lobster P. argus. We used complementary methodologies such as post-feeding flux of nutrients and metabolites, as well as measurements of α-amylase expression and activity in the digestive tract. Lobsters readily digested and absorbed carbohydrates with a time-course that is dependent on their content in diet. Lobster showed higher levels of free glucose and stored glycogen in different tissues as the inclusion of wheat flour increased. Modifications in intermediary metabolism revealed a decrease in amino acids catabolism coupled with a higher use of free glucose as carbohydrates rise up to 20%. However, this effect seems to be limited by the metabolic capacity of lobsters to use more than 20% of carbohydrates in diets. Lobsters were not able to tightly regulate α-amylase expression according to dietary carbohydrate level but exhibited a marked difference in secretion of this enzyme into the gut. Results are discussed to highlight the limitations to increasing carbohydrate utilization by lobsters. Further growout trials are needed to link the presented metabolic profiles with phenotypic outcomes.

Deciphering flux adjustments of engineered E. coli cells during fermentation with changing growth conditions

Energy Technology Data Exchange (ETDEWEB)

He, Lian [Washington Univ., St. Louis, MO (United States); Xiu, Yu [Rensselaer Polytechnic Inst., Troy, NY (United States); Beijing Univ. of Chemical Technology (China); Jones, J. Andrew [Rensselaer Polytechnic Inst., Troy, NY (United States); Hamilton College, Clinton, NY (United States); Baidoo, Edward E. K. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Keasling, Jay D. [Joint BioEnergy Inst. (JBEI), Emeryville, CA (United States); Univ. of California, Berkeley, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Technical Univ. of Denmark, Lyngby (Denmark); Tang, Yinjie J. [Washington Univ., St. Louis, MO (United States); Koffas, Mattheos A. G. [Rensselaer Polytechnic Inst., Troy, NY (United States)

2016-12-23

Microbial fermentation conditions are dynamic, due to transcriptional induction, nutrient consumption, or changes to incubation conditions. In this paper, ¹³C-metabolic flux analysis was used to characterize two violacein-producing E. coli strains with vastly different productivities, and to profile their metabolic adjustments resulting from external perturbations during fermentation. The two strains were first grown at 37 °C in stage 1, and then the temperature was transitioned to 20 °C in stage 2 for the optimal expression of the violacein synthesis pathway. After induction, violacein production was minimal in stage 3, but accelerated in stage 4 (early production phase) and 5 (late production phase) in the high producing strain, reaching a final concentration of 1.5 mmol/L. On the contrary, ~0.02 mmol/L of violacein was obtained from the low producing strain. To have a snapshot of the temporal metabolic changes in each stage, we performed ¹³C-MFA via isotopomer analysis of fast-turnover free metabolites. The results indicate strikingly stable flux ratios in the central metabolism throughout the early growth stages. In the late stages, however, the high producer rewired its flux distribution significantly, which featured an upregulated pentose phosphate pathway and TCA cycle, reflux from acetate utilization, negligible anabolic fluxes, and elevated maintenance loss, to compensate for nutrient depletion and drainage of some building blocks due to violacein overproduction. The low producer with stronger promoters shifted its relative fluxes in stage 5 by enhancing the flux through the TCA cycle and acetate overflow, while exhibiting a reduced biomass growth and a minimal flux towards violacein synthesis. Finally, interestingly, the addition of the violacein precursor (tryptophan) in the medium inhibited high producer but enhanced low producer's productivity, leading to hypotheses of unknown pathway regulations (such as metabolite

Engineering of metabolic control

Science.gov (United States)

Liao, James C.

2004-03-16

The invention features a method of producing heterologous molecules in cells under the regulatory control of a metabolite and metabolic flux. The method can enhance the synthesis of heterologous polypeptides and metabolites.

Signaling Pathways Regulating Redox Balance in Cancer Metabolism.

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De Santis, Maria Chiara; Porporato, Paolo Ettore; Martini, Miriam; Morandi, Andrea

2018-01-01

The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells' demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions.

Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production

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Brooks J Paul

2010-03-01

Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum

Heritability of eleven metabolic phenotypes in Danish and Chinese twins

DEFF Research Database (Denmark)

Li, Shuxia; Duan, Hongmei; Pang, Zengchang

2013-01-01

modeling was performed on full and nested models with the best fitting models selected. Results: Heritability estimates were compared between Danish and Chinese samples to identify differential genetic influences on each of the phenotypes. Except for hip circumference, all other body measures exhibited...

