Analysis of Neural-BOLD Coupling through Four Models of the Neural Metabolic Demand

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Christopher W Tyler

2015-12-01

Full Text Available The coupling of the neuronal energetics to the blood-oxygen-level-dependent (BOLD response is still incompletely understood. To address this issue, we compared the fits of four plausible models of neurometabolic coupling dynamics to available data for simultaneous recordings of the local field potential (LFP and the local BOLD response recorded from monkey primary visual cortex over a wide range of stimulus durations. The four models of the metabolic demand driving the BOLD response were: direct coupling with the overall LFP; rectified coupling to the LFP; coupling with a slow adaptive component of the implied neural population response; and coupling with the non-adaptive intracellular input signal defined by the stimulus time course. Taking all stimulus durations into account, the results imply that the BOLD response is most closely coupled with metabolic demand derived from the intracellular input waveform, without significant influence from the adaptive transients and nonlinearities exhibited by the LFP waveform.

Systems biology from micro-organisms to human metabolic diseases: the role of detailed kinetic models.

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Bakker, Barbara M; van Eunen, Karen; Jeneson, Jeroen A L; van Riel, Natal A W; Bruggeman, Frank J; Teusink, Bas

2010-10-01

Human metabolic diseases are typically network diseases. This holds not only for multifactorial diseases, such as metabolic syndrome or Type 2 diabetes, but even when a single gene defect is the primary cause, where the adaptive response of the entire network determines the severity of disease. The latter may differ between individuals carrying the same mutation. Understanding the adaptive responses of human metabolism naturally requires a systems biology approach. Modelling of metabolic pathways in micro-organisms and some mammalian tissues has yielded many insights, qualitative as well as quantitative, into their control and regulation. Yet, even for a well-known pathway such as glycolysis, precise predictions of metabolite dynamics from experimentally determined enzyme kinetics have been only moderately successful. In the present review, we compare kinetic models of glycolysis in three cell types (African trypanosomes, yeast and skeletal muscle), evaluate their predictive power and identify limitations in our understanding. Although each of these models has its own merits and shortcomings, they also share common features. For example, in each case independently measured enzyme kinetic parameters were used as input. Based on these 'lessons from glycolysis', we will discuss how to make best use of kinetic computer models to advance our understanding of human metabolic diseases.

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity.

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Marc Breit

2015-08-01

Full Text Available The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS with the concept of stable isotope dilution (SID for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2, showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001. In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001, classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001. These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling

Modeling metabolism and stage-specific growth of Plasmodium falciparum HB3 during the intraerythrocytic developmental cycle.

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Fang, Xin; Reifman, Jaques; Wallqvist, Anders

2014-10-01

The human malaria parasite Plasmodium falciparum goes through a complex life cycle, including a roughly 48-hour-long intraerythrocytic developmental cycle (IDC) in human red blood cells. A better understanding of the metabolic processes required during the asexual blood-stage reproduction will enhance our basic knowledge of P. falciparum and help identify critical metabolic reactions and pathways associated with blood-stage malaria. We developed a metabolic network model that mechanistically links time-dependent gene expression, metabolism, and stage-specific growth, allowing us to predict the metabolic fluxes, the biomass production rates, and the timing of production of the different biomass components during the IDC. We predicted time- and stage-specific production of precursors and macromolecules for P. falciparum (strain HB3), allowing us to link specific metabolites to specific physiological functions. For example, we hypothesized that coenzyme A might be involved in late-IDC DNA replication and cell division. Moreover, the predicted ATP metabolism indicated that energy was mainly produced from glycolysis and utilized for non-metabolic processes. Finally, we used the model to classify the entire tricarboxylic acid cycle into segments, each with a distinct function, such as superoxide detoxification, glutamate/glutamine processing, and metabolism of fumarate as a byproduct of purine biosynthesis. By capturing the normal metabolic and growth progression in P. falciparum during the IDC, our model provides a starting point for further elucidation of strain-specific metabolic activity, host-parasite interactions, stress-induced metabolic responses, and metabolic responses to antimalarial drugs and drug candidates.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling.

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Cuperlovic-Culf, Miroslava

2018-01-11

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies.

Machine Learning Methods for Analysis of Metabolic Data and Metabolic Pathway Modeling

Science.gov (United States)

Cuperlovic-Culf, Miroslava

2018-01-01

Machine learning uses experimental data to optimize clustering or classification of samples or features, or to develop, augment or verify models that can be used to predict behavior or properties of systems. It is expected that machine learning will help provide actionable knowledge from a variety of big data including metabolomics data, as well as results of metabolism models. A variety of machine learning methods has been applied in bioinformatics and metabolism analyses including self-organizing maps, support vector machines, the kernel machine, Bayesian networks or fuzzy logic. To a lesser extent, machine learning has also been utilized to take advantage of the increasing availability of genomics and metabolomics data for the optimization of metabolic network models and their analysis. In this context, machine learning has aided the development of metabolic networks, the calculation of parameters for stoichiometric and kinetic models, as well as the analysis of major features in the model for the optimal application of bioreactors. Examples of this very interesting, albeit highly complex, application of machine learning for metabolism modeling will be the primary focus of this review presenting several different types of applications for model optimization, parameter determination or system analysis using models, as well as the utilization of several different types of machine learning technologies. PMID:29324649

Kinetic modeling of cell metabolism for microbial production.

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Costa, Rafael S; Hartmann, Andras; Vinga, Susana

2016-02-10

Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. Copyright © 2015 Elsevier B.V. All rights reserved.

Role of the Mixed-Lineage Protein Kinase Pathway in the Metabolic Stress Response to Obesity

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Shashi Kant

2013-08-01

Full Text Available Saturated free fatty acid (FFA is implicated in the metabolic response to obesity. In vitro studies indicate that FFA signaling may be mediated by the mixed-lineage protein kinase (MLK pathway that activates cJun NH2-terminal kinase (JNK. Here, we examined the role of the MLK pathway in vivo using a mouse model of diet-induced obesity. The ubiquitously expressed MLK2 and MLK3 protein kinases have partially redundant functions. We therefore compared wild-type and compound mutant mice that lack expression of MLK2 and MLK3. MLK deficiency protected mice against high-fat-diet-induced insulin resistance and obesity. Reduced JNK activation and increased energy expenditure contribute to the metabolic effects of MLK deficiency. These data confirm that the MLK pathway plays a critical role in the metabolic response to obesity.

Modeling phenotypic metabolic adaptations of Mycobacterium tuberculosis H37Rv under hypoxia.

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Xin Fang

Full Text Available The ability to adapt to different conditions is key for Mycobacterium tuberculosis, the causative agent of tuberculosis (TB, to successfully infect human hosts. Adaptations allow the organism to evade the host immune responses during acute infections and persist for an extended period of time during the latent infectious stage. In latently infected individuals, estimated to include one-third of the human population, the organism exists in a variety of metabolic states, which impedes the development of a simple strategy for controlling or eradicating this disease. Direct knowledge of the metabolic states of M. tuberculosis in patients would aid in the management of the disease as well as in forming the basis for developing new drugs and designing more efficacious drug cocktails. Here, we propose an in silico approach to create state-specific models based on readily available gene expression data. The coupling of differential gene expression data with a metabolic network model allowed us to characterize the metabolic adaptations of M. tuberculosis H37Rv to hypoxia. Given the microarray data for the alterations in gene expression, our model predicted reduced oxygen uptake, ATP production changes, and a global change from an oxidative to a reductive tricarboxylic acid (TCA program. Alterations in the biomass composition indicated an increase in the cell wall metabolites required for cell-wall growth, as well as heightened accumulation of triacylglycerol in preparation for a low-nutrient, low metabolic activity life style. In contrast, the gene expression program in the deletion mutant of dosR, which encodes the immediate hypoxic response regulator, failed to adapt to low-oxygen stress. Our predictions were compatible with recent experimental observations of M. tuberculosis activity under hypoxic and anaerobic conditions. Importantly, alterations in the flow and accumulation of a particular metabolite were not necessarily directly linked to

Metabolic Adaptation to Muscle Ischemia

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Cabrera, Marco E.; Coon, Jennifer E.; Kalhan, Satish C.; Radhakrishnan, Krishnan; Saidel, Gerald M.; Stanley, William C.

2000-01-01

Although all tissues in the body can adapt to varying physiological/pathological conditions, muscle is the most adaptable. To understand the significance of cellular events and their role in controlling metabolic adaptations in complex physiological systems, it is necessary to link cellular and system levels by means of mechanistic computational models. The main objective of this work is to improve understanding of the regulation of energy metabolism during skeletal/cardiac muscle ischemia by combining in vivo experiments and quantitative models of metabolism. Our main focus is to investigate factors affecting lactate metabolism (e.g., NADH/NAD) and the inter-regulation between carbohydrate and fatty acid metabolism during a reduction in regional blood flow. A mechanistic mathematical model of energy metabolism has been developed to link cellular metabolic processes and their control mechanisms to tissue (skeletal muscle) and organ (heart) physiological responses. We applied this model to simulate the relationship between tissue oxygenation, redox state, and lactate metabolism in skeletal muscle. The model was validated using human data from published occlusion studies. Currently, we are investigating the difference in the responses to sudden vs. gradual onset ischemia in swine by combining in vivo experimental studies with computational models of myocardial energy metabolism during normal and ischemic conditions.

Deciphering hepatocellular responses to metabolic and oncogenic stress

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Kathrina L. Marcelo

2015-08-01

Full Text Available Each cell type responds uniquely to stress and fractionally contributes to global and tissue-specific stress responses. Hepatocytes, liver macrophages (MΦ, and sinusoidal endothelial cells (SEC play functionally important and interdependent roles in adaptive processes such as obesity and tumor growth. Although these cell types demonstrate significant phenotypic and functional heterogeneity, their distinctions enabling disease-specific responses remain understudied. We developed a strategy for the simultaneous isolation and quantification of these liver cell types based on antigenic cell surface marker expression. To demonstrate the utility and applicability of this technique, we quantified liver cell-specific responses to high-fat diet (HFD or diethylnitrosamine (DEN, a liver-specific carcinogen, and found that while there was only a marginal increase in hepatocyte number, MΦ and SEC populations were quantitatively increased. Global gene expression profiling of hepatocytes, MΦ and SEC identified characteristic gene signatures that define each cell type in their distinct physiological or pathological states. Integration of hepatic gene signatures with available human obesity and liver cancer microarray data provides further insight into the cell-specific responses to metabolic or oncogenic stress. Our data reveal unique gene expression patterns that serve as molecular “fingerprints” for the cell-centric responses to pathologic stimuli in the distinct microenvironment of the liver. The technical advance highlighted in this study provides an essential resource for assessing hepatic cell-specific contributions to metabolic and oncogenic stress, information that could unveil previously unappreciated molecular mechanisms for the cellular crosstalk that underlies the continuum from metabolic disruption to obesity and ultimately hepatic cancer.

Metabolic responses in Candida tropicalis to complex inhibitors during xylitol bioconversion.

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Wang, Shizeng; Li, Hao; Fan, Xiaoguang; Zhang, Jingkun; Tang, Pingwah; Yuan, Qipeng

2015-09-01

During xylitol fermentation, Candida tropicalis is often inhibited by inhibitors in hemicellulose hydrolysate. The mechanisms involved in the metabolic responses to inhibitor stress and the resistances to inhibitors are still not clear. To understand the inhibition mechanisms and the metabolic responses to inhibitors, a GC/MS-based metabolomics approach was performed on C. tropicalis treated with and without complex inhibitors (CI, including furfural, phenol and acetic acid). Partial least squares discriminant analysis was used to determine the metabolic variability between CI-treated groups and control groups, and 25 metabolites were identified as possible entities responsible for the discrimination caused by inhibitors. We found that xylose uptake rate and xylitol oxidation rate were promoted by CI treatment. Metabolomics analysis showed that the flux from xylulose to pentose phosphate pathway increased, and tricarboxylic acid cycle was disturbed by CI. Moreover, the changes in levels of 1,3-propanediol, trehalose, saturated fatty acids and amino acids showed different mechanisms involved in metabolic responses to inhibitor stress. The increase of 1,3-propanediol was considered to be correlated with regulating redox balance and osmoregulation. The increase of trehalose might play a role in protein stabilization and cellular membranes protection. Saturated fatty acids could cause the decrease of membrane fluidity and make the plasma membrane rigid to maintain the integrity of plasma membrane. The deeper understanding of the inhibition mechanisms and the metabolic responses to inhibitors will provide us with more information on the metabolism regulation during xylitol bioconversion and the construction of industrial strains with inhibitor tolerance for better utilization of bioresource. Copyright © 2015 Elsevier Inc. All rights reserved.

Metabolic Communication between Astrocytes and Neurons via Bicarbonate-Responsive Soluble Adenylyl Cyclase

OpenAIRE

Choi, Hyun B.; Gordon, Grant R.J.; Zhou, Ning; Tai, Chao; Rungta, Ravi L.; Martinez, Jennifer; Milner, Teresa A.; Ryu, Jae K.; McLarnon, James G.; Tresguerres, Martin; Levin, Lonny R.; Buck, Jochen; MacVicar, Brian A.

2012-01-01

Astrocytes are proposed to participate in brain energy metabolism by supplying substrates to neurons from their glycogen stores and from glycolysis. However, the molecules involved in metabolic sensing and the molecular pathways responsible for metabolic coupling between different cell types in the brain are not fully understood. Here we show that a recently cloned bicarbonate (HCO3−) sensor, soluble adenylyl cyclase (sAC), is highly expressed in astrocytes and becomes activated in response t...

Global patterns in lake ecosystem responses to warming based on the temperature dependence of metabolism.

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Kraemer, Benjamin M; Chandra, Sudeep; Dell, Anthony I; Dix, Margaret; Kuusisto, Esko; Livingstone, David M; Schladow, S Geoffrey; Silow, Eugene; Sitoki, Lewis M; Tamatamah, Rashid; McIntyre, Peter B

2017-05-01

Climate warming is expected to have large effects on ecosystems in part due to the temperature dependence of metabolism. The responses of metabolic rates to climate warming may be greatest in the tropics and at low elevations because mean temperatures are warmer there and metabolic rates respond exponentially to temperature (with exponents >1). However, if warming rates are sufficiently fast in higher latitude/elevation lakes, metabolic rate responses to warming may still be greater there even though metabolic rates respond exponentially to temperature. Thus, a wide range of global patterns in the magnitude of metabolic rate responses to warming could emerge depending on global patterns of temperature and warming rates. Here we use the Boltzmann-Arrhenius equation, published estimates of activation energy, and time series of temperature from 271 lakes to estimate long-term (1970-2010) changes in 64 metabolic processes in lakes. The estimated responses of metabolic processes to warming were usually greatest in tropical/low-elevation lakes even though surface temperatures in higher latitude/elevation lakes are warming faster. However, when the thermal sensitivity of a metabolic process is especially weak, higher latitude/elevation lakes had larger responses to warming in parallel with warming rates. Our results show that the sensitivity of a given response to temperature (as described by its activation energy) provides a simple heuristic for predicting whether tropical/low-elevation lakes will have larger or smaller metabolic responses to warming than higher latitude/elevation lakes. Overall, we conclude that the direct metabolic consequences of lake warming are likely to be felt most strongly at low latitudes and low elevations where metabolism-linked ecosystem services may be most affected. © 2016 John Wiley & Sons Ltd.

Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

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Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

2013-03-28

Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus. Copyright © 2013 Elsevier Inc. All rights reserved.

Irisin in response to exercise in humans with and without metabolic syndrome.

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Huh, Joo Young; Siopi, Aikaterina; Mougios, Vassilis; Park, Kyung Hee; Mantzoros, Christos S

2015-03-01

Irisin is a recently identified exercise-induced myokine. However, the circulating levels of irisin in response to different types of exercise in subjects with metabolic syndrome are unknown. This study aimed to study the levels of irisin in healthy males and subjects with metabolic syndrome at baseline and in response to exercise. Each individual completed high-intensity interval exercise (HIIE), continuous moderate-intensity exercise (CME), and resistance exercise (RE) sessions in a random, crossover design. Percentage change in circulating irisin levels was examined. Two different irisin assays were used to compare the results of the RE study. Circulating irisin increased immediately after HIIE, CME, and RE and declined 1 hour later. The increase was greater in response to resistance compared with either high-intensity intermittent exercise or CME. Change in irisin in response to exercise did not differ between individuals with and without metabolic syndrome. Exercise is able to increase circulating irisin levels in individuals with the metabolic syndrome as well as healthy individuals. Whether this increase may contribute to the beneficial effects of exercise on patients with the metabolic syndrome remains to be studied further.

Allometric scaling and cell ratios in multi-organ in vitro models of human metabolism

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Nadia eUcciferri

2014-12-01

Full Text Available Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step towards building an integrated picture of systemic metabolism and signalling in physiological or pathological conditions. However the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here we analyse the physiologic relationship between cells, cell metabolism and exchange in the human body using allometric rules, downscaling them to an organ-on-a plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (Cell Number Scaling Model, CNSM, and Metabolic and Surface Scaling model, MSSM are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions which can be extrapolated to the in vivo

Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism

International Nuclear Information System (INIS)

Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti

2014-01-01

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism

Energy Technology Data Exchange (ETDEWEB)

Ucciferri, Nadia [CNR Institute of Clinical Physiology, Pisa (Italy); Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa (Italy); Sbrana, Tommaso [Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa (Italy); Ahluwalia, Arti, E-mail: arti.ahluwalia@unipi.it [CNR Institute of Clinical Physiology, Pisa (Italy); Interdepartmental Research Center “E. Piaggio”, University of Pisa, Pisa (Italy)

2014-12-17

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

Allometric Scaling and Cell Ratios in Multi-Organ in vitro Models of Human Metabolism.

Science.gov (United States)

Ucciferri, Nadia; Sbrana, Tommaso; Ahluwalia, Arti

2014-01-01

Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell-cell or cell-tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.

Model-driven discovery of underground metabolic functions in Escherichia coli

DEFF Research Database (Denmark)

Guzmán, Gabriela I.; Utrilla, José; Nurk, Sergey

2015-01-01

-scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence......E, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations....

Sleep fragmentation alters brain energy metabolism without modifying hippocampal electrophysiological response to novelty exposure.

Science.gov (United States)

Baud, Maxime O; Parafita, Julia; Nguyen, Audrey; Magistretti, Pierre J; Petit, Jean-Marie

2016-10-01

Sleep is viewed as a fundamental restorative function of the brain, but its specific role in neural energy budget remains poorly understood. Sleep deprivation dampens brain energy metabolism and impairs cognitive functions. Intriguingly, sleep fragmentation, despite normal total sleep duration, has a similar cognitive impact, and in this paper we ask the question of whether it may also impair brain energy metabolism. To this end, we used a recently developed mouse model of 2 weeks of sleep fragmentation and measured 2-deoxy-glucose uptake and glycogen, glucose and lactate concentration in different brain regions. In order to homogenize mice behaviour during metabolic measurements, we exposed them to a novel environment for 1 h. Using an intra-hippocampal electrode, we first showed that hippocampal electroencephalograph (EEG) response to exploration was unaltered by 1 or 14 days of sleep fragmentation. However, after 14 days, sleep fragmented mice exhibited a lower uptake of 2-deoxy-glucose in cortex and hippocampus and lower cortical lactate levels than control mice. Our results suggest that long-term sleep fragmentation impaired brain metabolism to a similar extent as total sleep deprivation without affecting the neuronal responsiveness of hippocampus to a novel environment. © 2016 European Sleep Research Society.

Sleep fragmentation alters brain energy metabolism without modifying hippocampal electrophysiological response to novelty exposure

KAUST Repository

Baud, Maxime O.

2016-05-03

© 2016 European Sleep Research Society. Sleep is viewed as a fundamental restorative function of the brain, but its specific role in neural energy budget remains poorly understood. Sleep deprivation dampens brain energy metabolism and impairs cognitive functions. Intriguingly, sleep fragmentation, despite normal total sleep duration, has a similar cognitive impact, and in this paper we ask the question of whether it may also impair brain energy metabolism. To this end, we used a recently developed mouse model of 2 weeks of sleep fragmentation and measured 2-deoxy-glucose uptake and glycogen, glucose and lactate concentration in different brain regions. In order to homogenize mice behaviour during metabolic measurements, we exposed them to a novel environment for 1 h. Using an intra-hippocampal electrode, we first showed that hippocampal electroencephalograph (EEG) response to exploration was unaltered by 1 or 14 days of sleep fragmentation. However, after 14 days, sleep fragmented mice exhibited a lower uptake of 2-deoxy-glucose in cortex and hippocampus and lower cortical lactate levels than control mice. Our results suggest that long-term sleep fragmentation impaired brain metabolism to a similar extent as total sleep deprivation without affecting the neuronal responsiveness of hippocampus to a novel environment.

Reconstruction of genome-scale human metabolic models using omics data

DEFF Research Database (Denmark)

Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup

2015-01-01

used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....

Metabolic response to Klebsiella pneumoniae infection in an experimental rat model.

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Fangcong Dong

Full Text Available Bacteremia, the presence of viable bacteria in the blood stream, is often associated with several clinical conditions. Bacteremia can lead to multiple organ failure if managed incorrectly, which makes providing suitable nutritional support vital for reducing bacteremia-associated mortality. In order to provide such information, we investigated the metabolic consequences of a Klebsiella pneumoniae (K. pneumoniae infection in vivo by employing a combination of (1H nuclear magnetic resonance spectroscopy and multivariate data analysis. K. pneumoniae was intravenously infused in rats; urine and plasma samples were collected at different time intervals. We found that K. pneumoniae-induced bacteremia stimulated glycolysis and the tricarboxylic acid cycle and also promoted oxidation of fatty acids and creatine phosphate to facilitate the energy-demanding host response. In addition, K. pneumoniae bacteremia also induced anti-endotoxin, anti-inflammatory and anti-oxidization responses in the host. Furthermore, bacteremia could cause a disturbance in the gut microbiotal functions as suggested by alterations in a range of amines and bacteria-host co-metabolites. Our results suggest that supplementation with glucose and a high-fat and choline-rich diet could ameliorate the burdens associated with bacteremia. Our research provides underlying pathological processes of bacteremia and a better understanding of the clinical and biochemical manifestations of bacteremia.

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.

HEPATOKIN1 is a biochemistry-based model of liver metabolism for applications in medicine and pharmacology.

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Berndt, Nikolaus; Bulik, Sascha; Wallach, Iwona; Wünsch, Tilo; König, Matthias; Stockmann, Martin; Meierhofer, David; Holzhütter, Hermann-Georg

2018-06-19

The epidemic increase of non-alcoholic fatty liver diseases (NAFLD) requires a deeper understanding of the regulatory circuits controlling the response of liver metabolism to nutritional challenges, medical drugs, and genetic enzyme variants. As in vivo studies of human liver metabolism are encumbered with serious ethical and technical issues, we developed a comprehensive biochemistry-based kinetic model of the central liver metabolism including the regulation of enzyme activities by their reactants, allosteric effectors, and hormone-dependent phosphorylation. The utility of the model for basic research and applications in medicine and pharmacology is illustrated by simulating diurnal variations of the metabolic state of the liver at various perturbations caused by nutritional challenges (alcohol), drugs (valproate), and inherited enzyme disorders (galactosemia). Using proteomics data to scale maximal enzyme activities, the model is used to highlight differences in the metabolic functions of normal hepatocytes and malignant liver cells (adenoma and hepatocellular carcinoma).

Regulation of longevity by FGF21: Interaction between energy metabolism and stress responses.

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Salminen, Antero; Kaarniranta, Kai; Kauppinen, Anu

2017-08-01

Fibroblast growth factor 21 (FGF21) is a hormone-like member of FGF family which controls metabolic multiorgan crosstalk enhancing energy expenditure through glucose and lipid metabolism. In addition, FGF21 acts as a stress hormone induced by endoplasmic reticulum stress and dysfunctions of mitochondria and autophagy in several tissues. FGF21 also controls stress responses and metabolism by modulating the functions of somatotropic axis and hypothalamic-pituitary-adrenal (HPA) pathway. FGF21 is a potent longevity factor coordinating interactions between energy metabolism and stress responses. Recent studies have revealed that FGF21 treatment can alleviate many age-related metabolic disorders, e.g. atherosclerosis, obesity, type 2 diabetes, and some cardiovascular diseases. In addition, transgenic mice overexpressing FGF21 have an extended lifespan. However, chronic metabolic and stress-related disorders involving inflammatory responses can provoke FGF21 resistance and thus disturb healthy aging process. First, we will describe the role of FGF21 in interorgan energy metabolism and explain how its functions as a stress hormone can improve healthspan. Next, we will examine both the induction of FGF21 expression via the integrated stress response and the molecular mechanism through which FGF21 enhances healthy aging. Finally, we postulate that FGF21 resistance, similarly to insulin resistance, jeopardizes human healthspan and accelerates the aging process. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate and vegetation in a semi-arid savanna: Development of a climate–vegetation response model linking plant metabolic performance to climate and the effects on forage availability for large herbivores

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Armin H. Seydack

2012-02-01

Developing the climate–vegetation response model involved three main components, namely (1 defining indicators of forage availability to herbivores (nitrogen productivity, nitrogen quality, carbon-nutrient quality, (2 identifying herbivore species guilds of similar nutritional requirements with respect to these indicators [bulk feeders with tolerance to fibrous herbage (buffalo, waterbuck, bulk feeders with preference for high nitrogen quality forage (short grass preference grazers: blue wildebeest and zebra and selective feeders where dietary items of relatively high carbon-nutrient quality represented key forage resources (selective grazers: sable antelope, roan antelope, tsessebe, eland] and (3 developing a process model where the expected effects of plant metabolic responses to climate on key forage resources were made explicit. According to the climate–vegetation response model both shorter-term transient temperature acclimation pulses and longer-term shifts in plant metabolic functionality settings were predicted to have occurred in response to temperature trends over the past century. These temperature acclimation responses were expected to have resulted in transient pulses of increased forage availability (increased nitrogen- and carbon-nutrient quality, as well as the progressive long-term decline of the carbon-nutrient quality of forage. Conservation implications: The climate–vegetation response model represents a research framework for further studies contributing towards the enhanced understanding of landscape-scale functioning of savanna systems with reference to the interplay between climate, vegetation and herbivore population dynamics. Gains in such understanding can support sound conservation management.

Chronic myeloid leukemia patients sensitive and resistant to imatinib treatment show different metabolic responses.

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Jiye A

Full Text Available The BCR-ABL tyrosine kinase inhibitor imatinib is highly effective for chronic myeloid leukemia (CML. However, some patients gradually develop resistance to imatinib, resulting in therapeutic failure. Metabonomic and genomic profiling of patients' responses to drug interventions can provide novel information about the in vivo metabolism of low-molecular-weight compounds and extend our insight into the mechanism of drug resistance. Based on a multi-platform of high-throughput metabonomics, SNP array analysis, karyotype and mutation, the metabolic phenotypes and genomic polymorphisms of CML patients and their diverse responses to imatinib were characterized. The untreated CML patients (UCML showed different metabolic patterns from those of healthy controls, and the discriminatory metabolites suggested the perturbed metabolism of the urea cycle, tricarboxylic acid cycle, lipid metabolism, and amino acid turnover in UCML. After imatinib treatment, patients sensitive to imatinib (SCML and patients resistant to imatinib (RCML had similar metabolic phenotypes to those of healthy controls and UCML, respectively. SCML showed a significant metabolic response to imatinib, with marked restoration of the perturbed metabolism. Most of the metabolites characterizing CML were adjusted to normal levels, including the intermediates of the urea cycle and tricarboxylic acid cycle (TCA. In contrast, neither cytogenetic nor metabonomic analysis indicated any positive response to imatinib in RCML. We report for the first time the associated genetic and metabonomic responses of CML patients to imatinib and show that the perturbed in vivo metabolism of UCML is independent of imatinib treatment in resistant patients. Thus, metabonomics can potentially characterize patients' sensitivity or resistance to drug intervention.

Genetic dissection in a mouse model reveals interactions between carotenoids and lipid metabolism[S

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Palczewski, Grzegorz; Widjaja-Adhi, M. Airanthi K.; Amengual, Jaume; Golczak, Marcin; von Lintig, Johannes

2016-01-01

Carotenoids affect a rich variety of physiological functions in nature and are beneficial for human health. However, knowledge about their biological action and the consequences of their dietary accumulation in mammals is limited. Progress in this research field is limited by the expeditious metabolism of carotenoids in rodents and the confounding production of apocarotenoid signaling molecules. Herein, we established a mouse model lacking the enzymes responsible for carotenoid catabolism and apocarotenoid production, fed on either a β-carotene- or a zeaxanthin-enriched diet. Applying a genome wide microarray analysis, we assessed the effects of the parent carotenoids on the liver transcriptome. Our analysis documented changes in pathways for liver lipid metabolism and mitochondrial respiration. We biochemically defined these effects, and observed that β-carotene accumulation resulted in an elevation of liver triglycerides and liver cholesterol, while zeaxanthin accumulation increased serum cholesterol levels. We further show that carotenoids were predominantly transported within HDL particles in the serum of mice. Finally, we provide evidence that carotenoid accumulation influenced whole-body respiration and energy expenditure. Thus, we observed that accumulation of parent carotenoids interacts with lipid metabolism and that structurally related carotenoids display distinct biological functions in mammals. PMID:27389691

Genome-scale modeling for metabolic engineering.

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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.

[Response of arbuscular mycorrhizal fungal lipid metabolism to symbiotic signals in mycorrhiza].

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Tian, Lei; Li, Yuanjing; Tian, Chunjie

2016-01-04

Arbuscular mycorrhizal (AM) fungi play an important role in energy flow and nutrient cycling, besides their wide distribution in the cosystem. With a long co-evolution, AM fungi and host plant have formed a symbiotic relationship, and fungal lipid metabolism may be the key point to find the symbiotic mechanism in arbusculart mycorrhiza. Here, we reviewed the most recent progress on the interaction between AM fungal lipid metabolism and symbiotic signaling networks, especially the response of AM fungal lipid metabolism to symbiotic signals. Furthermore, we discussed the response of AM fungal lipid storage and release to symbiotic or non-symbiotic status, and the correlation between fungal lipid metabolism and nutrient transfer in mycorrhiza. In addition, we explored the feedback of the lipolysis process to molecular signals during the establishment of symbiosis, and the corresponding material conversion and energy metabolism besides the crosstalk of fungal lipid metabolism and signaling networks. This review will help understand symbiotic mechanism of arbuscular mycorrhiza fungi and further application in ecosystem.

Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles

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Gengjie Jia

2012-11-01

Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.

An accurate description of Aspergillus niger organic acid batch fermentation through dynamic metabolic modelling.

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Upton, Daniel J; McQueen-Mason, Simon J; Wood, A Jamie

2017-01-01

Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. Traditional strain development of this organism was achieved through random mutagenesis, but advances in genomics have enabled the development of genome-scale metabolic modelling that can be used to make predictive improvements in fermentation performance. The parent citric acid-producing strain of A. niger , ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. Here, we report the development of a novel double optimisation modelling approach that generates time-dependent citric acid fermentation using dynamic flux balance analysis. The output from this model shows a good match with empirical fermentation data. Our studies suggest that citric acid production commences upon a switch to phosphate-limited growth and this is validated by fitting to empirical data, which confirms the diauxic growth behaviour and the role of phosphate storage as polyphosphate. The calibrated time-course model reflects observed metabolic events and generates reliable in silico data for industrially relevant fermentative time series, and for the behaviour of engineered strains suggesting that our approach can be used as a powerful tool for predictive metabolic engineering.

Metabolic Response to Four Weeks of Muscular Endurance Resistance Training

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John W. Farrell III

2017-10-01

Full Text Available Background: Previous investigations have shown that muscular endurance resistance training (MERT is conducive in improving the onset of blood lactate accumulation (OBLA. However, the metabolic response and time course for adaption is still unclear. Objective: The aims of the current study were to evaluate and track the metabolic response to an individual session of MERT as well as to assess performance adaptations of supplementing an aerobic exercise training program with four weeks of MERT. Methods: Seventeen aerobically active men were randomly assigned to either the experimental (EX or control group (CON, 9 EX and 8 CON. Baseline measures included a graded exercise test (GXT and 1-repetition maximum (1RM testing for leg press (LP, leg curl (LC, and leg extension (LE. CON continued their regular aerobic activity while the EX supplemented their regular aerobic exercise with 4 weeks of MERT. Results: No significant group differences were observed for all pre-training variables. Following four weeks of training no significant differences in cardiorespiratory or metabolic variables were observed for either group. However, significant improvements in LC and LE 1-RM were observed in EX compared to CON. Substantial accumulations in blood lactate were observed following each MERT session. Conclusion: Four weeks of MERT did not improve cardiorespiratory or metabolic variables, but did significantly improve LC and LE. MERT was also observed to induce a blood lactate response similar to that of HIIT. These findings suggest greater than four weeks is need to see metabolic adaptations conducive for improved aerobic performance using MERT.

Metabolic communication between astrocytes and neurons via bicarbonate-responsive soluble adenylyl cyclase.

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Choi, Hyun B; Gordon, Grant R J; Zhou, Ning; Tai, Chao; Rungta, Ravi L; Martinez, Jennifer; Milner, Teresa A; Ryu, Jae K; McLarnon, James G; Tresguerres, Martin; Levin, Lonny R; Buck, Jochen; MacVicar, Brian A

2012-09-20

Astrocytes are proposed to participate in brain energy metabolism by supplying substrates to neurons from their glycogen stores and from glycolysis. However, the molecules involved in metabolic sensing and the molecular pathways responsible for metabolic coupling between different cell types in the brain are not fully understood. Here we show that a recently cloned bicarbonate (HCO₃⁻) sensor, soluble adenylyl cyclase (sAC), is highly expressed in astrocytes and becomes activated in response to HCO₃⁻ entry via the electrogenic NaHCO₃ cotransporter (NBC). Activated sAC increases intracellular cAMP levels, causing glycogen breakdown, enhanced glycolysis, and the release of lactate into the extracellular space, which is subsequently taken up by neurons for use as an energy substrate. This process is recruited over a broad physiological range of [K⁺](ext) and also during aglycemic episodes, helping to maintain synaptic function. These data reveal a molecular pathway in astrocytes that is responsible for brain metabolic coupling to neurons. Copyright © 2012 Elsevier Inc. All rights reserved.

Metabolic Response of Maize Roots to Hyperosmotic Shock 1

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Spickett, Corinne M.; Smirnoff, Nicholas; Ratcliffe, R. George

1992-01-01

31P nuclear magnetic resonance spectroscopy was used to study the response of maize (Zea mays L.) root tips to hyperosmotic shock. The aim was to identify changes in metabolism that might be relevant to the perception of low soil water potential and the subsequent adaptation of the tissue to these conditions. Osmotic shock was found to result in two different types of response: changes in metabolite levels and changes in intracellular pH. The most notable metabolic changes, which were produced by all the osmotica tested, were increases in phosphocholine and vacuolar phosphate, with a transient increase in cytoplasmic phosphate. It was observed that treatment with ionic and nonionic osmotica produced different effects on the concentrations of bioenergetically important metabolites. It is postulated that these changes are the result of hydrolysis of phosphatidylcholine and other membrane phospholipids, due to differential activation of specific membrane-associated phospholipases by changes in the surface tension of the plasmalemma. These events may be important in the detection of osmotic shock and subsequent acclimatization. A cytoplasmic alkalinization was also observed during hyperosmotic treatment, and this response, which is consistent with the activation of the plasmalemma H+-ATPase, together with the other metabolic changes, may suggest the existence of a complex and integrated mechanism of osmoregulation. PMID:16669012

The metabolic response of Candida albicans to farnesol under hyphae-inducing conditions.

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Han, Ting-Li; Cannon, Richard D; Villas-Bôas, Silas G

2012-12-01

Farnesol is a quorum-sensing molecule (QSM) produced, and sensed, by the polymorphic fungus, Candida albicans. This cell-to-cell communication molecule is known to suppress the hyphal formation of C. albicans at high cell density. Despite many studies investigating the signalling mechanisms by which QSMs influence the morphogenesis of C. albicans, the downstream metabolic effect of these signalling pathways in response to farnesol-mediated morphogenesis remains obscure. Here, we have used metabolomics to investigate the metabolic response of C. albicans upon exposure to farnesol under hyphae-inducing conditions. We have found a general up-regulation of central carbon metabolic pathways when hyphal formation was suppressed by farnesol evidenced by a considerably larger number of central carbon metabolic intermediates detected under this condition at an overall lower intracellular level. By combining the metabolic profiles from farnesol-exposed cells with previous metabolomics data for C. albicans undergoing morphogenesis, we have identified several metabolic pathways that are likely to be associated with the morphogenetic process of C. albicans, as well as metabolic pathways such as those involved in lipid metabolism that appeared to be specifically affected by farnesol. Therefore, our results provide important new insights into the metabolic role of farnesol in C. albicans metabolism. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Effects of sensitizers on cell respiration. 3. The effects of hypoxic cell radiosensitizers on oxidative metabolism and the radiation response of an in vitro tumour model

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Durand, R E [Wisconsin Clinical Cancer Center, Madison (USA). Dept. of Human Oncology; Biaglow, J E; Greenstock, C L

1978-06-01

Physiological factors are important when considering the effects of radiosensitizers on the radiation response of complex systems such as multi-cellular spheroids. In this system, under conditions of unlimited nutrient supply, cells are rendered hypoxic by metabolism. Thus, using the spheroid system as an in vitro model of the tumour-cell microenvironment, we have determined the relative contribution of radiosensitization and respiratory effects of a number of electron-affinic sensitizers having potential clinical use. These studies are indicative of physiological responses at the cellular level, and suggest optimal drug administration schemes for obtaining maximal radiation response in vivo with hypoxic cell sensitizers.

Discriminating response groups in metabolic and regulatory pathway networks.

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Van Hemert, John L; Dickerson, Julie A

2012-04-01

Analysis of omics experiments generates lists of entities (genes, metabolites, etc.) selected based on specific behavior, such as changes in response to stress or other signals. Functional interpretation of these lists often uses category enrichment tests using functional annotations like Gene Ontology terms and pathway membership. This approach does not consider the connected structure of biochemical pathways or the causal directionality of events. The Omics Response Group (ORG) method, described in this work, interprets omics lists in the context of metabolic pathway and regulatory networks using a statistical model for flow within the networks. Statistical results for all response groups are visualized in a novel Pathway Flow plot. The statistical tests are based on the Erlang distribution model under the assumption of independent and identically Exponential-distributed random walk flows through pathways. As a proof of concept, we applied our method to an Escherichia coli transcriptomics dataset where we confirmed common knowledge of the E.coli transcriptional response to Lipid A deprivation. The main response is related to osmotic stress, and we were also able to detect novel responses that are supported by the literature. We also applied our method to an Arabidopsis thaliana expression dataset from an abscisic acid study. In both cases, conventional pathway enrichment tests detected nothing, while our approach discovered biological processes beyond the original studies. We created a prototype for an interactive ORG web tool at http://ecoserver.vrac.iastate.edu/pathwayflow (source code is available from https://subversion.vrac.iastate.edu/Subversion/jlv/public/jlv/pathwayflow). The prototype is described along with additional figures and tables in Supplementary Material. julied@iastate.edu Supplementary data are available at Bioinformatics online.

Magnetic resonance metabolic profiling of breast cancer tissue obtained with core needle biopsy for predicting pathologic response to neoadjuvant chemotherapy.

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Ji Soo Choi

Full Text Available The purpose of this study was to determine whether metabolic profiling of core needle biopsy (CNB samples using high-resolution magic angle spinning (HR-MAS magnetic resonance spectroscopy (MRS could be used for predicting pathologic response to neoadjuvant chemotherapy (NAC in patients with locally advanced breast cancer. After institutional review board approval and informed consent were obtained, CNB tissue samples were collected from 37 malignant lesions in 37 patients before NAC treatment. The metabolic profiling of CNB samples were performed by HR-MAS MRS. Metabolic profiles were compared according to pathologic response to NAC using the Mann-Whitney test. Multivariate analysis was performed with orthogonal projections to latent structure-discriminant analysis (OPLS-DA. Various metabolites including choline-containing compounds were identified and quantified by HR-MAS MRS in all 37 breast cancer tissue samples obtained by CNB. In univariate analysis, the metabolite concentrations and metabolic ratios of CNB samples obtained with HR-MAS MRS were not significantly different between different pathologic response groups. However, there was a trend of lower levels of phosphocholine/creatine ratio and choline-containing metabolite concentrations in the pathologic complete response group compared to the non-pathologic complete response group. In multivariate analysis, the OPLS-DA models built with HR-MAS MR metabolic profiles showed visible discrimination between the pathologic response groups. This study showed OPLS-DA multivariate analysis using metabolic profiles of pretreatment CNB samples assessed by HR- MAS MRS may be used to predict pathologic response before NAC, although we did not identify the metabolite showing statistical significance in univariate analysis. Therefore, our preliminary results raise the necessity of further study on HR-MAS MR metabolic profiling of CNB samples for a large number of cancers.

