Affinity Membranes: Competitive Binding of the Human IgG

Sorption of the four subclasses of human immunoglobulin G (hIgG) to recombinant protein G immobilized to microporous membranes was examined to further...
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Affinity Membranes: Competitive Binding of the Human IgG Subclasses to Immobilized Protein G Clarivel Viera,† Heewon Yang,† and Mark R. Etzel*,†,‡ Department of Chemical Engineering, 1415 Engineering Drive, University of Wisconsin, Madison, Wisconsin 53706, and Department of Food Science, 1605 Linden Drive, University of Wisconsin, Madison, Wisconsin 53706

Sorption of the four subclasses of human immunoglobulin G (hIgG) to recombinant protein G immobilized to microporous membranes was examined to further the understanding and characterization of this medicallysimportant system. Using batch incubation, sorption of the individual hIgG subclasses was measured in competitive and noncompetitive experiments. Individually, all subclasses had very similar sorption rates and equilibrium capacities. In contrast, for mixtures of the subclasses, binding was distinctly different, with strong competitive binding occurring: as the system approached equilibrium, significantly more hIgG1 and hIgG3 bound to the membrane than did hIgG2 and hIgG4. A kinetic and equilibrium model was able to successfully simulate the binding of hIgG1, hIgG2, and hIgG4 but not hIgG3. The results are relevant to the healthcare and biotechnology industries: (1) the diagnosis and treatment of autoimmune diseases, (2) mitigation of rejection in recipients of organ transplants, and (3) production of monoclonal antibodies for use as therapeutic biopharmaceuticals. Introduction Affinity bioseparations are in common use because of high specificity when recovering target proteins from complex dilute solutions. Traditionally, these separations are carried out in packed columns containing porous beads onto which the ligand is immobilized. However, the throughput of the column method is limited by slow intraparticle diffusion for large beads and high column pressure drops for small beads. Affinity membranes offer the advantage of increased throughput inasmuch as the diffusion path length is greatly reduced because the protein solution flows through the micrometer-sized pores of the membrane. Therefore, protein is transported into the membrane structure to the binding site by the rapid process of convection. This work characterized the kinetics and equilibrium sorption of the four subclasses of human immunoglobulin G (hIgG) to affinity membranes containing recombinant protein G (rPG) immobilized onto affinity membranes. This system was chosen because it has important practical applications in healthcare and biopharmaceutical production. In addition, analytical methods are available for the determination of the hIgG subclass concentrations, and purified rPG and hIgG subclasses are readily available. Because rPG is known to bind all of the four hIgG subclasses, it provides the opportunity for studying multisolute competitive sorption behavior.1 hIgG, a component of the immune system, consists of four subclasses: hIgG1, hIgG2, hIgG3, and hIgG4. Each hIgG molecule consists of two identical heavy and two identical light polypeptide chains (see Figure 1). Within each hIgG subclass, the Fc region is constant (the * To whom correspondence should be addressed. E-mail: [email protected]. Telephone: 608-263-2083. Fax: 608-2626872. † Department of Chemical Engineering. ‡ Department of Food Science.

Figure 1. General structure of hIgG, showing the two heavy chains (black and dark gray) and two light chains (white and light gray).

same amino acid sequence), and the Fab region contains a constant domain close to the hinge region and a variable domain at the end of the Fab region which provides binding specificity.2 The Fc and hinge regions differ in sequence and size among the four subclasses. Protein G (PG) is an assortment of surface proteins that are expressed in group C and G streptococci. Native PG binds albumin, IgG, and R2-macroglobulin with high affinity.1 PG is known to bind all four subclasses of hIgG and IgG of several animals. It will not bind IgM or IgA,3 which makes it an important reagent in the separation of IgG from blood plasma. rPG is a genetically engineered version of the group G streptococcal PG that lacks affinity for albumin and has a lysine-rich tail that facilitates covalent coupling to solid matrixes. There are two IgG binding domains, B1 and B2, in rPG. The B1 domain has 7 times greater affinity for IgG than does the B2 domain.4 The Fc and Fab regions of IgG bind to rPG, but the Fc region has a 10-fold greater affinity. Therefore, the dominant binding interaction is between the B1 domain and the Fc region of each IgG subclass. The properties of rPG make this affinity separation

