Predator-prey dynamics in P systems ruled by metabolic algorithm

P systems are used to compute predator-prey dynamics expressed in the traditional formulation by Lotka and Volterra. By governing the action of the transition rules in such systems using the regulatory features of the metabolic algorithm we come up with simulations of the Lotka-Volterra equations, whose robustness is comparable to that obtained using Runge-Kutta schemes and Gillespie's Stochastic Simulation Algorithm. Besides their reliability, the results obtained using the metabolic algorithm on top of P systems have a clear biochemical interpretation concerning the role, of reactants or promoters, of the species involved.     

Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis

Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.     

Metabolic imidacloprid resistance in the brown planthopper,Nilaparvata lugens,relies on multiple P450 enzymes

Target insensitivity contributing to imidacloprid resistance in Nilaparvata lugens has been reported to occur either through point mutations or quantitative change in nicotinic acetylcholine receptors (nAChRs). However, the metabolic resistance, especially the enhanced detoxification by P450 enzymes, is the major mechanism in fields. From one field-originated N. lugens population, an imidacloprid resistant strain G25 and a susceptible counterpart S25 were obtained to analyze putative roles of P450s in imidacloprid resistance. Compared to S25, over-expression of twelve P450 genes was observed in G25, with ratios above 5.0-fold for CYP6AY1, CYP6ER1, CYP6CS1, CYP6CW1, CYP4CE1 and CYP425B1. RNAi against these genes in vivo and recombinant tests on the corresponding proteins in vitro revealed that four P450s, CYP6AY1, CYP6ER1, CYP4CE1 and CYP6CW1, played important roles in imidacloprid resistance. The importance of the four P450s was not equal at different stages of resistance development based on their over-expression levels, among which CYP6ER1 was important at all stages, and that the others might only contribute at certain stages. The results indicated that, to completely reflect roles of P450s in insecticide resistances, their over-expression in resistant individuals, expression changes at the stages of resistance development, and catalytic activities against insecticides should be considered. In this study, multiple P450s, CYP6AY1, CYP6ER1, CYP4CE1 and CYP6CW1, have proven to be important in imidacloprid resistance.     

Towards dynamical system models of language-related brain potentials

Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexical-semantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system’s phase space.

Stochastic P systems and the simulation of biochemical processes with dynamic compartments

We introduce a sequential rewriting strategy for P systems based on Gillespie's stochastic simulation algorithm, and show that the resulting formalism of stochastic P systems makes it possible to simulate biochemical processes in dynamically changing, nested compartments. Stochastic P systems have been implemented using the spatially explicit programming language MGS. Implementation examples include models of the Lotka-Volterra auto-catalytic system, and the life cycle of the Semliki Forest virus.     

A distance-based dynamical transition analysis of time series signals and application to biological systems

This study demonstrates an application of distance-based numerical measures to the phase space of time series signals, in order to obtain a temporal analysis of complex dynamical systems. This method is capable of detecting alterations appearing in the characters of the deterministic dynamical systems and provides a simple tool for the real-time analysis of time series data obtained from a complex dynamical system even with black box functionality. The study presents a possible application of the method in the dynamical transition analysis of real EEG records from epilepsy patients.     

Metabolic profiling as a means of characterizing plant-associated microbial communities

Abstract Microbial communities from leaf and root habitats associated with sugar beet ( Beta vulgaris ) were characterized according to their capacity to metabolize a range of 95 sole carbon sources available in a commercial assay, GN-BIOLOG MicroPlates. Metabolic profiling was assessed as a method for evaluating perturbation of microbial communities of glasshouse-grown sugar beet inoculated with a genetically modified microorganism. This technique has allowed microbial communities, colonising the immature leaves of treated and untreated plants to be differentiated, although no differences were observed when plants inoculated with genetically modified microorganisms and unmodified inoculated plants were compared. As plants developed and differentiated, the carbon utilization patterns observed allowed communities to be grouped according to the habitat from which they were isolated, irrespective of treatment. These studies demonstrate that the genetically modified microorganism, introduced as a seed dressing colonised developing immature tissue throughout the 231-day study but did not disrupt the natural succession of microbial communities in glasshouse-grown sugar beet plants.     

