Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Glycerol metabolism and PrfA activity in Listeria monocytogenes

ABSTRACT: Listeria monocytogenes is able to efficiently utilize glycerol as carbon source. In a defined minimal medium the growth rate is similar (during balanced growth) in presence of glycerol as in presence of glucose or cellobiose. Comparative transcriptome analyses of L. monocytogenes showed in the presence of glycerol (compared to glucose and/or cellobiose) high transcriptional upregulation of the known genes involved in glycerol uptake and metabolism (glpFK, glpD). Expression of the genes encoding a second putative glycerol uptake facilitator (GlpF-2) and a second putative glycerol kinase (GlpK-2) was less enhanced under these conditions. GlpK-1 but not GlpK-2 was essential for glycerol catabolism in L. monocytogenes under extracellular conditions, while loss of GlpK-1 affected replication in Caco-2 cells less than loss of GlpK-2 and GlpD. Additional genes whose transcription was higher in presence of glycerol than in presence of glucose and cellobiose included those for two dihydroxyacetone (Dha) kinases and many genes that are under carbon catabolite repression (CCR) control. Transcriptional down-regulation in the presence of glycerol (compared to glucose and cellobiose) was observed for several genes and operons that are positively regulated by glucose, including genes involved in glycolysis, N-metabolism and biosynthesis of branched chain amino acids. The highest transcriptional up-regulation was observed for all PrfA-dependent genes during early and late logarithmic growth in glycerol. Under these conditions a low level of HPr-Ser-P and a high level of HPr-His-P was present in the cells, suggesting that all EIIA (B) components of the PTS permeases expressed will be phosphorylated. These and other data reported suggest that the phosphorylation state of PTS permeases correlates with PrfA activity. Keywords: Response of Listeria monocytogenes to different carbon sources A total of four independently isolated RNA samples from each condition at each growth phase were used for the analysis. RNA from two isolations were pooled and hybridized onto two microarray slides with dye swap. Another two microarray slides were hybridized using the same principle. In total, we used four RNAs and four microarray slides to generate 16 replicate expression values for each combination except for the comparison between glucose and cellobiose, phase B where data generated from three microarray slides were used for further analysis

ORGANISM(S): Listeria monocytogenes

SUBMITTER: Biju Joseph

PROVIDER: E-GEOD-11459 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Glycerol metabolism and PrfA activity in Listeria monocytogenes.

Joseph Biju B Mertins Sonja S Stoll Regina R Schär Jennifer J Umesha Kanasinakatte Rudrappa KR Luo Qin Q Müller-Altrock Stefanie S Goebel Werner W

Journal of bacteriology 20080523 15

Listeria monocytogenes is able to efficiently utilize glycerol as a carbon source. In a defined minimal medium, the growth rate (during balanced growth) in the presence of glycerol is similar to that in the presence of glucose or cellobiose. Comparative transcriptome analyses of L. monocytogenes showed high-level transcriptional upregulation of the genes known to be involved in glycerol uptake and metabolism (glpFK and glpD) in the presence of glycerol (compared to that in the presence of glucos ...[more]

PMID: 18502850

Similar Datasets

Project description:The genome of the gastric pathogen Helicobacter pylori harbors a remarkably low number of regulatory genes, including three and five open reading frames encoding two-component histidine kinases and response regulators, respectively, which are putatively involved in transcriptional regulation. Inactivation of the response regulator gene hp1021 resulted in a severe growth defect, as indicated by a small-colony phenotype. Recently we found that phosphorylation of the receiver domain HP1021 is not needed for its response regulator function and may not occur at all. No target genes have been identified so far. In this study we define the HP1021-dependent regulon consisting of 79 genes (51 activated, 28 repressed) by global transcriptional profiling of an HP1021-deficient H. pylori mutant. Transcriptome analyses were performed using a whole-genome microarray containing 1649 PCR products generated with specific primer pairs derived from the genome sequences of H. pylori 26695 (Tomb et al., 1997. The complete genome sequence of the gastric pathogen Helicobacter pylori. Nature 388:539-547) and J99 (Alm et al., 1999. Genomic-sequence comparison of two unrelated isolates of the human gastric pathogen Helicobacter pylori. Nature 397:176-180) which were spotted in duplicate. Microarrays were produced as described by Gressmann et al. (Gressmann et al., 2005. Gain and loss of multiple genes during the evolution of Helicobacter pylori. PLoS Genet 1(4):e43). To determine genes which are differentially expressed in the HP1021-deficient mutant 26695/1021::km, cDNA was prepared from RNA extracted from H. pylori 26695 WT and 26695/1021::km. A total of eight RNA samples from two independent RNA preparations from strain 26695 WT and 26695/HP1021::km, respectively, was used for cDNA labelling und hybridisation. Dye reversal colour swaps were performed as follows: one cDNA sample was generated using Cy3-dCTP and the other using Cy5-dCTP resulting in four labelled cDNAs per colour swap. Cy5-dCTP and Cy3-dCTP labelled cDNAs were combined and hybridized to the H. pylori microarray. The slides were scanned using ScanArray HT and analysed by using the ScanArray express software (Perkin Elmer, version 3.0). Spots were flagged and eliminated from analysis when the signal to background ratio was less then three or in obvious instances of high background or stray fluorescent signals. Median intensities of spots were background corrected and differences in dye bias were normalized by using the LOWESS algorithm (Yang et al., 2002. Normalization for cDNA microarray data: a robuste composite method addressing single and multiple slide systematic variation. Nucleic Acid Res. 30:e15). The signal ratios as measure of differential expression between the red and green channels were obtained from processed signal intensities. Ratios were further analysed with Microsoft Excel (Microsoft) and SAM software for statistic significance (Tusher et al., 2001. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98:5116-5121). To determine the significance of differential expression RNA was isolated from the H. pylori 26695 WT grown in BHI broth, and 20 Âµg of this RNA were labelled either with Cy3-dCTP or with Cy5-dCTP. The two cDNA probes generated were hybridized onto the same slide, and the data were analysed as mentioned above. Signal ratios < 0.5 and > 2.0 were analyzed further.

