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Kröger, Carsten; Dillon, Shane C; Cameron, Andrew D. S; Papenfort, Kai; Sivasankaran, Sathesh K; Hokamp, Karsten; Chao, Yanjie; Sittka, Alexandra; Hébrard, Magali; Händler, Kristian; Colgan, Aoife; Leekitcharoenphon, Pimlapas; Langridge, Gemma C; Lohan, Amanda J; Loftus, Brendan; Lucchini, Sacha; Ussery, David W; Dorman, Charles J; Thomson, Nicholas R; Vogel, Jörg; Hinton, Jay C. D
Proceedings of the National Academy of Sciences, 05/2012, Letnik: 109, Številka: 20Journal Article
More than 50 y of research have provided great insight into the physiology, metabolism, and molecular biology of Salmonella enterica serovar Typhimurium (S. Typhimurium), but important gaps in our knowledge remain. It is clear that a precise choreography of gene expression is required for Salmonella infection, but basic genetic information such as the global locations of transcription start sites (TSSs) has been lacking. We combined three RNA-sequencing techniques and two sequencing platforms to generate a robust picture of transcription in S. Typhimurium. Differential RNA sequencing identified 1,873 TSSs on the chromosome of S. Typhimurium SL1344 and 13% of these TSSs initiated antisense transcripts. Unique findings include the TSSs of the virulence regulators phoP, slyA, and invF. Chromatin immunoprecipitation revealed that RNA polymerase was bound to 70% of the TSSs, and two-thirds of these TSSs were associated with σ70 (including phoP, slyA, and invF) from which we identified the –10 and –35 motifs of σ70-dependent S. Typhimurium gene promoters. Overall, we corrected the location of important genes and discovered 18 times more promoters than identified previously. S. Typhimurium expresses 140 small regulatory RNAs (sRNAs) at early stationary phase, including 60 newly identified sRNAs. Almost half of the experimentally verified sRNAs were found to be unique to the Salmonella genus, and <20% were found throughout the Enterobacteriaceae. This description of the transcriptional map of SL1344 advances our understanding of S. Typhimurium, arguably the most important bacterial infection model.
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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