The need for measurements of multiple biomarkers simultaneously at subnanomolar concentrations asks for the development of new sensors with high sensitivity, specificity, precision, and accuracy. Currently, multiplexed sensing in single molecule sensors increases the complexity of the system in terms of reagents and sample read-out. In this letter, we propose a novel approach to multiplex hairpin-based single-DNA molecule sensors, which overcomes the limitations of the present approaches for multiplexing. By target-dependent ssDNA hairpin design, we can create DNA tethers that have distinct tether dynamics upon target binding. Our numerical model shows that by changing the stem length of the ssDNA hairpin, significantly different dynamic tether behavior will be observed. By exploiting the distance-dependent coupling of AuNPs to gold films, we can probe this dynamic behavior along the z-axis using a simple laser equipped microscope.
The need for measurements of multiple biomarkers simultaneously at subnanomolar concentrations asks for the development of new sensors with high sensitivity, specificity, precision, and accuracy. Currently, multiplexed sensing in single molecule sensors increases the complexity of the system in terms of reagents and sample read-out. In this letter, we propose a novel approach to multiplex hairpin-based single-DNA molecule sensors, which overcomes the limitations of the present approaches for multiplexing. By target-dependent ssDNA hairpin design, we can create DNA tethers that have distinct tether dynamics upon target binding. Our numerical model shows that by changing the stem length of the ssDNA hairpin, significantly different dynamic tether behavior will be observed. By exploiting the distance-dependent coupling of AuNPs to gold films, we can probe this dynamic behavior along the z-axis using a simple laser equipped microscope.
With improvements in understanding
of diseases and their development, healthcare is increasingly interested
in early and simultaneous detection of multiple biomarkers.[1] Multiplexing, the analysis of various biomarkers
for a single disease type, has shown improvement in both sensitivity
and selectivity when detecting cancer and infectious diseases.[2−4] Disease-specific biomarkers can be collected more easily than ever
by using noninvasive techniques from the upcoming field of liquid
biopsies. However, the typically low concentration (Research is pushing toward biosensors with single-molecule
resolution
because these offer enhanced sensitivity, specificity, precision,
and accuracy compared to bulk measurement techniques.[5−8] Initial near-field approaches for single molecule sensors could
only detect a maximum of tens of single molecules simultaneously,
which results in low-throughput detection and a limited concentration
window.[9] More recently, massive parallelization
of these sensors in combination with wide-field observation has allowed
for measurements of hundreds if not millions of single detection events
of a specific analyte, improving both detection limit and sample throughput.[5]One downside of these wide-field single
molecule techniques is
their typical digital readout (they detect only target presence or
absence), which does not allow differentiation between different bound
targets. Therefore, multiplexing of wide-field single molecule sensors
has required one of several severe increases in complexity, such as
spatial separation of binding sites for different biomarkers,[10,11] washing with multiple reagents,[12] and
using targets of dramatically different affinity[13] or multichannel (fluorescence) read-out.[14] These complications reduce the application of multiplexed
sensors in the medical world where there is a need for reliable and
simple assays. In this letter, we propose a novel approach to overcome
the current limitations of multiplexed single molecule sensors. Specifically,
we propose that DNA hairpin-sensors, similar to those described in
literature,[15−21] besides its excellent performance in complex media,[22] may also be easily multiplexed by designing target-specific
changes into the hairpins’ structure. Analysis of sensor dynamics
then allows easy determination of which specific sensing element has
been activated.The proposed sensor (Figure ) will consist of thousands of individual
sensing elements,
each composed of a single ssDNA hairpin that tethers one gold nanoparticle
(AuNP) to a gold film (Figure A). Upon target binding, the hairpin unfolds, changing not
only the volume accessible to the AuNP but also the physical properties
of the tether. Just like the typical DNA hairpin sensors described
in literature,[15−20] our sensor consists of both ssDNA (originating from the self-complementary
part of the hairpin-stem not involved in target binding), and double-stranded
DNA (dsDNA) (Figure A) upon target binding. However, novelty comes from the multiplexability
of our proposed sensor: by making the length of both ssDNA and dsDNA
target dependent, we induce target-specific differences in both the
physical properties of the tether and the volume accessible to the
AuNP. These differences will be probed by looking at the dynamic behavior
of the AuNP.
Figure 1
Schematic representation of multiplexed TPM-based sensing.
(A)
ssDNA molecule bound to the gold film and AuNP. Because of a self-complementary
part, a stem structure will be formed that results in a so-called
hairpin. Upon target binding, part of the self-complementary DNA nucleotides
will bind to the target (in red), unzipping the hairpin, and resulting
in a ssDNA (in blue) tether followed by a dsDNA tether. (B) Schematic
representation of a sensing element prior to and after target-binding
with different ssDNA lengths. The changes in the z-axis over time increase after target binding and are dependent on
the length of original ssDNA stem, which adds to the total tether
length. (C) Detailed schematic overview of a single sensing element
bound to a target DNA sequence.
