Novel metabolic pathways in Archaea.

Science.gov (United States)

Sato, Takaaki; Atomi, Haruyuki

2011-06-01

The Archaea harbor many metabolic pathways that differ to previously recognized classical pathways. Glycolysis is carried out by modified versions of the Embden-Meyerhof and Entner-Doudoroff pathways. Thermophilic archaea have recently been found to harbor a bi-functional fructose-1,6-bisphosphate aldolase/phosphatase for gluconeogenesis. A number of novel pentose-degrading pathways have also been recently identified. In terms of anabolic metabolism, a pathway for acetate assimilation, the methylaspartate cycle, and two CO2-fixing pathways, the 3-hydroxypropionate/4-hydroxybutyrate cycle and the dicarboxylate/4-hydroxybutyrate cycle, have been elucidated. As for biosynthetic pathways, recent studies have clarified the enzymes responsible for several steps involved in the biosynthesis of inositol phospholipids, polyamine, coenzyme A, flavin adeninedinucleotide and heme. By examining the presence/absence of homologs of these enzymes on genome sequences, we have found that the majority of these enzymes and pathways are specific to the Archaea. Copyright © 2011 Elsevier Ltd. All rights reserved.

Stress transgenerationally programs metabolic pathways linked to altered mental health.

Science.gov (United States)

Kiss, Douglas; Ambeskovic, Mirela; Montina, Tony; Metz, Gerlinde A S

2016-12-01

Stress is among the primary causes of mental health disorders, which are the most common reason for disability worldwide. The ubiquity of these disorders, and the costs associated with them, lends a sense of urgency to the efforts to improve prediction and prevention. Down-stream metabolic changes are highly feasible and accessible indicators of pathophysiological processes underlying mental health disorders. Here, we show that remote and cumulative ancestral stress programs central metabolic pathways linked to mental health disorders. The studies used a rat model consisting of a multigenerational stress lineage (the great-great-grandmother and each subsequent generation experienced stress during pregnancy) and a transgenerational stress lineage (only the great-great-grandmother was stressed during pregnancy). Urine samples were collected from adult male F4 offspring and analyzed using 1 H NMR spectroscopy. The results of variable importance analysis based on random variable combination were used for unsupervised multivariate principal component analysis and hierarchical clustering analysis, as well as metabolite set enrichment analysis (MSEA) and pathway analysis. We identified distinct metabolic profiles associated with the multigenerational and transgenerational stress phenotype, with consistent upregulation of hippurate and downregulation of tyrosine, threonine, and histamine. MSEA and pathway analysis showed that these metabolites are involved in catecholamine biosynthesis, immune responses, and microbial host interactions. The identification of metabolic signatures linked to ancestral programming assists in the discovery of gene targets for future studies of epigenetic regulation in pathogenic processes. Ultimately, this research can lead to biomarker discovery for better prediction and prevention of mental health disorders.

Primary Metabolic Pathways and Metabolic Flux Analysis

DEFF Research Database (Denmark)

Villadsen, John

2015-01-01

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

Synthetic Metabolic Pathways

DEFF Research Database (Denmark)

topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Synthetic Metabolic Pathways: Methods and Protocols aims to ensure successful results in the further study...

Metabolic pathway analysis and kinetic studies for production of nattokinase in Bacillus subtilis.

Science.gov (United States)

Unrean, Pornkamol; Nguyen, Nhung H A

2013-01-01

We have constructed a reaction network model of Bacillus subtilis. The model was analyzed using a pathway analysis tool called elementary mode analysis (EMA). The analysis tool was used to study the network capabilities and the possible effects of altered culturing conditions on the production of a fibrinolytic enzyme, nattokinase (NK) by B. subtilis. Based on all existing metabolic pathways, the maximum theoretical yield for NK synthesis in B. subtilis under different substrates and oxygen availability was predicted and the optimal culturing condition for NK production was identified. To confirm model predictions, experiments were conducted by testing these culture conditions for their influence on NK activity. The optimal culturing conditions were then applied to batch fermentation, resulting in high NK activity. The EMA approach was also applied for engineering B. subtilis metabolism towards the most efficient pathway for NK synthesis by identifying target genes for deletion and overexpression that enable the cell to produce NK at the maximum theoretical yield. The consistency between experiments and model predictions proves the feasibility of EMA being used to rationally design culture conditions and genetic manipulations for the efficient production of desired products.

Aligning Metabolic Pathways Exploiting Binary Relation of Reactions.

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Yiran Huang

Full Text Available Metabolic pathway alignment has been widely used to find one-to-one and/or one-to-many reaction mappings to identify the alternative pathways that have similar functions through different sets of reactions, which has important applications in reconstructing phylogeny and understanding metabolic functions. The existing alignment methods exhaustively search reaction sets, which may become infeasible for large pathways. To address this problem, we present an effective alignment method for accurately extracting reaction mappings between two metabolic pathways. We show that connected relation between reactions can be formalized as binary relation of reactions in metabolic pathways, and the multiplications of zero-one matrices for binary relations of reactions can be accomplished in finite steps. By utilizing the multiplications of zero-one matrices for binary relation of reactions, we efficiently obtain reaction sets in a small number of steps without exhaustive search, and accurately uncover biologically relevant reaction mappings. Furthermore, we introduce a measure of topological similarity of nodes (reactions by comparing the structural similarity of the k-neighborhood subgraphs of the nodes in aligning metabolic pathways. We employ this similarity metric to improve the accuracy of the alignments. The experimental results on the KEGG database show that when compared with other state-of-the-art methods, in most cases, our method obtains better performance in the node correctness and edge correctness, and the number of the edges of the largest common connected subgraph for one-to-one reaction mappings, and the number of correct one-to-many reaction mappings. Our method is scalable in finding more reaction mappings with better biological relevance in large metabolic pathways.

Signaling Pathways Regulating Redox Balance in Cancer Metabolism.

Science.gov (United States)

De Santis, Maria Chiara; Porporato, Paolo Ettore; Martini, Miriam; Morandi, Andrea

2018-01-01

The interplay between rewiring tumor metabolism and oncogenic driver mutations is only beginning to be appreciated. Metabolic deregulation has been described for decades as a bystander effect of genomic aberrations. However, for the biology of malignant cells, metabolic reprogramming is essential to tackle a harsh environment, including nutrient deprivation, reactive oxygen species production, and oxygen withdrawal. Besides the well-investigated glycolytic metabolism, it is emerging that several other metabolic fluxes are relevant for tumorigenesis in supporting redox balance, most notably pentose phosphate pathway, folate, and mitochondrial metabolism. The relationship between metabolic rewiring and mutant genes is still unclear and, therefore, we will discuss how metabolic needs and oncogene mutations influence each other to satisfy cancer cells' demands. Mutations in oncogenes, i.e., PI3K/AKT/mTOR, RAS pathway, and MYC, and tumor suppressors, i.e., p53 and liver kinase B1, result in metabolic flexibility and may influence response to therapy. Since metabolic rewiring is shaped by oncogenic driver mutations, understanding how specific alterations in signaling pathways affect different metabolic fluxes will be instrumental for the development of novel targeted therapies. In the era of personalized medicine, the combination of driver mutations, metabolite levels, and tissue of origins will pave the way to innovative therapeutic interventions.

Unique Microbial Diversity and Metabolic Pathway Features of Fermented Vegetables From Hainan, China

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Peng, Qiannan; Jiang, Shuaiming; Chen, Jieling; Ma, Chenchen; Huo, Dongxue; Shao, Yuyu; Zhang, Jiachao

2018-01-01

Fermented vegetables are typically traditional foods made of fresh vegetables and their juices, which are fermented by beneficial microorganisms. Herein, we applied high-throughput sequencing and culture-dependent technology to describe the diversities of microbiota and identify core microbiota in fermented vegetables from different areas of Hainan Province, and abundant metabolic pathways in the fermented vegetables were simultaneously predicted. At the genus level, Lactobacillus bacteria were the most abundant. Lactobacillus plantarum was the most abundant species, followed by Lactobacillus fermentum, Lactobacillus pentosaceus, and Weissella cibaria. These species were present in each sample with average absolute content values greater than 1% and were thus defined as core microbiota. Analysis results based on the alpha and beta diversities of the microbial communities showed that the microbial profiles of the fermented vegetables differed significantly based on the regions and raw materials used, and the species of the vegetables had a greater effect on the microbial community structure than the region from where they were harvested. Regarding microbial functional metabolism, we observed an enrichment of metabolic pathways, including membrane transport, replication and repair and translation, which implied that the microbial metabolism in the fermented vegetables tended to be vigorous. In addition, Lactobacillus plantarum and Lactobacillus fermentum were calculated to be major metabolic pathway contributors. Finally, we constructed a network to better explain correlations among the core microbiota and metabolic pathways. This study facilitates an understanding of the differences in microbial profiles and fermentation pathways involved in the production of fermented vegetables, establishes a basis for optimally selecting microorganisms to manufacture high-quality fermented vegetable products, and lays the foundation for better utilizing tropical microbial

Unique Microbial Diversity and Metabolic Pathway Features of Fermented Vegetables From Hainan, China

Directory of Open Access Journals (Sweden)

Qiannan Peng

2018-03-01

Full Text Available Fermented vegetables are typically traditional foods made of fresh vegetables and their juices, which are fermented by beneficial microorganisms. Herein, we applied high-throughput sequencing and culture-dependent technology to describe the diversities of microbiota and identify core microbiota in fermented vegetables from different areas of Hainan Province, and abundant metabolic pathways in the fermented vegetables were simultaneously predicted. At the genus level, Lactobacillus bacteria were the most abundant. Lactobacillus plantarum was the most abundant species, followed by Lactobacillus fermentum, Lactobacillus pentosaceus, and Weissella cibaria. These species were present in each sample with average absolute content values greater than 1% and were thus defined as core microbiota. Analysis results based on the alpha and beta diversities of the microbial communities showed that the microbial profiles of the fermented vegetables differed significantly based on the regions and raw materials used, and the species of the vegetables had a greater effect on the microbial community structure than the region from where they were harvested. Regarding microbial functional metabolism, we observed an enrichment of metabolic pathways, including membrane transport, replication and repair and translation, which implied that the microbial metabolism in the fermented vegetables tended to be vigorous. In addition, Lactobacillus plantarum and Lactobacillus fermentum were calculated to be major metabolic pathway contributors. Finally, we constructed a network to better explain correlations among the core microbiota and metabolic pathways. This study facilitates an understanding of the differences in microbial profiles and fermentation pathways involved in the production of fermented vegetables, establishes a basis for optimally selecting microorganisms to manufacture high-quality fermented vegetable products, and lays the foundation for better utilizing

Phosphoketolase pathway contributes to carbon metabolism in cyanobacteria.

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Xiong, Wei; Lee, Tai-Chi; Rommelfanger, Sarah; Gjersing, Erica; Cano, Melissa; Maness, Pin-Ching; Ghirardi, Maria; Yu, Jianping

2015-12-07

Central carbon metabolism in cyanobacteria comprises the Calvin-Benson-Bassham (CBB) cycle, glycolysis, the pentose phosphate (PP) pathway and the tricarboxylic acid (TCA) cycle. Redundancy in this complex metabolic network renders the rational engineering of cyanobacterial metabolism for the generation of biomass, biofuels and chemicals a challenge. Here we report the presence of a functional phosphoketolase pathway, which splits xylulose-5-phosphate (or fructose-6-phosphate) to acetate precursor acetyl phosphate, in an engineered strain of the model cyanobacterium Synechocystis (ΔglgC/xylAB), in which glycogen synthesis is blocked, and xylose catabolism enabled through the introduction of xylose isomerase and xylulokinase. We show that this mutant strain is able to metabolise xylose to acetate on nitrogen starvation. To see whether acetate production in the mutant is linked to the activity of phosphoketolase, we disrupted a putative phosphoketolase gene (slr0453) in the ΔglgC/xylAB strain, and monitored metabolic flux using (13)C labelling; acetate and 2-oxoglutarate production was reduced in the light. A metabolic flux analysis, based on isotopic data, suggests that the phosphoketolase pathway metabolises over 30% of the carbon consumed by ΔglgC/xylAB during photomixotrophic growth on xylose and CO2. Disruption of the putative phosphoketolase gene in wild-type Synechocystis also led to a deficiency in acetate production in the dark, indicative of a contribution of the phosphoketolase pathway to heterotrophic metabolism. We suggest that the phosphoketolase pathway, previously uncharacterized in photosynthetic organisms, confers flexibility in energy and carbon metabolism in cyanobacteria, and could be exploited to increase the efficiency of cyanobacterial carbon metabolism and photosynthetic productivity.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses.

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Serbus, Laura R; Rodriguez, Brian Garcia; Sharmin, Zinat; Momtaz, A J M Zehadee; Christensen, Steen

2017-06-07

The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale. Copyright © 2017 Serbus et al.

Predictive Genomic Analyses Inform the Basis for Vitamin Metabolism and Provisioning in Bacteria-Arthropod Endosymbioses

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Laura R. Serbus

2017-06-01

Full Text Available The requirement of vitamins for core metabolic processes creates a unique set of pressures for arthropods subsisting on nutrient-limited diets. While endosymbiotic bacteria carried by arthropods have been widely implicated in vitamin provisioning, the underlying molecular mechanisms are not well understood. To address this issue, standardized predictive assessment of vitamin metabolism was performed in 50 endosymbionts of insects and arachnids. The results predicted that arthropod endosymbionts overall have little capacity for complete de novo biosynthesis of conventional or active vitamin forms. Partial biosynthesis pathways were commonly predicted, suggesting a substantial role in vitamin provisioning. Neither taxonomic relationships between host and symbiont, nor the mode of host-symbiont interaction were clear predictors of endosymbiont vitamin pathway capacity. Endosymbiont genome size and the synthetic capacity of nonsymbiont taxonomic relatives were more reliable predictors. We developed a new software application that also predicted that last-step conversion of intermediates into active vitamin forms may contribute further to vitamin biosynthesis by endosymbionts. Most instances of predicted vitamin conversion were paralleled by predictions of vitamin use. This is consistent with achievement of provisioning in some cases through upregulation of pathways that were retained for endosymbiont benefit. The predicted absence of other enzyme classes further suggests a baseline of vitamin requirement by the majority of endosymbionts, as well as some instances of putative mutualism. Adaptation of this workflow to analysis of other organisms and metabolic pathways will provide new routes for considering the molecular basis for symbiosis on a comprehensive scale.

Understanding specificity in metabolic pathways-Structural biology of human nucleotide metabolism

International Nuclear Information System (INIS)

Welin, Martin; Nordlund, Paer

2010-01-01

Interactions are the foundation of life at the molecular level. In the plethora of activities in the cell, the evolution of enzyme specificity requires the balancing of appropriate substrate affinity with a negative selection, in order to minimize interactions with other potential substrates in the cell. To understand the structural basis for enzyme specificity, the comparison of structural and biochemical data between enzymes within pathways using similar substrates and effectors is valuable. Nucleotide metabolism is one of the largest metabolic pathways in the human cell and is of outstanding therapeutic importance since it activates and catabolises nucleoside based anti-proliferative drugs and serves as a direct target for anti-proliferative drugs. In recent years the structural coverage of the enzymes involved in human nucleotide metabolism has been dramatically improved and is approaching completion. An important factor has been the contribution from the Structural Genomics Consortium (SGC) at Karolinska Institutet, which recently has solved 33 novel structures of enzymes and enzyme domains in human nucleotide metabolism pathways and homologs thereof. In this review we will discuss some of the principles for substrate specificity of enzymes in human nucleotide metabolism illustrated by a selected set of enzyme families where a detailed understanding of the structural determinants for specificity is now emerging.

Metabolic Pathways Visualization Skills Development by Undergraduate Students

Science.gov (United States)

dos Santos, Vanessa J. S. V.; Galembeck, Eduardo

2015-01-01

We have developed a metabolic pathways visualization skill test (MPVST) to gain greater insight into our students' abilities to comprehend the visual information presented in metabolic pathways diagrams. The test is able to discriminate students' visualization ability with respect to six specific visualization skills that we identified as key to…

Combining chemoinformatics with bioinformatics: in silico prediction of bacterial flavor-forming pathways by a chemical systems biology approach "reverse pathway engineering".

Science.gov (United States)

Liu, Mengjin; Bienfait, Bruno; Sacher, Oliver; Gasteiger, Johann; Siezen, Roland J; Nauta, Arjen; Geurts, Jan M W

2014-01-01

The incompleteness of genome-scale metabolic models is a major bottleneck for systems biology approaches, which are based on large numbers of metabolites as identified and quantified by metabolomics. Many of the revealed secondary metabolites and/or their derivatives, such as flavor compounds, are non-essential in metabolism, and many of their synthesis pathways are unknown. In this study, we describe a novel approach, Reverse Pathway Engineering (RPE), which combines chemoinformatics and bioinformatics analyses, to predict the "missing links" between compounds of interest and their possible metabolic precursors by providing plausible chemical and/or enzymatic reactions. We demonstrate the added-value of the approach by using flavor-forming pathways in lactic acid bacteria (LAB) as an example. Established metabolic routes leading to the formation of flavor compounds from leucine were successfully replicated. Novel reactions involved in flavor formation, i.e. the conversion of alpha-hydroxy-isocaproate to 3-methylbutanoic acid and the synthesis of dimethyl sulfide, as well as the involved enzymes were successfully predicted. These new insights into the flavor-formation mechanisms in LAB can have a significant impact on improving the control of aroma formation in fermented food products. Since the input reaction databases and compounds are highly flexible, the RPE approach can be easily extended to a broad spectrum of applications, amongst others health/disease biomarker discovery as well as synthetic biology.

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.

Gene prediction validation and functional analysis of redundant pathways

DEFF Research Database (Denmark)

Sønderkær, Mads

2011-01-01

have employed a large mRNA-seq data set to improve and validate ab initio predicted gene models. This direct experimental evidence also provides reliable determinations of UTR regions and polyadenylation sites, which are not easily predicted in plants. Furthermore, once an annotated genome sequence...... is available, gene expression by mRNA-Seq enables acquisition of a more complete overview of gene isoform usage in complex enzymatic pathways enabling the identification of key genes. Metabolism in potatoes This information is useful e.g. for crop improvement based on manipulation of agronomically important...

The effect of selected metals on the central metabolic pathways in ...

African Journals Online (AJOL)

compounds, interfere with xenobiotic metabolic pathways, and may also affect glycolysis, the Krebs cycle, oxidative phosphorylation, protein amino acid metabolism as well as carbohydrate and lipid metabolism. Therefore, in this review, we discuss the two phases of the central metabolic pathways, as well as how metals ...

Evidence that humans metabolize benzene via two pathways.

NARCIS (Netherlands)

Rappaport, S.M.; Kim, S.; Lan, Q.; Vermeulen, R.C.H.; Waidyanatha, S.; Zhang, L.; Li, G.; Yin, S.; Hayes, R.B.; Rothman, N.; Smith, M.T.

2009-01-01

BACKGROUND: Recent evidence has shown that humans metabolize benzene more efficiently at environmental air concentrations than at concentrations > 1 ppm. This led us to speculate that an unidentified metabolic pathway was mainly responsible for benzene metabolism at ambient levels. OBJECTIVE: We

Clinical pathways for inborn errors of metabolism: warranted and feasible

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Demirdas Serwet

2013-02-01

Full Text Available Abstract Inborn errors of metabolism (IEMs are known for their low prevalence and multidisciplinary care mostly founded on expert opinion. Clinical pathways are multidisciplinary tools to organise care which provide a clear route to the best care and improve communication. In 2010 the Dutch Society for Children and Adults with an Inborn Error of Metabolism (VKS initiated development of clinical pathways for inborn errors of metabolism. In this letter to the editor we describe why it is warranted to develop clinical pathways for IEMs and shortly discuss the process of development for these pathways in the Netherlands.

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

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Akιn Ata

2007-12-01

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

Population FBA predicts metabolic phenotypes in yeast.

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Piyush Labhsetwar

2017-09-01

Full Text Available Using protein counts sampled from single cell proteomics distributions to constrain fluxes through a genome-scale model of metabolism, Population flux balance analysis (Population FBA successfully described metabolic heterogeneity in a population of independent Escherichia coli cells growing in a defined medium. We extend the methodology to account for correlations in protein expression arising from the co-regulation of genes and apply it to study the growth of independent Saccharomyces cerevisiae cells in two different growth media. We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen, while FBA without proteomics constraints predicts respirative metabolism almost exclusively. The comparisons to the 13C study showed improvement upon inclusion of the correlations and motivated a technique to systematically identify inconsistent kinetic parameters in the literature. The minor secretion fluxes for glycerol and acetate are underestimated by our method, which indicate a need for further refinements to the metabolic model. For yeast cells grown in synthetic defined (SD medium, the calculated broad distribution of growth rates matches experimental observations from single cell studies, and we characterize several metabolic phenotypes within our modeled populations that make use of diverse pathways. Fast growing yeast cells are predicted to perform significant amount of respiration, use serine-glycine cycle and produce ethanol in mitochondria as opposed to slow growing cells. We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. We find that a core set of 51 constraints are essential but

Putative drug and vaccine target protein identification using comparative genomic analysis of KEGG annotated metabolic pathways of Mycoplasma hyopneumoniae.

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Damte, Dereje; Suh, Joo-Won; Lee, Seung-Jin; Yohannes, Sileshi Belew; Hossain, Md Akil; Park, Seung-Chun

2013-07-01

In the present study, a computational comparative and subtractive genomic/proteomic analysis aimed at the identification of putative therapeutic target and vaccine candidate proteins from Kyoto Encyclopedia of Genes and Genomes (KEGG) annotated metabolic pathways of Mycoplasma hyopneumoniae was performed for drug design and vaccine production pipelines against M.hyopneumoniae. The employed comparative genomic and metabolic pathway analysis with a predefined computational systemic workflow extracted a total of 41 annotated metabolic pathways from KEGG among which five were unique to M. hyopneumoniae. A total of 234 proteins were identified to be involved in these metabolic pathways. Although 125 non homologous and predicted essential proteins were found from the total that could serve as potential drug targets and vaccine candidates, additional prioritizing parameters characterize 21 proteins as vaccine candidate while druggability of each of the identified proteins evaluated by the DrugBank database prioritized 42 proteins suitable for drug targets. Copyright © 2013 Elsevier Inc. All rights reserved.

Pathway Thermodynamics Highlights Kinetic Obstacles in Central Metabolism

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Flamholz, Avi; Reznik, Ed; Liebermeister, Wolfram; Milo, Ron

2014-01-01

In metabolism research, thermodynamics is usually used to determine the directionality of a reaction or the feasibility of a pathway. However, the relationship between thermodynamic potentials and fluxes is not limited to questions of directionality: thermodynamics also affects the kinetics of reactions through the flux-force relationship, which states that the logarithm of the ratio between the forward and reverse fluxes is directly proportional to the change in Gibbs energy due to a reaction (ΔrG′). Accordingly, if an enzyme catalyzes a reaction with a ΔrG′ of -5.7 kJ/mol then the forward flux will be roughly ten times the reverse flux. As ΔrG′ approaches equilibrium (ΔrG′ = 0 kJ/mol), exponentially more enzyme counterproductively catalyzes the reverse reaction, reducing the net rate at which the reaction proceeds. Thus, the enzyme level required to achieve a given flux increases dramatically near equilibrium. Here, we develop a framework for quantifying the degree to which pathways suffer these thermodynamic limitations on flux. For each pathway, we calculate a single thermodynamically-derived metric (the Max-min Driving Force, MDF), which enables objective ranking of pathways by the degree to which their flux is constrained by low thermodynamic driving force. Our framework accounts for the effect of pH, ionic strength and metabolite concentration ranges and allows us to quantify how alterations to the pathway structure affect the pathway's thermodynamics. Applying this methodology to pathways of central metabolism sheds light on some of their features, including metabolic bypasses (e.g., fermentation pathways bypassing substrate-level phosphorylation), substrate channeling (e.g., of oxaloacetate from malate dehydrogenase to citrate synthase), and use of alternative cofactors (e.g., quinone as an electron acceptor instead of NAD). The methods presented here place another arrow in metabolic engineers' quiver, providing a simple means of evaluating

An Automated Pipeline for Engineering Many-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization.

Science.gov (United States)

Halper, Sean M; Cetnar, Daniel P; Salis, Howard M

2018-01-01

Engineering many-enzyme metabolic pathways suffers from the design curse of dimensionality. There are an astronomical number of synonymous DNA sequence choices, though relatively few will express an evolutionary robust, maximally productive pathway without metabolic bottlenecks. To solve this challenge, we have developed an integrated, automated computational-experimental pipeline that identifies a pathway's optimal DNA sequence without high-throughput screening or many cycles of design-build-test. The first step applies our Operon Calculator algorithm to design a host-specific evolutionary robust bacterial operon sequence with maximally tunable enzyme expression levels. The second step applies our RBS Library Calculator algorithm to systematically vary enzyme expression levels with the smallest-sized library. After characterizing a small number of constructed pathway variants, measurements are supplied to our Pathway Map Calculator algorithm, which then parameterizes a kinetic metabolic model that ultimately predicts the pathway's optimal enzyme expression levels and DNA sequences. Altogether, our algorithms provide the ability to efficiently map the pathway's sequence-expression-activity space and predict DNA sequences with desired metabolic fluxes. Here, we provide a step-by-step guide to applying the Pathway Optimization Pipeline on a desired multi-enzyme pathway in a bacterial host.

Evolutionary Rate Heterogeneity of Primary and Secondary Metabolic Pathway Genes in Arabidopsis thaliana.

Science.gov (United States)

Mukherjee, Dola; Mukherjee, Ashutosh; Ghosh, Tapash Chandra

2015-11-10

Primary metabolism is essential to plants for growth and development, and secondary metabolism helps plants to interact with the environment. Many plant metabolites are industrially important. These metabolites are produced by plants through complex metabolic pathways. Lack of knowledge about these pathways is hindering the successful breeding practices for these metabolites. For a better knowledge of the metabolism in plants as a whole, evolutionary rate variation of primary and secondary metabolic pathway genes is a prerequisite. In this study, evolutionary rate variation of primary and secondary metabolic pathway genes has been analyzed in the model plant Arabidopsis thaliana. Primary metabolic pathway genes were found to be more conserved than secondary metabolic pathway genes. Several factors such as gene structure, expression level, tissue specificity, multifunctionality, and domain number are the key factors behind this evolutionary rate variation. This study will help to better understand the evolutionary dynamics of plant metabolism. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Rewriting the Metabolic Blueprint: Advances in Pathway Diversification in Microorganisms

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Gazi Sakir Hossain

2018-02-01

Full Text Available Living organisms have evolved over millions of years to fine tune their metabolism to create efficient pathways for producing metabolites necessary for their survival. Advancement in the field of synthetic biology has enabled the exploitation of these metabolic pathways for the production of desired compounds by creating microbial cell factories through metabolic engineering, thus providing sustainable routes to obtain value-added chemicals. Following the past success in metabolic engineering, there is increasing interest in diversifying natural metabolic pathways to construct non-natural biosynthesis routes, thereby creating possibilities for producing novel valuable compounds that are non-natural or without elucidated biosynthesis pathways. Thus, the range of chemicals that can be produced by biological systems can be expanded to meet the demands of industries for compounds such as plastic precursors and new antibiotics, most of which can only be obtained through chemical synthesis currently. Herein, we review and discuss novel strategies that have been developed to rewrite natural metabolic blueprints in a bid to broaden the chemical repertoire achievable in microorganisms. This review aims to provide insights on recent approaches taken to open new avenues for achieving biochemical production that are beyond currently available inventions.

Rewriting the Metabolic Blueprint: Advances in Pathway Diversification in Microorganisms.

Science.gov (United States)

Hossain, Gazi Sakir; Nadarajan, Saravanan Prabhu; Zhang, Lei; Ng, Tee-Kheang; Foo, Jee Loon; Ling, Hua; Choi, Won Jae; Chang, Matthew Wook

2018-01-01

Living organisms have evolved over millions of years to fine tune their metabolism to create efficient pathways for producing metabolites necessary for their survival. Advancement in the field of synthetic biology has enabled the exploitation of these metabolic pathways for the production of desired compounds by creating microbial cell factories through metabolic engineering, thus providing sustainable routes to obtain value-added chemicals. Following the past success in metabolic engineering, there is increasing interest in diversifying natural metabolic pathways to construct non-natural biosynthesis routes, thereby creating possibilities for producing novel valuable compounds that are non-natural or without elucidated biosynthesis pathways. Thus, the range of chemicals that can be produced by biological systems can be expanded to meet the demands of industries for compounds such as plastic precursors and new antibiotics, most of which can only be obtained through chemical synthesis currently. Herein, we review and discuss novel strategies that have been developed to rewrite natural metabolic blueprints in a bid to broaden the chemical repertoire achievable in microorganisms. This review aims to provide insights on recent approaches taken to open new avenues for achieving biochemical production that are beyond currently available inventions.

Metabolic pathway alignment between species using a comprehensive and flexible similarity measure

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de Ridder Dick

2008-12-01

Full Text Available Abstract Background Comparative analysis of metabolic networks in multiple species yields important information on their evolution, and has great practical value in metabolic engineering, human disease analysis, drug design etc. In this work, we aim to systematically search for conserved pathways in two species, quantify their similarities, and focus on the variations between them. Results We present an efficient framework, Metabolic Pathway Alignment and Scoring (M-PAS, for identifying and ranking conserved metabolic pathways. M-PAS aligns all reactions in entire metabolic networks of two species and assembles them into pathways, taking mismatches, gaps and crossovers into account. It uses a comprehensive scoring function, which quantifies pathway similarity such that we can focus on different pathways given different biological motivations. Using M-PAS, we detected 1198 length-four pathways fully conserved between Saccharomyces cerevisiae and Escherichia coli, and also revealed 1399 cases of a species using a unique route in otherwise highly conserved pathways. Conclusion Our method efficiently automates the process of exploring reaction arrangement possibilities, both between species and within species, to find conserved pathways. We not only reconstruct conventional pathways such as those found in KEGG, but also discover new pathway possibilities. Our results can help to generate hypotheses on missing reactions and manifest differences in highly conserved pathways, which is useful for biology and life science applications.

NemaPath: online exploration of KEGG-based metabolic pathways for nematodes

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Wang Zhengyuan

2008-11-01

Full Text Available Abstract Background Nematode.net http://www.nematode.net is a web-accessible resource for investigating gene sequences from parasitic and free-living nematode genomes. Beyond the well-characterized model nematode C. elegans, over 500,000 expressed sequence tags (ESTs and nearly 600,000 genome survey sequences (GSSs have been generated from 36 nematode species as part of the Parasitic Nematode Genomics Program undertaken by the Genome Center at Washington University School of Medicine. However, these sequencing data are not present in most publicly available protein databases, which only include sequences in Swiss-Prot. Swiss-Prot, in turn, relies on GenBank/Embl/DDJP for predicted proteins from complete genomes or full-length proteins. Description Here we present the NemaPath pathway server, a web-based pathway-level visualization tool for navigating putative metabolic pathways for over 30 nematode species, including 27 parasites. The NemaPath approach consists of two parts: 1 a backend tool to align and evaluate nematode genomic sequences (curated EST contigs against the annotated Kyoto Encyclopedia of Genes and Genomes (KEGG protein database; 2 a web viewing application that displays annotated KEGG pathway maps based on desired confidence levels of primary sequence similarity as defined by a user. NemaPath also provides cross-referenced access to nematode genome information provided by other tools available on Nematode.net, including: detailed NemaGene EST cluster information; putative translations; GBrowse EST cluster views; links from nematode data to external databases for corresponding synonymous C. elegans counterparts, subject matches in KEGG's gene database, and also KEGG Ontology (KO identification. Conclusion The NemaPath server hosts metabolic pathway mappings for 30 nematode species and is available on the World Wide Web at http://nematode.net/cgi-bin/keggview.cgi. The nematode source sequences used for the metabolic pathway

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.

Biochemical research elucidating metabolic pathways in Pneumocystis*

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Kaneshiro E.S.

2010-12-01

Full Text Available Advances in sequencing the Pneumocystis carinii genome have helped identify potential metabolic pathways operative in the organism. Also, data from characterizing the biochemical and physiological nature of these organisms now allow elucidation of metabolic pathways as well as pose new challenges and questions that require additional experiments. These experiments are being performed despite the difficulty in doing experiments directly on this pathogen that has yet to be subcultured indefinitely and produce mass numbers of cells in vitro. This article reviews biochemical approaches that have provided insights into several Pneumocystis metabolic pathways. It focuses on 1 S-adenosyl-L-methionine (AdoMet; SAM, which is a ubiquitous participant in numerous cellular reactions; 2 sterols: focusing on oxidosqualene cyclase that forms lanosterol in P. carinii; SAM:sterol C-24 methyltransferase that adds methyl groups at the C-24 position of the sterol side chain; and sterol 14α-demethylase that removes a methyl group at the C-14 position of the sterol nucleus; and 3 synthesis of ubiquinone homologs, which play a pivotal role in mitochondrial inner membrane and other cellular membrane electron transport.

Metabolism of cysteine by cyteinesulfinate-independent pathway(s) in rat hepatocytes

International Nuclear Information System (INIS)

Stipanuk, M.H.; De La Rosa, J.; Drake, M.R.

1986-01-01

The metabolism of cysteine (CYS) and that of cysteinesulfinate (CSA) were studied in freshly isolated hepatocytes from fed rats. In incubations of rat hepatocytes with either 1 or 25 mM CSA, over 90% of the 14 CO 2 formed from [1- 14 C]CSA could be accounted for by production of hypotaurine plus taurine. In similar incubations with 1 or 25 mM CYS, only 4% of 14 CO 2 evolution from [1- 14 C]CYS could be accounted for by production of hypotaurine plus taurine. Addition of unlabeled CSA inhibited recovery of label from [1- 14 C]CYS as 14 CO 2 by 33%. Metabolism of CYS and of CSA were affected differently by addition of α-ketoglutarate, a cosubstrate for transamination, or of propargylglycine, an inhibitor of cystathionase activity. These data suggest that a substantial proportion of CYS is catabolized by CSA-independent pathways in the rat hepatocyte. Although addition of α-ketoglutarate to incubations of hepatocytes with CSA resulted in a marked increase in CSA catabolism via the transamination pathway, addition of keto acids to incubation systems had little or no effect on production of any metabolite from CYS. Thus, CYS transamination does not appear to be a major pathway of CYS metabolism in the hepatocyte. Inhibition of cystathionase with propargylglycine reduced both 14 CO 2 production from [1- 14 C]CYS and ammonia plus urea nitrogen production from CYS by about 50%; CSA catabolism was not affected. Thus, cleavage of cyst(e)ine by cystathionase may be an important physiological pathway for CYS catabolism in the liver

Unique Microbial Diversity and Metabolic Pathway Features of Fermented Vegetables From Hainan, China

OpenAIRE

Qiannan Peng; Shuaiming Jiang; Jieling Chen; Chenchen Ma; Dongxue Huo; Yuyu Shao; Jiachao Zhang; Jiachao Zhang

2018-01-01

Fermented vegetables are typically traditional foods made of fresh vegetables and their juices, which are fermented by beneficial microorganisms. Herein, we applied high-throughput sequencing and culture-dependent technology to describe the diversities of microbiota and identify core microbiota in fermented vegetables from different areas of Hainan Province, and abundant metabolic pathways in the fermented vegetables were simultaneously predicted. At the genus level, Lactobacillus bacteria we...

Sucrose metabolic pathways in sweetgum and pecan seedlings

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S.S. Sung; P.P. Kormanik; D.P. Xu; C.C. Black

1989-01-01

Sucrose metabolism and glycolysis were studied in one- to two-year-old seedlings of sweetgum (Liquidambar styraciflua L.) and pecan (Carya illinoinensis (Wangenh.) C. Koch). The sucrose synthase pathway was identified as the dominant sucrose metabolic activity in sucrose sink tissues such as terminal buds and the root cambial...

Caveat emptor: limitations of the automated reconstruction of metabolic pathways in Plasmodium.

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Ginsburg, Hagai

2009-01-01

The functional reconstruction of metabolic pathways from an annotated genome is a tedious and demanding enterprise. Automation of this endeavor using bioinformatics algorithms could cope with the ever-increasing number of sequenced genomes and accelerate the process. Here, the manual reconstruction of metabolic pathways in the functional genomic database of Plasmodium falciparum--Malaria Parasite Metabolic Pathways--is described and compared with pathways generated automatically as they appear in PlasmoCyc, metaSHARK and the Kyoto Encyclopedia for Genes and Genomes. A critical evaluation of this comparison discloses that the automatic reconstruction of pathways generates manifold paths that need an expert manual verification to accept some and reject most others based on manually curated gene annotation.

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

Large-scale transcriptome analysis reveals arabidopsis metabolic pathways are frequently influenced by different pathogens.

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Jiang, Zhenhong; He, Fei; Zhang, Ziding

2017-07-01

Through large-scale transcriptional data analyses, we highlighted the importance of plant metabolism in plant immunity and identified 26 metabolic pathways that were frequently influenced by the infection of 14 different pathogens. Reprogramming of plant metabolism is a common phenomenon in plant defense responses. Currently, a large number of transcriptional profiles of infected tissues in Arabidopsis (Arabidopsis thaliana) have been deposited in public databases, which provides a great opportunity to understand the expression patterns of metabolic pathways during plant defense responses at the systems level. Here, we performed a large-scale transcriptome analysis based on 135 previously published expression samples, including 14 different pathogens, to explore the expression pattern of Arabidopsis metabolic pathways. Overall, metabolic genes are significantly changed in expression during plant defense responses. Upregulated metabolic genes are enriched on defense responses, and downregulated genes are enriched on photosynthesis, fatty acid and lipid metabolic processes. Gene set enrichment analysis (GSEA) identifies 26 frequently differentially expressed metabolic pathways (FreDE_Paths) that are differentially expressed in more than 60% of infected samples. These pathways are involved in the generation of energy, fatty acid and lipid metabolism as well as secondary metabolite biosynthesis. Clustering analysis based on the expression levels of these 26 metabolic pathways clearly distinguishes infected and control samples, further suggesting the importance of these metabolic pathways in plant defense responses. By comparing with FreDE_Paths from abiotic stresses, we find that the expression patterns of 26 FreDE_Paths from biotic stresses are more consistent across different infected samples. By investigating the expression correlation between transcriptional factors (TFs) and FreDE_Paths, we identify several notable relationships. Collectively, the current study

Autophagic pathways and metabolic stress.

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Kaushik, S; Singh, R; Cuervo, A M

2010-10-01

Autophagy is an essential intracellular process that mediates degradation of intracellular proteins and organelles in lysosomes. Autophagy was initially identified for its role as alternative source of energy when nutrients are scarce but, in recent years, a previously unknown role for this degradative pathway in the cellular response to stress has gained considerable attention. In this review, we focus on the novel findings linking autophagic function with metabolic stress resulting either from proteins or lipids. Proper autophagic activity is required in the cellular defense against proteotoxicity arising in the cytosol and also in the endoplasmic reticulum, where a vast amount of proteins are synthesized and folded. In addition, autophagy contributes to mobilization of intracellular lipid stores and may be central to lipid metabolism in certain cellular conditions. In this review, we focus on the interrelation between autophagy and different types of metabolic stress, specifically the stress resulting from the presence of misbehaving proteins within the cytosol or in the endoplasmic reticulum and the stress following a lipogenic challenge. We also comment on the consequences that chronic exposure to these metabolic stressors could have on autophagic function and on how this effect may underlie the basis of some common metabolic disorders. © 2010 Blackwell Publishing Ltd.

Identification of cisplatin-regulated metabolic pathways in pluripotent stem cells.

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Louise von Stechow

Full Text Available The chemotherapeutic compound, cisplatin causes various kinds of DNA lesions but also triggers other pertubations, such as ER and oxidative stress. We and others have shown that treatment of pluripotent stem cells with cisplatin causes a plethora of transcriptional and post-translational alterations that, to a major extent, point to DNA damage response (DDR signaling. The orchestrated DDR signaling network is important to arrest the cell cycle and repair the lesions or, in case of damage beyond repair, eliminate affected cells. Failure to properly balance the various aspects of the DDR in stem cells contributes to ageing and cancer. Here, we performed metabolic profiling by mass spectrometry of embryonic stem (ES cells treated for different time periods with cisplatin. We then integrated metabolomics with transcriptomics analyses and connected cisplatin-regulated metabolites with regulated metabolic enzymes to identify enriched metabolic pathways. These included nucleotide metabolism, urea cycle and arginine and proline metabolism. Silencing of identified proline metabolic and catabolic enzymes indicated that altered proline metabolism serves as an adaptive, rather than a toxic response. A group of enriched metabolic pathways clustered around the metabolite S-adenosylmethionine, which is a hub for methylation and transsulfuration reactions and polyamine metabolism. Enzymes and metabolites with pro- or anti-oxidant functions were also enriched but enhanced levels of reactive oxygen species were not measured in cisplatin-treated ES cells. Lastly, a number of the differentially regulated metabolic enzymes were identified as target genes of the transcription factor p53, pointing to p53-mediated alterations in metabolism in response to genotoxic stress. Altogether, our findings reveal interconnecting metabolic pathways that are responsive to cisplatin and may serve as signaling modules in the DDR in pluripotent stem cells.

Synthetic metabolic engineering-a novel, simple technology for designing a chimeric metabolic pathway

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Ye Xiaoting

2012-09-01

Full Text Available Abstract Background The integration of biotechnology into chemical manufacturing has been recognized as a key technology to build a sustainable society. However, the practical applications of biocatalytic chemical conversions are often restricted due to their complexities involving the unpredictability of product yield and the troublesome controls in fermentation processes. One of the possible strategies to overcome these limitations is to eliminate the use of living microorganisms and to use only enzymes involved in the metabolic pathway. Use of recombinant mesophiles producing thermophilic enzymes at high temperature results in denaturation of indigenous proteins and elimination of undesired side reactions; consequently, highly selective and stable biocatalytic modules can be readily prepared. By rationally combining those modules together, artificial synthetic pathways specialized for chemical manufacturing could be designed and constructed. Results A chimeric Embden-Meyerhof (EM pathway with balanced consumption and regeneration of ATP and ADP was constructed by using nine recombinant E. coli strains overproducing either one of the seven glycolytic enzymes of Thermus thermophilus, the cofactor-independent phosphoglycerate mutase of Pyrococcus horikoshii, or the non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase of Thermococcus kodakarensis. By coupling this pathway with the Thermus malate/lactate dehydrogenase, a stoichiometric amount of lactate was produced from glucose with an overall ATP turnover number of 31. Conclusions In this study, a novel and simple technology for flexible design of a bespoke metabolic pathway was developed. The concept has been testified via a non-ATP-forming chimeric EM pathway. We designated this technology as “synthetic metabolic engineering”. Our technology is, in principle, applicable to all thermophilic enzymes as long as they can be functionally expressed in the host, and thus would be

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

Energy Technology Data Exchange (ETDEWEB)

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

2008-03-15

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

The SMARTCyp cytochrome P450 metabolism prediction server

DEFF Research Database (Denmark)

Rydberg, Patrik; Gloriam, David Erik Immanuel; Olsen, Lars

2010-01-01

The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism.......The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism....

Lipoprotein metabolism indicators improve cardiovascular risk prediction.

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Daniël B van Schalkwijk

Full Text Available BACKGROUND: Cardiovascular disease risk increases when lipoprotein metabolism is dysfunctional. We have developed a computational model able to derive indicators of lipoprotein production, lipolysis, and uptake processes from a single lipoprotein profile measurement. This is the first study to investigate whether lipoprotein metabolism indicators can improve cardiovascular risk prediction and therapy management. METHODS AND RESULTS: We calculated lipoprotein metabolism indicators for 1981 subjects (145 cases, 1836 controls from the Framingham Heart Study offspring cohort in which NMR lipoprotein profiles were measured. We applied a statistical learning algorithm using a support vector machine to select conventional risk factors and lipoprotein metabolism indicators that contributed to predicting risk for general cardiovascular disease. Risk prediction was quantified by the change in the Area-Under-the-ROC-Curve (ΔAUC and by risk reclassification (Net Reclassification Improvement (NRI and Integrated Discrimination Improvement (IDI. Two VLDL lipoprotein metabolism indicators (VLDLE and VLDLH improved cardiovascular risk prediction. We added these indicators to a multivariate model with the best performing conventional risk markers. Our method significantly improved both CVD prediction and risk reclassification. CONCLUSIONS: Two calculated VLDL metabolism indicators significantly improved cardiovascular risk prediction. These indicators may help to reduce prescription of unnecessary cholesterol-lowering medication, reducing costs and possible side-effects. For clinical application, further validation is required.

A critique of the molecular target-based drug discovery paradigm based on principles of metabolic control: advantages of pathway-based discovery.

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Hellerstein, Marc K

2008-01-01

Contemporary drug discovery and development (DDD) is dominated by a molecular target-based paradigm. Molecular targets that are potentially important in disease are physically characterized; chemical entities that interact with these targets are identified by ex vivo high-throughput screening assays, and optimized lead compounds enter testing as drugs. Contrary to highly publicized claims, the ascendance of this approach has in fact resulted in the lowest rate of new drug approvals in a generation. The primary explanation for low rates of new drugs is attrition, or the failure of candidates identified by molecular target-based methods to advance successfully through the DDD process. In this essay, I advance the thesis that this failure was predictable, based on modern principles of metabolic control that have emerged and been applied most forcefully in the field of metabolic engineering. These principles, such as the robustness of flux distributions, address connectivity relationships in complex metabolic networks and make it unlikely a priori that modulating most molecular targets will have predictable, beneficial functional outcomes. These same principles also suggest, however, that unexpected therapeutic actions will be common for agents that have any effect (i.e., that complexity can be exploited therapeutically). A potential operational solution (pathway-based DDD), based on observability rather than predictability, is described, focusing on emergent properties of key metabolic pathways in vivo. Recent examples of pathway-based DDD are described. In summary, the molecular target-based DDD paradigm is built on a naïve and misleading model of biologic control and is not heuristically adequate for advancing the mission of modern therapeutics. New approaches that take account of and are built on principles described by metabolic engineers are needed for the next generation of DDD.

Metabolic pathway redundancy within the apicomplexan-dinoflagellate radiation argues against an ancient chromalveolate plastid

KAUST Repository

Waller, Ross F.

2015-12-08

The chromalveolate hypothesis presents an attractively simple explanation for the presence of red algal-derived secondary plastids in 5 major eukaryotic lineages: “chromista” phyla, cryptophytes, haptophytes and ochrophytes; and alveolate phyla, dinoflagellates and apicomplexans. It posits that a single secondary endosymbiotic event occurred in a common ancestor of these diverse groups, and that this ancient plastid has since been maintained by vertical inheritance only. Substantial testing of this hypothesis by molecular phylogenies has, however, consistently failed to provide support for the predicted monophyly of the host organisms that harbour these plastids—the “chromalveolates.” This lack of support does not disprove the chromalveolate hypothesis per se, but rather drives the proposed endosymbiosis deeper into the eukaryotic tree, and requires multiple plastid losses to have occurred within intervening aplastidic lineages. An alternative perspective on plastid evolution is offered by considering the metabolic partnership between the endosymbiont and its host cell. A recent analysis of metabolic pathways in a deep-branching dinoflagellate indicates a high level of pathway redundancy in the common ancestor of apicomplexans and dinoflagellates, and differential losses of these pathways soon after radiation of the major extant lineages. This suggests that vertical inheritance of an ancient plastid in alveolates is highly unlikely as it would necessitate maintenance of redundant pathways over very long evolutionary timescales.

Metabolic pathway redundancy within the apicomplexan-dinoflagellate radiation argues against an ancient chromalveolate plastid

KAUST Repository

Waller, Ross F.; Gornik, Sebastian G.; Koreny, Ludek; Pain, Arnab

2015-01-01

The chromalveolate hypothesis presents an attractively simple explanation for the presence of red algal-derived secondary plastids in 5 major eukaryotic lineages: “chromista” phyla, cryptophytes, haptophytes and ochrophytes; and alveolate phyla, dinoflagellates and apicomplexans. It posits that a single secondary endosymbiotic event occurred in a common ancestor of these diverse groups, and that this ancient plastid has since been maintained by vertical inheritance only. Substantial testing of this hypothesis by molecular phylogenies has, however, consistently failed to provide support for the predicted monophyly of the host organisms that harbour these plastids—the “chromalveolates.” This lack of support does not disprove the chromalveolate hypothesis per se, but rather drives the proposed endosymbiosis deeper into the eukaryotic tree, and requires multiple plastid losses to have occurred within intervening aplastidic lineages. An alternative perspective on plastid evolution is offered by considering the metabolic partnership between the endosymbiont and its host cell. A recent analysis of metabolic pathways in a deep-branching dinoflagellate indicates a high level of pathway redundancy in the common ancestor of apicomplexans and dinoflagellates, and differential losses of these pathways soon after radiation of the major extant lineages. This suggests that vertical inheritance of an ancient plastid in alveolates is highly unlikely as it would necessitate maintenance of redundant pathways over very long evolutionary timescales.

The return of metabolism: biochemistry and physiology of the pentose phosphate pathway

Science.gov (United States)

Stincone, Anna; Prigione, Alessandro; Cramer, Thorsten; Wamelink, Mirjam M. C.; Campbell, Kate; Cheung, Eric; Olin-Sandoval, Viridiana; Grüning, Nana-Maria; Krüger, Antje; Alam, Mohammad Tauqeer; Keller, Markus A.; Breitenbach, Michael; Brindle, Kevin M.; Rabinowitz, Joshua D.; Ralser, Markus

2015-01-01

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares reactions with the Entner–Doudoroff pathway and Calvin cycle and divides into an oxidative and non-oxidative branch. The oxidative branch is highly active in most eukaryotes and converts glucose 6-phosphate into carbon dioxide, ribulose 5-phosphate and NADPH. The latter function is critical to maintain redox balance under stress situations, when cells proliferate rapidly, in ageing, and for the ‘Warburg effect’ of cancer cells. The non-oxidative branch instead is virtually ubiquitous, and metabolizes the glycolytic intermediates fructose 6-phosphate and glyceraldehyde 3-phosphate as well as sedoheptulose sugars, yielding ribose 5-phosphate for the synthesis of nucleic acids and sugar phosphate precursors for the synthesis of amino acids. Whereas the oxidative PPP is considered unidirectional, the non-oxidative branch can supply glycolysis with intermediates derived from ribose 5-phosphate and vice versa, depending on the biochemical demand. These functions require dynamic regulation of the PPP pathway that is achieved through hierarchical interactions between transcriptome, proteome and metabolome. Consequently, the biochemistry and regulation of this pathway, while still unresolved in many cases, are archetypal for the dynamics of the metabolic network of the cell. In this comprehensive article we review seminal work that led to the discovery and description of the pathway that date back now for 80 years, and address recent results about genetic and metabolic mechanisms that regulate its activity. These biochemical principles are discussed in the context of PPP deficiencies causing metabolic disease and the role of this pathway in biotechnology, bacterial and

Quantitative trait loci and metabolic pathways

Science.gov (United States)

McMullen, M. D.; Byrne, P. F.; Snook, M. E.; Wiseman, B. R.; Lee, E. A.; Widstrom, N. W.; Coe, E. H.