10.1021/ie0001927 CCC: $19.00 © 2000 American Chemical Society Published on Web 08/06/2000

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system suitable for several applications. rPG could be used in the detection and treatment of autoimmune diseases. For example, in systemic lupus, rPG could be used to detect the levels of autoantibodies in blood plasma, and this would aid in the monitoring of the progress of the disease. Extracorporeal removal of antibodies from blood plasma using a rPG system would readily relieve patients’ symptoms. Also, a rPG affinity separation system is important in industrial applications, because the purification of monoclonal antibodies (MAbs) is an important step in the production of many biopharmaceuticals. Experimental Section Materials. Immobilon AV (IAV) affinity membranes (Millipore, Bedford, MA) were used to immobilize rPG. A single IAV membrane is 140 µm thick and has an average membrane pore size of 0.65 µm and an internal surface area of 155 cm2/cm2 of frontal area. The void fraction is 0.7. The membrane is made of poly(vinylidene difluoride) that has been modified at the surface to minimize nonspecific interactions and to provide sites for covalent immobilization of proteins through a primary amine group using the N,N′-carbonyldiimidazole activation chemistry. An imidazole group is displaced to form a stable amide bond in the presence of a primary amine.5 rPG, 22 kDa molecular weight from Escherichia coli, was obtained from Calbiochem-Novabiochem Corp. (San Diego, CA). Bovine IgG was obtained from ICN Biomedicals, Inc. (Aurora, OH). Purified hIgG subclasses (hIgG1, Myeloma; hIgG2, Myeloma; hIgG3, Myeloma; hIgG4, Myeloma) were obtained from CalbiochemNovabiochem Corp. (San Diego, CA). The hIgG Subclass Profile Kit was purchased from Zymed Laboratories, Inc. (San Francisco, CA). The kit consists of a sandwichtype enzyme-linked immunoadsorption assay (ELISA) that utilizes a horseradish peroxidase detection system. The buffers used for loading of hIgG onto the affinity membranes were 0.15 M phosphate buffered saline (pH 7.4) with 0.01% (w/v) NaN3 (PBSA) for experiments lasting for up to 24 h and with 0.05% (w/v) NaN3 for experiments lasting for more than 24 h. The 0.05% NaN3 PBSA was also used as a washing buffer during the dissociation kinetic experiments. The membrane regeneration buffer was 0.5 M glycine (pH 2.5). Buffers were vacuum filtered with a 0.2 µm membrane (Supor200, Gelman Sciences, Ann Arbor, MI), prior to use. Protein solutions were prepared about 1 h before use. The initial concentration of the IgG solutions was confirmed by absorbance spectroscopy (Cary 1, Varian Instrument Group, Sugarland, TX) at 280 nm. All experiments were performed at 22 °C. Immobilization of rPG. The IAV membranes were cut into disks of 25 mm diameter. A group of 20 membranes were cut, and each was placed separately in a disposable Petri dish. A volume of 70 µL of a 7.14 mg/mL rPG (for a total of 0.5 mg of rPG/membrane) in 0.5 M sodium bicarbonate buffer (pH 9.5) was incubated with each membrane for a period of 24 h. To determine the amount of rPG bound to the membrane, each membrane was incubated in 1 mL of 0.5 M sodium bicarbonate (pH 9.5) for 1 h to remove the rPG that was not immobilized. This supernatant was collected and later analyzed using a bicinchoninic acid (BCA) protein assay kit (Pierce Chemical, Rockford, IL). The amount of rPG immobilized was 0.17 mg/membrane disk. The

