Phenotype prediction in regulated metabolic networks

<p>Abstract</p> <p>Background</p> <p>Due 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.</p> <p>Results</p> <p>We 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 <it>E. coli </it>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.</p> <p>Conclusion</p> <p>The 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.</p

Multi-scale stochastic organization-oriented coarse-graining exemplified on the human mitotic checkpoint

The complexity of biological models makes methods for their analysis and understanding highly desirable. Here, we demonstrate the orchestration of various novel coarse-graining methods by applying them to the mitotic spindle assembly checkpoint. We begin with a detailed fine-grained spatial model in which individual molecules are simulated moving and reacting in a three-dimensional space. A sequence of manual and automatic coarse-grainings finally leads to the coarsest deterministic and stochastic models containing only four molecular species and four states for each kinetochore, respectively. We are able to relate each more coarse-grained level to a finer one, which allows us to relate model parameters between coarse-grainings and which provides a more precise meaning for the elements of the more abstract models. Furthermore, we discuss how organizational coarse-graining can be applied to spatial dynamics by showing spatial organizations during mitotic checkpoint inactivation. We demonstrate how these models lead to insights if the model has different “meaningful” behaviors that differ in the set of (molecular) species. We conclude that understanding, modeling and analyzing complex bio-molecular systems can greatly benefit from a set of coarse-graining methods that, ideally, can be automatically applied and that allow the different levels of abstraction to be related

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 Ca(2+) 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 Ca(2+) 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

Chemical organization theory: towards a theory of constructive dynamical systems

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. Our world is changing, qualitatively and quantitatively. The characteristics of its dynamics can be as simple as in the case of a friction-less swinging pendulum, or as complex as the dynamical process that results in the creative apparition of novel ideas or entities. We might characterize the nature of

Abstract in: Journal of Three Dimensional Images, 16(4):160-163 Artificial Chemistry’s Global Dynamic. Movements in the Lattice of Organisation

As artificial life is the study of life as it could be, artificial chemistry can be seen as the study of chemistry as it could be. In such systems molecules interact to generate new molecules, possibly different from the original ones. Here, we will focus on a general theoretical approach to study artificial chemistries. In this approach we consider the set of all possible organisations (closed and self-maintaining sets) in an artificial chemistry. As was shown in [2, 3] this set generates a lattice. We consider the dynamical movement of a system in this lattice, under the influence of its inner dynamic and random noise. We notice that some organisations, while being algebraically closed, are not stable under the influence of random external noise. While others, while being algebraically self-maintaining, do not dynamically self-maintain all their elements. This leads to a definition of attractive organisations.

Bio Systems Analysis Group

Chemical evolution describes the first step in the development of life, such as the formation of complex organic molecules from simpler (in-)organic compounds. A deeper understanding of this period requires not only a refinement of our chemical knowledge but also improved theoretical concepts that help to explain how complex chemical systems evolve in principle. Here we investigate how chemical evolution appears in the light of chemical organization theory. We identify two main dimensions of chemical evolution: the “actual evolution ” of the reaction vessel and the “organizational evolution ” of the set of molecular species reachable from the actual set of chemical species present in the vessel. The organizational evolution can be described precisely as a movement through the set of chemical organizations. We describe three types of such movements: upwards, downwards, and sidewards. The concepts are illustrated by simulation studies on a constructive artificial chemistry.

Structure and Hierarchy of Influenza Virus Models Revealed by Reaction Network Analysis

Influenza A virus is recognized today as one of the most challenging viruses that threatens both human and animal health worldwide. Understanding the control mechanisms of influenza infection and dynamics is crucial and could result in effective future treatment strategies. Many kinetic models based on differential equations have been developed in recent decades to capture viral dynamics within a host. These models differ in their complexity in terms of number of species elements and number of reactions. Here, we present a new approach to understanding the overall structure of twelve influenza A virus infection models and their relationship to each other. To this end, we apply chemical organization theory to obtain a hierarchical decomposition of the models into chemical organizations. The decomposition is based on the model structure (reaction rules) but is independent of kinetic details such as rate constants. We found different types of model structures ranging from two to eight organizations. Furthermore, the model&#8217;s organizations imply a partial order among models entailing a hierarchy of model, revealing a high model diversity with respect to their long-term behavior. Our methods and results can be helpful in model development and model integration, also beyond the influenza area