Oscillations in plant membrane transport: model predictions, experimental validation, and physiological implications

Although oscillations in membrane-transport activity are ubiquitous in plants, the ionic mechanisms of ultradian oscillations in plant cells remain largely unknown, despite much phenomenological data. The physiological role of such oscillations is also the subject of much speculation. Over the last decade, much experimental evidence showing oscillations in net ion fluxes across the plasma membrane of plant cells has been accumulated using the non-invasive MIFE technique. In this study, a recently proposed feedback-controlled oscillatory model was used. The model adequately describes the observed ion flux oscillations within the minute range of periods and predicts: (i) strong dependence of the period of oscillations on the rate constants for the H+ pump; (ii) a substantial phase shift between oscillations in net H+ and K+ fluxes; (iii) cessation of oscillations when H+ pump activity is suppressed; (iv) the existence of some 'window' of external temperatures and ionic concentrations, where non-damped oscillations are observed: outside this range, even small changes in external parameters lead to progressive damping and aperiodic behaviour; (v) frequency encoding of environmental information by oscillatory patterns; and (vi) strong dependence of oscillatory characteristics on cell size. All these predictions were successfully confirmed by direct experimental observations, when net ion fluxes were measured from root and leaf tissues of various plant species, or from single cells. Because oscillatory behaviour is inherent in feedback control systems having phase shifts, it is argued from this model that suitable conditions will allow oscillations in any cell or tissue. The possible physiological role of such oscillations is discussed in the context of plant adaptive responses to salinity, temperature, osmotic, hypoxia, and pH stresses.     

Metabolic flux distributions in Penicillium chrysogenum during fed-batch cultivations

Based on a review of the Penicillium chrysogenum biochemistry a stoichiometric model has been set up. The model considers 61 internal fluxes and there are 49 intracellular metabolites which are assumed to be in pseudo-steady state. In addition to the intracellular fluxes the model considers the uptake of 21 amino acids. From the stoichiometric model the maximum theoretical yield of penicillin V is calculated to 0.43 mol/mol glucose. If biosynthesis of cysteine is by direct sulfhydrylation rather than by transsulfuration, the maximum theoretical yield is about 20% higher, i.e., 0.50 mol/mol glucose. The theoretical yield decreases substantially if alpha-aminoadipate is converted to 6-oxo-piperidine-2-carboxylic acid (OPC). If only 40% of the alpha-aminoadipate is recycled, the maximum theoretical yield is 0.31 mol/mol glucose. The uptake rates of glucose, lactate, gamma-aminobutyrate, and 21 amino acids were measured during fed-batch cultivations. The rates of formation of penicillin V, delta-(L-alpha)-aminoadipyl-L-cysteinyl-D-valine (ACV), OPC, and the pool of isopenicillin N, 6-APA, and 8-HPA were also measured. Finally the synthesis rates of the biomass constituents RNA/DNA, protein, lipid, carbohydrate, and amino carbohydrate were measured. From these measured rates and the stoichiometric model the metabolic fluxes through the different intracellular pathways are calculated. The calculations show that penicillin formation is accompanied by a large flux through the pentose phosphate (PP) pathway due to a large requirement for nicotinamide-adenine dinucleotide phosphate (NADPH) used in the biosynthesis of cysteine. If cysteine is added to the medium, the flux through the PP pathway decreases. From the stoichiometric model Y(xATP) is calculated to 87 mmol adenosine triphosphate (ATP)/g dry weight (DW), and from the flux calculations m(ATP) is found to 3 mmol ATP/g DW/h. (c) 1995 John Wiley & Sons, Inc.     

Computational predictions and experimental affinity distributions for a homovanillic acid molecularly imprinted polymer

Density Functional Theory calculations have been used to select, among a set of chemicals traditionally used in the formulation of non-covalent molecularly imprinted polymers (MIPs), the best functional monomer and porogenic solvent for the construction of a recognition element for the dopamine metabolite homovanillic acid (HVA). Theoretical predictions were confirmed through batch binding assays and voltammetric detection. The computational method predicts that trifluoromethacrylic acid and toluene are the monomer and solvent rendering the highest stabilization energy for the pre-polymerization adducts. HVA-MIP prepared using this formulation gives rise to a binding isotherm that is accurately modelled by the Freundlich isotherm. The binding properties of this polymer were estimated using affinity distribution analysis. An apparent number of sites of 13 micromol g(-1) with an average affinity constant of 2 x 10(4) M(-1) was obtained in the concentration window studied.     

