Iodide-Responsive CuâAu Nanoparticle-Based Colorimetric Sensor

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Iodide-responsive Cu-Au nanoparticles-based colorimetric sensor array for protein discrimination Hong Qiang, Xiangcong Wei, Qingyun Liu, and Zhengbo Chen ACS Sustainable Chem. Eng., Just Accepted Manuscript • DOI: 10.1021/ acssuschemeng.8b04235 • Publication Date (Web): 12 Oct 2018 Downloaded from http://pubs.acs.org on October 13, 2018

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ACS Sustainable Chemistry & Engineering

Iodide-responsive Cu-Au nanoparticles-based colorimetric sensor array for protein discrimination Hong Qiang,1† Xiangcong Wei,1† Qingyun Liu,2 Zhengbo Chen1* 1Department 2College

of Chemistry, Capital Normal University, Beijing, 100048, China

of Chemical and Environmental Engineering, Shandong University of Science and Technology,

Qingdao, 266590, China †These

authors contributed equally to this work

E-mail: [email protected] ABSTRACT: Here, for the first time, we present a colorimetric sensor array toward sensitive protein discrimination based on a novel strategy of diverse DNA-protein interactions with the performance of iodide-responsive Cu-Au nanoparticles (NPs). Different steric hindrance effects generated from differential interactions of DNA and proteins inhibit the accessibility of iodide to the NP surfaces, generating diverse colorimetric signals as “fingerprints” associated with each specific protein, which is subjected to linear discriminant analysis (LDA), a pluralistic statistic analysis technique for assignment of unknown samples to their suitable categories and data classification, to generate a clustering map. On the basis of the LDA analysis, eight proteins with a concentration of 20 nM in pure aqueous buffer and in real serum samples were successfully discriminated with 100% accuracy. KEYWORDS: Non-specific DNA; Sensor array; Cu-Au nanoparticles; Colorimetric; Protein discrimination

INTRODUCTION The development of fast, portable, and sensitive sensing techniques for discrimination of various proteins is very important in early clinical diagnosis and treatment.1-3 However, traditional sensors with ACS Paragon Plus Environment

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“lock-key” sensing mode always requires highly selective and specific binding receptors for each analyte and tedious synthetic procedures.4 In contrast, optical sensor arrays, in addition to possessing optical advantages,5-7 they are similar to the mammalian olfactory or gustatory systems,8-10 utilizing a set of non-specific sensing elements to produce a distinctive optical “fingerprint” after binding with each target protein.11-13 Highly specific receptors in sensor arrays are non essential, and therefore, the design and fabrication of the receptors of sensor array is more labor- and time-saving. Recently, many efforts have been devoted to develop optical sensor arrays, especially and colorimetric and fluorescent sensor arrays, to identify proteins. Fan, Chunhai group presented a graphene-based fluorescence sensor array for protein discrimination using DNA modified with 6carboxyfluorescein as receptors.14 Zhang, Xinrong et al. synthesized five AuNPs as receptors to construct a fluorescent sensor array for discrimination of proteins.15 Wang, Jianhua et al. developed a fluorescent sensor array based on ionic liquid-quantum dots as receptors for discrimination of proteins.16 Yeung et al. developed fluorescent sensor array for protein discrimination based on gold nanodots.12 These fluorescent sensor arrays, with advantages of strong discriminatory power and excellent sensitivity, however, tedious and taxing synthesis of fluorescent materials and photobleaching limit their utilization for on-site discrimination of proteins. In comparasion with fluorescent sensor arrays, colorimetric sensor array technology with the strengths of rapid response, simpleness, and visual detection, has been proven to be a strong analytical technique for the identification of multiple analytes.17-25 Nevertheless, the application of many sensor arrays is hindered by the difficulties of molecular designing and chemical synthesis and of identification elements. The combination of nanoparticles with nonspecific or specific DNA may address this issue to the development of extensible sensor arrays. Even a very short DNA chain with 15 bases, which consists of only A, T, C, and G bases, has billions of combinations,26 nonspecific DNA sequence can provide unlimited recognition elements that can be utilized to map delicate biomolecular interaction and discriminate closely similar analytes. The use of nonspecific DNA as sensing elements of sensor array for protein discrimination has been developed recently.14,19,27,28 Furthermore, the highly specific interaction between I- and Cu-Au nanoparticles (CuACS Paragon Plus Environment