Epigenomics, gestational programming and risk of metabolic syndrome.

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Desai, M; Jellyman, J K; Ross, M G

2015-04-01

Epigenetic mechanisms are emerging as mediators linking early environmental exposures during pregnancy with programmed changes in gene expression that alter offspring growth and development. There is irrefutable evidence from human and animal studies that nutrient and environmental agent exposures (for example, endocrine disruptors) during pregnancy may affect fetal/newborn development resulting in offspring obesity and obesity-associated metabolic abnormalities (metabolic syndrome). This concept of 'gestational programming' is associated with alterations to the epigenome (nongenomic) rather than changes in the DNA sequence (genomic). Epigenetic alterations induced by suboptimal maternal nutrition/endocrine factors include DNA methylation, histone modifications, chromatin remodeling and/or regulatory feedback by microRNAs, all of which have the ability to modulate gene expression and promote the metabolic syndrome phenotype. Recent studies have shown tissue-specific transcriptome patterns and phenotypes not only in the exposed individual, but also in subsequent progeny. Notably, the transmission of gestational programming effects to subsequent generations occurs in the absence of continued adverse environmental exposures, thus propagating the cycle of obesity and metabolic syndrome. This phenomenon may be attributed to an extrinsic process resulting from the maternal phenotype and the associated nutrient alterations occurring within each pregnancy. In addition, epigenetic inheritance may occur through somatic cells or through the germ line involving both maternal and paternal lineages. Since epigenetic gene modifications may be reversible, understanding how epigenetic mechanisms contribute to transgenerational transmission of obesity and metabolic dysfunction is crucial for the development of novel early detection and prevention strategies for programmed metabolic syndrome. In this review we discuss the evidence in human and animal studies for the role of

Quantitative intracellular flux modeling and applications in biotherapeutic development and production using CHO cell cultures.

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Huang, Zhuangrong; Lee, Dong-Yup; Yoon, Seongkyu

2017-12-01

Chinese hamster ovary (CHO) cells have been widely used for producing many recombinant therapeutic proteins. Constraint-based modeling, such as flux balance analysis (FBA) and metabolic flux analysis (MFA), has been developing rapidly for the quantification of intracellular metabolic flux distribution at a systematic level. Such methods would produce detailed maps of flows through metabolic networks, which contribute significantly to better understanding of metabolism in cells. Although these approaches have been extensively established in microbial systems, their application to mammalian cells is sparse. This review brings together the recent development of constraint-based models and their applications in CHO cells. The further development of constraint-based modeling approaches driven by multi-omics datasets is discussed, and a framework of potential modeling application in cell culture engineering is proposed. Improved cell culture system understanding will enable robust developments in cell line and bioprocess engineering thus accelerating consistent process quality control in biopharmaceutical manufacturing. © 2017 Wiley Periodicals, Inc.

MKR mice have increased dynamic glucose disposal despite metabolic inflexibility, and hepatic and peripheral insulin insensitivity.

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Vaitheesvaran, B; LeRoith, D; Kurland, I J

2010-10-01

Recent work has shown that there can be significant differences when glucose disposal is assessed for high-fat induced insulin resistance by static clamp methods vs dynamic assessment during a stable isotope i.p. glucose tolerance test. MKR mice, though lean, have severe insulin resistance and decreased muscle fatty acid oxidation. Our goal was to assess dynamic vs static glucose disposal in MKR mice, and to correlate glucose disposal and muscle-adipose-liver flux interactions with metabolic flexibility (indirect calorimetry) and muscle characteristics. Stable isotope flux phenotyping was performed using [6,6-(2)H(2)]glucose, [U-(13)C(6)]glucose and [2-(13)C]glycerol. Muscle triacylglycerol (TAG) and diacylglycerol (DAG) content was assessed by thin layer chromatography, and histological determination of fibre type and cytochrome c activity performed. Metabolic flexibility was assessed by indirect calorimetry. Indirect calorimetry showed that MKR mice used more glucose than FVB/N mice during fasting (respiratory exchange ratio [RER] 0.88 vs 0.77, respectively). Compared with FVB/N mice, MKR mice had faster dynamic glucose disposal, despite increased whole-muscle DAG and TAG, and similar hepatic glucose production with higher fasting insulin and unchanged basal glucose. Fed MKR muscle had more glycogen, and increased levels of GLUT1 and GLUT4 than FVB/N muscle. Histology indicated that MKR soleus had mildly decreased cytochrome c activity overall and more type II (glycolytic) fibres compared with that in FVB/N mice. MKR muscle adapts to using glucose, with more type II fibres present in red muscle. Fasting RER is elevated and glucose disposal during an i.p. glucose tolerance test is accelerated despite increased muscle DAG and TAG. Metabolic inflexibility may result from the compensatory use of fuel that can be best utilised for energy requirements; static vs dynamic glucose disposal assessments may measure complementary aspects of metabolic flexibility and insulin

