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Aug 25, 2016 - ABSTRACT: Single molecule electrochemistry (SME) has gained much progress in fundamental studies, but it is difficult to use in practic...
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Reliable Digital Single Molecule Electrochemistry for Ultrasensitive Alkaline Phosphatase Detection Zhen Wu, Chuan-Hua Zhou, Liang-Jun Pan, Tao Zeng, Lian Zhu, Dai-Wen Pang, and Zhi-Ling Zhang* Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), College of Chemistry and Molecular Sciences, State Key Laboratory of Virology, Wuhan University, Wuhan 430072, People’s Republic of China S Supporting Information *

ABSTRACT: Single molecule electrochemistry (SME) has gained much progress in fundamental studies, but it is difficult to use in practice due to its less reliability. We have solved the reliability of single molecule electrochemical detection by integration of digital analysis with efficient signal amplification of enzyme-induced metallization (EIM) together with highthroughput parallelism of microelectrode array (MA), establishing a digital single molecule electrochemical detection method (dSMED). Our dSMED has been successfully used for alkaline phosphatase (ALP) detection in the complex sample of liver cancer cells. Compared to direct measurement of the oxidation current of enzyme products, EIM can enhance signals by about 100 times, achieving signal-to-background ratio high enough for single molecule detection. The integration of digital analysis with SME can further decrease the detection limit of ALP to 1 aM relative to original 50 aM, enabling dSMED to be sensitively, specifically and reliably applied in liver cancer cells. The presented dSMED is enormously promising in exploring physical and chemical properties of single molecules, single biomolecular detection, or single-cell analysis.

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Mirkin et al. proposed a similar technique by immersing a recessed Pt nanoelectrode in an Hg bath.11 Recently, Lemay et al. fabricated well-defined and reproducible nanochannels based on modern lithography techniques to realize redox cycling.12 Although redox cycling enables direct signal transduction, the application is limited by the nondeterministic Brownian motion, together with the difficulty in constructing two closed nanoelectrodes and the requirement of averaging over many redox events. The second category is to monitor the redox state of a single molecule in combination with fluorescence techniques.14−17 Bohn et al. studied single molecule spectroelectrochemistry of flavin adenine dinucleotide (FAD) based on zero-mode waveguides.17 The fluorescence of FAD is strong in oxidized form and negligible in reduced form, enabling fluorescence detection of single electron transfer event. By spectroelectrochemistry, single redox events can be detected with a high spatial resolution, but only partial redox molecules have alterable optical properties required for detection. In general, these previous experiments have demonstrated SME mostly at the proof-of-concept level and great attempts are desired to improve its reliability in practical application. The sensitivity of many developed signal-amplification strategies based on nanoparticles and enzymes18−21 could reach aM level,

ith the development of technology and methodology, the exploration of life and nature has gone into singlecell and single-molecule level,1,2 resulting in tremendous challenges for general analytical methods. In conventional experiments, the average behaviors of molecule assembly usually mask some key phenomena. Accurate and specific detection of single molecules, especially biomolecules such as DNA and proteins, may lead to breakthroughs in biological science and clinical medicine. Contrary to ensemble tests, single-molecule detection (SMD) can reveal the molecular heterogeneities, intermolecular reaction, physical and chemical characteristics at the single-molecule level.3−5 Since Rotman6 published the first paper of measuring the fluorescence of single β-D-galactosidase encapsulated in microdroplets in 1961, more and more SMD works have appeared with fluorescence,7 force microscope,8 and electrochemistry.5 Currently, fluorescence has been the most well-established and widely used technique in SMD. In 1995, Fan and Bard first proposed SME based on redox cycling,9 proving the possibility of detecting electrochemical signal from single molecules and made a great contribution to the development of SME. So far, SME has gained much progress and falls into two major categories. The first one is to detect the redox current of a single molecule by successive oxidation and reduction cycles.9−13 Fan and Bard used scanning electrochemical microscope to trap and sense single [(trimethylammonio)methyl]ferrocene molecule in a 10 nm gap between a Pt−Ir tip and an ITO ultramicroelectrode by redox cycling.9,10 After that, © XXXX American Chemical Society

