The UNICELLSYS Project

Eukaryotic unicellular organism biology – systems biology of the control of cell growth and proliferation

The overall objective of UNICELLSYS is a quantitative understanding of fundamental characteristics of eukaryotic unicellular organism biology: how cell growth and proliferation are controlled and coordinated by extracellular and intrinsic stimuli.

Achieving an understanding of the principles with which bio-molecular systems function requires integrating quantitative experimentation with simulations of dynamic mathematical models. UNICELLSYS brings together a consortium of leading European experimental and computational systems biologists tol study cell growth and proliferation at the levels of cell population, single cell, cellular network, largescale dynamic systems and functional module.

Building computational reconstructions and dynamic models involves different precise quantitative measurements as well as complementary approaches of mathematical modelling. A major challenge is the generation of comprehensive dynamic models of the entire control system of cell growth and proliferation, which requires integration of smaller sub-models and reduction of complexity. Implementation of the models will allow observing responses to altered growth conditions zooming in seamlessly from populations consisting of cells of different replicative age and cell cycle stage via genome-wide molecular networks, large dynamic systems to detailed functional modules. Employing computational simulations combined with experimentation will allow discovering new and emerging principles of bio-molecular organisation and analysing the control mechanisms of cell growth and proliferation.

The project will deliver new knowledge on fundamental eukaryotic biology as well as tools for quantitative experimentation and modelling. Detailed plans for dissemination and exploitation will ensure that UNICELLSYS will have major impact on the development of Systems Biology in Europe ensuring a competitive advantage of Europe in dynamic quantitative modelling of biomolecular processes.