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Recognition of Single-Point Mutation Usinga Biological Nanopore
Ping Liu and Ryuji Kawano*
minutes to several tens of minutes),[10,11] amore rapid detection method could offer
improved diagnostic performance.
Nanopore technology[12–16] is a promi­
sing candidate for the rapid detection of
mutated ctDNAs. There are two different
nanopore approaches for liquid biopsy:
nanopore sequencing of ctDNA or direct
sensing of ctDNA using a nanopore. Nano­pore sequencing has recently emerged asa rapid and inexpensive method of DNA
sequencing.[17] Nanopore sequencing iscapable of recognizing a small differencein ionic current when an single-stranded DNA (ssDNA) passes
through the nanopore under an applied voltage. Advantages ofsuch sequencing include the use of compact bench-top instru­
ments and the capacity for long read. While there have previ­
ously been many applications of nanopore sequencing focusing
on genome sequencing, the analysis of ctDNA has remained
a challenge. On the other hand, nanopore sensing is able todirectly detect the translocation of short DNA strands via theblocking current of the open-pore state.[18] Regarding the point
mutation analysis of short DNA using nanopore sensing, sev­
eral approaches have been reported, including using an enzyme
reaction,[19] nanolock,[20] DNA nanopore,[21] or probe DNA.[22,23]
Although these methods can determine the presence or absenceof a single mutation, prediction of the mutation position has
remained challenging.
We have previously developed single molecular detection
methods using nanopores,[24–31] including analysis of the unzip­
ping time of double-stranded DNA and RNA with bootstrap­
ping.[14,29] Hiratani and Kawano applied nanopore decoding ofDNA computing outputs for miRNA pattern recognition.[29]Two miRNAs that are overexpressed and secreted from tumor
cells were recognized via diagnostic DNA (dgDNA) hybridiza­tion, with formation of a four-way junction in the presence ofboth miRNAs. Nanopore measurements were able to decodetranslocation behavior to discriminate the four AND opera­
tions: (0,0) in the absence of either miRNA; (0,1) and (1,0) in
the presence of a single miRNA; and (1,1) demonstrating theunzipping pattern of the four-way junction in the presence ofboth miRNAs. Bootstrapping of the data offered significant
improvement in distinguishing between all four systems incases where the raw duration data had been unable to distin­
guish any differences. The unzipping analysis has widely used
not only the oligonucleotides but also protein unfolding.[32–34]
In this study, discernment of the position of the single-point
mutation in oligonucleotides was achieved by analysis of unzip­
ping behavior in a method analogous to that of Hiratani’s work.[29]The target oligonucleotides (21 nt) based on an EGFR sequence
were hybridized with probe DNA to form a double-stranded

Here the recognition of a single-point mutation in oligonucleotides is
described by using nanopore measurements. The translocation behavior ofa series of mutated DNA strands, hybridized with a complementary DNA
probe, is analyzed via blocking current and unzipping time. Discernment of
the mutation position at the single nucleotide level is achieved by analysis ofa 2D graph of the bootstrapped translocation data. The proposed approachprovides a useful tool for the mutation detection of oligonucleotides secreted
from tumor cells and is applicable in simple and label-free diagnoses as ananopore liquid biopsy.

1. Introduction
Liquid biopsy is a recently emerging approach for cancer diag­nosis.[1] Tumor-related biomaterials such as DNA and RNA
fragments, in addition to whole cancer cells, are released fromtumors into bodily fluids. For instance, circulating tumor
cells (CTCs) that circulate in the bloodstream contain detect­able information about the parent tumor cell.[2] On the other
hand, circulating tumor DNA (ctDNA) or microRNA (miRNA)
also have genetic information relating to the tumor cells.[3,4]These short fragments of nucleic acids are usually encapsu­
lated in extracellular vesicles or bound to proteins and circu­
late in the blood. Diagnosis via ctDNA detection is particularlycommon for cancers such as lung cancer.[5–7] The epidermal
growth factor receptor (EGFR) gene, which is a component of
the molecular signaling pathway that controls the prolifera­tion and growth of cells, is the most crucial driver oncogeneof lung cancer. Namely, the mutation of L858R and T790M in
EGFR is expressed in patients with non-small-cell lung cancer.
Liquid biopsy of ctDNA from the bloodstream can be used todetect this mutation and for the subsequent diagnosis of lungcancer.[8] Current methods to assess the mutation of ctDNA
include digital polymerase chain reaction and next-generation
sequencing (NGS).[9] These measurements require multiple
procedures and are often time-consuming. Considering therelatively short half-life of ctDNA sampled from blood (several
P. LiuDepartment of Food and Energy Systems Science
Tokyo University of Agriculture and Technology
Tokyo 184-8588, Japan
Prof. R. Kawano
Department of Biotechnology and Life Science
Tokyo University of Agriculture and Technology
Tokyo 184-8588, Japan
E-mail: rjkawano@cc.tuat.ac.jp
The ORCID identification number(s) for the author(s) of this article
can be found under https://doi.org/10.1002/smtd.202000101.

