Silicon-based biosensors for rapid detection of protein or nucleic acid targets.
BACKGROUND: We developed a silicon-based biosensor that generates visual, qualitative results or quantitative results for the detection of protein or nucleic acid targets in a multiplex format. METHODS: Capture probes were immobilized either passively or covalently on the optically coated surface of the biosensor. Intermolecular interactions of the immobilized capture probe with specific target molecules were transduced into a molecular thin film. Thin films were generated by enzyme-catalyzed deposition in the vicinity of the surface-bound target. The increased thickness on the surface changed the apparent color of the biosensor by altering the interference pattern of reflected light. RESULTS: Cytokine detection was achieved in a 40-min multiplex assay. Detection limits were 4 ng/L for interleukin (IL)-6, 31 ng/L for IL1-beta, and 437 ng/L for interferon-gamma. In multianalyte experiments, cytokines were specifically detected with signal-to-noise ratios ranging from 15 to 80. With a modified optical surface, specificity was also demonstrated in a nucleic acid array with unambiguous discrimination of single-base changes in a 15-min assay. For homozygous wild-type and homozygous mutant samples, signal-to-noise ratios of approximately 100 were observed. Heterozygous samples yielded approximately equivalent signals for wild-type and mutant capture probes. CONCLUSIONS: The thin-film biosensor allows rapid, sensitive, and specific detection of protein or nucleic acid targets in an array format with results read visually or quantified with a charge-coupled device camera. This biosensor is suited for multianalyte detection in clinical diagnostic assays.[1]References
- Silicon-based biosensors for rapid detection of protein or nucleic acid targets. Jenison, R., La, H., Haeberli, A., Ostroff, R., Polisky, B. Clin. Chem. (2001) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg
