Monolayers of the HSA dimer on polymeric microparticles-electrokinetic characteristics

Colloids and Surfaces B: Biointerfaces 148 (2016) 229–237

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Colloids and Surfaces B: Biointerfaces journal homepage: www.elsevier.com/locate/colsurfb

Monolayers of the HSA dimer on polymeric microparticles-electrokinetic characteristics Marta Kujda a , Zbigniew Adamczyk a,∗ , Michał Ciesla b a b

J. Haber Institute of Catalysis and Surface Chemistry Polish Academy of Sciences, Niezapominajek 8, 30-239 Krakow, Poland Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, Łojasiewicza 11, 30-348 Krakow, Poland

a r t i c l e

i n f o

Article history: Received 30 May 2016 Received in revised form 9 August 2016 Accepted 12 August 2016 Available online 23 August 2016 Keywords: Adsorption of dimeric HSA on microspheres Monolayers of dimeric HSA on microspheres HSA in dimeric form adsorption on microspheres Isoelectric point of dHSA monolayers on microspheres

a b s t r a c t Human serum albumin dimer (dHSA) enhances the accumulation and retention of anti-tumor drugs. In this work, monolayers of dHSA on polystyrene microparticles were prepared and thoroughly characterized. The changes in the electrophoretic mobility of microparticles upon the addition of controlled amounts of dHSA were measured using Laser Doppler Velocimetry (LDV) technique. These dependencies were quantitatively interpreted in terms of the 3D electrokinetic model. This allowed to determine the coverage of dHSA on microparticles under in situ conditions. Additionally, the maximum coverage of dHSA was precisely determined by the concentration depletion method. At physiological ionic strength, the maximum coverage of dHSA monolayer on microparticles was 1.05 mg m−2 . This agrees with the theoretical value predicted from the random sequential adsorption approach by assuming a side-on orientation of molecules. A high stability of the monolayers under pH cycling was confirmed, which proved irreversibility of the protein adsorption on the microparticles. The obtained results can be exploited to prepare and characterize polymeric drug-capsule conjugated with albumin dimer. © 2016 Elsevier B.V. All rights reserved.

1. Introduction A selective delivery of anti-cancer drugs to tumor tissues is required in order to avoid undesired side effects. Therefore, various drug delivery systems are developed to improve stability and drug specificity [1]. These systems often incorporate monomeric human serum albumin (HSA) [2–12]. However, such drug formulations can be removed from the blood circulation under pathological conditions because of increased capillary permeability of HSA molecules to the extravascular compartments [13]. In order to eliminate this disadvantage, the use of the chemically synthesized dimeric form of HSA with a 1,6-Bis(maleimido)hexane (BMH) spacer in the Cys-34 residues was suggested [13]. Due to its favorable pharmacokinetic properties such formulations show a prolonged blood retention and enhanced delivery of the drug to target area [13]. This albumin dimer is also applied as plasma expander, drug carrier [14–16] and a plasma-retaining agent for antidiabetic drugs [17]. Recently, it was also observed that S-nitrosylation modification of the dimer enhances the delivery efficiency and increases the retention time of anticancer drugs in tumor cells [1]. Therefore, there is growing interest in exploring the application range of the HSA dimer

∗ Corresponding author. E-mail address: [email protected] (Z. Adamczyk). http://dx.doi.org/10.1016/j.colsurfb.2016.08.017 0927-7765/© 2016 Elsevier B.V. All rights reserved.

as a potential drug carrier and for producing new biomaterials for medicine [15]. However, despite a major significance of the HSA dimer in various fields, there is little information available in the literature about its interactions and adsorption mechanisms at solid substrates, especially at polymeric microparticles often used as cores in drug delivery systems. One of the exception represents the work [18] where the its adsorption on mica was quantitatively studied by using the streaming potential method. Given the deficit of reliable information concerning this issue, the main goal of this work is a thorough characteristics of the physical adsorption process of the albumin dimer on polystyrene microparticles. In order to obtain quantitative data, the electrophoretic mobility measurements of high sensitivity are applied. Another objective of our work was to develop a robust bead model of the dimer molecule that facilitates a precise determination of its maximum coverage for various ionic strengths and molecule orientations. By using the model, efficient random sequential adsorption (RSA) calculations are performed where the protein molecule interactions are approximated by the screened Yukawa-type potential [19]. The results of theoretical calculations are used for the interpretation of experimental data derived by the depletion method involving the electrokinetic measurements [20]. This unique combination of experimental and theoretical results allows one to elucidate mechanisms of the HSA dimer adsorption on polymeric

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interfaces of a spherical shape. It is expected that the obtained results can be exploited for preparing nanocapsule formulations involving the albumin dimer.