1998-01-01

The interpretation of quantitative trait locus (QTL) studies is limited by the lack of information on metabolic pathways leading to most economic traits. Inferences about the roles of the underlying genes with a pathway or the nature of their interaction with other loci are generally not possible. An exception is resistance to the corn earworm Helicoverpa zea (Boddie) in maize (Zea mays L.) because of maysin, a C-glycosyl flavone synthesized in silks via a branch of the well characterized flavonoid pathway. Our results using flavone synthesis as a model QTL system indicate: (i) the importance of regulatory loci as QTLs, (ii) the importance of interconnecting biochemical pathways on product levels, (iii) evidence for “channeling” of intermediates, allowing independent synthesis of related compounds, (iv) the utility of QTL analysis in clarifying the role of specific genes in a biochemical pathway, and (v) identification of a previously unknown locus on chromosome 9S affecting flavone level. A greater understanding of the genetic basis of maysin synthesis and associated corn earworm resistance should lead to improved breeding strategies. More broadly, the insights gained in relating a defined genetic and biochemical pathway affecting a quantitative trait should enhance interpretation of the biological basis of variation for other quantitative traits. PMID:9482823

Controlled sumoylation of the mevalonate pathway enzyme HMGS-1 regulates metabolism during aging

NARCIS (Netherlands)

Sapir, Amir; Tsur, Assaf; Koorman, Thijs; Ching, Kaitlin; Mishra, Prashant; Bardenheier, Annabelle; Podolsky, Lisa; Bening-Abu-Shach, Ulrike; Boxem, Mike; Chou, Tsui-Fen; Broday, Limor; Sternberg, Paul W

2014-01-01

Many metabolic pathways are critically regulated during development and aging but little is known about the molecular mechanisms underlying this regulation. One key metabolic cascade in eukaryotes is the mevalonate pathway. It catalyzes the synthesis of sterol and nonsterol isoprenoids, such as

Nucleotide metabolism in Lactococcus lactis: Salvage pathways of exogenous pyrimidines

DEFF Research Database (Denmark)

Martinussen, Jan; Andersen, Paal Skytt; Hammer, Karin

1994-01-01

By measuring enzyme activities in crude extracts and studying the effect of toxic analogs (5-fluoropyrimidines) on cell growth, the metabolism of pyrimidines in Lactococcus lactis was analyzed. Pathways by which uracil, uridine, deoxyuridine, cytidine, and deoxycytidine are metabolized in L. lact...

Features of an altered AMPK metabolic pathway in Gilbert’s Syndrome, and its role in metabolic health

OpenAIRE

Christine Mölzer; Marlies Wallner; Carina Kern; Anela Tosevska; Ursula Schwarz; Rene Zadnikar; Daniel Doberer; Rodrig Marculescu; Karl-Heinz Wagner

2016-01-01

Energy metabolism, involving the ATP-dependent AMPK-PgC-Ppar pathway impacts metabolic health immensely, in that its impairment can lead to obesity, giving rise to disease. Based on observations that individuals with Gilbert?s syndrome (GS; UGT1A1 *28 promoter mutation) are generally lighter, leaner and healthier than controls, specific inter-group differences in the AMPK pathway regulation were explored. Therefore, a case-control study involving 120 fasted, healthy, age- and gender matched s...

Characterizing metabolic pathway diversification in the context of perturbation size.

Science.gov (United States)

Yang, Laurence; Srinivasan, Shyamsundhar; Mahadevan, Radhakrishnan; Cluett, William R

2015-03-01

Cell metabolism is an important platform for sustainable biofuel, chemical and pharmaceutical production but its complexity presents a major challenge for scientists and engineers. Although in silico strains have been designed in the past with predicted performances near the theoretical maximum, real-world performance is often sub-optimal. Here, we simulate how strain performance is impacted when subjected to many randomly varying perturbations, including discrepancies between gene expression and in vivo flux, osmotic stress, and substrate uptake perturbations due to concentration gradients in bioreactors. This computational study asks whether robust performance can be achieved by adopting robustness-enhancing mechanisms from naturally evolved organisms-in particular, redundancy. Our study shows that redundancy, typically perceived as a ubiquitous robustness-enhancing strategy in nature, can either improve or undermine robustness depending on the magnitude of the perturbations. We also show that the optimal number of redundant pathways used can be predicted for a given perturbation size. Copyright © 2015. Published by Elsevier Inc.

Regulation of dual glycolytic pathways for fructose metabolism in heterofermentative Lactobacillus panis PM1.

Science.gov (United States)

Kang, Tae Sun; Korber, Darren R; Tanaka, Takuji

2013-12-01

Lactobacillus panis PM1 belongs to the group III heterofermentative lactobacilli that use the 6-phosphogluconate/phosphoketolase (6-PG/PK) pathway as their central metabolic pathway and are reportedly unable to grow on fructose as a sole carbon source. We isolated a variant PM1 strain capable of sporadic growth on fructose medium and observed its distinctive characteristics of fructose metabolism. The end product pattern was different from what is expected in typical group III lactobacilli using the 6-PG/PK pathway (i.e., more lactate, less acetate, and no mannitol). In addition, in silico analysis revealed the presence of genes encoding most of critical enzymes in the Embden-Meyerhof (EM) pathway. These observations indicated that fructose was metabolized via two pathways. Fructose metabolism in the PM1 strain was influenced by the activities of two enzymes, triosephosphate isomerase (TPI) and glucose 6-phosphate isomerase (PGI). A lack of TPI resulted in the intracellular accumulation of dihydroxyacetone phosphate (DHAP) in PM1, the toxicity of which caused early growth cessation during fructose fermentation. The activity of PGI was enhanced by the presence of glyceraldehyde 3-phosphate (GAP), which allowed additional fructose to enter into the 6-PG/PK pathway to avoid toxicity by DHAP. Exogenous TPI gene expression shifted fructose metabolism from heterolactic to homolactic fermentation, indicating that TPI enabled the PM1 strain to mainly use the EM pathway for fructose fermentation. These findings clearly demonstrate that the balance in the accumulation of GAP and DHAP determines the fate of fructose metabolism and the activity of TPI plays a critical role during fructose fermentation via the EM pathway in L. panis PM1.

A hybrid mathematical modeling approach of the metabolic fate of a fluorescent sphingolipid analogue to predict cancer chemosensitivity.

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Molina-Mora, J A; Kop-Montero, M; Quirós-Fernández, I; Quiros, S; Crespo-Mariño, J L; Mora-Rodríguez, R A

2018-04-13

Sphingolipid (SL) metabolism is a complex biological system that produces and transforms ceramides and other molecules able to modulate other cellular processes, including survival or death pathways key to cell fate decisions. This signaling pathway integrates several types of stress signals, including chemotherapy, into changes in the activity of its metabolic enzymes, altering thereby the cellular composition of bioactive SLs. Therefore, the SL pathway is a promising sensor of chemosensitivity in cancer and a target hub to overcome resistance. However, there is still a gap in our understanding of how chemotherapeutic drugs can disturb the SL pathway in order to control cellular fate. We propose to bridge this gap by a systems biology approach to integrate i) a dynamic model of SL analogue (BODIPY-FL fluorescent-sphingomyelin analogue, SM-BOD) metabolism, ii) a Gaussian mixture model (GMM) of the fluorescence features to identify how the SL pathway senses the effect of chemotherapy and iii) a fuzzy logic model (FLM) to associate SL composition with cell viability by semi-quantitative rules. Altogether, this hybrid model approach was able to predict the cell viability of double experimental perturbations with chemotherapy, indicating that the SL pathway is a promising sensor to design strategies to overcome drug resistance in cancer. Copyright © 2018 Elsevier Ltd. All rights reserved.

Oral cancer cells may rewire alternative metabolic pathways to survive from siRNA silencing of metabolic enzymes

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Zhang, Min; Chai, Yang D; Brumbaugh, Jeffrey; Liu, Xiaojun; Rabii, Ramin; Feng, Sizhe; Misuno, Kaori; Messadi, Diana; Hu, Shen

2014-01-01

Cancer cells may undergo metabolic adaptations that support their growth as well as drug resistance properties. The purpose of this study is to test if oral cancer cells can overcome the metabolic defects introduced by using small interfering RNA (siRNA) to knock down their expression of important metabolic enzymes. UM1 and UM2 oral cancer cells were transfected with siRNA to transketolase (TKT) or siRNA to adenylate kinase (AK2), and Western blotting was used to confirm the knockdown. Cellular uptake of glucose and glutamine and production of lactate were compared between the cancer cells with either TKT or AK2 knockdown and those transfected with control siRNA. Statistical analysis was performed with student T-test. Despite the defect in the pentose phosphate pathway caused by siRNA knockdown of TKT, the survived UM1 or UM2 cells utilized more glucose and glutamine and secreted a significantly higher amount of lactate than the cells transferred with control siRNA. We also demonstrated that siRNA knockdown of AK2 constrained the proliferation of UM1 and UM2 cells but similarly led to an increased uptake of glucose/glutamine and production of lactate by the UM1 or UM2 cells survived from siRNA silencing of AK2. Our results indicate that the metabolic defects introduced by siRNA silencing of metabolic enzymes TKT or AK2 may be compensated by alternative feedback metabolic mechanisms, suggesting that cancer cells may overcome single defective pathways through secondary metabolic network adaptations. The highly robust nature of oral cancer cell metabolism implies that a systematic medical approach targeting multiple metabolic pathways may be needed to accomplish the continued improvement of cancer treatment

CAMPways: constrained alignment framework for the comparative analysis of a pair of metabolic pathways.

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Abaka, Gamze; Bıyıkoğlu, Türker; Erten, Cesim

2013-07-01

Given a pair of metabolic pathways, an alignment of the pathways corresponds to a mapping between similar substructures of the pair. Successful alignments may provide useful applications in phylogenetic tree reconstruction, drug design and overall may enhance our understanding of cellular metabolism. We consider the problem of providing one-to-many alignments of reactions in a pair of metabolic pathways. We first provide a constrained alignment framework applicable to the problem. We show that the constrained alignment problem even in a primitive setting is computationally intractable, which justifies efforts for designing efficient heuristics. We present our Constrained Alignment of Metabolic Pathways (CAMPways) algorithm designed for this purpose. Through extensive experiments involving a large pathway database, we demonstrate that when compared with a state-of-the-art alternative, the CAMPways algorithm provides better alignment results on metabolic networks as far as measures based on same-pathway inclusion and biochemical significance are concerned. The execution speed of our algorithm constitutes yet another important improvement over alternative algorithms. Open source codes, executable binary, useful scripts, all the experimental data and the results are freely available as part of the Supplementary Material at http://code.google.com/p/campways/. Supplementary data are available at Bioinformatics online.

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

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

2013-12-01

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

The Application of the Weighted k-Partite Graph Problem to the Multiple Alignment for Metabolic Pathways.

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Chen, Wenbin; Hendrix, William; Samatova, Nagiza F

2017-12-01

The problem of aligning multiple metabolic pathways is one of very challenging problems in computational biology. A metabolic pathway consists of three types of entities: reactions, compounds, and enzymes. Based on similarities between enzymes, Tohsato et al. gave an algorithm for aligning multiple metabolic pathways. However, the algorithm given by Tohsato et al. neglects the similarities among reactions, compounds, enzymes, and pathway topology. How to design algorithms for the alignment problem of multiple metabolic pathways based on the similarity of reactions, compounds, and enzymes? It is a difficult computational problem. In this article, we propose an algorithm for the problem of aligning multiple metabolic pathways based on the similarities among reactions, compounds, enzymes, and pathway topology. First, we compute a weight between each pair of like entities in different input pathways based on the entities' similarity score and topological structure using Ay et al.'s methods. We then construct a weighted k-partite graph for the reactions, compounds, and enzymes. We extract a mapping between these entities by solving the maximum-weighted k-partite matching problem by applying a novel heuristic algorithm. By analyzing the alignment results of multiple pathways in different organisms, we show that the alignments found by our algorithm correctly identify common subnetworks among multiple pathways.

Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle.

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Hyun-Seob Song

Full Text Available Prediction of possible flux distributions in a metabolic network provides detailed phenotypic information that links metabolism to cellular physiology. To estimate metabolic steady-state fluxes, the most common approach is to solve a set of macroscopic mass balance equations subjected to stoichiometric constraints while attempting to optimize an assumed optimal objective function. This assumption is justifiable in specific cases but may be invalid when tested across different conditions, cell populations, or other organisms. With an aim to providing a more consistent and reliable prediction of flux distributions over a wide range of conditions, in this article we propose a framework that uses the flux minimization principle to predict active metabolic pathways from mRNA expression data. The proposed algorithm minimizes a weighted sum of flux magnitudes, while biomass production can be bounded to fit an ample range from very low to very high values according to the analyzed context. We have formulated the flux weights as a function of the corresponding enzyme reaction's gene expression value, enabling the creation of context-specific fluxes based on a generic metabolic network. In case studies of wild-type Saccharomyces cerevisiae, and wild-type and mutant Escherichia coli strains, our method achieved high prediction accuracy, as gauged by correlation coefficients and sums of squared error, with respect to the experimentally measured values. In contrast to other approaches, our method was able to provide quantitative predictions for both model organisms under a variety of conditions. Our approach requires no prior knowledge or assumption of a context-specific metabolic functionality and does not require trial-and-error parameter adjustments. Thus, our framework is of general applicability for modeling the transcription-dependent metabolism of bacteria and yeasts.

Carbohydrate Metabolism in Archaea: Current Insights into Unusual Enzymes and Pathways and Their Regulation

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Esser, Dominik; Rauch, Bernadette

2014-01-01

SUMMARY The metabolism of Archaea, the third domain of life, resembles in its complexity those of Bacteria and lower Eukarya. However, this metabolic complexity in Archaea is accompanied by the absence of many “classical” pathways, particularly in central carbohydrate metabolism. Instead, Archaea are characterized by the presence of unique, modified variants of classical pathways such as the Embden-Meyerhof-Parnas (EMP) pathway and the Entner-Doudoroff (ED) pathway. The pentose phosphate pathway is only partly present (if at all), and pentose degradation also significantly differs from that known for bacterial model organisms. These modifications are accompanied by the invention of “new,” unusual enzymes which cause fundamental consequences for the underlying regulatory principles, and classical allosteric regulation sites well established in Bacteria and Eukarya are lost. The aim of this review is to present the current understanding of central carbohydrate metabolic pathways and their regulation in Archaea. In order to give an overview of their complexity, pathway modifications are discussed with respect to unusual archaeal biocatalysts, their structural and mechanistic characteristics, and their regulatory properties in comparison to their classic counterparts from Bacteria and Eukarya. Furthermore, an overview focusing on hexose metabolic, i.e., glycolytic as well as gluconeogenic, pathways identified in archaeal model organisms is given. Their energy gain is discussed, and new insights into different levels of regulation that have been observed so far, including the transcript and protein levels (e.g., gene regulation, known transcription regulators, and posttranslational modification via reversible protein phosphorylation), are presented. PMID:24600042

In silico analysis of phytohormone metabolism and communication pathways in citrus transcriptome

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Vera Quecini

2007-01-01

Full Text Available Plant hormones play a crucial role in integrating endogenous and exogenous signals and in determining developmental responses to form the plant body throughout its life cycle. In citrus species, several economically important processes are controlled by phytohormones, including seed germination, secondary growth, fruit abscission and ripening. Integrative genomics is a powerful tool for linking newly researched organisms, such as tropical woody species, to functional studies already carried out on established model organisms. Based on gene orthology analyses and expression patterns, we searched the Citrus Genome Sequencing Consortium (CitEST database for Expressed Sequence Tags (EST consensus sequences sharing similarity to known components of hormone metabolism and signaling pathways in model species. More than 600 homologs of functionally characterized hormone metabolism and signal transduction members from model species were identified in citrus, allowing us to propose a framework for phytohormone signaling mechanisms in citrus. A number of components from hormone-related metabolic pathways were absent in citrus, suggesting the presence of distinct metabolic pathways. Our results demonstrated the power of comparative genomics between model systems and economically important crop species to elucidate several aspects of plant physiology and metabolism.

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

KAUST Repository

Hahn, Aria S.; Altman, Tomer; Konwar, Kishori M.; Hanson, Niels W.; Kim, Dongjae; Relman, David A.; Dill, David L.; Hallam, Steven J.

2017-01-01

the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions

Plasma metabolomics reveal the correlation of metabolic pathways and Prakritis of humans

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Amey Shirolkar

2018-04-01

Full Text Available Background: Ayurveda, an ancient Indian medicinal system, has categorized human body constitutions in three broad constitutional types (prakritis i.e. Vata, Pitta and Kapha. Objectives: Analysis of plasma metabolites and related pathways to classify Prakriti specific dominant marker metabolites and metabolic pathways. Materials and methods: 38 healthy male individuals were assessed for dominant Prakritis and their fasting blood samples were collected. The processed plasma samples were subjected to rapid resolution liquid chromatography–electrospray ionization–quadrupole time of flight mass spectrometry (RRLC–ESI–QTOFMS. Mass profiles were aligned and subjected to multivariate analysis. Results: Partial least square discriminant analysis (PLS-DA model showed 97.87% recognition capability. List of PLS-DA metabolites was subjected to permutative Benjamini–Hochberg false discovery rate (FDR correction and final list of 76 metabolites with p  2.0 was identified. Pathway analysis using metascape and JEPETTO plugins in Cytoscape revealed that steroidal hormone biosynthesis, amino acid, and arachidonic acid metabolism are major pathways varying with different constitution. Biological Go processes analysis showed that aromatic amino acids, sphingolipids, and pyrimidine nucleotides metabolic processes were dominant in kapha type of body constitution. Fat soluble vitamins, cellular amino acid, and androgen biosynthesis process along with branched chain amino acid and glycerolipid catabolic processes were dominant in pitta type individuals. Vata Prakriti was found to have dominant catecholamine, arachidonic acid and hydrogen peroxide metabolomics processes. Conclusion: The neurotransmission and oxidative stress in vata, BCAA catabolic, androgen, xenobiotics metabolic processes in pitta, and aromatic amino acids, sphingolipid, and pyrimidine metabolic process in kapha Prakriti were the dominant marker pathways. Keywords: Ayurveda, Prakriti, Human

The CD36-PPARγ Pathway in Metabolic Disorders

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Loïze Maréchal

2018-05-01

Full Text Available Uncovering the biological role of nuclear receptor peroxisome proliferator-activated receptors (PPARs has greatly advanced our knowledge of the transcriptional control of glucose and energy metabolism. As such, pharmacological activation of PPARγ has emerged as an efficient approach for treating metabolic disorders with the current use of thiazolidinediones to improve insulin resistance in diabetic patients. The recent identification of growth hormone releasing peptides (GHRP as potent inducers of PPARγ through activation of the scavenger receptor CD36 has defined a novel alternative to regulate essential aspects of lipid and energy metabolism. Recent advances on the emerging role of CD36 and GHRP hexarelin in regulating PPARγ downstream actions with benefits on atherosclerosis, hepatic cholesterol biosynthesis and fat mitochondrial biogenesis are summarized here. The response of PPARγ coactivator PGC-1 is also discussed in these effects. The identification of the GHRP-CD36-PPARγ pathway in controlling various tissue metabolic functions provides an interesting option for metabolic disorders.

Computational Modeling of Fluctuations in Energy and Metabolic Pathways of Methanogenic Archaea

Energy Technology Data Exchange (ETDEWEB)

Luthey-Schulten, Zaida [Univ. of Illinois, Urbana-Champaign, IL (United States). Dept. of Chemistry; Carl R. Woese Inst. for Genomic Biology

2017-01-04

The methanogenic archaea, anaerobic microbes that convert CO2 and H2 and/or other small organic fermentation products into methane, play an unusually large role in the global carbon cycle. As they perform the final step in the anaerobic breakdown of biomass, methanogens are a biogenic source of an estimated one billion tons methane each year. Depending on the location, produced methane can be considered as either a greenhouse gas (agricultural byproduct), sequestered carbon storage (methane hydrate deposits), or a potential energy source (organic wastewater treatment). These microbes therefore represent an important target for biotechnology applications. Computational models of methanogens with predictive power are useful aids in the adaptation of methanogenic systems, but need to connect processes of wide-ranging time and length scales. In this project, we developed several computational methodologies for modeling the dynamic behavior of entire cells that connects stochastic reaction-diffusion dynamics of individual biochemical pathways with genome-scale modeling of metabolic networks. While each of these techniques were in the realm of well-defined computational methods, here we integrated them to develop several entirely new approaches to systems biology. The first scientific aim of the project was to model how noise in a biochemical pathway propagates into cellular phenotypes. Genetic circuits have been optimized by evolution to regulate molecular processes despite stochastic noise, but the effect of such noise on a cellular biochemical networks is currently unknown. An integrated stochastic/systems model of Escherichia coli species was created to analyze how noise in protein expression gives—and therefore noise in metabolic fluxes—gives rise to multiple cellular phenotype in isogenic population. After the initial work developing and validating methods that allow characterization of the heterogeneity in the model organism E. coli, the project shifted toward

Metabolic profiling reveals reprogramming of lipid metabolic pathways in treatment of polycystic ovary syndrome with 3-iodothyronamine.

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Selen Alpergin, Ebru S; Bolandnazar, Zeinab; Sabatini, Martina; Rogowski, Michael; Chiellini, Grazia; Zucchi, Riccardo; Assadi-Porter, Fariba M

2017-01-01

Complex diseases such as polycystic ovary syndrome (PCOS) are associated with intricate pathophysiological, hormonal, and metabolic feedbacks that make their early diagnosis challenging, thus increasing the prevalence risks for obesity, cardiovascular, and fatty liver diseases. To explore the crosstalk between endocrine and lipid metabolic pathways, we administered 3-iodothyronamine (T1AM), a natural analog of thyroid hormone, in a mouse model of PCOS and analyzed plasma and tissue extracts using multidisciplinary omics and biochemical approaches. T1AM administration induces a profound tissue-specific antilipogenic effect in liver and muscle by lowering gene expression of key regulators of lipid metabolism, PTP1B and PLIN2, significantly increasing metabolites (glucogenic, amino acids, carnitine, and citrate) levels, while enhancing protection against oxidative stress. In contrast, T1AM has an opposing effect on the regulation of estrogenic pathways in the ovary by upregulating STAR, CYP11A1, and CYP17A1. Biochemical measurements provide further evidence of significant reduction in liver cholesterol and triglycerides in post-T1AM treatment. Our results shed light onto tissue-specific metabolic vs. hormonal pathway interactions, thus illuminating the intricacies within the pathophysiology of PCOS This study opens up new avenues to design drugs for targeted therapeutics to improve quality of life in complex metabolic diseases. © 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.

Metabolism of chlorofluorocarbons and polybrominated compounds by Pseudomonas putida G786(pHG-2) via an engineered metabolic pathway.

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Hur, H G; Sadowsky, M J; Wackett, L P

1994-11-01

The recombinant bacterium Pseudomonas putida G786(pHG-2) metabolizes pentachloroethane to glyoxylate and carbon dioxide, using cytochrome P-450CAM and toluene dioxygenase to catalyze consecutive reductive and oxidative dehalogenation reactions (L.P. Wackett, M.J. Sadowsky, L.N. Newman, H.-G. Hur, and S. Li, Nature [London] 368:627-629, 1994). The present study investigated metabolism of brominated and chlorofluorocarbon compounds by the recombinant strain. Under anaerobic conditions, P. putida G786(pHG-2) reduced 1,1,2,2-tetrabromoethane, 1,2-dibromo-1,2-dichloroethane, and 1,1,1,2-tetrachloro-2,2-difluoroethane to products bearing fewer halogen substituents. Under aerobic conditions, P. putida G786(pHG-2) oxidized cis- and trans-1,2-dibromoethenes, 1,1-dichloro-2,2-difluoroethene, and 1,2-dichloro-1-fluoroethene. Several compounds were metabolized by sequential reductive and oxidative reactions via the constructed metabolic pathway. For example, 1,1,2,2-tetrabromoethane was reduced by cytochrome P-450CAM to 1,2-dibromoethenes, which were subsequently oxidized by toluene dioxygenase. The same pathway metabolized 1,1,1,2-tetrachloro-2,2-difluoroethane to oxalic acid as one of the final products. The results obtained in this study indicate that P. putida G786(pHG-2) metabolizes polyfluorinated, chlorinated, and brominated compounds and further demonstrates the value of using a knowledge of catabolic enzymes and recombinant DNA technology to construct useful metabolic pathways.

Biosynthetic Pathway and Metabolic Engineering of Plant Dihydrochalcones.

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Ibdah, Mwafaq; Martens, Stefan; Gang, David R

2018-03-14

Dihydrochalcones are plant natural products containing the phenylpropanoid backbone and derived from the plant-specific phenylpropanoid pathway. Dihydrochalcone compounds are important in plant growth and response to stresses and, thus, can have large impacts on agricultural activity. In recent years, these compounds have also received increased attention from the biomedical community for their potential as anticancer treatments and other benefits for human health. However, they are typically produced at relatively low levels in plants. Therefore, an attractive alternative is to express the plant biosynthetic pathway genes in microbial hosts and to engineer the metabolic pathway/host to improve the production of these metabolites. In the present review, we discuss in detail the functions of genes and enzymes involved in the biosynthetic pathway of the dihydrochalcones and the recent strategies and achievements used in the reconstruction of multi-enzyme pathways in microorganisms in efforts to be able to attain higher amounts of desired dihydrochalcones.

Method for determining heterologous biosynthesis pathways

KAUST Repository

Gao, Xin

2017-08-10

The present invention relates to a method and system for dynamically analyzing, determining, predicting and displaying ranked suitable heterologous biosynthesis pathways for a specified host. The present invention addresses the problem of finding suitable pathways for the endogenous metabolism of a host organism because the efficacy of heterologous biosynthesis is affected by competing endogenous pathways. The present invention is called MRE (Metabolic Route Explorer), and it was conceived and developed to systematically and dynamically search for, determine, analyze, and display promising heterologous pathways while considering competing endogenous reactions in a given host organism.

3-Bromopyruvate treatment induces alterations of metabolic and stress-related pathways in glioblastoma cells.

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Chiasserini, Davide; Davidescu, Magdalena; Orvietani, Pier Luigi; Susta, Federica; Macchioni, Lara; Petricciuolo, Maya; Castigli, Emilia; Roberti, Rita; Binaglia, Luciano; Corazzi, Lanfranco

2017-01-30

Glioblastoma (GBM) is the most common and aggressive brain tumour of adults. The metabolic phenotype of GBM cells is highly dependent on glycolysis; therefore, therapeutic strategies aimed at interfering with glycolytic pathways are under consideration. 3-Bromopyruvate (3BP) is a potent antiglycolytic agent, with a variety of targets and possible effects on global cell metabolism. Here we analyzed the changes in protein expression on a GBM cell line (GL15 cells) caused by 3BP treatment using a global proteomic approach. Validation of differential protein expression was performed with immunoblotting and enzyme activity assays in GL15 and U251 cell lines. The results show that treatment of GL15 cells with 3BP leads to extensive changes in the expression of glycolytic enzymes and stress related proteins. Importantly, other metabolisms were also affected, including pentose phosphate pathway, aminoacid synthesis, and glucose derivatives production. 3BP elicited the activation of stress response proteins, as shown by the phosphorylation of HSPB1 at serine 82, caused by the concomitant activation of the p38 pathway. Our results show that inhibition of glycolysis in GL15 cells by 3BP influences different but interconnected pathways. Proteome analysis may help in the molecular characterization of the glioblastoma response induced by pharmacological treatment with antiglycolytic agents. Alteration of the glycolytic pathway characterizes glioblastoma (GBM), one of the most common brain tumours. Metabolic reprogramming with agents able to inhibit carbohydrate metabolism might be a viable strategy to complement the treatment of these tumours. The antiglycolytic agent 3-bromopyruvate (3BP) is able to strongly inhibit glycolysis but it may affect also other cellular pathways and its precise cellular targets are currently unknown. To understand the protein expression changes induced by 3BP, we performed a global proteomic analysis of a GBM cell line (GL15) treated with 3BP. We

Responsive eLearning exercises to enhance student interaction with metabolic pathways.

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Roesler, William J; Dreaver-Charles, Kristine

2018-05-01

Successful learning of biochemistry requires students to engage with the material. In the past this often involved students writing out pathways by hand, and more recently directing students to online resources such as videos, songs, and animated slide presentations. However, even these latter resources do not really provide students an opportunity to engage with the material in an active fashion. As part of an online introductory metabolism course that was developed at our university, we created a series of twelve online interactive activities using Adobe Captivate 9. These activities targeted glycolysis, gluconeogenesis, the pentose phosphate pathway, glycogen metabolism, the citric acid cycle, and fatty acid oxidation. The interactive exercises consisted of two types. One involved dragging objects such as names of enzymes or allosteric modifiers to their correct drop locations such as a particular point in a metabolic pathway, a specific enzyme, and so forth. A second type involved clicking on objects, locations within a pathway, and so forth, in response to a particular question. In both types of exercises, students received feedback on their decisions in order to enhance learning. The student feedback received on these activities was very positive, and indicated that they found them to increase their confidence in the material and that they had learned the key principles of each pathway. © 2018 by The International Union of Biochemistry and Molecular Biology, 46(3):223-229, 2018. © 2018 The International Union of Biochemistry and Molecular Biology.

Human Cytomegalovirus: Coordinating Cellular Stress, Signaling, and Metabolic Pathways.

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Shenk, Thomas; Alwine, James C

2014-11-01

Viruses face a multitude of challenges when they infect a host cell. Cells have evolved innate defenses to protect against pathogens, and an infecting virus may induce a stress response that antagonizes viral replication. Further, the metabolic, oxidative, and cell cycle state may not be conducive to the viral infection. But viruses are fabulous manipulators, inducing host cells to use their own characteristic mechanisms and pathways to provide what the virus needs. This article centers on the manipulation of host cell metabolism by human cytomegalovirus (HCMV). We review the features of the metabolic program instituted by the virus, discuss the mechanisms underlying these dramatic metabolic changes, and consider how the altered program creates a synthetic milieu that favors efficient HCMV replication and spread.

Mitochondrial quality control pathways as determinants of metabolic health

NARCIS (Netherlands)

Held, Ntsiki M.; Houtkooper, Riekelt H.

2015-01-01

Mitochondrial function is key for maintaining cellular health, while mitochondrial failure is associated with various pathologies, including inherited metabolic disorders and age-related diseases. In order to maintain mitochondrial quality, several pathways of mitochondrial quality control have

DESHARKY: automatic design of metabolic pathways for optimal cell growth.

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Rodrigo, Guillermo; Carrera, Javier; Prather, Kristala Jones; Jaramillo, Alfonso

2008-11-01

The biological solution for synthesis or remediation of organic compounds using living organisms, particularly bacteria and yeast, has been promoted because of the cost reduction with respect to the non-living chemical approach. In that way, computational frameworks can profit from the previous knowledge stored in large databases of compounds, enzymes and reactions. In addition, the cell behavior can be studied by modeling the cellular context. We have implemented a Monte Carlo algorithm (DESHARKY) that finds a metabolic pathway from a target compound by exploring a database of enzymatic reactions. DESHARKY outputs a biochemical route to the host metabolism together with its impact in the cellular context by using mathematical models of the cell resources and metabolism. Furthermore, we provide the sequence of amino acids for the enzymes involved in the route closest phylogenetically to the considered organism. We provide examples of designed metabolic pathways with their genetic load characterizations. Here, we have used Escherichia coli as host organism. In addition, our bioinformatic tool can be applied for biodegradation or biosynthesis and its performance scales with the database size. Software, a tutorial and examples are freely available and open source at http://soft.synth-bio.org/desharky.html

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

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Xu, Zixiang; Sun, Jibin; Wu, Qiaqing; Zhu, Dunming

2017-12-11

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry. In addition, the shortest pathways may not be the pathways with high yield. At the same time, a pathway, which exists in stoichiometry, may not be feasible in thermodynamics. By using mixed integer programming strategy, we put forward an algorithm to identify all the smallest balanced pathways which convert the source compound to the target compound in large-scale metabolic networks. The resulting pathways by our method can finely satisfy the stoichiometric constraints and non-decomposability condition. Especially, the functions of high yield and thermodynamics feasibility have been considered in our approach. This tool is tailored to direct the metabolic engineering practice to enlarge the metabolic potentials of industrial strains by integrating the extensive metabolic network information built from systems biology dataset.

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.

Unbiased plasma metabolomics reveal the correlation of metabolic pathways and Prakritis of humans.

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Shirolkar, Amey; Chakraborty, Sutapa; Mandal, Tusharkanti; Dabur, Rajesh

2017-11-25

Ayurveda, an ancient Indian medicinal system, has categorized human body constitutions in three broad constitutional types (prakritis) i.e. Vata, Pitta and Kapha. Analysis of plasma metabolites and related pathways to classify Prakriti specific dominant marker metabolites and metabolic pathways. 38 healthy male individuals were assessed for dominant Prakritis and their fasting blood samples were collected. The processed plasma samples were subjected to rapid resolution liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (RRLC-ESI-QTOFMS). Mass profiles were aligned and subjected to multivariate analysis. Partial least square discriminant analysis (PLS-DA) model showed 97.87% recognition capability. List of PLS-DA metabolites was subjected to permutative Benjamini-Hochberg false discovery rate (FDR) correction and final list of 76 metabolites with p  2.0 was identified. Pathway analysis using metascape and JEPETTO plugins in Cytoscape revealed that steroidal hormone biosynthesis, amino acid, and arachidonic acid metabolism are major pathways varying with different constitution. Biological Go processes analysis showed that aromatic amino acids, sphingolipids, and pyrimidine nucleotides metabolic processes were dominant in kapha type of body constitution. Fat soluble vitamins, cellular amino acid, and androgen biosynthesis process along with branched chain amino acid and glycerolipid catabolic processes were dominant in pitta type individuals. Vata Prakriti was found to have dominant catecholamine, arachidonic acid and hydrogen peroxide metabolomics processes. The neurotransmission and oxidative stress in vata, BCAA catabolic, androgen, xenobiotics metabolic processes in pitta, and aromatic amino acids, sphingolipid, and pyrimidine metabolic process in kaphaPrakriti were the dominant marker pathways. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights

Identification of Discriminating Metabolic Pathways and Metabolites in Human PBMCs Stimulated by Various Pathogenic Agents

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Xiang Zhang

2018-02-01

Full Text Available Immunity and cellular metabolism are tightly interconnected but it is not clear whether different pathogens elicit specific metabolic responses. To address this issue, we studied differential metabolic regulation in peripheral blood mononuclear cells (PBMCs of healthy volunteers challenged by Candida albicans, Borrelia burgdorferi, lipopolysaccharide, and Mycobacterium tuberculosis in vitro. By integrating gene expression data of stimulated PBMCs of healthy individuals with the KEGG pathways, we identified both common and pathogen-specific regulated pathways depending on the time of incubation. At 4 h of incubation, pathogenic agents inhibited expression of genes involved in both the glycolysis and oxidative phosphorylation pathways. In contrast, at 24 h of incubation, particularly glycolysis was enhanced while genes involved in oxidative phosphorylation remained unaltered in the PBMCs. In general, differential gene expression was less pronounced at 4 h compared to 24 h of incubation. KEGG pathway analysis allowed differentiation between effects induced by Candida and bacterial stimuli. Application of genome-scale metabolic model further generated a Candida-specific set of 103 reporter metabolites (e.g., desmosterol that might serve as biomarkers discriminating Candida-stimulated PBMCs from bacteria-stimuated PBMCs. Our analysis also identified a set of 49 metabolites that allowed discrimination between the effects of Borrelia burgdorferi, lipopolysaccharide and Mycobacterium tuberculosis. We conclude that analysis of pathogen-induced effects on PBMCs by a combination of KEGG pathways and genome-scale metabolic model provides deep insight in the metabolic changes coupled to host defense.

Engineering the fatty acid metabolic pathway in Saccharomyces cerevisiae for advanced biofuel production

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Xiaoling Tang

2015-12-01

Full Text Available Fatty acid-derived fuels and chemicals have attracted a great deal of attention in recent decades, due to their following properties of high compatibility to gasoline-based fuels and existing infrastructure for their direct utilization, storage and distribution. The yeast Saccharomyces cerevisiae is the ideal biofuel producing candidate, based on the wealth of available genetic information and versatile tools designed to manipulate its metabolic pathways. Engineering the fatty acid metabolic pathways in S. cerevisiae is an effective strategy to increase its fatty acid biosynthesis and provide more pathway precursors for production of targeted products. This review summarizes the recent progress in metabolic engineering of yeast cells for fatty acids and fatty acid derivatives production, including the regulation of acetyl-CoA biosynthesis, NADPH production, fatty acid elongation, and the accumulation of activated precursors of fatty acids for converting enzymes. By introducing specific enzymes in the engineered strains, a powerful platform with a scalable, controllable and economic route for advanced biofuel production has been established. Keywords: Metabolic engineering, Fatty acid biosynthesis, Fatty acid derivatives, Saccharomyces cerevisiae

Drug metabolism by cytochrome p450 enzymes: what distinguishes the pathways leading to substrate hydroxylation over desaturation?

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Ji, Li; Faponle, Abayomi S; Quesne, Matthew G; Sainna, Mala A; Zhang, Jing; Franke, Alicja; Kumar, Devesh; van Eldik, Rudi; Liu, Weiping; de Visser, Sam P

2015-06-15

Cytochrome P450 enzymes are highly versatile biological catalysts in our body that react with a broad range of substrates. Key functions in the liver include the metabolism of drugs and xenobiotics. One particular metabolic pathway that is poorly understood relates to the P450 activation of aliphatic groups leading to either hydroxylation or desaturation pathways. A DFT and QM/MM study has been carried out on the factors that determine the regioselectivity of aliphatic hydroxylation over desaturation of compounds by P450 isozymes. The calculations establish multistate reactivity patterns, whereby the product distributions differ on each of the spin-state surfaces; hence spin-selective product formation was found. The electronic and thermochemical factors that determine the bifurcation pathways were analysed and a model that predicts the regioselectivity of aliphatic hydroxylation over desaturation pathways was established from valence bond and molecular orbital theories. Thus, the difference in energy of the OH versus the OC bond formed and the π-conjugation energy determines the degree of desaturation products. In addition, environmental effects of the substrate binding pocket that affect the regioselectivities were identified. These studies imply that bioengineering P450 isozymes for desaturation reactions will have to include modifications in the substrate binding pocket to restrict the hydroxylation rebound reaction. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

MiYA, an efficient machine-learning workflow in conjunction with the YeastFab assembly strategy for combinatorial optimization of heterologous metabolic pathways in Saccharomyces cerevisiae.

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Zhou, Yikang; Li, Gang; Dong, Junkai; Xing, Xin-Hui; Dai, Junbiao; Zhang, Chong

2018-05-01

Facing boosting ability to construct combinatorial metabolic pathways, how to search the metabolic sweet spot has become the rate-limiting step. We here reported an efficient Machine-learning workflow in conjunction with YeastFab Assembly strategy (MiYA) for combinatorial optimizing the large biosynthetic genotypic space of heterologous metabolic pathways in Saccharomyces cerevisiae. Using β-carotene biosynthetic pathway as example, we first demonstrated that MiYA has the power to search only a small fraction (2-5%) of combinatorial space to precisely tune the expression level of each gene with a machine-learning algorithm of an artificial neural network (ANN) ensemble to avoid over-fitting problem when dealing with a small number of training samples. We then applied MiYA to improve the biosynthesis of violacein. Feed with initial data from a colorimetric plate-based, pre-screened pool of 24 strains producing violacein, MiYA successfully predicted, and verified experimentally, the existence of a strain that showed a 2.42-fold titer improvement in violacein production among 3125 possible designs. Furthermore, MiYA was able to largely avoid the branch pathway of violacein biosynthesis that makes deoxyviolacein, and produces very pure violacein. Together, MiYA combines the advantages of standardized building blocks and machine learning to accelerate the Design-Build-Test-Learn (DBTL) cycle for combinatorial optimization of metabolic pathways, which could significantly accelerate the development of microbial cell factories. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

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

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

2016-01-01

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

Obesity-driven gut microbiota inflammatory pathways to metabolic syndrome

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Luiz Henrique Agra eCavalcante-Silva

2015-11-01

Full Text Available The intimate interplay between immune system, metabolism and gut microbiota plays an important role in controlling metabolic homeostasis and possible obesity development. Obesity involves impairment of immune response affecting both innate and adaptive immunity. The main factors involved in the relationship of obesity with inflammation have not been completely elucidated. On the other hand, gut microbiota, via innate immune receptors, has emerged as one of the key factors regulating events triggering acute inflammation associated with obesity and metabolic syndrome. Inflammatory disorders lead to several signalling transduction pathways activation, inflammatory cytokine, chemokine production and cell migration, which in turn cause metabolic dysfunction. Inflamed adipose tissue, with increased macrophages infiltration, is associated with impaired preadipocyte development and differentiation to mature adipose cells, leading to ectopic lipid accumulation and insulin resistance. This review focuses on the relationship between obesity and inflammation, which is essential to understand the pathological mechanisms governing metabolic syndrome.

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

Science.gov (United States)

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

2016-09-01

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

Engineering the spatial organization of metabolic pathways

DEFF Research Database (Denmark)

Albertsen, Line; Maury, Jerome; Bach, Lars Stougaard

One of the goals of metabolic engineering is to optimize the production of valuable metabolites in cell factories. In this context, modulating the gene expression and activity of enzymes are tools that have been extensively used. Another approach that is gaining interest is the engineering...... of the spatial organization of biosynthetic pathways. Several natural systems for ensuring optimal spatial arrangement of biosynthetic enzymes exist. Sequentially acting enzymes can for example be positioned in close proximity by attachment to cellular structures, up-concentration in membrane enclosed organelles...... or assembly into large complexes. The vision is that by positioning sequentially acting enzymes in close proximity, the cell can accelerate reaction rates and thereby prevent loss of intermediates through diffusion, degradation or competing pathways. The production of valuable metabolites in cell factories...

Role of Heme and Heme-Proteins in Trypanosomatid Essential Metabolic Pathways

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Karina E. J. Tripodi

2011-01-01

Full Text Available Around the world, trypanosomatids are known for being etiological agents of several highly disabling and often fatal diseases like Chagas disease (Trypanosoma cruzi, leishmaniasis (Leishmania spp., and African trypanosomiasis (Trypanosoma brucei. Throughout their life cycle, they must cope with diverse environmental conditions, and the mechanisms involved in these processes are crucial for their survival. In this review, we describe the role of heme in several essential metabolic pathways of these protozoans. Notwithstanding trypanosomatids lack of the complete heme biosynthetic pathway, we focus our discussion in the metabolic role played for important heme-proteins, like cytochromes. Although several genes for different types of cytochromes, involved in mitochondrial respiration, polyunsaturated fatty acid metabolism, and sterol biosynthesis, are annotated at the Tritryp Genome Project, the encoded proteins have not yet been deeply studied. We pointed our attention into relevant aspects of these protein functions that are amenable to be considered for rational design of trypanocidal agents.

Characterizability of metabolic pathway systems from time series data.

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Voit, Eberhard O

2013-12-01

Over the past decade, the biomathematical community has devoted substantial effort to the complicated challenge of estimating parameter values for biological systems models. An even more difficult issue is the characterization of functional forms for the processes that govern these systems. Most parameter estimation approaches tacitly assume that these forms are known or can be assumed with some validity. However, this assumption is not always true. The recently proposed method of Dynamic Flux Estimation (DFE) addresses this problem in a genuinely novel fashion for metabolic pathway systems. Specifically, DFE allows the characterization of fluxes within such systems through an analysis of metabolic time series data. Its main drawback is the fact that DFE can only directly be applied if the pathway system contains as many metabolites as unknown fluxes. This situation is unfortunately rare. To overcome this roadblock, earlier work in this field had proposed strategies for augmenting the set of unknown fluxes with independent kinetic information, which however is not always available. Employing Moore-Penrose pseudo-inverse methods of linear algebra, the present article discusses an approach for characterizing fluxes from metabolic time series data that is applicable even if the pathway system is underdetermined and contains more fluxes than metabolites. Intriguingly, this approach is independent of a specific modeling framework and unaffected by noise in the experimental time series data. The results reveal whether any fluxes may be characterized and, if so, which subset is characterizable. They also help with the identification of fluxes that, if they could be determined independently, would allow the application of DFE. Copyright © 2013 Elsevier Inc. All rights reserved.

Microbial pathways in colonic sulfur metabolism and links with health and disease

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Franck eCarbonero

2012-11-01

Full Text Available Sulfur is both crucial to life and a potential threat to health. While colonic sulfur metabolism mediated by eukaryotic cells is relatively well studied, much less is known about sulfur metabolism within gastrointestinal microbes. Sulfated compounds in the colon are either of inorganic (e.g., sulfates, sulfites or organic (e.g., dietary amino acids and host mucins origin. The most extensively studied of the microbes involved in colonic sulfur metabolism are the sulfate-reducing bacteria, which are common colonic inhabitants. Many other microbial pathways are likely to shape colonic sulfur metabolism as well as the composition and availability of sulfated compounds, and these interactions need to be examined in more detail. Hydrogen sulfide is the sulfur derivative that has attracted the most attention in the context of colonic health, and the extent to which it is detrimental or beneficial remains in debate. Several lines of evidence point to sulfate-reducing bacteria or exogenous hydrogen sulfide as potential players in the etiology of intestinal disorders, inflammatory bowel diseases and colorectal cancer in particular. Generation of hydrogen sulfide via pathways other than dissimilatory sulfate reduction may be as, or more, important than those involving the sulfate-reducing bacteria. We suggest here that a novel axis of research is to assess the effects of hydrogen sulfide in shaping colonic microbiome structure. Clearly, in-depth characterization of the microbial pathways involved in colonic sulfur metabolism is necessary for a better understanding of its contribution to colonic disorders and development of therapeutic strategies.

Genome-Based Construction of the Metabolic Pathways of Orientia tsutsugamushi and Comparative Analysis within the Rickettsiales Order

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Chan-Ki Min

2008-01-01

Full Text Available Orientia tsutsugamushi, the causative agent of scrub typhus, is an obligate intracellular bacterium that belongs to the order of Rickettsiales. Recently, we have reported that O. tsutsugamushi has a unique genomic structure, consisting of highly repetitive sequences, and suggested that it may provide valuable insight into the evolution of intracellular bacteria. Here, we have used genomic information to construct the major metabolic pathways of O. tsutsugamushi and performed a comparative analysis of the metabolic genes and pathways of O. tsutsugamushi with other members of the Rickettsiales order. While O. tsutsugamushi has the largest genome among the members of this order, mainly due to the presence of repeated sequences, its metabolic pathways have been highly streamlined. Overall, the metabolic pathways of O. tsutsugamushi were similar to Rickettsia but there were notable differences in several pathways including carbohydrate metabolism, the TCA cycle, and the synthesis of cell wall components as well as in the transport systems. Our results will provide a useful guide to the postgenomic analysis of O. tsutsugamushi and lead to a better understanding of the virulence and physiology of this intracellular pathogen.

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

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Elad Noor

2016-11-01

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

Cocoa procyanidins modulate transcriptional pathways linked to inflammation and metabolism in human dendritic cells

DEFF Research Database (Denmark)

Midttun, Helene L E; Ramsay, Aina; Mueller-Harvey, Irene

2018-01-01

the mechanistic basis of this inhibition, here we conducted transcriptomic analysis on DCs cultured with either LPS or LPS combined with oligomeric cocoa PC. Procyanidins suppressed a number of genes encoding cytokines and chemokines such as CXCL1, but also genes involved in the cGMP pathway such as GUCY1A3...... (encoding guanylate cyclase soluble subunit alpha-3). Upregulated genes were involved in diverse metabolic pathways, but notably two of the four most upregulated genes (NMB, encoding neuromedin B and ADCY3, encoding adenyl cyclase type 3) were involved in the cAMP signalling pathway. Gene-set enrichment...... analysis demonstrated that upregulated gene pathways were primarily involved in nutrient transport, carbohydrate metabolism and lysosome function, whereas down-regulated gene pathways involved cell cycle, signal transduction and gene transcription, as well as immune function. qPCR analysis verified...

Metabolic engineering of biosynthetic pathway for production of renewable biofuels.

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Singh, Vijai; Mani, Indra; Chaudhary, Dharmendra Kumar; Dhar, Pawan Kumar

2014-02-01

Metabolic engineering is an important area of research that involves editing genetic networks to overproduce a certain substance by the cells. Using a combination of genetic, metabolic, and modeling methods, useful substances have been synthesized in the past at industrial scale and in a cost-effective manner. Currently, metabolic engineering is being used to produce sufficient, economical, and eco-friendly biofuels. In the recent past, a number of efforts have been made towards engineering biosynthetic pathways for large scale and efficient production of biofuels from biomass. Given the adoption of metabolic engineering approaches by the biofuel industry, this paper reviews various approaches towards the production and enhancement of renewable biofuels such as ethanol, butanol, isopropanol, hydrogen, and biodiesel. We have also identified specific areas where more work needs to be done in the future.

NAD+ salvage pathway in cancer metabolism and therapy.

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Kennedy, Barry E; Sharif, Tanveer; Martell, Emma; Dai, Cathleen; Kim, Youra; Lee, Patrick W K; Gujar, Shashi A

2016-12-01

Nicotinamide adenine dinucleotide (NAD + ) is an essential coenzyme for various physiological processes including energy metabolism, DNA repair, cell growth, and cell death. Many of these pathways are typically dysregulated in cancer cells, making NAD + an intriguing target for cancer therapeutics. NAD + is mainly synthesized by the NAD + salvage pathway in cancer cells, and not surprisingly, the pharmacological targeting of the NAD + salvage pathway causes cancer cell cytotoxicity in vitro and in vivo. Several studies have described the precise consequences of NAD + depletion on cancer biology, and have demonstrated that NAD+ depletion results in depletion of energy levels through lowered rates of glycolysis, reduced citric acid cycle activity, and decreased oxidative phosphorylation. Additionally, depletion of NAD + causes sensitization of cancer cells to oxidative damage by disruption of the anti-oxidant defense system, decreased cell proliferation, and initiation of cell death through manipulation of cell signaling pathways (e.g., SIRT1 and p53). Recently, studies have explored the effect of well-known cancer therapeutics in combination with pharmacological depletion of NAD + levels, and found in many cases a synergistic effect on cancer cell cytotoxicity. In this context, we will discuss the effects of NAD + salvage pathway inhibition on cancer cell biology and provide insight on this pathway as a novel anti-cancer therapeutic target. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways.

