Schmidt, P.; Brandt, D.; Busche, T.; Kalinowski, J. Characterization of Bacterial Transcriptional Regulatory Networks in Escherichia coli through Genome-Wide In Vitro Run-Off Transcription/RNA-seq (ROSE). Microorganisms2023, 11, 1388.
Schmidt, P.; Brandt, D.; Busche, T.; Kalinowski, J. Characterization of Bacterial Transcriptional Regulatory Networks in Escherichia coli through Genome-Wide In Vitro Run-Off Transcription/RNA-seq (ROSE). Microorganisms 2023, 11, 1388.
Schmidt, P.; Brandt, D.; Busche, T.; Kalinowski, J. Characterization of Bacterial Transcriptional Regulatory Networks in Escherichia coli through Genome-Wide In Vitro Run-Off Transcription/RNA-seq (ROSE). Microorganisms2023, 11, 1388.
Schmidt, P.; Brandt, D.; Busche, T.; Kalinowski, J. Characterization of Bacterial Transcriptional Regulatory Networks in Escherichia coli through Genome-Wide In Vitro Run-Off Transcription/RNA-seq (ROSE). Microorganisms 2023, 11, 1388.
Abstract
We developed and applied a method for characterizing bacterial promoters genome-wide by in vitro transcription coupled to transcriptome sequencing specific for native 5’-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 E. coli RNAP holoenzyme (including σ70) and yielded 3,226 transcription start sites, 2,167 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.
Biology and Life Sciences, Biochemistry and Molecular Biology
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