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Biomolecular discrimination analyses by surface plasmon resonance Subash C. B. Gopinath* and Penmetcha K. R. Kumar
Received 31st October 2013 Accepted 18th February 2014 DOI: 10.1039/c3an02052e www.rsc.org/analyst
Biomolecular discrimination is one of the most important ways to discriminate closely related species. In the past, several biomolecules have been observed with higher discrimination using different sensing systems. Herein, we have displayed discrimination of human and rabbit IgG and human clotting factors on Biacore-carboxymethylated dextran coated sensor chips.
The development of detection systems with specic probes, such as antibodies, aptamers, glycans and receptors, that distinguish closely related species will have great impact on developing specic diagnosis. Using the advantages of available probes, efficient biomolecular discrimination has been demonstrated for developing sensing systems. In the past, discrimination between closely related molecules such as theophylline vs. caffeine,1 L-arginine vs. D-arginine,2 oxidised vs. reduced forms of nicotinamide,3 closely related proteins,4 phosphorylated vs. non phosphorylated forms,5 peptide enantiomers,6 bovine vs. human thrombin,7,8 closely related inuenza sub-types,9 bovine vs. human clotting factor IX,10 human vs. avian receptors11,12 and sulfated natural polysaccharides have been demonstrated.13 Molecular discriminations are important events in the eld of biology, in order to distinguish molecules for functional analyses and classication. Using the advantages of the above probes, several sensing systems have been generated in this direction. Previously, it has been demonstrated with antibodybased discrimination on the BioDVD platform14 and waveguidemode sensors.12 Using antibody-activated magnetic nanoparticles, tumor discrimination was performed by ultralow-eld magnetic resonance imaging.15 Surface Plasmon Resonance (SPR)-Biacore discrimination of inuenza viruses were shown using aptamer-based9 and glycan-based11 probes. Biacore is a SPR-based system that has been widely used for immunosensing and other strategies including Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565, Japan. E-mail: gopis11@ gmail.com
2678 | Analyst, 2014, 139, 2678–2682
discrimination.11,16 Previously, we have shown RNA-aptamer based higher discrimination over 1000 fold for the differences between bovine and human factor IX with Biacore.13 Wang et al.17 have studied the interaction between plasminogen and antiplasmin variants by Biacore. Thus, Biacore is an important platform to discriminate closely related biomolecules based on bio-recognition elements such as monoclonal antibodies or aptamers. The Biacore system is designed based on SPR to evaluate the interaction between molecules in a real time manner. This system has an approach that involves the immobilization of an interacting partner onto the sensing surface, followed by the ow of the sample containing the binding partners over the surface. The interacting partners bound to the immobilized molecules on the sensor surface generate a response which is proportional to the bound mass (Fig. 1). In this study, we have explored further evidence using human and rabbit anti-immunoglobulin for their discrimination from immunoglobulin (IgG) from humans and rabbits.
Diagrammatic representation of the principles involved in surface plasmon resonance. On the sensing surface the ligand is attached and the interaction with the analyte is analysed. The light source passes through the prism, hitting the sensing surface and generating spectral changes due to an angular shift.
Fig. 1
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Fig. 2 Determination of the dissociation constant by SPR for antihuman IgG (Fc) vs. human full-length IgG (a); vs. human Fc (b); antirabbit IgG vs. rabbit IgG (c). The activated CM5 chip was coated with 20 mg ml1 antibody at pH 4.0 by injecting 100 ml of the solution at a flow rate of 10 ml min1, and was blocked with 1 M ethanolamine hydrochloride at a similar flow rate for 7 min. Then, 60 ml aliquots (different concentrations) of the antigen were injected at a flow rate of 30 ml min1 for 2 min. The running buffer contained 10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20.
