Fully Integrated Microfluidic Device for Direct Sample-to-Answer Genetic Analysis

Integration of microfluidics technology with DNA microarrays enables building complete sample-to-answer systems that are useful in many applications such as clinic diagnostics. In this chapter, a fully integrated microfluidic device [ 1 ] that consists of microfluidic mixers, valves, pumps, channels, chambers, heaters, and a DNA microarray sensor to perform DNA analysis of complex biological sample solutions is present. This device can perform on-chip sample preparation (including magnetic bead-based cell capture, cell preconcentration and purification, and cell lysis) of complex biological sample solutions (such as whole blood), polymerase chain reaction, DNA hybridization, and electrochemical detection. A few novel microfluidic techniques were developed and employed. A micromix-ing technique based on a cavitation microstreaming principle was implemented to enhance target cell capture from whole blood samples using immunomagnetic beads. This technique was also employed to accelerate DNA hybridization reaction. Thermally actuated paraffin-based microvalves were developed to regulate flows. Electrochemical pumps and thermopneumatic pumps were integrated on the chip to provide pumping of liquid solutions. The device is completely self-contained: no external pressure sources, fluid storage, mechanical pumps, or valves are necessary for fluid manipulation, thus eliminating possible sample contamination and simplifying device operation. Pathogenic bacteria detection from ~mL whole blood samples and single-nucleotide polymorphism analysis directly from diluted blood were demonstrated. The device provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus has a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.