Name: Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms (Video) | JoVE Journal
Uploaded: 2017-04-17T15:00:00.000+00:00
Duration: 15 min 27 s
Description: Learn to measure antibody-antigen binding kinetics using four biosensor platforms for drug discovery research. This comparative study guides selection of reliable instruments for therapeutic antibody evaluation.

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5 minutes

The authors thank Noah Ditto and Adam Miles for technical assistance on the IBIS MX96.

<ol><li>Cooper, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optical+biosensors+in+drug+discovery%5BTitle%5D)+AND+%22Nat+Rev+Drug+Discov%22%5BJournal%5D)">Optical biosensors in drug discovery.</a> Nat Rev Drug Discov. 1 (7), 515-528 (2002).</li>
<li>Van Regenmortel, M. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Measurement+of+antigen-antibody+interactions+with+biosensors%5BTitle%5D)+AND+%22J+Mol+Rec%22%5BJournal%5D)">Measurement of antigen-antibody interactions with biosensors.</a> J Mol Rec. 11 (1-6), 163-167 (1998).</li>
<li>Davidoff, S. N., Ditto, N. T., Brooks, A. E., Eckman, J., Brooks, B. D. Surface Plasmon Resonance for Therapeutic Antibody Characterization. Label-Free Biosensor Methods in Drug Discovery. , Available from:
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<li>Canziani, G. A., Klakamp, S., Myszka, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Kinetic+screening+of+antibodies+from+crude+hybridoma+samples+using+Biacore%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Kinetic screening of antibodies from crude hybridoma samples using Biacore.</a> Anal Biochem. 325 (2), 301-307 (2004).</li>
<li>Katsamba, P. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Kinetic+analysis+of+a+high-affinity+antibody%2Fantigen+interaction+performed+by+multiple+Biacore+users%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Kinetic analysis of a high-affinity antibody/antigen interaction performed by multiple Biacore users.</a> Anal Biochem. 352 (2), 208-221 (2006).</li>
<li>Abdiche, Y. N., Malashock, D. S., Pinkerton, A., Pons, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Exploring+blocking+assays+using+Octet%2C+ProteOn%2C+and+Biacore+biosensors%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Exploring blocking assays using Octet, ProteOn, and Biacore biosensors.</a> Anal Biochem. 386 (2), 172-180 (2009).</li>
<li>Abdiche, Y. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-Throughput+Epitope+Binning+Assays+on+Label-Free+Array-Based+Biosensors+Can+Yield+Exquisite+Epitope+Discrimination+That+Facilitates+the+Selection+of+Monoclonal+Antibodies+with+Functional+Activity%5BTitle%5D)+AND+%22PLoS+ONE%22%5BJournal%5D)">High-Throughput Epitope Binning Assays on Label-Free Array-Based Biosensors Can Yield Exquisite Epitope Discrimination That Facilitates the Selection of Monoclonal Antibodies with Functional Activity.</a> PLoS ONE. 9 (3), e92451(2014).</li>
<li>Ecker, D. M., Jones, S. D., Levine, H. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+therapeutic+monoclonal+antibody+market%5BTitle%5D)+AND+%22mAbs%22%5BJournal%5D)">The therapeutic monoclonal antibody market.</a> mAbs. 7 (1), 9-14 (2014).</li>
<li>Rich, R. L., Myszka, D. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Higher-throughput%2C+label-free%2C+real-time+molecular+interaction+analysis%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Higher-throughput, label-free, real-time molecular interaction analysis.</a> Anal Biochem. 361 (1), 1-6 (2007).</li>
<li>Keighley, W. <a target="_blank" href="http://www.ddw-online.com/p-149288">The need for high throughput kinetics early in the drug discovery process.</a> Drug Disc World. 12 (3), 39-45 (2011).</li>
<li>Lad, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((High-throughput+kinetic+screening+of+hybridomas+to+identify+high-affinity+antibodies+using+bio-layer+interferometry%5BTitle%5D)+AND+%22J+Biomol+Screen%22%5BJournal%5D)">High-throughput kinetic screening of hybridomas to identify high-affinity antibodies using bio-layer interferometry.</a> J Biomol Screen. 20 (4), 498-507 (2015).</li>
<li>Bravman, T., Bronner, V., Nahshol, O., Schreiber, G. <a target="_blank" href="http://link.springer.com/article/10.1007/s12195-008-0036-4">The ProteOn XPR36TM Array System-High Throughput Kinetic Binding Analysis of Biomolecular Interactions.</a> Cell Mol Bioeng. 1 (4), 216-228 (2008).</li>
<li>Eddings, M. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Improved+continuous-flow+print+head+for+micro-array+deposition%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Improved continuous-flow print head for micro-array deposition.</a> Anal Biochem. 382 (1), 55-59 (2008).</li>
<li>Abdiche, Y., Malashock, D., Pinkerton, A., Pons, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Determining+kinetics+and+affinities+of+protein+interactions+using+a+parallel+real-time+label-free+biosensor+the+Octet%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Determining kinetics and affinities of protein interactions using a parallel real-time label-free biosensor the Octet.</a> Anal Biochem. 377 (2), 209-217 (2008).</li>
<li>Abdiche, Y. N., Lindquist, K. C., Pinkerton, A., Pons, J., Rajpal, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Expanding+the+ProteOn+XPR36+biosensor+into+a+36-ligand+array+expedites+protein+interaction+analysis%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Expanding the ProteOn XPR36 biosensor into a 36-ligand array expedites protein interaction analysis.</a> Anal Biochem. 411 (1), 139-151 (2011).</li>
<li>Rich, R. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((A+global+benchmark+study+using+affinity-based+biosensors%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">A global benchmark study using affinity-based biosensors.</a> Anal Biochem. 386 (2), 194-216 (2009).</li>
<li>Yang, D., Singh, A., Wu, H., Kroe-Barrett, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Comparison+of+biosensor+platforms+in+the+evaluation+of+high+affinity+antibody-antigen+binding+kinetics%5BTitle%5D)+AND+%22Anal+Biochem%22%5BJournal%5D)">Comparison of biosensor platforms in the evaluation of high affinity antibody-antigen binding kinetics.</a> Anal Biochem. 508, 78-96 (2016).</li>
<li>Yang, D., Singh, A., Wu, H., Kroe-Barrett, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Dataset+of+the+binding+kinetic+rate+constants+of+anti-PCSK9+antibodies+obtained+using+the+Biacore+T100+ProteOn+XPR36%2C+Octet+RED384%2C+and+IBIS+MX96+biosensor+platforms%5BTitle%5D)+AND+%22Data+in+Brief%22%5BJournal%5D)">Dataset of the binding kinetic rate constants of anti-PCSK9 antibodies obtained using the Biacore T100 ProteOn XPR36, Octet RED384, and IBIS MX96 biosensor platforms.</a> Data in Brief. 8, 1173-1183 (2016).</li>
<li>Bouvier, E. S. P., Koza, S. M. <a target="_blank" href="http://www.sciencedirect.com/science/article/pii/S0165993614001952">Advances in size-exclusion separations of proteins and polymers by UHPLC.</a> Trends Anal Chem. 63, 85-94 (2014).</li>
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Publication fees for this video-article were paid by&#160;Boehringer Ingelheim Pharmaceuticals.

