Designed "DNA carriers" have been proposed as a new method for nanopore based specific protein detection. In this system, target protein molecules bind to a long DNA strand at a defined position creating a second level transient current drop against the background DNA translocation. Here, we demonstrate the ability of this system to quantify protein concentrations in the nanomolar range. After incubation with target protein at different concentrations, the fraction of DNA translocations showing a secondary current spike allows for the quantification of the corresponding protein concentration. For our proof-of-principle experiments we use two standard binding systems, biotin-streptavidin and digoxigenin-antidigoxigenin, that allow for measurements of the concentration down to the low nanomolar range. The results demonstrate the potential for a novel quantitative and specific protein detection scheme using the DNA carrier method.
Designed "DNA carriers" have been proposed as a new method for nanopore based specific protein detection. In this system, target protein molecules bind to a long DNA strand at a defined position creating a second level transient current drop against the background DNA translocation. Here, we demonstrate the ability of this system to quantify protein concentrations in the nanomolar range. After incubation with target protein at different concentrations, the fraction of DNA translocations showing a secondary current spike allows for the quantification of the corresponding protein concentration. For our proof-of-principle experiments we use two standard binding systems, biotin-streptavidin and digoxigenin-antidigoxigenin, that allow for measurements of the concentration down to the low nanomolar range. The results demonstrate the potential for a novel quantitative and specific protein detection scheme using the DNA carrier method.
Proteins are essential for living systems and serve in diverse roles
for instance in transport, catalysis, molecular motion and structural
support. Most of their functions are modulated and controlled by both
the identity and abundance. The accurate and specific measurement
of protein concentrations is therefore of fundamental importance in
biological and medical research, drug screening, and disease diagnosis.
Several well-established methods are used for determining protein
concentration. High accuracy can be achieved using radio labeling[1] and mass spectrometry[2] in which protein molecules are analyzed at peptide or single amino
acid level. Specific binding based methods such as electrophoretic
mobility shift (EMSA),[3] fluorescent polarization
(FP),[4] and enzyme-linked immunosorbent
assays (ELISA)[5] are commonly used for routine
protein concentration determination. Efforts have been made toward
lowering the detection limit, required sample volumes and throughput
by introducing micro or nano arrays[6] and
nanoparticles.[7]Solid-state nanopore
based sensing is being actively investigated as a versatile platform
for single-molecule protein sensing. This research is driven by the
potential for fast detection, avoiding the sometimes cumbersome fluorescent
labeling of proteins, with a single molecule sensing method which
can be integrated into silicon electronics. Furthermore, since the
throughput of the acquired signal is independent of the sample volume,
and rather depends on the concentration, there is the possibility
for microfluidic integration[8] which provides
an advantage over established techniques such as ELISA and radio-labeling.
However, results to-date using solid-state nanopore indicate that
the translocation speeds of most protein monomers are too fast for
all translocations to be accurately recorded at typical experimental
bandwidths.[9] Although high bandwidth systems
combined with thin membranes can record most translocations in a limited
voltage range, the fast translocation aspect makes it particularly
challenging to accurately determine protein concentration.[10] Another complication is added by the potential
for various protein-nanopore wall interactions[11] limiting the ability to differentiate protein species.
Creating a binding site for a target protein on a long DNA strand
(DNA carrier) and measuring the translocation signals of the complex
helps to address these problems in protein monomer only translocations.[12] First the binding site can be selective for
a certain protein which enables its identification. Second the easily
discernible signal from the current event produced by the DNA strand
provides a marker for predicting when the protein signal will occur.
Therefore, protein signals are only analyzed when occurring during
the DNA signals rather than the whole experimental current trace.In this study we employ the method of DNA carriers for evaluating
protein concentration (Figure ). We determine the concentration by measuring the fraction
of DNA carriers which show a secondary signal indicating the presence
of a protein. Two model systems are investigated, namely, biotin–streptavidin
and digoxigenin–antidigoxigenin. Binding curves are constructed
by varying the protein concentration in these two systems. Our results
show good agreement between the nanopore based binding curve and a
model using a dissociation constant value determined by other standard
assays. For the biotin–streptavidin system, we measure a small
deviation from the expected binding curve which we assign to the lower
signal-to-noise ratio for the 52.8 kDa streptavidin bound on the DNA.