Table 1
IgG, an antibody, is a protein with a ‘Y’ shaped structure in the immune system, which identies foreign targets called antigens on its two-armed region (variable region). Antibodies have ve isotypes known as IgD, IgE, IgG (monomers), IgA (dimer) and IgM (pentamer), among which IgG is most abundant. To carry out the present study, human monoclonal mouse IgG (Fc region), full-length human IgG and recombinant human IgG (Fc region) were purchased from R&D system, USA. Goat anti-rabbit IgG and antigen rabbit IgG were procured from Millipore, USA. The rate constant for antibody and antigen binding was measured using SPR (Biacore T100) at 25 C on a dextran-coated sensor chip (the CM5 chip from GE Healthcare, USA). Initially we carried out pH scouting and found that an acidic condition of pH 4.0 was ideal in both cases. The ow cells (1 and 2) of the CM5 chip were activated using N-hydroxysuccinimide and 1ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride. Aer this activation step, the antibody (20 mg ml1) was passed through ow cell 2 at a ow rate of 10 ml min1 for 10 min, resulting in the immobilization of the antibody on ow cell 2 of the CM5 chip through the primary amine group on the protein (antibody). Once immobilization of the antibody was complete, we blocked the remaining activated surface of the CM5 chip and ow cell 1 with 1 M ethanolamine HCl (pH 8.5) at a ow rate of 10 ml min1 for 7 min. The excess unbound molecules retained in ow cells 1 and 2 were washed out with binding buffer (10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20). Flow cell 1 was used as the control surface to rule out non-specic binding to the dextran as this ow cell was devoid of the antibody. To analyze the binding kinetics, single-cycle kinetics were measured with various concentrations of the antigen (2.5, 5, 10, 20, 40 nM or 25, 50, 100, 200, 400 nM) injected through the experimental ow cell (ow cell 2) and the control ow cell (ow cell 1) at a ow rate of 30 ml min1, with a total volume of 60 ml. The dissociation time was set for 2 min to obtain a smooth curve. Sensorgrams were corrected for the non-specic binding by subtracting the control curve (FC1) from the antigen curve (FC2), and the binding kinetics were evaluated. All of the sensorgrams were evaluated using the Biacore T100 Evaluation soware, version 2.0.2 (GE Healthcare), and were tted with a 1 : 1 binding model. This is the simplest model for the interaction between antigen and antibody according to the equation A + B ¼ AB. The rate of association was measured from the forward reaction, and the dissociation rate was measured from the reverse reaction. The equilibrium dissociation rate constant (Kd) is kd/ka, where kd is the dissociation rate and ka is the association rate. For each dataset, the chi-squared (c2) value for
Kinetic parameters for the analyses of antibodies against antigens from humans and rabbits
Ligand
Analyte
Association constant ka (M1 s1)
Dissociation constant kd (s1)
Equilibrium constant kd (nM)
Anti-human Anti-human Anti-human Anti-rabbit Anti-rabbit
Hu-full Hu-fc Ra-full Ra-full Hu-full
2.5 104 8.6 104 0.5 104 5.9 104 No binding
1.5 103 7.8 103 5.3 104 6.4 105 No binding
61 90 102 1 No binding
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Fig. 3 Determination of the dissociation constant by SPR for antihuman IgG (Fc) vs. rabbit IgG. The activated CM5 chip was coated with 20 mg ml1 antibody at pH 4.0 by injecting 100 ml of the solution at a flow rate of 10 ml min1, and was blocked with 1 M ethanolamine hydrochloride at a similar flow rate for 7 min. Then, 60 ml aliquots (25 to 400 nM) of antigen were injected at a flow rate of 30 ml min1 for 2 min. The running buffer was 10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20.
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a molecular weight of 150 000 daltons. Gagnon et al.18 reported the separation of fragments from IgG and showed the molecular weight of the Fc region to be 55 000 daltons on non-reduced SDS-PAGE. In addition, the affinity of the full-length IgG and Fc group may also differ with the antigen. In addition, though other regions are not involved in binding to the target, these ‘non-essential’ regions might be involved in strengthening the overall interaction of the antibody with its corresponding partner. Moreover, the full-length antigen used in this study is puried directly from human plasma, whereas the Fc-antigen is the recombinant protein, which also accounts for the affinity difference. We also evaluated the affinity between anti-rabbit IgG and the rabbit IgG antigen. Initially, we maintained the
Fig. 4 3D crystal structure of the Gla (g-carboxyglutamic acid-rich) domain of FIX complexed FIX-bp (PDB accession code 1J35).