membranes were then placed in a 150 mL beaker and rinsed with 50 mL of 0.5 M sodium bicarbonate buffer (pH 9.5). This was followed by incubation with 50 ml of 2% nonfat dry milk in PBSA for 30 min to cap remaining activated sites. The membranes were then washed with 50 mL of 0.1% (w/v) Tween 20 in PBSA and washed extensively with PBSA. Nonspecific binding of polyclonal hIgG to membranes capped with nonfat dry milk and not containing immobilized rPG was measured versus the equilibrium polyclonal hIgG concentration in solution (c). Binding was cs ) 2.1 µM at c ) 1 µM and increased linearly to cs ) 21 µM at c ) 5 µM (data not shown). Nonspecific binding was a very minor contributor to the overall binding. Adsorption Isotherm. The multisolute adsorption isotherm was measured by incubation of the membranes with equal amounts of each of the four hIgG subclasses in PBSA containing 0.2% (w/v) of bovine serum albumin (BSA) (Calbiochem-Novabiochem Corp.). BSA was added to successfully hinder nonspecific binding. A group of four membranes was incubated with a 10 mL solution. The beaker was covered and shaken at 800 rpm for 24 h. Various total initial concentrations of the hIgG subclasses were used for different incubation trials. Appropriate dilutions of the initial and final solutions were analyzed for the concentration of the hIgG subclasses using the ELISA kit. A Titerteck Microplate Washer S8/12 (Flow Laboratories, Irvine, Scotland) was used during the intermediate washing steps in this ELISA assay. Absorbance was measured at a wavelength of 410 nm using a MR 700 Plate Reader (Dynatech Laboratories, Chantilly, VA). Dissociation Kinetics. A group of four membranes was incubated with 10 mL of a solution of 0.05 mg/mL of each purified hIgG subclass in 0.05% NaN3 PBSA in a beaker. The beaker was covered and shaken at 800 rpm for 24 h. The membranes were then blotted dry and washed with 10 mL of 0.05% NaN3 PBSA for 2 min (5 times) to remove any unbound hIgG. The membranes were then blotted dry and incubated with 10 mL of a solution of 4.0 mg/mL bovine IgG in 0.05% NaN3 PBSA. Bovine IgG will displace hIgG dissociating from the binding sites on the membrane. The beaker was then covered and shaken at 800 rpm for 160 h. Samples of 50 µL were taken from the initial and final hIgG solutions used in the first incubation and the initial bovine IgG solution used in the second incubation and at different time intervals from the bovine IgG supernatant. These samples were analyzed using the ELISA kit. Association Kinetics. Two different sets of experiments were performed to investigate the association kinetics of the hIgG-rPG system. In the first group, association kinetics were measured for the purified hIgG subclasses in a noncompetitive single-solute system. In the second group, the concentrations of the hIgG subclasses were monitored in association kinetic experiments using a competitive multisolute system with a mixture of all four purified hIgG subclasses and a mixture of purified hIgG2 and hIgG3. Determination of the association kinetics for each one of the four purified hIgG subclasses as a noncompetitive single-solute system was performed by incubating 10 mL of a 0.08 mg/mL purified hIgG subclass solution in PBSA with four membranes in a beaker. The beaker was covered and shaken at 800 rpm. The initial hIgG

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Figure 2. Composite adsorption isotherm for hIgG obtained by adding the contribution of each of the hIgG subclasses in the foursolute isotherm (Figure 3). Also shown is the single-solute Langmuir model that was fit to the experimental data. Error bars are as described in Figure 3.

subclass concentration was determined from the measured absorbance at 280 nm. Samples of 1 mL of the supernatant were withdrawn at various time intervals, and the absorbance at 280 nm was recorded. The samples were then returned to the beaker. Association kinetics for hIgG subclasses as a competitive multisolute system were determined by incubating 10 mL of a hIgG solution in PBSA with four membranes in a beaker. The beaker was covered and shaken at 800 rpm. Samples of 50 µL were taken at different time intervals and analyzed for the concentration of the hIgG subclasses using the ELISA kit. Instructions included with the kit were followed, except that the absorbance was measured at a wavelength of 410 nm instead of the 450 nm recommended by the manufacturer, using the MR 700 plate reader (Dynatech Laboratories, Chantilly, VA). The Titerteck microplate washer S8/12 (Flow Laboratories, Irvine, Scotland) was used during the intermediate washing steps. The hIgG solutions tried were a mixture of 0.04 mg/mL of each of the four purified hIgG subclasses in PBSA and a mixture of 0.05 mg/mL of each of the purified hIgG2 and hIgG3 in PBSA. Results Adsorption Isotherms. The competitive adsorption isotherm for the mixture of hIgG subclasses was measured using a solution containing equal initial concentrations of each subclasses and an excess of BSA to quench nonspecific binding. A composite isotherm was obtained by summing the contribution of each of the hIgG subclasses (Figure 2). The bound composite hIgG concentration was based on the solid volume of the membrane (cs) and plotted against the composite equilibrium hIgG concentration in solution (c). The values of the dissociation equilibrium constant (Kd) and the maximum binding capacity based on the solid membrane volume (cl) for the corrected adsorption isotherm were fitted to the Langmuir isotherm equation [cs ) ccl/ (Kd + c)] using the general regression (GREG6) software package: Kd ) 9.7 (5.1) × 10-8 M and cl ) 4.3 (0.5) × 10-5 M, expressed as the mean (standard deviation). The single-solute Langmuir isotherm equation was a reasonable approximation to the composite isotherm. On the basis of this observation, it seems that the hIgG subclass system behaves as a simple homogeneous system. Examination of the binding of each subclass in the mixture revealed heterogeneous competitive binding

