Project description:DNA microarray analysis of genes regulated by the alternative sigma factor, sigma 32 (rpoH). Sigma 32-dependent genes were initially identified by comparing a wild type (wt) E. coli K-12 strain that has a low level of sigma 32, with a strain over-expressing sigma 32 (following induction of rpoH from an inducible promoter by IPTG). We monitored changes in gene expression in 4 separate time-courses. Because sigma 32 is negatively regulated, its activity decreases 10 min after overexpression. Consequently, to identify genes regulated by sigma 32 we analyzed the expression data for 10 min after overexpression using SAM (Statistical Analysis of Microarrays). We identified 105 genes organized in 66 separate transcription units. This study is detailed in Nonaka et al 2006 (submitted). Keywords: time course
Project description:This study examined the genes under the control of sigma32 in E. coli by moderate induction of a plasmid-borne rpoH gene under defined steady-state growth condition. Samples were taken from culture at mid log phase (OD=0.2) before or 5 minutes, 10 minutes or 15 minutes after induction. Samples were then RNA-stabilized using Qiagen RNAProtect Bacterial Reagent (Qiagen). Total RNA was then isolated using MasterPure kits (Epicentre Technologies). Purified RNA was reverse-transcribed to cDNA, labeled and hybridized to Affymetrix GeneChip E. coli Antisense Genome Arrays as recommended in the technical manual (www.affymetrix.com). Meanwhile, we measured the protein level of sigma32 during the time course. The changes of some sigma32 –dependent genes were also determined in a DnaK null mutant to examine the anti- sigma32 function of DnaK. Keywords = sigma factor Keywords = regulon Keywords = microarray Keywords = Western blot Keywords = E. coli Keywords = anti-sigma factor Keywords: time-course
Project description:When performed at single bp resolution, the genome-wide location, occupancy level, and structural organization of DNA binding proteins provides mechanistic insights into genome regulation. Here we use ChIP-exo to provide the first high resolution view of the epigenomic organization of the E. coli transcription machinery and nucleoid structural proteins when cells are growing exponentially and upon rapid reprogramming (acute heat shock). We suggest that indirect readout of DNA shape at the flanks of cognate motifs provide major contributions to site specificity at promoter positions -35/-24 and -10/-12. We examined the site specificity of three sigma factors (RpoD/70, RpoH/32, and RpoN/54), RNA polymerase (RNAP or RpoA, B, C) and two nucleoid proteins (Fis and IHF). Our results confirm and refine reports that RpoD binds most annotated promoters, whereas RpoH and RpoN bind a much smaller subset, each through their cognate motifs. However, only upon heat shock does RpoH becomes active for RNAP recruitment. In contrast, upon heat shock RpoD remains active at its cognate promoters (including at heat shock genes), whereas RpoN remains inactive at its cognate promoters. RpoN binds ~1,000 non-annotated RpoN motifs, which may reflect a large number of condition-specific transcription units. Occupancy patterns of sigma factors and RNAP suggest a common promoter recruitment mechanism that differs from the long-standing views that sigma and RNAP are co-recruited as a complex, and also simultaneously dissociate from promoters. Our findings suggest that sigma factors are recruited and/or maintained at most promoters via an RNAP-independent mechanism. When RNAP arrives, it dwells for a relatively short time before clearing the promoter, leaving sigma behind. Taken together these findings add new dimensions to how sigma factors achieve promoter specificity through DNA sequence and shape and redefine mechanistic steps in regulated promoter assembly in E. coli.
