An improved algorithm for stoichiometric network analysis: theory and applications

Urbanczik, Robert; Wagner, Clemens

doi:10.1093/bioinformatics/bti127

Cited by 109 publications

(86 citation statements)

References 11 publications

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“…Owing to a combinatorial explosion of the number of elementary vectors, this approach becomes computationally intractable for genome scale networks. To develop an analysis approach computationally feasible even for genome scale networks, Urbanczik & Wagner (2005) proposed to focus on conversion cone, the projection of the flux cone, which describes the interaction of the metabolism with its external chemical environment. The method for calculating the elementary vectors of this cone was applied to study the metabolism of Saccharomyces cerevisiae.…”

Section: Computational Methods For Metabolic Pathway Analysis Using Mmentioning

confidence: 99%

Computational Methods to Interpret and Integrate Metabolomic Data

Li¹,

Wang²,

Zhang³

2012

Metabolomics

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Section: Computational Methods For Metabolic Pathway Analysis Using Mmentioning

confidence: 99%

Computational Methods to Interpret and Integrate Metabolomic Data

Li¹,

Wang²,

Zhang³

2012

Metabolomics

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“…These procedures are not repeated here because an exhaustive description already exists. Suffice it to mention that sodium [2][3][4][5][6][7][8][9][10][11][12][13][14] C] pyruvate was used as a substrate, and allowed measurement of the pertinent metabolic flows in incubated mitochondria from rat liver. The model investigated was somewhat simplified by omitting activation of the pyruvate carboxylase by acetyl-CoA and its inhibition by ADP in order to get an idea of the general properties of the unconstrained free-flow system and compare it with incubated mitochondria.…”

Section: Experimental Data and Computational Proceduresmentioning

confidence: 99%

“…Only when all reactions are irreversible, are the elementary flux modes identical to the extremal currents, otherwise they are a projection from the extremal current polytope into a polytope with a lower dimension. Because a proper transformation operator exists [13], one can switch from one representation to the other without losing information.…”

Section: Experimental Data and Computational Proceduresmentioning

confidence: 99%

Pyruvate metabolism in rat liver mitochondria

Stucki

Urbanczik

2005

The FEBS Journal

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Mitochondria are generally regarded as the powerhouse of the cell having the main task of supplying energy in the form of ATP produced during oxidative phosphorylation from ADP and P i . Furthermore, it is well known that mitochondria take up Ca 2+ ions in an energy-dependent manner. Other important reactions are the Krebs cycle, oxidation of fatty acids and the urea cycle [1,2]. One may ask, which of these reactions are optimized and play the most important role? There are probably no dominant tasks in liver mitochondria and we are therefore faced with multiple optimizations, depending on the cellular demands.Mitochondria from liver and kidney contain pyruvate carboxylase and are actively involved in gluconeogenesis [3]. The aim of this study was to discover the importance of this first step in gluconeogenenesis, and special conditions were therefore chosen to allow us to study the carboxylation of pyruvate, the Krebs cycle and ketone body production by ignoring the many other reactions also present in these organelles. In this sense, the model and experiments of mitochondrial pyruvate metabolism are biased and do not consider the typical intracellular environment of hepatocytes.Genomics has led to construction of the stoichiometry matrices of several simple organisms such as Escherichia coli and Saccharomyces cerevisiae. Applying linear programming methods, researchers have analysed the optimizations of different goals, the most prominent being the maximization of cellular growth [4][5][6][7]. It goes without saying that this cannot be the major task of liver mitochondria. Therefore, we investigated the optimization of metabolic functions. In A representative model of mitochondrial pyruvate metabolism was broken down into its extremal independent currents and compared with experimental data obtained from liver mitochondria incubated with pyruvate as a substrate but in the absence of added adenosine diphosphate. Assuming no regulation of enzymatic activities, the free-flow prediction for the output of the model shows large discrepancies with the experimental data. To study the objective of the incubated mitochondria, we calculate the conversion cone of the model, which describes the possible input ⁄ output behaviour of the network. We demonstrate the consistency of the experimental data with the model because all measured data are within this cone. Because they are close to the boundary of the cone, we deduce that pyruvate is converted very efficiently (93%) to produce the measured extramitochondrial metabolites. We find that the main function of the incubated mitochondria is the production of malate and citrate, supporting the anaplerotic pathways in the cytosol, notably gluconeogenesis and fatty acid synthesis. Finally, we show that the major flow through the enzymatic steps of the mitochondrial pyruvate metabolism can be reliably predicted based on the stoichiometric model plus the measured extramitochondrial products. A major advantage of this method is that neither kinetic simulations nor radioactive trace...

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“…Algorithms have been developed to enumerate all the EFMs in medium-size metabolic networks [8][9][10]. However, despite the development of novel methods using state of the art computational techniques expediting their application in larger networks [11], this family of algorithms fails on GSMNs using standard computers, because of the combinatorial explosion in the number of EFMs [4].…”

Section: Introductionmentioning

confidence: 99%

A new approach to obtaining EFMs using graph methods based on the shortest path between end nodes

Hidalgo¹,

Guil²,

García³

2016

Genomics Comput Biol

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Genome-scale metabolic networks let us understand the behaviour of the metabolism in the cells of living organisms. The availability of great amounts of such data gives the scientific community the opportunity to infer in silico new metabolic knowledge. Elementary Flux Modes (EFM) are minimal contained pathways or subsets of a metabolic network that are very useful to achieving the comprehension of a very specific metabolic function (as well as dysfunctions), and to get the knowledge to develop new drugs. Metabolic networks can have large connectivity and, therefore, EFMs resolution faces a combinational explosion challenge to be solved. In this paper we propose a new approach to obtain EFMs based on graph theory, the balanced graph concept and the shortest path between end nodes.Our proposal uses the shortest path between end nodes (input and output nodes) that finds all the pathways in the metabolic network and is able to prioritise the pathway search accounting the biological mean pursued. Our technique has two phases, the exploration phase and the characterisation one, and we show how it works in a well-known case study. We also demonstrate the relevance of the concept of balanced graph to achieve to the full list of EFMs.

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An improved algorithm for stoichiometric network analysis: theory and applications

Cited by 109 publications

References 11 publications

Computational Methods to Interpret and Integrate Metabolomic Data

Computational Methods to Interpret and Integrate Metabolomic Data

Pyruvate metabolism in rat liver mitochondria

A new approach to obtaining EFMs using graph methods based on the shortest path between end nodes

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