Figure 3. Four-solute competitive adsorption isotherm for mixtures of the hIgG subclasses. Values are mean ( standard deviation, n ) 2 separate experiments, except for the largest solution concentration where n ) 3.

behavior (Figure 3). If the binding of each subclass was equivalent, then the four individual subclass isotherms would lie on one line. This did not occur. Instead, hIgG1 and hIgG3 generally bound more to the membrane than did hIgG2 and hIgG4. Capture of the individual subclasses by the membrane depended on the free concentration of the subclass wherein hIgG2, hIgG3, and hIgG4 were captured to similar extents at low free subclass concentrations. At high free subclass concentrations, hIgG2 and hIgG4 were poorly bound to the membrane and hIgG3 was strongly bound to the membrane. At all free subclass concentrations, hIgG1 was strongly bound to the membrane. Dissociation Kinetics. In the dissociation kinetic experiments, an excess of bovine IgG was used to displace the hIgG subclasses bound to immobilized rPG. Under these conditions, reassociation of dissociated hIgG with the membrane can be neglected. The dissociation process was slow, occurring over a period of days (Figure 4). Dissociation was assumed to follow first-order kinetics,7,8 wherein the supernatant concentration of hIgG as a function of time can be expressed as

c ) cmax(1 - e-kdt)

(1)

where c is the measured concentration of hIgG in the supernatant, cmax is the asymptotic maximum hIgG subclass concentration in the supernatant solution, and kd is the dissociation rate constant. Binding of the hIgG subclasses was reversible: an average of 87% (range between 81 and 92%) of the bound subclasses dissociated during the length of the experiment (Table 1). The values of kd obtained using GREG are presented in Table 2. Reported values are the averages of values from trials 1 and 2. The dissociation kinetics for each of the hIgG subclasses were extremely slow and were not significantly different from each other. The time scale for hIgG diffusion was compared to the time scale for dissociation. The time scale for diffusion in the membrane was l2/D,9 where D is the diffusion coefficient, equal to 3.8 × 10-7 cm2/s,10 and l is the diffusion path length, equal to 70 µm. The time scale for diffusion in the membrane is 2 min. The time scale for diffusion through the boundary layer adjacent to the membrane would also be quite short because the solution and membranes were agitated vigorously at 800 rpm. The time scale for hIgG dissociation, 1/kd, was 1014 h. Therefore, diffusion was not a significant contributor to the hIgG dissociation rate.

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Figure 4. Dissociation kinetics for the individual hIgG subclasses (O, trial 1; b, trial 2). The first-order dissociation kinetic rate equation was fitted to the experimental data. Table 1. Dissociation of the hIgG Subclasses trial 1: dissociated/bound (µg/mL) trial 2: dissociated/bound (µg/mL)

hIgG1

hIgG2

hIgG3

hIgG4

28.8/34.6

14.5/18.0

37.7/43.5

12.9/14.5

29.9/34.0

12.6/13.8

30.1/37.0

10.9/11.8

Noncompetitive Association Kinetics. In the association kinetics experiments, a single subclass was incubated with the membranes containing immobilized rPG, and the decrease in supernatant concentration was measured versus time (Figure 5a). The single-solute Langmuir kinetic equation8 was fit to the data

ˆ Gkat) 2cl(0.5V c (2) )1c0 G cosh(0.5V ˆ Gkat) + B sinh(0.5V ˆ Gkat) where

B)

(

c0 Kd + cl + V ˆ V ˆ

G ) B2 V ˆ )

)

4c0cl V ˆ

(3)

1/2

(1 - )(total membrane volume) (experimental solution volume)

(4) (5)

Using the dissociation rate constant (kd) obtained in the dissociation kinetic experiment, the association rate constant (ka) and the maximum binding capacity (cl) were used as the fitting parameters in GREG. Fitted ka and cl values for the hIgG subclasses are presented in Table 2.