2. Materials and methods 2.1. Experimental The HSA dimer (hereafter referred to as dHSA) was synthesized according to the modified procedure described in the previous work [18]. In the first stage, 0.32 g of HSA powder (supplied by Sigma cat. Number 3282) was dissolved in 6.5 ml of phosphate buffer solution (10 mM pH 7.0). This protein solution was purged during 15 min with high quality argon gas in order to remove oxygen. Secondly, aqueous dithiothreitol (DTT) 1.0 M (20 ␮l) was added to the protein solution, mixed by vortex. The mixtures solution was incubated for 45 min at room temperature, under argon atmosphere. This step is necessary in order to obtain a reduced form of HSA and eliminate native dimer form in the solution. After the incubation time, the mixtures solution was moved to cellulose membrane MWCO 30 kDa in the centrifugation system Vivaspin and washed by 65 ml phosphate buffer (2.25 mM pH 7.0) that remove of the excess of the DTT. This step effectively eliminates sulfhydryl-containing components (such as DTT) from the reaction solution. After centrifugation, the protein solution was concentrated to the final volume of 3.0 ml. The BMH (3.52 mg) was dissolved in 2 ml anhydrous ethanol. Afterwards, the BMH solution (0.534 ml) was added to the protein solution in three portions during 1 h, under argon atmosphere, in the dark. The solution was slowly mixed using a magnetic stirrer at room temperature (overnight). In the last step, the protein solution was washed with 30 ml phosphate buffer, to remove free, unbounded BMH crosslinker. The purity of the dimer samples was determined via Gel Filtration Chromatography technique using Superdex 200 − column and via SDS-PAGE electrophoresis in Laemmli system [21], using non-reducing sample buffer and 12% polyacrylamide gel. Before the adsorption experiments, the dHSA solution was dialyzed for one day with several exchanges of solution against 0.01 M NaCl or 0.15 M NaCl at pH 3.5, by using dialysis tubes MWCO 6–8 kDa with the capacity 0.1–3 ml, from Pur-A-LyzerTM Maxi 6000 Dialysis Kit supplied by Sigma Aldrich. During the dialysis process, the electric conductivity was measured after each solution exchange. The dialysis was continued until the conductivity attained 1.3 mS/cm for 0.01 M NaCl or 15 mS for 0.15 NaCl. In order to determine the effective bulk concentration of dHSA in its stock solutions, the BCA (bicinchoninic acid) Protein Assays, was used [22]. Then, the stock solution was diluted prior to each adsorption experiment to the desired bulk concentration varying in the range 1–5 mg L−1 (ppm). In the adsorption experiments negatively charged sulfonate polystyrene microparticles were used. The polystyrene particles suspension was synthesized in our laboratory according to the Goodwin procedure [23]. The stock suspension of microparticles of the concentration of 10% was diluted prior to each adsorption experiment to a desired mass concentration. In order to determine the diffusion coefficient and electrophoretic mobility of dHSA and polystyrene microparticles at various pHs and ionic strengths, the dynamic light scattering (DLS) and Laser Doppler Velocimetry (LDV) techniques were applied by using the Zetasizer Nano ZS device of Malvern. Adsorption experiments of the dHSA were carried out as follows: initially the protein solution of controlled concentration, typically 0.1 and 5 mg/ L, was mixed with the suspension of microparticles (having a fixed concentration of 40 mg/L) and incubated for 15 min at room temperature (at pH 3.5, ionic strength

0.01 or 0.15 M regulated by NaCl addition). After the incubation time, the electrophoretic mobility of protein covered particles was measured. In this way, the primary dependencies of the electrophoretic mobility (or zeta potential calculated by using the Smoluchowski’s equation) of microparticles on the amount of protein added were determined. The residual concentration of dHSA remaining in the suspension after the adsorption step was determined by the cencentration depletion method involving again the LDV method, which is more sensitive than the classical spectroscopic methods or colorimetric tests. Accordingly, the suspension was centrifuged in order to remove protein covered microparticles. The supernatant containing an unknown amount of dHSA was again incubated with the pure microparticle suspension of the same concentration (40 mg/L) as in the previous step and the zeta potential of latex was determined. In this way, the dependencies of the electrophoretic mobility (zeta potential) of microparticles acquired after the second adsorption step on the amount of the dHSA initially added in the first step were obtained. From the intersection of these curves with the horizontal line representing the zeta potential of bare microparticles the threshold concentration of dHSA, i.e., the concentration where all molecules become irreversibly adsorbed was directly obtained. Knowing the threshold concentration, the volume of the microparticles suspension and the surface area one can precisely calculate the maximum dHSA coverage on microparticles. 2.2. Theoretical modelling The theoretical modeling of dHSA adsorption on microparticles was performed according to the random sequential adsorption (RSA) approach originally developed in Refs. [24,25]. In these calculations, the specific interactions among protein molecules were neglected and their shape was approximated by a circular disk. Afterwards, the RSA model was extensively used for calculating the available surface function, adsorption kinetics and for predicting the maximum (jamming) coverage and the monolayer structure of non-spherical particles [26–28]. The RSA modeling was also applied in Ref. [29] for predicting the jamming coverage of fibrinogen on microparticles under various orientations. However, in none of these works the influence of the curvature of the interface and the lateral interactions among adsorbed particles were considered. The basic rules of the Monte-Carlo simulation scheme based on the RSA approach were as follows: (i) a virtual particle (molecule) is created, and its position and orientation are selected randomly with a probability depending on the interaction energy, (ii) if the particle fulfills the adsorption criteria, it is assumed to adsorb irreversibly, therefore its position is not changed during the simulation process, (iii) if the deposition criteria are violated, a new, uncorrelated attempt is made. Typically, two major adsorption criteria are specified defined: firstly, no overlapping of the virtual particle with any previously adsorbed particles and, secondly, the appearance of a physical contact of the virtual particle with the interface (microsphere particle). These modeling algorithm is more efficient compared to the Brownian dynamic simulations, making it possible to generate populations characterized by a high number of molecules. Additionally, its enables one to efficiency perform calculation for molecules of anisotropic shapes and interfaces of various geometry, e.g., spherical. In this work, adsorption of dHSA molecules on microparticles was theoretically studied using the Bead Model A, see Fig. 1, where the real molecule shape was approximated by a configuration of 6 spheres (beads) whose centers were located in one plane. The two larger spheres have an equal diameter d3 and the diameters of the internal spheres are d1 and d2 , respectively. The distances among the spheres’ centers l1 , l, l3 and the electrokinetic charges q1 , q2 , q3

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Fig. 1. The simulated crystallographic shape of dHSA molecule and its Bead Model A (BMA) developed in this work.

are defined in Fig. 1. It is assumed that the model dHSA molecule exhibits a rigid structure that does not change upon adsorption on microparticles. The dimensions of the beads in this model were estimated by applying the theoretical modeling performed according to the multipole expansion method described in Ref. [30]. Accordingly, the hydrodynamic diameter of the model dHSA molecule was numerically calculated by using an efficient algorithm as a function of varied bead sizes in order to match the value experimentally determined by DLS. The details of these calculations will be published in another work. It should be mentioned, however, that this choice is not unique because various bead combination may furnish the same hydrodynamic diameter. Therefore, an additional criterion was used to select the appropriate bead dimension, i.e., the molecule cross-section equal to 89 nm2 that matches the cross-section area previously derived from the streaming potential measurements [18]. The model molecules were adsorbed according to the above RSA scheme on a homogenous sphere (microparticle) whose diameter exactly matched the dimension of the microparticles used in the adsorption experiments. The lateral interactions among molecules were accounted for by using the Yukawa (screened Coulomb) pair potential, and summing up contributions stemming from various beads. On the other hand, the electrostatic interactions of the protein with the microparticles were assumed to be of the square well (perfect sink) type that enabled a higher efficiency of the modeling without affecting the precision of the calculations. This was confirmed by performing additional calculation carried out by using the Yukawa potential between the beads and the micro-particle. The differences in the maximum coverage between both cases were significantly smaller that the experimental error of the measurements. Typically, in one simulation run, at least 2000 model molecules were generated. Therefore, in order to improve the statistics, averages from ca. 50 independent runs were taken, with the total number of particles exceeding 100,000. This ensures the relative precision of the simulation at better than 99.5%. The primary parameter derived from these simulations was the average number of molecules adsorbed on microparticles, denoted by Np calculated for various ionic strengths that influences the magnitude of charges. Knowing Np , the average surface concentration of dHSA on the microparticle was calculated as Np /Sl where Sl surface area

of the microparticle of the diameter dl ,. The commonly used mass coverage of the protein expressed in mg m−2 is calculated as  = (M w /Av)N p /Sl

(1)

where Mw is the molar mass of dHSA and Av is the Avogadro’s constant. 3. Results and discussion 3.1. Bulk characteristics of microparticles and the dHSA molecules To characterize the physicochemical properties of the microparticles, the diffusion coefficient D was determined by dynamic light scattering (DLS) and the electrophoretic mobility e was determined by Laser Doppler Velocimetry (LDV). All measurements were conducted for the ionic strength range 0.01–0.15 M and pH 3.5. From the diffusion coefficient the hydrodynamic diameter (size) of microparticles was calculated using the Stokes-Einstein dependence [30]. The hydrodynamic diameter of the microparticles was equal to 820 ± 10 nm. By exploiting the electrophoretic mobility data, the zeta potential of microparticles was calculated from the Henry’s equation [31]. It was determined in this way that the zeta potential of bare microparticles was negative and equal to −90 mV for 10−2 M, NaCl and −48 mV for 0.15 NaCl (pH 3.5). These zeta potential values changed slightly with pH attaining −89 mV for 0.01 M, NaCl and −65 mV for 0.15 NaCl (pH 9). The electrokinetic (uncompensated) surface charge of microparticles can be calculated from the zeta potential by using the Gouy-Chapman equation [32]. Accordingly, at pH 3.5,  0 = −0.032 C m−2 (−0.20 e nm−2 ) and −0.051 C m−2 (−0.32 e nm−2 ) for the NaCl concentrations of 0.01 and 0.15 M, respectively, where e is the elementary charge equal to 1.602 × 10−19 C. In an analogous way, physicochemical characteristics of the dHSA molecules were acquired. The diffusion coefficient D measured by DLS at the bulk protein concentration of 500 mg L−1 , pH 3,5, ionic strength range of 0.01 M–0.15 M and T = 298 K was equal to 4.1 × 10−7 cm2 s−1 . Using the diffusion coefficient value, it was calculated from the Stokes–Einstein relationship that the hydrodynamic diameter of the dimer denoted by dH , was equal to 12 nm. The electrophoretic mobility of dHSA molecules was measured by the LDV method for ionic strength 0.01 M-0.15 M and pH 3.5.

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Table 1 Electrophoretic mobility, zeta potential and the electrokinetic charge per one dHSA molecule calculated from Eqs. (2) and (3), pH 3.5. Every experiment was done in triplicate. I [M]

0.01 0.15 a b c

dHSA ␮e [␮m cm (Vs)−1 ]

␨ [mV]

Qc a [e]

Qc b [e]

2.39 ± 0.1 1.4 ± 0.1

43 22

14 9.0

39 62

c

Calculated from Eq. (2). Calculated from Eq. (3). Data from Ref. [18].

The electrophoretic mobility was equal to 2.39 ␮m cm (V s)−1 and 1.4 ␮m cm (V s)−1 respectively. These values correspond to the zeta potential equal to 43 mV for 0.01 M, NaCl and 22 mV for 0.15 M calculated with the use of the Henry’s model. It was observed that for higher pHs, the electrophoretic mobility of the dimer monotonically decreases and vanishes at pH 5.2. This result indicates the isoelectric point of dHSA at pH 5.2. The isoelectric point of dHSA is identical to the isoelectric point previously determined for the recombinant HSA monomer [33]. By using the electrophoretic mobility data one can calculate the electrokinetic charge of the dHSA molecule, Qc (expressed in Coulombs) from the Lorenz–Stokes relationship [34,35]: Qc = 3dH e

(2)

where  is the dynamic viscosity of the dimer’s solution. Although Eq. (2) is valid for molecules of arbitrary shape and arbitrary electrophoretic mobility, its accuracy is limited for higher ionic strengths. Therefore, in this case, the following equation can be used for calculating the electrokinetic charge [36]. Qc = 2dH

1 + dH e = 2εdH (1 + dH ) fH (dH )

(3)



1/2

where fH (dH ) is the Henry’s function, −1 = Le = εkT is the 2e2 I Debye screening length (double-layer thickness), ε is the permittivity of the medium, k is the Boltzmann constant and I is the ionic strength of the electrolyte solution. It should be mentioned, however, that Eq. (3) is only valid for low electrophoretic mobility (zeta potentials) and molecules of a spherical shape [35]. The number of elementary charges per molecule can be calculated from Eqs. (2) and (3) by considering that e = 1.602 × 10−19 C. The results obtained in this way are collected in Table 1. It should be mentioned that this charge is a net quantity pertinent to the entire dHSA molecule. Therefore, from the electrophoretic mobility measurements alone one cannot predict how the charge is distributed among various parts of the dHSA molecule (beads).

tein added to the microparticles suspension. The nominal coverage of dHSA on the microparticles was defined as  = vs c i /Sl

(4)

vs is the volume of the mixture (L), ci is the initial dHSA concentra-

tion in the suspension after mixing with the microparticles (mg L−1 ) and Sl , is the surface area of microparticle expressed in m2 . Knowing  one can calculate the surface concentration of dHSA molecules on microparticles from the dependence: N =  Av/Mw . Additionally, in order to facilitate the theoretical interpretation of experimental data, it is useful to introduce the dimensionless surface coverage defined as

= S g N = S g (Av/M w )

where Sg is the characteristic cross-section area of the dHSA molecule equal to 89 nm2 . By exploiting these definitions, one can analyze quantitatively adsorption runs expressed as the dependence of the microparticles electrophoretic mobility e or the zeta potential on the nominal dHSA coverage,  , calculated from Eq. (4). Experimental results obtained in this way are shown in Fig. 2 for ionic strength of 0.01 M (part a) and 0.15 M (part b). One can observe that in both cases, the mobility increases abruptly with the dHSA coverage and becomes positive for  > 0.35 mg m−2 . Afterwards, for still larger dHSA coverage, the changes in the electrophoretic mobility become rather moderate. From the data shown in Fig. 2, it is possible to estimate these limiting coverages where the zeta potential of microparticles ceases to change. They were ca. 1 mg m−2 for both ionic strengths. This corresponds to the dimensionless coverage equal to 0.4. It should be mentioned that the precision of the coverage determination via these direct electrophoretic mobility measurements is rather limited, not exceeding 0.1 mg m−2 . In order to obtain quantitative information about the mechanism of dHSA adsorption on microparticles, the experimental results shown in Fig. 2 were interpreted in terms of the Gouy-Chapman (GC) model and the three-dimensional (3D) electrokinetic model where the flow damping near the interface due to adsorbed molecules and the additional ion flow from the double layer near molecules are quantitatively considered [37–39]. For the GC model, where it is assumed that protein molecules adsorb as flat (two-dimensional) objects underneath the shear plane, the net surface charge density variations are governed by the charge balance equation [35,40]:  =  0 +  p =  0 + eN c (Av/M w )

(6)

where  0 is the surface charge density of bare microparticles,  p is the electrokinetic charge density of dHSA and Nc is the number of elementary charges per one dHSA molecule. If the charge density is known, one can calculate from the GC model the zeta potential of protein covered microparticles from the relationship [34]:



3.2. dHSA adsorption on microparticles =± Monolayers of dHSA on microparticles were adsorbed under diffusion-controlled transport according to the above described procedure: initially, the reference electrophoretic mobility (zeta potential) of bare microparticles in the suspensions of well-known bulk concentration was determined, afterward, equal volumes of the protein solution with the polystyrene microparticles suspension were mixed, the adsorption time was 900 s. Finally, the electrophoretic mobility of the dHSA covered microparticles was measured. The above procedure was reliable and reproducible, enabling a precise determination of the electrophoretic mobility of microparticles as a function of the bulk concentration of the pro-

(5)

2kT ln e

2

|| ¯ + ¯ + 4 2

1⁄2 (7)

where the plus and minus sign corresponds to the positive and 1/2 negative sign of ,  = /(2εkTnb ) is the dimensionless electrokinetic charge density and nb is the electrolyte concentration expressed in m−3 . As can be seen in Fig. 2, the theoretical results derived from the GC model (depicted by dashed lines) by using the charge density calculated from Eqs. (6) and (7) significantly underestimate the experimental data. This is so because the dHSA molecules are not flat disks as it is assumed in the GC model but three-dimensional objects. Therefore, it is expected that the 3D electrokinetic model

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233

Fig. 2. The dependencies of the zeta potential of microparticles on the coverage of dHSA expressed in  [mg m−2 ] (lower axis) and the dimensionless coverage  (upper axis). The points denote experimental results obtained from the LDV measurements at pH 3.5. The solid lines denote exact theoretical results calculated from the 3D adsorption model and the dashed line denotes the theoretical results calculated from the Gouy–Chapman (GC) model. Part “a”: I = 0.01 M. Part “b”: I = 0.15 M.

Fig. 3. The dependencies of the zeta potential of microparticles on the dHSA loading cb expressed in mg L−1 (upper axis). The lower axis shows the nominal coverage of dHSA corresponding to this loading. The solid line denotes the reference line (smoothened) for the initial dHSA adsorption step and the dashed-dotted lines denote the linear fits of the experimental data for the second adsorption step after suspension centrifugation, (pH 3.5). Part “a”: I = 0.01 M. Part “b”: I = 0.15 M.

should be more appropriate as previously demonstrated for the adsorption of the HSA monomer [20,33]. According to this model, the zeta potential of interfaces covered by protein molecules is given by the expression: () = Fi () i + Fp () p

 

 

(8)

where Fi  , Fp  are the dimensionless functions of the protein coverage , i is the zeta potential of bare microparticles and p is the zeta potential of dHSA in the bulk.     As previously shown [38,39], the functions Fi  , Fp  for particles of spherical shape can be approximated by the following analytical expressions: Fi () = e−Ci

√ 1 Fp () = √ (1 − e− 2Cp ) 2

(9)

where, the Ci , Cp constants depend on the a parameter. For thinner double layers, where a > 1, Ci , Cp attain constant values of 10.2 and 6.5, respectively [38]. As can be observed in Fig. 2, the theoretical results calculated from Eqs. (8,9) agree with experimental data for the entire range of coverages that confirms the validity of the 3D model for interpreting dHSA adsorption on polymeric microparticles. This observation has interesting implications indicating that the zeta potential of dHSA molecules can be determined via the microparticle electrophoretic mobility measurements instead of the tedious bulk LDV measurements that require considerably higher protein quantity. The potential can be calculated from Eqs. (7) and (8) that can be transformed to the following relationship:

p = [ () − Fi () i ]/Fp ()

(10)

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Fig. 4. Monolayers of dHSA on microparticles at the jamming limit derived from the RSA modeling for different electrolyte concentrations: (a) 10−2 M; end on (b) 10−2 M side-on; (c) 0.15 M end-on, (d) 0.15 M side-on.

It is interesting to mention that Eq. (10) is valid for arbitrary coverage of dHSA including the low coverage range, where it simplifies to the linear form





p = − i + Ci  i /Cp 

(11)

However, as mentioned above, the electrophoretic mobility method is of a limited utility for determining the maximum coverage of dHSA monolayers on microparticles. Therefore, in order to increase the precision of the maximum coverage determination, the concentration depletion method was applied involving the LDV electrophoretic mobility measurements [20]. Accordingly, after the dHSA adsorption step, the microparticle suspension was centrifuged and a fixed volume of clear supernatant was acquired. The supernatant containing an unknown concentration of the protein was mixed once again using with the native microparticle suspension of the same volume and the bulk concentration as in the first step. The electrophoretic mobility of the microparticles

after the second adsorption step was determined. Such experimental runs acquired for ionic strength 0.01 and 0.15 M are presented in Fig. 3 as the dependence of the zeta potential of microparticles on the dHSA concentration in the initial mixture (loading) denoted as cb . The solid lines represent the reference data (smoothened) for the initial dHSA adsorption step and the dashed-dotted lines denote the linear fits of the experimental data for the second adsorption step after suspension centrifugation. The intersection of these lines with the horizontal line pertinent to bare microparticle mobility gives the break-through concentration of dHSA, denoted by cimx . Thus, for cb < cimx all protein molecules are adsorbed on the microparticle surface and for cb > cimx there appeared unbound dHSA molecules in the supernatant. By knowing cimx one can precisely calculate the maximum coverage of dHSA from Eq. (4). In this way, one obtains 0.96 ± 0.02 and 1.05 ± 0.02 mg m−2 for ionic strength of 0.01 and 0.15 M, respectively (see Table 2) that agrees within error bounds with previous data obtained by direct electrophoretic measurements of dHSA covered microparticles. On the other hand, the maximum coverage of dHSA on mica was equal to 0.50 mg m−2 for ionic strength of 0.01 M [18]. that is almost two times smaller than the maximum coverage determined in this work for microparticles. This low value of dHSA coverage on mica was interpreted in Ref. [18] as the indication of the side-on adsorption mechanism. Hence, the comparison of the experimental data for mica and microparticles suggests a considerable contribution of the end-on adsorption mechanism of dHSA in the latter case. Another feature that confirms this prediction is that the maximum coverage of dHSA on microparticles does not appreciably increase with ionic strength as was observed for monomeric HSA [20] and for KfrA [41]. In other series of experiments, the irreversibility of dHSA adsorption was evaluated by determining the zeta potential and the hydrodynamic diameter of a microparticle suspension of the concentration 40 mg/L covered by a saturated monolayer of dHSA (adsorbed at pH 3.5 and ionic strength of 0.01 or 0.15 M) as a function of the storage time up to 48 h. These parameters were determined over time intervals of 1 h by taking ca. 2 ml samples from the stock suspension. It was observed that the changes in the electrophoretic mobility of protein-covered microparticles were negligible for this period of time that suggested the lack of dHSA desorption from the monolayers. Additionally, at the end of the experiments, the suspension was centrifuged and the negligible concentration of free dHSA was confirmed by the LDV aided test. Also, the lack of hydrodynamic diameter changes within this time period confirmed the latex suspension stability. A more precise information about the adsorption mechanisms of dHSA on microparticles can be derived by comparing the experimental data with theoretical modeling performed according to the above described algorithm. In these calculations the size of the external (larger) beads d3 was equal to 5 nm and the size of the internal (smaller) beads d1 , d2 was equal to 4 nm. This gives the geometrical cross-section area of the model molecule Sg = 89 nm2 that matches the experimental cross-section value. The net charge per molecule was taken from Table 1, to be equal to 14 and 9 e for ionic strength of 0.01 and 0.15 M, respectively. The charges q1 = q2 and q3 were calculated as proportional to the surface area of beads. Monolayers of dHSA on microparticles at the jamming limit derived from the RSA modeling for the ionic strength of 10−2 M and 0.15 M are shown in Fig. 4 both for the end on and side-on orientations. It should be mentioned that the end-on orientation is defined in our calculations as perpendicular to the side-on (flat) orientation shown in Fig. 1. The theoretical results derived from these calculations are collected in Table 2. It can be observed that for the lower ionic strength of 0.01 M, the theoretical maximum coverage calculated as the average of side-on and end-on orientation is equal to 0.98 mg m−2 that is close to the experimental value of 0.96 mg m−2 . On the other hand, for higher ionic strength of 0.15 M, the theo-

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235

Table 2 Experimental and theoretical maximum coverages of dHSA on polystyrene microparticles expressed in mg m−2 for different ionic strength and pH 3.5. The standard deviation of experimental measurements is equal to 0.02 mg m−2 . I [M] −2

10 0.15 ∞ *

max, exp. [mg m−2 ]

max, exp.* [mg m−2 ]

max theoretical, side-on [mg m−2 ]

max theoretical, end-on [mg m−2 ]

0.96 ± 0.02 1.05 ± 0.02 –

0.50 – –

0.841 ± 0.001 1.07 ± 0.0006 1.12 ± 0.0006

1.13 ± 0.001 1.98 ± 0.0006 2.18 ± 0.0006

Previous measurements for mica by using the streaming potential method [18].

Fig. 5. The dependence of zeta potential of dHSA monolayers on microparticles on pH cycling from 3.5 to 8 and back to pH 3.5 (three cycles). The experimental results interpolated by curve 1) were obtained for ionic strength of 0.01 M and the dHSA monolayer coverage equal to 0.96 mg m−2 . The experimental results interpolated by curve 2) were obtained for ionic strength of 0.15 M and the dHSA monolayer coverage equal to 1.05 mg m−2 .

Fig. 6. Zeta potential vs. pH of: 1) dHSA in the bulk, 2) dHSA monolayer on microparticles of the coverage equal to 0.96 mg m−2 3) dHSA monolayer on microparticles of the coverage equal to 0.96 mg m−2 normalized by using Eqs. (10) and (4)) bare microparticles in the bulk, for ionic strength of 10−2 M. The lines denote the fits of experimental data. Every experimental point was done in triplicate.

retical value of the maximum coverage in the side-on orientation that was equal to 1.07 mg m−2 agrees with the experimental value.

In contrast, the theoretical end-on value, equal to 1.98 mg m−2 is almost two times larger than the experimental value. Given the

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high precision of the experimental and theoretical results, one can argue that for lower ionic strength, the dHSA molecules adsorb under random orientations and for higher ionic strength almost exclusively in the side-on orientation. Indirectly, this fact confirms a electrostatically driven adsorption mechanism of dHSA. One can also expect that the high density monolayers of dHSA can be used for thorough electrokinetic characteristics of the protein, especially for determining its isoelectric point as described below.

3.3. Electrokinetic characteristics of dHSA monolayers on microparticles The stability and acid-base properties of dHSA monolayers on microparticles were determined by performing pH cycling experiments according to the following procedure: firstly, a dHSA monolayer of a maximum coverage was adsorbed on microparticles at pH 3.5 and different ionic strength, either 0.01 or 0.15 M. Then, the pH of the microparticle suspension was increased in a step-wise manner by adding an appropriate amount of NaOH (this proved advantageous over using buffers that could specifically adsorb on the protein monolayer). After stabilizing the pH value, the electrophoretic mobility of the microparticles was determined and the zeta potential was calculated as described above. The procedure was continued up to pH 8, where the pH cycle was reversed by adding appropriate amounts of HCl. Three pH cycles were made in order to determine the reproducibility of this procedure. In Fig. 5 primary experimental results obtained in this way for ionic strengths of 0.01 and 0.15 M and the dHSA monolayer coverage equal to 0.96 and 1.05 mg m−2 , are presented. As can be seen, the dependencies of the zeta potential of dHSA monolayers on pH were almost identical (within error bounds) in each cycle. This suggests that the protein-covered microparticles was stable during the pH cycling and that dHSA molecules were irreversibly adsorbed. It is also interesting to mention that both curves intersect each other at pH 4.7 that can be identified as the isoelectric point of dHSA monolayers on microparticles. However, it should be mentioned that the precision of isoelectric point determination can be increased by considering the correction stemming from the microparticle surface described by the term Fi () i in Eq. (10). Because of a large negative zeta potential of microparticles, this term plays a significant role for pHs close to the isoelectric point of dHSA where its zeta potential vanishes. The dependence of dHSA monolayer zeta potential, corrected by using Eq. (10), is presented in Fig. 6. As can be observed, the isoelectric point of the dHSA monolayer is shifted to pH 5 that almost matches the bulk value (pH 5.2). Therefore, these results suggest that the acid base properties of dHSA monolayers physically adsorbed on polymer microparticles are similar to the bulk properties of the protein molecules. This has practical implications, confirming that the molecules preserve their surface properties upon adsorption. In this way, a controlled adsorption of dHSA on microparticles, requiring order of magnitude smaller quantities of protein compared to bulk electrophoretic measurements, can be efficiently used to gain essential information about its electrokinetic properties, especially its isoelectric point and the electrokinetic charge as a function of pH and ionic strength.

4. Conclusions Electrokinetic measurements supplemented by an efficient modeling performed according to the random sequential adsorption approach enabled a quantitative analysis of adsorption mechanism of dHSA on polystyrene microparticles.