DOI: 10.1002/smtd.202000101

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Figure 1. Illustration of the unzipping technique for detection of mutation position in target nucleotides by combining the analyzation of blocking
level and unzipping time.

complex with a polynucleotide tail. The mutation position intarget nucleotides was detected by the analysis of bootstrapped
data of the blocking ratio and duration time of unzipping events(Figure 1).
Our approach offers a useful tool for the rapid and label-freedetection of mutation positions not only in ctDNA but also in awide variety of oligonucleotides.

2. Results
2.1. The Design of the Complementary Probe for the Target
Oligonucleotides
The target sequence used in this study relates to the Exon21 regionof the EGFR. To facilitate detection of this target, two DNA probes
were prepared. The P5T probe consisted of the complemen­tary sequence, with the target poly(deoxyadenylicacid) 30-merssequence (poly(dA)30) at the 5′ terminus, while the P3T probe
had this positioned at the 3′ terminus. poly(dA)30 is sufficiently
long to extend in one instance from the cis to the trans side of thealpha-hemolysin (αHL) pore, and hence ensures the capturing of
double-stranded DNA (dsDNA) in the nanopore. Regarding thetarget DNAs, five sequences were designed that had a single-point
mutation from (C–G) to (C–A) at five different positions, named
G1A, G2A, G3A, G11A, and G21A, respectively. Besides, thenucleotide variation from (C–G) to (C–A), (C–T), and (C–C) at theterminus was also investigated, in targets named G1A, G1T, andG1C. All sequences used in this study are listed in Table 1.
2.2. Detection of Point-Mutation Position Using the P5T Probe
Figure 2a–e shows the typical current and time traces of
the unzipping events using P5T with G1A, G11A, and G21A
Small Methods 2020, 2000101

under application of +120 mV voltage. In the case of the P5Tprobe itself (ssP5T, Figure 2a), rapid translocation eventswere observed. In contrast, longer blocking durations forthe hybridized complexes (Figure 2b–e) indicate the unzip­
ping events between the target and P5T probe in the nano­pore. Although the blocking ratio of the three mutated DNA
targets was less than that of the wild-type (WT) system, thedifference was too small for discrimination between thesemutants. On the other hand, the unzipping time is shown to
be exponentially dependent upon the Gibbs free energy (ΔG)
of the hybridization, as simulated by Nucleic Acid Package(NUPACK) (Figure 2f ). However, significant overlap in thehistograms of unzipping time (Figure 2g) led to difficulty in
distinguishing between mutation positions. It can be further
seen that overlapping data remain in the clusters of plot data
even when combining the blocking duration and unzipping
time (Figure 2g). Hence, although use of the P5T probe wasable to demonstrate differences in measured parameters,
Table 1. Sequences of probe DNA and target DNA.
Name

Sequence

P5T

5′-(A)30CCCTTGACGACAGCAGTTCCC-3′

P3T

5′-CCCTTGACGACAGCAGTTCCC(A)30-3′

Wild

5′-GGGAACTGCTGTCGTCAAGGG-3′

G1A

5′-AGGAACTGCTGTCGTCAAGGG-3′

G2A

5′-GAGAACTGCTGTCGTCAAGGG-3′

G3A

5′-GGAAACTGCTGTCGTCAAGGG-3′

G11A

5′-GGGAACTGCTATCGTCAAGGG-3′

G21A

5′-GGGAACTGCTGTCGTCAAGGA-3′

G1T

5′-TGGAACTGCTGTCGTCAAGGG-3′

G1C

5′-CGGAACTGCTGTCGTCAAGGG-3′

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Figure 2. Results when using P5T for the detection of mutation position. Typical current traces of P5T hybridized to a) ssP5T, b) wild-type, c) G1A, d)
G11A, and e) G21A. f) Unzipping time as a function of the simulated hybridization energy calculated using NUPACK. g) Scatter plot of unzipping time
versus blocking ratio.

