Visual colorimetric sensor array for discrimination of antioxidants in serum using MnO2 nanosheets triggered multicolor chromogenic system

Author’s Accepted Manuscript Visual colorimetric sensor array for discrimination of antioxidants in serum using MnO2 nanosheets triggered multicolor chromogenic system Wei Huang, Yuequan Deng, Yi He www.elsevier.com/locate/bios

PII: DOI: Reference:

S0956-5663(16)31256-8 http://dx.doi.org/10.1016/j.bios.2016.12.028 BIOS9421

To appear in: Biosensors and Bioelectronic Received date: 10 September 2016 Revised date: 27 October 2016 Accepted date: 12 December 2016 Cite this article as: Wei Huang, Yuequan Deng and Yi He, Visual colorimetric sensor array for discrimination of antioxidants in serum using MnO2 nanosheets triggered multicolor chromogenic system, Biosensors and Bioelectronic, http://dx.doi.org/10.1016/j.bios.2016.12.028 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Visual colorimetric sensor array for discrimination of antioxidants in serum using MnO2 nanosheets triggered multicolor chromogenic system Wei Huanga, Yuequan Denga, Yi Heb* a

School of Materials Science and Engineering, Southwest University of Science and

Technology, Mianyang, 621010, P. R. China. b

School of National Defence Science & Technology, Southwest University of Science

and Technology, Mianyang, 621010, P. R. China. *

Corresponding

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6089885;

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Abstract Here we report a unique visual colorimetric sensor array for discrimination of antioxidants in serum based on MnO2 nanosheets-3,3',5,5'-tetramethylbenzidine (TMB) multicolor chromogenic system. The absorbance values of the system at 370, 450, and 650 nm provide three cross-reactive sensing elements. The presence of antioxidant will inhibit the reaction between TMB and MnO2 nanosheets due to the presence of the competitive reaction of MnO2 nanosheets and antioxidants. Different antioxidants containing uric acid, glutathione, ascorbic acid, cysteine, and melatonin have distinct reducing ability, producing a differential inhibition of MnO2 nanosheets-TMB system, and therefore generating distinct colorimetric response patterns at 370, 450, and 650 nm. The obtained patterns for each antioxidant at a concentration of 20 μM were successfully discriminated using principal component analysis both in buffer and when spiked into fetal bovine serum (FBS). The identification accuracy of 45 unknown samples was found to be 100%. Remarkably, this sensor assay can visually discriminate antioxidants in diluted FBS with the naked eye.

Graphical abstract

Keywords: antioxidants; sensor array; MnO2 nanosheets; visualization; discrimination

1. Introduction Oxidative stress reflects an imbalance that occurs when the generated reactive oxygen species (ROS) exceed the antioxidant capacity in a biological system (Chandra et al., 2015). Oxidative stress can damage all components of the cell (proteins, DNA, and lipids), resulting in various diseases including cancers, cardiovascular diseases, and neurodegenerative diseases (Hu et al., 2014). To mitigate such oxidative damage, living organisms maintain complex systems of antioxidants. Uric acid (UA) is the highest concentration antioxidant in human blood, and it provides over half of the total antioxidant capacity (Sautin and Johnson 2008). It is demonstrated that high levels of UA can lead to gout and Lesch-Nyhan syndrome. The lack of ascorbic acid (AA) will cause scurvy (Zhu et al. 2015). And an abnormal level of cysteine (Cys) has been linked to liver damage and cardiovascular disease (Zong et al. 2014). Also, melatonin (Mel) may regulate sleep, and a low level of Mel is also associated with various cancers (Lee et al. 2013). Other antioxidants such as glutathione (GSH) have also played a key role in metabolic processes. Accordingly, development of simple, facile, and reliable methods for detection of antioxidants in serum is of great importance to medical diagnosis. Traditional analytical techniques such as high performance liquid chromatography (HPLC), surface-enhanced Raman scattering (SERS), and electrochemistry have been

