The authors are grateful to Dr. Yangyang Yan in the laboratory of Dr. Fred Sigworth at Yale University for the generous donation of HEK293 cells&#160;stably expressing rat Slack-B protein. Additionally the authors are grateful to Dr. Sigworth for cryo-electron microscopy homology model of Slack displayed in the video introduction.&#160;This research was supported by NIH Grants DH067517 and NS073943 to L.K.K.

1. Cell Culture (Adapted from Fleming and Kaczmarek18)
<ol>
	<li>Culture cells in appropriate media for greater than 2 but less than 10 passages before use in this assay. Untransfected HEK-293 cells and HEK-293 cells stably expressing rat Slack-B protein are grown in one half Dulbecco&#39;s Modified Eagle medium and one half Leibovitz&#39;s L-15 Medium supplemented with 10% heat inactivated fetal bovine serum and antibiotics. 500 &#181;g/ml&#160;Geneticin (G418) is added to HEK-293 cells stably expressing Slack-B to select for expression of the Slack channel. Passage cells at 70-90% confluence by dissociation from dishes with a 0.25% trypsin-EDTA solution.</li>
</ol>
2. Extracellular Matrix (ECM) Coating of the TiO2 384-well Optical Biosensor Plate with Fibronectin and Ovalbumin
<ol>
	<li>Preparation of the fibronectin ECM mixture and ovalbumin blocking solution
	<ol>
		<li>Prepare a working solution of fibronectin in phosphate buffered saline (PBS) with a final concentration of 5 &#181;g/ml&#160;of fibronectin in 20.0 ml&#160;PBS. From a 1.0 mg/ml&#160;stock concentration, add 100 &#181;l&#160;to 20.0 ml&#160;PBS for a 200-fold dilution. The working solution of fibronectin can be aliquoted and stored at -20 &#176;C after preparation.</li>
		<li>Prepare a 5% stock solution of heat-inactivated ovalbumin in sterile water. Dilute ovalbumin in sterile tissue culture grade water for a 5% solution and heat-inactivate for 30 min at 60 &#176;C. Cool the solution to room temperature and sterile filter the solution. Aliquot the 5% ovalbumin solution and store at 4 &#176;C.</li>
		<li>Prepare a 2% working solution of ovalbumin by diluting the 5% stock solution into PBS. For example, add 12.0 ml of 5% ovalbumin stock solution to 18.0 ml of PBS for a final volume of 30.0 ml.</li>
	</ol>
	</li>
	<li>384-well optical biosensor plate coating
	<ol>
		<li>Hydrate the TiO2 plate with 20.0 &#181;l/well of sterile tissue culture grade water for 15 min. The following steps should be performed with a 16-channel pipettor.</li>
		<li>Wash plate 1x with 50.0 &#181;l PBS per well.</li>
		<li>Add 20.0 &#181;l of the fibronectin working solution to each well and incubate for 2 hr at room temperature to create the ECM.</li>
		<li>Wash plate 1x with 50.0 &#181;l PBS per well.</li>
		<li>Add 40.0 &#181;l of the ovalbumin working solution to each well and incubate overnight at 4 &#176;C to block the plate.</li>
		<li>Wash plate 3x with 50.0 &#181;l PBS per well. ECM coated plates can be stored at 4 &#176;C for up to 48 hr.</li>
	</ol>
	</li>
</ol>
3. Seeding of Cells onto the 384-well Optical Biosensor Plate
<ol>
	<li>Remove growth media from the cells and add trypsin to dislodge the cells from the plate. Collect the cells and centrifuge at 1,000 x g for 1 min. Remove the trypsin media and resuspend cells in growth media.</li>
	<li>Using a hemocytometer or an automated cell counter, determine the concentration of the cells.</li>
	<li>To minimize the effects of evaporation during incubation, 50.0 &#181;l of growth medium per well will be used. Cells should be diluted to achieve the desired number of cells per well in a volume of 50.0 &#181;l of growth medium. For these experiments, 1,000 cells/well were plated onto the biosensor.</li>
	<li>Allow the seeded cells to incubate overnight in growth medium at 37 &#176;C under air/5% CO2.</li>
</ol>
4. Preparation of the Biosensor and Compound Plates for the RWG Optical Biosensor Assay
<ol>
	<li>Remove the plate from the incubator and remove growth media from the cells. Wash the cells 1x with Hanks Balanced Salt Solution (HBSS). Add 25.0 &#181;l of HBSS to each well.</li>