goodness of t was less than 1, and the residuals were within 6 RU, suggesting that the data had a good t to the binding model. The tting data are displayed with the global rate constants (ka, kd, and Kd). By following the above set-up, initially we analysed the antihuman antibody against human full-length IgG and the Fc region of IgG and determined the dissociation constants. The anti-Fc region of IgG was bound to the full-length human IgG with an association constant (ka) and dissociation constant (kd) of 2.5 104 M1 s1 and 1.5 103 s1, respectively. The equilibrium dissociation constant (Kd) was estimated at 61 109 M (Fig. 2a and Table 1). However, the anti-Fc region of IgG was bound to the Fc region of human IgG with an association constant (ka), dissociation constant (kd), and equilibrium dissociation constant (Kd) of 8.6 104 M1 s1, 7.8 103 s1, and 90 109 M, respectively (Fig. 2b and Table 1). Based on this comparison between the binding of the anti-Fc region of human IgG against the antigen human full-length IgG and Fc region, it was evident that the full length IgG has higher affinity than the Fc region. This might be due to the larger size of the IgG than the Fc region. It is commonly known that IgG can have
2680 | Analyst, 2014, 139, 2678–2682
Fig. 5 (a) Cartoon illustrating the interaction between FIX or FX and FIX-bp. (b) Discrimination of clotting factor binding with FIX-bp by SPR. (c) Binding model on a sensor chip. The activated CM4 chip was coated with 20 mg ml1 FIX-bp by injecting 100 ml of the solution at a flow rate of 10 ml min1, and was blocked with 1 M ethanolamine hydrochloride. Then, 60 ml aliquots (100 nM final concentration) of the clotting factors were injected at a flow rate of 30 ml min1 for 2 min. 1 mM MgCl2 and 5 mM CaCl2 were added to the buffer (10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20).
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Table 2
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Kinetic parameters for the analyses of FIXbp against blood clotting factors from human21
Analyte
Association constant ka (M1 s1)
Dissociation constant kd (s1)
Equilibrium constant kd (nM)
FIX FX FVIIa FXIa
1.6 105 1.8 105 No binding No binding
2.5 103 6.7 103 No binding No binding
34 40 No binding No binding
same concentrations (25 to 400 nM) used in the human sample case, but the sensorgram showed a higher response (3000 RU) and it was hard to calculate the kinetic parameters as it was out of range. It is generally believed that low concentrations of antigen give reliable kinetic data. Thus, we have re-evaluated using concentrations 10-fold less (2.5 to 40 nM), which reduced the response of the sensorgram 40 times (75 RU) and enabled calculation of the kinetic parameters. The association constant (ka), dissociation constant (kd), and equilibrium dissociation constant (Kd) were approximated at 5.9 104 M1 s1, 6.4 105 s1, and 1 109 M, respectively (Fig. 2c and Table 1). When compared to anti-human-antigen binding affinities, antirabbit and its corresponding antigen were 100 fold higher. This indicated that anti-rabbit IgG and IgG have better specicities to be used for sensing studies. Similarly, we have also performed a cross-reactivity study between the anti-human IgG and antigen rabbit IgG. The values obtained for the association constant (ka), dissociation constant (kd), and equilibrium dissociation constant (Kd) were 0.5 104 M1 s1, 5.3 104 s1, and 102 109 M, respectively (Fig. 3 and Table 1). This low discrimination might be due to the binding of anti-human antibody with the rabbit IgG antigen in the region of similarity between the human and rabbit IgG. Previously, cross reactivity of human and rabbit antibodies with fungal antigens was reported by immunoblotting.19 However, in the present study when we carried out crossreactivity binding between the anti-rabbit IgG and the antigen human IgG, no binding was observed (Table 1). These results proved that the anti-rabbit IgG used in this study is the right agent for discrimination between human and rabbit IgG. The advantage of SPR for discrimination of human and rabbit IgG is the multichannel system with simultaneous on-line measurements. Moreover, the system shown here can also be used for high-throughput analyses and for selective binding in a mixture of samples. As performed in the above study, we also gathered evidence using a SPR sensor for the discrimination of clotting factors involved in the human blood coagulation cascade using the receptor factor IX-binding protein (FIX-bp). FIX-bp is originally from snake venom, which is found to interact with Factor IX (FIX) and Factor X (FX).20,21 To carry out these interactive analyses, we have utilized the CM4 sensor chip from Biacore 2000. Human FIX, FIXa, FXa and XIa were purchased from American Diagnostica Inc. (USA). Human factor VIIa was obtained from Haematologic Technologies Inc. (USA). The FIX-bp was puried from the snake venom of Trimeresurus avoviridis, following the published purication protocol.20