Metabolic Modeling of Common Escherichia coli Strains in Human Gut Microbiome

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Yue-Dong Gao

2014-01-01

Full Text Available The recent high-throughput sequencing has enabled the composition of Escherichia coli strains in the human microbial community to be profiled en masse. However, there are two challenges to address: (1 exploring the genetic differences between E. coli strains in human gut and (2 dynamic responses of E. coli to diverse stress conditions. As a result, we investigated the E. coli strains in human gut microbiome using deep sequencing data and reconstructed genome-wide metabolic networks for the three most common E. coli strains, including E. coli HS, UTI89, and CFT073. The metabolic models show obvious strain-specific characteristics, both in network contents and in behaviors. We predicted optimal biomass production for three models on four different carbon sources (acetate, ethanol, glucose, and succinate and found that these stress-associated genes were involved in host-microbial interactions and increased in human obesity. Besides, it shows that the growth rates are similar among the models, but the flux distributions are different, even in E. coli core reactions. The correlations between human diabetes-associated metabolic reactions in the E. coli models were also predicted. The study provides a systems perspective on E. coli strains in human gut microbiome and will be helpful in integrating diverse data sources in the following study.

Rodent Models for Metabolic Syndrome Research

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Sunil K. Panchal

2011-01-01

Full Text Available Rodents are widely used to mimic human diseases to improve understanding of the causes and progression of disease symptoms and to test potential therapeutic interventions. Chronic diseases such as obesity, diabetes and hypertension, together known as the metabolic syndrome, are causing increasing morbidity and mortality. To control these diseases, research in rodent models that closely mimic the changes in humans is essential. This review will examine the adequacy of the many rodent models of metabolic syndrome to mimic the causes and progression of the disease in humans. The primary criterion will be whether a rodent model initiates all of the signs, especially obesity, diabetes, hypertension and dysfunction of the heart, blood vessels, liver and kidney, primarily by diet since these are the diet-induced signs in humans with metabolic syndrome. We conclude that the model that comes closest to fulfilling this criterion is the high carbohydrate, high fat-fed male rodent.

LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models

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Winslow, Luke; Zwart, Jacob A.; Batt, Ryan D.; Dugan, Hilary; Woolway, R. Iestyn; Corman, Jessica; Hanson, Paul C.; Read, Jordan S.

2016-01-01

Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.

Metabolic response to feeding in Tupinambis merianae: circadian rhythm and a possible respiratory constraint.

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Klein, Wilfried; Perry, Steven F; Abe, Augusto S; Andrade, Denis V

2006-01-01

The diurnal tegu lizard Tupinambis merianae exhibits a marked circadian variation in metabolism that is characterized by the significant increase in metabolism during part of the day. These increases in metabolic rate, found in the fasting animal, are absent during the first 2 d after meal ingestion but reappear subsequently, and the daily increase in metabolic rate is added to the increase in metabolic rate caused by digestion. During the first 2 d after feeding, priority is given to digestion, while on the third and following days, the metabolic demands are clearly added to each other. This response seems to be a regulated response of the animal, which becomes less active after food ingestion, rather than an inability of the respiratory system to support simultaneous demands at the beginning of digestion. The body cavity of Tupinambis is divided into two compartments by a posthepatic septum (PHS). Animals that had their PHS surgically removed showed no significant alteration in the postprandial metabolic response compared to tegus with intact PHS. The maximal metabolic increment during digestion, the relative cost of meal digestion, and the duration of the process were virtually unaffected by the removal of the PHS.

Sex differences in metabolic and adipose tissue responses to juvenile-onset obesity in sheep.

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Bloor, Ian D; Sébert, Sylvain P; Saroha, Vivek; Gardner, David S; Keisler, Duane H; Budge, Helen; Symonds, Michael E; Mahajan, Ravi P

2013-10-01

Sex is a major factor determining adipose tissue distribution and the subsequent adverse effects of obesity-related disease including type 2 diabetes. The role of gender on juvenile obesity and the accompanying metabolic and inflammatory responses is not well established. Using an ovine model of juvenile onset obesity induced by reduced physical activity, we examined the effect of gender on metabolic, circulatory, and related inflammatory and energy-sensing profiles of the major adipose tissue depots. Despite a similar increase in fat mass with obesity between genders, males demonstrated a higher storage capacity of lipids within perirenal-abdominal adipocytes and exhibited raised insulin. In contrast, obese females became hypercortisolemic, a response that was positively correlated with central fat mass. Analysis of gene expression in perirenal-abdominal adipose tissue demonstrated the stimulation of inflammatory markers in males, but not females, with obesity. Obese females displayed increased expression of genes involved in the glucocorticoid axis and energy sensing in perirenal-abdominal, but not omental, adipose tissue, indicating a depot-specific mechanism that may be protective from the adverse effects of metabolic dysfunction and inflammation. In conclusion, young males are at a greater risk than females to the onset of comorbidities associated with juvenile-onset obesity. These sex-specific differences in cortisol and adipose tissue could explain the earlier onset of the metabolic-related diseases in males compared with females after obesity.

Structural and metabolic responses of Ceratophyllum demersum to ...

African Journals Online (AJOL)

Eutrophication in water bodies affects the growth of aquatic plants. In this study, we conducted static experiments to better understand the structural and metabolic responses of Ceratophyllum demersum under eutrophication conditions. The anatomical structure, nitrogen (N) and phosphorous (P) levels in tissue, ...

Predicting effects of structural stress in a genome-reduced model bacterial metabolism

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Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

2012-08-01

Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

Prediction of lithium-ion battery capacity with metabolic grey model

International Nuclear Information System (INIS)

Chen, Lin; Lin, Weilong; Li, Junzi; Tian, Binbin; Pan, Haihong

2016-01-01

Given the popularity of Lithium-ion batteries in EVs (electric vehicles), predicting the capacity quickly and accurately throughout a battery's full life-time is still a challenging issue for ensuring the reliability of EVs. This paper proposes an approach in predicting the varied capacity with discharge cycles based on metabolic grey theory and consider issues from two perspectives: 1) three metabolic grey models will be presented, including MGM (metabolic grey model), MREGM (metabolic Residual-error grey model), and MMREGM (metabolic Markov-residual-error grey model); 2) the universality of these models will be explored under different conditions (such as various discharge rates and temperatures). Furthermore, the research findings in this paper demonstrate the excellent performance of the prediction depending on the three models; however, the precision of the MREGM model is inferior compared to the others. Therefore, we have obtained the conclusion in which the MGM model and the MMREGM model have excellent performances in predicting the capacity under a variety of load conditions, even using few data points for modeling. Also, the universality of the metabolic grey prediction theory is verified by predicting the capacity of batteries under different discharge rates and different temperatures. - Highlights: • The metabolic mechanism is introduced in a grey system for capacity prediction. • Three metabolic grey models are presented and studied. • The universality of these models under different conditions is assessed. • A few data points are required for predicting the capacity with these models.

Unique attributes of cyanobacterial metabolism revealed by improved genome-scale metabolic modeling and essential gene analysis

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Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.

2016-01-01

The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809

Computational fluid dynamics simulation of an industrial P. chrysogenum fermentation with a coupled 9-pool metabolic model : Towards rational scale-down and design optimization

NARCIS (Netherlands)

Haringa, C.; Tang, W.; Wang, G.; Deshmukh, A.T.; van Winden, Wouter A.; Chu, Ju; van Gulik, W.M.; Heijnen, J.J.; Mudde, R.F.; Noorman, H.J.

2018-01-01

We assess the effect of substrate heterogeneity on the metabolic response of P. chrysogenum in industrial bioreactors via the coupling of a 9-pool metabolic model with Euler-Lagrange CFD simulations. In this work, we outline how this coupled hydrodynamic-metabolic modeling can be utilized in 5

The metabolic responses to aerial diffusion of essential oils.

Directory of Open Access Journals (Sweden)

Yani Wu

Full Text Available Anxiety disorders are the most prevalent psychiatric disorders and affect a great number of people worldwide. Essential oils, take effects through inhalation or topical application, are believed to enhance physical, emotional, and spiritual well-being. Although clinical studies suggest that the use of essential oils may have therapeutic potential, evidence for the efficacy of essential oils in treating medical conditions remains poor, with a particular lack of studies employing rigorous analytical methods that capture its identifiable impact on human biology. Here, we report a comprehensive gas chromatography time-of-flight mass spectrometry (GC-TOFMS based metabonomics study that reveals the aromas-induced metabolic changes and the anxiolytic effect of aromas in elevated plus maze (EPM induced anxiety model rats. The significant alteration of metabolites in the EPM group was attenuated by aromas treatment, concurrent with the behavioral improvement with significantly increased open arms time and open arms entries. Brain tissue and urinary metabonomic analysis identified a number of altered metabolites in response to aromas intervention. These metabolic changes included the increased carbohydrates and lowered levels of neurotransmitters (tryptophan, serine, glycine, aspartate, tyrosine, cysteine, phenylalanine, hypotaurine, histidine, and asparagine, amino acids, and fatty acids in the brain. Elevated aspartate, carbohydrates (sucrose, maltose, fructose, and glucose, nucleosides and organic acids such as lactate and pyruvate were also observed in the urine. The EPM induced metabolic differences observed in urine or brain tissue was significantly reduced after 10 days of aroma inhalation, as noted with the loss of statistical significance on many of the metabolites in the aroma-EPM group. This study demonstrates, for the first time, that the metabonomics approach can capture the subtle metabolic changes resulting from exposure to essential oils

Citric Acid Metabolism in Resistant Hypertension: Underlying Mechanisms and Metabolic Prediction of Treatment Response.

Science.gov (United States)

Martin-Lorenzo, Marta; Martinez, Paula J; Baldan-Martin, Montserrat; Ruiz-Hurtado, Gema; Prado, Jose Carlos; Segura, Julian; de la Cuesta, Fernando; Barderas, Maria G; Vivanco, Fernando; Ruilope, Luis Miguel; Alvarez-Llamas, Gloria

2017-11-01

Resistant hypertension (RH) affects 9% to 12% of hypertensive adults. Prolonged exposure to suboptimal blood pressure control results in end-organ damage and cardiovascular risk. Spironolactone is the most effective drug for treatment, but not all patients respond and side effects are not negligible. Little is known on the mechanisms responsible for RH. We aimed to identify metabolic alterations in urine. In addition, a potential capacity of metabolites to predict response to spironolactone was investigated. Urine was collected from 29 patients with RH and from a group of 13 subjects with pseudo-RH. For patients, samples were collected before and after spironolactone administration and were classified in responders (n=19) and nonresponders (n=10). Nuclear magnetic resonance was applied to identify altered metabolites and pathways. Metabolites were confirmed by liquid chromatography-mass spectrometry. Citric acid cycle was the pathway most significantly altered ( P citric acid cycle and deregulation of reactive oxygen species homeostasis control continue its activation after hypertension was developed. A metabolic panel showing alteration before spironolactone treatment and predicting future response of patients is shown. These molecular indicators will contribute optimizing the rate of control of RH patients with spironolactone. © 2017 American Heart Association, Inc.

A Mathematical Model of Metabolism and Regulation Provides a Systems-Level View of How Escherichia coli Responds to Oxygen

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Michael eEderer

2014-03-01

Full Text Available The efficient redesign of bacteria for biotechnological purposes, such as biofuel production, waste disposal or specific biocatalytic functions, requires a quantitative systems-level understanding of energy supply, carbon and redox metabolism. The measurement of transcript levels, metabolite concentrations and metabolic fluxes per se gives an incomplete picture. An appreciation of the interdependencies between the different measurement values is essential for systems-level understanding. Mathematical modeling has the potential to provide a coherent and quantitative description of the interplay between gene expression, metabolite concentrations and metabolic fluxes. Escherichia coli undergoes major adaptations in central metabolism when the availability of oxygen changes. Thus, an integrated description of the oxygen response provides a benchmark of our understanding of carbon, energy and redox metabolism. We present the first comprehensive model of the central metabolism of E. coli that describes steady-state metabolism at different levels of oxygen availability. Variables of the model are metabolite concentrations, gene expression levels, transcription factor activities, metabolic fluxes and biomass concentration. We analyze the model with respect to the production capabilities of central metabolism of E. coli. In particular, we predict how precursor and biomass concentration are affected by product formation.

The human hepatocyte cell lines IHH and HepaRG: models to study glucose, lipid and lipoprotein metabolism.

Science.gov (United States)

Samanez, Carolina Huaman; Caron, Sandrine; Briand, Olivier; Dehondt, Hélène; Duplan, Isabelle; Kuipers, Folkert; Hennuyer, Nathalie; Clavey, Véronique; Staels, Bart

2012-07-01

Metabolic diseases reach epidemic proportions. A better knowledge of the associated alterations in the metabolic pathways in the liver is necessary. These studies need in vitro human cell models. Several human hepatoma models are used, but the response of many metabolic pathways to physiological stimuli is often lost. Here, we characterize two human hepatocyte cell lines, IHH and HepaRG, by analysing the expression and regulation of genes involved in glucose and lipid metabolism. Our results show that the glycolysis pathway is activated by glucose and insulin in both lines. Gluconeogenesis gene expression is induced by forskolin in IHH cells and inhibited by insulin in both cell lines. The lipogenic pathway is regulated by insulin in IHH cells. Finally, both cell lines secrete apolipoprotein B-containing lipoproteins, an effect promoted by increasing glucose concentrations. These two human cell lines are thus interesting models to study the regulation of glucose and lipid metabolism.

Metabolic response of Candida albicans to phenylethyl alcohol under hyphae-inducing conditions.

Science.gov (United States)

Han, Ting-Li; Tumanov, Sergey; Cannon, Richard D; Villas-Boas, Silas G

2013-01-01

Phenylethyl alcohol was one of the first quorum sensing molecules (QSMs) identified in C. albicans. This extracellular signalling molecule inhibits the hyphal formation of C. albicans at high cell density. Little is known, however, about the underlying mechanisms by which this QSM regulates the morphological switches of C. albicans. Therefore, we have applied metabolomics and isotope labelling experiments to investigate the metabolic changes that occur in C. albicans in response to phenylethyl alcohol under defined hyphae-inducing conditions. Our results showed a global upregulation of central carbon metabolism when hyphal development was suppressed by phenylethyl alcohol. By comparing the metabolic changes in response to phenylethyl alcohol to our previous metabolomic studies, we were able to short-list 7 metabolic pathways from central carbon metabolism that appear to be associated with C. albicans morphogenesis. Furthermore, isotope-labelling data showed that phenylethyl alcohol is indeed taken up and catabolised by yeast cells. Isotope-labelled carbon atoms were found in the majority of amino acids as well as in lactate and glyoxylate. However, isotope-labelled carbon atoms from phenylethyl alcohol accumulated mainly in the pyridine ring of NAD(+)/NADH and NADP(-/)NADPH molecules, showing that these nucleotides were the main products of phenylethyl alcohol catabolism. Interestingly, two metabolic pathways where these nucleotides play an important role, nitrogen metabolism and nicotinate/nicotinamide metabolism, were also short-listed through our previous metabolomics works as metabolic pathways likely to be closely associated with C. albicans morphogenesis.

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....

Computational Modeling of Human Metabolism and Its Application to Systems Biomedicine.

Science.gov (United States)

Aurich, Maike K; Thiele, Ines

2016-01-01

Modern high-throughput techniques offer immense opportunities to investigate whole-systems behavior, such as those underlying human diseases. However, the complexity of the data presents challenges in interpretation, and new avenues are needed to address the complexity of both diseases and data. Constraint-based modeling is one formalism applied in systems biology. It relies on a genome-scale reconstruction that captures extensive biochemical knowledge regarding an organism. The human genome-scale metabolic reconstruction is increasingly used to understand normal cellular and disease states because metabolism is an important factor in many human diseases. The application of human genome-scale reconstruction ranges from mere querying of the model as a knowledge base to studies that take advantage of the model's topology and, most notably, to functional predictions based on cell- and condition-specific metabolic models built based on omics data.An increasing number and diversity of biomedical questions are being addressed using constraint-based modeling and metabolic models. One of the most successful biomedical applications to date is cancer metabolism, but constraint-based modeling also holds great potential for inborn errors of metabolism or obesity. In addition, it offers great prospects for individualized approaches to diagnostics and the design of disease prevention and intervention strategies. Metabolic models support this endeavor by providing easy access to complex high-throughput datasets. Personalized metabolic models have been introduced. Finally, constraint-based modeling can be used to model whole-body metabolism, which will enable the elucidation of metabolic interactions between organs and disturbances of these interactions as either causes or consequence of metabolic diseases. This chapter introduces constraint-based modeling and describes some of its contributions to systems biomedicine.

Similar metabolic responses in pigs and humans to breads with different contents and compositions of dietary fibers: a metabolomics study

DEFF Research Database (Denmark)

Nielsen, Kirstine Lykke; Hartvigsen, Merete; Hedemann, Mette Skou

2014-01-01

Background: In nutritional studies, pigs are often used as models for humans because of nutritional and physiologic similarities. However, evidence supporting similar metabolic responses to nutritional interventions is lacking. Objective: The objective was to establish whether pigs and humans...... respond similarly to a nutritional intervention. Using metabolomics, we compared the acute metabolic response to 4 test breads between conventional pigs (growing) and adult human subjects (with the metabolic syndrome). Design: Six catheterized pigs and 15 human subjects were tested in a randomized...... different basal metabolome concentrations in the plasma of pigs and humans. Humans had higher contents of phosphatidylcholines, oleic acid, and carnitine in plasma, possibly reflecting a higher intake of meats and fats. In pigs, betaine, choline, creatinine, tryptophan, and phenylalanine were higher...

A dynamic, mechanistic model of metabolism in adipose tissue of lactating dairy cattle.

Science.gov (United States)

McNamara, J P; Huber, K; Kenéz, A

2016-07-01

Research in dairy cattle biology has resulted in a large body of knowledge on nutrition and metabolism in support of milk production and efficiency. This quantitative knowledge has been compiled in several model systems to balance and evaluate rations and predict requirements. There are also systems models for metabolism and reproduction in the cow that can be used to support research programs. Adipose tissue plays a significant role in the success and efficiency of lactation, and recent research has resulted in several data sets on genomic differences and changes in gene transcription of adipose tissue in dairy cattle. To fully use this knowledge, we need to build and expand mechanistic, dynamic models that integrate control of metabolism and production. Therefore, we constructed a second-generation dynamic, mechanistic model of adipose tissue metabolism of dairy cattle. The model describes the biochemical interconversions of glucose, acetate, β-hydroxybutyrate (BHB), glycerol, C16 fatty acids, and triacylglycerols. Data gathered from our own research and published references were used to set equation forms and parameter values. Acetate, glucose, BHB, and fatty acids are taken up from blood. The fatty acids are activated to the acyl coenzyme A moieties. Enzymatically catalyzed reactions are explicitly described with parameters including maximal velocity and substrate sensitivity. The control of enzyme activity is partially carried out by insulin and norepinephrine, portraying control in the cow. Model behavior was adequate, with sensitive responses to changing substrates and hormones. Increased nutrient uptake and increased insulin stimulate triacylglycerol synthesis, whereas a reduction in nutrient availability or increase in norepinephrine increases triacylglycerol hydrolysis and free fatty acid release to blood. This model can form a basis for more sophisticated integration of existing knowledge and future studies on metabolic efficiency of dairy cattle

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

KAUST Repository

Jolivet, Renaud

2015-02-26

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

Multi-timescale Modeling of Activity-Dependent Metabolic Coupling in the Neuron-Glia-Vasculature Ensemble

Science.gov (United States)

Jolivet, Renaud; Coggan, Jay S.; Allaman, Igor; Magistretti, Pierre J.

2015-01-01

Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell) can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS) are still debated. To address this question, we developed a detailed biophysical model of the brain’s metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV) ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging. PMID:25719367

Multi-timescale modeling of activity-dependent metabolic coupling in the neuron-glia-vasculature ensemble.

Directory of Open Access Journals (Sweden)

Renaud Jolivet

2015-02-01

Full Text Available Glucose is the main energy substrate in the adult brain under normal conditions. Accumulating evidence, however, indicates that lactate produced in astrocytes (a type of glial cell can also fuel neuronal activity. The quantitative aspects of this so-called astrocyte-neuron lactate shuttle (ANLS are still debated. To address this question, we developed a detailed biophysical model of the brain's metabolic interactions. Our model integrates three modeling approaches, the Buxton-Wang model of vascular dynamics, the Hodgkin-Huxley formulation of neuronal membrane excitability and a biophysical model of metabolic pathways. This approach provides a template for large-scale simulations of the neuron-glia-vasculature (NGV ensemble, and for the first time integrates the respective timescales at which energy metabolism and neuronal excitability occur. The model is constrained by relative neuronal and astrocytic oxygen and glucose utilization, by the concentration of metabolites at rest and by the temporal dynamics of NADH upon activation. These constraints produced four observations. First, a transfer of lactate from astrocytes to neurons emerged in response to activity. Second, constrained by activity-dependent NADH transients, neuronal oxidative metabolism increased first upon activation with a subsequent delayed astrocytic glycolysis increase. Third, the model correctly predicted the dynamics of extracellular lactate and oxygen as observed in vivo in rats. Fourth, the model correctly predicted the temporal dynamics of tissue lactate, of tissue glucose and oxygen consumption, and of the BOLD signal as reported in human studies. These findings not only support the ANLS hypothesis but also provide a quantitative mathematical description of the metabolic activation in neurons and glial cells, as well as of the macroscopic measurements obtained during brain imaging.

Metabolic mapping of the brain's response to visual stimulation: studies in humans

International Nuclear Information System (INIS)

Phelps, M.E.; Kuhl, D.E.; Mazziotta, J.C.

1981-01-01

These studies demonstrated increasing glucose metabolic rates in the human primary (PVC) and associative (AVC) visual cortex as the complexity of visual scenes increased. The metabolic response of the AVC increased more rapidly with scene complexity than that of the PVC, indicating the greater involvement of the higher order AVC for complex visual interpretations. Increases in local metabolic activity by as much as a factor of 2 above that of control subjects with eyes closed indicate the wide range and metabolic reserve of the visual cortex

Muscular and metabolic responses to different Nordic walking techniques, when style matters.

Science.gov (United States)

Pellegrini, Barbara; Boccia, Gennaro; Zoppirolli, Chiara; Rosa, Raffaela; Stella, Federico; Bortolan, Lorenzo; Rainoldi, Alberto; Schena, Federico

2018-01-01

Due to poling action and upper body engagement, Nordic walking (NW) has additional health benefits with respect to conventional walking. The aim of this study was to evaluate the differences in muscle activation and metabolic responses between NW, performed with the technique suggested by NW instructors, and with some modifications in the way to move upper limb and poles. Ten NW instructors volunteered to walk on a treadmill at 5.5 km•h-1 in five conditions: walking (W), Nordic walking (NW), NW with a weak poling action (NWweak), with straight-upper limbs moving the shoulders (NWshoulder) and with elbow flexion-extension pattern and shoulder freezed (NWelbow). Poling forces, body segments and poles movement, upper and lower body muscle activation, as well as metabolic parameters were measured.All modified NW techniques elicited lower muscular activation and metabolic responses with respect to the suggested NW technique (P walking instructors, sport technicians and practitioners should be aware that any deviation from the technique usually suggested might lead to lower benefits. However it is worth to note that any walking technique with poles elicits higher metabolic responses and muscular activation than walking.

Do diabetes and obesity affect the metabolic response to exercise?

Science.gov (United States)

Plomgaard, Peter; Weigert, Cora

2017-07-01

Exercise is recommended as therapeutic intervention for people at risk to develop type 2 diabetes to prevent or treat the disease. Recent studies on the influence of obesity and type 2 diabetes on the outcome of exercise programs are discussed. Poor glycemic control before an intervention can be a risk factor of reduced therapeutic benefit from exercise. But the acute metabolic response to exercise and the transcriptional profile of the working muscle is similar in healthy controls and type 2 diabetic patients, including but not limited to intact activation of skeletal muscle AMP-activated kinase signaling, glucose uptake and expression of peroxisome proliferator-activated receptor gamma coactivator 1α. The increase in plasma acylcarnitines during exercise is not influenced by type 2 diabetes or obesity. The hepatic response to exercise is dependent on the glucagon/insulin ratio and the exercise-induced increase in hepatokines such as fibroblast growth factor 21 and follistatin is impaired in type 2 diabetes and obesity, but consequences for the benefit from exercise are unknown yet. Severe metabolic dysregulation can reduce the benefit from exercise, but the intact response of key metabolic regulators in exercising skeletal muscle of diabetic patients demonstrates the effectiveness of exercise programs to treat the disease.

Computational Modeling of Lipid Metabolism in Yeast

Directory of Open Access Journals (Sweden)

Vera Schützhold

2016-09-01

Full Text Available Lipid metabolism is essential for all major cell functions and has recently gained increasing attention in research and health studies. However, mathematical modeling by means of classical approaches such as stoichiometric networks and ordinary differential equation systems has not yet provided satisfactory insights, due to the complexity of lipid metabolism characterized by many different species with only slight differences and by promiscuous multifunctional enzymes.Here, we present a object-oriented stochastic model approach as a way to cope with the complex lipid metabolic network. While all lipid species are treated objects in the model, they can be modified by the respective converting reactions based on reaction rules, a hybrid method that integrates benefits of agent-based and classical stochastic simulation. This approach allows to follow the dynamics of all lipid species with different fatty acids, different degrees of saturation and different headgroups over time and to analyze the effect of parameter changes, potential mutations in the catalyzing enzymes or provision of different precursors. Applied to yeast metabolism during one cell cycle period, we could analyze the distribution of all lipids to the various membranes in time-dependent manner.The presented approach allows to efficiently treat the complexity of cellular lipid metabolism and to derive conclusions on the time- and location-dependent distributions of lipid species and their properties such as saturation. It is widely applicable, easily extendable and will provide further insights in healthy and diseased states of cell metabolism.

The cross-tissue metabolic response of abalone (Haliotis midae) to functional hypoxia.

Science.gov (United States)

Venter, Leonie; Loots, Du Toit; Mienie, Lodewyk J; Jansen van Rensburg, Peet J; Mason, Shayne; Vosloo, Andre; Lindeque, Jeremie Z

2018-03-23

Functional hypoxia is a stress condition caused by the abalone itself as a result of increased muscle activity, which generally necessitates the employment of anaerobic metabolism if the activity is sustained for prolonged periods. With that being said, abalone are highly reliant on anaerobic metabolism to provide partial compensation for energy production during oxygen-deprived episodes. However, current knowledge on the holistic metabolic response for energy metabolism during functional hypoxia, and the contribution of different metabolic pathways and various abalone tissues towards the overall accumulation of anaerobic end-products in abalone are scarce. Metabolomics analysis of adductor muscle, foot muscle, left gill, right gill, haemolymph and epipodial tissue samples indicated that South African abalone ( Haliotis midae) subjected to functional hypoxia utilises predominantly anaerobic metabolism, and depends on all of the main metabolite classes (proteins, carbohydrates and lipids) for energy supply. Functional hypoxia caused increased levels of anaerobic end-products: lactate, alanopine, tauropine, succinate and alanine. Also, elevation in arginine levels was detected, confirming that abalone use phosphoarginine to generate energy during functional hypoxia. Different tissues showed varied metabolic responses to hypoxia, with functional hypoxia showing excessive changes in the adductor muscle and gills. From this metabolomics investigation, it becomes evident that abalone are metabolically able to produce sufficient amounts of energy when functional hypoxia is experienced. Also, tissue interplay enables the adjustment of H. midae energy requirements as their metabolism shifts from aerobic to anaerobic respiration during functional hypoxia.This article has an associated First Person interview with the first author of the paper. © 2018. Published by The Company of Biologists Ltd.

The cross-tissue metabolic response of abalone (Haliotis midae to functional hypoxia

Directory of Open Access Journals (Sweden)

Leonie Venter

2018-03-01

Full Text Available Functional hypoxia is a stress condition caused by the abalone itself as a result of increased muscle activity, which generally necessitates the employment of anaerobic metabolism if the activity is sustained for prolonged periods. With that being said, abalone are highly reliant on anaerobic metabolism to provide partial compensation for energy production during oxygen-deprived episodes. However, current knowledge on the holistic metabolic response for energy metabolism during functional hypoxia, and the contribution of different metabolic pathways and various abalone tissues towards the overall accumulation of anaerobic end-products in abalone are scarce. Metabolomics analysis of adductor muscle, foot muscle, left gill, right gill, haemolymph and epipodial tissue samples indicated that South African abalone (Haliotis midae subjected to functional hypoxia utilises predominantly anaerobic metabolism, and depends on all of the main metabolite classes (proteins, carbohydrates and lipids for energy supply. Functional hypoxia caused increased levels of anaerobic end-products: lactate, alanopine, tauropine, succinate and alanine. Also, elevation in arginine levels was detected, confirming that abalone use phosphoarginine to generate energy during functional hypoxia. Different tissues showed varied metabolic responses to hypoxia, with functional hypoxia showing excessive changes in the adductor muscle and gills. From this metabolomics investigation, it becomes evident that abalone are metabolically able to produce sufficient amounts of energy when functional hypoxia is experienced. Also, tissue interplay enables the adjustment of H. midae energy requirements as their metabolism shifts from aerobic to anaerobic respiration during functional hypoxia. This article has an associated First Person interview with the first author of the paper.

Topological and kinetic determinants of the modal matrices of dynamic models of metabolism.

Directory of Open Access Journals (Sweden)

Bin Du

Full Text Available Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J and the modal matrix (M-1 arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions.

Positron computed tomography studies of cerebral metabolic responses to complex motor tasks

International Nuclear Information System (INIS)

Phelps, M.E.; Mazziotta, J.C.

1984-01-01

Human motor system organization was explored in 8 right-handed male subjects using /sup 18/F-fluorodeoxyglucose and positron computed tomography to measure cerebral glucose metabolism. Five subjects had triple studies (eyes closed) including: control (hold pen in right hand without moving), normal size writing (subject repeatedly writes name) and large (10-15 X normal) name writing. In these studies normal and large size writing had a similar distribution of metabolic responses when compared to control studies. Activations (percent change from control) were in the range of 12-20% and occurred in the striatum bilaterally > contralateral Rolandic cortex > contralateral thalamus. No significant activations were observed in the ipsilateral thalamus, Rolandic cortex or cerebellum (supplementary motor cortex was not examined). The magnitude of the metabolic response in the striatum was greater with the large versus normal sized writing. This differential response may be due to an increased number and topographic distribution of neurons responding with the same average activity between tasks or an increase in the functional activity of the same neuronal population between the two tasks (present spatial resolution inadequate to differentiate). When subjects (N=3) performed novel sequential finger movements, the maximal metabolic response was in the contralateral Rolandic cortex > striatum. Such studies provide a means of exploring human motor system organization, motor learning and provide a basis for examining patients with motor system disorders

Supplementation of Saccharomyces cerevisiae modulates the metabolic response to lipopolysaccharide challenge in feedlot steers

Science.gov (United States)

Live yeast has the potential to serve as an alternative to the use of low-dose supplementation of antibiotics in cattle due to the ability to alter ruminant metabolism; which in turn may influence the immune response. Therefore, the objective of this study was to determine the metabolic response to ...

SU-C-303-02: Correlating Metabolic Response to Radiation Therapy with HIF-1alpha Expression

International Nuclear Information System (INIS)

Campos, D; Peeters, W; Nickel, K; Eliceiri, K; Kimple, R; Van Der Kogel, A; Kissick, M

2015-01-01

Purpose: To understand radiation induced alterations in cellular metabolism which could be used to assess treatment or normal tissue response to aid in patient-specific adaptive radiotherapy. This work aims to compare the metabolic response of two head and neck cell lines, one malignant (UM-SCC-22B) and one benign (Normal Oral Keratinocyte), to ionizing radiation. Responses are compared to alterations in HIF-1alpha expression. These dynamics can potentially serve as biomarkers in assessing treatment response allowing for patient-specific adaptive radiotherapy. Methods: Measurements of metabolism and HIF-1alpha expression were taken before and X minutes after a 10 Gy dose of radiation delivered via an orthovoltage x-ray source. In vitro changes in metabolic activity were measured via fluorescence lifetime imaging (FLIM) to assess the mean lifetime of NADH autofluorescence following a dose of 10 Gy. HIF-1alpha expression was measured via immunohistochemical staining of in vitro treated cells and expression was quantified using the FIJI software package. Results: FLIM demonstrated a decrease in the mean fluorescence lifetime of NADH by 100 ps following 10 Gy indicating a shift towards glycolytic pathways for malignant cells; whereas this benign cell line showed little change in metabolic signature. Immunohistochemical analysis showed significant changes in HIF-1alpha expression in response to 10 Gy of radiation that correlate to metabolic profiles. Conclusion: Radiation induces significant changes in metabolic activity and HIF-1alpha expression. These alterations occur on time scales approximating the duration of common radiation treatments (approximately tens of minutes). Further understanding these dynamics has important implications with regard to improvement of therapy and biomarkers of treatment response

SU-C-303-02: Correlating Metabolic Response to Radiation Therapy with HIF-1alpha Expression

Energy Technology Data Exchange (ETDEWEB)

Campos, D [University of Wisconsin Madison, Madison, WI (United States); Peeters, W [Radboud University Medical Center, Nijmegen, GA (United States); Nickel, K [University of Wisconsin, Madison, WI (United States); Eliceiri, K; Kimple, R; Van Der Kogel, A; Kissick, M [University of Wisconsin, Madison, Wisconsin (United States)

2015-06-15

Purpose: To understand radiation induced alterations in cellular metabolism which could be used to assess treatment or normal tissue response to aid in patient-specific adaptive radiotherapy. This work aims to compare the metabolic response of two head and neck cell lines, one malignant (UM-SCC-22B) and one benign (Normal Oral Keratinocyte), to ionizing radiation. Responses are compared to alterations in HIF-1alpha expression. These dynamics can potentially serve as biomarkers in assessing treatment response allowing for patient-specific adaptive radiotherapy. Methods: Measurements of metabolism and HIF-1alpha expression were taken before and X minutes after a 10 Gy dose of radiation delivered via an orthovoltage x-ray source. In vitro changes in metabolic activity were measured via fluorescence lifetime imaging (FLIM) to assess the mean lifetime of NADH autofluorescence following a dose of 10 Gy. HIF-1alpha expression was measured via immunohistochemical staining of in vitro treated cells and expression was quantified using the FIJI software package. Results: FLIM demonstrated a decrease in the mean fluorescence lifetime of NADH by 100 ps following 10 Gy indicating a shift towards glycolytic pathways for malignant cells; whereas this benign cell line showed little change in metabolic signature. Immunohistochemical analysis showed significant changes in HIF-1alpha expression in response to 10 Gy of radiation that correlate to metabolic profiles. Conclusion: Radiation induces significant changes in metabolic activity and HIF-1alpha expression. These alterations occur on time scales approximating the duration of common radiation treatments (approximately tens of minutes). Further understanding these dynamics has important implications with regard to improvement of therapy and biomarkers of treatment response.

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.

Mouse Models as Predictors of Human Responses: Evolutionary Medicine.

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Uhl, Elizabeth W; Warner, Natalie J

Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.

Integrative Analysis of Metabolic Models – from Structure to Dynamics

Energy Technology Data Exchange (ETDEWEB)

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de [Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben (Germany); Schreiber, Falk [Monash University, Melbourne, VIC (Australia); Martin-Luther-University Halle-Wittenberg, Halle (Germany)

2015-01-26

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the context of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.

Metabolic and inflammatory responses to the common sweetener stevioside and a glycemic challenge in horses with equine metabolic syndrome.

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Elzinga, S E; Rohleder, B; Schanbacher, B; McQuerry, K; Barker, V D; Adams, A A

2017-07-01

Extracts derived from the leaves of the stevia plant (stevioside) are commonly used as sweeteners for humans and horses. Stevioside appears to be safe for human consumption, including for individuals with insulin dysregulation. In the horse, the safety or metabolic effects of stevioside on normal animals or on those with metabolic dysfunction are unknown. Furthermore, the inflammatory response to a glycemic challenge or to stevioside in horses is not well defined. Therefore, the objective of this study was to measure the effects of stevioside and a glycemic challenge on insulin, glucose, and inflammatory responses in horses with a common metabolic dysfunction (equine metabolic syndrome or EMS) compared with non-EMS controls. To accomplish this, 15 horses were selected; 8 EMS and 7 age-matched controls. An oral sugar test was performed using Karo corn syrup (karo) or stevioside in a random crossover design. Horses were given 0.15 mL/kg body weight of karo or its equivalent grams of sugar in stevia dissolved in water. Blood samples were collected by jugular venipuncture before administration of either stevia or karo and at 60 and 240 min after administration. Serum was used for glucose and insulin determination and plasma for isolation of peripheral blood mononuclear cells (PBMCs) for inflammatory cytokine analysis via flow cytometry and reverse transcription PCR (RT-PCR). Stevia appeared to stimulate lower glycemic and insulinemic responses when compared to karo, in particular in EMS horses. EMS and control horses had inverse inflammatory responses to administration of either stevia or karo with EMS horses having a proinflammatory response (P ≤ 0.05). These data provide evidence as to why horses with EMS may be predisposed to developing laminitis, potentially as a result of an exaggerated inflammatory response to glycemic and insulinemic responses. Furthermore, the data provide new avenues for exploring mechanisms behind the syndrome, in particular when using a

Response of melanoma tumor phospholipid metabolism to chloroethyle nitrosourea: a high resolution proton NMR spectroscopy study.

Science.gov (United States)

Morvan, Daniel; Demidem, Aïcha; Madelmont, Jean-Claude

2003-07-01

Phospholipid metabolism is tightly involved in tumor growth regulation and tumor cell survival. The response of phospholipid metabolism to chloroethyle nitrosourea treatment is investigated in a murine B16 melanoma model. Measurements of phospholipid derivatives are performed on intact tumor tissue samples using one- and two-dimensional proton NMR spectroscopy. During the tumor growth inhibition phase under treatment, tumors overexpress phosphocholine, phosphoethanolamine, glycerophosphocholine and glycerophosphoethanolamine, whereas phosphatidylcholine and phosphatidylethanolamine levels are maintained to control levels. During re-growth, which remained quantitatively much below control growth, chloroethyle nitrosourea-treated melanoma tumors overexpress phosphocholine and phosphoethanolamine only. In treated melanoma, phosphatidylcholine levels show an inverse relationship with tumor growth rates. In conclusion, chloroethyle nitrosourea-treated melanoma tumors maintain their phosphatidylcholine levels and exhibit transformed phospholipid metabolism phenotype, by mechanisms that could participate in tumor cell survival.

Metabolic engineering tools in model cyanobacteria.

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Carroll, Austin L; Case, Anna E; Zhang, Angela; Atsumi, Shota

2018-03-26

Developing sustainable routes for producing chemicals and fuels is one of the most important challenges in metabolic engineering. Photoautotrophic hosts are particularly attractive because of their potential to utilize light as an energy source and CO 2 as a carbon substrate through photosynthesis. Cyanobacteria are unicellular organisms capable of photosynthesis and CO 2 fixation. While engineering in heterotrophs, such as Escherichia coli, has result in a plethora of tools for strain development and hosts capable of producing valuable chemicals efficiently, these techniques are not always directly transferable to cyanobacteria. However, recent efforts have led to an increase in the scope and scale of chemicals that cyanobacteria can produce. Adaptations of important metabolic engineering tools have also been optimized to function in photoautotrophic hosts, which include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9, 13 C Metabolic Flux Analysis (MFA), and Genome-Scale Modeling (GSM). This review explores innovations in cyanobacterial metabolic engineering, and highlights how photoautotrophic metabolism has shaped their development. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Long-term salt stress responsive growth, carbohydrate metabolism ...

African Journals Online (AJOL)

We investigated the long-term responses of tobacco tissues to salt stress, with a particular interest for growth parameters, proline (Pro) accumulation, and carbohydrate metabolism. Exposure of 17-day-old tobacco plants to 0.2 M NaCl was followed by a higher decrease in dry matter in roots than shoots with a decrease of ...

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.

Induction of a stringent metabolic response in intracellular stages of Leishmania mexicana leads to increased dependence on mitochondrial metabolism.

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Eleanor C Saunders

2014-01-01

Full Text Available Leishmania parasites alternate between extracellular promastigote stages in the insect vector and an obligate intracellular amastigote stage that proliferates within the phagolysosomal compartment of macrophages in the mammalian host. Most enzymes involved in Leishmania central carbon metabolism are constitutively expressed and stage-specific changes in energy metabolism remain poorly defined. Using (13C-stable isotope resolved metabolomics and (2H2O labelling, we show that amastigote differentiation is associated with reduction in growth rate and induction of a distinct stringent metabolic state. This state is characterized by a global decrease in the uptake and utilization of glucose and amino acids, a reduced secretion of organic acids and increased fatty acid β-oxidation. Isotopomer analysis showed that catabolism of hexose and fatty acids provide C4 dicarboxylic acids (succinate/malate and acetyl-CoA for the synthesis of glutamate via a compartmentalized mitochondrial tricarboxylic acid (TCA cycle. In vitro cultivated and intracellular amastigotes are acutely sensitive to inhibitors of mitochondrial aconitase and glutamine synthetase, indicating that these anabolic pathways are essential for intracellular growth and virulence. Lesion-derived amastigotes exhibit a similar metabolism to in vitro differentiated amastigotes, indicating that this stringent response is coupled to differentiation signals rather than exogenous nutrient levels. Induction of a stringent metabolic response may facilitate amastigote survival in a nutrient-poor intracellular niche and underlie the increased dependence of this stage on hexose and mitochondrial metabolism.

