Topic Information Award/Contract Number Proposal Information Company Performance

Rare Variant Detection Using Next Generation Sequencing Technology

N10PC20199 1011114
(FY10.1 Phase I)
Utility of Next Generation Sequencing Data for Rare Variant Detection and Identification in a Bacterial Sample

Eureka Genomics
750 Alfred Nobel Drive, #108
hercules, CA 94547-1387


The long-term objective is to develop a statistically sound rare variant (SNPs) detection and SNP profile comparison method, based on high throughput sequencing (HTS) and advanced bioinformatics, that is capable of detecting a mutations present in as low as 1/5000 bacterial cells in the sample. This will be accomplished in five tasks: (1) Develop and test a statistical model to predict sample coverage required to detect SNPs in a strain of given rarity with pre-specified level of confidence. (2) Determine the ability to use HTS reads to assign SNPs to correct rare variants (3) Quantify the effect of limitations of the sequencing platform on rare variant detection (4) Develop a statistical framework to compare SNP profiles, (5) Develop a research plan for phase II. Rare variant detection and matching will be important for prosecution of bioterrorism attacks or attempts. The commercial opportunity of the forensic application is unknown, but commercial applications in clinical diagnostics associated with the detection of drug resistant variants are extensive. There is an urgent need (estimated 100M USD US market annually) for a diagnostic test to identify the presence of multi- or extensively- drug resistant tuberculosis present in 1 percent or less of the sample.

Molecular Recognition for Explosives Detection

N10PC20203 1011131
(FY10.1 Phase I)
Imprinted polymer nanoparticles for explosives detection

Seacoast Science, Inc.
2151 Las Palmas Drive
Suite C
Calrsbad, CA 92011-1575


This Small Business Innovative Research Phase I project consists of fundamental research into molecularly imprinted polymer (MIP) nanoparticles to act as sensing points in novel detection system for explosives. The system is based upon MIP nanoparticles deposited upon a MEMS-based chemicapacitive sensor array. As the MIP nanoparticle binds the explosive, the polarizability of the material changes thus affecting the measured capacitance on the sensor chip. The monomer, cross-linker, and template of the MIP nanoparticle will be systematically varied to optimize the detection of explosives. The MIP nanoparticles will be synthesized by Dr. David Spivak. Similar materials have been developed and investigated in his laboratory in the Chemistry Department at the Louisiana State University (LSU). Sensors coated with these materials will be tested using Seacoast Science`s test systems under varied environmental conditions. Tasks include: design, synthesis, and characterization of MIP nanoparticles; inkjet deposition of MIP nanoparticles; and testing of the coated sensors against one explosive simulant and environmental interferrents. The overall goal of this program is the development and demonstration of an inventive biologically-inspired sensing motif for the sensitive and selective detection of not only explosives but eventually a wide range of chemicals relevant to the mission of DHS.

GPS Resolution in Denied Location (GRIDLOC)

N10PC20207 1011077
(FY10.1 Phase I)
Cheetah-Traks: Subterranean Navigation via Inertial Sensors and Multipath Resistant RF Ranging

TrellisWare Technologies, Inc.
16516 Via Esprillo
Suite 300
San Diego, CA 92127-1728


To support DHS`s goals of developing real-time positioning of first responder personnel TrellisWare Technologies proposes to extend and integrate two advanced systems for accurate position resolution in severe multi-path, GPS-denied environments such as subterranean tunnels. This approach will demonstrate the effectiveness of integrating these systems consisting of low drift inertial sensors with an iteration-based multi-path resistant RF communications/ranging radio to create a high precision denied GPS navigation solution called Cheetah-Traks. The proposed integration will focus on the enhancement of key metrics which have limited the success and accuracy of competing navigation solutions providing a tactically relevant navigation solution without compromising performance, ease of use and deployment, mobility, and scalability.