Characterization of Bacterial Transcriptional Regulatory Networks in Escherichia coli through Genome-Wide In Vitro Run-Off Transcription/RNA-seq (ROSE)

The global characterization of transcriptional regulatory networks almost exclusively uses in vivo conditions, thereby providing a snapshot on multiple regulatory interactions at the same time. To complement these approaches, we developed and applied a method for characterizing bacterial promoters genome-wide by in vitro transcription coupled to transcriptome sequencing specific for native 5 & PRIME;-ends of transcripts. This method, called ROSE (run-off transcription/RNA-sequencing), only requires chromosomal DNA, ribonucleotides, RNA polymerase (RNAP) core enzyme, and a specific sigma factor, recognizing the corresponding promoters, which have to be analyzed. ROSE was performed on E. coli K-12 MG1655 genomic DNA using Escherichia coli RNAP holoenzyme (including & sigma;70) and yielded 3226 transcription start sites, 2167 of which were also identified in in vivo studies, and 598 were new. Many new promoters not yet identified by in vivo experiments might be repressed under the tested conditions. Complementary in vivo experiments with E. coli K-12 strain BW25113 and isogenic transcription factor gene knockout mutants of fis, fur, and hns were used to test this hypothesis. Comparative transcriptome analysis demonstrated that ROSE could identify bona fide promoters that were apparently repressed in vivo. In this sense, ROSE is well-suited as a bottom-up approach for characterizing transcriptional networks in bacteria and ideally complementary to top-down in vivo transcriptome studies.

Automated summary

A method called ROSE was developed for characterizing bacterial promoters genome-wide using in vitro transcription coupled to transcriptome sequencing. ROSE identified 3226 transcription start sites in E. coli K-12 MG1655 genomic DNA, with 2167 also identified in in vivo studies and 598 being new. In vivo experiments confirmed that ROSE could identify repressed promoters not detected in in vivo experiments. Therefore, ROSE is a complementary method to study bacterial transcriptional networks and can identify promoters not captured by in vivo transcriptome studies.