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

Summary

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.

Abstract

We describe the use of Bio-layer Interferometry to study inhibitory interactions of subunit ε with the catalytic complex of Escherichia coli ATP synthase. Bacterial F-type ATP synthase is the target of a new, FDA-approved antibiotic to combat drug-resistant tuberculosis. Understanding bacteria-specific auto-inhibition of ATP synthase by the C-terminal domain of subunit ε could provide a new means to target the enzyme for discovery of antibacterial drugs. The C-terminal domain of ε undergoes a dramatic conformational change when the enzyme transitions between the active and inactive states, and catalytic-site ligands can influence which of ε's conformations is predominant. The assay measures kinetics of ε's binding/dissociation with the catalytic complex, and indirectly measures the shift of enzyme-bound ε to and from the apparently nondissociable inhibitory conformation. The Bio-layer Interferometry signal is not overly sensitive to solution composition, so it can also be used to monitor allosteric effects of catalytic-site ligands on ε's conformational changes.

Introduction

Protein-protein interactions are important for many biological processes, and label-free optical methods like Surface Plasmon Resonance (SPR) have been used in vitro to study kinetics of binding and dissociation¹. Most label-free methods immobilize one biomolecule on a sensor surface and use an optical signal to detect a binding partner from solution as it associates with the immobilized biomolecule¹. While SPR is a highly sensitive method, it is prone to interference due to changes in the refractive index of the solution flowing over the sensor². Although not as sensitive as SPR, Bio-layer Interferometry (BLI) is less affected by changes in sample composition^1,3. BLI uses fiber optic biosensors that have a proprietary biocompatible coating at the tip. The system used here (Octet-RED96) contains eight spectrophotometers. White light is piped to a row of probes that move on a robotic arm. Fiber optic sensors are picked up by the probes and moved to a 96-well plate containing samples. One of the target molecules is immobilized on the biosensor surface. Then sensors are moved to wells containing the binding partner in solution. BLI monitors association of the binding partner with the immobilized molecule, and then monitors dissociation after moving the sensors to solution without the binding partner. Binding of molecules to the biosensor surface leads to changes in optical interference between light waves that reflect back to the spectrophotometers from an internal surface and from the external interface between sensor and solution. These changes in interference can be quantified and used to determine kinetic rates of binding and dissociation, as summarized in the animation of Figure 1.

We have applied BLI to measure interactions between the catalytic complex of bacterial ATP synthase and its ε subunit, which can auto-inhibit the enzyme. ATP synthase is a membrane-embedded rotary nanomotor that catalyzes synthesis and hydrolysis of ATP⁴. The catalytic complex (F₁) can be isolated in a soluble form that works as an ATPase. Subunit ε has two domains: the N-terminal domain (NTD) is necessary for proper assembly and functional coupling of the enzyme but does not interact directly with the catalytic subunits; the C-terminal domain (CTD) can inhibit the enzyme by interacting with multiple catalytic subunits^5,6. This ε-mediated regulation is specific to bacterial ATP synthases and is not observed in the mitochondrial homologue. ATP synthase has emerged as a target for antibacterial drugs, as shown by recent FDA approval of bedaquiline to treat drug-resistant tuberculosis⁷. Thus, targeting ε’s inhibitory role for drug discovery could yield antibacterials that do not inhibit the mitochondrial ATP synthase. With the isolated catalytic complex (F₁), ε becomes a dissociable subunit. However, with ε bound to F₁, the εCTD can undergo a dramatic conformational change, partially inserting into the enzyme’s central cavity and forming an inhibitory state that is unlikely to dissociate directly^6,8. We use BLI to measure kinetics of F₁/ε binding and dissociation, and indirectly, to examine allosteric effects of catalytic-site ligands on ε’s conformation.

In our system, ε was chosen for immobilization on the sensor surface since BLI signal (like SPR) is sensitive to the mass of the molecules binding at the surface. The ε subunit is small (~15 kDa) relative to the main F₁ complex (~347 kDa). Thus, a larger BLI signal will result from binding of F₁ to immobilized ε. In order to monitor F₁ dissociation, which can be very slow, ε must be strongly immobilized. Thus we chose to biotinylate and immobilize it on streptavidin-coated biosensors. Proteins can be biotinylated by (i) random modification of surface lysines⁹, (ii) reaction of a unique native or engineered cysteine with a biotin-maleimide reagent¹⁰ or (iii) genetically adding a specific biotin-acceptor peptide that is enzymatically biotinylated during in vivo expression of the tagged protein¹¹. In our system, ε is biotinylated using method (iii)⁸. Once biotin-tagged ε is immobilized on streptavidin sensors, BLI can measure the binding and dissociation of F₁ that has been depleted of subunit ε (F₁(-ε)). For the experiments described here, preliminary assays had been done to determine reasonable amounts of the biotinylated protein to immobilize on the sensors. This can vary, depending on the molecular weight of the protein and its binding partner, but the goal is to determine a minimal amount of immobilized protein that provides (i) acceptable signal-to-noise for binding kinetics with a low concentration of the binding partner (below K_D) and (ii) minimal distortion of binding kinetics with near-saturating concentration of the binding partner. Also, stoichiometry of biotinylation may vary (but avoid >1 mol biotin/mol protein), so some initial assay may be needed for each new lot of biotinylated protein to confirm that a consistent BLI signal can be achieved during immobilization on the streptavidin-coated sensors.

