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A double responsive smart upconversion fluorescence sensing material for glycoprotein
Biosensors and Bioelectronics 85 (2016) 596–602
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Biosensors and Bioelectronics journal homepage: www.elsevier.com/locate/bios
A double responsive smart upconversion fluorescence sensing material for glycoprotein Ting Guo a, Qiliang Deng a,n, Guozhen Fang a, Yaguang Yun a, Yongjin Hu b, Shuo Wang a,n a Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin Key Laboratory of Food Nutrition and Safety, Tianjin University of Science and Technology, Tianjin 300457, China b Institute of Food Science and Technology, Yunnan Agricultural University, Yunnan 650201, China
art ic l e i nf o
a b s t r a c t
Article history: Received 16 March 2016 Received in revised form 12 May 2016 Accepted 19 May 2016 Available online 20 May 2016
A novel strategy was developed to prepare double responsive smart upconversion fluorescence material for highly specific enrichment and sensing of glycoprotein. The novel double responsive smart sensing material was synthesized by choosing Horse radish peroxidase (HRP) as modal protein, the grapheme oxide (GO) as support material, upconversion nanoparticles (UCNPs) as fluorescence signal reporter, N-isopropyl acrylamide (NIPAAM) and 4-vinylphenylboronic acid (VPBA) as functional monomers. The structure and component of smart sensing material was investigated by transmission electron microscopy (TEM), Scanning electron microscopy (SEM), X-ray photoelectron spectroscopic (XPS) and Fourier transform infrared (FTIR), respectively. These results illustrated the smart sensing material was prepared successfully. The recognition characterizations of smart sensing material were evaluated, and results showed that the fluorescence intensity of smart sensing material was reduced gradually, as the concentration of protein increased, and the smart sensing material showed selective recognition for HRP among other proteins. Furthermore, the recognition ability of the smart sensing material for glycoprotein was regulated by controlling the pH value and temperature. Therefore, this strategy opens up new way to construct smart material for detection of glycoprotein. & 2016 Elsevier B.V. All rights reserved.
Keywords: Smart material Molecular imprinting Upconversion nanoparticles Glycoprotein Graphene oxide
1. Introduction Recently, sensors have been utilized widely in clinical diagnosis, food analysis and bioprocess monitoring. Sensors, as analytical device for detecting analytes, usually include recognition element, transducer element and read-out device. According to the transducer types, sensors can be classified chemical sensors, thermal sensors, fluorescence sensors and electrochemical sensors and so on (Ronkainen et al., 2010; Haupt and Mosbach, 2000; Kriz et al., 1995). Yang et al. (2014) reported the microfluidic electrochemical DNA sensors for the detection of single-nucleotide polymorphisms. The fluorescence sensors process can directly convert an event into a fluorescence signal and have attracted increasing attention due to their rapid response and high sensitivity (Wu and Chiu, 2013; Shen et al., 2012). Ma and co-workers constructed the fluorescence sensors for the detection of protein tyrosine kinase-7 and a potential cancer biomarker (AGR2) based on iridium (Ⅲ) and G-quadruplex (Lin et al., 2015; Wang et al., 2016a). At present, upconversion nanoparticles (UCNPs) have n
Corresponding authors. E-mail addresses: [email protected] (Q. Deng), [email protected] (S. Wang).
http://dx.doi.org/10.1016/j.bios.2016.05.056 0956-5663/& 2016 Elsevier B.V. All rights reserved.
shown great potential as fluorescence probes in biological science (Cheng et al., 2011; Liu et al., 2011; Yang et al., 2012; AlonsoCristonbal et al., 2015; Zhu et al., 2012; Kumar et al., 2009; Wang et al., 2016b). Compared with traditional fluorescence dye and quantum dots (QDs), sensors based on UCNPs have plenty of advantages, such as low toxicity, good photostability, long lifetime, and importantly, little background autofluorescence, making them application in a number of areas (Zhang et al., 2012a; Guo et al., 2015, 2016). The smart materials with stimuli-responsive ability can reversible change dimensions of their structure depending on temperature (Chen et al., 1995; Zhang et al., 2012b; Kawamura et al., 2014; Li et al., 2014), pH (Ma et al., 2014; Li et al., 2015, 2014; Zhang et al., 2013) and light (Takashima et al., 2012) stimulation from the environment. The smart materials based on changes in the hydrophilicity of polymer networks have potential applications in the drug delivery systems and fabrication of sensors. As one of the smart materials, thermo-sensitivity materials prepared with N-isopropyl acrylamide (NIPAAM) can change the dimensions of their structure response to temperature changes, which because NIPAAM as a well-known thermo-sensitivity compound undergoes a reversible hydrophilic-hydrophobic phase transition
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at the lower critical solution temperature (LCST) of 32 °C. When the temperature reaches LCST, NIPAAM changes from a hydrophilic, coil state to a hydrophobic, collapsed state (Li et al., 2014a; Sun et al., 2014). The boronate affinity materials as another smart material have attracted increasing attention for detection and enrichment of glycoprotein owing to the reversible covalent bonds between bornate and molecules containing cis-diol groups such as glycans or glycoproteins in an alkaline aqueous solution, whereas such bonds dissociate when the medium transform to the acidic solution (Wang et al., 2013; Li et al., 2013; Ye et al., 2014; Li et al., 2014b; Wang et al., 2014; Stepheneson-Brown et al., 2015; Nishiyabu et al., 2011). However, the studies on smart materials response to pH and temperature simultaneously are less (Man et al., 2015; Zhang et al., 2014). Glycoproteins, which are one of the most important posttranslational modifications, play a critical role in a variety of biological activities and they have been used as disease biomarkers and therapeutic targets for clinical