Accession Number:

ADA433516

Title:

Using Advanced Hybrid Stochastic Methods to Design Biological Gene Networks That Rapidly Respond To Harmful Substance Detection

Descriptive Note:

Corporate Author:

MINNESOTA UNIV MINNEAPOLIS DEPT OF CHEMICAL ENGINEERING AND MATERIALS SCIENCE

Personal Author(s):

Report Date:

2004-12-01

Pagination or Media Count:

3.0

Abstract:

Force protection during both peacetime and combat is extremely important to the safety and efficiency of the Army. Currently, the detection of harmful biological organisms involves microbiological culturing and biochemical tests that require at least three hours and access to a laboratory. Chemical tests for the detection of harmful chemical toxins are faster, but still require a mobile laboratory. On the battlefield, access to a laboratory may be limited and timing is critical. The method of detecting harmful substances must be fast and highly portable, capable of being carried by every soldier. By increasing the number of detectors on the battlefield, one increases the chance of successfully detecting a harmful substance. However, detectors that use biochemical tests, such as Real-Time PCR, to monitor for biological agents will always be limited to mobile laboratories, operated by trained biochemists. Biological organisms, on the other hand, are able to innately interact with the chemical world and specifically distinguish harmful chemicals or biological organisms, such as Sarin or Anthrax. Biological organisms possess an internal analog signal processor, its regulated gene expression, that responds to environmental stimuli and produces a programmed response. By harnessing a biological organisms ability to interact with specific harmful substances, detect their presence, and produce a programmed response such as fluorescence or color change, we can engineer organisms to become detectors possessing extraordinary sensitivity and specificity. One benefit to the usage of biological harmful substance detectors is that they self-replicate, operate independently, and may be deployed prior to any soldier setting foot on the ground.

Subject Categories:

  • Genetic Engineering and Molecular Biology
  • Microbiology
  • Statistics and Probability
  • Miscellaneous Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE