Aberrant expression of short non-coding micro RNAs (miRNA) in many human diseases, along with remarkable stability in physiological media, has made them attractive clinical biomarkers. In particular, miRNA-122 is substantially elevated in plasma of patients with established drug-induced liver injury and can also be used to identify early liver injury when current markers, such as alanine aminotransferase (ALT), still show normal levels. The development of a rapid test for miRNA-122 e.g. in drug poisoning would allow earlier and more sensitive clinical diagnosis of liver injury. Nucleic acids are traditionally analysed by polymerase chain reaction (PCR), which has a high degree of sensitivity but suffers from high cost and is prone to sample contamination. The aim of this project is to develop a PCR free method to directly detect miRNA- 122 in biological samples using SMART technology. The SMART technology takes advantage of dynamic chemistry for sequence specific recognition of nucleic acids using aldehyde-modified nucleobases (SMART nucleobases), and target-complementary peptide nucleic acid (PNA) probe containing an “abasic” position (so called modified PNA probe). In this study, this unique detection method was used in a fluorescent detection with the use of light up probes, which are probes with an environmental dye as nucleobase; a FRET system was also designed to allow the discrimination between perfect match target and mismatched one. The SMART technology was also transferred onto magnetic beads to develop an ELISA like assay allowing sensitive and rapid detection of single stranded DNA mimic of the miRNA-122. With its potential PCR free approach, this easily adapted platform promises to transform and expand routine clinical diagnostic testing and screening for circulating miRNAs.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:738793 |
| Date | January 2017 |
| Creators | Sailis, Fiammetta |
| Contributors | Bradley, Mark ; Cockroft, Scott |
| Publisher | University of Edinburgh |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/1842/28891 |
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