Figure 1
(a) Schematic
representation of incubated DNA carrier (black line) and protein complexes
(black line with a blue cuboid attached) translocating through a nanopore
driven by the electric field. (b) Example occupied carrier translocation
event shows an extra second level current drop in the very middle
of the event, which is caused by the targeted protein binding. To
find the positive events through data processing, we set a searching
window of 25% of the total event duration. (c, d, e) Schematic and
example DNA carrier translocation events after incubation with targeted
protein of different concentrations. The concentration ratios (cProtein/cCarrier) are decreasing from c to e. The carriers are fully occupied in
c showing that all the carrier translocation events have secondary
current spike positioned in the middle (occupied events), while in
d and e, less occupied events are found. Example events are produced
by the biotin–streptavidin system.
(a) Schematic
representation of incubated DNA carrier (black line) and protein complexes
(black line with a blue cuboid attached) translocating through a nanopore
driven by the electric field. (b) Example occupied carrier translocation
event shows an extra second level current drop in the very middle
of the event, which is caused by the targeted protein binding. To
find the positive events through data processing, we set a searching
window of 25% of the total event duration. (c, d, e) Schematic and
example DNA carrier translocation events after incubation with targeted
protein of different concentrations. The concentration ratios (cProtein/cCarrier) are decreasing from c to e. The carriers are fully occupied in
c showing that all the carrier translocation events have secondary
current spike positioned in the middle (occupied events), while in
d and e, less occupied events are found. Example events are produced
by the biotin–streptavidin system.The basic structure of the DNA carrier is fabricated by using
a linearized 7.2 kb m13mp18 virus genome (New England BioLabs) and
190 designed oligonucleotides (Integrated DNA Technologies) each 38
bases in length. These oligonucleotides hybridize to the m13mp18 single-stranded
(ss) DNA forming a long double-strand. The oligonucleotide in the
center of the DNA carrier was modified with a 5′ extension
of three thymines and either digoxigenin or biotin. Full details of
the assembly were described previously.[12]We use glass nanopores derived from the laser-assisted pulling
of quartz glass capillaries with outer diameters of 0.5 mm and inner
diameter of 0.2 mm (Sutter Instruments, USA). In order to optimize
the signal-to-noise ratio, two slightly different pulling programs
were used for the two different protein systems. The detailed parameters
for nanopore fabrication can be found in the Supporting Information (Table S1). The magnitude of the dsDNA current
drops is −0.160 ± 0.023 nA and −0.146 ± 0.025
nA for pulling program 1 and 2, respectively (distributions shown
in Supporting Information, Figure S1, errors
are standard deviations). Slightly larger nanopores produced by program
2 were used for the digoxigenin system with the aim of reducing unspecific
protein–nanopore surface interactions. The dsDNA current level
was used in the data analysis protocol for setting the appropriate
threshold (see Supporting Information,
Figure S2).Monovalent streptavidin was generously provided
by the Howarth Lab.[13] The three digoxigenin
antibody samples were purchased from three companies (Roche, Invitrogen,
and Abcam) (monoclonal, isotype IgG). The protein concentrations were
checked by measuring absorbance at 280 nm (Nanodrop 2000) before any
dilutions were done. DNA carriers with 3 nM concentration were incubated
with the target proteins for 30 min in 100 mM NaCl and 2 mM MgCl2 buffered with 10 mM Tris-HCl (pH ∼ 8). The sample
was then diluted by adding the same volume of 8 M LiCl, 100 mM NaCl,
and 2 mM MgCl2 with the same buffer condition, making the
final DNA carrier concentration of 1.5 nM in 4 M LiCl, 100 mM NaCl,
and 2 mM MgCl2 buffered with 10 mM Tris-HCl (pH ∼
7.5). The protein concentrations used range from 0 to 5.6 nM for streptavidin
and 0 to 31 nM for the digoxigenin antibody. All translocation measurements
were carried out at 600 mV applied voltage. The ionic current data