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Lee, Yun; Lafontaine Rivera, Jimmy G; Liao, James C

2014-09-01

Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Exploring metabolic pathway reconstruction and genome-wide expression profiling in Lactobacillus reuteri to define functional probiotic features.

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Delphine M Saulnier

2011-04-01

Full Text Available The genomes of four Lactobacillus reuteri strains isolated from human breast milk and the gastrointestinal tract have been recently sequenced as part of the Human Microbiome Project. Preliminary genome comparisons suggested that these strains belong to two different clades, previously shown to differ with respect to antimicrobial production, biofilm formation, and immunomodulation. To explain possible mechanisms of survival in the host and probiosis, we completed a detailed genomic comparison of two breast milk-derived isolates representative of each group: an established probiotic strain (L. reuteri ATCC 55730 and a strain with promising probiotic features (L. reuteri ATCC PTA 6475. Transcriptomes of L. reuteri strains in different growth phases were monitored using strain-specific microarrays, and compared using a pan-metabolic model representing all known metabolic reactions present in these strains. Both strains contained candidate genes involved in the survival and persistence in the gut such as mucus-binding proteins and enzymes scavenging reactive oxygen species. A large operon predicted to encode the synthesis of an exopolysaccharide was identified in strain 55730. Both strains were predicted to produce health-promoting factors, including antimicrobial agents and vitamins (folate, vitamin B(12. Additionally, a complete pathway for thiamine biosynthesis was predicted in strain 55730 for the first time in this species. Candidate genes responsible for immunomodulatory properties of each strain were identified by transcriptomic comparisons. The production of bioactive metabolites by human-derived probiotics may be predicted using metabolic modeling and transcriptomics. Such strategies may facilitate selection and optimization of probiotics for health promotion, disease prevention and amelioration.

Exploring metabolic pathway reconstruction and genome-wide expression profiling in Lactobacillus reuteri to define functional probiotic features.

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Saulnier, Delphine M; Santos, Filipe; Roos, Stefan; Mistretta, Toni-Ann; Spinler, Jennifer K; Molenaar, Douwe; Teusink, Bas; Versalovic, James

2011-04-29

The genomes of four Lactobacillus reuteri strains isolated from human breast milk and the gastrointestinal tract have been recently sequenced as part of the Human Microbiome Project. Preliminary genome comparisons suggested that these strains belong to two different clades, previously shown to differ with respect to antimicrobial production, biofilm formation, and immunomodulation. To explain possible mechanisms of survival in the host and probiosis, we completed a detailed genomic comparison of two breast milk-derived isolates representative of each group: an established probiotic strain (L. reuteri ATCC 55730) and a strain with promising probiotic features (L. reuteri ATCC PTA 6475). Transcriptomes of L. reuteri strains in different growth phases were monitored using strain-specific microarrays, and compared using a pan-metabolic model representing all known metabolic reactions present in these strains. Both strains contained candidate genes involved in the survival and persistence in the gut such as mucus-binding proteins and enzymes scavenging reactive oxygen species. A large operon predicted to encode the synthesis of an exopolysaccharide was identified in strain 55730. Both strains were predicted to produce health-promoting factors, including antimicrobial agents and vitamins (folate, vitamin B(12)). Additionally, a complete pathway for thiamine biosynthesis was predicted in strain 55730 for the first time in this species. Candidate genes responsible for immunomodulatory properties of each strain were identified by transcriptomic comparisons. The production of bioactive metabolites by human-derived probiotics may be predicted using metabolic modeling and transcriptomics. Such strategies may facilitate selection and optimization of probiotics for health promotion, disease prevention and amelioration.

Comparison of Metabolic Pathways in Escherichia coli by Using Genetic Algorithms

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Patricia Ortegon

2015-01-01

Full Text Available In order to understand how cellular metabolism has taken its modern form, the conservation and variations between metabolic pathways were evaluated by using a genetic algorithm (GA. The GA approach considered information on the complete metabolism of the bacterium Escherichia coli K-12, as deposited in the KEGG database, and the enzymes belonging to a particular pathway were transformed into enzymatic step sequences by using the breadth-first search algorithm. These sequences represent contiguous enzymes linked to each other, based on their catalytic activities as they are encoded in the Enzyme Commission numbers. In a posterior step, these sequences were compared using a GA in an all-against-all (pairwise comparisons approach. Individual reactions were chosen based on their measure of fitness to act as parents of offspring, which constitute the new generation. The sequences compared were used to construct a similarity matrix (of fitness values that was then considered to be clustered by using a k-medoids algorithm. A total of 34 clusters of conserved reactions were obtained, and their sequences were finally aligned with a multiple-sequence alignment GA optimized to align all the reaction sequences included in each group or cluster. From these comparisons, maps associated with the metabolism of similar compounds also contained similar enzymatic step sequences, reinforcing the Patchwork Model for the evolution of metabolism in E. coli K-12, an observation that can be expanded to other organisms, for which there is metabolism information. Finally, our mapping of these reactions is discussed, with illustrations from a particular case.

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-01-01

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

Metabolic 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.

kpath: integration of metabolic pathway linked data.

Science.gov (United States)

Navas-Delgado, Ismael; García-Godoy, María Jesús; López-Camacho, Esteban; Rybinski, Maciej; Reyes-Palomares, Armando; Medina, Miguel Ángel; Aldana-Montes, José F

2015-01-01

In the last few years, the Life Sciences domain has experienced a rapid growth in the amount of available biological databases. The heterogeneity of these databases makes data integration a challenging issue. Some integration challenges are locating resources, relationships, data formats, synonyms or ambiguity. The Linked Data approach partially solves the heterogeneity problems by introducing a uniform data representation model. Linked Data refers to a set of best practices for publishing and connecting structured data on the Web. This article introduces kpath, a database that integrates information related to metabolic pathways. kpath also provides a navigational interface that enables not only the browsing, but also the deep use of the integrated data to build metabolic networks based on existing disperse knowledge. This user interface has been used to showcase relationships that can be inferred from the information available in several public databases. © The Author(s) 2015. Published by Oxford University Press.

Exploring metabolic pathway disruption in the subchronic phencyclidine model of schizophrenia with the Generalized Singular Value Decomposition

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Morris Brian J

2011-05-01

Full Text Available Abstract Background The quantification of experimentally-induced alterations in biological pathways remains a major challenge in systems biology. One example of this is the quantitative characterization of alterations in defined, established metabolic pathways from complex metabolomic data. At present, the disruption of a given metabolic pathway is inferred from metabolomic data by observing an alteration in the level of one or more individual metabolites present within that pathway. Not only is this approach open to subjectivity, as metabolites participate in multiple pathways, but it also ignores useful information available through the pairwise correlations between metabolites. This extra information may be incorporated using a higher-level approach that looks for alterations between a pair of correlation networks. In this way experimentally-induced alterations in metabolic pathways can be quantitatively defined by characterizing group differences in metabolite clustering. Taking this approach increases the objectivity of interpreting alterations in metabolic pathways from metabolomic data. Results We present and justify a new technique for comparing pairs of networks--in our case these networks are based on the same set of nodes and there are two distinct types of weighted edges. The algorithm is based on the Generalized Singular Value Decomposition (GSVD, which may be regarded as an extension of Principle Components Analysis to the case of two data sets. We show how the GSVD can be interpreted as a technique for reordering the two networks in order to reveal clusters that are exclusive to only one. Here we apply this algorithm to a new set of metabolomic data from the prefrontal cortex (PFC of a translational model relevant to schizophrenia, rats treated subchronically with the N-methyl-D-Aspartic acid (NMDA receptor antagonist phencyclidine (PCP. This provides us with a means to quantify which predefined metabolic pathways (Kyoto

Coregulation of terpenoid pathway genes and prediction of isoprene production in Bacillus subtilis using transcriptomics

Energy Technology Data Exchange (ETDEWEB)

Hess, Becky M.; Xue, Junfeng; Markillie, Lye Meng; Taylor, Ronald C.; Wiley, H. S.; Ahring, Birgitte K.; Linggi, Bryan E.

2013-06-19

The isoprenoid pathway converts pyruvate to isoprene and related isoprenoid compounds in plants and some bacteria. Currently, this pathway is of great interest because of the critical role that isoprenoids play in basic cellular processes as well as the industrial value of metabolites such as isoprene. Although the regulation of several pathway genes has been described, there is a paucity of information regarding the system level regulation and control of the pathway. To address this limitation, we examined Bacillus subtilis grown under multiple conditions and then determined the relationship between altered isoprene production and the pattern of gene expression. We found that terpenoid genes appeared to fall into two distinct subsets with opposing correlations with respect to the amount of isoprene produced. The group whose expression levels positively correlated with isoprene production included dxs, the gene responsible for the commitment step in the pathway, as well as ispD, and two genes that participate in the mevalonate pathway, yhfS and pksG. The subset of terpenoid genes that inversely correlated with isoprene production included ispH, ispF, hepS, uppS, ispE, and dxr. A genome wide partial least squares regression model was created to identify other genes or pathways that contribute to isoprene production. This analysis showed that a subset of 213 regulated genes was sufficient to create a predictive model of isoprene production under different conditions and showed correlations at the transcriptional level. We conclude that gene expression levels alone are sufficiently informative about the metabolic state of a cell that produces increased isoprene and can be used to build a model which accurately predicts production of this secondary metabolite across many simulated environmental conditions.

Metabolic analysis of the soil microbe Dechloromonas aromatica str. RCB: indications of a surprisingly complex life-style and cryptic anaerobic pathways for aromatic degradation

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Salinero, Kennan Kellaris; Keller, Keith; Feil, William S.; Feil, Helene; Trong, Stephan; Di Bartolo, Genevieve; Lapidus, Alla

2008-11-17

Initial interest in Dechloromonas aromatica strain RCB arose from its ability to anaerobically degrade benzene. It is also able to reduce perchlorate and oxidize chlorobenzoate, toluene, and xylene, creating interest in using this organism for bioremediation. Little physiological data has been published for this microbe. It is considered to be a free-living organism. The a priori prediction that the D. aromatica genome would contain previously characterized 'central' enzymes involved in anaerobic aromatic degradation proved to be false, suggesting the presence of novel anaerobic aromatic degradation pathways in this species. These missing pathways include the benzyl succinyl synthase (bssABC) genes (responsible for formate addition to toluene) and the central benzoylCoA pathway for monoaromatics. In depth analyses using existing TIGRfam, COG, and InterPro models, and the creation of de novo HMM models, indicate a highly complex lifestyle with a large number of environmental sensors and signaling pathways, including a relatively large number of GGDEF domain signal receptors and multiple quorum sensors. A number of proteins indicate interactions with an as yet unknown host, as indicated by the presence of predicted cell host remodeling enzymes, effector enzymes, hemolysin-like proteins, adhesins, NO reductase, and both type III and type VI secretory complexes. Evidence of biofilm formation including a proposed exopolysaccharide complex with the somewhat rare exosortase (epsH), is also present. Annotation described in this paper also reveals evidence for several metabolic pathways that have yet to be observed experimentally, including a sulphur oxidation (soxFCDYZAXB) gene cluster, Calvin cycle enzymes, and nitrogen fixation (including RubisCo, ribulose-phosphate 3-epimerase, and nif gene families, respectively). Analysis of the D. aromatica genome indicates there is much to be learned regarding the metabolic capabilities, and life-style, for this microbial

Metabolic analysis of the soil microbe Dechloromonas aromatica str. RCB: indications of a surprisingly complex life-style and cryptic anaerobic pathways for aromatic degradation

Directory of Open Access Journals (Sweden)

Feil Helene

2009-08-01

Full Text Available Abstract Background Initial interest in Dechloromonas aromatica strain RCB arose from its ability to anaerobically degrade benzene. It is also able to reduce perchlorate and oxidize chlorobenzoate, toluene, and xylene, creating interest in using this organism for bioremediation. Little physiological data has been published for this microbe. It is considered to be a free-living organism. Results The a priori prediction that the D. aromatica genome would contain previously characterized "central" enzymes to support anaerobic aromatic degradation of benzene proved to be false, suggesting the presence of novel anaerobic aromatic degradation pathways in this species. These missing pathways include the benzylsuccinate synthase (bssABC genes (responsible for fumarate addition to toluene and the central benzoyl-CoA pathway for monoaromatics. In depth analyses using existing TIGRfam, COG, and InterPro models, and the creation of de novo HMM models, indicate a highly complex lifestyle with a large number of environmental sensors and signaling pathways, including a relatively large number of GGDEF domain signal receptors and multiple quorum sensors. A number of proteins indicate interactions with an as yet unknown host, as indicated by the presence of predicted cell host remodeling enzymes, effector enzymes, hemolysin-like proteins, adhesins, NO reductase, and both type III and type VI secretory complexes. Evidence of biofilm formation including a proposed exopolysaccharide complex and exosortase (epsH are also present. Annotation described in this paper also reveals evidence for several metabolic pathways that have yet to be observed experimentally, including a sulphur oxidation (soxFCDYZAXB gene cluster, Calvin cycle enzymes, and proteins involved in nitrogen fixation in other species (including RubisCo, ribulose-phosphate 3-epimerase, and nif gene families, respectively. Conclusion Analysis of the D. aromatica genome indicates there is much to be

Reconstructing phylogeny by aligning multiple metabolic pathways using functional module mapping

NARCIS (Netherlands)

Huang, Yiran; Zhong, Cheng; Lin, H.X.; Wang, Jianyi; Peng, Yuzhong

2018-01-01

Comparison of metabolic pathways provides a systematic way for understanding the evolutionary and phylogenetic relationships in systems biology. Although a number of phylogenetic methods have been developed, few efforts have been made to provide a unified phylogenetic framework that sufficiently

Malaria Parasite Metabolic Pathways (MPMP) Upgraded with Targeted Chemical Compounds

KAUST Repository

Ginsburg, Hagai

2015-10-31

Malaria Parasite Metabolic Pathways (MPMP) is the website for the functional genomics of intraerythrocytic Plasmodium falciparum. All the published information about targeted chemical compounds has now been added. Users can find the drug target and publication details linked to a drug database for further information about the medicinal properties of each compound.

Malaria Parasite Metabolic Pathways (MPMP) Upgraded with Targeted Chemical Compounds

KAUST Repository

Ginsburg, Hagai; Abdel-Haleem, Alyaa M.

2015-01-01

Malaria Parasite Metabolic Pathways (MPMP) is the website for the functional genomics of intraerythrocytic Plasmodium falciparum. All the published information about targeted chemical compounds has now been added. Users can find the drug target and publication details linked to a drug database for further information about the medicinal properties of each compound.

A new course in the clinical pathways for metabolic syndrome

International Nuclear Information System (INIS)

Kageyama, Shoko; Wada, Yumi; Nakamura, Rie

2006-01-01

Metabolic syndrome is consisted with multiple risk factors such as diabetes, dyslipidemia, and hypertension based on visceral fat accumulation, for the development of arteriosclerosis. We present, here, a clinical pathway for education of patients with metabolic syndrome. The program contains an adequate explanation of the high risk for arteriosclerosis to the patients, the measurement of visceral fat content by computed tomography, and several clinical examinations for the evaluation of arteriosclerotic lesions. We have presented this program on the ward of diabetes center in our hospital for patients diagnosed as having metabolic syndrome. Because the focus of education is to clarify understanding of the harmful effects of visceral fat and the benefits of its reduction, it might be a valuable tool to motivate and empower the patient and improve the patient's lifestyle. (author)

A new course in the clinical pathways for metabolic syndrome

Energy Technology Data Exchange (ETDEWEB)

Kageyama, Shoko; Wada, Yumi; Nakamura, Rie [Sumitomo Hospital, Osaka, Osaka (Japan)

2006-07-15

Metabolic syndrome is consisted with multiple risk factors such as diabetes, dyslipidemia, and hypertension based on visceral fat accumulation, for the development of arteriosclerosis. We present, here, a clinical pathway for education of patients with metabolic syndrome. The program contains an adequate explanation of the high risk for arteriosclerosis to the patients, the measurement of visceral fat content by computed tomography, and several clinical examinations for the evaluation of arteriosclerotic lesions. We have presented this program on the ward of diabetes center in our hospital for patients diagnosed as having metabolic syndrome. Because the focus of education is to clarify understanding of the harmful effects of visceral fat and the benefits of its reduction, it might be a valuable tool to motivate and empower the patient and improve the patient's lifestyle. (author)

Genome wide expression analysis in HPV16 Cervical Cancer: identification of altered metabolic pathways

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Salcedo Mauricio

2007-09-01

Full Text Available Abstract Background Cervical carcinoma (CC is a leading cause of death among women worldwide. Human papilloma virus (HPV is a major etiological factor in CC and HPV 16 is the more frequent viral type present. Our aim was to characterize metabolic pathways altered in HPV 16 tumor samples by means of transcriptome wide analysis and bioinformatics tools for visualizing expression data in the context of KEGG biological pathways. Results We found 2,067 genes significantly up or down-modulated (at least 2-fold in tumor clinical samples compared to normal tissues, representing ~3.7% of analyzed genes. Cervical carcinoma was associated with an important up-regulation of Wnt signaling pathway, which was validated by in situ hybridization in clinical samples. Other up-regulated pathways were those of calcium signaling and MAPK signaling, as well as cell cycle-related genes. There was down-regulation of focal adhesion, TGF-β signaling, among other metabolic pathways. Conclusion This analysis of HPV 16 tumors transcriptome could be useful for the identification of genes and molecular pathways involved in the pathogenesis of cervical carcinoma. Understanding the possible role of these proteins in the pathogenesis of CC deserves further studies.

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

Science.gov (United States)

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

Highly proliferative primitive fetal liver hematopoietic stem cells are fueled by oxidative metabolic pathways

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Javed K. Manesia

2015-11-01

Full Text Available Hematopoietic stem cells (HSCs in the fetal liver (FL unlike adult bone marrow (BM proliferate extensively, posing different metabolic demands. However, metabolic pathways responsible for the production of energy and cellular building blocks in FL HSCs have not been described. Here, we report that FL HSCs use oxygen dependent energy generating pathways significantly more than their BM counterparts. RNA-Seq analysis of E14.5 FL versus BM derived HSCs identified increased expression levels of genes involved in oxidative phosphorylation (OxPhos and the citric acid cycle (TCA. We demonstrated that FL HSCs contain more mitochondria than BM HSCs, which resulted in increased levels of oxygen consumption and reactive oxygen species (ROS production. Higher levels of DNA repair and antioxidant pathway gene expression may prevent ROS-mediated (genotoxicity in FL HSCs. Thus, we here for the first time highlight the underestimated importance of oxygen dependent pathways for generating energy and building blocks in FL HSCs.

UV light selectively coinduces supply pathways from primary metabolism and flavonoid secondary product formation in parsley

Science.gov (United States)

Logemann, Elke; Tavernaro, Annette; Schulz, Wolfgang; Somssich, Imre E.; Hahlbrock, Klaus

2000-01-01

The UV light-induced synthesis of UV-protective flavonoids diverts substantial amounts of substrates from primary metabolism into secondary product formation and thus causes major perturbations of the cellular homeostasis. Results from this study show that the mRNAs encoding representative enzymes from various supply pathways are coinduced in UV-irradiated parsley cells (Petroselinum crispum) with two mRNAs of flavonoid glycoside biosynthesis, encoding phenylalanine ammonia-lyase and chalcone synthase. Strong induction was observed for mRNAs encoding glucose 6-phosphate dehydrogenase (carbohydrate metabolism, providing substrates for the shikimate pathway), 3-deoxyarabinoheptulosonate 7-phosphate synthase (shikimate pathway, yielding phenylalanine), and acyl-CoA oxidase (fatty acid degradation, yielding acetyl-CoA), and moderate induction for an mRNA encoding S-adenosyl-homocysteine hydrolase (activated methyl cycle, yielding S-adenosyl-methionine for B-ring methylation). Ten arbitrarily selected mRNAs representing various unrelated metabolic activities remained unaffected. Comparative analysis of acyl-CoA oxidase and chalcone synthase with respect to mRNA expression modes and gene promoter structure and function revealed close similarities. These results indicate a fine-tuned regulatory network integrating those functionally related pathways of primary and secondary metabolism that are specifically required for protective adaptation to UV irradiation. Although the response of parsley cells to UV light is considerably broader than previously assumed, it contrasts greatly with the extensive metabolic reprogramming observed previously in elicitor-treated or fungus-infected cells. PMID:10677554

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors.

Science.gov (United States)

Loboda, Andrey; Nebozhyn, Michael; Klinghoffer, Rich; Frazier, Jason; Chastain, Michael; Arthur, William; Roberts, Brian; Zhang, Theresa; Chenard, Melissa; Haines, Brian; Andersen, Jannik; Nagashima, Kumiko; Paweletz, Cloud; Lynch, Bethany; Feldman, Igor; Dai, Hongyue; Huang, Pearl; Watters, James

2010-06-30

Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90%) sensitivity but relatively low (50%) specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical utility in lung and breast tumors.

A gene expression signature of RAS pathway dependence predicts response to PI3K and RAS pathway inhibitors and expands the population of RAS pathway activated tumors

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Paweletz Cloud

2010-06-01

Full Text Available Abstract Background Hyperactivation of the Ras signaling pathway is a driver of many cancers, and RAS pathway activation can predict response to targeted therapies. Therefore, optimal methods for measuring Ras pathway activation are critical. The main focus of our work was to develop a gene expression signature that is predictive of RAS pathway dependence. Methods We used the coherent expression of RAS pathway-related genes across multiple datasets to derive a RAS pathway gene expression signature and generate RAS pathway activation scores in pre-clinical cancer models and human tumors. We then related this signature to KRAS mutation status and drug response data in pre-clinical and clinical datasets. Results The RAS signature score is predictive of KRAS mutation status in lung tumors and cell lines with high (> 90% sensitivity but relatively low (50% specificity due to samples that have apparent RAS pathway activation in the absence of a KRAS mutation. In lung and breast cancer cell line panels, the RAS pathway signature score correlates with pMEK and pERK expression, and predicts resistance to AKT inhibition and sensitivity to MEK inhibition within both KRAS mutant and KRAS wild-type groups. The RAS pathway signature is upregulated in breast cancer cell lines that have acquired resistance to AKT inhibition, and is downregulated by inhibition of MEK. In lung cancer cell lines knockdown of KRAS using siRNA demonstrates that the RAS pathway signature is a better measure of dependence on RAS compared to KRAS mutation status. In human tumors, the RAS pathway signature is elevated in ER negative breast tumors and lung adenocarcinomas, and predicts resistance to cetuximab in metastatic colorectal cancer. Conclusions These data demonstrate that the RAS pathway signature is superior to KRAS mutation status for the prediction of dependence on RAS signaling, can predict response to PI3K and RAS pathway inhibitors, and is likely to have the most clinical

XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks.

Science.gov (United States)

Zaretzki, Jed; Matlock, Matthew; Swamidass, S Joshua

2013-12-23

Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these properties. The cytochrome P450s (CYPs) are proteins responsible for metabolizing 90% of drugs on the market, and many computational methods can predict which atomic sites of a molecule--sites of metabolism (SOMs)--are modified during CYP-mediated metabolism. This study improves on prior methods of predicting CYP-mediated SOMs by using new descriptors and machine learning based on neural networks. The new method, XenoSite, is faster to train and more accurate by as much as 4% or 5% for some isozymes. Furthermore, some "incorrect" predictions made by XenoSite were subsequently validated as correct predictions by revaluation of the source literature. Moreover, XenoSite output is interpretable as a probability, which reflects both the confidence of the model that a particular atom is metabolized and the statistical likelihood that its prediction for that atom is correct.

Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

Science.gov (United States)

Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

2016-01-01

Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

A metabolic pathway for catabolizing levulinic acid in bacteria

International Nuclear Information System (INIS)

Rand, Jacqueline M.; Pisithkul, Tippapha; Clark, Ryan L.; Thiede, Joshua M.; Mehrer, Christopher R.

2017-01-01

Microorganisms can catabolize a wide range of organic compounds and therefore have the potential to perform many industrially relevant bioconversions. One barrier to realizing the potential of biorefining strategies lies in our incomplete knowledge of metabolic pathways, including those that can be used to assimilate naturally abundant or easily generated feedstocks. For instance, levulinic acid (LA) is a carbon source that is readily obtainable as a dehydration product of lignocellulosic biomass and can serve as the sole carbon source for some bacteria. Yet, the genetics and structure of LA catabolism have remained unknown. Here, we report the identification and characterization of a seven-gene operon that enables LA catabolism in Pseudomonas putida KT2440. When the pathway was reconstituted with purified proteins, we observed the formation of four acyl-CoA intermediates, including a unique 4-phosphovaleryl-CoA and the previously observed 3-hydroxyvaleryl-CoA product. Using adaptive evolution, we obtained a mutant of Escherichia coli LS5218 with functional deletions of fadE and atoC that was capable of robust growth on LA when it expressed the five enzymes from the P. putida operon. Here, this discovery will enable more efficient use of biomass hydrolysates and metabolic engineering to develop bioconversions using LA as a feedstock.

Malaria Parasite Metabolic Pathways (MPMP) Upgraded with Targeted Chemical Compounds.

Science.gov (United States)

Ginsburg, Hagai; Abdel-Haleem, Alyaa M

2016-01-01

Malaria Parasite Metabolic Pathways (MPMP) is the website for the functional genomics of intraerythrocytic Plasmodium falciparum. All the published information about targeted chemical compounds has now been added. Users can find the drug target and publication details linked to a drug database for further information about the medicinal properties of each compound. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of altered metabolic pathways in plasma and CSF in mild cognitive impairment and Alzheimer's disease using metabolomics.

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Eugenia Trushina

Full Text Available Alzheimer's Disease (AD currently affects more than 5 million Americans, with numbers expected to grow dramatically as the population ages. The pathophysiological changes in AD patients begin decades before the onset of dementia, highlighting the urgent need for the development of early diagnostic methods. Compelling data demonstrate that increased levels of amyloid-beta compromise multiple cellular pathways; thus, the investigation of changes in various cellular networks is essential to advance our understanding of early disease mechanisms and to identify novel therapeutic targets. We applied a liquid chromatography/mass spectrometry-based non-targeted metabolomics approach to determine global metabolic changes in plasma and cerebrospinal fluid (CSF from the same individuals with different AD severity. Metabolic profiling detected a total of significantly altered 342 plasma and 351 CSF metabolites, of which 22% were identified. Based on the changes of >150 metabolites, we found 23 altered canonical pathways in plasma and 20 in CSF in mild cognitive impairment (MCI vs. cognitively normal (CN individuals with a false discovery rate <0.05. The number of affected pathways increased with disease severity in both fluids. Lysine metabolism in plasma and the Krebs cycle in CSF were significantly affected in MCI vs. CN. Cholesterol and sphingolipids transport was altered in both CSF and plasma of AD vs. CN. Other 30 canonical pathways significantly disturbed in MCI and AD patients included energy metabolism, Krebs cycle, mitochondrial function, neurotransmitter and amino acid metabolism, and lipid biosynthesis. Pathways in plasma that discriminated between all groups included polyamine, lysine, tryptophan metabolism, and aminoacyl-tRNA biosynthesis; and in CSF involved cortisone and prostaglandin 2 biosynthesis and metabolism. Our data suggest metabolomics could advance our understanding of the early disease mechanisms shared in progression from CN to

Dissection of Biological Property of Chinese Acupuncture Point Zusanli Based on Long-Term Treatment via Modulating Multiple Metabolic Pathways

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Guangli Yan

2013-01-01

Full Text Available Acupuncture has a history of over 3000 years and is a traditional Chinese medical therapy that uses hair-thin metal needles to puncture the skin at specific points on the body to promote wellbeing, while its molecular mechanism and ideal biological pathways are still not clear. High-throughput metabolomics is the global assessment of endogenous metabolites within a biologic system and can potentially provide a more accurate snap shot of the actual physiological state. We hypothesize that acupuncture-treated human would produce unique characterization of metabolic phenotypes. In this study, UPLC/ESI-HDMS coupled with pattern recognition methods and system analysis were carried out to investigate the mechanism and metabolite biomarkers for acupuncture treatment at “Zusanli” acupoint (ST-36 as a case study. The top 5 canonical pathways including alpha-linolenic acid metabolism, d-glutamine and d-glutamate metabolism, citrate cycle, alanine, aspartate, and glutamate metabolism, and vitamin B6 metabolism pathways were acutely perturbed, and 53 differential metabolites were identified by chemical profiling and may be useful to clarify the physiological basis and mechanism of ST-36. More importantly, network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Urine metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture.

Dissection of Biological Property of Chinese Acupuncture Point Zusanli Based on Long-Term Treatment via Modulating Multiple Metabolic Pathways.

Science.gov (United States)

Yan, Guangli; Zhang, Aihua; Sun, Hui; Cheng, Weiping; Meng, Xiangcai; Liu, Li; Zhang, Yingzhi; Xie, Ning; Wang, Xijun

2013-01-01

Acupuncture has a history of over 3000 years and is a traditional Chinese medical therapy that uses hair-thin metal needles to puncture the skin at specific points on the body to promote wellbeing, while its molecular mechanism and ideal biological pathways are still not clear. High-throughput metabolomics is the global assessment of endogenous metabolites within a biologic system and can potentially provide a more accurate snap shot of the actual physiological state. We hypothesize that acupuncture-treated human would produce unique characterization of metabolic phenotypes. In this study, UPLC/ESI-HDMS coupled with pattern recognition methods and system analysis were carried out to investigate the mechanism and metabolite biomarkers for acupuncture treatment at "Zusanli" acupoint (ST-36) as a case study. The top 5 canonical pathways including alpha-linolenic acid metabolism, d-glutamine and d-glutamate metabolism, citrate cycle, alanine, aspartate, and glutamate metabolism, and vitamin B6 metabolism pathways were acutely perturbed, and 53 differential metabolites were identified by chemical profiling and may be useful to clarify the physiological basis and mechanism of ST-36. More importantly, network construction has led to the integration of metabolites associated with the multiple perturbation pathways. Urine metabolic profiling might be a promising method to investigate the molecular mechanism of acupuncture.

Study on the regulatory mechanism of the lipid metabolism pathways during chicken male germ cell differentiation based on RNA-seq.

Science.gov (United States)

Zuo, Qisheng; Li, Dong; Zhang, Lei; Elsayed, Ahmed Kamel; Lian, Chao; Shi, Qingqing; Zhang, Zhentao; Zhu, Rui; Wang, Yinjie; Jin, Kai; Zhang, Yani; Li, Bichun

2015-01-01

Here, we explore the regulatory mechanism of lipid metabolic signaling pathways and related genes during differentiation of male germ cells in chickens, with the hope that better understanding of these pathways may improve in vitro induction. Fluorescence-activated cell sorting was used to obtain highly purified cultures of embryonic stem cells (ESCs), primitive germ cells (PGCs), and spermatogonial stem cells (SSCs). The total RNA was then extracted from each type of cell. High-throughput analysis methods (RNA-seq) were used to sequence the transcriptome of these cells. Gene Ontology (GO) analysis and the KEGG database were used to identify lipid metabolism pathways and related genes. Retinoic acid (RA), the end-product of the retinol metabolism pathway, induced in vitro differentiation of ESC into male germ cells. Quantitative real-time PCR (qRT-PCR) was used to detect changes in the expression of the genes involved in the retinol metabolic pathways. From the results of RNA-seq and the database analyses, we concluded that there are 328 genes in 27 lipid metabolic pathways continuously involved in lipid metabolism during the differentiation of ESC into SSC in vivo, including retinol metabolism. Alcohol dehydrogenase 5 (ADH5) and aldehyde dehydrogenase 1 family member A1 (ALDH1A1) are involved in RA synthesis in the cell. ADH5 was specifically expressed in PGC in our experiments and aldehyde dehydrogenase 1 family member A1 (ALDH1A1) persistently increased throughout development. CYP26b1, a member of the cytochrome P450 superfamily, is involved in the degradation of RA. Expression of CYP26b1, in contrast, decreased throughout development. Exogenous RA in the culture medium induced differentiation of ESC to SSC-like cells. The expression patterns of ADH5, ALDH1A1, and CYP26b1 were consistent with RNA-seq results. We conclude that the retinol metabolism pathway plays an important role in the process of chicken male germ cell differentiation.

Metabolic Pathways Involved in Carbon Dioxide Enhanced Heat Tolerance in Bermudagrass

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Jingjin Yu

2017-09-01

Full Text Available Global climate changes involve elevated temperature and CO2 concentration, imposing significant impact on plant growth of various plant species. Elevated temperature exacerbates heat damages, but elevated CO2 has positive effects on promoting plant growth and heat tolerance. The objective of this study was to identify metabolic pathways affected by elevated CO2 conferring the improvement of heat tolerance in a C4 perennial grass species, bermudagrass (Cynodon dactylon Pers.. Plants were planted under either ambient CO2 concentration (400 μmol⋅mol-1 or elevated CO2 concentration (800 μmol⋅mol-1 and subjected to ambient temperature (30/25°C, day/night or heat stress (45/40°C, day/night. Elevated CO2 concentration suppressed heat-induced damages and improved heat tolerance in bermudagrass. The enhanced heat tolerance under elevated CO2 was attributed to some important metabolic pathways during which proteins and metabolites were up-regulated, including light reaction (ATP synthase subunit and photosystem I reaction center subunit and carbon fixation [(glyceraldehyde-3-phosphate dehydrogenase, GAPDH, fructose-bisphosphate aldolase, phosphoglycerate kinase, sedoheptulose-1,7-bisphosphatase and sugars of photosynthesis, glycolysis (GAPDH, glucose, fructose, and galactose and TCA cycle (pyruvic acid, malic acid and malate dehydrogenase of respiration, amino acid metabolism (aspartic acid, methionine, threonine, isoleucine, lysine, valine, alanine, and isoleucine as well as the GABA shunt (GABA, glutamic acid, alanine, proline and 5-oxoproline. The up-regulation of those metabolic processes by elevated CO2 could at least partially contribute to the improvement of heat tolerance in perennial grass species.

Carbon metabolic pathways in phototrophic bacteria and their broader evolutionary implications

Directory of Open Access Journals (Sweden)

Kuo-Hsiang eTang

2011-08-01

Full Text Available Photosynthesis is the biological process that converts solar energy to biomass, bio-products and biofuel. It is the only major natural solar energy storage mechanism on Earth. To satisfy the increased demand for sustainable energy sources and identify the mechanism of photosynthetic carbon assimilation, which is one of the bottlenecks in photosynthesis, it is essential to understand the process of solar energy storage and associated carbon metabolism in photosynthetic organisms. Researchers have employed physiological studies, microbiological chemistry, enzyme assays, genome sequencing, transcriptomics, and 13C-based metabolomics/fluxomics to investigate central carbon metabolism and enzymes that operate in phototrophs. In this report, we review diverse CO2 assimilation pathways, acetate assimilation, carbohydrate catabolism, the TCA cycle and some key and/or unconventional enzymes in central carbon metabolism of phototrophic microorganisms. We also discuss the reducing equivalent flow during photoautotrophic and photoheterotrophic growth, evolutionary links in the central carbon metabolic network, and correlations between photosynthetic and non-photosynthetic organisms. Considering the metabolic versatility in these fascinating and diverse photosynthetic bacteria, many essential questions in their central carbon metabolism still remain to be addressed.

The Neural Baroreflex Pathway in Subjects With Metabolic Syndrome

OpenAIRE

Zanoli, Luca; Empana, Jean-Philippe; Estrugo, Nicolas; Escriou, Guillaume; Ketthab, Hakim; Pruny, Jean-Francois; Castellino, Pietro; Laude, Dominique; Thomas, Frederique; Pannier, Bruno; Jouven, Xavier; Boutouyrie, Pierre; Laurent, Stephane

2016-01-01

Abstract The mechanisms that link metabolic syndrome (MetS) to increased cardiovascular risk are incompletely understood. We examined whether MetS is associated with the neural baroreflex pathway (NBP) and whether any such associations are independent of blood pressure values. This study involved the cross-sectional analysis of data on 2835 subjects aged 50 to 75 years from the Paris Prospective Study 3. The prevalence of MetS was defined according to the American Heart Association/National H...

Hippo pathway phylogenetics predicts monoubiquitylation of Salvador and Merlin/Nf2.

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Robert G Wisotzkey

Full Text Available Recently we employed phylogenetics to predict that the cellular interpretation of TGF-β signals is modulated by monoubiquitylation cycles affecting the Smad4 signal transducer/tumor suppressor. This prediction was subsequently validated by experiments in flies, frogs and mammalian cells. Here we apply a phylogenetic approach to the Hippo pathway and predict that two of its signal transducers, Salvador and Merlin/Nf2 (also a tumor suppressor are regulated by monoubiquitylation. This regulatory mechanism does not lead to protein degradation but instead serves as a highly efficient "off/on" switch when the protein is subsequently deubiquitylated. Overall, our study shows that the creative application of phylogenetics can predict new roles for pathway components and new mechanisms for regulating intercellular signaling pathways.

Thermodynamics in Neurodegenerative Diseases: Interplay Between Canonical WNT/Beta-Catenin Pathway-PPAR Gamma, Energy Metabolism and Circadian Rhythms.

Science.gov (United States)

Vallée, Alexandre; Lecarpentier, Yves; Guillevin, Rémy; Vallée, Jean-Noël

2018-03-23

Entropy production rate is increased by several metabolic and thermodynamics abnormalities in neurodegenerative diseases (NDs). Irreversible processes are quantified by changes in the entropy production rate. This review is focused on the opposing interactions observed in NDs between the canonical WNT/beta-catenin pathway and PPAR gamma and their metabolic and thermodynamic implications. In amyotrophic lateral sclerosis and Huntington's disease, WNT/beta-catenin pathway is upregulated, whereas PPAR gamma is downregulated. In Alzheimer's disease and Parkinson's disease, WNT/beta-catenin pathway is downregulated while PPAR gamma is upregulated. The dysregulation of the canonical WNT/beta-catenin pathway is responsible for the modification of thermodynamics behaviors of metabolic enzymes. Upregulation of WNT/beta-catenin pathway leads to aerobic glycolysis, named Warburg effect, through activated enzymes, such as glucose transporter (Glut), pyruvate kinase M2 (PKM2), pyruvate dehydrogenase kinase 1(PDK1), monocarboxylate lactate transporter 1 (MCT-1), lactic dehydrogenase kinase-A (LDH-A) and inactivation of pyruvate dehydrogenase complex (PDH). Downregulation of WNT/beta-catenin pathway leads to oxidative stress and cell death through inactivation of Glut, PKM2, PDK1, MCT-1, LDH-A but activation of PDH. In addition, in NDs, PPAR gamma is dysregulated, whereas it contributes to the regulation of several key circadian genes. NDs show many dysregulation in the mediation of circadian clock genes and so of circadian rhythms. Thermodynamics rhythms operate far-from-equilibrium and partly regulate interactions between WNT/beta-catenin pathway and PPAR gamma. In NDs, metabolism, thermodynamics and circadian rhythms are tightly interrelated.

The return of metabolism: biochemistry and physiology of the pentose phosphate pathway

NARCIS (Netherlands)

Stincone, A.; Prigione, A.; Cramer, T.; Wamelink, M.M.C.; Campbell, K.; Cheung, E.; Olin-Sandoval, V.; Gruning, N.M.; Kruger, A.; Alam, M.T.; Keller, M.A.; Breitenbach, M.; Brindle, K.M.; Rabinowitz, J.D.; Ralser, M.

2015-01-01

The pentose phosphate pathway (PPP) is a fundamental component of cellular metabolism. The PPP is important to maintain carbon homoeostasis, to provide precursors for nucleotide and amino acid biosynthesis, to provide reducing molecules for anabolism, and to defeat oxidative stress. The PPP shares

Structure of Pigment Metabolic Pathways and Their Contributions to White Tepal Color Formation of Chinese Narcissus tazetta var. chinensis cv Jinzhanyintai.

Science.gov (United States)

Ren, Yujun; Yang, Jingwen; Lu, Bingguo; Jiang, Yaping; Chen, Haiyang; Hong, Yuwei; Wu, Binghua; Miao, Ying

2017-09-08

Chinese narcissus ( Narcissus tazetta var. chinensis ) is one of the ten traditional flowers in China and a famous bulb flower in the world flower market. However, only white color tepals are formed in mature flowers of the cultivated varieties, which constrains their applicable occasions. Unfortunately, for lack of genome information of narcissus species, the explanation of tepal color formation of Chinese narcissus is still not clear. Concerning no genome information, the application of transcriptome profile to dissect biological phenomena in plants was reported to be effective. As known, pigments are metabolites of related metabolic pathways, which dominantly decide flower color. In this study, transcriptome profile and pigment metabolite analysis methods were used in the most widely cultivated Chinese narcissus "Jinzhanyintai" to discover the structure of pigment metabolic pathways and their contributions to white tepal color formation during flower development and pigmentation processes. By using comparative KEGG pathway enrichment analysis, three pathways related to flavonoid, carotenoid and chlorophyll pigment metabolism showed significant variations. The structure of flavonoids metabolic pathway was depicted, but, due to the lack of F3'5'H gene; the decreased expression of C4H , CHS and ANS genes; and the high expression of FLS gene, the effect of this pathway to synthesize functional anthocyanins in tepals was weak. Similarly, the expression of DXS , MCT and PSY genes in carotenoids synthesis sub-pathway was decreased, while CCD1 / CCD4 genes in carotenoids degradation sub-pathway was increased; therefore, the effect of carotenoids metabolic pathway to synthesize adequate color pigments in tepals is restricted. Interestingly, genes in chlorophyll synthesis sub-pathway displayed uniform down-regulated expression, while genes in heme formation and chlorophyll breakdown sub-pathways displayed up-regulated expression, which also indicates negative regulation

Clinical utility of polymorphisms in one-carbon metabolism for breast cancer risk prediction

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Shaik Mohammad Naushad

2011-01-01

Full Text Available This study addresses the issues in translating the laboratory derived data obtained during discovery phase of research to a clinical setting using a breast cancer model. Laboratory-based risk assessment indi-cated that a family history of breast cancer, reduced folate carrier 1 (RFC1 G80A, thymidylate synthase (TYMS 5’-UTR 28bp tandem repeat, methylene tetrahydrofolate reductase (MTHFR C677T and catecholamine-O-methyl transferase (COMT genetic polymorphisms in one-carbon metabolic pathway increase the risk for breast cancer. Glutamate carboxypeptidase II (GCPII C1561T and cytosolic serine hydroxymethyl transferase (cSHMT C1420T polymorphisms were found to decrease breast cancer risk. In order to test the clinical validity of this information in the risk prediction of breast cancer, data was stratified based on number of protective alleles into four categories and in each category sensitivity and 1-specificity values were obtained based on the distribution of number of risk alleles in cases and controls. Receiver operating characteristic (ROC curves were plotted and the area under ROC curve (C was used as a measure of discriminatory ability between cases and controls. In subjects without any protective allele, aberrations in one-carbon metabolism showed perfect prediction (C=0.93 while the predictability was lost in subjects with one protective allele (C=0.60. However, predictability increased steadily with increasing number of protective alleles (C=0.63 for 2 protective alleles and C=0.71 for 3 protective alleles. The cut-off point for discrimination was >4 alleles in all predictable combinations. Models of this kind can serve as valuable tools in translational re-search, especially in identifying high-risk individuals and reducing the disease risk either by life style modification or by medical intervention.

Essential pathway identification: from in silico analysis to potential antifungal targets in Aspergillus fumigatus

DEFF Research Database (Denmark)

Thykær, Jette; Andersen, Mikael Rørdam; Baker, S. E.

2009-01-01

with the reactions, we identified orthologous candidate essential genes in Aspergillus fumigatus. Our predictions are validated in part by the modes of action for some antifungal drugs and by molecular genetic studies of essential genes in A. fumigatus and other fungi. The use of metabolic models to predict...... of 1190 biochemically unique reactions that are associated with 871 open reading frames. Through a systematic in silico deletion of single metabolic reactions using this model, several essential metabolic pathways were identified for A. niger. A total of 138 reactions were identified as being essential...... biochemical reactions during growth on a minimal glucose medium. The majority of the reactions grouped into essential biochemical pathways covering cell wall biosynthesis, amino acid biosynthesis, energy metabolism and purine and pyrimidine metabolism. Based on the A. niger open reading frames associated...

SISMA: A SOFTWARE FOR DYNAMIC SIMULATION OF METABOLIC PATHWAYS IN BIOCHEMICAL EDUCATION

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J.A. Macedo

2008-05-01

Full Text Available The main purpose of metabolic pathway charts is  clarifying the flow of reactants and products  devised by enzyme  catalytic  reactions . Learning the wealth of information in metabolic pathways , however, is both challenging and overwhelming for students, mainly due to the static nature of printed charts.  In this sense the goal of this work was to develop a software environment for  metabolic chart studies, enhancing both student learning and retention. The system named SISMA (Sistema de Simulações Metabólicas was developed using  the  Unified Modeling Language (UML and Rational Unified Process (RUP tools for specifying, visualizing, constructing, and documenting  the  software system.  SISMA  was modelled with  JAVA programming  language, due to its versatility, efficiency, platform portability, and security. Use Case diagrams were constructing to describe the available functionality of  the software  and  the set of scenarios describing the interactions with the end user, with constraints defined by B usiness  Rules.  In brief, SISMA  can  dynamically  illustrate standard and physiopathological  flow of reactants, create and modifiy compounds, pathways,  and co-factors, and report kinectic data,  among others.  In this way SISMA  can be used as a complementary tool on both conventional full-time as distance learning courses in biochemistry and biotechnology.

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Science.gov (United States)

Li, Chunquan; Han, Junwei; Yao, Qianlan; Zou, Chendan; Xu, Yanjun; Zhang, Chunlong; Shang, Desi; Zhou, Lingyun; Zou, Chaoxia; Sun, Zeguo; Li, Jing; Zhang, Yunpeng; Yang, Haixiu; Gao, Xu; Li, Xia

2013-05-01

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

A method for accounting for maintenance costs in flux balance analysis improves the prediction of plant cell metabolic phenotypes under stress conditions.

Science.gov (United States)

Cheung, C Y Maurice; Williams, Thomas C R; Poolman, Mark G; Fell, David A; Ratcliffe, R George; Sweetlove, Lee J

2013-09-01

Flux balance models of metabolism generally utilize synthesis of biomass as the main determinant of intracellular fluxes. However, the biomass constraint alone is not sufficient to predict realistic fluxes in central heterotrophic metabolism of plant cells because of the major demand on the energy budget due to transport costs and cell maintenance. This major limitation can be addressed by incorporating transport steps into the metabolic model and by implementing a procedure that uses Pareto optimality analysis to explore the trade-off between ATP and NADPH production for maintenance. This leads to a method for predicting cell maintenance costs on the basis of the measured flux ratio between the oxidative steps of the oxidative pentose phosphate pathway and glycolysis. We show that accounting for transport and maintenance costs substantially improves the accuracy of fluxes predicted from a flux balance model of heterotrophic Arabidopsis cells in culture, irrespective of the objective function used in the analysis. Moreover, when the new method was applied to cells under control, elevated temperature and hyper-osmotic conditions, only elevated temperature led to a substantial increase in cell maintenance costs. It is concluded that the hyper-osmotic conditions tested did not impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources to cell maintenance. © 2013 The Authors The Plant Journal © 2013 John Wiley & Sons Ltd.

Metabolic engineering of the phenylpropanoid pathway enhances the antioxidant capacity of Saussurea involucrata.

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Jian Qiu

Full Text Available The rare wild species of snow lotus Saussurea involucrata is a commonly used medicinal herb with great pharmacological value for human health, resulting from its uniquely high level of phenylpropanoid compound production. To gain information on the phenylpropanid biosynthetic pathway genes in this critically important medicinal plant, global transcriptome sequencing was performed. It revealed that the phenylpropanoid pathway genes were well represented in S. involucrata. In addition, we introduced two key phenylpropanoid pathway inducing transcription factors (PAP1 and Lc into this medicinal plant. Transgenic S. involucrata co-expressing PAP1 and Lc exhibited purple pigments due to a massive accumulation of anthocyanins. The over-expression of PAP1 and Lc largely activated most of the phenylpropanoid pathway genes, and increased accumulation of several phenylpropanoid compounds significantly, including chlorogenic acid, syringin, cyanrine and rutin. Both ABTS (2,2'-azinobis-3-ethylbenzotiazo-line-6-sulfonic acid and FRAP (ferric reducing anti-oxidant power assays revealed that the antioxidant capacity of transgenic S. involucrata lines was greatly enhanced over controls. In addition to providing a deeper understanding of the molecular basis of phenylpropanoid metabolism, our results potentially enable an alternation of bioactive compound production in S. involucrata through metabolic engineering.

Understanding bistability in yeast glycolysis using general properties of metabolic pathways.

Science.gov (United States)

Planqué, Robert; Bruggeman, Frank J; Teusink, Bas; Hulshof, Josephus

2014-09-01

Glycolysis is the central pathway in energy metabolism in the majority of organisms. In a recent paper, van Heerden et al. showed experimentally and computationally that glycolysis can exist in two states, a global steady state and a so-called imbalanced state. In the imbalanced state, intermediary metabolites accumulate at low levels of ATP and inorganic phosphate. It was shown that Baker's yeast uses a peculiar regulatory mechanism--via trehalose metabolism--to ensure that most yeast cells reach the steady state and not the imbalanced state. Here we explore the apparent bistable behaviour in a core model of glycolysis that is based on a well-established detailed model, and study in great detail the bifurcation behaviour of solutions, without using any numerical information on parameter values. We uncover a rich suite of solutions, including so-called imbalanced states, bistability, and oscillatory behaviour. The techniques employed are generic, directly suitable for a wide class of biochemical pathways, and could lead to better analytical treatments of more detailed models. Copyright © 2014 Elsevier Inc. All rights reserved.

Curcumin regulates insulin pathways and glucose metabolism in the brains of APPswe/PS1dE9 mice.

