Application Note

Kinetic Analysis of Antibody Binding to an Expressed Membrane Protein on Captured Lipoparticles

Download PDF    

Introduction

Author: Bettina Heidecker, Scientist, Krista Witte, Senior Director, Wesley McGinn-Straub, data courtesy of Integral Molecular

Membrane proteins govern the majority of input and output signals of cells and represent the largest class of pharmaceutical drug targets, making the analysis of their molecular interactions critical to mapping the interactome as well as drug discovery efforts. Due to their integration into a lipid bilayer, in vitro characterization of molecular interactions of membrane proteins presents a unique challenge compared to soluble proteins. By capturing 150 nmsized lipoparticles that contain a targeted membrane protein on the surface of a biosensor, ForteBio’s Octet platform enables the kinetic analysis (kon, kdiss and KD) of membrane protein-analyte interactions. Due to the large size of the lipoparticle, the observed data trace is often inverted, requiring a “flip” during data processing. Using a membrane protein-antibody model system, data processing and analysis of the membrane protein-analyte interaction on a lipoparticle is discussed and validated.

Lipoparticless

Lipoparticles, available from Integral Molecular (www.integralmolecular.com), offer expression of integral membrane proteins in a native lipid bilayer format for nanoscale in vitro protein analysis research (Figure 1). The proprietary retroviralbased technology incorporates a high concentration of conformationally intact membrane protein into a ~150 nm virus-like particle (VLP) composed of natural cell membranes. This cell-free solution for membrane protein analysis creates a unique biochemical tool to study GPCRs, ion channels, and other membrane proteins. Lipoparticles do not contain a genome and are thus non-infectious.

membrane protein of interest expressed

Figure 1: A membrane protein of interest expressed into a lipid bilayer lipoparticle, prepared using a proprietary technology from Integral Molecular and ready for in vitro interaction analysis. The dense protein core of the lipoparticle provides a biologically relevant context at the inner membrane surface.

Octet platform and BLI

ForteBio’s label-free detection platform provides instruments, biosensors, reagents and assay kits for analyzing biomolecular interactions in 96- and 384-well microplate formats. A proprietary subtraction Bio-Layer Interferometry (BLI) technology enables real-time analysis of interactions on the surface of a fiber optic biosensor (Figure 2), providing information on affinity, kinetics and concentration. The efficient workflow of the platform provides easy, fast and highquality characterization of drug candidates in drug development applications where existing methods have limitations in throughput, performance and cost.

ForteBios fiber optic sensors

Figure 2: ForteBio’s fiber optic sensors contain a biocompatible matrix layer on their bottom surface. Immobilization of molecules of interest within the biocompatible matrix enables kinetic characterization of molecular interactions and quantitation of analytes.

Workflow

Biomolecular analysis of the interaction between a lipoparticle associated membrane protein and an antibody begins with immobilization of the lipoparticle upon the biosensor surface. This example exploits the high affinity between wheat germ agglutinin and lipoparticle carbohydrates for lipoparticle immobilization. The basic experiment contains 6 steps (Figure 3): Step 1, biosensor hydration; Step 2, immobilization of biotinylated wheat germ agglutinin (WGA) on a ForteBio Streptavidin Biosensor; Step 3, capture of the VLP utilizing the immobilized WGA; Step 4, wash and establish baseline; Step 5, measure membrane protein-antibody association kinetics; and Step 6, measure membrane protein-antibody dissociation kinetics. Alternative methods of lipoparticle capture or immobilization, such as amine coupling, are available.

Example workflow for kinetic characterization

Figure 3: Example workflow for kinetic characterization of the interaction between the CXCR4 membrane protein and an anti-CXCR4 antibody. Step 1: Streptavidin Biosensor hydration, Step 2: Load biotinylated wheat germ agglutinin, Step 3: Immobilization of the CXCR4 containing lipoparticle, Step 4: Baseline in buffer, Step 5: Measure association kinetics between anti-CXCR4 antibody and lipoparticle-displayed CXCR4, Step 6: Measure dissociation kinetics between anti-CXCR4 antibody and lipoparticledisplayed CXCR4.

Tips For Optimal Peformance

  • Octet RED, Octet RED96 and Octet RED384 instruments are recommended.
  • 180 μL to 200 μL/well of reagent is required in a 96-well microplate. 100 μL/well is required for a 384-well microplate and 40 μL/well is required for a 384-tilted well plate.
  • Evaluate shake speeds between 500 and 1000 rpm for optimal performance with each ligand-analyte system.
  • Due to their large size, lipoparticles can generate a negative response in biolayer interferometry and, consequently, all binding events subsequent to the loading step may also be expected to generate negative responses. This negative response can be managed in the Octet Data Analysis software (Version 6.3 or greater) by signal inversion using the “flip” feature, followed by standard processing protocols.
  • Employ one of three referencing methods:
    • Use null lipoparticles (without over-expressed target membrane protein) as a reference biosensor either as a single biosensor in a column of biosensors (reference biosensor) or as a parallel column of biosensors against the same analyte series (parallel reference subtraction).
    • Use receptor-containing lipoparticles to probe a “reference well” of buffer (no analyte or negative control antibody).
    • Combine the use of reference biosensor(s) and a reference well with double referencing.
  • Choose controls that closely match the analytes of interest (e.g., if testing murine-derived antibodies, the control should be a murine-derived antibody with an epitope not present on the protein of interest or the lipoparticles).
  • If inter-step correction is to be used during data processing, the same well should be for both baseline and dissociation steps.

Required Reagents

  • Streptavidin (SA) Biosensor Tray (ForteBio part no. 18-5019)
  • Black 96-well (Greiner part no. 655209), 384-well (Greiner part no. 781209) or 384-tilted well (ForteBio part no. 18‑5080) polypropylene plate
  • PBS supplemented with 1 mg/mL BSA (PBS-B; BSA Fraction V, Sigma part no. A3059, 0.2 μm filtered)
  • Biotinylated Wheat Germ Agglutinin (WGA) (Vector Laboratories part no. B-1025)
  • 1 to 7 units lipoparticles (ligand) per biosensor
  • Antibody (analyte) of interest
  • Negative control analyte

Optional Reagents For Regeneration

  • 1% Empigen (Sigma part no. 45165)
  • 500 mM NaCl
  • 500 mM N-acetyl-D-glucosamine (NAG) (Alfa Aesar part no. A13407)
  • 10 mM HCl

Assay Protocol With Single Reference Well

Sample Plate Preparation

Prepare a microtiter plate (96-well, 384-well or 384-tilted well) with the required ligands, analytes and wash buffers (refer to Figure 4A for representative plate setup for single reference well subtraction).

Sample plate setup for experiment using single reference well subtraction

Figure 4: Sample plate setups for measuring the kinetics for the interaction between the membrane protein CXCR4 and an anti-CXCR4 antibody with different reference subtraction methods. Reagents required for regeneration are optional. The assay buffer used is PBS-B (PBS with 0.1 % BSA). If inter-step correction is to be applied during data processing, the same well should be utilized for both the baseline and dissociation steps.

Panel A represents an assay utilizing a single reference well (H7) of PBS-B containing no analyte for reference subtraction. Subtraction of the signal generated in H7 from A7–G7 corrects for sensor drift over time.

Sample plate setup for experiment using parallel reference sensor subtraction

Panel B represents an assay utilizing parallel reference subtraction. Column 5 contains lipoparticles containing the target membrane protein CXCR4. Column 6 contains null lipoparticles. Parallel reference subtraction is executed by running the complete assay twice within one experiment. CXCR4 containing lipoparticles are used for the first pass (use of columns 1, 2, 3, 4, 5, 7, 8, 7) and null lipoparticles are used for the second pass (use of columns 1, 2, 3, 4, 6, 7, 8, 7). The signal generated by null particles is subtracted from the signal generated using CXCR4-containing particles, correcting for potential nonspecific interactions of the sample matrix with the lipoparticle-loaded biosensors.

Sample plate setup for experiment using double reference interactions in 96- and 384-well microplate formats. A proprietary subtraction

Panel C represents an assay utilizing double reference subtraction (one reference well and one column of reference biosensors). Column 8 contains 7 wells with analyte (A8– G8) and one reference well with no analyte (H8). Column 6 contains null lipoparticles as reference biosensors. Similar to parallel reference subtraction, double reference subtraction is executed by running the complete assay twice within one experiment. CXCR4 containing lipoparticles are used for the first pass (use of columns 1, 2, 3, 4, 5, 7, 8, 7) and null lipoparticles are used for the second pass (use of columns 1, 2, 3, 4, 6, 7, 8, 7). Double reference subtraction corrects for both sensor drift over time and potential nonspecific interactions between the sample matrix and lipoparticle loaded biosensors.

