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Chemical Organisation Theory

Complex dynamical networks consisting of many components that interact and produce each other are difficult to understand, especially, when new components may appear. In this paper we outline a theory to deal with such systems. The theory consists of two parts. The first part introduces the concept of a chemical organization as a closed and mass-maintaining set of components. This concept allows to map a complex (reaction) network to the set of organizations, providing a new view on the system’s structure. The second part connects dynamics with the set of organizations, which allows to map a movement of the system in state space to a movement in the set of organizations.

ATP enhances spontaneous calcium activity in cultured suburothelial myofibroblasts of the human bladder.

Background Suburothelial myofibroblasts (sMF) are located underneath the urothelium in close proximity to afferent nerves. They express purinergic receptors and show calcium transients in response to ATP. Therefore they are supposed to be involved in afferent signaling of the bladder fullness. Since ATP concentration is likely to be very low during the initial filling phase, we hypothesized that sMF Ca2+ activity is affected even at very low ATP concentrations. We investigated ATP induced modulation of spontaneous activity, intracellular calcium response and purinergic signaling in cultured sMF. Methodology/Principal Findings Myofibroblast cultures, established from cystectomies, were challenged by exogenous ATP in presence or absence of purinergic antagonist. Fura-2 calcium imaging was used to monitor ATP (10−16 to 10−4 mol/l) induced alterations of calcium activity. Purinergic receptors (P2X1, P2X2, P2X3) were analysed by confocal immunofluorescence. We found spontaneous calcium activity in 55.18%±1.65 of the sMF (N = 48 experiments). ATP significantly increased calcium activity even at 10−16 mol/l. The calcium transients were partially attenuated by subtype selective antagonist (TNP-ATP, 1 µM; A-317491, 1 µM), and were mimicked by the P2X1, P2X3 selective agonist α,β-methylene ATP. The expression of purinergic receptor subtypes in sMF was confirmed by immunofluorescence. Conclusions/Significance Our experiments demonstrate for the first time that ATP can modulate spontaneous activity and induce intracellular Ca2+ response in cultured sMF at very low concentrations, most likely involving P2X receptors. These findings support the notion that sMF are able to register bladder fullness very sensitively, which predestines them for the modulation of the afferent bladder signaling in normal and pathological conditions.

Phenotype prediction in regulated metabolic networks

BackgroundDue to the growing amount of biological knowledge that is incorporated into metabolic network models, their analysis has become more and more challenging. Here, we examine the capabilities of the recently introduced chemical organization theory (OT) to ease this task. Considering only network stoichiometry, the theory allows the prediction of all potentially persistent species sets and therewith rigorously relates the structure of a network to its potential dynamics. By this, the phenotypes implied by a metabolic network can be predicted without the need for explicit knowledge of the detailed reaction kinetics.ResultsWe propose an approach to deal with regulation – and especially inhibitory interactions – in chemical organization theory. One advantage of this approach is that the metabolic network and its regulation are represented in an integrated way as one reaction network. To demonstrate the feasibility of this approach we examine a model by Covert and Palsson (J Biol Chem, 277(31), 2002) of the central metabolism of E. coli that incorporates the regulation of all involved genes. Our method correctly predicts the known growth phenotypes on 16 different substrates. Without specific assumptions, organization theory correctly predicts the lethality of knockout experiments in 101 out of 116 cases. Taking into account the same model specific assumptions as in the regulatory flux balance analysis (rFBA) by Covert and Palsson, the same performance is achieved (106 correctly predicted cases). Two model specific assumptions had to be considered: first, we have to assume that secreted molecules do not influence the regulatory system, and second, that metabolites with increasing concentrations indicate a lethal state.ConclusionThe introduced approach to model a metabolic network and its regulation in an integrated way as one reaction network makes organization analysis a universal technique to study the potential behavior of biological network models. Applying multiple methods like OT and rFBA is shown to be valuable to uncover critical assumptions and helps to improve model coherence.

