Chitosan Microgels Embedded with Catalase Nanozyme-Loaded

Feb 17, 2017 - A glucose-responsive closed-loop insulin delivery system represents an ideal form of treatment for type 1 diabetes mellitus. Here, we d...
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Chitosan Microgels Embedded with Catalase Nanozyme-Loaded Mesocellular Silica Foam for Glucose-Responsive Drug Delivery Myung Yoon Kim, and Jaeyun Kim ACS Biomater. Sci. Eng., Just Accepted Manuscript • DOI: 10.1021/acsbiomaterials.6b00716 • Publication Date (Web): 17 Feb 2017 Downloaded from http://pubs.acs.org on February 21, 2017

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ACS Biomaterials Science & Engineering

Chitosan Microgels Embedded with Catalase Nanozyme-Loaded Mesocellular Silica Foam for Glucose-Responsive Drug Delivery

Myungyoon Kim1 and Jaeyun Kim1,2*

1

School of Chemical Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea

2

Department of Health Sciences and Technology, Samsung Advanced Institute for Health

Science & Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Republic of Korea.

* To whom correspondence should be addressed: Jaeyun Kim, [email protected]

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Abstract A glucose-responsive closed-loop insulin delivery system represents an ideal form of treatment for type 1 diabetes mellitus. Here, we develop a glucose-responsive protein delivery system based on chitosan microgels loaded with enzyme-mimicking inorganic nanoparticles. The pH-sensitive chitosan microgels, integrated with glucose-mediated pHlowering enzymatic large-pore mesoporous silica (MCF), were fabricated via an electrospray process. Ceria nanoparticles (CeNPs), which is catalase-mimicking inorganic artificial enzyme with a substantial stability compared to catalase, were incorporated into the MCF along with glucose oxidase. In hyperglycemic conditions, CeNPs successfully decomposed the toxic hydrogen peroxide that was generated from the glucose oxidation reaction mediated by glucose oxidase and regenerate oxygen; this protected glucose oxidase from denaturation. The pH-lowering induced by the enzymatic MCF in high glucose concentration resulted in swelling of the chitosan microgels and the subsequent release of the encapsulated model protein drug, such as bovine serum albumin and insulin. Finally, we successfully demonstrated self-regulated repetitive protein release from the chitosan microgels, which showed a basal release rate under normoglycemic conditions and an enhanced release rate under hyperglycemic conditions.

Keywords: glucose-responsive drug delivery, type I diabetes, enzyme mimetics, ceria nanoparticles, mesoporous silica

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Introduction Diabetes mellitus is defined as a group of metabolic disorders characterized by high blood glucose levels (hyperglycemia).1 Type 1 diabetes (T1D) results from deficient production and secretion of insulin due to the autoimmune destruction of pancreatic β-cells, which regulate blood glucose levels by stimulating liver and muscle cells to take up glucose from blood.2 When left untreated, prolonged hyperglycemia can lead to kidney failure, blindness, and increased susceptibility to infection. In contrast, insulin overdose can lead to fatal hypoglycemia.3,4 Recently, common care for T1D patients requires monitoring of blood glucose levels and insulin injections to maintain normoglycemia; this is known as openloop insulin delivery.5,6 However, owing to the harsh environment of the gastrointestinal tract, insulin must be injected subcutaneously for open-loop insulin delivery, which can be inconvenient and painful, leading to poor patient compliance. Alternatively, a closed-loop insulin delivery system that continuously and specifically releases insulin in response to changing blood glucose levels can be beneficial to patients. One of the typical closed-loop systems integrates a glucose-monitoring moiety and a sensor-triggered insulin-releasing moiety into a single system; these contain polymeric hydrogels that swell or shrink to adjust the insulin release rate depending on blood glucose levels.7 A common glucose-sensitive moiety is glucose oxidase (GOx), which catalyzes the oxidation of glucose to gluconic acid and hydrogen peroxide.8 The pHlowering effect that is derived from the generation of gluconic acid results in swelling of the GOx-entrapped pH-sensitive polymer, which subsequently releases insulin from the polymer matrix.9,10 However, the continuous generation of hydrogen peroxide by GOx is toxic to normal cells and deactivates GOx in response to glucose.11 To resolve this issue,

