Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Metabolic analysis”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9Linked to original sources
PubMed2006

Towards industrial application of quasi real-time metabolic flux analysis for mammalian cell culture.

Cellular physiology and metabolism were monitored using a quasi real-time combination of on-line and off-line data to estimate metabolic fluxes in an established bioreaction network. The utility of this approach towards optimizing bioreactor operation was demonstrated for CHO cells cultivated in 15 L perfusion reactors at 20 x 10(6) cells/mL. Medium composition and dilution rates were changed to obtain several steady states with varying glucose and glutamine concentrations. When cells were restored to initial culture medium and perfusion rate conditions after being exposed to lower glucose and glutamine concentrations, the pyruvate flux into the TCA cycle was increased 30% while the pyruvate flux through lactate was decreased 30%, suggesting steady-state multiplicity. By appropriately altering cellular metabolism, perfusion bioreactors can operate at lower perfusion rates without significant accumulation of inhibitory metabolites such as lactate. Changes in glucose, lactate and glutamine uptake/production rates had significant effects on the calculation of other fluxes in the network. Sensitivity analysis of these key metabolic fluxes highlighted the need for accurate and reliable real-time sensors. Overall, rapid observation of metabolic fluxes can be a valuable tool for bioprocess development, monitoring and control. The framework presented in this study offers a convenient means for quasi real-time estimation of metabolic fluxes and represents a step towards realizing the potential of metabolic flux analysis for accelerated bioprocess optimization.

Animals↗
PubMed2004

Metabolic control analysis as a mechanism that conserves genetic variance during advanced cycle breeding.

The recycling of elite inbreds (i.e., advanced cycle breeding) has led to significant genetic gains but also to a narrow gene pool in plant breeding programs. Sustained yield improvements in many crops have suggested that genetic variance is not depleted at a rate predicted by an additive genetic model. Unlike the additive model in classical quantitative genetic theory, metabolic control analysis relates the variation in a biochemical process with the genetic variation in a quantitative trait. Our objective was to determine whether metabolic control analysis is a mechanism that slows the decrease in genetic variance during advanced cycle breeding. Three cycles of advanced cycle breeding were simulated with 10, 50, or 100 quantitative trait loci (QTL) controlling a trait. In metabolic control analysis, these QTL coded for enzymes involved in a linear metabolic pathway that converted a substrate into a product. In the absence of selection, both the additive model and the metabolic control analysis model led to about a 50% reduction in genetic variance from cycle to cycle. With selection, the additive model led to a 50-58% reduction in genetic variance, but the metabolic control analysis model generally led to only a 12-54% reduction. We suggest selection in a metabolic control analysis model as a mechanism that slows the decrease in genetic variance during advanced cycle breeding. This conservation of genetic variance would allow breeders to achieve genetic gains for a longer period than expected under the additive model.

Conserved Sequence↗
PubMed1990

Integration of temporal analysis and control analysis of metabolic systems.

A theory is developed that integrates approaches to the analysis of pathway transient response and metabolic control analysis. A Temporal Control Coefficient is defined that is a measure of the system's transient response to modulation of enzyme activity or concentration. The approach allows for the analysis of the establishment of a steady state from rest, of the system's 'agility' of response to minor perturbations of a pre-existing steady state and of the macroscopic transition between steady states. In the last-mentioned case it is shown that, like the transient time itself, the control of transient response retains the property of independence from the mechanism of the transition. In consequence, the Temporal Control Coefficient can be defined in terms of the control properties of the initial and final states alone without reference to the mechanism of transition. A summation property is shown to apply to the Temporal Control Coefficients in each case. Connectivity relationships between elasticities and Temporal Control Coefficients are also established.

Enzymes↗
PubMed2004

Metabolic flux analysis based on 13C-labeling experiments and integration of the information with gene and protein expression patterns.