diagnostics (Krishnamoorthy and Mahal, 2009; Pan et al., 2013; Ohtsubo et al., 2006). At present, the methods based on mass spectrometry (MS) have been proven to be a useful tool for the analysis of glycoproteins, but it is still a challenge to directly determine glycoproteins without any enrichment process because of the low abundance of glycoprotein and their poor ionization efficiency during mass spectrometric analysis (Alley et al., 2013; Nie et al., 2013; Dell et al., 2001). Therefore, to develop an effective, facile and highly sensitive method for detection and enrichment of glycoproteins is of a great importance. To date, antibodies are the most commonly recognition elements for the sensing systems because of its high specificity. However, antibodies are high cost and low stability, which limited their further application (McConnell et al., 2014). Therefore, to develop stability and low cost recognition element is urgently needed. Molecular imprinting has been considered as an important method to create recognition sites which are spatially and chemically complementary to the template. Due to their excellent mechanical and chemical stability, low cost, ease of preparation and reusable, molecularly imprinted polymers (MIPs) have been the most promising recognition element and have been extensively used in separation, sensing and drug delivery (Lofgreen et al., 2011; Tan et al., 2013). The strategy that MIPs combined with smart materials has a wide range of application. Herein, we present a novel smart upconversion fluorescence sensing material response to pH and temperature for glycoprotein, where UCNPs as transducer element and MIPs with response to pH and temperature as recognition elements. Graphene oxide (GO) is covalently decorated with functional groups involving hydroxyl and carboxyl on the basal plane or at the edges of the thin sheet of grapheme. GO have been used in different areas due to their ultrahigh specific surface area and excellent property in electrical, thermal and mechanical (Zhu et al., 2010; Wang et al., 2011; Song et al., 2010). In this study, Horseradish peroxidase (HRP) was chosen as target protein to investigate the properties of the smart sensing material. The proposed smart material has potential application in biomedicine and clinical diagnostics.
2. Materials and methods 2.1. Materials and chemicals All reagents were analytical grade at least. HRP (molecular weight (MW) 44 kDa, isoelectric point (pI) 6), Ovalbumin (OVA, MW 45 kDa, pI 4.7) and Bovine serum albumin (BSA, MW 67 kDa, pI 4.9) were obtained from Sangon Biotech Co. Ltd. (Shanghai, China). Y(CH3COO)3 4H2O (99.9%), Yb(CH3COO)3 4H2O (99.9%),
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Er(CH3COO)3 xH2O (99.9%), polyacrylic acid (PAA, M ¼1800), diethylene glycol (DEG) were purchased from Sigma Aldrich (St Louis, USA). Oleic acid (OA, 90%), 1-octadecene (ODE, 90%), GO was obained from Xianfeng nano (Nanjing, China). VPBA and NIPAAM were purchased from Alfa Aesar Co. Ltd. (Massachusetts, USA). 3-meracaptopropionic acid (MBA), ammonium perulfate (APS) and N,N,N,N-tetramethylenediamine (TEMED) were provided by Aladdin (Los Angeles, USA). 2.2. Characterizations Ultraviolet absorbance at a wavelength of 279 nm was recorded on a Cary 50-Bio Ultraviolet-visible (UV–vis) spectrometer. Fluorescence measurements were performed on a Hitachi F-2500 fluorescence spectrometer connected with an external 980 nm diode laser (1 W, continuous wave with 1 m fiber) as the excitation source. Scanning electron microscopy (SEM) images were obtained on a Hitachi SU1510 microscope. Transmission electron microscopy (TEM) was obtained by a 2010 FEF microscope. Energydispersive X-ray photoelectron spectroscopic (XPS) measurements were performed on PHI-5000 Versaprobe. Fourier transform infrared (FTIR) spectra (4000–400 cm-1) in KBr were recorded in a Vector 22 FT-IR spectrophotometer (Bruker, Germany). 2.3. Preparation of UCNPs UCNPs were prepared according to the previous literature (Li and Zhang, 2008). Y (CH3COO)3 (0.78 mmol), Yb (CH3COO)3 (0.2 mmol) and Er (CH3COO)3 (0.02 mmol), 6 mL OA and 17 mL ODE were added into a 100 mL flask and the mixture solution was heated to 160 °C, to form a transparent solution. The mixture solution was cooled down to room temperature naturally. Methanol (10 mL) solution with NaOH (2.5 mmol) and NH4F (4 mmol) was slowly dropped into the flask and stirred for 30 min To removal of methanol, the solution was slowly heated, degassed at 100 °C for 10 min Subsequently, the solution was heated to 300 °C and kept for 1 h at argon protection. After the resulted solution was cooled down naturally, UCNPs were obtained via centrifugation, and washed with ethanol for three times. PAA-UCNPs were synthesized according to the previous method with a modified procedure (Naccache et al., 2009). PAA (300 mg) was mixed with DEG (30 mL) in a 100 mL flask. The mixture solution was heated to 110 °C. Toluene (3 mL) solution with hydrophobic UCNPs (100 mg) was added, and maintained at 110 °C for 1 h under argon atmosphere. Then the mixture solution was heated to 240 °C and kept for 1 h. The resulted solution was cooled down to room temperature naturally, the PAA-UCNPs were collected from the resulted solution with the excess dilute hydrochloric aqueous solution, and washed three times with water. 2.4. Synthesis of the smart sensing material UCNPs (20 mg) and GO (3.5 mg) were dispersed in deionized water (10 mL) by ultrasonication and stirred for 30 min Then, HRP (10 mg), NIPAAM (100 mg), VPBA (25 mg) and MBA (40 mg) were added to the mixture, which was incubated 1.5 h under stirring for pre-polymerizaiton. The oxygen was removed by nitrogen bubbling for 10 min The polymerizaiton was initiated by APS (10 mg) and TEMED (100 μL, 5%, v/v), and then polymerization was carried out at 25 °C for 20 h. The smart sensing material was collected via centrifugation and washed with 0.5% (w/v) SDS 0.5% (v/v) HAc and doubly distilled water in order, which was repeated several times until no template was detected by UV–vis spectrophotometry. Finally, the control (non-imprinted polymer, NIP) was prepared using the same procedure except addition of the template protein.