Science.gov (United States)

Wang, Pengwen; Su, Caixin; Feng, Huili; Chen, Xiaopei; Dong, Yunfang; Rao, Yingxue; Ren, Ying; Yang, Jinduo; Shi, Jing; Tian, Jinzhou; Jiang, Shucui

2017-03-01

Recent studies have shown the therapeutic potential of curcumin in Alzheimer's disease (AD). In 2014, our lab found that curcumin reduced Aβ40, Aβ42 and Aβ-derived diffusible ligands in the mouse hippocampus, and improved learning and memory. However, the mechanisms underlying this biological effect are only partially known. There is considerable evidence in brain metabolism studies indicating that AD might be a brain-specific type of diabetes with progressive impairment of glucose utilisation and insulin signalling. We hypothesised that curcumin might target both the glucose metabolism and insulin signalling pathways. In this study, we monitored brain glucose metabolism in living APPswe/PS1dE9 double transgenic mice using a micro-positron emission tomography (PET) technique. The study showed an improvement in cerebral glucose uptake in AD mice. For a more in-depth study, we used immunohistochemical (IHC) staining and western blot techniques to examine key factors in both glucose metabolism and brain insulin signalling pathways. The results showed that curcumin ameliorated the defective insulin signalling pathway by upregulating insulin-like growth factor (IGF)-1R, IRS-2, PI3K, p-PI3K, Akt and p-Akt protein expression while downregulating IR and IRS-1. Our study found that curcumin improved spatial learning and memory, at least in part, by increasing glucose metabolism and ameliorating the impaired insulin signalling pathways in the brain.

Pathway elucidation and metabolic engineering of specialized plant metabolites

DEFF Research Database (Denmark)

Salomonsen, Bo

A worldwide need to liberate ourselves from unsustainable petrochemicals has led to numerous metabolic engineering projects, mostly carried out in microbial hosts. Using systems biology for predicting and altering the metabolism of microorganisms towards production of a desired metabolite......, these projects have increased revenues on fermentative production of several biochemicals. The use of systems biology is, however, not limited to microorganisms. Recent advances in biotechnology methods have provided a wealth of data within functional genomics, metabolomics, transcriptomics, proteomics...... and fluxomics for a considerable number of organisms. Unfortunately, transferring the wealth of data to valuable information for metabolic engineering purposes is a non-obvious task. This PhD thesis describes a palate of tools used in generation of cell factories for production of specialized plant metabolites...

De novo assembly and functional annotation of Myrciaria dubia fruit transcriptome reveals multiple metabolic pathways for L-ascorbic acid biosynthesis.

Science.gov (United States)

Castro, Juan C; Maddox, J Dylan; Cobos, Marianela; Requena, David; Zimic, Mirko; Bombarely, Aureliano; Imán, Sixto A; Cerdeira, Luis A; Medina, Andersson E

2015-11-24

Myrciaria dubia is an Amazonian fruit shrub that produces numerous bioactive phytochemicals, but is best known by its high L-ascorbic acid (AsA) content in fruits. Pronounced variation in AsA content has been observed both within and among individuals, but the genetic factors responsible for this variation are largely unknown. The goals of this research, therefore, were to assemble, characterize, and annotate the fruit transcriptome of M. dubia in order to reconstruct metabolic pathways and determine if multiple pathways contribute to AsA biosynthesis. In total 24,551,882 high-quality sequence reads were de novo assembled into 70,048 unigenes (mean length = 1150 bp, N50 = 1775 bp). Assembled sequences were annotated using BLASTX against public databases such as TAIR, GR-protein, FB, MGI, RGD, ZFIN, SGN, WB, TIGR_CMR, and JCVI-CMR with 75.2 % of unigenes having annotations. Of the three core GO annotation categories, biological processes comprised 53.6 % of the total assigned annotations, whereas cellular components and molecular functions comprised 23.3 and 23.1 %, respectively. Based on the KEGG pathway assignment of the functionally annotated transcripts, five metabolic pathways for AsA biosynthesis were identified: animal-like pathway, myo-inositol pathway, L-gulose pathway, D-mannose/L-galactose pathway, and uronic acid pathway. All transcripts coding enzymes involved in the ascorbate-glutathione cycle were also identified. Finally, we used the assembly to identified 6314 genic microsatellites and 23,481 high quality SNPs. This study describes the first next-generation sequencing effort and transcriptome annotation of a non-model Amazonian plant that is relevant for AsA production and other bioactive phytochemicals. Genes encoding key enzymes were successfully identified and metabolic pathways involved in biosynthesis of AsA, anthocyanins, and other metabolic pathways have been reconstructed. The identification of these genes and pathways is in agreement with

Spatial localization of the first and last enzymes effectively connects active metabolic pathways in bacteria.

Science.gov (United States)

Meyer, Pablo; Cecchi, Guillermo; Stolovitzky, Gustavo

2014-12-14

Although much is understood about the enzymatic cascades that underlie cellular biosynthesis, comparatively little is known about the rules that determine their cellular organization. We performed a detailed analysis of the localization of E.coli GFP-tagged enzymes for cells growing exponentially. We found that out of 857 globular enzymes, at least 219 have a discrete punctuate localization in the cytoplasm and catalyze the first or the last reaction in 60% of biosynthetic pathways. A graph-theoretic analysis of E.coli's metabolic network shows that localized enzymes, in contrast to non-localized ones, form a tree-like hierarchical structure, have a higher within-group connectivity, and are traversed by a higher number of feed-forward and feedback loops than their non-localized counterparts. A Gene Ontology analysis of these enzymes reveals an enrichment of terms related to essential metabolic functions in growing cells. Given that these findings suggest a distinct metabolic role for localization, we studied the dynamics of cellular localization of the cell wall synthesizing enzymes in B. subtilis and found that enzymes localize during exponential growth but not during stationary growth. We conclude that active biochemical pathways inside the cytoplasm are organized spatially following a rule where their first or their last enzymes localize to effectively connect the different active pathways and thus could reflect the activity state of the cell's metabolic network.

The "parallel pathway": a novel nutritional and metabolic approach to cancer patients.

Science.gov (United States)

Muscaritoli, Maurizio; Molfino, Alessio; Gioia, Gianfranco; Laviano, Alessandro; Rossi Fanelli, Filippo

2011-04-01

Cancer-associated malnutrition results from a deadly combination of anorexia, which leads to reduced food intake, and derangements of host metabolism inducing body weight loss, and hindering its reversal with nutrient supplementation. Cancer patients often experience both anorexia and weight loss, contributing to the onset of the clinical feature named as anorexia-cachexia syndrome. This condition has a negative impact upon patients' nutritional status. The pathogenesis of the anorexia-cachexia syndrome is multifactorial, and is related to: tumour-derived factors, host-derived factors inducing metabolic derangements, and side effects of anticancer therapies. In addition, the lack of awareness of cancer patients' nutritional issues and status by many oncologists, frequently results in progressive weight loss going undiagnosed until it becomes severe. The critical involvement of host inflammatory response in the development of weight loss, and, in particular, lean body mass depletion, limits the response to the provision of standard nutrition support. A novel nutritional and metabolic approach, named "parallel pathway", has been devised that may help maintain or improve nutritional status, and prevent or delay the onset of cancer cachexia. Such an approach may improve tolerance to aggressive anticancer therapies, and ameliorate the functional capacity and quality of life even in advanced disease stages. The "parallel pathway" implies a multiprofessional and multimodal approach aimed at ensuring early, appropriate and continuous nutritional and metabolic support to cancer patients in any phase of their cancer journey.

Evaluation by mass fragmentography of metabolic pathways of endogenous and exogenous compounds in eukaryote cell cultures

International Nuclear Information System (INIS)

Padieu, P.; Maume, B.F.

1977-01-01

Carbon-14 labelled compounds in cell cultures are used to establish the interconnections between different metabolic pathways as well as the competitive action of effectors on these different pathways. Analysis was performed by the GC-MS combination. Identification was carried out by comparison with the mass spectra of d9-TMS, 35 Cl-TMS and 37 Cl-TMS derivatizations of the culture extracts. Examples are given of the metabolic study of hormonal steroids and of safrale, a carcinogenic compound, by differentiated eukaryotic cells in cultures from the rat

Fast prediction of cytochrome P450 mediated drug metabolism

DEFF Research Database (Denmark)

Rydberg, Patrik Åke Anders; Poongavanam, Vasanthanathan; Oostenbrink, Chris

2009-01-01

Cytochrome P450 mediated metabolism of drugs is one of the major determinants of their kinetic profile, and prediction of this metabolism is therefore highly relevant during the drug discovery and development process. A new rule-based method, based on results from density functional theory...... calculations, for predicting activation energies for aliphatic and aromatic oxidations by cytochromes P450 is developed and compared with several other methods. Although the applicability of the method is currently limited to a subset of P450 reactions, these reactions describe more than 90...

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

Directory of Open Access Journals (Sweden)

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.

Waist-to-height: cutoff matters in predicting metabolic syndrome in Mexican children.

Science.gov (United States)

Elizondo-Montemayor, Leticia; Serrano-González, Mónica; Ugalde-Casas, Patricia A; Bustamante-Careaga, Humberto; Cuello-García, Carlos

2011-06-01

Body-mass index (BMI), waist circumference (WC), and, recently, waist-to-height ratio (WHtR) have been proposed as clinical indexes to identify children at cardiometabolic risk. The aim was to identify the usefulness of WHtR cutoffs, WC, and BMI as predictors of metabolic syndrome in Mexican children, according to BMI z-scores, and the severity of obesity to cardiometabolic risk factors and metabolic syndrome. This was a cross-sectional study of 214 overweight/obese and 47 normal-weight Mexican children 6-12 years old. Children were divided in groups according to BMI z-scores. Anthropometric and biochemical measurements were determined. Receiver-operating characteristic (ROC) curves and areas under the curves were calculated to compare the abilities of the anthropometric measurements to predict metabolic syndrome. The overall prevalence of metabolic syndrome was 23.3%, ranging from 11.0% in the overweight group to 73.9% in the severely obese one. Children with metabolic syndrome had significantly higher WHtR, WC, BMI, percentage of body fat, triglycerides, total cholesterol, low-density lipoprotein cholesterol (LDL-C), systolic and diastolic blood pressure, and lower high-density lipoprotein cholesterol (HDL-C). A WHtR cutoff point of 0.59 from the ROC curve was identified as strong predictor of metabolic syndrome in our population, whereas a cutoff of 0.5 showed very poor specificity (22.7%). WC predicted metabolic syndrome as well. Cutoff values for WHtR make a difference in predicting metabolic syndrome. A cutoff of 0.59 for WHtR strongly predicted metabolic syndrome; it might be a simpler to use screening tools and counters for short people. Further studies are required to determine the cutoff points for an accurate prediction, because there are few in children and none in Mexico.

Effect of CAR activation on selected metabolic pathways in normal and hyperlipidemic mouse livers.

Science.gov (United States)

Rezen, Tadeja; Tamasi, Viola; Lövgren-Sandblom, Anita; Björkhem, Ingemar; Meyer, Urs A; Rozman, Damjana

2009-08-19

Detoxification in the liver involves activation of nuclear receptors, such as the constitutive androstane receptor (CAR), which regulate downstream genes of xenobiotic metabolism. Frequently, the metabolism of endobiotics is also modulated, resulting in potentially harmful effects. We therefore used 1,4-Bis [2-(3,5-dichloropyridyloxy)] benzene (TCPOBOP) to study the effect of CAR activation on mouse hepatic transcriptome and lipid metabolome under conditions of diet-induced hyperlipidemia. Using gene expression profiling with a dedicated microarray, we show that xenobiotic metabolism, PPARalpha and adipocytokine signaling, and steroid synthesis are the pathways most affected by TCPOBOP in normal and hyperlipidemic mice. TCPOBOP-induced CAR activation prevented the increased hepatic and serum cholesterol caused by feeding mice a diet containing 1% cholesterol. We show that this is due to increased bile acid metabolism and up-regulated removal of LDL, even though TCPOBOP increased cholesterol synthesis under conditions of hyperlipidemia. Up-regulation of cholesterol synthesis was not accompanied by an increase in mature SREBP2 protein. As determined by studies in CAR -/- mice, up-regulation of cholesterol synthesis is however CAR-dependent; and no obvious CAR binding sites were detected in promoters of cholesterogenic genes. TCPOBOP also affected serum glucose and triglyceride levels and other metabolic processes in the liver, irrespective of the diet. Our data show that CAR activation modulates hepatic metabolism by lowering cholesterol and glucose levels, through effects on PPARalpha and adiponectin signaling pathways, and by compromising liver adaptations to hyperlipidemia.

Autotrophic microbe metagenomes and metabolic pathways differentiate adjacent red sea brine pools

KAUST Repository

Wang, Yong

2013-04-29

In the Red Sea, two neighboring deep-sea brine pools, Atlantis II and Discovery, have been studied extensively, and the results have shown that the temperature and concentrations of metal and methane in Atlantis II have increased over the past decades. Therefore, we investigated changes in the microbial community and metabolic pathways. Here, we compared the metagenomes of the two pools to each other and to those of deep-sea water samples. Archaea were generally absent in the Atlantis II metagenome; Bacteria in the metagenome were typically heterotrophic and depended on aromatic compounds and other extracellular organic carbon compounds as indicated by enrichment of the related metabolic pathways. In contrast, autotrophic Archaea capable of CO2 fixation and methane oxidation were identified in Discovery but not in Atlantis II. Our results suggest that hydrothermal conditions and metal precipitation in the Atlantis II pool have resulted in elimination of the autotrophic community and methanogens.

Water deficit alters differentially metabolic pathways affecting important flavor and quality traits in grape berries of Cabernet Sauvignon and Chardonnay

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Deluc, Laurent G; Quilici, David R; Decendit, Alain; Grimplet, Jérôme; Wheatley, Matthew D; Schlauch, Karen A; Mérillon, Jean-Michel; Cushman, John C; Cramer, Grant R

2009-01-01

Background Water deficit has significant effects on grape berry composition resulting in improved wine quality by the enhancement of color, flavors, or aromas. While some pathways or enzymes affected by water deficit have been identified, little is known about the global effects of water deficit on grape berry metabolism. Results The effects of long-term, seasonal water deficit on berries of Cabernet Sauvignon, a red-wine grape, and Chardonnay, a white-wine grape were analyzed by integrated transcript and metabolite profiling. Over the course of berry development, the steady-state transcript abundance of approximately 6,000 Unigenes differed significantly between the cultivars and the irrigation treatments. Water deficit most affected the phenylpropanoid, ABA, isoprenoid, carotenoid, amino acid and fatty acid metabolic pathways. Targeted metabolites were profiled to confirm putative changes in specific metabolic pathways. Water deficit activated the expression of numerous transcripts associated with glutamate and proline biosynthesis and some committed steps of the phenylpropanoid pathway that increased anthocyanin concentrations in Cabernet Sauvignon. In Chardonnay, water deficit activated parts of the phenylpropanoid, energy, carotenoid and isoprenoid metabolic pathways that contribute to increased concentrations of antheraxanthin, flavonols and aroma volatiles. Water deficit affected the ABA metabolic pathway in both cultivars. Berry ABA concentrations were highly correlated with 9-cis-epoxycarotenoid dioxygenase (NCED1) transcript abundance, whereas the mRNA expression of other NCED genes and ABA catabolic and glycosylation processes were largely unaffected. Water deficit nearly doubled ABA concentrations within berries of Cabernet Sauvignon, whereas it decreased ABA in Chardonnay at véraison and shortly thereafter. Conclusion The metabolic responses of grapes to water deficit varied with the cultivar and fruit pigmentation. Chardonnay berries, which lack any

Water deficit alters differentially metabolic pathways affecting important flavor and quality traits in grape berries of Cabernet Sauvignon and Chardonnay

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Deluc Laurent G

2009-05-01

Full Text Available Abstract Background Water deficit has significant effects on grape berry composition resulting in improved wine quality by the enhancement of color, flavors, or aromas. While some pathways or enzymes affected by water deficit have been identified, little is known about the global effects of water deficit on grape berry metabolism. Results The effects of long-term, seasonal water deficit on berries of Cabernet Sauvignon, a red-wine grape, and Chardonnay, a white-wine grape were analyzed by integrated transcript and metabolite profiling. Over the course of berry development, the steady-state transcript abundance of approximately 6,000 Unigenes differed significantly between the cultivars and the irrigation treatments. Water deficit most affected the phenylpropanoid, ABA, isoprenoid, carotenoid, amino acid and fatty acid metabolic pathways. Targeted metabolites were profiled to confirm putative changes in specific metabolic pathways. Water deficit activated the expression of numerous transcripts associated with glutamate and proline biosynthesis and some committed steps of the phenylpropanoid pathway that increased anthocyanin concentrations in Cabernet Sauvignon. In Chardonnay, water deficit activated parts of the phenylpropanoid, energy, carotenoid and isoprenoid metabolic pathways that contribute to increased concentrations of antheraxanthin, flavonols and aroma volatiles. Water deficit affected the ABA metabolic pathway in both cultivars. Berry ABA concentrations were highly correlated with 9-cis-epoxycarotenoid dioxygenase (NCED1 transcript abundance, whereas the mRNA expression of other NCED genes and ABA catabolic and glycosylation processes were largely unaffected. Water deficit nearly doubled ABA concentrations within berries of Cabernet Sauvignon, whereas it decreased ABA in Chardonnay at véraison and shortly thereafter. Conclusion The metabolic responses of grapes to water deficit varied with the cultivar and fruit pigmentation

Predicting metabolic syndrome using decision tree and support vector machine methods

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Farzaneh Karimi-Alavijeh

2016-06-01

Full Text Available BACKGROUND: Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. METHODS: This study aims to employ decision tree and support vector machine (SVM to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP, diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs, total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. RESULTS: SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758, 0.74 (0.72 and 0.757 (0.739 in SVM (decision tree method. CONCLUSION: The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most

Predicting metabolic syndrome using decision tree and support vector machine methods.

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Karimi-Alavijeh, Farzaneh; Jalili, Saeed; Sadeghi, Masoumeh

2016-05-01

Metabolic syndrome which underlies the increased prevalence of cardiovascular disease and Type 2 diabetes is considered as a group of metabolic abnormalities including central obesity, hypertriglyceridemia, glucose intolerance, hypertension, and dyslipidemia. Recently, artificial intelligence based health-care systems are highly regarded because of its success in diagnosis, prediction, and choice of treatment. This study employs machine learning technics for predict the metabolic syndrome. This study aims to employ decision tree and support vector machine (SVM) to predict the 7-year incidence of metabolic syndrome. This research is a practical one in which data from 2107 participants of Isfahan Cohort Study has been utilized. The subjects without metabolic syndrome according to the ATPIII criteria were selected. The features that have been used in this data set include: gender, age, weight, body mass index, waist circumference, waist-to-hip ratio, hip circumference, physical activity, smoking, hypertension, antihypertensive medication use, systolic blood pressure (BP), diastolic BP, fasting blood sugar, 2-hour blood glucose, triglycerides (TGs), total cholesterol, low-density lipoprotein, high density lipoprotein-cholesterol, mean corpuscular volume, and mean corpuscular hemoglobin. Metabolic syndrome was diagnosed based on ATPIII criteria and two methods of decision tree and SVM were selected to predict the metabolic syndrome. The criteria of sensitivity, specificity and accuracy were used for validation. SVM and decision tree methods were examined according to the criteria of sensitivity, specificity and accuracy. Sensitivity, specificity and accuracy were 0.774 (0.758), 0.74 (0.72) and 0.757 (0.739) in SVM (decision tree) method. The results show that SVM method sensitivity, specificity and accuracy is more efficient than decision tree. The results of decision tree method show that the TG is the most important feature in predicting metabolic syndrome. According

β-N-Methylamino-L-alanine (BMAA) perturbs alanine, aspartate and glutamate metabolism pathways in human neuroblastoma cells as determined by metabolic profiling.

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Engskog, Mikael K R; Ersson, Lisa; Haglöf, Jakob; Arvidsson, Torbjörn; Pettersson, Curt; Brittebo, Eva

2017-05-01

β-Methylamino-L-alanine (BMAA) is a non-proteinogenic amino acid that induces long-term cognitive deficits, as well as an increased neurodegeneration and intracellular fibril formation in the hippocampus of adult rodents following short-time neonatal exposure and in vervet monkey brain following long-term exposure. It has also been proposed to be involved in the etiology of neurodegenerative disease in humans. The aim of this study was to identify metabolic effects not related to excitotoxicity or oxidative stress in human neuroblastoma SH-SY5Y cells. The effects of BMAA (50, 250, 1000 µM) for 24 h on cells differentiated with retinoic acid were studied. Samples were analyzed using LC-MS and NMR spectroscopy to detect altered intracellular polar metabolites. The analysis performed, followed by multivariate pattern recognition techniques, revealed significant perturbations in protein biosynthesis, amino acid metabolism pathways and citrate cycle. Of specific interest were the BMAA-induced alterations in alanine, aspartate and glutamate metabolism and as well as alterations in various neurotransmitters/neuromodulators such as GABA and taurine. The results indicate that BMAA can interfere with metabolic pathways involved in neurotransmission in human neuroblastoma cells.

Organization of metabolic pathways in vastus lateralis of patients with chronic obstructive pulmonary disease.

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Green, Howard J; Bombardier, Eric; Burnett, Margaret; Iqbal, Sobia; D'Arsigny, Christine L; O'Donnell, Dennis E; Ouyang, Jing; Webb, Katherine A

2008-09-01

The objective of this study was to determine whether patients with chronic obstructive lung disease (COPD) display differences in organization of the metabolic pathways and segments involved in energy supply compared with healthy control subjects. Metabolic pathway potential, based on the measurement of the maximal activity (V(max)) of representative enzymes, was assessed in tissue extracted from the vastus lateralis in seven patients with COPD (age 67 +/- 4 yr; FEV(1)/FVC = 44 +/- 3%, where FEV(1) is forced expiratory volume in 1 s and FVC is forced vital capacity; means +/- SE) and nine healthy age-matched controls (age 68 +/- 2 yr; FEV(1)/FVC = 75 +/- 2%). Compared with control, the COPD patients displayed lower (P chain and glycogenolysis and glycolysis relative to beta-oxidation.

Molecular Characterization and Clinical Relevance of Metabolic Expression Subtypes in Human Cancers

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Xinxin Peng

2018-04-01

Full Text Available Summary: Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes—modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility. : Peng et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to characterize tumor subtypes based on the expression of seven metabolic pathways. They find metabolic expression subtypes are associated with patient survivals and suggest the therapeutic and predictive relevance of subtype-related master regulators. Keywords: The Cancer Genome Atlas, tumor subtypes, prognostic markers, somatic drivers, master regulator, therapeutic targets, drug sensitivity, carbohydrate metabolism

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.

Dietary modification of metabolic pathways via nuclear hormone receptors.

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Caiozzi, Gianella; Wong, Brian S; Ricketts, Marie-Louise

2012-10-01

Nuclear hormone receptors (NHRs), as ligand-dependent transcription factors, have emerged as important mediators in the control of whole body metabolism. Because of the promiscuous nature of several members of this superfamily that have been found to bind ligand with lower affinity than the classical steroid NHRs, they consequently display a broader ligand selectivity. This promiscuous nature has facilitated various bioactive dietary components being able to act as agonist ligands for certain members of the NHR superfamily. By binding to these NHRs, bioactive dietary components are able to mediate changes in various metabolic pathways, including, glucose, cholesterol and triglyceride homeostasis among others. This review will provide a general overview of the nuclear hormone receptors that have been shown to be activated by dietary components. The physiological consequences of such receptor activation by these dietary components will then be discussed in more detail. Copyright © 2012 John Wiley & Sons, Ltd.

Evolution of a flipped pathway creates metabolic innovation in tomato trichomes through BAHD enzyme promiscuity.

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Fan, Pengxiang; Miller, Abigail M; Liu, Xiaoxiao; Jones, A Daniel; Last, Robert L

2017-12-12

Plants produce hundreds of thousands of structurally diverse specialized metabolites via multistep biosynthetic networks, including compounds of ecological and therapeutic importance. These pathways are restricted to specific plant groups, and are excellent systems for understanding metabolic evolution. Tomato and other plants in the nightshade family synthesize protective acylated sugars in the tip cells of glandular trichomes on stems and leaves. We describe a metabolic innovation in wild tomato species that contributes to acylsucrose structural diversity. A small number of amino acid changes in two acylsucrose acyltransferases alter their acyl acceptor preferences, resulting in reversal of their order of reaction and increased product diversity. This study demonstrates how small numbers of amino acid changes in multiple pathway enzymes can lead to diversification of specialized metabolites in plants. It also highlights the power of a combined genetic, genomic and in vitro biochemical approach to identify the evolutionary mechanisms leading to metabolic novelty.

An ensemble method to predict target genes and pathways in uveal melanoma

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Wei Chao

2018-04-01

Full Text Available This work proposes to predict target genes and pathways for uveal melanoma (UM based on an ensemble method and pathway analyses. Methods: The ensemble method integrated a correlation method (Pearson correlation coefficient, PCC, a causal inference method (IDA and a regression method (Lasso utilizing the Borda count election method. Subsequently, to validate the performance of PIL method, comparisons between confirmed database and predicted miRNA targets were performed. Ultimately, pathway enrichment analysis was conducted on target genes in top 1000 miRNA-mRNA interactions to identify target pathways for UM patients. Results: Thirty eight of the predicted interactions were matched with the confirmed interactions, indicating that the ensemble method was a suitable and feasible approach to predict miRNA targets. We obtained 50 seed miRNA-mRNA interactions of UM patients and extracted target genes from these interactions, such as ASPG, BSDC1 and C4BP. The 601 target genes in top 1,000 miRNA-mRNA interactions were enriched in 12 target pathways, of which Phototransduction was the most significant one. Conclusion: The target genes and pathways might provide a new way to reveal the molecular mechanism of UM and give hand for target treatments and preventions of this malignant tumor.

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

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

2006-07-17

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

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

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Sugimoto Masahiro

2006-07-01

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

Ties that bind: the integration of plastid signalling pathways in plant cell metabolism.

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Brunkard, Jacob O; Burch-Smith, Tessa M

2018-04-13

Plastids are critical organelles in plant cells that perform diverse functions and are central to many metabolic pathways. Beyond their major roles in primary metabolism, of which their role in photosynthesis is perhaps best known, plastids contribute to the biosynthesis of phytohormones and other secondary metabolites, store critical biomolecules, and sense a range of environmental stresses. Accordingly, plastid-derived signals coordinate a host of physiological and developmental processes, often by emitting signalling molecules that regulate the expression of nuclear genes. Several excellent recent reviews have provided broad perspectives on plastid signalling pathways. In this review, we will highlight recent advances in our understanding of chloroplast signalling pathways. Our discussion focuses on new discoveries illuminating how chloroplasts determine life and death decisions in cells and on studies elucidating tetrapyrrole biosynthesis signal transduction networks. We will also examine the role of a plastid RNA helicase, ISE2, in chloroplast signalling, and scrutinize intriguing results investigating the potential role of stromules in conducting signals from the chloroplast to other cellular locations. © 2018 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Tools and strategies for discovering novel enzymes and metabolic pathways

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John A. Gerlt

2016-12-01

Full Text Available The number of entries in the sequence databases continues to increase exponentially – the UniProt database is increasing with a doubling time of ∼4 years (2% increase/month. Approximately 50% of the entries have uncertain, unknown, or incorrect function annotations because these are made by automated methods based on sequence homology. If the potential in complete genome sequences is to be realized, strategies and tools must be developed to facilitate experimental assignment of functions to uncharacterized proteins discovered in genome projects. The Enzyme Function Initiative (EFI; previously supported by U54GM093342 from the National Institutes of Health, now supported by P01GM118303 developed web tools for visualizing and analyzing (1 sequence and function space in protein families (EFI-EST and (2 genome neighbourhoods in microbial and fungal genomes (EFI-GNT to assist the design of experimental strategies for discovering the in vitro activities and in vivo metabolic functions of uncharacterized enzymes. The EFI developed an experimental platform for large-scale production of the solute binding proteins (SBPs for ABC, TRAP, and TCT transport systems and their screening with a physical ligand library to identify the identities of the ligands for these transport systems. Because the genes that encode transport systems are often co-located with the genes that encode the catabolic pathways for the transported solutes, the identity of the SBP ligand together with the EFI-EST and EFI-GNT web tools can be used to discover new enzyme functions and new metabolic pathways. This approach is demonstrated with the characterization of a novel pathway for ethanolamine catabolism.

Predictive Modelling Risk Calculators and the Non Dialysis Pathway.

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Robins, Jennifer; Katz, Ivor

2013-04-16

This guideline will review the current prediction models and survival/mortality scores available for decision making in patients with advanced kidney disease who are being considered for a non-dialysis treatment pathway. Risk prediction is gaining increasing attention with emerging literature suggesting improved patient outcomes through individualised risk prediction (1). Predictive models help inform the nephrologist and the renal palliative care specialists in their discussions with patients and families about suitability or otherwise of dialysis. Clinical decision making in the care of end stage kidney disease (ESKD) patients on a non-dialysis treatment pathway is currently governed by several observational trials (3). Despite the paucity of evidence based medicine in this field, it is becoming evident that the survival advantages associated with renal replacement therapy in these often elderly patients with multiple co-morbidities and limited functional status may be negated by loss of quality of life (7) (6), further functional decline (5, 8), increased complications and hospitalisations. This article is protected by copyright. All rights reserved.

Critical assessment of human metabolic pathway databases: a stepping stone for future integration

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Stobbe Miranda D

2011-10-01

Full Text Available Abstract Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison

Fenofibrate inhibits atrial metabolic remodelling in atrial fibrillation through PPAR-α/sirtuin 1/PGC-1α pathway.

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Liu, Guang-Zhong; Hou, Ting-Ting; Yuan, Yue; Hang, Peng-Zhou; Zhao, Jing-Jing; Sun, Li; Zhao, Guan-Qi; Zhao, Jing; Dong, Jing-Mei; Wang, Xiao-Bing; Shi, Hang; Liu, Yong-Wu; Zhou, Jing-Hua; Dong, Zeng-Xiang; Liu, Yang; Zhan, Cheng-Chuang; Li, Yue; Li, Wei-Min

2016-03-01

Atrial metabolic remodelling is critical for the process of atrial fibrillation (AF). The PPAR-α/sirtuin 1 /PPAR co-activator α (PGC-1α) pathway plays an important role in maintaining energy metabolism. However, the effect of the PPAR-α agonist fenofibrate on AF is unclear. Therefore, the aim of this study was to determine the effect of fenofibrate on atrial metabolic remodelling in AF and explore its possible mechanisms of action. The expression of metabolic proteins was examined in the left atria of AF patients. Thirty-two rabbits were divided into sham, AF (pacing with 600 beats·min(-1) for 1 week), fenofibrate treated (pretreated with fenofibrate before pacing) and fenofibrate alone treated (for 2 weeks) groups. HL-1 cells were subjected to rapid pacing in the presence or absence of fenofibrate, the PPAR-α antagonist GW6471 or sirtuin 1-specific inhibitor EX527. Metabolic factors, circulating biochemical metabolites, atrial electrophysiology, adenine nucleotide levels and accumulation of glycogen and lipid droplets were assessed. The PPAR-α/sirtuin 1/PGC-1α pathway was significantly inhibited in AF patients and in the rabbit/HL-1 cell models, resulting in a reduction of key downstream metabolic factors; this effect was significantly restored by fenofibrate. Fenofibrate prevented the alterations in circulating biochemical metabolites, reduced the level of adenine nucleotides and accumulation of glycogen and lipid droplets, reversed the shortened atrial effective refractory period and increased risk of AF. Fenofibrate inhibited atrial metabolic remodelling in AF by regulating the PPAR-α/sirtuin 1/PGC-1α pathway. The present study may provide a novel therapeutic strategy for AF. © 2016 The British Pharmacological Society.

Microchip electrophoresis with electrochemical detection for the determination of analytes in the dopamine metabolic pathway

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Saylor, Rachel A.; Reid, Erin A.; Lunte, Susan M.

2016-01-01

A method for the separation and detection of analytes in the dopamine metabolic pathway was developed using microchip electrophoresis with electrochemical detection. The microchip consisted of a 5 cm PDMS separation channel in a simple-t configuration. Analytes in the dopamine metabolic pathway were separated using a background electrolyte composed of 15 mM phosphate at pH 7.4, 15 mM SDS, and 2.5 mM boric acid. Two different microchip substrates using different electrode materials were compared for the analysis: a PDMS/PDMS device with a carbon fiber electrode and a PDMS/glass hybrid device with a pyrolyzed photoresist film carbon electrode. While the PDMS/PDMS device generated high separation efficiencies and good resolution, more reproducible migration times were obtained with the PDMS/glass hybrid device, making it a better choice for biological applications. Lastly, the optimized method was used to monitor L-DOPA metabolism in a rat brain slice. PMID:25958983

Evolutionary rate patterns of the Gibberellin pathway genes

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Zhang Fu-min

2009-08-01

Full Text Available Abstract Background Analysis of molecular evolutionary patterns of different genes within metabolic pathways allows us to determine whether these genes are subject to equivalent evolutionary forces and how natural selection shapes the evolution of proteins in an interacting system. Although previous studies found that upstream genes in the pathway evolved more slowly than downstream genes, the correlation between evolutionary rate and position of the genes in metabolic pathways as well as its implications in molecular evolution are still less understood. Results We sequenced and characterized 7 core structural genes of the gibberellin biosynthetic pathway from 8 representative species of the rice tribe (Oryzeae to address alternative hypotheses regarding evolutionary rates and patterns of metabolic pathway genes. We have detected significant rate heterogeneity among 7 GA pathway genes for both synonymous and nonsynonymous sites. Such rate variation is mostly likely attributed to differences of selection intensity rather than differential mutation pressures on the genes. Unlike previous argument that downstream genes in metabolic pathways would evolve more slowly than upstream genes, the downstream genes in the GA pathway did not exhibited the elevated substitution rate and instead, the genes that encode either the enzyme at the branch point (GA20ox or enzymes catalyzing multiple steps (KO, KAO and GA3ox in the pathway had the lowest evolutionary rates due to strong purifying selection. Our branch and codon models failed to detect signature of positive selection for any lineage and codon of the GA pathway genes. Conclusion This study suggests that significant heterogeneity of evolutionary rate of the GA pathway genes is mainly ascribed to differential constraint relaxation rather than the positive selection and supports the pathway flux theory that predicts that natural selection primarily targets enzymes that have the greatest control on fluxes.

Multi-variant pathway association analysis reveals the importance of genetic determinants of estrogen metabolism in breast and endometrial cancer susceptibility.

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Yen Ling Low

2010-07-01

Full Text Available Despite the central role of estrogen exposure in breast and endometrial cancer development and numerous studies of genes in the estrogen metabolic pathway, polymorphisms within the pathway have not been consistently associated with these cancers. We posit that this is due to the complexity of multiple weak genetic effects within the metabolic pathway that can only be effectively detected through multi-variant analysis. We conducted a comprehensive association analysis of the estrogen metabolic pathway by interrogating 239 tagSNPs within 35 genes of the pathway in three tumor samples. The discovery sample consisted of 1,596 breast cancer cases, 719 endometrial cancer cases, and 1,730 controls from Sweden; and the validation sample included 2,245 breast cancer cases and 1,287 controls from Finland. We performed admixture maximum likelihood (AML-based global tests to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three sub-pathways for androgen synthesis, androgen-to-estrogen conversion, and estrogen removal. In the discovery sample, although no single polymorphism was significant after correction for multiple testing, the pathway-based AML global test suggested association with both breast (p(global = 0.034 and endometrial (p(global = 0.052 cancers. Further testing revealed the association to be focused on polymorphisms within the androgen-to-estrogen conversion sub-pathway, for both breast (p(global = 0.008 and endometrial cancer (p(global = 0.014. The sub-pathway association was validated in the Finnish sample of breast cancer (p(global = 0.015. Further tumor subtype analysis demonstrated that the association of the androgen-to-estrogen conversion sub-pathway was confined to postmenopausal women with sporadic estrogen receptor positive tumors (p(global = 0.0003. Gene-based AML analysis suggested CYP19A1 and UGT2B4 to be the major players within the sub-pathway. Our study indicates that the composite

Transcriptome Analysis of Three Sheep Intestinal Regions reveals Key Pathways and Hub Regulatory Genes of Large Intestinal Lipid Metabolism.

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Chao, Tianle; Wang, Guizhi; Ji, Zhibin; Liu, Zhaohua; Hou, Lei; Wang, Jin; Wang, Jianmin

2017-07-13

The large intestine, also known as the hindgut, is an important part of the animal digestive system. Recent studies on digestive system development in ruminants have focused on the rumen and the small intestine, but the molecular mechanisms underlying sheep large intestine metabolism remain poorly understood. To identify genes related to intestinal metabolism and to reveal molecular regulation mechanisms, we sequenced and compared the transcriptomes of mucosal epithelial tissues among the cecum, proximal colon and duodenum. A total of 4,221 transcripts from 3,254 genes were identified as differentially expressed transcripts. Between the large intestine and duodenum, differentially expressed transcripts were found to be significantly enriched in 6 metabolism-related pathways, among which PPAR signaling was identified as a key pathway. Three genes, CPT1A, LPL and PCK1, were identified as higher expression hub genes in the large intestine. Between the cecum and colon, differentially expressed transcripts were significantly enriched in 5 lipid metabolism related pathways, and CEPT1 and MBOAT1 were identified as hub genes. This study provides important information regarding the molecular mechanisms of intestinal metabolism in sheep and may provide a basis for further study.

New insights into uremia-induced alterations in metabolic pathways.

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Rhee, Eugene P; Thadhani, Ravi

2011-11-01

This article summarizes recent studies on uremia-induced alterations in metabolism, with particular emphasis on the application of emerging metabolomics technologies. The plasma metabolome is estimated to include more than 4000 distinct metabolites. Because these metabolites can vary dramatically in size and polarity and are distributed across several orders of magnitude in relative abundance, no single analytical method is capable of comprehensive metabolomic profiling. Instead, a variety of analytical techniques, including targeted and nontargeted liquid chromatography-mass spectrometry, have been employed for metabolomic analysis of human plasma. Recent efforts to apply this technology to study uremia have reinforced the common view that end-stage renal disease is a state of generalized small molecule excess. However, the identification of precursor depletion and downstream metabolite excess - for example, with tryptophan and downstream kynurenine metabolites, with low molecular weight triglycerides and dicarboxylic acids, and with phosphatidylcholines, choline, and trimethylamine-N-oxide - suggest that uremia may directly modulate these metabolic pathways. Metabolomic studies have also begun to expand some of these findings to individuals with chronic kidney disease and in model systems. Uremia is associated with diverse, but incompletely understood metabolic disturbances. Metabolomic approaches permit higher resolution phenotyping of these disturbances, but significant efforts will be required to understand the functional significance of select findings.

Plant metabolic modeling: achieving new insight into metabolism and metabolic engineering.

Science.gov (United States)

Baghalian, Kambiz; Hajirezaei, Mohammad-Reza; Schreiber, Falk

2014-10-01

Models are used to represent aspects of the real world for specific purposes, and mathematical models have opened up new approaches in studying the behavior and complexity of biological systems. However, modeling is often time-consuming and requires significant computational resources for data development, data analysis, and simulation. Computational modeling has been successfully applied as an aid for metabolic engineering in microorganisms. But such model-based approaches have only recently been extended to plant metabolic engineering, mainly due to greater pathway complexity in plants and their highly compartmentalized cellular structure. Recent progress in plant systems biology and bioinformatics has begun to disentangle this complexity and facilitate the creation of efficient plant metabolic models. This review highlights several aspects of plant metabolic modeling in the context of understanding, predicting and modifying complex plant metabolism. We discuss opportunities for engineering photosynthetic carbon metabolism, sucrose synthesis, and the tricarboxylic acid cycle in leaves and oil synthesis in seeds and the application of metabolic modeling to the study of plant acclimation to the environment. The aim of the review is to offer a current perspective for plant biologists without requiring specialized knowledge of bioinformatics or systems biology. © 2014 American Society of Plant Biologists. All rights reserved.

Perturbations in amino acids and metabolic pathways in osteoarthritis patients determined by targeted metabolomics analysis.

Science.gov (United States)

Chen, Rui; Han, Su; Liu, Xuefeng; Wang, Kunpeng; Zhou, Yong; Yang, Chundong; Zhang, Xi

2018-05-15

Osteoarthritis (OA) is a degenerative synovial joint disease affecting people worldwide. However, the exact pathogenesis of OA remains unclear. Metabolomics analysis was performed to obtain insight into possible pathogenic mechanisms and diagnostic biomarkers of OA. Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-TQ-MS), followed by multivariate statistical analysis, was used to determine the serum amino acid profiles of 32 OA patients and 35 healthy controls. Variable importance for project values and Student's t-test were used to determine the metabolic abnormalities in OA. Another 30 OA patients were used as independent samples to validate the alterations in amino acids. MetaboAnalyst was used to identify the key amino acid pathways and construct metabolic networks describing their relationships. A total of 25 amino acids and four biogenic amines were detected by UPLC-TQ-MS. Differences in amino acid profiles were found between the healthy controls and OA patients. Alanine, γ-aminobutyric acid and 4-hydroxy-l-proline were important biomarkers distinguishing OA patients from healthy controls. The metabolic pathways with the most significant effects were involved in metabolism of alanine, aspartate, glutamate, arginine and proline. The results of this study improve understanding of the amino acid metabolic abnormalities and pathogenic mechanisms of OA at the molecular level. The metabolic perturbations may be important for the diagnosis and prevention of OA. Copyright © 2018 Elsevier B.V. All rights reserved.

Metabolite damage and repair in metabolic engineering design

Energy Technology Data Exchange (ETDEWEB)

Sun, Jiayi; Jeffryes, James G.; Henry, Christopher S.; Bruner, Steven D.; Hanson, Andrew D.

2017-11-01

The necessarily sharp focus of metabolic engineering and metabolic synthetic biology on pathways and their fluxes has tended to divert attention from the damaging enzymatic and chemical side-reactions that pathway metabolites can undergo. Although historically overlooked and underappreciated, such metabolite damage reactions are now known to occur throughout metabolism and to generate (formerly enigmatic) peaks detected in metabolomics datasets. It is also now known that metabolite damage is often countered by dedicated repair enzymes that undo or prevent it. Metabolite damage and repair are highly relevant to engineered pathway design: metabolite damage reactions can reduce flux rates and product yields, and repair enzymes can provide robust, host-independent solutions. Herein, after introducing the core principles of metabolite damage and repair, we use case histories to document how damage and repair processes affect efficient operation of engineered pathways - particularly those that are heterologous, non-natural, or cell-free. We then review how metabolite damage reactions can be predicted, how repair reactions can be prospected, and how metabolite damage and repair can be built into genome-scale metabolic models. Lastly, we propose a versatile 'plug and play' set of well-characterized metabolite repair enzymes to solve metabolite damage problems known or likely to occur in metabolic engineering and synthetic biology projects.

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

Directory of Open Access Journals (Sweden)

Margrit Urbanek

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

Metabolite damage and repair in metabolic engineering design.

Science.gov (United States)

Sun, Jiayi; Jeffryes, James G; Henry, Christopher S; Bruner, Steven D; Hanson, Andrew D

2017-11-01

The necessarily sharp focus of metabolic engineering and metabolic synthetic biology on pathways and their fluxes has tended to divert attention from the damaging enzymatic and chemical side-reactions that pathway metabolites can undergo. Although historically overlooked and underappreciated, such metabolite damage reactions are now known to occur throughout metabolism and to generate (formerly enigmatic) peaks detected in metabolomics datasets. It is also now known that metabolite damage is often countered by dedicated repair enzymes that undo or prevent it. Metabolite damage and repair are highly relevant to engineered pathway design: metabolite damage reactions can reduce flux rates and product yields, and repair enzymes can provide robust, host-independent solutions. Herein, after introducing the core principles of metabolite damage and repair, we use case histories to document how damage and repair processes affect efficient operation of engineered pathways - particularly those that are heterologous, non-natural, or cell-free. We then review how metabolite damage reactions can be predicted, how repair reactions can be prospected, and how metabolite damage and repair can be built into genome-scale metabolic models. Lastly, we propose a versatile 'plug and play' set of well-characterized metabolite repair enzymes to solve metabolite damage problems known or likely to occur in metabolic engineering and synthetic biology projects. Copyright © 2017 International Metabolic Engineering Society. All rights reserved.

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

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Kim, Woonsu; Park, Hyesun; Seo, Seongwon

2016-01-01

The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle. PMID

Metabolic cytometry: capillary electrophoresis with two-color fluorescence detection for the simultaneous study of two glycosphingolipid metabolic pathways in single primary neurons.

Science.gov (United States)

Essaka, David C; Prendergast, Jillian; Keithley, Richard B; Palcic, Monica M; Hindsgaul, Ole; Schnaar, Ronald L; Dovichi, Norman J

2012-03-20

Metabolic cytometry is a form of chemical cytometry wherein metabolic cascades are monitored in single cells. We report the first example of metabolic cytometry where two different metabolic pathways are simultaneously monitored. Glycolipid catabolism in primary rat cerebella neurons was probed by incubation with tetramethylrhodamine-labeled GM1 (GM1-TMR). Simultaneously, both catabolism and anabolism were probed by coincubation with BODIPY-FL labeled LacCer (LacCer-BODIPY-FL). In a metabolic cytometry experiment, single cells were incubated with substrate, washed, aspirated into a capillary, and lysed. The components were separated by capillary electrophoresis equipped with a two-spectral channel laser-induced fluorescence detector. One channel monitored fluorescence generated by the metabolic products produced from GM1-TMR and the other monitored the metabolic products produced from LacCer-BODIPY-FL. The metabolic products were identified by comparison with the mobility of a set of standards. The detection system produced at least 6 orders of magnitude dynamic range in each spectral channel with negligible spectral crosstalk. Detection limits were 1 zmol for BODIPY-FL and 500 ymol for tetramethylrhodamine standard solutions.

A board game to assist pharmacy students in learning metabolic pathways.

Science.gov (United States)

Rose, Tyler M

2011-11-10

To develop and evaluate a board game designed to increase students' enjoyment of learning metabolic pathways; their familiarity with pathway reactions, intermediates, and regulation; and, their understanding of how pathways relate to one another and to selected biological conditions. The board game, entitled Race to Glucose, was created as a team activity for first-year pharmacy students in the biochemistry curriculum. A majority of respondents agreed that the game was helpful for learning regulation, intermediates, and interpathway relationships but not for learning reactions, formation of energetic molecules, or relationships, to biological conditions. There was a significant increase in students' scores on game-related examination questions (68.8% pretest vs. 81.3% posttest), but the improvement was no greater than that for examination questions not related to the game (12.5% vs. 10.9%). First-year pharmacy students considered Race to Glucose to be an enjoyable and helpful tool for learning intermediates, regulation, and interpathway relationships.

A geographically-diverse collection of 418 human gut microbiome pathway genome databases

KAUST Repository

Hahn, Aria S.

2017-04-11

Advances in high-throughput sequencing are reshaping how we perceive microbial communities inhabiting the human body, with implications for therapeutic interventions. Several large-scale datasets derived from hundreds of human microbiome samples sourced from multiple studies are now publicly available. However, idiosyncratic data processing methods between studies introduce systematic differences that confound comparative analyses. To overcome these challenges, we developed GutCyc, a compendium of environmental pathway genome databases (ePGDBs) constructed from 418 assembled human microbiome datasets using MetaPathways, enabling reproducible functional metagenomic annotation. We also generated metabolic network reconstructions for each metagenome using the Pathway Tools software, empowering researchers and clinicians interested in visualizing and interpreting metabolic pathways encoded by the human gut microbiome. For the first time, GutCyc provides consistent annotations and metabolic pathway predictions, making possible comparative community analyses between health and disease states in inflammatory bowel disease, Crohn’s disease, and type 2 diabetes. GutCyc data products are searchable online, or may be downloaded and explored locally using MetaPathways and Pathway Tools.

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

Directory of Open Access Journals (Sweden)

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.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-01-20

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

Enhanced volatile fatty acids production from anaerobic fermentation of food waste: A mini-review focusing on acidogenic metabolic pathways.

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Zhou, Miaomiao; Yan, Binghua; Wong, Jonathan W C; Zhang, Yang

2018-01-01

Recently, efficient disposal of food waste (FW) with potential resource recovery has attracted great attentions. Due to its easily biodegradable nature, rich nutrient availability and high moisture content, FW is regarded as favorable substrate for anaerobic digestion (AD). Both waste disposal and energy recovery can be fulfilled during AD of FW. Volatile fatty acids (VFAs) which are the products of the first-two stages of AD, are widely applied in chemical industry as platform chemicals recently. Concentration and distribution of VFAs is the result of acidogenic metabolic pathways, which can be affected by the micro-environment (e.g. pH) in the digester. Hence, the clear elucidation of the acidogenic metabolic pathways is essential for optimization of acidogenic process for efficient product recovery. This review summarizes major acidogenic metabolic pathways and regulating strategies for enhancing VFAs recovery during acidogenic fermentation of FW. Copyright © 2017 Elsevier Ltd. All rights reserved.

Accuracy of algorithms to predict accessory pathway location in children with Wolff-Parkinson-White syndrome.

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Wren, Christopher; Vogel, Melanie; Lord, Stephen; Abrams, Dominic; Bourke, John; Rees, Philip; Rosenthal, Eric

2012-02-01

The aim of this study was to examine the accuracy in predicting pathway location in children with Wolff-Parkinson-White syndrome for each of seven published algorithms. ECGs from 100 consecutive children with Wolff-Parkinson-White syndrome undergoing electrophysiological study were analysed by six investigators using seven published algorithms, six of which had been developed in adult patients. Accuracy and concordance of predictions were adjusted for the number of pathway locations. Accessory pathways were left-sided in 49, septal in 20 and right-sided in 31 children. Overall accuracy of prediction was 30-49% for the exact location and 61-68% including adjacent locations. Concordance between investigators varied between 41% and 86%. No algorithm was better at predicting septal pathways (accuracy 5-35%, improving to 40-78% including adjacent locations), but one was significantly worse. Predictive accuracy was 24-53% for the exact location of right-sided pathways (50-71% including adjacent locations) and 32-55% for the exact location of left-sided pathways (58-73% including adjacent locations). All algorithms were less accurate in our hands than in other authors' own assessment. None performed well in identifying midseptal or right anteroseptal accessory pathway locations.

