scholarly journals Genome-scale modeling of Pseudomonas aeruginosa PA14 unveils its broad metabolic capabilities and role of metabolism in drug potentiation

2021 ◽  
Author(s):  
Sanjeev Dahal ◽  
Laurence Yang
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Substrate Utilization ◽  
Scale Model ◽  
Extensive Literature ◽  
Gene Essentiality ◽  
Carnitine Metabolism ◽  
Utilization Data ◽  
Opportunistic Human Pathogen ◽  
Specific Reactions ◽  
Genome Scale

AbstractIn this study, we developed an updated genome-scale model (GEM) of Pseudomonas aeruginosa PA14 and utilized it to showcase the broad capabilities of the GEM. P. aeruginosa is an opportunistic human pathogen that is one of the leading causes of nosocomial infections in hospital settings. We used both automated and manual approaches to reconstruct and curate the model, and then added strain-specific reactions (e.g., phenazine transport and redox metabolism, cofactor metabolism, carnitine metabolism, oxalate production, etc.) after extensive literature review. We validated and improved the model using a set of gene essentiality and substrate utilization data. This effort led to a highly curated, three-compartment and mass-and-charge balanced BiGG model of PA14 that contains 1511 genes and 2036 reactions. Even with considerable increase in model contents (genes, reactions, and metabolites), compared to the previous model (mPA14) of the same strain, this model (iSD1511) has similar prediction accuracy for gene essentiality and higher accuracy for substrate utilization assay. We assessed iSD1511 using another set of gene essentiality and substrate utilization data and computed the prediction accuracies as high as 92.7% and 93.5%, respectively. The model can simulate growth in both aerobic and anaerobic conditions. Finally, we utilized the model to recapitulate the results of multiple case studies including drug potentiation by citric acid cycle intermediates. Overall, we have built a highly curated computational model of the P. aeruginosa to decipher the metabolic mechanisms of drug resistance, and to help in the development of effective intervention strategies.

scholarly journals Genome-Scale Metabolic Network Analysis of the Opportunistic Pathogen Pseudomonas aeruginosa PAO1

2008 ◽  
Vol 190 (8) ◽  
pp. 2790-2803 ◽  
Author(s):  
Matthew A. Oberhardt ◽  
Jacek Puchałka ◽  
Kimberly E. Fryer ◽  
Vítor A. P. Martins dos Santos ◽  
Jason A. Papin
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Metabolic Network ◽  
Opportunistic Pathogen ◽  
Scale Model ◽  
Modeling Framework ◽  
Major Life ◽  
Metabolic Versatility ◽  
A Genome ◽  
Scale Properties ◽  
Genome Scale

ABSTRACT 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.

scholarly journals A comprehensive genome-scale model forRhodosporidium toruloidesIFO0880 accounting for functional genomics and phenotypic data

2019 ◽  
Author(s):  
Hoang V. Dinh ◽  
Patrick F. Suthers ◽  
Siu Hung Joshua Chan ◽  
Yihui Shen ◽  
Tianxia Xiao ◽  
...  
Keyword(s):  
Functional Genomics ◽  
Current Knowledge ◽  
Biomass Composition ◽  
Scale Model ◽  
Phenotypic Data ◽  
Gene Essentiality ◽  
A Genome ◽  
Genetic Interventions ◽  
Genome Scale ◽  
Genome Scale Model

AbstractBackgroundRhodosporidium toruloidesis a basidiomycetes yeast that can accumulate large amount of lipids and natively produce carotenoids. To better assess this non-model yeast’s metabolic capabilities, we reconstruct a genome-scale model ofR. toruloidesIFO0880’s metabolic network (iRhto1108) using recent functional genomics and phenotypic data in literature or generated herein.ResultsThe modeliRhto1108 accounts for 2,203 reactions, 1,985 metabolites and 1,108 genes. In this work, we integrate and supplement the current knowledge with in-house generated biomass composition and experimental measurements pertaining to the organism’s metabolic capabilities. Phenotype-genotype relationship predictions were improved through manual curation of gene-protein-reaction rules for 543 reactions and validations with gene essentiality data leading to correct recapitulations of 84.5% of gene essentiality data (sensitivity of 94.3% and specificity of 53.8%). Organism-specific macromolecular composition and ATP maintenance requirements were experimentally measured for two separate growth conditions: (i) carbon and (ii) nitrogen limitations. Overall,iRhto1108 reproducedR. toruloides’s utilization capabilities for 18 alternate substrates, matched measured wild-type growth yield, and recapitulated the viability of 772 out of 819 deletion mutants. As a demonstration to the model’s fidelity in guiding engineering interventions, the OptForce procedure was applied oniRhto1108 for the overproduction of triacylglycerol. Suggested interventions recapitulated many of the previously successfully implemented genetic modifications and put forth a few new ones.ConclusioniRhto1108 offers a highly curated model for a non-model yeast supported by multiple layers of experimental data that can be used to inform genetic interventions.

scholarly journals Reconciling high-throughput gene essentiality data with metabolic network reconstructions

2018 ◽  
Author(s):  
Anna S. Blazier ◽  
Jason A. Papin
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Metabolic Network ◽  
High Throughput ◽  
Large Scale ◽  
Essential Genes ◽  
Growth And Survival ◽  
Gene Essentiality ◽  
Model Driven ◽  
Functional Explanations ◽  
Genome Scale

AbstractThe identification of genes essential for bacterial growth and survival represents a promising strategy for the discovery of antimicrobial targets. Essential genes can be identified on a genome-scale using transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification of both condition-independent and condition-dependent essential genes. To illustrate the scope of these challenges, we perform a large-scale comparison of multiple published Pseudomonas aeruginosa gene essentiality datasets, revealing substantial differences between the screens. We then contextualize essentiality using genome-scale metabolic network reconstructions and demonstrate the utility of this approach in providing functional explanations for essentiality and reconciling differences between screens. Genome-scale metabolic network reconstructions also enable a high-throughput, quantitative analysis to assess the impact of media conditions on the identification of condition-independent essential genes. Our computational model-driven analysis provides mechanistic insight into essentiality and contributes novel insights for design of future gene essentiality screens and the identification of core metabolic processes.Author SummaryWith the rise of antibiotic resistance, there is a growing need to discover new therapeutic targets to treat bacterial infections. One attractive strategy is to target genes that are essential for growth and survival. Essential genes can be identified with transposon mutagenesis approaches; however, variability between screens and challenges with interpretation of essentiality data hinder the identification and analysis of essential genes. We performed a large-scale comparison of multiple gene essentiality screens of the microbial pathogen Pseudomonas aeruginosa. We implemented a computational model-driven approach to provide functional explanations for essentiality and reconcile differences between screens. The integration of computational modeling with high-throughput experimental screens may enable the identification of drug targets with high-confidence and provide greater understanding for the development of novel therapeutic strategies.

scholarly journals A Novel Infection Protocol in Zebrafish Embryo to Assess Pseudomonas aeruginosa Virulence and Validate Efficacy of a Quorum Sensing Inhibitor In Vivo

Pathogens ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 401
Author(s):  
Pauline Nogaret ◽  
Fatima El El Garah ◽  
Anne-Béatrice Blanc-Potard
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Animal Model ◽  
Quorum Sensing ◽  
Drug Testing ◽  
Drug Efficacy ◽  
Embryo Viability ◽  
Immersion Method ◽  
Opportunistic Human Pathogen

The opportunistic human pathogen Pseudomonas aeruginosa is responsible for a variety of acute infections and is a major cause of mortality in chronically infected cystic fibrosis patients. Due to increased resistance to antibiotics, new therapeutic strategies against P. aeruginosa are urgently needed. In this context, we aimed to develop a simple vertebrate animal model to rapidly assess in vivo drug efficacy against P. aeruginosa. Zebrafish are increasingly considered for modeling human infections caused by bacterial pathogens, which are commonly microinjected in embryos. In the present study, we established a novel protocol for zebrafish infection by P. aeruginosa based on bath immersion in 96-well plates of tail-injured embryos. The immersion method, followed by a 48-hour survey of embryo viability, was first validated to assess the virulence of P. aeruginosa wild-type PAO1 and a known attenuated mutant. We then validated its relevance for antipseudomonal drug testing by first using a clinically used antibiotic, ciprofloxacin. Secondly, we used a novel quorum sensing (QS) inhibitory molecule, N-(2-pyrimidyl)butanamide (C11), the activity of which had been validated in vitro but not previously tested in any animal model. A significant protective effect of C11 was observed on infected embryos, supporting the ability of C11 to attenuate in vivo P. aeruginosa pathogenicity. In conclusion, we present here a new and reliable method to compare the virulence of P. aeruginosa strains in vivo and to rapidly assess the efficacy of clinically relevant drugs against P. aeruginosa, including new antivirulence compounds.

