Feasibility of a DNA-Based Combinatorial Array Recognition Surface (CARS) in a Polyacrylamide Gel Matrix

Abstract

We report initial attempts al developing a self-assembled combinatorial DNA biosensor array which may be capable of binding and identilYing vir1ually any soluble analyte that binds the array by pattern recognition, in effect making it a universal biosensor surface. Data are presented for differential binding pattcrns of various analytcs to one-dimensional arrays of combinatorial DNA concatamer libraries, which are spatially separatcd according to size and charge by electrophoresis in polyacrylamide gels. These DNA concatamer librarics arc essentially composed of single-stranded (ss) random DNA 60mers, which fonn a "'smear" pattern in gels following elcctrophoresis. Whcn used to bind and detect various analytcs or mixtures of analytes in the gel, we refer to the DNA smear as a "Combinatorial Array Recognition Surface" (CARS). Differences in intrinsic fluorescence scanning patterns of CARS gel strips were compared before and after addition of various analytes to the arrays to detcct binding pallems. Scans revealed a high level of reproducibility for individual CARS arrays in a given gel with or without bound analytes. Scan patterns between diffcrent CARS gel strips were initially less reproducible, but purification of the DNA library using spin columns prior to electrophoresis improved gel-to-gel reproducibility.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 12, 2007
Accession Number
ADA551688

Entities

People

  • John G Bruno
  • John L. Alls
  • Johnathan L. Kiel

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Air Force Research Laboratories
  • Biosensors
  • Chemistry
  • Deoxyribonucleic Acids
  • Detection
  • Dna Microarrays
  • Electromagnetic Radiation
  • Emission Spectra
  • Energy Transfer
  • Genetic Structures
  • Microbiology
  • Nucleic Acids
  • Pattern Recognition
  • Recognition
  • Two Dimensional

Readers

  • Nanocomposite Materials Science
  • Neural Network Machine Learning.
  • Semiconductor Device Technology

Technology Areas

  • AI & ML
  • Biotechnology