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.     

Metabolic network properties help assign weights to elementary modes to understand physiological flux distributions

MOTIVATION: Elementary modes (EMs) analysis has been well established. The existing methodologies for assigning weights to EMs cannot be directly applied for large-scale metabolic networks, since the tremendous number of modes would make the computation a time-consuming or even an impossible mission. Therefore, developing more efficient methods to deal with large set of EMs is urgent. RESULT: We develop a method to evaluate the performance of employing a subset of the elementary modes to reconstruct a real flux distribution by using the relative error between the real flux vector and the reconstructed one as an indicator. We have found a power function relationship between the decrease of relative error and the increase of the number of the selecting EMs, and a logarithmic relationship between the increases of the number of non-zero weighted EMs and that of the number of the selecting EMs. Our discoveries show that it is possible to reconstruct a given flux distribution by a selected subset of EMs from a large metabolic network and furthermore, they help us identify the 'governing modes' to represent the cellular metabolism for such a condition.     

Metabolic flux analysis and visualization

One of the ultimate goals of systems biology research is to obtain a comprehensive understanding of the control mechanisms of complex cellular metabolisms. Metabolic Flux Analysis (MFA) is a important method for the quantitative estimation of intracellular metabolic flows through metabolic pathways and the elucidation of cellular physiology. The primary challenge in the use of MFA is that many biological networks are underdetermined systems; it is therefore difficult to narrow down the solution space from the stoichiometric constraints alone. In this tutorial, we present an overview of Flux Balance Analysis (FBA) and (13)C-Metabolic Flux Analysis ((13)C-MFA), both of which are frequently used to solve such underdetermined systems, and we demonstrate FBA and (13)C-MFA using the genome-scale model and the central carbon metabolism model, respectively. Furthermore, because such comprehensive study of intracellular fluxes is inherently complex, we subsequently introduce various pathway mapping and visualization tools to facilitate understanding of these data in the context of the pathways. Specific visualization of MFA results using the BioCyc Omics Viewer and Pathway Projector are shown as illustrative examples.     

GENEVIEW and the DNACE data bus: computational tools for analysis, display and exchange of genetic information.

We describe an interactive computational tool, GENEVIEW, that allows the scientist to retrieve, analyze, display and exchange genetic information. The scientist may request a display of information from a GenBank locus, request that a restriction map be computed, stored and superimposed on GenBank information, and interactively view this information. GENEVIEW provides an interface between the GenBank data base and the programs of the Lilly DNA Computing Environment (DNACE). This interface stores genetic information in a simple, free format that has become the universal convention of DNACE; this format will serve as the convention for all future software development at Eli Lilly and Company, and could serve as a convention for genetic information exchange.     

Verification, validation and sensitivity studies in computational biomechanics

Computational techniques and software for the analysis of problems in mechanics have naturally moved from their origins in the traditional engineering disciplines to the study of cell, tissue and organ biomechanics. Increasingly complex models have been developed to describe and predict the mechanical behavior of such biological systems. While the availability of advanced computational tools has led to exciting research advances in the field, the utility of these models is often the subject of criticism due to inadequate model verification and validation (V&V). The objective of this review is to present the concepts of verification, validation and sensitivity studies with regard to the construction, analysis and interpretation of models in computational biomechanics. Specific examples from the field are discussed. It is hoped that this review will serve as a guide to the use of V&V principles in the field of computational biomechanics, thereby improving the peer acceptance of studies that use computational modeling techniques.     

Metabolic pathway analysis of Scheffersomyces (Pichia) stipitis: effect of oxygen availability on ethanol synthesis and flux distributions

Elementary mode analysis (EMA) identifies all possible metabolic states of the cell metabolic network. Investigation of these states can provide a detailed insight into the underlying metabolism in the cell. In this study, the flux states of Scheffersomyces (Pichia) stipitis metabolism were examined. It was shown that increasing oxygen levels led to a decrease of ethanol synthesis. This trend was confirmed by experimental evaluation of S. stipitis in glucose-xylose fermentation. The oxygen transfer rate for an optimal ethanol production was 1.8 mmol/l/h, which gave the ethanol yield of 0.40 g/g and the ethanol productivity of 0.25 g/l/h. For a better understanding of the cell's regulatory mechanism in response to oxygenation levels, EMA was used to examine metabolic flux patterns under different oxygen levels. Up- and downregulation of enzymes in the network during the change of culturing condition from oxygen limitation to oxygen sufficiency were identified. The results indicated the flexibility of S. stipitis metabolism to cope with oxygen availability. In addition, relevant genetic targets towards improved ethanol-producing strains under all oxygenation levels were identified. These targeted genes limited the metabolic functionality of the cell to function according to the most efficient ethanol synthesis pathways. The presented approach is promising and can contribute to the development of culture optimization and strain engineers for improved lignocellulosic ethanol production by S. stipitis.     

