Affinity reagent pairs that recognize distinct epitopes on a target protein can greatly improve the sensitivity and specificity of molecular detection. Importantly, such pairs can be conjugated to generate reagents that achieve two-site "bidentate" target recognition, with affinities greatly exceeding either monovalent component. DNA aptamers are especially well-suited for such constructs, because they can be linked via standard synthesis techniques without requiring chemical conjugation. Unfortunately, aptamer pairs are difficult to generate, primarily because conventional selection methods preferentially yield aptamers that recognize a dominant "hot spot" epitope. Our array-based discovery platform for multivalent aptamers (AD-MAP) overcomes this problem to achieve efficient discovery of aptamer pairs. We use microfluidic selection and high-throughput sequencing to obtain an enriched pool of aptamer sequences. Next, we synthesize a custom array based on these sequences, and perform parallel affinity measurements to identify the highest-affinity aptamer for the target protein. We use this aptamer to form complexes that block the primary binding site on the target, and then screen the same array with these complexes to identify aptamers that bind secondary epitopes. We used AD-MAP to discover DNA aptamer pairs that bind distinct sites on human angiopoietin-2 with high affinities, even in undiluted serum. To the best of our knowledge, this is the first work to discover new aptamer pairs using arrays. We subsequently conjugated these aptamers with a flexible linker to construct ultra-high-affinity bidentate reagents, with equilibrium dissociation constants as low as 97 pM: >200-fold better than either component aptamer. Functional studies confirm that both aptamers critically contribute to this ultrahigh affinity, highlighting the promise of such reagents for research and clinical use.
Affinity reagent pairs that recognize distinct epitopes on a target protein can greatly improve the sensitivity and specificity of molecular detection. Importantly, such pairs can be conjugated to generate reagents that achieve two-site "bidentate" target recognition, with affinities greatly exceeding either monovalent component. DNA aptamers are especially well-suited for such constructs, because they can be linked via standard synthesis techniques without requiring chemical conjugation. Unfortunately, aptamer pairs are difficult to generate, primarily because conventional selection methods preferentially yield aptamers that recognize a dominant "hot spot" epitope. Our array-based discovery platform for multivalent aptamers (AD-MAP) overcomes this problem to achieve efficient discovery of aptamer pairs. We use microfluidic selection and high-throughput sequencing to obtain an enriched pool of aptamer sequences. Next, we synthesize a custom array based on these sequences, and perform parallel affinity measurements to identify the highest-affinity aptamer for the target protein. We use this aptamer to form complexes that block the primary binding site on the target, and then screen the same array with these complexes to identify aptamers that bind secondary epitopes. We used AD-MAP to discover DNA aptamer pairs that bind distinct sites on humanangiopoietin-2 with high affinities, even in undiluted serum. To the best of our knowledge, this is the first work to discover new aptamer pairs using arrays. We subsequently conjugated these aptamers with a flexible linker to construct ultra-high-affinity bidentate reagents, with equilibrium dissociation constants as low as 97 pM: >200-fold better than either component aptamer. Functional studies confirm that both aptamers critically contribute to this ultrahigh affinity, highlighting the promise of such reagents for research and clinical use.
Molecular
recognition mechanisms
based on multivalent receptor–ligand interactions can offer
dramatically higher affinity and specificity in comparison to monovalent
binding. Accordingly, many biological systems in nature have evolved
to exploit multivalent interactions to their advantage. For example,
multivalent lectin–carbohydrate interactions generate strong
adhesive forces at the cell surface for the attachment of micro-organisms,[1] and many important cell-signaling pathways exploit
multivalent binding to achieve high specificity for the regulation
of critical functions.[2] Multivalent interactions
in which two different affinity reagents recognize two distinct sites
on a target molecule have also been extensively used to improve the
accuracy of in vitro diagnostics. For example, the enzyme-linked immunosorbent
assay (ELISA),[3] the most widely used protein
detection assay, utilizes antibody pairs in a sandwich format to dramatically
increase its specificity. ELISA can effectively minimize false positive
results because the detection signal is generated only when both antibodies
independently bind to distinct epitopes on the same target protein.[4,5]Importantly, these pairs can also be physically linked to
create
a single reagent that binds its target molecule via two-site, “bidentate”
recognition. The binding affinities of these bidentate reagents can
be dramatically higher than those of the individual components, as
described by the Winter group and others.[6] Nucleic acid aptamers are especially well-suited for the synthesis
of these useful molecular constructs, because aptamers can readily
be combined via standard DNA synthesis techniques without the need
for additional chemical conjugation processes. Previously, this approach
has been utilized to combine identical aptamers that bind in a multivalent
fashion to a homodimeric target[7] as well
as bidentate aptamer pairs that each recognize distinct sites on a
single protein.[7,8] For example, Lao et al. demonstrated
that that they could improve the sensitivity of an array based thrombin
sensor by several orders of magnitude by synthesizing bivalent array
features that display two distinct thrombin aptamers.[9]Unfortunately, the discovery of aptamer pairs that
can recognize
distinct epitopes on a common target has proven to be exceptionally
challenging. This is primarily because conventional aptamer discovery
methods (i.e., SELEX)[10,11] have a strong tendency to only
yield aptamers that preferentially bind to the primary, dominant epitope
at the expense of other aptamers that bind to secondary, nondominant
epitopes.[12] Furthermore, the identification
of aptamer pairs remains a low-throughput process because binding
measurements must be performed serially for every combination of potential
binding pairs. As a result, aptamer pairs are currently available
only for a handful of proteins including thrombin,[13,14] prion protein (PrP),[15,16] TATA-binding protein[17] and integrin αVβ3.[18] Thus, there is an urgent need for more efficient technologies
for aptamer pair discovery.To address this important need,
here we report a systematic screening
method that utilizes aptamer arrays to efficiently identify aptamer
pairs in a parallel and scalable manner. Our method, which we have
termed the array-based discovery platform for multivalent aptamers
(AD-MAP), starts with microfluidic SELEX[19] followed by high-throughput sequencing (HTS)[20,21] in order to identify a high-quality pool of aptamers that bind to
the target protein of interest (Figure 1A).
