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

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.

Rapid countermeasure discovery against Francisella tularensis based on a metabolic network reconstruction.

In the future, we may be faced with the need to provide treatment for an emergent biological threat against which existing vaccines and drugs have limited efficacy or availability. To prepare for this eventuality, our objective was to use a metabolic network-based approach to rapidly identify potential drug targets and prospectively screen and validate novel small-molecule antimicrobials. Our target organism was the fully virulent Francisella tularensis subspecies tularensis Schu S4 strain, a highly infectious intracellular pathogen that is the causative agent of tularemia and is classified as a category A biological agent by the Centers for Disease Control and Prevention. We proceeded with a staggered computational and experimental workflow that used a strain-specific metabolic network model, homology modeling and X-ray crystallography of protein targets, and ligand- and structure-based drug design. Selected compounds were subsequently filtered based on physiological-based pharmacokinetic modeling, and we selected a final set of 40 compounds for experimental validation of antimicrobial activity. We began screening these compounds in whole bacterial cell-based assays in biosafety level 3 facilities in the 20th week of the study and completed the screens within 12 weeks. Six compounds showed significant growth inhibition of F. tularensis, and we determined their respective minimum inhibitory concentrations and mammalian cell cytotoxicities. The most promising compound had a low molecular weight, was non-toxic, and abolished bacterial growth at 13 µM, with putative activity against pantetheine-phosphate adenylyltransferase, an enzyme involved in the biosynthesis of coenzyme A, encoded by gene coaD. The novel antimicrobial compounds identified in this study serve as starting points for lead optimization, animal testing, and drug development against tularemia. Our integrated in silico/in vitro approach had an overall 15% success rate in terms of active versus tested compounds over an elapsed time period of 32 weeks, from pathogen strain identification to selection and validation of novel antimicrobial compounds.

Biolog phenotype microarrays.

Phenotype microarrays nicely complement traditional genomic, transcriptomic, and proteomic analysis by offering opportunities for researchers to ground microbial systems analysis and modeling in a broad yet quantitative assessment of the organism's physiological response to different metabolites and environments. Biolog phenotype assays achieve this by coupling tetrazolium dyes with minimally defined nutrients to measure the impact of hundreds of carbon, nitrogen, phosphorous, and sulfur sources on redox reactions that result from compound-induced effects on the electron transport chain. Over the years, we have used Biolog's reproducible and highly sensitive assays to distinguish closely related bacterial isolates, to understand their metabolic differences, and to model their metabolic behavior using flux balance analysis. This chapter describes Biolog phenotype microarray system components, reagents, and methods, particularly as they apply to bacterial identification, characterization, and metabolic analysis.

Systems approach to investigating host-pathogen interactions in infections with the biothreat agent Francisella. Constraints-based model of Francisella tularensis.

BACKGROUND: Francisella tularensis is a prototypic example of a pathogen for which few experimental datasets exist, but for which copious high-throughout data are becoming available because of its re-emerging significance as biothreat agent. The virulence of Francisella tularensis depends on its growth capabilities within a defined environmental niche of the host cell. RESULTS: We reconstructed the metabolism of Francisella as a stoichiometric matrix. This systems biology approach demonstrated that changes in carbohydrate utilization and amino acid metabolism play a pivotal role in growth, acid resistance, and energy homeostasis during infection with Francisella. We also show how varying the expression of certain metabolic genes in different environments efficiently controls the metabolic capacity of F. tularensis. Selective gene-expression analysis showed modulation of sugar catabolism by switching from oxidative metabolism (TCA cycle) in the initial stages of infection to fatty acid oxidation and gluconeogenesis later on. Computational analysis with constraints derived from experimental data revealed a limited set of metabolic genes that are operational during infection. CONCLUSIONS: This integrated systems approach provides an important tool to understand the pathogenesis of an ill-characterized biothreat agent and to identify potential novel drug targets when rapid target identification is required should such microbes be intentionally released or become epidemic.

Modulation of iron homeostasis in macrophages by bacterial intracellular pathogens.