It was confirmed that for the higher ionic strength of 0.15 M the molecules adsorb preferentially in the side-on orientation. Accordingly, the maximum coverage of dHSA monolayer on microparticles attained 1.05 mg m−2 that agrees with the theoretical value predicted from the RSA model. A high stability of the monolayers under pH cycling between 3.5 and 8 was confirmed, which proved irreversibility of the protein molecule adsorption on the microparticles. The acid-base properties and the electrokinetic charge of dHSA monolayers were determined via the electrophoretic mobility measurements carried out for different ionic strength. These methods and results can be exploited to prepare and characterize polymeric drug-capsule conjugated with albumin dimer. This has significance for improving anti-cancer drug delivery and avoiding undesired side effects during cancer therapy. Acknowledgements: This work was financially supported by the Polish National Science Centre project: UMO-2012/07/B/ST4/00559. The authors ˙ and E. Wajnryb for supplyare indebted to M.L. Ekiel Jezewska ing numerical data of the hydrodynamic diameter of the model dHSA molecule calculated for various bead size. The authors also are thankful to M. Nattich-Rak for her assistance in artwork preparation. References [1] R. Kinoshita, Y. Ishima, M. Ikeda, U. Kragh-Hansen, J. Fang, H. Nakamura, V.T.G. Chuang, R. Tanaka, H. Maeda, A. Kodama, H. Watanabe, H. Maeda, M. Otagiri, T. Maruyama, J. Control. Release 217 (2015) 1. [2] S. Pignatta, I. Orienti, M. Falconi, G. Teti, C. Arienti, L. Medri, M. Zanoni, S. Carloni, W. Zoli, D. Amadori, A. Tesei, Nanomedicine 11 (2015) 263. [3] Z. Li, T. Yang, C. Lin, Q. Li, S. Liu, F. Xu, H. Wang, X. Cui, ACS Appl. Mater. Interfaces 7 (2015) 19390. [4] A. Rollett, T. Reiter, P. Nogueira, M. Cardinale, A. Loureiro, A. Gomes, A. Cavaco-Paulo, A. Moreira, A.M. Carmo, G.M. Guebitz, Int. J. Pharm. 427 (2012) 460. [5] J.Y. Lee, K.H. Bae, J.S. Kim, Y.S. Nam, T.G. Park, Biomaterials 32 (2011) 8635. [6] D.V. Peralta, J. He, D.A. Wheeler, J.Z. Zhang, M.A. Tarr, J. Microencapsul. 31 (2014) 824. [7] Y. Wu, S. Ihme, M. Feuring-Buske, S.L. Kuan, K. Eisele, M. Lamla, Y. Wang, C. Buske, T. Weil, Adv. Healthcare Mater. 2 (2013) 884. [8] Z. Chen, J. Chen, L. Wu, W. Li, J. Chen, H. Cheng, J. Pan, B. Cai, Int. J. Nanomed. 8 (2013) 3843. [9] T. Peters Jr., All About Albumin: Biochemistry, Genetics, and Medical Applications, Academic Press, 1995. [10] M. Otagiri, Drug Metab. Pharmacokinet. 20 (2005) 309. [11] J. Ghuman, P.A. Zunszain, I. Petitpas, A.A. Bhattacharya, M. Otagiri, S. Curry, J. Mol. Biol. 353 (2005) 38. [12] D. Sleep, Expert Opin. Drug Deliv. 12 (2015) 793. [13] K. Taguchi, Y. Urata, M. Anraku, H. Watanabe, K. Kawai, T. Komatsu, E. Tsuchida, T. Maruyama, M. Otagiri, Drug Metab. Dispos. 38 (2010) 2124. [14] T. Komatsu, Y. Oguro, Y. Teramura, S. Takeoka, J. Okai, M. Anraku, M. Otagiri, E. Tsuchida, Biochim. Biophys. Acta Gen. Subj. 1675 (2004) 21. [15] K. Taguchi, V.T.G. Chuang, T. Maruyama, M. Otagiri, J. Pharm. Sci. 101 (2012) 3033. [16] S. Matsushita, V.T.G. Chuang, M. Kanazawa, S. Tanase, K. Kawai, T. Maruyama, A. Suenaga, M. Otagiri, Pharm. Res. 23 (2006) 882. [17] K. Taguchi, V.T.G. Chuang, K. Yamasaki, Y. Urata, R. Tanaka, M. Anraku, H. Seo, K. Kawai, T. Maruyama, T. Komatsu, M. Otagiri, J. Pharm. Pharmacol. 67 (2015) 255. [18] M. Kujda, Z. Adamczyk, S. Zapotoczny, E. Kowalska, Colloids Surf. B Biointerfaces 136 (2015) 1207. [19] M. Kujda, Z. Adamczyk, M. Cie´sla, M. Adamczyk, J. Stat. Mech. 2015 (2015) P04003. ´ [20] K. Sofinska, Z. Adamczyk, M. Kujda, M. Nattich-Rak, Langmuir 30 (2014) 250. [21] U.K. Laemmli, Nature 227 (1970) 680. [22] P.K. Smith, R.I. Krohn, G.T. Hermanson, A.K. Mallia, F.H. Gartner, M.D. Provenzano, E.K. Fujimoto, N.M. Goeke, B.J. Olson, D.C. Klenk, Anal. Biochem. 150 (1985) 76. [23] J.W. Goodwin, J. Hearn, C.C. Ho, R.H. Ottewill, Colloid Polym. Sci. 252 (1974) 464. [24] J. Feder, I. Giaever, J. Colloid Interface Sci. 78 (1980) 144. [25] E.L. Hinrichsen, J. Feder, T. Jøssang, J. Stat. Phys. 44 (1986) 793. [26] P. Viot, G. Tarjus, S.M. Ricci, J. Talbot, J. Chem. Phys. 97 (1992) 5212. [27] J.W. Evans, Rev. Mod. Phys. 65 (1993) 1281.

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