reported for detection of various antioxidants (Huang et al., 2009; Matemadombo et al., 2012; Mateos et al., 2005). However, most of them require expensive instrumentation and laborious sample pre-treatment process. In order to overcome these problems, new materials-based sensors for antioxidants, such as gold nanoclusters (Hu et al., 2014), ceria nanoparticle (Sharpe et al., 2013), upconversion nanoparticles (Zhai et al., 2013), MIL53(Fe) (Lu et al., 2015), and gold nanoparticles (Andreu-Navarro et al., 2011), have been widely developed, which provide a facile and low-cost approach for detection of antioxidants. Nevertheless, these sensors only determine a single antioxidant, which do not allow high-throughput detection. Besides, they are lack of good selectivity among the antioxidants owing to their similar chemical properties, which can not differentiate various antioxidants or antioxidant mixtures with different compositions. Array-based sensing approaches using nanomaterials have emerged as a powerful tool for discrimination of a variety of analytes with similar structure and properties, for example, explosives (Peveler et al., 2015), proteins (He et al., 2014; Lu et al., 2013; Pei et al., 2012; Xu et al., 2014; You et al., 2007; Yuan et al., 2015), metal ions (Sener et al., 2014), pesticides (He et al., 2015; Qian and Lin 2015), thiols (Lei et al., 2016), and toxic gases (Zhang et al., 2016). This technology employs cross-reactive sensing elements to produce unique response patterns to each analyte, which is further employed for discrimination and identification of various analytes with the help of statistical analysis. However, nanomaterials-based sensor arrays for antioxidants have not been reported to date. In this study, we proposed use of MnO2 nanosheets triggered multicolor chromogenic system for discrimination of antioxidants. In the colorimetric sensor array, MnO2 nanosheets are used for oxidizing 3,3',5,5'-tetramethylbenzidine (TMB) solution to yield blue, green, and yellow colors and different absorption wavelengths with different absorbance values as sensing elements. The system responses to a range of antioxidants though the redox reaction between MnO2 nanosheets and antioxidants, leading to absorbance value decrease at different wavelengths to create analytical patterns to each antioxidant. The sensor array is tested against five water-soluble serum antioxidants, UA, GSH, AA, Cys, and Mel. It was also employed to identify 45 unknown samples with an accuracy of 100 % and differentiate antioxidant mixtures. Finally, the colorimetric sensor array was applied for discrimination of five selected antioxidant in real serum sample to

demonstrate the potential application.

2. Experimental section 2.1. Materials UA, GSH, AA, Cys, and Mel were purchased from Sangon Biotech (Shanghai) Co., Ltd. TMB, hydrogen peroxide (30 wt%), manganese (II) chloride tetrahydrate, and tetramethylammonium hydroxide were obtained from Aladdin (Shanghai, China). Fetal bovine serum was purchased from Sinopharm Chemical Reagent Co., Ltd (Shanghai, China). All the materials were of analytical grade and used as received. 2.2. Instrumentation The morphology of MnO2 nanosheets was characterized by a HT7700 transmission electron microscopy (TEM). All absorption spectra were recorded with a Shimadzu spectrophotometer (UV-1800, Japan). 2.3. Procedures for colorimetric array sensing of antioxidants MnO2 nanosheets were prepared by literature methods (He and Zhang 2016). Briefly, MnO2 nanosheets dispersion (0.6 mL, 0.06 mg/mL) and antioxidants with different concentrations or water were added to a 5 mL glass bottle and the mixture was brought to 3 mL with Britton-Robinson (BR) buffer (pH 2.8) solution. Then, 0.5 mL TMB (0.5 mM) solution was injected into the above mixture. After incubation for 15 min at room temperature (25 °C), the ultraviolet-visible (UV-vis) absorption spectra of the mixture were recorded, and the absorbance values at 370, 450, and 650 nm were employed for discriminating different antioxidants. This process was repeated for the five antioxidant analytes to obtain five replicates of each. Therefore, the five antioxidants were tested against the three absorbance values five times to give a 5 antioxidants × 3 absorbance values × 5 replicates training data matrix. The obtained training data matrix was analyzed using principal component analysis (PCA), and the confidence ellipses were performed on Matlab (Version 8.0). 2.4. Unknown identification For detection of unknown analyte concentrations, 45 unknown antioxidant solutions were prepared by three separate researchers. The absorbance values at 370, 450, and 650 nm were repeatedly measured five times used to produce the training data matrix. The average absorbance values of three replicates for a single unknown antioxidant were

analyzed with five known antioxidants in the PCA. 2.5. Real sample analysis To evaluate the potential applicability of this colorimetric sensor array in real samples, discrimination of antioxidants was carried out in fetal bovine serum. The serum samples was diluted 10-fold with BR solution (pH 2.8), and then spiked with 20 μM of the selected five antioxidants. The spiked serum samples were analyzed by the same procedure as described above.