Schematic representation of multiplexed TPM-based sensing.
(A)
ssDNA molecule bound to the gold film and AuNP. Because of a self-complementary
part, a stem structure will be formed that results in a so-called
hairpin. Upon target binding, part of the self-complementary DNA nucleotides
will bind to the target (in red), unzipping the hairpin, and resulting
in a ssDNA (in blue) tether followed by a dsDNA tether. (B) Schematic
representation of a sensing element prior to and after target-binding
with different ssDNA lengths. The changes in the z-axis over time increase after target binding and are dependent on
the length of original ssDNA stem, which adds to the total tether
length. (C) Detailed schematic overview of a single sensing element
bound to a target DNA sequence.Our derivation of tether properties from the observed dynamics
is based on the fundamentals of tethered particle motion (TPM). TPM
describes the motion of microparticles connected to a substrate by
a tether.[23] The tether, in this case a
DNA molecule consisting of a ssDNA and dsDNA part and several linkers,
confines the bead to a certain volume of space, within which Brownian
motion determines the particle position over time. Because the tether
properties play an important role in the movement of the particle,
TPM is typically used to study tether properties like persistence
length[24] and looping kinetics.[25,26] Furthermore, TPM has been used to investigate interactions between
DNA and proteins such as polymerases[27] and
lac repressors,[28] as these interactions
induce changes in DNA flexibility. While these studies use TPM to
probe unknown properties of the tether, we propose the reverse: using
TPM to discriminate between different tethers of known properties,
with each distinct tether type matching a specific ssDNA target molecule.
To do this, we will perform simulations of the dynamic behavior of
tethers consisting of different ssDNA lengths, followed by varying
lengths of dsDNA. In real experiments, we could match observed TPM
dynamic behavior with the behavior obtained via calibration or the
simulation experiments as presented in this letter.Because
we focus on the detection of DNA sequences in liquid biopsies,
the typical DNA target fragment length is <100 base pairs (bp),[29,30] which correspond to a length of ∼30 nm. This requires a relatively
short total hairpin length, which limits localization precision. In
current TPM experiments, read-out precision is limited by the spatial
localization precision of typical optical microscopes when resolving
conformational bead changes, which is typically ∼10 nm. This
results in the use of >200 bp dsDNA tethers in most TPM experiments
to allow precise tracking of the movement of the bead.[31,32] Here we propose to overcome the localization issue for short tethers
by using plasmonic sensing, in which the distance-dependent plasmonic
coupling of AuNPs to gold films is exploited to precisely determine
particle position. Plasmonic sensing is based on the resonant scattering
of a sub-100 nm AuNP, which has a resonance peak in the green region
of the optical spectrum when free in a buffer.[33] When the same AuNP is placed near a gold film, the gold
film acts as a mirror, and allows the AuNP to interact with its mirror
image, resulting in a red-shift, comparable to the spectral shift
observed for AuNP dimers.[34,35] The degree of red-shift
of the AuNP scattering spectrum is strongly distance dependent, with
the largest first derivative over the range of 0–50 nm, which
makes this system extremely suitable to probe the changes along the z-axis of our tethered AuNP.[36,37]To prove
that multiplexing is indeed possible with such a sensor,
we numerically predict the differences in tether composition needed
to perform plasmonic multiplexed nucleotide binding assays with ssDNA
hairpin tethers. A model was developed which considers both tether
properties and Brownian AuNP movement in a sequential fashion, coupled
to electromagnetic simulations to simulate the detected optical signal
over time for different tethers (Supporting Information methods 1, 2, and 3). In short, the simulations
consist of three separate steps that together form our model (Figure ). It all starts
with defining the parameters, such as the length of the ssDNA (10,
20, or 30 nucleotides (nt)) left after target binding, length of dsDNA
after target binding (50–70 bp with a 2 bp step size), and
AuNP size (80, 78, and 82 nm to account for polydispersity of the
AuNPs used). In the first step of the model, the tether-dependent
position distributions of the particles are determined using a Monte
Carlo simulation method. The output of this model is a probability
map of the particle positions. The second step involves the use of
inverse Boltzmann statistics, where the probability distribution of
the AuNP positions is converted to a potential energy map.[36,38] The potential energy map then forms the input to Brownian Dynamics
simulations of the AuNP, where the potential energy results in a position-dependent
force on the AuNP. From the Brownian Dynamics simulations, we obtain
a time series of the AuNP position along the z-axis,[36],[39] which then together
with the plasmonic model results in the simulated detector signal.
