Understanding the genome-wide transcription response to varying cAMP levels using phenomenological models in bacteria

Attempts to understand gene regulation by global transcription factors (TF) have largely been limited to expression studies under binary conditions of presence and absence of the TF. Studies addressing genome-wide transcriptional responses to changing TF concentration at high resolution are lacking. Here, we create a dataset containing the entire E.coli transcriptome as it responds to 10 different cAMP concentrations spanning the biological range. We use the Hills model to accurately summarise individual gene responses into 3 intuitively understandable parameters - k, n and Emax reflecting the midpoint of dynamic range, non-linearity and sensitivity of a gene. cAMP-regulated genes show a small dynamic range with midpoints centred around wild-type cAMP concentrations, with genes activating in a switch-like fashion. Using this approach we show that cAMP-CRP affinity at promoters is well correlated to the sensitivity(Emax) of genes but not to the midpoints of dynamic range(k). Finally, genes belonging to different functional classes are tuned to different k, n and Emax. We show phenomenological models to be a better alternative for studying gene expression trends compared to classical clustering methods with the phenomenological constants providing greater insights into how genes are tuned in a regulatory network.