Using the sequence information from HTS, we fabricate a custom aptamer
array and identify the aptamer with the highest-affinity on the array.
Then, we form an aptamer–protein complex wherein the primary
binding site on the target protein is blocked by this highest-affinity
aptamer. Finally, we use this aptamer–protein complex to perform
systematic and parallel screening of the array in order to identify
aptamers that recognize secondary binding sites on the protein. As
a proof of concept, we have used AD-MAP to discover novel DNA aptamer
pairs that bind to human angiopoeitin-2 (Ang2), an important protein
mediator of angiogenesis for colon, prostate and breast cancers.[22,23] To the best of our knowledge, this is the first work to discover
aptamer pairs using arrays. We show that these aptamers are capable
of binding to Ang2 in complex samples such as undiluted serum. Finally,
we demonstrate that these aptamer pairs can be linked together to
create ultra-high-affinity bidentate reagents with equilibrium dissociation
constants (Kd) as low as 97 pM, a >200-fold
improvement over the individual component aptamers. Thus, we show
that AD-MAP could effectively facilitate the development of high-sensitivity,
aptamer-based molecular detection assays for clinical and basic research
applications.
Figure 1
(A) Overview of the AD-MAP process. (Step 1) We obtain a pool of
aptamer candidates with microfluidic selection and identify enriched
candidate sequences via high-throughput sequencing. (Step 2) The sequences
with the highest copy number are in situ synthesized on a custom aptamer
array, which is used to measure the affinity of every candidate in
parallel and identify the highest-affinity aptamer. (Step 3) We identify
potential bidentate pairs by screening for array features that can
bind the target simultaneously with this highest-affinity aptamer,
as described in panel B. (B) We obtained the baseline fluorescence
intensity (F0, left) for each aptamer
feature by challenging our aptamer array with fluorescently labeled
Ang2. In parallel, we obtained the fluorescence intensity (F, right) from a second, identical aptamer array challenged
with fluorescently labeled Ang2–ABA1 complexes. We then determined
the relative difference in fluorescence intensity (ΔF = F – F0) for each aptamer candidate; candidates that recognize the same
site as ABA1 (red) will be outcompeted by this highest-affinity aptamer
and yield a negative ΔF, whereas candidates
recognizing distinct sites (green) will bind the ABA1–Ang2
complex and are thus predicted to yield a non-negative ΔF.
Materials and Methods
Microfluidic SELEX Targeting
Human Angiopoietin-2 (Ang2)
We immobilized Ang2 (R&D
Systems) on the surface of micrometer-sized
magnetic beads. First, M-270 carboxylic acid Dynabeads (Life Technologies)
were activated with ethyl(dimethylaminopropyl) carbodiimide (EDC)
and N-hydroxysuccinimide (NHS), and target protein
was immobilized after activation following the manufacturer’s
procedure. Immobilized Ang2 proteins were quantified using the NanoOrange
protein quantification kit (Life Technologies).Each member
of the single-stranded DNA (ssDNA) random library included 40 randomized
nucleotides flanked by two 20 nt primer binding sequences for PCR
(5′-AGCAGCACAGA GGTCAGATG-[40N]-CCTATGCGTGCTACCGTGAA-3′).
The library was synthesized by Integrated DNA Technologies (IDT).