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2.5. The double responsive of smart material experiments In the experiments, fluorescence measurements were performed on an F-2500 fluorescence spectrometer attached with an external 980 nm laser instead of internal excitation source. The external laser was set at 1 A. For thermo-sensitivity of smart material experiment, 2 mg of smart sensing material or NIP was dispersed in 2 mL of HRP solution with a certain concentration. The mixture was shaken as a function of temperature at 28 and 44 °C for a period of time and centrifuged. The concentration of template protein in the supernatant was measured by a UV–vis at 279 nm. The adsorption capacity (Q) of the protein bond to the smart sensing material is calculated by following equation.
Q = ( C0 − Ct ) V/W Where, C0 and Ct (mg/mL) are the initial concentration and the residual concentration of HRP, respectively. V (mL) represents the volume of the initial solution and W (g) is the weight of the material. For smart material response to pH experiment, 2 mg of smart sensing material or NIP was dispersed in 2 mL of HRP solution with a certain concentration at pH 6 or 9. The mixture was shaken at 28 or 44 °C for a period of time and centrifuged. The concentration of template protein in the supernatant was measured by a UV–vis at 279 nm. 2.6. Adsorption experiments For equilibrium binding experiment, 2 mg of smart sensing material or NIP was dispersed in 2 mL of HRP solution with a certain concentration. The mixture was shaken at 28 °C for a period of time and measured quickly.
The specificity experiment was performed by choosing OVA and BSA as competitive protein. 2 mg of smart sensing material was dispersed in 2 mL of signal (HRP, BSA or OVA) or binary protein (HRP-BSA) solution with a certain concentration. The mixture was shaken at 28 °C for a period of time and determined quickly.
3. Results and discussion 3.1. Preparation of sensing material In this work, UCNPs as fluorescence signal were used to sensing of template protein. Amino-functionalized GO was introduced as support material to enhance mass transfer. Furthermore, NIPAAM was used as thermo-sensitivity functional monomer that allowed for swelling and shrinking in response to temperature to capture or release protein, and VPBA was added to control the glycoprotein capture and release based on pH value changes. Fig. 1 illustrates the principle for the synthesis of the novel smart sensing material. In the first step, the UCNPs (NaYF4: Yb3 þ , Er3 þ ) were prepared through the solvothermal approach in oleic acid (OA) and 1-octadecene (ODE). Due to the organic ligand on the surface of the UCNPs, these nanocrystals were not dispersed in polar solvents, which limited further application. The resulted UCNPs were converted into carboxyl modified UCNPs with hydrophilic by ligand exchange of OA with PAA. In the second step, amino-functionalized GO was coated with carboxyl modified UCNPs through the hydrogen bonding interaction. Subsequently, template glycoprotein, UCNPs-coated GO, monomers NIPAAM and VPBA were copolymerized to form the smart sensing material. After removal of the template glycoprotein, the imprinted cavities were formed. When the template glycoprotein was rebound to the cavities, the fluorescence intensity of smart sensing material was reduced
Fig. 1. Synthesis of smart sensing material based on the UCNPs and GO.
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Fig. 2. TEM and SEM images of UCNPs (a, c) and smart material (b, d).
Fig. 3. (a) Changes of the fluorescence intensity and (b) adsorption capacity of smart sensing material for HRP with a temperature swing between 28 and 44 °C. The error bars were calculated from three parallel experiments.
gradually. The fluorescence of the smart sensing material recovered, when the template HRP was extracted from the smart sensing material. 3.2. Characterization of sensing material The smart material was characterized by TEM, SEM, FTIR and XPS, which verified the successful synthesis of the smart sensing material. TEM and SEM images of UCNPs in Fig. 2(a) and (b) showed that the UCNPs were well shaped with a size of about 50 nm. TEM and SEM images of smart sensing material in Fig. 2
(c) and (d) revealed that the smart sensing material had a size of about 100 nm and covered on the surface of GO. In the FTIR spectra (Fig. S1), the peak of B-O absorption at around 1345 cm 1 and the phenyl ring skeletal vibration at around 1550 cm 1 illustrated the existence of VPBA in smart material. The bands at around 3434 cm 1 and around 1640 cm 1 were attributed to N-H stretching and C ¼O bond vibration, which suggested that the NIPAAM was anchored onto the surface of the material. To confirm the surface composition of smart sensing material, XPS was performed. The XPS survey spectrum (Fig. S2) showed the signals of B 1s at 190 eV, C 1s at 285 eV, N 1 s at 400 eV and O 1s at 531 eV,
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Fig. 4. (a) Changes of fluorescence intensity and (b) adsorption capacity of smart sensing material for HRP at pH 6 and 9. The error bars were calculated from three parallel experiments.
Fig. 5. (a) Fluorescence emission spectra of MIP-smart sensing material and (b) NIP with addition of the certain concentration of HRP solution. Inset is the Stern-Volmer cure. F and F0 represent the fluorescence intensity in presence and absence of HRP.
which indicated that the smart sensing material was synthesized successful, although the signal of the B peak was relatively weak due to its low abundance. 3.3. The double responsive of smart material Thermo-sensitivity materials are well known as a temperature gate for controlling the capture and release of target molecules. To confirm the thermo-sensitivity properties of smart sensing material, the experiments of temperature influence were carried out (Fig. 3). Fig. 3(a) showed the fluorescence intensity of the smart sensing material with the template glycoprotein HRP as a function
of temperature at 28 and 44 °C. The interaction of smart sensing material with HRP revealed obviously temperature dependent onoff fluorescence intensity, which suggested the capture and release for the template HRP upon changes in temperature. We investigated the effect of the temperature on adsorption performance of smart sensing material for HRP (Fig. 3(b)) and found that the adsorption capacity for HRP at 28 °C was larger than that at 44 °C. The result was because the structure of smart sensing material changed with a change in temperature due to the existence of NIPAAM. Furthermore, due to ultra-high specific surface area and π electronic structure of GO, the adsorption capacity of smart sensing material was much higher than that of other smart material (Zhang et al., 2012b, 2014). The pH value is important for the interaction of boronate with cis-diol-containing compounds such as glycans or glycoproteins. Boronate can covalently interact with compounds containing a cis diol to form stable cyclic esters in alkaline solution, whereas the covalent bond dissociates once changing the medium to acidic solution. Boronate affinity imprinted material is more convenience to removal of template because reversible bond between template glycoproteins and boronate can dissociate using an acidic solution. To verify smart sensing material response to pH, the influence of pH value on recognition ability was investigated (Fig. 4). In Fig. 4 (a), the interaction of smart sensing material with HRP revealed conspicuous pH dependent on-off fluorescence intensity between at pH 9 and pH 6, which indicated the recognition of smart sensing material upon changing in pH. The result of adsorption ability experiment showed that the adsorption capacity of smart sensing material was larger at pH 9 than that at pH 6 (Fig. 4(b)). The above results are agreement with the stable bond between glycoprotein and boronate at higher pH values. To further investigate the double responsive, the adsorption ability of smart material response to pH at 44 °C was performed. Results showed that the adsorption capacity of smart sensing material was 31.1 mg g 1 and 56.5 mg g 1 at pH 6 and 9 (44 °C), respectively. 3.4. Adsorption characterization of smart material Adsorption kinetics studies were performed to investigate the adsorption process (Fig. S3). The adsorption rate rapidly increased in 60 min and the adsorption process quickly reached the equilibrium which because the ultra-high specific surface area of GO enhance mass transfer. To further investigate the recognition performance of smart sensing material, the recognition ability was studied through the changes of the fluorescence signal at different concentrations (Fig. 5). As the concentration of HRP increased, the
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Fig. 6. Selectivity behaviours (a) of template glycoprotein and competitive proteins on the MIP-smart sensing material and NIP. Effect of the competitive protein BSA (b) on the recognition of template glycoprotein HRP on the MIP-smart sensing material. Experiments were done by fixing the concentration of HRP and increasing the concentration of BSA. The error bars were from three parallel experiments.
fluorescence of smart sensing material was quenched gradually, which due to the specific affinity interaction between the imprinted cavities within sensing material and template protein. The inset A and B in Fig. 5(a) and (b) was plotted by the Stern-Volmer equation analysis for the smart sensing material and the control in the presence of template protein, respectively.
F0/F = 1 + KSV ⎡⎣ Q⎤⎦ Where, F and F0 are the fluorescence intensity of sensing material in the presence and absence of HRP, respectively, Ksv is the quenching constant of HRP, and [Q] is the concentration of HRP. The ratio of KSV, MIP and KSV, NIP (KSV, MIP and KSV, NIP are the linear slopes of inset A and B in Fig. 5) is defined as the imprinting factor (IF) to evaluate the selectivity of the smart sensing material. Under the optimal conditions, the IF (KSV, MIP/ KSV, NIP) was 3.51, which suggested that the smart sensing material with imprinted cavities could recognition the template protein. To demonstrate the specificity of the smart sensing material, OVA as a glycoprotein and BSA as a non-glycoprotein were used as competitive proteins. A series of single protein and binary protein solution of HRP-BSA were investigated to show the specific recognition ability (Fig. 6). It was clearly seen from Fig. 6(a) that the changes in fluorescence intensity of smart sensing material to HRP were much more obvious than that to the other protein, while the changes in fluorescence intensity of NIP were not significantly different for HRP, BSA and OVA. We found that the fluorescence intensity was not significant affected with the increase of the ratio of CBSA/CHRP (Fig. 6(b)). Thus, these results clearly indicated that the smart sensing material showed specificity for the template protein. 3.5. Detection range and limit To further demonstrate the performance of smart sensing material, the detection range and limit were investigated. The smart sensing material exhibited a linear in the range of 1–10 μM (Table S1) with a correlation of 0.991 for HRP. The detection limit, which was calculated as the concentration of HRP that quenched three times the standard deviation of the blank signal, divided by the slope of the standard curve, was 0.66 μM (Table S1). The precision for three replicate measurements at 6 μM was 1.10% (relative standard deviation). 4. Conclusions In this work, we propose a strategy for the development of
double responsive smart upconversion fluorescence material for glycoprotein. The smart material utilized as recognition element of the fluorescence sensor was prepared by combining the ultra-high specific surface area of GO, highly sensitive of UCNPs and high specific of MIP. The recognition performance of the smart material for glycoprotein was regulated by pH and temperature due to the existence of NIPAAM and VPBA in the recognition element. This strategy opens up new way to construct the fluorescence sensor for facile and quick detection of glycoprotein.
Acknowledgments The authors are grateful for the financial support provided by the National Natural Science Foundation of China (Project No. 21375094 and 31225021), the Ministry of Science and Technology of China (Project No. 2013AA102202) and Innovation Talents of Science and Technology Plan of Yunnan Province (Project No. 2012HA009).
Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.bios.2016.05.056.
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Biosensors and Bioelectronics journal homepage: www.elsevier.com/locate/bios
A double responsive smart upconversion fluorescence sensing material for glycoprotein Ting Guo a, Qiliang Deng a,n, Guozhen Fang a, Yaguang Yun a, Yongjin Hu b, Shuo Wang a,n a Key Laboratory of Food Nutrition and Safety, Ministry of Education, Tianjin Key Laboratory of Food Nutrition and Safety, Tianjin University of Science and Technology, Tianjin 300457, China b Institute of Food Science and Technology, Yunnan Agricultural University, Yunnan 650201, China
art ic l e i nf o
a b s t r a c t
Article history: Received 16 March 2016 Received in revised form 12 May 2016 Accepted 19 May 2016 Available online 20 May 2016
A novel strategy was developed to prepare double responsive smart upconversion fluorescence material for highly specific enrichment and sensing of glycoprotein. The novel double responsive smart sensing material was synthesized by choosing Horse radish peroxidase (HRP) as modal protein, the grapheme oxide (GO) as support material, upconversion nanoparticles (UCNPs) as fluorescence signal reporter, N-isopropyl acrylamide (NIPAAM) and 4-vinylphenylboronic acid (VPBA) as functional monomers. The structure and component of smart sensing material was investigated by transmission electron microscopy (TEM), Scanning electron microscopy (SEM), X-ray photoelectron spectroscopic (XPS) and Fourier transform infrared (FTIR), respectively. These results illustrated the smart sensing material was prepared successfully. The recognition characterizations of smart sensing material were evaluated, and results showed that the fluorescence intensity of smart sensing material was reduced gradually, as the concentration of protein increased, and the smart sensing material showed selective recognition for HRP among other proteins. Furthermore, the recognition ability of the smart sensing material for glycoprotein was regulated by controlling the pH value and temperature. Therefore, this strategy opens up new way to construct smart material for detection of glycoprotein. & 2016 Elsevier B.V. All rights reserved.
Keywords: Smart material Molecular imprinting Upconversion nanoparticles Glycoprotein Graphene oxide
1. Introduction Recently, sensors have been utilized widely in clinical diagnosis, food analysis and bioprocess monitoring. Sensors, as analytical device for detecting analytes, usually include recognition element, transducer element and read-out device. According to the transducer types, sensors can be classified chemical sensors, thermal sensors, fluorescence sensors and electrochemical sensors and so on (Ronkainen et al., 2010; Haupt and Mosbach, 2000; Kriz et al., 1995). Yang et al. (2014) reported the microfluidic electrochemical DNA sensors for the detection of single-nucleotide polymorphisms. The fluorescence sensors process can directly convert an event into a fluorescence signal and have attracted increasing attention due to their rapid response and high sensitivity (Wu and Chiu, 2013; Shen et al., 2012). Ma and co-workers constructed the fluorescence sensors for the detection of protein tyrosine kinase-7 and a potential cancer biomarker (AGR2) based on iridium (Ⅲ) and G-quadruplex (Lin et al., 2015; Wang et al., 2016a). At present, upconversion nanoparticles (UCNPs) have n
Corresponding authors. E-mail addresses: [email protected] (Q. Deng), [email protected] (S. Wang).
http://dx.doi.org/10.1016/j.bios.2016.05.056 0956-5663/& 2016 Elsevier B.V. All rights reserved.
shown great potential as fluorescence probes in biological science (Cheng et al., 2011; Liu et al., 2011; Yang et al., 2012; AlonsoCristonbal et al., 2015; Zhu et al., 2012; Kumar et al., 2009; Wang et al., 2016b). Compared with traditional fluorescence dye and quantum dots (QDs), sensors based on UCNPs have plenty of advantages, such as low toxicity, good photostability, long lifetime, and importantly, little background autofluorescence, making them application in a number of areas (Zhang et al., 2012a; Guo et al., 2015, 2016). The smart materials with stimuli-responsive ability can reversible change dimensions of their structure depending on temperature (Chen et al., 1995; Zhang et al., 2012b; Kawamura et al., 2014; Li et al., 2014), pH (Ma et al., 2014; Li et al., 2015, 2014; Zhang et al., 2013) and light (Takashima et al., 2012) stimulation from the environment. The smart materials based on changes in the hydrophilicity of polymer networks have potential applications in the drug delivery systems and fabrication of sensors. As one of the smart materials, thermo-sensitivity materials prepared with N-isopropyl acrylamide (NIPAAM) can change the dimensions of their structure response to temperature changes, which because NIPAAM as a well-known thermo-sensitivity compound undergoes a reversible hydrophilic-hydrophobic phase transition
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at the lower critical solution temperature (LCST) of 32 °C. When the temperature reaches LCST, NIPAAM changes from a hydrophilic, coil state to a hydrophobic, collapsed state (Li et al., 2014a; Sun et al., 2014). The boronate affinity materials as another smart material have attracted increasing attention for detection and enrichment of glycoprotein owing to the reversible covalent bonds between bornate and molecules containing cis-diol groups such as glycans or glycoproteins in an alkaline aqueous solution, whereas such bonds dissociate when the medium transform to the acidic solution (Wang et al., 2013; Li et al., 2013; Ye et al., 2014; Li et al., 2014b; Wang et al., 2014; Stepheneson-Brown et al., 2015; Nishiyabu et al., 2011). However, the studies on smart materials response to pH and temperature simultaneously are less (Man et al., 2015; Zhang et al., 2014). Glycoproteins, which are one of the most important posttranslational modifications, play a critical role in a variety of biological activities and they have been used as disease biomarkers and therapeutic targets for clinical diagnostics (Krishnamoorthy and Mahal, 2009; Pan et al., 2013; Ohtsubo et al., 2006). At present, the methods based on mass spectrometry (MS) have been proven to be a useful tool for the analysis of glycoproteins, but it is still a challenge to directly determine glycoproteins without any enrichment process because of the low abundance of glycoprotein and their poor ionization efficiency during mass spectrometric analysis (Alley et al., 2013; Nie et al., 2013; Dell et al., 2001). Therefore, to develop an effective, facile and highly sensitive method for detection and enrichment of glycoproteins is of a great importance. To date, antibodies are the most commonly recognition elements for the sensing systems because of its high specificity. However, antibodies are high cost and low stability, which limited their further application (McConnell et al., 2014). Therefore, to develop stability and low cost recognition element is urgently needed. Molecular imprinting has been considered as an important method to create recognition sites which are spatially and chemically complementary to the template. Due to their excellent mechanical and chemical stability, low cost, ease of preparation and reusable, molecularly imprinted polymers (MIPs) have been the most promising recognition element and have been extensively used in separation, sensing and drug delivery (Lofgreen et al., 2011; Tan et al., 2013). The strategy that MIPs combined with smart materials has a wide range of application. Herein, we present a novel smart upconversion fluorescence sensing material response to pH and temperature for glycoprotein, where UCNPs as transducer element and MIPs with response to pH and temperature as recognition elements. Graphene oxide (GO) is covalently decorated with functional groups involving hydroxyl and carboxyl on the basal plane or at the edges of the thin sheet of grapheme. GO have been used in different areas due to their ultrahigh specific surface area and excellent property in electrical, thermal and mechanical (Zhu et al., 2010; Wang et al., 2011; Song et al., 2010). In this study, Horseradish peroxidase (HRP) was chosen as target protein to investigate the properties of the smart sensing material. The proposed smart material has potential application in biomedicine and clinical diagnostics.
2. Materials and methods 2.1. Materials and chemicals All reagents were analytical grade at least. HRP (molecular weight (MW) 44 kDa, isoelectric point (pI) 6), Ovalbumin (OVA, MW 45 kDa, pI 4.7) and Bovine serum albumin (BSA, MW 67 kDa, pI 4.9) were obtained from Sangon Biotech Co. Ltd. (Shanghai, China). Y(CH3COO)3 4H2O (99.9%), Yb(CH3COO)3 4H2O (99.9%),
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Er(CH3COO)3 xH2O (99.9%), polyacrylic acid (PAA, M ¼1800), diethylene glycol (DEG) were purchased from Sigma Aldrich (St Louis, USA). Oleic acid (OA, 90%), 1-octadecene (ODE, 90%), GO was obained from Xianfeng nano (Nanjing, China). VPBA and NIPAAM were purchased from Alfa Aesar Co. Ltd. (Massachusetts, USA). 3-meracaptopropionic acid (MBA), ammonium perulfate (APS) and N,N,N,N-tetramethylenediamine (TEMED) were provided by Aladdin (Los Angeles, USA). 2.2. Characterizations Ultraviolet absorbance at a wavelength of 279 nm was recorded on a Cary 50-Bio Ultraviolet-visible (UV–vis) spectrometer. Fluorescence measurements were performed on a Hitachi F-2500 fluorescence spectrometer connected with an external 980 nm diode laser (1 W, continuous wave with 1 m fiber) as the excitation source. Scanning electron microscopy (SEM) images were obtained on a Hitachi SU1510 microscope. Transmission electron microscopy (TEM) was obtained by a 2010 FEF microscope. Energydispersive X-ray photoelectron spectroscopic (XPS) measurements were performed on PHI-5000 Versaprobe. Fourier transform infrared (FTIR) spectra (4000–400 cm-1) in KBr were recorded in a Vector 22 FT-IR spectrophotometer (Bruker, Germany). 2.3. Preparation of UCNPs UCNPs were prepared according to the previous literature (Li and Zhang, 2008). Y (CH3COO)3 (0.78 mmol), Yb (CH3COO)3 (0.2 mmol) and Er (CH3COO)3 (0.02 mmol), 6 mL OA and 17 mL ODE were added into a 100 mL flask and the mixture solution was heated to 160 °C, to form a transparent solution. The mixture solution was cooled down to room temperature naturally. Methanol (10 mL) solution with NaOH (2.5 mmol) and NH4F (4 mmol) was slowly dropped into the flask and stirred for 30 min To removal of methanol, the solution was slowly heated, degassed at 100 °C for 10 min Subsequently, the solution was heated to 300 °C and kept for 1 h at argon protection. After the resulted solution was cooled down naturally, UCNPs were obtained via centrifugation, and washed with ethanol for three times. PAA-UCNPs were synthesized according to the previous method with a modified procedure (Naccache et al., 2009). PAA (300 mg) was mixed with DEG (30 mL) in a 100 mL flask. The mixture solution was heated to 110 °C. Toluene (3 mL) solution with hydrophobic UCNPs (100 mg) was added, and maintained at 110 °C for 1 h under argon atmosphere. Then the mixture solution was heated to 240 °C and kept for 1 h. The resulted solution was cooled down to room temperature naturally, the PAA-UCNPs were collected from the resulted solution with the excess dilute hydrochloric aqueous solution, and washed three times with water. 2.4. Synthesis of the smart sensing material UCNPs (20 mg) and GO (3.5 mg) were dispersed in deionized water (10 mL) by ultrasonication and stirred for 30 min Then, HRP (10 mg), NIPAAM (100 mg), VPBA (25 mg) and MBA (40 mg) were added to the mixture, which was incubated 1.5 h under stirring for pre-polymerizaiton. The oxygen was removed by nitrogen bubbling for 10 min The polymerizaiton was initiated by APS (10 mg) and TEMED (100 μL, 5%, v/v), and then polymerization was carried out at 25 °C for 20 h. The smart sensing material was collected via centrifugation and washed with 0.5% (w/v) SDS 0.5% (v/v) HAc and doubly distilled water in order, which was repeated several times until no template was detected by UV–vis spectrophotometry. Finally, the control (non-imprinted polymer, NIP) was prepared using the same procedure except addition of the template protein.