Modeling the role of negative cooperativity in metabolic regulation and homeostasis.

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Eliot C Bush

Full Text Available A significant proportion of enzymes display cooperativity in binding ligand molecules, and such effects have an important impact on metabolic regulation. This is easiest to understand in the case of positive cooperativity. Sharp responses to changes in metabolite concentrations can allow organisms to better respond to environmental changes and maintain metabolic homeostasis. However, despite the fact that negative cooperativity is almost as common as positive, it has been harder to imagine what advantages it provides. Here we use computational models to explore the utility of negative cooperativity in one particular context: that of an inhibitor binding to an enzyme. We identify several factors which may contribute, and show that acting together they can make negative cooperativity advantageous.

Concepts, challenges, and successes in modeling thermodynamics of metabolism.

Science.gov (United States)

Cannon, William R

2014-01-01

The modeling of the chemical reactions involved in metabolism is a daunting task. Ideally, the modeling of metabolism would use kinetic simulations, but these simulations require knowledge of the thousands of rate constants involved in the reactions. The measurement of rate constants is very labor intensive, and hence rate constants for most enzymatic reactions are not available. Consequently, constraint-based flux modeling has been the method of choice because it does not require the use of the rate constants of the law of mass action. However, this convenience also limits the predictive power of constraint-based approaches in that the law of mass action is used only as a constraint, making it difficult to predict metabolite levels or energy requirements of pathways. An alternative to both of these approaches is to model metabolism using simulations of states rather than simulations of reactions, in which the state is defined as the set of all metabolite counts or concentrations. While kinetic simulations model reactions based on the likelihood of the reaction derived from the law of mass action, states are modeled based on likelihood ratios of mass action. Both approaches provide information on the energy requirements of metabolic reactions and pathways. However, modeling states rather than reactions has the advantage that the parameters needed to model states (chemical potentials) are much easier to determine than the parameters needed to model reactions (rate constants). Herein, we discuss recent results, assumptions, and issues in using simulations of state to model metabolism.

Maternal Diet, Metabolic State, and Inflammatory Response Exert Unique and Long-Lasting Influences on Offspring Behavior in Non-Human Primates

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Jacqueline R. Thompson

2018-04-01

Full Text Available Nutritional status influences brain health and gestational exposure to metabolic disorders (e.g. obesity and diabetes increases the risk of neuropsychiatric disorders. The aim of the present study was to further investigate the role of maternal Western-style diet (WSD, metabolic state, and inflammatory factors in the programming of Japanese macaque offspring behavior. Utilizing structural equation modeling, we investigated the relationships between maternal diet, prepregnancy adiposity, third trimester insulin response, and plasma cytokine levels on 11-month-old offspring behavior. Maternal WSD was associated with greater reactive and ritualized anxiety in offspring. Maternal adiposity and third trimester macrophage-derived chemokine (MDC exerted opposing effects on offspring high-energy outbursts. Elevated levels of this behavior were associated with low maternal MDC and increased prepregnancy adiposity. This is the first study to show that maternal MDC levels influence offspring behavior. We found no evidence suggesting maternal peripheral inflammatory response mediated the effect of maternal diet and metabolic state on aberrant offspring behavior. Additionally, the extent of maternal metabolic impairment differentially influenced chemokine response. Elevated prepregnancy adiposity suppressed third trimester chemokines, while obesity-induced insulin resistance augmented peripheral chemokine levels. WSD also directly increased maternal interleukin-12. This is the first non-human primate study to delineate the effects of maternal diet and metabolic state on gestational inflammatory environment and subsequent offspring behavior. Our findings give insight to the complex mechanisms by which diet, metabolic state, and inflammation during pregnancy exert unique influences on offspring behavioral regulation.

Maternal high-fat diet intensifies the metabolic response to stress in male rat offspring

OpenAIRE

Karbaschi, Roxana; Zardooz, Homeira; Khodagholi, Fariba; Dargahi, Leila; Salimi, Mina; Rashidi, FatemehSadat

2017-01-01

Background The mother?s consumption of high-fat food can affect glucose metabolism and the hypothalamic?pituitary?adrenal axis responsiveness in the offspring and potentially affect the metabolic responses to stress as well. This study examines the effect of maternal high-fat diet on the expression of pancreatic glucose transporter 2 and the secretion of insulin in response to stress in offspring. Methods Female rats were randomly divided into normal and high-fat diet groups and were fed in a...

Adipose tissue and metabolic and inflammatory responses to stroke are altered in obese mice

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Michael J. Haley

2017-10-01

Full Text Available Obesity is an independent risk factor for stroke, although several clinical studies have reported that obesity improves stroke outcome. Obesity is hypothesised to aid recovery by protecting against post-stroke catabolism. We therefore assessed whether obese mice had an altered metabolic and inflammatory response to stroke. Obese ob/ob mice underwent a 20-min middle cerebral artery occlusion and 24-h reperfusion. Lipid metabolism and expression of inflammatory cytokines were assessed in the plasma, liver and adipose tissue. The obese-specific metabolic response to stroke was assessed in plasma using non-targeted ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS metabolomics coupled with univariate and multivariate analysis. Obesity had no effect on the extent of weight loss 24 h after stroke but affected the metabolic and inflammatory responses to stroke, predominantly affecting lipid metabolism. Specifically, obese mice had increases in plasma free fatty acids and expression of adipose lipolytic enzymes. Metabolomics identified several classes of metabolites affected by stroke in obese mice, including fatty acids and membrane lipids (glycerophospholipids, lysophospholipids and sphingolipids. Obesity also featured increases in inflammatory cytokines in the plasma and adipose tissue. Overall, these results demonstrate that obesity affected the acute metabolic and inflammatory response to stroke and suggest a potential role for adipose tissue in this effect. These findings could have implications for longer-term recovery and also further highlight the importance of considering comorbidities in preclinical stroke research, especially when identifying biomarkers for stroke. However, further work is required to assess whether these changes translate into long-term effects on recovery.

Understanding variation in ecosystem pulse responses to wetting: Benefits of data-model coupling

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Jenerette, D.

2011-12-01

Metabolic pulses of activity are a common ecological response to intermittently available resources and in water-limited ecosystems these pulses often occur in response to wetting. Net ecosystem CO2 exchange (NEE) in response to episodic wetting events is hypothesized to have a complex trajectory reflecting the distinct responses, or "pulses", of respiration and photosynthesis. To help direct research activities a physiological-based model of whole ecosystem metabolic activity up- and down-regulation was developed to investigate ecosystem energy balance and gas exchange pulse responses following precipitation events. This model was to investigate pulse dynamics from a local network of sites in southern Arizona, a global network of eddy-covariance ecosystem monitoring sites, laboratory incubation studies, and field manipulations. Pulse responses were found to be ubiquitous across ecosystem types. These pulses had a highly variable influence on NEE following wetting, ranging from large net sinks to sources of CO2 to the atmosphere. Much of the variability in pulse responses of NEE could be described through a coupled up- and down-regulation pulse response model. Respiration pulses were hypothesized to occur through a reduction in whole ecosystem activation energy; this model was both useful and corroborated through laboratory incubation studies of soil respiration. Using the Fluxnet eddy-covariance measurement database event specific responses were combined with the pulse model into an event specific twenty-five day net flux calculation. Across all events observed a general net accumulation of CO2 following a precipitation event, with the largest net uptake within deciduous broadleaf forests and smallest within grasslands. NEE pulses favored greater uptake when pre-event ecosystem respiration rates and total precipitation were higher. While the latter was expected, the former adds to previous theory by suggesting a larger net uptake of CO2 when pre-event metabolic

Genome-scale modeling using flux ratio constraints to enable metabolic engineering of clostridial metabolism in silico.

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McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S

2012-05-14

Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.

Globular adiponectin ameliorates metabolic insulin resistance via AMPK-mediated restoration of microvascular insulin responses

Science.gov (United States)

Zhao, Lina; Fu, Zhuo; Wu, Jing; Aylor, Kevin W; Barrett, Eugene J; Cao, Wenhong; Liu, Zhenqi

2015-01-01

Abstract Hypoadiponectinaemia is closely associated with endothelial dysfunction and insulin resistance, and microvasculature plays a critical role in the regulation of insulin action in muscle. Here we tested whether adiponectin replenishment could improve metabolic insulin sensitivity in male rats fed a high-fat diet (HFD) via the modulation of microvascular insulin responses. Male Sprague–Dawley rats were fed either a HFD or low-fat diet (LFD) for 4 weeks. Small resistance artery myograph changes in tension, muscle microvascular recruitment and metabolic response to insulin were determined. Compared with rats fed a LFD, HFD feeding abolished the vasodilatory actions of globular adiponectin (gAd) and insulin on pre-constricted distal saphenous arteries. Pretreatment with gAd improved insulin responses in arterioles isolated from HFD rats, which was blocked by AMP-activated protein kinase (AMPK) inhibition. Similarly, HFD abolished microvascular responses to either gAd or insulin and decreased insulin-stimulated glucose disposal by ∼60%. However, supplementing gAd fully rescued insulin’s microvascular action and significantly improved the metabolic responses to insulin in HFD male rats and these actions were abolished by inhibition of either AMPK or nitric oxide production. We conclude that HFD induces vascular adiponectin and insulin resistance but gAd administration can restore vascular insulin responses and improve insulin’s metabolic action via an AMPK- and nitric oxide-dependent mechanism in male rats. Key points Adiponectin is an adipokine with anti-inflammatory and anti-diabetic properties. Hypoadiponectinaemia is closely associated with endothelial dysfunction and insulin resistance in obesity and diabetes. Insulin resistance is present in muscle microvasculature and this may contribute to decreased insulin delivery to, and action in, muscle. In this study we examined whether adiponectin ameliorates metabolic insulin resistance by affecting muscle

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...

Differential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to Xylose.

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Du Toit W P Schabort

Full Text Available We investigated the transcriptomic response of a new strain of the yeast Kluyveromyces marxianus, in glucose and xylose media using RNA-seq. The data were explored in a number of innovative ways using a variety of networks types, pathway maps, enrichment statistics, reporter metabolites and a flux simulation model, revealing different aspects of the genome-scale response in an integrative systems biology manner. The importance of the subcellular localisation in the transcriptomic response is emphasised here, revealing new insights. As was previously reported by others using a rich medium, we show that peroxisomal fatty acid catabolism was dramatically up-regulated in a defined xylose mineral medium without fatty acids, along with mechanisms to activate fatty acids and transfer products of β-oxidation to the mitochondria. Notably, we observed a strong up-regulation of the 2-methylcitrate pathway, supporting capacity for odd-chain fatty acid catabolism. Next we asked which pathways would respond to the additional requirement for NADPH for xylose utilisation, and rationalised the unexpected results using simulations with Flux Balance Analysis. On a fundamental level, we investigated the contribution of the hierarchical and metabolic regulation levels to the regulation of metabolic fluxes. Metabolic regulation analysis suggested that genetic level regulation plays a major role in regulating metabolic fluxes in adaptation to xylose, even for the high capacity reactions, which is unexpected. In addition, isozyme switching may play an important role in re-routing of metabolic fluxes in subcellular compartments in K. marxianus.

Metabolic Response to NAD Depletion across Cell Lines Is Highly Variable.

Science.gov (United States)

Xiao, Yang; Kwong, Mandy; Daemen, Anneleen; Belvin, Marcia; Liang, Xiaorong; Hatzivassiliou, Georgia; O'Brien, Thomas

2016-01-01

Nicotinamide adenine dinucleotide (NAD) is a cofactor involved in a wide range of cellular metabolic processes and is a key metabolite required for tumor growth. NAMPT, nicotinamide phosphoribosyltransferase, which converts nicotinamide (NAM) to nicotinamide mononucleotide (NMN), the immediate precursor of NAD, is an attractive therapeutic target as inhibition of NAMPT reduces cellular NAD levels and inhibits tumor growth in vivo. However, there is limited understanding of the metabolic response to NAD depletion across cancer cell lines and whether all cell lines respond in a uniform manner. To explore this we selected two non-small cell lung carcinoma cell lines that are sensitive to the NAMPT inhibitor GNE-617 (A549, NCI-H1334), one that shows intermediate sensitivity (NCI-H441), and one that is insensitive (LC-KJ). Even though NAD was reduced in all cell lines there was surprising heterogeneity in their metabolic response. Both sensitive cell lines reduced glycolysis and levels of di- and tri-nucleotides and modestly increased oxidative phosphorylation, but they differed in their ability to combat oxidative stress. H1334 cells activated the stress kinase AMPK, whereas A549 cells were unable to activate AMPK as they contain a mutation in LKB1, which prevents activation of AMPK. However, A549 cells increased utilization of the Pentose Phosphate pathway (PPP) and had lower reactive oxygen species (ROS) levels than H1334 cells, indicating that A549 cells are better able to modulate an increase in oxidative stress. Inherent resistance of LC-KJ cells is associated with higher baseline levels of NADPH and a delayed reduction of NAD upon NAMPT inhibition. Our data reveals that cell lines show heterogeneous response to NAD depletion and that the underlying molecular and genetic framework in cells can influence the metabolic response to NAMPT inhibition.

Metabolic Response to NAD Depletion across Cell Lines Is Highly Variable.

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Yang Xiao

Full Text Available Nicotinamide adenine dinucleotide (NAD is a cofactor involved in a wide range of cellular metabolic processes and is a key metabolite required for tumor growth. NAMPT, nicotinamide phosphoribosyltransferase, which converts nicotinamide (NAM to nicotinamide mononucleotide (NMN, the immediate precursor of NAD, is an attractive therapeutic target as inhibition of NAMPT reduces cellular NAD levels and inhibits tumor growth in vivo. However, there is limited understanding of the metabolic response to NAD depletion across cancer cell lines and whether all cell lines respond in a uniform manner. To explore this we selected two non-small cell lung carcinoma cell lines that are sensitive to the NAMPT inhibitor GNE-617 (A549, NCI-H1334, one that shows intermediate sensitivity (NCI-H441, and one that is insensitive (LC-KJ. Even though NAD was reduced in all cell lines there was surprising heterogeneity in their metabolic response. Both sensitive cell lines reduced glycolysis and levels of di- and tri-nucleotides and modestly increased oxidative phosphorylation, but they differed in their ability to combat oxidative stress. H1334 cells activated the stress kinase AMPK, whereas A549 cells were unable to activate AMPK as they contain a mutation in LKB1, which prevents activation of AMPK. However, A549 cells increased utilization of the Pentose Phosphate pathway (PPP and had lower reactive oxygen species (ROS levels than H1334 cells, indicating that A549 cells are better able to modulate an increase in oxidative stress. Inherent resistance of LC-KJ cells is associated with higher baseline levels of NADPH and a delayed reduction of NAD upon NAMPT inhibition. Our data reveals that cell lines show heterogeneous response to NAD depletion and that the underlying molecular and genetic framework in cells can influence the metabolic response to NAMPT inhibition.

A workflow for mathematical modeling of subcellular metabolic pathways in leaf metabolism of Arabidopsis thaliana

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Thomas eNägele

2013-12-01

Full Text Available During the last decade genome sequencing has experienced a rapid technological development resulting in numerous sequencing projects and applications in life science. In plant molecular biology, the availability of sequence data on whole genomes has enabled the reconstruction of metabolic networks. Enzymatic reactions are predicted by the sequence information. Pathways arise due to the participation of chemical compounds as substrates and products in these reactions. Although several of these comprehensive networks have been reconstructed for the genetic model plant Arabidopsis thaliana, the integration of experimental data is still challenging. Particularly the analysis of subcellular organization of plant cells limits the understanding of regulatory instances in these metabolic networks in vivo. In this study, we develop an approach for the functional integration of experimental high-throughput data into such large-scale networks. We present a subcellular metabolic network model comprising 524 metabolic intermediates and 548 metabolic interactions derived from a total of 2769 reactions. We demonstrate how to link the metabolite covariance matrix of different Arabidopsis thaliana accessions with the subcellular metabolic network model for the inverse calculation of the biochemical Jacobian, finally resulting in the calculation of a matrix which satisfies a Lyaponov equation involving a covariance matrix. In this way, differential strategies of metabolite compartmentation and involved reactions were identified in the accessions when exposed to low temperature.

Activation of SAT1 engages polyamine metabolism with p53-mediated ferroptotic responses.

Science.gov (United States)

Ou, Yang; Wang, Shang-Jui; Li, Dawei; Chu, Bo; Gu, Wei

2016-11-01

Although p53-mediated cell-cycle arrest, senescence, and apoptosis remain critical barriers to cancer development, the emerging role of p53 in cell metabolism, oxidative responses, and ferroptotic cell death has been a topic of great interest. Nevertheless, it is unclear how p53 orchestrates its activities in multiple metabolic pathways into tumor suppressive effects. Here, we identified the SAT1 (spermidine/spermine N 1 -acetyltransferase 1) gene as a transcription target of p53. SAT1 is a rate-limiting enzyme in polyamine catabolism critically involved in the conversion of spermidine and spermine back to putrescine. Surprisingly, we found that activation of SAT1 expression induces lipid peroxidation and sensitizes cells to undergo ferroptosis upon reactive oxygen species (ROS)-induced stress, which also leads to suppression of tumor growth in xenograft tumor models. Notably, SAT1 expression is down-regulated in human tumors, and CRISPR-cas9-mediated knockout of SAT1 expression partially abrogates p53-mediated ferroptosis. Moreover, SAT1 induction is correlated with the expression levels of arachidonate 15-lipoxygenase (ALOX15), and SAT1-induced ferroptosis is significantly abrogated in the presence of PD146176, a specific inhibitor of ALOX15. Thus, our findings uncover a metabolic target of p53 involved in ferroptotic cell death and provide insight into the regulation of polyamine metabolism and ferroptosis-mediated tumor suppression.

AMPK regulates metabolism and survival in response to ionizing radiation

International Nuclear Information System (INIS)

Zannella, Vanessa E.; Cojocari, Dan; Hilgendorf, Susan; Vellanki, Ravi N.; Chung, Stephen; Wouters, Bradly G.; Koritzinsky, Marianne

2011-01-01

Background and purpose: AMPK is a metabolic sensor and an upstream inhibitor of mTOR activity. AMPK is phosphorylated by ionizing radiation (IR) in an ATM dependent manner, but the cellular consequences of this phosphorylation event have remained unclear. The objective of this study was to assess whether AMPK plays a functional role in regulating cellular responses to IR. Methods: The importance of AMPK expression for radiation responses was investigated using both MEFs (mouse embryo fibroblasts) double knockout for AMPK α1/α2 subunits and human colorectal carcinoma cells (HCT 116) with AMPK α1/α2 shRNA mediated knockdown. Results: We demonstrate here that IR results in phosphorylation of both AMPK and its substrate, ACC. IR moderately stimulated mTOR activity, and this was substantially exacerbated in the absence of AMPK. AMPK was required for IR induced expression of the mTOR inhibitor REDD1, indicating that AMPK restrains mTOR activity through multiple mechanisms. Likewise, cellular metabolism was deregulated following irradiation in the absence of AMPK, as evidenced by a substantial increase in oxygen consumption rates and lactate production. AMPK deficient cells showed impairment of the G1/S cell cycle checkpoint, and were unable to support long-term proliferation during starvation following radiation. Lastly, we show that AMPK proficiency is important for clonogenic survival after radiation during starvation. Conclusions: These data reveal novel functional roles for AMPK in regulating mTOR signaling, cell cycle, survival and metabolic responses to IR.

The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism

DEFF Research Database (Denmark)

Birkel, Garrett W.; Ghosh, Amit; Kumar, Vinay S.

2017-01-01

analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed.Results: The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes......, it introduces the capability to use C-13 labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale C-13 Metabolic Flux Analysis (2S-C-13 MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable...... insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs.Conclusions: jQMM will facilitate the design...

Ruminant Nutrition Symposium: ruminant production and metabolic responses to heat stress.

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Baumgard, L H; Rhoads, R P

2012-06-01

Heat stress compromises efficient animal production by marginalizing nutrition, management, and genetic selection efforts to maximize performance endpoints. Modifying farm infrastructure has yielded modest success in mitigating heat stress-related losses, yet poor production during the summer remains arguably the costliest issue facing livestock producers. Reduced output (e.g., milk yield and muscle growth) during heat stress was traditionally thought to result from decreased nutrient intake (i.e., a classic biological response shared by all animals during environmental-induced hyperthermia). Our recent observations have begun to challenge this belief and indicate heat-stressed animals employ novel homeorhetic strategies to direct metabolic and fuel selection priorities independently of nutrient intake or energy balance. Alterations in systemic physiology support a shift in carbohydrate metabolism, evident by increased basal and stimulated circulating insulin concentrations. Perhaps most intriguing given the energetic shortfall of the heat-stressed animal is the apparent lack of basal adipose tissue mobilization coupled with a reduced responsiveness to lipolytic stimuli. Thus, the heat stress response markedly alters postabsorptive carbohydrate, lipid, and protein metabolism independently of reduced feed intake through coordinated changes in fuel supply and utilization by multiple tissues. Interestingly, the systemic, cellular, and molecular changes appear conserved amongst different species and physiological states. Ultimately, these changes result in the reprioritization of fuel selection during heat stress, which appears to be primarily responsible for reduced ruminant animal productivity during the warm summer months.

Metabolomics reveals differences in postprandial responses to breads and fasting metabolic characteristics associated with postprandial insulin demand in postmenopausal women.

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Moazzami, Ali A; Shrestha, Aahana; Morrison, David A; Poutanen, Kaisa; Mykkänen, Hannu

2014-06-01

Changes in serum metabolic profile after the intake of different food products (e.g., bread) can provide insight into their interaction with human metabolism. Postprandial metabolic responses were compared after the intake of refined wheat (RWB), whole-meal rye (WRB), and refined rye (RRB) breads. In addition, associations between the metabolic profile in fasting serum and the postprandial concentration of insulin in response to different breads were investigated. Nineteen postmenopausal women with normal fasting glucose and normal glucose tolerance participated in a randomized, controlled, crossover meal study. The test breads, RWB (control), RRB, and WRB, providing 50 g of available carbohydrate, were each served as a single meal. The postprandial metabolic profile was measured using nuclear magnetic resonance and targeted LC-mass spectrometry and was compared between different breads using ANOVA and multivariate models. Eight amino acids had a significant treatment effect (P insulin. Women with higher fasting concentrations of leucine and isoleucine and lower fasting concentrations of sphingomyelins and phosphatidylcholines had higher insulin responses despite similar glucose concentration after all kinds of bread (cross-validated ANOVA, P = 0.048). High blood concentration of branched-chain amino acids, i.e., leucine and isoleucine, has been associated with the increased risk of diabetes, which suggests that additional consideration should be given to bread proteins in understanding the beneficial health effects of different kinds of breads. The present study suggests that the fasting metabolic profile can be used to characterize the postprandial insulin demand in individuals with normal glucose metabolism that can be used for establishing strategies for the stratification of individuals in personalized nutrition. © 2014 American Society for Nutrition.

LKB1 promotes metabolic flexibility in response to energy stress.

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Parker, Seth J; Svensson, Robert U; Divakaruni, Ajit S; Lefebvre, Austin E; Murphy, Anne N; Shaw, Reuben J; Metallo, Christian M

2017-09-01

The Liver Kinase B1 (LKB1) tumor suppressor acts as a metabolic energy sensor to regulate AMP-activated protein kinase (AMPK) signaling and is commonly mutated in various cancers, including non-small cell lung cancer (NSCLC). Tumor cells deficient in LKB1 may be uniquely sensitized to metabolic stresses, which may offer a therapeutic window in oncology. To address this question we have explored how functional LKB1 impacts the metabolism of NSCLC cells using 13 C metabolic flux analysis. Isogenic NSCLC cells expressing functional LKB1 exhibited higher flux through oxidative mitochondrial pathways compared to those deficient in LKB1. Re-expression of LKB1 also increased the capacity of cells to oxidize major mitochondrial substrates, including pyruvate, fatty acids, and glutamine. Furthermore, LKB1 expression promoted an adaptive response to energy stress induced by anchorage-independent growth. Finally, this diminished adaptability sensitized LKB1-deficient cells to combinatorial inhibition of mitochondrial complex I and glutaminase. Together, our data implicate LKB1 as a major regulator of adaptive metabolic reprogramming and suggest synergistic pharmacological strategies for mitigating LKB1-deficient NSCLC tumor growth. Copyright © 2016. Published by Elsevier Inc.

Mechanisms of metabonomic for a gateway drug: nicotine priming enhances behavioral response to cocaine with modification in energy metabolism and neurotransmitter level.

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Hongyu Li

Full Text Available Nicotine, one of the most commonly used drugs, has become a major concern because tobacco serves as a gateway drug and is linked to illicit drug abuse, such as cocaine and marijuana. However, previous studies mainly focused on certain genes or neurotransmitters which have already been known to participate in drug addiction, lacking endogenous metabolic profiling in a global view. To further explore the mechanism by which nicotine modifies the response to cocaine, we developed two conditioned place preference (CPP models in mice. In threshold dose model, mice were pretreated with nicotine, followed by cocaine treatment at the dose of 2 mg/kg, a threshold dose of cocaine to induce CPP in mice. In high-dose model, mice were only treated with 20 mg/kg cocaine, which induced a significant CPP. (1H nuclear magnetic resonance based on metabonomics was used to investigate metabolic profiles of the nucleus accumbens (NAc and striatum. We found that nicotine pretreatment dramatically increased CPP induced by 2 mg/kg cocaine, which was similar to 20 mg/kg cocaine-induced CPP. Interestingly, metabolic profiles showed considerable overlap between these two models. These overlapped metabolites mainly included neurotransmitters as well as the molecules participating in energy homeostasis and cellular metabolism. Our results show that the reinforcing effect of nicotine on behavioral response to cocaine may attribute to the modification of some specific metabolites in NAc and striatum, thus creating a favorable metabolic environment for enhancing conditioned rewarding effect of cocaine. Our findings provide an insight into the effect of cigarette smoking on cocaine dependence and the underlying mechanism.

Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model.

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Dash, Ranjan K; Li, Yanjun; Kim, Jaeyeon; Beard, Daniel A; Saidel, Gerald M; Cabrera, Marco E

2008-09-09

Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and

Dynamical feedback between circadian clock and sucrose availability explains adaptive response of starch metabolism to various photoperiods

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Francois Gabriel Feugier

2013-01-01

Full Text Available Plants deal with resource management during all their life. During the day they feed on photosynthetic carbon, sucrose, while storing a part into starch for night use. Careful control of carbon partitioning, starch degradation and sucrose export rates is crucial to avoid carbon starvation, insuring optimal growth whatever the photoperiod. Efficient regulation of these key metabolic rates can give an evolutionary advantage to plants. Here we propose a model of adaptive starch metabolism in response to various photoperiods. We assume the three key metabolic rates to be circadian regulated in leaves and that their phases of oscillations are shifted in response to sucrose starvation. We performed gradient descents for various photoperiod conditions to find the corresponding optimal sets of phase shifts that minimize starvation. Results at convergence were all consistent with experimental data: i diurnal starch profile showed linear increase during the day and linear decrease at night; ii shorter photoperiod tended to increase starch synthesis speed while decreasing its degradation speed during the longer night; iii sudden early dusk showed slower starch degradation during the longer night. Profiles that best explained observations corresponded to circadian regulation of all rates. This theoretical study would establish a framework for future research on feedback between starch metabolism and circadian clock as well as plant productivity.

Radiographic and metabolic response rates following image-guided stereotactic radiotherapy for lung tumors

International Nuclear Information System (INIS)

Mohammed, Nasiruddin; Grills, Inga S.; Wong, Ching-Yee Oliver; Galerani, Ana Paula; Chao, Kenneth; Welsh, Robert; Chmielewski, Gary; Yan Di; Kestin, Larry L.

2011-01-01

Purpose: To evaluate radiographic and metabolic response after stereotactic body radiotherapy (SBRT) for early lung tumors. Materials and methods: Thirty-nine tumors were treated prospectively with SBRT (dose = 48-60 Gy, 4-5 Fx). Thirty-six cases were primary NSCLC (T1N0 = 67%; T2N0 = 25%); three cases were solitary metastases. Patients were followed using CT and PET at 6, 16, and 52 weeks post-SBRT, with CT follow-up thereafter. RECIST and EORTC criteria were used to evaluate CT and PET responses. Results: At median follow-up of 9 months (0.4-26), RECIST complete response (CR), partial response (PR), and stable disease (SD) rates were 3%, 43%, 54% at 6 weeks; 15%, 38%, 46% at 16 weeks; 27%, 64%, 9% at 52 weeks. Mean baseline tumor volume was reduced by 46%, 70%, 87%, and 96%, respectively at 6, 16, 52, and 72 weeks. Mean baseline maximum standardized uptake value (SUV) was 8.3 (1.1-20.3) and reduced to 3.4, 3.0, and 3.7 at 6, 16, and 52 weeks after SBRT. EORTC metabolic CR/PR, SD, and progressive disease rates were 67%, 22%, 11% at 6 weeks; 86%, 10%, 3% at 16 weeks; 95%, 5%, 0% at 52 weeks. Conclusions: SBRT yields excellent RECIST and EORTC based response. Metabolic response is rapid however radiographic response occurs even after 1-year post treatment.

Cardiovascular Changes in Animal Models of Metabolic Syndrome

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Alexandre M. Lehnen

2013-01-01

Full Text Available Metabolic syndrome has been defined as a group of risk factors that directly contribute to the development of cardiovascular disease and/or type 2 diabetes. Insulin resistance seems to have a fundamental role in the genesis of this syndrome. Over the past years to the present day, basic and translational research has used small animal models to explore the pathophysiology of metabolic syndrome and to develop novel therapies that might slow the progression of this prevalent condition. In this paper we discuss the animal models used for the study of metabolic syndrome, with particular focus on cardiovascular changes, since they are the main cause of death associated with the condition in humans.

The metabolic cost of mounting an immune response in male brown anoles (Anolis sagrei).

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Cox, Christian L; Peaden, Robert T; Cox, Robert M

2015-09-09

The tradeoff between reproduction and survival is central to life-history theory and is thought to reflect underlying energetic tradeoffs between reproduction and self-maintenance. Immune responses to parasites and pathogens are important components of self-maintenance in many species, but whether these defenses impose significant energetic costs has only been tested in a handful of organisms. We tested for a metabolic cost of mounting an immune response in the male brown anole (Anolis sagrei), a lizard in which we have previously shown that reproduction causes a marked reduction in immune response to the novel antigen phytohaemagglutinin (PHA). We treated captive male anoles with a subcutaneous injection of either PHA, which induces an immune response that manifests as localized swelling, or saline vehicle as a control. Prior to injection and at 24, 48, and 72 hr post-injection, we measured swelling at the site of injection and whole-animal resting metabolic rate (RMR) using stop-flow respirometry. Although we detected a robust swelling response to PHA at 24, 48, and 72 hr post-injection, mean RMR did not differ between treatments at any of these time points. However, within the PHA treatment group, RMR increased with the extent of swelling, suggesting a variable metabolic cost that scales with the magnitude of the induced immune response. Although individual anoles varied considerably in the extent to which they responded to PHA challenge, our results suggest that an immune response can impose a substantial metabolic cost (potentially as much as 63% above baseline RMR) for individuals that do respond maximally. J. Exp. Zool. 9999A:XX-XX, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Mechanistic modeling of aberrant energy metabolism in human disease

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Vineet eSangar

2012-10-01

Full Text Available Dysfunction in energy metabolism—including in pathways localized to the mitochondria—has been implicated in the pathogenesis of a wide array of disorders, ranging from cancer to neurodegenerative diseases to type II diabetes. The inherent complexities of energy and mitochondrial metabolism present a significant obstacle in the effort to understand the role that these molecular processes play in the development of disease. To help unravel these complexities, systems biology methods have been applied to develop an array of computational metabolic models, ranging from mitochondria-specific processes to genome-scale cellular networks. These constraint-based models can efficiently simulate aspects of normal and aberrant metabolism in various genetic and environmental conditions. Development of these models leverages—and also provides a powerful means to integrate and interpret—information from a wide range of sources including genomics, proteomics, metabolomics, and enzyme kinetics. Here, we review a variety of mechanistic modeling studies that explore metabolic functions, deficiency disorders, and aberrant biochemical pathways in mitochondria and related regions in the cell.

Integrating Cellular Metabolism into a Multiscale Whole-Body Model

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Krauss, Markus; Schaller, Stephan; Borchers, Steffen; Findeisen, Rolf; Lippert, Jörg; Kuepfer, Lars

2012-01-01

Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development. PMID:23133351

It must be my metabolism: Metabolic control of mind

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Dana M Small

2014-07-01

participant ingested the same caloric dose during conditioning, changes in plasma glucose depended upon individual differences in glucose absorption/metabolism. Therefore, these findings provide indirect, and yet convincing, support for our hypothesis that glucose metabolism regulates response to calorie-predictive flavors in brain reward circuits. We can therefore conclude that, at least for carbohydrates, responses to calorie predictive food cues reflect the learned association between the cue and its ability to result in a change in blood glucose. This finding has important implications for understanding how the modern food environment promotes weight gain. Carbohydrates now come in forms and doses not experienced during our evolutionary past. Not only are calories increased, but the way in which they are metabolized differs. For example, calories ingested in liquid form are trafficked through the gut faster than solids (e.g. 18. Might this influence metabolic regulation of reward circuits? Certainly it stands to reason that larger loads delivered more quickly to the circulation might increase the metabolic impact and hence more efficiently engage reward circuits to enhance food cue reactivity and promote eating in the absence of hunger. In summary, our result indicates that, as in the rodent model, metabolic response drives the reinforcement potency of carbohydrates and regulates food cue reactivity. We conclude that not only are modern foods more caloric, but in addition their increased metabolic impact drives reward circuits and may therefore promote intake by enhancing food cue reactivity. Our finding further suggests that metabolic regulation of reward circuits may differ in individuals with altered glucose metabolism, such as type II diabetes, offering a potential mechanism by which they become susceptible to weight gain.

GENOME-BASED MODELING AND DESIGN OF METABOLIC INTERACTIONS IN MICROBIAL COMMUNITIES

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Radhakrishnan Mahadevan

2012-10-01

With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae.

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Baroukh, Caroline; Muñoz-Tamayo, Rafael; Steyer, Jean-Philippe; Bernard, Olivier

2014-01-01

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.

DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae.

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Caroline Baroukh

Full Text Available Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.

Effect of radiographic contrast agents on leukocyte metabolic response

International Nuclear Information System (INIS)

Hernanz-Schulman, M.; Vanholder, R.; Waterloos, M.A.; Hakim, R.; Schulman, G.

2000-01-01

Barium, at clinical dilutions, causes a significant increase of baseline ''resting state'' phagocytic activity, which in turn leads to significant blunting of subsequent response to phagocytic challenge and adversely affects the response to all bacteria tested. There is no baseline activation of leukocytes by the water-soluble media, although there was some inhibition (rather than activation) of leukocyte metabolic activity. The effect of the water-soluble media in bacteria was more complex (although inhibition is minor compared to barium). Our data demonstrate that barium is a significant activator of phagocytic cells, which results in deactivation of phagocytic response when challenged; these data serve to explain the enhanced adverse effect of barium in cased of fecal peritonitis. (orig.)

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.

MetaFluxNet: the management of metabolic reaction information and quantitative metabolic flux analysis.

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Lee, Dong-Yup; Yun, Hongsoek; Park, Sunwon; Lee, Sang Yup

2003-11-01

MetaFluxNet is a program package for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes in an interactive and customized way. It allows users to interpret and examine metabolic behavior in response to genetic and/or environmental modifications. As a result, quantitative in silico simulations of metabolic pathways can be carried out to understand the metabolic status and to design the metabolic engineering strategies. The main features of the program include a well-developed model construction environment, user-friendly interface for metabolic flux analysis (MFA), comparative MFA of strains having different genotypes under various environmental conditions, and automated pathway layout creation. http://mbel.kaist.ac.kr/ A manual for MetaFluxNet is available as PDF file.

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

Model-based design of bistable cell factories for metabolic engineering.

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Srinivasan, Shyam; Cluett, William R; Mahadevan, Radhakrishnan

2018-04-15

Metabolism can exhibit dynamic phenomena like bistability due to the presence of regulatory motifs like the positive feedback loop. As cell factories, microorganisms with bistable metabolism can have a high and a low product flux at the two stable steady states, respectively. The exclusion of metabolic regulation and network dynamics limits the ability of pseudo-steady state stoichiometric models to detect the presence of bistability, and reliably assess the outcomes of design perturbations to metabolic networks. Using kinetic models of metabolism, we assess the change in the bistable characteristics of the network, and suggest designs based on perturbations to the positive feedback loop to enable the network to produce at its theoretical maximum rate. We show that the most optimal production design in parameter space, for a small bistable metabolic network, may exist at the boundary of the bistable region separating it from the monostable region of low product fluxes. The results of our analysis can be broadly applied to other bistable metabolic networks with similar positive feedback network topologies. This can complement existing model-based design strategies by providing a smaller number of feasible designs that need to be tested in vivo. http://lmse.biozone.utoronto.ca/downloads/. krishna.mahadevan@utoronto.ca. Supplementary data are available at Bioinformatics online.

Caenorhabditis elegans: A Useful Model for Studying Metabolic Disorders in Which Oxidative Stress Is a Contributing Factor

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Elizabeth Moreno-Arriola

2014-01-01

Full Text Available Caenorhabditis elegans is a powerful model organism that is invaluable for experimental research because it can be used to recapitulate most human diseases at either the metabolic or genomic level in vivo. This organism contains many key components related to metabolic and oxidative stress networks that could conceivably allow us to increase and integrate information to understand the causes and mechanisms of complex diseases. Oxidative stress is an etiological factor that influences numerous human diseases, including diabetes. C. elegans displays remarkably similar molecular bases and cellular pathways to those of mammals. Defects in the insulin/insulin-like growth factor-1 signaling pathway or increased ROS levels induce the conserved phase II detoxification response via the SKN-1 pathway to fight against oxidative stress. However, it is noteworthy that, aside from the detrimental effects of ROS, they have been proposed as second messengers that trigger the mitohormetic response to attenuate the adverse effects of oxidative stress. Herein, we briefly describe the importance of C. elegans as an experimental model system for studying metabolic disorders related to oxidative stress and the molecular mechanisms that underlie their pathophysiology.

Necrosis-Driven Systemic Immune Response Alters SAM Metabolism through the FOXO-GNMT Axis

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Fumiaki Obata

2014-05-01

Full Text Available Sterile inflammation triggered by endogenous factors is thought to contribute to the pathogenesis of acute and chronic inflammatory diseases. Here, we demonstrate that apoptosis-deficient mutants spontaneously develop a necrosis-driven systemic immune response in Drosophila and provide an in vivo model for studying the organismal response to sterile inflammation. Metabolomic analysis of hemolymph from apoptosis-deficient mutants revealed increased sarcosine and reduced S-adenosyl-methionine (SAM levels due to glycine N-methyltransferase (Gnmt upregulation. We showed that Gnmt was elevated in response to Toll activation induced by the local necrosis of wing epidermal cells. Necrosis-driven inflammatory conditions induced dFoxO hyperactivation, leading to an energy-wasting phenotype. Gnmt was cell-autonomously upregulated by dFoxO in the fat body as a possible rheostat for controlling energy loss, which functioned during fasting as well as inflammatory conditions. We propose that the dFoxO-Gnmt axis is essential for the maintenance of organismal SAM metabolism and energy homeostasis.

Next-generation genome-scale models for metabolic engineering

DEFF Research Database (Denmark)

King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.

2015-01-01

Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....

Metabolic responses of primary and transformed cells to intracellular Listeria monocytogenes.

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Nadine Gillmaier

Full Text Available The metabolic response of host cells, in particular of primary mammalian cells, to bacterial infections is poorly understood. Here, we compare the carbon metabolism of primary mouse macrophages and of established J774A.1 cells upon Listeria monocytogenes infection using (13C-labelled glucose or glutamine as carbon tracers. The (13C-profiles of protein-derived amino acids from labelled host cells and intracellular L. monocytogenes identified active metabolic pathways in the different cell types. In the primary cells, infection with live L. monocytogenes increased glycolytic activity and enhanced flux of pyruvate into the TCA cycle via pyruvate dehydrogenase and pyruvate carboxylase, while in J774A.1 cells the already high glycolytic and glutaminolytic activities hardly changed upon infection. The carbon metabolism of intracellular L. monocytogenes was similar in both host cells. Taken together, the data suggest that efficient listerial replication in the cytosol of the host cells mainly depends on the glycolytic activity of the hosts.

Photoacoustic microscopy of cerebral hemodynamic and oxygen-metabolic responses to anesthetics

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Cao, Rui; Li, Jun; Ning, Bo; Sun, Naidi; Wang, Tianxiong; Zuo, Zhiyi; Hu, Song

2017-02-01

General anesthetics are known to have profound effects on cerebral hemodynamics and neuronal activities. However, it remains a challenge to directly assess anesthetics-induced hemodynamic and oxygen-metabolic changes from the true baseline under wakefulness at the microscopic level, due to the lack of an enabling technology for high-resolution functional imaging of the awake mouse brain. To address this challenge, we have developed head-restrained photoacoustic microscopy (PAM), which enables simultaneous imaging of the cerebrovascular anatomy, total concentration and oxygen saturation of hemoglobin (CHb and sO2), and blood flow in awake mice. From these hemodynamic measurements, two important metabolic parameters, oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2), can be derived. Side-by-side comparison of the mouse brain under wakefulness and anesthesia revealed multifaceted cerebral responses to isoflurane, a volatile anesthetic widely used in preclinical research and clinical practice. Key observations include elevated cerebral blood flow (CBF) and reduced oxygen extraction and metabolism.