Ang2-coated magnetic beads were washed with Ang2 binding buffer (20
mM HEPES, 150 mM NaCl, 1 mM MgCl2, 1 mM CaCl2, pH 7.4) before each selection. A total of 2 × 107 protein-coated beads were used in the first round (R1), 4 ×
106 beads for the second round (R2), and 1 × 106 beads for the third (R3) and fourth rounds (R4). The ssDNA
library (∼1014 molecules) was denatured by heating
at 95 °C for 10 min, and cooled down to room temperature. This
ssDNA library was incubated with magnetic beads in Ang2 binding buffer
for 1 h at room temperature. After incubation, we diluted the complex
solution into large volumes of Ang2 wash buffer (20 mM HEPES, 150
mM NaCl, 1 mM MgCl2, 1 mM CaCl2, 0.001% Tween-20,
pH 7.4) with a dilution factor of 40 (R1:1 mL), 200 (R2:10 mL) or
400 (R3 and R4:20 mL). The beads were trapped in a magnetic particle
concentrator (Invitrogen) for R1 and MMS chip for R2–R4. For
R2–R4, diluted samples were loaded onto the chip at a flow-rate
of 100 mL/h to continuously separate protein-bound aptamers from unbound
and weakly bound DNAs. Aptamer-bound beads were collected and the
bound aptamers were amplified by PCR using forward and phosphorylated
reverse primers. ssDNA was generated for the next round of selection
by lambda exonuclease (New England Biolabs) digestion.
High-Throughput
Sequencing and Data Analysis
To prepare
initial DNA samples for sequencing, we collected 400 μL of eluted
ssDNA pools after each washing step for amplification via PCR at an
optimized cycle number determined by pilot PCR. We used unmodified
forward and reverse primers for PCR and purified the resulting product
via a MinElute PCR Purification Kit (Qiagen). We used Illumina’s
single-read Chip-Seq DNA Sample Prep Kit to prepare double-stranded
aptamers for sequencing on the Genome Analyzer IIx. We initially used
62 ng of sample, which we then subjected to end repair, addition of
adenosine to the 3′ end, adapter ligation, size selection by
gel extraction and PCR. After each step, samples were cleaned with
DNA Clean & Concentrator columns (Zymo Research). For the adaptor
ligation step, the adaptor mix was diluted 1:20 to avoid sequencing
an abundance of adaptors. Following adapter ligation, a specific size
range of molecules was isolated for proper cluster formation on the
cluster station. We ran a 2% agarose gel, excised 100–200 base
pair fragments from the gel, and cleaned these using the Gel Purification
Mini kit from Qiagen. We followed the spin column protocol supplied
by the kit manufacturer. After size selection, we amplified the selected
fragments using Illumina-supplied PCR primers. Forward and reverse
primers were diluted 1:2 before being added to the sample. We conducted
ten cycles of PCR using Illumina’s recommended PCR recipe.
After PCR, the sample was quantitated with the Invitrogen Qubit fluorometer.We loaded the prepared DNA samples at a concentration of 8 pM and
hybridized them to an Illumina flowcell via the Illumina cluster station.
The cluster station performed bridge amplification to amplify single
DNA molecules 35 times into clusters. Each cluster was then linearized,
blocked, and the sequencing primer was hybridized. The flowcell was
then loaded onto the Genome Analyzer IIx and run with the Single Read
75 Base Pair Recipe. Individual nucleotides of each cluster were sequenced
base by base. Illumina Sequencing Control Software produced image
intensities and quality-scored base calls in real-time. After sequencing
was complete, Illumina Casava software processed the data for quality
analysis.
Fluorescence Labeling on Ang2
Ang2 was labeled with
Alexa Fluor 647 dye (Invitrogen) according to manufacturer’s
protocol. Briefly, 1 mg/mL of Ang2 (100 mM NaHCO3, pH 8.3)
was incubated with 3 μL of Alexa Fluor 647 succinimidyl ester
(7.94 nmol/μL) for 1 h at room temperature. To separate the
labeled protein from unreacted dye, a spin column was filled with
750 μL of supplied purification resin and centrifuged at 15000
rpm for 15 s. After washing the column three times with PBSM buffer
(10.1 mM Na2HPO4, 1.8 mM KH2PO4, 137 mM NaCl, 2.7 mM KCl and 1 mM MgCl2, pH 7.4),
we loaded the conjugate reaction mixture onto the center of the resin.
After centrifuging at 15000 rpm for 1 min, we collected the purified
dye-labeled protein. The eluted conjugates were analyzed using a ND-2000
spectrophotometer (NanoDrop Technologies). We obtained ∼95%
yield for the conjugate with a degree of labeling (DOL) of 9.35. The
labeled protein was stored at 4 °C, protected from light.
Aptamer
Array Design and Analysis
We designed and ordered
custom DNA microarrays through Agilent, where each slide consisted
of eight identical subarrays of 15 000 individual features.
The array design was based on aptamer sequences identified from high-throughput
sequencing. Each aptamer sequence on the array was synthesized with
a 3′ poly T20 linker. The 150 most highly represented sequences
from R4 were incorporated into the array design, with each sequence
synthesized in triplicate. The array also featured library, R1–R3
pool sequences and R4 aptamer sequences with different linkers. We
also synthesized negative control sequences including primer repeats
and linkers only, and aptamer sequences against human α thrombin
and PDGF-BB (see Table S1 (Supporting Information) for details).
