FluxAnalyzer: exploring structure,pathways, and flux distributions in metabolic networks on interactive flux maps

MOTIVATION: The analysis of structure, pathways and flux distributions in metabolic networks has become an important approach for understanding the functionality of metabolic systems. The need of a user-friendly platform for stoichiometric modeling of metabolic networks in silico is evident. RESULTS: The FluxAnalyzer is a package for MATLAB and facilitates integrated pathway and flux analysis for metabolic networks within a graphical user interface. Arbitrary metabolic network models can be composed by instances of four types of network elements. The abstract network model is linked with network graphics leading to interactive flux maps which allow for user input and display of calculation results within a network visualization. Therein, a large and powerful collection of tools and algorithms can be applied interactively including metabolic flux analysis, flux optimization, detection of topological features and pathway analysis by elementary flux modes or extreme pathways. The FluxAnalyzer has been applied and tested for complex networks with more than 500,000 elementary modes. Some aspects of the combinatorial complexity of pathway analysis in metabolic networks are discussed. AVAILABILITY: Upon request from the corresponding author. Free for academic users (license agreement). Special contracts are available for industrial corporations. SUPPLEMENTARY INFORMATION: http://www.mpi-magdeburg.mpg.de/projects/fluxanalyzer.     

Manipulating flux through plant metabolic pathways

The past two years have seen a marked increase in patent applications for novel methods of altering the level and spectrum of commercially important products in plants. Results from these studies have proven surprising, showing that in many cases those enzymes traditionally thought of as flux-controlling have no impact on product formation when they are directly altered by genetic manipulation. In many cases, successful induction of increased flux throughout an entire pathway has been achieved by targeting one of the terminal enzymes in the pathway.     

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.     

Competition for enzymes in metabolic pathways: implications for optimal distributions of enzyme concentrations and for the distribution of flux control

The structures of biochemical pathways are assumed to be determined by evolutionary optimization processes. In the framework of mathematical models, these structures should be explained by the formulation of optimization principles. In the present work, the principle of minimal total enzyme concentration at fixed steady state fluxes is applied to metabolic networks. According to this principle there exists a competition of the reactions for the available amount of enzymes such that all biological functions are maintained. In states which fulfil these optimization criteria the enzyme concentrations are distributed in a non-uniform manner among the reactions. This result has consequences for the distribution of flux control. It is shown that the flux control matrix c, the elasticity matrix epsilon, and the vector e of enzyme concentrations fulfil in optimal states the relations c(T)e = e and epsilon(T)e = 0. Starting from a well-balanced distribution of enzymes the minimization of total enzyme concentration leads to a lowering of the SD of the flux control coefficients.     

Effects of metabolic flux on stress response pathways in Lactococcus lactis

Studies of cellular responses to stress conditions such as heat, oxygen or starvation have revealed the existence of numerous specific or interactive response pathways. We previously observed in Lactococcus lactis that inactivation of the recA gene renders the lactococcal strain sensitive not only to DNA-damaging agents but also to oxygen and heat. To further examine the stress response pathways in L. lactis, we isolated thermoresistant insertional mutants (Trm) of the recA strain. Eighteen independent trm mutations were identified and characterized. We found that mutations map in only seven genes, implicated in purine metabolism (deoB, guaA and tktA), phosphate uptake (pstB and pstS), mRNA stability (pnpA) and in one uncharacterized gene (trmA). All the trm mutations, with the exception of trmA, confer multiple stress resistance to the cell. Some of the mutations confer improved heat stress resistance not only in the recA but also in the wild-type context. Our results reveal that cellular metabolic pathways are intimately related to stress response and that the flux of particular metabolites, notably guanine and phosphate, may be implicated in stress response in lactococci.     

An algorithm for efficient identification of branched metabolic pathways

This article presents a new graph-based algorithm for identifying branched metabolic pathways in multi-genome scale metabolic data. The term branched is used to refer to metabolic pathways between compounds that consist of multiple pathways that interact biochemically. A branched pathway may produce a target compound through a combination of linear pathways that split compounds into smaller ones, work in parallel with many compounds, and join compounds into larger ones. While branched metabolic pathways predominate in metabolic networks, most previous work has focused on identifying linear metabolic pathways. The ability to automatically identify branched pathways is important in applications that require a deeper understanding of metabolism, such as metabolic engineering and drug target identification. The algorithm presented in this article utilizes explicit atom tracking to identify linear metabolic pathways and then merges them together into branched metabolic pathways. We provide results on several well-characterized metabolic pathways that demonstrate that the new merging approach can efficiently find biologically relevant branched metabolic pathways.     

The role of multiple enzyme activation in metabolic flux control

Over recent years, the concept that flux through a metabolic pathway is controlled by a single rate-limiting enzyme has been challenged from a number of quarters. We have presented three lines of evidence that the control of pathway flux by activation of multiple several steps, including steps responsible for consumption of pathway products, is an important feature of physiological flux control in response to external stimmuli. Theoretical tools exist that can be used to analyze the distribution of flux control between the steps involved in signal transduction and enzyme activation.     

Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks

Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al. have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a given metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.     

Comparison of metabolic flux distributions for MDCK cell growth in glutamine- and pyruvate-containing media

In mammalian cell cultures, ammonia that is released into the medium as a result of glutamine metabolism and lactate that is excreted due to incomplete glucose oxidation are both known to essentially inhibit the growth of cells. For some cell lines, for example, hybridoma cells, excreted ammonia also has an effect on product formation. Although glutamine has been generally considered as the major energy source for mammalian cells, it was recently found that various adherent cell lines (MDCK, CHO-K1, and BHK21) can grow as well in glutamine-free medium, provided glutamine is substituted with pyruvate. In such a medium the level of both ammonia and lactate released was significantly reduced. In this study, metabolic flux analysis (MFA) was applied to Madin Darby Canine Kidney (MDCK) cells cultivated in glutamine-containing and glutamine-free medium. The results of the MFA allowed further investigation of the influence of glutamine substitution with pyruvate on the metabolism of MDCK cells during different growth stages of adherent cells, e.g., early exponential and late contact-inhibited phase. Pyruvate seemed to directly enter the TCA cycle, whereas most of the glucose consumed was excreted as lactate. Although the exact mechanisms are not clear so far, this resulted in a reduction of the glucose uptake necessary for cellular metabolism in glutamine-free medium. Furthermore, consumption of ATP by futile cycles seemed to be significantly reduced when substituting glutamine with pyruvate. These findings imply that glutamine-free medium favors a more efficient use of nutrients by cells. However, a number of metabolic fluxes were similar in the two cultivations considered, e.g., most of the amino acid uptake and degradation rates or fluxes through the branch of the TCA cycle converting alpha-ketoglutarate to malate, which is responsible for the mitochondrial ATP synthesis. Besides, the specific rate of cell growth was approximately the same in both cultivations. Thus, the switch from glutamine-containing to glutamine-free medium with pyruvate provided a series of benefits without dramatic changes of cellular metabolism.     

Application of metabolic flux analysis for the identification of metabolic bottlenecks in the biosynthesis of penicillin-G

A detailed stoichiometric model was developed for growth and penicillin-G production in Penicillium chrysogenum. From an a priori metabolic flux analysis using this model it appeared that penicillin production requires significant changes in fluxes through the primary metabolic pathways. This is brought about by the biosynthesis of carbon precursors for the beta-lactan nucleus and an increased demand for NADPH, mainly for sulfate reduction. As a result, significant changes in flux partitioning occur around four principal nodes in primary metabolism. These are located at: (1) glucose-6-phosphate; (2) 3-phosphoglycerate; (3) mitochondrial pyruvate; and (4) mitochondrial isocitrate. These nodes should be regarded as potential bottlenecks for increased productivity. The flexibility of these principal nodes was investigated by experimental manipulation of the fluxes through the central metabolic pathways using a high-producing strain of P. chrysogenum. Metabolic fluxes were manipulated through growth of the cells on different substrates in carbon-limited chemostat culture. Metabolic flux analysis, based on measured input and output fluxes, was used to calculate the fluxes around the principal nodes. It was found that, for growth on glucose, ethanol, and acetate, the flux partitioning around these nodes differed significantly. However, this had hardly any effect on penicillin productivity, showing that primary carbon metabolism is not likely to contain potential bottlenecks. Further experiments were performed to manipulate the total metabolic demand for the cofactor nicotinamide adenine dinucleotide phosphate (NADPH). NADPH demand was increased stepwise by cultivating the cells on glucose or xylose as the carbon source combined with either ammonia or nitrate as the nitrogen source, which resulted in a stepwise decrease of penicillin production. This clearly shows that, in penicillin fermentation, possible limitations in primary metabolism reside in the supply/regeneration of cofactors (NADPH) rather than in the supply of carbon precursors.     

Iterative computation of metabolic flux and stoichiometric parameters for alternate pathways in rumen fermentation.

A model is presented which has been derived to compute the end-products of rumen fermentation from knowledge of the input of feedstuff. The model comprises a set of algebraic equations for the fermentation of each of the following feedstuff components: soluble sugars, starch, cellulose, hemicellulose and protein. The equations were derived from known biochemical stoichiometric relationships. A iterative, non-linear least sqares method (steepest descent) was used to estimate parameter values. In a sample run the inputs used were from an experiment where eight sheep were fed white clover. The model predicted values were in good agreement with the experimental values.     

Oxygen-enriched fermentation of sodium gluconate by Aspergillus niger and its impact on intracellular metabolic flux distributions

Bioprocess and Biosystems Engineering - Different concentrations of oxygen-enriched air were utilized for sodium gluconate (SG) fermentation by Aspergillus niger. The fermentation time shortened...