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2.5. The double responsive of smart material experiments In the experiments, fluorescence measurements were performed on an F-2500 fluorescence spectrometer attached with an external 980 nm laser instead of internal excitation source. The external laser was set at 1 A. For thermo-sensitivity of smart material experiment, 2 mg of smart sensing material or NIP was dispersed in 2 mL of HRP solution with a certain concentration. The mixture was shaken as a function of temperature at 28 and 44 °C for a period of time and centrifuged. The concentration of template protein in the supernatant was measured by a UV–vis at 279 nm. The adsorption capacity (Q) of the protein bond to the smart sensing material is calculated by following equation.
Q = ( C0 − Ct ) V/W Where, C0 and Ct (mg/mL) are the initial concentration and the residual concentration of HRP, respectively. V (mL) represents the volume of the initial solution and W (g) is the weight of the material. For smart material response to pH experiment, 2 mg of smart sensing material or NIP was dispersed in 2 mL of HRP solution with a certain concentration at pH 6 or 9. The mixture was shaken at 28 or 44 °C for a period of time and centrifuged. The concentration of template protein in the supernatant was measured by a UV–vis at 279 nm. 2.6. Adsorption experiments For equilibrium binding experiment, 2 mg of smart sensing material or NIP was dispersed in 2 mL of HRP solution with a certain concentration. The mixture was shaken at 28 °C for a period of time and measured quickly.
The specificity experiment was performed by choosing OVA and BSA as competitive protein. 2 mg of smart sensing material was dispersed in 2 mL of signal (HRP, BSA or OVA) or binary protein (HRP-BSA) solution with a certain concentration. The mixture was shaken at 28 °C for a period of time and determined quickly.
3. Results and discussion 3.1. Preparation of sensing material In this work, UCNPs as fluorescence signal were used to sensing of template protein. Amino-functionalized GO was introduced as support material to enhance mass transfer. Furthermore, NIPAAM was used as thermo-sensitivity functional monomer that allowed for swelling and shrinking in response to temperature to capture or release protein, and VPBA was added to control the glycoprotein capture and release based on pH value changes. Fig. 1 illustrates the principle for the synthesis of the novel smart sensing material. In the first step, the UCNPs (NaYF4: Yb3 þ , Er3 þ ) were prepared through the solvothermal approach in oleic acid (OA) and 1-octadecene (ODE). Due to the organic ligand on the surface of the UCNPs, these nanocrystals were not dispersed in polar solvents, which limited further application. The resulted UCNPs were converted into carboxyl modified UCNPs with hydrophilic by ligand exchange of OA with PAA. In the second step, amino-functionalized GO was coated with carboxyl modified UCNPs through the hydrogen bonding interaction. Subsequently, template glycoprotein, UCNPs-coated GO, monomers NIPAAM and VPBA were copolymerized to form the smart sensing material. After removal of the template glycoprotein, the imprinted cavities were formed. When the template glycoprotein was rebound to the cavities, the fluorescence intensity of smart sensing material was reduced
Fig. 1. Synthesis of smart sensing material based on the UCNPs and GO.
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Fig. 2. TEM and SEM images of UCNPs (a, c) and smart material (b, d).
Fig. 3. (a) Changes of the fluorescence intensity and (b) adsorption capacity of smart sensing material for HRP with a temperature swing between 28 and 44 °C. The error bars were calculated from three parallel experiments.
gradually. The fluorescence of the smart sensing material recovered, when the template HRP was extracted from the smart sensing material. 3.2. Characterization of sensing material The smart material was characterized by TEM, SEM, FTIR and XPS, which verified the successful synthesis of the smart sensing material. TEM and SEM images of UCNPs in Fig. 2(a) and (b) showed that the UCNPs were well shaped with a size of about 50 nm. TEM and SEM images of smart sensing material in Fig. 2
(c) and (d) revealed that the smart sensing material had a size of about 100 nm and covered on the surface of GO. In the FTIR spectra (Fig. S1), the peak of B-O absorption at around 1345 cm 1 and the phenyl ring skeletal vibration at around 1550 cm 1 illustrated the existence of VPBA in smart material. The bands at around 3434 cm 1 and around 1640 cm 1 were attributed to N-H stretching and C ¼O bond vibration, which suggested that the NIPAAM was anchored onto the surface of the material. To confirm the surface composition of smart sensing material, XPS was performed. The XPS survey spectrum (Fig. S2) showed the signals of B 1s at 190 eV, C 1s at 285 eV, N 1 s at 400 eV and O 1s at 531 eV,
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Fig. 4. (a) Changes of fluorescence intensity and (b) adsorption capacity of smart sensing material for HRP at pH 6 and 9. The error bars were calculated from three parallel experiments.