Project description:Mice used in this study were 129/sv males, 8-15 weeks of age, which were housed individually and received water ad libitum. Normal fed animals were fed before and during the 48h experiment with standard food ad libitum. Sugar fed animals were fed before the experiment with standard food ad libitum and during the 48h experiment with 50% (w/v) sugar solution (40% glucose, 10% sucrose). Mice were killed by CO2 asphyxiation. The livers were snap-frozen in liquid nitrogen and stored at -80 degrees C. Total RNA was prepared using the Nucleospin RNA L kit (Macherey-Nagel, Düren, Germany), with an additional step in which the final eluate was used for a subsequent elution step. PolyA RNA was extracted with the Ambion (Ambion Inc, Austin, USA) Purist kit according to the manufacturer's protocols. Equal amounts of polyA RNA were pooled to generate pools of all animals. Pool1, normal = 3 animals (N1, N2, N3), pool2, normal = 3 animals (N4, N5, N6), pool3, = 4 animals (N7, N8, N9, N10), pool1, sugar = 3 animals (Su1, Su2, Su3), pool2, sugar = 3 animals (Su4, Su5, Su6), pool3, sugar = 4 animals (Su7, Su8, Su9, Su10). Labeled cDNA was synthesized from 1.5 µg polyA RNA using the Amersham (Amersham Europe, Freiburg, Germany) direct cDNA labeling kit. Removal of the unincorporated dyes and concentration of the target were done with Microcon 30 (Millipore, Bedford, MA) spin columns according to the manufacturer's instructions. The concentrated probes were hybridized to the microarray in 1x dig easy hyb buffer (Hoffman-la Roche, Basel, CH) overnight at 42 degrees C. After hybridization the microarrays are washed 5’ in 2x SSC, 0.1% SDS at 42 degrees C; 10’ in 0.1x SSC, 0.1% SDS at RT; 4 times 1’ in 0.1x SSC at RT and shortly dipped into 0.01x SSC. Drying is performed in centrifuge on a microtiterplate holder at 130 rcf for 7’. Slides are stored in dark until they are scanned. Arrays were scanned using the dual laser scanner Axon 4000B and the corresponding software Genepix 4 (Axon Inc., Union City, CA, USA). Both channels (532 nm for Cy3 and 635 nm Cy5) were scanned in parallel and stored as 16 bit tiff files. The absolute intensity values span the range from 0 to 65,535. The scans were performed with a resolution of 10 µm. From each spot with a mean diameter of 100 µm, 100 data pixels were recorded. Individual local background area around the spots were defined, which included approximately 400 pixels and excludes neighboring spots. For each channel, the raw data was calculated as the median intensity of all foreground pixels with respect to all background pixels. Each array was scanned three times (low, medium and high scan) with different signal amplification factors (voltage settings of the photo multiplier tubes), but with the same laser power. The channels for Cy3 and Cy5 were balanced in each scan for approximately the same intensity profile. In the low scan no spot was saturated, in the high scan the signal amplification for Cy5 was set to approximately 80% of maximum and the Cy3 amplification was adjusted to this. The settings used in the medium scan lie between the low and the high scan. This method for scanning has several advantages. In the low scan where no spot is in saturation, it is possible to calculate the real ratio for genes with high expression levels; however, those with a low expression level are most likely not recognized. In order not to lose these a high scan is made; in this case the information on the saturated spots is lost so the two scans complement each other. The medium scan produces additional values for subsequent calculations. By scanning the arrays three times errors which occur while recording and which might increase the error factor in the normalization are averaged. The data processing was automated in a Visual Basic/Excel (Microsoft) program, which integrates the following steps. Raw data are derived from the result files generated by scanning and picture analysis software Genepix. The spot diameter is to lie in the range from 80 to 120 µm otherwise these spots are not included in analysis. From the pixel to pixel ratios between the foreground values of both colors, the standard deviation (SD) is calculated. Those spots which show a ratio SD of higher than 3 are excluded from analysis due to inconsistency. The foreground signal of each spot is corrected by subtracting the corresponding local background. Resulting values which are lower than the background are replaced by the background value. This defines the minimum measurement threshold as the background and avoids calculations of completely wrong ratios, e.g., if the background corrected value for one channel is close to zero. Spots are marked as saturated in one channel if more than 10% of the foreground pixels are at the highest absolute value. From the unsaturated data points of all three scans, linear regression between the low and medium, and between low and high scans, are calculated for both colors. Taking these regressions, the values of saturated spots are replaced by estimated ones which reflect the real intensity. The generated data set of each scan is normalized afterwards based on the intensity-dependent methods as described by Yang et al (Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, and Speed TP. Normalization for cDNA microarray data: robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 30: e15, 2002). The ratios are calculated as log2 transformed values: M=log2 (Cy5/Cy3). Number describing the spot intensity A=log2sqrt (Cy5*Cy3) is calculated according to Yang et al. A within pin-tip group loess fit to the MA-plot was made. The loess scatter plot smoother performs robust locally fits using a tricube function to weight the values relative to the median point in the intensity interval. As interval size 20% was chosen, which corresponds to 180 data points in a pin-tip group containing 30 by 30 spots. After combining the normalized data from all blocks the data sets of all scans are additionally normalized using a global approach. The normalization was performed so that the sum of all log transformed ratios (M) is 0. All statistical normalizations are based on the assumption that (1) the majority of genes are not changed in their expression and (2) that the overall up and down regulations statistically compensate each other in sum. Taking this into account, the standard deviation in the ratios of the stable genes (80% of the most unchanged genes) could be seen as the measurement noise of the array experiments. To be able to compare the different scans and different normalized microarrays, the SD of the stable genes ratios was adjusted to a medium estimated value of 0.2, which is dependent on the used array system. This value does not influence the subsequent statistical analysis because the normal distribution of the data is not changed. For each microarray the normalized and adjusted log ratios of the three scans are averaged. Keywords = microarray analysis Keywords = nutrient response Keywords = caloric restriction Keywords = metabolic signaling Keywords = aging/longevity This SuperSeries is composed of the following subset Series: GSE851: liver, 48h sugar GSE852: liver, 48h starved GSE853: liver, 24h starved Refer to individual Series