Received: June 13, 2016 Accepted: August 25, 2016

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hydrochloric acid to strip off the unpatterned ITO portion and the rectangle MA with a width of 100 μm was fabricated. The photoresist on the ITO MA surface was washed away by ultrasonic rinsing in ethanol and soaked in piranha solution (7:3 v/v concentrated H2SO4/30% H2O2; Caution! The piranha solution should be handled with extreme care). After that, the microelectrodes were modified by Au nanoparticles through electrochemical deposition of gold chloride acid solution under constant potential of −0.1 V (vs Ag/AgCl). PDMS (10:1 w/w RTV615A/RTV615B) was added onto a silicon wafer and baked at 75 °C for 2 h. Then the solid PDMS was peeled off and punched with 1 mm diameter needle. A 10 × 10 individual Au MA with facile manufacture and controllable size was fabricated by simply covering a piece of PDMS with 100 holes on a MA pattern consisting of ten 100 μm width gold strips. Single ALP Detection by dSMED. First, ALP solution was diluted with pH 9.8 0.5 M diethanolamine (DEA) to the concentration of 20 aM and then mixed with the solution containing 1 mM p-APP and 100 μM AgNO3 to obtain different final concentrations of ALP. Each 0.5 μL solution was injected into the MA cells. The diameter, depth, and volume of each reactor are about 1 mm, 6.5 mm, and 5.1 μL, respectively. However, the reaction volume of each microelectrode was controlled by adding 0.5 μL enzyme solution rather than the volume of the reactor itself. The final enzyme concentration and reaction volume were controlled to be no more than one enzyme molecule per microelectrode. After incubation for 30 min at 37 °C and washing with ultrapure water, 5 μL 0.5 M KCl solution was added to the microelectrode with an Ag/AgCl wire as counter electrode and reference electrode to obtain silver stripping currents by linear sweep voltammetry (LSV) from −0.1 to 0.2 V with a 100 mV/s scanning rate. Finally, the current distribution of 500 microelectrodes under different ALP concentrations were recorded and the probabilities distribution of 500 microelectrodes (containing 0, 1, 2, or more enzyme molecules per microelectrode) were compared with the theoretical values of Poisson distribution to demonstrate the reliability of dSMED. In view of the amplification effect of EIM, 5 μL DEA buffer containing different concentrations of ALP and 1 mM p-APP was added to MA respectively. After reaction at 37 °C for 30 min, the LSV signals of p-aminophenol (p-AP) oxidation were obtained to compare with the signals achieved by EIM. Ultrasensitive ALP Detection in Liver Cancer Cells. To implement ALP detection in liver cancer cells, about ten thousand cells were collected and lysised by ultrasonic cell crusher followed by centrifuging 10 min with 10000 rpm to obtain 1 mL supernatant. Then each 0.5 μL supernatant with 1 mM p-APP and 100 μM AgNO3 was added to 500 microelectrodes. After reaction at 37 °C for 30 min, the 500 electrochemical signals were output as either “0” (containing 0 molecules) or “1” (containing at least 1 enzyme molecule) and then the ALP concentration in liver cancer cells could be calculated by the probability of “0” based on Poisson distribution and digital analysis.

providing the possibility for SME. For example, an electrochemical genosensor for miRNA was reported with an ultralow detection limit of 0.76 aM.19 However, the lack of reliable and reproducibly quantitative method has hampered SME from becoming a realistic tool suitable for complex systems.22 Sykes et al. recognized that the combination of limiting dilution, end-point PCR, and Poisson statistics could implement DNA detection,23 which was later known as digital PCR.24 Recently, digital analysis has been regarded as a reliable quantitative method in SMD of enzymes, cells, nanoparticles and rare mutants.25−29 In digital analysis, the output signals are denoted as “0” or “1” without considering the specific intensity of signals, where “0” represents the absence of target molecules and “1” stands for the presence of target molecules.30 The target concentration can be easily calculated from the probability of “0” using Poisson statistics, which can effectively avoid signal variations of single molecules, more suitable for small probability events in biological systems. The introduction of digital analysis is promising to improve the accuracy and reliability of SME in practical application. However, to date no report on combination of digital analysis and SME has appeared. To improve the reliability of SME, we propose a dSMED strategy based on integration of the high-sensitivity digital analysis with EIM capable of efficient signal amplification for single molecule detection. About 8 nA current can be obtained under single enzyme molecule conditions. The integration of digital analysis can not only decrease the current fluctuate influence of single molecules, but also solve the reliability of SME, facilitating its application in the complex sample of liver cancer cells. Owing to the popularity of enzyme-labeling, the presented dSMED strategy will make SME more suitable for practical application.