Redox balance is key to explaining full vs. partial switching to low-yield metabolism

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van Hoek Milan JA

2012-03-01

Full Text Available Abstract Background Low-yield metabolism is a puzzling phenomenon in many unicellular and multicellular organisms. In abundance of glucose, many cells use a highly wasteful fermentation pathway despite the availability of a high-yield pathway, producing many ATP molecules per glucose, e.g., oxidative phosphorylation. Some of these organisms, including the lactic acid bacterium Lactococcus lactis, downregulate their high-yield pathway in favor of the low-yield pathway. Other organisms, including Escherichia coli do not reduce the flux through the high-yield pathway, employing the low-yield pathway in parallel with a fully active high-yield pathway. For what reasons do some species use the high-yield and low-yield pathways concurrently and what makes others downregulate the high-yield pathway? A classic rationale for metabolic fermentation is overflow metabolism. Because the throughput of metabolic pathways is limited, influx of glucose exceeding the pathway's throughput capacity is thought to be redirected into an alternative, low-yield pathway. This overflow metabolism rationale suggests that cells would only use fermentation once the high-yield pathway runs at maximum rate, but it cannot explain why cells would decrease the flux through the high-yield pathway. Results Using flux balance analysis with molecular crowding (FBAwMC, a recent extension to flux balance analysis (FBA that assumes that the total flux through the metabolic network is limited, we investigate the differences between Saccharomyces cerevisiae and L. lactis that downregulate the high-yield pathway at increasing glucose concentrations, and E. coli, which keeps the high-yield pathway functioning at maximal rate. FBAwMC correctly predicts the metabolic switching mode in these three organisms, suggesting that metabolic network architecture is responsible for differences in metabolic switching mode. Based on our analysis, we expect gradual, "overflow-like" switching behavior in

Microbial-Host Co-metabolites Are Prodromal Markers Predicting Phenotypic Heterogeneity in Behavior, Obesity, and Impaired Glucose Tolerance

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Marc-Emmanuel Dumas

2017-07-01

Full Text Available The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50 and show that microbial-host co-metabolites are prodromal (i.e., early markers predicting future divergence in metabolic (obesity and glucose homeostasis and behavioral (anxiety and activity outcomes with 94%–100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO, a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT, and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity.

Understanding Regulation of Metabolism through Feasibility Analysis

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Nikerel, Emrah; Berkhout, Jan; Hu, Fengyuan; Teusink, Bas; Reinders, Marcel J. T.; de Ridder, Dick

2012-01-01

Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but through non-obvious combinations of hierarchical (gene and enzyme levels) and metabolic regulation (mass action and allosteric interaction). Quantitative analyses relating changes in metabolic fluxes to changes in transcript or protein levels have revealed a remarkable lack of understanding of the regulation of these networks. We study metabolic regulation via feasibility analysis (FA). Inspired by the constraint-based approach of Flux Balance Analysis, FA incorporates a model describing kinetic interactions between molecules. We enlarge the portfolio of objectives for the cell by defining three main physiologically relevant objectives for the cell: function, robustness and temporal responsiveness. We postulate that the cell assumes one or a combination of these objectives and search for enzyme levels necessary to achieve this. We call the subspace of feasible enzyme levels the feasible enzyme space. Once this space is constructed, we can study how different objectives may (if possible) be combined, or evaluate the conditions at which the cells are faced with a trade-off among those. We apply FA to the experimental scenario of long-term carbon limited chemostat cultivation of yeast cells, studying how metabolism evolves optimally. Cells employ a mixed strategy composed of increasing enzyme levels for glucose uptake and hexokinase and decreasing levels of the remaining enzymes. This trade-off renders the cells specialized in this low-carbon flux state to compete for the available glucose and get rid of over-overcapacity. Overall, we show that FA is a powerful tool for systems biologists to study regulation of metabolism, interpret experimental data and evaluate hypotheses. PMID

YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities

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