Electrochemical Gold(III) Sensor with High Sensitivity and Tunable

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An Electrochemical Gold(III) Sensor with High Sensitivity and Tunable Dynamic Range Yao Wu, and Rebecca Y Lai Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.5b03868 • Publication Date (Web): 18 Jan 2016 Downloaded from http://pubs.acs.org on January 27, 2016

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Analytical Chemistry

An Electrochemical Gold(III) Sensor with High Sensitivity and Tunable Dynamic Range Yao Wua and Rebecca Y. Lai*a

a

651 Hamilton Hall, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, USA. Fax: +1

402 472 9402; Tel: +1 402 472 5340; E-mail: [email protected]

*Correspondence should be addressed to Rebecca Y. Lai.

1 ACS Paragon Plus Environment


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Abstract We report the design and fabrication of a sensitive, specific, and selective electrochemical ion (E-ION) sensor for detection of Au(III). The signaling mechanism is based on the interactions between Au(III) and adenine; formation of these complexes rigidifies the methylene blue (MB)modified oligoadenine probes, resulting in a concentration-dependent reduction in the MB signal. The dynamic range of the sensor can be tuned by simply changing the length of the DNA probe (six (A6) or twelve (A12) adenines). Independent of the probe length, both sensors have demonstrated to be sensitive, with a limit of detection of 50 nM and 20 nM for the A6 and A12 sensors, respectively. With further optimization, this sensing strategy may offer a promising approach for analyzing Au(III).


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Introduction Throughout human history, metallic gold (Au) has been admired for its corrosion resistance and aesthetic qualities; however, only in the past few decades that other properties of Au have been explored. Au can exist in various oxidation states, with 1+ and 3+ being the most common oxidation states. Various Au compounds have been used to treat diseases such as tuberculosis1 and rheumatoid arthritis.2 More recently, Au(III) compounds have been found capable of interacting with biologically important ligands, including DNA,3 amino acids,4 peptides,5 and proteins,6 in a similar manner to cisplatin by forming square-planar complexes.7 Several Au(III) complexes are now considered as potential anticancer agents. Owing to the diverse applications that require Au, global demand for Au is not going to subside. Geochemical exploration for Au is becoming increasingly important to the mining industry. There is a need for developing sensitive, selective, and cost-effective analytical methods capable of identifying and quantifying Au in complex biological and environmental samples. Laboratory analysis of Au is often accomplished using analytical techniques such as flame atomic absorption spectroscopy (FAAS),8-10 atomic emission spectroscopy,11 and inductively coupled plasma quadrupole mass spectrometry.12 Electrochemical methods like anodic stripping voltammetry have also been employed for detection of Au(III).13,14 Several fluorescence-based Au(III)/Au(I) sensors have been developed to date; while suitable for in vivo applications, most of them require the use of custom synthesized fluorescent probes.15-20 Detection strategies involving nanomaterials have also been reported in recent years. Kumeria et al. developed an interferometric Au(III) sensor using nanoporous anodic alumina.21 Yang et al. reported the first gold nanoparticles-based colorimetric sensing system for rapid and label-free detection of Au(III) via oxidation of L-cysteine to cysteine.22 This sensor is very sensitive, with a limit of detection



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(LOD) of 50 nM. A whole cell biosensor that utilizes transgenic E. Coli has found application in Au(III)/Au(I) analysis, despite the more complex experimental procedure, it has demonstrated to be highly sensitive, with a LOD of 10 nM.23 Electrochemical techniques are promising analytical tools for metal ions analysis, however, more emphasis has been placed on detecting heavy metal contaminants such as Hg(II), Pb(II), and Cd(II).24-26 The folding- and dynamics-based electrochemical sensing platform is one of the more promising detection approaches; these sensors are sensitive, specific, and selective, in addition to being reagentless and reusable.27,28 Many of these sensors exploit known interactions between metal ions and specific DNA bases. The most well-characterized interaction is between Hg(II) and thymine. In addition to Hg(II), DNA is capable of binding to different cationic metal ions, the specificity is thus dependent on the DNA sequence and the experimental condition.29,30 Adenine and its derivatives are versatile ligands known to coordinate with transition metal ions such as Au(III), Ag(I), and Cu(II) through the participation of ring nitrogen atoms.31-35 Although these interactions have been well-studied, they have not been exploited for use in electrochemical metal ion sensing. Here we report for the first time the use of oligoadenines as the recognition probe for electrochemical detection of Au(III). The design and signaling mechanism of the two E-ION Au(III) sensors are shown in Scheme 1. DNA probes with 6 (A6) and 12 (A12) consecutive adenines were used in this study. As designed, in the absence of Au(III), the probes are quite flexible; electron transfer between the tethered MB and the electrode is eﬃcient. In the presence of Au(III), complex formation between Au(III) and the adenine bases rigidifies the probes, restricting the access of MB to the electrode. This change in probe rigidity results in a measurable decrease in the MB signal. Previous reports have shown that the ring nitrogen atoms


