scholarly journals Quantitative analysis of metabolic networks and design of minimal bioreaction models

2008 ◽  
Vol Volume 9, 2007 Conference in... ◽  
Author(s):  
Georges Bastin
Keyword(s):  
Quantitative Analysis ◽  
Metabolic Networks ◽  
Metabolic Flux ◽  
Flux Distribution ◽  
Cell Metabolism ◽  
Flux Analysis ◽  
Minimal Models ◽  
Elementary Modes ◽  
International Audience

International audience This tutorial paper is concerned with the design of macroscopic bioreaction models on the basis a quantitative analysis of the underlying cell metabolism. The paper starts with a review of two fundamental algebraic techniques for the quantitative analysis of metabolic networks : (i) the decomposition of complex metabolic networks into elementary pathways (or elementary modes), (ii) the metabolic flux analysis which aims at computing the entire intracellular flux distribution from a limited number of flux meaurements. Then it is discussed how these two fundamental techniques can be exploited to design minimal bioreaction models by using a systematic model reduction approach that automatically produces a family of equivalent minimal models which are fully compatible with the underlying metabolism and consistent with the available experimental data. The theory is illustrated with an experimental case-study on CHO cells. Cet article tutoriel traite de la conception de modèles de bioréactions macroscopiques sur la base d’une analyse quantitative du métabolisme cellulaire sous-jacent. L’article commence par un rappel de deux techniques algébriques fondamentales pour l’analyse quantitative des réseaux métaboliques : (i) la décomposition des réseaux métaboliques complexes en chemins élémentaires (ou modes élémentaires), (ii) l’analyse des flux métaboliques qui vise à calculer la totalité des flux métaboliques intracellulaires à partir d’un ensemble limité de mesures. On montre ensuite comment ces deux techniques peuvent être exploitées pour concevoir des modèles minimaux de bioréactions en utilisant une approche systématique de réduction de modèle qui produit automatiquement une famille de modèles minimaux équivalents compatibles non seulement avec les données expérimentales mais aussi avec le métabolisme sous-jacent. La théorie est illustrée avec une étude de cas expérimentale sur des cellules CHO.

scholarly journals Metabolic Flux Analysis of VERO Cells under Various Culture Conditions

Processes ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 2097
Author(s):  
Georges Bastin ◽  
Véronique Chotteau ◽  
Alain Vande Wouwer
Keyword(s):  
Cell Growth ◽  
Metabolic Networks ◽  
Metabolic Flux ◽  
Flux Distribution ◽  
Cell Metabolism ◽  
Lactate Concentration ◽  
Vero Cells ◽  
Culture Conditions ◽  
Exponential Growth Phase ◽  
Flux Analysis

Although the culture of VERO cells in bioreactors is an important industrial bioprocess for the production of viruses and vaccines, surprisingly few reports on the analysis of the flux distribution in the cell metabolism have been published. In this study, an attempt is made to fill this gap by providing an analysis of relatively simple metabolic networks, which are constructed to describe the cell behavior in different culture conditions, e.g., the exponential growth phase (availability of glucose and glutamine), cell growth without glutamine, and cell growth without glucose and glutamine. The metabolic networks are kept as simple as possible in order to avoid underdeterminacy linked to the lack of extracellular measurements, and a unique flux distribution is computed in each case based on a mild assumption that the macromolecular composition of the cell is known. The result of this computation provides some insight into the metabolic changes triggered by the culture conditions, which could support the design of feedback control strategies in fed batch or perfusion bioreactors where the lactate concentration is measured online and regulated by controlling the delivery rates of glucose and, possibly, of some essential amino acids.

Measuring non-steady-state metabolic fluxes in starch-converting faecal microbiota in vitro

2010 ◽  
Vol 1 (4) ◽  
pp. 391-405 ◽  
Author(s):  
T. Binsl ◽  
A. De Graaf ◽  
K. Venema ◽  
J. Heringa ◽  
A. Maathuis ◽  
...  
Keyword(s):  
Steady State ◽  
Metabolic Flux ◽  
Flux Distribution ◽  
Computational Modelling ◽  
Total Carbon ◽  
Flux Analysis ◽  
Small Contribution ◽  
Faecal Microbiota ◽  
Isotope Labelling