The association kinetic behavior of each of the individual hIgG subclasses was similar. For subclasses hIgG1, hIgG2, and hIgG4, the fitted parameter values for ka and cl were similar and had small standard deviations, and the numerical simulations generated using these values were a close fit to the data. However, the fitted values of ka and cl for hIgG3 had large standard deviations. Also, the numerical simulation for hIgG3 deviated from the data at longer times (t > 300 min). The time scale for association was slow for each of the subclasses (1/kac0 ≈ 102 min) and was not significantly influenced by the time scale for diffusion (2 min). The measured supernatant concentrations were used to calculate the bound concentration cs of hIgG for each subclass by mass balance (Figure 5b). Maximum binding of the subclasses followed the order hIgG1 > hIgG4 > hIgG2, and the numerical simulations generated using the fitted parameter values were a close fit to the data. In contrast, the numerical simulation for hIgG3 deviated from the data: overpredicting binding at short times (t < 200 min) and underpredicting binding at longer times. The maximum value of cs was 50-55 µM for each subclass. By comparison, the values for cl were 90-120 µM for hIgG1, hIgG2, and hIgG4. The maximum value of cs for hIgG3 was within the range of the value of cl for hIgG3 but only because of the large standard deviation for the mean value of cl. The other values for cs at maximum binding were about 0.5 times the values for cl. This result agreed with predictions from the Langmuir isotherm equation, because the measured supernatant concentrations c at equilibrium were about equal to the fitted values for the dissociation equilibrium constant Kd (i.e., cs/cl ) c/(Kd + c) ≈ 0.5). Competitive Association Kinetics. Competitive binding between four solutes was measured by incubating the rPG membranes with a solution having an initial concentration of 0.04 mg/mL for each hIgG subclass and measuring the supernatant concentration over time using the ELISA kit (Figure 5c). At short times ( hIgG1 > hIgG4 > hIgG2. The numerical simulations generated using the fitted parameter values were a close fit to the data, except for times longer than 450 min, where measured hIgG3 binding was greater and hIgG4 binding was less than the predictions from the model. Another experiment was performed to further illustrate that, despite obtaining similar individual noncompetitive hIgG subclass binding curves, mixtures of hIgG subclasses behaved very differently, with competition for binding occurring between each subclass. In this experiment, competitive binding between only two solutes was measured by incubating the hIgG2 and hIgG3 subclasses with the rPG membranes and mea-

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parameter. This fit provided values for the maximum binding capacities (cl) and for ka for hIgG3 (Table 2). These values agreed with the values obtained for the single-solute association kinetic data for hIgG3 and hIgG2 within the error of determination. However, the parameter values for hIgG3 were again uncertain because of the large standard deviation. Measured supernatant concentrations were used to calculate the bound concentration of each subclass over time by mass balance (Figure 6b). Binding was strong for hIgG3 and weak for hIgG2. Numerical simulations generated using the fitted parameter values (Table 2) were a reasonable approximation of the data, but actual hIgG3 binding was somewhat greater, and hIgG2 binding was somewhat less, than the simulations. Discussion

Figure 6. Binary-solute competitive adsorption kinetics for hIgG2 and hIgG3. The multisolute Langmuir equations were fitted to the experimental data. Values are mean ( standard deviation, n ) 2 experiments.