Seaweed supplements normalise metabolic, cardiovascular and liver responses in high-carbohydrate, high-fat fed rats.

Science.gov (United States)

Kumar, Senthil Arun; Magnusson, Marie; Ward, Leigh C; Paul, Nicholas A; Brown, Lindsay

2015-02-02

Increased seaweed consumption may be linked to the lower incidence of metabolic syndrome in eastern Asia. This study investigated the responses to two tropical green seaweeds, Ulva ohnoi (UO) and Derbesia tenuissima (DT), in a rat model of human metabolic syndrome. Male Wistar rats (330-340 g) were fed either a corn starch-rich diet or a high-carbohydrate, high-fat diet with 25% fructose in drinking water, for 16 weeks. High-carbohydrate, high-fat diet-fed rats showed the signs of metabolic syndrome leading to abdominal obesity, cardiovascular remodelling and non-alcoholic fatty liver disease. Food was supplemented with 5% dried UO or DT for the final 8 weeks only. UO lowered total final body fat mass by 24%, systolic blood pressure by 29 mmHg, and improved glucose utilisation and insulin sensitivity. In contrast, DT did not change total body fat mass but decreased plasma triglycerides by 38% and total cholesterol by 17%. UO contained 18.1% soluble fibre as part of 40.9% total fibre, and increased magnesium, while DT contained 23.4% total fibre, essentially as insoluble fibre. UO was more effective in reducing metabolic syndrome than DT, possibly due to the increased intake of soluble fibre and magnesium.

Seaweed Supplements Normalise Metabolic, Cardiovascular and Liver Responses in High-Carbohydrate, High-Fat Fed Rats

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Senthil Arun Kumar

2015-02-01

Full Text Available Increased seaweed consumption may be linked to the lower incidence of metabolic syndrome in eastern Asia. This study investigated the responses to two tropical green seaweeds, Ulva ohnoi (UO and Derbesia tenuissima (DT, in a rat model of human metabolic syndrome. Male Wistar rats (330–340 g were fed either a corn starch-rich diet or a high-carbohydrate, high-fat diet with 25% fructose in drinking water, for 16 weeks. High-carbohydrate, high-fat diet-fed rats showed the signs of metabolic syndrome leading to abdominal obesity, cardiovascular remodelling and non-alcoholic fatty liver disease. Food was supplemented with 5% dried UO or DT for the final 8 weeks only. UO lowered total final body fat mass by 24%, systolic blood pressure by 29 mmHg, and improved glucose utilisation and insulin sensitivity. In contrast, DT did not change total body fat mass but decreased plasma triglycerides by 38% and total cholesterol by 17%. UO contained 18.1% soluble fibre as part of 40.9% total fibre, and increased magnesium, while DT contained 23.4% total fibre, essentially as insoluble fibre. UO was more effective in reducing metabolic syndrome than DT, possibly due to the increased intake of soluble fibre and magnesium.

Seaweed Supplements Normalise Metabolic, Cardiovascular and Liver Responses in High-Carbohydrate, High-Fat Fed Rats

Science.gov (United States)

Kumar, Senthil Arun; Magnusson, Marie; Ward, Leigh C.; Paul, Nicholas A.; Brown, Lindsay

2015-01-01

Increased seaweed consumption may be linked to the lower incidence of metabolic syndrome in eastern Asia. This study investigated the responses to two tropical green seaweeds, Ulva ohnoi (UO) and Derbesia tenuissima (DT), in a rat model of human metabolic syndrome. Male Wistar rats (330–340 g) were fed either a corn starch-rich diet or a high-carbohydrate, high-fat diet with 25% fructose in drinking water, for 16 weeks. High-carbohydrate, high-fat diet-fed rats showed the signs of metabolic syndrome leading to abdominal obesity, cardiovascular remodelling and non-alcoholic fatty liver disease. Food was supplemented with 5% dried UO or DT for the final 8 weeks only. UO lowered total final body fat mass by 24%, systolic blood pressure by 29 mmHg, and improved glucose utilisation and insulin sensitivity. In contrast, DT did not change total body fat mass but decreased plasma triglycerides by 38% and total cholesterol by 17%. UO contained 18.1% soluble fibre as part of 40.9% total fibre, and increased magnesium, while DT contained 23.4% total fibre, essentially as insoluble fibre. UO was more effective in reducing metabolic syndrome than DT, possibly due to the increased intake of soluble fibre and magnesium. PMID:25648511

Microbial physiology-based model of ethanol metabolism in subsurface sediments

Science.gov (United States)

Jin, Qusheng; Roden, Eric E.

2011-07-01

A biogeochemical reaction model was developed based on microbial physiology to simulate ethanol metabolism and its influence on the chemistry of anoxic subsurface environments. The model accounts for potential microbial metabolisms that degrade ethanol, including those that oxidize ethanol directly or syntrophically by reducing different electron acceptors. Out of the potential metabolisms, those that are active in the environment can be inferred by fitting the model to experimental observations. This approach was applied to a batch sediment slurry experiment that examined ethanol metabolism in uranium-contaminated aquifer sediments from Area 2 at the U.S. Department of Energy Field Research Center in Oak Ridge, TN. According to the simulation results, complete ethanol oxidation by denitrification, incomplete ethanol oxidation by ferric iron reduction, ethanol fermentation to acetate and H 2, hydrogenotrophic sulfate reduction, and acetoclastic methanogenesis: all contributed significantly to the degradation of ethanol in the aquifer sediments. The assemblage of the active metabolisms provides a frame work to explore how ethanol amendment impacts the chemistry of the environment, including the occurrence and levels of uranium. The results can also be applied to explore how diverse microbial metabolisms impact the progress and efficacy of bioremediation strategies.

Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

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Sriram Chandrasekaran

2017-12-01

Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

Integrating cellular metabolism into a multiscale whole-body model.

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Markus Krauss

Full Text Available Cellular metabolism continuously processes an enormous range of external compounds into endogenous metabolites and is as such a key element in human physiology. The multifaceted physiological role of the metabolic network fulfilling the catalytic conversions can only be fully understood from a whole-body perspective where the causal interplay of the metabolic states of individual cells, the surrounding tissue and the whole organism are simultaneously considered. We here present an approach relying on dynamic flux balance analysis that allows the integration of metabolic networks at the cellular scale into standardized physiologically-based pharmacokinetic models at the whole-body level. To evaluate our approach we integrated a genome-scale network reconstruction of a human hepatocyte into the liver tissue of a physiologically-based pharmacokinetic model of a human adult. The resulting multiscale model was used to investigate hyperuricemia therapy, ammonia detoxification and paracetamol-induced toxication at a systems level. The specific models simultaneously integrate multiple layers of biological organization and offer mechanistic insights into pathology and medication. The approach presented may in future support a mechanistic understanding in diagnostics and drug development.

Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

Energy Technology Data Exchange (ETDEWEB)

Liao, James C. [Univ. of California, Los Angeles, CA (United States)

2016-10-01

Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

Cerebral Metabolic Changes Related to Oxidative Metabolism in a Model of Bacterial Meningitis Induced by Lipopolysaccharide

DEFF Research Database (Denmark)

Munk, Michael; Rom Poulsen, Frantz; Larsen, Lykke

2018-01-01

BACKGROUND: Cerebral mitochondrial dysfunction is prominent in the pathophysiology of severe bacterial meningitis. In the present study, we hypothesize that the metabolic changes seen after intracisternal lipopolysaccharide (LPS) injection in a piglet model of meningitis is compatible...... with mitochondrial dysfunction and resembles the metabolic patterns seen in patients with bacterial meningitis. METHODS: Eight pigs received LPS injection in cisterna magna, and four pigs received NaCl in cisterna magna as a control. Biochemical variables related to energy metabolism were monitored by intracerebral...... dysfunction with increasing cerebral LPR due to increased lactate and normal pyruvate, PbtO2, and ICP. The metabolic pattern resembles the one observed in patients with bacterial meningitis. Metabolic monitoring in these patients is feasible to monitor for cerebral metabolic derangements otherwise missed...

The contribution of mathematical modeling to understanding the dynamic aspects of rumen metabolism

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André Bannink

2016-11-01

Full Text Available All rumen models cover the main drivers of variation in rumen function, which are feed intake, the differences between feedstuffs and feeds in their intrinsic rumen degradation characteristics, and fractional outflow rate of fluid and particulate matter. Dynamic modeling approaches are best suited to the prediction of more nuanced responses in rumen metabolism, and represent the dynamics of the interaction between substrates and micro-organisms and inter-microbial interactions. The concepts of dynamics are discussed for the case of rumen starch digestion as influenced by starch intake rate and frequency of feed intake, and for the case of fermentation of fiber in the large intestine. Adding representations of new functional classes of micro-organisms (i.e. with new characteristics from the perspective of whole rumen function in rumen models only delivers new insights if complemented by the dynamics of their interactions with other functional classes. Rumen fermentation conditions have to be represented due to their profound impact on the dynamics of substrate degradation and microbial metabolism. Although the importance of rumen acidity is generally acknowledged, more emphasis is needed on predicting its variation as well as variation in the processes that underlie rumen fluid dynamics. The rumen wall has an important role in adapting to rapid changes in the rumen environment, clearing of volatile fatty acids (VFA, and maintaining rumen pH within limits. Dynamics of rumen wall epithelia and its role in VFA absorption needs to be better represented in models which aim to predict rumen responses across nutritional or physiological states. For a detailed prediction of rumen N balance there is merit in a dynamic modeling approach compared to the static approaches adopted in current protein evaluation systems. Improvement is needed on previous attempts to predict rumen VFA profiles, and this should be pursued by introducing factors that relate more

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 responses to exogenous ghrelin in obesity and early after Roux-en-Y gastric bypass in humans.

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Tamboli, Robyn A; Antoun, Joseph; Sidani, Reem M; Clements, Austin; Harmata, Emily E; Marks-Shulman, Pam; Gaylinn, Bruce D; Williams, Brandon; Clements, Ronald H; Albaugh, Vance L; Abumrad, Naji N

2017-09-01

Ghrelin is a gastric-derived hormone that stimulates growth hormone (GH) secretion and has a multi-faceted role in the regulation of energy homeostasis, including glucose metabolism. Circulating ghrelin concentrations are modulated in response to nutritional status, but responses to ghrelin in altered metabolic states are poorly understood. We investigated the metabolic effects of ghrelin in obesity and early after Roux-en-Y gastric bypass (RYGB). We assessed central and peripheral metabolic responses to acyl ghrelin infusion (1 pmol kg -1  min -1 ) in healthy, lean subjects (n = 9) and non-diabetic, obese subjects (n = 9) before and 2 weeks after RYGB. Central responses were assessed by GH and pancreatic polypeptide (surrogate for vagal activity) secretion. Peripheral responses were assessed by hepatic and skeletal muscle insulin sensitivity during a hyperinsulinaemic-euglycaemic clamp. Ghrelin-stimulated GH secretion was attenuated in obese subjects, but was restored by RYGB to a response similar to that of lean subjects. The heightened pancreatic polypeptide response to ghrelin infusion in the obese was attenuated after RYGB. Hepatic glucose production and hepatic insulin sensitivity were not altered by ghrelin infusion in RYGB subjects. Skeletal muscle insulin sensitivity was impaired to a similar degree in lean, obese and post-RYGB individuals in response to ghrelin infusion. These data suggest that obesity is characterized by abnormal central, but not peripheral, responsiveness to ghrelin that can be restored early after RYGB before significant weight loss. Further work is necessary to fully elucidate the role of ghrelin in the metabolic changes that occur in obesity and following RYGB. © 2017 John Wiley & Sons Ltd.

L-carnitine: a partner between immune response and lipid metabolism ?

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Giuseppe Famularo

1993-01-01

Full Text Available The authors demonstrated that in vivo administered L-carnitine strongly ameliorated the immune response in both healthy individuals receiving Intralipid and ageing subjects with cardiovascular diseases, as shown by the enhancement of mixed lymphocyte reaction. Notably, in the latter group L-carnitine treatment also resulted in a significant reduction of serum levels of both cholesterol and triglycerides. Therefore, the hypothesis is that L-carnitine supplementation could ameliorate both the dysregulated immune response and the abnormal lipid metabolism in several conditions.

Whole-body CO2 production as an index of the metabolic response to sepsis

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Whole-body carbon dioxide (CO2) production (RaCO2) is an index of substrate oxidation and energy expenditure; therefore, it may provide information about the metabolic response to sepsis. Using stable isotope techniques, we determined RaCO2 and its relationship to protein and glucose metabolism in m...

Dynamic optimal metabolic control theory: a cybernetic approach for modelling of the central nitrogen metabolism of S. cerevisiae

NARCIS (Netherlands)

Riel, van N.A.W.; Giuseppin, M.L.F.; Verrips, C.T.

2000-01-01

The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the

The Metabolic Response to Stress and Infection in Critically Ill Children: The Opportunity of an Individualized Approach

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Valentina De Cosmi

2017-09-01

Full Text Available The metabolic response to stress and infection is closely related to the corresponding requirements of energy and nutrients. On a general level, the response is driven by a complex endocrine network and related to the nature and severity of the insult. On an individual level, the effects of nutritional interventions are highly variable and a possible source of complications. This narrative review aims to discuss the metabolic changes in critically-ill children and the potential of developing personalized nutritional interventions. Through a literature search strategy, we have investigated the importance of blood glucose levels, the nutritional aspects of the different phases of acute stress response, and the reliability of the available tools to assess the energy expenditure. The dynamics of metabolism during stressful events reveals the difficult balance between risk of hypo- or hyperglycemia and under- or overfeeding. Within this context, individualized and accurate measurement of energy expenditure may help in defining the metabolic needs of patients. Given the variability of the metabolic response in critical conditions, randomized clinical studies in ill children are needed to evaluate the effect of individualized nutritional intervention on health outcomes.

Hypothalamic miR-219 regulates individual metabolic differences in response to diet-induced weight cycling

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Mariana Schroeder

2018-03-01

Full Text Available Consumption of a low calorie diet is the most common approach to lose weight. While generally effective at first, it is frequently followed by a relapse where the pre-diet weight is regained, and often exceeded. This pattern of repeated weight loss/regain is referred to as weight cycling and the resulting metabolic response varies greatly between individuals. Objective: We attempted to address the issue of individual differences in the response to weight cycling in male mice. Methods: We first exposed adult wild type mice to repeated cycles of high/low fat food. Next, using a lentiviral approach, we knocked-down or over-expressed miR-219 in the ventromedial hypothalamus (VMH of an additional mouse cohort and performed a full metabolic assessment. Results: Exposure of wild type males to weight cycling resulted in the division of the cohort into subsets of resistant versus metabolic-syndrome-prone (MS animals, which differed in their metabolic profile and hypothalamic miR-219 levels. Lentiviral knock-down of miR-219 in the VMH led to exacerbation of metabolic syndrome. In contrast, over-expression of miR-219 resulted in moderation of the metabolic syndrome phenotype. Conclusions: Our results suggest a role for miR-219 in the mediation of the metabolic phenotype resulting from repeated weight cycling. Keywords: Weight cycling, Metabolic syndrome, miRNAs, Ventromedial hypothalamus, High fat diet, Diabetes

Computational modeling to predict nitrogen balance during acute metabolic decompensation in patients with urea cycle disorders.

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MacLeod, Erin L; Hall, Kevin D; McGuire, Peter J

2016-01-01

Nutritional management of acute metabolic decompensation in amino acid inborn errors of metabolism (AA IEM) aims to restore nitrogen balance. While nutritional recommendations have been published, they have never been rigorously evaluated. Furthermore, despite these recommendations, there is a wide variation in the nutritional strategies employed amongst providers, particularly regarding the inclusion of parenteral lipids for protein-free caloric support. Since randomized clinical trials during acute metabolic decompensation are difficult and potentially dangerous, mathematical modeling of metabolism can serve as a surrogate for the preclinical evaluation of nutritional interventions aimed at restoring nitrogen balance during acute decompensation in AA IEM. A validated computational model of human macronutrient metabolism was adapted to predict nitrogen balance in response to various nutritional interventions in a simulated patient with a urea cycle disorder (UCD) during acute metabolic decompensation due to dietary non-adherence or infection. The nutritional interventions were constructed from published recommendations as well as clinical anecdotes. Overall, dextrose alone (DEX) was predicted to be better at restoring nitrogen balance and limiting nitrogen excretion during dietary non-adherence and infection scenarios, suggesting that the published recommended nutritional strategy involving dextrose and parenteral lipids (ISO) may be suboptimal. The implications for patients with AA IEM are that the medical course during acute metabolic decompensation may be influenced by the choice of protein-free caloric support. These results are also applicable to intensive care patients undergoing catabolism (postoperative phase or sepsis), where parenteral nutritional support aimed at restoring nitrogen balance may be more tailored regarding metabolic fuel selection.

Effect of radiographic contrast agents on leukocyte metabolic response

Energy Technology Data Exchange (ETDEWEB)

Hernanz-Schulman, M. [Dept. of Pediatric Radiology, Vanderbilt Children' s Hospital, Nashville, TN (United States); Vanholder, R.; Waterloos, M.A. [Dept. of Internal Medicine, Nephrology Section, University Hospital, Gent (Belgium); Hakim, R.; Schulman, G. [Department of Nephrology, Vanderbilt University Medical Center, Nashville, TN (United States)

2000-06-01

Barium, at clinical dilutions, causes a significant increase of baseline ''resting state'' phagocytic activity, which in turn leads to significant blunting of subsequent response to phagocytic challenge and adversely affects the response to all bacteria tested. There is no baseline activation of leukocytes by the water-soluble media, although there was some inhibition (rather than activation) of leukocyte metabolic activity. The effect of the water-soluble media in bacteria was more complex (although inhibition is minor compared to barium). Our data demonstrate that barium is a significat activator of phagocytic cells, which results in deactivation of phagocytic response when challenged; these dsata serve to explain the enhanced adverse effect of barium in cased of fecal peritonitis. (orig.)

Investigating the Cellular and Metabolic Responses of World-Class Canoeists Training: A Sportomics Approach

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Wagner Santos Coelho

2016-11-01

Full Text Available (1 Background: We have been using the Sportomics approach to evaluate biochemical and hematological changes in response to exercise. The aim of this study was to evaluate the metabolic and hematologic responses of world-class canoeists during a training session; (2 Methods: Blood samples were taken at different points and analyzed for their hematological properties, activities of selected enzymes, hormones, and metabolites; (3 Results: Muscle stress biomarkers were elevated in response to exercise which correlated with modifications in the profile of white blood cells, where a leukocyte rise was observed after the canoe session. These results were accompanied by an increase in other exercise intensity parameters such as lactatemia and ammonemia. Adrenocorticotropic hormone and cortisol increased during the exercise sessions. The acute rise in both erythrocytes and white blood profile were probably due to muscle cell damage, rather than hepatocyte integrity impairment; (4 Conclusion: The cellular and metabolic responses found here, together with effective nutrition support, are crucial to understanding the effects of exercise in order to assist in the creation of new training and recovery planning. Also we show that Sportomics is a primal tool for training management and performance improvement, as well as to the understanding of metabolic response to exercise.

14C and tritium dynamics in wild mammals: a metabolic model

International Nuclear Information System (INIS)

Galeriu, D.; Beresford, N.A.; Melintescu, A.; Crout, N.M.J.; Takeda, H.

2004-01-01

The protection of biota from ionising radiations needs reliable predictions of radionuclide dynamics in wild animals. Data specific for many wild animals radionuclide combinations is lacking and a number of approaches including allometry have been proposed to address this. However, for 14 C and tritium, which are integral components of animals tissues and their diets, a different approach is needed in the absence of experimental data. Here we propose a metabolically based model which can be parameterized predominantly on the basis of published metabolic data. We begin with a metabolic definition of the 14 C and OBT loss rate (assumed to be the same) from the whole body and also specific organs, using available information on field metabolic rate and body composition. The mammalian body is conceptually partitioned into compartments (body water, viscera, adipose, muscle, blood and remainder) and a simple model defined using net maintenance and growth needs of mammals. Intake and excretion, and transfer to body water are modelled using basic metabolic knowledge and published relationships. The model is tested with data from studies using rats and sheep. It provides a reliable prediction for whole body and muscle activity concentrations without the requirement for any calibration specific to 3 H and 14 C. Predictions from the model for representative wild mammals (as selected to be reference organisms within international programmes) are presented. Potential developments of a metabolic model for birds and the application of our work to human food chain modelling are also discussed. (author)

Dynamic Responses of Phosphorus Metabolism to Acute and Chronic Dietary Phosphorus-Limitation in Daphnia

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Nicole D. Wagner

2017-06-01

Full Text Available Food quality is highly dynamic within lake ecosystems and varies spatially and temporally over the growing season. Consumers may need to continuously adjust their metabolism in response to this variation in dietary nutrient content. However, the rates of metabolic responses to changes in food nutrient content has received little direct study. Here, we examine responses in two metabolic phosphorus (P pools, ribonucleic acids (RNA and adenosine triphosphate (ATP, along with body mass and body P content in Daphnia magna exposed to chronic and acute dietary P-limitation. First, we examined food quality effects on animals consuming different food carbon (C:P quality over a 14 day period. Then, we raised daphnids on one food quality for 4 days, switched them to contrasting dietary treatments, and measured changes in their metabolic responses at shorter time-scales (over 48 h. Animal P, RNA, and ATP content all changed through ontogeny with adults containing relatively less of these pools with increasing body mass. Irrespective of age, Daphnia consuming high C:P diets had lower body %P, %RNA, %ATP, and mass compared to animals eating low C:P diets. Diet switching experiments revealed diet dependent changes in body %P, %RNA, %ATP, and animal mass within 48 h. We found that Daphnia switched from low to high C:P diets had some metabolic buffering capacity with decreases in body %P occurring after 24 h but mass remaining similar to initial diet conditions for 36 h after the diet switch. Switching Daphnia from low to high C:P diets caused a decrease in the RNA:P ratio after 48 h. Daphnia switched from high to low C:P diets increased their body P, RNA, and ATP content within 8–24 h. This switch from high to low C:P diets also led to increased RNA:P ratios in animal bodies. Overall, our study revealed that consumer P metabolism reflects both current and past diet due to more dynamic and rapid changes in P biochemistry than total body mass. This metabolic

Photons, photosynthesis, and high-performance computing: challenges, progress, and promise of modeling metabolism in green algae

International Nuclear Information System (INIS)

Chang, C H; Graf, P; Alber, D M; Kim, K; Murray, G; Posewitz, M; Seibert, M

2008-01-01

The complexity associated with biological metabolism considered at a kinetic level presents a challenge to quantitative modeling. In particular, the relatively sparse knowledge of parameters for enzymes with known kinetic responses is problematic. The possible space of these parameters is of high-dimension, and sampling of such a space typifies a combinatorial explosion of possible dynamic states. However, with sufficient quantitative transcriptomics, proteomics, and metabolomics data at hand, these challenges could be met by high-performance software with sampling, fitting, and optimization capabilities. With this in mind, we present the High-Performance Systems Biology Toolkit HiPer SBTK, an evolving software package to simulate, fit, and optimize metabolite concentrations and fluxes within the space of rate and binding parameters associated with detailed enzyme kinetic models. We present our chosen modeling paradigm for the formulation of metabolic pathway models, the means to address the challenge of representing such models in a precise and persistent fashion using the standardized Systems Biology Markup Language, and our second-generation model of H2-associated Chlamydomonas metabolism. Processing of such models for hierarchically parallelized simulation and optimization, job specification by the user through a GUI interface, software capabilities and initial scaling data, and the mapping of the computation to biological questions is also discussed. Moreover, we present near-term future software and model development goals

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

Cardiovascular and metabolic responses to fasting and thermoneutrality are conserved in obese Zucker rats.

Science.gov (United States)

Overton, J M; Williams, T D; Chambers, J B; Rashotte, M E

2001-04-01

The primary purpose of the study was to test the hypothesis that reduced leptin signaling is necessary to elicit the cardiovascular and metabolic responses to fasting. Lean (Fa/?; normal leptin receptor; n = 7) and obese (fa/fa; mutated leptin receptor; n = 8) Zucker rats were instrumented with telemetry transmitters and housed in metabolic chambers at 23 degrees C (12:12-h light-dark cycle) for continuous (24 h) measurement of metabolic and cardiovascular variables. Before fasting, mean arterial pressure (MAP) was higher (MAP: obese = 103 +/- 3; lean = 94 +/- 1 mmHg), whereas oxygen consumption (VO(2): obese = 16.5 +/- 0.3; lean = 18.6 +/- 0.2 ml. min(-1). kg(-0.75)) was lower in obese Zucker rats compared with their lean controls. Two days of fasting had no effect on MAP in either lean or obese Zucker rats, whereas VO(2) (obese = -3.1 +/- 0.3; lean = -2.9 +/- 0.1 ml. min(-1). kg(-0.75)) and heart rate (HR: obese = -56 +/- 4; lean = -42 +/- 4 beats/min) were decreased markedly in both groups. Fasting increased HR variability both in lean (+1.8 +/- 0.4 ms) and obese (+2.6 +/- 0.3 ms) Zucker rats. After a 6-day period of ad libitum refeeding, when all parameters had returned to near baseline levels, the cardiovascular and metabolic responses to 2 days of thermoneutrality (ambient temperature 29 degrees C) were determined. Thermoneutrality reduced VO(2) (obese = -2.4 +/- 0.2; lean = -3.3 +/- 0.2 ml. min(-1). kg(-0.75)), HR (obese = -46 +/- 5; lean = -55 +/- 4 beats/min), and MAP (obese = -13 +/- 6; lean = -10 +/- 1 mmHg) similarly in lean and obese Zucker rats. The results indicate that the cardiovascular and metabolic responses to fasting and thermoneutrality are conserved in Zucker rats and suggest that intact leptin signaling may not be requisite for the metabolic and cardiovascular responses to reduced energy intake.

Construction and analysis of the model of energy metabolism in E. coli.

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Zixiang Xu

Full Text Available Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy and there have been several genome-scale gene-protein-reaction models. But research on the modelling for energy metabolism of organisms just began in recent years and research on metabolic weighted complex network are rare in literature. We have made three research based on the complete model of E. coli's energy metabolism. We first constructed a metabolic weighted network using the rates of free energy consumption within metabolic reactions as the weights. We then analyzed some structural characters of the metabolic weighted network that we constructed. We found that the distribution of the weight values was uneven, that most of the weight values were zero while reactions with abstract large weight values were rare and that the relationship between w (weight values and v (flux values was not of linear correlation. At last, we have done some research on the equilibrium of free energy for the energy metabolism system of E. coli. We found that E(out (free energy rate input from the environment can meet the demand of E(ch(in (free energy rate dissipated by chemical process and that chemical process plays a great role in the dissipation of free energy in cells. By these research and to a certain extend, we can understand more about the energy metabolism of E. coli.

The structure of wheat bread influences the postprandial metabolic response in healthy men.

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Eelderink, Coby; Noort, Martijn W J; Sozer, Nesli; Koehorst, Martijn; Holst, Jens J; Deacon, Carolyn F; Rehfeld, Jens F; Poutanen, Kaisa; Vonk, Roel J; Oudhuis, Lizette; Priebe, Marion G

2015-10-01

Postprandial high glucose and insulin responses after starchy food consumption, associated with an increased risk of developing several metabolic diseases, could possibly be improved by altering food structure. We investigated the influence of a compact food structure; different wheat products with a similar composition were created using different processing conditions. The postprandial glucose kinetics and metabolic response to bread with a compact structure (flat bread, FB) was compared to bread with a porous structure (control bread, CB) in a randomized, crossover study with ten healthy male volunteers. Pasta (PA), with a very compact structure, was used as the control. The rate of appearance of exogenous glucose (RaE), endogenous glucose production, and glucose clearance rate (GCR) was calculated using stable isotopes. Furthermore, postprandial plasma concentrations of glucose, insulin, several intestinal hormones and bile acids were analyzed. The structure of FB was considerably more compact compared to CB, as confirmed by microscopy, XRT analysis (porosity) and density measurements. Consumption of FB resulted in lower peak glucose, insulin and glucose-dependent insulinotropic polypeptide (ns) responses and a slower initial RaE compared to CB. These variables were similar to the PA response, except for RaE which remained slower over a longer period after PA consumption. Interestingly, the GCR after FB was higher than expected based on the insulin response, indicating increased insulin sensitivity or insulin-independent glucose disposal. These results demonstrate that the structure of wheat bread can influence the postprandial metabolic response, with a more compact structure being more beneficial for health. Bread-making technology should be further explored to create healthier products.

Selected Metabolic Responses to Skateboarding

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Hetzler, Ronald K.; Hunt, Ian; Stickley, Christopher D.; Kimura, Iris F.

2011-01-01

Despite the popularity of skateboarding worldwide, the authors believe that no previous studies have investigated the metabolic demands associated with recreational participation in the sport. Although metabolic equivalents (METs) for skateboarding were published in textbooks, the source of these values is unclear. Therefore, the rise in…

Metabolic network modeling of microbial interactions in natural and engineered environmental systems

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Octavio ePerez-Garcia

2016-05-01

Full Text Available We review approaches to characterize metabolic interactions within microbial communities using Stoichiometric Metabolic Network (SMN models for applications in environmental and industrial biotechnology. SMN models are computational tools used to evaluate the metabolic engineering potential of various organisms. They have successfully been applied to design and optimize the microbial production of antibiotics, alcohols and amino acids by single strains. To date however, such models have been rarely applied to analyze and control the metabolism of more complex microbial communities. This is largely attributed to the diversity of microbial community functions, metabolisms and interactions. Here, we firstly review different types of microbial interaction and describe their relevance for natural and engineered environmental processes. Next, we provide a general description of the essential methods of the SMN modeling workflow including the steps of network reconstruction, simulation through Flux Balance Analysis (FBA, experimental data gathering, and model calibration. Then we broadly describe and compare four approaches to model microbial interactions using metabolic networks, i.e. i lumped networks, ii compartment per guild networks, iii bi-level optimization simulations and iv dynamic-SMN methods. These approaches can be used to integrate and analyze diverse microbial physiology, ecology and molecular community data. All of them (except the lumped approach are suitable for incorporating species abundance data but so far they have been used only to model simple communities of two to eight different species. Interactions based on substrate exchange and competition can be directly modeled using the above approaches. However, interactions based on metabolic feedbacks, such as product inhibition and synthropy require extensions to current models, incorporating gene regulation and compounding accumulation mechanisms. SMN models of microbial

Role of the mixed-lineage protein kinase pathway in the metabolic stress response to obesity

OpenAIRE

Kant, Shashi; Barrett, Tamera; Vertii, Anastassiia; Noh, Yun Hee; Jung, Dae Young; Kim, Jason K.; Davis, Roger J.

2013-01-01

Saturated free fatty acid (FFA) is implicated in the metabolic response to obesity. In vitro studies indicate that FFA signaling may be mediated by the mixed-lineage protein kinase (MLK) pathway that activates cJun NH2-terminal kinase (JNK). Here, we examined the role of the MLK pathway in vivo using a mouse model of diet-induced obesity. The ubiquitously expressed MLK2 and MLK3 protein kinases have partially redundant functions. We therefore compared wild-type and compound mutant mice that l...

Metabolic response assessment with 18F-FDG-PET/CT is superior to modified RECIST for the evaluation of response to platinum-based doublet chemotherapy in malignant pleural mesothelioma

Energy Technology Data Exchange (ETDEWEB)

Kanemura, Shingo [Department of Respiratory Medicine, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan); Kuribayashi, Kozo, E-mail: kuririn@hyo-med.ac.jp [Department of Respiratory Medicine, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan); Funaguchi, Norihiko [Department of Respiratory Medicine, Murakami Memorial Hospital, Asahi University, 3-23 Hashimoto-cho, Gifu 500-8523 (Japan); Shibata, Eisuke; Mikami, Koji [Department of Respiratory Medicine, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan); Doi, Hiroshi [Department of Radiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan); Kitajima, Kazuhiro [Division of Nuclear Medicine and PET center, Department of Radiology, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan); Hasegawa, Seiki [Department of Thoracic Surgery, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan); Nakano, Takashi [Department of Respiratory Medicine, Hyogo College of Medicine, 1-1 Mukogawa-cho, Nishinomiya, Hyogo 663-8501 (Japan)

2017-01-15

Highlights: • 18F-FDG-PET/CT and mRESIST were used for tumour responsiveness evaluation in MPM. • 29% of mRESIST stable disease (SD) patients were metabolic non-responders. • Disease control rate was 93.9% and metabolic response rate was 71.9%. • Progressive metabolic disease patients had lower time to progression. • MRESIST stable disease (SD) patients should be further screened by 18F-FDG-PET/CT. - Abstract: Purpose: Efficient monitoring of tumor responsiveness to chemotherapy is essential to mitigate high mortality risks and cytotoxic effects of chemotherapeutics. However, there is no consensus on the most suitable diagnostic technique/parameters for assessing response to chemotherapy in malignant pleural mesothelioma (MPM). We compared the tumor responsiveness of MPM patients as assessed using modified RECIST (mRECIST) criteria and integrated 18F-FDG-PET/CT. Methods: Histologically confirmed MPM patients (N = 82) who were treated with three cycles of cisplatin and pemetrexed, or carboplatin and pemetrexed, were included. mRECIST and integrated 18F-FDG-PET/CT were used to evaluate MPM tumor response to chemotherapy. Metabolic non-responders were defined as those with a 25% or greater increase in SUVmax compared with the previous value. Time to progression (TTP) and overall survival (OS) were compared between metabolic-responders and non-responders. Results: After three cycles of chemotherapy, 62(75.6%) of the patients were classified as having SD, 15 (18%) with partial remission (PR), and 5 (6%) with progressive disease (PD), based on mRECIST criteria. The cumulative median OS was 728.0 days (95% confidence interval [CI]: 545.9–910.1) and cumulative median TTP was 365.0 days (95% CI: 296.9–433.1). For the 82 patients, the disease control rate was 93.9%, whereas the metabolic response rate was only 71.9% (p < 0.001). All PD and PR patients were found to be metabolic responders on 18F-FDG-PET/CT; however, among the 62mRECIST SD patients, 18 (29

Predicting growth of the healthy infant using a genome scale metabolic model.

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Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens

2017-01-01

An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.

RNA metabolism in Xylella fastidiosa during cold adaptation and survival responses

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Fastidious plant pathogen Xylella fastidiosa has a reduced ability to adapt to cold temperatures, limiting persistence in perennial hosts, such as grapevine, growing in colder regions. RNA metabolism is an essential part of bacterial response to low temperature, including inducible expression of RNA...

Origin of endotoxemia influences the metabolic response to endotoxin in dogs

NARCIS (Netherlands)

Moeniralam, H. S.; Bemelman, W. A.; Romijn, J. A.; Endert, E.; Ackermans, M. T.; van Lanschot, J. J.; Hermsen, R. C.; Sauerwein, H. P.

1997-01-01

Different routes of endotoxin administration have been used to mimic inflammatory and metabolic responses observed during sepsis. Because the origin of endotoxemia may affect the reactions to endotoxin, we compared the induction of tumor necrosis factor (TNF), interleukin-6 (IL-6), hormones, and

Assessment of chitosan-affected metabolic response by peroxisome proliferator-activated receptor bioluminescent imaging-guided transcriptomic analysis.

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Chia-Hung Kao

Full Text Available Chitosan has been widely used in food industry as a weight-loss aid and a cholesterol-lowering agent. Previous studies have shown that chitosan affects metabolic responses and contributes to anti-diabetic, hypocholesteremic, and blood glucose-lowering effects; however, the in vivo targeting sites and mechanisms of chitosan remain to be clarified. In this study, we constructed transgenic mice, which carried the luciferase genes driven by peroxisome proliferator-activated receptor (PPAR, a key regulator of fatty acid and glucose metabolism. Bioluminescent imaging of PPAR transgenic mice was applied to report the organs that chitosan acted on, and gene expression profiles of chitosan-targeted organs were further analyzed to elucidate the mechanisms of chitosan. Bioluminescent imaging showed that constitutive PPAR activities were detected in brain and gastrointestinal tract. Administration of chitosan significantly activated the PPAR activities in brain and stomach. Microarray analysis of brain and stomach showed that several pathways involved in lipid and glucose metabolism were regulated by chitosan. Moreover, the expression levels of metabolism-associated genes like apolipoprotein B (apoB and ghrelin genes were down-regulated by chitosan. In conclusion, these findings suggested the feasibility of PPAR bioluminescent imaging-guided transcriptomic analysis on the evaluation of chitosan-affected metabolic responses in vivo. Moreover, we newly identified that downregulated expression of apoB and ghrelin genes were novel mechanisms for chitosan-affected metabolic responses in vivo.

SirT1 regulates energy metabolism and response to caloric restriction in mice.

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Gino Boily

Full Text Available The yeast sir2 gene and its orthologues in Drosophila and C. elegans have well-established roles in lifespan determination and response to caloric restriction. We have studied mice carrying two null alleles for SirT1, the mammalian orthologue of sir2, and found that these animals inefficiently utilize ingested food. These mice are hypermetabolic, contain inefficient liver mitochondria, and have elevated rates of lipid oxidation. When challenged with a 40% reduction in caloric intake, normal mice maintained their metabolic rate and increased their physical activity while the metabolic rate of SirT1-null mice dropped and their activity did not increase. Moreover, CR did not extend lifespan of SirT1-null mice. Thus, SirT1 is an important regulator of energy metabolism and, like its orthologues from simpler eukaryotes, the SirT1 protein appears to be required for a normal response to caloric restriction.

Cardiovascular, hormonal and metabolic responses to graded exercise in juvenile diabetics with and without autonomic neuropathy

DEFF Research Database (Denmark)

Hilsted, J; Galbo, H; Christensen, N J

1980-01-01

Thirteen juvenile diabetics were studied in order to determine if decreased beat-to-beat variation during deep respiration, indicating abnormal autonomic nerve function, imply that cardiovascular, hormonal and metabolic responses are impaired. Patients with decreased beat-to-beat variation had to...... to be more heavily stressed during exercise to reach a certain heart rate or catecholamine level. The relation between other metabolic and hormonal response is discussed....

Genome-based Modeling and Design of Metabolic Interactions in Microbial Communities.

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Mahadevan, Radhakrishnan; Henson, Michael A

2012-01-01

Biotechnology research is traditionally focused on individual microbial strains that are perceived to have the necessary metabolic functions, or the capability to have these functions introduced, to achieve a particular task. For many important applications, the development of such omnipotent microbes is an extremely challenging if not impossible task. By contrast, nature employs a radically different strategy based on synergistic combinations of different microbial species that collectively achieve the desired task. These natural communities have evolved to exploit the native metabolic capabilities of each species and are highly adaptive to changes in their environments. However, microbial communities have proven difficult to study due to a lack of suitable experimental and computational tools. With the advent of genome sequencing, omics technologies, bioinformatics and genome-scale modeling, researchers now have unprecedented capabilities to analyze and engineer the metabolism of microbial communities. The goal of this review is to summarize recent applications of genome-scale metabolic modeling to microbial communities. A brief introduction to lumped community models is used to motivate the need for genome-level descriptions of individual species and their metabolic interactions. The review of genome-scale models begins with static modeling approaches, which are appropriate for communities where the extracellular environment can be assumed to be time invariant or slowly varying. Dynamic extensions of the static modeling approach are described, and then applications of genome-scale models for design of synthetic microbial communities are reviewed. The review concludes with a summary of metagenomic tools for analyzing community metabolism and an outlook for future research.

Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism

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2016-03-15

RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic

Neuro-fuzzy model of homocysteine metabolism

Indian Academy of Sciences (India)

In view of well-documented association of hyperhomocysteinaemia with a wide spectrum of diseases and higher incidence of vitamin deficiencies in Indians, we proposed a mathematical model to forecast the role of demographic and geneticvariables in influencing homocysteine metabolism and investigated the influence ...

Constraint based modeling of metabolism allows finding metabolic cancer hallmarks and identifying personalized therapeutic windows.

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Bordel, Sergio

2018-04-13

In order to choose optimal personalized anticancer treatments, transcriptomic data should be analyzed within the frame of biological networks. The best known human biological network (in terms of the interactions between its different components) is metabolism. Cancer cells have been known to have specific metabolic features for a long time and currently there is a growing interest in characterizing new cancer specific metabolic hallmarks. In this article it is presented a method to find personalized therapeutic windows using RNA-seq data and Genome Scale Metabolic Models. This method is implemented in the python library, pyTARG. Our predictions showed that the most anticancer selective (affecting 27 out of 34 considered cancer cell lines and only 1 out of 6 healthy mesenchymal stem cell lines) single metabolic reactions are those involved in cholesterol biosynthesis. Excluding cholesterol biosynthesis, all the considered cell lines can be selectively affected by targeting different combinations (from 1 to 5 reactions) of only 18 metabolic reactions, which suggests that a small subset of drugs or siRNAs combined in patient specific manners could be at the core of metabolism based personalized treatments.