3. Results and Discussion 3.1. Fabrication and principle of visual colorimetric sensor array Fig. 1 illustrates the principle of visual colorimetric sensor array. TMB is a popular chromogenic substrate used in enzyme-linked immunosorbent assays because it can be oxidized to TMB radical cation and the charge-transfer complex of the diamine (blue color) with a strong absorption peak at 650 and 370 nm, and TMB diamine (yellow color) a strong absorption peak at 450 nm by horseradish peroxidase- H2O2 system (Josephy et al., 1982). The intermediate state consisting of initial blue product and final yellow product displays a green color (Josephy et al., 1982). On the other hand, MnO2 nanosheets have a strong oxidation ability (Zhai et al., 2014). The addition of MnO2 nanosheets will induce the oxidation of TMB, generating multicolors with different absorption peaks at 370, 650, and 450 nm dependent on the concentration of MnO2 nanosheets. However, the presence of antioxidants will inhibit the reaction between MnO2 nanosheets and TMB, and the absorbance values at 370, 650, and 450 nm will change. Hence, the absorbance values at 370, 450, and 650 nm (A370, A450, and A650) can be considered as three cross-reactive sensing elements for fabrication of visual colorimetric sensor array. The different reduction capacity of various antioxidants provide a different reaction activity with MnO2 nanosheets. For each antioxidant, the colorimetric sensor array generates a distinct response pattern, which can be further differentiated via PCA.

Fig. 1. Schematic of the colorimetric sensor array for discrimination of five antioxidants based on MnO2 nanosheets triggered multicolor chromogenic system. The colors represent different absorbance values at 370, 450, and 650 nm (A370, A450, and A650) in the presence of various antioxidants. 3.2. MnO2 nanosheets triggered multicolor chromogenic system The obtained MnO2 nanosheets was characterized by TEM and UV-vis absorption spectra. As shown in Fig. S1, the obtained MnO2 nanosheets show a typical twodimensional layer structure, and exhibit multiple wrinkles. Fig. S2 displays the UV-vis spectrum of MnO2 nanosheets dispersion. A strong absorption band at 370 nm is observed, which is attributed to the d-d transition of Mn(IV) ions in the MnO6 octahedra of MnO2 nanosheets (Kai et al., 2008; Liu et al., 2015).

Fig. 2. (A) UV-vis absorption spectra and (B) the corresponding photograph of TMB solution in the presence of MnO2 nanosheets with different concentrations (from left to right: 0, 1, 2, 4, 6, 8, 10, 12, and 14 μg/mL). To demonstrate that the oxidation of TMB can generate multiple colors with different absorption bands, different concentrations of MnO2 nanosheets dispersion were added to the TMB solution. The UV-vis absorption spectra and the corresponding photograph are shown in Fig. 2. In the absence of MnO2 nanosheets, the TMB solution is colorless, and no absorption band in range of 320-750 nm is found (black line, Fig. 2A). When 1 μg/mL MnO2 sheets dispersion was added to TMB solution, the solution changes from colorless to blue, and shows two strong absorption bands at 370 and 650 nm, demonstrating the production of TMB radical cation and the charge-transfer complex of the diamine. The reaction between TMB and MnO2 nanosheets is highly dependent on the pH of the medium as shown in Fig. S3. With decreasing the pH from 11.9 to 2.8, the absorbance values at 370, 450, and 650 nm increase because MnO2 exhibit a strong oxidation activity in an acidic medium. However, if the pH is less than 2.8, the peak at 370 nm almost disappears which is adverse to fabricate the sensor array because of the lack of enough sensing elements. Therefore, the pH of the medium was chosen as 2.8. Interestingly, with increasing concentration of MnO2 nanosheets, a strong absorption band at 450 nm appears and reaches a maximum when the concentration exceeds 12 μg/mL, confirming the formation of TMB diamine. During this process, the solution

gradually turns blue to green and finally yellow. These results indicate that TMB can be oxidized to various products with different colors by MnO2 nanosheets. In order to get a high sensitivity, 12 μg/mL MnO2 nanosheets dispersion was selected. Additionally, other chromogenic systems such as MnO2 nanosheets-2,2’-azino-bis(3-ethylbenzthiazoline-6sulphonic acid) (ABTS) and MnO2 nanosheets-3,3’-diaminobenzidine (DAB) were investigated. It was found that ABTS and DAB can also react with MnO2 nanosheets, producing a color solution as shown in Fig. S4 and Fig. S5. However, these reaction chromogenic systems can only generate a single color (blue or yellow). It was difficult to realize visual discrimination of antioxidants because each of them had a single color. 3.3. Discrimination of antioxidants After demonstrating that the reaction of MnO2 nanosheets and TMB can generate multiple colors, we examined possible discrimination of five selected antioxidants using A370, A450, and A650 as sensing elements. The basic properties of the selected five antioxidants are listed in Table 1. Table 1. Basic properties of the five selected antioxidants Thiols