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catalase (CAT) is commonly added to the closed-loop system to generate harmless oxygen and water by consuming the undesired toxic hydrogen peroxide that is produced by glucose oxidation.12-14 However, the natural enzymes used in previous closed-loop insulin delivery systems have general limitations such as low stability against stringent conditions, high cost, and difficulties tuning the catalytic activity. In this context, replacing natural enzymes with artificial enzymes that have high stability and activity in closed-loop insulin delivery system is highly demanded.15-17 Cerium oxide nanoparticles (CeNPs) have been reported to have excellent antioxidant catalytic activities, similar to the activity of catalase (CAT), and can protect cells against ROS-induced damage.17 Compared to their bulk counterparts, in which most cerium atoms are present in the Ce4+ state, cerium exists in either the Ce3+ (reduced) or Ce4+ (oxidized) state at the particle surface due to oxygen vacancies in the surface of CeNPs. The reversible redox reaction between the two cerium oxidation states on the surface of CeNPs is the origin of the CAT-mimicking property of CeNPs, which decompose hydrogen peroxide. Smaller CeNPs have higher surface area to volume ratios; thus, a higher ratio of Ce3+ to Ce4+ is important for the catalytic activity. Owing to the intrinsic high stability and low cost of inorganic oxide nanoparticles, CeNPs have the potential to replace fragile enzymes such as CAT.18-22 Herein, we report an artificial inorganic enzyme-assisted glucose-responsive protein delivery system based on a pH-responsive hydrogel (Figure 1). Large-pore sized mesoporous silica (MCF), loaded with cross-linked GOx and CeNPs (designated as an enzymatic MCF), was prepared and subsequently encapsulated in pH-responsive chitosan microgels along with a model protein. MCF was used as an enzyme support for GOx and

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CeNPs to decrease the denaturation and loss of GOx from the chitosan microgels.21,22 When a high level of glucose is sensed and oxidized by GOx, the resulting pH-lowering effect in the chitosan microgels leads to the swelling of the chitosan matrix due to the protonation of chitosan chains; this induces the release of the model protein loaded in the chitosan matrix. CeNPs were used as an artificial catalase-mimetic enzyme to decompose hydrogen peroxide and to produce the oxygen that is required for the oxidation of glucose by GOx. The intrinsic autocatalytic properties of CeNPs, which have a higher stability compared to catalase, lead to the enhanced stability of the glucose-responsive closed-loop delivery system.

Materials and Methods Materials. HCl (37%), 1,2,3-trimethylbenzene (TMB), tetraethoxysilane (TEOS), ammonium fluoride (NH4F), glucose oxidase (GOx), catalase (CAT), 6-aminohexanoic acid, chitosan, and glutaraldehyde (GA) were purchased from Sigma–Aldrich. Pluronic 123 (P123) was purchased from BASF. Cerium nitrate hexahydrate (Ce(III)(NO3)3·6H2O) was purchased from Alfa-Aesar. Bovine Serum Albumin (BSA) was purchased from Millipore. Pierce BCA Protein Assay Kit was purchased from Thermo Scientific. Amplex® Red Hydrogen Peroxide/Peroxidase Assay Kit was purchased from Invitrogen. Preparation of MCF. 4 g of triblock copolymer Pluronic P123 was dissolved in an acidic solution (a mixture solution of 10 mL of HCl and 65 mL of water). 5 g of TMB was then added and the resulting solution was heated to 37-40 oC with vigorous stirring for 2 h. 9.2 mL of TEOS was then added and the mixture solution was stirred for 5 min. The resulting solution was transferred to an autoclave and aged at 40 oC for 20 h under quiescent

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conditions. 46 mg of NH4F was added, and the mixture was aged at 140 oC for another 24 h. The resulting precipitate was filtered, washed with water and ethanol, and dried. The resulting powder was calcined in air at 900 oC for 6 h. Synthesis of CeNPs. 6-aminohexane acid (10 mmol) was dissolved in 60 mL of distilled water. The obtained solution was heated to 95 oC and 70 µL of HCl was added to the solution to obtain a pH 5.5. Ce(III)(NO3)3·6H2O (2.5 mmol) dissolved in 50 mL of distilled water was then immediately added into the heated solution. After 2 min, the solution was cooled down to room temperature. The ceria nanoparticles were washed with acetone three times and dispersed in 10 mL of water. Catalytic stability of CeNPs and CAT. 4 µg/mL CeNPs and 0.09 U/mL CAT solution were pre-incubated at various temperatures between 20 and 70 oC for 2 h, and subsequently incubated in a 20 µM hydrogen peroxide at 37 oC for 5 h. 50 µL of the supernatant of each sample was removed for the measurement of the concentration of hydrogen peroxide using the Amplex® Red Hydrogen Peroxide/Peroxidase Assay Kit. The concentration of hydrogen peroxide was calculated from the measured fluorescence (excitation: 530 nm, emission: 590 nm) following the manufacturer’s instruction. Preparation of enzymatic MCF loaded with GOx and CeNPs. MCF was mixed with 200 mg/mL GOx in a sodium phosphate buffer solution (10 mM, pH 7.8), vortexed for 30 s, sonicated for 3 s, and incubated at room temperature under shaking conditions (200 rpm). After 20 min of incubation, to allow for the adsorption of GOx into MCF, the samples were washed with a sodium phosphate buffer (100 mM, pH 8.0) and incubated with a 0.1% GA solution in a phosphate buffer (100 mM, pH 8.0) at 200 rpm for 30 min. After the GA treatment, the samples were washed by a phosphate buffer (100 mM, pH 8.0). The obtained

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samples were mixed with ceria nanoparticles (CeNPs), vortexed for 30 s, and incubated at room temperature under shaking conditions (200 rpm). After 30 min of incubation, to allow for the adsorption of CeNPs into enzymatic MCF, the samples were washed with a sodium phosphate buffer (100 mM, pH 8.0) and incubated with a 0.1% GA solution in a phosphate buffer (100 mM, pH 8.0) at 200 rpm for 20 min. After the GA treatment, the samples were washed by a phosphate buffer (100 mM, pH 8.0). Formation of microgels with enzymatic MCF. An aqueous solution of chitosan (2% w/v) was prepared by dissolving sterilized chitosan powder (molecular weight: ∼200 kDa) in a 1% acetic acid solution. The obtained solution was centrifuged at 10000 rpm to remove undissolved impurities. The enzymatic MCF and BSA as a model drug protein were added and

thoroughly

mixed

with

the

chitosan

solution.

The

weight

ratio

of

chitosan/BSA/enzymes was 2/2/3. The homogeneous mixture was transferred into a 1-mL syringe with an attached blunt tip (a 27-gauge metal needle). The syringe was placed in an electrospray system equipped with a syringe pump. The positive electrode of the electrospray system was connected to the needle, and the negative electrode was connected to a sterile metal receiving container with 40 mL of 5% TPP. The solution was sprayed at high voltage into the receiving container with gentle agitation. The collected particles were washed twice with PBS and concentrated by centrifugation at 2000 rpm. The BSA loading was calculated by subtracting the unadsorbed BSA left in the supernatant from the initial amount of BSA mixed using BCA Protein Assay Kit (Thermo Scientific). Swelling properties of enzymatic MCF@CTS microgels. Enzymatic MCF@CTS microgels were incubated in different concentration of glucose solution (400 mg/dL and

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100 mg/dL) until reaching the equilibrium. Swelling ratio (SR) of microgels was calculated by the following formula, SR (%) = (Ws − Wd) / Wd x 100 where Ws and Wd refer to weight of swollen gels and dry gels, respectively. Validation of H2O2 decomposition. The GOx-loaded MCF (G@MCF) and GOx- and CeNPs-co-loaded MCF (GC@MCF) were incubated in a 400 mg/dL glucose solution at 37 o

C. At predetermined time points, the samples were centrifuged (11,000 rpm, 2 min) and 50

µL of the supernatant was removed for the measurement of hydrogen peroxide generated. pH measurements. After preparation of the enzymatic MCFs and enzymatic MCF@CTS microgels, 1 mL of various solutions (PBS, 100 or 400 mg/dL of a glucose solution) were added to each sample and incubated at 37 oC. At predetermined time points, the sample was centrifuged (3,000 rpm, 2 min) and pH of the supernatant was measured in a pH meter. Characterization. Nitrogen adsorption–desorption isotherms of mesoporous silica particles were measured on a Micromeritics ASAP 2000 apparatus at liquid nitrogen temperature (77 K). The pore size distribution was calculated from the adsorption branch of the isotherm using the Barret–Joyner–Hallenda (BJH) model. Transmission electron microscope (TEM) images were obtained with a JEOL 2100 electron microscope operating at 200 kV. Prior to measurements, the material was supersonically dispersed in ethanol and the suspended particulates were deposited onto a perforated carbon film supported on a copper grid. Scanning electron microscope (SEM) images were obtained with a JEOL JSM6700F. The samples were distributed on carbon tape attached to the sample mount. Before analysis, all of the samples were coated with a thin layer of Pt by sputter coating. Circular dichroism (CD) spectrum was obtained with a Chirascan-Plus CD Spectrometer. The X-ray

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diffraction (XRD) was measured on a Bruker D8 Advance. The UV-Vis spectra and fluorescence were obtained using a Thermo Scientific Varioskan Lux.

Results and Discussion As both GOx and CeNPs are necessary to fabricate a glucose-responsive drug delivery system, we utilized large-pore mesoporous silica (MCF) as a supporting material to co-load GOx and CeNPs. Mesoporous silica materials are attractive vehicles for drug delivery due to their unique features such as their stable mesoporous structures, high surface areas, tunable pore size, large accessible pore volumes, relatively low toxicity, and biocompatibility.23-25 In particular, because MCF has ultra-large pores connected via welldefined window channels, it has been studied as a carrier for relatively large guest molecules including proteins and cytokines.26 The MCFs in this study were 5-µm-sized spherical particulates, and their ultra-porosity was clearly observed in scanning electron microscopy (SEM) images (Figure 2a). The pore size was further characterized by nitrogen sorption, which showed that MCF has 55-nm cellular pores (as determined from the adsorption branch) and 24-nm window channels (as determined from the desorption branch) (Figure 2b). The sizes of the cellular and window pores of MCF were sufficiently large for the loading of large biomolecules such as GOx and even CeNPs. The Brunauer– Emmett–Teller (BET) surface area and pore volume of MCFs were 346 m2/g and 2.4 cm3/g, respectively. We first investigated the effect of GOx loading on ultra-large pore MCFs based on a ship-in-a-bottle approach.27 GOx was first loaded into MCF via a physical adsorption and subsequently crosslinked by glutaraldehyde (GA) via the Schiff base reaction. This resulted

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in larger crosslinked enzyme molecules within the pores of MCFs (Figure 2c). Incubation of GOx-loaded MCFs in 400 mg/dL glucose solution at 37 ºC, used to mimic hyperglycemic conditions, showed the successful generation of hydrogen peroxide (Figure 2d) and a decrease in the pH (Figure 2e) depending on the amount of GOx loaded in MCF. These results indicate that loading and crosslinking GOx in MCFs did not inhibit the catalytic properties; the MCFs could still convert glucose to gluconic acid and hydrogen peroxide as a side product. To regenerate oxygen required in GOx enzymatic reaction by consuming the undesired toxic hydrogen peroxide that is produced by glucose oxidation, CeNPs, which are an artificial inorganic CAT mimic, were synthesized in the aqueous phase via a simple solgel reaction of cerium ions in the presence of 6-aminohexanoic acid. The TEM image shows that the CeNPs were 4.3-nm-sized uniform nanoparticles (Figure 3a). X-ray diffraction (XRD) pattern of CeNPs showed a mixed phase of cubic CeO2 and hexagonal Ce2O3 (Figure S1). The crystalline size estimated by Scherrer equation was 5.4 nm, which is matched with the size measured on TEM. Due to the terminal amine groups of the surface-stabilizing agent, 6-aminohexanoic acid, the ζ-potential of CeNPs was +33 mV (Figure S2a), which led to a good dispersion of CeNPs in water. The hydrodunamic size of CeNPs in water was 16 nm (Figure S2b). We tested the CAT-mimicking activity of CeNPs using a hydrogen peroxide assay. The concentration of hydrogen peroxide was successfully decreased depending on the concentration of incubated CeNPs in solution, representing the CAT-mimicking property of the water-dispersible CeNPs (Figure 3b). To test the catalytic stability of CAT-mimicking CeNPs compared to the native CAT enzyme, the catalytic activity was measured at different temperatures (20-70 ºC) using hydrogen peroxide assay

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and the relative activity was calculated based on the activity of each sample at 37 oC (Figure 3c). The catalytic activity of CAT varied significantly depending on temperature, showing a significant decrease in activity at higher temperature. In contrast, CeNPs showed almost constant catalytic activity regardless of working temperature. This demonstrates that the inorganic CeNPs have an intrinsic high catalytic stability as an artificial enzymemimetics compared to the natural enzyme counterpart. Using CAT-mimicking artificial enzyme, we next prepared the enzymatic MCF by co-loading GOx and CeNPs into the pores of MCF via glutaraldehyde (GA) crosslinking. Because the surface of CeNPs was coated with 6-aminohexanoic acid, the surface amine group of CeNPs and amine groups of GOx could participate in GA-mediated crosslinking in the MCF pores (Figure 3d). To determine the responsiveness to glucose, GOx-loaded MCF (G@MCF) and GOx- and CeNPs-co-loaded MCF (GC@MCF) were incubated in a 400 mg/dL glucose solution at 37 ºC and the production of hydrogen peroxide was measured (Figure 3e). The amount of GOx loaded in both samples was the same. Both G@MCF and GC@MCF samples resulted in the generation of hydrogen peroxide. However, the concentration of hydrogen peroxide in the GC@MCF-treated glucose solution was lower than that of the G@MCF-treated solution, indicating that the hydrogen peroxide generated by GOx was immediately decomposed by the CeNPs. The observed pH change of the hyperglycemic solutions also showed a similar result (Figure 3f). Compared to the control MCF sample, the pH values of G@MCF- and GC@MCF-treated solutions significantly decreased over time. Moreover, the pH was lower in the GC@MCF-treated solution than in the G@MCF-treated solution, indicating that a higher amount of glucose was converted to gluconic acid in the GC@MCF-treated solution. This result is likely

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derived from the regeneration of oxygen by the catalytic activity of CeNPs because oxygen is consistently needed in the GOx catalytic reaction. Therefore, the use of CeNPs is beneficial to the GOx activity for sensing glucose and lowering the pH of the environment. We next prepared a glucose-responsive protein delivery system based on pHresponsive chitosan microgels that were integrated with the enzymatic MCFs and a model protein drug (Figure 4a). The microgels were made of chitosan due to its successful use in medicine, biocompatibility, and ease of protonation (pKa: 6.2-6.8).28 Chitosan microgels were synthesized by a one-step process with a high-voltage electrospraying system to obtain monodispersed particles.29 Tripolyphosphate (TPP) was used to crosslink the chitosan polymer chains through electrostatic interactions. The homogeneous mixture of GC@MCF and bovine serum albumin (BSA) as a model drug protein in a sterilized chitosan solution (2% w/v in a 1% acetic acid solution) was transferred into a syringe and sprayed at a high voltage (12 kV) onto the receiving container, which was filled with a 5% TPP solution for cross-linking. By optimizing the flow rate of the mixture solution, spherical and monodisperse microgel particles with a diameter of 650 µm were obtained as observed on optical microscopy (Figure 4b). The chitosan microgels integrated with enzymatic MCF (designated as enzymatic MCF@CTS) showed a more turbid image compared to the bare CTS microgels, due to the encapsulation of MCF particles. To determine the glucose-responsive properties, bare CTS microgels and enzymatic MCF@CTS microgels were incubated in a hyperglycemic condition (400 mg/dL glucose) and in a normoglycemic level (100 mg/dL glucose), respectively, and the pH of the solution was monitored (Figure 4c). Bare CTS microgels showed similar slight pH decreases in both the hyperglycemic and normoglycemic solutions. In contrast, enzymatic MCF@CTS

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microgels resulted in a steep decrease of the solution pH from 7.25 to 6.80 in normoglycemic conditions. Moreover, the enzymatic MCF@CTS microgels caused a larger pH decrease (to 6.38) in the hyperglycemic solution. These results represent that the enzymatic MCF encapsulated in chitosan microgels successfully lowered the pH in response to the high level of glucose in hyperglycemic solution. As chitosan has a pKa around 6.8, the chitosan matrix can be significantly protonated below its pKa and the protonation of the primary amines of chitosan causes the microgels to swell due to the electrostatic repulsion between the positively charged chitosan chains.28 The swelling of enzymatic MCF@CTS microgels in 100 and 400 mg/dL glucose solution was 1,255% and 1,640%, respectively (Figure S3), representing that higher glucose condition resulted in enhanced swelling of chitosan microgels. This is probably attributed to the higher protonation of chitosan chains and subsequent higher repulsions between polymer chains in lower pH conditions achieved by enzymatic MCF in higher glucose level. The resulting gel swelling could facilitate the release of the encapsulated protein drugs. To evaluate the glucose-responsive release properties of the chitosan microgels integrated with enzymatic MCFs, BSA-loaded enzymatic MCF@CTS microgels were prepared (encapsulation efficiency, 86.9 ± 1.2%), incubated in no-glucose condition and glucose solutions (100 and 400 mg/dL), and then the released BSA was measured over time (Figure 5a). The amounts of released BSA were dependent on the concentration of glucose in the incubating solution. Compared to the no-glucose conditions and normoglycemic conditions, incubation in the hyperglycemic solution clearly showed a much faster release profile, indicating that the pH-lowering effect induced by the enzymatic MCF encapsulated in the CTS microgels caused the microgels to swell, thereby enhancing

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the release of the model protein loaded in the microgels. To check the protein stability in the presence of H2O2 generated by glucose oxidase in microgel, we incubated insulin in the H2O2 solution (1 mM, Figure 3e), mimicking H2O2 level generated by glucose oxidase in microgel. The insulin exposed to H2O2 and the intact insulin were analyzed in circular dichroism (CD) spectroscopy (Figure S4). CD spectra of both insulins were almost similar, representing that stability of insulin was maintained under such concentration of H2O2 that can be produced by the enzymatic microgels. To mimic the repetitive alternation of glucose levels that a patient experiences in daily life, we applied alternating hyperglycemic and normoglycemic conditions every hour and monitored BSA that was released into solution (Figure 5b). Microgels successfully responded to the changes in the glucose level and the on-off release of the model protein was achieved. This confirmed the glucoseresponsive and self-regulated activity of the enzymatic MCF@CTS microgels. For the potential application to the treatment of diabetes, insulin was also encapsulated in enzymatic MCF@CTS microgels (encapsulation efficiency, 60.5 ± 1.6%) and tested for glucose-responsive release (Figure S5). Consistent to the results from BSA release, hyperglycemic condition led to higher release rate of insulin from the microgels than normoglycemic condition and the insulin release was actuated by repetitive alternation of glucose levels, representing the enzymatic MCF@CTS microgels would be potentially applicable to glucose-responsive insulin delivery system in T1D. Most natural enzymes have intrinsic drawbacks, such as low long-term stability, loss of activity upon exposure to the environment, difficulties in recovery and recycling, and high cost.30,31 When stable inorganic CeNPs with excellent antioxidant catalytic

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activities were used as an alternative to catalase, glucose-responsive protein release was successfully achieved. The preparation of CeNPs is facile and inexpensive and their ROSscavenging activity is almost permanently regenerated due to the autocatalytic redox reaction between Ce3+ and Ce4+, which is involved in the decomposition of the hydrogen peroxide generated by GOx. Therefore, this artificial inorganic enzyme-involved system has the potential to be used for the treatment T1D.