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of adenine can coordinate with Au(III), and given that there are three ring nitrogen sites in adenine, there are many possible Au(III)-adenine complexes that could co-exist on the sensor surface.36,37 One of the possible complexes is the adenine-Au(III)-adenine complex which bears resemblance to the thymine-Hg(II)-thymine complex, the binding motif of the E-ION Hg(II) sensor.27 Although this simple adenine-Au(III)-adenine binding motif is shown in Scheme 1, we do not preclude the existence of other complexes that could produce a similar sensor response (i.e., reduction in MB current), these aspects are currently under investigation in the laboratory.

Scheme 1. Signaling mechanism of the A6 (A) and A12 (B) E-ION Au(III) sensors. Target binding rigidifies the oligoadenine probes, resulting in a measurable decrease in the MB current.

Materials & Methods Materials and Reagents 6-mercapto-1-hexanol (C6-OH), ethylenediaminetetraacetic acid (EDTA), L-cysteine, tris-(2carboxyethyl) phosphine hydrochloride (TCEP), hydrochloric acid, sulfuric acid (H2SO4), chromium nitrate (Cr(NO3)3), sodium chloride (NaCl), potassium chloride (KCl), silver nitrate



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(AgNO3), gold (III) chloride trihydrate (HAuCl4·3H2O), zinc chloride (ZnCl2), nickel chloride (NiCl2), aluminum chloride (AlCl3), arsenic trioxide, cobalt acetate (Co(CH3COO)2), manganese acetate (Mn(CH3COO)2), iron chloride (FeCl3), calcium sulfate (CaSO4), magnesium sulfate (MgSO4), potassium sulfate (K2SO4), sodium bicarbonate (NaHCO3), sodium fluoride (NaF), sodium sulfate (Na2SO4), sodium bromide (NaBr) were used as received (Sigma-Aldrich, St. Louis, MO). FLUKA TraceCERT standards for lead (Pb(II)), cadmium (Cd(II)), and mercury (Hg(II)) purchased from Sigma-Aldrich (St. Louis, MO) were used without further purification. All other chemicals were of analytical grade. All of the solutions were made with deionized (DI) water purified through a Synergy Ultrapure Water System (18.2 MΩ•cm, Millipore, Billerica, MA). Electrochemical experiments were performed in a 10 mM phosphate buffer saline supplemented with 2 M NaClO4 at pH 6.7 (PBS-6.7) and PBS-6.7 with added ions found in the South Dakota Minnelusa aquifer (127 mg L-1 calcium, 32 mg L-1 magnesium, 521 mg L-1 sodium, 3 mg L-1 potassium, 252 mg L-1 bicarbonate, 257 mg L-1 sulfate, 12 mg L-1 chloride, 0.5 mg L-1fluoride, 0.3 mg L-1 bromide, and 0.01 mg L-1 iodide). Experiments were also performed in PBS-6.7 with 50 µM EDTA and metal ions found in surface water of the Linglong gold mining area in China (69.63 µg L-1 Pb(II), 60.93 µg L-1 Hg(II), 1011.33 µg L-1 Zn(II), 1641.98 µg L-1 Cu(II), 11.33 µg L-1 Cr(III), 14.55 µg L-1 As(III), and 30.01 µg L-1 Cd(II)). Two DNA probes purchased from Biosearch Technologies, Inc. (Novato, CA) were used as received. The DNA probes were modified at the 5’ terminus with a 6-carbon alkanethiol linker and at the 3’ end with a MB redox label (Figure. S1). DNA Probes: A6: 5’- HS-(CH2)6-AAAAAA T-MB-3’ A12: 5’- HS-(CH2)6-AAAAAAAAAAAA T-MB-3’


