Modeling the effects of a Staphylococcal Enterotoxin B (SEB) on the apoptosis pathway

BACKGROUND: The lack of detailed understanding of the mechanism of action of many biowarfare agents poses an immediate challenge to biodefense efforts. Many potential bioweapons have been shown to affect the cellular pathways controlling apoptosis [1-4]. For example, pathogen-produced exotoxins such as Staphylococcal Enterotoxin B (SEB) and Anthrax Lethal Factor (LF) have been shown to disrupt the Fas-mediated apoptotic pathway [2,4]. To evaluate how these agents affect these pathways it is first necessary to understand the dynamics of a normally functioning apoptosis network. This can then serve as a baseline against which a pathogen perturbed system can be compared. Such comparisons can expose both the proteins most susceptible to alteration by the agent as well as the most critical reaction rates to better instill control on a biological network. RESULTS: We explore this through the modeling and simulation of the Fas-mediated apoptotic pathway under normal and SEB influenced conditions. We stimulated human Jurkat cells with an anti-Fas antibody in the presence and absence of SEB and determined the relative levels of seven proteins involved in the core pathway at five time points following exposure. These levels were used to impute relative rate constants and build a quantitative model consisting of a series of ordinary differential equations (ODEs) that simulate the network under both normal and pathogen-influenced conditions. Experimental results show that cells exposed to SEB exhibit an increase in the rate of executioner caspase expression (and subsequently apoptosis) of 1 hour 43 minutes (± 14 minutes), as compared to cells undergoing normal cell death. CONCLUSION: Our model accurately reflects these results and reveals intervention points that can be altered to restore SEB-influenced system dynamics back to levels within the range of normal conditions

PheMaDB: A solution for storage, retrieval, and analysis of high throughput phenotype data

<p>Abstract</p> <p>Background</p> <p>OmniLog™ phenotype microarrays (PMs) have the capability to measure and compare the growth responses of biological samples upon exposure to hundreds of growth conditions such as different metabolites and antibiotics over a time course of hours to days. In order to manage the large amount of data produced from the OmniLog™ instrument, PheMaDB (Phenotype Microarray DataBase), a web-based relational database, was designed. PheMaDB enables efficient storage, retrieval and rapid analysis of the OmniLog™ PM data.</p> <p>Description</p> <p>PheMaDB allows the user to quickly identify records of interest for data analysis by filtering with a hierarchical ordering of Project, Strain, Phenotype, Replicate, and Temperature. PheMaDB then provides various statistical analysis options to identify specific growth pattern characteristics of the experimental strains, such as: outlier analysis, negative controls analysis (signal/background calibration), bar plots, pearson's correlation matrix, growth curve profile search, <it>k</it>-means clustering, and a heat map plot. This web-based database management system allows for both easy data sharing among multiple users and robust tools to phenotype organisms of interest.</p> <p>Conclusions</p> <p>PheMaDB is an open source system standardized for OmniLog™ PM data. PheMaDB could facilitate the banking and sharing of phenotype data. The source code is available for download at <url>http://phemadb.sourceforge.net</url>.</p

Genomic Signatures of Strain Selection and Enhancement in Bacillus atrophaeus var. globigii, a Historical Biowarfare Simulant

(BG) as a simulant for biological warfare (BW) agents, knowledge of its genome composition is limited. Furthermore, the ability to differentiate signatures of deliberate adaptation and selection from natural variation is lacking for most bacterial agents. We characterized a lineage of BGwith a long history of use as a simulant for BW operations, focusing on classical bacteriological markers, metabolic profiling and whole-genome shotgun sequencing (WGS). on the nucleotide level. WGS of variants revealed that several strains were mixed but highly related populations and uncovered a progressive accumulation of mutations among the “military” isolates. Metabolic profiling and microscopic examination of bacterial cultures revealed enhanced growth of “military” isolates on lactate-containing media, and showed that the “military” strains exhibited a hypersporulating phenotype.Our analysis revealed the genomic and phenotypic signatures of strain adaptation and deliberate selection for traits that were desirable in a simulant organism. Together, these results demonstrate the power of whole-genome and modern systems-level approaches to characterize microbial lineages to develop and validate forensic markers for strain discrimination and reveal signatures of deliberate adaptation

