Specificity and robustness in transcription control networks - PubMed (original) (raw)
Specificity and robustness in transcription control networks
Anirvan M Sengupta et al. Proc Natl Acad Sci U S A. 2002.
Abstract
Recognition by transcription factors of the regulatory DNA elements upstream of genes is the fundamental step in controlling gene expression. How does the necessity to provide stability with respect to mutation constrain the organization of transcription control networks? We examine the mutation load of a transcription factor interacting with a set of n regulatory response elements as a function of the factor/DNA binding specificity and conclude on theoretical grounds that the optimal specificity decreases with n. The predicted correlation between variability of binding sites (for a given transcription factor) and their number is supported by the genomic data for Escherichia coli. The analysis of E. coli genomic data was carried out using an algorithm suggested by the biophysical model of transcription factor/DNA binding. Complete results of the search for candidate transcription factor binding sites are available at http://www.physics.rockefeller.edu/\~boris/public/search\_ecoli.
Figures
Figure 1
Schematic model of transcription control. _F_s are active transcription factor proteins, _x_s are response element subsequences upstream of the coding regions of the genes, G. Arrows indicate regulatory interactions.
Figure 2
Typical energy histogram, ρ(E), for a transcription factor interacting with a random DNA subsequences. In equilibrium, strings corresponding to energies below the chemical potential, μ (set by factor concentration), bind the factor with high probability given explicitly by + 1]−1.
Figure 3
Response elements (dots) and factor binding subsets (disks) in sequence space. RE located within a disk binds the corresponding factor. Black dots lying outside the discs represent potential cis-regulatory sites, which must not bind transcription factors in order to avoid interference with transcription control. Arrows represent random changes in the sequence of REs (and of potential cis-regulatory sites) due to mutation.
Figure 4
The number of (candidate) response element sites, n, obtained from the E. coli genomic data versus factor binding specificity σ (circles). Note that exp(−σ) is the fraction of random sequences which bind the factor. Red line: expected number of binding sites for the random sequence background (reproducing the base frequency and nearest neighbor correlations of the noncoding segments). Green line: asymptotic fit to the predicted specificity/pleiotropy relation, Eq. 3.
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