Name: selection of transporter-targeted inhibitory nanobodies by solid-supported-membrane (ssm)-based electrophysiology
Uploaded: 2021-05-03T14:00:00
Description: Watch this Scientific Journal Video about Selection of Transporter-Targeted Inhibitory Nanobodies by Solid-Supported-Membrane SSM-Based Electrophysiology at JoVE.com

We thank Cedric A. J. Hutter and Markus A. Seeger from the Institute of Medical Microbiology at the University of Zurich, and Gonzalo Cebrero from Biozentrum of the University of Basel for collaboration in the generation of synthetic nanobodies (sybodies). We thank Maria Barthmes and Andre Bazzone from NANION Technologies for technical assistance. This work was supported by the Swiss National Science Foundation (SNSF) (PP00P3_170607 and NANION Research Grant Initiative to C.P.).

1. Membrane protein reconstitution
<ol>
	<li>Mix 3 mL of E. coli polar lipids with 1 mL of phosphatidylcholine in a round bottom flask under a ventilated hood.</li>
	<li>Dry the lipid mixture for 20 min under vacuum using a rotary evaporator and a water bath at 37 &#176;C to remove chloroform. If needed, dry further under nitrogen or argon gas.</li>
	<li>Using TS buffer (20 mM Tris-HCl pH 8.0, 150 mM NaCl) containing 2 mM &#946;-mercaptoethanol, resuspend lipids to 25 mg/mL.</li>
	<li>Aliquot lipids in 500 &#1...

<ol>
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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anatomy+an+antibody+molecule:+structure,+kinetics,+thermodynamics,+and+mutational+studies+of+the+antilysozyme+antibody+D1.3.">Anatomy an antibody molecule: structure, kinetics, thermodynamics, and mutational studies of the antilysozyme antibody D1.3.</a> Immunology Reviews. 163, 45-57 (1998).</li><li>Hamers-Casterman, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Naturally+occurring+antibodies+devoid+of+light+chains.">Naturally occurring antibodies devoid of light chains.</a> Nature. 363, 446-448 (1993).</li><li>Perez, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+basis+of+inhibition+of+lipid-linked+oligosaccharide+flippase+PglK+by+a+conformational+nanobody.">Structural basis of inhibition of lipid-linked oligosaccharide flippase PglK by a conformational nanobody.</a> Science Reports. 7, 46641 (2017).</li><li>Grahl, A., Abiko, L. 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The technique presented here classifies nanobodies with inhibitory and non-inhibitory properties targeting electrogenic transporters. Assessing the substrate transport is possible due to the detection of the movement of charges through the transporter embedded in the membrane of proteoliposomes. Some of the critical steps during the setup of an experiment are reconstitution of active protein in liposomes, preparation of stable monolayers on SSM chips, and recovering of initial conditions after the application of the wash...

