G-protein-coupled receptors (GPCRs) have been shown to form dimers, but the relevance of this phenomenon in G-protein activation is not known. Among the large GPCR family, metabotropic glutamate (mGlu) receptors are constitutive dimers. Here we examined whether both heptahelical domains (HDs) are turned on upon full receptor activation. To that aim, we measured G-protein coupling efficacy of dimeric mGlu receptors in which one subunit bears specific mutations. We show that a mutation in the third intracellular loop (i3 loop) known to prevent Gprotein activation in a single subunit decreases coupling efficacy. However, when a single HD is blocked in its inactive state using an inverse agonist, 2-methyl-6-(phenylethynyl)pyridine (MPEP), no decrease in receptor activity is observed. Interestingly, in a receptor dimer in which the subunit that binds MPEP is mutated in its i3 loop, MPEP enhances agonist-induced activity, reflecting a 'better' activation of the adjacent HD. These data are consistent with a model in which a single HD is turned on upon activation of such homodimeric receptors and raise important issues in deciphering the functional role of GPCR dimer formation for G-protein activation.

An example of bacterium, which undergoes a complex development, is the genus of Streptomyces whose importance lies in their wide capacity to produce secondary metabolites, including antibiotics. In this work, a proteomic approach was applied to the systems study of germination as a transition from dormancy to the metabolically active stage. The protein expression levels were examined throughout the germination time course, the kinetics of the accumulated and newly synthesized proteins were clustered, and proteins detected in each group were identified. Altogether, 104 2DE gel images at 13 time points, from dormant state until 5.5 h of growth, were analyzed. The mass spectrometry identified proteins were separated into functional groups and their potential roles during germination were further assessed. The results showed that the full competence of spores to effectively undergo active metabolism is derived from the sporulation step, which facilitates the rapid initiation of global protein expression during the first 10 min of cultivation. Within the first hour, the majority of proteins were synthesized. From this stage, the full capability of regulatory mechanisms to respond to environmental cues is presumed. The obtained results might also provide a data source for further investigations of the process of germination.

HrdB in streptomycetes is a principal sigma factor whose deletion is lethal. This is also the reason why its regulon has not been investigated so far. To overcome experimental obstacles, for investigating the HrdB regulon, we constructed a strain whose HrdB protein was tagged by an HA epitope. ChIP-seq experiment, done in 3 repeats, identified 2137 protein-coding genes organized in 337 operons, 75 small RNAs, 62 tRNAs, 6 rRNAs and 3 miscellaneous RNAs. Subsequent kinetic modeling of regulation of protein-coding genes with HrdB alone and with a complex of HrdB and a transcriptional cofactor RbpA, using gene expression time series, identified 1694 genes that were under their direct control. When using the HrdB–RbpA complex in the model, an increase of the model fidelity was found for 322 genes. Functional analysis revealed that HrdB controls the majority of gene groups essential for the primary metabolism and the vegetative growth. Particularly, almost all ribosomal protein-coding genes were found in the HrdB regulon. Analysis of promoter binding sites revealed binding motif at the −10 region and suggested the possible role of mono- or di-nucleotides upstream of the −10 element.

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.