The recent progress on metabolic systems engineering was reviewed, in particular focusing on the metabolic flux analysis (MFA) based on the isotopomer distribution obtained using NMR and/or GC-MS. After the brief explanation of how to estimate the metabolic flux distribution (MFD) based on 13C-labeling experiments, the metabolic regulation analysis was made based on the protein expression patterns obtained by two-dimensional electrophoresis (2DE) together with enzyme activity data, and the gene expression patterns obtained by RT-PCR analysis. The particular application was considered for Escherichia coli. The effect of culture conditions such as different carbon sources (glucose, gluconate, glycerol, acetate, etc.) and different dissolved oxygen (DO) concentration, etc. on the metabolism was investigated. The effect of some single-gene knockout such as pgi-, pyk-, and gnd- was also investigated. It was found to be quite useful to integrate the information obtained from metabolic flux analysis, gene and protein expressions as well as intracellular metabolite concentrations to understand the overall picture of metabolic regulation.

Aldehyde-Lyases↗
PubMed1998

Increasing the flux in metabolic pathways: A metabolic control analysis perspective

The problems of engineering increased flux in metabolic pathways are analyzed in terms of the understanding provided by metabolic control analysis. Over-expression of a single enzyme is unlikely to be effective unless it is known to have a high flux control coefficient, which can be used as an approximate predictive tool. This is likely to rule out enzymes subject to feedback inhibition, because it transfers control downstream from the inhibited enzyme to the enzymes utilizing the feedback metabolite. Although abolishing feedback inhibition can restore flux control to an enzyme, it is also likely to cause large increases in the concentrations of metabolic intermediates. Simultaneous and coordinated over-expression of most of the enzymes in a pathway can, in principle, produce substantial flux increases without changes in metabolite levels, though technically it may be difficult to achieve. It is, however, closer to the method used by cells to change flux levels, where coordinated changes in the level of activity of pathway enzymes are the norm. Another option is to increase the demand for the pathway product, perhaps by increasing its rate of excretion or removal. Copyright 1998 John Wiley & Sons, Inc.

Journal Article↗
PubMed2003

Analysis of metabolic syndrome phenotypes in Framingham Heart Study families from Genetic Analysis Workshop 13.

Twelve teams of investigators constituted a group which analyzed phenotypes related to metabolic syndrome, making use of the available longitudinal measurements from the family component of the Framingham Heart Study or the simulated data, as distributed by Genetic Analysis Workshop 13 (GAW13). Body mass index, obesity, lipid abnormalities, glucose, or combinations of these traits were analyzed by this group. A wide variety of approaches were taken to construct phenotypes from the longitudinal measurements, including considering single or multiple cross-sectional time points, single ages, minimum values, maximum values, means, other lifetime values, ever/never dichotomy, or age at onset of some threshold value. Approaches also differed in the family structures utilized (sib pairs to full extended pedigrees), the genetic data considered (two-point or multipoint), and the statistics calculated (model-free and parametric), and led to a diverse set of analyses being performed. Inferences were made about heritability, and attempts were made to map underlying genes. Over 40 genome-wide linkage analyses were conducted. Despite the broad range of approaches, several regions of the genome were repeatedly identified across multiple analyses.

Cardiovascular Diseases↗
PubMed2001

Innovations in generation and analysis of 2D [(13)C,(1)H] COSY NMR spectra for metabolic flux analysis purposes.

2D [(13)C,(1)H] COSY NMR is used by the metabolic engineering community for determining (13)C-(13)C connectivities in intracellular compounds that contain information regarding the steady-state fluxes in cellular metabolism. This paper proposes innovations in the generation and analysis of these specific NMR spectra. These include a computer tool that allows accurate determination of the relative peak areas and their complete covariance matrices even in very complex spectra. Additionally, a method is introduced for correcting the results for isotopic non-steady-state conditions. The proposed methods were applied to measured 2D [(13)C,(1)H] COSY NMR spectra. Peak intensities in a one-dimensional section of the spectrum are frequently not representative for relative peak volumes in the two-dimensional spectrum. It is shown that for some spectra a significant amount of additional information can be gained from long-range (13)C-(13)C scalar couplings in 2D [(13)C,(1)H] COSY NMR spectra. Finally, the NMR resolution enhancement by dissolving amino acid derivatives in a nonpolar solvent is demonstrated.

Amino Acids↗
PubMed2002

Metabolic flux analysis using mass spectrometry.