Antibodies are composed of two identical heavy chains and two light chains that are responsible for the antigen binding. Camelids have heavy-chain only antibodies that exhibit similar affinity for their cognate antigen compared to conventional antibodies1,2. The single variable domain (VHH) of heavy-chain only antibodies retain the full antigen-binding potential and has been shown to be very stable1,2. These isolated VHH molecules or &#34;nanobodies&#34; have been implemented in studies related to membrane proteins biochemistry as tools for stabilizing conformations3,4, as inhibitors5,6, as stabilization agents7, and as gadgets for&#160;structure determination8,9,10. Nanobodies can be generated by the immunization of camelids for the pre-enrichment of B-cells that encode target-specific nanobodies and subsequent isolation of B cells, followed by cloning of the nanobody library and selection by phage display11,12,13. An alternate way to generate nanobodies is based on in vitro selection methods that rely on the construction of libraries and selection by phage display, ribosome display, or yeast display14,15,16,17,18,19,20. These in vitro methods require large library sizes but benefit from avoiding animal immunization and favor the selection of nanobodies targeting proteins with relatively low stability.
The small size of nanobodies, their high stability and solubility, strong antigen affinity, low immunogenicity, and relatively easy production, make them strong candidates for the development of therapeutics21,22,23. In particular, nanobodies inhibiting the activity of multiple membrane proteins are potential assets for clinical applications5,24,25,26. In the case of membrane transporters, to evaluate whether a nanobody has inhibitory activity, it is necessary to develop an assay that allows the detection of transported substrates and/or co-substrates. Such assays usually involve labeled molecules or the design of substrate-specific detection methods, which may lack a universal application. Furthermore, the identification of inhibitory nanobodies generally requires the screening of large numbers of binders. Thus, a method that can be used in a high-throughput mode and that does not rely on labeled substrates is essential for this selection.
SSM-based electrophysiology is an extremely sensitive, highly time-resolved technique that allows the detection of movement of charges across membranes (e.g., ion binding/transport)27,28. This technique has been applied to characterize electrogenic transporters, which are difficult to study using other electrophysiology techniques due to the relative low turnover of these proteins29,30,31,32,33,34,35. SSM electrophysiology does not require the use of labeled substrates, it is suitable for high-throughput screening, and either proteoliposomes or membrane vesicles containing the transporter of interest can be used. Here, we demonstrate that SSM-based electrophysiology can be used to classify transporter-targeted nanobodies with inhibitory and non-inhibitory properties. As a proof-of-principle, we describe the reconstitution of a bacterial choline transporter into liposomes, followed by detailed steps for immobilization of proteoliposomes on the SSM sensors. We next describe how to perform SSM-based electrophysiology measurements of choline transport and how to determine the half-maximal effective concentration (EC50). We then show how to use SSM-based electrophysiology to screen multiple nanobodies and to identify inhibitors of choline transport. Finally, we describe how to determine the half maximal inhibitory concentrations (IC50) of selected inhibitory nanobodies.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>1-octadecanethiol solution</td>
			<td>Sigma Aldrich</td>
			<td>O1858-25ML</td>
			<td></td>
		</tr>
		<tr>
			<td>1,2-diphytanoyl-sn-glycero-3-phosphocholine</td>
			<td>Avanti Polar Lipids</td>
			<td>850356C-25mg</td>
			<td></td>
		</tr>
		<tr>
			<td>Bio-Beads SM-2 Adsorbent (Polystyrene adsorbent beads)</td>
			<td>BioRad</td>
			<td>#152-3920</td>
			<td></td>
		</tr>
		<tr>
			<td>PD 10 Desalting Columns</td>
			<td>GE Healthcare</td>
			<td>GE17-0851-01</td>
			<td></td>
		</tr>
		<tr>
			<td>Filter 200 nm membrane</td>
			<td>Whatman Nucleopore</td>
			<td>WHA800282</td>
			<td></td>
		</tr>
		<tr>
			<td>2-Propanol</td>
			<td>Merck</td>
			<td>33539-1L-R</td>
			<td></td>
		</tr>
		<tr>
			<td>n-Decane</td>
			<td>Sigma Aldrich</td>
			<td>8034051000</td>
			<td></td>
		</tr>
		<tr>
			<td>n-dodecyl-&#223;-D-maltoside (DDM)</td>
			<td>Avanti Polar Lipids</td>
			<td>850520P-25g</td>
			<td></td>
		</tr>
		<tr>
			<td>Sodium Chloride</td>
			<td>AppliChem</td>
			<td>131659.1211</td>
			<td></td>
		</tr>
		<tr>
			<td>(SSM setup) SURFE2R N1</td>
			<td>Nanion</td>
			<td>-----</td>
			<td></td>
		</tr>
		<tr>
			<td>SURFE2R N1 Single Sensor Chips</td>
			<td>Nanion</td>
			<td># 161001</td>
			<td></td>
		</tr>
		<tr>
			<td>Trizma Base</td>
			<td>Sigma Aldrich</td>
			<td>T1503</td>
			<td></td>
		</tr>
		<tr>
			<td>E. coli Polar Lipid Extract</td>
			<td>Avanti Polar Lipids</td>
			<td>100600C</td>
			<td></td>
		</tr>
		<tr>
			<td>Egg PC L-&#945;-phosphatidylcholine </td>
			<td>Avanti Polar Lipids</td>
			<td>840051C</td>
			<td></td>
		</tr>
	</tbody>
</table>

selection of transporter-targeted inhibitory nanobodies by solid-supported-membrane (ssm)-based electrophysiology