For plasmonic response calculations, electromagnetic boundary element
method (BEM) simulations were performed to calculate the distance-dependent
scattering and absorption of AuNPs (Supporting Information, Method 4). With the BEM simulations, the z-axis dependent scattering cross section of the particle
can be obtained. From the positional time series obtained by the Brownian
motion simulations, the probe wavelength dependent scattering cross
section over time (σscat(t,λprobe)) is then calculated, which, together
with setup dependent factors, results in a time-variant number of
photons detected by the setup. A more elaborate explanation of the
model and its considerations can be found in the Supporting Information.
Figure 2
Schematic of the developed model consisting
of the Monte Carlo
simulations, Brownian dynamics simulations, and MNP-BEM simulations,
that together result in the simulated detector signal.
Schematic of the developed model consisting
of the Monte Carlo
simulations, Brownian dynamics simulations, and MNP-BEM simulations,
that together result in the simulated detector signal.Our model results in “raw” time traces, and
we started
with calculating the traces for an optical signal integration time
of 50 μs, chosen to filter out false motion of the particle
due to shot-noise or thermal expansion and/or contraction of the microscope.[25,40−43] The probability density function (PDF) of the total optical output
was subsequently calculated (Figure A), and it was found that the average of the photon
counts did not significantly differ for 50 bp DNA tethers with three
different lengths of ssDNA (10, 20, 30 nt) (Figure B). For all other tested hairpin compositions
(with varying ssDNA and dsDNA length), the same result was found (Figure S10). This indicates that the difference
in possible positions introduced by different hairpin properties is
averaged out by the many positions shared among the different tethered
AuNPs. Differences in total photon count can thus not be used to distinguish
between different tethers.
Figure 3
Comparison between average positions (A,B) and
average mean square
fluctuations (C,D) as discriminators for different tether properties.
All results in this figure are generated for a 50 bp dsDNA strand
with either a 10, 20, and 30 nt ssDNA and a simulated signal with
an integration time of 50 μs. (A) Position probability map for
a tether consisting of a 50 bp dsDNA strand and a 10 nt ssDNA strand.
(B) Plotted distribution of the detector signal for different lengths
of ssDNA. (C) Mean square fluctuation plot for increasing time step
for different ssDNA strand lengths. (D) Distribution of mean square
fluctuation values found for different ssDNA strand lengths..
Comparison between average positions (A,B) and
average mean square
fluctuations (C,D) as discriminators for different tether properties.
All results in this figure are generated for a 50 bp dsDNA strand
with either a 10, 20, and 30 nt ssDNA and a simulated signal with
an integration time of 50 μs. (A) Position probability map for
a tether consisting of a 50 bp dsDNA strand and a 10 nt ssDNA strand.
(B) Plotted distribution of the detector signal for different lengths
of ssDNA. (C) Mean square fluctuation plot for increasing time step
for different ssDNA strand lengths. (D) Distribution of mean square
fluctuation values found for different ssDNA strand lengths..In contrast to the average photon count, the tether-dependent
particle
dynamics do show a significant difference between different tether
lengths. The mean square fluctuation (MSF) is a measure of the deviation
of the plasmonic signal with respect to a reference signal over time.
It is commonly used to express the spatial extent of random motion
and can be used to determine whether a particle is moving solely by
diffusion or is experiencing additional forces. In this case, the
additional force originates from the tether, which limits the diffusion
of the AuNP compared to free diffusion, in a tether-dependent fashion
(Figure C). We took
the mean over 500 points of the maximum of the MSF curve and plotted
the distribution of the values for the same tether with 50 bp dsDNA
and 10, 20, and 30 nt lengths of ssDNA, as was tested in Figure B. The predicted
MSFs in Figure D significantly
differ (F(10,90) = 18.681, p = 0.00),
demonstrating that the particles dynamics rather than average position
will allow target discrimination. To study the effect of multiple
tether lengths, we calculated the average MSF for DNA tethers with
a size of 50–70 bp dsDNA and either 10, 20, or 30 nt of ssDNA.
An (almost) linear relationship between the length of the dsDNA and
the MSF can be found and the individual tether properties can clearly
be distinguished (Figure ). With a univariate analysis in SPSS followed by a post-HOC
Tukey’s multiple comparison test, we could determine whether
the MSF of each ssDNA–dsDNA combination was significantly different
from the other combinations. From this, we could conclude that a maximum
of four ssDNA–dsDNA combinations could be distinguished simultaneously,
which means that with the proposed sensing method four different target
sequences could be measured on a single sensing surface (Supporting
Information, Figure S13).
Figure 4
Mean square fluctuation
of the maximum detector signal for different
tether properties where n = 3 individual simulations
for each data point. Error bars represent the mean ± sd, where n = 3 (three independent simulations).