Conclusions In summary, we have developed chitosan microgels that can be used in an artificial enzymatic system for glucose-responsive delivery of proteins. Chitosan microgels, integrated with large-pore mesoporous silica loaded with GOx and CeNPs, responded to high glucose levels, resulting in the self-regulated release of a model protein under in vitro conditions

that

mimicked

the

repetitive

change

between

hyperglycemia

and

normoglycemia. Due to the diverse advantages of the artificial inorganic enzyme that we used, this chitosan microgel system may provide a useful plat-form for glucose-responsive insulin delivery systems for diabetes therapy. Looking forward, the development of artificial inorganic enzymes that mimic glucose oxidase may lead to the development of robust glucose-sensitive systems by replacing all natural enzymes in current closed-loop insulin delivery systems.

Supporting Information The Supporting Information is available in the internet at http:///pubs.acs.org.

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Author information Corresponding Author *J. Kim. E-mail: [email protected]. Tel.: +82-31-290-7252 Notes The authors declare no competing financial interest.

Acknowledgement

This work was supported by grants funded by the National Research Foundation under the Ministry of Science, ICT and Future Planning (2010-0027955, 2015R1A2A2A01005548) and a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare (HI14C0211), Republic of Korea

References (1) Bratlie, K. M.; York, R. L.; Michael A.; Invernale, M. A.; Langer, R.; Anderson, D. G. Materials for diabetes therapeutics. Adv. Healthc. Mater. 2012, 1, 267–284. (2) Dabelea, D. The accelerating epidemic of childhood diabetes. Lancet. 2009, 373, 1999–2000. (3) Scognamiglio, V. Nanotechnology in glucose monitoring: advances and challenges in the last 10 years. Biosens. Bioelectron. 2013, 47, 12–25. (4) Heinemann, L. New ways of insulin delivery. Int. J. Clin. Pract. 2011, 65, 31–46.

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(5) Ismail-Beigi, F. N. Glycemic management of type 2 diabetes mellitus. N. Engl. J. Med. 2012, 366, 1319–1327. (6) Owens, D. R. New horizons - alternative routes for insulin therapy. Nat. Rev. Drug Discovery. 2002, 1, 529–540. (7) Zimmet, P.; Alberti, K. G. M. M.; Shaw, J. Global and societal implications of the diabetes epidemic. Lancet 2010, 375, 2215–2222. (8) Sandip, B. B.; Mahesh V. B.; Rekha S. S.; Laxmi, A. Glucose oxidase - an overview. Biotechnol. Adv. 2009, 27, 489–501. (9) Ricci, F.; Moscone. D.; Tuta, C. S.; Palleschi, G.; Amine, A.; Poscia, A.; Valgimigli, F.; Messeri, D. Novel planar glucose biosensors for continuous monitoring use. Biosens. Bioelectron. 2005, 20, 1993–2000. (10) Cornelia, W. E.; Jacqueline, M. T. Klein, G.; Marieke, A.; Johannes, L.; Johannes, G. Accuracy of bedside glucose measurement from three glucometers in critically ill patients. Crit. Care Med. 2008, 36, 3062–3066. (11) Zhen, Gu.; Alex, A.; Aimetti.; Wang, Q.; Dang, T. T.; Zhang, Y.; Veiseh, O.; Cheng, H.; Robert, S. L.; Anderson, D. G. Injectable nano-network for glucose-mediated insulin delivery. ACS Nano 2014, 7, 4194–4201. (12) Hussain, A. M. P.; Sarangi, S. N.; Kesarwani, J. A.; Sahu, S. N. Au-nanocluster emission based glucose sensing. Biosens. Bioelectron. 2011, 29, 60–65. (13) Jiang, L. C.; Zhang, W. D. A highly sensitive nonenzymatic glucose sensor based on CuO nanoparticles-modified carbon nanotube electrode. Biosens. Bioelectron. 2010, 25, 1402–1407.