Pathway analysis of gene signatures predicting metastasis of node-negative primary breast cancer

International Nuclear Information System (INIS)

Yu, Jack X; Sieuwerts, Anieta M; Zhang, Yi; Martens, John WM; Smid, Marcel; Klijn, Jan GM; Wang, Yixin; Foekens, John A

2007-01-01

Published prognostic gene signatures in breast cancer have few genes in common. Here we provide a rationale for this observation by studying the prognostic power and the underlying biological pathways of different gene signatures. Gene signatures to predict the development of metastases in estrogen receptor-positive and estrogen receptor-negative tumors were identified using 500 re-sampled training sets and mapping to Gene Ontology Biological Process to identify over-represented pathways. The Global Test program confirmed that gene expression profilings in the common pathways were associated with the metastasis of the patients. The apoptotic pathway and cell division, or cell growth regulation and G-protein coupled receptor signal transduction, were most significantly associated with the metastatic capability of estrogen receptor-positive or estrogen-negative tumors, respectively. A gene signature derived of the common pathways predicted metastasis in an independent cohort. Mapping of the pathways represented by different published prognostic signatures showed that they share 53% of the identified pathways. We show that divergent gene sets classifying patients for the same clinical endpoint represent similar biological processes and that pathway-derived signatures can be used to predict prognosis. Furthermore, our study reveals that the underlying biology related to aggressiveness of estrogen receptor subgroups of breast cancer is quite different

Interrelationship of canonical and non-canonical Wnt signalling pathways in chronic metabolic diseases.

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Ackers, Ian; Malgor, Ramiro

2018-01-01

Chronic diseases account for approximately 45% of all deaths in developed countries and are particularly prevalent in countries with the most sophisticated and robust public health systems. Chronic metabolic diseases, specifically lifestyle-related diseases pertaining to diet and exercise, continue to be difficult to treat clinically. The most prevalent of these chronic metabolic diseases include obesity, diabetes, non-alcoholic fatty liver disease, chronic kidney disease and cardiovascular disease and will be the focus of this review. Wnt proteins are highly conserved glycoproteins best known for their role in development and homeostasis of tissues. Given the importance of Wnt signalling in homeostasis, aberrant Wnt signalling likely regulates metabolic processes and may contribute to the development of chronic metabolic diseases. Expression of Wnt proteins and dysfunctional Wnt signalling has been reported in multiple chronic diseases. It is interesting to speculate about an interrelationship between the Wnt signalling pathways as a potential pathological mechanism in chronic metabolic diseases. The aim of this review is to summarize reported findings on the contrasting roles of Wnt signalling in lifestyle-related chronic metabolic diseases; specifically, the contribution of Wnt signalling to lipid accumulation, fibrosis and chronic low-grade inflammation.

Role of insulin, adipocyte hormones, and nutrient-sensing pathways in regulating fuel metabolism and energy homeostasis: a nutritional perspective of diabetes, obesity, and cancer.

Science.gov (United States)

Marshall, Stephen

2006-08-01

Traditionally, nutrients such as glucose and amino acids have been viewed as substrates for the generation of high-energy molecules and as precursors for the biosynthesis of macromolecules. However, it is now apparent that nutrients also function as signaling molecules in functionally diverse signal transduction pathways. Glucose and amino acids trigger signaling cascades that regulate various aspects of fuel and energy metabolism and control the growth, proliferation, and survival of cells. Here, we provide a functional and regulatory overview of three well-established nutrient signaling pathways-the hexosamine signaling pathway, the mTOR (mammalian target of rapamycin) signaling pathway, and the adenosine monophosphate-activated protein kinase (AMPK) signaling pathway. Nutrient signaling pathways are interconnected, coupled to insulin signaling, and linked to the release of metabolic hormones from adipose tissue. Thus, nutrient signaling pathways do not function in isolation. Rather, they appear to serve as components of a larger "metabolic regulatory network" that controls fuel and energy metabolism (at the cell, tissue, and whole-body levels) and links nutrient availability with cell growth and proliferation. Understanding the diverse roles of nutrients and delineating nutrient signaling pathways should facilitate drug discovery research and the search for novel therapeutic compounds to prevent and treat various human diseases such as diabetes, obesity, and cancer.

Clinical Relevance of Kynurenine Pathway in HIV/AIDS : An Immune Checkpoint at the Crossroads of Metabolism and Inflammation

NARCIS (Netherlands)

Routy, Jean-Pierre; Mehraj, Vikram; Vyboh, Kishanda; Cao, Wei; Kema, Ido; Jenabian, Mohammad-Ali

2015-01-01

Tryptophan degradation along the kynurenine pathway is associated with a wide variety of pathophysiological processes, of which tumor tolerance and immune dysfunction in several chronic viral infections including HIV are well known. The kynurenine pathway is at the crossroads of metabolism and

Consortium analysis of gene and gene–folate interactions in purine and pyrimidine metabolism pathways with ovarian carcinoma risk

DEFF Research Database (Denmark)

Kelemen, Linda E; Terry, Kathryn L; Goodman, Marc T

2014-01-01

SCOPE: We reevaluated previously reported associations between variants in pathways of one-carbon (1-C) (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake. METHODS AND RESULTS: Odds rat...

Prioritizing Candidate Disease Metabolites Based on Global Functional Relationships between Metabolites in the Context of Metabolic Pathways

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Yang, Haixiu; Xu, Yanjun; Han, Junwei; Li, Jing; Su, Fei; Zhang, Yunpeng; Zhang, Chunlong; Li, Dongguo; Li, Xia

2014-01-01

Identification of key metabolites for complex diseases is a challenging task in today's medicine and biology. A special disease is usually caused by the alteration of a series of functional related metabolites having a global influence on the metabolic network. Moreover, the metabolites in the same metabolic pathway are often associated with the same or similar disease. Based on these functional relationships between metabolites in the context of metabolic pathways, we here presented a pathway-based random walk method called PROFANCY for prioritization of candidate disease metabolites. Our strategy not only takes advantage of the global functional relationships between metabolites but also sufficiently exploits the functionally modular nature of metabolic networks. Our approach proved successful in prioritizing known metabolites for 71 diseases with an AUC value of 0.895. We also assessed the performance of PROFANCY on 16 disease classes and found that 4 classes achieved an AUC value over 0.95. To investigate the robustness of the PROFANCY, we repeated all the analyses in two metabolic networks and obtained similar results. Then we applied our approach to Alzheimer's disease (AD) and found that a top ranked candidate was potentially related to AD but had not been reported previously. Furthermore, our method was applicable to prioritize the metabolites from metabolomic profiles of prostate cancer. The PROFANCY could identify prostate cancer related-metabolites that are supported by literatures but not considered to be significantly differential by traditional differential analysis. We also developed a freely accessible web-based and R-based tool at http://bioinfo.hrbmu.edu.cn/PROFANCY. PMID:25153931

Metabolic Impact on the Hypothalamic Kisspeptin-Kiss1r Signaling Pathway

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Fazal Wahab

2018-03-01

Full Text Available A large body of data has established the hypothalamic kisspeptin (KP and its receptor, KISS1R, as major players in the activation of the neuroendocrine reproductive axis at the time of puberty and maintenance of reproductive capacity in the adult. Due to its strategic location, this ligand-receptor pair acts as an integrator of cues from gonadal steroids as well as of circadian and seasonal variation-related information on the reproductive axis. Besides these cues, the activity of the hypothalamic KP signaling is very sensitive to the current metabolic status of the body. In conditions of energy imbalance, either positive or negative, a number of alterations in the hypothalamic KP signaling pathway have been documented in different mammalian models including nonhuman primates and human. Deficiency of metabolic fuels during fasting causes a marked reduction of Kiss1 gene transcript levels in the hypothalamus and, hence, decreases the output of KP-containing neurons. Food intake or exogenous supply of metabolic cues, such as leptin, reverses metabolic insufficiency-related changes in the hypothalamic KP signaling. Likewise, alterations in Kiss1 expression have also been reported in other situations of energy imbalance like diabetes and obesity. Information related to the body’s current metabolic status reaches to KP neurons both directly as well as indirectly via a complex network of other neurons. In this review article, we have provided an updated summary of the available literature on the regulation of the hypothalamic KP-Kiss1r signaling by metabolic cues. In particular, the potential mechanisms of metabolic impact on the hypothalamic KP-Kiss1r signaling, in light of available evidence, are discussed.

Redox balance is key to explaining full vs. partial switching to low-yield metabolism

Directory of Open Access Journals (Sweden)

van Hoek Milan JA

2012-03-01

Full Text Available Abstract Background Low-yield metabolism is a puzzling phenomenon in many unicellular and multicellular organisms. In abundance of glucose, many cells use a highly wasteful fermentation pathway despite the availability of a high-yield pathway, producing many ATP molecules per glucose, e.g., oxidative phosphorylation. Some of these organisms, including the lactic acid bacterium Lactococcus lactis, downregulate their high-yield pathway in favor of the low-yield pathway. Other organisms, including Escherichia coli do not reduce the flux through the high-yield pathway, employing the low-yield pathway in parallel with a fully active high-yield pathway. For what reasons do some species use the high-yield and low-yield pathways concurrently and what makes others downregulate the high-yield pathway? A classic rationale for metabolic fermentation is overflow metabolism. Because the throughput of metabolic pathways is limited, influx of glucose exceeding the pathway's throughput capacity is thought to be redirected into an alternative, low-yield pathway. This overflow metabolism rationale suggests that cells would only use fermentation once the high-yield pathway runs at maximum rate, but it cannot explain why cells would decrease the flux through the high-yield pathway. Results Using flux balance analysis with molecular crowding (FBAwMC, a recent extension to flux balance analysis (FBA that assumes that the total flux through the metabolic network is limited, we investigate the differences between Saccharomyces cerevisiae and L. lactis that downregulate the high-yield pathway at increasing glucose concentrations, and E. coli, which keeps the high-yield pathway functioning at maximal rate. FBAwMC correctly predicts the metabolic switching mode in these three organisms, suggesting that metabolic network architecture is responsible for differences in metabolic switching mode. Based on our analysis, we expect gradual, "overflow-like" switching behavior in

Deep Proteomics of Mouse Skeletal Muscle Enables Quantitation of Protein Isoforms, Metabolic Pathways, and Transcription Factors*

Science.gov (United States)

Deshmukh, Atul S.; Murgia, Marta; Nagaraj, Nagarjuna; Treebak, Jonas T.; Cox, Jürgen; Mann, Matthias

2015-01-01

Skeletal muscle constitutes 40% of individual body mass and plays vital roles in locomotion and whole-body metabolism. Proteomics of skeletal muscle is challenging because of highly abundant contractile proteins that interfere with detection of regulatory proteins. Using a state-of-the art MS workflow and a strategy to map identifications from the C2C12 cell line model to tissues, we identified a total of 10,218 proteins, including skeletal muscle specific transcription factors like myod1 and myogenin and circadian clock proteins. We obtain absolute abundances for proteins expressed in a muscle cell line and skeletal muscle, which should serve as a valuable resource. Quantitation of protein isoforms of glucose uptake signaling pathways and in glucose and lipid metabolic pathways provides a detailed metabolic map of the cell line compared with tissue. This revealed unexpectedly complex regulation of AMP-activated protein kinase and insulin signaling in muscle tissue at the level of enzyme isoforms. PMID:25616865

Novel pathway of NAD metabolism in Aspergillus niger

International Nuclear Information System (INIS)

Kuwahara, Masaaki

1977-01-01

New steps of NAD metabolism were shown in Aspergillus niger. Radioactive nicotinic acid and nicotinamide were incorporated into nicotinamide ribose diphosphate ribose (NAmRDPR), which had been isolated from the culture filtrate. The enzyme preparation of the mold degraded NAmRDPR to form nicotinamide mononucleotide and nicotinic acid under the neutral and alkaline conditions. In the acid extracts of the mycelia grown on the radioactive precursors, high level of radioactivity was detected on NAD. The experimental results showed that the Preiss-Handler pathway and the NAD cycling system function in the NAD biosynthesis in A. niger. A part of the radioactive precursors was also incorporated into nicotinic acid ribonucleoside, which was thought to be formed from nicotinic acid mononucleotide. (auth.)

Characterization of glucose‐related metabolic pathways in differentiated rat oligodendrocyte lineage cells

Science.gov (United States)

Amaral, Ana I.; Hadera, Mussie G.; Tavares, Joana M.

2015-01-01

Although oligodendrocytes constitute a significant proportion of cells in the central nervous system (CNS), little is known about their intermediary metabolism. We have, therefore, characterized metabolic functions of primary oligodendrocyte precursor cell cultures at late stages of differentiation using isotope‐labelled metabolites. We report that differentiated oligodendrocyte lineage cells avidly metabolize glucose in the cytosol and pyruvate derived from glucose in the mitochondria. The labelling patterns of metabolites obtained after incubation with [1,2‐13C]glucose demonstrated that the pentose phosphate pathway (PPP) is highly active in oligodendrocytes (approximately 10% of glucose is metabolized via the PPP as indicated by labelling patterns in phosphoenolpyruvate). Mass spectrometry and magnetic resonance spectroscopy analyses of metabolites after incubation of cells with [1‐13C]lactate or [1,2‐13C]glucose, respectively, demonstrated that anaplerotic pyruvate carboxylation, which was thought to be exclusive to astrocytes, is also active in oligodendrocytes. Using [1,2‐13C]acetate, we show that oligodendrocytes convert acetate into acetyl CoA which is metabolized in the tricarboxylic acid cycle. Analysis of labelling patterns of alanine after incubation of cells with [1,2‐13C]acetate and [1,2‐13C]glucose showed catabolic oxidation of malate or oxaloacetate. In conclusion, we report that oligodendrocyte lineage cells at late differentiation stages are metabolically highly active cells that are likely to contribute considerably to the metabolic activity of the CNS. GLIA 2016;64:21–34 PMID:26352325

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

Science.gov (United States)

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

2016-10-01

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

Stress, autonomic imbalance, and the prediction of metabolic risk: A model and a proposal for research.

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Wulsin, Lawson; Herman, James; Thayer, Julian F

2018-03-01

Devising novel prevention strategies for metabolic disorders will depend in part on the careful elucidation of the common pathways for developing metabolic risks. The neurovisceral integration model has proposed that autonomic imbalance plays an important role in the pathway from acute and chronic stress to cardiovascular disease. Though generally overlooked by clinicians, autonomic imbalance (sympathetic overactivity and/or parasympathetic underactivity) can be measured and modified by methods that are available in primary care. This review applies the neurovisceral integration concept to the clinical setting by proposing that autonomic imbalance plays a primary role in the development of metabolic risks. We present a testable model, a systematic review of the evidence in support of autonomic imbalance as a predictor for metabolic risks, and specific approaches to test this model as a guide to future research on the role of stress in metabolic disorders. We propose that autonomic imbalance deserves consideration by researchers, clinicians, and policymakers as a target for early interventions to prevent metabolic disorders. Published by Elsevier Ltd.

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

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Kumari Sonal Choudhary

2016-06-01

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

EGFR Signal-Network Reconstruction Demonstrates Metabolic Crosstalk in EMT.

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

2016-06-01

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

Alternative Cell Death Pathways and Cell Metabolism

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Simone Fulda

2013-01-01

Full Text Available While necroptosis has for long been viewed as an accidental mode of cell death triggered by physical or chemical damage, it has become clear over the last years that necroptosis can also represent a programmed form of cell death in mammalian cells. Key discoveries in the field of cell death research, including the identification of critical components of the necroptotic machinery, led to a revised concept of cell death signaling programs. Several regulatory check and balances are in place in order to ensure that necroptosis is tightly controlled according to environmental cues and cellular needs. This network of regulatory mechanisms includes metabolic pathways, especially those linked to mitochondrial signaling events. A better understanding of these signal transduction mechanisms will likely contribute to open new avenues to exploit our knowledge on the regulation of necroptosis signaling for therapeutic application in the treatment of human diseases.

Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation

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Dall’Olio Giovanni

2012-06-01

Full Text Available Abstract Background Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment and innate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1. Conclusions These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show

Two Distinct Pathways for Metabolism of Theophylline and Caffeine Are Coexpressed in Pseudomonas putida CBB5▿ †

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Yu, Chi Li; Louie, Tai Man; Summers, Ryan; Kale, Yogesh; Gopishetty, Sridhar; Subramanian, Mani

2009-01-01

Pseudomonas putida CBB5 was isolated from soil by enrichment on caffeine. This strain used not only caffeine, theobromine, paraxanthine, and 7-methylxanthine as sole carbon and nitrogen sources but also theophylline and 3-methylxanthine. Analyses of metabolites in spent media and resting cell suspensions confirmed that CBB5 initially N demethylated theophylline via a hitherto unreported pathway to 1- and 3-methylxanthines. NAD(P)H-dependent conversion of theophylline to 1- and 3-methylxanthines was also detected in the crude cell extracts of theophylline-grown CBB5. 1-Methylxanthine and 3-methylxanthine were subsequently N demethylated to xanthine. CBB5 also oxidized theophylline and 1- and 3-methylxanthines to 1,3-dimethyluric acid and 1- and 3-methyluric acids, respectively. However, these methyluric acids were not metabolized further. A broad-substrate-range xanthine-oxidizing enzyme was responsible for the formation of these methyluric acids. In contrast, CBB5 metabolized caffeine to theobromine (major metabolite) and paraxanthine (minor metabolite). These dimethylxanthines were further N demethylated to xanthine via 7-methylxanthine. Theobromine-, paraxanthine-, and 7-methylxanthine-grown cells also metabolized all of the methylxanthines mentioned above via the same pathway. Thus, the theophylline and caffeine N-demethylation pathways converged at xanthine via different methylxanthine intermediates. Xanthine was eventually oxidized to uric acid. Enzymes involved in theophylline and caffeine degradation were coexpressed when CBB5 was grown on theophylline or on caffeine or its metabolites. However, 3-methylxanthine-grown CBB5 cells did not metabolize caffeine, whereas theophylline was metabolized at much reduced levels to only methyluric acids. To our knowledge, this is the first report of theophylline N demethylation and coexpression of distinct pathways for caffeine and theophylline degradation in bacteria. PMID:19447909

PROXIMAL: a method for Prediction of Xenobiotic Metabolism.

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Yousofshahi, Mona; Manteiga, Sara; Wu, Charmian; Lee, Kyongbum; Hassoun, Soha

2015-12-22

Contamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved. PROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical's substructures. We evaluate the accuracy of PROXIMAL's predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools. PROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation.

Regional cerebral glucose metabolic changes in oculopalatal myoclonus: implication for neural pathways, underlying the disorder

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Cho, Sang Soo; Moon, So Young; Kim, Ji Soo; Kim, Sang Eun [College of Medicine, Seoul National University, Seoul (Korea, Republic of)

2004-07-01

Palatal myoclonus (PM) is characterized by rhythmic involuntary jerky movements of the soft palate of the throat. When associated with eye movements, it is called oculopalatal myoclonus (OPM). Ordinary PM is characterized by hypertrophic olivary degeneration, a trans-synaptic degeneration following loss of neuronal input to the inferior olivary nucleus due to an interruption of the Guillain-Mollaret triangle usually by a hemorrhage. However, the neural pathways underlying the disorder are uncertain. In an attempt to understand the pathologic neural pathways, we examined the metabolic correlates of this tremulous condition. Brain FDG PET scans were acquired in 8 patients with OPM (age, 49.9{+-}4.6 y: all males: 7 with pontine hemorrhage, 1 with diffuse brainstem infarction) and age-matched 50 healthy males (age, 50.7{+-} 9.0) and the regional glucose metabolism compared using SPM99. For group analysis, the hemispheres containing lesions were assigned to the right side of the brain. Patients with OPM had significant hypometabolism in the ipsilateral (to the lesion) brainstem and superior temporal and parahippocampal gyri (P < 0.05 corrected, k = 100). By contrast, there was significant hypermetabolism in the contralateral middle and inferior temporal gyri, thalamus, middle frontal gyrus and precuneus (P < 0.05 corrected, k=l00). Our data demonstrate the distinct metabolic changes between several ipsilateral and contralateral brain regions (hypometabolism vs. hypermetabolism) in patients with OPM. This may provide clues for understanding the neural pathways underlying the disorder.

Regional cerebral glucose metabolic changes in oculopalatal myoclonus: implication for neural pathways, underlying the disorder

International Nuclear Information System (INIS)

Cho, Sang Soo; Moon, So Young; Kim, Ji Soo; Kim, Sang Eun

2004-01-01

Palatal myoclonus (PM) is characterized by rhythmic involuntary jerky movements of the soft palate of the throat. When associated with eye movements, it is called oculopalatal myoclonus (OPM). Ordinary PM is characterized by hypertrophic olivary degeneration, a trans-synaptic degeneration following loss of neuronal input to the inferior olivary nucleus due to an interruption of the Guillain-Mollaret triangle usually by a hemorrhage. However, the neural pathways underlying the disorder are uncertain. In an attempt to understand the pathologic neural pathways, we examined the metabolic correlates of this tremulous condition. Brain FDG PET scans were acquired in 8 patients with OPM (age, 49.9±4.6 y: all males: 7 with pontine hemorrhage, 1 with diffuse brainstem infarction) and age-matched 50 healthy males (age, 50.7± 9.0) and the regional glucose metabolism compared using SPM99. For group analysis, the hemispheres containing lesions were assigned to the right side of the brain. Patients with OPM had significant hypometabolism in the ipsilateral (to the lesion) brainstem and superior temporal and parahippocampal gyri (P < 0.05 corrected, k = 100). By contrast, there was significant hypermetabolism in the contralateral middle and inferior temporal gyri, thalamus, middle frontal gyrus and precuneus (P < 0.05 corrected, k=l00). Our data demonstrate the distinct metabolic changes between several ipsilateral and contralateral brain regions (hypometabolism vs. hypermetabolism) in patients with OPM. This may provide clues for understanding the neural pathways underlying the disorder

Induction of autophagy by ARHI (DIRAS3) alters fundamental metabolic pathways in ovarian cancer models

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Ornelas, Argentina; McCullough, Christopher R.; Lu, Zhen; Zacharias, Niki M.; Kelderhouse, Lindsay E.; Gray, Joshua; Yang, Hailing; Engel, Brian J.; Wang, Yan; Mao, Weiqun; Sutton, Margie N.; Bhattacharya, Pratip K.; Bast, Robert C. Jr.; Millward, Steven W.

2016-01-01

Autophagy is a bulk catabolic process that modulates tumorigenesis, therapeutic resistance, and dormancy. The tumor suppressor ARHI (DIRAS3) is a potent inducer of autophagy and its expression results in necroptotic cell death in vitro and tumor dormancy in vivo. ARHI is down-regulated or lost in over 60 % of primary ovarian tumors yet is dramatically up-regulated in metastatic disease. The metabolic changes that occur during ARHI induction and their role in modulating death and dormancy are unknown. We employed Nuclear Magnetic Resonance (NMR)-based metabolomic strategies to characterize changes in key metabolic pathways in both cell culture and xenograft models of ARHI expression and autophagy. These pathways were further interrogated by cell-based immunofluorescence imaging, tracer uptake studies, targeted metabolic inhibition, and in vivo PET/CT imaging. Induction of ARHI in cell culture models resulted in an autophagy-dependent increase in lactate production along with increased glucose uptake and enhanced sensitivity to glycolytic inhibitors. Increased uptake of glutamine was also dependent on autophagy and dramatically sensitized cultured ARHI-expressing ovarian cancer cell lines to glutaminase inhibition. Induction of ARHI resulted in a reduction in mitochondrial respiration, decreased mitochondrial membrane potential, and decreased Tom20 staining suggesting an ARHI-dependent loss of mitochondrial function. ARHI induction in mouse xenograft models resulted in an increase in free amino acids, a transient increase in [ 18 F]-FDG uptake, and significantly altered choline metabolism. ARHI expression has previously been shown to trigger autophagy-associated necroptosis in cell culture. In this study, we have demonstrated that ARHI expression results in decreased cellular ATP/ADP, increased oxidative stress, and decreased mitochondrial function. While this bioenergetic shock is consistent with programmed necrosis, our data indicates that the accompanying up

Metabolic investigation of host/pathogen interaction using MS2-infected Escherichia coli

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Jain Rishi

2009-12-01

Full Text Available Abstract Background RNA viruses are responsible for a variety of illnesses among people, including but not limited to the common cold, the flu, HIV, and ebola. Developing new drugs and new strategies for treating diseases caused by these viruses can be an expensive and time-consuming process. Mathematical modeling may be used to elucidate host-pathogen interactions and highlight potential targets for drug development, as well providing the basis for optimizing patient treatment strategies. The purpose of this work was to determine whether a genome-scale modeling approach could be used to understand how metabolism is impacted by the host-pathogen interaction during a viral infection. Escherichia coli/MS2 was used as the host-pathogen model system as MS2 is easy to work with, harmless to humans, but shares many features with eukaryotic viruses. In addition, the genome-scale metabolic model of E. coli is the most comprehensive model at this time. Results Employing a metabolic modeling strategy known as "flux balance analysis" coupled with experimental studies, we were able to predict how viral infection would alter bacterial metabolism. Based on our simulations, we predicted that cell growth and biosynthesis of the cell wall would be halted. Furthermore, we predicted a substantial increase in metabolic activity of the pentose phosphate pathway as a means to enhance viral biosynthesis, while a break down in the citric acid cycle was predicted. Also, no changes were predicted in the glycolytic pathway. Conclusions Through our approach, we have developed a technique of modeling virus-infected host metabolism and have investigated the metabolic effects of viral infection. These studies may provide insight into how to design better drugs. They also illustrate the potential of extending such metabolic analysis to higher order organisms, including humans.

PPAR ligands improve impaired metabolic pathways in fetal hearts of diabetic rats.

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Kurtz, Melisa; Capobianco, Evangelina; Martinez, Nora; Roberti, Sabrina Lorena; Arany, Edith; Jawerbaum, Alicia

2014-10-01

In maternal diabetes, the fetal heart can be structurally and functionally affected. Maternal diets enriched in certain unsaturated fatty acids can activate the nuclear receptors peroxisome proliferator-activated receptors (PPARs) and regulate metabolic and anti-inflammatory pathways during development. Our aim was to investigate whether PPARα expression, lipid metabolism, lipoperoxidation, and nitric oxide (NO) production are altered in the fetal hearts of diabetic rats, and to analyze the putative effects of in vivo PPAR activation on these parameters. We found decreased PPARα expression in the hearts of male but not female fetuses of diabetic rats when compared with controls. Fetal treatments with the PPARα ligand leukotriene B4 upregulated the expression of PPARα and target genes involved in fatty acid oxidation in the fetal hearts. Increased concentrations of triglycerides, cholesterol, and phospholipids were found in the hearts of fetuses of diabetic rats. Maternal treatments with diets supplemented with 6% olive oil or 6% safflower oil, enriched in unsaturated fatty acids that can activate PPARs, led to few changes in lipid concentrations, but up-regulated PPARα expression in fetal hearts. NO production, which was increased in the hearts of male and female fetuses in the diabetic group, and lipoperoxidation, which was increased in the hearts of male fetuses in the diabetic group, was reduced by the maternal treatments supplemented with safflower oil. In conclusion, impaired PPARα expression, altered lipid metabolism, and increased oxidative and nitridergic pathways were evidenced in hearts of fetuses of diabetic rats and were regulated in a gender-dependent manner by treatments enriched with PPAR ligands. © 2014 Society for Endocrinology.

Identifying developmental toxicity pathways for a subset of ToxCast chemicals using human embryonic stem cells and metabolomics

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Kleinstreuer, N.C., E-mail: kleinstreuer.nicole@epa.gov [NCCT, US EPA, RTP, NC 27711 (United States); Smith, A.M.; West, P.R.; Conard, K.R.; Fontaine, B.R. [Stemina Biomarker Discovery, Inc., Madison, WI 53719 (United States); Weir-Hauptman, A.M. [Covance, Inc., Madison, WI 53704 (United States); Palmer, J.A. [Stemina Biomarker Discovery, Inc., Madison, WI 53719 (United States); Knudsen, T.B.; Dix, D.J. [NCCT, US EPA, RTP, NC 27711 (United States); Donley, E.L.R. [Stemina Biomarker Discovery, Inc., Madison, WI 53719 (United States); Cezar, G.G. [Stemina Biomarker Discovery, Inc., Madison, WI 53719 (United States); University of Wisconsin-Madison, Madison, WI 53706 (United States)

2011-11-15

Metabolomics analysis was performed on the supernatant of human embryonic stem (hES) cell cultures exposed to a blinded subset of 11 chemicals selected from the chemical library of EPA's ToxCast Trade-Mark-Sign chemical screening and prioritization research project. Metabolites from hES cultures were evaluated for known and novel signatures that may be indicative of developmental toxicity. Significant fold changes in endogenous metabolites were detected for 83 putatively annotated mass features in response to the subset of ToxCast chemicals. The annotations were mapped to specific human metabolic pathways. This revealed strong effects on pathways for nicotinate and nicotinamide metabolism, pantothenate and CoA biosynthesis, glutathione metabolism, and arginine and proline metabolism pathways. Predictivity for adverse outcomes in mammalian prenatal developmental toxicity studies used ToxRefDB and other sources of information, including Stemina Biomarker Discovery's predictive DevTox Registered-Sign model trained on 23 pharmaceutical agents of known developmental toxicity and differing potency. The model initially predicted developmental toxicity from the blinded ToxCast compounds in concordance with animal data with 73% accuracy. Retraining the model with data from the unblinded test compounds at one concentration level increased the predictive accuracy for the remaining concentrations to 83%. These preliminary results on a 11-chemical subset of the ToxCast chemical library indicate that metabolomics analysis of the hES secretome provides information valuable for predictive modeling and mechanistic understanding of mammalian developmental toxicity. -- Highlights: Black-Right-Pointing-Pointer We tested 11 environmental compounds in a hESC metabolomics platform. Black-Right-Pointing-Pointer Significant changes in secreted small molecule metabolites were observed. Black-Right-Pointing-Pointer Perturbed mass features map to pathways critical for normal

Identifying developmental toxicity pathways for a subset of ToxCast chemicals using human embryonic stem cells and metabolomics

International Nuclear Information System (INIS)

Kleinstreuer, N.C.; Smith, A.M.; West, P.R.; Conard, K.R.; Fontaine, B.R.; Weir-Hauptman, A.M.; Palmer, J.A.; Knudsen, T.B.; Dix, D.J.; Donley, E.L.R.; Cezar, G.G.

2011-01-01

Metabolomics analysis was performed on the supernatant of human embryonic stem (hES) cell cultures exposed to a blinded subset of 11 chemicals selected from the chemical library of EPA's ToxCast™ chemical screening and prioritization research project. Metabolites from hES cultures were evaluated for known and novel signatures that may be indicative of developmental toxicity. Significant fold changes in endogenous metabolites were detected for 83 putatively annotated mass features in response to the subset of ToxCast chemicals. The annotations were mapped to specific human metabolic pathways. This revealed strong effects on pathways for nicotinate and nicotinamide metabolism, pantothenate and CoA biosynthesis, glutathione metabolism, and arginine and proline metabolism pathways. Predictivity for adverse outcomes in mammalian prenatal developmental toxicity studies used ToxRefDB and other sources of information, including Stemina Biomarker Discovery's predictive DevTox® model trained on 23 pharmaceutical agents of known developmental toxicity and differing potency. The model initially predicted developmental toxicity from the blinded ToxCast compounds in concordance with animal data with 73% accuracy. Retraining the model with data from the unblinded test compounds at one concentration level increased the predictive accuracy for the remaining concentrations to 83%. These preliminary results on a 11-chemical subset of the ToxCast chemical library indicate that metabolomics analysis of the hES secretome provides information valuable for predictive modeling and mechanistic understanding of mammalian developmental toxicity. -- Highlights: ► We tested 11 environmental compounds in a hESC metabolomics platform. ► Significant changes in secreted small molecule metabolites were observed. ► Perturbed mass features map to pathways critical for normal development and pregnancy. ► Arginine, proline, nicotinate, nicotinamide and glutathione pathways were affected.

Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.

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Matthew B Biggs

2017-03-01

Full Text Available Genome-scale metabolic network reconstructions (GENREs are repositories of knowledge about the metabolic processes that occur in an organism. GENREs have been used to discover and interpret metabolic functions, and to engineer novel network structures. A major barrier preventing more widespread use of GENREs, particularly to study non-model organisms, is the extensive time required to produce a high-quality GENRE. Many automated approaches have been developed which reduce this time requirement, but automatically-reconstructed draft GENREs still require curation before useful predictions can be made. We present a novel approach to the analysis of GENREs which improves the predictive capabilities of draft GENREs by representing many alternative network structures, all equally consistent with available data, and generating predictions from this ensemble. This ensemble approach is compatible with many reconstruction methods. We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA. We validate EnsembleFBA by predicting growth and gene essentiality in the model organism Pseudomonas aeruginosa UCBPP-PA14. We demonstrate how EnsembleFBA can be included in a systems biology workflow by predicting essential genes in six Streptococcus species and mapping the essential genes to small molecule ligands from DrugBank. We found that some metabolic subsystems contributed disproportionately to the set of predicted essential reactions in a way that was unique to each Streptococcus species, leading to species-specific outcomes from small molecule interactions. Through our analyses of P. aeruginosa and six Streptococci, we show that ensembles increase the quality of predictions without drastically increasing reconstruction time, thus making GENRE approaches more practical for applications which require predictions for many non-model organisms. All of our functions and accompanying example code are available in an open online repository.

The Glycerate and Phosphorylated Pathways of Serine Synthesis in Plants: The Branches of Plant Glycolysis Linking Carbon and Nitrogen Metabolism.

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Igamberdiev, Abir U; Kleczkowski, Leszek A

2018-01-01

Serine metabolism in plants has been studied mostly in relation to photorespiration where serine is formed from two molecules of glycine. However, two other pathways of serine formation operate in plants and represent the branches of glycolysis diverging at the level of 3-phosphoglyceric acid. One branch (the glycerate - serine pathway) is initiated in the cytosol and involves glycerate formation from 3-phosphoglycerate, while the other (the phosphorylated serine pathway) operates in plastids and forms phosphohydroxypyruvate as an intermediate. Serine formed in these pathways becomes a precursor of glycine, formate and glycolate accumulating in stress conditions. The pathways can be linked to GABA shunt via transamination reactions and via participation of the same reductase for both glyoxylate and succinic semialdehyde. In this review paper we present a hypothesis of the regulation of redox balance in stressed plant cells via participation of the reactions associated with glycerate and phosphorylated serine pathways. We consider these pathways as important processes linking carbon and nitrogen metabolism and maintaining cellular redox and energy levels in stress conditions.

Antimalarial drug targets in Plasmodium falciparum predicted by stage-specific metabolic network analysis

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Huthmacher Carola

2010-08-01

Full Text Available Abstract Background Despite enormous efforts to combat malaria the disease still afflicts up to half a billion people each year of which more than one million die. Currently no approved vaccine is available and resistances to antimalarials are widely spread. Hence, new antimalarial drugs are urgently needed. Results Here, we present a computational analysis of the metabolism of Plasmodium falciparum, the deadliest malaria pathogen. We assembled a compartmentalized metabolic model and predicted life cycle stage specific metabolism with the help of a flux balance approach that integrates gene expression data. Predicted metabolite exchanges between parasite and host were found to be in good accordance with experimental findings when the parasite's metabolic network was embedded into that of its host (erythrocyte. Knock-out simulations identified 307 indispensable metabolic reactions within the parasite. 35 out of 57 experimentally demonstrated essential enzymes were recovered and another 16 enzymes, if additionally the assumption was made that nutrient uptake from the host cell is limited and all reactions catalyzed by the inhibited enzyme are blocked. This predicted set of putative drug targets, shown to be enriched with true targets by a factor of at least 2.75, was further analyzed with respect to homology to human enzymes, functional similarity to therapeutic targets in other organisms and their predicted potency for prophylaxis and disease treatment. Conclusions The results suggest that the set of essential enzymes predicted by our flux balance approach represents a promising starting point for further drug development.

Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.

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Jiang, Yue; Xiong, Xuejian; Danska, Jayne; Parkinson, John

2016-01-12

Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function. Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions. The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of

Metabolic pathways of decabromodiphenyl ether (BDE209) in rainbow trout (Oncorhynchus mykiss) via intraperitoneal injection.

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Feng, Chenglian; Xu, Yiping; Zha, Jinmiao; Li, Jian; Wu, Fengchang; Wang, Zijian

2015-03-01

Decabromodiphenyl ether (BDE209) was of great concern due to its biotransformation in different organisms. However, most studies devoted to the metabolic intermediates of BDE209, less has been done on the metabolic pathways in vivo, especially on the relationships among debrominated-BDEs, OH-BDEs and MeO-BDEs. In this study, the metabolic pathways and intermediates of BDE209 in rainbow trout (Oncorhynchus mykiss) were investigated, and the time-dependent transformations of the metabolites were also examined. The primary debrominated metabolites were BDE47, 49, 99, 197, 207; the main MeO-BDEs were MeO-BDE47, MeO-BDE68 and MeO-BDE100; OH-BDEs were primarily composed of OH-BDE28 and OH-BDE42. From the time-dependent and dose-effect relationships, the debromination should be followed by hydroxylation, and then by methoxylation. The increasing in body burden of MeO-BDEs corresponded to the decreasing of OH-BDEs, which could indirectly prove the inter-conversion between OH-BDEs and MeO-BDEs. This study would motivate the future research of toxicological mechanisms of BDEs. Copyright © 2015 Elsevier B.V. All rights reserved.

Deep proteomics of mouse skeletal muscle enables quantitation of protein isoforms, metabolic pathways, and transcription factors.

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Deshmukh, Atul S; Murgia, Marta; Nagaraj, Nagarjuna; Treebak, Jonas T; Cox, Jürgen; Mann, Matthias

2015-04-01

Skeletal muscle constitutes 40% of individual body mass and plays vital roles in locomotion and whole-body metabolism. Proteomics of skeletal muscle is challenging because of highly abundant contractile proteins that interfere with detection of regulatory proteins. Using a state-of-the art MS workflow and a strategy to map identifications from the C2C12 cell line model to tissues, we identified a total of 10,218 proteins, including skeletal muscle specific transcription factors like myod1 and myogenin and circadian clock proteins. We obtain absolute abundances for proteins expressed in a muscle cell line and skeletal muscle, which should serve as a valuable resource. Quantitation of protein isoforms of glucose uptake signaling pathways and in glucose and lipid metabolic pathways provides a detailed metabolic map of the cell line compared with tissue. This revealed unexpectedly complex regulation of AMP-activated protein kinase and insulin signaling in muscle tissue at the level of enzyme isoforms. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Pulmonary Ozone Exposure Alters Essential Metabolic Pathways involved in Glucose Homeostasis in the Liver

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Pulmonary Ozone Exposure Alters Essential Metabolic Pathways involved in Glucose Homeostasis in the Liver D.B. Johnson, 1 W.O. Ward, 2 V.L. Bass, 2 M.C.J. Schladweiler, 2A.D. Ledbetter, 2 D. Andrews, and U.P. Kodavanti 2 1 Curriculum in Toxicology, UNC School of Medicine, Cha...

An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

Science.gov (United States)

Costa, Michael A.; Collins, R. Eric; Anterola, Aldwin M.; Cochrane, Fiona C.; Davin, Laurence B.; Lewis, Norman G.

2003-01-01

The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member

Danqi Pill regulates lipid metabolism disorder induced by myocardial ischemia through FATP-CPTI pathway.

Science.gov (United States)

Wang, Yong; Li, Chun; Wang, Qiyan; Shi, Tianjiao; Wang, Jing; Chen, Hui; Wu, Yan; Han, Jing; Guo, Shuzhen; Wang, Yuanyuan; Wang, Wei

2015-02-21

Danqi Pill (DQP), which contains Chinese herbs Salvia miltiorrhiza Bunge and Panax notoginseng, is widely used in the treatment of myocardial ischemia (MI) in China. Its regulatory effects on MI-associated lipid metabolism disorders haven't been comprehensively studied so far. We aimed to systematically investigate the regulatory mechanism of DQP on myocardial ischemia-induced lipid metabolism disorders. Myocardial ischemia rat model was induced by left anterior descending coronary artery ligation. The rat models were divided into three groups: model group with administration of normal saline, study group with administration of DanQi aqueous solution (1.5 mg/kg) and positive-control group with administration of pravastatin aqueous solution (1.2 mg/kg). In addition, another sham-operated group was set as negative control. At 28 days after treatment, cardiac function and degree of lipid metabolism disorders in rats of different groups were measured. Plasma lipid disorders were induced by myocardial ischemia, with manifestation of up-regulation of triglyceride (TG), low density lipoprotein (LDL), Apolipoprotein B (Apo-B) and 3-hydroxy-3-methyl glutaryl coenzyme A reductase (HMGCR). DQP could down-regulate the levels of TG, LDL, Apo-B and HMGCR. The Lipid transport pathway, fatty acids transport protein (FATP) and Carnitine palmitoyltransferase I (CPTI) were down-regulated in model group. DQP could improve plasma lipid metabolism by up-regulating this lipid transport pathway. The transcription factors peroxisome proliferator-activated receptor α (PPARα) and retinoid X receptors (RXRs), which regulate lipid metabolism, were also up-regulated by DQP. Furthermore, DQP was able to improve heart function and up-regulate ejection fraction (EF) by increasing the cardiac diastolic volume. Our study reveals that DQP would be an ideal alternative drug for the treatment of dyslipidemia which is induced by myocardial ischemia.

Regulatory network of secondary metabolism in Brassica rapa: insight into the glucosinolate pathway.

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Dunia Pino Del Carpio

Full Text Available Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomics approach to identify regulatory genes for six biosynthetic pathways of health-related phytochemicals, i.e carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids. Leaves from six weeks-old plants of a Brassica rapa doubled haploid population, consisting of 92 genotypes, were profiled for their secondary metabolite composition, using both targeted and LC-MS-based untargeted metabolomics approaches. Furthermore, the same population was profiled for transcript variation using a microarray containing EST sequences mainly derived from three Brassica species: B. napus, B. rapa and B. oleracea. The biochemical pathway analysis was based on the network analyses of both metabolite QTLs (mQTLs and transcript QTLs (eQTLs. Co-localization of mQTLs and eQTLs lead to the identification of candidate regulatory genes involved in the biosynthesis of carotenoids, tocopherols and glucosinolates. We subsequently focused on the well-characterized glucosinolate pathway and revealed two hotspots of co-localization of eQTLs with mQTLs in linkage groups A03 and A09. Our results indicate that such a large-scale genetical genomics approach combining transcriptomics and metabolomics data can provide new insights into the genetic regulation of metabolite composition of Brassica vegetables.

Generation of an atlas for commodity chemical production in Escherichia coli and a novel pathway prediction algorithm, GEM-Path

DEFF Research Database (Denmark)

Campodonico, Miguel A.; Andrews, Barbara A.; Asenjo, Juan A.

2014-01-01

The production of 75% of the current drug molecules and 35% of all chemicals could be achieved through bioprocessing (Arundel and Sawava, 2009). To accelerate the transition from a petroleum based chemical industry to a sustainable bio-based industry, systems metabolic engineering has emerged...... to computationally design metabolic pathways for chemical production. Although algorithms able to provide specific metabolic interventions and heterologous production pathways are available, a systematic analysis for all possible production routes to commodity chemicals in Escherichia call is lacking. Furthermore...... could be identified for 1271 of the 6615 conditions evaluated. This study characterizes the potential for E coli to produce commodity chemicals, and outlines a generic strain design workflow to design production strains. (C) 2014 international Metabolic Engineering Society. Published by Elsevier Inc...

Absolute quantitative profiling of the key metabolic pathways in slow and fast skeletal muscle

DEFF Research Database (Denmark)

Rakus, Dariusz; Gizak, Agnieszka; Deshmukh, Atul

2015-01-01

. Proteomic analysis of mouse slow and fast muscles allowed estimation of the titers of enzymes involved in the carbohydrate, lipid, and energy metabolism. Notably, we observed that differences observed between the two muscle types occur simultaneously for all proteins involved in a specific process......Slow and fast skeletal muscles are composed of, respectively, mainly oxidative and glycolytic muscle fibers, which are the basic cellular motor units of the motility apparatus. They largely differ in excitability, contraction mechanism, and metabolism. Because of their pivotal role in body motion...... and homeostasis, the skeletal muscles have been extensively studied using biochemical and molecular biology approaches. Here we describe a simple analytical and computational approach to estimate titers of enzymes of basic metabolic pathways and proteins of the contractile machinery in the skeletal muscles...

Elucidation of primary metabolic pathways in Aspergillus species: orphaned research in characterizing orphan genes.

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Andersen, Mikael Rørdam

2014-11-01

Primary metabolism affects all phenotypical traits of filamentous fungi. Particular examples include reacting to extracellular stimuli, producing precursor molecules required for cell division and morphological changes as well as providing monomer building blocks for production of secondary metabolites and extracellular enzymes. In this review, all annotated genes from four Aspergillus species have been examined. In this process, it becomes evident that 80-96% of the genes (depending on the species) are still without verified function. A significant proportion of the genes with verified metabolic functions are assigned to secondary or extracellular metabolism, leaving only 2-4% of the annotated genes within primary metabolism. It is clear that primary metabolism has not received the same attention in the post-genomic area as many other research areas--despite its role at the very centre of cellular function. However, several methods can be employed to use the metabolic networks in tandem with comparative genomics to accelerate functional assignment of genes in primary metabolism. In particular, gaps in metabolic pathways can be used to assign functions to orphan genes. In this review, applications of this from the Aspergillus genes will be examined, and it is proposed that, where feasible, this should be a standard part of functional annotation of fungal genomes. © The Author 2014. Published by Oxford University Press.

Defining a novel leptin–melanocortin–kisspeptin pathway involved in the metabolic control of puberty

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Maria Manfredi-Lozano

2016-10-01

Full Text Available Objective: Puberty is a key developmental phenomenon highly sensitive to metabolic modulation. Worrying trends of changes in the timing of puberty have been reported in humans. These might be linked to the escalating prevalence of childhood obesity and could have deleterious impacts on later (cardio-metabolic health, but their underlying mechanisms remain unsolved. The neuropeptide α-MSH, made by POMC neurons, plays a key role in energy homeostasis by mediating the actions of leptin and likely participates in the control of reproduction. However, its role in the metabolic regulation of puberty and interplay with kisspeptin, an essential puberty-regulating neuropeptide encoded by Kiss1, remain largely unknown. We aim here to unveil the potential contribution of central α-MSH signaling in the metabolic control of puberty by addressing its role in mediating the pubertal effects of leptin and its potential interaction with kisspeptin. Methods: Using wild type and genetically modified rodent models, we implemented pharmacological studies, expression analyses, electrophysiological recordings, and virogenetic approaches involving DREADD technology to selectively inhibit Kiss1 neurons, in order to interrogate the physiological role of a putative leptin→α-MSH→kisspeptin pathway in the metabolic control of puberty. Results: Stimulation of central α-MSH signaling robustly activated the reproductive axis in pubertal rats, whereas chronic inhibition of melanocortin receptors MC3/4R, delayed puberty, and prevented the permissive effect of leptin on puberty onset. Central blockade of MC3/4R or genetic elimination of kisspeptin receptors from POMC neurons did not affect kisspeptin effects. Conversely, congenital ablation of kisspeptin receptors or inducible, DREADD-mediated inhibition of arcuate nucleus (ARC Kiss1 neurons resulted in markedly attenuated gonadotropic responses to MC3/4R activation. Furthermore, close appositions were observed between

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...

Conversion of KEGG metabolic pathways to SBGN maps including automatic layout.

Science.gov (United States)

Czauderna, Tobias; Wybrow, Michael; Marriott, Kim; Schreiber, Falk

2013-08-16

Biologists make frequent use of databases containing large and complex biological networks. One popular database is the Kyoto Encyclopedia of Genes and Genomes (KEGG) which uses its own graphical representation and manual layout for pathways. While some general drawing conventions exist for biological networks, arbitrary graphical representations are very common. Recently, a new standard has been established for displaying biological processes, the Systems Biology Graphical Notation (SBGN), which aims to unify the look of such maps. Ideally, online repositories such as KEGG would automatically provide networks in a variety of notations including SBGN. Unfortunately, this is non-trivial, since converting between notations may add, remove or otherwise alter map elements so that the existing layout cannot be simply reused. Here we describe a methodology for automatic translation of KEGG metabolic pathways into the SBGN format. We infer important properties of the KEGG layout and treat these as layout constraints that are maintained during the conversion to SBGN maps. This allows for the drawing and layout conventions of SBGN to be followed while creating maps that are still recognizably the original KEGG pathways. This article details the steps in this process and provides examples of the final result.

Linking metabolic QTLs with network and cis-eQTLs controlling biosynthetic pathways.

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Adam M Wentzell

2007-09-01

Full Text Available Phenotypic variation between individuals of a species is often under quantitative genetic control. Genomic analysis of gene expression polymorphisms between individuals is rapidly gaining popularity as a way to query the underlying mechanistic causes of variation between individuals. However, there is little direct evidence of a linkage between global gene expression polymorphisms and phenotypic consequences. In this report, we have mapped quantitative trait loci (QTLs-controlling glucosinolate content in a population of 403 Arabidopsis Bay x Sha recombinant inbred lines, 211 of which were previously used to identify expression QTLs controlling the transcript levels of biosynthetic genes. In a comparative study, we have directly tested two plant biosynthetic pathways for association between polymorphisms controlling biosynthetic gene transcripts and the resulting metabolites within the Arabidopsis Bay x Sha recombinant inbred line population. In this analysis, all loci controlling expression variation also affected the accumulation of the resulting metabolites. In addition, epistasis was detected more frequently for metabolic traits compared to transcript traits, even when both traits showed similar distributions. An analysis of candidate genes for QTL-controlling networks of transcripts and metabolites suggested that the controlling factors are a mix of enzymes and regulatory factors. This analysis showed that regulatory connections can feedback from metabolism to transcripts. Surprisingly, the most likely major regulator of both transcript level for nearly the entire pathway and aliphatic glucosinolate accumulation is variation in the last enzyme in the biosynthetic pathway, AOP2. This suggests that natural variation in transcripts may significantly impact phenotypic variation, but that natural variation in metabolites or their enzymatic loci can feed back to affect the transcripts.

Postprandial regulation of hepatic microRNAs predicted to target the insulin pathway in rainbow trout.