Our head-to-head comparison study shows that each biosensor platform has its own strengths and weaknesses. Even though the binding profiles of the antibodies are similar by visual comparison (Figures 3 - 6), and the rank order of the acquired kinetic rate constants are highly consistent across the instruments (Figure 7), our results show that SPR-based instruments with continuous flow fluidics) are better at resolving high-affinity interactions with slow dissociation rates. Upward drift during the dissociation phase is observed in datasets (e.g., mAb 2, mAb 5, and mAb 9; Figure 5) generated by the BLI fluidics-free instrument. This finding can be attributed in large part to sample evaporation over time in the microplate, which is a primary limitation of the system. With this inherent limitation, the experimental time is also restricted to less than 12 h; the experiments were therefore programmed with shorter times (500 s association and 30 min dissociation) compared to those of the other platforms (10 min association and 45 min dissociation). However, shortening the experimental time did not appear to mitigate the impact of evaporation on data quality/consistency, as the rate constants generated by the BLI-based instrument show less linearity as a result of fluctuations in some of the off-rates (Figure 8C). In addition to sample evaporation, differences in the capture reagents used may have also contributed to the differences in the results obtained. While protein A/G was used in all three fluidics-based SPR platforms, AHC sensors were used in the non-fluidics BLI platform. Since protein A/G is likely to have a weaker affinity for the mAbs than does the AHC, an antibody-based biosensor surface, the off-rates of the mAb-antigen complex from the protein A/G surfaces may artificially appear faster than those obtained from the AHC surface. This possibility is supported by the experimental data showing that the off-rate values generated by the BLI platform were consistently lower than those obtained from the other instruments (Figure 7, red line). Nevertheless, the BLI platform has different advantages over the other platforms. For example, it is highly flexible with regard to sensor choice and assay configuration due to the various pre-coated sensors for immediate use. In our experiments, use of the AHC sensors eliminated the need for ligand immobilization steps, reducing the preparation time. Furthermore, the BLI platform requires much less maintenance compared to the other fluidics SPR platforms, which feature complicated tubing and value switch configurations. This feature is an advantage for experiments involving crude samples that can cause clogging and contamination issues.
As the demand for the efficient, rapid, and accurate identification of therapeutic candidates increases, the need for biosensor throughput is also rising. Among the four biosensor platforms, the throughput from the biosensor capable of 96-ligand array printing is the highest, followed by the biosensor coupled to a crisscrossing 36-ligand format and the BLI-based biosensor with 16-channel simultaneous readout, which ultimately increase the number of interactions measured in a single binding cycle to 96, 36 and 16, respectively. These throughput capabilities are significantly higher than that of the traditional SPR platform, which is limited by having only four flow cells connected by a single serial flow. Since our experiments involved a relatively small sample set of 10 mAbs evaluated at multiple surface densities with long dissociation times, the instrumental throughputs played a moderate role in determining the efficiency of the experiments. There were no significant differences in the experimental times of the three high-throughput platforms, and in all cases the experiments were completed in one day. On the other hand, the traditional serial flow SPR experiments required 3 days to complete, despite the walk-away automation of data acquisition after setup. In other studies that involve a large number of samples (i.e. in the hundreds or thousands), for off-rate ranking/kinetic screening or epitope binning purposes, the throughput becomes a critical factor.
Although the throughput in the IBIS MX96 is orders of magnitude higher than that of the other biosensors and is therefore an optimal choice for these purposes, it has a few shortcomings. In particular, the array printing by the CFM shows large surface inconsistencies (Figure 1) and reduced data reproducibility (Figure 8D and 8E). For accurate kinetic measurements, the amount of ligand on the biosensor surface is a critical parameter that needs to be controlled to ensure that the binding responses are not disturbed by secondary factors such as mass transfer or steric hindrance. For the Biacore T100 and ProteOn XPR36, the optimal RL levels were determined based on the standard calculation of set Rmax values as described in the research article17. On the other hand, for the Octet RED384 and IBIS MX96 platforms, the mAb capture levels were attained empirically using a series of 2-fold serially diluted antibodies at constant times. The lack of knowledge or control of the capture step resulted in a high-density surface and high binding response signals (Figure 2) that may have compromised the accuracy of the kinetic rate constants. Furthermore, the separation of the printer from the SPR detector also presents a challenge when conducting multiple binding cycle measurements involving regenerations. The only way to perform the multi-cycle kinetics setup was through direct amine coupling of the mAbs, as opposed to capture through the mAb Fc by the immobilized protein A/G surface in the other three biosensor platforms. As a result, an additional regeneration scouting experiment was required to determine the optimal regeneration conditions. The outcome of this setup was linked to a ~90% lower observed surface activity compared to the Fc capture method (Figure 9), in addition to a longer experimental time. To execute the Fc capture method, an alternative single-cycle kinetic approach was adopted. This approach involves the sequential injection of analyte at increasing concentrations without regeneration between each injection (Figure 2). This highly convenient, but less commonly applied approach not only shortened the experimental time and reduced reagent consumption, but also produced kinetic rate constants highly similar to those from the other biosensors (Figure 7). Therefore, applying this single-cycle kinetics approach overcomes the inherent configuration limitation of the instrument and presents an opportunity for obtaining high-resolution kinetic rate constants in a high-throughput manner.
Despite the throughput being a major limitation in the Biacore T100, our results collectively show that it generated the most consistent data with the highest quality. This was followed by the ProteOn XPR36, which has ~ 10-fold higher throughput. Their ability to generate high-quality data becomes an advantage when characterizing high-affinity antibody-antigen interactions that can be technically challenging when the instruments&#39; detection limits are reached. While the systematic limitations in instrumentation of the Octet RED384 hinder the accurate measurement of dissociation rate constants (i.e., falling short of the sensitivity to resolve sufficient signal decay for slow off-rates), both the Biacore T100 and ProteOn XPR36 can provide sensitive and reliable detection for differentiation.

