There has been an increasing interest in cyanobacteria because these photosynthetic organisms convert solar energy into biomass and because of their potential for the production of biofuels. However, the exploitation of cyanobacteria for bioengineering requires knowledge of their transcriptional organization. Using differential RNA sequencing, we have established a genome-wide map of 3,527 transcriptional start sites (TSS) of the model organism Synechocystis sp. PCC6803. One-third of all TSS were located upstream of an annotated gene; another third were on the reverse complementary strand of 866 genes, suggesting massive antisense transcription. Orphan TSS located in intergenic regions led us to predict 314 noncoding RNAs (ncRNAs). Complementary microarray-based RNA profiling verified a high number of noncoding transcripts and identified strong ncRNA regulations. Thus, ∼64% of all TSS give rise to antisense or ncRNAs in a genome that is to 87% protein coding. Our data enhance the information on promoters by a factor of 40, suggest the existence of additional small peptide-encoding mRNAs, and provide corrected 5′ annotations for many genes of this cyanobacterium. The global TSS map will facilitate the use of Synechocystis sp. PCC6803 as a model organism for further research on photosynthesis and energy research.gene expression regulation | promoter prediction | RNA polymerase

SUMMARY A substantial amount of antisense transcription is a hallmark of gene expression in eukaryotes. However, antisense transcription was first demonstrated in bacteria almost 50 years ago. The transcriptomes of bacteria as different as Helicobacter pylori , Bacillus subtilis , Escherichia coli , Synechocystis sp. strain PCC6803, Mycoplasma pneumoniae , Sinorhizobium meliloti , Geobacter sulfurreducens , Vibrio cholerae , Chlamydia trachomatis , Pseudomonas syringae , and Staphylococcus aureus have now been reported to contain antisense RNA (asRNA) transcripts for a high percentage of genes. Bacterial asRNAs share functional similarities with trans -acting regulatory RNAs, but in addition, they use their own distinct mechanisms. Among their confirmed functional roles are transcription termination, codegradation, control of translation, transcriptional interference, and enhanced stability of their respective target transcripts. Here, we review recent publications indicating that asRNAs occur as frequently in simple unicellular bacteria as they do in higher organisms, and we provide a comprehensive overview of the experimentally confirmed characteristics of asRNA actions and intimately linked quantitative aspects. Emerging functional data suggest that asRNAs in bacteria mediate a plethora of effects and are involved in far more processes than were previously anticipated. Thus, the functional impact of asRNAs should be considered when developing new strategies against pathogenic bacteria and when optimizing bacterial strains for biotechnology.

CopraRNA (Comparative prediction algorithm for small RNA targets) is the most recent asset to the Freiburg RNA Tools webserver. It incorporates and extends the functionality of the existing tool IntaRNA (Interacting RNAs) in order to predict targets, interaction domains and consequently the regulatory networks of bacterial small RNA molecules. The CopraRNA prediction results are accompanied by extensive postprocessing methods such as functional enrichment analysis and visualization of interacting regions. Here, we introduce the functionality of the CopraRNA and IntaRNA webservers and give detailed explanations on their postprocessing functionalities. Both tools are freely accessible at http://rna.informatik.uni-freiburg.de.

Significance This study presents a unique approach (CopraRNA, for Comparative Prediction Algorithm for sRNA Targets) towards reliably predicting the targets of bacterial small regulatory RNAs (sRNAs). These molecules are important regulators of gene expression. Their detailed analysis thus far has been hampered by the lack of reliable algorithms to predict their mRNA targets. CopraRNA integrates phylogenetic information to predict sRNA targets at the genomic scale, reconstructs regulatory networks upon functional enrichment and network analysis, and predicts the sRNA domains for target recognition and interaction. Our results demonstrate that CopraRNA substantially improves the bioinformatic prediction of target genes and opens the field for the application to nonmodel bacteria.

The molecular and physiological mechanisms involved in the transition of microbial cells from a resting state to the active vegetative state are critically relevant for solving problems in fields ranging from microbial ecology to infection microbiology. Cyanobacteria that cannot fix nitrogen are able to survive prolonged periods of nitrogen starvation as chlorotic cells in a dormant state. When provided with a usable nitrogen source, these cells re-green within 48 hr and return to vegetative growth. Here we investigated the resuscitation of chlorotic Synechocystis sp. PCC 6803 cells at the physiological and molecular levels with the aim of understanding the awakening process of a dormant bacterium. Almost immediately upon nitrate addition, the cells initiated a highly organized resuscitation program. In the first phase, they suppressed any residual photosynthetic activity and activated respiration to gain energy from glycogen catabolism. Concomitantly, they restored the entire translational apparatus, ATP synthesis, and nitrate assimilation. After only 12-16 hr, the cells re-activated the synthesis of the photosynthetic apparatus and prepared for metabolic re-wiring toward photosynthesis. When the cells reached full photosynthetic capacity after ∼48 hr, they resumed cell division and entered the vegetative cell cycle. An analysis of the transcriptional dynamics during the resuscitation process revealed a perfect match to the observed physiological processes, and it suggested that non-coding RNAs play a major regulatory role during the lifestyle switch in awakening cells. This genetically encoded program ensures rapid colonization of habitats in which nitrogen starvation imposes a recurring growth limitation.