Towards de novo design of deoxyribozyme biosensors for GMO detection

Elebeoba E. May; Patricia L. Dolan; Paul S. Crozier; Susan Brozik; Monica Manginell

doi:10.1109/JSEN.2008.923945

Towards de novo design of deoxyribozyme biosensors for GMO detection

Elebeoba E. May, Patricia L. Dolan, Paul S. Crozier, Susan Brozik, Monica Manginell

Research output: Contribution to journal › Article › peer-review

42 Scopus citations

Abstract

Hybrid systems that provide a seamless interface between nanoscale molecular events and microsystem technologies enable the development of complex biological sensor systems that not only detect biomolecular threats, but also are able to determine and execute a programmed response to such threats. The challenge is to move beyond the current paradigm of compartmentalizing detection, analysis, and interpretation into separate steps. We present methods that will enable the de novo design and development of customizable biosensors that can exploit deoxyribozyme computing (Stojanovic and Stefanovic, 2003) to concurrently perform in vitro target detection, genetically modified organism detection, and classification.

Original language	English (US)
Article number	4529200
Pages (from-to)	1011-1019
Number of pages	9
Journal	IEEE Sensors Journal
Volume	8
Issue number	6
DOIs	https://doi.org/10.1109/JSEN.2008.923945
State	Published - Jun 2008

Keywords

Avian influenza
Biosensor
Deoxyribozyme
Error control codes
Hybridization thermodynamics
Molecular beacons
Single nucleotide polymorphism

ASJC Scopus subject areas

Engineering(all)
Electrical and Electronic Engineering

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10.1109/JSEN.2008.923945

Cite this

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title = "Towards de novo design of deoxyribozyme biosensors for GMO detection",

abstract = "Hybrid systems that provide a seamless interface between nanoscale molecular events and microsystem technologies enable the development of complex biological sensor systems that not only detect biomolecular threats, but also are able to determine and execute a programmed response to such threats. The challenge is to move beyond the current paradigm of compartmentalizing detection, analysis, and interpretation into separate steps. We present methods that will enable the de novo design and development of customizable biosensors that can exploit deoxyribozyme computing (Stojanovic and Stefanovic, 2003) to concurrently perform in vitro target detection, genetically modified organism detection, and classification.",

keywords = "Avian influenza, Biosensor, Deoxyribozyme, Error control codes, Hybridization thermodynamics, Molecular beacons, Single nucleotide polymorphism",

author = "May, {Elebeoba E.} and Dolan, {Patricia L.} and Crozier, {Paul S.} and Susan Brozik and Monica Manginell",

note = "Funding Information: Manuscript received March 20, 2008; accepted March 21, 2008. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company for the United States Department of Energys National Nuclear Security Administration under contract DEAC0494AL85000. This work was supported by Sandia National Laboratories{\textquoteright} Laboratory Directed Research and Development Program. E.E.M. and P.L.D. contributed equally to this work. The associate editor coordinating the review of this paper and approving it for publication was Dr. Dennis Polla. Copyright: Copyright 2008 Elsevier B.V., All rights reserved.",

year = "2008",

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doi = "10.1109/JSEN.2008.923945",

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AU - May, Elebeoba E.

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AU - Crozier, Paul S.

AU - Brozik, Susan

AU - Manginell, Monica

N1 - Funding Information: Manuscript received March 20, 2008; accepted March 21, 2008. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company for the United States Department of Energys National Nuclear Security Administration under contract DEAC0494AL85000. This work was supported by Sandia National Laboratories’ Laboratory Directed Research and Development Program. E.E.M. and P.L.D. contributed equally to this work. The associate editor coordinating the review of this paper and approving it for publication was Dr. Dennis Polla. Copyright: Copyright 2008 Elsevier B.V., All rights reserved.

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N2 - Hybrid systems that provide a seamless interface between nanoscale molecular events and microsystem technologies enable the development of complex biological sensor systems that not only detect biomolecular threats, but also are able to determine and execute a programmed response to such threats. The challenge is to move beyond the current paradigm of compartmentalizing detection, analysis, and interpretation into separate steps. We present methods that will enable the de novo design and development of customizable biosensors that can exploit deoxyribozyme computing (Stojanovic and Stefanovic, 2003) to concurrently perform in vitro target detection, genetically modified organism detection, and classification.

AB - Hybrid systems that provide a seamless interface between nanoscale molecular events and microsystem technologies enable the development of complex biological sensor systems that not only detect biomolecular threats, but also are able to determine and execute a programmed response to such threats. The challenge is to move beyond the current paradigm of compartmentalizing detection, analysis, and interpretation into separate steps. We present methods that will enable the de novo design and development of customizable biosensors that can exploit deoxyribozyme computing (Stojanovic and Stefanovic, 2003) to concurrently perform in vitro target detection, genetically modified organism detection, and classification.

KW - Avian influenza

KW - Biosensor

KW - Deoxyribozyme

KW - Error control codes

KW - Hybridization thermodynamics

KW - Molecular beacons

KW - Single nucleotide polymorphism

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Towards de novo design of deoxyribozyme biosensors for GMO detection

Abstract

Keywords

ASJC Scopus subject areas

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