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U.S. Department of Energy
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Bead-Based Assays for Biodetection: From Flow-Cytometry to Microfluidics

Conference ·
DOI:https://doi.org/10.1117/12.819951· OSTI ID:973735

ABSTRACT The potential for the use of biological agents by terrorists is a real threat. Two approaches for detection of biological species will be described: 1) The use of microbead arrays for multiplexed flow cytometry detection of cytokines and botulinum neurotoxin simulant, and 2) a microfluidic platform for capture and separation of different size superparamagnetic nanoparticles followed by on-chip fluorescence detection of the sandwich complex. The methods and automated fluidic systems used for trapping functionalized microbeads will be described. This approach allows sample, assay reagents, and wash solutions to be perfused over a micro-column of beads, resulting in faster and more sensitive assays. The automated fluidic approach resulted in up to five-fold improvements in assay sensitivity/speed as compared to identical assays performed in a typical manual batch mode. A second approach for implementing multiplexed bead-based assays without using flow cytometry detection is currently under development. The goal of the microfluidic-based approach is to achieve rapid (<20 minutes), multiplexed (> 3 bioagents) detection using a simple and low-cost, integrated microfluidic/optical detection platform. Using fiber-optic guided laser-induced fluorescence, assay detection limits were shown to be in the 100’s of picomolar range (10’s of micrograms per liter) for botulinum neurotoxin simulant without any optimization of the microfluidic device or optical detection approach. Video taping magnetic nanoparticle capture and release was used to improve understanding of the process and revealed interesting behavior.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
973735
Report Number(s):
PNNL-SA-65500
Country of Publication:
United States
Language:
English