A Universal Bio-Sensing Platform James Diggans, Principal Investigator Problems:
Current biosensor technology is extremely limited for several reasons. Most research platforms focus on more traditional diseases or environmental hazards instead of biothreats. Individual sensors look for a few very specific threats (10-12 at most), and existing biothreat sensors are tested only in the laboratory environment. Moreover, only well-trained clinical technicians can use the sensors.
Objectives:
This project will develop a more generalized sensing platform to identify a larger number of pathogens, leveraging microarray technology and automated processing expertise. Steps will include identifying sequences that will broadly attach to genetic material of various organisms, designing microarray probes for the sequences, and designing algorithms to mine the microarray data and classify the organisms in the environment.
Activities:
Microarray design will include selection of representative DNA sequences to be used as microarray probes, applying modeling and simulation to identify inappropriate sequences. Pattern classification: will involve application of data mining and pattern recognition techniques to distinguish among patterns for different agents. Multivariate pattern classification techniques will be used, focusing on techniques that can handle large amounts of data.
Impact:
The project will develop a handheld sensor that can automate sensing analysis of any known biothreat agent, and has the capability to expand easily to meet novel threats. A byproduct of this work will be identification of the sequences that prove informative for distinguishing between organisms, thereby providing a mechanism to compare different pathogenic agents.
Approved for Public Release: 06-1448 Presentation [PDF]
Camelid (Llama glama) Immunomolecules for Advanced Biosensing Lynn Cooper, Principal Investigator Problems:
Many biosensor platforms use immunomolecules called antibodies to detect microbial pathogens and toxins. Standard, reagent-grade antibodies are not heat stable and can degrade quickly under harsh environmental conditions. Replacing these temperature-sensitive reagents with a new type of immunomolecule that is environmentally stable could greatly increase the country's bio-sensing capabilities.
Objectives:
The objective of this work is to develop and test prototype immunoassays that are based on environmentally stable molecules. Our research hypothesis is that small, toxin-specific immunomolecules derived from camelid species, specifically llamas, can be efficiently produced and applied to the next generation of field-deployable biosensors and detection/diagnostic platforms.
Activities:
Our research investigates the in vivo and in vitro properties of heavy-chain antibodies produced by llamas. In short, toxin-specific antibodies will be isolated from llamas, characterized, and then incorporated into an existing hand-held assay format for comparison with standard antibody-based assays.
Impact:
This work fills a critical need for robust field-deployable reagents for antibody-based biosensor technologies. Its direct application is to biosensors designed to detect microbial threat agents or their toxins. It has broader importance for the fields of immuno-detection and immuno-diagnostics because it demonstrates the feasibility of improving the basic component common to all platform and assay types: the immunomolecule.
Approved for Public Release: 06-1523
Detection of Viruses by Fluorescence Generated From Artificial RNA Constructs Juan Arroyo, Principal Investigator Problems:
Emerging and engineered viruses inherently elude bio-sensors or methods used to diagnose a viral infection. Most systems for virus detection either hunt for known gene sequences or rely on binding to anticipated virus surface proteins. Although unknown viruses have unidentified genes and are coated with unfamiliar structures, they maintain predictable virus generation machinery.
Objectives:
Focusing on virus detection through the innate activities of proteins engaged in replication provides the ability to widen the spectrum of detection to entire families of viruses with one system. Our program will evaluate the ability to detect viruses of the dengue family and will expand to other families of priority pathogens. We will focus on speed, sensitivity, and wide-spectrum detection.
Activities:
We will create artificial RNA constructs encoding motifs recognizable by virus enzymes. The artificial RNA will also encode a gene to yield fluorescent activity. The incorporation of the RNA into a virus-infected cell line will trigger amplification of the signal able to generate fluorescence. Success with dengue viruses will direct the effort to other families of interest.
Impact:
We will develop a cell-based technology for broad spectrum detection of viruses. The program will concentrate on detection of unknown, emerging, and genetically altered viruses. Cell culture-based detection will complement existing genome amplification-based technologies. This cost-effective approach may become a first-tier sensing countermeasure of interest to national security and public safety.
