Section: New Results
Qualitative modeling, simulation, analysis, and verification of gene regulatory networks
Genetic Network Analyzer (GNA) is a tool for the qualitative modeling and simulation of the dynamics of gene regulatory networks by means of PL models, as described in Section 5.1 . GNA has been integrated with the other bioinformatics tools distributed by Genostar (http://www.genostar.com/ ). Version 8.3 of GNA was released by IBIS and Genostar this year. This version is an update of version 8.0, deposited at the Agence pour la Protection des Programmes (APP). Some bugs have been corrected in the new version and the program has been adapted to the latest versions of Java and the software platform of Genostar. A book chapter describing the current version of GNA has been published in a volume on the modeling of bacterial molecular networks  . The chapter is a tutorial illustrating the practical use of recent functionalities of GNA like the network editor and the formal verification module by means of an example network in E. coli (see also  ). A paper on the use of temporal logic and formal verification in the context of GNA appeared in Theoretical Computer Science this year  , in a special issue associated with the conference Computational Methods in System (CMSB), held in Rostock in 2008.
Notwithstanding the above improvements of the software, most of our efforts in the past year have gone into applications in collaboration with users of GNA . For example, Delphine Ropers has worked with several groups at IST Lisbon on the modeling of the FLR1 network in yeast, resulting in a paper in IET Systems Biology  . The paper reports on the qualitative modelling and simulation of the transcriptional regulatory network controlling the response of the model eukaryote Saccharomyces cerevisiae to the agricultural fungicide mancozeb. The model has allowed the analysis of the regulation level and activity of the components of the mancozeb-induced network controlling the transcriptional activation of FLR1. This gene is proposed to confer multidrug resistance to the cell through its putative role as a drug efflux pump. Formal verification analysis of the network allowed us to confront model predictions with experimental data and to assess the model robustness to parameter ordering and gene deletion. This analysis led to a better understanding of the mechanisms regulating the response of FLR1 to mancozeb and confirmed the need for a new transcription factor to account for the full transcriptional activation of the gene YAP1. The result is a model of the response of FLR1 to mancozeb, permitting a quick and cost-effective test of hypotheses prior to experimental validation.
As another example of the use of GNA , Hidde de Jong has contributed to the modeling of the TOL system in Pseudomonas putida, carried out at the Spanish National Biotechnology Center (CNB). The gene regulatory network of the TOL plasmid pWW0 of the soil bacterium Pseudomonas putida mt-2 for catabolism of m-xylene is an archetypal model for environmental biodegradation of aromatic pollutants. Although nearly every metabolic and transcriptional component of this regulatory system is known in detail, the complexity of its architecture is still perplexing. To gain an insight into the inner layout of this network a PL model of the TOL system was implemented, simulated and experimentally validated by measuring the expression of the genes encoding the regulators XylR and XylS when specific portions of the network were activated with selected inducers (m-xylene, o-xylene, 3-methylbenzylalcohol and 3-methylbenzoate). This analysis made sense of the specific regulatory topology on the basis of an unprecedented network motif in the genetic circuit for m-xylene catabolism. The motif appears to ensure a simultaneous expression of the upper and lower segments of the m-xylene catabolic route that would be difficult to bring about with a standard substrate-responsive single promoter. Furthermore, it is plausible that the motif helps to avoid biochemical conflicts between competing plasmid-encoded and chromosomally-encoded pathways in this bacterium. The analysis of the TOL system has been published in BMC Systems Biology  .