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FIX-bp is known to bind specically to the Gla-domain of FIX. The three dimensional crystal structure of the Gla-domain of FIX complexed FIX-bp is available in the protein data bank and displayed in Fig. 4. The Gla-domain is responsible for binding to phospholipid membranes and assists in localizing these proteins to sites of injury and helps in properly positioning these proteins for interactions with various factors in the presence of metal ions22 (Fig. 5a). FIX is involved in two pathways of clotting, namely, intrinsic and extrinsic pathways. FXIa participates in the intrinsic pathway whereas FVIIa is involved with the extrinsic pathway.21 Binding analyses were executed between FXIa, FVIIa, FXa, FIX, FIXa and FIX-bp, by following the methods described above for the IgG discrimination. Aer attaching FIXbp onto the surface of the CM4 sensor chip, 100 nM of the above clotting factors were injected independently on different ow cells, with the addition of 1 mM MgCl2 and 5 mM CaCl2 into the reaction mixture, as these metals are vital.22 As indicated in Fig. 5b, we could detect the interaction of FIX-bp with FIX, FIXa and FXa, but FIX-bp failed to interact with FXIa and FVIIa. Previously, we have determined the kinetic parameters for the interactions of FIX-bp with FIX and FX. For the interaction of FIX-bp and FIX, an association constant (ka), a dissociation constant (kd), and an equilibrium dissociation constant (Kd) of 1.6 105 M1 s1, 2.5 103 s1, and 34 109 M, respectively were obtained. Values of 1.8 105 M1 s1, 6.7 103 s1 and 40 109 M were recorded for the association constant (ka), dissociation constant (kd) and equilibrium dissociation constant (Kd), respectively for the interaction between FIX-bp and FX (Table 2).21 The complex structure revealed for the interaction of FIX and FIXbp by Shikamoto et al.21 supports the genuine interaction from the results obtained in this study. Based on these values, it was concluded that FIX-bp has equal affinity to FIX and FX. The present study revealed that the efficient recognition of bio-molecules with high specicity without any ambiguity is possible upon integration onto a SPR platform, for discrimination and high throughput analyses.
References 1 R. D. Jenison, S. C. Gill, A. Pardi and B. Polisky, Science, 1994, 263, 1425–1429. 2 A. Geiger, P. Burgstaller, H. V. Eltz, A. Roeder and M. Famulok, Nucleic Acids Res., 1996, 24, 1029–1036. 3 C. T. Lauhon and J. W. Szostak, J. Am. Chem. Soc., 1995, 117, 1246–1257. 4 J. A. Doudna, T. R. Cech and B. A. Sullenger, Proc. Natl. Acad. Sci. U. S. A., 1995, 92, 2355–2359. Analyst, 2014, 139, 2678–2682 | 2681
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5 S. D. Seiwert, T. S. Nahreini, S. Aigner, N. G. Ahn and O. C. Uhlenbeck, Chem. Biol., 2000, 7, 833–843. 6 M. Michaud, E. Jourdan, A. Villet, A. Ravel, C. Grosset and E. Peyrin, J. Am. Chem. Soc., 2003, 125, 8672–8679. 7 X. M. Liu, D. Zhang, G. Cao, G. Yang, H. Ding, G. Liu, M. Fan, B. Shen and N. Shao, J. Mol. Recognit., 2003, 16, 23–27. 8 X. M. Liu, G. Cao, H. Ding, D. Zhang, G. Yang, N. Liu, M. Fan, B. Shen and N. Shao, FEBS Lett., 2004, 562, 125–128. 9 S. C. B. Gopinath, T. Misono, K. Kawasaki, T. Mizuno, M. Imai, T. Odagiri and P. K. R. Kumar, J. Gen. Virol., 2006, 87, 479–487. 10 S. C. B. Gopinath, D. Balasundaresan, J. Akitomi and H. Mizuno, J. Biochem., 2006, 140, 667–676. 11 E. Suenaga, H. Mizuno and P. K. R. Kumar, Biosens. Bioelectron., 2012, 32, 195–201. 12 S. C. B. Gopinath, K. Awazu, M. Fujimaki and K. Shimizu, Acta Biomater., 2013, 9, 5080–5087. 13 S. C. B. Gopinath, K. Hayashi, J. Lee, T. Kamori, C. Dong, T. Hayashi and P. K. R. Kumar, Anal. Chem., 2013, 85, 10455–10462.