Approved for Public Release: 07-1310 Presentation [PDF]
End-to-End Model for Evaluating Planned Responses for Pandemic Influenza Jennifer Mathieu, Principal Investigator Problems:
Federal guidelines for disaster response face many challenges; for example, the National Response Plan has not been tested. Pandemic influenza could have a devastating impact on the population (e.g., ~40% employee absenteeism), leading to consequences for maintaining critical infrastructure. Currently, there is no means for the national level to evaluate what is being planned at the state and local levels.
Objectives:
Local to national operational plans should be evaluated now, including estimating the effectiveness of planned roles, responsibilities, and procedures; determining gaps in responsibilities and risk assessment; identifying pandemic affected critical infrastructure; and performing trade-off analyses under limited resources and personnel. To this end, an end-to-end process model is proposed for evaluating planned responses for pandemic influenza, useful at all levels.
Activities:
This research presents an opportunity to link sponsors involved in pandemic influenza response; collaborations are being actively pursued from the local to national level. Impacted critical infrastructure could include staffing medical facilities, communications infrastructure, as well as food and commodity distribution. Information, patient, and materiel flows are being modeled in a discrete event simulation to evaluate outcomes for selected scenarios.
Impact:
Output of this analysis will provide input to decision makers at all levels for planning and infrastructure analysis. Tailored prototypes will be available to collaborators (e.g., DHHS, DHS, USDA; and regional, state, and local groups) in August 2008. Individual operational procedures for pandemic influenza will be placed into the context of an overall, end-to-end pandemic influenza planning and response model.
Approved for Public Release: 08-0557 Presentation [PDF]
Genomics for Bioforensics Lynette Hirschman, Principal Investigator Problems:
Bioforensics is used to distinguish between an outbreak caused by a naturally occurring biological agent from that caused by an artificially introduced bioagent, and further, between a known strain and an engineered organism.
Objectives:
The objective is to create a phylogenetics-based sample matching procedure for attribution. Given the sequenced genome of an agent, such as influenza or foot and mouth disease, our goals are to determine its most likely source, based on comparison to a database of sequenced reference samples and their associated time-space coordinates, and provide a probability for that determination.
Activities:
We will start with one virus (influenza) and then generalize the methodology and matching procedure for additional viruses and engineered viruses. Our exploratory work used 200 influenza sequences (from the Institute for Genomic Research using New York State data) to develop phylogenetic trees to identify and explain outliers (e.g., travelers returning from the UK with a variant flu strain).
Impact:
The science underlying bioforensics supports related work on the modeling, prediction and management of disease outbreaks, including applications to epidemiology, public health surveillance, vaccine selection and development of new vaccines and drugs.
Approved for Public Release: 08-0542 Presentation [PDF]
Human Monoclonal Antibodies for Neutralization and Diagnosis of H5N1 Juan Arroyo, Principal Investigator Problems:
Treatments for infectious diseases depend on vaccines, antimicrobials, or passive transfer of antibodies. The source of antibodies may be polyclonal (serum) or monoclonal. Monoclonal antibodies have yielded dramatic therapeutic benefits in cancer treatment worldwide. This same power may be used to bind and neutralize toxins, viruses, and bacteria. Our approach will produce 100% human monoclonals to avoid common side effects.
Objectives:
We will use a new methodology for producing human monoclonal antibodies and assess its efficiency and capacity to generate antibodies against the pandemic strain of avian influenza, the H5N1 virus. We will establish the superior efficiency of this technology over competing technologies. Our ultimate goal is to develop therapies to prevent H5N1 infection in humans.
Activities:
We will differentiate B cells derived from human tonsils to yield clones capable of secreting high-specificity antibody, screen for antibody binding to the hemagglutinin protein of H5N1 virus, test for a subset that can neutralize H5N1 virus, and map where on the hemagglutinin protein the antibodies bind. We expect to find sites unique to H5N1 and universal to influenza hemagglutinin proteins.
Impact:
We will develop a rapid and unique approach to producing monoclonal antibodies that protect against pathogens and toxins. Rapid scale-up will produce large amounts of antibodies for stockpiling. Antibodies can be used for diagnosis or as injectable therapy for protection against lethal outcomes. With cost-effective manufacturing, the approach may become a deployable countermeasure of interest to national security and the U.S. population.