Identification of the Aptamer with the Highest
Binding Affinity
To measure Kd, we incubated each array
with 5, 10, 25, 50, 75, 100, 150 or 200 nM Alexa Fluor 647-labeled
Ang2. After washing with washing buffer (10 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, 137 mM
NaCl, 1 mM MgCl2, pH 7.4) with decreasing amounts of Tween-20
(0.1%, 0.01% and 0.001%), slides were disassembled in nanopure H2O and then dried via centrifugation (1500 rpm for 2 min using
a swing bucket rotor). We used an array scanner to measure the fluorescence
intensity (excitation = 649 nm, emission = 666 nm) from every feature.
We averaged the triplicate signals from each aptamer candidate, and
used these data to calculate Kd values.
We assumed a Langmuirian binding isotherm and used the equation Y = Bmax × X/(Kd + X), where Y is the net fluorescence intensity at each concentration, X is the concentration of fluorescently labeled Ang2 and Bmax is the net fluorescence intensity at saturation.
We discarded sequences whose Bmax was
less than double the background. We then sorted aptamer sequences
with Kd values, and finally identified
the aptamer with the lowest Kd value.
Aptamer Pair Screening
Slides were assembled with 8-well
gaskets in an Agilent hybridization chamber for blocking and sample
incubation. Each gasket was filled with 40 μL of blocking or
sample solution. The microarray surface was initially blocked for
1 h at room temperature with blocking buffer (10 mg/mL casein, 0.1%
Tween-20, 8.1 mM Na2HPO4, 1.1 mM KH2PO4, 2.7 mM KCl, 137 mM NaCl, 1 mM MgCl2, 138
mM NaCl, pH 7.4). Slides were disassembled in nanopure H2O and then dried by centrifuging (1500 rpm for 2 min using a swing
bucket rotor). Prior to screening, we preincubated 50 nM of Alexa
Fluor 647-labeled Ang2 with 10 μM of ABA1 aptamer for 1 h at
room temperature. We incubated one “reference” array
with Alexa Fluor 647-labeled Ang2 and another identical array with
the Ang2–ABA1 complex solution and incubated for 1 h at room
temperature. After sample incubation, the slides were disassembled
in PBSM buffer with 0.1% Tween-20 and rinsed three times in washing
buffer with decreasing amounts of Tween-20 (0.1%, 0.01% and 0.001%).
Then, the slides were dipped in nanopure H2O to remove
any remaining salt and dried by centrifugation (1500 rpm for 2 min
using a swing bucket rotor). Slides were scanned using Bio-Rad VersArray
ChipReader at a 3 μm resolution, and image data were extracted
using Bio-Rad VersArray Analyzer software.
Binding Affinity Measurements
Using a Magnetic Bead-based Fluorescence
Assay
We tested the binding affinity of individual aptamers
and bidentate aptamer constructs for Ang2 using a fluorescence binding
assay. FAM-modified aptamer constructs were synthesized by Biosearch
Technologies with high-performance liquid chromatography (HPLC) purification.
We incubated a range of concentrations of FAM-labeled DNAs with 2
× 106 Ang2-coated magnetic beads for 1 h at room temperature
with gentle rotation. To remove unbound DNA, each sample was then
washed three times in Ang2 binding buffer using a magnetic particle
concentrator. Bound DNAs were eluted from the beads by heating at
95 °C for 10 min. Released DNAs were quantified by fluorescence
measurement using a Tecan microplate reader (excitation = 490 nm,
emission = 520 nm). We calculated Kd by
nonlinear fitting analysis.
Enzyme-Linked Oligonucleotide Assay (ELONA)
Individual
aptamers were biotinylated at the 5′ end and purified using
HPLC. Streptavidin-coated microtiter plate wells were coated with
biotinylated capture aptamers by adding 50 μL of DNA solution
in PBS (20 μg/mL of Ang2 aptamers) and incubating at 4 °C
overnight. After incubation, we washed the plate two times with 150
μL of PBS buffer with 0.1% Tween-20 (PBST buffer) and then blocked
each well with 100 μL PBST plus 1% BSA for 1 h as described
in ref (18). We then
washed the plate with 150 μL of PBST three times, and incubated
with 50 μL of protein solution in PBST (10 μg/mL of Ang2)
for 1h. After washing three times with 150 μL of PBST, we added
50 μL of biotinylated detection aptamer (1 μg/mL of Ang2
aptamers) dissolved in PBST and incubated for 1 h.For binding
experiments in undiluted serum, after coating microtiter plate wells
with biotinylated capture aptamers as described above, we added undiluted
fetal bovine serum (FBS) containing various concentrations (0–200
nM) of Ang2. After washing, we added 50 μL of biotinylated detection
aptamer (1 μg/mL of Ang2 aptamers) in PBST and incubated for
1 h.For Kd measurements, microtiter
plate
wells were coated with Ang2 by adding 50 μL of protein solution
in PBS (100 nM of Ang2) and incubating at 4 °C overnight. After
washing the plate twice with 150 μL of PBST, we blocked each
well with 100 μL of 1% BSA in PBST for 1 h. We then washed the
plate with 150 μL of PBST three times, and incubated with 50
μL of biotinylated bidentate aptamers in PBST at various concentrations
(0, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 4 and 8 nM) for 1 h.Next,
we washed the plate three times with 150 μL of PBST
and added streptavidin-conjugated horseradish peroxidase (HRP) dissolved
in 100 μL of PBST at 1:500 dilution. After 30 min of incubation,
we washed the plate four times and added the 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate)
(ABTS) substrate. This substrate becomes oxidized by HRP to produce
a blue-green color, which we measured with a Tecan microplate reader
at 405 nm.