Single domain antibodies (nanobodies) have been extensively used in mechanistic and structural studies of proteins and they pose an enormous potential as tools for developing clinical therapies, many of which depend on the inhibition of membrane proteins such as transporters. However, most of the methods used to determine the inhibition of transport activity are difficult to perform in high-throughput routines and depend on labeled substrates availability thereby complicating the screening of large nanobody libraries. Solid-supported membrane (SSM) electrophysiology is a high-throughput method, used for characterizing electrogenic transporters and measuring their transport kinetics and inhibition. Here we show the implementation of SSM-based electrophysiology to select inhibitory and non-inhibitory nanobodies targeting an electrogenic secondary transporter and to calculate nanobodies inhibitory constants. This technique may be especially useful for selecting inhibitory nanobodies targeting transporters for which labeled substrates are not available.

SSM-based electrophysiology has been extensively used for the characterization of electrogenic transporters. In the protocol presented here, we show how to use SSM-based electrophysiology to classify nanobodies targeting a secondary transporter (here a bacterial choline symporter) based on their inhibitory and non-inhibitory properties. One of the most useful features of this technique is that it allows for the high-throughput screening of multiple buffer conditions. This particular characteristic is beneficial for the a...

Watch this Scientific Journal Video about Selection of Transporter-Targeted Inhibitory Nanobodies by Solid-Supported-Membrane SSM-Based Electrophysiology at JoVE.com

Selection of Transporter-Targeted Inhibitory Nanobodies by Solid-Supported-Membrane SSM-Based Electrophysiology

Nanobodies are important tools in structural biology and pose a great potential for the development of therapies. However, the selection of nanobodies with inhibitory properties can be challenging. Here we demonstrate the use of solid-supported-membrane (SSM)-based electrophysiology for the classification of inhibitory and non-inhibitory nanobodies targeting electrogenic membrane transporters.

Selection of Transporter-Targeted Inhibitory Nanobodies by Solid-Supported-Membrane (SSM)-Based Electrophysiology

Single domain antibodies (nanobodies) have been extensively used in mechanistic and structural studies of proteins and they pose an enormous potential as ...

