Enzyme Induced Formation of Monodisperse Hydrogel Nanoparticles

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Enzyme Induced Formation of Monodisperse Hydrogel Nanoparticles Tunable in Size Vera Bocharova,*,† Danna Sharp,§ Aaron Jones,§ Shiwang Cheng,† Philip J. Griffin,‡ Alexander L. Agapov,§ Dmitry Voylov,§ Yangyang Wang,† Alexander Kisliuk,† Artem Melman,∥ and Alexei P. Sokolov†,§ †

Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6211, United States Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, United States § Department of Chemistry, University of Tennessee, Knoxville, Tennessee 37996-1600, United States ∥ Department of Chemistry & Biomolecular Science, Clarkson University, Potsdam, New York 13699-5810, United States ‡

ABSTRACT: We report a novel approach to synthesize monodisperse hydrogel nanoparticles that are tunable in size. The distinctive feature of our approach is the use of a multicopper oxidase enzyme, laccase, as both a biocatalyst and template for nanoparticle growth. We utilize the ferroxidase activity of laccase to initiate localized production of iron(III) cations from the oxidation of iron(II) cations. We demonstrate that nanoparticles are formed in a dilute polymer solution of alginate as a result of cross-linking between alginate and enzymatically produced iron(III) cations. Exerting control over the enzymatic reaction allows for nanometer-scale tuning of the hydrogel nanoparticle radii in the range of 30− 100 nm. The nanoparticles and their growth kinetics were characterized via dynamic light scattering, atomic force microscopy, and UV−vis spectroscopy. This finding opens up a new avenue for the synthesis of tunable nanoscale hydrogel particles for biomedical applications.

1. INTRODUCTION Various organic1,2 and inorganic3,4 nanoparticles ranging in size from 2 to 100 nm are a central topic in current biochemical and medical research. Due to their unique size range, nanoparticles are capable of crossing numerous biological barriers within the human body,5 allowing for more efficient drug delivery5 and more reliable medical diagnostics.6 However, concerns about potential toxicity and excretion pathways of many nanoparticles7,8 have shifted the main focus of preclinical research toward the development of synthetic strategies to produce biodegradable and biocompatible nanoparticles.7−9 Various hydrogel-based nanoparticles10−22 have been considered promising injectable materials for diagnostics and drug delivery because of their good biocompatibility and high permeability for oxygen and soluble metabolites. Despite significant advances in the synthesis of hydrogel-based nanocarriers,10−22 fabrication methods leading to size-tunable biocompatible nanoparticles have not yet been fully developed. Currently, hydrogel nanoparticles are either gelled chemically11,12 via various cross-linking polymerization reactions or physically12−22 by using hydrophobic and ionic interactions. Size limitation is a major challenge to grow particles on the nanoscale by means of chemical polymerization.11,12 To overcome this difficulty, various self-assembly methods based on physical interactions13−22 have been developed. However, the limited number of biocompatible components that can be naturally assembled into nanogels and the lack of flexibility within each designed system to be easily adjusted to different © 2015 American Chemical Society

monodisperse sizes are drawbacks in existing self-assembled nanogel particles. The ability to adjust the size of nanogel particles within the same delivery system while preserving their monodispersity is extremely important for effective drug administration to the numerous cells and cellular compartments of the body. Furthermore, taking into account that the size of nanoparticles is strongly connected to their drug delivery profile,23−25 adjustable nanogels will provide a desired versatility in the drug release kinetics by variation of particle size. Other documented methods for preparation of hydrogels with tunable sizes such as nanolithography,11,12 microfluidics11,12 and so forth are deficient because they are costly and difficult to scale up. In this paper, we have described a novel approach to produce monodisperse hydrogel nanoparticles that effectively overcome the most prominent limitation of traditional self-assembly based systems by developing nanoparticles that are tunable in size. The distinctive feature of our study was the utilization of an enzyme as both a biocatalyst and a template for nanoparticle growth. This approach allows us to control the size of the growing particles by adjusting the speed of the enzymatic reaction and to promote the nanoscale growth of the particles using the surface of the nanometer size enzymes as a template. Received: January 15, 2015 Revised: March 6, 2015 Published: March 9, 2015 2557

