Project description:Legionella pneumophila is a gram-negative opportunistic human pathogen that infects and multiplies in a broad range of phagocytic protozoan and mammalian phagocytes. Based on the observation that small regulatory RNAs (sRNAs) play an important role in controlling virulence-related genes in several pathogenic bacteria, we attempted to test the hypothesis that sRNAs play a similar role in L. pneumophila. We used computational prediction followed by experimental verification to identify and characterize sRNAs encoded in the L. pneumophila genome. A 50-mer probe microarray was constructed to test the expression of predicted sRNAs in bacteria grown under a variety of conditions. This strategy successfully identified 22 expressed RNAs, out of which six were confirmed by northern blot and RACE. One of the identified sRNAs is highly expressed when the bacteria enter post exponential phase and computational prediction of its secondary structure reveals a striking similarity to the structure of 6S RNA, a widely distributed prokaryotic sRNA, known to regulate the activity of Ï70-containing RNAP. A 70-mer probe microarray was used to identify genes affected by L. pneumophila 6S RNA in stationary phase. The 6S RNA encoded by the ssrS gene positively regulates expression of genes encoding type IVB secretion system effectors, stress response genes such as groES and recA as well as many genes with unknown or hypothetical functions. Deletion of 6S RNA significantly reduced L. pneumophila intracellular multiplication in both protist and mammalian host cells, but had no detectable effect on growth in rich media. The 70-mer microarray representing all annotated ORFs of L. pneumophila has been previously described (Charpentier et al., 2008). RNA was extracted from ssrS mutant strain and the wild-type strain grown to PE phase. gDNA was used as a reference channel on each slides. Labelling of samples, hybridization strategy and data acquisition were performed as described in the Methods section. Local background was removed from spot signal intensity and normalization was carried out by calculating the fraction over the total signal intensity in both channel as previously described (Faucher et al., 2006). Signal levels that were lower than background in experiments and controls were filtered out. A total of six cDNA to reference ratios were recorded for each time point. Statistical analysis between mutant and wild-type strain was performed using unpaired one-tailed studentâs t-test. Genes were considered as differentially expressed if they demonstrated a ratio to control value of Â±2-fold with a p < 0.001.

Project description:Legionella pneumophila is a gram-negative opportunistic human pathogen that infects and multiplies in a broad range of phagocytic protozoan and mammalian phagocytes. Based on the observation that small regulatory RNAs (sRNAs) play an important role in controlling virulence-related genes in several pathogenic bacteria, we attempted to test the hypothesis that sRNAs play a similar role in L. pneumophila. We used computational prediction followed by experimental verification to identify and characterize sRNAs encoded in the L. pneumophila genome. A 50-mer probe microarray was constructed to test the expression of predicted sRNAs in bacteria grown under a variety of conditions. This strategy successfully identified 22 expressed RNAs, out of which six were confirmed by northern blot and RACE. One of the identified sRNAs is highly expressed when the bacteria enter post exponential phase and computational prediction of its secondary structure reveals a striking similarity to the structure of 6S RNA, a widely distributed prokaryotic sRNA, known to regulate the activity of Ï70-containing RNAP. A 70-mer probe microarray was used to identify genes affected by L. pneumophila 6S RNA in stationary phase. The 6S RNA encoded by the ssrS gene positively regulates expression of genes encoding type IVB secretion system effectors, stress response genes such as groES and recA as well as many genes with unknown or hypothetical functions. Deletion of 6S RNA significantly reduced L. pneumophila intracellular multiplication in both protist and mammalian host cells, but had no detectable effect on growth in rich media. A microarray was designed for the detection of 101 predicted sRNAs by using OligiWiz version 2.1.3 (Nielsen et al., 2003, Wernersson & Nielsen, 2005). The prokaryotic setting was used to design 50-mers probes located, when possible, at the 3â end of the predicted genes. Probes for 10 negative controls, representing 10 genes of the L. pneumophila Paris plasmid, were also designed. Probes (Illumina) were dissolved in 50% DMSO to a final concentration of 30 uM and printed in triplicate on UltraGAPS coated glass slides (Corning) using a PerkinElmer SpotArray microarray printer. Fifteen micrograms of total RNA was labelled during cDNA synthesis using Superscript II reverse transcriptase (Invitrogen) and amino-allyl dUTP (Sigma). Bacterial genomic DNA was used as the reference channel on each slide to allow comparison of each time point and different samples (Talaat et al., 2002). Five micrograms of genomic DNA (gDNA) was labelled with amino-allyl dUTP by using Klenow fragment and random primers (Invitrogen) at 37 Â°C for 18 h. DNA was subsequently coupled to the succinimidyl ester fluorescent dye AlexaFluor 546 (for cDNA) or Alexa Fluor 647 (for gDNA) (Invitrogen) following manufacturerâs protocols. Hybridization and data acquisition were performed as previously described (Hovel-Miner et al., 2009).Very low density array, like the sRNA microarray used here, cannot be normalised with common procedure like total intensity or lowess. Local background was removed from spot signal intensity and the noise signal was estimated by recording the average signal intensity of 10 negative controls printed on the chip. Normalisation of signal intensity was carried out by calculating the fold increase over the noise signal value. Correlation of replicates using this normalisation procedure was â¥ 0.95.

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