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(24) Xia, T.; Kovochich, M.; Liong, M.; Meng, H.; Kabehie, S.; George, S.; Zink, J. I.; Nel, A. Polyethyleneimine coating enhances the cellular uptake of mesoporous silica nanoparticles and allows safe delivery of siRNA and DNA constructs. ACS Nano 2009, 3, 3273–3286. (25) Cha B. G.; Piaob, Y.; Kim, J. Asymmetric nanoparticle assembly via simple mechanical pressing using relative hardness of materials. Mater. Res. Bull. 2015, 70, 424–429. (26) Han, Y.; Lee, S. S.; Ying, J. Y. Spherical siliceous mesocellular foam particles for high-speed size exclusion chromatography. Chem. Mater. 2007, 19, 2292-2298. (27) Lee, J.; Na, H. B.; Kim, B. C.; Lee, J. H.; Lee, B.; Kwak, H. J.; Hwang, Y.; Park, J. G.; Gu, M. B.; Kim, J.; Joo, J.; Shin, C.H.; Grate, W. J.; Hyeon, T.; Kim, J. J. Magnetically-separable and highly-stable enzyme system based on crosslinked enzyme aggregates shipped in magnetite-coated mesoporous silica. J. Mater. Chem. 2009, 19, 7864–7870. (28) Kumar, M. N. V.; Muzzarelli, R. A.; Muzzarelli, C.; Sashiwa, H.; Domb, A. J. Chitosan chemistry and pharmaceutical perspectives. Chem. Rev. 2004, 104, 6017– 6084. (29) Gu, Z.; Dang, T. T.; Ma, M.; Tang, B. C.; Cheng, H.; Jiang, S.; Dong, Y.; Zhang, Y.; Anderson, D. G. Glucose-responsive microgels integrated with enzyme nanocapsules for closed-loop insulin delivery. ACS Nano 2013, 7, 6758–6766. (30) He, W.; Liu, Y.; Yuan, J.; Yin, J. J.; Wu, X.; Hu, X.; Zhang, K.; Liu, J.; Chen, C.; Ji, Y.; Guo, Y. Au@Pt nanostructures as oxidase and peroxidase mimetics for use in immunoassays. Biomaterials 2011, 32, 1139-47.

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Figures

Figure 1. Schematic of the glucose-responsive chitosan microgel encapsulating enzymatic MCF and model protein drugs. The enzymatic MCF was loaded with crosslinked glucose oxidase and ceria nanoparticles in its main pores. The simultaneous occurrence of the glucose oxidation reaction and the decomposition of hydrogen peroxide in the enzymatic MCF lead to the reversible pH-responsive swelling of chitosan microgels and the subsequent glucose-responsive release of the protein.

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Figure 2. a) High-magnification and low-magnification (inset) SEM images and b) N2 adsorption-desorption isotherms and pore size distributions (inset) of the large-pore mesoporous silica (MCF). c) MCF was loaded with crosslinked GOx in its main pores. d) H2O2 assay and e) pH change of the hyperglycemic solution (400 mg/dL) after incubation with GOx-loaded MCF with different GOx loadings. Error bars, mean ± s.d. (n=3).

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Figure3. a) TEM image of CeNPs. b) H2O2 assay by incubation of different concentration of CeNPs in H2O2 solution. c) Comparison of the enzymatic stability of CeNPs and CAT at different temperatures. d) MCF was loaded with crosslinked GOx and CeNPs in its main pores. Change of catalytic activity to decompose H2O2 of catalase and CeNPs over time. e) H2O2 generation after 6 h and f) pH change over time by incubation of bare MCF, GOxloaded MCF (G@MCF), and GOx and CeNPs-co-loaded MCF (GC@MCF) in 400 mg/dL glucose solution at 37 oC. Error bars, mean ± s.d. (n=3).

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Figure 4. a) Schematic illustration and b) optical microscope image of enzymatic MCFloaded microgels. c) pH changes in the incubating medium of bare CTS microgels and enzymatic MCF@CTS microgels at different concentration of glucose. Error bars, mean ± s.d. (n=3).

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Figure 5. a) In vitro protein release profiles from enzymatic MCF-loaded CTS microgels in different glucose concentrations. e) Self-regulated glucose-responsive release profile of enzymatic MCF-loaded CTS microgels exposed to repetitive alternations between hyperglycemic and normoglycemic conditions. Error bars, mean ± s.d. (n=3).

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Table of Contents

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