Fig. 5. (a) Fluorescence emission spectra of MIP-smart sensing material and (b) NIP with addition of the certain concentration of HRP solution. Inset is the Stern-Volmer cure. F and F0 represent the fluorescence intensity in presence and absence of HRP.
which indicated that the smart sensing material was synthesized successful, although the signal of the B peak was relatively weak due to its low abundance. 3.3. The double responsive of smart material Thermo-sensitivity materials are well known as a temperature gate for controlling the capture and release of target molecules. To confirm the thermo-sensitivity properties of smart sensing material, the experiments of temperature influence were carried out (Fig. 3). Fig. 3(a) showed the fluorescence intensity of the smart sensing material with the template glycoprotein HRP as a function
of temperature at 28 and 44 °C. The interaction of smart sensing material with HRP revealed obviously temperature dependent onoff fluorescence intensity, which suggested the capture and release for the template HRP upon changes in temperature. We investigated the effect of the temperature on adsorption performance of smart sensing material for HRP (Fig. 3(b)) and found that the adsorption capacity for HRP at 28 °C was larger than that at 44 °C. The result was because the structure of smart sensing material changed with a change in temperature due to the existence of NIPAAM. Furthermore, due to ultra-high specific surface area and π electronic structure of GO, the adsorption capacity of smart sensing material was much higher than that of other smart material (Zhang et al., 2012b, 2014). The pH value is important for the interaction of boronate with cis-diol-containing compounds such as glycans or glycoproteins. Boronate can covalently interact with compounds containing a cis diol to form stable cyclic esters in alkaline solution, whereas the covalent bond dissociates once changing the medium to acidic solution. Boronate affinity imprinted material is more convenience to removal of template because reversible bond between template glycoproteins and boronate can dissociate using an acidic solution. To verify smart sensing material response to pH, the influence of pH value on recognition ability was investigated (Fig. 4). In Fig. 4 (a), the interaction of smart sensing material with HRP revealed conspicuous pH dependent on-off fluorescence intensity between at pH 9 and pH 6, which indicated the recognition of smart sensing material upon changing in pH. The result of adsorption ability experiment showed that the adsorption capacity of smart sensing material was larger at pH 9 than that at pH 6 (Fig. 4(b)). The above results are agreement with the stable bond between glycoprotein and boronate at higher pH values. To further investigate the double responsive, the adsorption ability of smart material response to pH at 44 °C was performed. Results showed that the adsorption capacity of smart sensing material was 31.1 mg g 1 and 56.5 mg g 1 at pH 6 and 9 (44 °C), respectively. 3.4. Adsorption characterization of smart material Adsorption kinetics studies were performed to investigate the adsorption process (Fig. S3). The adsorption rate rapidly increased in 60 min and the adsorption process quickly reached the equilibrium which because the ultra-high specific surface area of GO enhance mass transfer. To further investigate the recognition performance of smart sensing material, the recognition ability was studied through the changes of the fluorescence signal at different concentrations (Fig. 5). As the concentration of HRP increased, the
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Fig. 6. Selectivity behaviours (a) of template glycoprotein and competitive proteins on the MIP-smart sensing material and NIP. Effect of the competitive protein BSA (b) on the recognition of template glycoprotein HRP on the MIP-smart sensing material. Experiments were done by fixing the concentration of HRP and increasing the concentration of BSA. The error bars were from three parallel experiments.
fluorescence of smart sensing material was quenched gradually, which due to the specific affinity interaction between the imprinted cavities within sensing material and template protein. The inset A and B in Fig. 5(a) and (b) was plotted by the Stern-Volmer equation analysis for the smart sensing material and the control in the presence of template protein, respectively.
F0/F = 1 + KSV ⎡⎣ Q⎤⎦ Where, F and F0 are the fluorescence intensity of sensing material in the presence and absence of HRP, respectively, Ksv is the quenching constant of HRP, and [Q] is the concentration of HRP. The ratio of KSV, MIP and KSV, NIP (KSV, MIP and KSV, NIP are the linear slopes of inset A and B in Fig. 5) is defined as the imprinting factor (IF) to evaluate the selectivity of the smart sensing material. Under the optimal conditions, the IF (KSV, MIP/ KSV, NIP) was 3.51, which suggested that the smart sensing material with imprinted cavities could recognition the template protein. To demonstrate the specificity of the smart sensing material, OVA as a glycoprotein and BSA as a non-glycoprotein were used as competitive proteins. A series of single protein and binary protein solution of HRP-BSA were investigated to show the specific recognition ability (Fig. 6). It was clearly seen from Fig. 6(a) that the changes in fluorescence intensity of smart sensing material to HRP were much more obvious than that to the other protein, while the changes in fluorescence intensity of NIP were not significantly different for HRP, BSA and OVA. We found that the fluorescence intensity was not significant affected with the increase of the ratio of CBSA/CHRP (Fig. 6(b)). Thus, these results clearly indicated that the smart sensing material showed specificity for the template protein. 3.5. Detection range and limit To further demonstrate the performance of smart sensing material, the detection range and limit were investigated. The smart sensing material exhibited a linear in the range of 1–10 μM (Table S1) with a correlation of 0.991 for HRP. The detection limit, which was calculated as the concentration of HRP that quenched three times the standard deviation of the blank signal, divided by the slope of the standard curve, was 0.66 μM (Table S1). The precision for three replicate measurements at 6 μM was 1.10% (relative standard deviation). 4. Conclusions In this work, we propose a strategy for the development of
double responsive smart upconversion fluorescence material for glycoprotein. The smart material utilized as recognition element of the fluorescence sensor was prepared by combining the ultra-high specific surface area of GO, highly sensitive of UCNPs and high specific of MIP. The recognition performance of the smart material for glycoprotein was regulated by pH and temperature due to the existence of NIPAAM and VPBA in the recognition element. This strategy opens up new way to construct the fluorescence sensor for facile and quick detection of glycoprotein.
Acknowledgments The authors are grateful for the financial support provided by the National Natural Science Foundation of China (Project No. 21375094 and 31225021), the Ministry of Science and Technology of China (Project No. 2013AA102202) and Innovation Talents of Science and Technology Plan of Yunnan Province (Project No. 2012HA009).
Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.bios.2016.05.056.
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