	<li>Place the biosensor plate on the BIND Scanner and allow the cells to equilibrate to room temperature for 1-2 hr.</li>
	<li>Prepare a separate compound plate from which ligands of interest will be added to the biosensor plate during the assay. For these assays, 25.0 &#181;l of solution containing compound was added to each well on the biosensor plate for a total volume of 50.0 &#181;l. As such, compounds in solution were prepared in 2x the desired final concentration.</li>
</ol>
5. Perform the RWG Optical Biosensor Assay
<ol>
	<li>Take a baseline measurement with the Scanner system for wells A1-P12 (half of the SBS 384-well plate) using a maximum resolution of 3.75 &#181;m/pixel for the central 1.5 mm of each well using the BIND Scan software . This baseline scan will take approximately 30 min.</li>
	<li>Add 25.0 &#181;l of the compound solutions to each well for wells A1-P12.</li>
	<li>Take a baseline measurement of wells A13-P24.</li>
	<li>Add 25.0 &#181;l of the compound solutions to each well for wells A13-P24.</li>
	<li>Take a post&#160;compound addition measurement for wells A1-P12, and repeat for wells A13-P24.</li>
</ol>
6. Analysis of Assay Data with BIND View
<ol>
	<li>Open the BIND assay data for the baseline measurement in Windows, and click the &#34;Grid Editor&#34; button to enable cell selection. The software will calculate metrics of interest defined by the user.</li>
	<li>Open the &#34;Plug-ins&#34;, which include the &#34;Cell Finder&#34; and &#34;Baseliner&#34; function. Set parameters in &#34;Cell Finder&#34; so that cells are distinguishable from the background of the biosensor.</li>
	<li>Export the cell map file which contains the &#34;Cell Finder&#34; data for the baseline measurement.</li>
	<li>Repeat steps 6.1-6.2 for post&#160;compound addition data.</li>
	<li>Open the &#34;Baseliner&#34; plug-in and import the cell map from the baseline measurement. The software will calculate the shift in PWV between the background and post&#160;compound data.</li>
	<li>Select &#34;&#916; Cell Mean&#34; for the output of the mean shift in PWV for cells. The data can then be exported to Microsoft Excel for further analysis.</li>
</ol>

<ol>
	<li>Hille, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Ion Channels of Excitable Membranes. , (1992).</li><li>Kaczmarek, L. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Non-conducting+functions+of+voltage-gated+ion+channels.">Non-conducting functions of voltage-gated ion channels.</a> Nat. Rev. Neurosci. 7, 761-771 (2006).</li><li>Levitan, I. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signaling+protein+complexes+associated+with+neuronal+ion+channels.">Signaling protein complexes associated with neuronal ion channels.</a> Nat. Neurosci. 9, 305-310 (2006).</li><li>Shamah, S. M., Cunningham, B. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-free+cell-based+assays+using+photonic+crystal+optical+biosensors.">Label-free cell-based assays using photonic crystal optical biosensors.</a> Analyst. 136, 1090-1102 (2011).</li><li>Cunningham, B. T., Laing, L. M. i. c. r. o. p. l. a. t. e. -. b. a. s. e. d. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=label-free+detection+of+biomolecular+interactions:+applications+in+proteomics.">label-free detection of biomolecular interactions: applications in proteomics.</a> Expert Rev. Proteomics. 3, 271-281 (2006).</li><li>Peters, M. F., Vaillancourt, F., Heroux, M., Valiquette, M., Scott, C. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+label-free+biosensors+for+pharmacological+screening+with+cell-based+functional+assays.">Comparing label-free biosensors for pharmacological screening with cell-based functional assays.</a> Assay Drug Dev. 8, 219-227 (2010).</li><li>Fang, Y., Ferrie, A. M., Fontaine, N. H., Mauro, J., Balakrishnan, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resonant+waveguide+grating+biosensor+for+living+cell+sensing.">Resonant waveguide grating biosensor for living cell sensing.</a> Biophys. J. 91, 1925-1940 (2006).