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Sensor Fabrication Prior to sensor fabrication, gold disk electrodes with a geometric area of 0.0314 cm2 (CH Instruments, Austin, TX) were polished with 0.1 µm diamond slurry (Buehler, Lake Bluff, IL), rinsed with DI water, and sonicated in a low-power sonicator for ~5 min to remove bound particulates. They were then electrochemically cleaned by a series of oxidation and reduction cycles in 0.5 M H2SO4. The real surface area of each electrode was estimated on the basis of the amount of charge consumed during the reduction of the gold surface oxide in 0.05 M H2SO4 using a reported value of 400 µC cm-2. The roughness factor (real area/geometric area) of the electrodes used in this study ranged from 1.0-1.5. Fabrication of the sensors involved several steps. First, 1 µL of the 200 µM DNA probe solution was mixed with 1 µL of 10 mM TCEP; this solution was left at room temperature (~22 o

C) for 1 hr to reduce the disulfide bonds. Next, the solution was diluted with 5 mM PBS

supplemented with 0.05 M NaCl (pH 7.4). The diluted solution of the two DNA probes (0.035 µM A6 and A12) was drop casted onto freshly cleaned gold electrodes for 1 hr at ~4 oC (in the fridge). The probe-modified electrodes were then rinsed with water and subsequently passivated with a 2 mM C6-OH solution made with 10 mM PBS supplemented with 1 M NaClO4 overnight at ~4 oC to displace nonspecifically bound DNA probes. The density of electroactive DNA probes on the electrode surface, Γ, was determined by integrating the charge under the MB reduction peak in the cyclic voltammograms (CV) collected at slow scan rates (Equation 1). Γ = Q/nFA

(1)

where Q is the integrated charge of the reduction peak in the CVs, n is the number of electrons transferred per redox event (n = 2 for MB), F is the Faraday’s constant, and A is the real



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electrode area. Γ for each of the two sensors is presented as an average value obtained from CVs recorded at three different scan rates (10, 20 and 50 mV s-1). Sensor Characterization and Target Interrogation Electrochemical measurements were performed at room temperature using a CHI 1040A Electrochemical Workstation (CH Instruments, Austin, TX). Four electrochemical techniques, including alternating current voltammetry (ACV), CV, square wave voltammetry (SWV) and differential pulse voltammetry (DPV) were used in sensor interrogation. ACVs were collected over a wide range of frequencies (1 - 1000 Hz) with an amplitude of 25 mV. CVs were recorded using scan rates between 0.01 and 1000 V s-1. SWVs were collected using an amplitude of 25 mV from 1 to 500 Hz. DPVs were recorded over a wide range of pulse widths (1 -100 ms) while maintaining an amplitude of 50 mV. DNA probe-modified gold disk electrodes were used as working electrodes. A platinum wire was used as the counter electrode and a Ag/AgCl (3 M KCl) electrode served as the reference electrode (CH Instruments, Austin, TX). After sensor fabrication, the electrodes were placed in a 10% SDS solution for 4 min, followed by a DI water rinse. The sensors were allowed to equilibrate in PBS-6.7 for at least 20 min prior to the addition of the target. The target was added after no change in the MB peak current was observed in ACV. After the addition of 1 µM Au(III), ACVs were collected every 5 min until signal saturation had been achieved (i.e., stable MB peak current). The concentration of Au(III) was 1 µM for all experiments other than the calibration experiments. The concentrations used in the calibration experiments for the A6 sensor were 50, 100, 200, 400, 600, 800, 1000, 1500, and 2000 nM. For the A12 sensor, the concentrations were 20, 50, 100, 200, 400, 600, 800, and 1000 nM.


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For data obtained in ACV and CV, the ratio between the MB peak current in the absence and presence of Au(III) was used to calculate the % signal suppression (SS) (Equation 2). Signal Suppression (%) = [(I0 - I)/I0] * 100

(2)

For data obtained in SWV and DPV, the following equation (Equation 3) was used to calculate the % signal enhancement (SE). Signal Enhancement (%) = [(I - I0)/I0] * 100

(3)

where I0 is the baseline-subtracted peak current in the target-free solution, and I is the baselinesubtracted peak current obtained in the presence of the target. Sensor regeneration was achieved by incubating the electrodes in PBS-6.7 containing an additional 500µM L-cysteine for 10 min. ACVs were collected every 5 min until the MB signal remained constant. The electrodes were then rinsed with DI water for 40 sec and placed in a new aliquot of PBS-6.7. Sensor specificity experiments were performed in PBS-6.7 with additional metal ions. The first sample contained 1 µM each of the following ten metal ions: Ag(I), Cd(II), Mn(II), Pb(II), Co(II), Ni(II), Zn(II), Cr(III), Fe(III), Al(III). The second sample contained 1 µM Cu(II), 1 µM Hg(II), and 10 µM EDTA. The third sample contained 10 µM EDTA, 1 µM Au(III), and 1 µM each of the following twelve metal ions: Cu(II), Hg(II), Ag(I), Cd(II), Mn(II), Pb(II), Co(II), Ni(II), Zn(II), Cr(III), Fe(III), Al(III). All experiments were performed at room temperature and without mechanical stirring. Unless mentioned otherwise, all experimental results presented here are averaged from three different sensors (n = 3). Results & Discussion Sensor Characterization Using Alternating Current Voltammetry and Cyclic Voltammetry



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ACV is one of the most commonly used sensor interrogation techniques for this class of electrochemical biosensors,27,38-43 thus it was first used to characterize the E-ION Au(III) sensors. In the absence of Au(III), we observed a well-deﬁned MB peak at ∼−0.26 V (vs. Ag/AgCl) for both A6 and A12 sensors; this potential is consistent with the reduction potential of MB in this buffer (PBS-6.7) (Figure 1). Using the optimal sensor fabrication protocol, probe coverage of 6.3(±0.4) × 1011 and 7.8(±0.3) × 1011 molecules cm-2 can be reproducibly achieved for the A6 and A12 sensors, respectively. A large decrease in the MB current was observed in the presence of 1 µM Au(III), suggesting formation of the presumed Au(III)-adenine complexes. After target interrogation, both sensors were regenerated via a room temperature, 10-min incubation in PBS6.7 supplemented with 500 µM L-cysteine, followed by a 40-s DI water rinse. Like the E-ION Hg(II) sensor, the regeneration efficiency of the Au(III) sensors was quite high (~ 95%).27

Figure 1. ACVs of the A6 (A) and A12 (B) sensors in PBS-6.7 in the absence, presence of 1 µM Au(III), and after sensor regeneration. The AC frequency was 10 Hz.

Despite the overall similarity in the total signal change, the sensors’ response time is quite different. For the A6 sensor, signal saturation was achieved in ~5 min, with ~80% SS; whereas 10 ACS Paragon Plus Environment

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for the A12 sensor, signal saturation was reached in ~1 min, but with a higher %SS (~90%) (Figure S2). It is worth mentioning that the sensor response time is much shorter than most sensors of this class, including the E-ION Hg(II) sensor which requires ~30 min to reach signal saturation.27 The response time was found to be dependent on both the probe coverage and ionic strength of the buffer. Sensors with a high probe coverage responded slightly slower to the target when compared to the sensors with the optimal probe coverage (Figure S3A). This difference is rather minute when compared to the changes seen with the same sensor interrogated in buffers with a different ionic composition. In the absence of the supporting electrolyte (i.e., 10 mM PBS only), signal saturation was achieved in ~20 min for the A6 sensor (Figure S3B). This trend was also observed with the A12 sensor; a high ionic strength is clearly needed for the complexation reactions to occur quickly. To understand the sensing mechanism, we studied the AC frequency-dependent current response of the two sensors in the absence and presence of Au(III) (Figure S4). In general, for a surface-confined reversible redox system, the peak current should be proportional to the AC frequency when the frequency is sufficiently lower than the electron-transfer rate. However, as the applied frequency approaches a critical value above which electron transfer can no longer keep up with the rapidly oscillating potential, the peak current diminishes relative to the background current.44 For both sensors, in the absence of the target, the MB current increased rapidly between 1 and 200 Hz, the current remained relatively steady at frequencies between 200 and 1000 Hz. This profile is rather different from sensors fabricated with long and unstructured DNA probes, in which a large drop in the MB current can be seen at a rather low frequency (e.g., 50 Hz).27,43 This behavior could be explained; owing to the shorter probe length, these sensors can support efficient electron transfer even at high frequencies, significant decrease in the MB



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current is not likely to be observed till extremely high frequencies. But in the presence of 1 µM Au(III), the change in the MB peak current with frequency was much smaller for the A6 sensor, especially when compared to the A12 sensor. For the A12 sensor, a linear increase in the peak current was evident between 50 and 1000 Hz, we are currently exploring the reasons behind this unusual behavior. Nevertheless, given that the %SS is calculated using both pre-and post-binding MB currents, it should also be dependent on the applied frequency. For both A6 and A12 sensors, 10 Hz was found to be the optimal interrogation frequency and was thus used for the rest of the study. In addition ACV, CV was also used to characterize the sensors.27,43 Figure S5 shows the CVs of the A6 and A12 sensors before, after the addition of 1 µM Au(III), and after sensor regeneration. We observed ∼80% SS in the reduction peak current for both sensors; this change in the peak current was accompanied by an increase (∼90 mV) in the hysteresis (i.e., peak-topeak separation). This alludes to a reduction in the electron-transfer rate for MB upon target binding, which is in agreement with the ACV data and the proposed sensing mechanism. These two sensors are classified as “signal-off” sensors based on their response in ACV and CV. Although functional, “signal-off” sensors have several disadvantages when compared to “signalon” sensors. One of the main drawbacks is that only 100% SS can be obtained under any experimental conditions. There are merits in employing an electrochemical technique capable of converting conventional “signal-off” sensors to “signal-on” sensors. SWV and DPV have previously been used for this application.27,45-47 In brief, at a low SWV frequency or long DPV pulse width, the current from the target-bound state is enhanced and the current from the targetfree state is suppressed due to the rapid current decay (i.e., fast electron transfer), thereby resulting in a “signal-on”-like behavior. Both techniques were employed here and the results are


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shown in Figure S6. The optimal frequency for the A12 sensor in SWV was 5 Hz, the %SE in the presence of Au(III) was ∼356 %. As with DPV, the optimal pulse width was 100 ms; negligible MB peak current was observed in the absence of Au(III), addition of 1 µM Au(III) resulted in a large increase in the MB peak current (~457 %SE). Although not shown in here, similar results were obtained with the A6 sensor when these two techniques were employed. Sensor Sensitivity and Reusability Despite obvious improvements in terms of the total signal gain in SWV and DPV, the tilted baseline in the voltammograms renders accurate analysis of small changes in the peak current more challenging. ACV was thus used to determine sensor sensitivity. Shown in Figure 2 are the dose-response curves for the two sensors. For the A6 sensor, the LOD was 50 nM and with a linear dynamic range between 0 and 600 nM. In contrast, for the A12 sensor, the LOD was 20 nM and with a more limited dynamic range (0 - 200 nM). The data were also fitted to a one site binding model; the dissociation constant (Kd) was determined to be 534 nM and 114 nM for the A6 and A12 sensors, respectively. Based on these results, it is reasonable to assume that the linear dynamic range and LOD of this sensor can be tuned by simply increasing or decreasing the length of the oligoadenine probe. Although other methods for tuning the dynamic range of optical metal ion sensors have been reported,22,48-50 this aspect has not been previously addressed for this class of E-ION sensors. Shown in Table S1 are the LODs and linear dynamic ranges of recently developed Au(III) sensors. 8-10,13-23 As can be seen, the sensors reported in this study are clearly two of the more sensitive Au(III) sensors.



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Figure 2. Dose-response curves for the A6 (A) and A12 (B) sensors obtained using ACV at 10 Hz. Shown in the inset are the corresponding voltammograms.

Another attribute of this class of sensors is reusability. As mentioned previously, L-cysteine was used to regenerate the sensors. L-cysteine is known to reduce Au(III) to Au(I), thereby altering the interactions between Au(III) and the adenine bases in the probes. Removal of Au(III) results in a decrease in probe rigidity, which is reflected in the increase in the MB current.27 Although both sensors were found to be reusable for up to five times, a slight decrease in the %SS was seen after each interrogation cycle (Figure S7). This decrease in %SS could be attributed to the incomplete removal of the target, as well as monolayer degradation. L-cysteine could interact with the gold electrode surface, resulting in the removal of some thiolated probes and C6-OH. While other complexation agents with a high affinity for Au(III) could be used here, our results show that L-cysteine is the most effective in removing Au(III) from the adenine complexes. Sensor Specificity and Selectivity Metal ion sensors designed for real world analysis should be able to detect the specific metal ion in the presence of other potentially interfering metal ions. However, designing metal ion 14 ACS Paragon Plus Environment