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Au NPs)Cu-Au NPs induces gray-to-red color change, and different binding affinities between DNA and target proteins cause diverse steric hindrance on the surface of Cu-Au NPs. Inspired by these finding, herein, a highly sensitive colorimetric sensor array for protein discrimination was presented, which uses three nonspecific DNA with modification of thiol-functionalized Cu-Au NPs as receptors to identify various proteins. 8 proteins featuring different charge and size, including egg white albumin (EA), hemoglobin (Hem), Pepsin (Pep) 1:3000, bovine serum albumin (BSA), myoglobin (Myo), cytochrome c (Cyt-C), trypsin (Try), and concanavalin (Con), were chosen as targets to test the array’s performance. The core of the sensing strategy lies in that different interactions of proteins with DNAfunctionalized Cu-Au NPs can inhibit the accessibility of I- to the surfaces of NPs to varying degrees, leading to a color change in solutions with the reaction substrate (iodide ions). The responses can be observed with bare eyes and read with the UV-vis spectrometer. Linear discriminant analysis (LDA) was utilized to process the absorbance values, and LDA plots were formed for a clear discrimination of these proteins.

EXPERIMENTAL SECTION Materials. HAuCl4 ·3H2O, CuSO4, NaBH4, trisodium citrate, egg white albumin (EA), hemoglobin (Hem), pepsin (Pep) 1:3000, bovine serum albumin (BSA), myoglobin (Myo), cytochrome c (Cyt-C), trypsin (Try), and concanavalin (Con) were purchased from Sigma-Aldrich. 5’-SH-TTT TTT TTT TTT TTT-3’ (15T), 5’-SH-CCC CCC CCC CCC CCC-3’ (15C), and5’-SH-AAA AAA AAA AAA AAA-3’ (15A) were purchased by Sangon Biotech (Shanghai) Co., Ltd.. Instrumentation. UV-vis spectra were measured with a UV-2550 Spectrophotometer and processed using OriginLab software (Shimadzu Corporation). Trans-mission electron microscope (TEM) images were obtained by a Hitachi (H-7650, Japan) transmission electron microscope at an acceleration voltage of 80 kV. Preparation of and DNA Functionalization of Cu-Au NPs. Cu-Au NPs were synthesized by the reduction reaction between HAuCl4 and CuSO4 in the existance of sodium citrate and NaBH4.29 Briefly, 75 μL of CuSO4 (0.1 M) and 50 μL of sodium citrate (0.1 M) were injected to 20 mL deionized water at

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room temperature. Subsequently, 1 mL of NaBH4 (3.8 mg in 4 mL H2O) was added to the mixed solution quickly. After 15 minutes of reaction, 50 μL of HAuCl4 solution (0.1 M) was added, and kept vigorous stirring for 15 min. The final NP solution was stored at 4°C prior to further use. The size, morphology, and structural composition of the NPs were characterized by TEM, and HRTEM images. As shown in Fig. 1A, we observed that the prepared NPs were chain like and nonspherical. HRTEM image shows a clear lattice fringe (Fig. 1B), indicating that chains of Cu-Au NPs were formed. To investigate the dispersion stability of chain of NPs in aqueous solution, the NPs were found to remain 93.7% of the original absorbance value after 30 days’ storage at 4 °C, which indicates that the NPs possessed high stability. To prepare DNA-functionalized Cu-Au NPs, the 800 μL of NP solution 20 μL of 5’-SH-DNA solution (1μM) were mixed thoroughly. After incubation for 24 h, DNA-functionalized NP solution was centrifuged at 10 000 rpm for 10 min and then redispersed in Tris-HCl buffer (pH 7.4). (Figure 1) Sensing Procedure. For the discrimination of target proteins, firstly, 820 µL of DNA functionalizedNP solution and with 40 µL of proteins (final concentration: 20 nM) were mixed. After incubation of 30 min at 37 °C, 20 µL of I- (40 μM) was injected to the above mixture for incubation of 25 min. Afterward, the array’s responses were obtained by the absorbance, and the variations of absorbance intensities (A520 nm/A550 nm)