Dynamic metabolic modeling of heterotrophic and mixotrophic microalgal growth on fermentative wastes.

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Caroline Baroukh

2017-06-01

Full Text Available Microalgae are promising microorganisms for the production of numerous molecules of interest, such as pigments, proteins or triglycerides that can be turned into biofuels. Heterotrophic or mixotrophic growth on fermentative wastes represents an interesting approach to achieving higher biomass concentrations, while reducing cost and improving the environmental footprint. Fermentative wastes generally consist of a blend of diverse molecules and it is thus crucial to understand microalgal metabolism in such conditions, where switching between substrates might occur. Metabolic modeling has proven to be an efficient tool for understanding metabolism and guiding the optimization of biomass or target molecule production. Here, we focused on the metabolism of Chlorella sorokiniana growing heterotrophically and mixotrophically on acetate and butyrate. The metabolism was represented by 172 metabolic reactions. The DRUM modeling framework with a mildly relaxed quasi-steady-state assumption was used to account for the switching between substrates and the presence of light. Nine experiments were used to calibrate the model and nine experiments for the validation. The model efficiently predicted the experimental data, including the transient behavior during heterotrophic, autotrophic, mixotrophic and diauxic growth. It shows that an accurate model of metabolism can now be constructed, even in dynamic conditions, with the presence of several carbon substrates. It also opens new perspectives for the heterotrophic and mixotrophic use of microalgae, especially for biofuel production from wastes.

Uncovering transcriptional regulation of metabolism by using metabolic network topology

DEFF Research Database (Denmark)

Patil, Kiran Raosaheb; Nielsen, Jens

2005-01-01

in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic......Cellular response to genetic and environmental perturbations is often reflected and/or mediated through changes in the metabolism, because the latter plays a key role in providing Gibbs free energy and precursors for biosynthesis. Such metabolic changes are often exerted through transcriptional...... therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns...

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.

Context-Specific Metabolic Model Extraction Based on Regularized Least Squares Optimization.

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Semidán Robaina Estévez

Full Text Available Genome-scale metabolic models have proven highly valuable in investigating cell physiology. Recent advances include the development of methods to extract context-specific models capable of describing metabolism under more specific scenarios (e.g., cell types. Yet, none of the existing computational approaches allows for a fully automated model extraction and determination of a flux distribution independent of user-defined parameters. Here we present RegrEx, a fully automated approach that relies solely on context-specific data and ℓ1-norm regularization to extract a context-specific model and to provide a flux distribution that maximizes its correlation to data. Moreover, the publically available implementation of RegrEx was used to extract 11 context-specific human models using publicly available RNAseq expression profiles, Recon1 and also Recon2, the most recent human metabolic model. The comparison of the performance of RegrEx and its contending alternatives demonstrates that the proposed method extracts models for which both the structure, i.e., reactions included, and the flux distributions are in concordance with the employed data. These findings are supported by validation and comparison of method performance on additional data not used in context-specific model extraction. Therefore, our study sets the ground for applications of other regularization techniques in large-scale metabolic modeling.

Prenatal metformin exposure in a maternal high fat diet mouse model alters the transcriptome and modifies the metabolic responses of the offspring.

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Salomäki, Henriikka; Heinäniemi, Merja; Vähätalo, Laura H; Ailanen, Liisa; Eerola, Kim; Ruohonen, Suvi T; Pesonen, Ullamari; Koulu, Markku

2014-01-01

Despite the wide use of metformin in metabolically challenged pregnancies, the long-term effects on the metabolism of the offspring are not known. We studied the long-term effects of prenatal metformin exposure during metabolically challenged pregnancy in mice. Female mice were on a high fat diet (HFD) prior to and during the gestation. Metformin was administered during gestation from E0.5 to E17.5. Male and female offspring were weaned to a regular diet (RD) and subjected to HFD at adulthood (10-11 weeks). Body weight and several metabolic parameters (e.g. body composition and glucose tolerance) were measured during the study. Microarray and subsequent pathway analyses on the liver and subcutaneous adipose tissue of the male offspring were performed at postnatal day 4 in a separate experiment. Prenatal metformin exposure changed the offspring's response to HFD. Metformin exposed offspring gained less body weight and adipose tissue during the HFD phase. Additionally, prenatal metformin exposure prevented HFD-induced impairment in glucose tolerance. Microarray and annotation analyses revealed metformin-induced changes in several metabolic pathways from which electron transport chain (ETC) was prominently affected both in the neonatal liver and adipose tissue. This study shows the beneficial effects of prenatal metformin exposure on the offspring's glucose tolerance and fat mass accumulation during HFD. The transcriptome data obtained at neonatal age indicates major effects on the genes involved in mitochondrial ATP production and adipocyte differentiation suggesting the mechanistic routes to improved metabolic phenotype at adulthood.

A whole-body mathematical model of cholesterol metabolism and its age-associated dysregulation

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Mc Auley Mark T

2012-10-01

Full Text Available Abstract Background Global demographic changes have stimulated marked interest in the process of aging. There has been, and will continue to be, an unrelenting rise in the number of the oldest old ( >85 years of age. Together with an ageing population there comes an increase in the prevalence of age related disease. Of the diseases of ageing, cardiovascular disease (CVD has by far the highest prevalence. It is regarded that a finely tuned lipid profile may help to prevent CVD as there is a long established relationship between alterations to lipid metabolism and CVD risk. In fact elevated plasma cholesterol, particularly Low Density Lipoprotein Cholesterol (LDL-C has consistently stood out as a risk factor for having a cardiovascular event. Moreover it is widely acknowledged that LDL-C may rise with age in both sexes in a wide variety of groups. The aim of this work was to use a whole-body mathematical model to investigate why LDL-C rises with age, and to test the hypothesis that mechanistic changes to cholesterol absorption and LDL-C removal from the plasma are responsible for the rise. The whole-body mechanistic nature of the model differs from previous models of cholesterol metabolism which have either focused on intracellular cholesterol homeostasis or have concentrated on an isolated area of lipoprotein dynamics. The model integrates both current and previously published data relating to molecular biology, physiology, ageing and nutrition in an integrated fashion. Results The model was used to test the hypothesis that alterations to the rate of cholesterol absorption and changes to the rate of removal of LDL-C from the plasma are integral to understanding why LDL-C rises with age. The model demonstrates that increasing the rate of intestinal cholesterol absorption from 50% to 80% by age 65 years can result in an increase of LDL-C by as much as 34 mg/dL in a hypothetical male subject. The model also shows that decreasing the rate of hepatic

Use of genome-scale microbial models for metabolic engineering

DEFF Research Database (Denmark)

Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

2004-01-01

Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing

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María P. Cortés

2017-12-01

Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.

Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling

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Mahadevan Radhakrishnan

2010-05-01

Full Text Available Abstract Background Geobacter sulfurreducens is a member of the Geobacter species, which are capable of oxidation of organic waste coupled to the reduction of heavy metals and electrode with applications in bioremediation and bioenergy generation. While the metabolism of this organism has been studied through the development of a stoichiometry based genome-scale metabolic model, the associated regulatory network has not yet been well studied. In this manuscript, we report on the implementation of a thermodynamics based metabolic flux model for Geobacter sulfurreducens. We use this updated model to identify reactions that are subject to regulatory control in the metabolic network of G. sulfurreducens using thermodynamic variability analysis. Findings As a first step, we have validated the regulatory sites and bottleneck reactions predicted by the thermodynamic flux analysis in E. coli by evaluating the expression ranges of the corresponding genes. We then identified ten reactions in the metabolic network of G. sulfurreducens that are predicted to be candidates for regulation. We then compared the free energy ranges for these reactions with the corresponding gene expression fold changes under conditions of different environmental and genetic perturbations and show that the model predictions of regulation are consistent with data. In addition, we also identify reactions that operate close to equilibrium and show that the experimentally determined exchange coefficient (a measure of reversibility is significant for these reactions. Conclusions Application of the thermodynamic constraints resulted in identification of potential bottleneck reactions not only from the central metabolism but also from the nucleotide and amino acid subsystems, thereby showing the highly coupled nature of the thermodynamic constraints. In addition, thermodynamic variability analysis serves as a valuable tool in estimating the ranges of ΔrG' of every reaction in the model

Larval starvation improves metabolic response to adult starvation in honey bees (Apis mellifera L.).

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Wang, Ying; Campbell, Jacob B; Kaftanoglu, Osman; Page, Robert E; Amdam, Gro V; Harrison, Jon F

2016-04-01

Environmental changes during development have long-term effects on adult phenotypes in diverse organisms. Some of the effects play important roles in helping organisms adapt to different environments, such as insect polymorphism. Others, especially those resulting from an adverse developmental environment, have a negative effect on adult health and fitness. However, recent studies have shown that those phenotypes influenced by early environmental adversity have adaptive value under certain (anticipatory) conditions that are similar to the developmental environment, though evidence is mostly from morphological and behavioral observations and it is still rare at physiological and molecular levels. In the companion study, we applied a short-term starvation treatment to fifth instar honey bee larvae and measured changes in adult morphology, starvation resistance, hormonal and metabolic physiology and gene expression. Our results suggest that honey bees can adaptively respond to the predicted nutritional stress. In the present study, we further hypothesized that developmental starvation specifically improves the metabolic response of adult bees to starvation instead of globally affecting metabolism under well-fed conditions. Here, we produced adult honey bees that had experienced a short-term larval starvation, then we starved them for 12 h and monitored metabolic rate, blood sugar concentrations and metabolic reserves. We found that the bees that experienced larval starvation were able to shift to other fuels faster and better maintain stable blood sugar levels during starvation. However, developmental nutritional stress did not change metabolic rates or blood sugar levels in adult bees under normal conditions. Overall, our study provides further evidence that early larval starvation specifically improves the metabolic responses to adult starvation in honey bees. © 2016. Published by The Company of Biologists Ltd.

A human model of inflammatory cardio-metabolic dysfunction; a double blind placebo-controlled crossover trial

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Mehta Nehal N

2012-06-01

Full Text Available Abstract Background Chronic inflammation may contribute to insulin resistance (IR, metabolic syndrome and atherosclerosis although evidence of causality is lacking in humans. We hypothesized that very low-dose experimental endotoxemia would induce adipose tissue inflammation and systemic IR during a low-grade but asymptomatic inflammatory response and thus provide an experimental model for future tests of pharmacologic and genomic modulation of cardio-metabolic traits in humans. Methods Ten healthy, human volunteers (50% male, 90% Caucasian, mean age 22.7 ± 3.8 were randomized in a double-masked, placebo-controlled, crossover study to separate 36-hour inpatient visits (placebo versus intravenous-LPS 0.6 ng/kg. We measured clinical symptoms via the McGill pain questionnaire and serial vital signs. Plasma and serum were collected for measurement of cytokines, C-reactive protein, insulin and glucose, serial whole blood & subcutaneous adipose tissue mRNA expression were measured by real-time PCR. HOMA-IR, a well-validated measure of IR was calculated to estimate insulin resistance, and frequently sampled intravenous glucose tolerance testing (FSIGTT was performed to confirm an insulin resistant state. We performed ANOVA and within subject ANOVA to understand the differences in cytokines, adipose tissue inflammation and IR before and after LPS or placebo. Results There was no significant difference between placebo and LPS in clinical responses of symptom scores, body temperature or heart rate. However, low-dose endotoxemia induced a rapid and transient 25-fold induction of plasma TNF-alpha and 100-fold increase in plasma IL-6 (Figure 1B (p p p = 0.01 increased with MCP-1 (peak 10-fold, F = 5.6, p p p p  Conclusions We present a low dose human endotoxemia model of inflammation which induces adipose tissue inflammation and systemic insulin resistance in the absence of overt clinical response. Such a model has the potential

Diurnal changes in CN metabolism and response of rice seedlings to UV-B radiation.

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Yun, Hyejin; Lim, Sunhyung; Kim, Yangmin X; Lee, Yejin; Lee, Seulbi; Lee, Deogbae; Park, Keewoong; Sung, Jwakyung

2018-03-13

Plants regulate a number of primary metabolites, including carbohydrates, organic acids, and amino acids, in response to UV-B radiation. Therefore, it is essential to understand the time-dependent response of rice plants to UV-B stress. This study focused on the response of plants to UV-B at different leaf developmental phases (emerging, growing, and maturing) in an attempt to fully comprehend the metabolic shift. We analyzed the expression levels of genes related to starch/sucrose metabolism in the leaf blades of rice seedlings (Oryza sativa L. "Saechuchenog") exposed to UV-B irradiation for short (1 day) and long terms (5 days) using quantitative real-time polymerase chain reaction. We also examined the diurnal variations in the contents of primary metabolites using an established GCTOF-MS (gas chromatography time of flight-mass spectrometry) method. The results showed that the levels of primary metabolites were largely dependent upon the diurnal rhythm and leaf developmental phase. The young leaves (sink) produced and accumulated starch rather than sucrose. The short-term (4 h, 1 day) UV-B exposure inhibited sucrose synthesis, which could be the first target of UV-B radiation. Following short- and long-term (5 days) exposure to UV-B radiation, the dynamic response of primary metabolites was evaluated. It was found that the content of carbohydrates decreased throughout the period of exposure to UV-B stress, especially in terms of sucrose concentration. However, the content of the majority of amino acids increased after an early decrease. Our data revealed that the metabolic response, as well as the gene expression, differed with the period (intensity) of exposure to UV-B radiation and with the phase of leaf development. These findings provide new insights for a better understanding of the metabolic response of a variety of plant species exposed to a wide range of UV-B radiation. Copyright © 2018. Published by Elsevier GmbH.

Metabolic profiling reveals potential metabolic markers associated with Hypoxia Inducible Factor-mediated signalling in hypoxic cancer cells.

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Armitage, Emily G; Kotze, Helen L; Allwood, J William; Dunn, Warwick B; Goodacre, Royston; Williams, Kaye J

2015-10-28

Hypoxia inducible factors (HIFs) plays an important role in oxygen compromised environments and therefore in tumour survival. In this research, metabolomics has been applied to study HIFs metabolic function in two cell models: mouse hepatocellular carcinoma and human colon carcinoma, whereby the metabolism has been profiled for a range of oxygen potentials. Wild type cells have been compared to cells deficient in HIF signalling to reveal its effect on cellular metabolism under normal oxygen conditions as well as low oxygen, hypoxic and anoxic environments. Characteristic responses to hypoxia that were conserved across both cell models involved the anti-correlation between 2-hydroxyglutarate, 2-oxoglutarate, fructose, hexadecanoic acid, hypotaurine, pyruvate and octadecenoic acid with 4-hydroxyproline, aspartate, cysteine, glutamine, lysine, malate and pyroglutamate. Further to this, network-based correlation analysis revealed HIF specific pathway responses to each oxygen condition that were also conserved between cell models. From this, 4-hydroxyproline was revealed as a regulating hub in low oxygen survival of WT cells while fructose appeared to be in HIF deficient cells. Pathways surrounding these hubs were built from the direct connections of correlated metabolites that look beyond traditional pathways in order to understand the mechanism of HIF response to low oxygen environments.

Transcriptome Analysis Identifies Key Metabolic Changes in the Hooded Seal (Cystophora cristata Brain in Response to Hypoxia and Reoxygenation.

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Mariana Leivas Müller Hoff

Full Text Available The brain of diving mammals tolerates low oxygen conditions better than the brain of most terrestrial mammals. Previously, it has been demonstrated that the neurons in brain slices of the hooded seal (Cystophora cristata withstand hypoxia longer than those of mouse, and also tolerate reduced glucose supply and high lactate concentrations. This tolerance appears to be accompanied by a shift in the oxidative energy metabolism to the astrocytes in the seal while in terrestrial mammals the aerobic energy production mainly takes place in neurons. Here, we used RNA-Seq to compare the effect of hypoxia and reoxygenation in vitro on brain slices from the visual cortex of hooded seals. We saw no general reduction of gene expression, suggesting that the response to hypoxia and reoxygenation is an actively regulated process. The treatments caused the preferential upregulation of genes related to inflammation, as found before e.g. in stroke studies using mammalian models. Gene ontology and KEGG pathway analyses showed a downregulation of genes involved in ion transport and other neuronal processes, indicative for a neuronal shutdown in response to a shortage of O2 supply. These differences may be interpreted in terms of an energy saving strategy in the seal's brain. We specifically analyzed the regulation of genes involved in energy metabolism. Hypoxia and reoxygenation caused a similar response, with upregulation of genes involved in glucose metabolism and downregulation of the components of the pyruvate dehydrogenase complex. We also observed upregulation of the monocarboxylate transporter Mct4, suggesting increased lactate efflux. Together, these data indicate that the seal brain responds to the hypoxic challenge by a relative increase in the anaerobic energy metabolism.

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

DEFF Research Database (Denmark)

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...

Metingear: a development environment for annotating genome-scale metabolic models.

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May, John W; James, A Gordon; Steinbeck, Christoph

2013-09-01

Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.

Metabolic response to optic centers to visual stimuli in the albino rat: anatomical and physiological considerations

International Nuclear Information System (INIS)

Toga, A.W.; Collins, R.C.

1981-01-01

The functional organization of the visual system was studied in the albino rat. Metabolic differences were measured using the 14 C-2-deoxyglucose (DG) autoradiographic technique during visual stimulation of one entire retina in unrestrained animals. All optic centers responded to changes in light intensity but to different degrees. The greatest change occurred in the superior colliculus, less in the lateral geniculate, and considerably less in second-order sites such as layer IV of visual cortex. These optic centers responded in particular to on/off stimuli, but showed no incremental change during pattern reversal or movement of orientation stimuli. Both the superior colliculus and lateral geniculate increased their metabolic rate as the frequency of stimulation increased, but the magnitude was twice as great in the colliculus. The histological pattern of metabolic change in the visual system was not homogenous. In the superior colliculus glucose utilization increased only in stratum griseum superficiale and was greatest in visuotopic regions representing the peripheral portions of the visual field. Similarly, in the lateral geniculate, only the dorsal nucleus showed an increased response to greater stimulus frequencies. Second-order regions of the visual system showed changes in metabolism in response to visual stimulation, but no incremental response specific for type or frequency of stimuli. To label proteins of axoplasmic transport to study the terminal fields of retinal projections 14 C-amino acids were used. This was done to study how the differences in the magnitude of the metabolic response among optic centers were related to the relative quantity of retinofugal projections to these centers

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.

Prenatal metformin exposure in a maternal high fat diet mouse model alters the transcriptome and modifies the metabolic responses of the offspring.

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Henriikka Salomäki

Full Text Available AIMS: Despite the wide use of metformin in metabolically challenged pregnancies, the long-term effects on the metabolism of the offspring are not known. We studied the long-term effects of prenatal metformin exposure during metabolically challenged pregnancy in mice. MATERIALS AND METHODS: Female mice were on a high fat diet (HFD prior to and during the gestation. Metformin was administered during gestation from E0.5 to E17.5. Male and female offspring were weaned to a regular diet (RD and subjected to HFD at adulthood (10-11 weeks. Body weight and several metabolic parameters (e.g. body composition and glucose tolerance were measured during the study. Microarray and subsequent pathway analyses on the liver and subcutaneous adipose tissue of the male offspring were performed at postnatal day 4 in a separate experiment. RESULTS: Prenatal metformin exposure changed the offspring's response to HFD. Metformin exposed offspring gained less body weight and adipose tissue during the HFD phase. Additionally, prenatal metformin exposure prevented HFD-induced impairment in glucose tolerance. Microarray and annotation analyses revealed metformin-induced changes in several metabolic pathways from which electron transport chain (ETC was prominently affected both in the neonatal liver and adipose tissue. CONCLUSION: This study shows the beneficial effects of prenatal metformin exposure on the offspring's glucose tolerance and fat mass accumulation during HFD. The transcriptome data obtained at neonatal age indicates major effects on the genes involved in mitochondrial ATP production and adipocyte differentiation suggesting the mechanistic routes to improved metabolic phenotype at adulthood.

Integration of metabolomics data into metabolic networks.

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Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

2015-01-01

Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data.

Reconstruction of Oryza sativa indica Genome Scale Metabolic Model and Its Responses to Varying RuBisCO Activity, Light Intensity, and Enzymatic Cost Conditions

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Ankita Chatterjee

2017-11-01

Full Text Available To combat decrease in rice productivity under different stresses, an understanding of rice metabolism is needed. Though there are different genome scale metabolic models (GSMs of Oryza sativa japonica, no GSM with gene-protein-reaction association exist for Oryza sativa indica. Here, we report a GSM, OSI1136 of O.s. indica, which includes 3602 genes and 1136 metabolic reactions and transporters distributed across the cytosol, mitochondrion, peroxisome, and chloroplast compartments. Flux balance analysis of the model showed that for varying RuBisCO activity (Vc/Vo (i the activity of the chloroplastic malate valve increases to transport reducing equivalents out of the chloroplast under increased photorespiratory conditions and (ii glyceraldehyde-3-phosphate dehydrogenase and phosphoglycerate kinase can act as source of cytosolic ATP under decreased photorespiration. Under increasing light conditions we observed metabolic flexibility, involving photorespiration, chloroplastic triose phosphate and the dicarboxylate transporters of the chloroplast and mitochondrion for redox and ATP exchanges across the intracellular compartments. Simulations under different enzymatic cost conditions revealed (i participation of peroxisomal glutathione-ascorbate cycle in photorespiratory H2O2 metabolism (ii different modes of the chloroplastic triose phosphate transporters and malate valve, and (iii two possible modes of chloroplastic Glu–Gln transporter which were related with the activity of chloroplastic and cytosolic isoforms of glutamine synthetase. Altogether, our results provide new insights into plant metabolism.

Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm

Energy Technology Data Exchange (ETDEWEB)

Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.

2015-03-10

There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.

Changes in energy metabolism in response to 48 h of overfeeding and fasting in Caucasians and Pima Indians

DEFF Research Database (Denmark)

Weyer, C; Vozarova, B; Ravussin, E

2001-01-01

Differences in the metabolic response to overfeeding and starvation may confer susceptibility or resistance to obesity in humans. To further examine this hypothesis, we assessed the changes in 24 h energy metabolism in response to short-term overfeeding and fasting in Caucasians (C) and Pima...... Indians (I), a population with a very high propensity for obesity....

Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

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Hui Chen

2014-01-01

Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

An integrated model of cardiac mitochondrial energy metabolism and calcium dynamics.

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Cortassa, Sonia; Aon, Miguel A; Marbán, Eduardo; Winslow, Raimond L; O'Rourke, Brian

2003-04-01

We present an integrated thermokinetic model describing control of cardiac mitochondrial bioenergetics. The model describes the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, and mitochondrial Ca(2+) handling. The kinetic component of the model includes effectors of the TCA cycle enzymes regulating production of NADH and FADH(2), which in turn are used by the electron transport chain to establish a proton motive force (Delta mu(H)), driving the F(1)F(0)-ATPase. In addition, mitochondrial matrix Ca(2+), determined by Ca(2+) uniporter and Na(+)/Ca(2+) exchanger activities, regulates activity of the TCA cycle enzymes isocitrate dehydrogenase and alpha-ketoglutarate dehydrogenase. The model is described by twelve ordinary differential equations for the time rate of change of mitochondrial membrane potential (Delta Psi(m)), and matrix concentrations of Ca(2+), NADH, ADP, and TCA cycle intermediates. The model is used to predict the response of mitochondria to changes in substrate delivery, metabolic inhibition, the rate of adenine nucleotide exchange, and Ca(2+). The model is able to reproduce, qualitatively and semiquantitatively, experimental data concerning mitochondrial bioenergetics, Ca(2+) dynamics, and respiratory control. Significant increases in oxygen consumption (V(O(2))), proton efflux, NADH, and ATP synthesis, in response to an increase in cytoplasmic Ca(2+), are obtained when the Ca(2+)-sensitive dehydrogenases are the main rate-controlling steps of respiratory flux. These responses diminished when control is shifted downstream (e.g., the respiratory chain or adenine nucleotide translocator). The time-dependent behavior of the model, under conditions simulating an increase in workload, closely reproduces experimentally observed mitochondrial NADH dynamics in heart trabeculae subjected to changes in pacing frequency. The steady-state and time-dependent behavior of the model support the hypothesis that mitochondrial matrix Ca(2+) plays an

Metabolic Response to Food Restriction in Military-Eligible Women, with a Gender Comparison

National Research Council Canada - National Science Library

Young, Vernon

1998-01-01

Two major series of investigations are being undertaken to explore the metabolic responses of women who meet military standards for body-weight and percent body-fat to the nutritional stressors of food restriction...

Metabolic Response to Food Restriction in Military-Eligible Women, With a Gender Comparison

National Research Council Canada - National Science Library

Young, Vernon

1996-01-01

Two major series of investigations will be undertaken to explore the metabolic responses of women, who meet military standards of body-weight and percent body-fat to the nutritional stressors of food restriction...

Metabolic Response to Food Restriction in Military-Eligible Women, with a Gender Comparison

National Research Council Canada - National Science Library

Young, Vernon

1997-01-01

Two major series of investigations are being undertaken to explore the metabolic responses of women who meet military standards for body-weight and percent body-fat to the nutritional stressors of food restriction...

Modeling of Pharmaceutical Biotransformation by Enriched Nitrifying Culture under Different Metabolic Conditions

DEFF Research Database (Denmark)

Xu, Yifeng; Chen, Xueming; Yuan, Zhiguo

2018-01-01

Pharmaceutical removal could be significantly enhanced through cometabolism during nitrification processes. To date, pharmaceutical biotransformation models have not considered the formation of transformation products associated with the metabolic type of microorganisms. Here we report a comprehe......Pharmaceutical removal could be significantly enhanced through cometabolism during nitrification processes. To date, pharmaceutical biotransformation models have not considered the formation of transformation products associated with the metabolic type of microorganisms. Here we report...... a comprehensive model to describe and evaluate the biodegradation of pharmaceuticals and the formation of their biotransformation products by enriched nitrifying cultures. The biotransformation of parent compounds was linked to the microbial processes via cometabolism induced by ammonium-oxidizing bacteria (AOB......) growth, metabolism by AOB, cometabolism by heterotrophs (HET) growth, and metabolism by HET in the model framework. The model was calibrated and validated using experimental data from pharmaceutical biodegradation experiments at realistic levels, taking two pharmaceuticals as examples, i.e., atenolol...

Liposoluble vitamins in Crustacean feed: Metabolic and Histological responses.

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Fernández-Gimenez, Analía Verónica

2016-05-01

Vitamins are vital for normal growth and survival of living organisms and they are distributed in feedstuffs in small quantities. This review is focused on the liposoluble vitamins (A, D, E and K) in the diets and metabolic responses of the Argentine penaeoid shrimps Pleoticus muelleri and Artemesia longinaris, distributed along the South American coast line. Growth, survival and histological analyses serve as indicators of the nutritional value derived from vitamin deficiency. Liposoluble vitamins are also related to stress, antioxidant defense and immune response of shrimps. Effective diet for shrimp culture that provide not only macronutrients including protein and lipid but also micronutrients such as vitamins for optimal growth is an ever improving subject. This review may help formulating suitable feeds for shrimps.

Developmental Programming in Response to Intrauterine Growth Restriction Impairs Myoblast Function and Skeletal Muscle Metabolism

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Yates, D. T.; Macko, A. R.; Nearing, M.; Chen, X.; Rhoads, R. P.; Limesand, S. W.

2012-01-01

Fetal adaptations to placental insufficiency alter postnatal metabolic homeostasis in skeletal muscle by reducing glucose oxidation rates, impairing insulin action, and lowering the proportion of oxidative fibers. In animal models of intrauterine growth restriction (IUGR), skeletal muscle fibers have less myonuclei at birth. This means that myoblasts, the sole source for myonuclei accumulation in fibers, are compromised. Fetal hypoglycemia and hypoxemia are complications that result from placental insufficiency. Hypoxemia elevates circulating catecholamines, and chronic hypercatecholaminemia has been shown to reduce fetal muscle development and growth. We have found evidence for adaptations in adrenergic receptor expression profiles in myoblasts and skeletal muscle of IUGR sheep fetuses with placental insufficiency. The relationship of β-adrenergic receptors shifts in IUGR fetuses because Adrβ2 expression levels decline and Adrβ1 expression levels are unaffected in myofibers and increased in myoblasts. This adaptive response would suppress insulin signaling, myoblast incorporation, fiber hypertrophy, and glucose oxidation. Furthermore, this β-adrenergic receptor expression profile persists for at least the first month in IUGR lambs and lowers their fatty acid mobilization. Developmental programming of skeletal muscle adrenergic receptors partially explains metabolic and endocrine differences in IUGR offspring, and the impact on metabolism may result in differential nutrient utilization. PMID:22900186

Developmental Programming in Response to Intrauterine Growth Restriction Impairs Myoblast Function and Skeletal Muscle Metabolism

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D. T. Yates

2012-01-01

Full Text Available Fetal adaptations to placental insufficiency alter postnatal metabolic homeostasis in skeletal muscle by reducing glucose oxidation rates, impairing insulin action, and lowering the proportion of oxidative fibers. In animal models of intrauterine growth restriction (IUGR, skeletal muscle fibers have less myonuclei at birth. This means that myoblasts, the sole source for myonuclei accumulation in fibers, are compromised. Fetal hypoglycemia and hypoxemia are complications that result from placental insufficiency. Hypoxemia elevates circulating catecholamines, and chronic hypercatecholaminemia has been shown to reduce fetal muscle development and growth. We have found evidence for adaptations in adrenergic receptor expression profiles in myoblasts and skeletal muscle of IUGR sheep fetuses with placental insufficiency. The relationship of β-adrenergic receptors shifts in IUGR fetuses because Adrβ2 expression levels decline and Adrβ1 expression levels are unaffected in myofibers and increased in myoblasts. This adaptive response would suppress insulin signaling, myoblast incorporation, fiber hypertrophy, and glucose oxidation. Furthermore, this β-adrenergic receptor expression profile persists for at least the first month in IUGR lambs and lowers their fatty acid mobilization. Developmental programming of skeletal muscle adrenergic receptors partially explains metabolic and endocrine differences in IUGR offspring, and the impact on metabolism may result in differential nutrient utilization.

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.

The obese Göttingen minipig as a model of the metabolic syndrome

DEFF Research Database (Denmark)

Johansen, T.; Malmlöf, K.; Hansen, Harald S.

2001-01-01

The objective of the study reported here was to induce obesity in the female Göttingen minipig to establish a model of the human metabolic syndrome. Nine- to ten-month-old female Göttingen minipigs received a high-fat high-energy (HFE) diet or a low-fat, low-energy (LFE) diet. The energy contents...... of the metabolic impairments seen in obese humans, and may thus serve as a model of the metabolic syndrome....

TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

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Jensen Paul A

2011-09-01

Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

Novel insights into obesity and diabetes through genome-scale metabolic modeling

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Leif eVäremo

2013-04-01

Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.

Genetic response to metabolic fluctuations: correlation between central carbon metabolism and DNA replication in Escherichia coli

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Szalewska-Pałasz Agnieszka

2011-03-01

Full Text Available Abstract Background Until now, the direct link between central carbon metabolism and DNA replication has been demonstrated only in Bacillus. subtilis. Therefore, we asked if this is a specific phenomenon, characteristic for this bacterium and perhaps for its close relatives, or a more general biological rule. Results We found that temperature-sensitivity of mutants in particular genes coding for replication proteins could be suppressed by deletions of certain genes coding for enzymes of the central carbon metabolism. Namely, the effects of dnaA46(ts mutation could be suppressed by dysfunction of pta or ackA, effects of dnaB(ts by dysfunction of pgi or pta, effects of dnaE486(ts by dysfunction of tktB, effects of dnaG(ts by dysfunction of gpmA, pta or ackA, and effects of dnaN159(ts by dysfunction of pta or ackA. The observed suppression effects were not caused by a decrease in bacterial growth rate. Conclusions The genetic correlation exists between central carbon metabolism and DNA replication in the model Gram-negative bacterium, E. coli. This link exists at the steps of initiation and elongation of DNA replication, indicating the important global correlation between metabolic status of the cell and the events leading to cell reproduction.

Insulin response of the glucose and fatty acid metabolism in dry dairy cows across a range of body condition scores.

Science.gov (United States)

De Koster, J; Hostens, M; Van Eetvelde, M; Hermans, K; Moerman, S; Bogaert, H; Depreester, E; Van den Broeck, W; Opsomer, G

2015-07-01

The objective of the present research was to determine the insulin response of the glucose and fatty acid metabolism in dry dairy cows with a variable body condition score (BCS). Ten pregnant Holstein Friesian dairy cows (upcoming parity 2 to 5) were selected based on BCS at the beginning of the study (2mo before expected parturition date). During the study, animals were monitored weekly for BCS and backfat thickness and in the last 2wk, blood samples were taken for determination of serum nonesterified fatty acid (NEFA) concentration. Animals underwent a hyperinsulinemic euglycemic clamp test in the third week before the expected parturition date. The hyperinsulinemic euglycemic clamp test consisted of 4 consecutive insulin infusions with increasing insulin doses: 0.1, 0.5, 2, and 5mIU/kg per minute. For each insulin infusion period, a steady state was defined as a period of 30min where no or minor changes of the glucose infusion were necessary to keep the blood glucose concentration constant and near basal levels. During the steady state, the glucose infusion rate [steady state glucose infusion rate (SSGIR) in µmol/kg per minute] and NEFA concentration [steady state NEFA concentration (SSNEFA) in mmol/L] were determined and reflect the insulin response of the glucose and fatty acid metabolism. Dose response curves were created based on the insulin concentrations during the steady state and the SSGIR or SSNEFA. The shape of the dose response curves is determined by the concentration of insulin needed to elicit the half maximal effect (EC50) and the maximal SSGIR or the minimal SSNEFA for the glucose or fatty acid metabolism, respectively. The maximal SSGIR was negatively associated with variables reflecting adiposity of the cows (BCS, backfat thickness, NEFA concentration during the dry period, and absolute weight of the different adipose depots determined after euthanasia and dissection of the different depots), whereas the EC50 of the glucose metabolism was

Type 2 responses at the interface between immunity and fat metabolism.

Science.gov (United States)

Odegaard, Justin I; Chawla, Ajay

2015-10-01

Adipose tissue resident leukocytes are often cast solely as the effectors of obesity and its attendant pathologies; however, recent observations have demonstrated that these cells support and effect 'healthy' physiologic function as well as pathologic dysfunction. Importantly, these two disparate outcomes are underpinned by similarly disparate immune programs; type 2 responses instruct and promote metabolic normalcy, while type 1 responses drive tissue dysfunction. In this Review, we summarize the literature regarding type 2 immunity's role in adipose tissue physiology and allude to its potential therapeutic implications. Copyright © 2015 Elsevier Ltd. All rights reserved.

OpenFLUX: efficient modelling software for 13C-based metabolic flux analysis

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Nielsen Lars K

2009-05-01

Full Text Available Abstract Background The quantitative analysis of metabolic fluxes, i.e., in vivo activities of intracellular enzymes and pathways, provides key information on biological systems in systems biology and metabolic engineering. It is based on a comprehensive approach combining (i tracer cultivation on 13C substrates, (ii 13C labelling analysis by mass spectrometry and (iii mathematical modelling for experimental design, data processing, flux calculation and statistics. Whereas the cultivation and the analytical part is fairly advanced, a lack of appropriate modelling software solutions for all modelling aspects in flux studies is limiting the application of metabolic flux analysis. Results We have developed OpenFLUX as a user friendly, yet flexible software application for small and large scale 13C metabolic flux analysis. The application is based on the new Elementary Metabolite Unit (EMU framework, significantly enhancing computation speed for flux calculation. From simple notation of metabolic reaction networks defined in a spreadsheet, the OpenFLUX parser automatically generates MATLAB-readable metabolite and isotopomer balances, thus strongly facilitating model creation. The model can be used to perform experimental design, parameter estimation and sensitivity analysis either using the built-in gradient-based search or Monte Carlo algorithms or in user-defined algorithms. Exemplified for a microbial flux study with 71 reactions, 8 free flux parameters and mass isotopomer distribution of 10 metabolites, OpenFLUX allowed to automatically compile the EMU-based model from an Excel file containing metabolic reactions and carbon transfer mechanisms, showing it's user-friendliness. It reliably reproduced the published data and optimum flux distributions for the network under study were found quickly ( Conclusion We have developed a fast, accurate application to perform steady-state 13C metabolic flux analysis. OpenFLUX will strongly facilitate and

Integrative investigation of metabolic and transcriptomic data

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Önsan Z İlsen

2006-04-01

Full Text Available Abstract Background New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods. Results Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions was investigated using linear modelling, and open reading-frames (ORFs whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures – PLS using PLS toolbox in Matlab. Conclusion The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.

Generalized framework for context-specific metabolic model extraction methods

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Semidán eRobaina Estévez

2014-09-01

Full Text Available Genome-scale metabolic models are increasingly applied to investigate the physiology not only of simple prokaryotes, but also eukaryotes, such as plants, characterized with compartmentalized cells of multiple types. While genome-scale models aim at including the entirety of known metabolic reactions, mounting evidence has indicated that only a subset of these reactions is active in a given context, including: developmental stage, cell type, or environment. As a result, several methods have been proposed to reconstruct context-specific models from existing genome-scale models by integrating various types of high-throughput data. Here we present a mathematical framework that puts all existing methods under one umbrella and provides the means to better understand their functioning, highlight similarities and differences, and to help users in selecting a most suitable method for an application.

The effect of metabolic alkalosis on the ventilatory response in healthy subjects.

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Oppersma, E; Doorduin, J; van der Hoeven, J G; Veltink, P H; van Hees, H W H; Heunks, L M A

2018-02-01

Patients with acute respiratory failure may develop respiratory acidosis. Metabolic compensation by bicarbonate production or retention results in posthypercapnic alkalosis with an increased arterial bicarbonate concentration. The hypothesis of this study was that elevated plasma bicarbonate levels decrease respiratory drive and minute ventilation. In an intervention study in 10 healthy subjects the ventilatory response using a hypercapnic ventilatory response (HCVR) test was assessed, before and after administration of high dose sodium bicarbonate. Total dose of sodiumbicarbonate was 1000 ml 8.4% in 3 days. Plasma bicarbonate increased from 25.2 ± 2.2 to 29.2 ± 1.9 mmol/L. With increasing inspiratory CO 2 pressure during the HCVR test, RR, V t , Pdi, EAdi and V E increased. The clinical ratio ΔV E /ΔP et CO 2 remained unchanged, but Pdi, EAdi and V E were significantly lower after bicarbonate administration for similar levels of inspired CO 2 . This study demonstrates that in healthy subjects metabolic alkalosis decreases the neural respiratory drive and minute ventilation, as a response to inspiratory CO 2 . Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Computational Modelling of the Metabolic States Regulated by the Kinase Akt

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Ettore eMosca

2012-11-01

Full Text Available Signal transduction pathways and gene regulation determine a major reorganization of metabolic activities in order to support cell proliferation. Protein Kinase B (PKB, also known as Akt, participates in the PI3K/Akt/mTOR pathway, a master regulator of aerobic glycolysis and cellular biosynthesis, two activities shown by both normal and cancer proliferating cells. Not surprisingly considering its relevance for cellular metabolism, Akt/PKB is often found hyperactive in cancer cells. In the last decade, many efforts have been made to improve the understanding of the control of glucose metabolism and the identification of a therapeutic window between proliferating cancer cells and proliferating normal cells. In this context, we have modelled the link between the PI3K/Akt/mTOR pathway, glycolysis, lactic acid production and nucleotide biosynthesis. We used a computational model in order to compare two metabolic states generated by the specific variation of the metabolic fluxes regulated by the activity of the PI3K/Akt/mTOR pathway. One of the two states represented the metabolism of a growing cancer cell characterised by aerobic glycolysis and cellular biosynthesis, while the other state represented the same metabolic network with a reduced glycolytic rate and a higher mitochondrial pyruvate metabolism, as reported in literature in relation to the activity of the PI3K/Akt/mTOR. Some steps that link glycolysis and pentose phosphate pathway revealed their importance for controlling the dynamics of cancer glucose metabolism.

Network analysis of metabolic enzyme evolution in Escherichia coli

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Kraulis Per

2004-02-01

Full Text Available Abstract Background The two most common models for the evolution of metabolism are the patchwork evolution model, where enzymes are thought to diverge from broad to narrow substrate specificity, and the retrograde evolution model, according to which enzymes evolve in response to substrate depletion. Analysis of the distribution of homologous enzyme pairs in the metabolic network can shed light on the respective importance of the two models. We here investigate the evolution of the metabolism in E. coli viewed as a single network using EcoCyc. Results Sequence comparison between all enzyme pairs was performed and the minimal path length (MPL between all enzyme pairs was determined. We find a strong over-representation of homologous enzymes at MPL 1. We show that the functionally similar and functionally undetermined enzyme pairs are responsible for most of the over-representation of homologous enzyme pairs at MPL 1. Conclusions The retrograde evolution model predicts that homologous enzymes pairs are at short metabolic distances from each other. In general agreement with previous studies we find that homologous enzymes occur close to each other in the network more often than expected by chance, which lends some support to the retrograde evolution model. However, we show that the homologous enzyme pairs which may have evolved through retrograde evolution, namely the pairs that are functionally dissimilar, show a weaker over-representation at MPL 1 than the functionally similar enzyme pairs. Our study indicates that, while the retrograde evolution model may have played a small part, the patchwork evolution model is the predominant process of metabolic enzyme evolution.

