Detection and Identification of Double-Stranded Small RNA using a Reusable Silicon Nanowire Field-Effect Transistor
| Autor: | Keng-Hui Li, 李耕慧 |
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| Rok vydání: | 2011 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 99 Silicon nanowire field-effect transistors (SiNW-FETs) have been extensively used as biosensors in a variety of detections, ranging from DNA hybridization, proteins, virus, and small molecules. Taking advantages of the ultrahigh sensitivity, selectivity, label-free and real-time detection capabilities of a SiNW-FET, we have applied reusable SiNW-FETs for the study of protein-small RNA interactions. Post-transcriptional gene silencing (PTGS) is an antiviral strategy in plants to avoid the virus infection. However, the virus can produce a viral suppressor protein to suppress the PTGS in order to prevent the silencing machinery from attacking virus. P19 of Tombusvirus (with 19 kDa molecular weight) has been identified as a viral suppressor that can specifically bind 21 nucleotide (nt) double-strand short-interfering RNA (ds-siRNA) with high affinity and size selection. In this study, we reported the application of the nanotechnology to develop a highly sensitive SiNW-FET biosensor immobilized with P19 protein (referred to as P19/SiNW-FET) for the detection of interacting siRNAs. This P19/SiNW-FET biosensor is capable of not only detecting 21 nt ds-siRNAs to a 500 pM level, but also distinguishing the various secondary structures of ds-siRNAs, such as their size, and the mismatch between P19 and ds-siRNAs. Moreover, unknown ds-siRNAs captured by P19/SiNW-FET in the sensing measurement can be recovered after detection for the further identification with the polymerase chain reaction (PCR) technique. From these sensing measurements, we demonstrate that SiNW-FET biosensors provide an excellent platform for high-throughput screening protein-RNA interactions. In particular, the interacting siRNAs recorvered from a specific protein-modified SiNW-FET can be identified to reveal their profile. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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