BACKGROUND: Intracellular bacterial pathogens depend on acquisition of iron for their success as pathogens. The host cell requires iron as an essential component for cellular functions that include innate immune defense mechanisms. The transferrin receptor TfR1 plays an important part for delivering iron to the host cell during infection. Its expression can be modulated by infection, but its essentiality for bacterial intracellular survival has not been directly investigated. RESULTS: We identified two distinct iron-handling scenarios for two different bacterial pathogens. Francisella tularensis drives an active iron acquisition program via the TfR1 pathway program with induction of ferrireductase (Steap3), iron membrane transporter Dmt1, and iron regulatory proteins IRP1 and IRP2, which is associated with a sustained increase of the labile iron pool inside the macrophage. Expression of TfR1 is critical for Francisella's intracellular proliferation. This contrasts with infection of macrophages by wild-type Salmonella typhimurium, which does not require expression of TfR1 for successful intracellular survival. Macrophages infected with Salmonella lack significant induction of Dmt1, Steap3, and IRP1, and maintain their labile iron pool at normal levels. CONCLUSION: The distinction between two different phenotypes of iron utilization by intracellular pathogens will allow further characterization and understanding of host-cell iron metabolism and its modulation by intracellular bacteria.

Severe pandemic (H1N1) 2009 influenza with false negative direct fluorescent antibody assay: case series.

Between May and June of 2009 we observed 4 patients that presented with severe influenza-like symptoms and respiratory failure. All cases tested negative for influenza A and B by direct fluorescent antibody assay. Further investigation revealed all cases to be positive for pandemic (H1N1) 2009 influenza virus by real-time RT-PCR. This article includes a description of these cases and the characteristics associated with them.

Constraint-based analysis of metabolic capacity of Salmonella typhimurium during host-pathogen interaction.

BACKGROUND: Infections with Salmonella cause significant morbidity and mortality worldwide. Replication of Salmonella typhimurium inside its host cell is a model system for studying the pathogenesis of intracellular bacterial infections. Genome-scale modeling of bacterial metabolic networks provides a powerful tool to identify and analyze pathways required for successful intracellular replication during host-pathogen interaction. RESULTS: We have developed and validated a genome-scale metabolic network of Salmonella typhimurium LT2 (iRR1083). This model accounts for 1,083 genes that encode proteins catalyzing 1,087 unique metabolic and transport reactions in the bacterium. We employed flux balance analysis and in silico gene essentiality analysis to investigate growth under a wide range of conditions that mimic in vitro and host cell environments. Gene expression profiling of S. typhimurium isolated from macrophage cell lines was used to constrain the model to predict metabolic pathways that are likely to be operational during infection. CONCLUSION: Our analysis suggests that there is a robust minimal set of metabolic pathways that is required for successful replication of Salmonella inside the host cell. This model also serves as platform for the integration of high-throughput data. Its computational power allows identification of networked metabolic pathways and generation of hypotheses about metabolism during infection, which might be used for the rational design of novel antibiotics or vaccine strains.

Francisella targets cholesterol-rich host cell membrane domains for entry into macrophages.

Francisella tularensis is a pathogen optimally adapted to efficiently invade its respective host cell and to proliferate intracellularly. We investigated the role of host cell membrane microdomains in the entry of F. tularensis subspecies holarctica vaccine strain (F. tularensis live vaccine strain) into murine macrophages. F. tularensis live vaccine strain recruits cholesterol-rich lipid domains ("lipid rafts") with caveolin-1 for successful entry into macrophages. Interference with lipid rafts through the depletion of plasma membrane cholesterol, through induction of raft internalization with choleratoxin, or through removal of raft-associated GPI-anchored proteins by treatment with phosphatidylinositol phospholipase C significantly inhibited entry of Francisella and its intracellular proliferation. Lipid raft-associated components such as cholesterol and caveolin-1 were incorporated into Francisella-containing vesicles during entry and the initial phase of intracellular trafficking inside the host cell. These findings demonstrate that Francisella requires cholesterol-rich membrane domains for entry into and proliferation inside macrophages.

Identification of a NIPSNAP homologue as host cell target for Salmonella virulence protein SpiC.

Salmonella enterica uses a type III secretion system encoded by SPI-2 to target specific virulence factors into the host cytosol of macrophages to inhibit the phagosomal-lysosomal maturation pathway. This ensures survival of Salmonella inside its intracellular niche, the Salmonella-containing vacuole (SCV). One such virulence factor is SpiC, which was previously shown to interfere with intracellular vesicular trafficking. In this study we have used a yeast two-hybrid assay to identify a NIPSNAP homologue as host cell target for SpiC that we have termed TassC. In vitro and in vivo co-purification of SpiC and TassC confirm the specificity of this interaction. Suppression of TassC production compensates a SpiC production deficit and allows spiC-Salmonella to survive within macrophages at levels comparable to wild-type Salmonella. We hypothesize that TassC is a host cell factor that determines vesicular trafficking in macrophages and is inactivated by Salmonella SpiC.