Interplay between network structures, regulatory modes and sensing mechanisms of transcription factors in the transcriptional regulatory network of E. coli.

Though the bacterial transcription regulation apparatus is distinct in terms of several structural and functional features from its eukaryotic counterpart, the gross structure of the transcription regulatory network (TRN) is believed to be similar in both superkingdoms. Here, we explore the fine structure of the bacterial TRN and the underlying "co-regulatory network" (CRN) to show that despite the superficial similarities to the TRN of the eukaryotic model organism yeast, the bacterial networks display entirely different organizational principles. In particular unlike in eukaryotes, hubs of the bacterial networks are both global regulators and integrators of diverse disparate transcriptional responses. These and other organizational differences might correlate with the fundamental differences in gene and promoter organization in the two superkingdoms, especially the presence of operons and regulons in bacteria. Further we explored to find the interplay, if any, between network structures, mode of regulatory interactions and signal sensing of transcription factors (TFs) in shaping up the bacterial transcriptional regulatory responses. For this purpose, we first classified TFs according to their regulatory mode (activator, repressor or dual regulator) and sensory mechanism (one-component systems responding to internal or external signals, TFs from two-component systems and chromosomal structure modifying TFs) in the bacterial model organism Escherichia coli and then we studied the overall evolutionary optimization of network structures. The incorporation of TFs in different hierarchical elements of the TRN appears to involve on a multi-dimensional selection process depending on regulatory and sensory modes of TFs in motifs, co-regulatory associations between TFs of different functional classes and transcript half-lives. As a result it appears to have generated circuits that allow intricately regulated physiological state changes. We identified the biological significance of most of these optimizations, which can be further used as the basis to explore similar controls in other bacteria. We also show that, though on the larger evolutionary scale, unrelated TFs have evolved to become hubs, within lineages like gamma-proteobacteria there is strong tendency to retain hubs, as well as certain higher-order network modules that have emerged through lineage specific paralog duplications.