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14 S. C. B. Gopinath, K. Awazu, P. Fons, J. Tominaga and P. K. R. Kumar, Anal. Chem., 2009, 81, 4963–4970. 15 H. C. Yang, K. W. Huang, S. H. Liao, H. E. Horng, J. J. Chieh, H. H. Chen, M. J. Chen, K. L. Chen and L. M. Wang, Appl. Phys. Lett., 2013, 102, 013119. 16 P. Leonard, S. Hearty and R. O'Kennedy, Methods Mol. Biol., 2011, 681, 403–418. 17 H. Wang, A. Karlsson, I. Sj¨ ostr¨ om and B. Wiman, Biochim. Biophys. Acta, 2006, 1764, 1730–1734. 18 P. Gagnon, C. Cheung and P. J. Yazaki, J. Immunol. Methods, 2009, 342, 115–118. 19 B. V. Kumar, G. Medoff, G. S. Kobayashi and W. L. Sieling, Infect. Immun., 1985, 48, 806–812. 20 H. Atoda, M. Ishikawa, E. Yoshihara, F. Sekiya and T. Morita, J. Biochem., 1995, 118, 965–973. 21 S. C. B. Gopinath, Y. Shikamoto, H. Mizuno and P. K. R. Kumar, Biochem. J., 2007, 405, 351–357. 22 Y. Shikamoto, T. Morita, Z. Fujimoto and H. Mizuno, J. Biol. Chem., 2003, 278, 24090–24094.
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Cite this: Analyst, 2014, 139, 2678
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Biomolecular discrimination analyses by surface plasmon resonance Subash C. B. Gopinath* and Penmetcha K. R. Kumar
Received 31st October 2013 Accepted 18th February 2014 DOI: 10.1039/c3an02052e www.rsc.org/analyst
Biomolecular discrimination is one of the most important ways to discriminate closely related species. In the past, several biomolecules have been observed with higher discrimination using different sensing systems. Herein, we have displayed discrimination of human and rabbit IgG and human clotting factors on Biacore-carboxymethylated dextran coated sensor chips.
The development of detection systems with specic probes, such as antibodies, aptamers, glycans and receptors, that distinguish closely related species will have great impact on developing specic diagnosis. Using the advantages of available probes, efficient biomolecular discrimination has been demonstrated for developing sensing systems. In the past, discrimination between closely related molecules such as theophylline vs. caffeine,1 L-arginine vs. D-arginine,2 oxidised vs. reduced forms of nicotinamide,3 closely related proteins,4 phosphorylated vs. non phosphorylated forms,5 peptide enantiomers,6 bovine vs. human thrombin,7,8 closely related inuenza sub-types,9 bovine vs. human clotting factor IX,10 human vs. avian receptors11,12 and sulfated natural polysaccharides have been demonstrated.13 Molecular discriminations are important events in the eld of biology, in order to distinguish molecules for functional analyses and classication. Using the advantages of the above probes, several sensing systems have been generated in this direction. Previously, it has been demonstrated with antibodybased discrimination on the BioDVD platform14 and waveguidemode sensors.12 Using antibody-activated magnetic nanoparticles, tumor discrimination was performed by ultralow-eld magnetic resonance imaging.15 Surface Plasmon Resonance (SPR)-Biacore discrimination of inuenza viruses were shown using aptamer-based9 and glycan-based11 probes. Biacore is a SPR-based system that has been widely used for immunosensing and other strategies including Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology, 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565, Japan. E-mail: gopis11@ gmail.com
2678 | Analyst, 2014, 139, 2678–2682
discrimination.11,16 Previously, we have shown RNA-aptamer based higher discrimination over 1000 fold for the differences between bovine and human factor IX with Biacore.13 Wang et al.17 have studied the interaction between plasminogen and antiplasmin variants by Biacore. Thus, Biacore is an important platform to discriminate closely related biomolecules based on bio-recognition elements such as monoclonal antibodies or aptamers. The Biacore system is designed based on SPR to evaluate the interaction between molecules in a real time manner. This system has an approach that involves the immobilization of an interacting partner onto the sensing surface, followed by the ow of the sample containing the binding partners over the surface. The interacting partners bound to the immobilized molecules on the sensor surface generate a response which is proportional to the bound mass (Fig. 1). In this study, we have explored further evidence using human and rabbit anti-immunoglobulin for their discrimination from immunoglobulin (IgG) from humans and rabbits.