EXPERIMENTAL SECTION Materials and Reagents. Calf intestine alkaline phosphatase (ALP) was purchased from Sigma-Aldrich (St. Louis, MO). The p-aminophenyl phosphate monohydrate (p-APP) was purchased from Santa Cruz Biotechnology, Inc. Liver cancer Hep G2 and breast cancer MCF-7 cells were purchased from China Center for Type Culture Collection. AZ4620 positive photoresist and AZ400 K developer were obtained from AZ Electronic Materials (AZ Electronic Material Corp., U.S.A.). The poly(dimethylsiloxane) (PDMS) and curing agent were obtained from GE (GE Toshiba Silicones. Co., Ltd., Japan). All other chemical reagents were purchased from Sinopharm Chemical Reagent Co., Ltd. (Shanghai, China). All electrochemical assays were performed on a CHI660a electrochemical workstation (CH Instruments, Inc. Shanghai, China). Fabrication of 10 × 10 Individual Microelectrode Arrays. The MA was fabricated using traditional photoresist lithography with proper modification, as shown in Figure S1 in the Supporting Information. First, indium tin oxide (ITO) glasses were chosen as the substrates and put on the spin coater. Then the photoresist (AZ4620) was spin-coated on the surface of the slides with 600 rpm for 15 s followed by 2000 rpm for 30 s. Subsequently, the slides were put on the hot plate at 75 °C for 3 min and 105 °C for 5 min. A photomask with MA pattern was covered on the slide under UV source for 30 s. Then the photoresist was developed in an AZ developer (1:3 v/ v AZ400 K/H2O) followed by etching in the concentrated



RESULTS AND DISCUSSION Enzyme-Induced Metallization-Amplified Single Molecule Detection. Currently, although great advances have been achieved in SMD, SME is hampered by the difficulty of detecting a few electrons from single molecules. Some means of signal amplification are needed to increase the number of electrons passed per unit time (1.6 fA ≈ 104 electrons/s).31 B

DOI: 10.1021/acs.analchem.6b02284 Anal. Chem. XXXX, XXX, XXX−XXX

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Analytical Chemistry Here, single ALP detection was successfully realized based on the high-efficient signal amplification of enzyme-induced metallization (EIM), as shown in Figure 1A. ALP catalyzed

Figure 2. (A) Typical stripping curves of different solution compositions: (a) ALP + p-APP; (b) AgNO3 + ALP; (c) AgNO3 + p-APP; (d) AgNO3 + p-APP + ALP. (B) The current intensity under different ALP concentrations (0.001, 0.01, 0.02, 0.05, 0.1, 0.15, 0.2 fM) with three parallel tests, respectively.

Information). In the experiment, the buffer solution of pH 9.8 0.5 M DEA not only provided appropriate condition for ALP catalytic reaction but also prevented AgOH precipitate in alkaline condition by the complexation of amino and Ag+. Under optimizing conditions, currents increased with ALP concentrations and a good linear curve appeared from 0.05 to 0.2 fM with a detection limit of 50 aM (Figure 2B), indicating the possibility of single ALP detection. However, when the enzyme concentration is diluted to single molecule level, the random error of +1 or −1 molecule per microelectrode may have big influence on the amplification effect as well as electrochemical signals.28 Moreover, the activity heterogeneity of single enzyme molecules33−35 may further induce the instability of currents, greatly affecting the accuracy and reliability of SME in practical application. As shown in Figure 2B, the currents decreased in huge variability and only a part of microelectrodes achieved obvious electrochemical signals when ALP concentration was lower than 0.05 fM, revealing the big current fluctuation. The current fluctuate was further studied by recording the electrochemical signals of 50 parallel tests under different concentrations of 1, 20, and 50 aM (Figure S5, Supporting Information). Integration of Digital Analysis to Improve the Reliability of SME. The introduction of digital analysis can solve the current fluctuation and reliability problems of SME as signals are denoted as “0” (containing 0 molecules) or “1” (containing at least 1 enzyme molecule) (Figure 3A) without considering specific current intensities and then the target concentration can be calculated by the probability of “0”.36 In order to perform high-throughput parallel tests for digital analysis, a 10 × 10 individual MA was fabricated by simply covering a piece of PDMS with 100 holes on a MA pattern consisting of ten 100 μm width gold strips and the cyclic voltammetry (CV) of [Fe(CN)6]3‑/4‑ were obtained to demonstrate the uniformity of microelectrodes (Figure S6, Supporting Information). Without ALP, the average background was about 2 nA according to the current distribution of 500 microelectrodes (Figure S6D, Supporting Information). Under low concentrations of ALP, the electrochemical signals were denoted as “0” or “1” to avoid the influence of current fluctuation. By adding diluted enzyme solution into microelectrodes randomly, the resulting Poisson distribution will lead to microelectrodes containing 0, 1, 2, or multiple molecules whose probability can be calculated by Poisson law:

Figure 1. (A) Detection mechanism of single ALP. (B) The current intensity of (a) EIM and (b) direct oxidation of enzyme−product pAP. (C) Typical stripping signals in the presence of different ALP concentrations: (a) 0.05, (b) 0.2, (c) 0.5, (d) 0.7, (e) 1 fM.

its substrates p-APP to strong reduced p-AP and Ag+ was instantly reduced to Ag0 by p-AP since the half-wave potentials of p-AP and Ag+ (vs NHE) are 0.097 and 0.799 V, respectively. After appropriate deposition time, much Ag0 deposited on microelectrode array (MA) surface and obvious silver stripping signals were obtained by linear sweep voltammetry (LSV). Compared to the direct oxidation of p-AP, EIM could amplify electrochemical signals by about 100 times (Figure 1B). The main reasons are as follows: (1) The integration of EIM with silver stripping could dually amplify electrochemical signals and enhance the signal-to-background ratio; (2) ALP could catalyze substrate molecules at a high rate followed by silver deposition; (3) EIM could avoid the diffusion of enzyme products to the solution and accumulate much Ag0 on the microelectrode surface;32 (4) Au-plated MA could enhance EIM reaction and act as seeds for silver deposition to avoid the influence on enzyme activity (Figure S4, Supporting Information). As shown in Figure 1C, an apparent and stable electrochemical signal could also be detected even the concentration was down to 0.05 fM, providing the ability for single ALP detection when the reaction volume reached microliter level. Based on the efficient amplification of EIM, it was calculated that about 8.2 nA current could be obtained per ALP molecule (Figure S2, Supporting Information). In SME, an important issue is to control the background noise. In the presence of ALP and p-APP (a), AgNO3 and ALP (b), or AgNO3 and p-APP (c), the electrochemical signals were negligible indicating that p-APP or ALP alone was not easy to reduce Ag+ to Ag0. When AgNO3, ALP and p-APP existed at the same time, an obvious signal was obtained (Figure 2A), indicating the good specificity of ALP detection. Therefore, appropriate p-APP, AgNO3 and deposition time could keep rapid enzyme hydrolysis rate and obtain much Ag0 on microelectrode surface. The highest signal-to-background ratio could be obtained under the conditions of pH 9.8 0.5 M DEA, 1 mM p-APP, 100 μM AgNO3, 30 min deposition time and 20 s Au-plated time (Figure S3, Supporting

P(x = k) = C

λ k −λ e k!

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Figure 3. (A) Diagram of the MA and digital readout of electrochemical signals as “0” or “1”. (B) The current distribution of 500 microelectrodes under different single enzyme concentrations (1, 5, 10 aM). (C) The probability distribution of microelectrodes containing 0, 1, 2, or 3 enzyme molecules by experiment and Poisson distribution. (D) The transformation of 500 electrochemical signals to colorful balls through a MATLAB program.

analysis will well solve the influence of current fluctuation and enzyme heterogeneity of SME as signals are denoted as “0” (containing 0 molecules) or “1” (containing 1, 2, or 3 molecules) without considering specific current intensities. In order to simplify statistical process, 500 electrochemical signals were directly exported into a colorful imaging through a MATLAB program (Figure 3D). And the probabilities of “0” and “1” were easily calculated by counting the dark and bright balls. Kinetics Characteristics of Single ALP Molecules. The single enzyme reaction kinetics in microelectrodes was further studied based on the sensitivity and reliability of dSMED. First, enough ALP, p-APP, and relatively long reaction time can ensure adequate reduction of Ag+ to Ag0, obtaining a linear curve between electrochemical signals and Ag+ concentrations (Figure 4A). Under single enzyme conditions, the electrochemical signals increased with deposition time and the corresponding Ag0 amount could be indirectly calculated through the linear equation of Figure 4A. Then the relationship between Ag0 amount and deposition time could be obtained. As shown in Figure 4B, the Ag0 amount increased with the time up to 30 min and tended to the platform, agreeing with the above optimization result. Moreover, the relationship between Ag0 amount and time matched well with the relation of currents and time, which not only demonstrated the accuracy by dividing the microelectrodes according to their currents, but also ruled out