The acquisition of reliable kinetic parameters for characterizing antibody-antigen interactions is an essential component of the drug discovery and development process1. Optical Surface Plasmon Resonance (SPR) biosensors, the "gold standard" for real-time detection of these interactions, have been used for approximately two decades to enable early selection of criteria-meeting therapeutic antibody candidates2,3. In addition to providing an affinity ranking of antibody candidates by the rapid binding screening of crude supernatants4, and rigorous kinetic constant determinations of purified preparations5, biosensors can further differentiate the functional activity of lead candidates via epitope binning studies6,7. 
To meet the growing demand of antibody-based products for various therapeutic indications8, a wide variety of innovative biosensor instruments have been developed in recent years that increase the efficiency of candidate identification and characterization9,10. These instruments differ in microfluidic channel configuration design and/or in the optical principles involved in detecting biomolecular interactions. Specifically, the Octet RED38411, ProteOn XPR3612, and IBIS MX967 have expanded the number of interactions measured in a single binding cycle to 16, 36, and 96 respectively, representing significant throughput improvements over the traditional Biacore platform. Although these various biosensor platforms all provide essential kinetic data for characterizing antibody-antigen interactions, they differ in experimental setup and operational procedures due to variations in instrumental configurations. For example, in the IBIS MX96's SPR imaging array platform, the multiplex ligand immobilization step is performed in an off-line mode in an external printing device separate from the detector7,13; in contrast, the other three biosensor platforms utilize an "all-in-one" setup, where the addition of component onto the sensor surface, whether it is the activation reagent, ligand, or analyte, is recorded in real time and through pre-programmed commands in sequential order. In the Octet RED384, a unique feature of this BioLayer Interferometry (BLI)-based platform is the availability of pre-coated optical fiber biosensors for immediate "dip-and-read" use14, eliminating the need for ligand surface preparation and initiation/conditioning steps, which are often required for the sensor chips in SPR-based platforms. This instrument's fluidic-free design also simplifies the mechanics and avoids clogging and contamination concerns when dealing with crude samples. With the novel 6 x 6 crisscrossing fluidic design in the ProteOn XPR36, a "one-shot" kinetics approach can be implemented by switching the flow channels between horizontal and vertical directions to create 36 interaction spots15. Instead of assessing binding kinetics one ligand or analyte concentration at a time, as is done in the traditional serial flow Biacore T100 platform, this approach offers the ability to monitor up to 36 different interactions simultaneously in a single binding cycle. 
Despite their differences, these four biosensor platforms are all widely used by many laboratories worldwide. For new users with little hands-on biosensor experience, deciding which instrument to use can be a challenging task given the differences in instrumental design. To determine the most appropriate instrument for their research purposes, factors such as data quality, performance consistency, throughput, ease of operation, and material consumption need to be considered collectively. While several benchmark studies have explored the variability of kinetic rate constants obtained from multiple laboratories and biosensors5,16, a recently published head-to-head comparison study further addresses the systematic factors that influence data reliability from the instrumental performance point of view17,18. The protocols supplied in this video focus on the experimental setup and procedures in detail, and are accompanied by the research article entitled, "Comparison of biosensor platforms in the evaluation of high affinity antibody-antigen binding kinetics"17. These protocols are intended not only to help new biosensor users implement these instruments for their research purposes, but also to provide additional insights for current biosensor users regarding technical challenges and considerations in experimental designs for evaluating high-affinity antibody-antigen interactions.

<table><tbody><tr><td>Biacore T100 System</td><td>GE Healthcare</td><td>28975001</td><td>The T100 system has been upgraded to T200</td></tr><tr><td>CM5 Sensor Chip&amp;nbsp;</td><td>GE Healthcare</td><td>BR100012</td><td></td></tr><tr><td>BIAevaluation&amp;nbsp;</td><td>GE Healthcare</td><td></td><td>Version 4.1</td></tr><tr><td>Biacore T100 Control Software</td><td>GE Healthcare</td><td></td><td>The T100 control software has been upgraded to T200</td></tr><tr><td>Amine Coupling Kit</td><td>GE Healthcare</td><td>BR100050&amp;nbsp;</td><td>It contains: 750 mg 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC), 115 mg N-hydroxysuccinimide (NHS), 10.5 mL 1.0 M ethanolamine-HCl pH 8.5&amp;nbsp;</td></tr><tr><td>HBS-EP+ Buffer 10&amp;times;</td><td>GE Healthcare</td><td>BR100669</td><td>Concentrated stock solution&amp;nbsp;</td></tr><tr><td>Plastic Vials, o.d. 7 mm</td><td>GE Healthcare</td><td>BR100212&amp;nbsp;</td><td></td></tr><tr><td>Rubber Caps, type 3</td><td>GE Healthcare</td><td>BR100502</td><td></td></tr><tr><td>Plastic Vials and Caps, o.d. 11 mm</td><td>GE Healthcare</td><td>BR100214&amp;nbsp;</td><td></td></tr><tr><td>ProteOn XPR36 Protein Interaction Array System</td><td>Bio-Rad</td><td>1760100</td><td></td></tr><tr><td>ProteOn Manager Software&amp;nbsp;</td><td>Bio-Rad</td><td>1760200</td><td>Version 3.1.0.6</td></tr><tr><td>GLM Sensor Chip</td><td>Bio-Rad</td><td>1765012</td><td></td></tr><tr><td>Amine Coupling Kit</td><td>Bio-Rad</td><td>1762410</td><td>It includes EDAC (EDC), sulfo-NHS, ethanolamine HCl&amp;nbsp;</td></tr><tr><td>Regeneration and Conditioning Kit and Buffers</td><td>Bio-Rad</td><td>1762210</td><td>It includes 1 each glycine buffer (pH 1.5, 2.0, 2.5, 3.0), and NaOH, SDS, HCl, phosphoric acid, NaCl; 50 mL each solution&amp;nbsp;</td></tr><tr><td>2 L PBS/Tween/EDTA buffer</td><td>Bio-Rad</td><td>1762730</td><td>It includes hosphate buffered saline (PBS), pH 7.4, 0.005% Tween 20, 3 mM EDTA&amp;nbsp;</td></tr><tr><td>Octet RED384 System</td><td>Fort&amp;eacute;Bio</td><td></td><td></td></tr><tr><td>Data Analysis Software</td><td>Fort&amp;eacute;Bio</td><td></td><td>Version 9.0.0.4</td></tr><tr><td>Dip and Read Anti-hIgG Fc Capture (AHC) Biosensors</td><td>Fort&amp;eacute;Bio</td><td>18-5060</td><td>One tray of 96 biosensors&amp;nbsp;</td></tr><tr><td>384-Well Tilted-Bottom Plate&amp;nbsp;</td><td>Fort&amp;eacute;Bio</td><td>18-5080</td><td></td></tr><tr><td>Biosensor Dispenser</td><td>Fort&amp;eacute;Bio</td><td>18-5016</td><td></td></tr><tr><td>Kinetics Buffer 10x</td><td>Fort&amp;eacute;Bio</td><td>18-1092</td><td>10x concentration. Contains ProClin 300.&amp;nbsp;</td></tr><tr><td>IBIS MX96 SPRi System</td><td>Wasatch Microfluidics</td><td></td><td></td></tr><tr><td>Microfluidics Continuous Flow Microspotter (CFM) Printer</td><td>Wasatch Microfluidics</td><td></td><td>Version 2.0</td></tr><tr><td>SensEye COOH-G chip</td><td>Wasatch Microfluidics</td><td></td><td>1-09-04-004</td></tr><tr><td>Data Analysis Software</td><td>Wasatch Microfluidics</td><td></td><td>Version 6.19.3.17</td></tr><tr><td>SPRint Data Analysis Software</td><td>Wasatch Microfluidics</td><td></td><td>Version 6.15.2.1</td></tr><tr><td>Scrubber 2</td><td>BioLogic Software</td><td></td><td>Version 2</td></tr><tr><td>Pierce Recombinant Protein A/G</td><td>ThermoFisher Scientific</td><td>21186</td><td></td></tr></tbody></table>

determination of high-affinity antibody-antigen binding kinetics using four biosensor platforms

Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

Label-free optical biosensors are powerful tools in drug discovery for the characterization of biomolecular interactions. In this study, we describe the use of four routinely used biosensor platforms in our laboratory to evaluate the binding affinity and kinetics of ten high-affinity monoclonal antibodies (mAbs) against human proprotein convertase subtilisin kexin type 9 (PCSK9). While both Biacore T100 and ProteOn XPR36 are derived from the well-established Surface Plasmon Resonance (SPR) technology, the former has four flow cells connected by serial flow configuration, whereas the latter presents 36 reaction spots in parallel through an improvised 6 x 6 crisscross microfluidic channel configuration. The IBIS MX96 also operates based on the SPR sensor technology, with an additional imaging feature that provides detection in spatial orientation. This detection technique coupled with the Continuous Flow Microspotter (CFM) expands the throughput significantly by enabling multiplex array printing and detection of 96 reaction sports simultaneously. In contrast, the Octet RED384 is based on the BioLayer Interferometry (BLI) optical principle, with fiber-optic probes acting as the biosensor to detect interference pattern changes upon binding interactions at the tip surface. Unlike the SPR-based platforms, the BLI system does not rely on continuous flow fluidics; instead, the sensor tips collect readings while they are immersed in analyte solutions of a 384-well microplate during orbital agitation.
Each of these biosensor platforms has its own advantages and disadvantages. To provide a direct comparison of these instruments&#39; ability to provide quality kinetic data, the described protocols illustrate experiments that use the same assay format and the same high-quality reagents to characterize antibody-antigen kinetics that fit the simple 1:1 molecular interaction model.

Figure 1 shows the antibody array image from the CFM and the spotted mAb levels by the two immobilization methods, and Figure 2 shows the corresponding binding sensorgrams generated in the MX96 from the multi-cycle kinetic and the single-cycle kinetic measurements on these mAb arrays. The real-time binding and kinetically fitted curves from multiple antibody-coated surfaces generated in the four biosensor platforms are shown in Figures 3 - 6. Figure 7 shows the comparison of the final kinetic rates and equilibrium binding constants obtained from the global analysis of these binding curves. The individual association (ka), dissociation (kd), and equilibrium (KD) binding constants are presented in Table 1. To demonstrate the variability of datasets generated within the same instrument, Figure 8 shows plots of ka, kd, and KD at different mAb surface densities, and Figure 9 further compares the calculated binding activities of the mAb surfaces across the biosensor platforms.
<img alt="SPR assay; charts showing concentration-response of mAbs; microarray images with labeled wells." src="/files/ftp_upload/55659/55659fig1.jpg" data-altupdatedat="1788250015000" data-alt="Figure 1"> 
Figure 1. Multiplex Ligand Arrays of Amine-coupled (A) and Fc-captured (B) Antibody Surfaces from CFM Printing in the IBIS MX96. Images of the printed arrays are shown in the left panels, where the grey areas enclosed by red squares indicate the presence of antibody. The darker interspots located between the active antibody spots are used for reference subtraction. Each column contains an antibody printed at the titration concentrations identified below and to the left of the image. The amounts of the printed antibodies quantified by calculating the difference in bulk shifts between the active and reference locations are shown in the right panels. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Surface plasmon resonance graph showing response vs. time for protein interaction analysis." src="/files/ftp_upload/55659/55659fig2.jpg" data-altupdatedat="1788250015000" data-alt="Figure 2"> 
Figure 2. Comparison of Real-time Binding Sensorgrams from Multi-cycle (A) and Single-cycle (B) Kinetic Experiments in the IBIS MX96. The sequential injections of human PCSK9 at increasing concentrations across the 10 x 8 antibody arrays are noted above each corresponding sensorgram segment. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Biacore T100 sensorgram chart, mAb binding kinetics, surface plasmon resonance analysis." src="/files/ftp_upload/55659/55659fig3.jpg" data-altupdatedat="1788250015000" data-alt="Figure 3"> 
Figure 3. Binding Sensorgrams of the Captured Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the Biacore T100. The interactions are evaluated over high- (top panels), medium- (middle panels), and low- (bottom panels) density surfaces. The overlaid smooth black lines represent the kinetic fit of the binding response signals at different human PCSK9 concentrations (colored lines) to a 1:1 interaction model. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Protein interaction analysis, sensorgram graph for mAb binding affinity, ProteOn XPR36 results." src="/files/ftp_upload/55659/55659fig4.jpg" data-altupdatedat="1788250015000" data-alt="Figure 4"> 
Figure 4. Binding Sensorgrams of the Captured Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the ProteOn XPR36. The interactions are evaluated over high- (top panels), medium- (middle panels), and low- (bottom panels) density surfaces. The overlaid smooth black lines represent the kinetic fit of the binding response signals at different human PCSK9 concentrations (colored lines) to a 1:1 interaction model. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Octet RED384 binding curves, mAb kinetics, sensorgram data, immunoassay analysis, graph results." src="/files/ftp_upload/55659/55659fig5.jpg" data-altupdatedat="1788250015000" data-alt="Figure 5"> 
Figure 5. Binding Sensorgrams of the Captured Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the Octet RED384. The interactions are evaluated over high- (top panels), medium- (middle panels), and low- (bottom panels) density surfaces. The overlaid red lines represent the kinetic fit of the binding response signals at different human PCSK9 concentrations (colored lines) to a 1:1 interaction model. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="IBIS MX96 binding assay results, amine-coupled and Fc-captured, microarray sensorgram charts." src="/files/ftp_upload/55659/55659fig6.jpg" data-altupdatedat="1788250015000" data-alt="Figure 6"> 
Figure 6. Binding Sensorgrams of the Amine-coupled (A) and Fc-captured (B) Antibodies Interacting with Human PCSK9 and 1:1 Kinetic Model Fit Overlays in the IBIS MX96. The binding profiles are organized as 10 x 8 panels that follow the array plate map in Figure 1. The black lines represent the recorded binding response signals at different human PCSK9 concentrations, and the overlaid red lines represent the fitted curves. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig6large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Kinetics analysis graph, showing rates (ka, kd) and affinity (KD) for 10 mAbs; data comparison." src="/files/ftp_upload/55659/55659fig7.jpg" data-altupdatedat="1788250015000" data-alt="Figure 7"> 
Figure 7. Comparison of the Association ka (A), Dissociation kd (B), and Equilibrium KD (C) Binding Constants Generated by the Four Biosensor Platforms. The kinetic parameters are derived from global analysis of the binding curves in Figures 3 - 6. The instruments are represented as follows: Biacore T100 (blue), ProteOn XPR36 (green), Octet RED384 (red), IBIS MX96, amine-coupled (purple), and IBIS MX96, Fc-captured (orange). <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig7large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Kinetics analysis chart showing mAb captured density vs. kinetic constants (kon, koff, KD) in SPR." src="/files/ftp_upload/55659/55659fig8.jpg" data-altupdatedat="1788250015000" data-alt="Figure 8"> 
Figure 8. Comparison of the Consistency of Kinetic Rate Constants Over Multiple Antibody Surface Densities in the Biacore T100 (A), ProteOn XPR36 (B), Octet RED384 (C), IBIS MX96, amine-coupled (D), and IBIS MX96, Fc-captured (E). The kinetic parameters ka (top sub-panels), kd (middle sub-panels), and KD (bottom sub-panels) are derived from group analysis at individual antibody surface density. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig8large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Bar chart comparing % mAb surface activity in biosensor systems: Biacore, ProteOn, Octet, IBIS." src="/files/ftp_upload/55659/55659fig9.jpg" data-altupdatedat="1788250015000" data-alt="Figure 9"> 
Figure 9. Binding Activities of the Antibody Surfaces and Their Standard Deviations (error bars) in the Four Biosensor Platforms. The values are calculated using equations described in the research articles17. <a href="http://cloudflare.jove.com/files/ftp_upload/55659/55659fig9large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2"></td>
			<td>ka</td>
			<td>kd</td>
			<td>KD</td>
		</tr>
		<tr>
			<td>(M-1s-1)</td>
			<td>(s-1)</td>
			<td>(nM)</td>
		</tr>
		<tr>
			<td>mAb 1</td>
			<td>11.7 (7.8) x 105</td>
			<td>4.89 (4.18) x 10-5</td>
			<td>0.052 (0.05)</td>
		</tr>
		<tr>
			<td>mAb 2</td>
			<td>1.53 (0.28) x 105</td>
			<td>1.30 (1.54) x 10-5</td>
			<td>0.092 (0.12)</td>
		</tr>
		<tr>
			<td>mAb 3</td>
			<td>11.4 (8.3) x 105</td>
			<td>27.6 (11.0) x 10-5</td>
			<td>0.333 (0.20)</td>
		</tr>
		<tr>
			<td>mAb 4</td>
			<td>3.61 (1.6) x 105</td>
			<td>20.1 (12.3) x 10-5</td>
			<td>0.659 (0.54)</td>
		</tr>
		<tr>
			<td>mAb 5</td>
			<td>0.59 (0.21) x 105</td>
			<td>3.46 (2.50) x 10-5</td>
			<td>0.663 (0.46)</td>
		</tr>
		<tr>
			<td>mAb 6</td>
			<td>1.19 (0.78) x 105</td>
			<td>7.21 (3.83) x 10-5</td>
			<td>0.894 (0.64)</td>
		</tr>
		<tr>
			<td>mAb 7</td>
			<td>1.29 (0.53) x 105</td>
			<td>16.4 (5.63) x 10-5</td>
			<td>1.57 (1.02)</td>
		</tr>
		<tr>
			<td>mAb 8</td>
			<td>4.02 (2.23) x 105</td>
			<td>22.8 (10.7) x 10-5</td>
			<td>0.768 (0.68)</td>
		</tr>
		<tr>
			<td>mAb 9</td>
			<td>4.20 (2.13) x 105</td>
			<td>6.67 (4.3) x 10-5</td>
			<td>0.197 (0.16)</td>
		</tr>
		<tr>
			<td>mAb 10</td>
			<td>1.20 (0.49) x 105</td>
			<td>12.5 (7.64) x 10-5</td>
			<td>1.27 (0.80)</td>
		</tr>
	</tbody>
</table>
Table 1: Kinetic Rates and Equilibrium Binding Constants of 10 mAbs Obtained by Global Fitting of Binding Curves from Four Biosensor Instruments to the 1:1 Interaction Model.