Abbreviation

L-glutathione

GSH

Melatonin

L-cysteine Uric acid

Ascorbic Acid

Mel

Cys UA

AA

Molecular weight 307.32

232.27

121.15 168.11

176.13

Normal range in blood serum 1.7-3.5 μM (Bridgeman et al.,1991) 0.1-0.3 nM (Waldhauser et al, 1988) 3.5-8.1 μM (Bridgeman et al.,1991) 120-450 μM (Ames et al., 1981) 30-140 μM (Ames et al., 1981)

Structure SH

O

O

N H

HO NH2

O

H N

OH O

O

H N

N H

O

O

HS

OH H 2N

O

H N

NH

O

O

N H

HO

H O O

HO HO

OH

It is found that when the concentration of the five selected antioxidants is below 20 µM, the sensor array can not differentiate from each other effectively. Accordingly, the concentration of five selected antioxidants is controlled at 20 µM. The UV-vis absorption

spectra of the system of MnO2 nanosheets and TMB in the absence and presence of UA, GSH, AA, Cys, and Mel at a concentration of 20 μM as shown in Fig. S6. The responses of the three absorbance values (A370, A450, and A650) of the system were recorded, and the signal change was defined as A0-A, where A and A0 are the absorbance values in the presence and absence of antioxidant. The responses of the colorimetric sensor array to each antioxidant were determined five times in parallel, resulting in a 5 antioxidants × 3 absorbance values × 5 replicates training data matrix which is plotted in Fig. 3A. Compared with the system of MnO2 nanosheets and TMB, the absorbance values at 370 and 650 nm increases, whereas the absorbance value at 450 decreases in the presence of antioxidants, demonstrating that antioxidants can inhibit the reaction of MnO2 nanosheets and TMB. The absorbance values change induced by different antioxidants are distinct, indicating the feasibility of antioxidant discrimination. The distinct absorbance responses of this system toward antioxidants is mainly attributed to the different reduction ability. To further generate the colorimetric response patterns of this system against five antioxidants, the obtained values of A0-A were subjected to PCA , and the output data of the five antioxidants are plotted with respect to their first two principal components. At an antioxidant concentration of 20 μM, PCA demonstrates that the canonical patterns were clustered into five different groups that correspond to each specific antioxidant, which were visualized as a well clustered 2 D plot (Fig. 3B). This clear discrimination indicates that this colorimetric sensor array has a strong power for discriminating antioxidants.

Fig. 3. (A) Colorimetric response patterns of the system of MnO2 nanosheets and TMB toward antioxidants at 20 μM as an average of five parallel measurements. (B) PCA score plot for discrimination of five antioxidants using the first two principal components of the colorimetric response patterns. To evaluate the robustness of this colorimetric sensor array, unknown samples were also tested based on the training matrix obtained above (Table S1). The identification accuracy of 45 unknown samples at 20 μM was found to be 100% (Table S2). This result clearly implied that the present colorimetric sensor array can determine and identify antioxidants at a concentration of 20 μM. This sensitivity is comparable to that of microfluidic sensor arrays for discrimination of antioxidants (10 μM) (Park et al. 2016). Compared with the microfluidic sensor arrays, the present colorimetric sensor array does not require complicated device fabrication process and multiple redox indicators, making it more economic and facile. Next, a test was carried out to ascertain whether the sensor array can identify the various concentration levels of single antioxidant. To verify the ability of the sensor array, we performed experiments with Mel, UA, and GSH at three different

concentrations (10, 20, and 40 μM, respectively). As shown in Fig. 4A and Fig. S7, 9 groups of samples were located in 9 isolated clusters. Simultaneously, it was found that the PCA sore plot for Mel, UA, and GSH at various concentrations were not random, but rather followed definite patterns, and therefore can be readily differentiated from each other at many concentrations.

Fig. 4. PCA score plots for (A) discrimination of UA, GSH, and Mel at different concentrations (10, 20, and 40 μM) and (B) mixtures of UA and AA at different molar ratios (total antioxidant concentration: 20 μM). After successful discrimination of antioxidants at different concentrations, the performance of our colorimetric sensor assay was further demonstrated for the discrimination of antioxidant mixtures. We mixed UA and AA that are two of the most abundant serum antioxidants at different molar ratios including UA 0 - AA 100, UA 20 AA 80, UA 40 - AA 60, UA 50 - AA 50, UA 60 - AA 40, UA 80 - AA 20, and UA 100 AA 0 (Fig. S8). In Fig. 4B, the PCA output data for the mixture of UA and AA are plotted with respect to the first two principal components. The seven binary mixtures of UA and AA with different molar ratios are visually separated and grouped in the PCA score plot.

Besides, this sensor array can also differentiate the mixture of Cys and GSH at different molar ratios as shown in Fig. S9. These results suggest that this sensor array has potential applications for discrimination of antioxidant mixtures. 3.4. Identification of antioxidants in real samples In order to further explore the possible applicability of the sensor array for analyzing complex real samples, the selected five antioxidants in the presence of fetal bovine serum (FBS) were measured. In order to eliminate the matrix effect, the FBS was diluted 10fold with BR buffer solution (pH 2.8). Subsequently, various antioxidants at a concentration of 20 μM were spiked into the 10% FBS. The colorimetric responses of the sensor array toward the 10% FBS and five antioxidants in the presence of 10% FBS are shown in Fig. S10. The different responses offered distinct patterns which effectively classified FBS and five antioxidants into six groups by PCA (Fig. 5A). Furthermore, these patterns do not overlap those of various control experiments (Fig. S11), confirming that this sensor array works well in real sample. The responses of the sensor array toward 10% FBS is because of the antioxidants present in serum.

Fig. 5. (A) PCA score plot for discrimination of 10 % FBS and five antioxidants at a concentration of 20 μM in the presence of 10 % FBS. (B) Photograph of the color change upon addition of 10 % FBS and different antioxidants in the presence of 10 % FBS.

More significantly, this sensor assay for discrimination of antioxidants in FBS can be directly observed with the naked eye. Fig. 5B is a photograph of the MnO2 nanosheets-TMB reaction system upon addition of 10 % FBS and five antioxidants in the presence of 10 % FBS. As noted in the figure, 10 % FBS does not cause a great color change. However, in contrast to FBS, the spiked FBS with different antioxidants show distinct colors, including yellow, light-yellow, yellow-green, blue, and green. Accordingly, these results imply that the present colorimetric sensor array provides a great potential for discrimination of antioxidants in real biological matrix.

4. Conclusion In conclusion, three absorbance values of the MnO2 nanosheets triggered multicolor chromogenic system were employed as simple sensing elements in the development of visual colorimetric sensor array for discrimination of water-soluble antioxidants in serum. Using this sensor array, five antioxidants such as UA, GSH, AA, Cys, and Mel were successfully discriminated at a low concentration of 20 μM. Furthermore, this sensor array can also discriminate different concentrations of antioxidants and antioxidant mixtures. The identification accuracy of the unknown samples are 100 % at the 20 μM level (45 out of 45). Importantly, different antioxidants spiked FBS can be directly differentiated with the naked eye. Compared with the methods currently used in the medical field such as HPLC, this sensor array can simply, rapidly, economically identify various antioxidants. Taken together, the present work offers a simple and new avenue for development of sensor arrays using multiple absorbance values as the sensing elements. This visual colorimetric sensor assay may hold great promise for medical diagnosis and biosensor. It should be also noted that the sensor array can not determine ultralow antioxidant concentration (such as nM level). We will improve the sensitivity of the present sensor array to fulfill the demand for early detection of diseases, and the related work is now underway.

Acknowledgements The support of this research by the Foundation of Science and Technology Department of

Sichuan Province (Grant No. 2015JY0053), Doctoral Program of Southwest University of Science and Technology (Grant No. 14zx7165), is gratefully acknowledged.

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Highlights 

A unique visual colorimetric sensor array for discrimination of antioxidants in serum based on MnO2 nanosheets-3,3',5,5'-tetramethylbenzidine (TMB) multicolor chromogenic system.



Five antioxidants were successfully discriminated at a low concentration of 20 μM.



This sensor array can also discriminate different concentrations of antioxidants and antioxidant mixtures.



This sensor assay can visually discriminate antioxidants in diluted fetal bovine serum with the naked eye.