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sensors that are highly specific remains a significant challenge; even custom designed fluorescence probes have shown to cross react with metal ions other than the intended target.17,51 The same challenge is present in developing DNA-based metal ion sensors given that some DNA-metal ion interactions are either non-specific or weak. To overcome these challenges, some researchers have started using in vitro selected DNA sequences that possess high affinity towards the specific metal ion as the biorecognition element.52 A more convenient way is to utilize a masking agent to prevent interfering metal ions from interacting with the recognition probes.27 In some cases, more than one masking agent can be added.22 Adenine is known to coordinate with several transition metal ions, for the current application the two possible interfering metal ions are Cu(II) and Hg(II). The use of EDTA in this case is strategic for it has high affinity for both Cu(II) and Hg(II), but not Au(III). Shown in Figure 3 are the two sensors’ responses to various metal ions. They were first tested against a “cocktail” containing a total of 10 µM of ten different metal ions (Ag(I), Cd(II), Mn(II), Pb(II), Co(II), Ni(II), Zn(II), Cr(III), Fe(III), Al(III)). Only a slight change in the signal was observed for both sensors, suggesting minimal interferences from these ten metal ions. The sensors were then tested against a solution containing 1 µM Cu(II), 1 µM Hg(II), and 10 µM EDTA. The A6 sensor showed a stronger response to this mixture when compared to the A12 sensor. Nevertheless, both sensors responded strongly to 1 µM Au(III) even in the presence of the twelve metal ions and 10 µM EDTA. We observed ∼80% and ∼90% %SS for the A6 and A12 sensors, respectively. EDTA has demonstrated to be an effective masking agent, enabling the sensors to retain high specificity for Au(III).



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Figure 3. The sensors’ responses to 10 different metal ions (1 µM each), 1 µM Cu(II) and 1 µM Hg(II) with 10 µM EDTA, and 1 µM Au(III) in the presence of the twelve metal ions (1 µM each) and 10 µM EDTA.

Sensor selectivity is equally important as sensitivity and specificity. Here we evaluated the sensors’ response to Au(III) in a synthetic aquifer sample. The sample was prepared by adding the specific ions found in the South Dakota Minnelusa aquifer into the interrogation buffer (PBS6.7).26,53 Shown in Figure 4 are the ACVs of the two sensors in the absence, presence of 1 µM Au(III), and after sensor regeneration. The sensors responded well to the target, showing %SS comparable to that obtained in a pure buffer (Figure 1). We also evaluated the sensors’ response to Au(III) as a function of the applied frequency (Figure S8). The frequency-dependent current profiles did not change significantly when compared to those obtained in a pure buffer (Figure S4), verifying the sensors’ ability to function in a realistically complex sample. In addition, we interrogated the sensors in a sample containing 50 µM EDTA and seven metal ions found in the surface water of the Linglong gold mining area in China.54 response of the A12 sensor is shown


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in Figure S9; as can be seen, the sensor responded relatively well to 1 µM Au(III), the %SS was ~80% , slightly lower than that obtained in a pure buffer.

Figure 4. ACVs of both sensors in the absence, presence of 1 µM Au(III), and after sensor regeneration. These results were obtained in a synthetic aquifer sample.

Conclusion We have demonstrated the use of thiolated oligoadenine probes as recognition elements in the design of a dynamics-based E-ION Au(III) sensor. More importantly, by simply varying the number of adenine bases in the probe, we can tailor the response of the sensor to fit a specific dynamic range and LOD. Both sensors have been successfully employed for detection of Au(III) in synthetic aquifer and surface water samples. Although this sensing technology is still in its proof-of-concept stage and thus not ideal for mining and exploration applications, with proper optimization, including further improvement in sensor sensitivity by using a longer oligoadenine probe, this detection method can potentially be employed for cost-effective, on-site analysis of Au(III) in a wide range of samples.



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Acknowledgements The authors acknowledge the National Science Foundation (CHE-0955439) and National Institute of Health (R41ES24626) for financial support. Supporting Information Available: Structure of DNA probes, binding kinetics of both sensors in PBS-6.7, binding kinetics of the A6 sensor with a different probe coverage and in different buffers, AC frequency-dependent current profiles of both sensors in PBS-6.7, CVs of both sensors in PBS-6.7, SWVs and DPVs of the A12 sensor, sensor interrogation-regeneration plots for both sensors and additional experimental results are included in Figure S1 – S9 and Table S1. This material is available free of charge via the Internet at http://pubs.acs.org.


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