Metabolic imaging of tumor for diagnosis and response for therapy

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Zagaynova, Elena; Shirmanova, Marina; Lukina, Maria; Dudenkova, Varvara; Ignatova, Nadezgda; Elagin, Vadim; Shlivko, Irena; Scheslavsky, Vladislav; Orlinskay, Natalia

2018-02-01

Nonlinear optical microscopy combined with fluorescence lifetime imaging is a non-invasive imaging technique, based on the study of fluorescence decay times of naturally occurring fluorescent molecules, enabling a noninvasive investigation of the biological tissue with subcellular resolution. Cancer exhibits altered cellular metabolism, which affects the autofluorescence of metabolic cofactors NAD(P)H and FAD. In this study features of tumor metabolism in different systems of organization (from cell culture to patient lesion) was showed. The observed differences in the relative contributions of free NAD(P)H and FAD testify to an increased a glycolytic metabolism in cancer cells compare to fibroblasts. In 3D spheroids, the cells of the proliferating zone had greater a1 and lower tm values than the cells of the quiescent zone, which likely is a consequence of their higher glycolytic rate. During the growth of colorectal cancer in the experimental mouse model, the contribution of the free component of NAD(P)H was increased. Dysplastic nevus and melanoma is characterized by raised contribution of free NADH compare to healthy skin. Therefore, melanoma cells had very short value of τ1.

Dynamic modeling of lactic acid fermentation metabolism with Lactococcus lactis.

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Oh, Euhlim; Lu, Mingshou; Park, Changhun; Park, Changhun; Oh, Han Bin; Lee, Sang Yup; Lee, Jinwon

2011-02-01

A dynamic model of lactic acid fermentation using Lactococcus lactis was constructed, and a metabolic flux analysis (MFA) and metabolic control analysis (MCA) were performed to reveal an intensive metabolic understanding of lactic acid bacteria (LAB). The parameter estimation was conducted with COPASI software to construct a more accurate metabolic model. The experimental data used in the parameter estimation were obtained from an LC-MS/ MS analysis and time-course simulation study. The MFA results were a reasonable explanation of the experimental data. Through the parameter estimation, the metabolic system of lactic acid bacteria can be thoroughly understood through comparisons with the original parameters. The coefficients derived from the MCA indicated that the reaction rate of L-lactate dehydrogenase was activated by fructose 1,6-bisphosphate and pyruvate, and pyruvate appeared to be a stronger activator of L-lactate dehydrogenase than fructose 1,6-bisphosphate. Additionally, pyruvate acted as an inhibitor to pyruvate kinase and the phosphotransferase system. Glucose 6-phosphate and phosphoenolpyruvate showed activation effects on pyruvate kinase. Hexose transporter was the strongest effector on the flux through L-lactate dehydrogenase. The concentration control coefficient (CCC) showed similar results to the flux control coefficient (FCC).

Effects of Simulated Smog Atmospheres in Rodent Models of Metabolic and Immunologic Dysfunction.

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McGee Hargrove, Marie; Snow, Samantha J; Luebke, Robert W; Wood, Charles E; Krug, Jonathan D; Krantz, Q Todd; King, Charly; Copeland, Carey B; McCullough, Shaun D; Gowdy, Kymberly M; Kodavanti, Urmila P; Gilmour, M Ian; Gavett, Stephen H

2018-03-06

Air pollution is a diverse and dynamic mixture of gaseous and particulate matter, limiting our understanding of associated adverse health outcomes. The biological effects of two simulated smog atmospheres (SA) with different compositions but similar air quality health indexes were compared in a nonobese diabetic rat model (Goto-Kakizaki, GK) and three mouse immune models (house dust mite (HDM) allergy, antibody response to heat-killed pneumococcus, and resistance to influenza A infection). In GK rats, both SA-PM (high particulate matter) and SA-O 3 (high ozone) decreased cholesterol levels immediately after a 4-h exposure, whereas only SA-O 3 increased airflow limitation. Airway responsiveness to methacholine was increased in HDM-allergic mice compared with nonallergic mice, but exposure to SA-PM or SA-O 3 did not significantly alter responsiveness. Exposure to SA-PM did not affect the IgM response to pneumococcus, and SA-O 3 did not affect virus titers, although inflammatory cytokine levels were decreased in mice infected at the end of a 7-day exposure. Collectively, acute SA exposures produced limited health effects in animal models of metabolic and immune diseases. Effects of SA-O 3 tended to be greater than those of SA-PM, suggesting that gas-phase components in photochemically derived multipollutant mixtures may be of greater concern than secondary organic aerosol PM.

Prediction of residual metabolic activity after treatment in NSCLC patients

International Nuclear Information System (INIS)

Rios Velazquez, Emmanuel; Aerts, Hugo J.W.L.; Oberije, Cary; Ruysscher, Dirk De; Lambin, Philippe

2010-01-01

Purpose. Metabolic response assessment is often used as a surrogate of local failure and survival. Early identification of patients with residual metabolic activity is essential as this enables selection of patients who could potentially benefit from additional therapy. We report on the development of a pre-treatment prediction model for metabolic response using patient, tumor and treatment factors. Methods. One hundred and one patients with inoperable NSCLC (stage I-IV), treated with 3D conformal radical (chemo)-radiotherapy were retrospectively included in this study. All patients received a pre and post-radiotherapy fluorodeoxyglucose positron emission tomography-computed tomography FDG-PET-CT scan. The electronic medical record system and the medical patient charts were reviewed to obtain demographic, clinical, tumor and treatment data. Primary outcome measure was examined using a metabolic response assessment on a post-radiotherapy FDG-PET-CT scan. Radiotherapy was delivered in fractions of 1.8 Gy, twice a day, with a median prescribed dose of 60 Gy. Results. Overall survival was worse in patients with residual metabolic active areas compared with the patients with a complete metabolic response (p=0.0001). In univariate analysis, three variables were significantly associated with residual disease: larger primary gross tumor volume (GTVprimary, p=0.002), higher pre-treatment maximum standardized uptake value (SUV max , p=0.0005) in the primary tumor and shorter overall treatment time (OTT, p=0.046). A multivariate model including GTVprimary, SUV max , equivalent radiation dose at 2 Gy corrected for time (EQD2, T) and OTT yielded an area under the curve assessed by the leave-one-out cross validation of 0.71 (95% CI, 0.65-0.76). Conclusion. Our results confirmed the validity of metabolic response assessment as a surrogate of survival. We developed a multivariate model that is able to identify patients at risk of residual disease. These patients may benefit from

Drosophila as a Model to Study the Link between Metabolism and Cancer

DEFF Research Database (Denmark)

Herranz, Hector; Cohen, Stephen M.

2017-01-01

new approaches to therapy. Drosophila melanogaster is emerging as a valuable model to study multiple aspects of tumor formation and malignant transformation. In this review, we discuss the use of Drosophila as model to study how changes in cellular metabolism, as well as metabolic disease, contribute...

Metabolic regulation of inflammation.

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Gaber, Timo; Strehl, Cindy; Buttgereit, Frank

2017-05-01

Immune cells constantly patrol the body via the bloodstream and migrate into multiple tissues where they face variable and sometimes demanding environmental conditions. Nutrient and oxygen availability can vary during homeostasis, and especially during the course of an immune response, creating a demand for immune cells that are highly metabolically dynamic. As an evolutionary response, immune cells have developed different metabolic programmes to supply them with cellular energy and biomolecules, enabling them to cope with changing and challenging metabolic conditions. In the past 5 years, it has become clear that cellular metabolism affects immune cell function and differentiation, and that disease-specific metabolic configurations might provide an explanation for the dysfunctional immune responses seen in rheumatic diseases. This Review outlines the metabolic challenges faced by immune cells in states of homeostasis and inflammation, as well as the variety of metabolic configurations utilized by immune cells during differentiation and activation. Changes in cellular metabolism that contribute towards the dysfunctional immune responses seen in rheumatic diseases are also briefly discussed.

Proteomic Profiles of Adipose and Liver Tissues from an Animal Model of Metabolic Syndrome Fed Purple Vegetables

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Hala M Ayoub

2018-04-01

Full Text Available Metabolic Syndrome (MetS is a complex disorder that predisposes an individual to Cardiovascular Diseases and type 2 Diabetes Mellitus. Proteomics and bioinformatics have proven to be an effective tool to study complex diseases and mechanisms of action of nutrients. We previously showed that substitution of the majority of carbohydrate in a high fat diet by purple potatoes (PP or purple carrots (PC improved insulin sensitivity and hypertension in an animal model of MetS (obese Zucker rats compared to a control sucrose-rich diet. In the current study, we used TMT 10plex mass tag combined with LC-MS/MS technique to study proteomic modulation in the liver (n = 3 samples/diet and adipose tissue (n = 3 samples/diet of high fat diet-fed rats with or without substituting sucrose for purple vegetables, followed by functional enrichment analysis, in an attempt to elucidate potential molecular mechanisms responsible for the phenotypic changes seen with purple vegetable feeding. Protein folding, lipid metabolism and cholesterol efflux were identified as the main modulated biological themes in adipose tissue, whereas lipid metabolism, carbohydrate metabolism and oxidative stress were the main modulated themes in liver. We propose that enhanced protein folding, increased cholesterol efflux and higher free fatty acid (FFA re-esterification are mechanisms by which PP and PC positively modulate MetS pathologies in adipose tissue, whereas, decreased de novo lipogenesis, oxidative stress and FFA uptake, are responsible for the beneficial effects in liver. In conclusion, we provide molecular evidence for the reported metabolic health benefits of purple carrots and potatoes and validate that these vegetables are good choices to replace other simple carbohydrate sources for better metabolic health.

Rewiring monocyte glucose metabolism via C-type lectin signaling protects against disseminated candidiasis.

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Domínguez-Andrés, Jorge; Arts, Rob J W; Ter Horst, Rob; Gresnigt, Mark S; Smeekens, Sanne P; Ratter, Jacqueline M; Lachmandas, Ekta; Boutens, Lily; van de Veerdonk, Frank L; Joosten, Leo A B; Notebaart, Richard A; Ardavín, Carlos; Netea, Mihai G

2017-09-01

Monocytes are innate immune cells that play a pivotal role in antifungal immunity, but little is known regarding the cellular metabolic events that regulate their function during infection. Using complementary transcriptomic and immunological studies in human primary monocytes, we show that activation of monocytes by Candida albicans yeast and hyphae was accompanied by metabolic rewiring induced through C-type lectin-signaling pathways. We describe that the innate immune responses against Candida yeast are energy-demanding processes that lead to the mobilization of intracellular metabolite pools and require induction of glucose metabolism, oxidative phosphorylation and glutaminolysis, while responses to hyphae primarily rely on glycolysis. Experimental models of systemic candidiasis models validated a central role for glucose metabolism in anti-Candida immunity, as the impairment of glycolysis led to increased susceptibility in mice. Collectively, these data highlight the importance of understanding the complex network of metabolic responses triggered during infections, and unveil new potential targets for therapeutic approaches against fungal diseases.

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.

Exercise electrocardiographic responses and serum cystatin C levels among metabolic syndrome patients without overt diabetes mellitus

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Tanindi A

2011-02-01

Full Text Available Asli Tanindi1 Hilal Olgun1 Ayse Tuncel2 Bulent Celik3 Hatice Pasaoglu2 Bulent Boyaci11Department of Cardiology, 2Department of Medical Biochemistry, Faculty of Medicine, 3Department of Statistics, Faculty of Health Sciences, Gazi University, Ankara, TurkeyObjectives: An impaired heart rate response during exercise (chronotropic incompetence and an impaired heart rate recovery (HRR after exercise are predictors of cardiovascular risk and mortality. Cystatin C is a novel marker for cardiovascular disease. We aimed to investigate exercise electrocardiographic responses in patients with metabolic syndrome who were without overt diabetes mellitus, in addition to the association of serum cystatin C levels with the exercise electrocardiographic test results.Method: Forty-three consecutive patients admitted to a cardiology outpatient clinic without angina pectoris were recruited if they met criteria for metabolic syndrome but did not have overt diabetes mellitus. Serum cystatin C levels were measured, and all participants underwent exercise electrocardiographic testing. Patients who were found to have ischemia had a coronary angiography procedure.Results: The mean cystatin C level of patients was higher in metabolic syndrome group than healthy controls (610.1 ± 334.02 vs 337.3 ± 111.01 µg/L; P < 0.001. The percentage of patients with ischemia confirmed by coronary angiography was 13.9% in the metabolic syndrome group. Cystatin C levels in the ischemic patients of the metabolic syndrome group were higher than that in nonischemic patients (957.00 ± 375.6 vs 553.8 ± 295.3 µg /L; P = 0.005. Chronotropic incompetence was observed in 30.2% of the patients with metabolic syndrome compared with 16.7% in the control group (P = 0.186. Chronotropic response indices were 0.8 ± 0.18 versus 0.9 ± 0.10 for the two groups, respectively (P = 0.259. HRR was significantly lower in the metabolic syndrome patients compared with the controls (20.1 ± 8.01 vs 25.2 �

Molecular processes in cellular arsenic metabolism

International Nuclear Information System (INIS)

Thomas, David J.

2007-01-01

Elucidating molecular processes that underlie accumulation, metabolism and binding of iAs and its methylated metabolites provides a basis for understanding the modes of action by which iAs acts as a toxin and a carcinogen. One approach to this problem is to construct a conceptual model that incorporates available information on molecular processes involved in the influx, metabolism, binding and efflux of arsenicals in cells. This conceptual model is initially conceived as a non-quantitative representation of critical molecular processes that can be used as a framework for experimental design and prediction. However, with refinement and incorporation of additional data, the conceptual model can be expressed in mathematical terms and should be useful for quantitative estimates of the kinetic and dynamic behavior of iAs and its methylated metabolites in cells. Development of a quantitative model will be facilitated by the availability of tools and techniques to manipulate molecular processes underlying transport of arsenicals across cell membranes or expression and activity of enzymes involved in methylation of arsenicals. This model of cellular metabolism might be integrated into more complex pharmacokinetic models for systemic metabolism of iAs and its methylated metabolites. It may also be useful in development of biologically based dose-response models describing the toxic and carcinogenic actions of arsenicals

Immunosuppressive activity enhances central carbon metabolism and bioenergetics in myeloid-derived suppressor cells in vitro models

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Hammami Ines

2012-07-01

Full Text Available Abstract Background The tumor microenvironment contains a vast array of pro- and anti-inflammatory cytokines that alter myelopoiesis and lead to the maturation of immunosuppressive cells known as myeloid-derived suppressor cells (MDSCs. Incubating bone marrow (BM precursors with a combination of granulocyte-macrophage colony-stimulating factor (GM-CSF and interleukin-6 (IL-6 generated a tumor-infiltrating MDSC-like population that impaired anti-tumor specific T-cell functions. This in vitro experimental approach was used to simulate MDSC maturation, and the cellular metabolic response was then monitored. A complementary experimental model that inhibited L-arginine (L-Arg metabolizing enzymes in MSC-1 cells, an immortalized cell line derived from primary MDSCs, was used to study the metabolic events related to immunosuppression. Results Exposure of BM cells to GM-CSF and IL-6 activated, within 24 h, L-Arg metabolizing enzymes which are responsible for the MDSCs immunosuppressive potential. This was accompanied by an increased uptake of L-glutamine (L-Gln and glucose, the latter being metabolized by anaerobic glycolysis. The up-regulation of nutrient uptake lead to the accumulation of TCA cycle intermediates and lactate as well as the endogenous synthesis of L-Arg and the production of energy-rich nucleotides. Moreover, inhibition of L-Arg metabolism in MSC-1 cells down-regulated central carbon metabolism activity, including glycolysis, glutaminolysis and TCA cycle activity, and led to a deterioration of cell bioenergetic status. The simultaneous increase of cell specific concentrations of ATP and a decrease in ATP-to-ADP ratio in BM-derived MDSCs suggested cells were metabolically active during maturation. Moreover, AMP-activated protein kinase (AMPK was activated during MDSC maturation in GM-CSF and IL-6–treated cultures, as revealed by the continuous increase of AMP-to-ATP ratios and the phosphorylation of AMPK. Likewise, AMPK activity was

From whole body to cellular models of hepatic triglyceride metabolism: man has got to know his limitations.

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Green, Charlotte J; Pramfalk, Camilla; Morten, Karl J; Hodson, Leanne

2015-01-01

The liver is a main metabolic organ in the human body and carries out a vital role in lipid metabolism. Nonalcoholic fatty liver disease (NAFLD) is one of the most common liver diseases, encompassing a spectrum of conditions from simple fatty liver (hepatic steatosis) through to cirrhosis. Although obesity is a known risk factor for hepatic steatosis, it remains unclear what factor(s) is/are responsible for the primary event leading to retention of intrahepatocellular fat. Studying hepatic processes and the etiology and progression of disease in vivo in humans is challenging, not least as NAFLD may take years to develop. We present here a review of experimental models and approaches that have been used to assess liver triglyceride metabolism and discuss their usefulness in helping to understand the aetiology and development of NAFLD. Copyright © 2015 the American Physiological Society.

An in vitro model for screening estrogen activity of environmental samples after metabolism

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Chahbane, N.; Schramm, K.W. [GSF - Forschungszentrum fuer Umwelt und Gesundheit Neuherberg GmbH, Oberschleissheim (Germany). Inst. fuer Oekologische Chemie; Kettrup, A. [Technische Univ. Muenchen, Freising (Germany). Lehrstuhl fuer Oekologische Chemie

2004-09-15

For a few years, yeast estrogen assay (YES) was accepted as a reliable and economic model for screening of environmental estrogens. Though the chemicals directly act with estrogen receptor (ER) can be filtered out by this model, there are still chemicals act with ER only after metabolism and some chemicals eliminate their estrogen activities after metabolism. That is to say, their metabolites exert or have stronger estrogen activities than themselves, which can be called bio-activation. In this case, for the lack of the metabolism enzyme system as human and other animals, only the assay with recombinant yeast cells is insufficient. So, it is necessary to combine the YES with metabolism procedure to evaluate the estrogen activities of these chemicals. The most common method used currently for in vitro metabolic activation in mutagenicity testing and also be applied to the estrogen screening field is S-9 mixture. Also, there is an attempt to develop a chemical model for cytochrome P450 as a bio-mimetic metabolic activation system. All these methods can be used as in vitro models for metabolism. Compare with these models, using whole H4II E cells for metabolism is an alternative and with superiorities. It has the excellence of short experiment period as all other in vitro models, but is much more close to the real surroundings as in vivo. Furthermore, the activity of 7-ethoxyresorufin-O-deethylase (EROD) can be easily measured during the whole incubation period for us to discuss the metabolic activities in a quantitative foundation, not only in qualitative. Methoxychlor is one of the chemicals with bio-activation ability. When directly used in the YES, it shows weak estrogen activity. But a main metabolite of methoxychlor, 2,2-bis (p-hydroxyphenyl) - 1,1,1-trichloroethane (HPTE) is a known estrogen mimic. For the long time using methoxychlor as a pesticide and its clear background, it is an ideal chemical to establish this in vitro system.

Metabolic Compensation and Circadian Resilience in Prokaryotic Cyanobacteria

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Johnson, Carl Hirschie; Egli, Martin

2014-01-01

For a biological oscillator to function as a circadian pacemaker that confers a fitness advantage, its timing functions must be stable in response to environmental and metabolic fluctuations. One such stability enhancer, temperature compensation, has long been a defining characteristic of these timekeepers. However, an accurate biological timekeeper must also resist changes in metabolism, and this review suggests that temperature compensation is actually a subset of a larger phenomenon, namely metabolic compensation, which maintains the frequency of circadian oscillators in response to a host of factors that impinge on metabolism and would otherwise destabilize these clocks. The circadian system of prokaryotic cyanobacteria is an illustrative model because it is composed of transcriptional and nontranscriptional oscillators that are coupled to promote resilience. Moreover, the cyanobacterial circadian program regulates gene activity and metabolic pathways, and it can be manipulated to improve the expression of bioproducts that have practical value. PMID:24905782

Metabolic responses to high protein diet in Korean elite bodybuilders with high-intensity resistance exercise

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Choue Ryowon

2011-07-01

Full Text Available Abstract Background High protein diet has been known to cause metabolic acidosis, which is manifested by increased urinary excretion of nitrogen and calcium. Bodybuilders habitually consumed excessive dietary protein over the amounts recommended for them to promote muscle mass accretion. This study investigated the metabolic response to high protein consumption in the elite bodybuilders. Methods Eight elite Korean bodybuilders within the age from 18 to 25, mean age 21.5 ± 2.6. For data collection, anthropometry, blood and urinary analysis, and dietary assessment were conducted. Results They consumed large amounts of protein (4.3 ± 1.2 g/kg BW/day and calories (5,621.7 ± 1,354.7 kcal/day, as well as more than the recommended amounts of vitamins and minerals, including potassium and calcium. Serum creatinine (1.3 ± 0.1 mg/dl and potassium (5.9 ± 0.8 mmol/L, and urinary urea nitrogen (24.7 ± 9.5 mg/dl and creatinine (2.3 ± 0.7 mg/dl were observed to be higher than the normal reference ranges. Urinary calcium (0.3 ± 0.1 mg/dl, and phosphorus (1.3 ± 0.4 mg/dl were on the border of upper limit of the reference range and the urine pH was in normal range. Conclusions Increased urinary excretion of urea nitrogen and creatinine might be due to the high rates of protein metabolism that follow high protein intake and muscle turnover. The obvious evidence of metabolic acidosis in response to high protein diet in the subjects with high potassium intake and intensive resistance exercise were not shown in this study results. However, this study implied that resistance exercise with adequate mineral supplementation, such as potassium and calcium, could reduce or offset the negative effects of protein-generated metabolic changes. This study provides preliminary information of metabolic response to high protein intake in bodybuilders who engaged in high-intensity resistance exercise. Further studies will be needed to determine the effects of the intensity

Metabolic modeling of synthesis gas fermentation in bubble column reactors.

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Chen, Jin; Gomez, Jose A; Höffner, Kai; Barton, Paul I; Henson, Michael A

2015-01-01

A promising route to renewable liquid fuels and chemicals is the fermentation of synthesis gas (syngas) streams to synthesize desired products such as ethanol and 2,3-butanediol. While commercial development of syngas fermentation technology is underway, an unmet need is the development of integrated metabolic and transport models for industrially relevant syngas bubble column reactors. We developed and evaluated a spatiotemporal metabolic model for bubble column reactors with the syngas fermenting bacterium Clostridium ljungdahlii as the microbial catalyst. Our modeling approach involved combining a genome-scale reconstruction of C. ljungdahlii metabolism with multiphase transport equations that govern convective and dispersive processes within the spatially varying column. The reactor model was spatially discretized to yield a large set of ordinary differential equations (ODEs) in time with embedded linear programs (LPs) and solved using the MATLAB based code DFBAlab. Simulations were performed to analyze the effects of important process and cellular parameters on key measures of reactor performance including ethanol titer, ethanol-to-acetate ratio, and CO and H2 conversions. Our computational study demonstrated that mathematical modeling provides a complementary tool to experimentation for understanding, predicting, and optimizing syngas fermentation reactors. These model predictions could guide future cellular and process engineering efforts aimed at alleviating bottlenecks to biochemical production in syngas bubble column reactors.

The structure of wheat bread influences the postprandial metabolic response in healthy men

NARCIS (Netherlands)

Eelderink, Coby; Noort, Martijn W. J.; Sozer, Nesli; Koehorst, Martijn; Holst, Jens J.; Deacon, Carolyn F.; Rehfeld, Jens F.; Poutanen, Kaisa; Vonk, Roel J.; Oudhuis, Lizette; Priebe, Marion G.

2015-01-01

Postprandial high glucose and insulin responses after starchy food consumption, associated with an increased risk of developing several metabolic diseases, could possibly be improved by altering food structure. We investigated the influence of a compact food structure; different wheat products with

Norepinephrine metabolism in humans. Kinetic analysis and model

International Nuclear Information System (INIS)

Linares, O.A.; Jacquez, J.A.; Zech, L.A.; Smith, M.J.; Sanfield, J.A.; Morrow, L.A.; Rosen, S.G.; Halter, J.B.

1987-01-01

The present study was undertaken to quantify more precisely and to begin to address the problem of heterogeneity of the kinetics of distribution and metabolism of norepinephrine (NE) in humans, by using compartmental analysis. Steady-state NE specific activity in arterialized plasma during [ 3 H]NE infusion and postinfusion plasma disappearance of [ 3 H]NE were measured in eight healthy subjects in the supine and upright positions. Two exponentials were clearly identified in the plasma [ 3 H]NE disappearance curves of each subject studied in the supine (r = 0.94-1.00, all P less than 0.01) and upright (r = 0.90-0.98, all P less than 0.01) positions. A two-compartment model was the minimal model necessary to simultaneously describe the kinetics of NE in the supine and upright positions. The NE input rate into the extravascular compartment 2, estimated with the minimal model, increased with upright posture (1.87 +/- 0.08 vs. 3.25 +/- 0.2 micrograms/min per m2, P less than 0.001). Upright posture was associated with a fall in the volume of distribution of NE in compartment 1 (7.5 +/- 0.6 vs. 4.7 +/- 0.3 liters, P less than 0.001), and as a result of that, there was a fall in the metabolic clearance rate of NE from compartment 1 (1.80 +/- 0.11 vs. 1.21 +/- 0.08 liters/min per m2, P less than 0.001). We conclude that a two-compartment model is the minimal model that can accurately describe the kinetics of distribution and metabolism of NE in humans

Genome-scale metabolic models applied to human health and disease.

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Cook, Daniel J; Nielsen, Jens

2017-11-01

Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

Metabolic responses to pyruvate kinase deletion in lysine producing Corynebacterium glutamicum

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Wittmann Christoph

2008-03-01

Full Text Available Abstract Background Pyruvate kinase is an important element in flux control of the intermediate metabolism. It catalyzes the irreversible conversion of phosphoenolpyruvate into pyruvate and is under allosteric control. In Corynebacterium glutamicum, this enzyme was regarded as promising target for improved production of lysine, one of the major amino acids in animal nutrition. In pyruvate kinase deficient strains the required equimolar ratio of the two lysine precursors oxaloacetate and pyruvate can be achieved through concerted action of the phosphotransferase system (PTS and phosphoenolpyruvate carboxylase (PEPC, whereby a reduced amount of carbon may be lost as CO2 due to reduced flux into the tricarboxylic acid (TCA cycle. In previous studies, deletion of pyruvate kinase in lysine-producing C. glutamicum, however, did not yield a clear picture and the exact metabolic consequences are not fully understood. Results In this work, deletion of the pyk gene, encoding pyruvate kinase, was carried out in the lysine-producing strain C. glutamicum lysCfbr, expressing a feedback resistant aspartokinase, to investigate the cellular response to deletion of this central glycolytic enzyme. Pyk deletion was achieved by allelic replacement, verified by PCR analysis and the lack of in vitro enzyme activity. The deletion mutant showed an overall growth behavior (specific growth rate, glucose uptake rate, biomass yield which was very similar to that of the parent strain, but differed in slightly reduced lysine formation, increased formation of the overflow metabolites dihydroxyacetone and glycerol and in metabolic fluxes around the pyruvate node. The latter involved a flux shift from pyruvate carboxylase (PC to PEPC, by which the cell maintained anaplerotic supply of the TCA cycle. This created a metabolic by-pass from PEP to pyruvate via malic enzyme demonstrating its contribution to metabolic flexibility of C. glutamicum on glucose. Conclusion The metabolic

Formulation, construction and analysis of kinetic models of metabolism: A review of modelling frameworks

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Saa, Pedro A.; Nielsen, Lars K.

2017-01-01

Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive ca...

METABOLIC MODELLING IN THE DEVELOPMENT OF CELL FACTORIES BY SYNTHETIC BIOLOGY

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Paula Jouhten

2012-10-01

Full Text Available Cell factories are commonly microbial organisms utilized for bioconversion of renewable resources to bulk or high value chemicals. Introduction of novel production pathways in chassis strains is the core of the development of cell factories by synthetic biology. Synthetic biology aims to create novel biological functions and systems not found in nature by combining biology with engineering. The workflow of the development of novel cell factories with synthetic biology is ideally linear which will be attainable with the quantitative engineering approach, high-quality predictive models, and libraries of well-characterized parts. Different types of metabolic models, mathematical representations of metabolism and its components, enzymes and metabolites, are useful in particular phases of the synthetic biology workflow. In this minireview, the role of metabolic modelling in synthetic biology will be discussed with a review of current status of compatible methods and models for the in silico design and quantitative evaluation of a cell factory.

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

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Song, Hyun-Seob; Thomas, Dennis G.; Stegen, James C.; Li, Minjing; Liu, Chongxuan; Song, Xuehang; Chen, Xingyuan; Fredrickson, Jim K.; Zachara, John M.; Scheibe, Timothy D.

2017-09-29

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accounted for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.

Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data

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Kansuporn eSriyudthsak

2016-05-01

Full Text Available The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

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Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota

2016-01-01

The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

Metabolic response to glatiramer acetate therapy in multiple sclerosis patients

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Lidia De Riccardis

2016-12-01

Full Text Available Glatiramer acetate (GA; Copaxone is a random copolymer of glutamic acid, lysine, alanine, and tyrosine used for the treatment of patients with multiple sclerosis (MS. Its mechanism of action has not been already fully elucidated, but it seems that GA has an immune-modulatory effect and neuro-protective properties. Lymphocyte mitochondrial dysfunction underlines the onset of several autoimmune disorders. In MS first diagnosis patients, CD4+, the main T cell subset involved in the pathogenesis of MS, undergo a metabolic reprogramming that consist in the up-regulation of glycolysis and in the down-regulation of oxidative phosphorylation. Currently, no works exist about CD4+ T cell metabolism in response to GA treatment. In order to provide novel insight into the potential use of GA in MS treatment, blood samples were collected from 20 healthy controls (HCs and from 20 RR MS patients prior and every 6 months during the 12 months of GA administration. GA treated patients' CD4+ T cells were compared with those from HCs analysing their mitochondrial activity through polarographic and enzymatic methods in association with their antioxidant status, through the analysis of SOD, GPx and CAT activities. Altogether, our findings suggest that GA is able to reduce CD4+ T lymphocytes' dysfunctions by increasing mitochondrial activity and their response to oxidative stress.

Metabolic response to glatiramer acetate therapy in multiple sclerosis patients.

Science.gov (United States)

De Riccardis, Lidia; Ferramosca, Alessandra; Danieli, Antonio; Trianni, Giorgio; Zara, Vincenzo; De Robertis, Francesca; Maffia, Michele

2016-12-01

Glatiramer acetate (GA; Copaxone) is a random copolymer of glutamic acid, lysine, alanine, and tyrosine used for the treatment of patients with multiple sclerosis (MS). Its mechanism of action has not been already fully elucidated, but it seems that GA has an immune-modulatory effect and neuro-protective properties. Lymphocyte mitochondrial dysfunction underlines the onset of several autoimmune disorders. In MS first diagnosis patients, CD4 + , the main T cell subset involved in the pathogenesis of MS, undergo a metabolic reprogramming that consist in the up-regulation of glycolysis and in the down-regulation of oxidative phosphorylation. Currently, no works exist about CD4 + T cell metabolism in response to GA treatment. In order to provide novel insight into the potential use of GA in MS treatment, blood samples were collected from 20 healthy controls (HCs) and from 20 RR MS patients prior and every 6 months during the 12 months of GA administration. GA treated patients' CD4 + T cells were compared with those from HCs analysing their mitochondrial activity through polarographic and enzymatic methods in association with their antioxidant status, through the analysis of SOD, GPx and CAT activities. Altogether, our findings suggest that GA is able to reduce CD4 + T lymphocytes' dysfunctions by increasing mitochondrial activity and their response to oxidative stress.

Data-driven integration of genome-scale regulatory and metabolic network models

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Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

2015-01-01

Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

Global host metabolic response to Plasmodium vivax infection: a 1H NMR based urinary metabonomic study

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Sengupta Arjun

2011-12-01

Full Text Available Abstract Background Plasmodium vivax is responsible for the majority of malarial infection in the Indian subcontinent. This species of the parasite is generally believed to cause a relatively benign form of the disease. However, recent reports from different parts of the world indicate that vivax malaria can also have severe manifestation. Host response to the parasite invasion is thought to be an important factor in determining the severity of manifestation. In this paper, attempt was made to determine the host metabolic response associated with P. vivax infection by means of NMR spectroscopy-based metabonomic techniques in an attempt to better understand the disease pathology. Methods NMR spectroscopy of urine samples from P. vivax-infected patients, healthy individuals and non-malarial fever patients were carried out followed by multivariate statistical analysis. Two data analysis techniques were employed, namely, Principal Component Analysis [PCA] and Orthogonal Projection to Latent Structure Discriminant Analysis [OPLS-DA]. Several NMR signals from the urinary metabolites were further selected for univariate comparison among the classes. Results The urine metabolic profiles of P. vivax-infected patients were distinct from those of healthy individuals as well as of non-malarial fever patients. A highly predictive model was constructed from urine profile of malarial and non-malarial fever patients. Several metabolites were found to be varying significantly across these cohorts. Urinary ornithine seems to have the potential to be used as biomarkers of vivax malaria. An increasing trend in pipecolic acid was also observed. The results suggest impairment in the functioning of liver as well as impairment in urea cycle. Conclusions The results open up a possibility of non-invasive analysis and diagnosis of P. vivax using urine metabolic profile. Distinct variations in certain metabolites were recorded, and amongst these, ornithine may have the

Plasma proteome profiles associated with diet-induced metabolic syndrome and the early onset of metabolic syndrome in a pig model.

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Marinus F W te Pas

Full Text Available Obesity and related diabetes are important health threatening multifactorial metabolic diseases and it has been suggested that 25% of all diabetic patients are unaware of their patho-physiological condition. Biomarkers for monitoring and control are available, but early stage predictive biomarkers enabling prevention of these diseases are still lacking. We used the pig as a model to study metabolic disease because humans and pigs share a multitude of metabolic similarities. Diabetes was chemically induced and control and diabetic pigs were either fed a high unsaturated fat (Mediterranean diet or a high saturated fat/cholesterol/sugar (cafeteria diet. Physiological parameters related to fat metabolism and diabetes were measured. Diabetic pigs' plasma proteome profiles differed more between the two diets than control pigs plasma proteome profiles. The expression levels of several proteins correlated well with (pathophysiological parameters related to the fat metabolism (cholesterol, VLDL, LDL, NEFA and diabetes (Glucose and to the diet fed to the animals. Studying only the control pigs as a model for metabolic syndrome when fed the two diets showed correlations to the same parameters but now more focused on insulin, glucose and abdominal fat depot parameters. We conclude that proteomic profiles can be used as a biomarker to identify pigs with developing metabolic syndrome (prediabetes and diabetes when fed a cafeteria diet. It could be developed into a potential biomarkers for the early recognition of metabolic diseases.

[Dissociation of antihypertensive and metabolic response to losartan and spironolactone in experimental rats with metabolic sindrome].

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Machado, Hussen; Pinheiro, Helady Sanders; Terra, Marcella Martins; Guerra, Martha de Oliveira; de Paula, Rogerio Baumgratz; Peters, Vera Maria

2012-01-01

The treatment of arterial hypertension (AH) in patients with metabolic syndrome (MS) is a challenge, since non drug therapies are difficult to implement and optimal pharmacological treatment is not fully established. To assess the blockade of the rennin angiotensin aldosterone system (RAAS) in blood pressure (BP) in renal function and morphology in an experimental model of MS induced by high fat diet. Wistar rats were fed on high fat diet from the fourth week of life, for 20 weeks. The groups received Losartan or Spironolactone from the eighth week of life. We weekly evaluated the body weight and BP by tail plethysmography. At the end of the experiment oral glucose tolerance, lipid profile, creatinine clearance tests, and the direct measurement of BP were performed. A morphometric kidney analysis was performed. The administration of high-fat diet was associated with the development of MS, characterized by central fat accumulation, hypertension, hyperglycemia and hypertriglyceridemia. In this model there were no changes in renal histomorphometry. The blockade of angiotensin II (Ang II) receptor AT1 prevented the development of hypertension. The mineralocorticoid blockage did not have antihypertensive efficacy but was associated with reduction of abdominal fat. The dissociation of the antihypertensive response to the blockades of Ang II receptors and mineralocorticoid indicates the involvement of Ang II in the pathogenesis of hypertension associated with obesity. Reduction of central obesity with Spironolactone suggests the presence of mineralocorticoid adipogenic effect.

MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases

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Kumar Akhil

2012-01-01

Full Text Available Abstract Background Increasingly, metabolite and reaction information is organized in the form of genome-scale metabolic reconstructions that describe the reaction stoichiometry, directionality, and gene to protein to reaction associations. A key bottleneck in the pace of reconstruction of new, high-quality metabolic models is the inability to directly make use of metabolite/reaction information from biological databases or other models due to incompatibilities in content representation (i.e., metabolites with multiple names across databases and models, stoichiometric errors such as elemental or charge imbalances, and incomplete atomistic detail (e.g., use of generic R-group or non-explicit specification of stereo-specificity. Description MetRxn is a knowledgebase that includes standardized metabolite and reaction descriptions by integrating information from BRENDA, KEGG, MetaCyc, Reactome.org and 44 metabolic models into a single unified data set. All metabolite entries have matched synonyms, resolved protonation states, and are linked to unique structures. All reaction entries are elementally and charge balanced. This is accomplished through the use of a workflow of lexicographic, phonetic, and structural comparison algorithms. MetRxn allows for the download of standardized versions of existing genome-scale metabolic models and the use of metabolic information for the rapid reconstruction of new ones. Conclusions The standardization in description allows for the direct comparison of the metabolite and reaction content between metabolic models and databases and the exhaustive prospecting of pathways for biotechnological production. This ever-growing dataset currently consists of over 76,000 metabolites participating in more than 72,000 reactions (including unresolved entries. MetRxn is hosted on a web-based platform that uses relational database models (MySQL.

Cardiovascular-renal and metabolic characterization of a rat model of polycystic ovary syndrome.

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Yanes, Licy L; Romero, Damian G; Moulana, Mohaddetheh; Lima, Roberta; Davis, Deborah D; Zhang, Huimin; Lockhart, Rachel; Racusen, Lorraine C; Reckelhoff, Jane F

2011-04-01

Polycystic ovary syndrome (PCOS) is the most common reproductive dysfunction in premenopausal women. PCOS is also associated with increased risk of cardiovascular disease when PCOS first occurs and later in life. Hypertension, a common finding in women with PCOS, is a leading risk factor for cardiovascular disease. The mechanisms responsible for hypertension in women with PCOS have not been elucidated. This study characterized the cardiovascular-renal consequences of hyperandrogenemia in a female rat model. Female Sprague-Dawley rats (aged 4-6 weeks) were implanted with dihydrotestosterone or placebo pellets lasting 90 days. After 10 to 12 weeks, blood pressure (by radiotelemetry), renal function (glomerular filtration rate, morphology, protein, and albumin excretion), metabolic parameters (plasma insulin, glucose, leptin, cholesterol, and oral glucose tolerance test), inflammation (plasma tumor necrosis factor-α), oxidative stress (mRNA expression of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunits, p22(phox), p47(phox), gp91(phox), and NOX4), nitrate/nitrite excretion and mRNA expression of components of the renin-angiotensin system (angiotensinogen, angiotensin-I-converting enzyme [ACE], and AT1 receptor) were determined. Plasma dihydrotestosterone increased 3-fold in hyperandrogenemic female (HAF) rats, whereas plasma estradiol levels did not differ compared with control females. HAF rats exhibited estrus cycle dysfunction. They also had increased food intake and body weight, increased visceral fat, glomerular filtration rate, renal injury, insulin resistance and metabolic dysfunction, oxidative stress, and increased expression of angiotensinogen and ACE and reduced AT1 receptor expression. The HAF rat is a unique model that exhibits many of the characteristics of PCOS in women and is a useful model to study the mechanisms responsible for PCOS-mediated hypertension. Copyright © 2011 Elsevier HS Journals, Inc. All rights reserved.

Genetic dissection in a mouse model reveals interactions between carotenoids and lipid metabolism.

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Palczewski, Grzegorz; Widjaja-Adhi, M Airanthi K; Amengual, Jaume; Golczak, Marcin; von Lintig, Johannes

2016-09-01

Carotenoids affect a rich variety of physiological functions in nature and are beneficial for human health. However, knowledge about their biological action and the consequences of their dietary accumulation in mammals is limited. Progress in this research field is limited by the expeditious metabolism of carotenoids in rodents and the confounding production of apocarotenoid signaling molecules. Herein, we established a mouse model lacking the enzymes responsible for carotenoid catabolism and apocarotenoid production, fed on either a β-carotene- or a zeaxanthin-enriched diet. Applying a genome wide microarray analysis, we assessed the effects of the parent carotenoids on the liver transcriptome. Our analysis documented changes in pathways for liver lipid metabolism and mitochondrial respiration. We biochemically defined these effects, and observed that β-carotene accumulation resulted in an elevation of liver triglycerides and liver cholesterol, while zeaxanthin accumulation increased serum cholesterol levels. We further show that carotenoids were predominantly transported within HDL particles in the serum of mice. Finally, we provide evidence that carotenoid accumulation influenced whole-body respiration and energy expenditure. Thus, we observed that accumulation of parent carotenoids interacts with lipid metabolism and that structurally related carotenoids display distinct biological functions in mammals. Copyright © 2016 by the American Society for Biochemistry and Molecular Biology, Inc.