All steps in the following example were performed at a shake rate of 600 rpm, except for the association and dissociation steps, which were performed at a shake rate of 1000 rpm. Optimal shake speeds may vary.

Prepare and Load Biosensor Surface with WGA

  1. Move biosensors to PBS-B (Figure 4A, column 1) and equilibrate for 5 minutes.
  2. Perform a 3-minute wash step (Figure 4A, column 2).
  3. Load biosensors with WGA by incubating with 50 μg/mL biotinylated WGA in PBS-B (Figure 4A, column 3) for 3 minutes.
  4. Quickly rinse biosensors by running a 3-minute baseline in PBSB (Figure 4A, column 4).

Load Lipoparticles on Biosensors

  1. Load lipoparticles for 30 minutes. Typically, the lipoparticles are diluted to a concentration of 1–10 μg/mL in PBS-B with 1–7 units of membrane protein per well (Figure 4A, column 5). A shift of 1 to 2 nm during target loading is expected. The sign of the observed nm shift may be negative due to the large size of the lipoparticles. Loading levels can be modulated by varying either the particle concentration or the loading time.
  2. Place biosensors back in PBS-B (Figure 4A, column 6) and wash for approximately 45 minutes. The quality of any subsequent kinetic data is strongly dependent on baseline stability. Higher levels of lipoparticle loading may require longer stabilization times.

Regeneration (Optional)

  1. Biosensors can be regenerated back to the WGA surface (either on- or off-line).
  2. Place biosensors in a solution of 1% Empigen/500 mM NaCl/500 mM NAG for 1 minute (Figure 4A, column 8).
  3. Place biosensors in 10 mM HCl for 1 minute (Figure 4A, column 9).
  4. Repeat Steps 1 and 2 three to five times.
  5. Rinse biosensors in PBS or assay buffer to remove residual detergent or acid (Figure 4A, column 10).

Raw Data

Kinetic data for the interaction of lipoparticle-displayed CXCR4 and the mouse anti-CXCR4 antibody was obtained in a 9-step assay (Figure 5). After biosensor equilibration and wash steps, loading of the biotinylated WGA produced a large positive shift of approximately 3.5 nm (Figure 5, Step 3). Excess WGA was washed away (Figure 5, Step 4) and the CXCR4 displaying lipoparticles were loaded (Figure 5, Step 5). Due to the large size of the lipoparticles, the amplitude of the signal generated by their binding to the biosensor was negative, inducing an observed amplitude shift from approximately 3.5 nm to approximately 1.75 nm. The lipoparticleloaded biosensors were washed extensively (Figure 5, Step 6) in preparation for establishing a baseline signal (Figure 5, Step 7). Lastly, the kinetics of association (Figure 5, Step 8) and dissociation (Figure 5, Step 9) for the interaction between the anti-CXCR4 antibody and the lipoparticle-displayed CXCR4 were measured. The nm shift of the association and dissociation steps were significantly smaller than the nm shift than the loading steps, and are therefore expanded in Figure 6A and 6B for improved visualization.
 

Complete kinetic experiment assaying

Figure 5: Complete kinetic experiment assaying the interaction between the lipoparticle-displayed membrane protein CXCR4 with an anti-CXCR4 antibody. Step 1: Equilibration, Step 2: Wash, Step 3: Loading of biotinylated wheat germ agglutinin on to a Streptavidin Biosensor, Step 4: Wash, Step 5: Loading of lipoparticle (negative amplitude upon binding due to size of the particle), Step 6: Wash, Step 7: Baseline, Step 8: Measure association of anti-CXCR4 antibody to lipoparticle-displayed CXCR4 Step 9: Measure dissociation of anti-CXCR4 antibody from lipoparticle-displayed CXCR4.

Data Processing

The raw data acquired for the interaction between the lipoparticledisplayed CXCR4 and the anti-CXCR4 antibody was processed and fit to a curve in order to extract values of kon, kdiss and KD. Processing began with reference correction to compensate for signal drift of the immobilized biosensor with the assay buffer. Using a reference biosensor, the signal generated by a biosensor with CXCR4- containing lipoparticles that probed a blank matrix (PBS-B) was subtracted from both the association and dissociation steps for the interaction between the lipoparticle-displayed CXCR4 and the anti-CXCR4 antibody. Subsequently, Y-axis alignment, inter-step correction and Savitzky-Golay filtering were applied.