This paper explores human gut bacterial metabolism of starch using a combined analytical and computational modelling approach for metabolite and flux analysis. Non-steady-state isotopic labelling experiments were performed with human faecal microbiota in a well-established in vitro model of the human colon. After culture stabilisation, [U-13C] starch was added and samples were taken at regular intervals. Metabolite concentrations and 13C isotopomeric distributions were measured amongst other things for acetate, propionate and butyrate by mass spectrometry and NMR. The vast majority of metabolic flux analysis methods based on isotopomer analysis published to date are not applicable to metabolic non-steady-state experiments. We therefore developed a new ordinary differential equation-based representation of a metabolic model of human faecal microbiota to determine eleven metabolic parameters that characterised the metabolic flux distribution in the isotope labelling experiment. The feasibility of the model parameter quantification was demonstrated on noisy in silico data using a downhill simplex optimisation, matching simulated labelling patterns of isotopically labelled metabolites with measured metabolite and isotope labelling data. Using the experimental data, we determined an increasing net label influx from starch during the experiment from 94±1 µmol/l/min to 133±3 µmol/l/min. Only about 12% of the total carbon flux from starch reached propionate. Propionate production mainly proceeded via succinate with a small contribution via acrylate. The remaining flux from starch yielded acetate (35%) and butyrate (53%). Interpretation of 13C NMR multiplet signals further revealed that butyrate, valerate and caproate were mainly synthesised via cross-feeding, using acetate as a co-substrate. This study demonstrates for the first time that the experimental design and the analysis of the results by computational modelling allows the determination of time-resolved effects of nutrition on the flux distribution within human faecal microbiota in metabolic non-steady-state.

Metabolic flux analysis of CHO cell metabolism in the late non-growth phase

2010 ◽  
Vol 108 (1) ◽  
pp. 82-92 ◽  
Author(s):  
Neelanjan Sengupta ◽  
Steven T. Rose ◽  
John A. Morgan
Keyword(s):  
Growth Phase ◽  
Metabolic Flux Analysis ◽  
Metabolic Flux ◽  
Cell Metabolism ◽  
Flux Analysis ◽  
Cho Cell

scholarly journals iMTBGO: An Algorithm for Integrating Metabolic Networks with Transcriptomes Based on Gene Ontology Analysis

2019 ◽  
Vol 20 (4) ◽  
pp. 252-259
Author(s):  
Zhitao Mao ◽  
Hongwu Ma
Keyword(s):  
Gene Expression ◽  
Metabolic Networks ◽  
Metabolic Flux ◽  
Network Models ◽  
Reaction Rates ◽  
Marker Genes ◽  
Published Data ◽  
Flux Analysis ◽  
Prediction Errors ◽  
Balance Analysis

Background:Constraint-based metabolic network models have been widely used in phenotypic prediction and metabolic engineering design. In recent years, researchers have attempted to improve prediction accuracy by integrating regulatory information and multiple types of “omics” data into this constraint-based model. The transcriptome is the most commonly used data type in integration, and a large number of FBA (flux balance analysis)-based integrated algorithms have been developed.Methods and Results:We mapped the Kcat values to the tree structure of GO terms and found that the Kcat values under the same GO term have a higher similarity. Based on this observation, we developed a new method, called iMTBGO, to predict metabolic flux distributions by constraining reaction boundaries based on gene expression ratios normalized by marker genes under the same GO term. We applied this method to previously published data and compared the prediction results with other metabolic flux analysis methods which also utilize gene expression data. The prediction errors of iMTBGO for both growth rates and fluxes in the central metabolic pathways were smaller than those of earlier published methods.Conclusion:Considering the fact that reaction rates are not only determined by genes/expression levels, but also by the specific activities of enzymes, the iMTBGO method allows us to make more precise predictions of metabolic fluxes by using expression values normalized based on GO.

scholarly journals Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases

Metabolites ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 368
Author(s):  
Huan Jin ◽  
Joshua M. Mitchell ◽  
Hunter N. B. Moseley
Keyword(s):  
Metabolic Network ◽  
Graph Coloring ◽  
Metabolic Networks ◽  
Metabolic Flux ◽  
Enzyme Commission ◽  
Metabolic Model ◽  
Metabolic Reprogramming ◽  
Automatic Identification ◽  
Flux Analysis ◽  
Database Curation