were recorded as the signal output.

RESULTS AND DISCUSSION Sensing Principle. In this strategy, three non-specific SH-DNA strands (SH-A15, SH-C15, and SHT15) were individually functionalized with Cu-Au NPs via the formation of Au-S bonds. It is well known that Zhang group,29 Cheng group,30 Wang group,31 and our group32,33 all demonstrated the occurrence of highly specific interaction between I- and Cu-Au NPs produce an obvious color change (gray → red) of the Cu-Au NP solution through the transformation from the chain like NPs to the separated and almost spherical ones (Fig. S1). With target proteins, I- can easily be adsorbed on the surfaces of DNA-functionalized NPs due to the negligible steric hindrance and reacts with NPs, causing that the chain of Cu-Au NPs was destroyed, and NPs changed from interconnected chains to spherical


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ones.29-33 Whereas in the presence of target proteins, differential interactions between DNA and target proteins caused different steric hindrance, and affected the approach of iodide ions to the surfaces of the Cu-Au NPs to varying degrees, leading to obvious alteration in absorbance responses and color (Scheme 1). Discern pattern was produced with colorimetric signals provided by the specific interaction between NPs and I- before and after the addition of proteins. To further explore the discrimination mechanism of the sensor array, we used TEM images to characterize the I--responsive NPs in the absence and presence of proteins (here Hem and BSA were used as a model). As shown in Fig. 2, it is clearly shown that without target proteins, Cu-Au NPs are nearly separated and spherical due to the easy accessibility of I- to the surfaces of NPs. Whereas interconnected and irregularly shaped to different degrees after addition of proteins, mainly because that differential interactions of analyte proteins with Cu-Au NPs formed steric hindrance and affected the accessibility of iodide ion to the NP surface to diverse extents. (Scheme 1) (Figure 2) Optimization of Iodide Ion Concentration. Iodide ion can cause an obvious purple to red change of the Cu-AuNP solution from by converting the chain like nanoparticles to the separated and nearly spherical ones.29-31 Inspired by the gratifying phenomena, we investigated the effect of iodide concentrations as a critical factor on the array’s responses. As displayed in Fig. S2(A,B), with the increase of iodide from 0 to 40 μM, the absorption peak shifted negatively from 550 to 520 nm. At 40 μM, the absorbance value (A520

nm/A550 nm)

kept stable with the maximum value, indicating that the

reaction between Cu@Au NPs and iodide reached the saturation. Thus, 40 μM was the optimal Iconcentration. Solution pH is the other improtant factor affecting the array’s performance. As shown in Fig. S2C, when pH value was 7.40, the A520

nm/A550 nm

reached the maximum. Thus, pH=7.40 was

selected as the optimal solution pH. Discrimination of Proteins by LDA. Three different nonspecific DNA strands (A15, C15, and T15) were used as receptors to bind different proteins. As depicted in Fig. 3B and Fig. S3, in the presence of different proteins, the K/K0 values generated by various proteins were different, indicative of the ACS Paragon Plus Environment