Results and Discussion
Discovery of Aptamer Pairs
via AD-MAP
As shown in Figure 1A,
AD-MAP involves three main process steps. First,
we perform microfluidic selection against a target protein of interest
and characterize the selected pool via HTS. We then synthesize an
array consisting of the most highly enriched sequences from the HTS
data and identify the highest-affinity aptamer within the array. Finally,
we form an aptamer–protein complex to block the primary binding
site on the target protein with the highest-affinity aptamer found
in step 2, and then screen the remainder of the array to identify
aptamers that can recognize secondary epitopes and thus form a binding
pair. As a proof of concept, we performed this screening with Ang2
as the target protein, building on our previously published work in
aptamer generation from ref (24).(A) Overview of the AD-MAP process. (Step 1) We obtain a pool of
aptamer candidates with microfluidic selection and identify enriched
candidate sequences via high-throughput sequencing. (Step 2) The sequences
with the highest copy number are in situ synthesized on a custom aptamer
array, which is used to measure the affinity of every candidate in
parallel and identify the highest-affinity aptamer. (Step 3) We identify
potential bidentate pairs by screening for array features that can
bind the target simultaneously with this highest-affinity aptamer,
as described in panel B. (B) We obtained the baseline fluorescence
intensity (F0, left) for each aptamer
feature by challenging our aptamer array with fluorescently labeled
Ang2. In parallel, we obtained the fluorescence intensity (F, right) from a second, identical aptamer array challenged
with fluorescently labeled Ang2–ABA1 complexes. We then determined
the relative difference in fluorescence intensity (ΔF = F – F0) for each aptamer candidate; candidates that recognize the same
site as ABA1 (red) will be outcompeted by this highest-affinity aptamer
and yield a negative ΔF, whereas candidates
recognizing distinct sites (green) will bind the ABA1–Ang2
complex and are thus predicted to yield a non-negative ΔF.Briefly, we performed
four rounds of microfluidic selection with
Ang2, and performed HTS to obtain ∼3 × 107 candidate
aptamer sequences (see the Materials and Methods section). Microfluidic selection enables us to reproducibly control
the washing stringency during the selection.[19,25] This is important because sufficient aptamer diversity must be maintained
in the final pool in order to prevent the loss of aptamers capable
of binding to alternate sites on the target protein as a result of
“hot spot” selection bias. We then chose the 235 most
enriched sequences from the HTS data based on copy number, and synthesized
these on an Agilent custom DNA aptamer array. Each aptamer feature
on the array was synthesized with a 20 nt linker alongside various
controls (array features are described in Table S1, Supporting Information). We used a relatively small number
of sequences for this proof-of-concept experiment, but it is critical
to note that far larger aptamer arrays, with hundreds of thousands
of aptamer candidates, can be readily fabricated on a single array
using the same approach.[26] We fluorescently
labeled Ang2 and measured the relative binding affinity of all of
the aptamer candidates in parallel, which enabled us to identify the
aptamer with the highest binding affinity. This aptamer, which we
have termed Ang2-binding aptamer 1 (ABA1), exhibited a Kd of 20.5 ± 7.33 nM (Figure S1, Supporting Information).We then used ABA1 to screen
for aptamers that can form binding
pairs using the aptamer array. To do so, we first used an aptamer
array to establish baseline fluorescence intensity (F0) for each aptamer feature by challenging the array with
fluorescently labeled Ang2 (Figure 1B, left).