was acquired using an Axopatch 200B with a sampling frequency of 250
kHz and filtered at 49.9 kHz with an external 8-pole Bessel filter.For the independent determination of dissociation constants (Kd), electrophoretic mobility shift assay (EMSA)
and fluorescence polarization (FP) were used to investigate the affinity
of these two standard pairs. Detailed information on these assays
is given in the Supporting Information.The raw ionic current data contain translocations from free protein,
folded DNA carriers (observed in wide diameter nanopores as those
used here), and unfolded DNA carriers which pass through in a head-to-tail
fashion. There are also fragments of the full DNA carrier length due
to the synthesis procedure. It is important to note that we filter
the translocations to remove all subpopulations except the full length,
unfolded DNA carriers. This is achieved by an ECD (Event Charge Deficit)
threshold and ionic current threshold (1.5 times current drop amplitude
corresponding to double-stranded DNA) at the beginning and end of
the events. Details of this process were described previously.[12]An example translocation event after these
filtering steps is shown in Figure b. A searching window of 25% of the event duration
is created in the middle of each translocation to test for the presence
of a secondary peak due to the bound protein. The threshold to find
the peak was defined with a factor (I/IDNA) based on the dsDNA current amplitude. The fraction
of occupied events decreases with the increasing threshold factor
(Supporting Information, Figure S2). We
chose to use a threshold of 1.4 times the magnitude over the DNA carrier
signal, IDNA, for all the data analysis
in this work. This empirical threshold provides a clear differentiation
between the protein binding peak and the false positive peak observed
in DNA carrier measurements where there is no protein present.We chose the biotin–streptavidin interaction as it is one
of the strongest known noncovalent interactions with a dissociation
constant of Kd ∼ 10–15 M. Due to its extremely high affinity, this interaction is an ideal
model system for determining the ability of measuring protein concentrations
in the nanomolar range. First, we incubated an approximately four
times stoichiometric excess of monovalent streptavidin with the DNA
carrier. A few typical example events of the occupied biotin DNA carrier
are shown in Figure a. An extra transient current drop, representing a protein binding,
can be found in each of the example traces and is positioned in the
middle of the observation window of each event. A histogram of the
peak current drop (red) and an all points histogram (blue) of all
linear translocation events are shown in Figure b. The two peaks in the histograms are overlapping
indicating that the level of current drop caused by the monovalent
streptavidin is relatively close to that of the dsDNA level. This
explains why some streptavidin translocations may go undetected due
to the required threshold for event detection. Biotin–streptavidin
is known to retain its high affinity in a wide range of conditions
and extremes of pH, temperature and detergents[14] are needed to break the interaction. Therefore, we can
safely assume that the affinity remains significantly high, below
subnanomolar even in the high salt solution used for nanopore experiments.
Thus, we expect to observe a linear increase in the occupied fraction
of DNA carriers as a function of the streptavidin concentration until
all DNA carriers are saturated. As a control, EMSA was used to measure
the fraction of biotinylated DNA bound as a function of streptavidin
concentration. A 38 bp DNA duplex was synthesized with a three thymine
and biotin label and the protein was titrated against this duplex.
The upper bands in the gel image (Figure c) correspond to the duplexes with bound
streptavidin while the lower bands are the unbound duplexes. The binding
fraction obtained from the gel band intensity is plotted in Figure c. A good agreement
is found between the expected linear increase (gray dashed line) and
the gel intensity data.
Figure 2
Concentration measurement of streptavidin using
DNA carriers. (a) Schematic representation of biotin–streptavidin
systems and examples of occupied DNA carrier translocation events.