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likelihood of protein discrimination using the sensor array. The diverse and unique colorimetric responses to each of proteins could be utilized as a “fingerprint” map for protein discrimination. The color photos before and after the addition of target proteins are displayed in Fig. 3A. As seen from the color maps of the protein solutions extracted through Phtoshop software, the obvious color differences are observed. To further explore the array’s response pattern against diverse proteins, LDA was used to convert a set of observations that may be related to a set of linearly irrelevant variables, and two factors can be visualized in a two-dimensional (2D) plot. It can be clearly seen from Fig. 3C, five replicates were conducted for each target protein, and the 120 raw data matrix (3 DNA receptors × 8 proteins × 5 replicates) (Table S1) was processed using LDA to produce two factors (95.4 and 4.6%). The most important discrimination factors (factor 1 and factor 2) were present in a 2D plot where all target proteins at a 20 nM concentration level were separated from each other, indicative of the excellent separating capability of the DNA functionalized Cu-Au NPs based sensor array. The relative standard deviations (RSDs) for results from the sensor array for each protein are listed in Table S2, which show that the sensor array exhibited excellent reproducibility (RSDs < 5.98%, n = 5). In comparasion with other sensor arrays based on NPs for protein discrimination (Table S3), the sensor array we proposed possessed comparable or more excellent sensitivity. The response from only two sensing elements provides reasonable differentiation: 15A+15C, 15A+15T, and 15C+15T can differentiate the eight proteins with 97.5%, 92.5%, and 98.2% accuracy, respectively. It is noteworthy that by the use of the mixture of the three DNA (15A+15C+15T), the sensor array could detect and identify eight proteins with 100% accuracy (Fig. 4). (Figure 3) (Figure 4) To explore the resolving ability of the sensor array, we investigated whether the sensor array can discriminate varying concentrations of proteins, quantification of BSA was taken as an example. It is noteworthy that because factor 1 was 96.9% (Fig. 5A), we may use factor 1 to detect BSA. A good linear dependence between factor 1 and of BSA concentrations ranging from 0.1 to 50 nM was observed (Fig. 5B), revealing that the DNA-protein interactions were stable and homogeneous, and the assay was ACS Paragon Plus Environment

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highly reproducible. The training matrix of the sensor array against BSA expanding form 0.1 nM to 50 nM is depicted in Table S4. The linear dependence between factor 1 and other proteins with varying concentrations is displayed in Fig. S4. (Figure 5) Identification of the Mixtures (BSA and Hem). After successful identification of the 8 proteins, further experimental results showed that the discrimination ability of the sensor array was highly effective in the identification of protein mixture, as illustrated by the discrimination of 20 nM mixture of BSA and Hem (i.e., Hem 100%, Hem 75%-BSA 25%, Hem 50%-BSA 50%, Hem 25%-BSA 75%, and BSA 100%) (Table S5). Fig. 6 indicates that all five protein mixtures were visually separated and tightly grouped in the LDA plot. Interestingly, the identification accuracy of the sensor array was 100%. (Figure 6) Protein Identification in Serum Samples. To test the identification performance of the sensor array in detecting complex samples, human serum was tested (Table S6). Prior to measurement, the serum samples obtained from the General Hospital of the People's Liberation Army (Beijing, China) were first filtered with 0.22 μM nitrate cellulose membrane. And then, the serum samples was diluted 50-fold by 20 mM Tris-HCl buffer (pH 7.40). The colorimetric response profiles of various proteins, spiked to serum samples (final concentration: 200 nM), are shown in Fig. 7A. The combined colorimetric patterns of the sensors were subjected to LDA analysis (Fig. 7B), and eight proteins were well-clustered and discriminated thoroughly from each other in the 2D canonical score plot. Notably, similar array’s responses for serum, serum plus BSA, and serum plus Cyt-C were observed, presumably owing to complex components, such as electrolytes, phosphates, and proteins, in serum samples. (Figure 7)

CONCLUSION To sum up, we have developed a simple and sensitive colorimetric sensor array strategy for detection and discrimination of proteins. The sensing principle of the sensor array is dependent upon different steric hindrance effects formed by diverse DNA-protein interaction and iodide-responsive Cu-Au NPs.