Controllability of non-linear biochemical systems

Mathematical methods of biochemical pathway analysis are rapidly maturing to a point where it is possible to provide objective rationale for the natural design of metabolic systems and where it is becoming feasible to manipulate these systems based on model predictions, for instance, with the goal of optimizing the yield of a desired microbial product. So far, theory-based metabolic optimization techniques have mostly been applied to steady-state conditions or the minimization of transition time, using either linear stoichiometric models or fully kinetic models within biochemical systems theory (BST). This article addresses the related problem of controllability, where the task is to steer a non-linear biochemical system, within a given time period, from an initial state to some target state, which may or may not be a steady state. For this purpose, BST models in S-system form are transformed into affine non-linear control systems, which are subjected to an exact feedback linearization that permits controllability through independent variables. The method is exemplified with a small glycolytic-glycogenolytic pathway that had been analyzed previously by several other authors in different contexts.     

Metabolic monitoring by using the rate of change of NAD(P)H fluorescene

The amino acid fermentation by Corynebacterium glutamicum was monitored with an new technique that uses the first derivative of the NAD(P)H fluorescene signal. The rate of change of NAD(P)H pools is indicative of intracellular redox balance variations that correspond to metabolic changes. The profile of this signal showed several characteristics that coincided with major metabolic events during fermentation. We show here that the derivative fluorescence signal can accurately estimate points of threonine depletion, viable cell count, and the end of amino acid formation. Furthermore, on-line optimization strategies can be developed by using the derivative fluorescene signal. (c) 1994 John Wiley & Sons, Inc.     

A Dynamical Model of Lipoprotein Metabolism

We present a dynamical model of lipoprotein metabolism derived by combining a cascading process in the blood stream and cellular level regulatory dynamics. We analyse the existence and stability of equilibria and show that this low-dimensional, nonlinear model exhibits bistability between a low and a high cholesterol state. A sensitivity analysis indicates that the intracellular concentration of cholesterol is robust to parametric variations while the plasma cholesterol can vary widely. We show how the dynamical response to time-dependent inputs can be used to diagnose the state of the system. We also establish the connection between parameters in the system and medical and genetic conditions.     

Phenomenon of Activation of Cytochrome P450 by Nonionic Detergents

Mechanism of substitution of nonionic detergent Emulgen 913 for phospholipid as an activator of N-demethylase activity of cytochrome P450 form 2B4 (LM₂) has been studied. It is shown that such an activation takes place at the detergent concentrations below values critical for micelle formation. Under these conditions, Emulgen does not affect the hexameric state of the cytochrome. The stimulating effect proved to be similar in reconstituted monooxygenase systems containing (a) cytochrome P450 2B4 and NADPH-cytochrome P-450 reductase and (b) cytochrome 2B4 and organic hydroperoxides. These results indicate that the activation is due to an effect of the detergent upon P450 2B4 per se rather than upon P450/flavoprotein complex formation. The above conclusion is supported by the sedimentation data and measurement of the CD spectra of cytochrome P450 2B4 at 380–450 nm.     

Probabilistic polynomial dynamical systems for reverse engineering of gene regulatory networks

Elucidating the structure and/or dynamics of gene regulatory networks from experimental data is a major goal of systems biology. Stochastic models have the potential to absorb noise, account for un-certainty, and help avoid data overfitting. Within the frame work of probabilistic polynomial dynamical systems, we present an algorithm for the reverse engineering of any gene regulatory network as a discrete, probabilistic polynomial dynamical system. The resulting stochastic model is assembled from all minimal models in the model space and the probability assignment is based on partitioning the model space according to the likeliness with which a minimal model explains the observed data. We used this method to identify stochastic models for two published synthetic network models. In both cases, the generated model retains the key features of the original model and compares favorably to the resulting models from other algorithms.     

Integration of kinetic information on yeast sphingolipid metabolism in dynamical pathway models

For the first time, kinetic information from the literature was collected and used to construct integrative dynamical mathematical models of sphingolipid metabolism. One model was designed primarily with kinetic equations in the tradition of Michaelis and Menten whereas the other two models were designed as alternative power-law models within the framework of Biochemical Systems Theory. Each model contains about 50 variables, about a quarter of which are dependent (state) variables, while the others are independent inputs and enzyme activities that are considered constant. The models account for known regulatory signals that exert control over the pathway. Standard mathematical testing, repeated revisiting of the literature, and numerous rounds of amendments and refinements resulted in models that are stable and rather insensitive to perturbations in inputs or parameter values. The models also appear to be compatible with the modest amount of experimental experience that lends itself to direct comparisons. Even though the three models are based on different mathematical representations, they show dynamic responses to a variety of perturbations and changes in conditions that are essentially equivalent for small perturbations and similar for large perturbations. The kinetic information used for model construction and the models themselves can serve as a starting point for future analyses and refinements.     