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

Chromium supplementation enhances the metabolic response of steers to lipopolysaccharide (LPS) challenge

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The effect of chromium (Cr; KemTRACE®brandChromiumProprionate 0.04%, Kemin Industries) supplementation on the metabolic response to LPS challenge was examined. Steers (n=20; 235±4 kg body weight (BW)) received a premix that added 0 (Con) or 0.2 mg/kg Cr to the total diet (DM (dry matter) basis) for ...

Response to ‘comment on recent modeling studies of astrocyte–neuron metabolic interactions': much ado about nothing

OpenAIRE

Mangia, Silvia; DiNuzzo, Mauro; Giove, Federico; Carruthers, Anthony; Simpson, Ian A; Vannucci, Susan J

2011-01-01

For many years, a tenet of cerebral metabolism held that glucose was the obligate energy substrate of the mammalian brain and that neuronal oxidative metabolism represented the majority of this glucose utilization. In 1994, Pellerin and Magistretti formulated the astrocyte–neuron lactate shuttle (ANLS) hypothesis, in which astrocytes, not neurons, metabolized glucose, with subsequent transport of the glycolytically derived lactate to fuel the energy needs of the neuron during neurotransmissio...

Effect of dietary restriction on immune response of laboratory mice divergently selected for basal metabolic rate.

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Książek, Aneta; Konarzewski, Marek

2012-01-01

To study whether dietary restriction (DR; 70% of ad lib. feeding)-elicited immunosuppression results from the trade-off between the costs of mounting an immune response and the metabolic costs of maintenance, we subjected mice from two divergent lines selected for high basal metabolic rate (H-BMR) and low BMR (L-BMR) to 4 wk of DR and then challenged them with keyhole limpet hemocyanin (KLH) antigen. Those line types differ genetically with respect to BMR and to the mass of metabolically expensive internal organs, which are larger in H-BMR mice. In mice of both line types, DR resulted in a significant reduction of body mass, an immune response, and the downsizing of spleen, lymph nodes, thymus, heart, and kidneys but not small intestines. DR resulted in a greater reduction of the spleen and lymph nodes in mice of the H-BMR line type, whereas the thymus was more affected in L-BMR line type. In contrast, immunization resulted in an increase of liver mass in DR mice of both line types. A comparison of the results of current and earlier studies on the same mouse line types suggests that metabolic trade-offs involving the costs of an immune response are more apparent when animals are forced to increase energy demands (e.g., by cold exposure) compared to when energy demands are decreased through DR. Our findings also suggest that divelrgent selection on BMR resulted in between-line-type differences in T-cell- and B-cell-mediated types of an immune response. More generally, our results indicate that production of a wide repertoire of antibodies is not correlated with high BMR.

Metabolic Effects of Inflammation on Vitamin A and Carotenoids in Humans and Animal Models.

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Rubin, Lewis P; Ross, A Catharine; Stephensen, Charles B; Bohn, Torsten; Tanumihardjo, Sherry A

2017-03-01

The association between inflammation and vitamin A (VA) metabolism and status assessment has been documented in multiple studies with animals and humans. The relation between inflammation and carotenoid status is less clear. Nonetheless, it is well known that carotenoids are associated with certain health benefits. Understanding these relations is key to improving health outcomes and mortality risk in infants and young children. Hyporetinolemia, i.e., low serum retinol concentrations, occurs during inflammation, and this can lead to the misdiagnosis of VA deficiency. On the other hand, inflammation causes impaired VA absorption and urinary losses that can precipitate VA deficiency in at-risk groups of children. Many epidemiologic studies have suggested that high dietary carotenoid intake and elevated plasma concentrations are correlated with a decreased risk of several chronic diseases; however, large-scale carotenoid supplementation trials have been unable to confirm the health benefits and in some cases resulted in controversial results. However, it has been documented that dietary carotenoids and retinoids play important roles in innate and acquired immunity and in the body's response to inflammation. Although animal models have been useful in investigating retinoid effects on developmental immunity, it is more challenging to tease out the effects of carotenoids because of differences in the absorption, kinetics, and metabolism between humans and animal models. The current understanding of the relations between inflammation and retinoid and carotenoid metabolism and status are the topics of this review. © 2017 American Society for Nutrition.

Multisite Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate

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Pedro A. Gómez Damián

2014-01-01

Full Text Available Hyperpolarized 13C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1-13C]pyruvate and downstream metabolites [1-13C]alanine, [1-13C]lactate, and [13C]bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multisite, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multisite model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multisite model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues.

Transcriptional and metabolic effects of glucose on Streptococcus pneumoniae sugar metabolism

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Laura ePaixão

2015-10-01

Full Text Available Streptococcus pneumoniae is a strictly fermentative human pathogen that relies on carbohydrate metabolism to generate energy for growth. The nasopharynx colonised by the bacterium is poor in free sugars, but mucosa lining glycans can provide a source of sugar. In blood and inflamed tissues glucose is the prevailing sugar. As a result during progression from colonisation to disease S. pneumoniae has to cope with a pronounced shift in carbohydrate nature and availability. Thus, we set out to assess the pneumococcal response to sugars found in glycans and the influence of glucose (Glc on this response at the transcriptional, physiological and metabolic levels. Galactose (Gal, N-acetylglucosamine (GlcNAc and mannose (Man affected the expression of 8 to 14% of the genes covering cellular functions including central carbon metabolism and virulence. The pattern of end-products as monitored by in vivo 13C-NMR is in good agreement with the fermentation profiles during growth, while the pools of phosphorylated metabolites are consistent with the type of fermentation observed (homolactic vs. mixed and regulation at the metabolic level. Furthermore, the accumulation of α-Gal6P and Man6P indicate metabolic bottlenecks in the metabolism of Gal and Man, respectively. Glc added to cells actively metabolizing other sugar(s was readily consumed and elicited a metabolic shift towards a homolactic profile. The transcriptional response to Glc was large (over 5% of the genome. In central carbon metabolism (most represented category, Glc exerted mostly negative regulation. The smallest response to Glc was observed on a sugar mix, suggesting that exposure to varied sugars improves the fitness of S. pneumoniae. The expression of virulence factors was negatively controlled by Glc in a sugar-dependent manner. Overall, our results shed new light on the link between carbohydrate metabolism, adaptation to host niches and virulence.

Transcriptional and metabolic effects of glucose on Streptococcus pneumoniae sugar metabolism.

Science.gov (United States)

Paixão, Laura; Caldas, José; Kloosterman, Tomas G; Kuipers, Oscar P; Vinga, Susana; Neves, Ana R

2015-01-01

Streptococcus pneumoniae is a strictly fermentative human pathogen that relies on carbohydrate metabolism to generate energy for growth. The nasopharynx colonized by the bacterium is poor in free sugars, but mucosa lining glycans can provide a source of sugar. In blood and inflamed tissues glucose is the prevailing sugar. As a result during progression from colonization to disease S. pneumoniae has to cope with a pronounced shift in carbohydrate nature and availability. Thus, we set out to assess the pneumococcal response to sugars found in glycans and the influence of glucose (Glc) on this response at the transcriptional, physiological, and metabolic levels. Galactose (Gal), N-acetylglucosamine (GlcNAc), and mannose (Man) affected the expression of 8 to 14% of the genes covering cellular functions including central carbon metabolism and virulence. The pattern of end-products as monitored by in vivo (13)C-NMR is in good agreement with the fermentation profiles during growth, while the pools of phosphorylated metabolites are consistent with the type of fermentation observed (homolactic vs. mixed) and regulation at the metabolic level. Furthermore, the accumulation of α-Gal6P and Man6P indicate metabolic bottlenecks in the metabolism of Gal and Man, respectively. Glc added to cells actively metabolizing other sugar(s) was readily consumed and elicited a metabolic shift toward a homolactic profile. The transcriptional response to Glc was large (over 5% of the genome). In central carbon metabolism (most represented category), Glc exerted mostly negative regulation. The smallest response to Glc was observed on a sugar mix, suggesting that exposure to varied sugars improves the fitness of S. pneumoniae. The expression of virulence factors was negatively controlled by Glc in a sugar-dependent manner. Overall, our results shed new light on the link between carbohydrate metabolism, adaptation to host niches and virulence.

DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

Science.gov (United States)

Smith, Robert W; van Rosmalen, Rik P; Martins Dos Santos, Vitor A P; Fleck, Christian

2018-06-19

Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values. This greatly reduces the mathematical complexity, while providing a reasonably good description of the system in steady state. However, without a large number of constraints, many different flux sets can describe the optimal model and we obtain no information on how metabolite levels dynamically change. Thus, to accurately determine what is taking place within the cell, finer quality data and more detailed models need to be constructed. In this paper we present a computational framework, DMPy, that uses a network scheme as input to automatically search for kinetic rates and produce a mathematical model that describes temporal changes of metabolite fluxes. The parameter search utilises several online databases to find measured reaction parameters. From this, we take advantage of previous modelling efforts, such as Parameter Balancing, to produce an initial mathematical model of a metabolic pathway. We analyse the effect of parameter uncertainty on model dynamics and test how recent flux-based model reduction techniques alter system properties. To our knowledge this is the first time such analysis has been performed on large models of metabolism. Our results highlight that good estimates of at least 80% of the reaction rates are required to accurately model metabolic systems. Furthermore, reducing the size of the model by grouping reactions together based on fluxes alters the resulting system dynamics. The presented pipeline automates the

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

Science.gov (United States)

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.

Metabolic responses to high protein diet in Korean elite bodybuilders with high-intensity resistance exercise

OpenAIRE

Kim, Hyerang; Lee, Saningun; Choue, Ryowon

2011-01-01

Abstract Background High protein diet has been known to cause metabolic acidosis, which is manifested by increased urinary excretion of nitrogen and calcium. Bodybuilders habitually consumed excessive dietary protein over the amounts recommended for them to promote muscle mass accretion. This study investigated the metabolic response to high protein consumption in the elite bodybuilders. Methods Eight elite Korean bodybuilders within the age from 18 to 25, mean age 21.5 ± 2.6. For data collec...

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

Energy Technology Data Exchange (ETDEWEB)

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

2015-12-22

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in

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...

Data-driven integration of genome-scale regulatory and metabolic network models

Directory of Open Access Journals (Sweden)

Saheed eImam

2015-05-01

Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

Osteoarthritis and metabolic dysregulation: insights from a preclinical model

NARCIS (Netherlands)

Visser, H.M. de

2018-01-01

This thesis aims to identify the effect of metabolic factors, inflammatory processes and obesity in the pathophysiology of osteoarthritis (OA), using a high-fat diet and/or traumatic injury in a small animal model. The first part of this thesis describes, the rat Groove model of OA, using a one-time

Alterations in cellular metabolism modulate CD1d-mediated NKT-cell responses.

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Webb, Tonya J; Carey, Gregory B; East, James E; Sun, Wenji; Bollino, Dominique R; Kimball, Amy S; Brutkiewicz, Randy R

2016-08-01

Natural killer T (NKT) cells play a critical role in the host's innate immune response. CD1d-mediated presentation of glycolipid antigens to NKT cells has been established; however, the mechanisms by which NKT cells recognize infected or cancerous cells remain unclear. 5(')-AMP activated protein kinase (AMPK) is a master regulator of lipogenic pathways. We hypothesized that activation of AMPK during infection and malignancy could alter the repertoire of antigens presented by CD1d and serve as a danger signal to NKT cells. In this study, we examined the effect of alterations in metabolism on CD1d-mediated antigen presentation to NKT cells and found that an infection with lymphocytic choriomeningitis virus rapidly increased CD1d-mediated antigen presentation. Hypoxia inducible factors (HIF) enhance T-cell effector functions during infection, therefore antigen presenting cells pretreated with pharmacological agents that inhibit glycolysis, induce HIF and activate AMPK were assessed for their ability to induce NKT-cell responses. Pretreatment with 2-deoxyglucose, cobalt chloride, AICAR and metformin significantly enhanced CD1d-mediated NKT-cell activation. In addition, NKT cells preferentially respond to malignant B cells and B-cell lymphomas express HIF-1α. These data suggest that targeting cellular metabolism may serve as a novel means of inducing innate immune responses. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Metabolomics Analysis of Hormone-Responsive and Triple-Negative Breast Cancer Cell Responses to Paclitaxel Identify Key Metabolic Differences.

Science.gov (United States)

Stewart, Delisha A; Winnike, Jason H; McRitchie, Susan L; Clark, Robert F; Pathmasiri, Wimal W; Sumner, Susan J

2016-09-02

To date, no targeted therapies are available to treat triple negative breast cancer (TNBC), while other breast cancer subtypes are responsive to current therapeutic treatment. Metabolomics was conducted to reveal differences in two hormone receptor-negative TNBC cell lines and two hormone receptor-positive Luminal A cell lines. Studies were conducted in the presence and absence of paclitaxel (Taxol). TNBC cell lines had higher levels of amino acids, branched-chain amino acids, nucleotides, and nucleotide sugars and lower levels of proliferation-related metabolites like choline compared with Luminal A cell lines. In the presence of paclitaxel, each cell line showed unique metabolic responses, with some similarities by type. For example, in the Luminal A cell lines, levels of lactate and creatine decreased while certain choline metabolites and myo-inositol increased with paclitaxel. In the TNBC cell lines levels of glutamine, glutamate, and glutathione increased, whereas lysine, proline, and valine decreased in the presence of drug. Profiling secreted inflammatory cytokines in the conditioned media demonstrated a greater response to paclitaxel in the hormone-positive Luminal cells compared with a secretion profile that suggested greater drug resistance in the TNBC cells. The most significant differences distinguishing the cell types based on pathway enrichment analyses were related to amino acid, lipid and carbohydrate metabolism pathways, whereas several biological pathways were differentiated between the cell lines following treatment.

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

Directory of Open Access Journals (Sweden)

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.

Antioxidant gene expression and metabolic responses of earthworms (Eisenia fetida) after exposure to various concentrations of hexabromocyclododecane.

Science.gov (United States)

Shi, Yajuan; Xu, Xiangbo; Chen, Juan; Liang, Ruoyu; Zheng, Xiaoqi; Shi, Yajing; Wang, Yurong

2018-01-01

Hexabromocyclododecane (HBCD), a ubiquitous suspected contaminant, is one of the world's most prominent brominated flame retardants (BFRs). In the present study, earthworms (Eisenia fetida) were exposed to HBCD. The expression of selected antioxidant enzyme genes was measured, and the metabolic responses were assessed using nuclear magnetic resonance (NMR) to identify the molecular mechanism of the antioxidant stress reaction and the metabolic reactions of earthworms to HBCD. A significant up-regulation (p  0.05). Principal component analysis (PCA) of the metabolic responses showed that all groups could be clearly differentiated, and the highest concentration dose group was the most distant from the control group. Except for fumarate, the measured metabolites, which included adenosine triphosphate (ATP), valine, lysine, glycine, betaine and lactate, revealed significant (p earthworm exposure studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generation and Validation of the iKp1289 Metabolic Model for Klebsiella pneumoniae KPPR1

Energy Technology Data Exchange (ETDEWEB)

Henry, Christopher S.; Rotman, Ella; Lathem, Wyndham W.; Tyo, Keith E. J.; Hauser, Alan R.; Mandel, Mark J.

2017-02-15

Klebsiella pneumoniae has a reputation for causing a wide range of infectious conditions, with numerous highly virulent and antibiotic-resistant strains. Metabolic models have the potential to provide insights into the growth behavior, nutrient requirements, essential genes, and candidate drug targets in these strains. Here we develop a metabolic model for KPPR1, a highly virulent strain of K. pneumoniae. We apply a combination of Biolog phenotype data and fitness data to validate and refine our KPPR1 model. The final model displays a predictive accuracy of 75% in identifying potential carbon and nitrogen sources for K. pneumoniae and of 99% in predicting nonessential genes in rich media. We demonstrate how this model is useful in studying the differences in the metabolic capabilities of the low-virulence MGH 78578 strain and the highly virulent KPPR1 strain. For example, we demonstrate that these strains differ in carbohydrate metabolism, including the ability to metabolize dulcitol as a primary carbon source. Our model makes numerous other predictions for follow-up verification and analysis.

An insight into the metabolic responses of ultra-small superparamagnetic particles of iron oxide using metabonomic analysis of biofluids

International Nuclear Information System (INIS)

Feng Jianghua; Liu Huili; Zhang Limin; Bhakoo, Kishore; Lu Lehui

2010-01-01

Ultra-small superparamagnetic particles of iron oxides (USPIO) have been developed as intravenous organ/tissue-targeted contrast agents to improve magnetic resonance imaging (MRI) in vivo. However, their potential toxicity and effects on metabolism have attracted particular attention. In the present study, uncoated and dextran-coated USPIO were investigated by analyzing both rat urine and plasma metabonomes using high-resolution NMR-based metabonomic analysis in combination with multivariate statistical analysis. The wealth of information gathered on the metabolic profiles from rat urine and plasma has revealed subtle metabolic changes in response to USPIO administration. The metabolic changes include the elevation of urinary α-hydroxy-n-valerate, o- and p-HPA, PAG, nicotinate and hippurate accompanied by decreases in the levels of urinary α-ketoglutarate, succinate, citrate, N-methylnicotinamide, NAG, DMA, allantoin and acetate following USPIO administration. The changes associated with USPIO administration included a gradual increase in plasma glucose, N-acetyl glycoprotein, saturated fatty acid, citrate, succinate, acetate, GPC, ketone bodies (β-hydroxybutyrate, acetone and acetoacetate) and individual amino acids, such as phenylalanine, lysine, isoleucine, glycine, glutamine and glutamate and a gradual decrease of myo-inositol, unsaturated fatty acid and triacylglycerol. Hence USPIO administration effects are reflected in changes in a number of metabolic pathways including energy, lipid, glucose and amino acid metabolism. The size- and surface chemistry-dependent metabolic responses and possible toxicity were observed using NMR analysis of biofluids. These changes may be attributed to the disturbances of hepatic, renal and cardiac functions following USPIO administrations. The potential biotoxicity can be derived from metabonomic analysis and serum biochemistry analysis. Metabonomic strategy offers a promising approach for the detection of subtle

An insight into the metabolic responses of ultra-small superparamagnetic particles of iron oxide using metabonomic analysis of biofluids

Science.gov (United States)

Feng, Jianghua; Liu, Huili; Zhang, Limin; Bhakoo, Kishore; Lu, Lehui

2010-10-01

Ultra-small superparamagnetic particles of iron oxides (USPIO) have been developed as intravenous organ/tissue-targeted contrast agents to improve magnetic resonance imaging (MRI) in vivo. However, their potential toxicity and effects on metabolism have attracted particular attention. In the present study, uncoated and dextran-coated USPIO were investigated by analyzing both rat urine and plasma metabonomes using high-resolution NMR-based metabonomic analysis in combination with multivariate statistical analysis. The wealth of information gathered on the metabolic profiles from rat urine and plasma has revealed subtle metabolic changes in response to USPIO administration. The metabolic changes include the elevation of urinary α-hydroxy-n-valerate, o- and p-HPA, PAG, nicotinate and hippurate accompanied by decreases in the levels of urinary α-ketoglutarate, succinate, citrate, N-methylnicotinamide, NAG, DMA, allantoin and acetate following USPIO administration. The changes associated with USPIO administration included a gradual increase in plasma glucose, N-acetyl glycoprotein, saturated fatty acid, citrate, succinate, acetate, GPC, ketone bodies (β-hydroxybutyrate, acetone and acetoacetate) and individual amino acids, such as phenylalanine, lysine, isoleucine, glycine, glutamine and glutamate and a gradual decrease of myo-inositol, unsaturated fatty acid and triacylglycerol. Hence USPIO administration effects are reflected in changes in a number of metabolic pathways including energy, lipid, glucose and amino acid metabolism. The size- and surface chemistry-dependent metabolic responses and possible toxicity were observed using NMR analysis of biofluids. These changes may be attributed to the disturbances of hepatic, renal and cardiac functions following USPIO administrations. The potential biotoxicity can be derived from metabonomic analysis and serum biochemistry analysis. Metabonomic strategy offers a promising approach for the detection of subtle

An insight into the metabolic responses of ultra-small superparamagnetic particles of iron oxide using metabonomic analysis of biofluids

Energy Technology Data Exchange (ETDEWEB)

Feng Jianghua [Department of Physics, Fujian Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory of Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen, 361005 (China); Liu Huili; Zhang Limin [State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Chinese Academy of Sciences, Wuhan 430071 (China); Bhakoo, Kishore [Singapore Bioimaging Consortium, Agency for Science, Technology and Research (A-STAR) 138667 (Singapore); Lu Lehui, E-mail: jianghua.feng@hotmail.com, E-mail: jianghua.feng@wipm.ac.cn [State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022 (China)

2010-10-01

Ultra-small superparamagnetic particles of iron oxides (USPIO) have been developed as intravenous organ/tissue-targeted contrast agents to improve magnetic resonance imaging (MRI) in vivo. However, their potential toxicity and effects on metabolism have attracted particular attention. In the present study, uncoated and dextran-coated USPIO were investigated by analyzing both rat urine and plasma metabonomes using high-resolution NMR-based metabonomic analysis in combination with multivariate statistical analysis. The wealth of information gathered on the metabolic profiles from rat urine and plasma has revealed subtle metabolic changes in response to USPIO administration. The metabolic changes include the elevation of urinary {alpha}-hydroxy-n-valerate, o- and p-HPA, PAG, nicotinate and hippurate accompanied by decreases in the levels of urinary {alpha}-ketoglutarate, succinate, citrate, N-methylnicotinamide, NAG, DMA, allantoin and acetate following USPIO administration. The changes associated with USPIO administration included a gradual increase in plasma glucose, N-acetyl glycoprotein, saturated fatty acid, citrate, succinate, acetate, GPC, ketone bodies ({beta}-hydroxybutyrate, acetone and acetoacetate) and individual amino acids, such as phenylalanine, lysine, isoleucine, glycine, glutamine and glutamate and a gradual decrease of myo-inositol, unsaturated fatty acid and triacylglycerol. Hence USPIO administration effects are reflected in changes in a number of metabolic pathways including energy, lipid, glucose and amino acid metabolism. The size- and surface chemistry-dependent metabolic responses and possible toxicity were observed using NMR analysis of biofluids. These changes may be attributed to the disturbances of hepatic, renal and cardiac functions following USPIO administrations. The potential biotoxicity can be derived from metabonomic analysis and serum biochemistry analysis. Metabonomic strategy offers a promising approach for the detection of

Metabolic and cardiovascular responses to epinephrine in diabetic autonomic neuropathy

DEFF Research Database (Denmark)

Hilsted, J; Richter, E; Madsbad, S

1987-01-01

with autonomic neuropathy (P less than 0.01) but was unchanged in the other groups. Since cardiac output increased to a similar extent in the three groups, the decrease in blood pressure was due to a significantly larger decrease (P less than 0.01) in total peripheral vascular resistance in the patients......Norepinephrine-induced vasoconstriction, which is mediated by alpha-adrenergic receptors, is accentuated in patients with autonomic neuropathy. In contrast, responses mediated by beta-adrenergic receptors, including vasodilatation and metabolic changes, have not been evaluated in these patients....... To study these responses, we administered epinephrine in a graded intravenous infusion (0.5 to 5 micrograms per minute) to seven diabetic patients without neuropathy, seven diabetic patients with autonomic neuropathy, and seven normal subjects. Mean arterial pressure decreased significantly in the patients...

Modeling the role of covalent enzyme modification in Escherichia coli nitrogen metabolism

International Nuclear Information System (INIS)

Kidd, Philip B; Wingreen, Ned S

2010-01-01

In the bacterium Escherichia coli, the enzyme glutamine synthetase (GS) converts ammonium into the amino acid glutamine. GS is principally active when the cell is experiencing nitrogen limitation, and its activity is regulated by a bicyclic covalent modification cascade. The advantages of this bicyclic-cascade architecture are poorly understood. We analyze a simple model of the GS cascade in comparison to other regulatory schemes and conclude that the bicyclic cascade is suboptimal for maintaining metabolic homeostasis of the free glutamine pool. Instead, we argue that the lag inherent in the covalent modification of GS slows the response to an ammonium shock and thereby allows GS to transiently detoxify the cell, while maintaining homeostasis over longer times

Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae

DEFF Research Database (Denmark)

Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim

2008-01-01

Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...

Dynamic optimal control of homeostasis: an integrative system approach for modeling of the central nitrogen metabolism in Saccharomyces cerevisiae.

Science.gov (United States)

van Riel, N A; Giuseppin, M L; Verrips, C T

2000-01-01

The theory of dynamic optimal metabolic control (DOMC), as developed by Giuseppin and Van Riel (Metab. Eng., 2000), is applied to model the central nitrogen metabolism (CNM) in Saccharomyces cerevisiae. The CNM represents a typical system encountered in advanced metabolic engineering. The CNM is the source of the cellular amino acids and proteins, including flavors and potentially valuable biomolecules; therefore, it is also of industrial interest. In the DOMC approach the cell is regarded as an optimally controlled system. Given the metabolic genotype, the cell faces a control problem to maintain an optimal flux distribution in a changing environment. The regulation is based on strategies and balances feedback control of homeostasis and feedforward regulation for adaptation. The DOMC approach is an integrative, holistic approach, not based on mechanistic descriptions and (therefore) not biased by the variation present in biochemical and molecular biological data. It is an effective tool to structure the rapidly increasing amount of data on the function of genes and pathways. The DOMC model is used successfully to predict the responses of pulses of ammonia and glutamine to nitrogen-limited continuous cultures of a wild-type strain and a glutamine synthetase-negative mutant. The simulation results are validated with experimental data.

Humoral and cell-mediated immune responses to influenza vaccination in equine metabolic syndrome (EMS) horses.

Science.gov (United States)

Elzinga, Sarah; Reedy, Stephanie; Barker, Virginia D; Chambers, Thomas M; Adams, Amanda A

2018-05-01

Obesity is an increasing problem in the equine population with recent reports indicating that the percentage of overweight horses may range anywhere from 20.6-51%. Obesity in horses has been linked to more serious health concerns such as equine metabolic syndrome (EMS). EMS is a serious problem in the equine industry given its defining characteristics of insulin dysregualtion and obesity, as well as the involvement of laminitis. Little research however has been conducted to determine the effects of EMS on routine healthcare of these horses, in particular how they respond to vaccination. It has been shown that obese humans and mice have decreased immune responses to vaccination. EMS may have similar effects on vaccine responses in horses. If this is the case, these animals may be more susceptible to disease, acting as unknown disease reservoirs. Therefore, we investigated the effects of EMS on immune responses to routine influenza vaccination. Twenty-five adult horses of mixed-sex and mixed-breed (8-21 years old) horses; 13 EMS and 12 non-EMS were selected. Within each group, 4 horses served as non-vaccinate saline controls and the remaining horses were vaccinated with a commercially available equine influenza vaccine. Vaccination (influenza or saline) was administered on weeks 0 and 3, and peripheral blood samples taken on week 0 prior to vaccination and on weeks 1, 2, 3, 4, and 5 post vaccination. Blood samples were used to measure hemagglutination inhibition (HI) titers and equine influenza specific IgGa, IgGb, and IgGT levels. Blood samples were also used to isolate peripheral blood mononuclear cells (PBMCs) for analysis of cell mediated immune (CMI) responses via real-time polymerase chain reaction (RT-PCR). All horses receiving influenza vaccination responded with significant increases (P equine influenza specific antibodies following vaccination compared to saline controls. EMS did not significantly affect (P > 0.05) humoral immune responses as measured

Phase I to II cross-induction of xenobiotic metabolizing enzymes: A feedforward control mechanism for potential hormetic responses

International Nuclear Information System (INIS)

Zhang Qiang; Pi Jingbo; Woods, Courtney G.; Andersen, Melvin E.

2009-01-01

Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a

Phase I to II cross-induction of xenobiotic metabolizing enzymes: a feedforward control mechanism for potential hormetic responses.

Science.gov (United States)

Zhang, Qiang; Pi, Jingbo; Woods, Courtney G; Andersen, Melvin E

2009-06-15

Hormetic responses to xenobiotic exposure likely occur as a result of overcompensation by the homeostatic control systems operating in biological organisms. However, the mechanisms underlying overcompensation that leads to hormesis are still unclear. A well-known homeostatic circuit in the cell is the gene induction network comprising phase I, II and III metabolizing enzymes, which are responsible for xenobiotic detoxification, and in many cases, bioactivation. By formulating a differential equation-based computational model, we investigated in this study whether hormesis can arise from the operation of this gene/enzyme network. The model consists of two feedback and one feedforward controls. With the phase I negative feedback control, xenobiotic X activates nuclear receptors to induce cytochrome P450 enzyme, which bioactivates X into a reactive metabolite X'. With the phase II negative feedback control, X' activates transcription factor Nrf2 to induce phase II enzymes such as glutathione S-transferase and glutamate cysteine ligase, etc., which participate in a set of reactions that lead to the metabolism of X' into a less toxic conjugate X''. The feedforward control involves phase I to II cross-induction, in which the parent chemical X can also induce phase II enzymes directly through the nuclear receptor and indirectly through transcriptionally upregulating Nrf2. As a result of the active feedforward control, a steady-state hormetic relationship readily arises between the concentrations of the reactive metabolite X' and the extracellular parent chemical X to which the cell is exposed. The shape of dose-response evolves over time from initially monotonically increasing to J-shaped at the final steady state-a temporal sequence consistent with adaptation-mediated hormesis. The magnitude of the hormetic response is enhanced by increases in the feedforward gain, but attenuated by increases in the bioactivation or phase II feedback loop gains. Our study suggests a

Distinct mechanisms underlie adaptation of proximal tubule Na+/H+ exchanger isoform 3 in response to chronic metabolic and respiratory acidosis.

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Silva, Pedro Henrique Imenez; Girardi, Adriana Castello Costa; Neri, Elida Adalgisa; Rebouças, Nancy Amaral

2012-04-01

The Na(+/)H(+) exchanger isoform 3 (NHE3) is essential for HCO(3)(-) reabsorption in renal proximal tubules. The expression and function of NHE3 must adapt to acid-base conditions. The goal of this study was to elucidate the mechanisms responsible for higher proton secretion in proximal tubules during acidosis and to evaluate whether there are differences between metabolic and respiratory acidosis with regard to NHE3 modulation and, if so, to identify the relevant parameters that may trigger these distinct adaptive responses. We achieved metabolic acidosis by lowering HCO(3)(-) concentration in the cell culture medium and respiratory acidosis by increasing CO(2) tension in the incubator chamber. We found that cell-surface NHE3 expression was increased in response to both forms of acidosis. Mild (pH 7.21 ± 0.02) and severe (6.95 ± 0.07) metabolic acidosis increased mRNA levels, at least in part due to up-regulation of transcription, whilst mild (7.11 ± 0.03) and severe (6.86 ± 0.01) respiratory acidosis did not up-regulate NHE3 expression. Analyses of the Nhe3 promoter region suggested that the regulatory elements sensitive to metabolic acidosis are located between -466 and -153 bp, where two consensus binding sites for SP1, a transcription factor up-regulated in metabolic acidosis, were localised. We conclude that metabolic acidosis induces Nhe3 promoter activation, which results in higher mRNA and total protein level. At the plasma membrane surface, NHE3 expression was increased in metabolic and respiratory acidosis alike, suggesting that low pH is responsible for NHE3 displacement to the cell surface.

A general model for metabolic scaling in self-similar asymmetric networks.

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Alexander Byers Brummer

2017-03-01

Full Text Available How a particular attribute of an organism changes or scales with its body size is known as an allometry. Biological allometries, such as metabolic scaling, have been hypothesized to result from selection to maximize how vascular networks fill space yet minimize internal transport distances and resistances. The West, Brown, Enquist (WBE model argues that these two principles (space-filling and energy minimization are (i general principles underlying the evolution of the diversity of biological networks across plants and animals and (ii can be used to predict how the resulting geometry of biological networks then governs their allometric scaling. Perhaps the most central biological allometry is how metabolic rate scales with body size. A core assumption of the WBE model is that networks are symmetric with respect to their geometric properties. That is, any two given branches within the same generation in the network are assumed to have identical lengths and radii. However, biological networks are rarely if ever symmetric. An open question is: Does incorporating asymmetric branching change or influence the predictions of the WBE model? We derive a general network model that relaxes the symmetric assumption and define two classes of asymmetrically bifurcating networks. We show that asymmetric branching can be incorporated into the WBE model. This asymmetric version of the WBE model results in several theoretical predictions for the structure, physiology, and metabolism of organisms, specifically in the case for the cardiovascular system. We show how network asymmetry can now be incorporated in the many allometric scaling relationships via total network volume. Most importantly, we show that the 3/4 metabolic scaling exponent from Kleiber's Law can still be attained within many asymmetric networks.

A proposed model for the transfer of environmental tritium to man and tritium metabolism in model animals

International Nuclear Information System (INIS)

Saito, Masahiro; Ishida, M.R.

1987-01-01

To evaluate the accumulated dose in human bodies due to the environmental tritium, it is of required to establish an adequate model for the tritium transfer from the environment to man and to obtain enough information on the metabolic behaviour of tritium in animal bodies using model animal system. In this report, first we describe about a proposed model for the transfer of environmental tritium to man and secondly mention briefly about the recent works on the tritium metabolism in newborn animals which have been treated as a model system of tritium intake through food chain. (author)

Deciphering the mechanisms involved in Portulaca oleracea (C4) response to drought: metabolic changes including crassulacean acid-like metabolism induction and reversal upon re-watering.

Science.gov (United States)

D'Andrea, Rodrigo Matías; Andreo, Carlos Santiago; Lara, María Valeria

2014-11-01

Portulaca oleracea is a C(4) plant; however, under drought it can change its carbon fixation metabolism into a crassulacean acid metabolism (CAM)-like one. While the C(3) -CAM shift is well known, the C(4) -CAM transition has only been described in Portulaca. Here, a CAM-like metabolism was induced in P. oleracea by drought and then reversed by re-watering. Physiological and biochemical approaches were undertaken to evaluate the drought and recovery responses. In CAM-like plants, chlorophyll fluorescence parameters were transitory affected and non-radiative energy dissipation mechanisms were induced. Induction of flavonoids, betalains and antioxidant machinery may be involved in photosynthetic machinery protection. Metabolic analysis highlights a clear metabolic shift, when a CAM-like metabolism is induced and then reversed. Increases in nitrogenous compounds like free amino acids and urea, and of pinitol could contribute to withstand drought. Reciprocal variations in arginase and urease in drought-stressed and in re-watered plants suggest urea synthesis is strictly regulated. Recovery of C(4) metabolism was accounted by CO(2) assimilation pattern and malate levels. Increases in glycerol and in polyamines would be of importance of re-watered plants. Collectively, in P. oleracea multiple strategies, from induction of several metabolites to the transitory development of a CAM-like metabolism, participate to enhance its adaptation to drought. © 2014 Scandinavian Plant Physiology Society.

Metabolic Trade-offs between Biomass Synthesis and Photosynthate Export at Different Light Intensities in a Genome–Scale Metabolic Model of Rice

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Mark Graham Poolman

2014-11-01

Full Text Available Previously we have used a genome scale model of rice metabolism to describe how metabolism reconfigures at different light intensities in an expanding leaf of rice. Although this established that the metabolism of the leaf was adequatelyrepresented, in the model, the scenario was not that of the typical function of the leaf --- to provide material for the rest of the plant. Here we extend our analysis to explore the transition to a source leaf as export of photosynthate increases at the expense of making leaf biomass precursors, again as a function of light intensity. In particular we investigate whether, when the leaf is making a smaller range of compounds for export to the phloem, the same changes occur in the interactions between mitochondrial and chloroplast metabolism as seen in biomass synthesis for growth when light intensity increases. Our results show that the same changes occur qualitatively, though there are slight quantitative differences reflecting differences in the energy and redox requirements for the different metabolic outputs.

Cell Wall Metabolism in Response to Abiotic Stress

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Gall, Hyacinthe Le; Philippe, Florian; Domon, Jean-Marc; Gillet, Françoise; Pelloux, Jérôme; Rayon, Catherine

2015-01-01

This review focuses on the responses of the plant cell wall to several abiotic stresses including drought, flooding, heat, cold, salt, heavy metals, light, and air pollutants. The effects of stress on cell wall metabolism are discussed at the physiological (morphogenic), transcriptomic, proteomic and biochemical levels. The analysis of a large set of data shows that the plant response is highly complex. The overall effects of most abiotic stress are often dependent on the plant species, the genotype, the age of the plant, the timing of the stress application, and the intensity of this stress. This shows the difficulty of identifying a common pattern of stress response in cell wall architecture that could enable adaptation and/or resistance to abiotic stress. However, in most cases, two main mechanisms can be highlighted: (i) an increased level in xyloglucan endotransglucosylase/hydrolase (XTH) and expansin proteins, associated with an increase in the degree of rhamnogalacturonan I branching that maintains cell wall plasticity and (ii) an increased cell wall thickening by reinforcement of the secondary wall with hemicellulose and lignin deposition. Taken together, these results show the need to undertake large-scale analyses, using multidisciplinary approaches, to unravel the consequences of stress on the cell wall. This will help identify the key components that could be targeted to improve biomass production under stress conditions. PMID:27135320

Response of rainbow trout transcriptome to model chemical contaminants

International Nuclear Information System (INIS)

Koskinen, Heikki; Pehkonen, Petri; Vehniaeinen, Eeva; Krasnov, Aleksei; Rexroad, Caird; Afanasyev, Sergey; Moelsa, Hannu; Oikari, Aimo

2004-01-01

We used high-density cDNA microarray in studies of responses of rainbow trout fry at sublethal ranges of β-naphthoflavone, cadmium, carbon tetrachloride, and pyrene. The differentially expressed genes were grouped by the functional categories of Gene Ontology. Significantly different response to the studied compounds was shown by a number of classes, such as cell cycle, apoptosis, signal transduction, oxidative stress, subcellular and extracellular structures, protein biosynthesis, and modification. Cluster analysis separated responses to the contaminants at low and medium doses, whereas at high levels the adaptive reactions were masked with general unspecific response to toxicity. We found enhanced expression of many mitochondrial proteins as well as genes involved in metabolism of metal ions and protein biosynthesis. In parallel, genes related to stress and immune response, signal transduction, and nucleotide metabolism were down-regulated. We performed computer-assisted analyses of Medline abstracts retrieved for each compound, which helped us to indicate the expected and novel findings

Metabolic Responses and Pacing Strategies during Successive Sprint Skiing Time Trials

DEFF Research Database (Denmark)

Andersson, Erik; Holmberg, Hans-Christer; Ørtenblad, Niels

2016-01-01

PURPOSE: To examine the metabolic responses and pacing strategies during the performance of successive sprint time trials (STTs) in cross-country skiing. METHODS: Ten well-trained male cross-country skiers performed four self-paced 1300-m STTs on a treadmill, each separated by 45 min of recovery...... to estimate the anaerobic energy supply. RESULTS: The individual trial-to-trial variability in STT performance time was 1.3%, where variations in O2 deficit and V˙O2 explained 69% (P 0.05) of the variation in performance. The first and last STTs were equally fast (228 ± 10 s), and ~ 1...... on the first than second course half. In addition, metabolic rates were substantially higher (~_30%) for uphill than for flat skiing, indicating that pacing was regulated to the terrain. CONCLUSIONS: The fastest STTs were characterized primarily by a greater anaerobic energy production, which also explained 69...

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.

Metabolic changes in malnutrition.

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Emery, P W

2005-10-01

This paper is concerned with malnutrition caused by inadequate intake of all the major nutrients rather than deficiency diseases relating to a single micronutrient. Three common situations are recognised: young children in third world countries with protein-energy malnutrition; adults in the same countries who are chronically adapted to subsisting on marginally inadequate diets; and patients who become malnourished as a result of chronic diseases. In all these situations infectious diseases are often also present, and this complicates the interpretation of biochemical and physiological observations. The metabolic response to starvation is primarily concerned with maintaining a supply of water-soluble substrates to supply energy to the brain. Thus there is an initial rise in metabolic rate, reflecting gluconeogenic activity. As fasting progresses, gluconeogenesis is suppressed to minimise muscle protein breakdown and ketones become the main fuel for the brain. With chronic underfeeding the basal metabolic rate per cell appears to fall, but the mechanistic basis for this is not clear. The main adaptation to chronic energy deficiency is slow growth and low adult body size, although the reduction in energy requirement achieved by this is partially offset by the preservation of the more metabolically active organs at the expense of muscle, which has a lower metabolic rate. The interaction between malnutrition and the metabolic response to trauma has been studied using an animal model. The rise in energy expenditure and urinary nitrogen excretion following surgery were significantly attenuated in malnourished rats, suggesting that malnutrition impairs the ability of the body to mobilise substrates to support inflammatory and reparative processes. However, the healing process in wounded muscle remained unimpaired in malnutrition, suggesting that this process has a high biological priority.