where x is the molecule number and λ is the average enzyme molecules per microelectrode.30 The λ was calculated to be 0.05, 0.25, and 0.5 corresponding to the enzyme concentration 1, 5, and 10 aM, respectively. For example, when λ = 1, the proportion of microelectrodes with 0 or 1 molecule is e−1 = 0.368; with 2 molecules is e−1/2 = 0.184; with 3 molecules is e−1/6 = 0.08. From the current distribution of 500 microelectrodes in Figure 3B, it was clear that big current fluctuation appeared at each concentration and at most 1 molecule occupied microelectrodes while many microelectrodes had no molecule at 1 aM. But the probabilities containing 1, 2, or multiple molecules increased with the ALP concentration. The 500 microelectrodes could be divided into four groups containing 0, 1, 2, and multiple enzyme molecules with the electrochemical signals of 1.8 ± 1.0, 8.0 ± 1.0, 11.7 ± 1.5 and 15.8 ± 1.5 nA respectively. Among them, 1.8 nA represents the background noise and 8 nA stands for the current intensity of single ALP molecules. As shown in Figure 3C and Table S1, the enzyme distribution by experiment matched well with theoretical results of Poisson distribution under different concentrations of ALP, indicating the feasibility of SME and the accuracy of integrating digital analysis. However, a little deviation existed possibly resulting from the heterogeneity of a single enzyme, which has been reported to vary as much as 10-fold.34 Based on the obvious signal-to-background ratio, the integration of digital D

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Figure 5. (A) Curve between average number of enzyme molecules per microelectrode (AEM) and original input ALP concentrations (inset: its corresponding linear relationship). (B) Histogram for the specificity of dSMED for ALP detection.

well as the mean relative standard deviation (RSD) of 3.45% (Table 1) indicated the reliability of dSMED in single ALP Figure 4. (A) Linear curve between electrochemical signals and Ag+ concentration. (B) Relationship of Ag0 amount and current intensities with deposition time. (C) The linear relationship between reaction rate reciprocal and Ag+ concentration reciprocal. (D) Current−time response curve of single ALP molecules.

Table 1. Reliability and Accuracy of dSMED in Single ALP Detection

the interference of background and further verified the accuracy of single ALP detection. Finally, the linear relationship between reaction rate reciprocal and enzyme product reciprocal could be achieved (Figure 4C). According to the Lineweaver−Burk equation: K 1 1 1 = m + V Vmax [S] Vmax (2)

λ0 NAV

20 14 10 5 3 1

0.364 0.498 0.605 0.780 0.860 0.950

mean λ0 mean C0a (aM) 1.011 0.697 0.502 0.249 0.151 0.051

20.22 13.94 10.04 4.98 3.02 1.02

RSD %b 2.81 2.62 4.21 4.51 1.42 4.93

Values represent the average ALP concentration of parallel samples (n = 3). bValues represent the standard deviation of parallel results (n = 3).

detection. However, digital analysis based on Poisson statistics was achieved at the cost of dynamic range as the linear curve was limited in a narrow range of 1−20 aM. The upper limit was mainly controlled by the deviation of digital readout. As the enzyme concentration was higher, multiple enzyme molecules would occupy each microelectrode35 and influenced the counting results. Some attempts had been paid to expand dynamic range by integrating digital analysis with ensemble detection effectively.26 The specificity of the developed dSMED for ALP detection was demonstrated by employing glucose (10 pM), urea (10 pM), ascorbic acid (20 fM), and thrombin (15 fM) as negative controls. As shown in Figure 5B, the AEM of ALP (20 aM) sample was obvious higher than negative controls. The average number of enzyme molecules per microelectrode (AEM) of ALP sample was calculated to be about 20-fold than negative samples even when their concentrations were 3−6 orders of magnitude more concentrated than ALP, indicating the high specificity of dSMED as well as its potential application in the complex matrix. Reliable dSMED Applied for ALP Detection in Liver Cancer Cells. The proposed dSMED based on the integration of digital analysis with SME has been proved to specifically and sensitively detect ALP. Ultrasensitive ALP detection in the complex sample was further implemented to demonstrate the accuracy and reliability of dSMED. Here, ALP was extracted from lytic liver cancer Hep G2 cells and breast cancer MCF-7 cells to perform digital analysis in 500 microelectrodes (Figure 6A). The electrochemical signals were transformed to a colorful imaging through a MATLAB program and the probability of “0” (dark balls) could be easily counted (Figure 6B). Compared to Hep G2 cells, the bright balls were negligible and many