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Classification analysis (LDA) was employed to test the identification ability of the sensor array, eight proteins including Try, Hem, Pep, EA, Cyt-C, Con, BSA, and Myo in tris buffer were successfully identified at 20 nM level with 100% accuracy. In order to confirm the real application performance, 8 proteins was discriminated in human serum samples with 100% accuracy.

ACKNOWLEDGEMENTS The support of this research by the Scientific Research Project of Beijing Educational Committee (Grant No. KM201710028009), Capacity Building for Sci-Tech Innovation-Fundamental Scientific Research Funds (Grant No. 025185305000/195), and Youth Innovative Research Team of Capital Normal University, was gratefully acknowledged.

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Scheme 1 Schematic illustration of the design and fabrication process of the single-channel colorimetric sensor array for the discrimination of proteins. Fig. 1 (A) TEM image, and (B) HRTEM image of the Cu-Au NPs. Fig. 2 Representative TEM images of the Cu-Au NPs after interaction with iodide ion in the absence and presence of 20 nM proteins. Fig. 3 (A) Digital photographs of the solutions in the absence (named “before”) and presence (named “after”) of proteins. The color is extracted from photograph of the solution color using Phtoshop software. (B) Fingerprints of eight proteins based on the colorimetric response patterns of the sensor array against the eight proteins at 20 nM. (C) Canonical score plot for the discrimination of the eight proteins at 20 nM based on the sensor array. Experimental conditions: concentration of Cu-Au NP solution: 20 nM, DNA concentration: 1μM, I- concentration: 40 μM, incubation time of BSA: 30 min, incubation of I-: 25 min. Fig. 4 Canonical score plot for the sensor array against 20 nM protein in the presence of (A) 15A+15C, (B) 15A+15T, (C) 15C+15T, and (D) 15A+15C+15T. (E) Jackknifed classification matrix obtained using LDA based on 15A, 15C, and 15T as sensing elements for the discrimination of eight proteins. Experimental conditions: concentration of Cu-Au NP solution: 20 nM, DNA concentration: 1μM, Iconcentration: 40 μM, incubation time of BSA: 30 min, incubation of I-: 25 min. Fig. 5 (A) Canonical score plot for the colorimetric response patterns obtained with the sensor array against BSA at 0.1, 30 nM, 40 nM, and 50 nM; (B) The linear relationship between factor 1 and the concentrations of BSA in the range from 0.1 to 50 nM. Experimental conditions: concentration of CuAu NP solution: 20 nM, DNA concentration: 1μM, I- concentration: 40 μM, incubation time of BSA: 30 min, incubation of I-: 25 min. Fig. 6 Canonical score plot for the sensor array against 20 nM protein mixtures with various BSA/Hem molar ratios. Experimental conditions: concentration of Cu-Au NP solution: 20 nM, DNA concentration: 1μM, I- concentration: 40 μM, incubation time of BSA: 30 min, incubation of I-: 25 min. Fig. 7 (A) Colorimetric responses of the single-channel sensor array to eight proteins (all at 0.2 μM), in which K and K0 represent the UV adsorption (K=OD520 nm/OD600 nm) of the Cu-AuNPs in the presence ACS Paragon Plus Environment

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and absence of the target proteins, respectively; (B) Canonical score plot for the discrimination of the proteins in serum samples based on the colorimetric signal changes of the sensor array. Experimental conditions: concentration of Cu-Au NP solution: 20 nM, DNA concentration: 1μM, I- concentration: 40 μM, incubation time of BSA: 30 min, incubation of I-: 25 min.


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Scheme 1


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Fig. 1


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Fig. 2


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Fig. 3


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Fig. 4


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Fig. 5


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Fig. 6


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Fig. 7


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For Table of Contents Use Only A colorimetric sensor array for protein discrimination based on diverse DNA-protein interactions with the performance of iodideresponsive Cu-Au nanoparticles


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Iodide-Responsive CuâAu Nanoparticle-Based Colorimetric Sensor

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