Understanding flux in plant metabolic networks

The revolutionary growth in our ability to identify the 'parts list' of cellular infrastructure in plants in detail, and to alter it with precision, challenges us to develop methods to quantify how these parts function. For components of metabolism, this means mapping fluxes at the level of metabolic networks. Advances in experimental, analytical and software tools for metabolic flux analysis now allow maps of the fluxes through central metabolism to be obtained from the results of stable-isotope-labeling experiments. Such maps have led to notable successes in understanding and engineering metabolic function in microorganisms. Recent studies in plants are giving insight into particular fluxes, such as those of the pentose phosphate pathway, and into general phenomena, such as substrate- or futile-cycles and compartmentation. The importance of experimental design and statistical analysis have been illustrated, and analyses of fluxes in heterotrophic plant tissues have been carried out recently.     

On detecting and measuring competition in spatially structured plant communities

Recent models have shown that the development of spatial structure in plant mixtures may make strong competitive interactions between species hard to detect owing to spatial segregation of the competing species. Here we address the issue of measuring interspecific competition using a simulation based on a neighbourhood population model which assumes that both dispersal and competitive interactions are localized. Using known parameter combinations we use the model to test the power and efficiency of two approaches for detecting and measuring competition. The first approach is based on measuring the response of communities to the removal of neighbours. Measures of interspecific competition based on this approach are extremely biased by spatial segregation of species, although this bias may be partially overcome by altering the spatial scale at which the effects of removals are recorded. The second approach is based on multiple regression of per capita population growth rates on local densities of the interacting species. When dispersal is restricted, the regression approach provides accurate estimates of interspecific competition coefficients when the scale of the sampling unit (i.e. the quadrats within which plants are counted) is large compared to the scale at which interactions and dispersal occur. When seeds disperse globally the removal method performs best; the regression method fails because sampling units do not form closed dynamic systems. Our results highlight the importance of tailoring methods for detecting competition to the characteristics of the species in question. They also indicate that rapid nonmanipulative estimates of competition coefficients may be the best approach in communities where dispersal is restricted and competitive interactions localized, which is likely to be the case for the majority of plants.     

Strategies for investigating the plant metabolic network with steady-state metabolic flux analysis: lessons from an Arabidopsis cell culture and other systems

Steady-state (13)C metabolic flux analysis (MFA) is currently the experimental method of choice for generating flux maps of the compartmented network of primary metabolism in heterotrophic and mixotrophic plant tissues. While statistically robust protocols for the application of steady-state MFA to plant tissues have been developed by several research groups, the implementation of the method is still far from routine. The effort required to produce a flux map is more than justified by the information that it contains about the metabolic phenotype of the system, but it remains the case that steady-state MFA is both analytically and computationally demanding. This article provides an overview of principles that underpin the implementation of steady-state MFA, focusing on the definition of the metabolic network responsible for redistribution of the label, experimental considerations relating to data collection, the modelling process that allows a set of metabolic fluxes to be deduced from the labelling data, and the interpretation of flux maps. The article draws on published studies of Arabidopsis cell cultures and other systems, including developing oilseeds, with the aim of providing practical guidance and strategies for handling the issues that arise when applying steady-state MFA to the complex metabolic networks encountered in plants.     

Design of substrate label for steady state flux measurements in plant systems using the metabolic network of Brassica napus embryos

Steady state metabolic flux analysis using (13)C labeled substrates is of growing importance in plant physiology and metabolic engineering. The quality of the flux estimates in (13)C metabolic flux analysis depend on the: (i) network structure; (ii) flux values; (iii) design of the labeling substrate; and (iv) label measurements performed. Whereas the first two parameters are facts of nature, the latter two are to some extent controlled by the experimenter, yet they have received little attention in most plant studies. Using the metabolic flux map of developing Brassica napus (Rapeseed) embryos, this study explores the value of optimal substrate label designs obtained with different statistical criteria and addresses the applicability of different optimal designs to biological questions. The results demonstrate the value of optimizing the choice of labeled substrates and show that substrate combinations commonly used in bacterial studies can be far from optimal for mapping fluxes in plant systems. The value of performing additional experiments and the inclusion of measurements is also evaluated.     

Development of real-time radioisotope imaging systems for plant nutrient uptake studies

Ionic nutrition is essential for plant development. Many techniques have been developed to image and (or) measure ionic movement in plants. Nevertheless, most of them are destructive and limit the analysis. Here, we present the development of radioisotope imaging techniques that overcome such restrictions and allow for real-time imaging of ionic movement. The first system, called macroimaging, was developed to visualize and measure ion uptake and translocation between organs at a whole-plant scale. Such a device is fully compatible with illumination of the sample. We also modified fluorescent microscopes to set up various solutions for ion uptake analysis at the microscopic level. Both systems allow numerical analysis of images and possess a wide dynamic range of detection because they are based on radioactivity.     

