Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Porphyromonas gingivalis 33277 wild-type vs Fur orthologue Har isogenic mutant ECR455

ABSTRACT: Porphyromonas gingivalis is a major pathogen associated with the microbial biofilm-mediated disease chronic periodontitis. P. gingivalis has an obligate requirement for iron and protoporphyrin IX which it satisfies by transporting heme and iron liberated from the human host. The level of cellular iron in P. gingivalis affects the expression of a distinct iron-associated regulon of 64 genes and low iron invokes an iron sparing response. Iron homeostasis is usually mediated in Gram-negative bacteria at the transcriptional level by the Ferric Uptake Regulator (Fur). There is a single predicted P. gingivalis Fur superfamily orthologue named Har (heme associated regulator) that lacks the conserved metal binding residues found in other Fur orthologues. We show that Har binds both heme and ferrous iron resulting in a conformational change in the protein. Har was unable to complement the Escherichia coli H1780 fur mutant and there was no change in cellular metal content in a P. gingivalis Har mutant compared with the wild-type. The Har regulon of 44 genes is not predicted to play a role in iron homeostasis. Together these data indicated that Har does not regulate iron homeostasis in P. gingivalis. However, Har was required for heme-responsive biofilm development and its regulon overlapped P. gingivalis regulons previously identified after growth in heme limitation or as a homotypic biofilm. P. gingivalis is unique as an iron-dependent Gram-negative bacterium with a single heme-binding Fur superfamily orthologue, Har, that does not regulate iron homeostasis. Paired samples were compared on the same microarray using a two-colour system. A total of 6 paired microarray hybridizations were performed representing 6 biological replicates, where a balanced dye design was used, with the overall analysis including three microarrays where P. gingivalis 33277 samples were labeled with Cy3 and the paired ECR455 samples were labeled with Cy5 and three other microarrays where samples were labeled with the opposite combination of fluorophores.

ORGANISM(S): Porphyromonas gingivalis ATCC 33277

SUBMITTER: Catherine Butler

PROVIDER: E-GEOD-37099 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

The Porphyromonas gingivalis ferric uptake regulator orthologue binds hemin and regulates hemin-responsive biofilm development.

Butler Catherine A CA Dashper Stuart G SG Zhang Lianyi L Seers Christine A CA Mitchell Helen L HL Catmull Deanne V DV Glew Michelle D MD Heath Jacqueline E JE Tan Yan Y Khan Hasnah S G HS Reynolds Eric C EC

PloS one 20141106 11

Porphyromonas gingivalis is a Gram-negative pathogen associated with the biofilm-mediated disease chronic periodontitis. P. gingivalis biofilm formation is dependent on environmental heme for which P. gingivalis has an obligate requirement as it is unable to synthesize protoporphyrin IX de novo, hence P. gingivalis transports iron and heme liberated from the human host. Homeostasis of a variety of transition metal ions is often mediated in Gram-negative bacteria at the transcriptional level by m ...[more]

PMID: 25375181

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Project description:Periodontitis affects 47.1% of adult population in the U.S. Porphyromonas gingivalis is an opportunistic oral pathogen that colonizes the oral mucosa, invades myeloid dendritic cells and accesses the bloodstream, brain, placenta and other organs in human with periodontitis. Periodontitis also sustains a chronic long-term pro-inflammatory immune disorder, potentially contributing to other systemic conditions such as cardiovascular disease, type 2 diabetes mellitus, adverse pregnancy outcomes, and osteoporosis. However, the role of P. gingivalis minor and major fimbriae in DC-SIGN-TLR2 crosstalk during traverses from oral mucosa to these distant sites and its influence on survival of P. gingivalis within DCs and its immune-mechanism involve at molecular/transcriptome level has not been examined. In this study to address the role of fimbriae we utilized defined bacterial mutants that solely express minor fimbriae (Mfa1+Pg), major fimbriae (FimA+Pg) or are deficient in both fimbriae (MFB) and compared with un-infected control. P. gingivalis strains were maintained anaerobically (10% H2, 10% CO2, and 80% N2) in a Forma Scientific anaerobic system glove box model 1025/1029 at 37Â°C in Difco anaerobe broth MIC. Mutant strains were maintained using erythromycin (5 Î¼g/ml) for mutant Mfa1+Pg, tetracycline (2 Î¼g/ml) for mutant FimA+Pg and both erythromycin and tetracycline for double fimbriae mutant MFB. Bacterial suspensions were washed five times in PBS and re-suspended for spectrophotometer reading at OD 660 nm of 0.11, which previously determined to be equal to 5 x 107 CFU. For bacterial CFSE staining, the suspension were washed (3 times) and re-suspended in 5 Î¼M of CFSE in PBS. The bacteria were incubated for 30 min at 37Â°C in the dark. MoDCs were pulsed with Pg381, Mfa1+Pg, FimA+Pg and MFB at 10 MOI and incubated with the MoDCs for 12 hours and each experimental condition was performed in triplicate. To facilitate our understanding on host immunity and defense mechanism of this pathogen, here we used the Illumina High-throughput RNA-seq transcriptome profiling to investigate the myeloid dendritic cells response to oral Amphibiont (1. Pg381, 2. Mfa1+Pg, 3. FimA+Pg, 4. MFB and 5. Un-infected control group).