Exploring Metabolic Responses of Potato Tissue Induced by Electric Pulses

In this study, we investigated the metabolic responses of potato tissue induced by pulsed electric field (PEF). Potato tissue was subjected to field strengths ranging from 30 to 500 V/cm, with a single rectangular pulse of 10 μs, 100 μs, or 1 ms. Metabolic responses were monitored using isothermal calorimetry, changes on electrical resistance during the delivery of the pulse, as well as impedance measurements. Our results show that the metabolic response involves oxygen consuming pathways as well as other unidentified events that are shown to be insensitive to metabolic inhibitors such as KCN and sodium azide. The metabolic response is strongly dependent on pulsing conditions and is independent of the total permeabilization achieved by the pulse. Evidence shows that calorimetry is a simple and powerful method for exploring conditions for metabolic stimulation, providing information on metabolic responses that can not be obtained from electrical measurements. This study set the basis for further investigations on defense-related consequences of PEF-induced stress.     

Metabolic activation of 3-hydroxyanisole by isolated rat hepatocytes

A tyrosinase-directed therapeutic approach for malignant melanoma therapy uses the depigmenting phenolic agents such as 4-hydroxyanisole (4-HA) to form cytotoxic o-quinones. However, renal and hepatic toxicity was reported as side effects in a recent 4-HA clinical trial. In search of novel therapeutics, the cytotoxicity of the isomers 4-HA, 3-HA and 2-HA were investigated. In the following, the order of the HAs induced hepatotoxicity in mice, as measured by increased in vivo plasma transaminase activity, or in isolated rat hepatocytes, as measured by trypan blue exclusion, was 3-HA > 2-HA > 4-HA. Hepatocyte GSH depletion preceded HA induced cytotoxicity and a 4-MC-SG conjugate was identified by LC/MS/MS mass spectrometry analysis when 3-HA was incubated with NADPH/microsomes/GSH. 3-HA induced hepatocyte GSH depletion or GSH depletion when 3-HA was incubated with NADPH/microsomes was prevented by CYP 2E1 inhibitors. Dicumarol (an NAD(P)H: quinone oxidoreductase inhibitor) potentiated 3-HA- or 4-methoxycatechol (4-MC) induced toxicity whereas sorbitol (an NADH generating nutrient) greatly prevented cytotoxicity indicating a quinone-mediated cytotoxic mechanism. Ethylendiamine (an o-quinone trap) largely prevented 3-HA and 4-MC-induced cytotoxicity indicating that o-quinone was involved in cytotoxicity. Dithiothreitol (DTT) greatly reduced 3-HA and 4-MC induced toxicity. The ferric chelator deferoxamine slightly decreased 3-HA and 4-MC induced cytotoxicity whereas the antioxidants pyrogallol or TEMPOL greatly prevented the toxicity suggesting that oxidative stress contributed to 3-HA induced cytotoxicity. In summary, ring hydroxylation but not O-demethylation/epoxidation seems to be the bioactivation pathway for 3-HA in rat liver. The cytotoxic mechanism for 3-HA and its metabolite 4-MC likely consists cellular protein alkylation and oxidative stress. These results suggest that 3-HA is not suitable for treatment of melanoma.     

Functional diversity of cytochrome P450s of the white-rot fungus Phanerochaete chrysosporium

The functional diversity of cytochrome P450s (P450s) of the white-rot basidiomycete, Phanerochaete chrysosporium, was studied. A series of compounds known to be P450 substrates of other organisms were utilized for metabolic studies of P. chrysosporium. Metabolic conversions of benzoic acid, camphor, 1,8-cineol, cinnamic acid, p-coumaric acid, coumarin, cumene, 1,12-dodecanediol, 1-dodecanol, 4-ethoxybenzoic acid, and 7-ethoxycoumarin were observed with P. chrysosporium for the first time. 1-Dodecanol was hydroxylated at seven different positions to form 1,12-, 1,11-, 1,10-, 1,9-, 1,8-, 1,7-, and 1,6-dodecandiols. The effect of piperonyl butoxide, a P450 inhibitor, on the fungal conversion of 1-dodecanol was also investigated, indicating that hydroxylation reactions of 1-dodecanol were inhibited by piperonyl butoxide in a concentration-dependent manner. With 11 substrates, 23 hydroxylation reactions and 2 deethylation reactions were determined and 6 products were new with the position of hydroxyl group incorporated. In conclusion, fungal P450s were shown to have diverse and unique functions.