Metabolic flux analysis requires both a reliable metabolic model and reliable metabolic profiles in characterizing metabolic reprogramming. Advances in analytic methodologies enable production of high-quality metabolomics datasets capturing isotopic flux. However, useful metabolic models can be difficult to derive due to the lack of relatively complete atom-resolved metabolic networks for a variety of organisms, including human. Here, we developed a neighborhood-specific graph coloring method that creates unique identifiers for each atom in a compound facilitating construction of an atom-resolved metabolic network. What is more, this method is guaranteed to generate the same identifier for symmetric atoms, enabling automatic identification of possible additional mappings caused by molecular symmetry. Furthermore, a compound coloring identifier derived from the corresponding atom coloring identifiers can be used for compound harmonization across various metabolic network databases, which is an essential first step in network integration. With the compound coloring identifiers, 8865 correspondences between KEGG (Kyoto Encyclopedia of Genes and Genomes) and MetaCyc compounds are detected, with 5451 of them confirmed by other identifiers provided by the two databases. In addition, we found that the Enzyme Commission numbers (EC) of reactions can be used to validate possible correspondence pairs, with 1848 unconfirmed pairs validated by commonality in reaction ECs. Moreover, we were able to detect various issues and errors with compound representation in KEGG and MetaCyc databases by compound coloring identifiers, demonstrating the usefulness of this methodology for database curation.

Metabolic flux analysis of simultaneous production of vitamin B12 and propionic acid in a coupled fermentation process by Propionibacterium freudenreichii

2021 ◽  
Author(s):  
Yuhan Zhang ◽  
Xiaolian Li ◽  
Ziqiang Wang ◽  
Yunshan Wang ◽  
Yuanyuan Ma ◽  
...  
Keyword(s):  
Propionic Acid ◽  
Fermentation Process ◽  
Metabolic Flux ◽  
Flux Distribution ◽  
Vitamin B ◽  
Flux Analysis ◽  
Propionibacterium Freudenreichii ◽  
Simultaneous Production ◽  
Metabolic Flux Distribution ◽  
New Strategy

Abstract The metabolic processes involved in simultaneous production of vitamin B12 and propionic acid by Propionibacterium freudenreichii are very complicated. To further investigate the regulatory mechanisms of this metabolism, a simplified metabolic network was established. The effects of glucose feeding, propionic acid removal, and 5,6-dimethylbenzimidazole (DMB) addition on the metabolic flux distribution were investigated. The results showed that synthesis of propionic acid can be increased by increasing the metabolic flux through the oxaloacetate and methylmalonyl-CoA branches in the early and middle stages of the coupled fermentation. After DMB addition, the synthesis of vitamin B12 was significantly enhanced via increased metabolic flux through the δ-aminolevulinate branch, which promoted the synthesis of uroporphyrinogen III, a precursor of vitamin B12. Therefore, the analysis of metabolic flux at key nodes can provide theoretical guidance for the optimization of P. freudenreichii fermentation processes. In an experimental coupled fermentation process, the concentrations of vitamin B12 and propionic acid reached 21.6 and 50.12 g/L respectively, increased by 105.71% and 73.91% compared with batch fermentation, which provides a new strategy for industrial production.

scholarly journals Osmotic Stress Response: Quantification of Cell Maintenance and Metabolic Fluxes in a Lysine-Overproducing Strain of Corynebacterium glutamicum

2004 ◽  
Vol 70 (7) ◽  
pp. 4222-4229 ◽  
Author(s):  
Cristian A. Varela ◽  
Mauricio E. Baez ◽  
Eduardo Agosin
Keyword(s):  
Osmotic Stress ◽  
Corynebacterium Glutamicum ◽  
Metabolic Flux ◽  
Cell Metabolism ◽  
Compatible Solutes ◽  
Flux Analysis ◽  
High Dilution ◽  
Metabolic Fluxes ◽  
Cell Productivity ◽  
Osmotic Stress Response

ABSTRACT Osmotic stress diminishes cell productivity and may cause cell inactivation in industrial fermentations. The quantification of metabolic changes under such conditions is fundamental for understanding and describing microbial behavior during bioprocesses. We quantified the gradual changes that take place when a lysine-overproducing strain of Corynebacterium glutamicum is grown in continuous culture with saline gradients at different dilution rates. The use of compatible solutes depended on environmental conditions; certain osmolites predominated at different dilution rates and extracellular osmolalities. A metabolic flux analysis showed that at high dilution rates C. glutamicum redistributed its metabolic fluxes, favoring energy formation over growth. At low dilution rates, cell metabolism accelerated as the osmolality was steadily increased. Flexibility in the oxaloacetate node proved to be key for the energetic redistribution that occurred when cells were grown at high dilution rates. Substrate and ATP maintenance coefficients increased 30- and 5-fold, respectively, when the osmolality increased, which demonstrates that energy pool management is fundamental for sustaining viability.

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