Project description:Polyphosphate (polyP) is a ubiquitous and abundant compound found in bacteria, fungi, algae, plant, and animals. Among roles of intracellular polyP in bacteria are resistance and survival in the stationary phase of the growth against stress and stringent condition. Therefore, intracellular polyP is considered as a virulence factor of bacteria. In contrast, exogenous polyP has an antimicrobial activity against a variety of microorganisms. To date, much has been numerous studies of antibacterial effect of polyP against gram positive bacteria and fungi while relatively little reports have been published concerning gram negative bacteria. Here we describe bactericidal effect of polyP against gram negative periodontopathic bacterium, Porphyromonas gingivalis, and the transcriptional change by polyP in this bacterium. The bacterial growth was inhibited by polyP (chain length of P3~P75) at concentration of 0.02~0.03%, but not by Pi and PPi at the concentrations. polyP75 was chosen for further experiments, which suppressed the further growth of P. gingivalis as low as 0.03%. polyP75 completely killed the bacterial cells at the concentration of 0.035%. Microarray analysis was employed to identify genes that showed a greater than 1.5-fold difference in the expression by polyP75 at the concentration of 0.03%. It was found that 155 genes were up-regulated and 173 were down-regulated. Down-regulated genes include groups of energy metabolism-related genes, cell envelope-related genes, and genes in relation to biosynthesis of cofactors, prosthetic groups and carriers. Among the down-regulated genes were several involved in DNA replication, cell division protein, and biosynthesis of purines, pyrimidines, nucleosides and nucleotides. In contrast, a large number of ribosomal proteins, transciptional regulators and transposases were up-regulated. Oxidative stress-related genes and iron storage proteins also appeared to be increased in the expression. Real-time PCR confirmed up- and down-regulation of some selected genes. The overall results suggest that polyP has a bactericidal activity against P. gingivalis, interfering with translation, energy metabolism, DNA replication, cell division, and biosynthesis of purines, pyrimidines, nucleoside and nucleotides. polyP may be used as an agent for prevention and treatment of periodontal infections. Polyp-treated vs. untreated intensity ratio data linked below as a supplementary file. Keywords: agent response Twenty μg of each total RNA sample was used in separate hybridization experiments on identical arrays. The whole genome of 1,909 genes of P. gingivalis W83 (GenBank accession no. NC_002950) was submitted to NimbleGen System Inc. (Madison, WI) for microarray design and manufacture using maskless, digital micromirror technology. Five replicates of the genome were included per chip. An average of 19 different 60-base oligonucleotides (60-mer probes) represented each gene in the genome. Sixty-mer probes were selected such that each probe had at least three mismatches compared to all other 60-mers in the target genome. A quality control check (hybridization) was performed for each array, which contained on-chip control oligonucleotides. The arrays were analyzed using an Axon GenePix 4000B microarray scanner with associated software (Molecular Devices Corp., Sunnyvale, CA). Gene expression levels were calculated with NimbleScan Version 2.3 (NimbleGen). Relative signal intensities for each gene were generated using the Robust Multi-Array Average algorithm. The data were processed based on quantile normalization method using the R package. This normalization method aims to make the distribution of intensities for each array in a set of arrays the same. The background-adjusted, normalized, and log transformed intensity values were then analyzed using GeneSpring GX 7.3.1 (Silicon Genetics, Palo Alto, CA).