VX Hydrolysis by Human Serum Paraoxonase 1: A Comparison of Experimental and Computational Results

Human Serum paraoxonase 1 (HuPON1) is an enzyme that has been shown to hydrolyze a variety of chemicals including the nerve agent VX. While wildtype HuPON1 does not exhibit sufficient activity against VX to be used as an in vivo countermeasure, it has been suggested that increasing HuPON1's organophosphorous hydrolase activity by one or two orders of magnitude would make the enzyme suitable for this purpose. The binding interaction between HuPON1 and VX has recently been modeled, but the mechanism for VX hydrolysis is still unknown. In this study, we created a transition state model for VX hydrolysis (VXts) in water using quantum mechanical/molecular mechanical simulations, and docked the transition state model to 22 experimentally characterized HuPON1 variants using AutoDock Vina. The HuPON1-VXts complexes were grouped by reaction mechanism using a novel clustering procedure. The average Vina interaction energies for different clusters were compared to the experimentally determined activities of HuPON1 variants to determine which computational procedures best predict how well HuPON1 variants will hydrolyze VX. The analysis showed that only conformations which have the attacking hydroxyl group of VXts coordinated by the sidechain oxygen of D269 have a significant correlation with experimental results. The results from this study can be used for further characterization of how HuPON1 hydrolyzes VX and design of HuPON1 variants with increased activity against VX.United States. Defense Threat Reduction Agenc

Molecular Dynamics Simulations of Anti-Aggregation Effect of Ibuprofen

Using implicit solvent molecular dynamics and replica exchange simulations, we study the impact of ibuprofen on the growth of wild-type Aβ fibrils. We show that binding of ibuprofen to Aβ destabilizes the interactions between incoming peptides and the fibril. As a result, ibuprofen interference modifies the free energy landscape of fibril growth and reduces the free energy gain of Aβ peptide binding to the fibril by ≃2.5 RT at 360 K. Furthermore, ibuprofen interactions shift the thermodynamic equilibrium from fibril-like locked states to disordered docked states. Ibuprofen's anti-aggregation effect is explained by its competition with incoming Aβ peptides for the same binding site located on the fibril edge. Although ibuprofen impedes fibril growth, it does not significantly change the mechanism of fibril elongation or the structure of Aβ peptides bound to the fibril

Naproxen Interferes with the Assembly of Aβ Oligomers Implicated in Alzheimer's Disease

Experimental and epidemiological studies have shown that the nonsteroidal antiinflammatory drug naproxen may be useful in the treatment of Alzheimer's disease. To investigate the interactions of naproxen with Aβ dimers, which are the smallest cytotoxic aggregated Aβ peptide species, we use united atom implicit solvent model and exhaustive replica exchange molecular dynamics. We show that naproxen ligands bind to Aβ dimer and penetrate its volume interfering with the interpeptide interactions. As a result naproxen induces a destabilizing effect on Aβ dimer. By comparing the free-energy landscapes of naproxen interactions with Aβ dimers and fibrils, we conclude that this ligand has stronger antiaggregation potential against Aβ fibrils rather than against dimers. The analysis of naproxen binding energetics shows that the location of ligand binding sites in Aβ dimer is dictated by the Aβ amino acid sequence. Comparison of the in silico findings with experimental observations reveals potential limitations of naproxen as an effective therapeutic agent in the treatment of Alzheimer's disease

The transition state conformations for VX P(+) and VX P(−).

<p>The structures were generated with the QM/MM capabilities of the AMBER molecular dynamics suite <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0020335#pone.0020335-Case1" target="_blank">[21]</a>.</p