The potential of spatially resolved spectroscopy for monitoring angiogenesis in the chorioallantoic membrane

Over the last decade, the poultry sector has sought to develop ways to monitor chicken embryonic development as to optimize the incubation conditions. One of the parameters of development which may change under different incubation conditions is the angiogenesis in the chorioallantoic membrane (CAM). To be able to quantify these changes in the angiogenesis and detect long-term effects on health, a non-destructive technique is necessary. In this article, the first steps toward such a non-destructive technique are successfully taken. A spatially resolved spectroscopy set-up is built and tested for its potential to measure changes in angiogenesis with incubation time, and differences between a normal and hypercapnic incubation. In this first study, reflectance measurements are performed directly on the CAM as the eggshell considerably complicates the analysis. This issue should be addressed in future research to come to a really non-destructive technique. An experiment was conducted in which one group was incubated under normal conditions, and another under early prenatal hypercapnic conditions (i.e., increased CO(2) concentrations). The angiogenesis in the CAM was measured at embryonic day (ED) 10, 13, and 16. The measurements showed a clear blood spectrum with an increasing amount of blood in time, and significant differences in the reflectance as function of the source-detector distances. However, no significant differences between the hypercapnia and the control group could be detected.     

Enhanced low oxygen survival in Arabidopsis through increased metabolic flux in the fermentative pathway

We manipulated the enzyme activity levels of the alcohol fermentation pathway, pyruvate decarboxylase (PDC), and alcohol dehydrogenase (ADH) in Arabidopsis using sense and antisense overexpression of the corresponding genes (PDC1, PDC2, and ADH1). Transgenic plants were analyzed for levels of fermentation and evaluated for changes in hypoxic survival. Overexpression of either Arabidopsis PDC1 or PDC2 resulted in improved plant survival. In contrast, overexpression of Arabidopsis ADH1 had no effect on flooding survival. These results support the role of PDC as the control step in ethanol fermentation. Although ADH1 null mutants had decreased hypoxic survival, attempts to reduce the level of PDC activity enough to see an effect on plant survival met with limited success. The combination of flooding survival data and metabolite analysis allows identification of critical metabolic flux points. This information can be used to design transgenic strategies to improve hypoxic tolerance in plants.     

Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems

The elucidation of organism-scale metabolic networks necessitates the development of integrative methods to analyze and interpret the systemic properties of cellular metabolism. A shift in emphasis from single metabolic reactions to systemically defined pathways is one consequence of such an integrative analysis of metabolic systems. The constraints of systemic stoichiometry, and limited thermodynamics have led to the definition of the flux space within the context of convex analysis. The flux space of the metabolic system, containing all allowable flux distributions, is constrained to a convex polyhedral cone in a high-dimensional space. From metabolic pathway analysis, the edges of the high-dimensional flux cone are vectors that correspond to systemically defined "extreme pathways" spanning the capabilities of the system. The addition of maximum flux capacities of individual metabolic reactions serves to further constrain the flux space and has led to the development of flux balance analysis using linear optimization to calculate optimal flux distributions. Here we provide the precise theoretical connections between pathway analysis and flux balance analysis allowing for their combined application to study integrated metabolic function. Shifts in metabolic behavior are calculated using linear optimization and are then interpreted using the extreme pathways to demonstrate the concept of pathway utilization. Changes to the reaction network, such as the removal of a reaction, can lead to the generation of suboptimal phenotypes that can be directly attributed to the loss of pathway function and capabilities. Optimal growth phenotypes are calculated as a function of environmental variables, such as the availability of substrate and oxygen, leading to the definition of phenotypic phase planes. It is illustrated how optimality properties of the computed flux distributions can be interpreted in terms of the extreme pathways. Together these developments are applied to an example network and to core metabolism of Escherichia coli demonstrating the connections between the extreme pathways, optimal flux distributions, and phenotypic phase planes. The consequences of changing environmental and internal conditions of the network are examined for growth on glucose and succinate in the face of a variety of gene deletions. The convergence of the calculation of optimal phenotypes through linear programming and the definition of extreme pathways establishes a different perspective for the understanding of how a defined metabolic network is best used under different environmental and internal conditions or, in other words, a pathway basis for the interpretation of the metabolic reaction norm.     

