The Silicon Cell:

a1. Aim

The long-term goal of the Silicon Cell (SiC) Consortium is the computation of Life at the cellular level on the basis of the complete genomic, transcriptomic, proteomic, metabolomic and cell-physiomic information that will become available in the forthcoming years. Completing this ambition will take more than a decade. This application concentrates on three major challenges, i.e. networks, space and time, and deals with systematic handling of the relevant data and results.

(i) Computational models of catabolism, signal transduction, gene-expression regulation, coupling between supramolecular structures and fluxes, and biochemical cycling.

(ii) Model integration to calculate system properties for two real cells (E. coli and S. cerevisiae).

(iii) Demonstration of the cellular bioinformatics approach: calculating without fitting.

(iv) Methodology for modularisation to accurate mesoscopic descriptions.

(v) Visualisation, systematic data access and a www resource for two real living cells.

We shall focus on three different, but interconnected dimensions of cell functioning, i.e. (i) the 'chemical and information dimension': networks of biochemical reactions and their regulation, (ii) space: gradients and dynamic structures in signal transduction and gene expression (chromatin), and (iii) biological time: coherent glycolytic and cell-cycle oscillations. Our work will build on already available experimental and theoretical expertise. The specific cases connect to the glucose entry into S. cerevisiae en E. coli, subsequent carbon and energy metabolism, up to their coupling to examples of signal transduction, gene expression regulation and cell-cycle. This work will be coupled to biological experiments carried out (a) in the research school BioCentrum Amsterdam (not part of this application, and for which funding is already available), and (b) world-wide in collaborating groups and through the open literature.

Different from most traditional modelling methods, this programme will always start from real experimental data that stem from molecular biology, biochemistry, physics and chemistry. Rather than aiming at an understanding of principles of function (as would be done by theoretical biology or physics) we shall 'merely' compute the implications of the molecular data for system behavior.

The present program is among the few that integrate all relevant information from various scientific fields (e.g. molecular biology, biochemistry, and physics) into a single model for cell function.

Until now bioinformatic approaches to the dynamics of cell function have remained 'limited' to categorization of all enzymes, to flux analysis delimitation of metabolic, to metabolic pathway identification, and to the computational biochemistry of isolated metabolic pathways at steady state. For the first time metabolic pathways, their regulation, signal transduction and structure-flux relations will be addressed in a single context, using computational biochemistry, i.e. calculating dynamic concentrations and process rates from molecular data.

The research program calculates from molecular biology (and physics) to cell function. Therewith it will generate knowledge and insight from large amounts of information. It integrates information from all relevant sources, from DNA through gene expression to metabolomics, including kinetic and physical chemical data. It calculates expected dynamic structures, functions and dynamics at the supramolecular level. It will result in two interactive computationally 'live' replica of significant parts of two living cells (one prokaryotic, one eukaryotic), an interactive system accessible to outside researchers for mining of the models. The Silicon Cell will become an international repository of all relevant molecular data. It will focus on regulatory and other networks of gene expression, signal transduction and complex biochemical pathways. The program will develop computational technologies for modeling cell processes and for integrating all the available molecular information into the model.

- cellular bioinformatics.

- computational biochemistry

- metabolic control analysis, regulation

-model validation and calibration

-dynamic structures

- mesoscopic/particle based

-partial differential equations in living cells

-functional modules