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Jan A Mennigen

Full Text Available Rainbow trout are carnivorous fish and poor metabolizers of carbohydrates, which established this species as a model organism to study the comparative physiology of insulin. Following the recent characterisation of key roles of several miRNAs in the insulin action on hepatic intermediary metabolism in mammalian models, we investigated the hypothesis that hepatic miRNA expression is postprandially regulated in the rainbow trout and temporally coordinated in the context of insulin-mediated regulation of metabolic gene expression in the liver. To address this hypothesis, we used a time-course experiment in which rainbow trout were fed a commercial diet after short-term fasting. We investigated hepatic miRNA expression, activation of the insulin pathway, and insulin regulated metabolic target genes at several time points. Several miRNAs which negatively regulate hepatic insulin signaling in mammalian model organisms were transiently increased 4 h after the meal, consistent with a potential role in acute postprandial negative feed-back regulation of the insulin pathway and attenuation of gluconeogenic gene expression. We equally observed a transient increase in omy- miRNA-33 and omy-miRNA-122b 4 h after feeding, whose homologues have potent lipogenic roles in the liver of mammalian model systems. A concurrent increase in the activity of the hepatic insulin signaling pathway and the expression of lipogenic genes (srebp1c, fas, acly was equally observed, while lipolytic gene expression (cpt1a and cpt1b decreased significantly 4 h after the meal. This suggests lipogenic roles of omy-miRNA-33 and omy-miRNA-122b may be conserved between rainbow trout and mammals and that these miRNAs may furthermore contribute to acute postprandial regulation of de novo hepatic lipid synthesis in rainbow trout. These findings provide a framework for future research of miRNA regulation of hepatic metabolism in trout and will help to further elucidate the metabolic

Altered Levels of Aroma and Volatiles by Metabolic Engineering of Shikimate Pathway Genes in Tomato Fruits

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Vered Tzin

2015-06-01

Full Text Available The tomato (Solanum lycopersicum fruit is an excellent source of antioxidants, dietary fibers, minerals and vitamins and therefore has been referred to as a “functional food”. Ripe tomato fruits produce a large number of specialized metabolites including volatile organic compounds. These volatiles serve as key components of the tomato fruit flavor, participate in plant pathogen and herbivore defense, and are used to attract seed dispersers. A major class of specialized metabolites is derived from the shikimate pathway followed by aromatic amino acid biosynthesis of phenylalanine, tyrosine and tryptophan. We attempted to modify tomato fruit flavor by overexpressing key regulatory genes in the shikimate pathway. Bacterial genes encoding feedback-insensitive variants of 3-Deoxy-D-Arabino-Heptulosonate 7-Phosphate Synthase (DAHPS; AroG209-9 and bi-functional Chorismate Mutase/Prephenate Dehydratase (CM/PDT; PheA12 were expressed under the control of a fruit-specific promoter. We crossed these transgenes to generate tomato plants expressing both the AroG209 and PheA12 genes. Overexpression of the AroG209-9 gene had a dramatic effect on the overall metabolic profile of the fruit, including enhanced levels of multiple volatile and non-volatile metabolites. In contrast, the PheA12 overexpression line exhibited minor metabolic effects compared to the wild type fruit. Co-expression of both the AroG209-9 and PheA12 genes in tomato resulted overall in a similar metabolic effect to that of expressing only the AroG209-9 gene. However, the aroma ranking attributes of the tomato fruits from PheA12//AroG209-9 were unique and different from those of the lines expressing a single gene, suggesting a contribution of the PheA12 gene to the overall metabolic profile. We suggest that expression of bacterial genes encoding feedback-insensitive enzymes of the shikimate pathway in tomato fruits provides a useful metabolic engineering tool for the modification of

Exacerbation of substrate toxicity by IPTG in Escherichia coli BL21(DE3) carrying a synthetic metabolic pathway.

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Dvorak, Pavel; Chrast, Lukas; Nikel, Pablo I; Fedr, Radek; Soucek, Karel; Sedlackova, Miroslava; Chaloupkova, Radka; de Lorenzo, Víctor; Prokop, Zbynek; Damborsky, Jiri

2015-12-21

Heterologous expression systems based on promoters inducible with isopropyl-β-D-1-thiogalactopyranoside (IPTG), e.g., Escherichia coli BL21(DE3) and cognate LacI(Q)/P(lacUV5)-T7 vectors, are commonly used for production of recombinant proteins and metabolic pathways. The applicability of such cell factories is limited by the complex physiological burden imposed by overexpression of the exogenous genes during a bioprocess. This burden originates from a combination of stresses that may include competition for the expression machinery, side-reactions due to the activity of the recombinant proteins, or the toxicity of their substrates, products and intermediates. However, the physiological impact of IPTG-induced conditional expression on the recombinant host under such harsh conditions is often overlooked. The physiological responses to IPTG of the E. coli BL21(DE3) strain and three different recombinants carrying a synthetic metabolic pathway for biodegradation of the toxic anthropogenic pollutant 1,2,3-trichloropropane (TCP) were investigated using plating, flow cytometry, and electron microscopy. Collected data revealed unexpected negative synergistic effect of inducer of the expression system and toxic substrate resulting in pronounced physiological stress. Replacing IPTG with the natural sugar effector lactose greatly reduced such stress, demonstrating that the effect was due to the original inducer's chemical properties. IPTG is not an innocuous inducer; instead, it exacerbates the toxicity of haloalkane substrate and causes appreciable damage to the E. coli BL21(DE3) host, which is already bearing a metabolic burden due to its content of plasmids carrying the genes of the synthetic metabolic pathway. The concentration of IPTG can be effectively tuned to mitigate this negative effect. Importantly, we show that induction with lactose, the natural inducer of P lac , dramatically lightens the burden without reducing the efficiency of the synthetic TCP degradation

Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates

DEFF Research Database (Denmark)

Glazier, Douglas S.; Hirst, Andrew G.; Atkinson, D.

2016-01-01

in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR

Bayesian inference of the sites of perturbations in metabolic pathways via Markov chain Monte Carlo

NARCIS (Netherlands)

Jayawardhana, Bayu; Kell, Douglas B.; Rattray, Magnus

2008-01-01

Motivation: Genetic modifications or pharmaceutical interventions can influence multiple sites in metabolic pathways, and often these are ‘distant’ from the primary effect. In this regard, the ability to identify target and off-target effects of a specific compound or gene therapy is both a major

Gene-Gene Interactions in the Folate Metabolic Pathway and the Risk of Conotruncal Heart Defects

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Philip J. Lupo

2010-01-01

Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.

Detection of phytohormones in temperate forest fungi predicts consistent abscisic acid production and a common pathway for cytokinin biosynthesis.

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Morrison, Erin N; Knowles, Sarah; Hayward, Allison; Thorn, R Greg; Saville, Barry J; Emery, R J N

2015-01-01

The phytohormones, abscisic acid and cytokinin, once were thought to be present uniquely in plants, but increasing evidence suggests that these hormones are present in a wide variety of organisms. Few studies have examined fungi for the presence of these "plant" hormones or addressed whether their levels differ based on the nutrition mode of the fungus. This study examined 20 temperate forest fungi of differing nutritional modes (ectomycorrhizal, wood-rotting, saprotrophic). Abscisic acid and cytokinin were present in all fungi sampled; this indicated that the sampled fungi have the capacity to synthesize these two classes of phytohormones. Of the 27 cytokinins analyzed by HPLC-ESI MS/MS, seven were present in all fungi sampled. This suggested the existence of a common cytokinin metabolic pathway in fungi that does not vary among different nutritional modes. Predictions regarding the source of isopentenyl, cis-zeatin and methylthiol CK production stemming from the tRNA degradation pathway among fungi are discussed. © 2015 by The Mycological Society of America.

Pyrrolizidine Alkaloids: Metabolic Activation Pathways Leading to Liver Tumor Initiation.

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Fu, Peter P

2017-01-17

Pyrrolizidine alkaloids (PAs) and PA N-oxides are a class of phytochemical carcinogens contained in over 6000 plant species spread around the world. It has been estimated that approximately half of the 660 PAs and PA N-oxides that have been characterized are cytotoxic, genotoxic, and tumorigenic. It was recently determined that a genotoxic mechanism of liver tumor initiation mediated by PA-derived DNA adducts is a common metabolic activation pathway of a number of PAs. We proposed this set of PA-derived DNA adducts could be a common biological biomarker of PA exposure and a potential biomarker of PA-induced liver tumor formation. We have also found that several reactive secondary pyrrolic metabolites can dissociate and interconvert to other secondary pyrrolic metabolites, resulting in the formation of the same exogenous DNA adducts. This present perspective reports the current progress on these new findings and proposes future research needed for obtaining a greater understanding of the role of this activation pathway and validating the use of this set of PA-derived DNA adducts as a biological biomarker of PA-induced liver tumor initiation.

Metabolic pathways of lung inflammation revealed by high-resolution metabolomics (HRM) of H1N1 influenza virus infection in mice.

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Chandler, Joshua D; Hu, Xin; Ko, Eun-Ju; Park, Soojin; Lee, Young-Tae; Orr, Michael; Fernandes, Jolyn; Uppal, Karan; Kang, Sang-Moo; Jones, Dean P; Go, Young-Mi

2016-11-01

Influenza is a significant health concern worldwide. Viral infection induces local and systemic activation of the immune system causing attendant changes in metabolism. High-resolution metabolomics (HRM) uses advanced mass spectrometry and computational methods to measure thousands of metabolites inclusive of most metabolic pathways. We used HRM to identify metabolic pathways and clusters of association related to inflammatory cytokines in lungs of mice with H1N1 influenza virus infection. Infected mice showed progressive weight loss, decreased lung function, and severe lung inflammation with elevated cytokines [interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ] and increased oxidative stress via cysteine oxidation. HRM showed prominent effects of influenza virus infection on tryptophan and other amino acids, and widespread effects on pathways including purines, pyrimidines, fatty acids, and glycerophospholipids. A metabolome-wide association study (MWAS) of the aforementioned inflammatory cytokines was used to determine the relationship of metabolic responses to inflammation during infection. This cytokine-MWAS (cMWAS) showed that metabolic associations consisted of distinct and shared clusters of 396 metabolites highly correlated with inflammatory cytokines. Strong negative associations of selected glycosphingolipid, linoleate, and tryptophan metabolites with IFN-γ contrasted strong positive associations of glycosphingolipid and bile acid metabolites with IL-1β, TNF-α, and IL-10. Anti-inflammatory cytokine IL-10 had strong positive associations with vitamin D, purine, and vitamin E metabolism. The detailed metabolic interactions with cytokines indicate that targeted metabolic interventions may be useful during life-threatening crises related to severe acute infection and inflammation. Copyright © 2016 the American Physiological Society.

A summary of genomic data relating to E. coli organized by metabolic pathways: An initial version

Energy Technology Data Exchange (ETDEWEB)

Price, M.; Raju, M.; Taylor, R.

1993-01-01

This report summarizes the reactions that occur in some of the principal metabolic pathways of E. coli. These pathways have been encoded as objects in GenoBase, an integrated database under development at Argonne National Laboratory in collaboration with researchers at the National Institutes of Health and at Harvard University. The report lists the substrates, products, enzymes, and cofactors for each pathway as a whole, followed by a detailed description of each reaction in the pathway. In addition, for each enzyme, the report displays a description and activity as listed in the Enzyme Data Bank, followed by the corresponding Swiss Protein Data Bank entries. Separate summary lines are included for each of the E. coli genes associated with each enzyme.

Simulating metabolism with statistical thermodynamics.

Science.gov (United States)

Cannon, William R

2014-01-01

New methods are needed for large scale modeling of metabolism that predict metabolite levels and characterize the thermodynamics of individual reactions and pathways. Current approaches use either kinetic simulations, which are difficult to extend to large networks of reactions because of the need for rate constants, or flux-based methods, which have a large number of feasible solutions because they are unconstrained by the law of mass action. This report presents an alternative modeling approach based on statistical thermodynamics. The principles of this approach are demonstrated using a simple set of coupled reactions, and then the system is characterized with respect to the changes in energy, entropy, free energy, and entropy production. Finally, the physical and biochemical insights that this approach can provide for metabolism are demonstrated by application to the tricarboxylic acid (TCA) cycle of Escherichia coli. The reaction and pathway thermodynamics are evaluated and predictions are made regarding changes in concentration of TCA cycle intermediates due to 10- and 100-fold changes in the ratio of NAD+:NADH concentrations. Finally, the assumptions and caveats regarding the use of statistical thermodynamics to model non-equilibrium reactions are discussed.

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism.

Science.gov (United States)

Mohammed, Akram; Guda, Chittibabu

2015-01-01

Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids, cofactors and

Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism

Science.gov (United States)

2015-01-01

Background Enzymes are known as the molecular machines that drive the metabolism of an organism; hence identification of the full enzyme complement of an organism is essential to build the metabolic blueprint of that species as well as to understand the interplay of multiple species in an ecosystem. Experimental characterization of the enzymatic reactions of all enzymes in a genome is a tedious and expensive task. The problem is more pronounced in the metagenomic samples where even the species are not adequately cultured or characterized. Enzymes encoded by the gut microbiota play an essential role in the host metabolism; thus, warranting the need to accurately identify and annotate the full enzyme complements of species in the genomic and metagenomic projects. To fulfill this need, we develop and apply a method called ECemble, an ensemble approach to identify enzymes and enzyme classes and study the human gut metabolic pathways. Results ECemble method uses an ensemble of machine-learning methods to accurately model and predict enzymes from protein sequences and also identifies the enzyme classes and subclasses at the finest resolution. A tenfold cross-validation result shows accuracy between 97 and 99% at different levels in the hierarchy of enzyme classification, which is superior to comparable methods. We applied ECemble to predict the entire complements of enzymes from ten sequenced proteomes including the human proteome. We also applied this method to predict enzymes encoded by the human gut microbiome from gut metagenomic samples, and to study the role played by the microbe-derived enzymes in the human metabolism. After mapping the known and predicted enzymes to canonical human pathways, we identified 48 pathways that have at least one bacteria-encoded enzyme, which demonstrates the complementary role of gut microbiome in human gut metabolism. These pathways are primarily involved in metabolizing dietary nutrients such as carbohydrates, amino acids, lipids

Central melanin-concentrating hormone influences liver and adipose metabolism via specific hypothalamic nuclei and efferent autonomic/JNK1 pathways.

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Imbernon, Monica; Beiroa, Daniel; Vázquez, María J; Morgan, Donald A; Veyrat-Durebex, Christelle; Porteiro, Begoña; Díaz-Arteaga, Adenis; Senra, Ana; Busquets, Silvia; Velásquez, Douglas A; Al-Massadi, Omar; Varela, Luis; Gándara, Marina; López-Soriano, Francisco-Javier; Gallego, Rosalía; Seoane, Luisa M; Argiles, Josep M; López, Miguel; Davis, Roger J; Sabio, Guadalupe; Rohner-Jeanrenaud, Françoise; Rahmouni, Kamal; Dieguez, Carlos; Nogueiras, Ruben

2013-03-01

Specific neuronal circuits modulate autonomic outflow to liver and white adipose tissue. Melanin-concentrating hormone (MCH)-deficient mice are hypophagic, lean, and do not develop hepatosteatosis when fed a high-fat diet. Herein, we sought to investigate the role of MCH, an orexigenic neuropeptide specifically expressed in the lateral hypothalamic area, on hepatic and adipocyte metabolism. Chronic central administration of MCH and adenoviral vectors increasing MCH signaling were performed in rats and mice. Vagal denervation was performed to assess its effect on liver metabolism. The peripheral effects on lipid metabolism were assessed by real-time polymerase chain reaction and Western blot. We showed that the activation of MCH receptors promotes nonalcoholic fatty liver disease through the parasympathetic nervous system, whereas it increases fat deposition in white adipose tissue via the suppression of sympathetic traffic. These metabolic actions are independent of parallel changes in food intake and energy expenditure. In the liver, MCH triggers lipid accumulation and lipid uptake, with c-Jun N-terminal kinase being an essential player, whereas in adipocytes MCH induces metabolic pathways that promote lipid storage and decreases lipid mobilization. Genetic activation of MCH receptors or infusion of MCH specifically in the lateral hypothalamic area modulated hepatic lipid metabolism, whereas the specific activation of this receptor in the arcuate nucleus affected adipocyte metabolism. Our findings show that central MCH directly controls hepatic and adipocyte metabolism through different pathways. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

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

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

2016-05-01

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

A systems biology framework for modeling metabolic enzyme inhibition of Mycobacterium tuberculosis

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Reifman Jaques

2009-09-01

Full Text Available Abstract Background Because metabolism is fundamental in sustaining microbial life, drugs that target pathogen-specific metabolic enzymes and pathways can be very effective. In particular, the metabolic challenges faced by intracellular pathogens, such as Mycobacterium tuberculosis, residing in the infected host provide novel opportunities for therapeutic intervention. Results We developed a mathematical framework to simulate the effects on the growth of a pathogen when enzymes in its metabolic pathways are inhibited. Combining detailed models of enzyme kinetics, a complete metabolic network description as modeled by flux balance analysis, and a dynamic cell population growth model, we quantitatively modeled and predicted the dose-response of the 3-nitropropionate inhibitor on the growth of M. tuberculosis in a medium whose carbon source was restricted to fatty acids, and that of the 5'-O-(N-salicylsulfamoyl adenosine inhibitor in a medium with low-iron concentration. Conclusion The predicted results quantitatively reproduced the experimentally measured dose-response curves, ranging over three orders of magnitude in inhibitor concentration. Thus, by allowing for detailed specifications of the underlying enzymatic kinetics, metabolic reactions/constraints, and growth media, our model captured the essential chemical and biological factors that determine the effects of drug inhibition on in vitro growth of M. tuberculosis cells.

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.

Metabolic reprogramming of the urea cycle pathway in experimental pulmonary arterial hypertension rats induced by monocrotaline.

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Zheng, Hai-Kuo; Zhao, Jun-Han; Yan, Yi; Lian, Tian-Yu; Ye, Jue; Wang, Xiao-Jian; Wang, Zhe; Jing, Zhi-Cheng; He, Yang-Yang; Yang, Ping

2018-05-11

Pulmonary arterial hypertension (PAH) is a rare systemic disorder associated with considerable metabolic dysfunction. Although enormous metabolomic studies on PAH have been emerging, research remains lacking on metabolic reprogramming in experimental PAH models. We aim to evaluate the metabolic changes in PAH and provide new insight into endogenous metabolic disorders of PAH. A single subcutaneous injection of monocrotaline (MCT) (60 mg kg - 1 ) was used for rats to establish PAH model. Hemodynamics and right ventricular hypertrophy were adopted to evaluate the successful establishment of PAH model. Plasma samples were assessed through targeted metabolomic profiling platform to quantify 126 endogenous metabolites. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to discriminate between MCT-treated model and control groups. Metabolite Set Enrichment Analysis was adapted to exploit the most disturbed metabolic pathways. Endogenous metabolites of MCT treated PAH model and control group were well profiled using this platform. A total of 13 plasma metabolites were significantly altered between the two groups. Metabolite Set Enrichment Analysis highlighted that a disruption in the urea cycle pathway may contribute to PAH onset. Moreover, five novel potential biomarkers in the urea cycle, adenosine monophosphate, urea, 4-hydroxy-proline, ornithine, N-acetylornithine, and two candidate biomarkers, namely, O-acetylcarnitine and betaine, were found to be highly correlated with PAH. The present study suggests a new role of urea cycle disruption in the pathogenesis of PAH. We also found five urea cycle related biomarkers and another two candidate biomarkers to facilitate early diagnosis of PAH in metabolomic profile.

Oxygen and the evolution of metabolic pathways

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Jahnke, L. L.

1986-01-01

While a considerable amount of evidence has been accumulated about the history of oxygen on this planet, little is known about the relative amounts to which primitive cells might have been exposed. One clue may be found in the metabolic pathways of extant microorganisms. While eucaryotes are principally aerobic organisms, a number are capable of anaerobic growth by fermentation. One such eucaryotic microorganism, Saccharomyces cerevisiae, will grow in the complete absence of oxygen when supplemented with unsaturated fatty acid and sterol. Oxygen-requiring enzymes are involved in the synthesis of both of these compounds. Studies have demonstrated that the oxidative desaturation of palmitic acid and the conversion of squalene to sterols occur in the range of 10-(3) to 10(-2) PAL. Thus, if the oxygen requirements of these enzymatic processes are an indication, eucaryotes might be more primitive than anticipated from the microfossil record. Results of studies on the oxygen requirements for sterol and unsaturated fatty acid synthesis in a more primitive procaryotic system are also discussed.

A hepatic amino acid/mTOR/S6K-dependent signalling pathway modulates systemic lipid metabolism via neuronal signals.

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Uno, Kenji; Yamada, Tetsuya; Ishigaki, Yasushi; Imai, Junta; Hasegawa, Yutaka; Sawada, Shojiro; Kaneko, Keizo; Ono, Hiraku; Asano, Tomoichiro; Oka, Yoshitomo; Katagiri, Hideki

2015-08-13

Metabolism is coordinated among tissues and organs via neuronal signals. Levels of circulating amino acids (AAs), which are elevated in obesity, activate the intracellular target of rapamycin complex-1 (mTORC1)/S6kinase (S6K) pathway in the liver. Here we demonstrate that hepatic AA/mTORC1/S6K signalling modulates systemic lipid metabolism via a mechanism involving neuronal inter-tissue communication. Hepatic expression of an AA transporter, SNAT2, activates the mTORC1/S6K pathway, and markedly elevates serum triglycerides (TGs), while downregulating adipose lipoprotein lipase (LPL). Hepatic Rheb or active-S6K expression have similar metabolic effects, whereas hepatic expression of dominant-negative-S6K inhibits TG elevation in SNAT2 mice. Denervation, pharmacological deafferentation and β-blocker administration suppress obesity-related hypertriglyceridemia with adipose LPL upregulation, suggesting that signals are transduced between liver and adipose tissue via a neuronal pathway consisting of afferent vagal and efferent sympathetic nerves. Thus, the neuronal mechanism uncovered here serves to coordinate amino acid and lipid levels and contributes to the development of obesity-related hypertriglyceridemia.

Dynamic scenario of metabolic pathway adaptation in tumors and therapeutic approach.

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Peppicelli, Silvia; Bianchini, Francesca; Calorini, Lido

2015-01-01

Cancer cells need to regulate their metabolic program to fuel several activities, including unlimited proliferation, resistance to cell death, invasion and metastasis. The aim of this work is to revise this complex scenario. Starting from proliferating cancer cells located in well-oxygenated regions, they may express the so-called "Warburg effect" or aerobic glycolysis, meaning that although a plenty of oxygen is available, cancer cells choose glycolysis, the sole pathway that allows a biomass formation and DNA duplication, needed for cell division. Although oxygen does not represent the primary font of energy, diffusion rate reduces oxygen tension and the emerging hypoxia promotes "anaerobic glycolysis" through the hypoxia inducible factor-1α-dependent up-regulation. The acquired hypoxic phenotype is endowed with high resistance to cell death and high migration capacities, although these cells are less proliferating. Cells using aerobic or anaerobic glycolysis survive only in case they extrude acidic metabolites acidifying the extracellular space. Acidosis drives cancer cells from glycolysis to OxPhos, and OxPhos transforms the available alternative substrates into energy used to fuel migration and distant organ colonization. Thus, metabolic adaptations sustain different energy-requiring ability of cancer cells, but render them responsive to perturbations by anti-metabolic agents, such as inhibitors of glycolysis and/or OxPhos.

Metabolic Engineering of the Shikimate Pathway for Production of Aromatics and Derived Compounds—Present and Future Strain Construction Strategies

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Nils J. H. Averesch

2018-03-01

Full Text Available The aromatic nature of shikimate pathway intermediates gives rise to a wealth of potential bio-replacements for commonly fossil fuel-derived aromatics, as well as naturally produced secondary metabolites. Through metabolic engineering, the abundance of certain intermediates may be increased, while draining flux from other branches off the pathway. Often targets for genetic engineering lie beyond the shikimate pathway, altering flux deep in central metabolism. This has been extensively used to develop microbial production systems for a variety of compounds valuable in chemical industry, including aromatic and non-aromatic acids like muconic acid, para-hydroxybenzoic acid, and para-coumaric acid, as well as aminobenzoic acids and aromatic α-amino acids. Further, many natural products and secondary metabolites that are valuable in food- and pharma-industry are formed outgoing from shikimate pathway intermediates. (Reconstruction of such routes has been shown by de novo production of resveratrol, reticuline, opioids, and vanillin. In this review, strain construction strategies are compared across organisms and put into perspective with requirements by industry for commercial viability. Focus is put on enhancing flux to and through shikimate pathway, and engineering strategies are assessed in order to provide a guideline for future optimizations.

Flavin-containing monooxygenase 3 (FMO3) role in busulphan metabolic pathway

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Terelius, Ylva; Abedi-Valugerdi, Manuchehr; Naughton, Seán; Saghafian, Maryam; Moshfegh, Ali; Mattsson, Jonas; Potácová, Zuzana; Hassan, Moustapha

2017-01-01

Busulphan (Bu) is an alkylating agent used in the conditioning regimen prior to hematopoietic stem cell transplantation (HSCT). Bu is extensively metabolized in the liver via conjugations with glutathione to form the intermediate metabolite (sulfonium ion) which subsequently is degraded to tetrahydrothiophene (THT). THT was reported to be oxidized forming THT-1-oxide that is further oxidized to sulfolane and finally 3-hydroxysulfolane. However, the underlying mechanisms for the formation of these metabolites remain poorly understood. In the present study, we performed in vitro and in vivo investigations to elucidate the involvement of flavin-containing monooxygenase-3 (FMO3) and cytochrome P450 enzymes (CYPs) in Bu metabolic pathway. Rapid clearance of THT was observed when incubated with human liver microsomes. Furthermore, among different recombinant microsomal enzymes, the highest intrinsic clearance for THT was obtained via FMO3 followed by several CYPs including 2B6, 2C8, 2C9, 2C19, 2E1 and 3A4. In Bu- or THT-treated mice, inhibition of FMO3 by phenylthiourea significantly suppressed the clearance of both Bu and THT. Moreover, the simultaneous administration of a high dose of THT (200μmol/kg) to Bu-treated mice reduced the clearance of Bu. Consistently, in patients undergoing HSCT, repeated administration of Bu resulted in a significant up-regulation of FMO3 and glutathione-S-transfrase -1 (GSTA1) genes. Finally, in a Bu-treated patient, additional treatment with voriconazole (an antimycotic drug known as an FMO3-substrate) significantly altered the Bu clearance. In conclusion, we demonstrate for the first time that FMO3 along with CYPs contribute a major part in busulphan metabolic pathway and certainly can affect its kinetics. The present results have high clinical impact. Furthermore, these findings might be important for reducing the treatment-related toxicity of Bu, through avoiding interaction with other concomitant used drugs during conditioning and

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

Incremental Predictive Value of Serum AST-to-ALT Ratio for Incident Metabolic Syndrome: The ARIRANG Study

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Ahn, Song Vogue; Baik, Soon Koo; Cho, Youn zoo; Koh, Sang Baek; Huh, Ji Hye; Chang, Yoosoo; Sung, Ki-Chul; Kim, Jang Young

2016-01-01

Aims The ratio of aspartate aminotransferase (AST) to alanine aminotransferase (ALT) is of great interest as a possible novel marker of metabolic syndrome. However, longitudinal studies emphasizing the incremental predictive value of the AST-to-ALT ratio in diagnosing individuals at higher risk of developing metabolic syndrome are very scarce. Therefore, our study aimed to evaluate the AST-to-ALT ratio as an incremental predictor of new onset metabolic syndrome in a population-based cohort study. Material and Methods The population-based cohort study included 2276 adults (903 men and 1373 women) aged 40–70 years, who participated from 2005–2008 (baseline) without metabolic syndrome and were followed up from 2008–2011. Metabolic syndrome was defined according to the harmonized definition of metabolic syndrome. Serum concentrations of AST and ALT were determined by enzymatic methods. Results During an average follow-up period of 2.6-years, 395 individuals (17.4%) developed metabolic syndrome. In a multivariable adjusted model, the odds ratio (95% confidence interval) for new onset of metabolic syndrome, comparing the fourth quartile to the first quartile of the AST-to-ALT ratio, was 0.598 (0.422–0.853). The AST-to-ALT ratio also improved the area under the receiver operating characteristic curve (AUC) for predicting new cases of metabolic syndrome (0.715 vs. 0.732, P = 0.004). The net reclassification improvement of prediction models including the AST-to-ALT ratio was 0.23 (95% CI: 0.124–0.337, Pmetabolic syndrome and had incremental predictive value for incident metabolic syndrome. PMID:27560931

Strength of Temporal White Matter Pathways Predicts Semantic Learning.

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Ripollés, Pablo; Biel, Davina; Peñaloza, Claudia; Kaufmann, Jörn; Marco-Pallarés, Josep; Noesselt, Toemme; Rodríguez-Fornells, Antoni

2017-11-15

Learning the associations between words and meanings is a fundamental human ability. Although the language network is cortically well defined, the role of the white matter pathways supporting novel word-to-meaning mappings remains unclear. Here, by using contextual and cross-situational word learning, we tested whether learning the meaning of a new word is related to the integrity of the language-related white matter pathways in 40 adults (18 women). The arcuate, uncinate, inferior-fronto-occipital and inferior-longitudinal fasciculi were virtually dissected using manual and automatic deterministic fiber tracking. Critically, the automatic method allowed assessing the white matter microstructure along the tract. Results demonstrate that the microstructural properties of the left inferior-longitudinal fasciculus predict contextual learning, whereas the left uncinate was associated with cross-situational learning. In addition, we identified regions of special importance within these pathways: the posterior middle temporal gyrus, thought to serve as a lexical interface and specifically related to contextual learning; the anterior temporal lobe, known to be an amodal hub for semantic processing and related to cross-situational learning; and the white matter near the hippocampus, a structure fundamental for the initial stages of new-word learning and, remarkably, related to both types of word learning. No significant associations were found for the inferior-fronto-occipital fasciculus or the arcuate. While previous results suggest that learning new phonological word forms is mediated by the arcuate fasciculus, these findings show that the temporal pathways are the crucial neural substrate supporting one of the most striking human abilities: our capacity to identify correct associations between words and meanings under referential indeterminacy. SIGNIFICANCE STATEMENT The language-processing network is cortically (i.e., gray matter) well defined. However, the role of the

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

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

2014-01-01

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

Signatures of arithmetic simplicity in metabolic network architecture.

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William J Riehl

2010-04-01

Full Text Available Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity.

Proteomics of the rat myocardium during development of type 2 diabetes mellitus reveals progressive alterations in major metabolic pathways

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Edhager, Anders Valdemar; Povlsen, Jonas Agerlund; Løfgren, Bo

2018-01-01

in intracellular metabolic pathways in the Zucker diabetic fatty rat heart as T2DM develops using MS based proteomics. The pre-diabetic state only induced minor pathway changes, whereas onset and late T2DM caused pronounced perturbations. Two actin-associated proteins, ARPC2 and TPM3, were up-regulated at the pre...

Bidirectional Expression of Metabolic, Structural, and Immune Pathways in Early Myopia and Hyperopia

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Nina Riddell

2016-08-01

Full Text Available Myopia (short-sightedness affects 1.45 billion people worldwide, many of whom will develop sight-threatening secondary disorders. Myopic eyes are characterized by excessive size while hyperopic (long-sighted eyes are typically small. The biological and genetic mechanisms underpinning the retina’s local control of these growth patterns remain unclear. In the present study, we used RNA sequencing to examine gene expression in the retina/RPE/choroid across 3 days of optically-induced myopia and hyperopia induction in chick. Data were analysed for differential expression of single genes, and Gene Set Enrichment Analysis (GSEA was used to identify gene sets correlated with ocular axial length and refraction across lens groups. Like previous studies, we found few single genes that were differentially-expressed in a sign-of-defocus dependent manner (only BMP2 at 1 day. Using GSEA, however, we are the first to show that more subtle shifts in structural, metabolic, and immune pathway expression are correlated with the eye size and refractive changes induced by lens defocus. Our findings link gene expression with the morphological characteristics of refractive error, and suggest that physiological stress arising from metabolic and inflammatory pathway activation could increase the vulnerability of myopic eyes to secondary pathologies

SU-E-J-102: Separation of Metabolic Supply and Demand: From Power Grid Economics to Cancer Metabolism

Energy Technology Data Exchange (ETDEWEB)

Epstein, T; Xu, L; Gillies, R; Gatenby, R [Moffitt Cancer Center and Research Institute, Tampa, FL (United States)

2014-06-01

Purpose: To study a new model of glucose metabolism which is primarily governed by the timescale of the energetic demand and not by the oxygen level, and its implication on cancer metabolism (Warburg effect) Methods: 1) Metabolic profiling of membrane transporters activity in several cell lines, which represent the spectrum from normal breast epithelium to aggressive, metastatic cancer, using Seahorse XF reader.2) Spatial localization of oxidative and non-oxidative metabolic components using immunocytochemical imaging of the glycolytic ATP-producing enzyme, pyruvate kinase and mitochondria. 3) Finite element simulations of coupled partial differential equations using COMSOL and MATLAB. Results: Inhibition or activation of pumps on the cell membrane led to reduction or increase in aerobic glycolysis, respectively, while oxidative phosphorylation remained unchanged. These results were consistent with computational simulations of changes in short-timescale demand for energy by cell membrane processes. A specific model prediction was that the spatial distribution of ATP-producing enzymes in the glycolytic pathway must be primarily localized adjacent to the cell membrane, while mitochondria should be predominantly peri-nuclear. These predictions were confirmed experimentally. Conclusion: The results in this work support a new model for glucose metabolism in which glycolysis and oxidative phosphorylation supply different types of energy demand. Similar to power grid economics, optimal metabolic control requires the two pathways, even in normoxic conditions, to match two different types of energy demands. Cells use aerobic metabolism to meet baseline, steady energy demand and glycolytic metabolism to meet short-timescale energy demands, mainly from membrane transport activities, even in the presence of oxygen. This model provides a mechanism for the origin of the Warburg effect in cancer cells. Here, the Warburg effect emerges during carcinogenesis is a physiological

SU-E-J-102: Separation of Metabolic Supply and Demand: From Power Grid Economics to Cancer Metabolism

International Nuclear Information System (INIS)

Epstein, T; Xu, L; Gillies, R; Gatenby, R

2014-01-01

Purpose: To study a new model of glucose metabolism which is primarily governed by the timescale of the energetic demand and not by the oxygen level, and its implication on cancer metabolism (Warburg effect) Methods: 1) Metabolic profiling of membrane transporters activity in several cell lines, which represent the spectrum from normal breast epithelium to aggressive, metastatic cancer, using Seahorse XF reader.2) Spatial localization of oxidative and non-oxidative metabolic components using immunocytochemical imaging of the glycolytic ATP-producing enzyme, pyruvate kinase and mitochondria. 3) Finite element simulations of coupled partial differential equations using COMSOL and MATLAB. Results: Inhibition or activation of pumps on the cell membrane led to reduction or increase in aerobic glycolysis, respectively, while oxidative phosphorylation remained unchanged. These results were consistent with computational simulations of changes in short-timescale demand for energy by cell membrane processes. A specific model prediction was that the spatial distribution of ATP-producing enzymes in the glycolytic pathway must be primarily localized adjacent to the cell membrane, while mitochondria should be predominantly peri-nuclear. These predictions were confirmed experimentally. Conclusion: The results in this work support a new model for glucose metabolism in which glycolysis and oxidative phosphorylation supply different types of energy demand. Similar to power grid economics, optimal metabolic control requires the two pathways, even in normoxic conditions, to match two different types of energy demands. Cells use aerobic metabolism to meet baseline, steady energy demand and glycolytic metabolism to meet short-timescale energy demands, mainly from membrane transport activities, even in the presence of oxygen. This model provides a mechanism for the origin of the Warburg effect in cancer cells. Here, the Warburg effect emerges during carcinogenesis is a physiological

Prediction of the metabolic cost of walking with and without loads.

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Duggan, A; Haisman, M F

1992-04-01

Measurement of the metabolic cost of walking inconveniences subjects, and requires skilled technical support and expensive equipment. These factors have stimulated interest in predictive equations. The present study assessed existing equations. Under each of 17 combinations of gradient (0-6%) and carried load (4.1-37.4 kg), 7-12 men undertook treadmill walking at 1.67 m/s. Measured oxygen consumption and respiratory exchange ratio were used to calculate metabolic rate (MRobserved). Metabolic rate was also predicted from the equation of Pandolf et al. (1977) (MRpandolf) and, where appropriate, from another five equations relating to walking without loads. MRobserved and MRpandolf did not differ significantly (p greater than 0.05) under any combination of gradient and load. The overall mean MRobserved and MRpandolf of 609 W and 602 W, respectively, also did not differ significantly (p greater than 0.05). These variables were highly correlated (r = 0.94) with a standard deviation about the prediction error of 47 W. For level walking without loads, the mean predictions from the equations of Pandolf et al. (1977) and Cotes and Meade (1960) did not differ significantly (p greater than 0.05) from the mean MRobserved of 428 Watts, but four other equations overestimated by 17-74 W. In conclusion, the Pandolf et al. (1977) equation has given good results across the range of combinations of load and gradient tested, and the errors are considered acceptable for most practical purposes.

A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

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Hojung Nam

2014-09-01

Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

Plasma metabolomics reveals membrane lipids, aspartate/asparagine and nucleotide metabolism pathway differences associated with chloroquine resistance in Plasmodium vivax malaria

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Salinas, Jorge L.; Monteiro, Wuelton M.; Val, Fernando; Cordy, Regina J.; Liu, Ken; Melo, Gisely C.; Siqueira, Andre M.; Magalhaes, Belisa; Galinski, Mary R.; Lacerda, Marcus V. G.; Jones, Dean P.

2017-01-01

Background Chloroquine (CQ) is the main anti-schizontocidal drug used in the treatment of uncomplicated malaria caused by Plasmodium vivax. Chloroquine resistant P. vivax (PvCR) malaria in the Western Pacific region, Asia and in the Americas indicates a need for biomarkers of resistance to improve therapy and enhance understanding of the mechanisms associated with PvCR. In this study, we compared plasma metabolic profiles of P. vivax malaria patients with PvCR and chloroquine sensitive parasites before treatment to identify potential molecular markers of chloroquine resistance. Methods An untargeted high-resolution metabolomics analysis was performed on plasma samples collected in a malaria clinic in Manaus, Brazil. Male and female patients with Plasmodium vivax were included (n = 46); samples were collected before CQ treatment and followed for 28 days to determine PvCR, defined as the recurrence of parasitemia with detectable plasma concentrations of CQ ≥100 ng/dL. Differentially expressed metabolic features between CQ-Resistant (CQ-R) and CQ-Sensitive (CQ-S) patients were identified using partial least squares discriminant analysis and linear regression after adjusting for covariates and multiple testing correction. Pathway enrichment analysis was performed using Mummichog. Results Linear regression and PLS-DA methods yielded 69 discriminatory features between CQ-R and CQ-S groups, with 10-fold cross-validation classification accuracy of 89.6% using a SVM classifier. Pathway enrichment analysis showed significant enrichment (p<0.05) of glycerophospholipid metabolism, glycosphingolipid metabolism, aspartate and asparagine metabolism, purine and pyrimidine metabolism, and xenobiotics metabolism. Glycerophosphocholines levels were significantly lower in the CQ-R group as compared to CQ-S patients and also to independent control samples. Conclusions The results show differences in lipid, amino acids, and nucleotide metabolism pathways in the plasma of CQ-R versus

Analysis of metabolic networks of Streptomyces leeuwenhoekii C34 by means of a genome scale model: Prediction of modifications that enhance the production of specialized metabolites.

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Razmilic, Valeria; Castro, Jean F; Andrews, Barbara; Asenjo, Juan A

2018-07-01

The first genome scale model (GSM) for Streptomyces leeuwenhoekii C34 was developed to study the biosynthesis pathways of specialized metabolites and to find metabolic engineering targets for enhancing their production. The model, iVR1007, consists of 1,722 reactions, 1,463 metabolites, and 1,007 genes, it includes the biosynthesis pathways of chaxamycins, chaxalactins, desferrioxamines, ectoine, and other specialized metabolites. iVR1007 was validated using experimental information of growth on 166 different sources of carbon, nitrogen and phosphorous, showing an 83.7% accuracy. The model was used to predict metabolic engineering targets for enhancing the biosynthesis of chaxamycins and chaxalactins. Gene knockouts, such as sle03600 (L-homoserine O-acetyltransferase), and sle39090 (trehalose-phosphate synthase), that enhance the production of the specialized metabolites by increasing the pool of precursors were identified. Using the algorithm of flux scanning based on enforced objective flux (FSEOF) implemented in python, 35 and 25 over-expression targets for increasing the production of chaxamycin A and chaxalactin A, respectively, that were not directly associated with their biosynthesis routes were identified. Nineteen over-expression targets that were common to the two specialized metabolites studied, like the over-expression of the acetyl carboxylase complex (sle47660 (accA) and any of the following genes: sle44630 (accA_1) or sle39830 (accA_2) or sle27560 (bccA) or sle59710) were identified. The predicted knockouts and over-expression targets will be used to perform metabolic engineering of S. leeuwenhoekii C34 and obtain overproducer strains. © 2018 Wiley Periodicals, Inc.

Metabolic engineering of E. coli top 10 for production of vanillin through FA catabolic pathway and bioprocess optimization using RSM.

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Chakraborty, Debkumar; Gupta, Gaganjot; Kaur, Baljinder

2016-12-01

Metabolic engineering and construction of recombinant Escherichia coli strains carrying feruloyl-CoA synthetase and enoyl-CoA hydratase genes for the bioconversion of ferulic acid to vanillin offers an alternative way to produce vanillin. Isolation and designing of fcs and ech genes was carried out using computer assisted protocol and the designed vanillin biosynthetic gene cassette was cloned in pCCIBAC expression vector for introduction in E. coli top 10. Recombinant strain was implemented for the statistical optimization of process parameters influencing F A to vanillin biotransformation. CCD matrix constituted of process variables like FA concentration, time, temperature and biomass with intracellular, extracellular and total vanillin productions as responses. Production was scaled up and 68 mg/L of vanillin was recovered from 10 mg/L of FA using cell extracts from 1 mg biomass within 30 min. Kinetic activity of enzymes were characterized. From LCMS-ESI analysis a metabolic pathway of FA degradation and vanillin production was predicted. Copyright © 2016 Elsevier Inc. All rights reserved.

Computational and experimental analysis of redundancy in the central metabolism of Geobacter sulfurreducens.

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Daniel Segura

2008-02-01

Full Text Available Previous model-based analysis of the metabolic network of Geobacter sulfurreducens suggested the existence of several redundant pathways. Here, we identified eight sets of redundant pathways that included redundancy for the assimilation of acetate, and for the conversion of pyruvate into acetyl-CoA. These equivalent pathways and two other sub-optimal pathways were studied using 5 single-gene deletion mutants in those pathways for the evaluation of the predictive capacity of the model. The growth phenotypes of these mutants were studied under 12 different conditions of electron donor and acceptor availability. The comparison of the model predictions with the resulting experimental phenotypes indicated that pyruvate ferredoxin oxidoreductase is the only activity able to convert pyruvate into acetyl-CoA. However, the results and the modeling showed that the two acetate activation pathways present are not only active, but needed due to the additional role of the acetyl-CoA transferase in the TCA cycle, probably reflecting the adaptation of these bacteria to acetate utilization. In other cases, the data reconciliation suggested additional capacity constraints that were confirmed with biochemical assays. The results demonstrate the need to experimentally verify the activity of key enzymes when developing in silico models of microbial physiology based on sequence-based reconstruction of metabolic networks.

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

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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.

Harnessing natural diversity to probe metabolic pathways.

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Oliver R Homann

2005-12-01

Full Text Available Analyses of cellular processes in the yeast Saccharomyces cerevisiae rely primarily upon a small number of highly domesticated laboratory strains, leaving the extensive natural genetic diversity of the model organism largely unexplored and unexploited. We asked if this diversity could be used to enrich our understanding of basic biological processes. As a test case, we examined a simple trait: the utilization of di/tripeptides as nitrogen sources. The capacity to import small peptides is likely to be under opposing selective pressures (nutrient utilization versus toxin vulnerability and may therefore be sculpted by diverse pathways and strategies. Hitherto, dipeptide utilization in S. cerevisiae was solely ascribed to the activity of a single protein, the Ptr2p transporter. Using high-throughput phenotyping and several genetically diverse strains, we identified previously unknown cellular activities that contribute to this trait. We find that the Dal5p allantoate/ureidosuccinate permease is also capable of facilitating di/tripeptide transport. Moreover, even in the absence of Dal5p and Ptr2p, an additional activity--almost certainly the periplasmic asparaginase II Asp3p--facilitates the utilization of dipeptides with C-terminal asparagine residues by a different strategy. Another, as-yet-unidentified activity enables the utilization of dipeptides with C-terminal arginine residues. The relative contributions of these activities to the utilization of di/tripeptides vary among the strains analyzed, as does the vulnerability of these strains to a toxic dipeptide. Only by sampling the genetic diversity of multiple strains were we able to uncover several previously unrecognized layers of complexity in this metabolic pathway. High-throughput phenotyping facilitates the rapid exploration of the molecular basis of biological complexity, allowing for future detailed investigation of the selective pressures that drive microbial evolution.

D-Serine exposure resulted in gene expression changes indicative of activation of fibrogenic pathways and down-regulation of energy metabolism and oxidative stress response

International Nuclear Information System (INIS)

Soto, Armando; DelRaso, Nicholas J.; Schlager, John J.; Chan, Victor T.

2008-01-01

, metabolism and transport, inflammatory response, proteasome-mediated degradation of oxidatively damaged cytosolic proteins, Ras protein signal transduction, TGF-beta signaling pathway and mRNA transcription, processing, splicing and transport. On the other hand, major metabolic pathways, which include carbohydrate metabolism, TCA cycle, oxidative phosphorylation, ATP synthesis coupled electron transport, amino acid metabolism and transport, lipid metabolism, nucleotide metabolism, and vitamin metabolism, and oxidative stress response including induction of antioxidant genes and glutathione metabolism are down-regulated. As tubular epithelia have strong energy demand for normal functions, down-regulation of energy metabolism after D-serine treatment may be related to the mechanism of its nephrotoxicity. In addition, hydrogen peroxide, a reactive oxygen species, is produced as a byproduct of the metabolism of D-serine by D-amino acid oxidase in the peroxisomes of the tubular epithelia. Down-regulation of pathways for antioxidant genes induction and glutathione metabolism will likely exacerbate the cytotoxicity of this reactive oxygen species. The observation that the genes involved in apoptosis, DNA repair, proteasome pathway for the degradation of oxidatively damaged cytosolic proteins were up-regulated lends some supports to this premise. Up-regulation of pathways of cell proliferation cycle, DNA replication and gene expression process, including mRNA transcription, processing, splicing, transport, translation initiation, and protein transport along with protein complex assembly, suggests ongoing tissue repair and regeneration. Consistent with the fibrogenic function of the TGF-beta signaling pathway in various experimental renal diseases, genes encoding major extracellular matrix components such as collagens, laminins, fibronectin 1 and tenascins are also strongly up-regulated. Taken together, the results of this study provide important insights into the molecular mechanism

Metabolomics by proton nuclear magnetic resonance spectroscopy of the response to chloroethylnitrosourea reveals drug efficacy and tumor adaptive metabolic pathways.

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Morvan, Daniel; Demidem, Aicha

2007-03-01

Metabolomics of tumors may allow discovery of tumor biomarkers and metabolic therapeutic targets. Metabolomics by two-dimensional proton high-resolution magic angle spinning nuclear magnetic resonance spectroscopy was applied to investigate metabolite disorders following treatment by chloroethylnitrosourea of murine B16 melanoma (n = 33) and 3LL pulmonary carcinoma (n = 31) in vivo. Treated tumors of both types resumed growth after a delay. Nitrosoureas provoke DNA damage but the metabolic consequences of genotoxic stress are little known yet. Although some differences were observed in the metabolite profile of untreated tumor types, the prominent metabolic features of the response to nitrosourea were common to both. During the growth inhibition phase, there was an accumulation of glucose (more than x10; P < 0.05), glutamine (x3 to 4; P < 0.01), and aspartate (x2 to 5; P < 0.01). This response testified to nucleoside de novo synthesis down-regulation and drug efficacy. However, this phase also involved the increase in alanine (P < 0.001 in B16 melanoma), the decrease in succinate (P < 0.001), and the accumulation of serine-derived metabolites (glycine, phosphoethanolamine, and formate; P < 0.01). This response witnessed the activation of pathways implicated in energy production and resumption of nucleotide de novo synthesis, thus metabolic pathways of DNA repair and adaptation to treatment. During the growth recovery phase, it remained polyunsaturated fatty acid accumulation (x1.5 to 2; P < 0.05) and reduced utilization of glucose compared with glutamine (P < 0.05), a metabolic fingerprint of adaptation. Thus, this study provides the proof of principle that metabolomics of tumor response to an anticancer agent may help discover metabolic pathways of drug efficacy and adaptation to treatment.

Fatty Liver Index and Lipid Accumulation Product Can Predict Metabolic Syndrome in Subjects without Fatty Liver Disease

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Yuan-Lung Cheng

2017-01-01

Full Text Available Background. Fatty liver index (FLI and lipid accumulation product (LAP are indexes originally designed to assess the risk of fatty liver and cardiovascular disease, respectively. Both indexes have been proven to be reliable markers of subsequent metabolic syndrome; however, their ability to predict metabolic syndrome in subjects without fatty liver disease has not been clarified. Methods. We enrolled consecutive subjects who received health check-up services at Taipei Veterans General Hospital from 2002 to 2009. Fatty liver disease was diagnosed by abdominal ultrasonography. The ability of the FLI and LAP to predict metabolic syndrome was assessed by analyzing the area under the receiver operating characteristic (AUROC curve. Results. Male sex was strongly associated with metabolic syndrome, and the LAP and FLI were better than other variables to predict metabolic syndrome among the 29,797 subjects. Both indexes were also better than other variables to detect metabolic syndrome in subjects without fatty liver disease (AUROC: 0.871 and 0.879, resp., and the predictive power was greater among women. Conclusion. Metabolic syndrome increases the cardiovascular disease risk. The FLI and LAP could be used to recognize the syndrome in both subjects with and without fatty liver disease who require lifestyle modifications and counseling.

From pathways to genomes and beyond. The metabolic engineering toolbox and its place in biofuels production

Energy Technology Data Exchange (ETDEWEB)

Liu, Leqian; Reed, Ben; Alper, Hal [Texas Univ., Austin, TX (United States). Dept. of Chemical Engineering

2011-07-01

Concerns about the availability of petroleum-derived fuels and chemicals have led to the exploration of metabolically engineered organisms as novel hosts for biofuels and chemicals production. However, the complexity inherent in metabolic and regulatory networks makes this undertaking a complex task. To address these limitations, metabolic engineering has adapted a wide-variety of tools for altering phenotypes. In this review, we will highlight traditional and recent metabolic engineering tools for optimizing cells including pathway-based, global, and genomic-enabled approaches. Specifically, we describe these tools as well as provide demonstrations of their effectiveness in optimizing biofuels production. However, each of these tools provides stepping stones towards the grand goal of biofuels production. Thus, developing methods for large-scale cellular optimization and integrative approaches are invaluable for further cell optimization. This review highlights the challenges that still must be met to accomplish this goal. (orig.)

