High-throughput phenotypic characterization of Pseudomonas aeruginosa membrane transport genes.
ABSTRACT: The deluge of data generated by genome sequencing has led to an increasing reliance on bioinformatic predictions, since the traditional experimental approach of characterizing gene function one at a time cannot possibly keep pace with the sequence-based discovery of novel genes. We have utilized Biolog phenotype MicroArrays to identify phenotypes of gene knockout mutants in the opportunistic pathogen and versatile soil bacterium Pseudomonas aeruginosa in a relatively high-throughput fashion. Seventy-eight P. aeruginosa mutants defective in predicted sugar and amino acid membrane transporter genes were screened and clear phenotypes were identified for 27 of these. In all cases, these phenotypes were confirmed by independent growth assays on minimal media. Using qRT-PCR, we demonstrate that the expression levels of 11 of these transporter genes were induced from 4- to 90-fold by their substrates identified via phenotype analysis. Overall, the experimental data showed the bioinformatic predictions to be largely correct in 22 out of 27 cases, and led to the identification of novel transporter genes and a potentially new histamine catabolic pathway. Thus, rapid phenotype identification assays are an invaluable tool for confirming and extending bioinformatic predictions.
Project description:Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.
Project description:In this study, we show that the dppBCDF operon of Pseudomonas aeruginosa PA14 encodes an ABC transporter responsible for the utilization of di/tripeptides. The substrate specificity of ABC transporters is determined by its associated substrate-binding proteins (SBPs). Whereas in E. coli only one protein, DppA, determines the specificity of the transporter, five orthologous SBPs, DppA1-A5 are present in P. aeruginosa. Multiple SBPs might broaden the substrate specificity by increasing the transporter capacity. We utilized the Biolog phenotype MicroArray technology to investigate utilization of di/tripeptides in mutants lacking either the transport machinery or all of the five SBPs. This high-throughput method enabled us to screen hundreds of dipeptides with various side-chains, and subsequently, to determine the substrate profile of the dipeptide permease. The substrate spectrum of the SBPs was elucidated by complementation of a penta mutant, deficient of all five SBPs, with plasmids carrying individual SBPs. It became apparent that some dipeptides were utilized with different affinity for each SBP. We found that DppA2 shows the highest flexibility on substrate recognition and that DppA2 and DppA4 have a higher tendency to utilize tripeptides. DppA5 was not able to complement the penta mutant under our screening conditions. Phaseolotoxin, a toxic tripeptide inhibiting the enzyme ornithine carbamoyltransferase, is also transported into P. aeruginosa via the DppBCDF permease. The SBP DppA1, and with much greater extend DppA3, are responsible for delivering the toxin to the permease. Our results provide a first overview of the substrate pattern of the ABC dipeptide transport machinery in P. aeruginosa.
Project description:Analysis of the genome sequence of Pseudomonas aeruginosa PA14 revealed the presence of an operon encoding an ABC-type transporter (NppA1A2BCD) showing homology to the Yej transporter of Escherichia coli. The Yej transporter is involved in the uptake of the peptide-nucleotide antibiotic microcin C, a translation inhibitor that targets the enzyme aspartyl-tRNA synthetase. Furthermore, it was recently shown that the Opp transporter from P. aeruginosa PAO1, which is identical to Npp, is required for uptake of the uridyl peptide antibiotic pacidamycin, which targets the enzyme translocase I (MraY), which is involved in peptidoglycan synthesis. We used several approaches to further explore the substrate specificity of the Npp transporter. Assays of growth in defined minimal medium containing peptides of various lengths and amino acid compositions as sole nitrogen sources, as well as Biolog Phenotype MicroArrays, showed that the Npp transporter is not required for di-, tri-, and oligopeptide uptake. Overexpression of the npp operon increased susceptibility not just to pacidamycin but also to nickel chloride and the peptidyl nucleoside antibiotic blasticidin S. Furthermore, heterologous expression of the npp operon in a yej-deficient mutant of E. coli resulted in increased susceptibility to albomycin, a naturally occurring sideromycin with a peptidyl nucleoside antibiotic. Additionally, heterologous expression showed that microcin C is recognized by the P. aeruginosa Npp system. Overall, these results suggest that the NppA1A2BCD transporter is involved in the uptake of peptidyl nucleoside antibiotics by P. aeruginosa PA14.One of the world's most serious health problems is the rise of antibiotic-resistant bacteria. There is a desperate need to find novel antibiotic therapeutics that either act on new biological targets or are able to bypass known resistance mechanisms. Bacterial ABC transporters play an important role in nutrient uptake from the environment. These uptake systems could also be exploited by a Trojan horse strategy to facilitate the transport of antibiotics into bacterial cells. Several natural antibiotics mimic substrates of peptide uptake routes. In this study, we analyzed an ABC transporter involved in the uptake of nucleoside peptidyl antibiotics. Our data might help to design drug conjugates that may hijack this uptake system to gain access to cells.