Detailed knowledge on carbon flux distributions is crucial for the understanding and targeted optimization of cellular systems. Analytical methods to identify the topology of metabolic networks and to quantify fluxes through its different pathways are therefore in the core of metabolic engineering. An elegant approach for metabolic flux analysis is provided by tracer experiments. In such studies tracer substrates with stable isotopes such as 13C are applied and the labeling pattern of metabolites is subsequently measured. Detailed flux distributions can be obtained by a combination of tracer experiments and stoichiometric balancing. In recent years, mass spectrometry (MS) has emerged as an interesting method for labeling measurements in metabolic flux analysis and provided valuable insights into the cellular metabolism. The present review provides an overview on current experimental and modeling tools for metabolic flux analysis by MS. The application of MS for flux analysis is illustrated by examples from the literature for various biological systems, including bacteria, fungi, tissue cultures and in vivo studies in humans.

Carbon Isotopes↗
PubMed2003

Metabolic flux analysis of hepatocyte function in hormone- and amino acid-supplemented plasma.

Understanding the metabolic and regulatory pathways of hepatocytes is important for biotechnological applications involving liver cells. Previous attempts to culture hepatocytes in plasma yielded poor functional results. Recently we reported that hormone (insulin and hydrocortisone) and amino acid supplementation reduces intracellular lipid accumulation and restores liver-specific function in hepatocytes exposed to heparinized human plasma. In the current study, we performed metabolic flux analysis (MFA) using a simplified metabolic network model of cultured hepatocytes to quantitively estimate the changes in lipid metabolism and relevant intracellular pathways in response to hormone and amino acid supplementation. The model accounts for the majority of central carbon and nitrogen metabolism, and assumes pseudo-steady-state with no metabolic futile cycles. We found that beta-oxidation and tricarboxylic acid (TCA) cycle fluxes were upregulated by both hormone and amino acid supplementation, thus enhancing the rate of lipid oxidation. Concomitantly, hormone and amino acid supplementation increased gluconeogenic fluxes. This, together with an increased rate of glucose clearance, caused an increase in predicted glycogen synthesis. Urea synthesis was primarily derived from ammonia and aspartate generated through transamination reactions, while exogenous ammonia removal accounted for only 3-6% of the urea nitrogen. Amino acid supplementation increased the endogenous synthesis of oxaloacetate, and in turn that of aspartate, a necessary substrate for the urea cycle. These findings from MFA provide cues as to which genes/pathways relevant to fatty acid oxidation, urea production, and gluconeogenesis may be upregulated by plasma supplementation, and are consistent with current knowledge of hepatic amino acid metabolism, which provides further credence to this approach for evaluating the metabolic state of hepatocytes under various environmental conditions.

Albumins↗
PubMed2025

HUMESS: integrating quantitative transcriptomic analysis and metabolic modeling to unveil condition-specific gene signatures.

SUMMARY: Transcriptomic analysis is a key tool for exploring gene expression, but the complexity of biological systems often limits its insights. In particular, the lack of intermodal or multi-layered analysis hinders the ability to fully capture key cellular functions such as metabolism from transcriptomic data alone. Here, we introduce a novel approach that informs transcriptomic data analysis with metabolic network modeling to address this. Unlike traditional methods, HUman MEtabolism Specific Signature (HUMESS) uses genome-scale metabolic modeling and flux analysis to highlight reactions and involved genes based on their metabolic significance, offering a deeper understanding of transcriptomic data. Our computational pipeline, supported by a user-friendly Rshiny application, enhances gene expression analysis by uncovering metabolic phenotypic signatures. AVAILABILITY AND IMPLEMENTATION: HUMESS is open source and available under GitLab https://gitlab.univ-nantes.fr/bird_pipeline_registry/humess with the complete documentation available at https://gitlab.univ-nantes.fr/bird_pipeline_registry/humess/-/wikis/Home. A zenodo archive is also available at the following DOI: https://doi.org/10.5281/zenodo.15487717. An RShiny application has been developed to facilitate the exploration and analysis of HUMESS's results. The app is available online at the following address: https://shiny-bird.univ-nantes.fr/app/shinymess but can also be installed locally, available under GitLab https://gitlab.univ-nantes.fr/pare-l/shinymess.