Diagrammatic representation of the principles involved in surface plasmon resonance. On the sensing surface the ligand is attached and the interaction with the analyte is analysed. The light source passes through the prism, hitting the sensing surface and generating spectral changes due to an angular shift.
Fig. 1
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Fig. 2 Determination of the dissociation constant by SPR for antihuman IgG (Fc) vs. human full-length IgG (a); vs. human Fc (b); antirabbit IgG vs. rabbit IgG (c). The activated CM5 chip was coated with 20 mg ml1 antibody at pH 4.0 by injecting 100 ml of the solution at a flow rate of 10 ml min1, and was blocked with 1 M ethanolamine hydrochloride at a similar flow rate for 7 min. Then, 60 ml aliquots (different concentrations) of the antigen were injected at a flow rate of 30 ml min1 for 2 min. The running buffer contained 10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20.
Table 1
IgG, an antibody, is a protein with a ‘Y’ shaped structure in the immune system, which identies foreign targets called antigens on its two-armed region (variable region). Antibodies have ve isotypes known as IgD, IgE, IgG (monomers), IgA (dimer) and IgM (pentamer), among which IgG is most abundant. To carry out the present study, human monoclonal mouse IgG (Fc region), full-length human IgG and recombinant human IgG (Fc region) were purchased from R&D system, USA. Goat anti-rabbit IgG and antigen rabbit IgG were procured from Millipore, USA. The rate constant for antibody and antigen binding was measured using SPR (Biacore T100) at 25 C on a dextran-coated sensor chip (the CM5 chip from GE Healthcare, USA). Initially we carried out pH scouting and found that an acidic condition of pH 4.0 was ideal in both cases. The ow cells (1 and 2) of the CM5 chip were activated using N-hydroxysuccinimide and 1ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride. Aer this activation step, the antibody (20 mg ml1) was passed through ow cell 2 at a ow rate of 10 ml min1 for 10 min, resulting in the immobilization of the antibody on ow cell 2 of the CM5 chip through the primary amine group on the protein (antibody). Once immobilization of the antibody was complete, we blocked the remaining activated surface of the CM5 chip and ow cell 1 with 1 M ethanolamine HCl (pH 8.5) at a ow rate of 10 ml min1 for 7 min. The excess unbound molecules retained in ow cells 1 and 2 were washed out with binding buffer (10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20). Flow cell 1 was used as the control surface to rule out non-specic binding to the dextran as this ow cell was devoid of the antibody. To analyze the binding kinetics, single-cycle kinetics were measured with various concentrations of the antigen (2.5, 5, 10, 20, 40 nM or 25, 50, 100, 200, 400 nM) injected through the experimental ow cell (ow cell 2) and the control ow cell (ow cell 1) at a ow rate of 30 ml min1, with a total volume of 60 ml. The dissociation time was set for 2 min to obtain a smooth curve. Sensorgrams were corrected for the non-specic binding by subtracting the control curve (FC1) from the antigen curve (FC2), and the binding kinetics were evaluated. All of the sensorgrams were evaluated using the Biacore T100 Evaluation soware, version 2.0.2 (GE Healthcare), and were tted with a 1 : 1 binding model. This is the simplest model for the interaction between antigen and antibody according to the equation A + B ¼ AB. The rate of association was measured from the forward reaction, and the dissociation rate was measured from the reverse reaction. The equilibrium dissociation rate constant (Kd) is kd/ka, where kd is the dissociation rate and ka is the association rate. For each dataset, the chi-squared (c2) value for
Kinetic parameters for the analyses of antibodies against antigens from humans and rabbits
Ligand
Analyte
Association constant ka (M1 s1)
Dissociation constant kd (s1)
Equilibrium constant kd (nM)
Anti-human Anti-human Anti-human Anti-rabbit Anti-rabbit
Hu-full Hu-fc Ra-full Ra-full Hu-full
2.5 104 8.6 104 0.5 104 5.9 104 No binding
1.5 103 7.8 103 5.3 104 6.4 105 No binding
61 90 102 1 No binding
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Fig. 3 Determination of the dissociation constant by SPR for antihuman IgG (Fc) vs. rabbit IgG. The activated CM5 chip was coated with 20 mg ml1 antibody at pH 4.0 by injecting 100 ml of the solution at a flow rate of 10 ml min1, and was blocked with 1 M ethanolamine hydrochloride at a similar flow rate for 7 min. Then, 60 ml aliquots (25 to 400 nM) of antigen were injected at a flow rate of 30 ml min1 for 2 min. The running buffer was 10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20.
