Estimating the Location and Spatial Extent of a Covert Anthrax Release

Rapidly identifying the features of a covert release of an agent such as anthrax could help to inform the planning of public health mitigation strategies. Previous studies have sought to estimate the time and size of a bioterror attack based on the symptomatic onset dates of early cases. We extend the scope of these methods by proposing a method for characterizing the time, strength, and also the location of an aerosolized pathogen release. A back-calculation method is developed allowing the characterization of the release based on the data on the first few observed cases of the subsequent outbreak, meteorological data, population densities, and data on population travel patterns. We evaluate this method on small simulated anthrax outbreaks (about 25–35 cases) and show that it could date and localize a release after a few cases have been observed, although misspecifications of the spore dispersion model, or the within-host dynamics model, on which the method relies can bias the estimates. Our method could also provide an estimate of the outbreak's geographical extent and, as a consequence, could help to identify populations at risk and, therefore, requiring prophylactic treatment. Our analysis demonstrates that while estimates based on the first ten or 15 observed cases were more accurate and less sensitive to model misspecifications than those based on five cases, overall mortality is minimized by targeting prophylactic treatment early on the basis of estimates made using data on the first five cases. The method we propose could provide early estimates of the time, strength, and location of an aerosolized anthrax release and the geographical extent of the subsequent outbreak. In addition, estimates of release features could be used to parameterize more detailed models allowing the simulation of control strategies and intervention logistics

Neutralization of Botulinum Neurotoxin by a Human Monoclonal Antibody Specific for the Catalytic Light Chain

Background: Botulinum neurotoxins (BoNT) are a family of category A select bioterror agents and the most potent biological toxins known. Cloned antibody therapeutics hold considerable promise as BoNT therapeutics, but the therapeutic utility of antibodies that bind the BoNT light chain domain (LC), a metalloprotease that functions in the cytosol of cholinergic neurons, has not been thoroughly explored. Methods and Findings: We used an optimized hybridoma method to clone a fully human antibody specific for the LC of serotype A BoNT (BoNT/A). The 4LCA antibody demonstrated potent in vivo neutralization when administered alone and collaborated with an antibody specific for the HC. In Neuro-2a neuroblastoma cells, the 4LCA antibody prevented the cleavage of the BoNT/A proteolytic target, SNAP-25. Unlike an antibody specific for the HC, the 4LCA antibody did not block entry of BoNT/A into cultured cells. Instead, it was taken up into synaptic vesicles along with BoNT/A. The 4LCA antibody also directly inhibited BoNT/A catalytic activity in vitro. Conclusions: An antibody specific for the BoNT/A LC can potently inhibit BoNT/A in vivo and in vitro, using mechanisms not previously associated with BoNT-neutralizing antibodies. Antibodies specific for BoNT LC may be valuable components o

Investigating antimalarial drug interactions of emetine dihydrochloride hydrate using CalcuSyn-based interactivity calculations

The widespread introduction of artemisinin-based combination therapy has contributed to recent reductions in malaria mortality. Combination therapies have a range of advantages, including synergism, toxicity reduction, and delaying the onset of resistance acquisition. Unfortunately, antimalarial combination therapy is limited by the depleting repertoire of effective drugs with distinct target pathways. To fast-track antimalarial drug discovery, we have previously employed drug-repositioning to identify the anti-amoebic drug, emetine dihydrochloride hydrate, as a potential candidate for repositioned use against malaria. Despite its 1000-fold increase in in vitro antimalarial potency (ED50 47 nM) compared with its anti-amoebic potency (ED50 26±32 uM), practical use of the compound has been limited by dose-dependent toxicity (emesis and cardiotoxicity). Identification of a synergistic partner drug would present an opportunity for dose-reduction, thus increasing the therapeutic window. The lack of reliable and standardised methodology to enable the in vitro definition of synergistic potential for antimalarials is a major drawback. Here we use isobologram and combination-index data generated by CalcuSyn software analyses (Biosoft v2.1) to define drug interactivity in an objective, automated manner. The method, based on the median effect principle proposed by Chou and Talalay, was initially validated for antimalarial application using the known synergistic combination (atovaquone-proguanil). The combination was used to further understand the relationship between SYBR Green viability and cytocidal versus cytostatic effects of drugs at higher levels of inhibition. We report here the use of the optimised Chou Talalay method to define synergistic antimalarial drug interactivity between emetine dihydrochloride hydrate and atovaquone. The novel findings present a potential route to harness the nanomolar antimalarial efficacy of this affordable natural product