it was unable to offer precise discrimination of mutation
positions.
2.3. Detection of Point-Mutation Position Using the P3T Probe
Enhanced distinguishability between data clusters for each DNA
target was achieved by changing the complementary probefrom P5T to P3T. In the case of the P3T–WT hybridized com­plex, the unzipping time increased significantly from 38 ± 4 to587 ± 60 ms, and the blocking ratio also increased from 84% to89% (Figure 3a). Reasons for this are proposed in the “Discus­sion” section. Figure 3b presents the scatter plots of the blocking
ratio and unzipping time of the unzipping events of the WT
and five different mutants hybridized with P3T. The order of theblocking ratio is shown to be WT > G1A > G11A > G21A. It isnotable that this order was also demonstrable in the series where
the positions of mutated nucleotide were in high proximity: WT >G1A > G2A > G3A. On the other hand, the unzipping time did notshow such a clear tendency with mutation position. It has previ­
ously been reported that the unzipping time has correlation with
the ΔG of hybridization.[35,36] Our results support this hypothesis,
as evident in Figure 3c, in which there is a remarkably clear rela­tionship between unzipping time and ΔG of hybridization.

Small Methods 2020, 2000101

2.4. Different Mismatched Pairs at the Same
Mutation Position
The capacity to recognize varied nucleotide mutations at thesame position for G1A, G1C, G1T, and WT was also tested.
During unzipping initiation, this position is closest to theconstricted region of the αHL pore (Figure 4a). The order ofblocking and unzipping times was WT > G1A ≈ G1C > G1T
and WT ≫ G1A > G1T > G1C, respectively. Although eachparameter was individually insufficient for discernment of themutated nucleotide, the data points for a given mutant andfor the WT can be seen to lie in distinct regions of the scatterplot shown in Figure 4b. However, the ΔG of hybridizationin this case did not have correlation with the unzipping time
(Figure 4c).

3. Discussion
3.1. Differences between the P5T and P3T Probes
In the case of B-form DNA, molecular modeling demonstrates
that dsDNA overstretched from the 3′3′ ends is more stableagainst force-induced dehybridization than that from the2000101 (3 of 7)© 2020 Wiley-VCH GmbH

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Figure 3. Results when using P3T for the detection of mutation positions. a) Positioning the poly(dA)30 at the 3′ terminal shows increased unzipping timeand blocking ratio relative to P5T. b) Scatter plots of the blocking ratio and unzipping time of five different mutation patterns and the wild-type, each hybridized with P3T. c) Unzipping time versus simulated ΔG of hybridization. The dotted line shows to guide the eye. d) Diagram showing mutation positions.

5′5′ ends.[37] This behavior causes differing geometry forthese two cases under axial extension as studied in mag­netic bead experiments; extension from the 3′ ends leads toa flat ribbon conformation while extension from the 5′ ends
leads to a narrow fiber with a strongly negatively inclined base.
The pulling forces for the 3′3′ and 5′5′ ends are 141 ± 3 and122 ± 4 pN, respectively, demonstrating that the 3′3′ ends are
15% more stable than the 5′5′ ends. Similar behavior occurs in
nanopore unzipping events (Figure 5a,b). The mean unzipping
times of P5T (5′5′) and P3T (3′3′) were 101 ± 9 and 587 ± 61 ms,
respectively, revealing that the P3T (3′3′) system has an unzip­
ping time of over five times slower. Although the length of
dsDNA and the experimental conditions in this study differedto the previously reported magnetic bead experiment, the trend
in stability of P3T (stable) > P5T (unstable) was mostly con­sistent with the previous results.[38]3.2. Trends in Blocking Ratio in the P3T System
The level of current blocking in the mutant–P3T system is seen
to be much lower than that of the WT system. It is proposed that
increased flexibility of the unpaired bases offers a reduced bar­rier to ion mobility, and therefore a lower reduction in current.
The blocking level is dependent upon mutation position, with theorder of the blocking ratio following WT > G1A > G2A > G3A.

Figure 4. Results when using P3T for the detection of different mismatched pairs at the same position. a) Diagram showing different mismatchedpairs at the same position. b) Scatter plots of different mismatch patterns in the same position. c) Unzipping time versus simulated ΔG of hybridization. The dotted line shows to guide the eye.