Chemical Organizations in the Central Sugar Metabolism of Escherichia coli

The theory of chemical organizations is employed as a novel method to analyze and understand biological network models. The method allows us to decompose a chemical reaction network into sub-networks that are (algebraically) closed and self-maintaining. Such sub-networks are termed organizations. Although only stoichiometry is considered to compute organizations, the analysis allows us to narrow down the potential dynamic behavior of the network: organizations represent potential steady state compositions of the system. When applied to a model of sugar metabolism in E. coli including gene expression, signal transduction, and enzymatic activities, some organizations are found to coincide with inducible biochemical pathways.

Spontaneous Formation of Proto-cells in an Universal Artificial Chemistry on a Planar Graph

An artificial chemistry is embedded in a triangular planar graph, that allows the molecules to act only locally along the edges. We observe the formation of effectively separated components in the graph structure. Those components are kept separated by elastic reactions from molecules generated inside the component itself. We interpret those components as self-maintaining proto-cells and the elastic nodes as their proto-membrane. The possibility for these cells to be autopoietic is discussed.

A parallel algorithm to compute chemical organizations in biological networks

SUMMARY Analysing genome-scale in silico models with stoichiometry-based methods is computationally demanding. The current algorithms to compute chemical organizations in chemical reaction networks are limited to small-scale networks, prohibiting a thorough analysis of large models. Here, we introduce a parallelized version of the constructive algorithm to determine chemical organizations. The algorithm is implemented in the Standard C programming language and parallelized using the message passing interface (MPI) protocol. The resulting code can be executed on computer clusters making use of an arbitrary number of processors. The algorithm is parallelized in an embarrassing parallel manner, providing good scalability. AVAILABILITY An implementation of the algorithm including source code can be obtained from http://www.minet.uni-jena.de/csb/prj/ot/tools

Chemical Organization Theory Applied to Virus Dynamics Theorie chemischer Organisationen angewendet auf Infektionsmodelle

Summary Chemical organization theory has been proposed to provide a new perspective to study complex dynamical reaction networks. It decomposes a reaction network into overlapping sub-networks called organizations. An organization is an algebraically closed and self-maintaining set of molecular species. The set of organizations form a hierarchical “organizational structure”, which is here a lattice. In order to evaluate the usefulness of this approach we apply the theory to five models of immune response to HIV infection. We found four different lattices of organizations, which can be used as a first classification of the models. Furthermore, each organization found can be assigned to a functional state of the system. And finally, the lattice of organizations can be used to explain a treatment strategy on a more abstract level, i. e., as a movement from one organization into another.

Stability of Metabolic and Balanced Organisations

We investigate the possible organisations emerging from an artificial chemistry (AC) of colliding molecules in a well stirred reactor. The molecules are generated from 7 basic components (atoms), each with a different behavior. After discovering two main types of organisations (metabolic o. and balanced o.), we deepen our analysis by studying their behavior over time. The phases they pass through and their stability with respect to an external influx of random information are examined. We notice that no organisation seems to be totally stable over time, yet metabolic organisations pass through a growth phase with a much higher stability. Lastly we observe how the different phases are triggered by the presence or absence of particular atoms.

Don't vote, evolve!

We present an alternative form of decision making designed using a Human Based Genetic Algorithms. The algorithm permits the participants to tackle open questions, by letting all of them propose answers and evaluate each others answers. A successful example is described and some theoretical results are presented showing how the system scales up.

Using pareto front for a consensus building, human based, genetic algorithm

We present a decision making procedure, for a problem where no solution is known a priori. The decision making procedure is a human powered genetic algorithm that uses human beings to produce variations and evaluation of the partial solution proposed. Following [1] we then pick the pareto front of the proposed partial solutions proposed, eliminating the dominated ones. We then feed back the partial results to the human beings, asking them to find a alternative proposals, that integrate and synthesize the solutions in the pareto front. The algorithm is right now being implemented, and some preliminary results are being presented. Some possible variations on the algorithm, and some limits of it, are also discussed.