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Protocol

1. Programming the Instrument for BLI Assay

Turn on the instrument at least one hour in advance to allow the lamp to warm up; this is necessary to minimize noise and drift in optical signal during the experiment. Set the desired temperature via the instrument tab to prewarm the sample plate holder. Then set up the experimental design in the Data Acquisition software. Select "New Kinetics Experiment" in the Experiment Wizard tab. This presents a tabbed menu with all steps that must be defined.

1.1. Plate Definition

Define the columns to be used on the 96-well sample plate. Assign columns to contain buffer, immobilized protein or binding partner. For each association well, enter the concentration of binding partner to be used. Note: the plate definition shown in Figure 2 has options for distinct assays.

1.2. Assay Definition

Define all steps needed for the assay. These include (i) Baseline (several), (ii) Loading, (iii) Association and (iv) Dissociation of binding partner. Then, as described below, link individual assay steps with columns of wells on the sample plate by selecting the assay step and then double clicking on the respective column. This programs the sensors to be moved from one column of wells to the next during the assay.

1. Baseline
   Begin with a brief baseline step (≥60 sec), with sensors in assay buffer (Figure 2, column 1), to establish initial BLI signals in the 96-well plate.
2. Loading (immobilizing the biotinylated protein on the sensors)
   Assign sensors to wells that will contain the biotinylated protein (Figure 2, column 2). Use the threshold function to achieve a predetermined level of binding (see Introduction). Set the threshold option so that all sensors will be moved to the next column of wells when any one of the sensors reaches the threshold.
3. Baseline
   Include another baseline step in buffer (Figure 2, column 3; typically >5 min) to wash away nonimmobilized biotinylated proteins from the sensors and establish new, stable baseline signals. For basic binding/dissociation assays only (as in Figure 3), include an extra baseline step (60 sec) with sensors in new wells of buffer (Figure 2, column 4) before the Association step.
4. Association (of the binding partner to the immobilized protein)
   For a basic binding/dissociation assay (as in Figure 3), select a range of concentrations of binding partner to be used for different sensors/wells (Figure 2, column 5). Adjust the step time so that at least a saturating concentration of the binding partner should approach equilibrium binding signal. For an assay to test allosteric effects of small ligands on dissociation of the protein-protein complex (as in Figure 5), select a single high concentration of binding partner (~10-fold above the estimated K_D) for use in all association wells.
5. Dissociation (of the binding partner)
   For a basic binding/dissociation assay only (as in Figure 3), designate the sensors to return to column 4 (Figure 2), the same buffer wells as used for the extra baseline before Association. For an assay to test allosteric effects of small ligands, instead designate sensors to move to column 6 (Figure 2), where each well can contain buffer plus different allosteric ligands.

1.3. Sensor Assignment

Indicate the locations in the sensor tray that will contain prewetted sensors for the assay. Identify any empty positions since the experiment will fail if no sensors are picked up.

1.4. Review Experiment

Visualize all planned steps to check for mistakes and go back to correct them.

1.5. Run Experiment

Enter necessary details, including location of data files. Enter the desired temperature for the experiment. If sensors still require prewetting, select the option to delay starting the experiment. Finally, once all sample preparation is complete (step 2) and both the sample plate and sensor tray are loaded in the instrument , click the Go button to run the assay.

2. Sample Preparation

1. Prepare an appropriate assay buffer. Buffer used for experiments shown in Figures 3 and 5: 20 mM MOPS (3-(N-Morpholino)propanesulfonic acid), Tris (Tris(hydroxymethyl)amino-methane) (added to adjust pH to 8.0), 50 mM KCl. Include BSA (bovine serum albumin, fatty-acid free, 0.5 mg/ml final) in the buffer for all assay steps and for all dilutions of the biotinylated protein or binding partner to minimize nonspecific binding of proteins to the sensors.
2. Dilute the biotinylated protein (ε) in assay buffer to an appropriate concentration (see Introduction).
3. Prepare dilutions of the binding partner (F₁(-ε)) in assay buffer (see Discussion for range of concentrations to use).
4. Prewet the streptavidin-coated sensors for at least 10 min to remove their protective sucrose coating. Remove the sensor-containing rack from the sensor tray and insert a 96-well plate in the bottom of the tray, sliding one corner of the plate into the orienting notch on the tray. For the column of sensors to be used, add 200 μl of assay buffer per well in that column of the 96-well plate. Return the rack of sensors to the tray in the correct orientation (with tabs in slots).
5. As assigned during programming in Step 1, fill wells of the sample plate with assay buffer or the appropriate protein dilutions, as in Figure 2. Avoid introducing bubbles, as they can cause noise in the optical signal. Include one or more reference wells that omit either (i) biotinylated protein or (ii) binding partner.
6. Open the door of the instrument and insert the sensor tray onto the stage (left), with the tray’s tabs inserted into the slots of the stage. Insert the sample plate into the plate holder (right); make sure that the plate is seated flat and in the correct orientation, as indicated on the plate holder. Close the door and start the assay from the Data Acquisition program (step 1.5).