(3)

Then the whole ALP concentration could be calculated according to the equation:

C0 =

mean Px=0

a

the Michaelis−Menten constant (Km) of ALP was calculated to be about 0.169 mM, which was similar to 0.15 mM by ensemble experiment.34 Moreover, the high uniformity of microelectrodes facilitated the study of dynamic characteristics of single enzyme molecules. As shown in Figure 4D, obvious activity variation appeared among single ALP molecules, demonstrating the heterogeneity of the enzyme.33−35 Digital Single Molecule Electrochemical Detection of ALP. The integration of digital analysis can solve the current fluctuation and reliability of SME, providing an accurate and reproducibly quantitative method for practical application. When x = 0, the deformation of eq 1 is as follows: λ 0 = −ln Px = 0

input concentration (aM)

(4)

where NA stands for the Avogadro constant (6.02 × 1023 mol−1) and V is the reaction volume in each microelectrode. Then the λ0 and C0 can be calculated by simply counting the probability of “0” microelectrodes. As shown in Figure 5A, inset, a linear relationship between the average enzyme molecules per microelectrode (AEM) and original input concentrations of ALP appeared from 1 to 20 aM with an ultralow detection limit of 1 aM, which could be regarded as the most sensitive method for ALP detection.32,37,38 Therefore, the integration of digital analysis further decreased the detection limit of ALP from 50 aM to 1 aM and greatly improved the sensitivity of SME in practical application. Moreover, the small error bars under three parallel tests at each concentration as E

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Figure 6. (A) Protocol for ALP detection in liver cancer cells. (B) Transformation of 500 electrochemical signals into a colorful imaging by a MATLAB program. (C) Histogram for the specificity of dSMED for ALP detection in liver cancer cells.

properties of single molecules, intermolecular interaction, single-cell assays, and early diagnosis of diseases.

microelectrodes had no enzymes for MCF-7 cells. The possible reason maybe that ALP is one of the most common biomarkers in clinical diagnosis as higher levels of serum ALP are usually correlated to several diseases such as bone diseases, liver cancer, and diabetes.39,40 Then the ALP concentration could be calculated by eqs 3 and 4 under different cancer cell numbers. The average ALP concentration in a single liver cancer cell was calculated to be about 12.1 aM, indicating dSMED could measure very low target concentrations or even a single molecule in complex samples sensitively. Moreover, no significant differences appeared among three parallel tests under different cancer cell numbers and the RSD was about 5.69% (Table S2, Supporting Information), further demonstrating the good reliability of dSMED. Sodium orthovanadate (Na3VO4) is a well-known inhibitor for ALP. The specificity and selectivity of dSMED in complex samples was evaluated by using Hep G2 cells and Na3VO4 mixture, and MCF-7 cells as negative controls. As shown in Figure 6C, only elevated ALP concentration was detected in Hep G2 cells, which may be a result of an underlying liver cancer or a premalignant state.41,42 Therefore, the integration of digital analysis can solve the reliability of SME effectively, demonstrating the potential clinical applicability of the proposed dSMED strategy.



ASSOCIATED CONTENT

* Supporting Information S

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.6b02284. Sections S.1−S.8, Figures S1−S6, and Tables S1−S2. Figure S1, fabrication of microelectrode arrays. Figure S2, enzyme-induced metallization-amplified single molecule detection. Figure S3, optimizing conditions of single ALP detection. Figure S4, preparation of Au-modified MA. Figure S5, current fluctuations at low concentrations. Figure S6, fabrication and characterization of Au MA. Table S1, integration of digital analysis to improve the reliability of SME. Table S2, ALP detection in liver cancer cells (PDF).



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: 0086-27-68756759. Fax: 0086-27-68754067.



Notes

The authors declare no competing financial interest.