Approved for Public Release: 06-1405 Presentation [PDF]
Mathematical Modeling of Early Detection of Infectious Disease Outbreaks: Toward Real-Time Surveillance Mojdeh Mohtashemi, Principal Investigator Problems:
Global health, threatened by emerging infectious diseases, increasingly depends on the rapid acquisition, processing, and interpretation of massive amounts of data. Despite moderate advancements in data acquisition, real-time interpretation of data remains primitive. Early detection of infectious disease outbreaks requires timely and accurate detection of real-time epidemiological events for which current public health surveillance is inadequately prepared.
Objectives:
We propose to develop mathematical and computational models for early detection of unusual epidemiologic trends based on historical and real-time data from collaborating hospitals and emergency departments, thus advancing the art of surveillance from post-epidemic detection to pre-epidemic detection. Such methods can be applied to a broad range of outbreaks of infectious diseases, whether naturally occurring or maliciously instigated.
Activities:
We will acquire historical and real-time data from Harvard Medical School-affiliated hospitals and other collaborating hospitals. We will develop spatio-temporal and social contact structure models of early detection of infectious disease outbreaks. These models will be validated using expert assessments and standard statistical and simulation techniques, and incorporated into AEGIS, a real-time surveillance system at the Children's Hospital, Boston.
Impact:
The project outcomes will provide the public health community with novel methods for early detection of infectious disease outbreaks, while advancing MITRE expertise in mathematical modeling of infectious disease and biosurveillance. This work will position us to play a critical role in public health surveillance and biodefense research and will support key MITRE sponsors.
Approved for Public Release: 05-0230 Presentation [PDF]
Mathematics for Pathogenomics Andrzej Brodzik, Principal Investigator Problems:
Bacillus anthracis is one of the best known and most lethal pathogens. Similarity of cereus species and anthracis strains significantly obstructs forensics tasks, which in effect have to rely on subtle differences between genomes. Current methods are expensive, ad hoc, and only partly effective in identification of anthracis strains. The problem is compounded as new strains are being discovered and sequenced, and as design of synthetic pathogenic sequences becomes possible.
Objectives:
The advantage of tandem repeats over other biomarkers is in their high allelic diversity, resolving power and mutation rates. These properties make tandem repeats well suitable for the analysis of highly homologous and evolutionary young genomes such as anthrax. The goal of this research is to produce a complete mathematical characterization (a list of all variable number tandem repeats, or VNTRs) of the bacillus anthracis genome. This list will lead to the development of optimal anthrax strain markers.
Activities:
Previously developed algorithms for DNA sequence interrogation will be refined and encoded in MATLAB/C. Genomes of selected bacillus anthracis strains will be investigated, and all exact and approximate tandem repeats will be identified and cataloged. Lists of repeats of different anthrax strains will be compared and best strain markers will be selected.
Impact:
A more efficacious forensic approach towards anthrax strain ID will be developed. This approach will be particularly useful when applied to new sequence data with as yet undetermined mathematical characteristics (several sequencing efforts are currently being pursued at TIGR and LANL). Apart from Homeland Defense applications, the analysis and the approaches developed can be easily adapted for certain key molecular biology and applied molecular biology tasks, such as: phylogenetic studies of genomes, ab novo gene finding, synthetic biology applications (e.g., monitoring synthetic sequence requests), and personalized medicine (detection of predisposition to genetic diseases).
Approved for Public Release: 08-0289 Presentation [PDF]
MEG: Mapping Epidemic Growth Janet Hitzeman, Principal Investigator Problems:
The journal Nature has developed an award-winning system in Google Earth for mapping epidemic growth. Currently, the events of victims contracting illnesses are manually entered into the system, causing the data to be out-of-date and limiting the data to one disease only due to time constraints and lack of necessary personnel.
Objectives:
By automating this existing system using event extraction techniques, we will provide a system with up-to-date data which handles multiple diseases. Experts tracking diseases will have enhanced capability for determining the path of pandemics, and will have at their fingertips the same tool that their community has already expressed interest in.
Activities:
We will augment an in-house tool to perform event extraction, and then use it to automate the existing tool developed by Nature. It will process articles from the online World Health Organization (WHO) website and map information concerning victims of various diseases onto the Google Earth-based website.
Impact:
This work will contribute directly to enhancing capabilities of systems for current sponsors. It will also help to establish collaborations with other partners in the bioinformatics domain. These techniques can be readily applied to related domains such as tracking diseases in animals, plants, food, and the environment.