</li><li>Cunningham, B. T., 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=Label-free+assays+on+the+BIND+system.">Label-free assays on the BIND system.</a> J. Biomol. Screen. 9, 481-490 (2004).</li><li>Hessel, A. a. O., A, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+New+Theory+of+Wood's+Anomalies+on+Optical+Gratings.">A New Theory of Wood's Anomalies on Optical Gratings.</a> Appl. Optics. 4, 1275-1297 (1965).</li><li>Cunningham, B. T., Laing, L. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advantages+and+application+of+label-free+detection+assays+in+drug+screening.">Advantages and application of label-free detection assays in drug screening.</a> Expert Opin. Drug Discov. 3, 891-901 (2008).</li><li>Lee, P. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Label-free+optical+biosensor:+a+tool+for+G+protein-coupled+receptors+pharmacology+profiling+and+inverse+agonists+identification.">Label-free optical biosensor: a tool for G protein-coupled receptors pharmacology profiling and inverse agonists identification.</a> J. Recept. Signal Transduct. Res. 29, 146-153 (2009).</li><li>Bhattacharjee, A., Kaczmarek, L. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=For+K++channels,+Na++is+the+new+Ca2.">For K+ channels, Na+ is the new Ca2.</a> Trends Neurosci. 28, 422-428 (2005).</li><li>Santi, C. M., 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=Opposite+regulation+of+Slick+and+Slack+K++channels+by+neuromodulators.">Opposite regulation of Slick and Slack K+ channels by neuromodulators.</a> J. Neurosci. 26, 5059-5068 (2006).</li><li>Yang, B., Desai, R., Kaczmarek, L. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Slack+and+Slick+K(Na)+channels+regulate+the+accuracy+of+timing+of+auditory+neurons.">Slack and Slick K(Na) channels regulate the accuracy of timing of auditory neurons.</a> J. Neurosci. 27, 2617-2627 (2007).</li><li>Brown, M. R., 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=Fragile+X+mental+retardation+protein+controls+gating+of+the+sodium-activated+potassium+channel.">Fragile X mental retardation protein controls gating of the sodium-activated potassium channel.</a> 13, 819-821 (2010).</li><li>Zhang, Y., 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=Regulation+of+neuronal+excitability+by+interaction+of+fragile+X+mental+retardation+protein+with+slack+potassium+channels.">Regulation of neuronal excitability by interaction of fragile X mental retardation protein with slack potassium channels.</a> J. Neurosci. 32, 15318-15327 (2012).</li><li>Barcia, G., 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=De+novo+gain-of-function+KCNT1+channel+mutations+cause+malignant+migrating+partial+seizures+of+infancy.">De novo gain-of-function KCNT1 channel mutations cause malignant migrating partial seizures of infancy.</a> Nat. Genet. 44, 1255-1259 (2012).</li><li>Fleming, M. R., Kaczmarek, L. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+optical+biosensors+to+detect+modulation+of+Slack+potassium+channels+by+G+protein-coupled+receptors.">Use of optical biosensors to detect modulation of Slack potassium channels by G protein-coupled receptors.</a> J. Recept. Signal Transduct. Res. 29, 173-181 (2009).</li><li>Nelson, C. D., 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=Targeting+of+diacylglycerol+degradation+to+M1+muscarinic+receptors+by+beta-arrestins.">Targeting of diacylglycerol degradation to M1 muscarinic receptors by beta-arrestins.</a> Science. 315, 663-666 (2007).</li><li>Zhang, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Simple+Statistical+Parameter+for+Use+in+Evaluation+and+Validation+of+High+Throughput+Screening+Assays.">A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.</a> J. Biomol. Screen. 4, 67-73 (1999).</li><li>Gribbon, P., 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=Evaluating+real-life+high-throughput+screening+data.">Evaluating real-life high-throughput screening data.</a> J. Biomol. Screen. 10, 99-107 (2005).</li></ol>

Steven M. Shamah is an employee of X-BODY Biosciences.