A Dynamical Systems Model for Combinatorial Cancer Therapy Enhances Oncolytic Adenovirus Efficacy by MEK-Inhibition

Oncolytic adenoviruses, such as ONYX-015, have been tested in clinical trials for currently untreatable tumors, but have yet to demonstrate adequate therapeutic efficacy. The extent to which viruses infect targeted cells determines the efficacy of this approach but many tumors down-regulate the Coxsackievirus and Adenovirus Receptor (CAR), rendering them less susceptible to infection. Disrupting MAPK pathway signaling by pharmacological inhibition of MEK up-regulates CAR expression, offering possible enhanced adenovirus infection. MEK inhibition, however, interferes with adenovirus replication due to resulting G1-phase cell cycle arrest. Therefore, enhanced efficacy will depend on treatment protocols that productively balance these competing effects. Predictive understanding of how to attain and enhance therapeutic efficacy of combinatorial treatment is difficult since the effects of MEK inhibitors, in conjunction with adenovirus/cell interactions, are complex nonlinear dynamic processes. We investigated combinatorial treatment strategies using a mathematical model that predicts the impact of MEK inhibition on tumor cell proliferation, ONYX-015 infection, and oncolysis. Specifically, we fit a nonlinear differential equation system to dedicated experimental data and analyzed the resulting simulations for favorable treatment strategies. Simulations predicted enhanced combinatorial therapy when both treatments were applied simultaneously; we successfully validated these predictions in an ensuing explicit test study. Further analysis revealed that a CAR-independent mechanism may be responsible for amplified virus production and cell death. We conclude that integrated computational and experimental analysis of combinatorial therapy provides a useful means to identify treatment/infection protocols that yield clinically significant oncolysis. Enhanced oncolytic therapy has the potential to dramatically improve non-surgical cancer treatment, especially in locally advanced or metastatic cases where treatment options remain limited.National Institutes of Health (U.S.) (Grant R01 CA118545)National Institutes of Health (U.S.) (Grant R01 CA095701)National Institutes of Health (U.S.) (Grant U54 CA11297)National Institutes of Health (U.S.) (Grant U54-CA112967

Challenges for Australia's Bio/Nanopharma Policies: trade deals, public goods and reference pricing in sustainable industrial renewal

Industrial renewal in the bio/nanopharma sector is important for the long term strength of the Australian economy and for the health of its citizens. A variety of factors, however, may have caused inadequate attention to focus on systematically promoting domestic generic and small biotechnology manufacturers in Australian health policy

Exploiting Clinical Trial Data Drastically Narrows the Window of Possible Solutions to the Problem of Clinical Adaptation of a Multiscale Cancer Model

The development of computational models for simulating tumor growth and response to treatment has gained significant momentum during the last few decades. At the dawn of the era of personalized medicine, providing insight into complex mechanisms involved in cancer and contributing to patient-specific therapy optimization constitute particularly inspiring pursuits. The in silico oncology community is facing the great challenge of effectively translating simulation models into clinical practice, which presupposes a thorough sensitivity analysis, adaptation and validation process based on real clinical data. In this paper, the behavior of a clinically-oriented, multiscale model of solid tumor response to chemotherapy is investigated, using the paradigm of nephroblastoma response to preoperative chemotherapy in the context of the SIOP/GPOH clinical trial. A sorting of the model's parameters according to the magnitude of their effect on the output has unveiled the relative importance of the corresponding biological mechanisms; major impact on the result of therapy is credited to the oxygenation and nutrient availability status of the tumor and the balance between the symmetric and asymmetric modes of stem cell division. The effect of a number of parameter combinations on the extent of chemotherapy-induced tumor shrinkage and on the tumor's growth rate are discussed. A real clinical case of nephroblastoma has served as a proof of principle study case, demonstrating the basics of an ongoing clinical adaptation and validation process. By using clinical data in conjunction with plausible values of model parameters, an excellent fit of the model to the available medical data of the selected nephroblastoma case has been achieved, in terms of both volume reduction and histological constitution of the tumor. In this context, the exploitation of multiscale clinical data drastically narrows the window of possible solutions to the clinical adaptation problem

