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JoVE Journal
Biochemistry
Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms
Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms
JoVE Journal
Biochemistry
This content is Free Access.
JoVE Journal Biochemistry
Determination of High-affinity Antibody-antigen Binding Kinetics Using Four Biosensor Platforms

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

Full Text
21,580 Views
15:27 min
April 17, 2017

DOI: 10.3791/55659-v

Danlin Yang1, Ajit Singh2, Helen Wu1, Rachel Kroe-Barrett1

1Department of Biotherapeutics Discovery, Immune Modulation and Biotherapeutics Discovery,Boehringer Ingelheim Pharmaceuticals, Inc., 2The Fu Foundation School of Engineering and Applied Science,Columbia University

Overview

This study presents protocols for measuring antibody-antigen binding affinity and kinetics using four commonly used biosensor platforms. It aims to compare the performance of these platforms in providing reliable kinetic data.

Key Study Components

Area of Science

  • Biosensor technology
  • Antibody-antigen interactions
  • Drug discovery

Background

  • Understanding antibody-antigen interactions is crucial for therapeutic development.
  • Biosensors are essential tools for measuring these interactions.
  • Different biosensor platforms may yield varying results.
  • This study addresses the need for a comparative analysis of these platforms.

Purpose of Study

  • To evaluate the quality of kinetic data from four biosensor platforms.
  • To identify technical challenges in experimental design.
  • To guide researchers in selecting appropriate biosensor platforms for their assays.

Methods Used

  • Protocols for Biacore T100, ProteOn XPR36, and Octet RED384 biosensors.
  • Measurement of binding kinetics and affinity through various experimental setups.
  • Direct comparison of data consistency and operational efficiency across platforms.
  • Video demonstrations to assist new users in setting up experiments.

Main Results

  • Comprehensive comparison of biosensor platforms was achieved.
  • Insights into the operational efficiency and data quality were provided.
  • Specific protocols were outlined for each biosensor platform.
  • Technical challenges were identified and discussed.

Conclusions

  • This study aids researchers in selecting the most reliable biosensor platform.
  • It highlights the importance of experimental design in obtaining quality data.
  • Video demonstrations enhance understanding and usability for new users.

Frequently Asked Questions

What are the main biosensor platforms discussed?
The study discusses the Biacore T100, ProteOn XPR36, and Octet RED384 platforms.
Why is measuring antibody-antigen interactions important?
These interactions are critical for therapeutic development and drug discovery.
How does this study assist new users?
It provides video demonstrations and detailed protocols for setting up experiments.
What challenges are addressed in the study?
Technical challenges in experimental design and data consistency are discussed.
What is the purpose of the comparative analysis?
To guide researchers in selecting the most reliable biosensor platform for their needs.
What type of data is evaluated in this study?
The study evaluates kinetic data and binding affinity results from different biosensor platforms.

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

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.

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