The formation of root nodules and arbuscular mycorrhizal (AM) roots is controlled by a common signaling pathway including the calcium/calmodulin-dependent kinase Doesn't Make Infection3 (DMI3). While nodule initiation by lipochitooligosaccharide (LCO) Nod factors is well characterized, diffusible AM fungal signals were only recently identified as sulfated and nonsulfated LCOs. Irrespective of different outcomes, the perception of symbiotic LCOs in Medicago truncatula is mediated by the LysM receptor kinase M. truncatula Nod factor perception (MtNFP). To shed light on transcriptional responses toward symbiotic LCOs and their dependence on MtNFP and Ca 2+ signaling, we performed genome-wide expression studies of wild-type, Nod-factorperception mutant1, and dmi3 mutant roots challenged with Myc-and Nod-LCOs. We show that Myc-LCOs lead to transient, quick responses in the wild type, whereas Nod-LCOs require prolonged incubation for maximal expression activation. While Nod-LCOs are most efficient for an induction of persistent transcriptional changes, sulfated Myc-LCOs are less active, and nonsulfated Myc-LCOs display the lowest capacity to activate and sustain expression. Although all symbiotic LCOs upregulated a common set of genes, discrete subsets were induced by individual LCOs, suggesting common and specific functions for these in presymbiotic signaling. Surprisingly, even sulfated fungal Myc-LCOs and Sinorhizobium meliloti NodLCOs, having very similar structures, each elicited discrete subsets of genes, while a mixture of both Myc-LCOs activated responses deviating from those induced by single treatments. Focusing on the precontact phase, we identified signalingrelated and transcription factor genes specifically up-regulated by Myc-LCOs. Comparative gene expression studies in symbiotic mutants demonstrated that transcriptional reprogramming by AM fungal LCOs strictly depends on MtNFP and largely requires MtDMI3.

The lexA gene of Corynebacterium glutamicum ATCC 13032 was deleted to create the mutant strain C. glutamicum NJ2114, which has an elongated cell morphology and an increased doubling time. To characterize the SOS regulon in C. glutamicum, the transcriptomes of NJ2114 and a DNA-damage-induced wild-type strain were compared with that of a wild-type control using DNA microarray hybridization. The expression data were combined with bioinformatic pattern searches for LexA binding sites, leading to the detection of 46 potential SOS boxes located upstream of differentially expressed transcription units. Binding of a hexahistidyl-tagged LexA protein to 40 double-stranded oligonucleotides containing the potential SOS boxes was demonstrated in vitro by DNA band shift assays. It turned out that LexA binds not only to SOS boxes in the promoteroperator region of upregulated genes, but also to SOS boxes detected upstream of downregulated genes. These results demonstrated that LexA controls directly the expression of at least 48 SOS genes organized in 36 transcription units. The deduced genes encode a variety of physiological functions, many of them involved in DNA repair and survival after DNA damage, but nearly half of them have hitherto unknown functions. Alignment of the LexA binding sites allowed the corynebacterial SOS box consensus sequence TcGAA(a/c)AnnTGTtCGA to be deduced. Furthermore, the common intergenic region of lexA and the differentially expressed divS-nrdR operon, encoding a cell division suppressor and a regulator of deoxyribonucleotide biosynthesis, was characterized in detail. Promoter mapping revealed differences in divS-nrdR expression during SOS response and normal growth conditions. One of the four LexA binding sites detected in the intergenic region is involved in regulating divS-nrdR transcription, whereas the other sites are apparently used for negative autoregulation of lexA expression.

Background: The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions.

No abstract