The monovalent streptavidin (blue cuboid) is 52.8 kDa. (b) Histogram
of the peak current drop (red) and an all points histogram (blue)
of all linear translocation events. The histograms are fitted by a
Gaussian function, where the main peak in the all point histogram
(μB) determines the dsDNA level and the center of
the peak current drop (μO) shows the protein binding
signal. The concentration ratio was 3.8 (cStreptavidin/cCarrier), cStreptavidin = 5.8 nM. (c) EMSA showing titration of monovalent streptavidin
against a biotin labeled DNA duplex of 38 bp. The corresponding gel
image is shown in the inset. The intensity of the lanes is determined
using ImageJ. Lane L is a DNA ladder reference (low molecular weight
from 25 bp to 766 bp). The concentration of the DNA duplex was 80
nM for each lane. Lanes 1–7 correspond to biotin labeled oligo
incubated with streptavidin of different concentration ratio (cStreptavidin/cOligo) of 0, 0.1, 0.2, 0.5, 1, 1.5, and 2, respectively. The gray dashed
line shows the linear increase expected for an infinitely high affinity
pairing at equilibrium. (d) Binding curve based on nanopore measurements.
A DNA carrier of 1.5 nM concentration was incubated with monovalent
protein from 0 nM to 5.6 nM. Error bars are standard error of the
mean from different nanopores. The binding curve is obtained from
a total of n = 70 nanopore experiments. The event
numbers in the plots are 434, 479, 2044, 689, 174, and 905 for data
points at the concentration ratio from 0 to 3.8, respectively (statistics
in Supporting Information S7).
Concentration measurement of streptavidin using
DNA carriers. (a) Schematic representation of biotin–streptavidin
systems and examples of occupied DNA carrier translocation events.
The monovalent streptavidin (blue cuboid) is 52.8 kDa. (b) Histogram
of the peak current drop (red) and an all points histogram (blue)
of all linear translocation events. The histograms are fitted by a
Gaussian function, where the main peak in the all point histogram
(μB) determines the dsDNA level and the center of
the peak current drop (μO) shows the protein binding
signal. The concentration ratio was 3.8 (cStreptavidin/cCarrier), cStreptavidin = 5.8 nM. (c) EMSA showing titration of monovalent streptavidin
against a biotin labeled DNA duplex of 38 bp. The corresponding gel
image is shown in the inset. The intensity of the lanes is determined
using ImageJ. Lane L is a DNA ladder reference (low molecular weight
from 25 bp to 766 bp). The concentration of the DNA duplex was 80
nM for each lane. Lanes 1–7 correspond to biotin labeled oligo
incubated with streptavidin of different concentration ratio (cStreptavidin/cOligo) of 0, 0.1, 0.2, 0.5, 1, 1.5, and 2, respectively. The gray dashed
line shows the linear increase expected for an infinitely high affinity
pairing at equilibrium. (d) Binding curve based on nanopore measurements.
A DNA carrier of 1.5 nM concentration was incubated with monovalent
protein from 0 nM to 5.6 nM. Error bars are standard error of the
mean from different nanopores. The binding curve is obtained from
a total of n = 70 nanopore experiments. The event
numbers in the plots are 434, 479, 2044, 689, 174, and 905 for data
points at the concentration ratio from 0 to 3.8, respectively (statistics
in Supporting Information S7).Figure d depicts the fraction of occupied events as a function of
the concentration ratio (cStreptavidin/cCarrier) for the nanopore experiments.
The lower limit is ∼0.1 which is due to the false positive
rate of protein-like signals observed on bare DNA. This false positive
can be caused by the presence of folds or knots in the DNA or other
factors. As expected, a linear increase of occupied fraction is observed
until the curve levels off at a fraction of 0.8. This leveling off
at 0.8 instead of 1 is due to the signal-to-noise ratio of the streptavidin
system. Some protein events are buried in the noise–as suggested
by Figure b. The peak
current histogram for streptavidin detection (Figure b, top) overlaps the current distribution
of the dsDNA level (Figure b, bottom). Additionally, the occupied fraction saturated
at a concentration ratio of 2 rather than 1. The continuing increase
beyond the expected ratio of 1 is likely due to nonspecific adsorption
to walls of the fluidic chip. This is a known problem in microfluidic
chips which is particularly prevalent at the nanomolar concentrations
used here.[15] We note that each point in Figure d shows an average
of 6–25 independent nanopore measurements and 2 or 3 different
protein sample dilution runs. We measure significant variations in
the occupied fraction during these repeats which are explained by
signal size variations from different nanopores and the variability
in nonspecific adsorption during the protein handling at nanomolar
concentration (Supporting Information,
Table S3).In a second demonstration of this method, we investigated
how the occupied carrier fraction varies with a digoxigenin–antidigoxigenin
(Anti-dig) system. The molecular weight of antidigoxigenin is 150
kDa—significantly bigger than streptavidin at 52.8 kDa. Indeed,
the peak current amplitude of the occupied carrier is typically bigger
than streptavidin (Figure a) which improves the signal-to-noise ratio and thus our detection
accuracy. The improved resolution can also be directly observed in Figure b, in which the overlap
between dsDNA level and protein binding level is almost nonexistent
compared to the data in Figure b.