A simple and modified manometric method for measuring oxygen uptake rate of plant cells in flask cultures

Summary A simple and convenient technique was developed based on the principle of Warburg manometric method to measure O₂ uptake rate (OUR) and CO₂ evolution rate (CER) of suspended cells in a shake flask culture. It was successfully applied to suspension cultures of rice (Oryza sativa) and Panax notoginseng cells, and some important bioprocess parameters, such as OUR, CER, respiratory quotient (RQ), specific OUR (SOUR) and specific CER (SCER), were quantitatively obtained. The measuring system is easy to operate, able to treat many samples simultaneously and is economical.     

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.     

Comparison of two test systems for measuring plant phosphorus uptake via arbuscular mycorrhizal fungi

 Plant phosphorus uptake via external hyphae of arbuscular mycorrhizal fungi has been measured using compartmented systems where a hyphal compartment is separated from a rooting compartment by a fine mesh. By labelling the soil within the hyphal compartment with a radioactive phosphorus (P) isotope, hyphal uptake of P into the plant can be traced. The objective of this growth chamber study was to test two hyphal compartments of different design with respect to their suitabilities for measurement of hyphal P uptake. One hyphal compartment was simply a nylon mesh bag filled with ³²P-labelled soil. The labelled soil in the other hyphal compartment was completely surrounded by an 8–10 mm layer of unlabelled soil that served as a buffer zone. Mycorrhizal and non-mycorrhizal subterranean clover plants were grown in pots with a centrally positioned hyphal compartment. Uptake of radioactive P by non-mycorrhizal control plants was 25% of that by mycorrhizal plants with the mesh bag but only 3% when including the buffer zone. Based on this good control of non-mycorrhizal P uptake from within the hyphal compartment and its greater ease of handling once produced, we judged the hyphal compartment including a buffer zone to be superior to the mesh bag. Accepted: 15 September 1998     

Estimation of steady-state flux rates in metabolic systems by computer simulations of radioactive tracer experiments

The dynamics of radioactive tracers in metabolic systems canbe mathematically modelled by coupled systems of differentialequations for both the concentrations and the specific radio-activitiesof the metabolites involved. Computer simulations, i.e. directfitting of numerical solutions of these equations to observedtime-courses of metabolites and spec jflc radioactivities, enablesone to estimate unknown kinetic parameters of the system. Thetheoretical fundamentals of this approach and the main stepstowards the quantitative assessment of flux rates in stationarymetabolic systems are outlined. An application of the methodto the purine nucleotide metabolism of Ehrlich ascites twnorcells is given based on a simp4fied model of this pathway. Theobtained steady-state flux rates indicate a marked increasein the metabolism of the adenine nucleotides during the proliferatingphase in comparison to the resting phase of tumor growth.     

Epistasis for growth rate and total metabolic flux in yeast

Studies of interactions between gene deletions repeatedly show that the effect of epistasis on the growth of yeast cells is roughly null or barely positive. These observations relate generally to the pace of growth, its costs in terms of required metabolites and energy are unknown. We measured the maximum rate at which yeast cultures grow and amounts of glucose they consume per synthesized biomass for strains with none, single, or double gene deletions. Because all strains were maintained under a fermentative mode of growth and thus shared a common pattern of metabolic processes, we used the rate of glucose uptake as a proxy for the total flux of metabolites and energy. In the tested sample, the double deletions showed null or slightly positive epistasis both for the mean growth and mean flux. This concordance is explained by the fact that average efficiency of converting glucose into biomass was nearly constant, that is, it did not change with the strength of growth effect. Individual changes in the efficiency caused by gene deletions did have a genetic basis as they were consistent over several environments and transmitted between single and double deletion strains indicating that the efficiency of growth, although independent of its rate, was appreciably heritable. Together, our results suggest that data on the rate of growth can be used as a proxy for the rate of total metabolism when the goal is to find strong individual interactions or estimate the mean epistatic effect. However, it may be necessary to assay both growth and flux in order to detect smaller individual effects of epistasis.     

Binding and transport in norepinephrine transporters. Real-time,spatially resolved analysis in single cells using a fluorescent substrate

