Adrien Fauré

Logical modelling of regulatory networks with GINsim 2.3

Many important problems in cell biology require the consideration of dense nonlinear interactions between functional modules. The requirement of computer simulation for the understanding of cellular processes is now widely accepted, and a variety of modelling frameworks have been designed to meet this need. Here, we present a novel public release of the Gene Interaction Network simulation suite (GINsim), a software designed for the qualitative modelling and analysis of regulatory networks. The main functionalities of GINsim are illustrated through the analysis of a logical model for the core network controlling the fission yeast cell cycle. The last public release of GINsim (version 2.3), as well as development versions, can be downloaded from the dedicated website (http://gin.univ-mrs.fr/GINsim/), which further includes a model library, along with detailed tutorial and user manual.

A discrete model of Drosophila eggshell patterning reveals cell-autonomous and juxtacrine effects.

The Drosophila eggshell constitutes a remarkable system for the study of epithelial patterning, both experimentally and through computational modeling. Dorsal eggshell appendages arise from specific regions in the anterior follicular epithelium that covers the oocyte: two groups of cells expressing broad (roof cells) bordered by rhomboid expressing cells (floor cells). Despite the large number of genes known to participate in defining these domains and the important modeling efforts put into this developmental system, key patterning events still lack a proper mechanistic understanding and/or genetic basis, and the literature appears to conflict on some crucial points. We tackle these issues with an original, discrete framework that considers single-cell models that are integrated to construct epithelial models. We first build a phenomenological model that reproduces wild type follicular epithelial patterns, confirming EGF and BMP signaling input as sufficient to establish the major features of this patterning system within the anterior domain. Importantly, this simple model predicts an instructive juxtacrine signal linking the roof and floor domains. To explore this prediction, we define a mechanistic model that integrates the combined effects of cellular genetic networks, cell communication and network adjustment through developmental events. Moreover, we focus on the anterior competence region, and postulate that early BMP signaling participates with early EGF signaling in its specification. This model accurately simulates wild type pattern formation and is able to reproduce, with unprecedented level of precision and completeness, various published gain-of-function and loss-of-function experiments, including perturbations of the BMP pathway previously seen as conflicting results. The result is a coherent model built upon rules that may be generalized to other epithelia and developmental systems.

Glycogen is the primary source of glucose during the lag phase of E. coli proliferation

In the studies of Escherichia coli (E. coli), metabolomics analyses have mainly been performed using steady state culture. However, to analyze the dynamic changes in cellular metabolism, we performed a profiling of concentration of metabolites by using batch culture. As a first step, we focused on glucose uptake and the behavior of the first metabolite, G6P (glucose-6-phosphate). A computational formula was derived to express the glucose uptake rate by a single cell from two kinds of experimental data, extracellular glucose concentration and cell growth, being simulated by Cell Illustrator. In addition, average concentration of G6P has been measured by CE-MS. The existence of another carbon source was suggested from the computational result. After careful comparison between cell growth, G6P concentration, and the computationally obtained curve of glucose uptake rate, we predicted the consumption of glycogen in lag phase and its accumulation as an energy source in an E. coli cell for the next proliferation. We confirmed our prediction experimentally. This behavior indicates the importance of glycogen participation in the lag phase for the growth of E. coli. This article is part of a Special Issue entitled: Computational Methods for Protein Interaction and Structural Prediction.

Logical model specification aided by model-checking techniques: application to the mammalian cell cycle regulation

MOTIVATION Understanding the temporal behaviour of biological regulatory networks requires the integration of molecular information into a formal model. However, the analysis of model dynamics faces a combinatorial explosion as the number of regulatory components and interactions increases. RESULTS We use model-checking techniques to verify sophisticated dynamical properties resulting from the model regulatory structure in the absence of kinetic assumption. We demonstrate the power of this approach by analysing a logical model of the molecular network controlling mammalian cell cycle. This approach enables a systematic analysis of model properties, the delineation of model limitations, and the assessment of various refinements and extensions based on recent experimental observations. The resulting logical model accounts for the main irreversible transitions between cell cycle phases, the sequential activation of cyclins, and the inhibitory role of Skp2, and further emphasizes the multifunctional role for the cell cycle inhibitor Rb. AVAILABILITY AND IMPLEMENTATION The original and revised mammalian cell cycle models are available in the model repository associated with the public modelling software GINsim (http://ginsim.org/node/189). CONTACT thieffry@ens.fr SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Identification of key regulators in glycogen utilization in E. coli based on the simulations from a hybrid functional Petri net model

BackgroundGlycogen and glucose are two sugar sources available during the lag phase of E. coli, but the mechanism that regulates their utilization is still unclear.MethodsAttempting to unveil the relationship between glucose and glycogen, we propose an integrated hybrid functional Petri net (HFPN) model including glycolysis, PTS, glycogen metabolic pathway, and their internal regulatory systems.Results and conclusionsBy comparing known biological results to this model, basic necessary regulatory mechanism for utilizing glucose and glycogen were identified as a feedback circuit in which HPr and EIIAGlc play key roles. Based on this regulatory HFPN model, we discuss the process of glycogen utilization in E. coli in the context of a systematic understanding of carbohydrate metabolism.

Logical modelling and analysis of the budding yeast cell cycle

The budding yeast cell cycle core engine has been mod-elled in great detail, most notably by the groups of BelaNovak and John Tyson, using a differential formalism.Several models focusing on different regulatory moduleshave been developed. In this respect, the use of a logicalformalism facilitates the development of more integratedmodels, through the articulation of control modules tothe core engine. Such integrated models are difficult tobuild with the differential formalism due to the lack ofquantitative data, as well as to numerical instabilitiesinherent to large non linear systems.