Next, we incubated fluorescently labeled Ang2 with an excess of ABA1
in solution to form an aptamer–protein complex. We then challenged
another aptamer array with the same design with this preformed Ang2–ABA1
complex and obtained the fluorescence intensity (F) from each aptamer candidate on the array (Figure 1B, right). Using the data from these two arrays, we determined
the relative difference in fluorescence intensity (ΔF = F – F0) for each aptamer candidate. We reasoned that if an aptamer array
feature binds to the same site on Ang2 as ABA1, then ΔF would be negative; F would be smaller
than F0 because the highest-affinity ABA1
aptamer would outcompete the candidate aptamer for that particular
epitope, resulting in decreased F for that array
feature (Figure 1B, red aptamer). On the other
hand, we anticipated that ΔF would be non-negative
if the candidate aptamer recognizes a distinct epitope and can therefore
bind the preformed ABA1–Ang2 complex (Figure 1B, green aptamer).After obtaining F and F0 for all of the aptamers on the
array, we found 17 aptamers that
exhibited a non-negative ΔF out of our 235
candidates; the remainder yielded a negative ΔF, and therefore bound to the same site as ABA1. Of these 17 candidates,
we focused our investigations on three aptamers (ABA65, ABA92 and
ABA109) that exhibited positive ΔF, with F values at least 3-fold greater than F0 (Figure 2A, all sequences are
provided in Table S2, Supporting Information). We reasoned that the positive ΔF could
be a result of positive allostery resulting in enhanced binding, as
previously reported in the literature.[27,28] We verified
the affinity of these three aptamers for Ang2 by measuring their Kd values in solution using a bead-based fluorescence
assay (see the Materials and Methods section).
The Kd values ranged from 37.6 to 57.0
nM (Figure 2B). We note that the Kd values are ∼2–3-fold higher (i.e., lower
affinity) than ABA1 as measured by the same method. This is consistent
with our initial determination that ABA1 exhibits the highest affinity
of the 235 candidates on the array. Although ABA92 and ABA109 were
highly similar in their sequences, we characterized them separately,
because even single-nucleotide differences have been shown to affect
aptamer affinity and specificity.[26]
Figure 2
Identification
of three aptamers that form binding pairs with ABA1.
(A) We used our aptamer array to identify aptamers that can bind Ang2
in complex with ABA1. Negative ΔF (green) indicates
an aptamer feature on the array that binds the same site on Ang2 as
ABA1, while non-negative ΔF (magenta) indicates
aptamer features that bind a different site on Ang2 than ABA1. (B)
We identified three candidate aptamers (ABA65, ABA92 and ABA109) that
potentially form binding pairs with ABA1, and measured their Kds using a bead-based fluorescence assay. As
expected, their affinities were moderately lower than that of ABA1.
Fluorescence intensities are the average of triplicate measurements.
Identification
of three aptamers that form binding pairs with ABA1.
(A) We used our aptamer array to identify aptamers that can bind Ang2
in complex with ABA1. Negative ΔF (green) indicates
an aptamer feature on the array that binds the same site on Ang2 as
ABA1, while non-negative ΔF (magenta) indicates
aptamer features that bind a different site on Ang2 than ABA1. (B)
We identified three candidate aptamers (ABA65, ABA92 and ABA109) that
potentially form binding pairs with ABA1, and measured their Kds using a bead-based fluorescence assay. As
expected, their affinities were moderately lower than that of ABA1.
Fluorescence intensities are the average of triplicate measurements.
Binding Performance of
Aptamer Pairs
We performed multiple
experiments to confirm that the three aptamers indeed form binding
pairs with ABA1. First, we performed enzyme-linked oligonucleotide
assays (ELONA),[18,29] wherein we immobilized ABA65,
ABA92 and ABA109 as “capture aptamers” on the surface
of microtiter plate wells (see the Materials and
Methods section). After incubating with unlabeled Ang2 and
washing, we added biotinylated ABA1 as the “detection aptamer”
along with streptavidin-conjugated horseradish peroxidase (HRP). The
overall background signal was very low, even though both capture and
detection aptamers were labeled with biotin (Figure S2, Supporting Information). To quantify binding
of the detection aptamer to Ang2, we measured absorption in each well
after treatment with the HRP substrate 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonate)
(ABTS). We observed high absorbance signals from wells coated with
each of the three capture aptamers (Figure 3A, ABA1). As controls, we performed ELONA with these three aptamers
using the same aptamer for detection as was used for capture (Figure 3A, capture aptamer); in each case, this yielded
a significantly lower binding signal, because the aptamers compete
for the same binding site. As further controls, we used scrambled
detection aptamer sequences (Figure 3A, scrambled
aptamer; see Table S2 (Supporting Information) for sequences) or no detection aptamer (Figure 3A, no aptamer), and observed minimal binding in both scenarios,
providing further evidence that these three aptamers are capable of
binding Ang2 in conjunction with ABA1.
Figure 3
Verification of aptamer
pair binding. (A) Enzyme-linked oligonucleotide
assay (ELONA) using ABA65, ABA92 or ABA109 as capture aptamers. As
the detection aptamer, we used biotinylated ABA1; for controls, we
used the same aptamer used for capture, a scrambled aptamer sequence
or no detection aptamer. The three aptamers form pairs with ABA1 as
shown by the high absorbance signals. (B) ELONA experiments show that
these three aptamer pairs can detect unlabeled Ang2 in undiluted fetal
bovine serum. In comparison, we observed only a modest signal when
we used a scrambled aptamer sequence as the capture aptamer. All error
bars were obtained from triplicate measurements.
Verification of aptamer
pair binding. (A) Enzyme-linked oligonucleotide
assay (ELONA) using ABA65, ABA92 or ABA109 as capture aptamers. As
the detection aptamer, we used biotinylated ABA1; for controls, we
used the same aptamer used for capture, a scrambled aptamer sequence
or no detection aptamer. The three aptamers form pairs with ABA1 as
shown by the high absorbance signals. (B) ELONA experiments show that
these three aptamer pairs can detect unlabeled Ang2 in undiluted fetal
bovine serum. In comparison, we observed only a modest signal when
we used a scrambled aptamer sequence as the capture aptamer. All error
bars were obtained from triplicate measurements.To investigate whether these aptamer pairs can function as
effective
reagents in complex biological samples, we subsequently performed
ELONA experiments in undiluted fetal bovine serum (FBS). We used undiluted
FBS because it is a challenging sample matrix with extremely high
protein content (60–80 mg/mL). Specifically, we coated microtiter
plate wells with each of the three capture aptamers, and then added
undiluted FBS containing various concentrations (0–200 nM)
of unlabeled Ang2. After washing, we added ABA1 as the detection aptamer
as described above. Despite the high concentration of nontarget proteins
present in the serum, all three aptamers could form pairs with ABA1
and readily detected Ang2 at concentrations as low as 20 nM (Figure 3B).
Synthesis of Bidentate Aptamer Reagent
Having demonstrated
that these aptamers form binding pairs, we subsequently physically
linked the aptamers with ABA1 to create various bidentate aptamer
reagents, in an effort to generate molecules with significantly enhanced
affinities.[6] We focused our analysis on
bidentate reagents synthesized by linking ABA1 with ABA65 through
a flexible linker, because ABA65 exhibited the highest affinity of
the three candidates (Figure 2B). We connected
the two aptamers using poly-T linkers of different lengths, because
these linkers typically do not interfere with the folding of the individual
aptamers.[7] Since we did not have a priori
knowledge about the distance between the two aptamer binding sites
on Ang2, we synthesized four different constructs including those
with linkers that could span the end-to-end distance of the protein
as well as shorter lengths (5, 10, 16 or 25T). We then measured the
binding affinities of each construct using a bead-based fluorescence
assay (Figure S3, Supporting Information). The construct consisting of ABA65 linked to ABA1 via a 25T linker
showed the greatest increase in binding affinity compared to its individual
components (Figure 4A). This ABA1–ABA65
construct exhibited a Kd of 97 pM, an
affinity ∼210-fold higher than that of ABA1 and ∼390-fold
higher than that of ABA65. As independent verification, we again employed
ELONA to assess the affinities of our bidentate aptamer reagents.
Briefly, we coated microtiter plate wells with unlabeled Ang2 and
incubated each well with a different concentration of biotinylated
ABA1–ABA65. After washing, we added streptavidin-conjugated
HRP for detection. The resulting Kd value
for ABA1–ABA65 was 62 pM, (Figure S4, Supporting
Information), which is comparable with the measurement obtained
via our fluorescence assay.
Figure 4
Bidentate aptamer reagent exhibits greatly enhanced
binding affinity
over its component aptamers. (A) Fluorescence binding assays show
that the bidentate aptamer reagent formed by linking ABA1 with ABA65
via a 25T flexible linker exhibits greatly enhanced affinity. ABA1–ABA65
showed a Kd of 97 pM, a ∼210-fold
and ∼390-fold improvement in affinity over those for ABA1 and
ABA65, respectively. (B) Fluorescence binding assays with various
controls showed that both ABA1 and ABA65 make critical contributions
to this enhanced affinity. Aptamers fused only to poly-T linkers without
their partner aptamer (ABA1–25T, 25T–ABA65) showed much
poorer affinities. Likewise, replacing either aptamer with a scrambled
sequence (SC) (ABA1–SC and SC–ABA65) yielded at least
∼100-fold reduction in affinity relative to ABA1–ABA65.
All error bars were obtained from triplicate measurements.
Bidentate aptamer reagent exhibits greatly enhanced
binding affinity
over its component aptamers. (A) Fluorescence binding assays show
that the bidentate aptamer reagent formed by linking ABA1 with ABA65
via a 25T flexible linker exhibits greatly enhanced affinity. ABA1–ABA65
showed a Kd of 97 pM, a ∼210-fold
and ∼390-fold improvement in affinity over those for ABA1 and
ABA65, respectively. (B) Fluorescence binding assays with various
controls showed that both ABA1 and ABA65 make critical contributions
to this enhanced affinity. Aptamers fused only to poly-T linkers without
their partner aptamer (ABA1–25T, 25T–ABA65) showed much
poorer affinities. Likewise, replacing either aptamer with a scrambled
sequence (SC) (ABA1–SC and SC–ABA65) yielded at least
∼100-fold reduction in affinity relative to ABA1–ABA65.
