Direct Quantitative Detection of Microrna with a Purification-Free, Amplification-Free and Label-Free Technique

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2018-05

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Abstract

MicroRNAs play key roles in various types of cellular processes such as cell proliferation, and differentiation via post-transcriptional regulation. Therefore, they have great potential of being promising biomarkers for disease diagnosis and as a result have attracted much attention. To address the increasing need for their precise detection, many quantitative approaches have been developed. Recently, a new direct detection technique, Exchange-Induced Remnant Magnetization Spectroscopy (ExIRMS) has been reported by our laboratory with no amplification or washing procedures. However, it has not been demonstrated the bio-compatibility in the detection of cellular microRNAs and circulating microRNAs. Therefore, in this dissertation, I focus on the detection of microRNAs by ExIRMS in cells as well as body fluid. Firstly, the exchange reaction between the target microRNA and the probe with one mismatched base during competitive binding with the complementary magnetically labelled RNA was utilized. The results showed that ExIRMS was sufficiently robust to achieve a high sensitivity with 105 molecules for detecting microRNAs in cell lysate as well as clinical serum. Neither purification nor amplification are required for detection, which maximally simplify the analysis process and avoid possible loss during sample preparation for absolute quantification. Additionally, this technique was compared with conventional method, and it is confirmed that ExIRMS is comparable to qPCR for purified RNA from both cells and sera. Moreover, accurate absolute quantification of circulating microRNAs requires serum with fractionation and appropriate treatment such as proteinase K and Triton X100 was demonstrated. Further, ExIRMS was evaluated and optimized for specificity and sensitivity. It was demonstrated that new mismatch (G-U) at position 19 is able to distinguish let-7a from other paralogs of let-7 while old mismatch (C-C) can detect all let-7a family in an energy-based preference. By titration, it was also determined that 1 pM of mismatched-strand with 6 pM of let-7a complement plus 250 thousands of beads was optimal for the platform. In addition, force spectrum was applied prior to ExIRMS to remove non-specific interaction on the surface. Together, the evaluation and optimization provided us a promising future of ExIRMS in microRNAs profiling, which can be further applied in disease diagnosis and prognosis.

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MicroRNAs (miRNA), ExIRMS

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