scholarly journals Staphylococcus aureus Serves as an Iron Source for Pseudomonas aeruginosa during In Vivo Coculture

2005 ◽  
Vol 187 (2) ◽  
pp. 554-566 ◽  
Author(s):  
Lauren M. Mashburn ◽  
Amy M. Jett ◽  
Darrin R. Akins ◽  
Marvin Whiteley
Keyword(s):  
Staphylococcus Aureus ◽  
Pseudomonas Aeruginosa ◽  
Pathogenic Bacteria ◽  
Iron Acquisition ◽  
Low Oxygen ◽  
Dialysis Membrane ◽  
Opportunistic Human Pathogen ◽  
The Impact

ABSTRACT Pseudomonas aeruginosa is a gram-negative opportunistic human pathogen often infecting the lungs of individuals with the heritable disease cystic fibrosis and the peritoneum of individuals undergoing continuous ambulatory peritoneal dialysis. Often these infections are not caused by colonization with P. aeruginosa alone but instead by a consortium of pathogenic bacteria. Little is known about growth and persistence of P. aeruginosa in vivo, and less is known about the impact of coinfecting bacteria on P. aeruginosa pathogenesis and physiology. In this study, a rat dialysis membrane peritoneal model was used to evaluate the in vivo transcriptome of P. aeruginosa in monoculture and in coculture with Staphylococcus aureus. Monoculture results indicate that approximately 5% of all P. aeruginosa genes are differentially regulated during growth in vivo compared to in vitro controls. Included in this analysis are genes important for iron acquisition and growth in low-oxygen environments. The presence of S. aureus caused decreased transcription of P. aeruginosa iron-regulated genes during in vivo coculture, indicating that the presence of S. aureus increases usable iron for P. aeruginosa in this environment. We propose a model where P. aeruginosa lyses S. aureus and uses released iron for growth in low-iron environments.

scholarly journals Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation

Microbiology ◽  
2014 ◽  
Vol 160 (6) ◽  
pp. 1252-1266 ◽  
Author(s):  
Hassan B. Hartman ◽  
David A. Fell ◽  
Sergio Rossell ◽  
Peter Ruhdal Jensen ◽  
Martin J. Woodward ◽  
...  
Keyword(s):  
Salmonella Enterica ◽  
Energy Demand ◽  
Drug Targets ◽  
Minimal Medium ◽  
Model Organism ◽  
Metabolic Model ◽  
Scale Model ◽  
Glucose Minimal Medium ◽  
A Genome ◽  
Genome Scale

Salmonella enterica sv. Typhimurium is an established model organism for Gram-negative, intracellular pathogens. Owing to the rapid spread of resistance to antibiotics among this group of pathogens, new approaches to identify suitable target proteins are required. Based on the genome sequence of S. Typhimurium and associated databases, a genome-scale metabolic model was constructed. Output was based on an experimental determination of the biomass of Salmonella when growing in glucose minimal medium. Linear programming was used to simulate variations in the energy demand while growing in glucose minimal medium. By grouping reactions with similar flux responses, a subnetwork of 34 reactions responding to this variation was identified (the catabolic core). This network was used to identify sets of one and two reactions that when removed from the genome-scale model interfered with energy and biomass generation. Eleven such sets were found to be essential for the production of biomass precursors. Experimental investigation of seven of these showed that knockouts of the associated genes resulted in attenuated growth for four pairs of reactions, whilst three single reactions were shown to be essential for growth.

scholarly journals A Genome-Scale Model of Shewanella piezotolerans Simulates Mechanisms of Metabolic Diversity and Energy Conservation

mSystems ◽  
2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Keith Dufault-Thompson ◽  
Huahua Jian ◽  
Ruixue Cheng ◽  
Jiefu Li ◽  
Fengping Wang ◽  
...  
Keyword(s):  
Energy Conservation ◽  
Deep Sea ◽  
Carbon Sources ◽  
Scale Model ◽  
Anaerobic Conditions ◽  
A Genome ◽  
Group 2 ◽  
Genome Scale ◽  
Genome Scale Model ◽  
Group 1

ABSTRACT The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms. Shewanella piezotolerans strain WP3 belongs to the group 1 branch of the Shewanella genus and is a piezotolerant and psychrotolerant species isolated from the deep sea. In this study, a genome-scale model was constructed for WP3 using a combination of genome annotation, ortholog mapping, and physiological verification. The metabolic reconstruction contained 806 genes, 653 metabolites, and 922 reactions, including central metabolic functions that represented nonhomologous replacements between the group 1 and group 2 Shewanella species. Metabolic simulations with the WP3 model demonstrated consistency with existing knowledge about the physiology of the organism. A comparison of model simulations with experimental measurements verified the predicted growth profiles under increasing concentrations of carbon sources. The WP3 model was applied to study mechanisms of anaerobic respiration through investigating energy conservation, redox balancing, and the generation of proton motive force. Despite being an obligate respiratory organism, WP3 was predicted to use substrate-level phosphorylation as the primary source of energy conservation under anaerobic conditions, a trait previously identified in other Shewanella species. Further investigation of the ATP synthase activity revealed a positive correlation between the availability of reducing equivalents in the cell and the directionality of the ATP synthase reaction flux. Comparison of the WP3 model with an existing model of a group 2 species, Shewanella oneidensis MR-1, revealed that the WP3 model demonstrated greater flexibility in ATP production under the anaerobic conditions. Such flexibility could be advantageous to WP3 for its adaptation to fluctuating availability of organic carbon sources in the deep sea. IMPORTANCE The well-studied nature of the metabolic diversity of Shewanella bacteria makes species from this genus a promising platform for investigating the evolution of carbon metabolism and energy conservation. The Shewanella phylogeny is diverged into two major branches, referred to as group 1 and group 2. While the genotype-phenotype connections of group 2 species have been extensively studied with metabolic modeling, a genome-scale model has been missing for the group 1 species. The metabolic reconstruction of Shewanella piezotolerans strain WP3 represented the first model for Shewanella group 1 and the first model among piezotolerant and psychrotolerant deep-sea bacteria. The model brought insights into the mechanisms of energy conservation in WP3 under anaerobic conditions and highlighted its metabolic flexibility in using diverse carbon sources. Overall, the model opens up new opportunities for investigating energy conservation and metabolic adaptation, and it provides a prototype for systems-level modeling of other deep-sea microorganisms.

scholarly journals A Rapid Phenotypic Whole-Cell Screening Approach for the Identification of Small-Molecule Inhibitors That Counter β-Lactamase Resistance in Pseudomonas aeruginosa

2017 ◽  
Vol 23 (1) ◽  
pp. 55-64 ◽  
Author(s):  
Deanna Collia ◽  
Thomas D. Bannister ◽  
Hao Tan ◽  
Shouguang Jin ◽  
Taimour Langaee ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Small Molecule ◽  
Small Molecule Inhibitors ◽  
Laboratory Strain ◽  
Multidrug Resistant ◽  
First Line ◽  
Strain Pao1 ◽  
Whole Cell ◽  
Bacterial Sensitivity ◽  
Opportunistic Human Pathogen

Pseudomonas aeruginosa is an opportunistic human pathogen that is prevalent in hospitals and continues to develop resistance to multiple classes of antibiotics. Historically, β-lactam antibiotics have been the first line of therapeutic defense. However, the emergence of multidrug-resistant (MDR) strains of P. aeruginosa, such as AmpC β-lactamase overproducing mutants, limits the effectiveness of current antibiotics. Among AmpC hyperproducing clinical isolates, inactivation of AmpG, which is essential for the expression of AmpC, increases bacterial sensitivity to β-lactam antibiotics. We hypothesize that inhibition of AmpG activity will enhance the efficacy of β-lactams against P. aeruginosa. Here, using a highly drug-resistant AmpC-inducible laboratory strain PAO1, we describe an ultra-high-throughput whole-cell turbidity assay designed to identify small-molecule inhibitors of the AmpG. We screened 645,000 compounds to identify compounds with the ability to inhibit bacterial growth in the presence of cefoxitin, an AmpC inducer, and identified 2663 inhibitors that were also tested in the absence of cefoxitin to determine AmpG specificity. The Z′ and signal-to-background ratio were robust at 0.87 ± 0.05 and 2.2 ± 0.2, respectively. Through a series of secondary and tertiary studies, including a novel luciferase-based counterscreen, we ultimately identified eight potential AmpG-specific inhibitors.

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