The project lies at the border between Applied Mathematics, Computer Science and Control Theory on the one hand, Physiology, Molecular and Cellular Biology on the other hand. It falls within both Systems Biology and Mathematical physiology. It aims at studying the control of the ovarian function, and, more precisely, of the ovulation process, from a mechanistic viewpoint. The ovulatory success is the main limiting factor of the whole reproductive process, so that a better understanding of ovulation control is needed both for clinical and zootechnical applications. The identification of the targets of the control operated by the pituitarian gonadotrophins, especially the Follicle-Stimulating-Hormone (FSH), and the analysis of its operating way both lead naturally to a multi-scale representation. The project articulates on the coupling between different mathematical (mainly: conservation laws and control  theory) and computing (mainly temporal logic) formalisms with biological knowledge and data, combining high-throughput cell signalling data generation with physiological experimental investigations.

 

The project consists in analysing the connectivity and dynamics of the FSH signalling network in the granulosa cells of ovarian follicles and embedding the network within a multi-scale representation, from the molecular up to the organic level. We will examine the relative contributions of the Gαs and βarrestin-dependent pathways in response to FSH signal, determine how each pathway controls downstream cascades and which mechanisms are involved in the transition between different cellular states (quiescence, proliferation, differentiation and apoptosis). On the experimental ground, we propose to develop an antibody microarray approach in order to simultaneously measure the phosphorylation levels of a large number of signalling intermediates in a single experiment. On the modelling ground, we will use the BIOCHAM (biochemical abstract machine) environment first at the boolean level, to formalise the network of interactions corresponding to the FSH-induced signalling events on the cellular scale. This network will then be enriched with kinetic information coming from experimental data, which will allow the use of the ordinary differential equation level of BIOCHAM. In order to find and fine-tune the structure of the network and the values of the kinetic parameters, model-checking techniques will permit a systematic comparison between the model behaviour and the results of experiments. In the end, the cell-level model should be abstracted to a much simpler model that can be embedded into a multi-scale one without losing its main characteristics.

As far as terminal follicular development is concerned, we have at our disposal a multi-scale model based on a tight interaction between Physiologists and Biomathematicians. Our efforts will focus on the analysis of the control problems associated with the model as well as on the systematic exploration of the physiological or pathological situations issuing from different model parametrisations. As far as basal follicular development is concerned, we have to extend the model to account for the cellular state of quiescence and its joint control by FSH and AMH (Anti-Mullerian Hormone).

 

On cognitive grounds, we expect to dispose as main results of: (i) a detailed mechanistic model of the transduction mechanisms of FSH receptor enabling to distinguish between the relative contributions of the Gαs and βarr-dependent pathways to the activation of downstream signalling cascades; (ii) alternative models of the specific and differential action of FSH on granulosa cells according to their maturity stage; (iii) a multi-scale model of follicular development embedding the molecular scale and accounting for the emergence of macroscopic processes and their control: ability to pursue terminal follicular development and selection of ovulatory follicles. On applicative grounds, the expected middle-term fall-outs are connected with reproductive medicine and biotechnologies. The results of our work should be useful in: (i) developping new generations of pharmacological drugs to control ovarian function, based on a deep understanding of FSH operating way and the possibility of testing their efficiency in-silico from the FSH transduction network model; (ii) developping and assessing tools for predicting as well as improving the ovarian response to stimulation treatment. Such tools would help to minimise the individual variability which dramatically affects the current efficiency of stimulation treatments in their clinical and farming applications.

On the Computer Science side, the new methodology introduced by the formalisation of the biological properties of a system in temporal logic will be used for the first time to build a new model coming from brand new real-life experiments. It will also be adapted to the challenges of the multi-scale approach used in this project, through developments of the abstraction and modularity concepts.