Bioterrorism is becoming a major threat for many countries as a new style of war. To protect the public from such a biological attack, we need to establish improved diagnostic methods and sampling strategies in order to identify the pathogens more rapidly and precisely. We hypothesize that a smart 3-D arrayed protein nanotube chip, can diagnose a single binding event of a target pathogen in a flowed liquid by using a combination of the biological recognition functions of antibodies conjugated onto the ends of nanotubes and size discrimination such that the bound target must bridge a pre-defined nanotube-Au substrate gap to complete the circuit. Subsequently, specific confirmation of target identity will be conducted through microbiological or molecular identification steps. The target concentration will be estimated in real time by conductivity change as the target pathogen bridges the gap between the nanotube and the second electrical terminal comprising an Au substrate. This identification based on fulfilling two characteristics (presence of antigen and physical size) is an innovative method because A) A positive signal will require two parameters to be satisfied, i.e. size and antigenicity, and therefore it will reduce 'false positive signals' from cell fragments, food matrices, and environmental materials in which pathogens reside; B) it provides electrical signals in real-time; C) it is non-destructive, permitting subsequent analyses; D) it does not amplify potential biohazard; E) it can be stacked allowing flowed samples and multiple targets to be addressed; and F) it is potentially widely deployable.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Minority Biomedical Research Support - MBRS (S06)
Project #
5S06GM060654-08
Application #
7391707
Study Section
Minority Programs Review Committee (MPRC)
Project Start
Project End
Budget Start
2007-04-01
Budget End
2008-03-31
Support Year
8
Fiscal Year
2007
Total Cost
$196,235
Indirect Cost
Name
Hunter College
Department
Type
DUNS #
620127915
City
New York
State
NY
Country
United States
Zip Code
10065
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