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measuring spectra and deriving absorbance at 508 nm. Absorbance was recalculated to the concentration of ferrous cations by using the Lambert−Beer law, where the molar extinction coefficient36 of the [Fe(phen)3]2+ complex at λ = 508 nm is ε512 = 11.1 mM−1 cm−1. All UV−vis measurements were performed in 1 mL of poly(methyl methacrylate) (PMMA) cuvettes at room temperature. The effect of oxygen presence on iron(III) production was monitored in a reaction mixture containing 0.5 U/mL laccase. The two separate vials containing laccase in 50 mM of acetate buffer and 0.72 mM iron in water were bubbled with argon gas for 20 min before combining and measuring. Midway during the reaction with argon present, the sample was thoroughly mixed in order to enrich the solution with oxygen. Nanogel Growth Kinetics. To produce nanogel particles, the following ingredients were mixed to the final concentrations of 0.07 wt % sodium alginate, 0.02 mg in 1.4 mL (0.262 U) laccase, and 0.0714 M Na2SO4. Final solutions were run through 0.22 μm PES filters until clear solutions were achieved. FeSO4 was filtered separately and added to the samples at the start of measurements for resulting concentrations of 0.36 and 3.6 mM. The total volume of the mixtures was adjusted to 1.4 mL. To study the dynamics of particle growth and determine their sizes, dynamic light scattering (DLS) was employed. DLS measurements were immediately initiated upon the addition of the FeSO4 to all samples. Correlation curves were collected every minute over a period of 20 h using an ALV-7004/USBFAST digital correlator. Scattering intensity was measured at a 90° angle with respect to incident light. A solid state laser of 671 nm wavelength was used as the light source. All scattered light was collected with a lens and objective directed into a single mode optical fiber and split between two avalanche photodiode detectors. The use of two detectors allowed for cross-correlation enabling access to an extended dynamic range and reduced noise. Data Analysis. The intensity correlation function was calculated using the ALV-correlator software v.3. It was found that the normalized intensity correlation function (ICF, where ICF = g2(t) − 1) of the particles in the sample could be fit with three different equations throughout the growth process. For both concentrations of iron, the KWW stretched exponential function fit the ICF data best in the early stages of the growth process (regime I):

Although enzymatic reactions have been previously employed to initiate the gelation of polymers,26−30 to the best of our knowledge, formation of hydrogel nanoparticles due to enzyme activity has not been reported in the literature. We used laccase (a multicopper enzyme) from Trametes versicolor, which has the ability to oxidize iron(II) cations31,32 and alginate biocompatible polymer, which can be cross-linked with iron(III) cations.33−35 In our earlier papers, it was demonstrated that electrochemically induced conversion of iron(II) cations to iron(III) cations produced immediate gelation of alginate. Since rate conversion of iron(II) was controlled electrochemically, the growth of ultrathin films of iron(III) cross-linked alginate gels with controlled thickness33,34 was achieved. The main difference that distinguishes our current study from previous ones33,34 is the utilization of laccase enzymes to control the redox state of iron cations on the nanoscale.

2. EXPERIMENTAL SECTION Chemicals and Reagents. Sodium alginate and laccase from Trametes versicolor (E.C. 1.10.3.2) were purchased from Sigma-Aldrich. Sodium sulfate, iron(II) sulfate, 1,10-phenenthroline, and phosphate buffer solution saline (PBS) were purchased from Fisher Scientific. All chemicals were used as supplied without further purification. All solutions were prepared using ultrapure water (18.2 MΩ·cm; Barnstead Epure) and experiments performed at ambient temperatures, 25 °C ± 2 °C. The pH of the system was measured using an Accumet AB15 Plus pH meter from Fisher Scientific. Experimental Design. Bulk Gelation Study. To determine the kinetics of bulk gelation, changes in dynamics of four solutions with varying concentrations of FeSO 4 were monitored. All solutions were made in 50 mM sodium sulfate with 0.67 wt % alginate. Solution I additionally contained 1.67 mM FeSO4, and 0.1 mg (1.31U) of laccase. It exhibited no bulk gelation within 24 h of monitoring. Solution II contained 15 mM FeSO4 and 0.1 mg (1.31U) laccase and demonstrated bulk gelation after approximately 18 h. Solution III contained 32 mM FeSO4, 0.1 mg of laccase, and 0.67 wt % alginate. This solution turned into a gel after 6 h of the reaction. The control solution contained 15 mM FeSO4, with no laccase, and only began to show signs of gelation after 3 weeks. Ferroxidase Activity Assay. Using UV−vis spectroscopy, the kinetics of conversion of iron(II) to iron(III) by laccase was monitored at 400 nm for 20 min. The 2 mL of reaction mixtures at pH 6 contained 50 mM sodium acetate buffer and different concentrations of laccase (0, 0.1, 0.5, and 1 U/mL). Iron(II) sulfate at the concentration of 0.72 mM was added in each of these solutions just before the measurements. Initial pH of the solutions was 6 and remained constant during the measurements. The kinetics of the enzymatic reaction was monitored via optical absorption of the iron(III) acetate complex at 400 nm. Consumption of iron(II) was observed by measuring the optical absorbance of the complex ([Fe(phen)3]2+ formed by 1,10-phenanthroline and iron(II) cations) at 508 nm. The stock solution contained 0.5 U/mL of laccase and 0.72 mM iron(II) sulfate all dissolved in 50 mM acetate buffer. A 100 μL aliquot from the stock solution was taken approximately every 2 min and mixed with 100 μL (0.167 mM) of 1,10 phenanthroline with another 1.8 mL of water for a total volume of 2 mL. A control without laccase was tested in the same manner. The presence of a [Fe(phen)3]2+ complex was detected by

2 ⎛ ⎛ t ⎞β⎞ g (t ) − 1 = ⎜A × exp⎜ − ⎟ ⎟ + y0 ⎝ τ⎠ ⎠ ⎝ (2)

(1)

where A is the amplitude, t is the lag time, τ is the characteristic decay time, and β is the stretching parameter, being ∼0.6 during this initial stage of gelation. As growth continued in both samples (regime II), the stretching parameter increased from β = 0.6 to β = 1 such that the ICF was best described by a single exponential function: 2 ⎛ ⎛ t ⎞⎞ g(2)(t ) − 1 = ⎜A × exp⎜ − ⎟⎟ + y0 ⎝ τ ⎠⎠ ⎝

(2)

Late in the growth process (>300 min) of the 3.6 mM FeSO4 sample, the appearance of a second process was observed (regime III). It was found that the ICF at this longer time was best fit with a superposition of one single and one stretched exponential function, such that 2558

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Chemistry of Materials 2 ⎛ ⎛ t ⎞ ⎛ t ⎞β⎞ g(2)(t ) − 1 = ⎜A1 × exp⎜ − ⎟ + A 2 × exp⎜ − ⎟ ⎟ ⎝ τ1 ⎠ ⎝ τ2 ⎠ ⎠ ⎝

+ y0

3. RESULTS AND DISCUSSION Bulk Gelation. To determine conditions required for bulk gelation in the presence of the enzyme, visual inspection was adopted to study the sol−gel phase transition by varying the initial concentration of iron(II) sulfate while keeping alginate constant at 0.67 wt %. During these studies, we found that a continuous bulk gel was formed when the iron(II) cation concentration exceeded 10 mM. Below this concentration, either formation of chunks of gel or no gel formation was observed. A strong dependence between gelation time and iron(II) concentration was observed. With an increase in iron(II) concentration from 15 mM to 36 mM, the gelation time decreased from 18 to 6 h. The solution with 15 mM iron(II) and 0.67wt % of alginate resulted in no gelation within 18 h as demonstrated by inversion of the container (Figure 1A). The bulk gel was obtained after 18 h in the presence of 1.31 U of laccase, 15 mM of iron(II), and 0.67wt % of alginate as presented in Figure 1B. However, after 3 weeks of exposure to ambient conditions, the solution without any enzymes did show signs of gelation likely due to the oxidation of iron(II) to iron(III) by atmospheric oxygen.

(3)

The diffusion coefficient, D, was calculated using the characteristic decay times from these fitting procedures according to the following relation:

D=

1 τq2

(4)

where q is the scattering wavevector. The hydrodynamic radius of the particles, RH, was calculated using the Stokes−Einstein equation: D=

kBT 6πηRH

(5)

where η represents the viscosity of the system. In the scenario of nanoparticle growth, initial viscosity was twice higher than the viscosity of water. Atomic Force Microscopy. Atomic force microscopy studies of alginate gel were performed in tapping mode using a commercial instrument (Asylum Cypher). The calculation of the size distribution was performed using the WSxM image analysis program. For the image analysis procedure, single particles were located on the images, and the width and height were determined from the image cross-section analysis. The profile broadening was taken into consideration using the approximation that the tip radius is equal to the curvature of the scanning object. The volume of the particle was calculated using the volume of a spherical cap and accounted for the change in particle shape due to the surface confinement. The radius of the particle was calculated based on the assumption that the volume of a spherical particle is equal to the volume of a spherical cap. Viscosity Measurements. To determine the viscosity of the alginate solution, rheological measurements were conducted on samples containing 1 and 0.07 wt % of alginic acid. Experiments were performed by using Cannon-Ubbelohde Dilution Viscometer (model B941) at 18 °C. The loading procedure took approximately 1 min, and we repeated our measurements five times to reduce the measurement error. To get the absolute viscosity of the solution, we compared the flow time of the solution with that of pure water on the same geometry and testing conditions. The viscosity of 0.07 wt % was found to be 2.11 cP, which was 2.11 times of its solvent viscosity. According to the dilute solution viscosity theory, our 0.07 wt % solution was in the dilute limit. For the 1 wt % sample, we performed a creep shear measurement on AR 2000ex (TA Instruments) to directly measure the zero shear viscosity. To ensure the accuracy of our measurement, we chose a cone plate with a 60 mm diameter, 2° in cone angle, and 49 μm truncation length. The creep stress was set to be 10 Pa. During the measurements, the temperature was maintained at 18 °C by the bottom Peltier plate. The viscosity was found to be 131.4 cP by the linear dependence of compliance and time. To determine the molecular weight of alginate, we measured four dilute solutions with different alginate concentrations. The intrinsic viscosity for zero concentration of alginate was found to be 1340 mg/L. Following the Mark−Houwink equation for alginate in water,37 the molecular weight of alginate was estimated to be 333 000 g/ mol.

Figure 1. Alginate solution containing Fe2+ cations in the absence (A) and presence (B) of laccase. (C) Kinetics of conversion of 0.72 mM of iron(II) cations in the presence of laccase with concentrations of 1 U/ mL (upper blue line), 0.5 U/mL (red line second from top), 0.1 U/ mL (green line second from bottom), and 0 U/mL (bottom black line) in 50 mM acetate buffer. The inset represents the change in iron(II) concentration during the reaction with 0.5 U/mL (bottom bright red line) and 0 U/mL (upper black line) of laccase measured at 508 nm via absorbance of the 1,10-phenantroline−iron(II) complex. (D) Influence of oxygen presence on enzyme conversion kinetics of 0.72 mM of iron(II) cations in the presence of 0.5 U/mL (middle dark red) in acetate buffer recorded at 400 nm after argonation followed by oxygenation of the solution. The moment of oxygenation of the solution is indicated with the arrow. The kinetics for 0 U/mL (bottom line) and 0.5 U/mL (upper line) of laccase are given for comparison. 2559

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Figure 2. AFM images of (A) an undiluted mixture containing laccase, alginate, and 3.6 mM of iron(II) cations after 60 min of the reaction; (B) laccase protein adsorbed from 0.02 mg in 1.4 mL, and (C) laccase mixed with alginate polymer.

Figure 3. Time evolution of the normalized intensity correlation function (ICF = g(2)(t) − 1) for (A) 0.36 mM and (B) 3.6 mM Fe2+ cations. Selected fittings (solid lines) and corresponding hydrodynamic radii of nanogel particles for (C) 0.36 mM at time 80 min, (D) 3.6 mM at time 50 min, and (E) 3.6 mM at 700 min with deconvolution of the fitting (dashed and dotted lines).

Ferroxidase Activity of Laccase. During visual monitoring of the bulk gel formation, it was noticed that the solution changed hue from colorless to yellow (Figure 1). This observation prompted us to initiate a series of spectroscopic studies of the activity of laccase in the presence of iron(II) cations in acetate buffer and without alginate present to understand the underlying mechanisms responsible for the gelation of alginate. The formation of a colored complex between acetate and iron(III) cations has long been used to monitor concentrations of ferric ions.38 During the reaction in acetate buffer, the characteristic change in color (from colorless to yellow) during the experiment time (∼20 min) was observed. Here, we consider that the observed effect of the solution color change originates from the formation of the iron(III)−acetate complex. The kinetics of iron(III)−acetate complex formation for different concentrations of laccase was followed optically by measuring absorption at 400 nm. The results are presented in Figure 1C. The solution without enzymes remained colorless throughout the duration of the experiment. These results and observations suggest that the oxidation of iron(II) to iron(III) cations was driven by the enzyme while direct oxidation of ferrous cations by dissolved oxygen did not proceed at any appreciable rate under these conditions. Assuming that formation of the complex occurs immediately upon formation of iron(III) cations, the graph in Figure 1C can be interpreted as the kinetics of the iron(III) cations produced by the enzyme, whereas the increase in

enzyme concentration correlates with an increase in the rate of iron(III) production. Because absorption of the acetate−iron(III) complex varies widely with pH, we independently quantified the rate of iron(II) consumption during the reaction using complexation of iron(II) with 1,10-phenanthroline. Aliquots from the solution containing 0.5 U/mL and 0 U/mL of enzymes with 0.72 mM iron(II) in acetate buffer were measured approximately every 2 min. The change in iron(II) concentration as a function of time is presented in the inset of Figure 1C. In the presence of 0.5 U/mL of enzyme, more than half of the initial iron(II) concentration is consumed over a period of 10 min. As expected, rates of iron(II) cation consumption and of iron(III) cation formation measured by these two independent methods were very similar. In the absence of enzymes, the concentration of iron(II) remained unchanged within the same period of time (top line in inset, Figure 1C), indicating that a nonenzymatic oxidation of iron(II) cations with only dissolved oxygen under these conditions was very slow. To evaluate the role of oxygen in iron(II) oxidation, a solution of 0.5 U/mL of enzyme and a solution of 0.72 mM of iron(II) were bubbled with argon for 20 min. These solutions were mixed together prior to UV−vis measurements. The result of the UV−vis measurement is demonstrated in Figure 1D (middle curve). In comparison with the same solution without argon bubbling (Figure 1D, upper curve), a significantly slowed rate of formation of the iron(III)−acetate complex was detected. In the middle of the reaction (as pinpointed by the 2560

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Figure 4. Evolution of hydrodynamic radii and the stretching factor β for nanogel particles during growth for (A) 0.36 mM and (B) 3.6 mM of iron cations. The green dashed lines indicate the system data prior to addition of iron(II). The three marked regimes correspond to lag phase (I), fast growth (II), and plateau (A, B) accompanied by the irreversible aggregation (III) for 3.6 mM (B). Stars represent kinetics of aggregations and change in polydispersity during aggregations (B). AFM images of nanogel particles 50× diluted from their original concentration containing (C) 0.36 mM is captured in regime II and (D) 3.6 mM of iron(II) cations in regime III. The size distributions of nanogel particles with (E) 0.36 mM and (F) 3.6 mM iron(II) cations calculated from AFM images.

To further follow the growth of the nanogel particles, DLS was employed. The results of the DLS study are summarized in Figures 3 and 4A and B. Two samples with significantly different concentrations of iron(II) cations were selected to demonstrate the growth kinetics and to evaluate the influence of the iron(II) cation concentration on nanogel growth. The time evolution of the ICFs for solutions with 0.36 mM and 3.6 mM of iron(II) cations are represented in Figure 3A and B, respectively. Fitting of the ICFs was done using eqs 1−3. The decay time, τ, from the fitting was used to calculate the diffusion coefficient based on eq 4, where the hydrodynamic radius was derived from the Stokes−Einstein relation (eq 5). The time evolution profiles of the calculated hydrodynamic radii are plotted in Figure 4A and B. As demonstrated in Figure 4A and B, the entire growth process can be divided into three regimes. Regime I features a lag phase in both samples. The fitting of this regime was performed with a single stretched exponential function (eq 1). The example of the fitting for 0.36 mM iron(II) for 80 min of growth is represented in Figure 3C (solid curve). The quality of the fit was determined by analyzing the reduced χ2 parameter. As seen from the data, the stretched exponential function fits the data much better than the simple exponential function (χ22 < χ12). The lag phase is characterized by a small increase in the decay time (τ) responsible for insignificant enlargement of nanogel size in comparison to the control system without the addition of iron(II) cations. The unchanged value of the stretching parameter (β ≈ 0.6) reflects the initial heterogeneity of the system and the fact that it does not change during the

arrow in Figure 1D), vigorous mixing by repetitious pipetting was used to saturate the solution with oxygen. As a result, the complex formation after mixing occurred at the same rate as in the solution without argon bubbling (Figure 1D). The oxygenation of the solution by mixing resulted in an apparent increase of the rate of complex formation. Since oxygen is one of the substrates needed for the laccase enzymatic reaction to proceed,39 the experiment further confirms that the oxidation of iron(II) is likely catalyzed by the enzymatic reaction and not through any other mechanisms. Nanoparticle Growth Kinetics. To understand the mechanism of enzyme-induced gelation, AFM was employed to visualize formation of the nanostructures during reaction. In these experiments, as compared to the protocol for bulk gelation, we decreased concentrations of alginate to 0.07 wt %, FeSO4 to 3.6 mM, and laccase to ∼0.26 U. According to our viscosity measurements, changing the alginate concentration from 0.67 wt % to 0.07 wt % shifted the polymer solution from the semidilute to dilute regime. Apart from preventing the formation of a macroscopic gel, the dilute regime of the polymer solution favors the formation of hydrogel nanoparticles.40 The AFM study of the dried samples (Figure 2) shows that discrete nanogel particles were formed in the presence of iron(II) cations, proteins, and alginate (Figure 2A). The size and morphology of these nanoparticles are significantly different from the size of the pure proteins (Figure 2B) and the network-like morphology of the protein and alginate mixture (Figure 2C). 2561

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decay implies that the nanoparticle size distribution in the sample is monodisperse.44 In our methods, the intervals of radii over which particles can be grown monodispersely correspond to 34−40 nm for 0.36 mM and to 47−100 nm for 3.6 mM. A strong dependence of nanogel sizes on the initial iron concentration further indicates an enzymatic characteristic of nanogel growth. This is evidenced in the slow rate of nanogel growth with small particles sizes in the presence of 0.36 mM. While for the higher concentration of iron, a faster growth rate and a wider interval of sizes over which particles could be grown monodispersely was observed. Regime III represents significantly slowed kinetics of growth reaching a plateau. As evident from Figure 4A and B, the plateau regime is present in both kinetic curves. In this regime, systems reach monodisperse size distribution (evident from the stretching parameter) with the characteristic radii of 40 nm for 0.36 mM and 100 nm for 3.6 mM (Figure 4A and B). The plateau is stable in the case of low initial concentrations of iron(II). In contrast, evidence of an additional process that competes with the main plateau was observed in the ICF of the sample containing 3.6 mM iron after 200 min (Figure 4B). The presence and increasing magnitude of this additional process required the spectra to be fit with the sum of two stretched exponential functions (eq 3). The example of the fitting is presented in Figure 3E. The stretching parameter β of the main (fast) decay was found to be ∼1 at all times in regime III, and the β of the slower process was found to be less than 1 and decreased with increasing reaction time. A decrease in amplitude of the fast process and an increase for the slower process were detected. This slow process indicates formation of the large particles after 200 min. The fact that −β for this process decreases with reaction time indicates that the distribution of hydrodynamic sizes associated with this process increases with increasing reaction time. Since it is well-known that aggregation can result in the rapid increase of size and polydispersity, we tentatively attribute the origin of the slow process to a large scale aggregation of hydrogel particles. Additional confirmation of the association of the slow process with aggregation was obtained through independent estimates of the average distance between enzymatic centers in the solution. Calculation of the average distance between enzyme centers was performed with the assumptions that each enzyme seeds the growth of the individual particle in a volume V = 1.4 mL. The enzyme concentration in this volume was 0.26 U (equal to 3 × 10−10 mol based on molecular weight of ca. 66 kDa for fungal laccases45,46or N = 1 8 × 1013 particles in this volume). The conversion from milligrams to units of enzymes was done based on a conversion factor of 13.1 U/mg. The mean interparticle distance was calculated such that

course of regime I. Comparison of the duration lengths of regime I for different samples suggests that they depend on the initial concentration of iron(II) cations. In the presence of 0.36 mM iron(II), the lag phase continues for ∼200 min, and for 3.6 mM iron(II) cations, it continues only for ∼30 min, as demonstrated in Figure 4A and B, respectively. The presence of the initial lag phase might have several mechanisms. In particular, it might be related to the kinetics of iron(III) formation and/or rate of alginate cross-linking with iron(III). In our system, iron(III) cations are produced enzymatically from iron(II), so if the rate of iron(III) binding to alginate is slower than the production of iron(III) by the enzyme, the duration of the lag phase should not be affected by the initial concentration of iron(II) present in the system. However, this is the opposite of our experimental observations. Our results, on the other hand, can be explained by the enzymatic nature of the reaction. Indeed, it is known that the speed of an enzymatic reaction41 is controlled by a number of parameters, where substrate concentration is one of them. This leads us to the conclusion that the kinetic aspects of alginate cross-linking and initial network formation in our system are entirely controlled by the enzymatic reaction, which is in agreement with the literature on polymeric systems cross-linked by enzymes.42 Another justification of the delayed growth might come from the experimental complications in capturing the growth process. In our DLS investigation, the light scattering from a solution containing only alginate and laccase revealed a certain dynamic process. After fitting it with a stretched exponential function, the corresponding average hydrodynamic radius was ∼25 nm. Since we are in the dilute polymer regime, the size obtained from DLS likely corresponds to the average hydrodynamic radius of the polymer coil, as the radius of protein is ∼2.5 nm.43 The stretching of the DLS function to ∼0.6, on the other hand, can be attributed to the distribution in the molecular weight of the pure polymer.44 If we assume nanoparticle growth starts from laccase with a radius of 2.5 nm, then detection of this process with DLS would be challenged by the presence of scattering from the polymer coil with a radius 10 times larger than the protein molecule, because the scattering intensity is proportional to the diameter of the particles in high power.44 Only when the growing particles exceed the size of the polymer coil may the process of particle growth start to be visible in DLS. This agrees with our experimental observations where the lag phase of regime I is followed by the active growth of regime II (Figure 4A and B). However, additional experiments are required to select the most plausible mechanism(s) that explains the presence of this regime. At the end of the regime I, particle size starts to increase and polydispersity decreases. This is evidenced by the increase in both characteristic decay time and the stretching parameter as measured by DLS. This regime of fast growth is referred to as II and is marked on the size profiles in Figure 4A and B. As demonstrated in Figure 4A and B, the stretching parameters start to approach unity within regime II. For the 0.36 mM iron(II) sample, this interval starts at 1200 min (β = 0.87) and extends for weeks (not shown), where for the 3.6 mM sample the interval is quite narrow and occurs between 50 min (β = 0.91) and 200 min. The ICF within these time intervals was fit with a single exponential decay function (eq 2). The example of the spectra for 3.6 mM and its fittings is presented in Figure 3D. It is important to note that fitting with a single exponential

⟨d⟩∼

3

1 n

where the parameter n = (N/V) is the particle density. Assuming a spherical shape of growing nanogel particles, we estimate the maximum radius of the particle before it will contact another growing particle to be R = (⟨d⟩/2). This estimates the maximum radius as ∼100 nm. Interestingly, this number is in good agreement with the radius obtained from our experimental data (Figure 4B). Fitting the ICF of the sample containing 3.6 mM iron(II) at a time of 200 min (regime II) right before formation of the second process also yields a radius of approximately 100 nm. These findings indicate that the nature of the second process found in DLS is 2562

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Chemistry of Materials Scheme 1. Proposed Mechanism of Gel Formation in the Presence of Laccasea

a Enzymatic reaction is depicted in A. Schematic representation of iron(III) cation generation is in B, and shell generation is in C. The final structure of the iron(III) cross-linked alginate nanogel with an egg-box type structure is detailed in D. Formation of aggregated nanoparticles is detailed in E. X and Y stand for ligands that iron can be coordinated to during enzymatic transformation. Big circles represent free iron, where small circles indicate iron coordinated with alginate.

likely an aggregation of particles due to crowding. Our findings allow us to hypothesize that the single enzyme likely acts as a template for nanogel particle growth. This hypothesis is consistent with the observed increase in the DLS signal (increase in nanoparticles concentration) with an increase in enzyme concentration (data not shown). Furthermore, AFM data with the number of adsorbed nanogels (Figure 2A) coincides with the number of enzymes (Figure 2B) adsorbed from the same concentration. Finally, we do not see any gelation in the absence of enzymes. All these seem to be in agreement with the initial hypothesis. However, this hypothesis needs to be investigated further. Notably, it is possible to stop nanogel synthesis at any specific time by simply bubbling solution with argon. As discussed above, laccase can work only in the presence of oxygen, so the depletion of oxygen will result in termination of the reaction. This will provide an opportunity to control specific sizes and polydispersity of nanogels. The results from the DLS studies agree well with the AFM studies of the nanogel particles presented in Figure 4C and D. Utilization of 0.36 mM of iron(II) resulted in the formation of well-separated single nanogel particles (Figure 4C), while it is clearly seen that the higher iron(II) concentration of 3.6 mM stimulates aggregation of the nanoparticles. Formation of unbreakable aggregates that cannot be eliminated even after significant dilution of the nanoparticles is presented in Figure 4D. The corresponding AFM image-based analysis of particle size distribution is represented in Figure 4E and F. A narrow size distribution with an average radius of 30 nm was obtained for the nanogel particles grown from 0.36 mM of iron(II) in regime II and an average radius of 215 nm was found for the aggregates of 3.6 mM of iron(II) sample in regime III. Aiming at drug delivery application for nanogel systems, our future plans will include experiments with irreversible inhibition of laccase once particles are formed. Noninhibited laccase might cause unwanted oxidative damage to physicological components in the body, resulting in various side effects. Mechanism of Nanogel Formation. On the basis of the UV−vis results and experiments with bulk gelation, we propose that the gel formation in our system stems from enzyme induced oxidation of iron(II) to iron(III), followed by crosslinking of alginate by the newly formed cations. Similar to the