suring the supernatant concentration over time (Figure 6a). Subclasses hIgG2 and hIgG3 were chosen because hIgG2 bound to the least extent and hIgG3 bound to the greatest extent to the membrane in the four-solute binding experiments. The initial solute concentration was 0.05 mg/mL each for hIgG2 and hIgG3. After 100 min the hIgG3 concentration dropped to 20%, and the hIgG2 concentration dropped to 50% of the initial supernatant concentration. At longer times, the supernatant concentrations asymptotically approached different equilibrium concentrations. Because the initial concentrations were equal, supernatant concentrations, and final asymptotic concentrations would have been equal over time if the hIgG2 and hIgG3 subclasses did not compete for binding. Instead, these two subclasses exhibited competitive binding behavior. The binding behavior for the hIgG2 and hIgG3 subclasses in a mixture was in agreement with the results from the four-solute competitive association and adsorption isotherm experiments, in which hIgG3 bound more than hIgG2. Also, similar to the four-solute binding experiment, substantial dissociation or displacement of either subclass was not observed over the time scale of the experiments. Fitted parameters from the four-solute association experiments were able to simulate well the results from the binary-solute association experiments (data not shown). In addition, as an independent determination of the parameters, eq 6 was fitted to the binary-solute association data using the value of ka for hIgG2 from the single-solute association experiments and kd for hIgG2 and hIgG3 from the dissociation experiments. The value of ka for hIgG3 from the single-solute association experiments was not specified in the fitting procedure because it had a large standard deviation and was uncertain. Instead, the value of ka for hIgG3 was a fitted

This work investigated the binding of hIgG subclasses to membranes containing immobilized rPG. The composite isotherm (Figure 2) followed the single-solute isotherm equation. On the basis of this observation, it seemed that hIgG binding behaved as a simple homogeneous system. On closer examination, however, the four hIgG subclasses behaved very differently from each other in the isotherm (Figure 3). Competitive binding behavior was observed: hIgG1 and hIgG3 binded in greater amounts than did hIgG2 and hIgG4. The relative amount of each subclass that bound to the membrane varied strongly with free concentration (ci) in the competitive multisolute isotherm experiments. For example, at the third lowest concentration data point for ci in Figure 3, the observed concentrations of hIgG subclasses 1, 2, 3, and 4 on the membrane were 6.9, 4.7, 5.1, and 4.2 µM, respectively. As ci increased, the bound concentrations for the subclasses diverged substantially (to more than a 4-fold difference). For example, at the highest concentration data point for ci in Figure 3, the observed bound concentrations of hIgG subclasses 1, 2, 3, and 4 were 15, 6.9, 18, and 4.3 µM, respectively. Different values of cl and Kd for the hIgG subclasses can produce the divergent behavior observed in the multisolute isotherm experiments. The amount of each subclass bound to the membrane is given by the equi4 θijcsj)ci/Kdi. At librium solution of eq 6: csi ) (cli - ∑j)1 small ci (linear isotherm), most of the rPG binding sites would not be occupied and competitive binding behavior would not occur. Here, csi ≈ clici/Kdi, and cli/Kdi would be the major factor determining the amount of each subclass bound to the membrane. From Table 2 (the competitive four-solute association), cli is about 50% greater for hIgG1 than for hIgG4. In addition, other researchers have observed that IgG1 binds to Fc receptors with a greater affinity (lower Kdi) than does IgG4.13 Therefore, cli/Kdi would be greater for hIgG1 than for hIgG4, and the membrane would bind more hIgG1 at low ci, in agreement with experimental observations. As ci increases, the total hIgG concentration on the mem4 θijcsj is significant compared to cli) brane increases (∑j)1 and competition for binding sites occurs. The amount of an individual subclass that binds to the membrane is no longer determined simply by the ratio cli/Kdi, because simultaneous binding of the other subclasses to the membrane causes potential binding sites to be already occupied. The single-solute association kinetic experiments characterized the behavior of each individual hIgG

