Inferring the connectivity of a regulatory network from mRNA quantification in Synechocystis PCC6803

A major task of contemporary biology is to understand and predict the functioning of regulatory networks. We use expression data to deduce the regulation network connecting the sigma factors of Synechocystis PCC6803, the most global regulators in bacteria. Synechocystis contains one group 1 (SigA) and four group 2 (SigB, SigC, SigD and SigE) sigma factors. From the relative abundance of the sig mRNA measured in the wild-type and the four group 2 sigma mutants, we derive a network of the influences of each sigma factor on the transcription of all other sigma factors. Internal or external stimuli acting on only one of the sigma factors will thus indirectly modify the expression of most of the others. From this model, we predict the control points through which the circadian time modulates the expression of the sigma factors. Our results show that the cross regulation between the group 1 and group 2 sigma factors is very important for the adaptation of the bacterium to different environmental and physiological conditions.