oxidation mechanisms of other substrates,39 laccase enzymes use oxygen as an electron acceptor to convert iron(II) to iron(III) cations (Scheme 1A). The same mechanism is likely responsible for the enzymatic oxidation of iron(II) cations, which is supported by our UV−vis experimental data and by several reports in the literature31,32 where ferroxidase activity was found in laccases of different origins. The possible mechanism of nanogel formation is schematically represented in Scheme 1B−E. In the dilute regime, the presence of separated polymer coils in the solution is a prerequisite to forming discrete nanogels. The number of polymer coils per one protein molecule was estimated at 20:1, based on their molecular weights of 333 kDa and 66 kDa, respectively. It should be noted that in reality the number of polymer coils is much larger than our estimate. This is because our viscosity-based method of molecular weight determination is more sensitive to the higher molecular weights and does not account for any molecular weight distribution that is very broad for alginate extracted from seaweed. This suggests that most of our enzymes are entrapped within the polymer coils (Scheme 1B). The nanogel formation starts only inside the polymer coils which contain enzyme (“active coils”). As iron(II) cations are oxidized by the enzyme reaction depicted in Scheme 1A, newly formed iron(III) cations (Scheme 1B) start to be immediately trapped and bound by dissolved alginate chains (Scheme 1C) resulting in the cross-linking of alginate molecules within the coil. The network formation inside the coil can potentially be attributed to the regime of delayed growth observed in our experiments. Once the network inside the coil is formed, iron(III) cations start to diffuse across the hydrogel shell, bind alginate chains on the outer surface of the shell, and cross-link them with new alginate chains from the solution phase (Scheme 1C). Thus, the size of the nanogel particle starts to increase (Scheme 1D). In analogy to the known behavior of other metal cations,47 iron(III) cations will bind to carboxylate groups according to an egg-box model which is schematically shown in Scheme 1D.48 In the case of sufficiently high concentrations of iron(II) in the solution, growth of these shells continues until formation of cross-links between neighboring shells results in particle aggregations (Scheme 1E). The rate of iron production in the enzymatic reaction, ratio of proteins to 2563

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Chemistry of Materials polymer, molecular weight, and concentration of the polymer are tunable parameters that will affect the final size of the nanogel particles. In the semidilute polymer solution, where polymer forms a network, it is likely that formation of the bulk gel would be favored. Formation of the bulk gel is confirmed in our experiments with a solution containing 0.67 wt % alginate. However, since the gelation kinetics can be controlled by the enzymatic reaction, additional experiments are required to validate whether enzymatically induced conversion of iron can initiate the formation of nanogel particles in the semidilute polymer solution.

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ACKNOWLEDGMENTS

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REFERENCES

V.B. would like to acknowledge sponsorship by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy. D.S. and Y.W. acknowledge financial support by NSF (DMR-1408811). The AFM characterization was conducted at the Center for Nanophase Materials Sciences, which is sponsored at Oak Ridge National Laboratory by the Scientific User Facilities Division, Office of Basic Energy Sciences, U.S. Department of Energy. V.B. wants to specially acknowledge Dr. M. Ornatska for the critical reading of the manuscript and Dr. E. Strelcov for the technical support.

4. CONCLUSIONS AND OUTLOOK Our results demonstrate that laccase-catalyzed oxidation of iron(II) cations in the presence of alginate can be used for preparation of nanosized monodisperse hydrogel particles. To the best of our knowledge, this is the first study of enzyme induced formation of nanogels with a detailed exploration of gelation kinetics. On the basis of the presented UV−vis data, the likely mechanism of gelation starts with enzyme induced oxidation of iron(II) to iron(III) followed by the immediate cross-linking of alginate with iron(III) cations. AFM visualization of the growing discrete nanoparticles suggests that the rate of gel formation should be comparable to the diffusion of iron(III) cations; this allows the formation of a cross-linked shell surrounding the enzyme before iron(III) cations diffuse out of the enzyme vicinity. The kinetics of nanoparticle growth are shown to be dependent on the concentration of the crosslinker, further confirming the enzyme-dependent mechanism of the growth process. This dependence of different growth rates is advantageous because control over the size of the particles can be accomplished by tuning the initial concentration of iron(II) cations in the system. DLS and AFM characterizations revealed that narrow size distributions of the particles can be achieved. For 0.36 mM iron(II), particles with radii ranging from 30 to 40 nm can be grown, and with 3.6 mM nanoparticles, sizes ranging from 50 to 100 nm can be obtained. On the basis of our kinetic studies, especially the presence of the plateau regions for both concentrations of iron(II), we can conclude that, this method allows growing monodispersed nanogel particles that are tunable in size. This method is an innovative platform for the successful fabrication of hydrogel nanoparticles. The utilization of affordable components for nanoparticle growth makes our approach feasible and cost-effective, where biocompatible components of the reaction make our system promising for applications in drug delivery.

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The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest. 2564

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