Servizio Comunitario di Informazione in materia di Ricerca e Sviluppo - CORDIS


The ability to summarize observations using explanatory and predictive theories is one of the greatest strengths of modern science. Theories, of more or less formal character, attempt to link observations together into some reproducible patterns. Systems biology uses integrative modeling of interactions of molecular elements to develop a more complete understanding of cellular mechanisms by studying the functions of intra- and inter-cellular molecular interactions that trigger and coordinate cellular events. Relevance of this discipline arises from the need not only to explain cellular systems but also to predict and control their behavior. The success of the approach relies heavily on the quality of the biological data. Unfortunately, the complexity of biochemical systems causes informative experimentation to be a time consuming and expensive task. As a result the currently available data report on biological systems measured only in a limited number of, not necessarily most informative, experimental conditions. The major aim of the project is to investigate the possibility of using mathematically designed experimental protocols to better understand signalling pathways of the immune system.
We have taken a two pronged approach to address the objectives of the project. Primarily we have been developing a theoretical methodology to allow efficient parameter estimation and guided experimental design of multi-parameter models. Secondly we have experimentally examined cellular responses of two of the major pathways of the immune system: the NF-κΒ and the JAK-STAT pathways. Currently, the experimental data are being integrated with the modelling approaches to provide insight into principles of cellular signaling.
Within the theoretical component of the project we have so far designed a method for manipulation of multi-parameter models that allows to predict a prior which model parameters can be uniquely determined from a specific experimental measurements. The proposed methodology provides a natural mathematical language to design biological experiments aimed at parameter estimation of relatively large models.
On the experimental side, we have performed a set of experiments that examined response of the NF-κB pathway to TNFα stimulation at the single cell level. The collected data constitute a comprehensive quantitative description of dynamical activation of the NF-κB pathway at the single cell level. The data have served to calibrate the model of the pathway as well as to examine the possibility to control the system using a microfuidic device.
The major theoretical result of the work performed so far is the method that allows to asses which parameters of a biological model can be estimated in a given biological experiment. The method allows to compare various experimentally available measurements and design most informative experiments.
The collected experimental data reveal the spectrum of possible responses of the NF-κB pathway and allowed us to calibrate the model. The model together with the experimental data will reveal to what extend the system can be controlled be external stimuli.
Results of the project are anticipated to contribute significantly to plug the gap between statistics and experimental technologies and help to move biological sciences in the “observe-explain-predict-control-design” cycle. The move towards the ability to integrate models with experimental data is necessary to design effective therapies and provide societies with the solutions not available so far.

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Life Sciences