Project description:Porphyromonas gingivalis is a periodontal pathogen that is also associated with preterm low birth weight delivery. We investigated the transcriptional responses of human extravillous trophoblasts (HTR-8) to infection with P. gingivalis. Over 2000 genes were differentially regulated in HTR-8 cells by P. gingivalis. In ontology analyses of regulated genes, overpopulated biological pathways included MAP kinase signaling and cytokine production. Immunoblots confirmed over expression of the MAP kinase pathway components MEK3, p38 and Max. Furthermore, P. gingivalis infection induced phosphorylation and activation of MEK3 and p38. Increased production of IL-1Î² and IL-8 by HTR-8 cells was demonstrated phenotypically by ELISA of HTR-8 cell lysates and culture supernatants. Thus infection of trophoblasts by P. gingivalis can impact signal transduction pathways and modulate cytokine expression, outcomes that could disrupt the maintenance of pregnancy. P. gingivalis were reacted with HTR-8 cells at an MOI of 200 for 2 hours at 370C in 5% CO2. Co-cultures were carried out in quadruplicate. The HIGK cells were lysed with Trizol (Invitrogen) prior to RNA extraction. RNA isolation, cDNA synthesis, labeled cRNA synthesis and chip hybridization were conducted as previously described (Handfield et al., 2005). Briefly, total RNA was extracted from Trizol-lysed cells, treated with DNase I, purified and quantified according to standard methods (Qiagen, Valencia, CA; and Affymetrix, Santa Clara, CA). Complementary DNA (cDNA) synthesis was performed according to the Affymetrix protocol (SuperScript double-stranded cDNA synthesis kit; Invitrogen,) with 8 Âµg of total cellular RNA used as a template to amplify mRNA species for detection. Double-stranded cDNA was purified, and used as a template for labeled complementary RNA (cRNA) synthesis. In vitro transcription was performed using a BioArray high-yield RNA transcript labeling kit (T7) (Enzo Life Science, Farmingdale, NY), to incorporate biotinylated nucleotides. cRNA was subsequently fragmented and hybridized onto Genechip Human Genome (HG) U133-A Plus 2.0 oligonucleotide arrays (Affymetrix) with proper controls. Each sample was studied in parallel, and the samples were not pooled. The microarrays were hybridized for 16 h at 45Â°C, stained with phycoerythrin-conjugated streptavidin and washed according to the Affymetrix protocol (EukGE-WS2v4) using an Affymetrix fluidics station, and scanned with an Affymetrix GeneChip 3000 scanner. Microarray data analysis was performed as previously described (Mans et al., 2006, Hasegawa et al., 2008). Briefly, expression filters were applied to remove Affymetrix controls and probe-sets whose signal was undetected across all samples. The signal intensity values of the resulting dataset were variance-normalized, mean-centered and ranked by their coefficients of variation. Normalization was performed to give equal weight to all probe-sets in the analysis, regardless of the order of magnitude of the raw signal intensity. To reduce the confounding effect of background signal variation on the analysis, only the half of the dataset demonstrating the most variation across samples was used to perform unsupervised hierarchical cluster analysis using Cluster software (Eisen et al., 1998). The resulting heat-map and cluster dendrograms were visualized with Treeview software Eisen to reveal the extent of characteristic host cell responses to each infection state, defined as identical treatments clustering together. Additional quality control data for the arrays is provided in the supplemental material. Following initial assessment of the host cell response to each condition, supervised analysis was performed to investigate differences in gene regulation among experimental conditions. For this analysis, the raw signal intensities were log2-transformed for all probe-sets that passed the initial expression filters, and were correlated using BRB Array Tools (Simon and Peng-Lam, National Cancer Institute, Rockville, MD). In each supervised analysis, biological replicates were grouped into classes according to their infection state during co-culture experiments and probe sets significant at the p < 0.001 level between classes were identified. To test the ability of these significant probe sets to truly distinguish between the classes, leave-one-out-cross-validation (LOOCV) studies were preformed. In these LOOCV studies each array was left out in turn and a classifier was derived between the groups by selecting probe sets significant at p < 0.001. The significant probe sets were then used with several prediction models (compound covariate predictor, nearest neighbor predictor, and support vector machine predictor) to predict the class identity of the array that was left out and not included when the classification model was built. The significance (p<0.001) of the LOOCV analysis was estimated using a Monte Carlo simulation with 2,000 permutations of the dataset. KEGG pathways were populated using Pathway Express (Khatri et al., 2005), available at http://vortex.cs.wayne.edu/projects.htm

Dataset Information

Porphyromonas gingivalis 33277 wild-type vs Fur orthologue Har isogenic mutant ECR455

Publications

The Porphyromonas gingivalis ferric uptake regulator orthologue binds hemin and regulates hemin-responsive biofilm development.

Similar Datasets

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