Project Details
Projekt
The bacterial chemotaxis pathway - an optimal designed information processing network?
Subject Area
Electronic Semiconductors, Components and Circuits, Integrated Systems, Sensor Technology, Theoretical Electrical Engineering
Term
from 2010 to 2013
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 149300562
Living cells have developed sophisticated mechanisms to adapt to availability of specic nutrients, which are essential for survival in competitive environments. Within the microbial world, carbon catabolite repression is the most signicant response to nutrient availability. It results in hierarchical metabolization of the preferred (rapidly metabolizable) carbon sources, in order to maximize the growth rate. This is usually achieved through inhibition of synthesis of proteins involved in transport and/or catabolism of carbon sources other than the preferred one. The drawback of this regulation is a significant time span of reduced growth rate (diauxic shift), during which transporters and enzymes for less favored carbon sources have to be synthesized once the preferred carbon source has been exhausted. Under which conditions carbon catabolite repression provides an evolutionary benefit and what is the critical growth rate that distinguishes preferred and non-preferred carbon sources of a given organism is still unclear. To address this question we employ an information theoretic approach that models benefit and cost of carbon source utilization as a function of the growth rate. We propose that carbon catabolite repression is the consequence of a selective pressure that maximizes the mutual information between fluctuating environmental conditions and cellular response under energetic constraints. That carbon catabolite repression is a generally utilized strategy among living cells follows from that fact that it is observed across taxa, employing very different biomolecular realizations. The selective advantage of carbon catabolite repression and of the associated gene regulatory strategy will be measured in the model organism E. coli, and the underlying regulatory mechanisms will be characterized in greater quantitative detail.
DFG Programme
Priority Programmes