We describe here protocols for the measurement of antibody-antigen binding affinity and kinetics using four commonly used biosensor platforms.

Label-free optical biosensors are powerful tools in drug discovery for the characterization of biomolecular interactions. In this study, we describe the ...

The goal of this biosensor study is to compare the ability of the four routinely used biosensor platforms to provide quality kinetic data and to provide insights regarding technical challenges and considerations in experimental designs for evaluating high-affinity antibody-antigen interactions. This study answers key questions in the drug discovery field for the selection of biosensor platforms and assay formats that allow the most reliable results when evaluating therapeutic antibody candidates. The main advantage of this study is that it provides a direct and comprehensive comparison of the various biosensor platforms, with regard to data consistency, quality, and operational efficiency.Video demonstration of the four protocols is critical, as it helps new users with little hands-on experience learn how to set up experiments on these instruments. For kinetic measurements in the Biacore T100, click File, Open New Method, and open the method file. Review the parameters in the method.In Cycle Types, set the contact time to 220 seconds for capture 1 over flow path 2, 110 seconds for capture 2 over flow path 3, and 55 seconds for capture 3 over flow path 4. The flow rate is 10 microliters per minute for all of the capture cycles. Select Sample 1 and check sample solution as a variable.Then, set the contact time to 600 seconds, and the dissociation time to 2, 700 seconds over flow path 1, 2, 3, 4. The flow rate is set to 30 microliters per minute. Next, select Regeneration 1, enter glycine HCl pH 1.5 in the solution field, and set the contact time to 20 seconds over flow path 1, 2, 3, 4.In Variable Settings, enter twofold titrating concentrations of 100 nanomolar to 6.25 nanomolar for cycle 1-3, 50 nanomolar to 3.12 nanomolar for cycle 4-8, and 5 nanomolar to 0.323 nanomolar for cycle 9-10. In Setup Run, choose the detection flow path 2-1, 3-1, 4-1, then, click next. Check prime before run and then click next again.Select Sample and Reagent Rack 1 and define the location for the reagents. Pipette the reagents into the individual sample vials accordingly and insert the rack into the instrument. Click Eject Rack to open the sample tray compartment door and then insert the sample rack into the instrument.Then click Start and enter an experiment name to be saved to start the run. For the kinetic measurements in the ProteOn XPR36, begin immobilization by selecting Protocols and then Samples. Define EDC/Sulfo-NHS as activator in wells H1-H6, protein A/G as ligand in G1-G6, ethanolamine as deactivator in F1-F6, glycine as regenerator in E1-E6, PBS-T-EDTA as blank in D1-D6, monoclonal antibody X sample as ligand in C1-C6, and human PCSK9 as analyte in wells B1-B6.Select Steps and then double-click Immobilization in the protocol editor. The steps include three subsequent horizontal injections of EDC/Sulfo-NHS, protein A/G, and one molar ethanolamine. Each injection should have a flow rate of 30 microliters per minute and a contact time of 300 seconds.Next, click Regenerate. Inject three 18-second pulses of glycine at 100 microliters per minute in both the horizontal and vertical directions. Follow this with two 60-second pulses of PBS-T-EDTA at 25 microliters per minute, also in both directions.Then, click Ligand and inject monoclonal antibody 1, monoclonal antibody 2 in the vertical direction, using a flow rate of 25 microliters per minute and a contact time of 160 seconds. After clicking Analyte, inject five concentrations of human PCSK9 in a blank buffer over six horizontal channels simultaneously. Use 40 microliters per minute for 600 seconds of association time, followed by 2, 700 seconds of dissociation time.Then, click Regenerate and inject two 18-second pulses of glycine at 100 microliters per minute in both the horizontal and vertical directions. Next, prepare the samples and reagents in one 96-well plate according to the defined reagent positions. Transfer the plate to the instrument and then click the Run tab, select the protocol, and click Start.The six-needle parallel injection in the recording of live experimental data is demonstrated. For the kinetic measurements in the Octet RED384, set up the experimental method by first clicking Experiment, followed by New Experiment Wizard, New Kinetics Experiment, and then Basic Kinetics in the data acquisition software. Then click Modify Plates and change 96 Wells to 384 Wells in both Plate 1 and Plate 2.Define the sample types and positions in the plate as described in the text protocol. Navigate to assay definition to define the experimental setup. The experimental setup is defined as a baseline time of 30 seconds, a regeneration time of 30 seconds, an equilibration time of 18 seconds, a loading with a time of 200 seconds, an association time of 500 seconds, and a dissociation time of 1, 800 seconds.The shake speed is set to 1, 000 RPM. To add the steps to the assay steps list, first, click on a step, and then click on the wells located in either the sample or the reagent plate. First, enter in the equilibration regeneration instructions to precondition the anti-human Fc capture sensors by three cycles of 15-second dips in glycine alternating with 15-second