In silico analysis of human metabolism: Reconstruction, contextualization and application of genome-scale models

DEFF Research Database (Denmark)

Geng, Jun; Nielsen, Jens

2017-01-01

The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....

Proteomic Analysis of Metabolic Responses to Biofuels and Chemicals in Photosynthetic Cyanobacteria.

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Sun, T; Chen, L; Zhang, W

2017-01-01

Recent progresses in various "omics" technologies have enabled quantitative measurements of biological molecules in a high-throughput manner. Among them, high-throughput proteomics is a rapidly advancing field that offers a new means to quantify metabolic changes at protein level, which has significantly facilitated our understanding of cellular process, such as protein synthesis, posttranslational modifications, and degradation in responding to environmental perturbations. Cyanobacteria are autotrophic prokaryotes that can perform oxygenic photosynthesis and have recently attracted significant attentions as one promising alternative to traditionally biomass-based "microbial cell factories" to produce green fuels and chemicals. However, early studies have shown that the low tolerance to toxic biofuels and chemicals represented one major hurdle for further improving productivity of the cyanobacterial production systems. To address the issue, metabolic responses and their regulation of cyanobacterial cells to toxic end-products need to be defined. In this chapter, we discuss recent progresses in interpreting cyanobacterial responses to biofuels and chemicals using high-throughput proteomics approach, aiming to provide insights and guidelines on how to enhance tolerance and productivity of biofuels or chemicals in the renewable cyanobacteria systems in the future. © 2017 Elsevier Inc. All rights reserved.

Correlations of Eisenia fetida metabolic responses to extractable phenanthrene concentrations through time

Energy Technology Data Exchange (ETDEWEB)

McKelvie, Jennifer R.; Wolfe, David M.; Celejewski, Magda; Simpson, Andre J. [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail, Toronto, Ontario, M1C 1A4 (Canada); Simpson, Myrna J., E-mail: myrna.simpson@utoronto.c [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail, Toronto, Ontario, M1C 1A4 (Canada)

2010-06-15

Eisenia fetida earthworms were exposed to phenanthrene for thirty days to compare hydroxypropyl-beta-cyclodextrin (HPCD) extraction of soil and {sup 1}H NMR earthworm metabolomics as indicators of bioavailability. The phenanthrene 28-d LC{sub 50} value was 750 mg/kg (632-891, 95% confidence intervals) for the peat soil tested. The initial phenanthrene concentration was 319 mg/kg, which biodegraded to 16 mg/kg within 15 days, at which time HPCD extraction suggested that phenanthrene was no longer bioavailable. Multivariate statistical analysis of {sup 1}H NMR spectra for E. fetida tissue extracts indicated that phenanthrene exposed and control earthworms differed throughout the 30 day experiment despite the low phenanthrene concentrations present after 15 days. This metabolic response was better correlated to total phenanthrene concentrations (Q{sup 2} = 0.59) than HPCD-extractable phenanthrene concentrations (Q{sup 2} = 0.46) suggesting that {sup 1}H NMR metabolomics offers considerable promise as a novel, molecular-level method to directly monitor the bioavailability of contaminants to earthworms in the environment. - Metabolic responses of Eisenia fetida earthworms to phenanthrene exposure are better correlated to total phenanthrene concentrations than to cyclodextrin-extractable concentrations through time.

Correlations of Eisenia fetida metabolic responses to extractable phenanthrene concentrations through time

International Nuclear Information System (INIS)

McKelvie, Jennifer R.; Wolfe, David M.; Celejewski, Magda; Simpson, Andre J.; Simpson, Myrna J.

2010-01-01

Eisenia fetida earthworms were exposed to phenanthrene for thirty days to compare hydroxypropyl-β-cyclodextrin (HPCD) extraction of soil and 1 H NMR earthworm metabolomics as indicators of bioavailability. The phenanthrene 28-d LC 50 value was 750 mg/kg (632-891, 95% confidence intervals) for the peat soil tested. The initial phenanthrene concentration was 319 mg/kg, which biodegraded to 16 mg/kg within 15 days, at which time HPCD extraction suggested that phenanthrene was no longer bioavailable. Multivariate statistical analysis of 1 H NMR spectra for E. fetida tissue extracts indicated that phenanthrene exposed and control earthworms differed throughout the 30 day experiment despite the low phenanthrene concentrations present after 15 days. This metabolic response was better correlated to total phenanthrene concentrations (Q 2 = 0.59) than HPCD-extractable phenanthrene concentrations (Q 2 = 0.46) suggesting that 1 H NMR metabolomics offers considerable promise as a novel, molecular-level method to directly monitor the bioavailability of contaminants to earthworms in the environment. - Metabolic responses of Eisenia fetida earthworms to phenanthrene exposure are better correlated to total phenanthrene concentrations than to cyclodextrin-extractable concentrations through time.

Cytolytic T lymphocyte responses to metabolically inactivated stimulator cells. I. Metabolic inactivation impairs both CD and LD antigen signals

International Nuclear Information System (INIS)

Kelso, A.; Boyle, W.

1982-01-01

The effects of metabolic inactivation of spleen cells on antigen presentation to precursors of alloreactive cytolytic T lymphocytes (T/sub c/) were examined. By serological methods, populations inactivated by ultraviolet irradiation, glutaraldehyde fixation or plasma membrane isolation were found to retain normal levels of H-2K/D and Ia antigens. However, comparison of the antigen doses required to stimulate secondary T/sub c/ responses in mixed leukocyte culture showed that the inactivated preparations were approximately 10-fold less immunogenic than X-irradiated spleen cells. Their total inability to stimulate primary cytolytic responses pointed to at least a 100-fold impairment of immunogenicity for unprimed T/sub c/ precursors in the case of uv-irradiated and glutaraldehyde-treated stimulator cells, and at least a 10-fold impairment for membrane fragments. Experiments showing that the capacity of cell monolayers to absorb precursor T/sub c/ from unprimed spleen populations was reduced following uv-irradiation or glutaraldehyde treatment provided direct evidence that this loss of immunogenicity was due in part to suboptimal antigen presentation to precursor T/sub c/. It is concluded that, in addition to the traditional view that these treatments damage the ''LD'' signal to helper T lymphocytes, metabolic inactivation also impairs recognition of ''CD'' determinants by precursor T/sub c/

Metabonomics-based analysis of Brachyspira pilosicoli's response to tiamulin reveals metabolic activity despite significant growth inhibition.

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Le Roy, Caroline Ivanne; Passey, Jade Louise; Woodward, Martin John; La Ragione, Roberto Marcello; Claus, Sandrine Paule

2017-06-01

Pathogenic anaerobes Brachyspira spp. are responsible for an increasing number of Intestinal Spirochaetosis (IS) cases in livestock against which few approved treatments are available. Tiamulin is used to treat swine dysentery caused by Brachyspira spp. and recently has been used to handle avian intestinal spirochaetosis (AIS). The therapeutic dose used in chickens requires further evaluation since cases of bacterial resistance to tiamulin have been reported. In this study, we evaluated the impact of tiamulin at varying concentrations on the metabolism of B. pilosicoli using a 1 H-NMR-based metabonomics approach allowing the capture of the overall bacterial metabolic response to antibiotic treatment. Based on growth curve studies, tiamulin impacted bacterial growth even at very low concentration (0.008 μg/mL) although its metabolic activity was barely affected 72 h post exposure to antibiotic treatment. Only the highest dose of tiamulin tested (0.250 μg/mL) caused a major metabolic shift. Results showed that below this concentration, bacteria could maintain a normal metabolic trajectory despite significant growth inhibition by the antibiotic, which may contribute to disease reemergence post antibiotic treatment. Indeed, we confirmed that B. pilosicoli remained viable even after exposition to the highest antibiotic dose. This paper stresses the need to ensure new evaluation of bacterial viability post bacteriostatic exposure such as tiamulin to guarantee treatment efficacy and decrease antibiotic resistance development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling antibiotic and cytotoxic effects of the dimeric isoquinoline IQ-143 on metabolism and its regulation in Staphylococcus aureus, Staphylococcus epidermidis and human cells

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2011-01-01

Background Xenobiotics represent an environmental stress and as such are a source for antibiotics, including the isoquinoline (IQ) compound IQ-143. Here, we demonstrate the utility of complementary analysis of both host and pathogen datasets in assessing bacterial adaptation to IQ-143, a synthetic analog of the novel type N,C-coupled naphthyl-isoquinoline alkaloid ancisheynine. Results Metabolite measurements, gene expression data and functional assays were combined with metabolic modeling to assess the effects of IQ-143 on Staphylococcus aureus, Staphylococcus epidermidis and human cell lines, as a potential paradigm for novel antibiotics. Genome annotation and PCR validation identified novel enzymes in the primary metabolism of staphylococci. Gene expression response analysis and metabolic modeling demonstrated the adaptation of enzymes to IQ-143, including those not affected by significant gene expression changes. At lower concentrations, IQ-143 was bacteriostatic, and at higher concentrations bactericidal, while the analysis suggested that the mode of action was a direct interference in nucleotide and energy metabolism. Experiments in human cell lines supported the conclusions from pathway modeling and found that IQ-143 had low cytotoxicity. Conclusions The data suggest that IQ-143 is a promising lead compound for antibiotic therapy against staphylococci. The combination of gene expression and metabolite analyses with in silico modeling of metabolite pathways allowed us to study metabolic adaptations in detail and can be used for the evaluation of metabolic effects of other xenobiotics. PMID:21418624

A mathematical analysis of adaptations to the metabolic fate of fructose in essential fructosuria subjects.

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Allen, R J; Musante, Cynthia J

2018-04-17

Fructose is a major component of Western diets and is implicated in the pathogenesis of obesity and type 2 diabetes. In response to an oral challenge, the majority of fructose is cleared during "first-pass" liver metabolism, primarily via phosphorylation by ketohexokinase (KHK). A rare benign genetic deficiency in KHK, called essential fructosuria (EF), leads to altered fructose metabolism. The only reported symptom of EF is the appearance of fructose in the urine following either oral or intravenous fructose administration. Here we develop and use a mathematical model to investigate the adaptations to altered fructose metabolism in people with EF. Firstly, the model is calibrated to fit available data in normal healthy subjects. Then, to mathematically represent EF subjects we systematically implement metabolic adaptations such that model simulations match available data for this phenotype. We hypothesize that these modifications represent the major metabolic adaptations present in these subjects. This modeling approach suggests that several other aspects of fructose metabolism, beyond hepatic KHK deficiency, are altered and contribute to the etiology of this benign condition. Specifically, we predict that fructose absorption into the portal vein is altered, peripheral metabolism is slowed, renal re-absorption of fructose is mostly ablated and that alternate pathways for hepatic metabolism of fructose are up-regulated. Moreover, these findings have implications for drug discovery and development, suggesting that the therapeutic targeting of fructose metabolism could lead to unexpected metabolic adaptations, potentially due to a physiological response to high fructose conditions.

Modification of nucleotide metabolism in relationship with differentiation and in response to irradiation in human tumour cells

International Nuclear Information System (INIS)

Wei, Shuang

1998-01-01

This research thesis reports the study of the metabolism of nucleotides in human tumour cells. The first part addresses the modifications of nucleotide (more specifically purine) metabolism in relationship with human melanoma cell proliferation and differentiation. The second part addresses the modifications of this metabolism in response to an irradiation in human colon tumour cells. For each part, the author proposes a bibliographic synthesis, and a presentation of studied cells and of methods used to grow cells, and respectively to proliferate and differentiate them or to irradiate them, and then discusses the obtained results [fr

Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

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Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

2014-01-01

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

Renal responses of trout to chronic respiratory and metabolic acidoses and metabolic alkalosis.

Science.gov (United States)

Wood, C M; Milligan, C L; Walsh, P J

1999-08-01

Exposure to hyperoxia (500-600 torr) or low pH (4.5) for 72 h or NaHCO(3) infusion for 48 h were used to create chronic respiratory (RA) or metabolic acidosis (MA) or metabolic alkalosis in freshwater rainbow trout. During alkalosis, urine pH increased, and [titratable acidity (TA) - HCO(-)(3)] and net H(+) excretion became negative (net base excretion) with unchanged NH(+)(4) efflux. During RA, urine pH did not change, but net H(+) excretion increased as a result of a modest rise in NH(+)(4) and substantial elevation in [TA - HCO(-)(3)] efflux accompanied by a large increase in inorganic phosphate excretion. However, during MA, urine pH fell, and net H(+) excretion was 3.3-fold greater than during RA, reflecting a similar increase in [TA - HCO(-)(3)] and a smaller elevation in phosphate but a sevenfold greater increase in NH(+)(4) efflux. In urine samples of the same pH, [TA - HCO(-)(3)] was greater during RA (reflecting phosphate secretion), and [NH(+)(4)] was greater during MA (reflecting renal ammoniagenesis). Renal activities of potential ammoniagenic enzymes (phosphate-dependent glutaminase, glutamate dehydrogenase, alpha-ketoglutarate dehydrogenase, alanine aminotransferase, phosphoenolpyruvate carboxykinase) and plasma levels of cortisol, phosphate, ammonia, and most amino acids (including glutamine and alanine) increased during MA but not during RA, when only alanine aminotransferase increased. The differential responses to RA vs. MA parallel those in mammals; in fish they may be keyed to activation of phosphate secretion by RA and cortisol mobilization by MA.

A model to study intestinal and hepatic metabolism of propranolol in the dog.

Science.gov (United States)

Mills, P C; Siebert, G A; Roberts, M S

2004-02-01

A model to investigate hepatic drug uptake and metabolism in the dog was developed for this study. Catheters were placed in the portal and hepatic veins during exploratory laparotomy to collect pre- and posthepatic blood samples at defined intervals. Drug concentrations in the portal vein were taken to reflect intestinal uptake and metabolism of an p.o. administered drug (propranolol), while differences in drug and metabolite concentrations between portal and hepatic veins reflected hepatic uptake and metabolism. A significant difference in propranolol concentration between hepatic and portal veins confirmed a high hepatic extraction of this therapeutic agent in the dog. This technically uncomplicated model may be used experimentally or clinically to determine hepatic function and metabolism of drugs that may be administered during anaesthesia and surgery.

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.

Respiratory, cardiovascular and metabolic responses during different modes of overground bionic ambulation in persons with motor-incomplete spinal cord injury: A case series

Directory of Open Access Journals (Sweden)

Jochen Kressler

2017-09-01

Full Text Available Objective: To investigate the effects of overground bionic ambulation with variable assistance on cardiorespiratory and metabolic responses in persons with motor-incomplete spinal cord injury. Design: Case series. Subjects: Four participants with chronic, motor-incomplete spinal cord injury. Methods: Subjects completed a maximal graded exercise test on an arm-ergometer and 3 6-min bouts of overground bionic ambulation using different modes of assistance, i.e. Maximal, Adaptive, Fixed. Cardiorespiratory (oxygen consumption and metabolic (caloric expenditure and substrate utilization measures were taken using a mobile metabolic cart at each overground bionic ambulation assistance. Results: Cardiorespiratory responses ranged from low (24% VO2peak for the least impaired and fittest individual to supramaximal (124% VO2peak for the participant with the largest impairments and the lowest level of fitness. Different overground bionic ambulation assistive modes elicited small (3–8% VO2peak differences in cardiorespiratory responses for 3 participants. One participant had a large (28% VO2peak difference in cardiorespiratory responses to different modes of overground bionic ambulation. Metabolic responses mostly tracked closely with cardiorespiratory responses. Total energy expenditure ranged from 1.39 to 7.17 kcal/min. Fat oxidation ranged from 0.00 to 0.17 g/min across participants and different overground bionic ambulation modes. Conclusion: Overground bionic ambulation with variable assistance can substantially increase cardiorespiratory and metabolic responses; however, these responses vary widely across participants and overground bionic ambulation modes.

Metabolic flexibility of mitochondrial respiratory chain disorders predicted by computer modelling.

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Zieliński, Łukasz P; Smith, Anthony C; Smith, Alexander G; Robinson, Alan J

2016-11-01

Mitochondrial respiratory chain dysfunction causes a variety of life-threatening diseases affecting about 1 in 4300 adults. These diseases are genetically heterogeneous, but have the same outcome; reduced activity of mitochondrial respiratory chain complexes causing decreased ATP production and potentially toxic accumulation of metabolites. Severity and tissue specificity of these effects varies between patients by unknown mechanisms and treatment options are limited. So far most research has focused on the complexes themselves, and the impact on overall cellular metabolism is largely unclear. To illustrate how computer modelling can be used to better understand the potential impact of these disorders and inspire new research directions and treatments, we simulated them using a computer model of human cardiomyocyte mitochondrial metabolism containing over 300 characterised reactions and transport steps with experimental parameters taken from the literature. Overall, simulations were consistent with patient symptoms, supporting their biological and medical significance. These simulations predicted: complex I deficiencies could be compensated using multiple pathways; complex II deficiencies had less metabolic flexibility due to impacting both the TCA cycle and the respiratory chain; and complex III and IV deficiencies caused greatest decreases in ATP production with metabolic consequences that parallel hypoxia. Our study demonstrates how results from computer models can be compared to a clinical phenotype and used as a tool for hypothesis generation for subsequent experimental testing. These simulations can enhance understanding of dysfunctional mitochondrial metabolism and suggest new avenues for research into treatment of mitochondrial disease and other areas of mitochondrial dysfunction. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Genome-scale metabolic models as platforms for strain design and biological discovery.

Science.gov (United States)

Mienda, Bashir Sajo

2017-07-01

Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.

Metabolomics Reveals Metabolically Healthy and Unhealthy Obese Individuals Differ in their Response to a Caloric Challenge.

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Flavia Badoud

Full Text Available To determine if metabolically healthy obese (MHO individuals have a different metabolic response to a standardized diet compared to lean healthy (LH and metabolically unhealthy obese (MUO individuals.Thirty adults (35-70 yrs were classified as LH, MHO, and MUO according to anthropometric and clinical measurements. Participants consumed a standardized high calorie meal (~1330 kcal. Blood glucose and insulin were measured at fasting, and 15, 30, 60, 90 and 120 min postprandially. Additional blood samples were collected for the targeted analysis of amino acids (AAs and derivatives, and fatty acids (FAs.The postprandial response (i.e., area under the curve, AUC for serum glucose and insulin were similar between MHO and LH individuals, and significantly lower than MUO individuals (p < 0.05. Minor differences were found in postprandial responses for AAs between MHO and MUO individuals, while three polyunsaturated FAs (linoleic acid, γ-linolenic acid, arachidonic acid showed smaller changes in serum after the meal in MHO individuals compared to MUO. Fasting levels for various AAs (notably branched-chain AA and FAs (e.g., saturated myristic and palmitic acids were found to correlate with glucose and insulin AUC.MHO individuals show preserved insulin sensitivity and a greater ability to adapt to a caloric challenge compared to MUO individuals.

Common motifs in the response of cereal primary metabolism to fungal pathogens are not based on similar transcriptional reprogramming

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Lars Matthias Voll

2011-08-01

Full Text Available During compatible interactions with their host plants, biotrophic plant pathogens subvert host metabolism to ensure the sustained provision of nutrient assimilates by the colonized host cells. To investigate, whether common motifs can be revealed in the response of primary carbon and nitrogen metabolism towards colonization with biotrophic fungi in cereal leaves, we have conducted a combined metabolome and transcriptome study of three quite divergent pathosystems, the barley powdery mildew fungus (Blumeria graminis f.sp. hordei, the corn smut fungus Ustilago maydis and the maize anthracnose fungus Colletotrichum graminicola, the latter being a hemibiotroph that only exhibits an initial biotrophic phase during its establishment.Based on the analysis of 42 water-soluble metabolites, we were able to separate early biotrophic from late biotrophic interactions by hierarchical cluster analysis and principal component analysis, irrespective of the plant host. Interestingly, the corresponding transcriptome dataset could not discriminate between these stages of biotrophy, irrespective, of whether transcript data for genes of central metabolism or the entire transcriptome dataset was used. Strong differences in the transcriptional regulation of photosynthesis, glycolysis, the TCA cycle, lipid biosynthesis, and cell wall metabolism were observed between the pathosystems. Increased contents of Gln, Asn, and glucose as well as diminished contents of PEP and 3-PGA were common to early post-penetration stages of all interactions. On the transcriptional level, genes of the TCA cycle, nucleotide energy metabolism and amino acid biosynthesis exhibited consistent trends among the compared biotrophic interactions, identifying the requirement for metabolic energy and the rearrangement of amino acid pools as common transcriptional motifs during early biotrophy. Both metabolome and transcript data were employed to generate models of leaf primary metabolism during

Circadian clock genes Per1 and Per2 regulate the response of metabolism-associated transcripts to sleep disruption.

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Jana Husse

Full Text Available Human and animal studies demonstrate that short sleep or poor sleep quality, e.g. in night shift workers, promote the development of obesity and diabetes. Effects of sleep disruption on glucose homeostasis and liver physiology are well documented. However, changes in adipokine levels after sleep disruption suggest that adipocytes might be another important peripheral target of sleep. Circadian clocks regulate metabolic homeostasis and clock disruption can result in obesity and the metabolic syndrome. The finding that sleep and clock disruption have very similar metabolic effects prompted us to ask whether the circadian clock machinery may mediate the metabolic consequences of sleep disruption. To test this we analyzed energy homeostasis and adipocyte transcriptome regulation in a mouse model of shift work, in which we prevented mice from sleeping during the first six hours of their normal inactive phase for five consecutive days (timed sleep restriction--TSR. We compared the effects of TSR between wild-type and Per1/2 double mutant mice with the prediction that the absence of a circadian clock in Per1/2 mutants would result in a blunted metabolic response to TSR. In wild-types, TSR induces significant transcriptional reprogramming of white adipose tissue, suggestive of increased lipogenesis, together with increased secretion of the adipokine leptin and increased food intake, hallmarks of obesity and associated leptin resistance. Some of these changes persist for at least one week after the end of TSR, indicating that even short episodes of sleep disruption can induce prolonged physiological impairments. In contrast, Per1/2 deficient mice show blunted effects of TSR on food intake, leptin levels and adipose transcription. We conclude that the absence of a functional clock in Per1/2 double mutants protects these mice from TSR-induced metabolic reprogramming, suggesting a role of the circadian timing system in regulating the physiological effects

The Factor Inhibiting HIF Asparaginyl Hydroxylase Regulates Oxidative Metabolism and Accelerates Metabolic Adaptation to Hypoxia.

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Sim, Jingwei; Cowburn, Andrew S; Palazon, Asis; Madhu, Basetti; Tyrakis, Petros A; Macías, David; Bargiela, David M; Pietsch, Sandra; Gralla, Michael; Evans, Colin E; Kittipassorn, Thaksaon; Chey, Yu C J; Branco, Cristina M; Rundqvist, Helene; Peet, Daniel J; Johnson, Randall S

2018-04-03

Animals require an immediate response to oxygen availability to allow rapid shifts between oxidative and glycolytic metabolism. These metabolic shifts are highly regulated by the HIF transcription factor. The factor inhibiting HIF (FIH) is an asparaginyl hydroxylase that controls HIF transcriptional activity in an oxygen-dependent manner. We show here that FIH loss increases oxidative metabolism, while also increasing glycolytic capacity, and that this gives rise to an increase in oxygen consumption. We further show that the loss of FIH acts to accelerate the cellular metabolic response to hypoxia. Skeletal muscle expresses 50-fold higher levels of FIH than other tissues: we analyzed skeletal muscle FIH mutants and found a decreased metabolic efficiency, correlated with an increased oxidative rate and an increased rate of hypoxic response. We find that FIH, through its regulation of oxidation, acts in concert with the PHD/vHL pathway to accelerate HIF-mediated metabolic responses to hypoxia. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

The effect of environmental temperature on immune response and metabolism of the young chicken

NARCIS (Netherlands)

Henken, A.M.

1982-01-01

The effect of environmental temperature on immune response and metabolism was studied in young chickens. Immunization was performed by injecting intramuscularly 0.5 ml packed SRBC (sheep red blood cells) in both thighs of 32 days old pullets ( WarrenSSL ). The

Role of Glucocorticoids in the Response to Unloading of Muscle Protein and Amino Acid Metabolism

Science.gov (United States)

Tischler, M. E.; Jaspers, S. R.

1985-01-01

Intact control (weight bearing) and suspended rats gained weight at a similar rate during a 6 day period. Adrenaectomized (adx) weight bearing rats gained less weight during this period while adrenalectomized suspended rats showed no significant weight gain. Cortisol treatment of both of these groups of animals caused a loss of body weight. Results from these studies show several important findings: (1) Metabolic changes in the extensor digitorum longus muscle of suspended rats are due primarily to increased circulating gluccorticoids; (2) Metabolic changes in the soleus due to higher steroid levels are probably potentiated by greater numbers of receptors; and (3) Not all metabolic responses in the unloaded soleus muscle are due to direct action of elevated glucocorticoids or increased sensitivity to these hormones.

Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

Science.gov (United States)

Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

2016-05-10

In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress.

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

Science.gov (United States)

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.

Do diabetes and obesity affect the metabolic response to exercise?

DEFF Research Database (Denmark)

Plomgaard, Peter; Weigert, Cora

2017-01-01

control before an intervention can be a risk factor of reduced therapeutic benefit from exercise. But the acute metabolic response to exercise and the transcriptional profile of the working muscle is similar in healthy controls and type 2 diabetic patients, including but not limited to intact activation...... of skeletal muscle AMP-activated kinase signaling, glucose uptake and expression of peroxisome proliferator-activated receptor gamma coactivator 1α. The increase in plasma acylcarnitines during exercise is not influenced by type 2 diabetes or obesity. The hepatic response to exercise is dependent......PURPOSE OF REVIEW: Exercise is recommended as therapeutic intervention for people at risk to develop type 2 diabetes to prevent or treat the disease. Recent studies on the influence of obesity and type 2 diabetes on the outcome of exercise programs are discussed. RECENT FINDINGS: Poor glycemic...

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

The Role of Carbohydrate Response Element Binding Protein in Intestinal and Hepatic Fructose Metabolism

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Katsumi Iizuka

2017-02-01

Full Text Available Many articles have discussed the relationship between fructose consumption and the incidence of obesity and related diseases. Fructose is absorbed in the intestine and metabolized in the liver to glucose, lactate, glycogen, and, to a lesser extent, lipids. Unabsorbed fructose causes bacterial fermentation, resulting in irritable bowl syndrome. Therefore, understanding the mechanisms underlying intestinal and hepatic fructose metabolism is important for the treatment of metabolic syndrome and fructose malabsorption. Carbohydrate response element binding protein (ChREBP is a glucose-activated transcription factor that controls approximately 50% of de novo lipogenesis in the liver. ChREBP target genes are involved in glycolysis (Glut2, liver pyruvate kinase, fructolysis (Glut5, ketohexokinase, and lipogenesis (acetyl CoA carboxylase, fatty acid synthase. ChREBP gene deletion protects against high sucrose diet-induced and leptin-deficient obesity, because Chrebp−/− mice cannot consume fructose or sucrose. Moreover, ChREBP contributes to some of the physiological effects of fructose on sweet taste preference and glucose production through regulation of ChREBP target genes, such as fibroblast growth factor-21 and glucose-6-phosphatase catalytic subunits. Thus, ChREBP might play roles in fructose metabolism. Restriction of excess fructose intake will be beneficial for preventing not only metabolic syndrome but also irritable bowl syndrome.

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.

Genetic ancestry in relation to the metabolic response to a US versus traditional Mexican diet: a randomized crossover feeding trial among women of Mexican descent.

Science.gov (United States)

Santiago-Torres, M; De Dieu Tapsoba, J; Kratz, M; Lampe, J W; Breymeyer, K L; Levy, L; Song, X; Villaseñor, A; Wang, C-Y; Fejerman, L; Neuhouser, M L; Carlson, C S

2017-03-01

Certain populations with a large proportion of indigenous American (IA) genetic ancestry may be evolutionarily adapted to traditional diets high in legumes and complex carbohydrates, and may have a detrimental metabolic response to US diets high in refined carbohydrates and added sugars. We tested whether IA ancestry modified the metabolic response to a US versus traditional Mexican diet in a controlled dietary intervention. First and second generation Mexican immigrant women (n=53) completed a randomized crossover feeding trial testing the effects of a US versus traditional Mexican diet. The metabolic response to the diets was measured by fasting serum concentrations of glucose, insulin, insulin-like growth factor-1 (IGF-1), IGF-binding protein-3 (IGFBP-3), adiponectin, C-reactive protein, interleukin-6 and computed homeostasis model assessment for insulin resistance (HOMA IR ). Blood collected at baseline was used for genotyping, and estimation of African, European and IA ancestries with the use of 214 ancestry informative markers. The genetic ancestral background was 56% IA, 38% European and 6% African. Women in the highest IA ancestry tertile (>62%) were shorter in height, less educated and less acculturated to the US lifestyle, and tended to have higher waist-to-hip ratio compared with women in the middle and lowest IA ancestry tertiles, respectively. Compared with the US diet, the traditional Mexican diet tended to reduce glucose, insulin, IGF-1, IGFBP-3 and HOMA IR among women in the middle IA ancestry group (IA ancestry ⩽45-62%), whereas having no effect on biomarkers related to inflammation. We observed modest interactions between IA ancestry and the metabolic response to a US versus traditional Mexican diet among Mexican immigrant women.

Metabolic Effects of Inflammation on Vitamin A and Carotenoids in Humans and Animal Models123

Science.gov (United States)

Rubin, Lewis P; Ross, A Catharine; Stephensen, Charles B; Bohn, Torsten; Tanumihardjo, Sherry A

2017-01-01

The association between inflammation and vitamin A (VA) metabolism and status assessment has been documented in multiple studies with animals and humans. The relation between inflammation and carotenoid status is less clear. Nonetheless, it is well known that carotenoids are associated with certain health benefits. Understanding these relations is key to improving health outcomes and mortality risk in infants and young children. Hyporetinolemia, i.e., low serum retinol concentrations, occurs during inflammation, and this can lead to the misdiagnosis of VA deficiency. On the other hand, inflammation causes impaired VA absorption and urinary losses that can precipitate VA deficiency in at-risk groups of children. Many epidemiologic studies have suggested that high dietary carotenoid intake and elevated plasma concentrations are correlated with a decreased risk of several chronic diseases; however, large-scale carotenoid supplementation trials have been unable to confirm the health benefits and in some cases resulted in controversial results. However, it has been documented that dietary carotenoids and retinoids play important roles in innate and acquired immunity and in the body’s response to inflammation. Although animal models have been useful in investigating retinoid effects on developmental immunity, it is more challenging to tease out the effects of carotenoids because of differences in the absorption, kinetics, and metabolism between humans and animal models. The current understanding of the relations between inflammation and retinoid and carotenoid metabolism and status are the topics of this review. PMID:28298266

Seasonal variations in the pattern of RNA metabolism of tuber tissue in response to excision and culture

International Nuclear Information System (INIS)

Macleod, A.J.; Mills, E.D.; Yeoman, M.M.

1979-01-01

Between December 1975 and June 1976 explants excised from Jerusalem artichoke tubers were cultured in the presence and in the absence of 2,4-D, the cells in the tissue dividing only in the presence of 2,4-D, in which the length of the first cell cycle increased nonlinearly from 18 hours to 40 hours as the tubers aged in storage at 4 0 C. Simultaneously the amount of RNA in the tissue declined linearly from 8 to 5 μg RNA per explant. Detailed examination of the RNA metabolism in dividing and in non-dividing cells during February and June 1976 revealed superimposed but independent responses to wounding during excision and to stimulation into growth by 2,4-D. The responses to wounding involved only a very low level of metabolic activity, were complete within a few hours of excision and changed very little with the storage of the tubers. Tissue treated with 2,4-D showed a much higher level of metabolic activity including the periodic accumulation of RNA coupled to its discontinuous synthesis. The features of these growth-related responses changed considerably during the investigation. (author)

Copper metabolism: a multicompartmental model of copper kinetics in the rat

International Nuclear Information System (INIS)

Dunn, M.A.

1985-01-01

A qualitative multicompartmental model was developed that describes the whole-body kinetics of copper metabolism in the adult rat. The model was developed from radiocopper percent dose vs. time data measured over a three day period in plasma, liver, skin, skeletal muscle, bile and feces after the intravenous injection of 10 μg copper labeled with 64 Cu. Plasma radiocopper was separated into ceruloplasmin (Cp) and nonceruloplasmin (NCp) fractions. Liver cytosolic radiocopper was fractionated into void volume superoxide dismutase (SOD) containing and metallothionein fractions by gel filtration. Liver particulate fractions were isolated by differential centrifugation. The SAAM and CONSAM modeling programs were used to develop the model. The sizes of compartments, fractional rate constants and mass transfer rates between compartments were evaluated. The intracellular metabolism of copper was similar in hepatic and extrahepatic tissues being comprised of a faster turning over compartment (FTC) exchanging copper with NCp and a slower turning over compartment (STC) with input from Cp. Output from the STC was into the FTC. In the liver the STC was postulated to represent SOD copper which unlike the extrahepatic tissues received much of its input from the FTC. A small amount of biliary copper (9%) was postulated to return to plasma NCp by enterohepatic recycling. The model developed was contrasted and compared with two previous models of copper metabolism

Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

Science.gov (United States)

Henson, Michael A

2015-12-01

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

Effect of adrenal medullectomy on metabolic responses to chronic intermittent hypoxia in the frequently sampled intravenous glucose tolerance test.

Science.gov (United States)

Shin, Mi-Kyung; Han, Woobum; Joo, Hoon; Bevans-Fonti, Shannon; Shiota, Masakazu; Stefanovski, Darko; Polotsky, Vsevolod Y

2017-04-01

Obstructive sleep apnea is associated with type 2 diabetes. We have previously developed a mouse model of intermittent hypoxia (IH) mimicking oxyhemoglobin desaturations in patients with sleep apnea and have shown that IH increases fasting glucose, hepatic glucose output, and plasma catecholamines. We hypothesize that adrenal medulla modulates glucose responses to IH and that such responses can be prevented by adrenal medullectomy. We performed adrenal medullectomy or sham surgery in lean C57BL/6J mice, which were exposed to IH or intermittent air (control) for 4 wk followed by the frequently sampled intravenous glucose tolerance test (FSIVGTT) in unanesthetized unrestrained animals. IH was administered during the 12-h light phase (9 AM to 9 PM) by decreasing inspired oxygen from 21 to 6.5% 60 cycles/h. Insulin sensitivity (S I ), insulin independent glucose disposal [glucose effectiveness (S G )], and the insulin response to glucose (AIR G ) were determined using the minimal model method. In contrast to our previous data obtained in restrained mice, IH did not affect fasting blood glucose and plasma insulin levels in sham-operated mice. IH significantly decreased S G but did not affect S I and AIR G Adrenal medullectomy decreased fasting blood glucose and plasma insulin levels and increased glycogen synthesis in the liver in hypoxic mice but did not have a significant effect on the FSIVGTT metrics. We conclude that, in the absence of restraints, IH has no effect on glucose metabolism in lean mice with exception of decreased S G , whereas adrenal medullectomy decreases fasting glucose and insulin levels in the IH environment. NEW & NOTEWORTHY To our knowledge, this is the first study examining the role of adrenal catecholamines in glucose metabolism during intermittent hypoxia (IH) in unanesthetized unrestrained C57BL/6J mice. We report that IH did not affect fasting glucose and insulin levels nor insulin sensitivity and insulin secretion during, whereas glucose

Multi site Kinetic Modeling of 13C Metabolic MR Using [1-13C]Pyruvate

International Nuclear Information System (INIS)

Damian, P.A.G.; Sperl, J.I.; Janich, M.A.; Wiesinger, F.; Schulte, R.F.; Menzel, M.I.; Damian, P.A.G.; Damian, P.A.G.; Haase, A.; Janich, M.A.; Schwaiger, M.; Janich, M.A.; Khegai, O.; Glaser, S.J.

2014-01-01

Hyperpolarized 13 C imaging allows real-time in vivo measurements of metabolite levels. Quantification of metabolite conversion between [1- 13 C]pyruvate and downstream metabolites [1- 13 C]alanine, [1- 13 C]lactate, and [ 13 C] bicarbonate can be achieved through kinetic modeling. Since pyruvate interacts dynamically and simultaneously with its downstream metabolites, the purpose of this work is the determination of parameter values through a multi site, dynamic model involving possible biochemical pathways present in MR spectroscopy. Kinetic modeling parameters were determined by fitting the multi site model to time-domain dynamic metabolite data. The results for different pyruvate doses were compared with those of different two-site models to evaluate the hypothesis that for identical data the uncertainty of a model and the signal-to-noise ratio determine the sensitivity in detecting small physiological differences in the target metabolism. In comparison to the two-site exchange models, the multi site model yielded metabolic conversion rates with smaller bias and smaller standard deviation, as demonstrated in simulations with different signal-to-noise ratio. Pyruvate dose effects observed previously were confirmed and quantified through metabolic conversion rate values. Parameter interdependency allowed an accurate quantification and can therefore be useful for monitoring metabolic activity in different tissues

Network thermodynamic curation of human and yeast genome-scale metabolic models.

Science.gov (United States)

Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

2014-07-15

Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling

DEFF Research Database (Denmark)

Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna

2015-01-01

Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....

Dopamine D4 receptors modulate brain metabolic activity in the prefrontal cortex and cerebellum at rest and in response to methylphenidate

Energy Technology Data Exchange (ETDEWEB)

Michaelides, M.; Wang, G.; Michaelides, M.; Pascau, J.; Gispert, J.-D.; Delis, F.; Grandy, D.K.; Wang, G.-J.; Desco, M.; Rubinstein, M.; Volkow, N.D.; Thanos, P.K.

2010-07-16

Methylphenidate (MP) is widely used to treat attention deficit hyperactivity disorder (ADHD). Variable number of tandem repeats polymorphisms in the dopamine D4 receptor (D{sub 4}) gene have been implicated in vulnerability to ADHD and the response to MP. Here we examined the contribution of dopamine D4 receptors (D4Rs) to baseline brain glucose metabolism and to the regional metabolic responses to MP. We compared brain glucose metabolism (measured with micro-positron emission tomography and [{sup 18}F]2-fluoro-2-deoxy-D-glucose) at baseline and after MP (10 mg/kg, i.p.) administration in mice with genetic deletion of the D{sub 4}. Images were analyzed using a novel automated image registration procedure. Baseline D{sub 4}{sup -/-} mice had lower metabolism in the prefrontal cortex (PFC) and greater metabolism in the cerebellar vermis (CBV) than D{sub 4}{sup +/+} and D{sub 4}{sup +/-} mice; when given MP, D{sub 4}{sup -/-} mice increased metabolism in the PFC and decreased it in the CBV, whereas in D{sub 4}{sup +/+} and D{sub 4}{sup +/-} mice, MP decreased metabolism in the PFC and increased it in the CBV. These findings provide evidence that D4Rs modulate not only the PFC, which may reflect the activation by dopamine of D4Rs located in this region, but also the CBV, which may reflect an indirect modulation as D4Rs are minimally expressed in this region. As individuals with ADHD show structural and/or functional abnormalities in these brain regions, the association of ADHD with D4Rs may reflect its modulation of these brain regions. The differential response to MP as a function of genotype could explain differences in brain functional responses to MP between patients with ADHD and healthy controls and between patients with ADHD with different D{sub 4} polymorphisms.

Ozone modifies the metabolic and endocrine response to glucose: Reproduction of effects with the stress hormone corticosterone.

Science.gov (United States)

Thomson, Errol M; Pilon, Shinjini; Guénette, Josée; Williams, Andrew; Holloway, Alison C

2018-03-01

Air pollution is associated with increased incidence of metabolic disease (e.g. metabolic syndrome, obesity, diabetes); however, underlying mechanisms are poorly understood. Air pollutants increase the release of stress hormones (human cortisol, rodent corticosterone), which could contribute to metabolic dysregulation. We assessed acute effects of ozone, and stress axis involvement, on glucose tolerance and on the metabolic (triglyceride), endocrine/energy regulation (insulin, glucagon, GLP-1, leptin, ghrelin, corticosterone), and inflammatory/endothelial (TNF, IL-6, VEGF, PAI-1) response to exogenous glucose. Male Fischer-344 rats were exposed to clean air or 0.8 ppm ozone for 4 h in whole body chambers. Hypothalamic-pituitary-adrenal (HPA) axis involvement in ozone effects was tested through subcutaneous administration of the glucocorticoid synthesis inhibitor metyrapone (50 mg/kg body weight), corticosterone (10 mg/kg body weight), or vehicle (40% propylene glycol) prior to exposure. A glucose tolerance test (2 g/kg body weight glucose) was conducted immediately after exposure, with blood samples collected at 0, 30, 60, 90, and 120 min. Ozone exposure impaired glucose tolerance, an effect accompanied by increased plasma triglycerides but no impairment of insulin release. Ozone diminished glucagon, GLP-1, and ghrelin responses to glucose, but did not significantly impact inflammatory/endothelial analytes. Metyrapone reduced corticosterone but increased glucose and triglycerides, complicating evaluation of the impact of glucocorticoid inhibition. However, administration of corticosterone reproduced the profile of ozone effects, supporting a role for the HPA axis. The results show that ozone-dependent changes in glucose tolerance are accompanied by altered metabolic and endocrine responses to glucose challenge that are reproduced by exogenous stress hormone. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.