Project description:Background All animals must be able to adapt to changes in nutrient quality and supply. One striking aspect of this adaptive response is the extension of lifespan when caloric intake is reduced. These animals are also more resistant to various stresses, including starvation. We have characterized the response of adult Drosophila males and females to starvation and sugar conditions using high density microarrays. Results We have organized the regulated genes into specific metabolic and physiologic pathways. Most of the highly regulated genes have a strong sex bias. In addition to expected sex specific changes, such as egg production in females, we found unexpected biases in sensory systems, amino acid and purine metabolism, and signaling pathways. Comparison of starvation to caloric restriction revealed numerous overlaps. Conclusions Our results support the notion that starvation response shares similarities to caloric restriction. They have relevance for sex specific differences in longevity and in response to nutrient conditions which alter lifespan. Nutrient Conditions and Fly handling Larvae were kept on apple juice agar plates with yeast, and the larvae were raised at 25Â°C. For the developmental control larvae were collected 39-41 h AEL, for the developmental time-points at 51-53 hours and every 12 hours until 99-101 hours. Adult flies were kept at 25Â°C in 50 ml PS-tubes flat bottom (Greiner bio-one, Frickenhausen, Germany) on standard fly food (16.5 g yeast, 81,5 g cornmeal, 8 g agar, 100 ml sugar beet sirup and 200 ml 10% Nipagin in EtOH). Flies were collected that had hatched in 24 hours and kept in groups of ~200 flies/tube. After 5 days we separated males and females and put them in groups of 80/28 ml PS-tube. We allowed for one day CO2 recovery on standard fly food before flies were moved to 1) tubes with yeast paste on PBS soaked filter paper (control) 2) tubes with only PBS soaked filter paper (starvation) or 3) tubes with filter paper soaked in PBS with 20% Sucrose (sugar). After 24 or 48 hours flies were shock frozen in liquid nitrogen and stored at - 80Â°C for further handling. Males and females were assayed separately. For females, we performed 24 and 48 starvation, and 24 and 48 hours sugar. For the males only 24 hour starvation was done, since most died upon 48 hour starvation; and 24 and 48 hour sugar. Briefly, flies were collected within a 24 hour period, allowed to stay together for 4 days, separated into males and females, and allowed one day recovery in normal fly food. Afterwards, the flies were placed into three conditions: fresh yeast plus PBS, PBS or PBS plus 20 % sucrose. These experiments essentially parallel the experimental set up of previous larval experiments (7). The starvation and PBS were then compared with yeast (control).

Dataset Information

Glycerol metabolism and PrfA activity in Listeria monocytogenes

Publications

Glycerol metabolism and PrfA activity in Listeria monocytogenes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure