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Chemical Equilibrium-Based Mechanism for the Electrochemical Reduction of DNA-Bound Methylene Blue Explains Double Redox Waves in Voltammetry
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Chemical Equilibrium-Based Mechanism for the Electrochemical Reduction of DNA-Bound Methylene Blue Explains Double Redox Waves in Voltammetry
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  • J. D. Mahlum
    J. D. Mahlum
    Chemistry-Biology Interface Program, Zanvyl Krieger School of Arts & Sciences, Johns Hopkins University, Baltimore, Maryland 21218, United States
    More by J. D. Mahlum
  • Miguel Aller Pellitero
    Miguel Aller Pellitero
    Department of Pharmacology and Molecular Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21202, United States
  • Netzahualcóyotl Arroyo-Currás*
    Netzahualcóyotl Arroyo-Currás
    Chemistry-Biology Interface Program, Zanvyl Krieger School of Arts & Sciences, Johns Hopkins University, Baltimore, Maryland 21218, United States
    Department of Pharmacology and Molecular Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21202, United States
    Department of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
    Institute for Nanobiotechnology, Johns Hopkins University, Baltimore, Maryland 21218, United States
    *Email: [email protected]. Phone: 443-287-4798.
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The Journal of Physical Chemistry C

Cite this: J. Phys. Chem. C 2021, 125, 17, 9038–9049
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https://doi.org/10.1021/acs.jpcc.1c00336
Published April 21, 2021

Copyright © 2021 The Authors. Published by American Chemical Society. This publication is licensed under

CC-BY-NC-ND 4.0 .

Abstract

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Methylene blue is widely used as a redox reporter in DNA-based electrochemical sensors and, in particular, it is the benchmark DNA-bound reporter used in electrochemical, aptamer-based sensors (E-ABs). Our group recently published an approach to interrogate E-ABs via cyclic voltammetry, which uses the cathodic to anodic peak-to-peak voltage separation (ΔEP) from methylene blue to report on the electron-transfer kinetics and binding state of these sensors. Although effective at scanning rates ≤10 V·s–1, the method is limited at faster scanning rates because cyclic voltammograms of methylene blue-modified, electrode-bound DNA present double faradaic waves that prevent the accurate estimation of ΔEP. These double waves have been observed in previous works, but their origin was unknown. In response, here we investigated the origin of these redox waves by developing a numerical model that incorporates methylene blue’s chemical equilibria in phosphate buffer to predict the shape and magnitude of cyclic voltammograms with 85% or better accuracy from single- and double-stranded DNA. Our model confirms that the peak splitting observed at scanning rates >10 V·s–1 originates from the protonation equilibrium of the radical intermediate species formed after methylene blue receives the first electron. Moreover, the model reveals a strong interaction between the proton transferred during the reduction of methylene blue and the chemical make of blocking self-assembled monolayers typically used in the fabrication of E-ABs. This interaction affects the apparent rate of the first electron-transfer step, accelerating or decelerating it depending on the hydrophobicity and polarity of the blocking monolayer. By expanding our understanding of the effect that monolayer chemistries have on methylene blue’s protonation rates and E-AB signaling, this work may serve the rational design of future sensors with tunable electron-transfer kinetics.

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Copyright © 2021 The Authors. Published by American Chemical Society

Introduction

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Methylene blue is arguably one of the most used redox reporters in nucleic acid-based electrochemical sensors and is the benchmark reporter used in electrochemical, aptamer-based sensors (E-ABs). (1,2) This widespread use exists because, when bound to DNA, methylene blue and its reduced form, leucomethylene blue, are chemically stable and undergo an electrochemically reversible electron transfer. (3) Moreover, when co-tethered to the surface of gold electrodes with alkanethiol self-assembled monolayers (SAMs), methylene blue presents an ideal reduction potential far from background redox processes (e.g., the reduction of molecular oxygen and the surface oxidation of gold). (2,4) These features notwithstanding, the mechanism of methylene/leucomethylene blue electron transfer is complex. (5) First, it is pH-dependent, (6) making electron transfer susceptible to the acid–base chemistry of the medium. Furthermore, the voltammetric interrogation of the pair can generate multiple redox waves at fast voltage scanning rates. (7,8) These voltammetric features have been attributed to the occurrence of two different mechanisms of electron transfer (contact-mediated (9) vs through-DNA (10)). (7) Here, instead, we present a chemical equilibrium-based model that explains the origin of such features and demonstrates that they simply derive from the protonation equilibrium of an intermediate radical species.
The electrochemical reduction of methylene blue in aqueous solution (Figure 1A) involves a first electron-transfer step to produce a radical, (5) which undergoes a protonation reaction, followed by a second electron transfer to finally produce leucomethylene blue. Under conditions of molecular crowding, leucomethylene blue can self-associate to produce dimers (Figure 1B), (11−15) which appear in voltammograms at more negative reduction potentials relative to that of methylene blue. (13) It is expected that the electrochemical reduction of DNA-bound methylene blue follows the same electron-transfer mechanism as the solvated form. However, given the low surface density of methylene blue molecules on DNA-based sensors (typically in the order of a few picomolar (9)), self-stacking interactions are likely minimal. Thus, the voltammetric interrogation of such sensors often shows a single anodic/cathodic wave pair with peak-to-peak separation close to 0 mV at scanning rates ≤1 V s–1. (16,17)

Figure 1

Figure 1. Electrochemical reduction of methylene blue. This scheme uses the curved-arrow formalism to explain the electrochemical reduction of methylene blue according to the original mechanism proposed by Jean Chevalet. (13)

In prior work, (18) we have demonstrated the potential advantages of employing cyclic voltammetry (CV) at scanning rates >1 V s–1 to measure the electron-transfer kinetics and signaling of methylene blue-modified, electrode-bound DNA aptamers. In our approach, the target concentration is reported via changes in the cathodic to anodic peak-to-peak voltage separation (ΔEP) of cyclic voltammograms. Because the magnitude of ΔEP is insensitive to variations in the number of aptamer probes on the electrode, ΔEP-interrogated E-ABs were resistant to drift and showed decreased batch-to-batch and day-to-day variability in sensor performance relative to interrogation based on other electrochemical methods. Moreover, ΔEP-based measurements could be performed every few hundred milliseconds and were, thus, competitive with other subsecond interrogation strategies such as chronoamperometry (19) and electrochemical impedance. (20) Unfortunately, the method fails at scanning rates faster than 10 V·s–1 because methylene blue’s faradaic waves start to split, (7,8) turning into two uneven redox waves.
To our knowledge, the faradaic splitting in methylene blue’s cyclic voltammograms has been reported twice before. In 2011, Yang and Lai showed that the voltammetric reduction peak of methylene blue in DNA duplexes separates into two waves at high scan rates (see Figure S7 in the Supporting Information of ref (8)). However, the authors did not provide a discussion regarding the origin of such splitting. One year later, Pheeney and Barton reported that, at fast scanning rates (5 V·s–1), cyclic voltammograms of methylene blue-modified DNA duplexes present two reductive peaks (see Figure 7 in ref (7)). The authors attributed the origin of each peak to two different mechanisms of electron transfer, one transferring electrons via a contact-mediated mechanism (9) and another transferring them through the DNA chain. (10) This interpretation seems unlikely since voltammetric peak splitting that occurs when using single-stranded DNA is the same as when using double-stranded DNA, irrespective of length or sequence. To clarify the origin of this peak splitting, here we use a numerical model to demonstrate that the protonation equilibrium of methylene blue’s intermediate radical is the source of the two voltammetric waves. By quantitatively comparing our simulated currents against experimental measurements, we show that this model can accurately predict voltammetric peak currents at scanning rates spanning 3 orders of magnitude and under different conditions of oligonucleotide length, pH, monolayer chemistry, and electron-transfer kinetics. In addition, the model reveals a strong interaction between the proton transferred during the first reduction step of methylene blue and the chemical make of blocking SAMs. This interaction affects the apparent rate of the first electron-transfer step, accelerating or decelerating it depending on the hydrophobicity and polarity of the blocking monolayer. The results herein expand our understanding of DNA-bound methylene blue’s electron-transfer properties and of how these are tuned by monolayer chemistries often used for the fabrication of DNA-based sensors.

Methods

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Chemicals and Materials

6-Mercaptohexanol, 1-hexanethiol, 1H,1H,2H,2H-perfluoro-1-hexanethiol, 1-mercaptohexanoic acid, and tris(2-carboxyethyl)phosphine hydrochloride (TCEP) were purchased from Sigma-Aldrich (St. Louis, MO). Phosphate-buffered saline (PBS, 11.9 mM HPO32–; 137 mM NaCl; 2.7 mM KCl; pH = 7.4), trace-metal-grade sulfuric acid (H2SO4), hydrochloric acid (HCl), and sodium hydroxide (NaOH) were purchased from Fisher Scientific (Waltham, MA). Tobramycin sulfate was purchased from GoldBio (St. Louis, MO). We prepared all aqueous solutions using deionized water from a Milli-Q Direct purification system with a resistivity of 18 MΩ. Gold working electrodes (PN: 002314, diameter: 1.6 mm) and coiled platinum wire counter-electrodes (PN: 012961) were obtained from ALS Inc. (Tokyo, Japan). Ag|AgCl (KCl-saturated) reference electrodes (PN: CHI111) were purchased from CH Instruments (Austin, TX). For polishing electrodes, 1200/P2500 silicon carbide grinding paper (PN: 36-08-1200) was bought from Buehler (Lake Bluff, IL); cloth pads (PN: MF-1040) and alumina slurry (PN: CF-1050) were purchased from BASi (West Lafayette, IN). Oligonucleotides, modified on the 5′ end with hexanethiol and on the 3′ end with methylene blue were purchased from and HPLC-purified by Sigma-Aldrich (Houston, TX). We used the DNA sequences reported in Table S1. To prepare DNA solutions, we first incubated 1 μL of 100 μM thiolated MB-modified DNA with 2 μL of 5 mM TCEP aqueous solution to reduce the disulfide bond. We then diluted the DNA with freshly prepared 1 mM thiol aqueous solution to a final concentration of either 100 nM, 500 nM, 1 μM, or 25 μM as determined via molecular absorbance measurements employing an Implen Nanophotometer NP80 (Westlake Village, CA). Using these solutions, we obtained DNA-packing densities on electrode surfaces of 1.93 ± 0.64 pmol·cm–2, 2.24 ± 0.58 pmol·cm–2, 2.66 ± 0.45 pmol·cm–2, and 4.61 ± 0.68 pmol·cm–2, respectively.

Electrode Preparation

Gold electrodes were polished for ∼2 min on 1200/P2500 silicon carbide grinding paper and subsequently for ∼4 min on a cloth pad with alumina slurry. After rinsing with water to remove polishing debris, they were then electrochemically cleaned in 0.5 M NaOH and 0.5 M H2SO4 following a previously reported protocol. (21) Briefly, (1) in 0.5 M NaOH, we scanned from −0.3 to −1.6 V versus Ag|AgCl 200 times at a scan rate of 0.5 V·s–1; (2) in 0.5 M H2SO4, we scanned from 0 to 1.6 V versus Ag|AgCl 200 times at a scan rate of 0.5 V·s–1. Once the electrodes were clean, we rinsed them with water and placed them immediately into 1 mM alkanethiol solutions, with or without a DNA construct listed in Table S1, in water to incubate overnight at 25 °C. We prepared sensors via co-incubation, as we reported before. (4) Post incubation, we rinsed the electrodes with water and placed them into a custom electrochemical cell containing 1× PBS. The cell was deaerated for 5 min by bubbling nitrogen gas into the solution prior to taking any electrochemical measurements. All measurements were performed under a N2 atmosphere. For pH experiments, we potentiometrically titrated the baseline PBS pH value (7.4) to pH = 4 using HCl and pH = 9 using NaOH. To prepare dsDNA surfaces, we incubated electrodes functionalized with the anchor strand in solutions containing a 2-fold higher concentration of the complement. We confirmed full hybridization on the electrode surface using frequency maps as previously reported by Dauphin-Ducharme and colleagues. (9)

Electrochemical Measurements

A CH Instruments Electrochemical Analyzer (CHI 1040C, Austin, TX) multichannel potentiostat and associated software was used for all CV measurements. We used a three-electrode cell configuration consisting of gold disk working, coiled platinum wire counter, and Ag|AgCl (saturated KCl) reference electrodes. All CV measurements were recorded in 1× PBS solution at scanning rates of either 1, 4, 10, 50, 100, or 150 V·s–1 after a 3 s quiet time, sampling current every millisecond.

Experimental CV Analysis

Each cyclic voltammogram condition used in our analysis had four replicates taken. Only one replicate was used to fit the simulated data because averaging voltammograms artificially decreased and broadened peak currents due to heterogeneity between sensor surfaces (Figure S1). To choose which replicate would be used, we compared them using the scatter plot function of Microsoft Excel. The replicate with the largest difference between charging current and Faradaic current was then used for further analysis. Because we did not include parameters to simulate charging current in our model, we subtracted the background currents from the chosen measurements. To find the background currents, we first collected data using electrodes created as described above but without methylene blue attached to the DNA as our background scans. We aligned voltammograms from non-methylene blue sensors with those from sensors using methylene blue and subtracted the two. The resulting background-subtracted data were used in all figures and is presented throughout as solid lines.

Computational Model

We employed COMSOL v5.4 to create a numerical model for a one-dimensional electrochemical cell in order to simulate cyclic voltammograms. The COMSOL file is provided as Supporting Information. Our model simulates both homogenous equilibrium reactions occurring between the buffer and methylene blue and heterogenous electron transfer occurring between methylene blue and the electrode surface. Parameters reported in the Supporting Information were determined by manually adjusting such parameters in the model until each simulation matched the background-subtracted experimental data with an accuracy of 85% or better as described below. Our numerical model (Figure 2) approaches the experimental setup illustrated in Figure 3A,B as a one-dimensional electrochemical cell. We previously reported a similar model for the determination of DNA-bound methylene blue electron-transfer rates via square wave voltammetry. (22) In our current model, we define two boundaries, one representing the surface of the working electrode, and the other representing the 3′ DNA terminus where methylene blue sits (Figure 2A). We set the separation between these two boundaries to 10 nm with a uniform mesh of 1% of the total cell length (0.1 nm/mesh element). This length includes the hexanethiol monolayer, 0.8 nm, (22,23) plus an approximated maximum persistence length for a 27-nt-long, monolayer-attached DNA strand (assuming double-stranded DNA, which rises approximately 3.4 nm every 10 nt, is the closest expanded-DNA conformation). (24) We postulate that the length of double-stranded DNA is a good approximation to the maximum length of our short oligonucleotides in the absence of literature consensus for the persistent length of single-stranded DNA. (25)

Figure 2

Figure 2. Description of the numerical model. (A) We created a one-dimensional model representing the DNA-functionalized electrodes of Figure 3A,B. (B) We simulate the voltammetric response of these electrodes by using a triangular voltage waveform with slope E·t–1, which corresponds to the voltage scanning rate. (C) In response to this varying potential, the experimental system (Figure 3A,B) produces a cyclic voltammogram (black trace) which varies in shape and magnitude according to the chemical equilibrium of the redox species considered. Our model accurately simulates the same voltammogram (red circles) via eqs 1017, 19, and 20. The surface DNA concentration was 1.93 ± 0.64 pmol·cm–2 here and in all figures of the article, unless noted otherwise. All voltammetric measurements were performed in 1× PBS as defined in the Methods section, unless noted otherwise.

Figure 3

Figure 3. Electrode-attached, methylene blue-modified DNA exhibits voltammetric features that change with increasing voltage scanning rate. (A) To illustrate these features, we employ DNA constructs of different lengths and secondary structures (Table S1), including one aptamer (illustrated here) that binds to the antibiotic tobramycin. We modify these constructs with a hexanethiol linker in the 5′ terminus and a methylene blue reporter at the 3′ terminus and co-deposit them onto gold electrodes along with 1-hexanethiol to form a SAM. (B) In the presence of tobramycin, the aptamer undergoes binding-induced conformational changes that accelerate electron transfer from methylene blue to the gold electrode, possibly by bringing methylene blue closer to the electrode surface. (C) When we interrogate aptamer-functionalized electrodes at scan rates ≤10 V·s–1 with surface coverage concentrations of 1.93 ± 0.64 pmol·cm–2 and either no tobramycin added or 1 mM of tobramycin, we observe no splitting of voltammetric waves. (D) However, at voltage scanning rates > 10 V·s–1, we observe splitting of the oxidation wave. Moreover, the addition of the target causes an inversion of behavior, showing peak splitting in the reduction but not in the oxidation wave. See the Methods section for additional experimental information.

We based the reactions considered by our model on the mechanism proposed by Jean Chevalet (Figure 1) (13)
(1)
(2)
(3)
where O is MB+, R1 is MB, R1H is LMB+•, R2H is LMB; kf1 and kf2 are the rates of reduction for the first and second electron transfers, respectively; kb1 and kb2 are the rates of oxidation for the first and second electron transfers, respectively; and kb,R1H and kf,R1H are the rate of protonation and the rate of deprotonation, respectively. We note that eqs 13 denote the general formula for an ErCrEr reaction scheme, (26) which involves a first electron transfer, followed by a homogeneous chemical reaction, and, finally, a second electron transfer. We define the reaction of methylene blue at the working electrode in our simulation (Figure 2A) by using Fick’s second law of diffusion to describe electrochemical flux
(4)
(5)
where C denotes concentration of the subscripted species, t is time, x is the distance from the electrode surface, J is flux, and D is the diffusion coefficient of the subscripted species. For simplicity, we assume D = 10–5 cm2·s–1 for all redox-active species (see Figure S2 for more details). Per eqs 13, the initial conditions for the redox-active species were CO = CO* (where CO* is the initial bulk concentration of species O) and CR1 = CR1H = CR2H = 0 M. Thus, the right-most, no-flux boundary conditions are set as follows
(6)
(7)
(8)
(9)
We set the fluxes (eqs 4 and 5) to obey the Butler–Volmer formalism of electron-transfer kinetics
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
where k10 and k20 are heterogeneous rate constants for the first and second electron transfers, respectively; α1 and α2 are the transfer coefficients for the first and second electron transfers, respectively; n is the number of electrons transferred, F is Faraday’s constant, R is the gas constant, T is temperature, E is the applied voltage, and E10 and E20 are the standard reduction potentials for the first and second electron transfers, respectively. Using eqs 1017, we successfully model the electrochemical flux that occurs at the electrode boundary.
To evaluate pH effects related to the protonation step (eq 2), we incorporate all chemical equilibrium reactions participating in our experimental system, including protonation equilibria for phosphate-buffered saline (PBS, Table S2). We model PBS equilibria based on previously reported equilibrium constants and protonation rates. (27) To incorporate these equilibria into our flux calculations, we express eq 2 in its acid dissociation form
(18)
where CH+ is the concentration of protons. When the system is at equilibrium
(19)
(20)
where KR1H is the equilibrium constant for the proton dissociation of R1H. We set eq 20 as a domain variable so our model accounts for a proton equilibrium similar to our real-world experimental system.
Having defined the model physics, we next establish the triangular voltage waveform that CV uses (Figure 2B). To do so, we use the expression
(21)
where Ein is the initial voltage vs. Ag|AgCl (saturated KCl), Efin is the final voltage, sr is the scan rate, τ is the time required to sweep the voltage from Ein to Efin, and H1 and H2 define step functions: H1 jumps from 1 to 0 when χ1 = (τ – t)·t–1 ≤ 0, and H2 jumps from 0 to 1 when χ1 = (t – τ)·t–1 > 0. Thus, employing eqs 1017 to account for electrochemical fluxes and eqs 1821 to account for chemical equilibria and voltage perturbations, our model generates voltammetric currents that closely match the shape and magnitude of experimental voltammograms (Figure 2C).
To evaluate the accuracy of our numerical simulation, we modeled the effect the scanning rate has on the cyclic voltammograms of DNA-bound methylene blue. We perform this analysis by presenting a superposition of numerically simulated voltammograms over experimental, background-subtracted voltammograms measured at six different voltage scanning rates (Figure 4). To achieve a good fit, we adjusted the electron-transfer and proton dissociation parameters in eqs 13 and 1013. By keeping such parameters within an order of magnitude or closer for all scanning rates (Table S3), we accurately simulate scanning-rate-dependent voltammetric features. To determine the accuracy of our model, we calculate error as the percent difference between simulated and experimental currents at each voltage point, using the formula
(22)

Figure 4

Figure 4. Modeling the electrochemical reduction of DNA-tethered methylene blue at different voltage scanning rates. We recorded these background-subtracted cyclic voltammograms on gold electrodes functionalized with a 26-base DNA aptamer modified at one end with methylene blue (Figure 2A). As a model system, we co-deposit 500 nM of an aptamer that binds to the antibiotic tobramycin with 1 mM 1-hexanethiol. We then obtain cyclic voltammograms (black traces) in 1× PBS solution at voltage scanning rates of (A) 1, (B) 4, (C) 10, (D) 55, (E) 100, and (F) 150 V·s–1. Using the parameters described in Table S3 in our numerical model, we generate simulated voltammograms (colored circles) closely matching the experimental ones. We only show 1 in every 8 simulated currents for clarity. Error bars report the true differential error between experimental and simulated voltammograms. The color indicates percent error, which we use to demonstrate that our numerical model correctly estimates the current magnitude of the different voltammetric peaks with an accuracy of 85% or better; that is, ≤15% error (Figure S3).

To facilitate the visualization of relative error, we color-code the error bars in proper rainbow fashion to represent 0% (red) and 100% (violet) error (Figure 4). The error bar heights reported in each figure represent the real error between our model and the experimental data and are calculated by dividing P.D. by 100 and multiplying by the simulated data point. We stopped adjusting parameters when the peak magnitude for each simulation was 85% accurate or better (Figure S3). We observe that the largest error occurs in the flat regions of the voltammograms. However, this error arises because our numerical simulations report currents close to true zero, whereas the experimental voltammograms always have a nonzero current either because of noise or poor background correction in those regions.

Simulated CV Analysis

We exported the simulated voltammograms into a text file and mathematically compared them against experimental voltammograms in Microsoft Excel to determine the error. Using eq 22, we found the percent error. By dividing this by 100 and multiplying by the simulated value, we found the relative error. To visualize these errors, we used the built-in color function using the Rainbow color table. Error bars and simulated traces were colored according to the percent error where 0% error is red and 100% error is violet. Error bars represent the true error difference between simulated and experimental currents. All data were first analyzed in Microsoft Excel. Individual figure panels were graphed in Igor Pro v.8 and multipanel figures were assembled in Adobe Illustrator, Creative Cloud version.

Results and Discussion

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To analytically validate our numerical model, we use experimental voltammograms of the reduction of methylene blue covalently bound to single-stranded DNA of different lengths, sequences, and secondary structures and of double-stranded DNA (Table S1). To collect the experimental data, we modify these strands with a hexanethiol linker placed on the 5′ terminus and a linker functionalized with methylene blue on the 3′ terminus. (4) Then, we co-deposit the constructs with 1-hexanethiol onto the gold electrodes to form a SAM (Figure 3A). To better study the effect of electron-transfer kinetics on the voltammetric features of methylene blue, we include one aptamer sequence in our list of constructs (Table S1). In the presence of its target (the antibiotic tobramycin), this aptamer undergoes a binding-induced conformational change that accelerates the overall electron-transfer rate from methylene blue to the electrode (Figure 3B). (28,29) When we interrogate sensors functionalized with this aptamer by CV in PBS and at scanning rates ≤10 V·s–1, we observe faradaic waves with no visible splitting in either the reduction or oxidation peaks (Figure 3C). However, scanning the sensors at rates >10 V·s–1 causes a significant splitting of the oxidation wave (Figure 3D). Repeating the experiment in the presence of saturating concentrations of the aptamer’s target causes an inversion of the peak splitting behavior, with two waves becoming visible in the reduction scan but vanishing from the oxidation scan (Figure 3D). We explain this behavior by making the argument that such peak splitting is explained by the chemical equilibria involved in the voltammetric reduction of methylene blue.
The peak splitting we observe in the oxidation wave of voltammograms measured at >10 V·s–1 (Figure 4) originates from the protonation reaction of the methylene blue radical (Figure 1 and eq 2). Specifically, the acid dissociation constant (KR1H in eq 20) and protonation kinetics of this reaction determine how much the oxidation peak splits. To illustrate this effect, we performed numerical simulations holding all parameters constant in our model except for either KR1H (Figure S4) or kb,R1H (Figure S5). The resulting voltammograms clearly indicate that KR1H and kb,R1H strongly affect peak splitting. Fortunately, the acid dissociation constants for the methylene blue radical (pKa = 9.0) and leucomethylene blue (pKa = 5.8) have been reported before. (30) Thus, in our model, we assume the apparent acid dissociation constant for eq 2 to be approximately the average of the two known constants: pKa,R1H ∼ 7.4. Keeping this value constant in the model but modulating the protonation rate, we successfully fit all voltammograms reported in this work.
We can also use our model to discard the possibility that the peak splitting could be due to leucomethylene blue self-stacking (Figure 1B). To do this, we varied the concentration of the DNA aptamer used during the assembly of our monolayer. Increasing the DNA deposition concentration from 100 nM to 1 μM (packing densities of 1.93 ± 0.64, 2.24 ± 0.58, and 2.66 ± 0.45 pmol·cm–2, respectively) results in visually similar voltammograms (Figure 5A–C) that we accurately model (Figure S6 and Table S4) without including parameters to simulate leucomethylene blue dimerization. Employing the deposition concentrations used in the work by Pheeney and Barton (25 μM dsDNA solutions, Figure 5D), (7) we observe wave broadening and a 60 mV shift of the formal reduction potential in the negative direction but no additional voltammetric features. These results indicate that, at high electrode surface concentrations of methylene blue-modified DNA (4.61 ± 0.68 pmol·cm–2), stacking of neighboring methylene blue molecules may occur as suggested by the visible shift in reduction potential and wave broadening. However, this stacking does not seem to generate additional voltammetric features.

Figure 5

Figure 5. High deposition concentrations of methylene blue cause peak broadening and increased overpotentials but do not affect peak splitting. To show that higher packing density of DNA-bound methylene blue at the surface of an electrode does not affect peak splitting, we co-deposited 1-hexanethiol and either (A) 100 nM, (B) 500 nM, (C) 1 μM, or (D) 25 μM of the tobramycin aptamer (Table S1) onto gold electrodes with resulting surface coverages of (A) 1.93 ± 0.64, (B) 2.24 ± 0.58, (C) 2.66 ± 0.45,, and (D) 4.61 ± 0.68 pmol·cm–2. We then measured voltammograms at a scanning rate of 100 V·s–1 and fit the data with an accuracy of 85% or better (Figure S6) using the parameters found in Table S4. We speculate that the wave broadening and 60 mV shift in formal reduction potential observed in electrodes prepared from solutions containing 25 μM DNA relative to those prepared at 100 nM are due to leucomethylene blue self-stacking (Figure 1B).

The splitting of methylene blue reduction or oxidation waves is also not caused by different mechanisms of electron transfer (contact-mediated (9) vs through-DNA (7,10)). We demonstrate this by presenting cyclic voltammograms that interrogate single-stranded DNA of different lengths and varying sequences and double-stranded DNA (Table S1 and Figure 6). Specifically, we include DNA strands composed only of deoxythymine, which lacks the possibility of forming double-stranded DNA (a requirement to enable through-DNA electron transfer). (31) Irrespective of sequence, all constructs show peak splitting behavior in the voltammograms. However, we observe less pronounced wave splitting with decreasing DNA length, which is an effect of increased electron-transfer kinetics of the system due to bringing methylene blue and the electrode surface closer together. Using our model and adjusting electron-transfer kinetics (Table S5), we accurately fit the shape of voltammmograms obtained for each of the DNA strands considered (Figure S7).

Figure 6

Figure 6. Voltammetric peak splitting is dependent on DNA secondary structure. We employed nucleotide sequences of (A) 10, (B) 20, (C) 26, (D) 37 nt, (E) tobramycin aptamer hybridized to a fully complementary strand, and (F) tobramycin aptamer in the presence of the target to test whether secondary structure affects peak splitting. Each of the constructs were co-deposited at 500 nM with 1 mM 1-hexanethiol onto gold electrodes and are modified with methylene blue at the distal terminus. All experiments were done in 1× PBS solution and experiments A–E were performed at 100 V·s–1, while experiment F was performed at 150 V·s–1. We report the theoretical secondary structures for each construct as generated by mfold software (Table S1). (34) Although all constructs exhibit peak splitting, we observe a reduction in this splitting with decreasing oligonucleotide length (A vs D). This is because, as the DNA shortens, the electron-transfer kinetics of the system increase as previously demonstrated. (35) We also observe a reversal in peak splitting behavior as a stable secondary structure is introduced (E for double-stranded DNA and F for a folded tobramycin-binding aptamer in the presence of 1 mM tobramycin). This is related to a change in protonation rate (Table S5) which suggests a change in hydrogen bonding interactions between methylene blue and the DNA. Error bars report the true differential error between experimental and simulated voltammograms. The color indicates percent error, which we use to demonstrate that each simulation fits the peak currents of background-subtracted voltammograms with an accuracy of 85% or better; that is, <15% error (Figure S7).

The measurements using dsDNA (i.e., tobramycin-binding aptamer hybridized to a fully complementary strand) present a more pronounced peak splitting in the reduction scan (Figure 6E), in contrast to all ssDNA constructs, which present splitting in the reverse, oxidation scan. This inversion in electrochemical behavior may suggest a change in hydrogen bonding interactions between the DNA and methylene blue, a known DNA intercalator, (32,33) that affect the protonation reaction of the radical intermediate. We also observe this effect in ssDNA tobramycin-binding aptamers, which present significant self-complementarity when target-stabilized. To explore this, we challenged tobramycin-binding E-ABs with saturating tobramycin concentrations (1 mM) and fit the resulting voltammograms using our model (Figure 6F). When saturating concentrations of tobramycin are present, the overall electron-transfer kinetics of the system increase, as evidenced by a decrease in ΔEP visible between Figures 4F and 6F of ∼80 mV. The acceleration of the first electron-transfer step (from 261 to 354 s–1, Table S5) results in the disappearance of the original peak splitting in the oxidation wave (e.g., Figure 4F) and the appearance of new splitting in the reduction wave (Figure 6F). This is because although the first electron-transfer rate increases, the second electron transfer is still limited by the protonation rate, which in the case of the target-bound state has not significantly changed [4.0 × 107 m3·s–1·mol–1 for unbound vs 4.5 × 107 m3·s–1·mol–1 for bound aptamer (Table S5)]. These results demonstrate that peak splitting in methylene blue voltammetry does not arise from different mechanisms of electron transfer and underline the importance of understanding hydrogen bonding interactions between methylene blue and the DNA strand.
As one additional confirmation that our hypothesis is accurate and the observed peak splitting is caused by the rate-limiting protonation of the methylene blue radical (Figure 1 and eq 2), we tested peak splitting as a function of pH. The published literature indicates that methylene blue’s electron-transfer mechanism is itself pH-dependent. Specifically, several earlier reports (6,36,37) demonstrated that the formal reduction potential of methylene blue linearly becomes more negative with increasing pH, as expected from the Nernst equation. Yet, the slope of this line undergoes two marked transitions: one from −87 mV/pH (at pH < 5.4) to −58 mV/pH (at pH = 5.4–6.0) and a second transition to −28 mV/pH (at pH > 6.0). (6) These slope changes in the Nernstian curve are indirectly indicative of changes in the mechanism of electron transfer. Although such values are not transferable to our gold electrode system since they were measured on carbon fiber electrodes, they do indicate the mechanism of methylene blue reduction changes with pH.
Thus, we adapted our model to pH-induced changes in methylene blue’s reduction mechanism by assuming that the protonation reaction is no longer rate limiting at pH > 8.0 or pH < 6.0 (Figure 7). In other words, when the solution pH is far from methylene blue’s apparent pKa in either direction, the reaction mechanism changes from the ErCrEr scheme shown in eqs 13 to two serial and reversible electron transfers (ErEr)
(23)
(24)

Figure 7

Figure 7. Chemical equilibrium explains the changes in voltammetric features observed at different values of pH. To illustrate this point, we measured cyclic voltammograms on DNA-functionalized electrodes (tobramycin-binding aptamer) immersed in 1× PBS at pH = 4, 7, and 9. For the low and high pH values, we potentiometrically titrated the buffered solutions with HCl or sodium hydroxide, respectively. As shown here, our model accurately predicts the position and current magnitude of the main voltammetric features in background-subtracted voltammograms with greater than 85% accuracy at all values of pH (Figure S8). However, we note that at pH = 9 and pH = 4, the mechanism changes from an ErCrEr (eqs 13) reaction to an ErEr (eqs 23 and 24) scheme, where electrochemical reduction no longer requires protonation. The latter mechanism is included in our numerical model. We use the parameters reported in Table S6 to achieve these fits. Error bars report the true difference error between experimental and simulated voltammograms. The color indicates percent error.

The validity of eqs 23 and 24 is supported by previously reported results from the work of Caram and colleagues (38) on voltammetric measurements of methylene blue performed in aprotic media in the presence and absence of proton donors (see, e.g., Scheme 2 in ref (38)). Using this assumption, we compared the voltammetric response of a new batch of DNA-functionalized electrodes at pH = 4.0 (Figure 7A), 7.0 (Figure 7B), and 9.0 (Figure 7C) versus the output of our model. Our simulated results successfully match the experimental voltammograms in peak current magnitude (Figure S8). Moreover, the E1/2 for each of the modeled voltammograms was within 50 mV of the values reported in the literature (Table S6). (6) These results demonstrate that pH-induced changes in methylene blue’s radical intermediate’s protonation successfully account for shape changes observed in experimental voltammograms in acidic, neutral, and alkaline solutions.
Having demonstrated the validity of our proton equilibrium hypothesis at various voltage scanning rates (Figure 4), deposition concentration (Figure 5), secondary structures (Table S1 and Figure 6), and pH values (Figure 7), we next explored how the hydrophobicity of alkanethiol monolayers affect the electrochemical behavior of DNA-bound methylene blue. We were motivated to pursue this study by prior results from our group demonstrating that the terminal chemistries of alkanethiols can dramatically affect the signaling behavior of electrochemical DNA biosensors (e.g., as in aptamer-based sensors, Figure 3). (4) For this purpose, we prepared a new batch of electrodes, this time functionalizing them with monolayers of either 6-mercaptohexanol (Figure 8A), 1-hexanethiol (Figure 8B), or a fluorinated analogue of 1-hexanethiol (Figure 8C), interrogated them at different voltage scanning rates (1, 10, and 100 V·s–1), and accurately simulated the voltammogram for each monolayer (Figure S9). The more hydrophilic monolayer of 6-mercaptohexanol (Figure 8A) produces background-subtracted voltammograms with sharper peaks and less peak splitting relative to monolayers made of 1-hexanethiol (Figure 8B) and the fluorinated monolayer (Figure 8C). In contrast, the fluorinated monolayer exhibits more peak splitting than either of the other two monolayers. The signal-to-noise level is worse in electrodes functionalized with 6-mercaptohexanol because they generally present larger capacitive currents (Figure S10) that contribute to hiding a fraction of methylene blue’s voltammetric waves. (4) Next, we used our numerical model to establish differences in fit parameters between the three monolayers (Table 1). Doing this, we determined that 6-mercaptohexanol increases the protonation rate of the methylene blue radical (i.e., increases kb,R1H in eq 2) nearly 2-fold relative to 1-hexanethiol, thereby decreasing the extent of peak splitting seen at, for example, 100 V·s–1. We also see a nearly 3-fold decrease in protonation rate for the fluorinated monolayer as compared to 1-hexanethiol (Table 1, kb,R1H). Aiming to investigate the effect of negatively charged monolayers, we also experimented on a monolayer formed from solutions of 6-mercaptohexanoic acid. Unfortunately, in our hands, this monolayer presents voltammetric features even in the absence of methylene blue-modified DNA (Figure S11). Thus, we did not pursue these experiments further. However, the results presented so far demonstrate that methylene blue protonation, and the interactions of this proton with monolayer end groups, can dramatically affect the redox chemistry of DNA-bound methylene blue.

Figure 8

Figure 8. Electrode-blocking SAMs affect the protonation rate of the leucomethylene blue radical. After co-depositing 100 nM of the tobramycin aptamer and 1 mM either (A) 6-mercaptohexanol, (B) 1-hexanethiol, or (C) fluorinated analogue of 1-hexanethiol onto gold electrodes, we collected cyclic voltammograms at 1, 10, and 100 V·s–1 that we model with an accuracy of 85% or greater (Figure S9). We adjusted the starting concentration of species O to account for the smaller background-corrected peak currents of 6-mercaptohexanol when compared to 1-hexanethiol, which are a product of the removal of the charging current (Table 1). (34) We observe less peak splitting occurring in 6-mercaptohexanol, which can be explained by its nearly 2-fold higher average apparent protonation rate as compared with 1-hexanethiol (Table 1). However, we observe greater peak splitting occurring for the fluorinated monolayer, which can be explained by the nearly 3-fold decrease in apparent protonation rate as compared with 1-hexanethiol.

Table 1. Electrochemical and Equilibrium Parameters Corresponding to the Reduction of DNA-Bound Methylene Blue in the Presence of Different Monolayer Chemistries in Comparison to the Values Determined by Other Works
parameters6-mercaptohexanol1-hexanethiolfluorinated monolayerother works
k1° (s–1)124 ± 57417 ± 54143 ± 43k° = 80a
k2° (s–1)298 ± 208252 ± 196261 ± 197 
E1°′ (V)–0.30 ± 0.01–0.29 ± 0.00–0.31 ± 0.01 
E2°′ (V)–0.28 ± 0.02–0.29 ± 0.02–0.32 ± 0.01 
α10.57 ± 0.020.55 ± 0.000.49 ± 0.1 
α20.47 ± 0.120.41 ± 0.000.48 ± 0.06 
pKa7.00 ± 0.007.35 ± 0.037.30 ± 0.00∼7.4b
kb,R1H (m3 s–1 mol–1)5.01 × 107 ± 0.002.82 × 107 ± 0.000.97 × 107 ± 0.70 × 1072 × 108,c 4.5 × 108 ± 0.4 × 108,d
a

Reference (35).

b

Reference (30).

c

Reference (40).

d

Reference (39).

