Nanozyme as artificial receptor with multiple readouts for pattern

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Letter

Nanozyme as artificial receptor with multiple readouts for pattern recognition Hao Qiu, Fang Pu, Xiang Ran, Chaoqun Liu, Jinsong Ren, and Xiaogang Qu Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b03807 • Publication Date (Web): 28 Sep 2018 Downloaded from http://pubs.acs.org on September 28, 2018

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Analytical Chemistry

Nanozyme as artificial receptor with multiple readouts for pattern recognition Hao Qiu,ab Fang Pu,*a Xiang Ran,a Chaoqun Liu, a Jinsong Ren,*a and Xiaogang Qu*a a. Laboratory of Chemical Biology and State Key Laboratory of Rare Earth Resources Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, P. R. China b. University of Science and Technology of China, Hefei , Anhui 230026 , P. R. China ABSTRACT: Nanozymes have been widely used for the construction of colorimetric sensors. However, the simultaneous discrimination of multiple targets using nanozymes is still a challenge. In this work, we construct a multiple-readout system for pattern recognition of proteins using nanozyme. g-C3N4 nanosheets which possess peroxidase-like activity are chosen as the single sensing receptor. The catalytic activity of g-C3N4 can be changed to different degrees owing to the different interactions between g-C3N4 and proteins. By choosing different combinations of absorbance intensities at various time points, multichannel information can be extracted from a single material for pattern recognition. The platform avoids the synthesis of multiplex sensing receptors and the requirement of sophisticated instruments, leading to lower cost and time consumption. The study provides a new method for the construction of feasible, convenient and flexibly nanozyme-based sensing arrays.

Nanomaterial-based artificial enzymes, termed nanozymes, have attracted considerable interest due to their high stability, low cost of synthesis, and ease of recycling and reuse.1-3 Until now, lots of nanomaterials, such as graphene oxide, magnetic nanoparticles and gold nanoparticles, have been discovered to possess intrinsic enzyme-mimicking activity.4-12 These nanozymes were widely employed in the construction of colorimetric sensors. However, due to the lack of molecular recognition ability, lots of nanozyme-based sensors were restricted for the non-specific assay of H2O2 or glucose.13-20 In order to extend the range of the analytes, efforts were made to introduce receptors with specific recognition ability.21-31 For example, Sharma et al. reported a specific assay for the detection of kanamycin based on aptamer-mediated nanozyme activity of gold nanoparticles.21 Although valuable, this kind of ‘‘lock-and-key’’ principle was employed to detect individual targets, which makes the strategy difficult to satisfy the requirement of simultaneous assay for multiple targets. Array-based sensor using an array of sensing receptors has emerged as a powerful tool for the recognition of multiple analytes.32-40 However, most of the array-based sensors need the synthesis of multiple sensing units, which increases the complexity and cost.41,42 To address the issue, multidimensional sensing devices which could extract multi-dimensional signals from a single sensing receptor were developed.43-46 Although valuable, sophisticated instruments or switch between different detection modes are still required, which may lead to undesirable reproducibility.47-49 Therefore, it remains a substantial challenge to construct multitarget detection system with single signal-source.50,51 Recently, layered graphitic carbon nitride (g-C3N4) is attractive owing to their favorable characteristics, such as high stability, non-toxicity, high surface-area-to-volume ratio, novel optical properties and extraordinary catalytic activities.52-59 Moreover, the structure and functional groups on the surface

of g-C3N4 endow it with high affinity to biomolecules through π−π stacking and electrostatic interaction.60-65 Here, by taking advantage of peroxidase-like activity and affinity to biomolecules of g-C3N4, we construct an array-based sensor for multiprotein assay for the first time. The strategy avoids synthesis of multiplex sensing receptors and exhibits ability to extract multichannel information from a single material. Scheme1. Representative scheme of a sensing device based on g-C3N4 nanosheets for discrimination of different proteins.

The schematic illustration of the single g-C3N4 for multianalyte detection is shown in Scheme 1. g-C3N4 can catalyze

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the chromogenic substrate 3,3,5,5-tetramethylbenzidine (TMB) in the presence of H2O2 to produce a blue color.58 Proteins bearing various functional groups would exhibit different affinities to the surface of g-C3N4, which may influence the interaction between g-C3N4 and substrates. As a consequence, concomitant alteration in catalytic efficiency of g-C3N4 would occur, leading to distinct initial velocities of catalytic reaction, the time to reach reaction plateau, and the absorbance values of the final product. These parameters can be reflected in the spectra of time-dependent absorbance change as a result of the catalyzed oxidation of TMB. By extracting absorbance values at 652 nm at different time, a fingerprint-like pattern can be produced. The obtained data are analyzed with principal component analysis (PCA) to distinguish proteins. First, g-C3N4 sheet was prepared via a thermal exfoliation strategy.53 The XRD image showed a (002) peak, which demonstrated that the layered g-C3N4 had been successfully exfoliated (Figure 1A). The morphology of g-C3N4 was characterized by TEM and AFM. TEM image showed that g-C3N4 was sheet structure (Figure 1B). AFM height analysis showed the thickness of g-C3N4 was about 2.4 nm, suggesting the nanosheet was comprised of a small number of C–N layers (Figure 1C). The chemical structure of g-C3N4 was affirmed by FTIR spectroscopy (Figure 1D). The band at 807 cm-1 was attributed to the breathing mode of the s-triazine ring system, and the peaks in the region of 1000–1650 cm-1 originated from the typical stretching vibration modes of C=N and C–N heterocycles. The broad peaks between 3600 and 3000 cm-1 corresponded to N–H stretching.52 The functional groups on the surface g-C3N4 nanosheets, i.e., NH2/–NH–/=N–, can served as well-characterized ligands to adsorb other molecules.

Figure 1. (A) XRD image of g-C3N4 nanosheets. (B) TEM image of g-C3N4 nanosheets. (C) AFM image of g-C3N4 nanosheets. Inset: the corresponding height profile of selected g-C3N4 nanosheets. (D) FTIR spectrum of g-C3N4 nanosheets.

To confirm the influence of the interaction between g-C3N4 nanosheets and protein on the catalytic activity of g-C3N4, bovine serum albumin (BSA) was elected as the model protein. In the experiment, BSA was mixed with g-C3N4 and incubated for half an hour at room temperature. Then TMB and H2O2

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were successively added to the solution. The reaction was monitored spectrophotometrically at 652 nm. g-C3N4 without protein was used as control under the same conditions. A timedependent absorbance change could be observed, indicating that the adsorbed protein could influence the catalytic activity of g-C3N4 to various degrees (Figure 2). Based on the phenomenon, we constructed an array-based sensor for protein assay.

Figure 2. Absorbance spectra of the catalyzed oxidation of TMB by (A) g-C3N4 and (B) g-C3N4-BSA complexes with the increase of time.

To verify the feasibility of the sensor system, eight proteins with different isoelectric point (pI), molecular weight (MW) and metal/non-metal containing properties were selected as representative analytes (Table S1), including bovine serum albumin (BSA), cytochrome c (Cc), calmodulin (CAM), glutathione reductase (GR), hemoglobin (Hb), lysozyme (Lys), protease K (Pro K), and trypsin (Try). In the procedure, each protein solution with concentration of 250 nM was first mixed with C3N4 nanosheets (20 µg/mL) and incubated for 30 minutes, followed by the addition of H2O2 (25 mM) and TMB (1 mM). The changes of absorbance signals at 652 nm within 20 min were recorded. The diverse responses of the sensor array to different proteins were shown in Figure 3A.

Figure 3. (A) Time-dependent absorbance changes of the catalyzed oxidation of TMB at 652 nm in the presence of g-C3N4 and g-C3N4-protein complexes. [proteins]= 250 nM. (B) The fingerprint pattern of the eight proteins based on the absorbance intensities at 100, 200, 400, 600, 1000 and 1200 s. I and I0 are the absorbance intensities in the presence and absence of proteins, re-

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Analytical Chemistry spectively. (C) PCA plot for the discrimination of the eight proteins. (D) Hierarchical cluster analysis for various proteins.

In the system, the multiple readouts for constructing sensor arrays originated from the absorbance signals at different time points. We chose absorbance values at six time points (100, 200, 400, 600, 1000 and 1200 s) as receptors for straightforward data acquisition, which contains much information about the catalytic activity of the g-C3N4-protein hybrids. Three replicates were tested for each protein. The fingerprint-like pattern of the proteins was generated, as shown in Figure 3B. The response data including 144 data points (6 receptors × 8 analytes × 3 replicates) was obtained and further analyzed with PCA. The data matrix was transformed into three principal components. After the analysis, the first two principal components were employed to produce a two-dimensional (2D) plot. As shown in Figure 3C, eight separate clusters corresponding to eight proteins demonstrated the proteins were identified from each other. Meanwhile, the short distances between the three dots in each cluster suggested high accuracy and satisfactory reproducibility of the measurement. In short, the proposed strategy could identify various proteins efficiently. As a matter of fact, we found that using three absorbance values as receptors could also achieve satisfactory discrimination. The signals at 100, 400, and 1200 s were collected and analyzed with PCA to produce a 2D plot. As shown in Figure S1, the well-separated groups suggested that the proteins could still be clearly distinguished. These results indicated that our system was sufficiently flexible and alterable to achieve high-order sensing. g-C3N4 nanosheets could interact with proteins through different intermolecular interactions, such as electrostatic interaction, π–π stacking and hydrogen bonding, etc. The different interactions could affect the accessibility of substrates to the active sites on the surface of g-C3N4 nanosheets, causing concomitant alteration in catalytic efficiency of g-C3N4. Isoelectric points (pI) and molecular weights (MW) significantly affected the sensing performance. For example, proteins (BSA and CAM) which possess similar pI and different MW gave different signal patterns, implying that their molecular weight have different contributions to the signal changes. Meanwhile, proteins (Lys and CAM) with similar MW and different pI also gave different signal patterns, suggesting that the surface charge might be related to the g-C3N4-protein interactions. Besides, for the metal-containing proteins (Hb and Cc), the complexes of protein-g-C3N4 presented enhanced peroxidaselike activity. It could be attributed to that the Fe heme in the two proteins presented additional peroxidase-like activity. Taken together, the generation of the patterns of the tested proteins is the result of various factors, including charges, protein sizes, functional groups and metal ions containing in proteins. Hierarchical cluster analysis (HCA), another statistical classification method, was used to analyze the similarity of the proteins. HCA aims to group the distinct analytes according to their Euclidean distance in the full vector space. The generated HCA dendrogram are depicted in Figure 3D. Two distinct clusters were produced, corresponding to the nature of the proteins. Hb and Cc showed more difference from other proteins and were classified together, while other proteins were grouped together.

Figure 4. (A) Time-dependent absorbance changes of the catalyzed oxidation of TMB at 652 nm by g-C3N4 in the presence of trypsin with different concentrations. (B) PCA plot for the discrimination of trypsin with different concentrations.

Furthermore, we investigated the response of the strategy to specific proteins with different concentrations to examine the sensitivity. Trypsin, known as the essential part of the pancreatic exocrine system and a biomarker of pancreatitis, was chosen as an analyte.66,67 Different concentrations of trypsin were treated with the g-C3N4 sensor, separately. As shown in Figure 4A, the absorbance signals of the sensor array decreased with the increase of trypsin concentration. The PCA then transferred the obtained data to a 2D score plot. Four clusters could be observed in Figure 4B, suggesting that the system could be used for concentration analysis. The limit of detection reached 16 nM for trypsin, which was comparable to or even lower than the methods reported previously.68 To evaluate the robustness of the sensor array, we also tested unknown samples based on the procedure in previous report.69,70 In this work, unknown samples were prepared by one researcher, and the tests were performed by another. The sample identity was unknown during the analysis. The resulting responses were analyzed by PCA. The tested samples could be identified by comparing the results with the training matrix obtained in Figure 3C. 12 of 13 unknown samples were well identified according to the response pattern of the sensor, achieving 92.3% identification accuracy (Table S2). The results of discrimination of unknown samples validated the consistency and reproducibility of our work. In summary, we developed a sensitive and effective method for pattern recognition of proteins using nanozyme as receptor with multiple readouts for the first time. The novel strategy has several advantageous features compared with previous array-based sensors. The system is simple in design and facile to operate. g-C3N4 as the only sensing receptor is easy to synthesis in large quantities. It uses a common instrument to obtain multiple readouts for array generation, which eliminates the need to synthesize various sensor elements and switch between different instruments. Meanwhile, this platform can identify targets using different combinations of absorbance intensities at various time points, suggesting it is a flexible and alterable method. Since many biomolecules can interact with 2D nanosheets, the system offers a potential approach to the detection of a broad spectrum of analytes. It is hoped that this strategy will broaden the application field of nanozymes and provide a new direction for developing flexibly multichannel sensing system.

ASSOCIATED CONTENT Supporting Information



The Supporting Information is available free of charge on the ACS Publications website. Figures of the fingerprint pattern of the eight proteins based on the absorbance intensities at 100, 400 and 1200 s and PCA plot for the discrimination of the eight proteins. Tables of the properties of the proteins tested and the identifying results of 13 unknown samples.

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

ORCID Fang Pu: 0000-0001-6182-7966 Jinsong Ren: 0000-0002-7506-627X Xiaogang Qu: 0000-0003-2868-320

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT Financial support was provided by the National Natural Science Foundation of China (Grants 21673223, 21431007, 21533008, 21871249 and 21820102009), the Key Program of Frontier of Sciences (CAS QYZDJ-SSW-SLH052)) and the Youth Innovation Promotion Association CAS (2014202).

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