Project description:We recently demonstrated that Pseudomonas aeruginosa PAO1 undergoes a pronounced phenotypic change when introduced into the intestines of rats during surgical injury. Recovered strains displayed a specific phenotype (termed the P2 phenotype) characterized by altered pyocyanin production, high collagenase activity, high swarming motility, low resistance to chloramphenicol, and increased killing of Caenorhabditis elegans compared to the inoculating strain (termed the P1 phenotype). The aims of this study were to characterize the differences between the P. aeruginosa P1 and P2 phenotypes in quorum sensing and competitiveness. We then determined the presence of the P2 phenotype among PAO1 strains from various laboratories. Results demonstrated that P2 cells display accelerated growth during early exponential phase and early activation of quorum-sensing systems and overcome the growth of P1 cells in a mixed population. Among eight PAO1 strains obtained from different laboratories, four exhibited the P2 phenotype. Of 27 mutants analyzed from the P. aeruginosa MPAO1 transposon library, 25 displayed P2 phenotypes. The P2 phenotype in both cases correlated with a lack of expression of mexE or mexF due to mutations in mexT and mexF genes. In summary, strains possessing the P2 phenotype are distributed among PAO1 strains commonly used across a variety of research laboratories. Genetically, they are characterized by various mutations in mexT or mexF.
Project description:Transcriptomic studies have revealed a large number of uncharacterized genes that are differentially expressed in biofilms, which may be important in regulating biofilm phenotypes such as resistance to antimicrobial agents. To identify biofilm genes of unknown function in P. aeruginosa, we made use of RNA-seq and selected 27 uncharacterized genes that were induced upon biofilm growth. Biofilms by respective mutants were subsequently analyzed for two biofilm characteristics, the biofilm architecture and drug susceptibility. The screen revealed 12 out of 27 genes to contribute to biofilm formation and 13 drug susceptibility, with 8 genes affecting both biofilm phenotypes. Amongst the genes affecting both biofilm phenotypes was PA2146, encoding a small hypothetical protein that exhibited some of the most substantial increases in transcript abundance during biofilm growth by P. aeruginosa PAO1 and clinical isolates. PA2146 is highly conserved in ɣ-proteobacteria. Inactivation of PA2146 affected both biofilm phenotypes in P. aeruginosa PAO1, with inactivation of homologs in Klebsiella pneumoniae and Escherichia coli having similar effects. Heterologous expression of PA2146 homologs complemented the P. aeruginosa ∆PA2146, suggesting that PA2146 homologs substitute for and play a similar role as PA2146 in P. aeruginosa.
Project description:In principle, whole-genome sequencing (WGS) can predict phenotypic resistance directly from a genotype, replacing laboratory-based tests. However, the contribution of different bioinformatics methods to genotype-phenotype discrepancies has not been systematically explored to date. We compared three WGS-based bioinformatics methods (Genefinder [read based], Mykrobe [de Bruijn graph based], and Typewriter [BLAST based]) for predicting the presence/absence of 83 different resistance determinants and virulence genes and overall antimicrobial susceptibility in 1,379 Staphylococcus aureus isolates previously characterized by standard laboratory methods (disc diffusion, broth and/or agar dilution, and PCR). In total, 99.5% (113,830/114,457) of individual resistance-determinant/virulence gene predictions were identical between all three methods, with only 627 (0.5%) discordant predictions, demonstrating high overall agreement (Fleiss' kappa = 0.98, P < 0.0001). Discrepancies when identified were in only one of the three methods for all genes except the cassette recombinase, ccrC(b). The genotypic antimicrobial susceptibility prediction matched the laboratory phenotype in 98.3% (14,224/14,464) of cases (2,720 [18.8%] resistant, 11,504 [79.5%] susceptible). There was greater disagreement between the laboratory phenotypes and the combined genotypic predictions (97 [0.7%] phenotypically susceptible, but all bioinformatic methods reported resistance; 89 [0.6%] phenotypically resistant, but all bioinformatics methods reported susceptible) than within the three bioinformatics methods (54 [0.4%] cases, 16 phenotypically resistant, 38 phenotypically susceptible). However, in 36/54 (67%) cases, the consensus genotype matched the laboratory phenotype. In this study, the choice between these three specific bioinformatic methods to identify resistance determinants or other genes in S. aureus did not prove critical, with all demonstrating high concordance with each other and phenotypic/molecular methods. However, each has some limitations; therefore, consensus methods provide some assurance.
Project description:Solute binding proteins (SBPs) form a heterogeneous protein family that is found in all kingdoms of life. In bacteria, the ligand-loaded forms bind to transmembrane transporters providing the substrate. We present here the SBP repertoire of Pseudomonas aeruginosa PAO1 that is composed of 98 proteins. Bioinformatic predictions indicate that many of these proteins have a redundant ligand profile such as 27 SBPs for proteinogenic amino acids, 13 proteins for spermidine/putrescine, or 9 proteins for quaternary amines. To assess the precision of these bioinformatic predictions, we have purified 17 SBPs that were subsequently submitted to high-throughput ligand screening approaches followed by isothermal titration calorimetry studies, resulting in the identification of ligands for 15 of them. Experimentation revealed that PA0222 was specific for ?-aminobutyrate (GABA), DppA2 for tripeptides, DppA3 for dipeptides, CysP for thiosulphate, OpuCC for betaine, and AotJ for arginine. Furthermore, RbsB bound D-ribose and D-allose, ModA bound molybdate, tungstate, and chromate, whereas AatJ recognized aspartate and glutamate. The majority of experimentally identified ligands were found to be chemoattractants. Data show that the ligand class recognized by SPBs can be predicted with confidence using bioinformatic methods, but experimental work is necessary to identify the precise ligand profile.