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to follow the above trend for the GxA system, in which the flex­
ible base effect causes a reduction in current blocking ratio. The
effect of base identity on the blocking ratio (G1C ≈ G1A > G1T)
highlighted herein may be further explained based on a pre­vious study concerning the interaction between the hairpin DNA(hpDNA) terminus and the αHL pore wall.[39,40] The ten basepair hpDNA with a T-overhang (10 bp-•T) was shown to have a
low activation energy, indicating that there is a weak interaction
between the T-overhang and the constricted region of the αHLnanopore. The T-terminal mutant therefore is proposed to have amore flexible terminus which is less able to impair ion mobility.
3.3. Trends in Unzipping Time in the P3T System
The unzipping time is shown to be dependent upon the ΔG
within the same mutation group (GxA). This result is con­sistent with the previous studies.[35,36] It has been previously
discussed that the unzipping kinetics of dsDNA through thenanopore follows the first-order reaction as follows[ dsDNA + α HL ] → [ssDNA ] + [α HL ] (1)The rate constant of this reaction can be described as below
k = k0 exp( −∆Gsim / kBT )(2)k = 1 / t (3)Figure 5. a) Diagram demonstrating the unzipping conformation of the
5′5′ double-stranded DNA–P5T hybrid in an αHL pore. b) Diagram demonstrating the unzipping conformation of the 3′3′ double-stranded DNA–P3T hybrid in an αHL pore. c) Scatter plots showing the combined resultof both mutation at differing position, and mutation at the same position
but to differing nucleotides.

This pattern demonstrates that a reduced ion current flows whenthe mutation position is further from the constricted region of the
αHL nanopore during unzipping. It can be explained that due tothe short strand length of two or fewer nucleotides (G3A, G2A,
and G1A) below the mutated site, only weak hydrogen bonding ofthese bases occurs. Thermodynamic simulations with NUPACK
at 25 °C, the same DNA concentration in the channel current
measurements (1 × 10−6 m) has been set, support this assumption(Figure S1, Supporting Information). While in the unzipping con­formation, these weakly bound bases are less able to restrict ion
mobility than in dsDNA where the mutation lies further from theconstricted pore site. In such cases where mutations are further
from the limiting aperture in αHL during unzipping, the ordering
showed inconsistencies. For instance, the blocking ratio of G11A
was higher than that of G3A although the position of G11A is fur­ther from the constricted site than G3A. This result may indicatethat G3A presents a minimum blocking level, with any mutation
above G3A having a similar blocking ratio.
In the GxC and GxT mutants, the order of the blocking ratio
was WT > G1C ≈ G1A > G1T. Reasons for this trend are proposed

Small Methods 2020, 2000101

where k is the dissociation rate constant, k0 is the initial rate
constant, ΔGsim is the simulated ΔG, kB is the Boltzmann con­stant used for the single-molecule study, T is the temperature,and t is the peak value of unzipping time histogram after boot­strapping. Unzipping data of the GxA series were fitted using
Equation (2) as shown in Figure S2 (Supporting Information).
Equation (2) was well fitted and this result suggests the firstorder reaction even in the mutation system. On the other hand,
the mutation series such as GxT and GxC did not fit well using
an exponential curve (Figure 4c). This result may imply that
there is a unique relationship between the ΔG and the unzip­
ping time in each mutation series.

4. Conclusion
A method for the detection of single-point mutation in oligo­
nucleotides using nanopore measurement was developed.
Conventional nanopore measurements use two parameters toanalyze molecule detection: the blocking current and the dura­tion time of molecular translocation through the nanopore. In
the case of conventional detection of mutated oligonucleotides,
the translocation speed of the oligonucleotides is too rapid torecognize the mutation. In this study, translocation speed isslowed by using a hybridized probe on the target nucleotides.
Bootstrapping was applied for a more precise analysis of theunzipping time, which was shown to exhibit the correlation
with the hybridization energy predicted by thermodynamic
simulations. By optimization of the DNA probe, discriminationof mutation position at the single-nucleotide resolution was

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achieved. Furthermore, mutant variations such as GxA, GxC,
and GxT are also discernible using the method described. Byplotting the blocking ratio against unzipping time, it shown to
be possible to distinguish between mutants. Our method offersa powerful tool for the mutation detection for oligonucleotides
and is proposed to be applicable for simple cancer diagnosis
using ctDNA as a nanopore liquid biopsy.

Supporting Information
Supporting Information is available from the Wiley Online Library orfrom the author.

