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Carbon Nanodots–Based Fluorescent Turn-On Sensor Array for Biothiols Yapei Wu, Xue Liu, Qiuhua Wu, Jie Yi, and Guolin Zhang Anal. Chem., Just Accepted Manuscript • Publication Date (Web): 12 Jun 2017 Downloaded from http://pubs.acs.org on June 12, 2017

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Analytical Chemistry

Carbon

Nanodots–Based

Fluorescent

Turn-On

Sensor Array for Biothiols Yapei Wu, Xue Liu*, Qiuhua Wu, Jie Yi and Guolin Zhang* Liaoning Province Key Laboratory for Green Synthesis and Preparative Chemistry of Advanced Materials, College of Chemistry, Liaoning University, Shenyang, 110036, (P. R. China) E-mail: [email protected], [email protected]

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ABSTRACT: Biothiols play important roles in biological processes. In this study, a novel sensor array-based method was proposed to detect and differentiate biothiols. The sensor array was constructed using three kinds of Ag+-sensitive carbon nanodots (CDs). The CDs were synthesised with amino acids and urea as carbon sources via a simple microwave method. Results revealed that Ag+ can bind with CDs and depress the fluorescence of CDs, while the subsequently joined biothiols can take Ag+ away from CDs and recover the fluorescence of CDs. Due to the different binding ability between Ag+ and various CDs, as well as Ag+ and various biothiols, the CD-Ag+ array exhibits a unique pattern of fluorescence variations when interacting with six biothiol samples (cysteamine, dithiothreitol, mercaptosuccinic acid, glutathione, mercaptoacetic acid, and mercaptoethanol). Principal component analysis (PCA) was applied to analyze the pattern and generate a clustering map for a clearer identification of these biothiols. PCA can also be employed to simplify the established three-sensor array into a two-sensor array. Both the three- and two-sensor arrays can identify these biothiols in a wide biothiol concentration range (>10 µM).

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INTRODUCTION The development of rapid, sensitive, portable and inexpensive sensing systems for various analytes has become an urgent societal need. Traditional sensors with high selectivity are designed through tailoring the sensing materials according to a given analyte, which always require time-consuming tedious synthetic procedures.1 Inspired by human olfactory and gustatory sensing systems,2,3 cross-reactive sensor arrays have been extensively investigated.4-6 Sensor arrays are constructed by utilising a series of non-selective sensors, and analytes can be recognised through cumulative non-specific responses from all the sensors.7-9 Highly specific sensors in sensor arrays are unnecessary, and thus designing and constructing sensing systems based on sensor arrays is more time and labour–saving. The construction of sensor arrays needs to choose appropriate sensing materials. Sensing materials with simple synthetic methods and excellent sensing performances can propel the development of sensor arrays. Carbon nanodots (CDs) are sensing materials exhibiting these advantages.10−12 CDs can be prepared from extensive and low-cost carbon sources by using simple and convenient methods.13 The high photostability of CDs guarantees stable fluorescence signal output and accurate detection results. Up to now, extensive analytes have been detected based on CD sensors, including metal ions,14-17 small organic molecules,18-20 biomolecules,21,22 pH23,24 and temperature25-27. With these beneficial characteristics, CDs are promising candidates for sensor arrays.28,29 Biothiols widely exist in nature and play an important role in biological processes in animals and plants. For example, glutathione is involved in many cellular processes, and abnormal glutathione levels can lead to cancer, abnormal aging, heart problems and other illnesses.30 Thioglycollic acid can cause environmental pollution, skin poisoning, genotoxicity and mutagenicity.31 Mercaptamine can act as a radiation protective agent to treat acetaminophen poisoning and prevent serious liver injury.32 Mercaptoethanol can enhance the immune function of lymphocytes.33 As for mercaptosuccinic acid, it perform well to assist nitro-glycerine to bring into full play the potential of hypotensive effect.34 Dithiothreitol can affect some oxygen catalytic reactions in living organisms.35 Biothiols have been detected by using some CDs with Ag+ as a bridge through an interesting on-off-on three-state fluorescence emission.36,37 The first step of adding Ag+ can result in fluorescence quenching of CDs because of electron or energy transfer during CD-Ag+ complexes forming process. Given the strong thiophilicity of Ag+, CD-Ag+ complexes can be disassembled with further addition of biothiols, and thus the fluorescence of CDs recovers. However, these detecting systems can only recognise a given biothiol or sulfhydryl compounds, but cannot efficiently differentiate among various biothiols. In this study, a sensor array was constructed by using three kinds of Ag+-sensitive CDs to detect and differentiate various biothiols. Six kinds of biothiols with sufficiently different structures and functionalities, including cysteamine (C-SH), dithiothreitol (D-SH), glutathione (G-SH), mercaptosuccinic acid (MS-SH), mercaptoacetic acid (MA-SH), and mercaptoethanol (ME-SH), were chosen as analytes to evaluate the sensor array. Principal component analysis (PCA) was applied to process the resulting response pattern data, and a clustering map came into being for a clearer identification of these biothiols. Meanwhile, the three-sensor array could also be simplified to a two-sensor array in PCA process. Both the three- and two-sensor array performed a highly differentiable and sensitive detection of biothiols. The following scheme is the working mechanism of the as-prepared CD-Ag+ sensor array for biothiols. -3-



