Section: New Results

Systems biology

Participants : Jérémie Bourdon, Jean Coquet, Victorien Delannée, Jacques Nicolas, Anne Siegel, Nathalie Théret, Pierre Vignet.

Representation of symbolic dynamical systems generated by a substitution. Iterated morphisms are combinatorial processes which are related to several classes of dynamical systems appearing in several fields of computer sciences and mathematics: numeration, ergodic theory, discrete geometry. They may be associated to fractal sets called "Rauzy fractals" whose topological properties are linked to the properties of the underlying dynamical system. We have introduced a generic algorithm framework to check such topological properties within a complete family of iterated morphism. This makes efficient the verification of conjectures on several families of substitutions related to multi-dimensional continued fraction algorithms. [A. Siegel] [14]

Identification of logical models for signaling pathways. Logical models of signaling pathways are a promising way of building effective in silico functional models of a cell. The automated learning of Boolean logic models describing signaling pathways can be achieved by training to phosphoproteomics data. In our work, combinatorial optimization methods based on recent logic programming paradigm allow to enumerate, and discriminate the family of logical models explaining data. Together, these approaches enable a robust understanding of the system response. The results are implemented in the caspo software. The main weakness of ASP-based learning algorithm is that they focus on the comparison of two time-points and assumes that the system has reached an early steady state. We have generalized such a learning procedure in order to discriminate Boolean networks according to their transient dynamics. To that goal, we exhibit a necessary condition that must be satisfied by a Boolean network dynamics to be consistent with a discretized time series trace. [A. Siegel] [23], [28]

Model of the Delayed Translation of Cyclin B Maternal mRNA After Sea Urchin Fertilization. An extended model of the numerical model introduced in [74] was developed to have a better understanding of the role of cyclin B in protein synthesis within minutes after fertilization of sea urchin eggs. The model confirms that regulation of cyclin B biosynthesis is an example of a select protein whose translation is controlled by pathways that are distinct from housekeeping proteins, even though both involve the same cap-dependent initia- tion pathway. Therefore, this model should help provide insight to the signaling utilized for the biosynthesis of cyclin B and other select proteins. [J. Bourdon, A. Siegel] [24]

Deciphering pathways involved in TGF-β signalling network. TGF-β is a multifunctional cytokine that regulates mammalian development, differentiation, and homeostasis. As a growth inhibitor of epithelial, endothelial, and hematopoietic cells, TGF-β is a potent anticancer agent in normal tissue. At the opposite TGF-β acts as a promoter of tumor by inducing the hallmarks of the cancer. Consequently targeting the deleterious effects of TGF-β without affecting its physiological role is the common goal of therapeutic strategies. While several strategies based on blocking TGF-β antibodies or small inhibitors of TGF-β receptors have been investigated, they did not take into account the impact of the (extracellular matrix) ECM remodeling that regulates TGF-β bioavailability and the complexity of TGF-β-dependent signaling pathways which regulate both physiological and pathological processes depending on context. In accordance with this, we recently demonstrated the benefical anti-tumor effect of the interplay between TGF-β signaling and the CD103 integrin pathway. At the opposite we have previously demonstrated that the disintegrin ADAMTS1 promotes TGF-β activation in chronic liver disease and we recently characterized interaction with inhibitor peptide to block such effects, using in silico approach. Importantly, we need to take into account a system-wide view and develop predictive models for therapeutic benefit. In that context we demonstrated that the ratio of TGFBR2 to TGFBR1 receptors concentrations can be used to discriminate between metastable regimes of TGF-β signaling model and predic the tumor cell aggressiveness [N. Théret][27], [16], [21].