dips in 1XKB.Then, enter the loading instructions to capture the monoclonal antibody samples onto the anti-human Fc capture sensors for 200 seconds. Next, enter the baseline instructions to establish the bio-layer interferometry signal for 60 seconds before the association step. Input the association step to dip the sensors into wells containing varying concentrations of human PCSK9 for a 500-second association period.Enter the dissociation step to dip the PCSK9-bound sensors into new wells of 1XKB for an 1, 800-second dissociation period. Finally, for the regeneration step, dip the monoclonal antibody PCSK9-bound sensors into wells of glycine with two 18-second pulses between each binding cycle. Go to Review Experiments, slide through the steps, then click the green open button to open the sample compartment.Transfer the sample plates into the instrument. Navigate to Run Experiments, enter a 60-second delay time, and shake the sample plate while waiting. Set the plate temperature to 25 degrees Celsius, enter experiment run name, and then press Go.Live data collection is shown here.For multi-cycle kinetic measurements in the IBIS-MX96, install the sensor chip into the continuous flow microspotter. Open the CFM2.0 software, then click Load Settings, and 96 Amine Couple. Place the two sample and reagent plates into the CFM printer.To create the antibody array, hit Run to start the printer and deliver the EDC/Sulfo-NHS in the top half of the reagent plate to the sensor using 48 microchannels and cycle them over the sensor surface for five minutes. Deliver the monoclonal antibody samples in the top half of the source plate to the sensor, and cycle them across the activated surfaces for 10 minutes. Then, deliver the immobilization buffer from a 50 milliliter conical tube over the antibody surface for five minutes.Dock the printed sensor chip into the instrument. In the control software, click File, Open measurement, Existing measurement, and select the method file. Transfer the printed sensor chip into the instrument.In the general menu, select G-System Prime under Full system script. Then, select G-Quench to deactivate the monoclonal antibody surfaces by injecting 150 microliters of one molar ethanolamine. In Analysis Cycle, select A-AP Standard Run under IBIS Scripts.Set 1.0 minutes for baseline, 10.0 minutes for association, and 90 steps for dissociation at eight microliters per second speed. Inside the cycles, inject human PCSK9 one concentration at a time, following five buffer injections. Regenerate the monoclonal antibody surfaces with glycine between each binding cycle.Recorded binding sensorgrams in one-to-one kinetic model fit overlays are shown for the antibodies interacting with human PCSK9 in four instruments. The binding profiles of the antibodies at multiple densities are similar across the instruments. Even though the rate constants associated with each of the antibodies varied across the instruments, their rank orders remained mostly the same.The reproducibility and consistency of affinities in kinetic rates over multiple antibody surfaces was investigated. As shown here, a strong linearity was observed for all rate constants generated using the Biacore T100 and ProteOn XPR36. However, the rate constants generated by Octet RED384 were less linear due to fluctuations in some of the off rates.This was potentially caused by sample evaporations over time in the microplate. The rate constants generated by the IBIS-MX96 were also less linear due to fluctuations in surface heterogeneities. The antibody binding activities associated with most of the systems were consistent, whereas an approximately tenfold lower activity was observed for the amine-coupled method from the IBIS-MX96.This was possibly due to antibody inactivation, or the generation of antibody orientations that were not conductive to antigen binding. After watching this video, you should have a good understanding of how to set up experiments in each of the four biosensor platforms, and how to select appropriate biosensor technology for your own research purpose. Our head-to-head comparison study shows that each biosensor platform has its own advantages and disadvantages.Despite certain inherent systematic limitations in instrumentation, direct order of both the association and dissociation rate constants were highly correlated between these instruments. For the purpose of candidate ranking, assuming the number of samples and the amount of materials are not limiting factors, any of these instruments may be used, because they can differentiate the antibodies comparably, irrespective of the import instrument. There is a trade-off between data reliability and sample throughput.Biacore T100, followed by ProteOn XPR36R, exhibited the best data quality and consistency. Whereas Octet RED384 and IBIS-MX96 demonstrate high flexibility and throughput with compromises in data accuracy and consistency. For studies that require sensitive and reliable detection, either Biacore T100 or ProteOn XPR36 is best suited.For studies in which speed is a critical factor and a large number of samples are involved, either Octet Red384 or IBIS-MX96 is preferred. Instruments with continuous flow fluid X provide high quality data for resolving interactions with slow dissociation rates. The major limitation for the BRI fluid ex-a-fray instrument is sample evaporation over time in the microplate, which may result in upward drift, compromising data accuracy.

