This paper describes
a method for detecting microRNA (miRNA) expression
patterns using the nanopore-based DNA computing technology. miRNAs
have shown promise as markers for cancer diagnosis due to their cancer
type specificity, and therefore simple strategies for miRNA pattern
recognition are required. We propose a system for pattern recognition
of five types of miRNAs overexpressed in bile duct cancer (BDC). The
information of miRNAs from BDC is encoded in diagnostic DNAs (dgDNAs)
and decoded electrically by nanopore analysis. With this system, we
succeeded in the label-free detection of miRNA expression patterns
from the plasma of BDC patients. Moreover, our dgDNA–miRNA
complexes can be detected at subfemtomolar concentrations, which is
a significant improvement compared to previously reported limits of
detection (∼10
–12
M) for similar analytical
platforms. Nanopore decoding of dgDNA-encoded information represents
a promising tool for simple and early cancer diagnosis.
This paper describes a method for the real-time counting and extraction of DNA molecules at the single-molecule level by nanopore technology. As a powerful tool for electrochemical single-molecule detection, nanopore technology eliminates the need for labeling or partitioning sample solutions at the femtoliter level. Here, we attempt to develop a DNA filtering system utilizing an α-hemolysin (αHL) nanopore. This system comprises two droplets, one filling with and one emptying DNA molecules, separated by a planar lipid bilayer containing αHL nanopores. The translocation of DNA through the nanopores is observed by measuring the channel current, and the number of translocated molecules can also be verified by quantitative polymerase chain reaction (qPCR). However, we found that the issue of contamination seems to be an almost insolvable problem in single-molecule counting. To tackle this problem, we tried to optimize the experimental environment, reduce the volume of solution containing the target molecule, and use the PCR clamp method. Although further efforts are still needed to achieve a singlemolecule filter with electrical counting, our proposed method shows a linear relationship between the electrical counting and qPCR estimation of the number of DNA molecules.
This paper describes nanopore decoding for microRNA (miRNA) expression patterns using DNA computing technology. miRNAs have shown promise as markers for cancer diagnosis due to their cancer type-specificity, and therefore simple strategies for miRNA-pattern recognition are required. We propose a system for pattern recognition of five types of miRNAs overexpressed in bile duct cancer (BDC). The information of miRNAs from BDC is encoded in diagnostic DNAs (dgDNAs) and decoded electrically by nanopore measurement. With this system, we succeeded in distinguishing miRNA expression patterns in the plasma of BDC patients using a label-free method and in real-time. Moreover, our dgDNA-miRNAs complexes can be captured by the nanopore at ultralow concentration, such as 0.1 fM. Such nanopore decoding with dgDNAs could be applied as a simple and early diagnostic tool for cancer in the future.
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