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subclass in a noncompetitive system (Figure 5a). All four hIgG subclasses had very similar single-solute association behavior when binding to rPG. Individually, the hIgG subclasses bound with identical initial rates and also bound to a similar extent. Despite observing similar binding behavior for the individual hIgG subclasses (Figure 5a,b), mixtures of the subclasses behaved very differently (Figure 5c,d), with competition for binding occurring between each subclass. In the four-solute association kinetic experiment (Figure 5c), the binding behavior of each subclass was distinctly different from the others. The same phenomenon was observed in the binary-solute association kinetic experiment (Figure 6). Each subclass behaved differently in a competitive situation. These observations were in agreement with the results from the four-solute isotherm, in which hIgG1 and hIgG3 bound to a greater extent than did hIgG2 and hIgG4. Because the initial concentrations were equal, the supernatant concentrations over time and the final equilibrium concentrations would have been equal for each subclasses if each had the same binding behavior. Therefore, all of the subclasses exhibited competitive binding behavior, illustrating that even highly purified hIgG will behave as a mixture of different proteins. In the four-solute association kinetic experiments, binding of the subclasses followed the order hIgG3 > hIgG1 > hIgG4 > hIgG2. It is interesting to note that the relative flexibility of the subclasses also follows the order hIgG3 > hIgG1 > hIgG4 > hIgG2.14 Flexibility was measured by nanosecond fluorescence depolarization and by electron microscopy. Furthermore, the hinge-folding mode of flexibility alone was shown to follow the same order. Perhaps the more flexible hIgG subclasses are more able to bind to the surface of immobilized rPG. Because the Fc portion of the hIgG subclasses interacts with the immobilized rPG, more flexibility of the hIgG subclasses in the hinge and Fab regions would perhaps facilitate assembly of hIgG on the rPG surface. Fitted values of ka and cl for hIgG1, hIgG2, and hIgG4 were similar. However, the fitted values of ka and cl for hIgG3 were not determined with certainty. For hIgG3, the model was insensitive to these parameter values and the predictions from the model did not match the experimental observations well. The Langmuir model was not successful in fitting the data for hIgG3, perhaps because its molecular structure is different from that of the other subclasses. The general structure of hIgG is shown in Figure 1. One difference in the molecular structure of hIgG3 is that the hinge region in hIgG3 is 4 times as long as the hinge region in the other hIgG subclasses.13 When hIgG binds to rPG, primarily the Fc region of hIgG interacts with rPG and the Fab region causes a steric repulsion effect. Because hIgG3 has a long hinge region, it could have different binding behavior than the other hIgG subclasses. The maximum binding capacities (cl values) can be compared to the concentration of a monolayer of polyclonal hIgG on the membrane. A monolayer of polyclonal hIgG corresponds to 100-150 µg/cm2 of hIgG,4 or a value for cl of 160-240 µM. The fitted values for cl (Table 2) for all but hIgG3 are 22-75% of a monolayer of polyclonal hIgG for all of the different experiments. This result is expected considering that the rPG binding sites are immobile and randomly located on the membrane

internal surface area, which precludes deposition of hIgG in a close-packed face-centered-cubic (fcc) lattice. The maximum binding capacities can be compared to the concentration of rPG on the membrane (370 µM). The fitted values for cl for all but hIgG3 are 14-32% of the concentration of rPG. In other words, there are 3-7 molecules of rPG on the membrane/molecule of hIgG at the maximum capacity. The membrane contains an excess of rPG. The results of this study are relevant to several practical applications in the areas of (1) the diagnosis and treatment of autoimmune diseases such as systemic lupus erythematosus, rheumatoid arthritis, and myasthemia gravis among others, (2) the adsorption of reactive antibodies to mitigate rejection in recipients of organ transplants, and (3) the production of monoclonal antibodies for use as therapeutic biopharmaceuticals. For example, the diagnosis of infections and other diseases often involves measurement of elevated concentrations of specific hIgG subclasses. Commonly, these assays are performed using 96-well flat-bottomed ELISA plates coated with protein G to capture hIgG from sera. On the basis of the results of this study, these ELISA assays are biased because the extent of binding of individual hIgG subclasses to immobilized protein G is not equal and the final proportion of each subclass bound to the plate is different from the proportion in the blood of the patient. In agreement, Jones et al.15 found that monoclonal murine IgG subclasses bound to immobilized protein G to similar extents when studied individually, but mixtures of the subclasses behaved very differently, with competition for binding sites occurring, causing IgG3 to bind much more than IgG1. They concluded that ELISA capture assays are biased and not likely to provide a bound concentration of IgG subclasses that accurately reflects the balance found in serum. Their work was with murine IgG, and our work was with human IgG. Therefore, ELISA assays for human healthcare are biased according to the results of our study. Another example application for the results of our work is in the capture of MAbs from cell culture supernatants. MAbs are the fastest growing therapeutic drug class with uses for breast cancer, Crohn’s disease, prevention of blood clots in coronary operations, the transport of medicines in the body, and inhibition of the complement system in diseases such as lupus and rheumatoid arthritis. Successful therapies utilize humanized MAbs, i.e., hIgGs. In this application, only one hIgG subclass is present, and the slow-binding kinetics are the most pertinent result. Broad breakthrough curves result from slow binding because the residence time of the liquid passing through the membrane is too short for protein to bind to the immobilized rPG. On the basis of the results from this study, unreasonably long residence times (>8 h) would be required for complete binding of hIgG to immobilized rPG. Therefore, using this system, operation will likely fall in a kinetically limited region where breakthrough curves are broad and dependent on the flow rate. In this case, the dynamic capacity of the rPG membranes will be far less than the static equilibrium capacity for hIgG. For rPG beads, in comparison, the dynamic capacity will also be less than the static capacity. Similar to membranes, the binding rate of bovine IgG (bIgG) with rPG beads (GammaBind G Sepharose, Amersham Pharmacia Biotech, Uppsala, Sweden) is slow and limited