Project description:The bacterial heat-shock response is regulated by the alternative sigma factor sigma 32 (RpoH), which responds to misfolded protein stress and directs the RNA polymerase to the promoterss for genes required for protein refolding or degradation. In P. aeruginosa, RpoH is essential for viability under laboratory growth conditions. Here, we used a transcriptomics approach to identify the genes of the RpoH regulon, including RpoH-regulated genes that are essential for P. aeruginosa. We placed the rpoH gene under control of the arabinose inducible PBAD promoter, then deleted the chromosomal rpoH allele. This allowed transcriptomic analysis of the RpoH regulon following a short up-shift in the cellular concentration of RpoH by arabinose addition, in the absence of a sudden increase in temperature. The P. aeruginosa ∆rpoH (PBAD-rpoH) strain grew in the absence of arabinose, indicating that some rpoH expression occurs without arabinose-induction. When arabinose was added, the rpoH mRNA abundance of P. aeruginosa ∆rpoH (PBAD-rpoH) measured by RT-qPCR increased fivefold within 15 min of arabinose addition. Whole genome transcriptome results showed that P. aeruginosa genes required for protein repair or degradation are induced by increased RpoH levels, and that many of the genes induced by RpoH are essential for P. aeruginosa growth. Other stress response genes induced by RpoH are involved in nucleic acid damage and repair and in amino acid metabolism. Annotation of the hypothetical proteins under RpoH control included proteins that may play a role in antibiotic resistances and in non-ribosomal peptide synthesis. The P. aeruginosa ∆rpoH (PBAD-rpoH) strain is impaired in its ability to survive during starvation compared to the wild-type strain. P. aeruginosa ∆rpoH (PBAD-rpoH) also has increased sensitivity to aminoglycoside antibiotics, but not to other classes of antibiotics, whether cultured planktonically or in biofilms. The enhanced aminoglycoside resistance of the mutant strain may be due to indirect effects, such as the build-up of toxic misfolded proteins, or to the direct effect of genes such as aminoglycoside acetyl transferases that are regulated by RpoH. Overall, the results demonstrate that RpoH regulates genes that are essential for viability of P. aeruginosa, that it protects P. aeruginosa from damage from aminoglycoside antibiotics, and that it is required for survival during nutrient limiting conditions. We used Affymetrix microarrays to characterize the RpoH regulon in P. aeruginosa. Using the P. aeruginosa ∆rpoH strain with rpoH under control of the PBAD promoter, we were able to perform transcriptomic analysis of genes induced by a sudden increase (15 min) in the cellular concentration of RpoH, independent from a sudden increase in temperature.
Project description:These data represent the ratios of charged to total tRNA for E. coli auxotrophic strain CP78 during starvation for leucine over a time course of 32 minutes. Keywords: time-course
Project description:DNA microarray analysis of genes regulated by the alternative sigma factor, sigma E (rpoE). Sigma E-dependent genes were initially identified by comparing a wild type (wt) E. coli K-12 strain that has a low level of sigma E, with a strain over-expressing sigma E (following induction of rpoE from an inducible promoter by IPTG). We monitored changes in gene expression in 4 separate time-courses after induction and used SAM (Statistical Analysis of Microarrays) to identify 75 significantly induced and 8 significantly repressed genes. Some of these genes are part of operons in which other gene members were clearly induced but were not marked as significant in our strict selection criteria. Therefore, to fully describe the sigma E regulon we expanded this set by using the statistics from SAM to analyze the reproducibility and significance of the expression ratios of all the genes adjacent to and in the same orientation as the highly significant genes. This gave 96 genes organized in 50 sigma E-dependent transcription units (TUs), of which 42 were induced and 8 were repressed. This study is detailed in Rhodius et al 2006 (PLoS Biol 4(1): e2) Keywords: time course
Project description:cDNA microarray analysis to identify genes regulated by the RNA chaperone, Hfq. Four experiments were performed: 1/ Hfq+ vs Hfq- strains. 269 significantly differentially regulated genes were identified by SAM (Statistical Analysis of Microarrays), of which 120 changed more than 1.5 fold (48 increased and 72 decreased in hfq-). Amongst other genes, these experiments identified significant regulation of the sigma E and sigma 32 regulons. However, only genes induced by sigma E were similarly induced in hfq-; 8 operons repressed by sigma E were not repressed in hfq-. 2/ wt vs delta rseA. RseA is the antisigma factor for sigmaE. This comparison results in elevated steady-state levels of sigma E, and confirmed induction and repression of target regulon members. 3/ hfq+ vs hfq+ rpoE overexpression. RpoE encoding sigma E was overexpressed in an hfq+ background, confirming normal regulation of the sigma E regulon. 4/ hfq+ vs hfq- rpoE overexpression. Sigma E was overexpressed in an hfq- background. This demonstrated that 8 operons normally repressed by sigma E require hfq for this repression. The simple conclusion is that sigma E regulates small RNAs that, together with Hfq, bind target mRNAs and results in their rapid degradation. This study is detailed in Guisbert et al 2007 (J Bacteriol, 189:1963-73) Keywords: Genetic modification