Figure 3
Concentration measurement of antidigoxigenin using DNA carriers.
(a) Schematic representation of digoxigenin–antidigoxigenin
system and examples of occupied digoxigenin carrier translocation
events. The digoxigenin antibody (green Y-shaped structure) is about
150 kDa. (b) Histogram of the peak current drop (red) together with
an all points histogram (blue) of all linear translocation events.
The histograms are fitted by a Gaussians function. The concentration
ratio was 10.5 (cAnti-dig/cCarrier), cAnti-dig = 15.8
nM. (c) Binding curve based on nanopore measurements. A DNA carrier
concentration of 1.5 nM was incubated with monovalent protein from
0 nM to 31 nM. Error bars are standard errors of the mean (not included
for data points with two nanopores at the concentration ratio of 10.5
and 20.9). The plot represents data are from n =
25 nanopores. The event numbers in the plots are 94, 141, 159, 145,
111, 93, and 32 for data points at the concentration ratio from 0
to 21 respectively (statistics in Supporting Information S7).
Concentration measurement of antidigoxigenin using DNA carriers.
(a) Schematic representation of digoxigenin–antidigoxigenin
system and examples of occupied digoxigenin carrier translocation
events. The digoxigenin antibody (green Y-shaped structure) is about
150 kDa. (b) Histogram of the peak current drop (red) together with
an all points histogram (blue) of all linear translocation events.
The histograms are fitted by a Gaussians function. The concentration
ratio was 10.5 (cAnti-dig/cCarrier), cAnti-dig = 15.8
nM. (c) Binding curve based on nanopore measurements. A DNA carrier
concentration of 1.5 nM was incubated with monovalent protein from
0 nM to 31 nM. Error bars are standard errors of the mean (not included
for data points with two nanopores at the concentration ratio of 10.5
and 20.9). The plot represents data are from n =
25 nanopores. The event numbers in the plots are 94, 141, 159, 145,
111, 93, and 32 for data points at the concentration ratio from 0
to 21 respectively (statistics in Supporting Information S7).The dissociation constant for
antidigoxigenin is in the range of nM at physiological salt concentrations.[16] Here, we measured the dissociation constant
of the monoclonal antidigoxigenin by fluorescence polarization. A Kd of ∼3.5 nM was estimated in buffers
with and without 4 M LiCl which is used in the nanopore experiments
(see Supplementary Figure S4). Details
of the fitting model are described in Supporting Information S4.As shown in Figure c, the upper limit of the occupied carrier
fraction is ∼0.95 which is considerably higher than that of
the biotin–streptavidin system (∼0.8). This clear improvement
is due to the higher signal-to-noise ratio of this larger antibody
system and confirms our assertion that some streptavidin–biotin
carrier translocations have a current value for the streptavidin level
which is not high enough above the noise for detection. The small
remaining fraction which does not show a positive signal for antidigoxigenin
is due to a small fraction of imperfect DNA carriers whereby not all
contain the digoxigenin labeled oligonucleotide.It has to be
noted that influencing factors mentioned previously with the biotin
system also apply here. Protein concentration variations among different
dilutions can occur due to losses caused by nonspecific surface binding.
Also, in particular for antibodies, our specific protein detection
method is sensitive for the active antibodies in the sample which
can therefore be different from the concentrations determined spectrophotometrically.In order to highlight the fact that we can assess active antibody
concentrations, we decided to compare binding curves of three antidigoxigenin
protein samples (A, B, and C) from different suppliers. All of the
nanopore measurements were done with the same protocol described previously.
