A colorimetric sensor for the visual detection of azodicarbonamide in

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A colorimetric sensor for the visual detection of azodicarbonamide in flour based on azodicarbonamide-induced anti-aggregation of gold nanoparticles Zhiqiang Chen, Lian Chen, Ling Lin, Yongning Wu, and FengFu Fu ACS Sens., Just Accepted Manuscript • Publication Date (Web): 21 Sep 2018 Downloaded from http://pubs.acs.org on September 21, 2018

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A colorimetric sensor for the visual detection of azodicarbonamide in flour based on azodicarbonamide-induced anti-aggregation of gold nanoparticles Zhiqiang Chen†, Lian Chen†, Ling Lin†, Yongning Wu‡, FengFu Fu*† †

Key Laboratory for Analytical Science of Food Safety and Biology of MOE, Fujian Provincial Key Lab of Analysis and Detection for Food Safety, College of Chemistry, Fuzhou University, Fuzhou, Fujian 350116, China. ‡

China National Center for Food Safety Risk Assessment, Beijing 100022, China

ABSTRACT: Azodicarbonamide (ADA) in flour products can be converted into carcinogenic biurea and semicarbazide hydrochloride after baking. Thus, it is mandatory to determine ADA in flour. We herein developed a colorimetric method for the rapid and visual detection of ADA in flour based on glutathione (GSH)-induced gold nanoparticles (AuNPs) aggregation and specific reaction between ADA and GSH. The GSH can react to AuNPs via Au-SH covalent bond to form a network structure, which leads to AuNPs aggregation to produce color change. Whereas, ADA can specifically react with GSH to lead to the coupling of two GSH molecules, which makes GSH lose -SH group and thus decreases the aggregation degree of AuNPs induced by GSH. This provided a platform for field-portable colorimetric detection of ADA. The colorimetric sensor can be used to detect as little as 0.33 µM (38.3 ppb) of ADA by bare eye observation and 0.23 µM (26.7 ppb) of ADA by spectrophotometry within 2 hours. The method was successfully used to detect ADA in flour with a recovery of 91-104 % and a relative standard deviation (RSD) < 6 %. The visual detection limit of sensor is lower than the ADA limitation in flour (45 mg/kg), which makes the sensor a potential approach for the instrument-free visual and on-site detection of ADA in flour. KEYWORDS: azodicarbonamide, flour, food additive, biurea, semicarbazide, gold nanoparticles.

Flour-related products make up a large portion in family's dietary structure in many countries, and the whiteness and gluten of flour can be improved by adding additives to meet the actual demand. Azodicarbonamide (ADA), which was employed initially as a foaming agent of rubber articles dating back to 1940, now has been wildly used in flour industry as bleaching agent, gluten fortifier, or dough conditioner in many countries.1-3 ADA itself has low acute toxicity and also doesn't react directly with flour, however, it can react with moist flour as an oxidizing agent to convert into biurea (BIU) and semicarbazide (SEM), which were reported to have genotoxicity in vitro and carcinogenicity, under high temperature environment such as baking.3-6 Therefore, chronic consumption of flourrelated products, which containing excess ADA, will cause severe harm to human.7 Thus, the maximum allowable level of ADA in flour has been set as 45 mg/kg (ppm) in the United States, Canada and Asia, and some regions and countries such as European Union and Australia even banned its utilization in flour.2-4 To control the effectiveness of these legal provisions and to ensure the safety of flour-related products for consumption, it is highly crucial to establish a simple method for the rapid and on-site detection of ADA in flour. Currently, the main methods used for the detection of ADA in flour included direct methods and indirect methods. Direct methods included infrared spectrometry (IR), Raman spectrometry, capillary electrophoresis and high performance liquid chromatography (HPLC).8-11 Indirect methods, which ADA was firstly converted into semicarbazide hydrochloride, and then the semicarbazide hydrochloride was determined

with liquid chromatography coupled with mass spectrometry (LC-MS) or enzyme linked immunosorbent assay (ELISA).3, 12-17 Both of direct and indirect methods have obvious shortcomings such as need laborious and time-consuming pretreatment of sample, require sophisticated and expensive instruments and have higher cost, which do not meet the requirement of rapid and on-site detection. Recently, some rapid methods have been developed for the detection of ADA in food based on surface-enhanced Raman spectroscopy (SERS).18, 19 However, these rapid methods also require sophisticated instruments and have higher cost. Gold nanoparticles (AuNPs) have been wildly used for color signal generation in the fabrication of various colorimetric sensors since it possesses distance-dependent optical property and higher extinction coefficient, which allows colorimetric detection of trace analytes with higher sensitivity.20-25 Glutathione (GSH), a tripeptide (γ-Glu-Cys-Gly), consists of the glutamate moiety with a carboxylic group and a amine group, the glycine moiety with a carboxylic group and thiol (-SH) moiety on the cysteine.26 It was demonstrated that GSH can be immobilized on AuNPs surface via Au-SH covalent bond and then induce AuNPs aggregation via electrostatic interaction between the zwitterionic groups from the glutamate moiety, which leads to wine-red to blue change in solution color.26-30 The previous study has also demonstrated that ADA can quantitatively react with GSH by oxidizing its -SH group, which leads to the coupling of two GSH molecules and thus make GSH lose -SH group.31 Inspired by above results, in this study, we developed a colorimetric method for the instrument-free

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visual, low-cost and on-site detection of ADA in flour by employing AuNPs for color signal generation and GSH for ADA recognition, in order to ensure the safe consumption of flour.

EXPERIMENTAL SECTION Preparation of AuNPs. The AuNPs were prepared according to a literature procedure.32 Briefly, 0.5 mL of 2% (w/v) HAuCl4 solution was added into a 100 mL clean flask containing 99.5 mL of pure water. The solution was heated to boiling under full stirring. Then, 4 mL of 1% trisodium citrate solution was quickly added, and the mixture was kept in a boiling and stirring state for 30 min until color of solution changes to wine-red. After cooling to room temperature, the prepared AuNPs solution was further concentrated (from 4 mL to 1 mL) by centrifugal filtration with a 10K MWCO centrifugal filter device at 4000g. The average size and Zeta-potential of the concentrated AuNPs were measured with a Nano Particle Size & Zeta Potential Analyzer (Microtrac Nanotrac Wave II, USA). As Figure S1 showed (see supporting information, SI), the as-prepared AuNPs has an average size of 23 nm with a width of 11 nm and a Zeta-potential of -104.2 mV, indicating that the as-prepared AuNPs has good homogeneity and stability. The as-prepared AuNPs solution was stored at 5 °C for next use within one month. The Zeta-potential of AuNPs in 3.3 mM Britton-Robinson (BR) buffer (pH 3.3) was also measured with a -38.7 mV, indicating that the AuNPs has good stability too under pH 3.3. Colorimetric Detection of ADA. 100 µL of 15 µM GSH and 100 µL of ADA standard solution or sample solution were added into a 1.5 mL centrifuge tube, successively. The mixture was incubated at 50 °C for 60 min with gentle shaking, then 100 µL of 20 mM BR buffer (pH 3.3) was added. Finally, 300 µL of above as-prepared AuNPs solution was added. The mixture was incubated for 40 min at room temperature, then the color change of the solution was recorded with a digital camera and the absorption spectrum of the solution was determined in the range of 400-800 nm with UV-visible spectrophotometer. The ADA concentration was quantified based on bare eye observation or the absorption ratio (A520/A690). Determination of Flour Samples. For detecting ADA in flour, 0.1 g flour was weighed and put into a centrifuge tube. Then, 10 mL of acetone was added, and the whole was fully agitated for 20 min followed by 15 min ultra-sonication to extract ADA. By centrifuging for 5 min at 3000 rpm, the 5 mL of the supernatant was taken and evaporated to near dryness by using a pressured nitrogen blowing concentrator. The residue was re-dissolved in 5 mL of water, and the solution was filtered through a 4.5 µm filter to remove any residue. Finally, the ADA in filtrate was measured with above procedure directly or after dilution with pure water (according to the ADA amount in flour). The flour samples spiked with different concentration of ADA were measured with the same manner to obtain recovery.

RESULTS AND DISCUSSION Detailed Principle for Colorimetric Detection of ADA. As we mentioned above, it was demonstrated that GSH can be immobilized on the surface of AuNPs by forming Au-SH covalent bond, and the GSH-modified AuNPs can assembled via electrostatic interaction between the zwitterionic groups from the glutamate moiety, which produce color change in solution.26-30 In addition, it was demonstrated that ADA can quan-

titatively react with GSH by oxidizing the -SH group of GSH, which leads to the coupling of two GSH molecules and thus make GSH lose -SH group like Scheme 1-A.31 Thus, a novel method was designed for the visual detection of ADA based on azodicarbonamide-induced anti-aggregation of the AuNPs. The detailed principle was schematically illustrated in Scheme 1. In the presence of a fixed concentration of GSH, GSH can react with AuNPs and thus induced homo-dispersed AuNPs to form aggregation, which lead to the color change from winered to dark-blue in solution. Correspondingly, the absorption of the solution at 520 nm (A520) decreased and a new absorption peak at 690 nm (A690) appeared (see Figure 1). However, in the presence of both ADA and GSH, ADA can quantitatively oxidized -SH group of GSH to lead to the coupling of two GSH molecules, as illustrated in Scheme 1-A. The coupling of two molecules GSH makes GSH loses -SH group, and thus cannot induce AuNPs to form aggregation. As a result, the AuNPs solution showed a relatively low aggregation degree, which showed a deeper red color and a lower absorption at 690 nm in the presence of ADA in comparison with the case without ADA. This provided a sensing platform for the simple and field-portable colorimetric detection of ADA.

Scheme 1. Schematic illustration of the experimental principle of the ADA colorimetric assay

To verify the feasibility of the experimental design, firstly, the size distribution and morphology of the AuNPs under various conditions was characterized by transmission electron microscope (TEM). As observed in Figure 1-A, in the absence of ADA and GSH, the as-prepared AuNPs was homogeneously dispersed in solution with a size of ~20 nm, and correspondingly the AuNPs solution showed wine-red color and only has a high absorption at 520 nm (a in Figure 1-D). In the presence of only GSH, a large number of AuNPs agglomerated together (Figure 1-C), and correspondingly the AuNPs solution showed dark blue color and the absorption at 520 nm (A520) decreased and a new absorption peak at 690 nm (A690) appeared (c in Figure 1-D). Whereas, in the presence of both ADA and GSH, the aggregation degree of AuNPs obviously decreased (Figure 1-B), and correspondingly the AuNPs solution showed purple-

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red color and has a medium absorption at 520 nm and 690 nm respectively (b in Figure 1-D), indicating that ADA can react with GSH and induce the anti-aggregation of gold nanoparticles. All above experimental results demonstrated that our strategy is feasible. B

A

50 nm

50 nm

c b a D C

50 nm

Wavelength/nm

Fig. 1. TEM images of the AuNPs, UV-visible absorption spectra and photographs of AuNPs solution under different conditions. (a) AuNPs without GSH and ADA; (b) AuNPs + 2.5 µM GSH + 1.0 µM ADA; (c) AuNPs + 2.5 µM GSH.

was controlled with BR buffer. Thus, we first optimized the pH value of BR buffer in the range of 2.5-3.5. As results shown in Figure S2 (see SI), in the absence of GSH, the AuNPs solution showed the same color (wine-red) and absorption spectrum (has only a high absorption at 520 nm) under different pH. Whereas, in the presence of GSH, the AuNPs showed a more obvious aggregation with the increasing of the pH when the pH value is lower than 3.3, and then the aggregation degree of AuNPs turn to decrease when pH is higher than 3.3 (Figure 2). This may be because that one of the carboxylic acid groups of GSH deprotonates when the pH is higher than 3.3 and then forms an additional anchor on the AuNPs surface, which hinders the GSH-induced AuNPs aggregation.26 Therefore, the pH 3.3 was chosen as the optimal pH. Subsequently, we optimized the concentration of BR buffer under pH 3.3. As observed in Figure S3 (see SI), the variation of the buffer concentration does not affect the color and absorption spectrum of the AuNPs solution in the absence of GSH. Whereas, in the presence of GSH, the GSH-induced aggregation degree of AuNPs increased gradually and correspondingly the color of solution change from wine-red to dark-blue with the increasing of BR buffer concentration when the concentration was less than 3.3 mM (see Figure 3). When the BR buffer concentration is higher than 3.3 mM, the AuNPs began to deposit and the absorption at 690 nm (A690) turn to decrease (see Figure 3). Consequently, we selected 3.3 mM as the optimal concentration of BR buffer. Original 6.6mM 5.3mM 4.0mM 3.3mM 2.6mM 1.3mM AuNPs

Optimization of Experimental Conditions. To obtain the best performance, based on above principle, several conditions including the pH and concentration of BR buffer, the concentration of GSH, the reaction temperature and time between ADA and GSH were optimized. 2.9

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0.4 0.2 0.0

pH pH pH pH pH pH pH

400

2.5 2.9 3.1 3.2 3.3 3.4 3.5

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600 700 Wavelength/nm

800

Fig. 3. Effect of the BR buffer concentration on the GSH-induced aggregation of AuNPs. Data was obtained under BR buffer (pH 3.3) and 2.5 µM GSH. Original AuNPs

500 600 700 Wavelength/nm

800

Fig. 2. Effect of the BR buffer pH on the GSH-induced aggregation of AuNPs. Data was obtained under 3.3 mM BR buffer and 2.5 µM GSH.

The pH will affect the ionization of the GSH that modified on the AuNPs surface, and thus affect the GSH-induced aggregation of AuNPs. In the experiment, the pH of the system

As shown in Scheme 1, in our method, the ADA was indirectly detected by determining the variation of GSH. Thus, it's crucial to choose the optimum concentration of GSH. As observed in Figure 4, the higher GSH concentration is favor of inducing the AuNPs aggregation, and thus generates a more strong absorption at 690 nm and an obvious color change (from wine-red to dark-blue). Lower concentration of GSH could not induce AuNPs to congregate completely, and thus decrease the sensitivity and linear range of the method (Figure S4 in SI). However, when the GSH concentration is bigger than 2.5 µM, the AuNPs began to deposit and the absorption at

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ACS Sensors samples. The relative standard deviation (RSD, n = 5) was calculated to be less than 5 % for detecting 0.17 µM ADA with UV-visible spectrophotometry, indicated that the method has good reproducibility. 0.0uM

0.12uM 0.17uM 0.33uM 0.50uM 0.66uM 0.83uM

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0.8 0.7

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690 nm (A690) turn to decrease. So 2.5 µM was selected as the best concentration of GSH and used in the experiment. As a rapid and field-portable colorimetric method, the interaction speed between ADA and GSH is another key consideration. To minimize reaction time, the reaction temperature between ADA and GSH was also optimized in the range of room temperature to 55 °C. The experimental results (see Figure S5 in SI) showed that the reaction speed increased with the increasing of reaction temperature. However, when temperature is higher than 50 °C, the GSH and ADA is easy to deteriorate and finally affect the accuracy and reproducibility of the method. Hence, 50 °C was regarded as the optimal reaction temperature. Under all above optimum conditions, the reaction time between GSH and ADA was investigated, and the results (Figure S6 in SI) revealed that the reaction between GSH and ADA was completed within 1 hour. Thus, 1 hour was selected in this study.

0.4 0.3

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Fig. 4. Effect of GSH concentration on the GSH-induced aggregation of AuNPs. Data was obtained under 3.3 mM BR buffer (pH 3.3).

The Analytical Performance of the Method. Under above optimal experimental conditions, the UV-visible absorption spectra and color changes of the assay system in the presence of ADA at different concentrations were performed to obtain the calibration curve. As shown in Figure 5, the absorption of solution at 690 nm (A690) decreased significantly and the absorption at 520 nm (A520) gradually increased with the increasing of ADA concentration from 0.12 to 1.00 µM. Correspondingly, the color of the solution gradually changed from dark blue to wine-red. When the concentration of ADA was higher than 0.33 µM, the color change of the solution can be definitely identified by bare eye observation, i.e. the visual limit of the method is as low as 0.33 µM (38.3 ppb) for ADA. The absorption ratio (A520/A690) showed a good linear relationship with the ADA concentration in the range of 0.12 µM to 1.00 µM. The regression equation was: A520/A690 = 0.6457×C + 0.9935 (correlation coefficient r = 0.9970), where C is the ADA concentration with the unit of µM. The limit of detection (LOD, 3σ/S) was calculated to be 0.07 µM and the limit of quantification (LOQ, 10σ/S) was calculated to be 0.23 µM (26.7 ppb). The visual limit and LOQ of UV-visible spectrophotometry are all much lower than the maximum allowable level of ADA in flour (45 ppm) defined by United States, Canada and Asia, indicating that our method meets the requirement of rapid, instrument-free visual and on-site detection of ADA in flour

0.2

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Fig. 5. Photographs and absorption spectra for detecting different concentrations of ADA with the proposed method under optimal conditions, and the calibration curve of the method.

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0.4 0.3 0.2 0.1 0.0

a b c d e 400 500 600 700 800 Wavelength/nm

Fig. 6. Photographs and absorption spectra for detecting different substances with the proposed method under optimal conditions. a: the extract of home-made flour; b: 1 µM of cysteine; c: 1 µM of dibenzoyl peroxide; d: 1 µM of potassium bromate; e: 1 µM of ADA.

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ACS Sensors Table 1. The analytical results of ADA in flour samples ADA detected *

Flour Sample

Home-made flour

§

ADA added (µg/g)

† †

Naked eye observation µM (µg/g)

UV-visible spectrometry

‡

Concentration µM (µg/g)

Recovery (%)

RSD (n=5)

HPLC (µg/g)

0.0

-

-

-

-

-

3.8

-

0.30 (3.5)

92%

4%

3.4

5.8

0.5 (5.8)

0.46 (5.3)

91%

4%

5.6

0.0

0.5 (23.2)

0.52 (24.1)

13.0

0.8 (37.1)

0.81 (37.6)

25.2

Market flour 104%

6%

37.1

*

The ADA concentration added into flour sample; †The ADA concentration in the extract of flour or its diluent obtained with our method, data in parentheses is the ADA concentration in flour calculated with the detected ADA in the extract; ‡The ADA concentration in flour obtained with HPLC; §The extract of flour was previously diluted for 4-folds with water before detection due to the higher concentration.

Selectivity and Resistance to Flour Matrix. As we mentioned above, ADA in the flour was firstly extracted with acetone and then was detected with our method. It is possible that a little of main components of flour such as starch, protein and so on were extracted out by acetone together with ADA, and thus interfere with the ADA detection. To investigate the resistance of our sensor to flour matrix, the effect of the extract of ourselves-milled flour sample (home-made flour, contains no ADA) on the AuNPs aggregation was investigated. As results shown in Figure S7 (see SI), the extract of home-made flour do not induce AuNPs aggregation, and thus do not interfere with the ADA detection. To further investigate the selectivity of our sensor, we detected ADA, the extract of homemade flour, and other common flour additives such as dibenzoyl peroxide, potassium bromate and cysteine with our sensor. From Figure 6, we observed that only ADA can react with GSH and decreased the aggregation degree of AuNPs induced by GSH. Other substances do not react with GSH and thus do not decrease the aggregation degree of AuNPs. All above results indicated that our sensor has good selectivity and robust resistance to flour matrix. Determination of ADA in Real Flour Samples. To further confirm the reliability and practicability of our sensor, the home-made flour and market flour samples were detected with our method, and the results obtained with our sensor were compared with that obtained with HPLC method reported by Xiang et al,33 a standard method for ADA detection. The flour

samples spiked with different concentrations of ADA were also determined with the same manner to obtain recovery. After the pretreatment as described in the experimental section, the amount of ADA in the filtrate was detected with our method by bare eye observation and UV-visible spectrometry, respectively. As observed in Table 1, the ADA in the flour samples can be detected by bare eye observation at 5.8 µg/g level and by UV-visible spectrometry at 3.5 µg/g level with a recovery of 91% - 104% and a RSD ˂ 6% (n = 5). In addition, the results obtained with our method are consistent with that obtained with HPLC method. All above facts indicated that the colorimetric sensor we constructed was reliable and can be applied to practical detection of trace ADA in flour samples. To date, many methods have been developed for the determination of ADA in flour, but most of them require sophisticated/expensive instrument and time-consuming pre-treatment, which lead to a longer analysis time and higher cost.8-19 Compared with these methods, our method has obvious analytical advantages such as low-cost, short analysis time and instrument-free, which is suitable for the rapid and on-site detection of ADA in flour sample.

CONCLUSSION In summary, a simple and convenient colorimetric sensor was developed for the instrument-free visual and on-site detection of trace ADA in flour. The colorimetric sensor employed AuNPs for color signal generation and GSH for ADA recogni-

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tion. GSH reacted with AuNPs via Au-SH covalent bond to form a network structure, and thus led to AuNPs aggregation to produce color change from wine-red to dark blue. ADA can quantitatively react with GSH to lead to the coupling of two GSH molecules, which makes GSH lose -SH group and thus decrease the aggregation degree of AuNPs with the color revive from dark blue to wine red. This provided a sensing platform for the simple, rapid and field-portable colorimetric detection of ADA. The colorimetric method can be used to detect as low as 0.33 µM (38.3 ppb) ADA by bare eye observation and 0.23 µM (26.7 ppb) ADA by UV-visible spectrophotometry within 2 hours. By using the method, we have successfully detected ADA in flour samples by bare eye observation and UV-visible spectrophotometry respectively with a recovery of 91% - 104% and a RSD ˂ 6% (n=5). In particular, the visual limit of the method is lower than the maximum allowable level of ADA in flour (45 mg/kg), indicating that our method meets the requirement of instrument-free visual, lowcost and on-site detection of ADA in flour.

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Chemicals and apparatus used in the experiments; average size of AuNPs, photographs and absorption spectra of AuNPs in different pH and concentrations of BR buffer, effect of reaction temperature and time between GSH and ADA on the analytical performance of the method, relationship between absorption ratio (A520/A690) and ADA concentration under lower GSH concentration and effect of the extract of home-made flour on AuNPs (Figure S1- S7) (PDF).

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected].

Author Contributions Experimental design, data analysis and interpretation were performed by F.-F. Fu. Experimental details were performed by Z. Q. Chen, L. Chen and L. Lin. The manuscript was written through contributions of all authors, and all authors have given approval to the final version of the manuscript.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors gratefully acknowledge The National Key Research and Development Program of China (2017YFC1600500), NSFC (21677034) and the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT-15R11) for financial support.

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