As demonstrated by the results presented in this work, methylene blue’s protonation equilibrium has a strong effect on E-AB signaling. For example, in prior work, we compared the signaling output of E-ABs functionalized with either 1-hexanethiol or 6-mercaptohexanol blocking monolayers. Doing so, we observed inverse signaling behavior between sensors functionalized with each of the two monolayers. (4) The results of this work (Table 1) now indicate that those differences in signaling are due, at least in part, to changes in proton interactions between methylene blue and monolayer end groups. The magnitudes of protonation rates reported in Table 1 are in the same order of those found by pulse photolysis from dilute solutions of methylene blue. (39,40) Thus, our numerical model represents an accurate, functional tool that will allow us to study and better understand electron transfer from DNA-bound methylene blue under various conditions of DNA sequence, blocking monolayer chemistries, and electrolyte pH. Note that Table 1 reports parameters used to fit voltammograms at pH = 7, corresponding to eqs 13. For equivalent parameters corresponding to eqs 23 and 24, we refer the reader to Table S6.

Conclusions

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We employed numerical simulations and CV to demonstrate that the voltammetric peak splitting observed in electrode-tethered, methylene blue-modified DNA at scan rates >10 V·s–1 originates from the protonation of a methylene blue radical. This peak splitting behavior limits the sensitivity and temporal resolution of ΔEP-based interrogation of E-ABs, which depends on the occurrence of single cathodic–anodic wave pairs. (18) However, by investigating the origin of this peak splitting behavior, we revealed that the rate of the electrochemical reduction of DNA-bound methylene blue can be a strong function of the extent of proton interactions with blocking monolayer end groups (Figure 8) and the DNA backbone (Figure 6E,F). These effects have been largely ignored in the field of E-ABs but could explain the dramatic changes in signaling behavior observed in sensors using varying aptamer secondary structures and monolayer chemistries; see, for example, ref (4).
Although we do not explore the position of methylene blue along the DNA chain in this work, it has been previously shown that internal placement of methylene blue causes a several-fold decrease in electron-transfer rates relative to identical constructs with the reporter at the 3′ terminus. (35) We now believe that this significant decrease in electron-transfer kinetics is caused by stronger hydrogen bonding interactions between methylene blue and the tail end of the DNA chain in internally modified oligonucleotides, which change the protonation rate of the radical intermediate. Therefore, a key result from this work is the increased understanding that methylene blue’s electron-transfer kinetics can be modulated by tuning the radical intermediate’s protonation rate, via either the positioning along the DNA chain, DNA secondary structure, and/or the chemical groups at the surface of blocking monolayer chemistries. We anticipate that similar effects are true for other redox reporters involving intermediate protonation steps, such as anthraquinone, nile blue, dabcyl, and others. (3)

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jpcc.1c00336.

  • Experimental and simulated voltammograms under various conditions; numerical data tables derived from simulated voltammograms; DNA sequences used in this work (PDF)

  • COMSOL Model file (ZIP)

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Author Information

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  • Corresponding Author
    • Netzahualcóyotl Arroyo-Currás - Chemistry-Biology Interface Program, Zanvyl Krieger School of Arts & Sciences, Johns Hopkins University, Baltimore, Maryland 21218, United StatesDepartment of Pharmacology and Molecular Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21202, United StatesDepartment of Chemical and Biomolecular Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United StatesInstitute for Nanobiotechnology, Johns Hopkins University, Baltimore, Maryland 21218, United StatesOrcidhttp://orcid.org/0000-0002-2740-6276 Email: [email protected]
  • Authors
    • J. D. Mahlum - Chemistry-Biology Interface Program, Zanvyl Krieger School of Arts & Sciences, Johns Hopkins University, Baltimore, Maryland 21218, United StatesOrcidhttp://orcid.org/0000-0003-0220-3058
    • Miguel Aller Pellitero - Department of Pharmacology and Molecular Sciences, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21202, United StatesOrcidhttp://orcid.org/0000-0001-8739-2542
  • Author Contributions

    J.D.M. built the numerical model and performed all simulations reported in this work. M.A.P. performed all experiments. N.A.C. collaboratively designed the experiments with J.D.M. and M.A.P. and supervised the development of the computational model. All authors contributed to the writing of this manuscript.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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We thank Johns Hopkins University School of Medicine for the startup funds provided in support of this work. Moreover, we thank the NIH for providing support in the form of a T32 training grant (GM080189) to support the graduate education of J.D.M. as part of the Chemistry–Biology Interface Program at Johns Hopkins University.

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The Journal of Physical Chemistry C

Cite this: J. Phys. Chem. C 2021, 125, 17, 9038–9049
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  • Abstract

    Figure 1

    Figure 1. Electrochemical reduction of methylene blue. This scheme uses the curved-arrow formalism to explain the electrochemical reduction of methylene blue according to the original mechanism proposed by Jean Chevalet. (13)

    Figure 2

    Figure 2. Description of the numerical model. (A) We created a one-dimensional model representing the DNA-functionalized electrodes of Figure 3A,B. (B) We simulate the voltammetric response of these electrodes by using a triangular voltage waveform with slope E·t–1, which corresponds to the voltage scanning rate. (C) In response to this varying potential, the experimental system (Figure 3A,B) produces a cyclic voltammogram (black trace) which varies in shape and magnitude according to the chemical equilibrium of the redox species considered. Our model accurately simulates the same voltammogram (red circles) via eqs 1017, 19, and 20. The surface DNA concentration was 1.93 ± 0.64 pmol·cm–2 here and in all figures of the article, unless noted otherwise. All voltammetric measurements were performed in 1× PBS as defined in the Methods section, unless noted otherwise.