The presented protocol is used for high-throughput screening and identification of inhibitory and non-inhibitory nanobodies targeting electrogenic transporters reconstituted in proteoliposomes or present in membrane vesicles. Designing transfer assays can be difficult in multiple cases, especially if labeled substrates are not available. If the same electrophysiology allows studying the effect of nanobodies on transport for virtually any electrogenic transporter, since SSM electrophysiology doesn't require labeled substrates.Nanobodies have been investigated for their usage in medical applications. This technique can help screen potential inhibitors targeting specific electrogenic transporters of humans or human pathogens. To begin, take 10 clean tubes and transfer 10 milliliters of the nonactivating solid-supported membrane, or SSM, buffer into each tube.To prepare the activating SSM buffers, add the substrate into the tubes using a series of concentrations around the expected half maximum concentration. Start the SSM software and let the machine initialize automatically. Set the saving path for data.Confirm by hitting the OK button. Select the standard initial cleaning protocol in the workflow options and click run. Next, mount the proteoliposome-coated chip on the socket.Move the arm to lock the chip. Enclose the mounted chip with the cap. Select the program CapCom in the workflow, and let it run to determine the conductivity and capacitance.Confirm that the conductivity is below five nanosiemens and the capacitance is between 15 and 35 nanofarad before using it for the measurement. Transfer the activating solutions into vials and position the buffers in the probe sampler. Transfer the nonactivating buffer into a reservoir and place it next to the chip holder at the reservoir position on the right.Create a protocol for the workflow using a sequence of nonactivating, activating, and nonactivating solution sequence, or a BAB sequence, in a loop that performs three measurements and moves to the next activating buffer for all 10 buffers. Use the default flow rate of 200 microliters per second with one second, one second, one second flow times for the BAB sequence and click play to start the measurement. Save the protocol and let the workflow run by clicking on the play button.Then perform the same experiment using protein-free liposomes. Use any preferred software for data analysis to plot the measured current versus time and use the function for peak height estimation in the range of the addition of the activating buffer. Plot the peak current against the substrate concentration to determine the half maximal effect of concentration, or EC50, of the substrate via nonlinear regression.Transfer 50 milliliters of the nonactivating SSM buffer into a clean tube. Add the substrate choline to a final concentration of five millimolar and use this for a positive control measurement. Transfer 10 milliliters of the non activating SSM buffer into a clean tube.Add substrate choline to five millimolar and nanobody to 500 nanomolar final concentration. Repeat the step for each nanobody to prepare the activating solutions as demonstrated. Start the SSM machine and measure the capacitance and conductivity of the proteoliposome-coated chip, as demonstrated earlier.Transfer the activating solution without a nanobody into a vial and place the buffer in the probe sampler. Transfer the nonactivating buffer without a nanobody into a reservoir and position it in the probe sampler. Then repeat this process for all solutions containing nanobodies with activating and nonactivating solution.Create a protocol for the workflow Using a BAB sequence. Create a loop that performs three measurements of the BAB sequence using buffers without nanobodies, two measurements of the BAB sequence with buffers containing a nanobody, 120 second delay time incubation with the nanobody, and three measurements of the BAB sequence with buffers containing the nanobody. Save the workflow and let it run by clicking the play button.Next, create a new protocol for the workflow using a BAB sequence and a loop of five measurements to wash out the reversibly bound nano body. Save the workflow and let it run by clicking the play button. Compare the last peak current of the measurements with the initial substrate-only measurement.If the peak current reaches the initial value, the nanobody has been successfully washed out and the initial conditions have been reestablished. Otherwise, repeat the workflow or change to a new chip. Repeat this process using individual chips for each nanobody screen, or repeat with multiple nanobodies using the same chip.Use any preferred software for data analysis to plot the measured current versus time. Then the software automatically selects the function for peak height estimation in the range of the addition of the activation buffer. Normalize the peak current and the presence of the nanobody based on the proceeding substrate-only measurement.Plot the peak currents in the histogram and compare the peak currents of the substrate-only measurements to the peak currents measured in the presence of nanobodies to identify inhibitory nanobodies. Transfer 50 milliliters of the nonactivating SSM buffer into a clean tube and add the substrate choline to a final concentration of five millimolar, and use this as the activating solution for positive control. Add five milliliters of the nonactivating solution to eight clean tubes, then add substrate choline and inhibitory nanobody to the tubes at concentrations in the expected IC50 range.Add 10 milliliters of the nonactivating solution to the eight tubes and add inhibitory nanobody to each tube corresponding to the nonactivation buffer. Start the SSM setup and measure the capacitance and conductivity of the proteoliposome-coated chip. Transfer the activating solution without nanobody into a vial and place it in the probe sampler.Then transfer the nonactivating buffer without nanobody into a reservoir and position it at the reservoir position next to the chip holder on the right. Transfer the activating and nonactivating solutions containing nanobodies into vials and position the buffers in the probe sampler. Create a protocol for the workflow using a BAB sequence.Include a loop to measure each concentration twice, incubate for 120 seconds and measure three more times. Use any preferred software for data analysis to plot the measured current versus time and select the function for the peak height estimation in the range of the addition of the activation buffer. Plot the peak currents against the nanobody concentration to determine the IC50 via nonlinear regression.For determining the substrate concentration to be used during a screening of nanobodies, electrogenic transport was measured under different substrate concentrations to determine EC50. A substrate concentration corresponding to saturating conditions, five millimolar, was selected and kept constant in all activating buffers. The effect of inhibitory nanobodies on electrogenic transport was visualized from the decrease in peak currents'amplitudes.After running the washing protocol to allow nanobody unbinding, a recovery of 80 to 95%of the initial peak current amplitude was observed. When changing from nonactivating to activating conditions, no significant artifact currents were introduced by nanobodies present in these buffers. After selecting nanobodies with inhibitory properties, the IC50 values for individual nanobodies were determined.It is crucial to give enough time for the calibration of the proteoliposomes on the chip with the buffer containing the nanobody. Since the binding is reversible, the nanobody needs to be present in both activating and nonactivating buffers.

Research

JoVE Journal

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