Analysis of control types in transcriptional regulation

• Applicant: Professor Dr. Marc-Thorsten Hütt
• Subject Area: Biochemistry
• Term: from 2010 to 2013
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 167242383

Transcriptional control of gene expression is essential for central biological processes including growth, differentiation and development. The current availability of high-throughput technology and bioinformatics approaches to complex systems provides an unprecedented opportunity to ask general questions on the organizational logic of transcriptional control. Independent lines of research over the last few years have focused on analyzing (1) the effect of DNA topology on global gene expression and (2) the imprint of the transcriptional regulatory network in gene expression profiles. From our perspective the system can employ these two types of control in different proportions under different experimental conditions. In addition, expression profiles can be thought of as evolutionarily shaped patterns matching the needs of metabolism. From all these constraints we attempt in this project to extract a consistent unifying control theory of transcriptional regulation. Using the classical model organism Escherichia coli and building up on our previous work we will experimentally study gene expression levels under variation of both types of control and develop mathematical tools for quantitatively assessing the importance of each control type in a given expression pattern. We will experimentally investigate the impact of mutations of structural proteins, the role of sigma factors and changes of RNA polymerase composition. On the theoretical side we will analyze the data using the concept of effective networks and appropriate null models. By translating binding site information into probability distributions of local DNA topological states we aim at predicting the patterns of changes of gene expression under defined changes of the system or the environment.

• DFG Programme: Research Grants
• Participating Person: Professor Dr. Georgi Muskhelishvili