Step Number Step Name Time (seconds) Shake Speed Step Type
1 Equilibration 600 600 Custom
2 Wash 180 600 Custom
3 Load Biotin-WGA 180 600 Loading
4 Wash 180 600 Custom
5 Load CXCR4-Lipoparticles 1800 600 Loading
6 Wash 3500 600 Custom
7 Baseline 2700 600 Baseline
8 Association 300 1000 Association
9 Dissociation 1800 1000 Dissociation

Table 1: Assay method for kinetic analysis of the interaction between CXCR4-containing lipoparticles and an anti-CXCR4 antibody.

Due to its large size, the lipoparticle placed the interaction surface approximately 150 nm away from the biosensor surface. In this example, the extended distance caused the amplitude of observed data to be inverted, but otherwise identical (Figure 6A). The “flip” function of the Octet Data Analysis software was used to invert the signal. In the results table of the analysis tab, all rows were selected and “flip” was selected from the right-click menu. All data inverted so that the nm shift was transformed from negative to positive. Inversion of the data to a positive signal allowed curve fitting of both the association and dissociation steps with a 1:1 binding model using the global fitting function (grouped by color, Rmax unlinked by biosensor). Kinetic fitting results are displayed as red lines in Figure 6B and as quantitative values in Figure 6C. Specific processing settings can vary due to both the experimental setup and analyte-ligand system probed.

expanded-view-of-association

Expanded view of association

Figure 6: Expanded view of association (Figure 5, Step 8) and dissociation (Figure 5, Step 9) of lipoparticle-expressed CXCR4 and an anti-CXCR4 antibody. After correction of the signal using a reference biosensor, the processed data was negative and therefore not amenable to curve fitting (6A). Application of the Octet Data Analysis software “flip” function inverted the data (6B), allowing fitting with a 1:1 heterogeneous ligand fitting model (red lines) and derivation of quantitative kinetic data (6C).

Validation of “Flip” Data Software Feature

A model system was developed to investigate the validity of inverting the kinetic data obtained from a lipoparticle experiment (Figure 7). In this model system, the interaction between a mouse anti-CXCR4 antibody and a donkey anti-mouse IgG was studied both on the surface of captured lipoparticles (resulting in inverted data) and on the surface of a Streptavidin Biosensor (standard data). The values of kon, kdiss, and KD, derived from curve fitting data for the two assays, were compared to determine if inverting the data from the lipoparticle assay delivered valid kinetic measurements.

model system developed to investigate the validity

Figure 7: A model system developed to investigate the validity of inverting kinetic data obtained from a lipoparticle experiment. The interaction of the mouse anti-CXCR4 antibody with the donkey anti-mouse IgG antibody was replicated both with (7A) and without (7B) a lipoparticle. The experimental arrangement allowed the same molecular interaction to be analyzed as inverted data (from a lipoparticle, 7A) and non-inverted data (no lipoparticle, 7B).

The lipoparticle-based model system was evaluated in a 8-step assay (Figure 8A). After biosensor equilibration (Figure 8A, Step 1), biotinylated WGA (50 μg/mL) was loaded onto the Streptavidin Biosensor (Figure 8A, Step 2). After a brief washing step (Figure 8A, Step 3), WGA was used to capture the lipoparticle displaying CXCR4 out of solution (10 μg/mL) (Figure 8A, Step 4), producing a large negative shift due to the binding of the 150 nm particle. After a wash step (Figure 8A, Step 5), the mouse anti-CXCR4 antibody (5 μg/mL) was loaded onto the surface of the lipoparticle (Figure 8A, Step 6). A baseline was established (Figure 8A, Step 7) and the interaction of interest, the binding of a donkey antimouse antibody with the mouse anti-CXCR4 antibody, was then observed (Figure 8A, Steps 8 and 9). The binding of the donkey anti-mouse antibody to the anti-CXCR4 antibody was measured in a half-log titration series from 3 to 100 nM, with the 3 nM and 100 nM samples run in duplicate. A 0 nM donkey anti-mouse IgG sample probed with CXCR4-containing lipoparticles was used as a reference control. The reference corrected data was inverted with the “flip” feature of the Octet Data Analysis software and fit to a 1:1 kinetic binding model (Figure 8B) to obtain values for kon, kdiss and KD (Figure 8C) as described in the Data Processing section.