3. Data Processing

1. After the assay has run, open the Data Analysis software and load the folder containing the data. Click the "Processing" tab to see a step-wise Processing menu (at left) and the raw kinetic data, with each sensor (A-H) assigned a different color (see Figure 3).
2. Under "Data Selection", click the "Sensor Selection" button. On the "Sample Plate Map", designate the wells for 1 or 2 control sensors (G, H in assay of Figure 3) as reference wells. On the Processing menu, check the "Subtraction" box and select "Reference Wells" to subtract reference signal (single or averaged) from every other sensor’s signal.
3. Align all traces to Y=0 by using the "Align Y Axis" step. Select "Baseline" as the alignment step (this being the last baseline before the Association step). For "Time Range", enter the last 10 sec of that baseline (i.e. 50-60 sec for a 60-sec baseline, as in Figure 3).
4. Check the "Inter-step Correction" box to minimize signal shifts between the Association and Dissociation steps. Select align to Baseline or Dissociation.
5. Select Savitzky-Golay filtering function in most cases and click "Process Data!" to proceed. Visually inspect the final processed data (lower right panel). With assays intended for global data analysis (as in Figure 4), if signal traces show a significant shift between Association and Dissociation steps, change the selection of Dissociation or Baseline for the "Inter-step Correction" and reprocess the data before proceeding to Data Analysis.

4. Data Analysis

Click the "Analysis" tab in Data Analysis to begin. Note: the example steps below are for global analysis of multiple binding/dissociation curves (as in Figure 3).

1. For "Step to Analyze", choose Association and Dissociation. For "Model", select 1:1. Note: other limited options are available.
2. For "Fitting", choose Global (Full). For "Group By" select Color (as on the graph). Select "R_max Unlinked By Sensor" to allow independent fitting of R_max (maximal signal response upon saturating binding of the partner to the immobilized protein). Note: we do this for most assays, as sensors vary slightly in the amount of protein immobilized (see Figure 3, Loading).
3. On the table shown, make sure all sensor traces to be analyzed have the same color, so they will be analyzed as a global set. If needed, select one or more sensor traces to omit from global fitting: under the "Include" column, right-click on the desired sensor position and select "Exclude Wells".
4. Click "Fit Curves!" to start the nonlinear regression analysis. Examine the fitting results, which include (i) overlay of regression curves with sensor data traces (as in Figure 4), (ii) plots of fitting residuals, and (iii) a table with determined parameter values (rate constants, R_max, K_D) and statistics (standard errors for parameters, Chi-squared, R²).
5. Under "Data Export", save fitting results by clicking "Export Table to .csv File". For graphing or further analysis of data/fitted curves with other software, click "Export Fitting Results" to save each sensor’s data and fitted curve in a text file.

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Results

Real time binding and dissociation BLI kinetics are shown in Figure 3. This experiment was done with assay buffer in association and dissociation. This experiment was started with a 10 min baseline step since the sensors had been prewet only briefly. Next, biotinylated ε was loaded on the sensors. No detectable dissociation of ε occurred throughout all remaining steps as seen from the reference curve (G) which had no binding partner added. A second reference sensor (H) was devoid of immobilized...

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Discussion

Currently available instruments for BLI allow significant throughput and flexibility in assays for biomolecular interactions. Various solution samples are dispensed in wells of a black microtiter plate, and a set of parallel BLI sensors are programmed to move back and forth between columns of wells on the plate. The samples are stirred by orbital shaking throughout the assay. The system used here has 8 sensors and uses a 96-well sample plate, but another system uses 16 sensors and a 384-well sample plate. Thus, interacti...

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Materials

Name	Company	Catalog Number	Comments
Octet-RED96	Pall/FortéBio	30-5048
Bovine Serum Albumin	Sigma	A6003-10G	Fatty Acid free
Biosensor/Streptavidin	Pall/FortéBio	18-5019	Tray of 96 sensors
Microtiter plate	Greiner Bio-one	655209	Black, Polypropylene
Data Acquisition software	Pall/FortéBio	Version 6.4	Newer versions available
Data Analysis software	Pall/FortéBio	Version 6.4	Newer versions available