All error bars were obtained from triplicate measurements.Finally, to elucidate the mechanism behind this
enhanced affinity,
we performed a series of control experiments with modified versions
of ABA1–ABA65, and found that both aptamers make critical contributions
in binding to Ang2 (Figure 4B). First, we synthesized
truncated variants of ABA1–ABA65 consisting of each individual
aptamer joined only to the 25T linker without its partner aptamer
(all sequences shown in Table S2, Supporting Information). Both constructs showed only slight improvements in binding affinity
compared to either individual aptamer (Figure 4B). In addition, the 25T linker alone showed minimal affinity for
Ang2 (Figure S5, Supporting Information). These findings exclude the possibility that the linker interacts
with Ang2 directly, or contributes meaningfully to the observed affinity
enhancement. Next, we synthesized constructs in which either aptamer
component was substituted with a scrambled sequence (SC). SC alone
exhibited negligible binding affinity for Ang2 (Figure S5, Supporting Information). Accordingly, constructs
in which either ABA1 (ABA1–SC) or ABA65 (SC–ABA65) was
linked with a scrambled sequence showed minimal enhancement in affinity
(Figure 4B). Given that all of these controls
showed at least 100-fold poorer affinity than ABA1–ABA65, we
conclude that both aptamers play critical roles in binding to Ang2.
Conclusion
In this work, we describe AD-MAP, an array-based
method for the
systematic discovery of aptamer pairs that are capable of simultaneously
binding to two different sites on a target protein. We used AD-MAP
to discover new DNA aptamer pairs that bind to humanAng2 and demonstrated
that these reagents can bind to Ang2 even in highly complex samples
such as undiluted serum. Importantly, by linking the aptamer pairs
through a flexible linker, we were able to synthesize bidentate aptamer
reagents with exceptional affinities, with Kd values as low as 97 pM. This represents a more than 200-fold
improvement over either of the individual component aptamers. Through
a series of controls, we showed that this dramatic enhancement in
affinity is indeed the result of bidentate binding by the two component
aptamers.The key advantage of our system is that screening
for pair binding
is performed in parallel for all aptamers on the array simultaneously.
As such, the time and labor required for measurement remain relatively
constant, regardless of the number of aptamer candidates being interrogated.
Although we used a relatively small number of sequences for this pilot
experiment (235 aptamers), the same experimental strategy can be used
to screen much larger aptamer arrays. Given that custom DNA arrays
with more than 1 million features are already commercially available
at reasonable costs, we believe our AD-MAP system is highly scalable
and could even be potentially expanded to discover aptamer pairs for
multiple target proteins simultaneously.We have identified
a number of opportunities to further improve
the AD-MAP system. First, we were constrained by the maximum length
of aptamers that could be synthesized on this particular array format
(60 nucleotides) and thus we could not synthesize the full-length,
80 nucleotide aptamers identified in our selection. We therefore eliminated
the PCR primer-binding sites and synthesized only the core sequences
on the array. These primer-binding regions are known to play an important
role in aptamer folding and can thus affect affinity.[30] We therefore expect that aptamer arrays that can accommodate
longer sequences would yield aptamer pairs with even higher affinities.
Furthermore, in this proof-of-principle study, we only explored a
small set of relatively simple flexible poly(T) linkers to join the
two aptamers. By optimizing the linker design, we believe it will
be possible to obtain aptamers with even higher affinities, as shown
by the work of Ahmad et al.[31]In
conclusion, we believe that the highly parallel screening enabled
by AD-MAP holds the potential to greatly accelerate the discovery
of high-performance aptamer pairs for a wide range of target proteins.
The resulting expanded access to such reagents should in turn enable
the development of more sensitive molecular diagnostic assays and
more effective targeted drug delivery.
Authors: Barry Schweitzer; Scott Roberts; Brian Grimwade; Weiping Shao; Minjuan Wang; Qin Fu; Quiping Shu; Isabelle Laroche; Zhimin Zhou; Velizar T Tchernev; Jason Christiansen; Mark Velleca; Stephen F Kingsmore Journal: Nat Biotechnol Date: 2002-04 Impact factor: 54.908
Authors: Kaori Takemura; Ping Wang; Ina Vorberg; Witold Surewicz; Suzette A Priola; Anumantha Kanthasamy; Ravi Pottathil; Shu G Chen; Srinand Sreevatsan Journal: Exp Biol Med (Maywood) Date: 2006-02
Authors: Bharat N Gawande; John C Rohloff; Jeffrey D Carter; Ira von Carlowitz; Chi Zhang; Daniel J Schneider; Nebojsa Janjic Journal: Proc Natl Acad Sci U S A Date: 2017-03-06 Impact factor: 11.205