Model reduction, experimental validation, and control for the gene expression machinery in E. coli – GeMCo

GeMCo is a multidisciplinary research project directed at studying, understanding the basic principles and interaction motifs underlying information processing at the cellular level, with the aim of controlling genetic regulation. To study how cells regulate and adapt to a changing environment, the field of synthetic biology has opened up a new generation of fundamental research by trying to redesign natural systems or create novel systems from scratch. Along these lines, we propose to focus on the gene expression machinery of the bacterium Escherichia coli, with the aim of controlling the growth rate of the cells. E. coli is a model organism that is easy to manipulate and much knowledge is available about its regulatory networks. While many experimental and theoretical studies have addressed the biological regulation of the growth rate, no attempts have been made to modify these control mechanisms in a directed way. In addition to the experimental difficulties, one of the main obstacles is theoretical: no control strategies with adequate biological constraints exist for such systems.
Mathematical modeling and analysis are essential components of systems and synthetic biology, as they help understanding the consequences of (changes in) the network of interactions on the dynamical behavior of the system. Thus, the goals of the present proposal are: (i) construct a detailed kinetic mathematical model of the network controlling the gene expression machinery in E. coli, (ii) identify the parameters and validate the model by comparing predictions with experimental data, (iii) develop appropriate mathematical control strategies to re-design the network structure and elicit a new global behavior, and (iv) experimentally validate the behavior of the re-designed system.
At the theoretical level, we propose to develop model reduction methods and explore control theoretical strategies specifically devoted to deal with the various constraints imposed by biological systems. Model reduction is aimed at finding smaller subsystems, possibly motifs, that can be more easily compared with data and facilitate parameter identification. These subsystems will also be analyzed from the control point of view, to generate control laws which may then be incorporated into the more complex global system.
The mathematical methodologies to be used in GeMCo echo the currently available experimental techniques. Quantitative and smooth measurements of gene expression can be obtained through the use of green fluorescence reporter genes. This justifies the use of continuous ordinary differential equations for model construction and validation. A standard procedure to control the transcription rate of a gene involves the construction of plasmid containing an inducer to that gene, so that its transcription rate can be increased by a certain factor simply by adding an amount of the corresponding inducer molecules to the system. This leads only to a qualitative knowledge of the system's inputs, and therefore justifies the choice of piecewise affine differential models to explore new control strategies.
The GeMCo consortium consists of three groups, with a large experience in multidisciplinary research, that cover the entire spectrum of competences needed to tackle the project: mathematical analysis and control of dynamical systems, modeling and identification of biological regulatory networks, microbiology and molecular biology. The methods to be developed extend existing approaches in applied mathematics and control theory into novel directions, adapted to the particularities of biological systems. They are intended to be generic tools, but their applicability will be tested on a specific biological modelling and control problem. The outcome of the application of these methods is interesting in its own right, as it presents a novel approach to a fundamental biological and biotechnological problem, the control of the growth rate of the cell.