Mean square fluctuation
of the maximum detector signal for different
tether properties where n = 3 individual simulations
for each data point. Error bars represent the mean ± sd, where n = 3 (three independent simulations).The above demonstrates that a hairpin-based plasmonic sensor can
be used to perform multiplexed ssDNA sensing by determining the tethered
particle MSF along the z-axis. Variations in both
the ssDNA length (10–30 nt) and the total tether length (60–100
nts) result in significantly different results as confirmed by ANOVA
statistical testing. For 80 nm AuNPs, a single wavelength can be used
to probe the z-axis MSF.The results presented
in Figure do not
consider some real-life measurement issues.
In the next part of this letter, we will consider three main issues
one could face while exploiting our sensing method and will propose
practical solutions. Concerning the sensor development, it is important
to know how many hairpins are needed in total to allow multiplexed
sensing. The number of available AuNPs, together with the reaction
kinetics of the target ssDNA with the hairpin-DNA, the target sequence
concentration, the number of different targets one wants to sense,
and the measurement time then determine the amount of sensing events
that will be measured.[44] The lower bound
for the number of sensing events will depend strongly on the analyte
of interest, but with statistics we can set a minimum, based on a
10% statistical error, of 100 sensing events per analyte. For an hour
of measuring at 1 nM concentration and a kon of 100 μM,[45,46] this requires 2800 hairpins per
target sequence. Because of the strong scattering properties of 80
nm AuNPs, a low microscope magnification is possible and up to 1000–5000
AuNPs could be followed simultaneously using a CMOS detector depending
on the resolution of the detector and the needed integration time,
where the point spread function of an 80 nm AuNP on average covers
870 nm2.[47,48] Taking the new generation of
affordable high speed cameras into consideration, and the integration
time of around 50 μs, this means that between 300 and 1000 AuNPs
can be sensed[49] Therefore, multiplexed
sensing of many different target sequences requires the further development
of ultrahigh resolution detectors with low magnification objectives
supporting high frame rates, or a more simple solution such as moving
the sensor surface along the detector to image a larger sensor surface.For all calculations and simulations presented in this letter,
we assumed AuNPs to be monodispersed with an 80 nm diameter. However,
all commercially available AuNPs are polydisperse. Because we observe
the variations over time of the gap size dependent plasmonic coupling
of individual particles, this could cause issues when distinguishing
whether changes in detector signal are due to particle or tether variations,[50,51] as the scattered intensity of a AuNP is proportional to the square
of the AuNP static polarizability. Therefore, larger particles have
a higher scattering intensity and a different relation between gap
size and scattering intensity at a specific wavelength. We can conveniently
overcome this issue by introducing a calibration step prior to target
binding by imaging the hairpin-AuNPs. In Supporting Information, Method 6, we show that in the hairpin state the
measured scattering intensity is mainly determined by the AuNP size
as the AuNP does not have a large accessible volume. This allows easy
self-calibration of the system to extract the AuNP size.The
last practical issue we would like to discuss is that short
target sequences found in liquid biopsies vary considerably in size
depending on the isolation method, patient, and origin of the biopsy.
We therefore performed a simple check on the influence of the size
of the target DNA on the dynamic fluctuations of the AuNP after target
binding and found that indeed this effect was significant (F(2,8) = 14.450, p = 0.005), Supporting
Information, method 7). However, if we
ignore the ssDNA length and look only at total tether length (sum
of ssDNA and dsDNA length = the original hairpin length), we see a
significant difference between the tether lengths (F(20,98) = 28.699, p = 0.000)). Thus, if we measure
ssDNA targets fragments of different lengths, we can still significantly
distinguish the different tether lengths and use this for multiplexed
sensing. For target lengths that exceed the length of the complementary
part of the hairpin, we did not perform any simulations. Here, we
anticipate two factors playing a role: long ssDNA target strands can
inhibit the degrees of freedom of the AuNP relative to short DNA fragments,
but as the persistence length of ssDNA is low (∼2 nm (ref (52)), it will be flexible
and probably not significantly inhibit the movement of the particle
compared to the drag force the particle is experiencing close to the
surface.In conclusion, the proposed sensing method allows robust
monitoring
of biomolecules with the possibility of simultaneous multiplexed gene
detection with high specificity using plasmonic AuNPs that offer single-molecule
read-out at a simple, laser-equipped, microscope.
Authors: Sanneke Brinkers; Heidelinde R C Dietrich; Frederik H de Groote; Ian T Young; Bernd Rieger Journal: J Chem Phys Date: 2009-06-07 Impact factor: 3.488
Authors: Jack J Mock; Ryan T Hill; Aloyse Degiron; Stefan Zauscher; Ashutosh Chilkoti; David R Smith Journal: Nano Lett Date: 2008-07-01 Impact factor: 11.189
Authors: Peter F J May; Justin N M Pinkney; Pawel Zawadzki; Geraint W Evans; David J Sherratt; Achillefs N Kapanidis Journal: Biophys J Date: 2014-09-02 Impact factor: 4.033