Approved for Public Release: 08-0220 Presentation [PDF]
Synthetic Biology: Engineering at the Sub-Cellular Level John Dileo, Principal Investigator Problems:
The proliferation of weapons of mass destruction such as chemical weapons (CW) poses a significant national security concern. However, the United States has only limited ability to remotely monitor suspected facilities for CW production. We believe that cellular mechanisms can be engineered to generate a cell-based system that can detect chemical signatures associated with CW production and produce a remotely observable signal.
Objectives:
We will develop the experimental and computational tools for the design of biologic systems at the genome, protein, and system level. More specifically, we will develop a biologically based sense-and-respond system for the remote detection of CW production.
Activities:
We will accomplish our goals through an iterative cycle of computational design, laboratory implementation and testing, and field validation. Specifically, we will (1) use recently developed computational methods to design proteins (receptors) that can detect small molecules associated with CW production, (2) implement complex logical processing circuitry in DNA, and (3) couple multiple protein detectors to DNA circuitry.
Impact:
This project will build on existing Technology Program investments in the life sciences and extend MITRE's expertise into new areas (experimental molecular biology and synthetic biology) that have the potential to assist multiple sponsors. This will provide MITRE with new capabilities that will allow us to better support current and future sponsors.
Approved for Public Release: 05-1506 Presentation [PDF]
The Application of Intelligence Analytical Tools (ChronoSkope) to the Progression of H5N1 Avian Influenza Viruses Across Asia Regina Tan, Principal Investigator Problems:
Avian influenza is hypothesized to be the next source of pandemic influenza. However, failure to understand disease transmission will hamper international control measures, a vulnerability in U.S. biosecurity measures. Modern techniques do not visualize disease transmission among human and animal populations. We hypothesize that ChronoSkope will provide an intuitive display, enabling more robust geographic and temporal analyses.
Objectives:
Our objective is to enable more comprehensive and intuitive detection and mitigation of disease transmission pathways. Specifically, we will develop new methods with ChronoSkope-like tools to achieve intuitive display and integration of genetic and medical intelligence (who/what/where/when) data.
Activities:
We will interview sponsors, survey methods and tools, and develop a framework for technology-enabled epidemiological analysis. We will work with government scientific collaborators to refine and extend tool capabilities. We will ingest data and develop and test hypotheses to compare with existing (World Health Organization and other) analysis. We will determine whether technology-enabled analysis provides additional benefits to users.
Impact:
ChronoSkope presents an opportunity to merge genetic and medical intelligence data. Public health professionals need to visualize (and mitigate) international influenza transmission. Intelligence professionals need to validate analytic assessments. ChronoSkope, with aspects intuitive to both the public health and intelligence fields, should provide enhanced analytic capabilities and facilitate collaboration between two communities with a history of difficult interactions.
Approved for Public Release: 07-1535
Virulence Factor Ontology for Biosecurity Marc Colosimo, Principal Investigator Problems:
Rapid identification of emerging or novel pathogens is an important public health and biosecurity issue. While sequence data increases rapidly, there is no agreed upon annotation standard for virulence factors. Information about virulence factors, their mechanisms of action, and metadata associating the pathogens with hosts and environmental conditions is lost or difficult to access in machine computable form.
Objectives:
Our objective is to develop a draft virulence factor ontology that will provide an organizing framework for annotating virulence factors, key pathways, and associated metadata, such as hosts, reservoirs, and environmental conditions. We will then host a workshop for key stakeholders to review the draft ontology and develop next steps.
Activities:
We will explore the creation of a virulence factor ontology for a catalog of known virulence factors and organisms by 1) drafting an ontology working with the pathogen community; 2) organizing a workshop where we can present the draft ontology to the community; and 3) summarizing the workshop decisions and sketching out next steps.
Impact:
Using an ontology of virulence factors might allow us to answer important questions: If we had had a better knowledge of circulating viruses, could we have identified the SARS corona virus faster? If we have a better understanding of the range of pathogenic organisms in the soil, air, or bodies of water, can this ontology provide useful baselines for improved biosensing?
Approved for Public Release: 07-1610 Presentation [PDF]
Last Updated:05/05/2008 | ^TOP | 