Humans↗
PubMed1999

Metabolic flux analysis elucidates the importance of the acid-formation pathways in regulating solvent production by Clostridium acetobutylicum.

Metabolic flux analysis was used to investigate the roles of the acid formation pathways in Clostridium acetobutylicum. The acid formation pathways were revealed to serve different roles in wildtype fermentations than previously expected. Specifically, enzymes known to catalyze butyrate formation were found to uptake butyrate without concomitant production of acetone. This role was further corroborated by flux analysis of a recombinant strain overexpressing the butyrate formation enzymes. Analysis of wildtype fermentation data also revealed an important role for the acetate formation enzymes, namely the cycling of carbon between acetate and acetylCoA during the stationary phase. Next, metabolic flux analysis was used to compare the patterns of activity in two butyrate kinase deficient strains of C. acetobutylicum. The strain developed by gene inactivation, PJC4BK, exhibited a shift in acid formation fluxes toward acetate while the strain developed by antisense RNA strategies, 824(pRD4), did not exhibit such a shift. However, both strains exhibited altered solvent formation patterns. PJC4BK exhibited a strong transient enhancement of solvent formation fluxes. In contrast, 824(pRD4) exhibited relatively lower levels of solvent formation fluxes, although fluxes were sustained over a longer period of time.

Acetic Acid↗
PubMedDate not supplied

Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era.

This article reviews the relatively short history of metabolic pathway analysis. Computer-aided algorithms for the synthesis of metabolic pathways are discussed. Important algebraic concepts used in pathway analysis, such as null space and convex cone, are explained. It is demonstrated how these concepts can be translated into meaningful metabolic concepts. For example, it is shown that the simplest vectors spanning the region of all admissible fluxes in stationary states, for which the term elementary flux modes was coined, correspond to fundamental pathways in the system. The concepts are illustrated with the help of a reaction scheme representing the glyoxylate cycle and adjacent reactions of aspartate and glutamate synthesis. The interrelations between pathway analysis and metabolic control theory are outlined. Promising applications for genome annotation and for biotechnological purposes are discussed. Armed with a better understanding of the architecture of cellular metabolism and the enormous amount of genomic data available today, biochemists and biotechnologists will be able to draw the entire metabolic map of a cell and redesign it by rational and directed metabolic engineering.

Biotechnology↗
PubMed2000

Characterization of energy conversion based on metabolic flux analysis in mixotrophic liverwort cells, Marchantia polymorpha.

In order to characterize the contributions of respiratory and photosynthetic actions to energy conversions, the mixotrophic cells of Marchantia polymorpha were cultivated in the medium containing 10kg/m(3) glucose as an organic carbon source. The cultures were conducted with the supply of ordinary air (0.03% CO(2)) at constant incident light intensities of 50 and 180W/m(2). From the results of metabolic analysis, it was found that the cell yield based on ATP synthesis was estimated to be 6.3x10(-3)kg-dry cells/mol-ATP in these cultures. Under the examined conditions, energy conversion efficiency through respiration was larger than that through photosynthesis, and efficiency of overall energy conversion to ATP was maximized when the sum of energies from glucose and light captured by the cells was approximately 7.2x10(5)J/(hkg-dry cells). Taking into account the efficiency of overall energy conversion, a batch culture of M. polymorpha in a bioreactor was carried out by regulating incident light intensity ranging from 9 to 58W/m(2). In the culture with light regulation, the cell yield of 6.2x10(-9)kg-dry cells/J was achieved on the basis of energy provided to the system throughout the culture, and this value was 2.3 and 9.3 times as large as those obtained in the cultures under constant incident light intensities of 50 and 180W/m(2), respectively.

Journal Article↗
PubMed1993

SCAMP: a general-purpose simulator and metabolic control analysis program.