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a molecular weight of 150 000 daltons. Gagnon et al.18 reported the separation of fragments from IgG and showed the molecular weight of the Fc region to be 55 000 daltons on non-reduced SDS-PAGE. In addition, the affinity of the full-length IgG and Fc group may also differ with the antigen. In addition, though other regions are not involved in binding to the target, these ‘non-essential’ regions might be involved in strengthening the overall interaction of the antibody with its corresponding partner. Moreover, the full-length antigen used in this study is puried directly from human plasma, whereas the Fc-antigen is the recombinant protein, which also accounts for the affinity difference. We also evaluated the affinity between anti-rabbit IgG and the rabbit IgG antigen. Initially, we maintained the
Fig. 4 3D crystal structure of the Gla (g-carboxyglutamic acid-rich) domain of FIX complexed FIX-bp (PDB accession code 1J35).
goodness of t was less than 1, and the residuals were within 6 RU, suggesting that the data had a good t to the binding model. The tting data are displayed with the global rate constants (ka, kd, and Kd). By following the above set-up, initially we analysed the antihuman antibody against human full-length IgG and the Fc region of IgG and determined the dissociation constants. The anti-Fc region of IgG was bound to the full-length human IgG with an association constant (ka) and dissociation constant (kd) of 2.5 104 M1 s1 and 1.5 103 s1, respectively. The equilibrium dissociation constant (Kd) was estimated at 61 109 M (Fig. 2a and Table 1). However, the anti-Fc region of IgG was bound to the Fc region of human IgG with an association constant (ka), dissociation constant (kd), and equilibrium dissociation constant (Kd) of 8.6 104 M1 s1, 7.8 103 s1, and 90 109 M, respectively (Fig. 2b and Table 1). Based on this comparison between the binding of the anti-Fc region of human IgG against the antigen human full-length IgG and Fc region, it was evident that the full length IgG has higher affinity than the Fc region. This might be due to the larger size of the IgG than the Fc region. It is commonly known that IgG can have
2680 | Analyst, 2014, 139, 2678–2682
Fig. 5 (a) Cartoon illustrating the interaction between FIX or FX and FIX-bp. (b) Discrimination of clotting factor binding with FIX-bp by SPR. (c) Binding model on a sensor chip. The activated CM4 chip was coated with 20 mg ml1 FIX-bp by injecting 100 ml of the solution at a flow rate of 10 ml min1, and was blocked with 1 M ethanolamine hydrochloride. Then, 60 ml aliquots (100 nM final concentration) of the clotting factors were injected at a flow rate of 30 ml min1 for 2 min. 1 mM MgCl2 and 5 mM CaCl2 were added to the buffer (10 mM Hepes, pH 7.4, 150 mM NaCl, 0.005% polysorbate 20).