As shown in Figure a, the three binding curves reveal clear differences: the saturation
point of sample A is at the concentration ratio of ∼4, while
the occupied fraction saturated at the ratio of ∼2 for sample
B and C. If the dissociation constant is assumed to be the same for
all samples, the active protein concentration can be determined. Figure b shows the increase
in the zoomed in range before the saturated concentration ratio. Accordingly,
sample B and C contain approximately twice more active antibodies
which is consistent with the EMSA results in Figure c. EMSA gel images are in the Supporting Information, Figure S3.
Figure 4
Comparison
of active Anti-dig concentrations
using three antibody samples (A, B, and C). (a) Binding curves obtained
from three antidigoxigenin samples. The curve of sample A is the same
as in Figure c. The
event numbers considered for sample B are 179, 218, 60, 116, 341,
and 507 for data points at the concentration ratio from 0.25 to 8,
respectively. The event numbers considered for sample C are 182, 253,
279, 683, 269, and 301 for data points at the same concentration ratio
from 0.25 to 8, respectively (statistics in Supporting Information S8). (b) Zoomed-in concentration dependence of
the occupied carrier fraction below the saturation point. Dashed lines
are added as a guide to the eye. (c) Concentration dependence of the
binding fraction obtained from EMSA.
Comparison
of active Anti-dig concentrations
using three antibody samples (A, B, and C). (a) Binding curves obtained
from three antidigoxigenin samples. The curve of sample A is the same
as in Figure c. The
event numbers considered for sample B are 179, 218, 60, 116, 341,
and 507 for data points at the concentration ratio from 0.25 to 8,
respectively. The event numbers considered for sample C are 182, 253,
279, 683, 269, and 301 for data points at the same concentration ratio
from 0.25 to 8, respectively (statistics in Supporting Information S8). (b) Zoomed-in concentration dependence of
the occupied carrier fraction below the saturation point. Dashed lines
are added as a guide to the eye. (c) Concentration dependence of the
binding fraction obtained from EMSA.The dynamic range for the high affinity binding protein systems
tested here is approximately 1 order of magnitude. This lower limit
is determined by the 5–10% of translocations that have false
positive protein signal and the upper limit is the level at which
the DNA is saturated with protein. The particular window of protein
concentration tested can then be adjusted by changing the DNA carrier
concentration (which we kept at 1.5 nM in these experiments). Since
the translocation frequency of our DNA carriers is independent of
the incubated protein concentration (Figure S6), higher concentrations could be used to achieve better statistics.
To extend the dynamic range, a reduction in false positives by using
shorter DNA lengths which show less folding is promising[17] or by strategies to increase the bending rigidity
of the DNA and therefore decrease the frequency of folds. Protein
systems with lower binding affinities could also be investigated by
employing chemical cross-linking strategies. All the latter techniques
should greatly enhance the application range to other relevant protein
systems. It is also important to note here that the single molecule
nanopore approach lends itself to the possibility of multiplexed sensing
which allows us to measure multiple proteins with a single nanopore.[18]In this work, we have shown that a combination
of solid-state nanopores and designed DNA carriers can be used as
a method for measuring nanomolar level of protein concentration. Several
other studies of the translocation of DNA–protein complexes
through solid-state nanopores have been used to qualitatively assess
the presence of binding between DNA and proteins including the DNA-repair
protein RecA,[19] DNA antibodies[20] and transcription factors.[21] Other interesting work with similar ideas has been used
to detect PNA and DNA targets where efforts have been made toward
quantification.[22] The results here show
that quantitative estimates of protein concentration can be made using
our DNA carrier analysis system by measuring the concentration dependence
of the occupied carrier fraction. The working protein concentrations
are at nanomolar range, and we use microfluidic chips with ∼10
μL volume so the total amount of protein needed is only 10 fmol.
The technique gives selectivity via protein binding sites and can
be used for proteins in their native conformations without the requirement
for any chemical modifications.
Authors: Wenhong Li; Nicholas A W Bell; Silvia Hernández-Ainsa; Vivek V Thacker; Alana M Thackray; Raymond Bujdoso; Ulrich F Keyser Journal: ACS Nano Date: 2013-04-22 Impact factor: 15.881
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