SCAMP is a general-purpose simulator of metabolic and chemical networks. The program is written in C and is portable to all computer systems that support an ANSI C compiler. SCAMP accepts metabolic models described in a biochemical language, and this enables novice as well as experienced users rapidly to build and simulate metabolic systems. The language is sufficiently flexible to enable other types of model to be built, e.g. chemostat or ecological models. The language offers many facilities, including: the ability to describe metabolic pathways of any structure and possessing any kinetics using normal chemical notation; optionally build models directly from the differential equations; differing compartment volumes; access to flux, concentration and rate of change information; detection of conserved cycles; access to all coefficients and elasticities of metabolic control analysis; user-defined forcing functions at the model boundaries; user-defined monitoring functions; user-configurable output of any quantity. From the model description SCAMP can either generate C code for later compilation to produce fast executable stand-alone models or run-time code for input to a run-time interpreter for immediate execution. The simulator also incorporates an inbuilt symbolic differentiator for evaluating the Jacobian and elasticity matrices.

Algorithms↗
PubMed2005

NMR analysis of plant nitrogen metabolism.

The analysis of primary and secondary nitrogen metabolism in plants by nuclear magnetic resonance (NMR) spectroscopy is comprehensively reviewed. NMR is a versatile analytical tool, and the combined use of (1)H, (2)H, (13)C, (14)N and (15)N NMR allows detailed investigation of the acquisition, assimilation and metabolism of nitrogen. The analysis of tissue extracts can be complemented by the in vivo NMR analysis of functioning tissues and cell suspensions, and by the application of solid state NMR techniques. Moreover stable isotope labelling with (2)H-, (13)C- and (15)N-labelled precursors provides direct insight into specific pathways, with the option of both time-course and steady state analysis increasing the potential value of the approach. The scope of the NMR method, and its contribution to studies of plant nitrogen metabolism, are illustrated with a wide range of examples. These include studies of the GS/GOGAT pathway of ammonium assimilation, investigations of the metabolism of glutamate, glycine and other amino acids, and applications to tropane alkaloid metabolism. The continuing development of the NMR technique, together with potential applications in the emerging fields of metabolomics and metabolic flux analysis, leads to the conclusion that NMR will play an increasingly valuable role in the analysis of plant nitrogen metabolism.

Carbon Isotopes↗
PubMed2003

Dynamic generation and qualitative analysis of metabolic pathways by a joint database/graph theoretical approach.

The dynamic generation and qualitative analysis of metabolic networks relying on continuously growing qualified metabolic data by a joint database/graph theoretical approach is described. The procedure is applied to analyze the connectivity of a metabolic network after enzyme removal and to subsequently perform shortest path analyses. The focus lies on the analysis of the connectivity of the metabolic network depending on model assumptions. Here we analyze the influence of the number of strongly connected components on the assignment of reversibility or irreversibility of the biochemical reactions.

Algorithms↗
PubMed2006

Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis.

BACKGROUND: Elementary mode analysis of metabolic pathways has proven to be a valuable tool for assessing the properties and functions of biochemical systems. However, little comprehension of how individual elementary modes are used in real cellular states has been achieved so far. A quantitative measure of fluxes carried by individual elementary modes is of great help to identify dominant metabolic processes, and to understand how these processes are redistributed in biological cells in response to changes in environmental conditions, enzyme kinetics, or chemical concentrations. RESULTS: Selecting a valid decomposition of a flux distribution onto a set of elementary modes is not straightforward, since there is usually an infinite number of possible such decompositions. We first show that two recently introduced decompositions are very closely related and assign the same fluxes to reversible elementary modes. Then, we show how such decompositions can be used in combination with kinetic modelling to assess the effects of changes in enzyme kinetics on the usage of individual metabolic routes, and to analyse the range of attainable states in a metabolic system. This approach is illustrated by the example of yeast glycolysis. Our results indicate that only a small subset of the space of stoichiometrically feasible steady states is actually reached by the glycolysis system, even when large variation intervals are allowed for all kinetic parameters of the model. Among eight possible elementary modes, the standard glycolytic route remains dominant in all cases, and only one other elementary mode is able to gain significant flux values in steady state. CONCLUSION: These results indicate that a combination of structural and kinetic modelling significantly constrains the range of possible behaviours of a metabolic system. All elementary modes are not equal contributors to physiological cellular states, and this approach may open a direction toward a broader identification of physiologically relevant elementary modes among the very large number of stoichiometrically possible modes.

Algorithms↗