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by the association kinetics and not diffusion.16 The association rate constant for bIgG and rPG beads was ka ) 1.6 × 103 M-1 s-1, the dissociation rate constant was kd ) 4.5 × 10-5 s-1, and the static capacity was cl ) 290 µM. In comparison, for binding of hIgG to rPG membranes, ka ≈ 2.7 × 102 M-1 s-1, kd ≈ 3.0 × 10-5 s-1, and cl ≈ 100 µM (Table 2). In other words, the time scale for bIgG association with rPG beads (1/kac0) was about 20 min, compared to about 120 min for hIgG association with rPG membranes, and the time scale for bIgG dissociation from rPG beads (1/kd) was about 6 h, compared to about 9 h for hIgG dissociation from rPG membranes. Therefore, for rPG beads, operation will also likely fall in a kinetically limited region where breakthrough curves are broad and dependent on the flow rate. Furthermore, the static capacity of rPG membranes was not greatly less than the static capacity of rPG beads. In addition, in the cross-flow mode, membranes can handle feed solutions containing cells, whereas cells must be removed before traditional beadbased chromatography systems. Therefore, membranes may find useful application in the capture of hIgG and MAbs. Conclusions Adsorption of hIgG subclasses to immobilized rPG membranes was studied in this work. All four hIgG subclasses had very similar association rates and binding amounts to immobilized rPG in a noncompetitive single-solute system. However, a mixture of the four hIgG subclasses behaved very differently. Competitive binding of the four-solute system was observed: hIgG1 and hIgG3 bound in greater amounts than did hIgG2 and hIgG4. Multisolute association of hIgG1, hIgG2, and hIgG4 was successfully modeled using parameters from the single-solute Langmuir equation when including the effect of unequal maximum binding capacities. When fitted values of the association rate constants and maximum binding capacities for the hIgG subclasses were compared, values for hIgG1, hIgG2, and hIgG4 were similar. The Langmuir model was not successful in fitting the data for hIgG3, perhaps because of its 4-fold longer hinge region than other hIgG subclasses. Binding of the hIgG subclasses was slow, taking several hours to approach equilibrium. The dissociation process was slower, occurring over a period of days. The measured rate constants and maximum binding capacities were in agreement with values for polyclonal hIgGrPG association and with a monolayer of polyclonal hIgG on the membrane surface, respectively. The results of this study are relevant to several practical applications in the human healthcare industry and the biotechnology industry, e.g., in the diagnosis and treatment of diseases such as cancer, viral infections, organ rejection, and autoimmune system activation. Acknowledgment Funding for this work was provided by the National Science Foundation (BES-9631962), National Institutes of Health Grant NIH 5T32-GM08349, and the College of Agricultural and Life Sciences. Nomenclature B ) parameter defined in eq 3 c ) solute concentration in the liquid phase, M

cl ) maximum binding capacity based on the solid volume, M cmax ) maximum solute concentration in the liquid phase, M cs ) solute concentration in the solid phase based on the solid volume, M c0 ) initial solute concentration in the liquid phase, M D ) diffusion coefficient of the solute, cm2/s ka ) association rate constant, M-1 s-1 kd ) dissociation rate constant, s-1 Kd ) dissociation equilibrium constant ()kd/ka), M G ) parameter defined in eq 4 t ) time, s V ˆ ) parameter defined in eq 5  ) membrane void fraction θ ) discount factor, defined in eq 7 Subscripts i,j ) solute indices max ) maximum value

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Received for review February 7, 2000 Revised manuscript received June 13, 2000 Accepted June 19, 2000 IE0001927