Monoamine transporters, the molecular targets for drugs of abuse and antidepressants, clear norepinephrine, dopamine, or serotonin from the synaptic cleft. Neurotransmitters, amphetamines, and neurotoxins bind before being transported, whereas cocaine and antidepressants bind to block transport. Although binding is crucial to transport, few assays separate binding from transport, nor do they provide adequate temporal or spatial resolution to describe real-time kinetics or localize sites of active uptake. Here, we report a new method that distinguishes substrate binding from substrate transport using single-cell, space-resolved, real-time fluorescence microscopy. For these studies we use a fluorescent analogue of 1-methyl-4-phenylpyridinium, a neurotoxic metabolite and known substrate of monoamine transporters, to assess binding and transport with 50-ms, sub-micron resolution. We show that ASP(+) (4-(4-(dimethylamino)styrl)-N-methylpyridinium) has micromolar potency for the human norepinephrine transporter, that ASP(+) accumulation is Na(+)-, Cl(-)-, cocaine-, and desipramine-sensitive and temperature-dependent, and that ASP(+) competes with norepinephrine uptake. Using this method we demonstrate that norepinephrine transporters are efficient buffers for substrate, with binding rates exceeding transport rates by 100-fold. Furthermore, substrates bind deep within the transporter, isolated from both the bath and the lipid bilayer. Although transport per se depends on Na(+) and Cl(-), binding is independent of Na(+) and actually increases in low Cl(-). We further demonstrate that ASP(+) interacts with transporters not only in transfected cells but in cultured neurons. ASP(+) is also a substrate for dopamine and serotonin transporters and therefore represents a powerful new technique for studying the biophysical properties of monoamine transporters, an approach also amenable to high throughput assays for drug discovery.     

Global profiling of reactive oxygen and nitrogen species in biological systems: high-throughput real-time analyses

Herein we describe a high-throughput fluorescence and HPLC-based methodology for global profiling of reactive oxygen and nitrogen species (ROS/RNS) in biological systems. The combined use of HPLC and fluorescence detection is key to successful implementation and validation of this methodology. Included here are methods to specifically detect and quantitate the products formed from interaction between the ROS/RNS species and the fluorogenic probes, as follows: superoxide using hydroethidine, peroxynitrite using boronate-based probes, nitric oxide-derived nitrosating species with 4,5-diaminofluorescein, and hydrogen peroxide and other oxidants using 10-acetyl-3,7-dihydroxyphenoxazine (Amplex® Red) with and without horseradish peroxidase, respectively. In this study, we demonstrate real-time monitoring of ROS/RNS in activated macrophages using high-throughput fluorescence and HPLC methods. This global profiling approach, simultaneous detection of multiple ROS/RNS products of fluorescent probes, developed in this study will be useful in unraveling the complex role of ROS/RNS in redox regulation, cell signaling, and cellular oxidative processes and in high-throughput screening of anti-inflammatory antioxidants.     

Determination of oxygen emission and uptake in leaves by pulsed, time resolved photoacoustics

Pulsed, time resolved photoacoustics has sufficient sensitivity to determine oxygen emission and uptake by single turnover flashes to leaves. The advantage over previous methodologies is that when combined with single turnover flashes the kinetics of the thermal and the gas signals can be resolved to 0.1 millisecond and separated. The S-state oscillations of oxygen formation are readily observed. The gas signal from common spongy leaves such as spinach (Spinacia sp.), Japanese andromeda (Pieris japonica), mock orange (Philadelphus coronarius) and viburnum (Viburnum tomentosum), after correction for instrumental rise time, show a lag of only 1 millisecond and a rise time of 5 milliseconds in the formation of oxygen. Thus a recent proposal that the formation of oxygen requires over 100 milliseconds cannot be true for choroplasts in vivo. The rapid emission is correlated with structure of the leaf. At low light flash energies a rapid gas uptake is observed. The uptake has slightly slower kinetics than oxygen evolution, and its magnitude increases with damage to the leaf. The pulse methodology shows that the uptake begins with the very first flash after dark adaption, and allows the detection of a positive signal (oxygen) on the third flash. These observations, the long wavelength of excitation (695 nanometers) and the magnitude of the signal support the contention that the gas uptake is oxygen reduction by electrons from photosystem I. These results show that important physiological aspects of a leaf can be studied by pulsed, time resolved photoacoustics.     

Utilizing elementary mode analysis,pathway thermodynamics,and a genetic algorithm for metabolic flux determination and optimal metabolic network design

Background  

Microbial hosts offer a number of unique advantages when used as production systems for both native and heterologous small-molecules. These advantages include high selectivity and benign environmental impact; however, a principal drawback is low yield and/or productivity, which limits economic viability. Therefore a major challenge in developing a microbial production system is to maximize formation of a specific product while sustaining cell growth. Tools to rationally reconfigure microbial metabolism for these potentially conflicting objectives remain limited. Exhaustively exploring combinations of genetic modifications is both experimentally and computationally inefficient, and can become intractable when multiple gene deletions or insertions need to be considered. Alternatively, the search for desirable gene modifications may be solved heuristically as an evolutionary optimization problem. In this study, we combine a genetic algorithm and elementary mode analysis to develop an optimization framework for evolving metabolic networks with energetically favorable pathways for production of both biomass and a compound of interest.