example-data-from-a-model-system

Example data from a model system

Example data from a model system c

The second model system assay, arranged without a lipoparticle to produce binding data with a positive nm shift, was performed in a 7-step assay (Figure 8D). After Streptavidin Biosensor equilibration (Figure 8D, Step 1), biotinylated goat anti-mouse antibody (0.63 μg/ mL) was loaded (Figure 8D, Step 2). Excess goat anti-mouse antibody was removed by washing (Figure 8D, Step 3) and mouse anti-CXCR4 antibody (5 μg/mL) was loaded (Figure 8D, Step 4). Excess mouse anti-CXCR4 was removed by washing (Figure 8D, Step 5) and the interaction of interest was then studied by binding donkey anti-mouse antibody to the mouse anti-CXCR4 antibody in a half-log titration (Figure 8D, Step 6). The donkey anti-mouse antibody was bound in a half-log titration series from 3 to 100 nM. Dissociation of the donkey anti-mouse antibody from the mouse anti-CXCR4 antibody was observed for one hour in PBS-B. A zero nM donkey anti-mouse antibody sample probed with a biosensor loaded with goat anti-mouse and mouse anti-CXCR4 antibodies was used as a reference control. The reference-corrected data was fit to a 1:1 kinetic binding model (Figure 8E) to obtain values for kon, kdiss and KD (Figure 8F) as described in the Data Processing section.

Example data from a model system

Example data from a model system

Example data from a model system

Figure 8: Example data from a model system designed to compare inverted and non-inverted kinetic data. The interaction between a mouse anti-CXCR4 antibody and a donkey anti-mouse antibody was measured both with (8A, 8B) and without (8D, 8E) the presence of a lipoparticle. The interaction between a mouse anti-CXCR4 antibody and a donkey anti-mouse antibody was measured on the surface of a lipoparticle in a 9-step assay (8A): Step 1: Streptavidin Biosensor equilibration, Step 2: Load biotinylated WGA, Step 3: Wash, Step 4: Load lipoparticle, Step 5: Wash, Step 6: Load mouse anti-CXCR4 antibody, Step 7: Baseline, Step 8: Measure association of donkey anti-mouse FAb to mouse anti-CXCR4 antibody, Step 9: Measure dissociation of donkey anti-mouse FAb from mouse anti-CXCR4 antibody. The association and dissociation steps from 8A were inverted for processing (8B). Curve fitting to the inverted data provided kon, kdiss, and KD for the interaction on a lipoparticle (8C). The interaction between a mouse anti-CXCR4 antibody and a donkey anti-mouse FAb fragment was measured without a lipoparticle in a 7-step assay (8D): Step 1: Streptavidin Biosensor equilibration, Step 2: Load biotinylated anti-mouse FAb, Step 3: Wash, Step 4: Load mouse anti-CXCR4 antibody, Step 5: Wash, Step 6: Measure association of donkey anti-mouse FAb to mouse anti-CXCR4 antibody Step 7: Measure dissociation of donkey anti-mouse FAb from mouse anti-CXCR4 antibody. The association and dissociation steps from 8D were processed and fit with a 1:1 binding model (8E). Curve fitting of the processed curves provided kon, kdiss, and KD for the interaction without a lipoparticle (8F).

After reference subtraction, data for both systems was successfully fitted using a 1:1 binding model to obtain values for kon, kdiss and KD (Figures 8C and 8F). The kon values obtained with (1.83 E+4 M-1s-1) and without (1.26 E+4 M-1s-1) the lipoparticle agreed within 0.57 E+4 M-1s-1. The kdiss values with (1.42 E-4s-1) and without (7.13 E-5s-1) the lipoparticle agreed within 0.7 E-4s-1. The KD values, calculated as the ratio of kdiss/kon, differed by less than 2.1 nM. Raw binding data for both experiments produced concentration-dependent binding curves for analyte (donkey anti-mouse antibody) from 3 to 100 nM (compare Figures 8B and 8E). While the total nm shift observed for the model system without the lipoparticle was consistently greater than corresponding data in the presence of the lipoparticle, derivation of kinetic values is independent of the magnitude of the nm shift and the difference therefore does not bear relevance to the experimental objective of obtaining kinetic information. Comparison of the data for model system experiments performed in the presence and absence of the lipoparticle therefore demonstrates excellent agreement between the two results, validating kinetic characterization of membrane protein-ligand interactions on a lipoparticle using the ForteBio Octet platform.

Download PDF