Beta-lactam evolution experiment H. influenzae Rd KW20
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PROVIDER: PRJEB86018 | ENA |
REPOSITORIES: ENA
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Project description:Bacterial outer membrane vesicles (OMVs) have important biological roles in pathogenesis and intercellular interactions, but a general mechanism of OMV formation is lacking. Here we show that the VacJ/Yrb ABC transport system, a proposed phospholipid (PL) transporter, is involved in OMV formation. Deletion or repression of VacJ/Yrb increases OMV production in two distantly related Gram-negative bacteria, Haemophilus influenzae and Vibrio cholerae. Within our studies we also analyzed the proteome of the OMV and outer membrane (OM) and found no massive alteration in Haemophilus influenzae Rd KW20, Rd ∆yrbE and Rd ∆vacJ. Lipidome analyses demonstrate that OMVs from VacJ/Yrb-defective mutants in H. influenzae are enriched in PLs and certain fatty acids. Furthermore, we demonstrate that OMV production and regulation of the VacJ/Yrb ABC transport system respond to iron starvation. Our results suggest a new general mechanism of OMV biogenesis based on PL accumulation in the outer leaflet of the outer membrane. This mechanism is highly conserved among Gram-negative bacteria, provides a means for regulation, can account for OMV formation under all growth conditions, and might have important pathophysiological roles in vivo.
2016-01-27 | PXD003249 | Pride
Project description:Haemophilus influenzae Rd KW20 strain:Rd Genome sequencing
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Project description:Haemophilus influenzae Rd KW20 Genome sequencing
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Project description:Transcriptional Profile of Haemophilus influenzae: Effects of Iron and Heme
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Project description:Haemophilus influenzae is a Gram negative bacterium that belongs to the family Pasteurellaceae, causes bacteremia, pneumonia and acute bacterial meningitis in infants. The emergence of multi-drug resistance H. influenzae strain in clinical isolates demands the development of better/new drugs against this pathogen. Our study combines a number of bioinformatics tools for function predictions of previously not assigned proteins in the genome of H. influenzae. This genome was extensively analyzed and found 1,657 functional proteins in which function of 429 proteins are unknown, termed as hypothetical proteins (HPs). Amino acid sequences of all 429 HPs were extensively annotated and we successfully assigned the function to 296 HPs with high confidence. We also characterized the function of 124 HPs precisely, but with less confidence. We believed that sequence of a protein can be used as a framework to explain known functional properties. Here we have combined the latest versions of protein family databases, protein motifs, intrinsic features from the amino acid sequence, pathway and genome context methods to assign a precise function to hypothetical proteins for which no experimental information is available. We found these HPs belong to various classes of proteins such as enzymes, transporters, carriers, receptors, signal transducers, binding proteins, virulence and other proteins. The outcome of this work will be helpful for a better understanding of the mechanism of pathogenesis and in finding novel therapeutic targets for H. influenzae.
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Project description:The proteome of Haemophilus influenzae strain Rd KW20 was analyzed by liquid chromatography (LC) coupled with ion trap tandem mass spectrometry (MS/MS). This approach does not require a gel electrophoresis step and provides a rapidly developed snapshot of the proteome. In order to gain insight into the central metabolism of H. influenzae, cells were grown microaerobically and anaerobically in a rich medium and soluble and membrane proteins of strain Rd KW20 were proteolyzed with trypsin and directly examined by LC-MS/MS. Several different experimental and computational approaches were utilized to optimize the proteome coverage and to ensure statistically valid protein identification. Approximately 25% of all predicted proteins (open reading frames) of H. influenzae strain Rd KW20 were identified with high confidence, as their component peptides were unambiguously assigned to tandem mass spectra. Approximately 80% of the predicted ribosomal proteins were identified with high confidence, compared to the 33% of the predicted ribosomal proteins detected by previous two-dimensional gel electrophoresis studies. The results obtained in this study are generally consistent with those obtained from computational genome analysis, two-dimensional gel electrophoresis, and whole-genome transposon mutagenesis studies. At least 15 genes originally annotated as conserved hypothetical were found to encode expressed proteins. Two more proteins, previously annotated as predicted coding regions, were detected with high confidence; these proteins also have close homologs in related bacteria. The direct proteomics approach to studying protein expression in vivo reported here is a powerful method that is applicable to proteome analysis of any (micro)organism.
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Project description:Haemophilus influenzae ATCC 51907 DAP-Seq epigenomics
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Project description:Human-specific organism that causes a variety of diseases (avirulent strain)
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Project description:Haemophilus influenzae is a gram-negative bacterium of relevant clinical interest. H. influenzae Rd KW20 was the first organism to be sequenced and for which a genome-scale metabolic model (GEM) was developed. However, current H. influenzae GEMs are unable to capture several aspects of metabolome nature related to metabolite pools. To directly and comprehensively characterize the endometabolome of H. influenzae Rd KW20, we performed a multiplatform MS-based metabolomics approach combining LC-MS, GC-MS and CE-MS. We obtained direct evidence of 15-20% of the endometabolome present in current H. influenzae GEMs and showed that polar metabolite pools are interconnected through correlating metabolite islands. Notably, we obtained high-quality evidence of 18 metabolites not previously included in H. influenzae GEMs, including the antimicrobial metabolite cyclo(Leu-Pro). Additionally, we comprehensively characterized and evaluated the quantitative composition of the phospholipidome of H. influenzae, revealing that the fatty acyl chain composition is largely independent of the lipid class, as well as that the probability distribution of phospholipids is mostly related to the conditional probability distribution of individual acyl chains. This finding enabled us to provide a rationale for the observed phospholipid profiles and estimate the abundance of low-level species, permitting the expansion of the phospholipidome characterization through predictive probabilistic modelling.
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