The Z prime (Z&#39;) factor is a common statistical method to quantify the quality of a high-throughput screening assay20, and because the screening of the GPCR agonists in this assay occurred in a SBS compatible 384-well assay, provides an excellent measure of the robustness and validity of this assay21. A Z&#39; value of 1 indicates a theoretically ideal assay with an infinite number of data points with nonexistent standard deviations. A Z&#39; value of between 0.5-1 is considered an excellent ass...

Examining living cells in their physiologically relevant context is crucial to understanding the biological functions of cellular targets. However, assays examining the interaction between channels and regulatory cytoplasmic proteins, such as coimmunoprecipitation assays, generally provide little information on the time course of interactions in living cells. The majority of current cell based assays measure a specific cellular event, such as the translocation of a fluorescently tagged protein of interest. These assays require modifications of the proteins of interest, which can potentially alter the protein&#39;s behavior and decrease the physiological relevance of the target. Noninvasive cell based assays, which do not require manipulation of the system, provide a continuous measurement of cellular activity and allow studies of cells in their most physiologically relevant state4.
Optical biosensors are designed to produce a measureable change in a characteristic of the light that is coupled to the sensor surface. Optical biosensors that utilize evanescent waves, which include surface plasmon resonance (SPR) and resonance wavelength grating (RWG) techniques, have been primarily used to detect the affinities and kinetics of molecules binding to their biological receptors immobilized on the sensor surface. More recently, commercially available RWG biosensors have been developed to allow the detection of the relative change in mass within the bottom portion of cells adherent to the sensor surface at high spatial resolution (up to 3.75 &#181;m/pixel)5. These biosensors can detect changes in mass near the plasma membrane of living cells that result from stimulation, such as cell adhesion and spreading, toxicity, proliferation&#160;and signaling pathways elicited by a variety of cell surface receptors including G-protein coupled receptors (GPCRs)6. RWG biosensors detect the relative change in the index of refraction as a function of the relative change in mass within 150 nm of the biosensor7. When cells are plated to the biosensor, this change in the index of refraction reflects the change in mass near the plasma membrane of the cell resulting from a change in cellular adherence to the biosensor. This protocol will discuss the detection of channel-protein interactions using RWG biosensors.
RWG data acquisition systems consist of several components. Because the X-BODY Biosciences BIND Scanner was used for these experiments, we shall refer to the components for this particular system, which consists of a plate reader, associated biosensors, BIND Scan acquisition software, and BIND View analysis software8. The photonic crystal biosensors, referred to hereafter as optical biosensors, are composed of a periodic arrangement of a dielectric and material in 2 or 3 dimensions which prevents the propagation of light at specific wavelengths and directions. Photonic crystal structures are based on a phenomenon called Wood&#39;s anomaly. First discovered by Wood in 1902, these anomalies are effects observed in the spectrum of light reflected by optical diffraction gratings where rapid variations in the intensity of particular diffraction orders occur in certain narrow frequency bands. In 1962, Hessel and Oliner presented a new theory of Wood&#39;s anomalies in which finite period grating generates a standing resonance wavelength9. In the optical biosensors described here, Wood&#39;s anomalies are used to produce a RWG biosensor that when stimulated with white light reflects only very narrow band of wavelengths (typically between 850-855 nm).
Individual biosensors consist of a low-refractive index plastic material with a periodic surface structure which is coated with a thin layer of the high-refractive dielectric material titanium dioxide (TiO2). When the biosensor is illuminated with a broad wavelength light source, the optical grating of photonic crystals reflects a narrow range of wavelengths of light which is measured by a spectrophotometer in the BIND Scanner. The peak intensity of the reflected wavelengths (Peak Wavelength Value, or PWV) is then calculated from the signal. The PWV of light shifts upon a change in the index of refraction as a result of an increase or decrease in mass within the proximity (~150 nm) of the biosensor surface. Optical biosensors are incorporated into a standard Society for Biomolecular Sciences (SBS) 384-well microplate for the assays used in these experiments.