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Scheme 1. The working mechanism of the sensor array for biothiols based on CD-Ag+ system.

EXPERIMENTAL SECTION Synthesis of CDs All of the CDs were prepared through microwave method. 0.3 g amino acid (glycine, histidine and leucine) and 1 g urea were dissolved in ultrapure water and then the solution was heated in the microwave oven for 4 minutes. The resulted solid powder was dissolved with 10 mL ultrapure water. The supernatant was collected by centrifugation at 12 000 rpm for 5 minutes and then dialyzed against ultrapure water through a dialysis membrane for 48 hours to remove the excess precursors and small molecules. The glycine CDs (G-CDs), histidine CDs (H-CDs) and leucine CDs (L-CDs) were obtained. And the resultant CDs was maintained at 4 °C for further use. Fluorescence quenching of CDs using Ag+ In order to minimize the concentration effect of CDs, the absorbance in CD solution were calibrated to 0.1 at their optimum excitation wavelength. The optimum excitation wavelength was the excitation wavelength where the fluorescence intensity of CDs reaches the maximum (λG-CD=330 nm; λH-CD=350 nm; λL-CD=350 nm). On this basis, fluorescence quenching and recovery experiments were carried out. 0.5 mL Ag+ solution with a calculated concentration was added into 3.5 mL CD solution, and then the PL spectra were recorded. Fluorescence recovery of CD-Ag+ using biothiols 3.5 mL CD solution was mixed with 0.5 mL Ag+ solution, and the concentration of Ag+ in the mixed solution was set as 400 µM. 20 µL biothiol solution was added into the mixed solution to recover the fluorescence of CDs. RESULTS AND DISCUSSION Characterization of CDs Three CDs were prepared using a microwave method. Three kinds of amino acids combined with urea were respectively chosen as the carbon source to prepare CDs. The CDs prepared from glycine, histidine and leucine were labelled as G-CDs, H-CDs and L-CDs. All of the CDs show a relatively high fluorescence quantum yield (10.32-17.19%) (Table S-1). The structure of three CDs were further characterized using UV–Vis test. There were obvious that characteristic absorption band of H-CDs in 220 nm and 280 nm (Figure 1A). The characteristic absorption band of G-CDs in 210 nm and 300 nm (Figure 1B). And the characteristic absorption band of L-CDs in 210 nm and 300 nm (Figure 1C). This is because there were π-π* and n-π* conjugate. According

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to the TEM, the size of H-CDs around 12 nm, G-CDs around 8 nm, the size of L-CDs around 10 nm (Figure 2).

Figure 1. The UV–Vis spectra of H-CDs (A), G-CDs (B) and L-CDs (C).

Figure 2. The TEM images of H-CDs (A), G-CDs (B) and L-CDs (C).

The Response of CD with Ag+ and Biothiols From the correlation curves between the fluorescence quenching value of CDs and the Ag+ concentrations, we can observe that the Ag+-binding ability is different for various CDs. Different kinds of amino acids contribute to the subtle structural difference between various CDs. Glycine, histidine and leucine have been reported to present various Ag+-binding ability,38-42 and their resulted CDs inherit these properties. The CDs are unresponsive on biothiols (Figure 3). However, the fluorescence intensity of CDs decreases when quantitative Ag+ is added to a CD solution (Figure 4). The subsequent addition of biothiols can take Ag+ away from the CDs and recover the fluorescence of each CD to a certain extent (Figure 5). The discriminative Ag+-binding effect of biothiols depends on the specific functional groups of biothiols. Firstly, apart from thiol groups, other functional groups can also generate weak interaction with Ag+, such as the electrostatic interaction between carboxyl groups and Ag+. Besides, the donor-acceptor electronic radicel can also influence the interaction between thiol groups and Ag+. Therefore, the Ag+-binding effect of biothiols is a result of synergistic action.43-47 The Linear correlation information of H-CD-Ag+-biothiols was also given (Figure S-1 and Table S-2).

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Figure 3. Response patterns of CDs in the presence of various biothiols. (A: G-CDs; B: H-CDs; C: L-CDs)

Figure 4. PL spectra of the CDs with different concentrations of Ag+, as well as the correlation curves between the fluorescence quenching value and Ag+ concentration. (G-CDs: A and B; H-CDs: B and D; L-CDs: E and F)

Figure 5. PL spectra of the H-CD–Ag+ system in the presence of various concentrations of biothiols. (Control: CD solution without Ag+ and biothiol; 0–1000 µM: CD solution with 400 µM Ag+ and various concentrations of biothiols)

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H-CDs display a wider linear response range for Ag+ compared with the other two CDs (Figure 4B, D, F). Therefore, the Ag+ concentration (400 µM) at the inflection points of its titrations to H-CDs was chosen to construct the sensor array for biothiols to obtain a maximum detection range and sensitivity. Biothiols with the same concentration (400 µM) were added to the CD-Ag+ solution, and the fluorescence recovery value was collected and normalized to construct the fingerprint for the biothiols (Figure 6). The fingerprints contain relevant information about that the CD-Ag+ sensor array respond to these biothiols. For example, for MA-SH, G-CD–Ag+ is the most sensitive response system, whereas L-CD–Ag+ is the most insensitive one.

Figure 6. Fingerprints (response patterns) of various biothiols generated by the CD-Ag+ sensor array.

Principal Component Analysis (PCA) The multi-dimensional response pattern (3 sensors × 6 biothiols × 5 trails) generated by the sensor array in the presence of six biothiols was statistically analysed through PCA. PCA can convert the fluorescence recovery data in the fingerprints into a new set of linearly uncorrelated principal components (PCs).48 According to Kaiser rule, PCs with eigenvalues greater than 1 are statistically significant.49 Therefore, only the first PC (PC 1, Eigenvalue=1.422) and the second PC (PC 2, Eigenvalue=1.145) are listed in Table 1. PC 1 accounts for 47.4% of the total variability in the data, whereas PC 2 contributes 38.2%. The first two PCs contribute ca. 85.6% of the total variability. Therefore, they can be applied as horizontal and vertical coordinates to plot a PCA scattergraph (Figure 7A). In the scattergraph, all of the data points from five repeated trials for each biothiol are close to each other and can be marked with a circle, representing an exclusive zone for a specific biothiol. No evident intersection among the data groups for various biothiols is observed, and this finding indicates that six biothiols can be differentiated through the scattergraph. The high level of data dispersion in the PCA scattergraph can be attributed to the high cross-reactivity given by the CD-Ag+-biothiol system. Table 1. PCA results of the CD-Ag+ sensor array including 3 sensors. PCA

PC 1

PC 2

Eigenvalue

1.422

1.145

Proportion

47.4%

38.2%

G-CDs

68.4%

25.9%

H-CDs

11.3%

79.0%

L-CDs

51.3%

-37.8%

Contribution

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Figure 7. A) The original sensor array contains 3 sensors (G-CDs, H-CDs and L-CDs). B) The simplified sensor array contains only 2 sensors (G-CDs and H-CDs).

Sensor array research mainly aims to use few sensor units to obtain good sensing performance. One of the most important applications of PCA is decreasing data dimensionality, and thus the as-constructed sensor arrays can be simplified using PCA.50 Considering our description, we chose PC 1 and PC 2 as the PCs of the simplified sensor array. Their correlation formulas are shown in Supporting Information, and factor scores are listed in Table 1. Factor scores can serve as important parameters to evaluate the contribution of each individual sensor to the construction of PCs.51 Perfect sensor unit can provide the highest contribution to each PC with statistical significance. Sensor G-CDs exhibit the highest contribution (68.4%) to PC 1, while sensor H-CDs contribute the most (79.0%) to PC 2. G-CDs and H-CDs are identified as the most important contributors to the sensor array. Hence, the sensor array was reconstructed using these two sensors to decrease the size of the array, and the PCA scattergraph was replotted in Figure 7B. The new PCA scattergraph displays separate clusters without a clear overlap between two kinds of biothiols. The reduction of the number of the sensor units has not significantly affected the working performance of the sensor array, and just two sensors are capable of differentiating between 6 analytes. Practical Application of Sensor Array Double blind experiments and interference experiments were performed to evaluate the practicability of the sensor array. In the double blind experiments, two kinds of unknown biothiols (UN1-SH and UN2-SH) were randomly selected from previous six biothiols. Their fluorescence parameters generated by the sensor array were taken into the formula and plotted in the PCA scattergraph (Figure 8A). Combining with Mahalanobis distance analysis (MDA), the data points of UN1-SH are close to those owing to MS-SH, which indicates that UN1-SH is MS-SH. In a similar way, UN2-SH can be judged as G-SH. The interference experiments was carried out in local tap water. The sensor array also performed well to discriminate six kinds of biothiols (Figure. 8B), which confirmed the practical utility and stability of our sensing system.

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Figure 8. A) Identification of unknown biothiols using sensor array; B) Working performance of sensor array in local tap water.

Optimal Concentration Range The concentration of biothiols may affect the working performance of the sensor array. Hence, the simplified two-sensor array was applied to investigate and discuss the biothiol concentration at which the sensor array is capable of differentiate between different biothiols. We chose seven typical biothiol concentrations in the concentration range of 0–2000 µM. A series of fingerprints related to these 6 biothiols at a given concentration exist (Figure S-2). Applying PCA to process the data at each concentration, seven sets of PC score data were generated and plotted in one PCA scattergraph (Figure 9). From the scattergraph, it is difficult to differentiate between different biothiols at lower concentration (≤10 µM), implying the sensors are close to their detection limits in this concentration range. At the concentration range of 100–500 µM, the data points at the same concentration present a clearer dispersive distribution as the biothiol concentration increases, indicating a good discriminative performance of the sensor array at these concentrations. When the biothiol concentration reaches a higher level (≥700 µM), the data points at various concentrations present a similar distribution, which means that the working performance of the sensor array is no longer influenced by biothiol concentration. From the working mechanism of the sensor array, biothiol is excessive in this concentration range and Ag+ can be completely removed from the CD sensors. These results confirm the as-constructed CD-Ag+ sensor array for biothiols can perform well in a wide biothiol concentration range (>10 µM).

Figure 9. PCA scattergraph for the response of the sensor array with six biothiols at different concentrations. 6 data points with the same colour represent 6 biothiols at the same concentration.

CONCLUSIONS In this study, a novel sensor array based on a CD-Ag+ system was designed and constructed to detect and differentiate biothiols. The sensor array utilizes CD-Ag+-biothiol on-off-on fluorescence signalling variation to establish the fingerprints of various biothiols. These -9-



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fingerprints can be analysed through PCA, and a clustering map was generated and applied for a clearer visible differentiation of biothiols. Meanwhile, the three-sensor array can also be simplified into a two-sensor array without influencing the working performance of the sensor array. The sensor array can clearly differentiate six kinds of biothiols in a wide biothiol concentration range (>10 µM). Considering the advantages of CDs with simple synthetic methods and abundant carbon sources, we think that the CD-based sensor array can provide satisfactory resolution for extensive analytes through subtle designing and construction of diverse sensing systems. FUNDING SOURCES This work was supported by the National Natural Science Foundation of China (51403093 and 51373073). ACKNOWLEDGMENT We are grateful to College of Chemistry, Liaoning University, Shenyang. SUPPORTING INFORMATION See supporting information for the detailed information including: chemicals and measurements; calculation of fluorescence quantum yields; additional data analysis from PCA; biothiol assay based on H-CD-Ag+ system; fingerprints of biothiols at various concentrations. This material is available free of charge via the Internet at http://pubs.acs.org. REFERENCES (1) Radislav, A. P.; Vladimir, M. M. Chem. Rev. 2008, 108, 770–813. (2) Buck, L.; Axel, R. Cell 1991, 65, 175–187. (3) Malnic, B.; Hirono, Sato, J. T.; Buck, L. B. Cell 1999, 96, 713–723. (4) Albert, K. J.; Schauer, C. L.; Stizel, S. E.; Vaid, T. P.; Walt, D. R. Chem. Rev. 2000, 100, 2595–2626. (5) Diehl, K. L.; Anslyn, E. V. Chem. Soc. Rev. 2013, 42, 8596–8611. (6) Askim, J. R.; Mahmoudi, M.; Suslick, K. S. Chem. Soc. Rev. 2013, 42, 8649–8682. (7) Na, N.; Zhang, S.; Wang S.; Zhang X. J. Am. Chem. Soc. 2006, 128, 14420–14421. (8) Wu, Y.; Na, N.; Zhang, S.; Wang, X.; Liu, D; Zhang X. Anal. Chem. 2009, 81, 961–966. (9) Kong, H.; Liu, D; Zhang, S.; Zhang X. Anal. Chem. 2011, 83, 1867–1870. (10) Baker, S. N.; Baker, G. A. Angew. Chem. Int. Ed. 2010, 49, 6726–6744. (11) Li, H. T.; Kang, Z. H. Liu, Y.; Lee, S. T. J. Mater. Chem. 2012, 22, 24230–24253. (12) Lim, S. Y.; Shen, W.; Gao, Z. Q. Chem. Soc. Rev. 2015, 44, 362–381. (13) Zhang, J.; Yu, S. H. Mater. Today 2016, 19, 382–393. (14) Zhang, R.; Chen, W. Biosens. Bioelectron. 2014, 55, 83–90. (15) Ju, J.; Chen, W. Biosens. Bioelectron. 2014, 58, 219–225. (16) Gao, X.; Lu, Y.; Zhang, R.; He, S.; Ju, J.; Liu, M. Li, L.; Chen, W. J. Mater. Chem. C 2015, 3, 2302–2309. (17) Liu, Y.; Liu, Y.; Lee, J.; Lee, J. H.; Mira, P,; Kim, H. Y. Analyst 2017, 142, 1149–1156. (18) Zhang, L.; Jiang, C.; Zhang, Z. Nanoscale 2013, 5, 3773–3779. (19) Zhang, K.; Zhou, H.; Wang, S.; Liu, R.; Zhang, J.; Zhang, Z. J. Am. Chem. Soc. 2011, 133, 8424–8427. (20) Da Silva, J. C. G.; Gonçalves, H. M. R. Trac-Trend Anal. Chem. 2011, 30, 1327–1336. (21) Zhang, R,; Zhao, J.; Liu, B.; Liu, R.; Zhao, T.; Han,Y.; Zhang, Z. J. Am. Chem. Soc., 2016, 138, 3769–3778. (22) Jiang, C.; Liu, R.; Han G.; Zhang, Z. Chem. Commun. 2013, 49, 6647–6649. (23) Liu, X.; Li, T.; Wu, Q.; Yan, X.; Wu, C.; Chen, X.; Zhang. G. Talanta 2017, 165, 216–222.

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