determination-high-affinity-antibody-antigen-binding-kinetics-using

Research

JoVE Journal

Biochemistry

This video demonstrates a conductimetric biosensor assay to study the interaction of an antibody with a target antigen immobilized on a transducer chip. The biosensor is engineered to have a bifunctional chimeric protein — a β-lactamase enzyme with a functional catalytic site fused to a nanobody for binding to the immobilized target antigen. Upon binding, the catalytic hydrolysis of an antibiotic substrate by the β-lactamase enzyme generates an electrical signal — confirming the...

&beta;-Lactamase-Based Conductimetric Biosensor Assay for Protein-Protein Interactions

The protocols here describe kinetic assays of protein-protein interactions with Bio-layer Interferometry. F-type ATP synthase, which is involved in cellular energy metabolism, can be inhibited by its ε subunit in bacteria. We have adapted Bio-layer Interferometry to study interactions of the catalytic complex with ε’s inhibitory C-terminal domain.

Bio-layer Interferometry for Measuring Kinetics of Protein-protein Interactions and Allosteric Ligand Effects

In this work, we report a new method to study protein-protein interactions using a conductimetric biosensor based on the hybrid β-lactamase technology. This method relies on release of protons upon hydrolysis of β-lactams.

The Use of a &#946;-lactamase-based Conductimetric Biosensor Assay to Detect Biomolecular Interactions

Here we present a protocol to describe the development and validation of a single molecule array digital ELISA assay, which enables the ultra-sensitive detection of all IFN-α subtypes in human samples.

Development and Validation of an Ultrasensitive Single Molecule Array Digital Enzyme-linked Immunosorbent Assay for Human Interferon-&#945;

Here we present a protocol to monitor the assembly and disassembly of the anthrax toxin using biolayer interferometry (BLI). Following assembly/disassembly on the biosensor surface, the large protein complexes are released from the surface for visualization and identification of components of the complexes using electron microscopy and mass spectrometry, respectively.

Analyzing Dynamic Protein Complexes Assembled On and Released From Biolayer Interferometry Biosensor Using Mass Spectrometry and Electron Microscopy

We describe a single-molecule approach to antigen-antibody affinity measurements using mass photometry (MP). The MP-based protocol is fast, accurate, uses a very small amount of material, and does not require protein modification.

Rapid Determination of Antibody-Antigen Affinity by Mass Photometry

This study aimed to present a strategy for identifying drug-peptide interactions. The strategy involves the biopanning of drug-recognizing short peptides based on a quartz-crystal microbalance (QCM) biosensor, followed by bioinformatics analysis for quantitatively assessing the information obtained for the drug recognition and annotation of the drug-binding sites on proteins.

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions

Field-effect biosensing (FEB) is a label-free technique for detecting biomolecular interactions. It measures the electric current through the graphene biosensor to which the binding targets are immobilized. The FEB technology was used to evaluate biomolecular interactions between Hsp90 and Cdc37 and a strong interaction between the two proteins was detected.

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

This article describes a protocol for studying DNA-protein interactions using a streptavidin-based biolayer interferometry (BLI) system. It outlines the essential steps and considerations for utilizing either basic or advanced binding kinetics to determine the equilibrium binding affinity (KD) of the interaction.

Analyzing DNA-Protein Interactions with Streptavidin-Based Biolayer Interferometry

MicroScale Thermophoresis (MST) is a sensitive technology to characterize aptamer-target interactions. This manuscript describes an MST protocol to characterize aptamer-small molecule interactions.

Mapping the Binding Site of an Aptamer on ATP Using MicroScale Thermophoresis

Learn to measure antibody-antigen binding kinetics using four biosensor platforms for drug discovery research. This comparative study guides selection of reliable instruments for therapeutic antibody evaluation.

Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

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