    Figure 3

    Figure 3. Electrode-attached, methylene blue-modified DNA exhibits voltammetric features that change with increasing voltage scanning rate. (A) To illustrate these features, we employ DNA constructs of different lengths and secondary structures (Table S1), including one aptamer (illustrated here) that binds to the antibiotic tobramycin. We modify these constructs with a hexanethiol linker in the 5′ terminus and a methylene blue reporter at the 3′ terminus and co-deposit them onto gold electrodes along with 1-hexanethiol to form a SAM. (B) In the presence of tobramycin, the aptamer undergoes binding-induced conformational changes that accelerate electron transfer from methylene blue to the gold electrode, possibly by bringing methylene blue closer to the electrode surface. (C) When we interrogate aptamer-functionalized electrodes at scan rates ≤10 V·s–1 with surface coverage concentrations of 1.93 ± 0.64 pmol·cm–2 and either no tobramycin added or 1 mM of tobramycin, we observe no splitting of voltammetric waves. (D) However, at voltage scanning rates > 10 V·s–1, we observe splitting of the oxidation wave. Moreover, the addition of the target causes an inversion of behavior, showing peak splitting in the reduction but not in the oxidation wave. See the Methods section for additional experimental information.

    Figure 4

    Figure 4. Modeling the electrochemical reduction of DNA-tethered methylene blue at different voltage scanning rates. We recorded these background-subtracted cyclic voltammograms on gold electrodes functionalized with a 26-base DNA aptamer modified at one end with methylene blue (Figure 2A). As a model system, we co-deposit 500 nM of an aptamer that binds to the antibiotic tobramycin with 1 mM 1-hexanethiol. We then obtain cyclic voltammograms (black traces) in 1× PBS solution at voltage scanning rates of (A) 1, (B) 4, (C) 10, (D) 55, (E) 100, and (F) 150 V·s–1. Using the parameters described in Table S3 in our numerical model, we generate simulated voltammograms (colored circles) closely matching the experimental ones. We only show 1 in every 8 simulated currents for clarity. Error bars report the true differential error between experimental and simulated voltammograms. The color indicates percent error, which we use to demonstrate that our numerical model correctly estimates the current magnitude of the different voltammetric peaks with an accuracy of 85% or better; that is, ≤15% error (Figure S3).

    Figure 5

    Figure 5. High deposition concentrations of methylene blue cause peak broadening and increased overpotentials but do not affect peak splitting. To show that higher packing density of DNA-bound methylene blue at the surface of an electrode does not affect peak splitting, we co-deposited 1-hexanethiol and either (A) 100 nM, (B) 500 nM, (C) 1 μM, or (D) 25 μM of the tobramycin aptamer (Table S1) onto gold electrodes with resulting surface coverages of (A) 1.93 ± 0.64, (B) 2.24 ± 0.58, (C) 2.66 ± 0.45,, and (D) 4.61 ± 0.68 pmol·cm–2. We then measured voltammograms at a scanning rate of 100 V·s–1 and fit the data with an accuracy of 85% or better (Figure S6) using the parameters found in Table S4. We speculate that the wave broadening and 60 mV shift in formal reduction potential observed in electrodes prepared from solutions containing 25 μM DNA relative to those prepared at 100 nM are due to leucomethylene blue self-stacking (Figure 1B).

    Figure 6

    Figure 6. Voltammetric peak splitting is dependent on DNA secondary structure. We employed nucleotide sequences of (A) 10, (B) 20, (C) 26, (D) 37 nt, (E) tobramycin aptamer hybridized to a fully complementary strand, and (F) tobramycin aptamer in the presence of the target to test whether secondary structure affects peak splitting. Each of the constructs were co-deposited at 500 nM with 1 mM 1-hexanethiol onto gold electrodes and are modified with methylene blue at the distal terminus. All experiments were done in 1× PBS solution and experiments A–E were performed at 100 V·s–1, while experiment F was performed at 150 V·s–1. We report the theoretical secondary structures for each construct as generated by mfold software (Table S1). (34) Although all constructs exhibit peak splitting, we observe a reduction in this splitting with decreasing oligonucleotide length (A vs D). This is because, as the DNA shortens, the electron-transfer kinetics of the system increase as previously demonstrated. (35) We also observe a reversal in peak splitting behavior as a stable secondary structure is introduced (E for double-stranded DNA and F for a folded tobramycin-binding aptamer in the presence of 1 mM tobramycin). This is related to a change in protonation rate (Table S5) which suggests a change in hydrogen bonding interactions between methylene blue and the DNA. Error bars report the true differential error between experimental and simulated voltammograms. The color indicates percent error, which we use to demonstrate that each simulation fits the peak currents of background-subtracted voltammograms with an accuracy of 85% or better; that is, <15% error (Figure S7).

    Figure 7

    Figure 7. Chemical equilibrium explains the changes in voltammetric features observed at different values of pH. To illustrate this point, we measured cyclic voltammograms on DNA-functionalized electrodes (tobramycin-binding aptamer) immersed in 1× PBS at pH = 4, 7, and 9. For the low and high pH values, we potentiometrically titrated the buffered solutions with HCl or sodium hydroxide, respectively. As shown here, our model accurately predicts the position and current magnitude of the main voltammetric features in background-subtracted voltammograms with greater than 85% accuracy at all values of pH (Figure S8). However, we note that at pH = 9 and pH = 4, the mechanism changes from an ErCrEr (eqs 13) reaction to an ErEr (eqs 23 and 24) scheme, where electrochemical reduction no longer requires protonation. The latter mechanism is included in our numerical model. We use the parameters reported in Table S6 to achieve these fits. Error bars report the true difference error between experimental and simulated voltammograms. The color indicates percent error.

    Figure 8

    Figure 8. Electrode-blocking SAMs affect the protonation rate of the leucomethylene blue radical. After co-depositing 100 nM of the tobramycin aptamer and 1 mM either (A) 6-mercaptohexanol, (B) 1-hexanethiol, or (C) fluorinated analogue of 1-hexanethiol onto gold electrodes, we collected cyclic voltammograms at 1, 10, and 100 V·s–1 that we model with an accuracy of 85% or greater (Figure S9). We adjusted the starting concentration of species O to account for the smaller background-corrected peak currents of 6-mercaptohexanol when compared to 1-hexanethiol, which are a product of the removal of the charging current (Table 1). (34) We observe less peak splitting occurring in 6-mercaptohexanol, which can be explained by its nearly 2-fold higher average apparent protonation rate as compared with 1-hexanethiol (Table 1). However, we observe greater peak splitting occurring for the fluorinated monolayer, which can be explained by the nearly 3-fold decrease in apparent protonation rate as compared with 1-hexanethiol.

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  • Supporting Information

    Supporting Information


    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jpcc.1c00336.

    • Experimental and simulated voltammograms under various conditions; numerical data tables derived from simulated voltammograms; DNA sequences used in this work (PDF)

    • COMSOL Model file (ZIP)


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