Dissecting the logical types of network control in gene expression profiles
- Equal contributors
1 Computational Systems Biology Group, Jacobs University, Campus Ring 1, 28759 Bremen, Germany
2 Molecular Genetics Group, Jacobs University, Campus Ring 1, 28759 Bremen, Germany
3 Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum München – German Research Center for Environmental Health, 85764 Neuherberg, Germany
BMC Systems Biology 2008, 2:18 doi:10.1186/1752-0509-2-18Published: 19 February 2008
In the bacterium Escherichia coli the transcriptional regulation of gene expression involves both dedicated regulators binding specific DNA sites with high affinity and also global regulators – abundant DNA architectural proteins of the bacterial nucleoid binding multiple sites with a wide range of affinities and thus modulating the superhelical density of DNA. The first form of transcriptional regulation is predominantly pairwise and specific, representing digitial control, while the second form is (in strength and distribution) continuous, representing analog control.
Here we look at the properties of effective networks derived from significant gene expression changes under variation of the two forms of control and find that upon limitations of one type of control (caused e.g. by mutation of a global DNA architectural factor) the other type can compensate for compromised regulation. Mutations of global regulators significantly enhance the digital control, whereas in the presence of global DNA architectural proteins regulation is mostly of the analog type, coupling spatially neighboring genomic loci. Taken together our data suggest that two logically distinct – digital and analog – types of control are balancing each other.
By revealing two distinct logical types of control, our approach provides basic insights into both the organizational principles of transcriptional regulation and the mechanisms buffering genetic flexibility. We anticipate that the general concept of distinguishing logical types of control will apply to many complex biological networks.