CONCLUSIONS In summary, a novel dSMED strategy has been proposed to solve the reliability of SME based on the integration of digital analysis with EIM, which realized the application of SME in biological systems. EIM can amplify electrochemical signals by about 100 times compared with the direct oxidation of enzyme products, offering an efficient signal-amplification method for single molecule detection. The integration of digital analysis can solve the current fluctuation of SME and activity heterogeneity of single enzyme molecules, further decreasing the detection limit of ALP to 1 aM relative to original 50 aM. The accuracy and reliability of SME are greatly improved by the integration of digital analysis, enabling dSMED to be successfully applied in the complex sample of liver cancer cells, which has great promise in exploring the physicochemical



ACKNOWLEDGMENTS This work was supported by the 863 Program (2013AA032204), the National Natural Science Foundation of China (21475099, 21535005), the Fundamental Research Funds for the Central Universities (2042014kf0196), and the Natural Science Foundation of Hubei (2014CFA003).



REFERENCES

(1) Li, Y. T.; Zhang, S. H.; Wang, X. Y.; Zhang, X. W.; Oleinick, A. I.; Svir, I.; Amatore, C.; Huang, W. H. Angew. Chem., Int. Ed. 2015, 54, 9313−9318. (2) Dunevall, J.; Fathali, H.; Najafinobar, N.; Lovric, J.; Wigström, J.; Cans, A. S.; Ewing, A. G. J. Am. Chem. Soc. 2015, 137, 4344−4346. (3) Kim, J.; Bard, A. J. J. Am. Chem. Soc. 2016, 138, 975−979.

F

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Analytical Chemistry

(38) Wei, H.; Chen, C. G.; Han, B. Y.; Wang, E. K. Anal. Chem. 2008, 80, 7051−7055. (39) Ooi, K.; Shiraki, K.; Morishita, Y.; Nobori, T. J. Clin. Lab. Anal. 2007, 21, 133−139. (40) Zhang, Z.; Chen, Z.; Wang, S.; Cheng, F.; Chen, L. ACS Appl. Mater. Interfaces 2015, 7, 27639−27645. (41) Qian, Z. S.; Chai, L. J.; Huang, Y. Y.; Tang, C.; Shen, J. J.; Chen, J. R.; Feng, H. Biosens. Bioelectron. 2015, 68, 675−680. (42) Colombatto, P.; Randone, A.; Civitico, G.; Monti Gorin, J.; Dolci, L.; Medaina, N.; Oliveri, F.; Verme, G.; Marchiaro, G.; Pagni, R.; Karayiannis, P.; Thomas, H. C.; Hess, G.; Bonino, F.; Brunetto, M. R. J. Viral Hepatitis 1996, 3, 301−306.

