Transcript 슬라이드 1 - Weill Cornell Medical College

Biosensors
Peter C. Doerschuk
Biomedical Engineering
and Electrical and Computer Engineering
Cornell University
 Extensive activity spread throughout
Engineering and Science.
 Organization:
• Within departments, e.g., BME, ECE, CBE, BEE, AEP.
• Within centers, especially the Nanobiotechnology Center (NBTC),
a National Science Foundation, Science and Technology Center.
 Goals:
• Biosensor devices (really biointerface devices since both sensing
and actuating are of interest).
• Inference and control algorithms for use with such devices.
• Basic science to clinical medicine.
 Examples
• Professor Harold Craighead, Applied and Engineering Physics,
Nanobiotechnology Center (NBTC)
(http://www.nbtc.cornell.edu/):
research in biomolecular devices & analysis, cellular microdynamics,
cell-surface interactions, and nanoscale cell biology
• Professor Antje Baeumner, Biological & Environmental Engineering,
Bioanalytical Microsystems & Biosensors Lab
(http://hive.bee.cornell.edu/bmb_lab/index.html):
devices for the detection of hazardous biological and chemical
substances in the environment, in food, and in medical diagnostics.
• Professor Peter Doerschuk, Biomedical Engineering and Electrical
and Computer Engineering: mathematical and statistical models,
signal and image processing, high performance computing; sketch
work on an implanted biosensor for ethanol.
Bioanalytical Microsystems &
Biosensors Laboratory
Department of Biological & Environmental Engineering
145 Riley-Robb Hall
Cornell University, Ithaca, NY
Antje J. Baeumner (PI)/Katie A. Edwards
Advantages of Liposomes
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Liposomes can serve as a substitute for fluorophore, colloidal gold, or enzymatic signal
enhancement
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Interior cavity can encapsulate many hydrophilic signaling molecules
– ~105-106 dye molecules
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Hydrophobic molecules can be bi-layer incorporated
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Lipid bilayers can be conjugated to biorecognition elements
– Functional groups available for post-formation conjugation
– Direct incorporation
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Facile control over analytical aspects:
– Liposome size, degree of conjugation, concentration of encapsulants
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Long-term stability
Instantaneous signal amplification
Comparison to other detection methods
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Signal:Noise
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Fluorescein-labeled antibody
Antibody-tagged dye-encapsulating liposomes
HRP-labeled antibody
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[CTB] (ng/mL)
Sandwich immunoassay for cholera toxin, subunit B using fluorescein, HRP, or dyeencapsulating liposome labeled antibody. Results are plotted in terms of signal to noise.
LOD (bkgd+3*stdev)
Maximum
S:N at maximum
Fluorescein-labeled antibody
13.3 ng/mL
500 ng/mL
3.35
HRP-labeled antibody
2.05 ng/mL
50 ng/mL
1.95
Antibody-tagged liposomes
0.45 ng/mL
500 ng/mL
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Recent Work
• Development of rapid lateral flow assays for:
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CD4 cells from human blood
Cryptosporidium parvum
Pathogenic bacteria (i.e.-Bacillus anthracis, Escherichia coli)
Dengue virus (serotype specific)
Herbicides (Alachlor, imazethapyr)
• Development of microtiter plate assays for cell culture supernatants:
– Cholera toxin
– Insulin
• Visualization and quantification of cholera toxin binding to epithelial cells
• Encapsulation of DNA oligonucleotides for detection of
protective antigen from B. anthracis – allowed for multi-analyte
analysis proof of principle
Assay Overview
• Biorecognition elements can be conjugated to liposomal bilayer:
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Antibodies
Streptavidin or Protein A/G, Enzymes, Other Proteins
Small-molecule analytes
Fluorophores
• Hydrophilic molecules can be encapsulated within interior cavity
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Enzymes
Fluorophores
Electrochemical markers
Oligonucleotides
• Assay types
– Sandwich immunoassays
– Sandwich hybridizations
– Competitive assays
• Assay formats
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Lateral-flow assays
Microfluidic devices
Sequential-injection analysis
Microtiter plates
• Methods to detect on-cell binding of
Cholera toxin and its production in
culture supernatants were developed
• Used to visualize and quantify the binding
of CT to Caco-2 epithelial cells cocultured with V. cholerae
• Detected by sandwich immunoassay for
detection by a fluorescence microtiter
plate reader and microscopy
Fluorescence Signal
Cholera toxin detection
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[CTB] (ng/mL)
Sandwich immunoassay using GM1-tagged
liposomes. Limit of detection (bkgd+3xStDev) =
0.34 ng/mL, Assay range: ~1-500 ng/mL, CV ≤ 3.7%,
Assay time: 3.5 hours
Caco-2 epithelial cells grown in microtiter
plates and incubated with cholera toxin
(CT) standards or V. cholerae. GM1
tagged fluorophore labeled liposomes were
used to visualize bound CT.
Analytical Biochemistry, vol. 368 (1), p. 39 – 48 (2007)
mRNA detection
• Sandwich-hybridization of amplified
RNA target between reporter probetagged liposomes and immobilized
capture probes
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Fluorescence (RFU)
• mRNA extracted from culture and
amplified using NASBA
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[Synthetic DNA Target] (nM)
• Synthetic DNA analogue used for
development work
• Assay proven successful for the
detection of mRNA from E. coli, B.
anthracis, Dengue virus and C. parvum
DNA-tagged liposomes in a sandwich hybridization
assay for B. anthracis atxA mRNA. Limit of
detection (bkgd+3xStDev) = 0.11 nM, Assay range:
~0.5-50 nM, CV ≤ 4.4%, Assay time: 1.75 hours
Analytical Bioanalytical Chemistry, vol. 386 (6), p. 1613 – 1623 (2006)
Dengue virus detection
• Sandwich hybridization detection of amplified mRNA using LFA
with capture probes immobilized in different zones
• Allows for distinction between 4 serotypes
• Sensitivity: 10 pfu/mL
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DNA-tagged liposomes in a sandwich hybridization
assay for Dengue virus mRNA. Serotype-specific
capture probes were immobilized in spatially
different zones
Analytical Bioanalytical Chemistry, vol. 380 (1), p. 46 – 53 (2004)
Serotype 1
Serotype 2
Serotype 3
Serotype 4
Negative control
Lab information
Antje J. Baeumner (PI)/Katie A. Edwards
3 Post-doctoral associates
3 Ph.D. students
1 Research support Specialist
4 Undergraduate students
Present technical capabilities:
Dynamic light scattering
Sequential injection analyses
Microfluidic device development
Lateral flow assay development
Microtiter plate assay development
Nucleic Acid Based Sequence Amplification (NASBA), PCR
Liposome preparation
Blood handling
Ethanol Biosensor: Models and Signal Processing
Jae-Joon Han, Martin Plawecki,
Peter Doerschuk, and Sean O’Connor