LeishCyc: a biochemical pathways database for Leishmania major

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Doyle Maria A

2009-06-01

Full Text Available Abstract Background Leishmania spp. are sandfly transmitted protozoan parasites that cause a spectrum of diseases in more than 12 million people worldwide. Much research is now focusing on how these parasites adapt to the distinct nutrient environments they encounter in the digestive tract of the sandfly vector and the phagolysosome compartment of mammalian macrophages. While data mining and annotation of the genomes of three Leishmania species has provided an initial inventory of predicted metabolic components and associated pathways, resources for integrating this information into metabolic networks and incorporating data from transcript, protein, and metabolite profiling studies is currently lacking. The development of a reliable, expertly curated, and widely available model of Leishmania metabolic networks is required to facilitate systems analysis, as well as discovery and prioritization of new drug targets for this important human pathogen. Description The LeishCyc database was initially built from the genome sequence of Leishmania major (v5.2, based on the annotation published by the Wellcome Trust Sanger Institute. LeishCyc was manually curated to remove errors, correct automated predictions, and add information from the literature. The ongoing curation is based on public sources, literature searches, and our own experimental and bioinformatics studies. In a number of instances we have improved on the original genome annotation, and, in some ambiguous cases, collected relevant information from the literature in order to help clarify gene or protein annotation in the future. All genes in LeishCyc are linked to the corresponding entry in GeneDB (Wellcome Trust Sanger Institute. Conclusion The LeishCyc database describes Leishmania major genes, gene products, metabolites, their relationships and biochemical organization into metabolic pathways. LeishCyc provides a systematic approach to organizing the evolving information about Leishmania

Construction and completion of flux balance models from pathway databases.

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

2012-02-01

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

Effects of CD44 Ligation on Signaling and Metabolic Pathways in Acute Myeloid Leukemia

KAUST Repository

Madhoun, Nour Y.

2017-04-01

Acute myeloid leukemia (AML) is characterized by a blockage in the differentiation of myeloid cells at different stages. CD44-ligation using anti-CD44 monoclonal antibodies (mAbs) has been shown to reverse the blockage of differentiation and to inhibit the proliferation of blasts in most AML-subtypes. However, the molecular mechanisms underlying this property have not been fully elucidated. Here, we sought to I) analyze the effects of anti-CD44 mAbs on downstream signaling pathways, including the ERK1/2 (extracellular signal-regulated kinase 1 and 2) and mTOR (mammalian target of rapamycin) pathways and II) use state-of-the-art Nuclear Magnetic Resonance (NMR) technology to determine the global metabolic changes during differentiation induction of AML cells using anti-CD44 mAbs and other two previously reported differentiation agents. In the first objective (Chapter 4), our studies provide evidence that CD44-ligation with specific mAbs in AML cells induced an increase in ERK1/2 phosphorylation. The use of the MEK inhibitor (U0126) significantly inhibited the CD44-induced differentiation of HL60 cells, suggesting that ERK1/2 is critical for the CD44-triggered differentiation in AML. In addition, this was accompanied by a marked decrease in the phosphorylation of the mTORC1 and mTORC2 complexes, which are strongly correlated with the inhibition of the PI3K/Akt pathway. In the second objective (Chapter 5), 1H NMR experiments demonstrated that considerable changes in the metabolic profiles of HL60 cells were induced in response to each differentiation agent. These most notable metabolites that significantly changed upon CD44 ligation were involved in the tricarboxylic acid (TCA) cycle and glycolysis such as, succinate, fumarate and lactate. Therefore, we sought to analyze the mechanisms underlying their alterations. Our results revealed that anti-CD44 mAbs treatment induced upregulation in fumarate hydratase (FH) expression and its activity which was accompanied by a

A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4

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Zi-Ru Dai

2015-06-01

Full Text Available Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s and the site(s of modification. The newly established model was applied to predict the metabolic site(s of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s of CYP3A4 on steroids with high predictive accuracy.

GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes

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Nakayama Yoichi

2006-03-01

Full Text Available Abstract Background Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology. Results We developed the Genome-based Modeling (GEM System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model. Conclusion The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.

Vitamin D metabolic pathway genes and pancreatic cancer risk.

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Hannah Arem

Full Text Available Evidence on the association between vitamin D status and pancreatic cancer risk is inconsistent. This inconsistency may be partially attributable to variation in vitamin D regulating genes. We selected 11 vitamin D-related genes (GC, DHCR7, CYP2R1, VDR, CYP27B1, CYP24A1, CYP27A1, RXRA, CRP2, CASR and CUBN totaling 213 single nucleotide polymorphisms (SNPs, and examined associations with pancreatic adenocarcinoma. Our study included 3,583 pancreatic cancer cases and 7,053 controls from the genome-wide association studies of pancreatic cancer PanScans-I-III. We used the Adaptive Joint Test and the Adaptive Rank Truncated Product statistic for pathway and gene analyses, and unconditional logistic regression for SNP analyses, adjusting for age, sex, study and population stratification. We examined effect modification by circulating vitamin D concentration (≤50, >50 nmol/L for the most significant SNPs using a subset of cohort cases (n = 713 and controls (n = 878. The vitamin D metabolic pathway was not associated with pancreatic cancer risk (p = 0.830. Of the individual genes, none were associated with pancreatic cancer risk at a significance level of p<0.05. SNPs near the VDR (rs2239186, LRP2 (rs4668123, CYP24A1 (rs2762932, GC (rs2282679, and CUBN (rs1810205 genes were the top SNPs associated with pancreatic cancer (p-values 0.008-0.037, but none were statistically significant after adjusting for multiple comparisons. Associations between these SNPs and pancreatic cancer were not modified by circulating concentrations of vitamin D. These findings do not support an association between vitamin D-related genes and pancreatic cancer risk. Future research should explore other pathways through which vitamin D status might be associated with pancreatic cancer risk.

From elementary flux modes to elementary flux vectors: Metabolic pathway analysis with arbitrary linear flux constraints

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Klamt, Steffen; Gerstl, Matthias P.; Jungreuthmayer, Christian; Mahadevan, Radhakrishnan; Müller, Stefan

2017-01-01

Elementary flux modes (EFMs) emerged as a formal concept to describe metabolic pathways and have become an established tool for constraint-based modeling and metabolic network analysis. EFMs are characteristic (support-minimal) vectors of the flux cone that contains all feasible steady-state flux vectors of a given metabolic network. EFMs account for (homogeneous) linear constraints arising from reaction irreversibilities and the assumption of steady state; however, other (inhomogeneous) linear constraints, such as minimal and maximal reaction rates frequently used by other constraint-based techniques (such as flux balance analysis [FBA]), cannot be directly integrated. These additional constraints further restrict the space of feasible flux vectors and turn the flux cone into a general flux polyhedron in which the concept of EFMs is not directly applicable anymore. For this reason, there has been a conceptual gap between EFM-based (pathway) analysis methods and linear optimization (FBA) techniques, as they operate on different geometric objects. One approach to overcome these limitations was proposed ten years ago and is based on the concept of elementary flux vectors (EFVs). Only recently has the community started to recognize the potential of EFVs for metabolic network analysis. In fact, EFVs exactly represent the conceptual development required to generalize the idea of EFMs from flux cones to flux polyhedra. This work aims to present a concise theoretical and practical introduction to EFVs that is accessible to a broad audience. We highlight the close relationship between EFMs and EFVs and demonstrate that almost all applications of EFMs (in flux cones) are possible for EFVs (in flux polyhedra) as well. In fact, certain properties can only be studied with EFVs. Thus, we conclude that EFVs provide a powerful and unifying framework for constraint-based modeling of metabolic networks. PMID:28406903

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.

Prediction of cytochrome P450 mediated metabolism

DEFF Research Database (Denmark)

Olsen, Lars; Oostenbrink, Chris; Jørgensen, Flemming Steen

2015-01-01

Cytochrome P450 enzymes (CYPs) form one of the most important enzyme families involved in the metabolism of xenobiotics. CYPs comprise many isoforms, which catalyze a wide variety of reactions, and potentially, a large number of different metabolites can be formed. However, it is often hard...... to rationalize what metabolites these enzymes generate. In recent years, many different in silico approaches have been developed to predict binding or regioselective product formation for the different CYP isoforms. These comprise ligand-based methods that are trained on experimental CYP data and structure...

Metabolic enzyme expression highlights a key role for MTHFD2 and the mitochondrial folate pathway in cancer

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Nilsson, Roland; Jain, Mohit; Madhusudhan, Nikhil; Sheppard, Nina Gustafsson; Strittmatter, Laura; Kampf, Caroline; Huang, Jenny; Asplund, Anna; Mootha, Vamsi K.

2014-01-01

Metabolic remodeling is now widely regarded as a hallmark of cancer, but it is not clear whether individual metabolic strategies are frequently exploited by many tumours. Here we compare messenger RNA profiles of 1,454 metabolic enzymes across 1,981 tumours spanning 19 cancer types to identify enzymes that are consistently differentially expressed. Our meta-analysis recovers established targets of some of the most widely used chemotherapeutics, including dihydrofolate reductase, thymidylate synthase and ribonucleotide reductase, while also spotlighting new enzymes, such as the mitochondrial proline biosynthetic enzyme PYCR1. The highest scoring pathway is mitochondrial one-carbon metabolism and is centred on MTHFD2. MTHFD2 RNA and protein are markedly elevated in many cancers and correlated with poor survival in breast cancer. MTHFD2 is expressed in the developing embryo, but is absent in most healthy adult tissues, even those that are proliferating. Our study highlights the importance of mitochondrial compartmentalization of one-carbon metabolism in cancer and raises important therapeutic hypotheses.

Plant interactions alter the predictions of metabolic scaling theory.

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Yue Lin

Full Text Available Metabolic scaling theory (MST is an attempt to link physiological processes of individual organisms with macroecology. It predicts a power law relationship with an exponent of -4/3 between mean individual biomass and density during density-dependent mortality (self-thinning. Empirical tests have produced variable results, and the validity of MST is intensely debated. MST focuses on organisms' internal physiological mechanisms but we hypothesize that ecological interactions can be more important in determining plant mass-density relationships induced by density. We employ an individual-based model of plant stand development that includes three elements: a model of individual plant growth based on MST, different modes of local competition (size-symmetric vs. -asymmetric, and different resource levels. Our model is consistent with the observed variation in the slopes of self-thinning trajectories. Slopes were significantly shallower than -4/3 if competition was size-symmetric. We conclude that when the size of survivors is influenced by strong ecological interactions, these can override predictions of MST, whereas when surviving plants are less affected by interactions, individual-level metabolic processes can scale up to the population level. MST, like thermodynamics or biomechanics, sets limits within which organisms can live and function, but there may be stronger limits determined by ecological interactions. In such cases MST will not be predictive.

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.

Shape shifting predicts ontogenetic changes in metabolic scaling in diverse aquatic invertebrates.

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Glazier, Douglas S; Hirst, Andrew G; Atkinson, David

2015-03-07

Metabolism fuels all biological activities, and thus understanding its variation is fundamentally important. Much of this variation is related to body size, which is commonly believed to follow a 3/4-power scaling law. However, during ontogeny, many kinds of animals and plants show marked shifts in metabolic scaling that deviate from 3/4-power scaling predicted by general models. Here, we show that in diverse aquatic invertebrates, ontogenetic shifts in the scaling of routine metabolic rate from near isometry (bR = scaling exponent approx. 1) to negative allometry (bR < 1), or the reverse, are associated with significant changes in body shape (indexed by bL = the scaling exponent of the relationship between body mass and body length). The observed inverse correlations between bR and bL are predicted by metabolic scaling theory that emphasizes resource/waste fluxes across external body surfaces, but contradict theory that emphasizes resource transport through internal networks. Geometric estimates of the scaling of surface area (SA) with body mass (bA) further show that ontogenetic shifts in bR and bA are positively correlated. These results support new metabolic scaling theory based on SA influences that may be applied to ontogenetic shifts in bR shown by many kinds of animals and plants. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Integration of Pathway Knowledge and Dynamic Bayesian Networks for the Prediction of Oral Cancer Recurrence.

Science.gov (United States)

Kourou, Konstantina; Papaloukas, Costas; Fotiadis, Dimitrios I

2017-03-01

Oral squamous cell carcinoma has been characterized as a complex disease which involves dynamic genomic changes at the molecular level. These changes indicate the worth to explore the interactions of the molecules and especially of differentially expressed genes that contribute to cancer progression. Moreover, based on this knowledge the identification of differentially expressed genes and related molecular pathways is of great importance. In the present study, we exploit differentially expressed genes in order to further perform pathway enrichment analysis. According to our results we found significant pathways in which the disease associated genes have been identified as strongly enriched. Furthermore, based on the results of the pathway enrichment analysis we propose a methodology for predicting oral cancer recurrence using dynamic Bayesian networks. The methodology takes into consideration time series gene expression data in order to predict a disease recurrence. Subsequently, we are able to conjecture about the causal interactions between genes in consecutive time intervals. Concerning the performance of the predictive models, the overall accuracy of the algorithm is 81.8% and the area under the ROC curve 89.2% regarding the knowledge from the overrepresented pre-NOTCH Expression and processing pathway.

Mood stabilizing drugs regulate transcription of immune, neuronal and metabolic pathway genes in Drosophila.

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Herteleer, L; Zwarts, L; Hens, K; Forero, D; Del-Favero, J; Callaerts, P

2016-05-01

Lithium and valproate (VPA) are drugs used in the management of bipolar disorder. Even though they reportedly act on various pathways, the transcriptional targets relevant for disease mechanism and therapeutic effect remain unclear. Furthermore, multiple studies used lymphoblasts of bipolar patients as a cellular proxy, but it remains unclear whether peripheral cells provide a good readout for the effects of these drugs in the brain. We used Drosophila culture cells and adult flies to analyze the transcriptional effects of lithium and VPA and define mechanistic pathways. Transcriptional profiles were determined for Drosophila S2-cells and adult fly heads following lithium or VPA treatment. Gene ontology categories were identified using the DAVID functional annotation tool with a cut-off of p neuronal development, neuronal function, and metabolism. (i) Transcriptional effects of lithium and VPA in Drosophila S2 cells and heads show significant overlap. (ii) The overlap between transcriptional alterations in peripheral versus neuronal cells at the single gene level is negligible, but at the gene ontology and pathway level considerable overlap can be found. (iii) Lithium and VPA act on evolutionarily conserved pathways in Drosophila and mammalian models.

Thermodynamic analysis of computed pathways integrated into the metabolic networks of E. coli and Synechocystis reveals contrasting expansion potential.

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Asplund-Samuelsson, Johannes; Janasch, Markus; Hudson, Elton P

2018-01-01

Introducing biosynthetic pathways into an organism is both reliant on and challenged by endogenous biochemistry. Here we compared the expansion potential of the metabolic network in the photoautotroph Synechocystis with that of the heterotroph E. coli using the novel workflow POPPY (Prospecting Optimal Pathways with PYthon). First, E. coli and Synechocystis metabolomic and fluxomic data were combined with metabolic models to identify thermodynamic constraints on metabolite concentrations (NET analysis). Then, thousands of automatically constructed pathways were placed within each network and subjected to a network-embedded variant of the max-min driving force analysis (NEM). We found that the networks had different capabilities for imparting thermodynamic driving forces toward certain compounds. Key metabolites were constrained differently in Synechocystis due to opposing flux directions in glycolysis and carbon fixation, the forked tri-carboxylic acid cycle, and photorespiration. Furthermore, the lysine biosynthesis pathway in Synechocystis was identified as thermodynamically constrained, impacting both endogenous and heterologous reactions through low 2-oxoglutarate levels. Our study also identified important yet poorly covered areas in existing metabolomics data and provides a reference for future thermodynamics-based engineering in Synechocystis and beyond. The POPPY methodology represents a step in making optimal pathway-host matches, which is likely to become important as the practical range of host organisms is diversified. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

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Shi, CY; Yang, H; Wei, CL; Yu, O; Zhang, ZZ; Sun, J; Wan, XC

2011-01-01

Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq) provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Using high-throughput Illumina RNA-seq, the transcriptome from poly (A){sup +} RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs). Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010). Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG) found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were analyzed by RT-PCR and quantitative real

Deep sequencing of the Camellia sinensis transcriptome revealed candidate genes for major metabolic pathways of tea-specific compounds

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Chen Qi

2011-02-01

Full Text Available Abstract Background Tea is one of the most popular non-alcoholic beverages worldwide. However, the tea plant, Camellia sinensis, is difficult to culture in vitro, to transform, and has a large genome, rendering little genomic information available. Recent advances in large-scale RNA sequencing (RNA-seq provide a fast, cost-effective, and reliable approach to generate large expression datasets for functional genomic analysis, which is especially suitable for non-model species with un-sequenced genomes. Results Using high-throughput Illumina RNA-seq, the transcriptome from poly (A+ RNA of C. sinensis was analyzed at an unprecedented depth (2.59 gigabase pairs. Approximate 34.5 million reads were obtained, trimmed, and assembled into 127,094 unigenes, with an average length of 355 bp and an N50 of 506 bp, which consisted of 788 contig clusters and 126,306 singletons. This number of unigenes was 10-fold higher than existing C. sinensis sequences deposited in GenBank (as of August 2010. Sequence similarity analyses against six public databases (Uniprot, NR and COGs at NCBI, Pfam, InterPro and KEGG found 55,088 unigenes that could be annotated with gene descriptions, conserved protein domains, or gene ontology terms. Some of the unigenes were assigned to putative metabolic pathways. Targeted searches using these annotations identified the majority of genes associated with several primary metabolic pathways and natural product pathways that are important to tea quality, such as flavonoid, theanine and caffeine biosynthesis pathways. Novel candidate genes of these secondary pathways were discovered. Comparisons with four previously prepared cDNA libraries revealed that this transcriptome dataset has both a high degree of consistency with previous EST data and an approximate 20 times increase in coverage. Thirteen unigenes related to theanine and flavonoid synthesis were validated. Their expression patterns in different organs of the tea plant were

Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks

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Chiappino-Pepe, Anush; Ataman, Meriç

2017-01-01

Novel antimalarial therapies are urgently needed for the fight against drug-resistant parasites. The metabolism of malaria parasites in infected cells is an attractive source of drug targets but is rather complex. Computational methods can handle this complexity and allow integrative analyses of cell metabolism. In this study, we present a genome-scale metabolic model (iPfa) of the deadliest malaria parasite, Plasmodium falciparum, and its thermodynamics-based flux analysis (TFA). Using previous absolute concentration data of the intraerythrocytic parasite, we applied TFA to iPfa and predicted up to 63 essential genes and 26 essential pairs of genes. Of the 63 genes, 35 have been experimentally validated and reported in the literature, and 28 have not been experimentally tested and include previously hypothesized or novel predictions of essential metabolic capabilities. Without metabolomics data, four of the genes would have been incorrectly predicted to be non-essential. TFA also indicated that substrate channeling should exist in two metabolic pathways to ensure the thermodynamic feasibility of the flux. Finally, analysis of the metabolic capabilities of P. falciparum led to the identification of both the minimal nutritional requirements and the genes that can become indispensable upon substrate inaccessibility. This model provides novel insight into the metabolic needs and capabilities of the malaria parasite and highlights metabolites and pathways that should be measured and characterized to identify potential thermodynamic bottlenecks and substrate channeling. The hypotheses presented seek to guide experimental studies to facilitate a better understanding of the parasite metabolism and the identification of targets for more efficient intervention. PMID:28333921

Bioenergetics-based modeling of Plasmodium falciparum metabolism reveals its essential genes, nutritional requirements, and thermodynamic bottlenecks.

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Anush Chiappino-Pepe

2017-03-01

Full Text Available Novel antimalarial therapies are urgently needed for the fight against drug-resistant parasites. The metabolism of malaria parasites in infected cells is an attractive source of drug targets but is rather complex. Computational methods can handle this complexity and allow integrative analyses of cell metabolism. In this study, we present a genome-scale metabolic model (iPfa of the deadliest malaria parasite, Plasmodium falciparum, and its thermodynamics-based flux analysis (TFA. Using previous absolute concentration data of the intraerythrocytic parasite, we applied TFA to iPfa and predicted up to 63 essential genes and 26 essential pairs of genes. Of the 63 genes, 35 have been experimentally validated and reported in the literature, and 28 have not been experimentally tested and include previously hypothesized or novel predictions of essential metabolic capabilities. Without metabolomics data, four of the genes would have been incorrectly predicted to be non-essential. TFA also indicated that substrate channeling should exist in two metabolic pathways to ensure the thermodynamic feasibility of the flux. Finally, analysis of the metabolic capabilities of P. falciparum led to the identification of both the minimal nutritional requirements and the genes that can become indispensable upon substrate inaccessibility. This model provides novel insight into the metabolic needs and capabilities of the malaria parasite and highlights metabolites and pathways that should be measured and characterized to identify potential thermodynamic bottlenecks and substrate channeling. The hypotheses presented seek to guide experimental studies to facilitate a better understanding of the parasite metabolism and the identification of targets for more efficient intervention.

Comparison of the accuracy of three algorithms in predicting accessory pathways among adult Wolff-Parkinson-White syndrome patients.

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Maden, Orhan; Balci, Kevser Gülcihan; Selcuk, Mehmet Timur; Balci, Mustafa Mücahit; Açar, Burak; Unal, Sefa; Kara, Meryem; Selcuk, Hatice

2015-12-01

The aim of this study was to investigate the accuracy of three algorithms in predicting accessory pathway locations in adult patients with Wolff-Parkinson-White syndrome in Turkish population. A total of 207 adult patients with Wolff-Parkinson-White syndrome were retrospectively analyzed. The most preexcited 12-lead electrocardiogram in sinus rhythm was used for analysis. Two investigators blinded to the patient data used three algorithms for prediction of accessory pathway location. Among all locations, 48.5% were left-sided, 44% were right-sided, and 7.5% were located in the midseptum or anteroseptum. When only exact locations were accepted as match, predictive accuracy for Chiang was 71.5%, 72.4% for d'Avila, and 71.5% for Arruda. The percentage of predictive accuracy of all algorithms did not differ between the algorithms (p = 1.000; p = 0.875; p = 0.885, respectively). The best algorithm for prediction of right-sided, left-sided, and anteroseptal and midseptal accessory pathways was Arruda (p algorithms were similar in predicting accessory pathway location and the predicted accuracy was lower than previously reported by their authors. However, according to the accessory pathway site, the algorithm designed by Arruda et al. showed better predictions than the other algorithms and using this algorithm may provide advantages before a planned ablation.

Enhancing GDP-fucose production in recombinant Escherichia coli by metabolic pathway engineering.

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Zhai, Yafei; Han, Donglei; Pan, Ying; Wang, Shuaishuai; Fang, Junqiang; Wang, Peng; Liu, Xian-wei

2015-02-01

Guanosine 5'-diphosphate (GDP)-fucose is the indispensible donor substrate for fucosyltransferase-catalyzed synthesis of fucose-containing biomolecules, which have been found involving in various biological functions. In this work, the salvage pathway for GDP-fucose biosynthesis from Bacterioides fragilis was introduced into Escherichia coli. Besides, the biosynthesis of guanosine 5'-triphosphate (GTP), an essential substrate for GDP-fucose biosynthesis, was enhanced via overexpression of enzymes involved in the salvage pathway of GTP biosynthesis. The production capacities of metabolically engineered strains bearing different combinations of recombinant enzymes were compared. The shake flask fermentation of the strain expressing Fkp, Gpt, Gmk and Ndk obtained the maximum GDP-fucose content of 4.6 ± 0.22 μmol/g (dry cell mass), which is 4.2 fold that of the strain only expressing Fkp. Through fed-batch fermentation, the GDP-fucose content further rose to 6.6 ± 0.14 μmol/g (dry cell mass). In addition to a better productivity than previous fermentation processes based on the de novo pathway for GDP-fucose biosynthesis, the established schemes in this work also have the advantage to be a potential avenue to GDP-fucose analogs encompassing chemical modification on the fucose residue. Copyright © 2014 Elsevier Inc. All rights reserved.

NAViGaTing the micronome--using multiple microRNA prediction databases to identify signalling pathway-associated microRNAs.

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Elize A Shirdel

2011-02-01

Full Text Available MicroRNAs are a class of small RNAs known to regulate gene expression at the transcript level, the protein level, or both. Since microRNA binding is sequence-based but possibly structure-specific, work in this area has resulted in multiple databases storing predicted microRNA:target relationships computed using diverse algorithms. We integrate prediction databases, compare predictions to in vitro data, and use cross-database predictions to model the microRNA:transcript interactome--referred to as the micronome--to study microRNA involvement in well-known signalling pathways as well as associations with disease. We make this data freely available with a flexible user interface as our microRNA Data Integration Portal--mirDIP (http://ophid.utoronto.ca/mirDIP.mirDIP integrates prediction databases to elucidate accurate microRNA:target relationships. Using NAViGaTOR to produce interaction networks implicating microRNAs in literature-based, KEGG-based and Reactome-based pathways, we find these signalling pathway networks have significantly more microRNA involvement compared to chance (p<0.05, suggesting microRNAs co-target many genes in a given pathway. Further examination of the micronome shows two distinct classes of microRNAs; universe microRNAs, which are involved in many signalling pathways; and intra-pathway microRNAs, which target multiple genes within one signalling pathway. We find universe microRNAs to have more targets (p<0.0001, to be more studied (p<0.0002, and to have higher degree in the KEGG cancer pathway (p<0.0001, compared to intra-pathway microRNAs.Our pathway-based analysis of mirDIP data suggests microRNAs are involved in intra-pathway signalling. We identify two distinct classes of microRNAs, suggesting a hierarchical organization of microRNAs co-targeting genes both within and between pathways, and implying differential involvement of universe and intra-pathway microRNAs at the disease level.

Structuring evolution: biochemical networks and metabolic diversification in birds.

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Morrison, Erin S; Badyaev, Alexander V

2016-08-25

Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a "global" carotenoid network - comprising of all known enzymatic reactions among naturally occurring carotenoids - with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds. We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network - compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution. The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.

Reprogramming One-Carbon Metabolic Pathways To Decouple l-Serine Catabolism from Cell Growth in Corynebacterium glutamicum.

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Zhang, Yun; Shang, Xiuling; Lai, Shujuan; Zhang, Yu; Hu, Qitiao; Chai, Xin; Wang, Bo; Liu, Shuwen; Wen, Tingyi

2018-02-16

l-Serine, the principal one-carbon source for DNA biosynthesis, is difficult for microorganisms to accumulate due to the coupling of l-serine catabolism and microbial growth. Here, we reprogrammed the one-carbon unit metabolic pathways in Corynebacterium glutamicum to decouple l-serine catabolism from cell growth. In silico model-based simulation showed a negative influence on glyA-encoding serine hydroxymethyltransferase flux with l-serine productivity. Attenuation of glyA transcription resulted in increased l-serine accumulation, and a decrease in purine pools, poor growth and longer cell shapes. The gcvTHP-encoded glycine cleavage (Gcv) system from Escherichia coli was introduced into C. glutamicum, allowing glycine-derived 13 CH 2 to be assimilated into intracellular purine synthesis, which resulted in an increased amount of one-carbon units. Gcv introduction not only restored cell viability and morphology but also increased l-serine accumulation. Moreover, comparative proteomic analysis indicated that abundance changes of the enzymes involved in one-carbon unit cycles might be responsible for maintaining one-carbon unit homeostasis. Reprogramming of the one-carbon metabolic pathways allowed cells to reach a comparable growth rate to accumulate 13.21 g/L l-serine by fed-batch fermentation in minimal medium. This novel strategy provides new insights into the regulation of cellular properties and essential metabolite accumulation by introducing an extrinsic pathway.

Pathway Design, Engineering, and Optimization.

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Garcia-Ruiz, Eva; HamediRad, Mohammad; Zhao, Huimin

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Actionable Metabolic Pathways in Heart Failure and Cancer—Lessons From Cancer Cell Metabolism

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Anja Karlstaedt

2018-06-01

Full Text Available Recent advances in cancer cell metabolism provide unprecedented opportunities for a new understanding of heart metabolism and may offer new approaches for the treatment of heart failure. Key questions driving the cancer field to understand how tumor cells reprogram metabolism and to benefit tumorigenesis are also applicable to the heart. Recent experimental and conceptual advances in cancer cell metabolism provide the cardiovascular field with the unique opportunity to target metabolism. This review compares cancer cell metabolism and cardiac metabolism with an emphasis on strategies of cellular adaptation, and how to exploit metabolic changes for therapeutic benefit.

GABA metabolism pathway genes, UGA1 and GAD1, regulate replicative lifespan in Saccharomycescerevisiae

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Kamei, Yuka; Tamura, Takayuki [Department of Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 (Japan); Yoshida, Ryo [Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871 (Japan); Ohta, Shinji [Department of Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 (Japan); Fukusaki, Eiichiro [Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka 565-0871 (Japan); Mukai, Yukio, E-mail: y_mukai@nagahama-i-bio.ac.jp [Department of Bioscience, Faculty of Bioscience, Nagahama Institute of Bio-Science and Technology, 1266 Tamura, Nagahama, Shiga 526-0829 (Japan)

2011-04-01

Highlights: {yields}We demonstrate that two genes in the yeast GABA metabolism pathway affect aging. {yields} Deletion of the UGA1 or GAD1 genes extends replicative lifespan. {yields} Addition of GABA to wild-type cultures has no effect on lifespan. {yields} Intracellular GABA levels do not differ in longevity mutants and wild-type cells. {yields} Levels of tricarboxylic acid cycle intermediates positively correlate with lifespan. -- Abstract: Many of the genes involved in aging have been identified in organisms ranging from yeast to human. Our previous study showed that deletion of the UGA3 gene-which encodes a zinc-finger transcription factor necessary for {gamma}-aminobutyric acid (GABA)-dependent induction of the UGA1 (GABA aminotransferase), UGA2 (succinate semialdehyde dehydrogenase), and UGA4 (GABA permease) genes-extends replicative lifespan in the budding yeast Saccharomycescerevisiae. Here, we found that deletion of UGA1 lengthened the lifespan, as did deletion of UGA3; in contrast, strains with UGA2 or UGA4 deletions exhibited no lifespan extension. The {Delta}uga1 strain cannot deaminate GABA to succinate semialdehyde. Deletion of GAD1, which encodes the glutamate decarboxylase that converts glutamate into GABA, also increased lifespan. Therefore, two genes in the GABA metabolism pathway, UGA1 and GAD1, were identified as aging genes. Unexpectedly, intracellular GABA levels in mutant cells (except for {Delta}uga2 cells) did not differ from those in wild-type cells. Addition of GABA to culture media, which induces transcription of the UGA structural genes, had no effect on replicative lifespan of wild-type cells. Multivariate analysis of {sup 1}H nuclear magnetic resonance spectra for the whole-cell metabolite levels demonstrated a separation between long-lived and normal-lived strains. Gas chromatography-mass spectrometry analysis of identified metabolites showed that levels of tricarboxylic acid cycle intermediates positively correlated with lifespan

GABA metabolism pathway genes, UGA1 and GAD1, regulate replicative lifespan in Saccharomycescerevisiae

International Nuclear Information System (INIS)

Kamei, Yuka; Tamura, Takayuki; Yoshida, Ryo; Ohta, Shinji; Fukusaki, Eiichiro; Mukai, Yukio

2011-01-01

Highlights: →We demonstrate that two genes in the yeast GABA metabolism pathway affect aging. → Deletion of the UGA1 or GAD1 genes extends replicative lifespan. → Addition of GABA to wild-type cultures has no effect on lifespan. → Intracellular GABA levels do not differ in longevity mutants and wild-type cells. → Levels of tricarboxylic acid cycle intermediates positively correlate with lifespan. -- Abstract: Many of the genes involved in aging have been identified in organisms ranging from yeast to human. Our previous study showed that deletion of the UGA3 gene-which encodes a zinc-finger transcription factor necessary for γ-aminobutyric acid (GABA)-dependent induction of the UGA1 (GABA aminotransferase), UGA2 (succinate semialdehyde dehydrogenase), and UGA4 (GABA permease) genes-extends replicative lifespan in the budding yeast Saccharomycescerevisiae. Here, we found that deletion of UGA1 lengthened the lifespan, as did deletion of UGA3; in contrast, strains with UGA2 or UGA4 deletions exhibited no lifespan extension. The Δuga1 strain cannot deaminate GABA to succinate semialdehyde. Deletion of GAD1, which encodes the glutamate decarboxylase that converts glutamate into GABA, also increased lifespan. Therefore, two genes in the GABA metabolism pathway, UGA1 and GAD1, were identified as aging genes. Unexpectedly, intracellular GABA levels in mutant cells (except for Δuga2 cells) did not differ from those in wild-type cells. Addition of GABA to culture media, which induces transcription of the UGA structural genes, had no effect on replicative lifespan of wild-type cells. Multivariate analysis of 1 H nuclear magnetic resonance spectra for the whole-cell metabolite levels demonstrated a separation between long-lived and normal-lived strains. Gas chromatography-mass spectrometry analysis of identified metabolites showed that levels of tricarboxylic acid cycle intermediates positively correlated with lifespan extension. These results strongly suggest

Metagenomic sequencing reveals altered metabolic pathways in the oral microbiota of sailors during a long sea voyage.

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Zheng, Weiwei; Zhang, Ze; Liu, Cuihua; Qiao, Yuanyuan; Zhou, Dianrong; Qu, Jia; An, Huaijie; Xiong, Ming; Zhu, Zhiming; Zhao, Xiaohang

2015-03-16

Seafaring is a difficult occupation, and sailors face higher health risks than individuals on land. Commensal microbiota participates in the host immune system and metabolism, reflecting the host's health condition. However, the interaction mechanisms between the microbiota and the host's health condition remain unclear. This study reports the influence of long sea voyages on human health by utilising a metagenomic analysis of variation in the microbiota of the buccal mucosa. Paired samples collected before and after a sea-voyage were analysed. After more than 120 days of ocean sailing, the oral microbial diversity of sailors was reduced by approximately 5 fold, and the levels of several pathogens (e.g., Streptococcus pneumonia) increased. Moreover, 69.46% of the identified microbial sequences were unclassified microbiota. Notably, several metabolic pathways were dramatically decreased, including folate biosynthesis, carbohydrate, lipid and amino acid pathways. Clinical examination of the hosts confirmed the identified metabolic changes, as demonstrated by decreased serum levels of haemoglobin and folic acid, a decreased neutrophil-to-lymphocyte ratio, and increased levels of triglycerides, cholesterol and homocysteine, which are consistent with the observed microbial variation. Our study suggests that oral mucosal bacteria may reflect host health conditions and could provide approaches for improving the health of sailors.

Identification of Proteins Involved in Carbohydrate Metabolism and Energy Metabolism Pathways and Their Regulation of Cytoplasmic Male Sterility in Wheat

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Xingxia Geng

2018-01-01

Full Text Available Cytoplasmic male sterility (CMS where no functional pollen is produced has important roles in wheat breeding. The anther is a unique organ for male gametogenesis and its abnormal development can cause male sterility. However, the mechanisms and regulatory networks related to plant male sterility are poorly understood. In this study, we conducted comparative analyses using isobaric tags for relative and absolute quantification (iTRAQ of the pollen proteins in a CMS line and its wheat maintainer. Differentially abundant proteins (DAPs were analyzed based on Gene Ontology classifications, metabolic pathways and transcriptional regulation networks using Blast2GO. We identified 5570 proteins based on 23,277 peptides, which matched with 73,688 spectra, including proteins in key pathways such as glyceraldehyde-3-phosphate dehydrogenase, pyruvate kinase and 6-phosphofructokinase 1 in the glycolysis pathway, isocitrate dehydrogenase and citrate synthase in the tricarboxylic acid cycle and nicotinamide adenine dinucleotide (NADH-dehydrogenase and adenosine-triphosphate (ATP synthases in the oxidative phosphorylation pathway. These proteins may comprise a network that regulates male sterility in wheat. Quantitative real time polymerase chain reaction (qRT-PCR analysis, ATP assays and total sugar assays validated the iTRAQ results. These DAPs could be associated with abnormal pollen grain formation and male sterility. Our findings provide insights into the molecular mechanism related to male sterility in wheat.

Identification of Proteins Involved in Carbohydrate Metabolism and Energy Metabolism Pathways and Their Regulation of Cytoplasmic Male Sterility in Wheat.

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Geng, Xingxia; Ye, Jiali; Yang, Xuetong; Li, Sha; Zhang, Lingli; Song, Xiyue

2018-01-23

Cytoplasmic male sterility (CMS) where no functional pollen is produced has important roles in wheat breeding. The anther is a unique organ for male gametogenesis and its abnormal development can cause male sterility. However, the mechanisms and regulatory networks related to plant male sterility are poorly understood. In this study, we conducted comparative analyses using isobaric tags for relative and absolute quantification (iTRAQ) of the pollen proteins in a CMS line and its wheat maintainer. Differentially abundant proteins (DAPs) were analyzed based on Gene Ontology classifications, metabolic pathways and transcriptional regulation networks using Blast2GO. We identified 5570 proteins based on 23,277 peptides, which matched with 73,688 spectra, including proteins in key pathways such as glyceraldehyde-3-phosphate dehydrogenase, pyruvate kinase and 6-phosphofructokinase 1 in the glycolysis pathway, isocitrate dehydrogenase and citrate synthase in the tricarboxylic acid cycle and nicotinamide adenine dinucleotide (NADH)-dehydrogenase and adenosine-triphosphate (ATP) synthases in the oxidative phosphorylation pathway. These proteins may comprise a network that regulates male sterility in wheat. Quantitative real time polymerase chain reaction (qRT-PCR) analysis, ATP assays and total sugar assays validated the iTRAQ results. These DAPs could be associated with abnormal pollen grain formation and male sterility. Our findings provide insights into the molecular mechanism related to male sterility in wheat.

Exposure to atrazine affects the expression of key genes in metabolic pathways integral to energy homeostasis in Xenopus laevis tadpoles

International Nuclear Information System (INIS)

Zaya, Renee M.; Amini, Zakariya; Whitaker, Ashley S.; Ide, Charles F.

2011-01-01

In our laboratory, Xenopus laevis tadpoles exposed throughout development to 200 or 400 μg/L atrazine, concentrations reported to periodically occur in puddles, vernal ponds and runoff soon after application, were smaller and had smaller fat bodies (the tadpole's lipid storage organ) than controls. It was hypothesized that these changes were due to atrazine-related perturbations of energy homeostasis. To investigate this hypothesis, selected metabolic responses to exposure at the transcriptional and biochemical levels in atrazine-exposed tadpoles were measured. DNA microarray technology was used to determine which metabolic pathways were affected after developmental exposure to 400 μg/L atrazine. From these data, genes representative of the affected pathways were selected for assay using quantitative real time polymerase chain reaction (qRT-PCR) to measure changes in expression during a 2-week exposure to 400 μg/L. Finally, ATP levels were measured from tadpoles both early in and at termination of exposure to 200 and 400 μg/L. Microarray analysis revealed significant differential gene expression in metabolic pathways involved with energy homeostasis. Pathways with increased transcription were associated with the conversion of lipids and proteins into energy. Pathways with decreased transcription were associated with carbohydrate metabolism, fat storage, and protein synthesis. Using qRT-PCR, changes in gene expression indicative of an early stress response to atrazine were noted. Exposed tadpoles had significant decreases in acyl-CoA dehydrogenase (AD) and glucocorticoid receptor protein (GR) mRNA after 24 h of exposure, and near-significant (p = 0.07) increases in peroxisome proliferator-activated receptor β (PPAR-β) mRNA by 72 h. Decreases in AD suggested decreases in fatty acid β-oxidation while decreases in GR may have been a receptor desensitization response to a glucocorticoid surge. Involvement of PPAR-β, an energy homeostasis regulatory molecule

Exposure to atrazine affects the expression of key genes in metabolic pathways integral to energy homeostasis in Xenopus laevis tadpoles

Energy Technology Data Exchange (ETDEWEB)

Zaya, Renee M., E-mail: renee.zaya@wmich.edu [Great Lakes Environmental and Molecular Sciences Center, Department of Biological Sciences, 3425 Wood Hall, Western Michigan University, 1903 West Michigan Avenue, Kalamazoo, MI 49008 (United States); Amini, Zakariya, E-mail: zakariya.amini@wmich.edu [Great Lakes Environmental and Molecular Sciences Center, Department of Biological Sciences, 3425 Wood Hall, Western Michigan University, 1903 West Michigan Avenue, Kalamazoo, MI 49008 (United States); Whitaker, Ashley S., E-mail: ashley.s.whitaker@wmich.edu [Great Lakes Environmental and Molecular Sciences Center, Department of Biological Sciences, 3425 Wood Hall, Western Michigan University, 1903 West Michigan Avenue, Kalamazoo, MI 49008 (United States); Ide, Charles F., E-mail: charles.ide@wmich.edu [Great Lakes Environmental and Molecular Sciences Center, Department of Biological Sciences, 3425 Wood Hall, Western Michigan University, 1903 West Michigan Avenue, Kalamazoo, MI 49008 (United States)

2011-08-15

In our laboratory, Xenopus laevis tadpoles exposed throughout development to 200 or 400 {mu}g/L atrazine, concentrations reported to periodically occur in puddles, vernal ponds and runoff soon after application, were smaller and had smaller fat bodies (the tadpole's lipid storage organ) than controls. It was hypothesized that these changes were due to atrazine-related perturbations of energy homeostasis. To investigate this hypothesis, selected metabolic responses to exposure at the transcriptional and biochemical levels in atrazine-exposed tadpoles were measured. DNA microarray technology was used to determine which metabolic pathways were affected after developmental exposure to 400 {mu}g/L atrazine. From these data, genes representative of the affected pathways were selected for assay using quantitative real time polymerase chain reaction (qRT-PCR) to measure changes in expression during a 2-week exposure to 400 {mu}g/L. Finally, ATP levels were measured from tadpoles both early in and at termination of exposure to 200 and 400 {mu}g/L. Microarray analysis revealed significant differential gene expression in metabolic pathways involved with energy homeostasis. Pathways with increased transcription were associated with the conversion of lipids and proteins into energy. Pathways with decreased transcription were associated with carbohydrate metabolism, fat storage, and protein synthesis. Using qRT-PCR, changes in gene expression indicative of an early stress response to atrazine were noted. Exposed tadpoles had significant decreases in acyl-CoA dehydrogenase (AD) and glucocorticoid receptor protein (GR) mRNA after 24 h of exposure, and near-significant (p = 0.07) increases in peroxisome proliferator-activated receptor {beta} (PPAR-{beta}) mRNA by 72 h. Decreases in AD suggested decreases in fatty acid {beta}-oxidation while decreases in GR may have been a receptor desensitization response to a glucocorticoid surge. Involvement of PPAR-{beta}, an energy

Wholly Rickettsia! Reconstructed Metabolic Profile of the Quintessential Bacterial Parasite of Eukaryotic Cells.

Science.gov (United States)

Driscoll, Timothy P; Verhoeve, Victoria I; Guillotte, Mark L; Lehman, Stephanie S; Rennoll, Sherri A; Beier-Sexton, Magda; Rahman, M Sayeedur; Azad, Abdu F; Gillespie, Joseph J

2017-09-26

Reductive genome evolution has purged many metabolic pathways from obligate intracellular Rickettsia ( Alphaproteobacteria ; Rickettsiaceae ). While some aspects of host-dependent rickettsial metabolism have been characterized, the array of host-acquired metabolites and their cognate transporters remains unknown. This dearth of information has thwarted efforts to obtain an axenic Rickettsia culture, a major impediment to conventional genetic approaches. Using phylogenomics and computational pathway analysis, we reconstructed the Rickettsia metabolic and transport network, identifying 51 host-acquired metabolites (only 21 previously characterized) needed to compensate for degraded biosynthesis pathways. In the absence of glycolysis and the pentose phosphate pathway, cell envelope glycoconjugates are synthesized from three imported host sugars, with a range of additional host-acquired metabolites fueling the tricarboxylic acid cycle. Fatty acid and glycerophospholipid pathways also initiate from host precursors, and import of both isoprenes and terpenoids is required for the synthesis of ubiquinone and the lipid carrier of lipid I and O-antigen. Unlike metabolite-provisioning bacterial symbionts of arthropods, rickettsiae cannot synthesize B vitamins or most other cofactors, accentuating their parasitic nature. Six biosynthesis pathways contain holes (missing enzymes); similar patterns in taxonomically diverse bacteria suggest alternative enzymes that await discovery. A paucity of characterized and predicted transporters emphasizes the knowledge gap concerning how rickettsiae import host metabolites, some of which are large and not known to be transported by bacteria. Collectively, our reconstructed metabolic network offers clues to how rickettsiae hijack host metabolic pathways. This blueprint for growth determinants is an important step toward the design of axenic media to rescue rickettsiae from the eukaryotic cell. IMPORTANCE A hallmark of obligate intracellular

Computational tools and resources for metabolism-related property predictions. 1. Overview of publicly available (free and commercial) databases and software.

Science.gov (United States)

Peach, Megan L; Zakharov, Alexey V; Liu, Ruifeng; Pugliese, Angelo; Tawa, Gregory; Wallqvist, Anders; Nicklaus, Marc C

2012-10-01

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

Vibrio Phage KVP40 Encodes a Functional NAD+ Salvage Pathway.

Science.gov (United States)

Lee, Jae Yun; Li, Zhiqun; Miller, Eric S

2017-05-01

The genome of T4-type Vibrio bacteriophage KVP40 has five genes predicted to encode proteins of pyridine nucleotide metabolism, of which two, nadV and natV , would suffice for an NAD + salvage pathway. NadV is an apparent nicotinamide phosphoribosyltransferase (NAmPRTase), and NatV is an apparent bifunctional nicotinamide mononucleotide adenylyltransferase (NMNATase) and nicotinamide-adenine dinucleotide pyrophosphatase (Nudix hydrolase). Genes encoding the predicted salvage pathway were cloned and expressed in Escherichia coli , the proteins were purified, and their enzymatic properties were examined. KVP40 NadV NAmPRTase is active in vitro , and a clone complements a Salmonella mutant defective in both the bacterial de novo and salvage pathways. Similar to other NAmPRTases, the KVP40 enzyme displayed ATPase activity indicative of energy coupling in the reaction mechanism. The NatV NMNATase activity was measured in a coupled reaction system demonstrating NAD + biosynthesis from nicotinamide, phosphoribosyl pyrophosphate, and ATP. The NatV Nudix hydrolase domain was also shown to be active, with preferred substrates of ADP-ribose, NAD + , and NADH. Expression analysis using reverse transcription-quantitative PCR (qRT-PCR) and enzyme assays of infected Vibrio parahaemolyticus cells demonstrated nadV and natV transcription during the early and delayed-early periods of infection when other KVP40 genes of nucleotide precursor metabolism are expressed. The distribution and phylogeny of NadV and NatV proteins among several large double-stranded DNA (dsDNA) myophages, and also those from some very large siphophages, suggest broad relevance of pyridine nucleotide scavenging in virus-infected cells. NAD + biosynthesis presents another important metabolic resource control point by large, rapidly replicating dsDNA bacteriophages. IMPORTANCE T4-type bacteriophages enhance DNA precursor synthesis through reductive reactions that use NADH/NADPH as the electron donor and NAD

Tumor Metabolism of Malignant Gliomas

Energy Technology Data Exchange (ETDEWEB)

Ru, Peng; Williams, Terence M.; Chakravarti, Arnab; Guo, Deliang, E-mail: deliang.guo@osumc.edu [Department of Radiation Oncology, Ohio State University Comprehensive Cancer Center & Arthur G James Cancer Hospital, Columbus, OH 43012 (United States)

2013-11-08

Constitutively activated oncogenic signaling via genetic mutations such as in the EGFR/PI3K/Akt and Ras/RAF/MEK pathways has been recognized as a major driver for tumorigenesis in most cancers. Recent insights into tumor metabolism have further revealed that oncogenic signaling pathways directly promote metabolic reprogramming to upregulate biosynthesis of lipids, carbohydrates, protein, DNA and RNA, leading to enhanced growth of human tumors. Therefore, targeting cell metabolism has become a novel direction for drug development in oncology. In malignant gliomas, metabolism pathways of glucose, glutamine and lipid are significantly reprogrammed. Moreover, molecular mechanisms causing these metabolic changes are just starting to be unraveled. In this review, we will summarize recent studies revealing critical gene alterations that lead to metabolic changes in malignant gliomas, and also discuss promising therapeutic strategies via targeting the key players in metabolic regulation.

Tumor Metabolism of Malignant Gliomas

International Nuclear Information System (INIS)

Ru, Peng; Williams, Terence M.; Chakravarti, Arnab; Guo, Deliang

2013-01-01

Constitutively activated oncogenic signaling via genetic mutations such as in the EGFR/PI3K/Akt and Ras/RAF/MEK pathways has been recognized as a major driver for tumorigenesis in most cancers. Recent insights into tumor metabolism have further revealed that oncogenic signaling pathways directly promote metabolic reprogramming to upregulate biosynthesis of lipids, carbohydrates, protein, DNA and RNA, leading to enhanced growth of human tumors. Therefore, targeting cell metabolism has become a novel direction for drug development in oncology. In malignant gliomas, metabolism pathways of glucose, glutamine and lipid are significantly reprogrammed. Moreover, molecular mechanisms causing these metabolic changes are just starting to be unraveled. In this review, we will summarize recent studies revealing critical gene alterations that lead to metabolic changes in malignant gliomas, and also discuss promising therapeutic strategies via targeting the key players in metabolic regulation

Insights on the evolution of metabolic networks of unicellular translationally biased organisms from transcriptomic data and sequence analysis.

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Carbone, Alessandra; Madden, Richard

2005-10-01

Codon bias is related to metabolic functions in translationally biased organisms, and two facts are argued about. First, genes with high codon bias describe in meaningful ways the metabolic characteristics of the organism; important metabolic pathways corresponding to crucial characteristics of the lifestyle of an organism, such as photosynthesis, nitrification, anaerobic versus aerobic respiration, sulfate reduction, methanogenesis, and others, happen to involve especially biased genes. Second, gene transcriptional levels of sets of experiments representing a significant variation of biological conditions strikingly confirm, in the case of Saccharomyces cerevisiae, that metabolic preferences are detectable by purely statistical analysis: the high metabolic activity of yeast during fermentation is encoded in the high bias of enzymes involved in the associated pathways, suggesting that this genome was affected by a strong evolutionary pressure that favored a predominantly fermentative metabolism of yeast in the wild. The ensemble of metabolic pathways involving enzymes with high codon bias is rather well defined and remains consistent across many species, even those that have not been considered as translationally biased, such as Helicobacter pylori, for instance, reveal some weak form of translational bias for this genome. We provide numerical evidence, supported by experimental data, of these facts and conclude that the metabolic networks of translationally biased genomes, observable today as projections of eons of evolutionary pressure, can be analyzed numerically and predictions of the role of specific pathways during evolution can be derived. The new concepts of Comparative Pathway Index, used to compare organisms with respect to their metabolic networks, and Evolutionary Pathway Index, used to detect evolutionarily meaningful bias in the genetic code from transcriptional data, are introduced.