(4) Liu, Z.; Ding, S. Y.; Chen, Z. B.; Wang, X.; Tian, J. H.; Anema, J. R.; Zhou, X. S.; Wu, D. Y.; Mao, B. W.; Xu, X.; Ren, B.; Tian, Z. Q. Nat. Commun. 2011, 2, 305−310. (5) Arán-Ais, R. M.; Yu, Y.; Hovden, R.; Solla-Gullón, J.; Herrero, E.; Feliu, J. M.; Abruña, H. D. J. Am. Chem. Soc. 2015, 137, 14992−14998. (6) Rotman, B. Proc. Natl. Acad. Sci. U. S. A. 1961, 47, 1981−1991. (7) Piatkowski, L.; Gellings, E.; van Hulst, N. F. Nat. Commun. 2016, 7, 10411−10419. (8) Neuman, K. C.; Nagy, A. Nat. Methods 2008, 5, 491−505. (9) Fan, F-RF.; Bard, A. J. Science 1995, 267, 871−874. (10) Fan, F-RF.; Kwak, J.; Bard, A. J. J. Am. Chem. Soc. 1996, 118, 9669−9675. (11) Sun, P.; Mirkin, M. V. J. Am. Chem. Soc. 2008, 130, 8241−8250. (12) Zevenbergen, M. A. G.; Singh, P. S.; Goluch, E. D.; Wolfrum, B. L.; Lemay, S. G. Nano Lett. 2011, 11, 2881−2886. (13) Byers, J. C.; Nadappuram, B. P.; Perry, D.; Mckelvey, K.; Colburn, A. W.; Unwin, P. R. Anal. Chem. 2015, 87, 10450−10456. (14) Palacios, R. E.; Fan, F-RF.; Grey, J. K.; Suk, J.; Bard, A. J.; Barbara, P. F. Nat. Mater. 2007, 6, 680−685. (15) Lei, C. H.; Hu, D. H.; Ackerman, E. Nano Lett. 2009, 9, 655− 658. (16) Zhang, G. F.; Xiao, L. T.; Chen, R. Y.; Gao, Y.; Wang, X. B.; Jia, S. T. Phys. Chem. Chem. Phys. 2011, 13, 13815−13820. (17) Zhao, J.; Zaino Iii, L. P.; Bohn, P. W. Faraday Discuss. 2013, 164, 57−69. (18) Zhao, Y.; Chen, F.; Li, Q.; Wang, L.; Fan, C. Chem. Rev. 2015, 115, 12491−12545. (19) Cheng, F.-F.; He, T.-T.; Miao, H.-T.; Shi, J.-J.; Jiang, L.-P.; Zhu, J.-J. ACS Appl. Mater. Interfaces 2015, 7, 2979−2985. (20) Wu, Z.; Zhou, C. H.; Chen, J. J.; Xiong, C.; Chen, Z.; Pang, D. W.; Zhang, Z. L. Biosens. Bioelectron. 2015, 68, 586−592. (21) de la Rica, R.; Stevens, M. M. Nat. Protoc. 2013, 8, 1759−1764. (22) Hoeben, F. J. M.; Meijer, F. S.; Dekker, C.; Albracht, S. P. J.; Heering, H. A.; Lemay, S. G. ACS Nano 2008, 2, 2497−2504. (23) Sykes, P. J.; Neoh, S. H.; Brisco, M. J.; Hughes, E.; Condon, J.; Morley, A. A. Biotechniques 1992, 13, 444−449. (24) Vogelstein, B.; Kinzler, K. W. Proc. Natl. Acad. Sci. U. S. A. 1999, 96, 9236−9241. (25) Rondelez, Y.; Tresset, G.; Tabata, K. V.; Arata, H.; Fujita, H.; Takeuchi, S.; Noji, H. Nat. Biotechnol. 2005, 23, 361−365. (26) Rissin, D. M.; Fournier, D. R.; Piech, T.; Kan, C. W.; Campbell, T. G.; Song, L.; Chang, L.; Rivnak, A. J.; Patel, P. P.; Provuncher, G. K.; Ferrell, E. P.; Howes, S. C.; Pink, B. A.; Minnehan, K. A.; Wilson, D. H.; Duffy, D. C. Anal. Chem. 2011, 83, 2279−2285. (27) Joensson, H. N.; Svahn, H. A. Angew. Chem., Int. Ed. 2012, 51, 12176−12192. (28) Paunescu, D.; Mora, C. A.; Querci, L.; Heckel, R.; Puddu, M.; Hattendorf, B.; Günther, D.; Grass, R. N. ACS Nano 2015, 9, 9564− 9572. (29) Obayashi, Y.; Lino, R.; Noji, H. Analyst 2015, 140, 5065−5073. (30) Guan, Z.; Zou, Y.; Zhang, M.; Lv, J.; Shen, H.; Yang, P.; Zhang, H.; Zhu, Z.; Yang, C. J. Biomicrofluidics 2014, 8, 014110−014123. (31) Oja, S. M.; Fan, Y.; Armstrong, C. M.; Defnet, P.; Zhang, B. Anal. Chem. 2016, 88, 414−430. (32) Zhou, C. H.; Zhao, J. Y.; Pang, D. W.; Zhang, Z. L. Anal. Chem. 2014, 86, 2752−2759. (33) Engelkamp, H.; Hatzakis, N. S.; Hofkens, J.; De Schryver, F. C.; Nolte, R. J. M.; Rowan, A. E. Chem. Commun. 2006, 935−940. (34) Craig, D. B.; Arriaga, E. A.; Wong, J. C. Y.; Lu, H.; Dovichi, N. J. J. Am. Chem. Soc. 1996, 118, 5245−5253. (35) Rissin, D. M.; Walt, D. R. J. Am. Chem. Soc. 2006, 128, 6286− 6287. (36) Rissin, D. M.; Kan, C. W.; Campbell, T. G.; Howes, S. C.; Fournier, D. R.; Song, L.; Piech, T.; Patel, P. P.; Chang, L.; Rivnak, A. J.; Ferrell, E. P.; Randall, J. D.; Provuncher, G. K.; Walt, D. R.; Duffy, D. C. Nat. Biotechnol. 2010, 28, 595−599. (37) Choi, Y.; Ho, N. H.; Tung, C. H. Angew. Chem., Int. Ed. 2007, 46, 707−709. G

DOI: 10.1021/acs.analchem.6b02284 Anal. Chem. XXXX, XXX, XXX−XXX