Project description:The cyanobacterium Microcystis aeruginosa is widely known for its production of the potent hepatotoxin microcystin. Microcystin is synthesized nonribosomally by the thiotemplate function of a large, modular enzyme complex encoded within the 55-kb microcystin synthetase (mcy) gene cluster. Also encoded within the mcy gene cluster is a putative ATP binding cassette (ABC) transporter, McyH. This study details the bioinformatic and mutational analyses of McyH and offers functional predictions for the hypothetical protein. The transporter is putatively comprised of two homodimers, each with an N-terminal hydrophobic domain and a C-terminal ATPase. Phylogenetically, McyH was found to cluster with members of the ABC-A1 subgroup of ABC ATPases, suggesting an export function for the protein. Two mcyH null mutant (DeltamcyH) strains were constructed by partial deletion of the mcyH gene. Microcystin production was completely absent in these strains. While the mcyH deletion had no apparent effect on the transcription of other mcy genes, the complete microcystin biosynthesis enzyme complex could not be detected in DeltamcyH mutant strains. Finally, expression levels of McyH in the wild type and in DeltamcyA, DeltamcyB, and DeltamcyH mutants were investigated by using immunoblotting with an anti-McyH antibody. Expression of McyH was found to be reduced in DeltamcyA and DeltamcyB mutants and completely absent in the DeltamcyH mutant. By virtue of its association with the mcy gene cluster and the bioinformatic and experimental data presented in this study, we predict that McyH functions as a microcystin exporter and is, in addition, intimately associated with the microcystin biosynthesis pathway.
Project description:Oberhardt2008 - Genome-scale metabolic
network of Pseudomonas aeruginosa (iMO1056)
This model is described in the article:
network analysis of the opportunistic pathogen Pseudomonas
Oberhardt MA, Puchałka J, Fryer
KE, Martins dos Santos VA, Papin JA.
J. Bacteriol. 2008 Apr; 190(8):
Pseudomonas aeruginosa is a major life-threatening
opportunistic pathogen that commonly infects immunocompromised
patients. This bacterium owes its success as a pathogen largely
to its metabolic versatility and flexibility. A thorough
understanding of P. aeruginosa's metabolism is thus pivotal for
the design of effective intervention strategies. Here we aim to
provide, through systems analysis, a basis for the
characterization of the genome-scale properties of this
pathogen's versatile metabolic network. To this end, we
reconstructed a genome-scale metabolic network of Pseudomonas
aeruginosa PAO1. This reconstruction accounts for 1,056 genes
(19% of the genome), 1,030 proteins, and 883 reactions. Flux
balance analysis was used to identify key features of P.
aeruginosa metabolism, such as growth yield, under defined
conditions and with defined knowledge gaps within the network.
BIOLOG substrate oxidation data were used in model expansion,
and a genome-scale transposon knockout set was compared against
in silico knockout predictions to validate the model.
Ultimately, this genome-scale model provides a basic modeling
framework with which to explore the metabolism of P. aeruginosa
in the context of its environmental and genetic constraints,
thereby contributing to a more thorough understanding of the
genotype-phenotype relationships in this resourceful and
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Project description:Pseudomonas aeruginosa is a major cause of morbidity and mortality in patients with cystic fibrosis (CF). We undertook Biolog Phenotype Microarray testing of P. aeruginosa CF isolates to investigate their catabolic capabilities compared to P. aeruginosa laboratory strains PAO1 and PA14. One strain, PASS4, displayed an unusual phenotype, only showing strong respiration on adenosine and inosine. Further testing indicated that PASS4 could grow on DNA as a sole carbon source, with a higher biomass production than PAO1. This suggested that PASS4 was specifically adapted to metabolize extracellular DNA, a substrate present at high concentrations in the CF lung. Transcriptomic and proteomic profiling of PASS4 and PAO1 when grown with DNA as a sole carbon source identified a set of upregulated genes, including virulence and host-adaptation genes. PASS4 was unable to utilize N-Acetyl-D-glucosamine, and when we selected PASS4 mutants able to grow on this carbon source, they also displayed a gain in ability to catabolize a broad range of other carbon sources. Genome sequencing of the mutants revealed they all contained mutations within the purK gene, encoding a key protein in the de novo purine biosynthesis pathway. This suggested that PASS4 was a purine auxotroph. Growth assays in the presence of 2 mM adenosine and the complementation of PASS4 with an intact purK gene confirmed this conclusion. Purine auxotrophy may represent a viable microbial strategy for adaptation to DNA-rich environments such as the CF lung.