4.7 Article

Lab-on-a-chip for label free biological semiconductor analysis of Staphylococcal Enterotoxin B

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LAB ON A CHIP
卷 10, 期 19, 页码 2534-2540

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ROYAL SOC CHEMISTRY
DOI: 10.1039/c005141a

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We describe a new lab-on-a-chip (LOC) which utilizes a biological semiconductor (BSC) transducer for label free analysis of Staphylococcal Enterotoxin B (SEB) (or other biological interactions) directly and electronically. BSCs are new transducers based on electrical percolation through a multi-layer carbon nanotube-antibody network. In BSCs the passage of current through the conductive network is dependent upon the continuity of the network. Molecular interactions within the network, such as binding of antigens to the antibodies, disrupt the network continuity causing increased resistance of the network. For the fabrication of a BSC based detector, we combined several elements: (1) BSC transducers for direct detection, (2) LOC for flow through continuous measurements, (3) a digital multimeter with computer connection for data logging, (4) pumps and valves for fluid delivery, and (5) a computer for fluid delivery control and data analysis. Polymer lamination technology was used for the fabrication of a four layer LOC for BSC detection, the BSC on the chip is fabricated by immobilizing pre-functionalized single-walled carbon nanotubes (SWNTs)-antibody complex directly on the PMMA surface of the LOC. SEB samples were loaded into the device using a peristaltic pump and the change in resistance resulting from antibody-antigen interactions was continuously monitored and recorded. Binding of SEB rapidly increases the BSC electrical resistance. SEB in buffer was assayed with limit of detection (LOD) of 5 ng mL(-1) at a signal to baseline (S/B) ratio of 2. A secondary antibody was used to verify the presence of the SEB captured on the surface of the BSC and for signal amplification. The new LOC system permits rapid detection and semi-automated operation of BSCs. Such an approach may enable the development of multiple biological elements Biological Central Processing Units (CPUs)'' for parallel processing and sorting out automatically information on multiple analytes simultaneously. Such an approach has potential use for point-of-care medical and environmental testing.

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