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Table 2
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Kinetic parameters for the analyses of FIXbp against blood clotting factors from human21
Analyte
Association constant ka (M1 s1)
Dissociation constant kd (s1)
Equilibrium constant kd (nM)
FIX FX FVIIa FXIa
1.6 105 1.8 105 No binding No binding
2.5 103 6.7 103 No binding No binding
34 40 No binding No binding
same concentrations (25 to 400 nM) used in the human sample case, but the sensorgram showed a higher response (3000 RU) and it was hard to calculate the kinetic parameters as it was out of range. It is generally believed that low concentrations of antigen give reliable kinetic data. Thus, we have re-evaluated using concentrations 10-fold less (2.5 to 40 nM), which reduced the response of the sensorgram 40 times (75 RU) and enabled calculation of the kinetic parameters. The association constant (ka), dissociation constant (kd), and equilibrium dissociation constant (Kd) were approximated at 5.9 104 M1 s1, 6.4 105 s1, and 1 109 M, respectively (Fig. 2c and Table 1). When compared to anti-human-antigen binding affinities, antirabbit and its corresponding antigen were 100 fold higher. This indicated that anti-rabbit IgG and IgG have better specicities to be used for sensing studies. Similarly, we have also performed a cross-reactivity study between the anti-human IgG and antigen rabbit IgG. The values obtained for the association constant (ka), dissociation constant (kd), and equilibrium dissociation constant (Kd) were 0.5 104 M1 s1, 5.3 104 s1, and 102 109 M, respectively (Fig. 3 and Table 1). This low discrimination might be due to the binding of anti-human antibody with the rabbit IgG antigen in the region of similarity between the human and rabbit IgG. Previously, cross reactivity of human and rabbit antibodies with fungal antigens was reported by immunoblotting.19 However, in the present study when we carried out crossreactivity binding between the anti-rabbit IgG and the antigen human IgG, no binding was observed (Table 1). These results proved that the anti-rabbit IgG used in this study is the right agent for discrimination between human and rabbit IgG. The advantage of SPR for discrimination of human and rabbit IgG is the multichannel system with simultaneous on-line measurements. Moreover, the system shown here can also be used for high-throughput analyses and for selective binding in a mixture of samples. As performed in the above study, we also gathered evidence using a SPR sensor for the discrimination of clotting factors involved in the human blood coagulation cascade using the receptor factor IX-binding protein (FIX-bp). FIX-bp is originally from snake venom, which is found to interact with Factor IX (FIX) and Factor X (FX).20,21 To carry out these interactive analyses, we have utilized the CM4 sensor chip from Biacore 2000. Human FIX, FIXa, FXa and XIa were purchased from American Diagnostica Inc. (USA). Human factor VIIa was obtained from Haematologic Technologies Inc. (USA). The FIX-bp was puried from the snake venom of Trimeresurus avoviridis, following the published purication protocol.20
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FIX-bp is known to bind specically to the Gla-domain of FIX. The three dimensional crystal structure of the Gla-domain of FIX complexed FIX-bp is available in the protein data bank and displayed in Fig. 4. The Gla-domain is responsible for binding to phospholipid membranes and assists in localizing these proteins to sites of injury and helps in properly positioning these proteins for interactions with various factors in the presence of metal ions22 (Fig. 5a). FIX is involved in two pathways of clotting, namely, intrinsic and extrinsic pathways. FXIa participates in the intrinsic pathway whereas FVIIa is involved with the extrinsic pathway.21 Binding analyses were executed between FXIa, FVIIa, FXa, FIX, FIXa and FIX-bp, by following the methods described above for the IgG discrimination. Aer attaching FIXbp onto the surface of the CM4 sensor chip, 100 nM of the above clotting factors were injected independently on different ow cells, with the addition of 1 mM MgCl2 and 5 mM CaCl2 into the reaction mixture, as these metals are vital.22 As indicated in Fig. 5b, we could detect the interaction of FIX-bp with FIX, FIXa and FXa, but FIX-bp failed to interact with FXIa and FVIIa. Previously, we have determined the kinetic parameters for the interactions of FIX-bp with FIX and FX. For the interaction of FIX-bp and FIX, an association constant (ka), a dissociation constant (kd), and an equilibrium dissociation constant (Kd) of 1.6 105 M1 s1, 2.5 103 s1, and 34 109 M, respectively were obtained. Values of 1.8 105 M1 s1, 6.7 103 s1 and 40 109 M were recorded for the association constant (ka), dissociation constant (kd) and equilibrium dissociation constant (Kd), respectively for the interaction between FIX-bp and FX (Table 2).21 The complex structure revealed for the interaction of FIX and FIXbp by Shikamoto et al.21 supports the genuine interaction from the results obtained in this study. Based on these values, it was concluded that FIX-bp has equal affinity to FIX and FX. The present study revealed that the efficient recognition of bio-molecules with high specicity without any ambiguity is possible upon integration onto a SPR platform, for discrimination and high throughput analyses.
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