Metabolic flux analysis and pharmaceutical production

Rational engineering of biological systems is an inherently complex process due to their evolved nature. Metabolic engineering emerged and developed over the past 20 years as a field in which methodologies for the rational engineering of biological systems is now being applied to specific industrial, medical, or scientific problems. Of considerable interest is the determination of metabolic fluxes within the cell itself, called metabolic flux analysis. This special issue and this review have a particular interest in the application of metabolic flux analysis for improving the pharmaceutical production process (for both small and large molecules). Though metabolic flux analysis has been somewhat limited in application towards pharmaceutical production, the overall goal is to: (1) have a better understanding of the organism and/or process in question, and (2) provide a rational basis to further engineer (on both metabolic and process scales) improved pharmaceutical production in these organisms. The focus of this review article is to present how experimental and computational methods of metabolic flux analysis have matured, mirroring the maturation of the metabolic engineering field itself, while highlighting some of the successful applications towards both small- and large-molecule pharmaceuticals.     

Relationships between population size and loss of genetic diversity: comparisons of experimental results with theoretical predictions

Preservation of genetic diversity is of fundamental concern toconservation biology, as genetic diversity is required for evolutionarychange. Predictions of neutral theory are used to guide conservationactions, especially genetic management of captive populations ofendangered species. Loss of heterozygosity is predicted to be inverselyrelated to effective population size. However, there is controversy asto whether allozymes behave as predicted by this theory. Loss of geneticdiversity for seven allozyme loci, chromosome II inversions andmorphological mutations was investigated in 23 Drosophilamelanogaster populations, maintained at effective population sizesof 25 (8 replicates), 50 (6), 100 (4), 250 (3) and 500 (2) for 50generations. Allozyme genetic diversity (heterozygosity, percentpolymorphism and allelic diversity), inversions and morphologicalmutations were all lost at greater rates in smaller than largerpopulations. Conservation concerns about loss of genetic diversity insmall populations are clearly warranted. Across our populations, loss ofallozyme heterozygosity over generations 0–24, 0–49 and25–49 did not differ from the predictions of neutral theory. Thetrend in deviations was always in the direction expected withassociative overdominance. Our results support the use of neutral theoryto guide conservation actions, such as the genetic management ofendangered species in captivity.     

Effects of Bcl-2 levels on Fas signaling-induced caspase-3 activation: molecular genetic tests of computational model predictions

Fas-induced apoptosis is a critical process for normal immune system development and function. Although many molecular components in the Fas signaling pathway have been identified, a systematic understanding of how they work together to determine network dynamics and apoptosis itself has remained elusive. To address this, we generated a computational model for interpreting and predicting effects of pathway component properties. The model integrates current information concerning the signaling network downstream of Fas activation, through both type I and type II pathways, until activation of caspase-3. Unknown parameter values in the model were estimated using experimental data obtained from human Jurkat T cells. To elucidate critical signaling network properties, we examined the effects of altering the level of Bcl-2 on the kinetics of caspase-3 activation, using both overexpression and knockdown in the model and experimentally. Overexpression was used to distinguish among alternative hypotheses for inhibitory binding interactions of Bcl-2 with various components in the mitochondrial pathway. In comparing model simulations with experimental results, we find the best agreement when Bcl-2 blocks the release of cytochrome c by binding to both Bax and truncated Bid instead of Bax, truncated Bid, or Bid alone. Moreover, although Bcl-2 overexpression strongly reduces caspase-3 activation, Bcl-2 knockdown has a negligible effect, demonstrating a general model finding that varying the expression levels of signal molecules frequently has asymmetric effects on the outcome. Finally, we demonstrate that the relative dominance of type I vs type II pathways can be switched by varying particular signaling component levels without changing network structure.