Team:Hong Kong HKU/Demonstrate
Demonstrate
RNA detection using DNA nanostructure
After showing that our DNA nanostructures can detect our target DNA (details can be found here), we went further to detect RNA.
This test aimed to simulate the detection of serum microRNA, which has potential real-world application to diagnose disease using microRNA disease biomarkers.
The following table shows the sequence of input used in the assay.
| Sequence | Length | |
|---|---|---|
| RNA Input | CAAUCAGGGUCUAACUCCACUGGGUGCCAU | 30 |
| RNA Mutant | CAGGCAGUAUCAUGCGACAUUGGGUGCAGC | 30 |
First, we used our simplified DNA nanostructure (formed from the G-quadruplex side of O1 and O5 of the tetrahedron,
which is the essential part of the 3D tetrahedral nanostructure) to detect RNA input.
Equimolar (100nM final) DNA nanostructure and RNA input were added in the assay.
The following bar chart shows the absorbance at 420nm after the addition of different RNAs.
Fig. A: Absorbance at 420nm after the addition of different RNAs to the simplified DNA nanostructure (formed from O1's G-quadruplex side and O5 of the tetrahedron) which is termed as "beacon" in the above graph.
The absorbance was taken 15 minutes after the addition of ABTS and H2O2. Error bars show standard deviation from triplicates.
Then, we repeated the experiment using our tetrahedral DNA nanostructure, which gave the following result.
Fig. B: Absorbance at 420nm after the addition of different RNAs to the tetrahedral DNA nanostructure.
The absorbance was taken 15 minutes after the addition of ABTS and H2O2. Error bars show standard deviation from triplicates.
From the above two graphs, it can be seen that the addition of RNA input resulted in a higher absorbance than that without the addition of RNA input, and the addition of a random RNA sequence did not lead to a higher absorbance.
Hence, we have successfully demonstrated that our design not only can detect our desired RNA, it can also distinguish the correct RNA input from a random RNA.
Limit of detection
Then, we determined the limit of detection (LOD) of our detection beacon (formed from O1's G-quadruplex side and O5 of the tetrahedron, the active component of the tetrahedral nanostructure) by ABTS assay.
Different concentrations of RNA input were added and their respective absorbance at 420nm was measured.
A regression line obtained is shown in the following graph.
Fig. C: Absorbance at 420nm against the concentration of RNA input to the simplified DNA nanostructure (formed from O1's G-quadruplex side and O5 of the tetrahedron).
The absorbance was taken 15 minutes after the addition of ABTS and H2O2. Error bars show standard deviation from triplicates.
The regression line obtained is y=0.0009x+0.1298 (R2=0.9739).
The LOD is calculated as follows.
CLOD = 3(sy/x)÷b, where
CLOD is the concentration LOD,
sy/x is the standard error of regression, and
b is the slope of regression line.
First, the standard error of regression is determined.
| X | Y | Y' | Y-Y' | (Y-Y')2 |
|---|---|---|---|---|
| 0 | 0.123333333333333 | 0.1298 | -0.00646666666666666 | 0.0000418177777777777 |
| 20 | 0.151 | 0.1478 | 0.00320000000000001 | 0.0000102400000000001 |
| 40 | 0.170666666666667 | 0.1658 | 0.00486666666666666 | 0.0000236844444444444 |
| 60 | 0.185666666666667 | 0.1838 | 0.00186666666666666 | 0.0000034844444444444 |
| 80 | 0.208333333333333 | 0.2018 | 0.00653333333333336 | 0.0000426844444444448 |
| 100 | 0.213666666666667 | 0.2198 | -0.00613333333333332 | 0.0000376177777777777 |
| SSE | 0.000159528888888889 | |||
(Y' is the predicted value from the regression line y=0.0009x+0.1298)
Standard error of regression = √(SSE÷no. of pairs)=√(0.0001595÷6)=0.005156
Limit of detection
CLOD = 3(sy/x)÷b = 3(0.005156)÷0.0009 = 17.19nM
Real-world application
Our DNA nanostructures can potentially be utilized as a simple diagnostic tool, where a higher absorbance in ABTS assay suggests the presence of our desired RNA target.
As microRNAs are potential disease biomarkers, our DNA nanostructures can potentially be used in disease screening by detecting the patien' s serum microRNA.
In addition, we can easily expand the application to detect different RNA sequences by modifying the sequence of two strands of our DNA nanostructure.