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

OpenAIRE

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

2006-01-01

Abstract Background In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law...

Interdisciplinary Pathways for Urban Metabolism Research

Science.gov (United States)

Newell, J. P.

2011-12-01

With its rapid rise as a metaphor to express coupled natural-human systems in cities, the concept of urban metabolism is evolving into a series of relatively distinct research frameworks amongst various disciplines, with varying definitions, theories, models, and emphases. In industrial ecology, housed primarily within the disciplinary domain of engineering, urban metabolism research has focused on quantifying material and energy flows into, within, and out of cities, using methodologies such as material flow analysis and life cycle assessment. In the field of urban ecology, which is strongly influenced by ecology and urban planning, research focus has been placed on understanding and modeling the complex patterns and processes of human-ecological systems within urban areas. Finally, in political ecology, closely aligned with human geography and anthropology, scholars theorize about the interwoven knots of social and natural processes, material flows, and spatial structures that form the urban metabolism. This paper offers three potential interdisciplinary urban metabolism research tracks that might integrate elements of these three "ecologies," thereby bridging engineering and the social and physical sciences. First, it presents the idea of infrastructure ecology, which explores the complex, emergent interdependencies between gray (water and wastewater, transportation, etc) and green (e.g. parks, greenways) infrastructure systems, as nested within a broader socio-economic context. For cities to be sustainable and resilient over time-space, the theory follows, these is a need to understand and redesign these infrastructure linkages. Second, there is the concept of an urban-scale carbon metabolism model which integrates consumption-based material flow analysis (including goods, water, and materials), with the carbon sink and source dynamics of the built environment (e.g. buildings, etc) and urban ecosystems. Finally, there is the political ecology of the material

Metagenomic approach reveals microbial diversity and predictive microbial metabolic pathways in Yucha, a traditional Li fermented food.

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Zhang, Jiachao; Wang, Xiaoru; Huo, Dongxue; Li, Wu; Hu, Qisong; Xu, Chuanbiao; Liu, Sixin; Li, Congfa

2016-08-31

Yucha is a typical traditional fermented food of the Li population in the Hainan province of China, and it is made up of cooked rice and fresh fish. In the present study, metagenomic approach and culture-dependent technology were applied to describe the diversity of microbiota and identify beneficial microbes in the Yucha. At the genus level, Lactobacillus was the most abundant genus (43.82% of the total reads), followed by Lactococcus, Enterococcus, Vibrio, Weissella, Pediococcus, Enterobacter, Salinivibrio, Acinetobacter, Macrococcus, Kluyvera and Clostridium; this result was confirmed by q-PCR. PCoA based on Weighted UniFrac distances showed an apparent clustering pattern for Yucha samples from different locations, and Lactobacillus sakei, Lactobacillus saniviri and Staphylococcus sciuri represented OTUs according to the major identified markers. At the microbial functional level, it was observed that there was an enrichment of metabolic functional features, including amino acid and carbohydrate metabolism, which implied that the microbial metabolism in the Yucha samples tended to be vigorous. Accordingly, we further investigated the correlation between the predominant microbes and metabolic functional features. Thirteen species of Lactobacillus (147 strains) were isolated, and Lactobacillus plantarum (60 isolates) and Lactobacillus pentosus (34 isolates) were isolated from every sample.

Microbial Community Pathways for the Production of Volatile Fatty Acids From CO2 and Electricity

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Jorge Wenzel

2018-04-01

Full Text Available This study aims at elucidating the metabolic pathways involved in the production of volatile fatty acids from CO2 and electricity. Two bioelectrochemical systems (BES were fed with pure CO2 (cells A and B. The cathode potential was first poised at −574 mV vs. standard hydrogen electrode (SHE and then at −756 mV vs. SHE in order to ensure the required reducing power. Despite applying similar operation conditions to both BES, they responded differently. A mixture of organic compounds (1.87 mM acetic acid, 2.30 mM formic acid, 0.43 mM propionic acid, 0.15 mM butyric acid, 0.55 mM valeric acid, and 0.62 mM ethanol was produced in cell A while mainly 1.82 mM acetic acid and 0.23 mM propionic acid were produced in cell B. The microbial community analysis performed by 16S rRNA gene pyrosequencing showed a predominance of Clostridium sp. and Serratia sp. in cell A whereas Burkholderia sp. and Xanthobacter sp. predominated in cell B. The coexistence of three metabolic pathways involved in carbon fixation was predicted. Calvin cycle was predicted in both cells during the whole experiment while Wood-Ljungdahl and Arnon-Buchanan pathways predominated in the period with higher coulombic efficiency. Metabolic pathways which transform organic acids into anabolic intermediaries were also predicted, indicating the occurrence of complex trophic interactions. These results further complicate the understanding of these mixed culture microbial processes but also expand the expectation of compounds that could potentially be produced with this technology.

A free radical-generating system regulates AβPP metabolism/processing: involvement of the ubiquitin/proteasome and autophagy/lysosome pathways.

Science.gov (United States)

Recuero, María; Munive, Victor A; Sastre, Isabel; Aldudo, Jesús; Valdivieso, Fernando; Bullido, María J

2013-01-01

Oxidative stress is an early event in the pathogenesis of Alzheimer's disease (AD). We previously reported that, in SK-N-MC cells, the xanthine/xanthine oxidase (X-XOD) free radical generating system regulates the metabolism/processing of the amyloid-β protein precursor (AβPP). Oxidative stress alters the two main cellular proteolytic machineries, the ubiquitin/proteasome (UPS) and the autophagy/lysosome systems, and recent studies have established connections between the malfunctioning of these and the pathogenesis of AD. The aim of the present work was to examine the involvement of these proteolytic systems in the regulation of AβPP metabolism by X-XOD. The proteasome inhibitor MG132 was found to accelerate the metabolism/processing of AβPP promoted by X-XOD because it significantly enhances the secretion of α-secretase-cleaved soluble AβPP and also the levels of both carboxy-terminal fragments (CTFs) produced by α- and β-secretase. Further, MG132 modulated the intracellular accumulation of holo-AβPP and/or AβPP CTFs. This indicates that the X-XOD modulation of AβPP metabolism/processing involves the UPS pathway. With respect to the autophagy/lysosome pathway, the AβPP processing and intracellular location patterns induced by X-XOD treatment closely resembled those produced by the lysosome inhibitor ammonium chloride. The present results suggest that the regulation of AβPP metabolism/processing by mild oxidative stress requires UPS activity with a simultaneous reduction in that of the autophagy/lysosome system.

Pathway confirmation and flux analysis of central metabolic pathways in Desulfovibrio vulgaris Hildenborough using Gas Chromatography-Mass Spectrometry and Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry

International Nuclear Information System (INIS)

Tang, Yinjie; Pingitore, Francesco; Mukhopadhyay, Aindrila; Phan, Richard; Hazen, Terry C.; Keasling, Jay D.

2007-01-01

Flux distribution in central metabolic pathways of Desulfovibrio vulgaris Hildenborough was examined using 13C tracer experiments. Consistent with the current genome annotation and independent evidence from enzyme activity assays, the isotopomer results from both GC-MS and Fourier Transform-Ion Cyclotron Resonance mass spectrometry (FT-ICR MS) indicate the lack of oxidatively functional TCA cycle and an incomplete pentose phosphate pathway. Results from this study suggest that fluxes through both pathways are limited to biosynthesis. The data also indicate that >80 percent of the lactate was converted to acetate and the reactions involved are the primary route of energy production (NAD(P)H and ATP production). Independent of the TCA cycle, direct cleavage of acetyl-CoA to CO and 5,10-methyl-THF also leads to production of NADH and ATP. Although the genome annotation implicates a ferredoxin-dependent oxoglutarate synthase, isotopic evidence does not support flux through this reaction in either the oxidative or reductive mode; therefore, the TCA cycle is incomplete. FT-ICR MS was used to locate the labeled carbon distribution in aspartate and glutamate and confirmed the presence of an atypical enzyme for citrate formation suggested in previous reports (the citrate synthesized by this enzyme is the isotopic antipode of the citrate synthesized by the (S)-citrate synthase). These findings enable a better understanding of the relation between genome annotation and actual metabolic pathways in D. vulgaris, and also demonstrate FT-ICR MS as a powerful tool for isotopomer analysis, overcoming problems in both GC-MS and NMR spectroscopy

Computational identification of signalling pathways in Plasmodium falciparum.

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Oyelade, Jelili; Ewejobi, Itunu; Brors, Benedikt; Eils, Roland; Adebiyi, Ezekiel

2011-06-01

Malaria is one of the world's most common and serious diseases causing death of about 3 million people each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Reports have shown that the resistance of the parasite to existing drugs is increasing. Therefore, there is a huge and urgent need to discover and validate new drug or vaccine targets to enable the development of new treatments for malaria. The ability to discover these drug or vaccine targets can only be enhanced from our deep understanding of the detailed biology of the parasite, for example how cells function and how proteins organize into modules such as metabolic, regulatory and signal transduction pathways. It has been noted that the knowledge of signalling transduction pathways in Plasmodium is fundamental to aid the design of new strategies against malaria. This work uses a linear-time algorithm for finding paths in a network under modified biologically motivated constraints. We predicted several important signalling transduction pathways in Plasmodium falciparum. We have predicted a viable signalling pathway characterized in terms of the genes responsible that may be the PfPKB pathway recently elucidated in Plasmodium falciparum. We obtained from the FIKK family, a signal transduction pathway that ends up on a chloroquine resistance marker protein, which indicates that interference with FIKK proteins might reverse Plasmodium falciparum from resistant to sensitive phenotype. We also proposed a hypothesis that showed the FIKK proteins in this pathway as enabling the resistance parasite to have a mechanism for releasing chloroquine (via an efflux process). Furthermore, we also predicted a signalling pathway that may have been responsible for signalling the start of the invasion process of Red Blood Cell (RBC) by the merozoites. It has been noted that the understanding of this pathway will give insight into the parasite virulence and will facilitate rational vaccine design

Contributions of citrate in redox potential maintenance and ATP production: metabolic pathways and their regulation in Lactobacillus panis PM1.

Science.gov (United States)

Kang, Tae Sun; Korber, Darren R; Tanaka, Takuji

2013-10-01

Lactobacillus panis PM1 belongs to the group III heterofermentative lactobacilli and can utilize various NADH-reoxidizing routes (e.g., citrate, glycerol, and oxygen) according to environmental conditions. In this study, we investigated the ability of L. panis PM1 to produce succinate, acetate, and lactate via citrate utilization. Possible pathways, as well as regulation, for citrate metabolism were examined on the basis of the genome sequence data and metabolic profiles of L. panis PM1. The presence of citrate led to the up-regulation, at the transcriptional level, of the genes encoding for citrate lyase, malate dehydrogenase, and malic enzyme of the citrate pathways by 10- to 120-fold. The transcriptional regulator of the dha operon coding for glycerol dehydratase of L. panis PM1 repressed the expression of the citrate lyase gene (10-fold). Metabolite analyses indicated that the transcriptional enhancement by citrate stimulated succinate yield. Citrate metabolism contributed to energy production by providing a major alternate pathway for NAD(+) regeneration and allowed acetyl phosphate to yield acetate/ATP instead of ethanol/NAD(+). Additionally, a branching pathway from oxaloacetate to pyruvate increased the pool of lactate, which was then used to produce ATP during stationary phase. However, the redirection of NADH-to-citrate utilization resulted in stress caused by end-products (i.e., succinate and acetate). This stress reduced succinate production by up to 50 % but did not cause significant changes at transcriptional level. Overall, citrate utilization was beneficial for the growth of L. panis PM1 by providing a NAD(+) regeneration route and producing extra ATP.

Characterization of the Usage of the Serine Metabolic Network in Human Cancer

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Mahya Mehrmohamadi

2014-11-01

Full Text Available The serine, glycine, one-carbon (SGOC metabolic network is implicated in cancer pathogenesis, but its general functions are unknown. We carried out a computational reconstruction of the SGOC network and then characterized its expression across thousands of cancer tissues. Pathways including methylation and redox metabolism exhibited heterogeneous expression indicating a strong context dependency of their usage in tumors. From an analysis of coexpression, simultaneous up- or downregulation of nucleotide synthesis, NADPH, and glutathione synthesis was found to be a common occurrence in all cancers. Finally, we developed a method to trace the metabolic fate of serine using stable isotopes, high-resolution mass spectrometry, and a mathematical model. Although the expression of single genes didn’t appear indicative of flux, the collective expression of several genes in a given pathway allowed for successful flux prediction. Altogether, these findings identify expansive and heterogeneous functions for the SGOC metabolic network in human cancer.

Method for determining heterologous biosynthesis pathways

KAUST Repository

Gao, Xin; Kuwahara, Hiroyuki; Alazmi, Meshari Saud; Cui, Xuefeng

2017-01-01

suitable pathways for the endogenous metabolism of a host organism because the efficacy of heterologous biosynthesis is affected by competing endogenous pathways. The present invention is called MRE (Metabolic Route Explorer), and it was conceived

Aspects of astrocyte energy metabolism, amino acid neurotransmitter homoeostasis and metabolic compartmentation

DEFF Research Database (Denmark)

Kreft, Marko; Bak, Lasse Kristoffer; Waagepetersen, Helle S

2012-01-01

Astrocytes are key players in brain function; they are intimately involved in neuronal signalling processes and their metabolism is tightly coupled to that of neurons. In the present review, we will be concerned with a discussion of aspects of astrocyte metabolism, including energy......-generating pathways and amino acid homoeostasis. A discussion of the impact that uptake of neurotransmitter glutamate may have on these pathways is included along with a section on metabolic compartmentation....

Erythrocyte metabolism in hyperthyroidism: a microcalorimetric study on changes in the Embden-Meyerhof and the hexose monophosphate pathways.

Science.gov (United States)

Monti, M; Hedner, P; Ikomi-Kumm, J; Valdemarsson, S

1987-05-01

Erythrocyte metabolism was studied in vitro by microcalorimetry in 10 hyperthyroid subjects before and after treatment. By inhibiting the enzyme enolase in the Embden-Meyerhof pathway with sodium fluoride (NaF) we have recorded the anaerobic and aerobic contributions in erythrocyte thermogenesis. The decrease in heat production rate in samples with NaF corresponds to the anaerobic contribution, whereas the values from samples with NaF reflect aerobic processes. Before treatment, total heat production rate was 120 +/- 2 mW/l erythrocytes which was higher than the post-treatment value of 99 +/- 2 (P less than 0.001) as well as the value for 14 euthyroid subjects, 108 +/- 2 mW/l (P less than 0.001). The NaF inhibitable rate was 73 +/- 2 before and 63 +/- 1 mW/l after therapy (P less than 0.01). These values correspond to 61 +/- 1 and 64 +/- 1% (n.s.) of the total heat production rate, and were similar to that of 61 +/- 2% for the controls. Heat production rates in the presence of NaF were 47 +/- 1 before and 36 +/- 1 mW/l after therapy (P less than 0.001), representing 39 +/- 1 and 36 +/- 1% of total values, respectively. The present results show that overall metabolism is increased in erythrocytes from hyperthyroid subjects before treatment and returns to normal after normalization of the thyroid function. Moreover, by using microcalorimetry we found that the metabolic activity along the Embden-Meyerhof anaerobic pathway as well as along the hexose monophosphate aerobic pathway in erythrocytes is stimulated by thyroid hormones.

Modulation of cell metabolic pathways and oxidative stress signaling contribute to acquired melphalan resistance in multiple myeloma cells

DEFF Research Database (Denmark)

Zub, Kamila Anna; Sousa, Mirta Mittelstedt Leal de; Sarno, Antonio

2015-01-01

of the AKR1C family involved in prostaglandin synthesis contribute to the resistant phenotype. Finally, selected metabolic and oxidative stress response enzymes were targeted by inhibitors, several of which displayed a selective cytotoxicity against the melphalan-resistant cells and should be further...... and pathways not previously associated with melphalan resistance in multiple myeloma cells, including a metabolic switch conforming to the Warburg effect (aerobic glycolysis), and an elevated oxidative stress response mediated by VEGF/IL8-signaling. In addition, up-regulated aldo-keto reductase levels...

SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases

Science.gov (United States)

Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A

2018-01-01

Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this

Predicting Metabolic Syndrome Using the Random Forest Method

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Apilak Worachartcheewan

2015-01-01

Full Text Available Aims. This study proposes a computational method for determining the prevalence of metabolic syndrome (MS and to predict its occurrence using the National Cholesterol Education Program Adult Treatment Panel III (NCEP ATP III criteria. The Random Forest (RF method is also applied to identify significant health parameters. Materials and Methods. We used data from 5,646 adults aged between 18–78 years residing in Bangkok who had received an annual health check-up in 2008. MS was identified using the NCEP ATP III criteria. The RF method was applied to predict the occurrence of MS and to identify important health parameters surrounding this disorder. Results. The overall prevalence of MS was 23.70% (34.32% for males and 17.74% for females. RF accuracy for predicting MS in an adult Thai population was 98.11%. Further, based on RF, triglyceride levels were the most important health parameter associated with MS. Conclusion. RF was shown to predict MS in an adult Thai population with an accuracy >98% and triglyceride levels were identified as the most informative variable associated with MS. Therefore, using RF to predict MS may be potentially beneficial in identifying MS status for preventing the development of diabetes mellitus and cardiovascular diseases.

Effects of glucose metabolism pathways on sperm motility and oxidative status during long-term liquid storage of goat semen.

Science.gov (United States)

Qiu, Jian-Hua; Li, You-Wei; Xie, Hong-Li; Li, Qing; Dong, Hai-Bo; Sun, Ming-Ju; Gao, Wei-Qiang; Tan, Jing-He

2016-08-01

Although great efforts were made to prolong the fertility of liquid-stored semen, limited improvements have been achieved in different species. Although it is expected that energy supply and the redox potential will play an essential role in sperm function, there are few reports on the impact of specific energy substrates on spermatozoa during liquid semen storage. Furthermore, although it is accepted that glucose metabolism through glycolysis provides energy, roles of pentose phosphate pathway (PPP) and tricarboxylic acid cycle remain to be unequivocally found in spermatozoa. We have studied the pathways by which spermatozoa metabolize glucose during long-term liquid storage of goat semen. The results indicated that among the substrates tested, glucose and pyruvate were better than lactate in maintaining goat sperm motility. Although both glycolysis and PPP were essential, PPP was more important than glycolysis to maintain sperm motility. Pentose phosphate pathway reduced oxidative stress and provided glycolysis with more intermediate products such as fructose-6-phosphate. Pyruvate entered goat spermatozoa through monocarboxylate transporters and was oxidized by the tricarboxylic acid cycle and electron transfer to sustain sperm motility. Long-term liquid semen storage can be used as a good model to study sperm glucose metabolism. The data are important for an optimal control of sperm survival during semen handling and preservation not only in the goat but also in other species. Copyright © 2016 Elsevier Inc. All rights reserved.

Topological analysis of metabolic control.

Science.gov (United States)

Sen, A K

1990-12-01

A topological approach is presented for the analysis of control and regulation in metabolic pathways. In this approach, the control structure of a metabolic pathway is represented by a weighted directed graph. From an inspection of the topology of the graph, the control coefficients of the enzymes are evaluated in a heuristic manner in terms of the enzyme elasticities. The major advantage of the topological approach is that it provides a visual framework for (1) calculating the control coefficients of the enzymes, (2) analyzing the cause-effect relationships of the individual enzymes, (3) assessing the relative importance of the enzymes in metabolic regulation, and (4) simplifying the structure of a given pathway, from a regulatory viewpoint. Results are obtained for (a) an unbranched pathway in the absence of feedback the feedforward regulation and (b) an unbranched pathway with feedback inhibition. Our formulation is based on the metabolic control theory of Kacser and Burns (1973) and Heinrich and Rapoport (1974).

Predicting protein folding pathways at the mesoscopic level based on native interactions between secondary structure elements

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Sze Sing-Hoi

2008-07-01

Full Text Available Abstract Background Since experimental determination of protein folding pathways remains difficult, computational techniques are often used to simulate protein folding. Most current techniques to predict protein folding pathways are computationally intensive and are suitable only for small proteins. Results By assuming that the native structure of a protein is known and representing each intermediate conformation as a collection of fully folded structures in which each of them contains a set of interacting secondary structure elements, we show that it is possible to significantly reduce the conformation space while still being able to predict the most energetically favorable folding pathway of large proteins with hundreds of residues at the mesoscopic level, including the pig muscle phosphoglycerate kinase with 416 residues. The model is detailed enough to distinguish between different folding pathways of structurally very similar proteins, including the streptococcal protein G and the peptostreptococcal protein L. The model is also able to recognize the differences between the folding pathways of protein G and its two structurally similar variants NuG1 and NuG2, which are even harder to distinguish. We show that this strategy can produce accurate predictions on many other proteins with experimentally determined intermediate folding states. Conclusion Our technique is efficient enough to predict folding pathways for both large and small proteins at the mesoscopic level. Such a strategy is often the only feasible choice for large proteins. A software program implementing this strategy (SSFold is available at http://faculty.cs.tamu.edu/shsze/ssfold.

Systems-wide metabolic pathway engineering in Corynebacterium glutamicum for bio-based production of diaminopentane.

Science.gov (United States)

Kind, Stefanie; Jeong, Weol Kyu; Schröder, Hartwig; Wittmann, Christoph

2010-07-01

In the present work the Gram-positive bacterium Corynebacterium glutamicum was engineered into an efficient, tailor-made production strain for diaminopentane (cadaverine), a highly attractive building block for bio-based polyamides. The engineering comprised expression of lysine decarboxylase (ldcC) from Escherichia coli, catalyzing the conversion of lysine into diaminopentane, and systems-wide metabolic engineering of central supporting pathways. Substantially re-designing the metabolism yielded superior strains with desirable properties such as (i) the release from unwanted feedback regulation at the level of aspartokinase and pyruvate carboxylase by introducing the point mutations lysC311 and pycA458, (ii) an optimized supply of the key precursor oxaloacetate by amplifying the anaplerotic enzyme, pyruvate carboxylase, and deleting phosphoenolpyruvate carboxykinase which otherwise removes oxaloacetate, (iii) enhanced biosynthetic flux via combined amplification of aspartokinase, dihydrodipicolinate reductase, diaminopimelate dehydrogenase and diaminopimelate decarboxylase, and (iv) attenuated flux into the threonine pathway competing with production by the leaky mutation hom59 in the homoserine dehydrogenase gene. Lysine decarboxylase proved to be a bottleneck for efficient production, since its in vitro activity and in vivo flux were closely correlated. To achieve an optimal strain having only stable genomic modifications, the combination of the strong constitutive C. glutamicum tuf promoter and optimized codon usage allowed efficient genome-based ldcC expression and resulted in a high diaminopentane yield of 200 mmol mol(-1). By supplementing the medium with 1 mgL(-1) pyridoxal, the cofactor of lysine decarboxylase, the yield was increased to 300 mmol mol(-1). In the production strain obtained, lysine secretion was almost completely abolished. Metabolic analysis, however, revealed substantial formation of an as yet unknown by-product. It was identified as an

Carbohydrate metabolism of Xylella fastidiosa: Detection of glycolytic and pentose phosphate pathway enzymes and cloning and expression of the enolase gene

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Facincani Agda Paula

2003-01-01

Full Text Available The objective of this work was to assess the functionality of the glycolytic pathways in the bacterium Xylella fastidiosa. To this effect, the enzymes phosphoglucose isomerase, aldolase, glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase of the glycolytic pathway, and glucose 6-phosphate dehydrogenase of the Entner-Doudoroff pathway were studied, followed by cloning and expression studies of the enolase gene and determination of its activity. These studies showed that X. fastidiosa does not use the glycolytic pathway to metabolize carbohydrates, which explains the increased duplication time of this phytopatogen. Recombinant enolase was expressed as inclusion bodies and solubilized with urea (most efficient extractor, Triton X-100, and TCA. Enolase extracted from X. fastidiosa and from chicken muscle and liver is irreversibly inactivated by urea. The purification of enolase was partial and resulted in a low yield. No enzymatic activity was detected for either recombinant and native enolases, aldolase, and glyceraldehyde-3-phosphate dehydrogenase, suggesting that X. fastidiosa uses the Entner-Doudoroff pathway to produce pyruvate. Evidence is presented supporting the idea that the regulation of genes and the presence of isoforms with regulation patterns might make it difficult to understand the metabolism of carbohydrates in X. fastidiosa.

An extensive case study of hairy-root cultures for enhanced secondary-metabolite production through metabolic-pathway engineering.

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Mehrotra, Shakti; Rahman, Laiq Ur; Kukreja, Arun Kumar

2010-08-23

An intrinsic improvement is taking place in the methodologies for the development of culture systems with first-rate production of plant-based molecules. The blending of HR (hairy root) cultures with ME (metabolic engineering) approaches offers new insights into, and possibilities for, improving the system productivity for known and/or novel high-value plant-derived active compounds. The introduction and expression of foreign genes in plants results in improvement of cellular activities by manipulating enzymatic, regulatory and transport function of the cell. The rational amendments in the rate-limiting steps of a biosynthetic pathway as well as inactivating the inefficient pathway(s) for by-product formation can be accomplished either through single-step engineering or through the multi-step engineering. The hierarchical control of any metabolic process can lead the engineer to apply the ME ideas and principles to any of the strata, including transcriptional, moving on to translational and enzymatic activity. The HR culture systems offer a remarkable potential for commercial production of a number of low-volume, but high-value, secondary metabolites. Taking HR as a model system, in the present review, we discuss engineering principles and perceptions to exploit secondary-metabolite pathways for the production of important bioactive compounds. We also talk about requisites and possible challenges that occur during ME, with emphasis on examples of various HR systems. Furthermore, it also highlights the utilization of global information obtained from '-omic' platforms in order to explore pathway architecture, structural and functional aspects of important enzymes and genes that can support the design of sets of engineering, resulting in the generation of wide-ranging views of DNA sequence-to-metabolite passageway networking and their control to obtain desired results.

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

Science.gov (United States)

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.

Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus

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Monier, Adam; Pagarete, António; de Vargas, Colomban; Allen, Michael J.; Read, Betsy; Claverie, Jean-Michel; Ogata, Hiroyuki

2009-01-01

Interactions between viruses and phytoplankton, the main primary producers in the oceans, affect global biogeochemical cycles and climate. Recent studies are increasingly revealing possible cases of gene transfers between cyanobacteria and phages, which might have played significant roles in the evolution of cyanobacteria/phage systems. However, little has been documented about the occurrence of horizontal gene transfer in eukaryotic phytoplankton/virus systems. Here we report phylogenetic evidence for the transfer of seven genes involved in the sphingolipid biosynthesis pathway between the cosmopolitan eukaryotic microalga Emiliania huxleyi and its large DNA virus EhV. PCR assays indicate that these genes are prevalent in E. huxleyi and EhV strains isolated from different geographic locations. Patterns of protein and gene sequence conservation support that these genes are functional in both E. huxleyi and EhV. This is the first clear case of horizontal gene transfer of multiple functionally linked enzymes in a eukaryotic phytoplankton–virus system. We examine arguments for the possible direction of the gene transfer. The virus-to-host direction suggests the existence of ancient viruses that controlled the complex metabolic pathway in order to infect primitive eukaryotic cells. In contrast, the host-to-virus direction suggests that the serial acquisition of genes involved in the same metabolic pathway might have been a strategy for the ancestor of EhVs to stay ahead of their closest relatives in the great evolutionary race for survival. PMID:19451591

Bi-directional gene set enrichment and canonical correlation analysis identify key diet-sensitive pathways and biomarkers of metabolic syndrome

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Gaora Peadar Ó

2010-10-01

Full Text Available Abstract Background Currently, a number of bioinformatics methods are available to generate appropriate lists of genes from a microarray experiment. While these lists represent an accurate primary analysis of the data, fewer options exist to contextualise those lists. The development and validation of such methods is crucial to the wider application of microarray technology in the clinical setting. Two key challenges in clinical bioinformatics involve appropriate statistical modelling of dynamic transcriptomic changes, and extraction of clinically relevant meaning from very large datasets. Results Here, we apply an approach to gene set enrichment analysis that allows for detection of bi-directional enrichment within a gene set. Furthermore, we apply canonical correlation analysis and Fisher's exact test, using plasma marker data with known clinical relevance to aid identification of the most important gene and pathway changes in our transcriptomic dataset. After a 28-day dietary intervention with high-CLA beef, a range of plasma markers indicated a marked improvement in the metabolic health of genetically obese mice. Tissue transcriptomic profiles indicated that the effects were most dramatic in liver (1270 genes significantly changed; p Conclusion Bi-directional gene set enrichment analysis more accurately reflects dynamic regulatory behaviour in biochemical pathways, and as such highlighted biologically relevant changes that were not detected using a traditional approach. In such cases where transcriptomic response to treatment is exceptionally large, canonical correlation analysis in conjunction with Fisher's exact test highlights the subset of pathways showing strongest correlation with the clinical markers of interest. In this case, we have identified selenoamino acid metabolism and steroid biosynthesis as key pathways mediating the observed relationship between metabolic health and high-CLA beef. These results indicate that this type of

Acetic acid activates the AMP-activated protein kinase signaling pathway to regulate lipid metabolism in bovine hepatocytes.

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Xinwei Li

Full Text Available The effect of acetic acid on hepatic lipid metabolism in ruminants differs significantly from that in monogastric animals. Therefore, the aim of this study was to investigate the regulation mechanism of acetic acid on the hepatic lipid metabolism in dairy cows. The AMP-activated protein kinase (AMPK signaling pathway plays a key role in regulating hepatic lipid metabolism. In vitro, bovine hepatocytes were cultured and treated with different concentrations of sodium acetate (neutralized acetic acid and BML-275 (an AMPKα inhibitor. Acetic acid consumed a large amount of ATP, resulting in an increase in AMPKα phosphorylation. The increase in AMPKα phosphorylation increased the expression and transcriptional activity of peroxisome proliferator-activated receptor α, which upregulated the expression of lipid oxidation genes, thereby increasing lipid oxidation in bovine hepatocytes. Furthermore, elevated AMPKα phosphorylation reduced the expression and transcriptional activity of the sterol regulatory element-binding protein 1c and the carbohydrate responsive element-binding protein, which reduced the expression of lipogenic genes, thereby decreasing lipid biosynthesis in bovine hepatocytes. In addition, activated AMPKα inhibited the activity of acetyl-CoA carboxylase. Consequently, the triglyceride content in the acetate-treated hepatocytes was significantly decreased. These results indicate that acetic acid activates the AMPKα signaling pathway to increase lipid oxidation and decrease lipid synthesis in bovine hepatocytes, thereby reducing liver fat accumulation in dairy cows.

Importance of metabolism in pharmacological studies: possible in vitro predictability

International Nuclear Information System (INIS)

Delaforge, M.

1998-01-01

Metabolic transformation of drug leads to the formation of a large number of secondary compounds. These metabolites may (a) participate to the elimination of the patent drug, (b) have similar or different therapeutic effects compared to the parent drug (c) exert toxic effects. Cytochromes P450 are the main enzymes involved in the biotransformation of exogenous drugs, leading to oxidized, reduced or peroxidized metabolites. Different isozymes of P450 are present in already all the organs and differ by their affinity for substrate families. P450 3A is the most abundant P450 protein in the adult human liver and is able to transform hundreds of substrates into either drugs or endogenous compounds such as testosterone. Its catalytic activities are regulated either by induction or by inhibition. Attempts to predict metabolic transformation of a given drug are based on the amount of P450 expressed in heterologous systems, induction, and inhibition experiments and by comparison to classical P450 substrates. Erythromycin metabolism and its P450 effects are used to illustrate the complexity and the consequences of metabolic transformation of a given drug

Metabolic syndrome and atypical antipsychotics: Possibility of prediction and control.

Science.gov (United States)

Franch Pato, Clara M; Molina Rodríguez, Vicente; Franch Valverde, Juan I

Schizophrenia and other psychotic disorders are associated with high morbidity and mortality, due to inherent health factors, genetic factors, and factors related to psychopharmacological treatment. Antipsychotics, like other drugs, have side-effects that can substantially affect the physical health of patients, with substantive differences in the side-effect profile and in the patients in which these side-effects occur. To understand and identify these risk groups could help to prevent the occurrence of the undesired effects. A prospective study, with 24 months follow-up, was conducted in order to analyse the physical health of severe mental patients under maintenance treatment with atypical antipsychotics, as well as to determine any predictive parameters at anthropometric and/or analytical level for good/bad outcome of metabolic syndrome in these patients. There were no significant changes in the physical and biochemical parameters individually analysed throughout the different visits. The baseline abdominal circumference (lambda Wilks P=.013) and baseline HDL-cholesterol levels (lambda Wilks P=.000) were the parameters that seem to be more relevant above the rest of the metabolic syndrome constituents diagnosis criteria as predictors in the long-term. In the search for predictive factors of metabolic syndrome, HDL-cholesterol and abdominal circumference at the time of inclusion were selected, as such that the worst the baseline results were, the higher probability of long-term improvement. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Rewiring the Glucose Transportation and Central Metabolic Pathways for Overproduction of N-Acetylglucosamine in Bacillus subtilis.

Science.gov (United States)

Gu, Yang; Deng, Jieying; Liu, Yanfeng; Li, Jianghua; Shin, Hyun-Dong; Du, Guocheng; Chen, Jian; Liu, Long

2017-10-01

N-acetylglucosamine (GlcNAc) is an important amino sugar extensively used in the healthcare field. In a previous study, the recombinant Bacillus subtilis strain BSGN6-P xylA -glmS-pP43NMK-GNA1 (BN0-GNA1) had been constructed for microbial production of GlcNAc by pathway design and modular optimization. Here, the production of GlcNAc is further improved by rewiring both the glucose transportation and central metabolic pathways. First, the phosphotransferase system (PTS) is blocked by deletion of three genes, yyzE (encoding the PTS system transporter subunit IIA YyzE), ypqE (encoding the PTS system transporter subunit IIA YpqE), and ptsG (encoding the PTS system glucose-specific EIICBA component), resulting in 47.6% increase in the GlcNAc titer (from 6.5 ± 0.25 to 9.6 ± 0.16 g L -1 ) in shake flasks. Then, reinforcement of the expression of the glcP and glcK genes and optimization of glucose facilitator proteins are performed to promote glucose import and phosphorylation. Next, the competitive pathways for GlcNAc synthesis, namely glycolysis, peptidoglycan synthesis pathway, pentose phosphate pathway, and tricarboxylic acid cycle, are repressed by initiation codon-optimization strategies, and the GlcNAc titer in shake flasks is improved from 10.8 ± 0.25 to 13.2 ± 0.31 g L -1 . Finally, the GlcNAc titer is further increased to 42.1 ± 1.1 g L -1 in a 3-L fed-batch bioreactor, which is 1.72-fold that of the original strain, BN0-GNA1. This study shows considerably enhanced GlcNAc production, and the metabolic engineering strategy described here will be useful for engineering other prokaryotic microorganisms for the production of GlcNAc and related molecules. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Energy Technology Data Exchange (ETDEWEB)

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

2007-08-13

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

Exposure to atrazine affects the expression of key genes in metabolic pathways integral to energy homeostasis in Xenopus laevis tadpoles.

Science.gov (United States)

Zaya, Renee M; Amini, Zakariya; Whitaker, Ashley S; Ide, Charles F

2011-08-01

In our laboratory, Xenopus laevis tadpoles exposed throughout development to 200 or 400 μg/L atrazine, concentrations reported to periodically occur in puddles, vernal ponds and runoff soon after application, were smaller and had smaller fat bodies (the tadpole's lipid storage organ) than controls. It was hypothesized that these changes were due to atrazine-related perturbations of energy homeostasis. To investigate this hypothesis, selected metabolic responses to exposure at the transcriptional and biochemical levels in atrazine-exposed tadpoles were measured. DNA microarray technology was used to determine which metabolic pathways were affected after developmental exposure to 400 μg/L atrazine. From these data, genes representative of the affected pathways were selected for assay using quantitative real time polymerase chain reaction (qRT-PCR) to measure changes in expression during a 2-week exposure to 400 μg/L. Finally, ATP levels were measured from tadpoles both early in and at termination of exposure to 200 and 400 μg/L. Microarray analysis revealed significant differential gene expression in metabolic pathways involved with energy homeostasis. Pathways with increased transcription were associated with the conversion of lipids and proteins into energy. Pathways with decreased transcription were associated with carbohydrate metabolism, fat storage, and protein synthesis. Using qRT-PCR, changes in gene expression indicative of an early stress response to atrazine were noted. Exposed tadpoles had significant decreases in acyl-CoA dehydrogenase (AD) and glucocorticoid receptor protein (GR) mRNA after 24 h of exposure, and near-significant (p=0.07) increases in peroxisome proliferator-activated receptor β (PPAR-β) mRNA by 72 h. Decreases in AD suggested decreases in fatty acid β-oxidation while decreases in GR may have been a receptor desensitization response to a glucocorticoid surge. Involvement of PPAR-β, an energy homeostasis regulatory molecule, also

Metabolic Disorder, Inflammation, and Deregulated Molecular Pathways Converging in Pancreatic Cancer Development: Implications for New Therapeutic Strategies

International Nuclear Information System (INIS)

Motoo, Yoshiharu; Shimasaki, Takeo; Ishigaki, Yasuhito; Nakajima, Hideo; Kawakami, Kazuyuki; Minamoto, Toshinari

2011-01-01

Pancreatic cancer develops and progresses through complex, cumulative biological processes involving metabolic disorder, local inflammation, and deregulated molecular pathways. The resulting tumor aggressiveness hampers surgical intervention and renders pancreatic cancer resistant to standard chemotherapy and radiation therapy. Based on these pathologic properties, several therapeutic strategies are being developed to reverse refractory pancreatic cancer. Here, we outline molecular targeting therapies, which are primarily directed against growth factor receptor-type tyrosine kinases deregulated in tumors, but have failed to improve the survival of pancreatic cancer patients. Glycogen synthase kinase-3β (GSK3β) is a member of a serine/threonine protein kinase family that plays a critical role in various cellular pathways. GSK3β has also emerged as a mediator of pathological states, including glucose intolerance, inflammation, and various cancers (e.g., pancreatic cancer). We review recent studies that demonstrate the anti-tumor effects of GSK3β inhibition alone or in combination with chemotherapy and radiation. GSK3β inhibition may exert indirect anti-tumor actions in pancreatic cancer by modulating metabolic disorder and inflammation

Metabolic Disorder, Inflammation, and Deregulated Molecular Pathways Converging in Pancreatic Cancer Development: Implications for New Therapeutic Strategies

Energy Technology Data Exchange (ETDEWEB)

Motoo, Yoshiharu, E-mail: motoo@kanazawa-med.ac.jp [Department of Medical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Ishikawa 920-0293 (Japan); Shimasaki, Takeo [Department of Medical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Ishikawa 920-0293 (Japan); Division of Translational & Clinical Oncology, Cancer Research Institute, Kanazawa University, Kanazawa (Japan); Ishigaki, Yasuhito [Medical Research Institute, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Ishikawa 920-0293 (Japan); Nakajima, Hideo [Department of Medical Oncology, Kanazawa Medical University, 1-1 Daigaku, Uchinada, Ishikawa 920-0293 (Japan); Kawakami, Kazuyuki; Minamoto, Toshinari [Division of Translational & Clinical Oncology, Cancer Research Institute, Kanazawa University, Kanazawa (Japan)

2011-01-24

Pancreatic cancer develops and progresses through complex, cumulative biological processes involving metabolic disorder, local inflammation, and deregulated molecular pathways. The resulting tumor aggressiveness hampers surgical intervention and renders pancreatic cancer resistant to standard chemotherapy and radiation therapy. Based on these pathologic properties, several therapeutic strategies are being developed to reverse refractory pancreatic cancer. Here, we outline molecular targeting therapies, which are primarily directed against growth factor receptor-type tyrosine kinases deregulated in tumors, but have failed to improve the survival of pancreatic cancer patients. Glycogen synthase kinase-3β (GSK3β) is a member of a serine/threonine protein kinase family that plays a critical role in various cellular pathways. GSK3β has also emerged as a mediator of pathological states, including glucose intolerance, inflammation, and various cancers (e.g., pancreatic cancer). We review recent studies that demonstrate the anti-tumor effects of GSK3β inhibition alone or in combination with chemotherapy and radiation. GSK3β inhibition may exert indirect anti-tumor actions in pancreatic cancer by modulating metabolic disorder and inflammation.

Metabolic Disorder, Inflammation, and Deregulated Molecular Pathways Converging in Pancreatic Cancer Development: Implications for New Therapeutic Strategies

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Toshinari Minamoto

2011-01-01

Full Text Available Pancreatic cancer develops and progresses through complex, cumulative biological processes involving metabolic disorder, local inflammation, and deregulated molecular pathways. The resulting tumor aggressiveness hampers surgical intervention and renders pancreatic cancer resistant to standard chemotherapy and radiation therapy. Based on these pathologic properties, several therapeutic strategies are being developed to reverse refractory pancreatic cancer. Here, we outline molecular targeting therapies, which are primarily directed against growth factor receptor-type tyrosine kinases deregulated in tumors, but have failed to improve the survival of pancreatic cancer patients. Glycogen synthase kinase-3β (GSK3β is a member of a serine/threonine protein kinase family that plays a critical role in various cellular pathways. GSK3β has also emerged as a mediator of pathological states, including glucose intolerance, inflammation, and various cancers (e.g., pancreatic cancer. We review recent studies that demonstrate the anti-tumor effects of GSK3β inhibition alone or in combination with chemotherapy and radiation. GSK3β inhibition may exert indirect anti-tumor actions in pancreatic cancer by modulating metabolic disorder and inflammation.

Flower abscission in Vitis vinifera L. triggered by gibberellic acid and shade discloses differences in the underlying metabolic pathways

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Sara eDomingos

2015-06-01

Full Text Available Understanding abscission is both a biological and an agronomic challenge. Flower abscission induced independently by shade and gibberellic acid (GAc sprays was monitored in grapevine (Vitis vinifera L. growing under a soilless greenhouse system during two seasonal growing conditions, in an early and late production cycle. Physiological and metabolic changes triggered by each of the two distinct stimuli were determined. Environmental conditions exerted a significant effect on fruit set as showed by the higher natural drop rate recorded in the late production cycle with respect to the early cycle. Shade and GAc treatments increased the percentage of flower drop compared to the control, and at a similar degree, during the late production cycle. The reduction of leaf gas exchanges under shade conditions was not observed in GAc treated vines. The metabolic profile assessed in samples collected during the late cycle differently affected primary and secondary metabolisms and showed that most of the treatment-resulting variations occurred in opposite trends in inflorescences unbalanced in either hormonal or energy deficit abscission-inducing signals. Particularly concerning carbohydrates metabolism, sucrose, glucose, tricarboxylic acid (TCA metabolites and intermediates of the raffinose family oligosaccharides pathway were lower in shaded and higher in GAc samples. Altered oxidative stress remediation mechanisms and indolacetic acid (IAA concentration were identified as abscission signatures common to both stimuli. According to the global analysis performed, we report that grape flower abscission mechanisms triggered by GAc application and C-starvation are not based on the same metabolic pathways.

Weight loss predictability by plasma metabolic signatures in adults with obesity and morbid obesity of the DiOGenes study

DEFF Research Database (Denmark)

Stroeve, Johanna H M; Saccenti, Edoardo; Bouwman, Jildau

2016-01-01

predictive for weight loss were acetoacetate, triacylglycerols, phosphatidylcholines, specific amino acids, and creatine and creatinine. This metabolic profile suggests that high energy metabolism activity results in higher amounts of weight loss. CONCLUSIONS: Possible predictive (pre-diet) markers were...

Identification and characterization of the furfural and 5-(hydroxymethyl)furfural degradation pathways of Cupriavidus basilensis HMF14

Energy Technology Data Exchange (ETDEWEB)

Koopman, F.; De Winde, J.H. [Bio-Based Sustainable Industrial Chemistry (B-Basic), Delft University of Technology, Department of Biotechnology, Julianalaan 67, 2628 BC, Delft (Netherlands); Wierckx, N. [Kluyver Centre for Genomics of Industrial Fermentation, P.O. Box 5057, 2600 GB, Delft (Netherlands); Ruijssenaars, H.J. [Netherlands Organization for Applied Scientific Research, Quality of Life, Department of Bioconversion, Julianalaan 67, 2628 BC, Delft (Netherlands); O' Neal Ingram, L. (ed.) [University of Florida, Gainesville, Gainesville, FL (United States)

2010-03-16

The toxic fermentation inhibitors in lignocellulosic hydrolysates pose significant problems for the production of second-generation biofuels and biochemicals. Among these inhibitors, 5-(hydroxymethyl) furfural (HMF) and furfural are specifically notorious. In this study, we describe the complete molecular identification and characterization of the pathway by which Cupriavidus basilensis HMF14 metabolizes HMF and furfural. The identification of this pathway enabled the construction of an HMF and furfural-metabolizing Pseudomonas putida. The genetic information obtained furthermore enabled us to predict the HMF and furfural degrading capabilities of sequenced bacterial species that had not previously been connected to furanic aldehyde metabolism. These results pave the way for in situ detoxification of lignocellulosic hydrolysates, which is a major step toward improved efficiency of utilization of lignocellulosic feedstock.

Identification and characterization of the furfural and 5-(hydroxymethyl)furfural degradation pathways of Cupriavidus basilensis HMF14

Science.gov (United States)

Koopman, Frank; Wierckx, Nick; de Winde, Johannes H.; Ruijssenaars, Harald J.

2010-01-01

The toxic fermentation inhibitors in lignocellulosic hydrolysates pose significant problems for the production of second-generation biofuels and biochemicals. Among these inhibitors, 5-(hydroxymethyl)furfural (HMF) and furfural are specifically notorious. In this study, we describe the complete molecular identification and characterization of the pathway by which Cupriavidus basilensis HMF14 metabolizes HMF and furfural. The identification of this pathway enabled the construction of an HMF and furfural-metabolizing Pseudomonas putida. The genetic information obtained furthermore enabled us to predict the HMF and furfural degrading capabilities of sequenced bacterial species that had not previously been connected to furanic aldehyde metabolism. These results pave the way for in situ detoxification of lignocellulosic hydrolysates, which is a major step toward improved efficiency of utilization of lignocellulosic feedstock. PMID:20194784

Yeast glucose pathways converge on the transcriptional regulation of trehalose biosynthesis

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Apweiler Eva

2012-06-01

Full Text Available Abstract Background Cellular glucose availability is crucial for the functioning of most biological processes. Our understanding of the glucose regulatory system has been greatly advanced by studying the model organism Saccharomyces cerevisiae, but many aspects of this system remain elusive. To understand the organisation of the glucose regulatory system, we analysed 91 deletion mutants of the different glucose signalling and metabolic pathways in Saccharomyces cerevisiae using DNA microarrays. Results In general, the mutations do not induce pathway-specific transcriptional responses. Instead, one main transcriptional response is discerned, which varies in direction to mimic either a high or a low glucose response. Detailed analysis uncovers established and new relationships within and between individual pathways and their members. In contrast to signalling components, metabolic components of the glucose regulatory system are transcriptionally more frequently affected. A new network approach is applied that exposes the hierarchical organisation of the glucose regulatory system. Conclusions The tight interconnection between the different pathways of the glucose regulatory system is reflected by the main transcriptional response observed. Tps2 and Tsl1, two enzymes involved in the biosynthesis of the storage carbohydrate trehalose, are predicted to be the most downstream transcriptional components. Epistasis analysis of tps2Δ double mutants supports this prediction. Although based on transcriptional changes only, these results suggest that all changes in perceived glucose levels ultimately lead to a shift in trehalose biosynthesis.

PDP-1 links the TGF-β and IIS pathways to regulate longevity, development, and metabolism.

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Sri Devi Narasimhan

2011-04-01

Full Text Available The insulin/IGF-1 signaling (IIS pathway is a conserved regulator of longevity, development, and metabolism. In Caenorhabditis elegans IIS involves activation of DAF-2 (insulin/IGF-1 receptor tyrosine kinase, AGE-1 (PI 3-kinase, and additional downstream serine/threonine kinases that ultimately phosphorylate and negatively regulate the single FOXO transcription factor homolog DAF-16. Phosphatases help to maintain cellular signaling homeostasis by counterbalancing kinase activity. However, few phosphatases have been identified that negatively regulate the IIS pathway. Here we identify and characterize pdp-1 as a novel negative modulator of the IIS pathway. We show that PDP-1 regulates multiple outputs of IIS such as longevity, fat storage, and dauer diapause. In addition, PDP-1 promotes DAF-16 nuclear localization and transcriptional activity. Interestingly, genetic epistasis analyses place PDP-1 in the DAF-7/TGF-β signaling pathway, at the level of the R-SMAD proteins DAF-14 and DAF-8. Further investigation into how a component of TGF-β signaling affects multiple outputs of IIS/DAF-16, revealed extensive crosstalk between these two well-conserved signaling pathways. We find that PDP-1 modulates the expression of several insulin genes that are likely to feed into the IIS pathway to regulate DAF-16 activity. Importantly, dysregulation of IIS and TGF-β signaling has been implicated in diseases such as Type 2 Diabetes, obesity, and cancer. Our results may provide a new perspective in understanding of the regulation of these pathways under normal conditions and in the context of disease.

Metabolic Profiling of Primary and Secondary Biosynthetic Pathways in Angiosperms: Comparative Metabonomics and Applications of Hyphenated LC-NMR and LC-MS

OpenAIRE

Kaiser, Kayla Anne

2012-01-01

The goal of this dissertation was to advance plant metabolomics through optimization of biological experimental design, sampling and sample preparation, data acquisition and pre-processing, and multivariable data analysis. The analytical platform most employed for comparative metabonomics was nuclear magnetic resonance (NMR). Liquid-chromatography (LC) coupled to NMR and mass spectrometry (MS) extended metabolic profile coverage from primary into secondary metabolic pathways. Comparative p...

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