Attomolar Detection of Botulinum Toxin Type A in Complex Biological Matrices

BACKGROUND: A highly sensitive, rapid and cost efficient method that can detect active botulinum neurotoxin (BoNT) in complex biological samples such as foods or serum is desired in order to 1) counter the potential bioterrorist threat 2) enhance food safety 3) enable future pharmacokinetic studies in medical applications that utilize BoNTs. METHODOLOGY/PRINCIPAL FINDINGS: Here we describe a botulinum neurotoxin serotype A assay with a large immuno-sorbent surface area (BoNT/A ALISSA) that captures a low number of toxin molecules and measures their intrinsic metalloprotease activity with a fluorogenic substrate. In direct comparison with the "gold standard" mouse bioassay, the ALISSA is four to five orders of magnitudes more sensitive and considerably faster. Our method reaches attomolar sensitivities in serum, milk, carrot juice, and in the diluent fluid used in the mouse assay. ALISSA has high specificity for the targeted type A toxin when tested against alternative proteases including other BoNT serotypes and trypsin, and it detects the holotoxin as well as the multi-protein complex form of BoNT/A. The assay was optimized for temperature, substrate concentration, size and volume proportions of the immuno-sorbent matrix, enrichment and reaction times. Finally, a kinetic model is presented that is consistent with the observed improvement in sensitivity. CONCLUSIONS/SIGNIFICANCE: The sensitivity, specificity, speed and simplicity of the BoNT ALISSA should make this method attractive for diagnostic, biodefense and pharmacological applications

Prioritizing Risks and Uncertainties from Intentional Release of Selected Category A Pathogens

This paper synthesizes available information on five Category A pathogens (Bacillus anthracis, Yersinia pestis, Francisella tularensis, Variola major and Lassa) to develop quantitative guidelines for how environmental pathogen concentrations may be related to human health risk in an indoor environment. An integrated model of environmental transport and human health exposure to biological pathogens is constructed which 1) includes the effects of environmental attenuation, 2) considers fomite contact exposure as well as inhalational exposure, and 3) includes an uncertainty analysis to identify key input uncertainties, which may inform future research directions. The findings provide a framework for developing the many different environmental standards that are needed for making risk-informed response decisions, such as when prophylactic antibiotics should be distributed, and whether or not a contaminated area should be cleaned up. The approach is based on the assumption of uniform mixing in environmental compartments and is thus applicable to areas sufficiently removed in time and space from the initial release that mixing has produced relatively uniform concentrations. Results indicate that when pathogens are released into the air, risk from inhalation is the main component of the overall risk, while risk from ingestion (dermal contact for B. anthracis) is the main component of the overall risk when pathogens are present on surfaces. Concentrations sampled from untracked floor, walls and the filter of heating ventilation and air conditioning (HVAC) system are proposed as indicators of previous exposure risk, while samples taken from touched surfaces are proposed as indicators of future risk if the building is reoccupied. A Monte Carlo uncertainty analysis is conducted and input-output correlations used to identify important parameter uncertainties. An approach is proposed for integrating these quantitative assessments of parameter uncertainty with broader, qualitative considerations to identify future research priorities

Iterative Structure-Based Peptide-Like Inhibitor Design against the Botulinum Neurotoxin Serotype A

The botulinum neurotoxin serotype A light chain (BoNT/A LC) protease is the catalytic component responsible for the neuroparalysis that is characteristic of the disease state botulism. Three related peptide-like molecules (PLMs) were designed using previous information from co-crystal structures, synthesized, and assayed for in vitro inhibition against BoNT/A LC. Our results indicate these PLMS are competitive inhibitors of the BoNT/A LC protease and their Ki values are in the nM-range. A co-crystal structure for one of these inhibitors was determined and reveals that the PLM, in accord with the goals of our design strategy, simultaneously involves both ionic interactions via its P1 residue and hydrophobic contacts by means of an aromatic group in the P2′ position. The PLM adopts a helical conformation similar to previously determined co-crystal structures of PLMs, although there are also major differences to these other structures such as contacts with specific BoNT/A LC residues. Our structure further demonstrates the remarkable plasticity of the substrate binding cleft of the BoNT/A LC protease and provides a paradigm for iterative structure-based design and development of BoNT/A LC inhibitors