Acknowledgements

5. Experimental Section
Reagents and Chemicals: In this study, the following reagents wereused: 1,2-diphytanoyl-sn-glycero-3-phosphocholine (DPhPC; Avanti Polar
Lipids, Alabaster, AL, USA), n-decane (Wako Pure Chemical Industries,
Ltd., Osaka, Japan), potassium chloride (KCl; Nacalai Tesque), Buffered
electrolyte solutions were prepared from ultrapure water, which was
obtained from a Milli-Q system (Millipore, Billerica, MA, USA). αHL(Sigma–Aldrich, St. Louis, MO, USA) was obtained as a monomer protein
isolated from Staphylococcus aureus in the form of a powder, dissolved
at a concentration of 1 mg mL−1 in 1 m KCl, and stored at −80 °C. Foruse, samples were diluted to 600 × 10−9 m using a buffered electrolyte
solution and stored at 4 °C. Each DNA (Eurofins Genomics K.K., Japan)
was obtained from DNA synthesis in the form of a powder, dissolved at
a concentration of 100 × 10−6 m in ultrapure water, and stored at −20 °C.
Design and Formation of the Probes and Mutated DNA: The freeenergies of P3T and P5T with mutated DNA were calculated bythermodynamic simulations using NUPACK web-server.[41] Annealing of
the double strands was conducted by heating a DNA sample for 5 min
at 50 × 10−6 m in ultrapure water at 95 °C and gradually cooling to room
temperature.
Bilayer Lipid Membrane Preparation and Reconstitution of α-Hemolysin:
Bilayer lipid membranes (BLMs) were prepared using a device producedby microfabrication (Figure S3a, Supporting Information). The methodof fabrication was previously reported.[26,42,43] BLMs can be formedin this device by the droplet contact method (Figure S3b, Supporting
Information). First, the DPhPC (lipids/n-decane, 10 mg mL−1) solution(0.6 µL) was dropped into each chamber. Second, the buffer solution(1 m KCl, 10 × 10−3 m 3-(N-morpholino)propane sulfonic acid, pH 7.0, and5 µL) with αHL and DNA (final concentration = 1 × 10−6 m) was dropped
into each chamber. A few minutes after adding the buffer solution, thetwo lipid monolayers combined to form BLMs. αHL formed nanoporesby insertion in the BLM. Upon rupture of BLMs, they were reformed bymanual agitation between two chambers with a hydrophobic stick.[44]Channel Current Measurements and Data Analysis: The channel current
was monitored using an Axopatch 200B amplifier (Molecular Devices,USA), filtered with a low-pass Bessel filter at 10 kHz at a sampling rateof 50 kHz. A constant voltage of +120 mV was applied from the transside, with the cis side was grounded. Recorded data were acquired with
Clampex 9.0 software (Molecular Devices, USA) through a Digidata
1440A analog-to-digital converter (Molecular Devices, USA). Data wereanalyzed using Clampfit 10.7 (Molecular Devices, USA), Excel (Microsoft,
Washington, USA), and Python (Python Software Foundation, Delaware,USA). The analyzed data were chosen from over three different αHLnanopores. DNA translocation event was defined at inhibition of >80%
of open αHL channel current. The blocking ratios were calculated withthe open and blocking channel conductance. Unzipping time wasfiltered between 7 and 12 000 ms. The bootstrap method is based on theresampling of the original random sample drawn from a population withan unknown distribution. The exact bootstrap method, which availed theentire space of resamples, was used. In the exact bootstrap method, theverification of accuracy will be made possible when the sample number
is over 30.[45] In this work, this bootstrap procedure took 300 samples
randomly from the primary common logarithmic translocation data with
65 536 replacements and to calculate the means for these samples. The
bootstrapped data produced the histograms and plots of logarithmic
unzipping time and blocking ratios. The error bars shown in Figures 2f,

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3c, and 4c were the widths of two standard deviations after bootstrapping(68.27% of the data fall within one standard deviation of the mean).

This work was partly supported by KAKENHI (Grant Nos. 17K19138 and
19H00901) from MEXT, Japan. With thanks to K. Shimizu, A. Tamotsu,
M. Yamaji, and A. Cooney for useful discussions on data analysis and for
language editing.

Conflict of Interest
The authors declare no conflict of interest.

Keywords
circulating-tumor DNA, liquid biopsy, nanopore sensing, single-point
mutation
Received: February 12, 2020
Revised: June 18, 2020
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