RWV biosensors are used to detect changes upon addition of exogenous signals in living cells10. Cells are directly cultured onto the surface of a RWG biosensor and the change in the local index of refraction is monitored upon treatment with specific stimuli. The direction of change in mass at the biosensor can be determined, because an increase in the local index of refraction results from an increase in mass near the biosensor&#160;and is measured as an increase in PWV. Conversely a decrease in mass produces a decrease in PWV. The change in detected PWV can result from numerous cellular events, including changes in cell adhesion, protein recruitment/release, endocytosis and recycling, exocytosis, apoptosis, and cytoskeletal rearrangement. For example, the assay can be detect changes in channel-protein interactions between potassium channels and other cytoplasmic or cytoskeletal components. The event, however, must occur within the ~150 nm detection zone near the biosensor, and in the case of an attached cell, near the plasma membrane. Acquisition of cellular responses is performed with BIND Scan software and an image representation of each of the 384 wells in the SBS plate is generated. This system has a resolution of up to 3.75 &#181;m/pixel, allowing detection of events in single cells, and can be used either with cell lines (such as HEK293 or CHO cells) or with more physiologically relevant primary cells. Image analysis with BIND View software allows the detection of cellular responses in both individual and populations of cells. As the biosensors are incorporated into standard SBS 384-well microplates, the system is readily adaptable to high-throughput screening (HTS).
Resonance-wavelength grating optical biosensors have previously been used to detect changes in mass near the plasma membrane of cells following activation of GPCRs11. Our laboratory has cloned two sodium-activated (KNa) potassium channels, Slack-B and Slick12. The activity of both Slack-B and Slick channels has been shown to be very strongly influenced by direct activation of protein kinase C (PKC)13. Activation of G&#945;q protein coupled receptors, such as the M1 muscarinic receptor and the mGluR1 metabotropic glutamate receptor, potently regulates channel activity through PKC activation. These KNa channels contribute to neuronal adaptation during sustained stimulation and regulate the accuracy of timing of action potentials14. Slack channels are known to interact with a variety of cytoplasmic signaling molecules, including FMRP, the Fragile X Mental Retardation protein15,16. Mutations in Slack result in Multiple Migrating Partial Seizures of Infancy (MMPSI), an early onset form of epilepsy which results in severe developmental delay17.

<table border="0" cellpadding="0" cellspacing="0" width="723">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">DMEM, High Glucose</td>
			<td style="width:172px;">Life Technologies</td>
			<td style="width:119px;">11965-092</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Leibovitz&#39;s L-15 Medium</td>
			<td style="width:172px;">Life Technologies</td>
			<td style="width:119px;">11415-064</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Penicillin-Streptomycin (10,000 U/ml)</td>
			<td style="width:172px;">Life Technologies</td>
			<td style="width:119px;">15140-122</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Geneticin G-418 Sulfate</td>
			<td style="width:172px;">American Bioanalytical</td>
			<td style="width:119px;">AB05057</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">HBSS</td>
			<td style="width:172px;">Life Technologies</td>
			<td style="width:119px;">14025-092</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Fibronectin from human plasma</td>
			<td style="width:172px;">Sigma-Aldrich</td>
			<td style="width:119px;">F0895</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Albumin from chicken egg white</td>
			<td style="width:172px;">Sigma-Aldrich</td>
			<td style="width:119px;">A5378</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">DPBS</td>
			<td style="width:172px;">Life Technologies</td>
			<td style="width:119px;">14190-144</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:265px;">Hausser Bright-Line Phase Hemocytometer</td>
			<td style="width:172px;">Fisher Scientific</td>
			<td style="width:119px;">02-671-6</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Carbamoylcholine chloride</td>
			<td style="width:172px;">Sigma-Aldrich</td>
			<td style="width:119px;">C4382</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">SFLLR-NH2 trifluoroacetate salt</td>
			<td style="width:172px;">Sigma-Aldrich</td>
			<td style="width:119px;">S8701</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">Finnpipette (5-50 &#181;l)</td>
			<td style="width:172px;">Thermo Scientific</td>
			<td align="right" style="width:119px;">4662090</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">BIND Scanner System</td>
			<td style="width:172px;">X-BODY Biosciences</td>
			<td style="width:119px;">N/A</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:265px;">384-well TiO2 coated plates</td>
			<td style="width:172px;">X-BODY Biosciences</td>
			<td style="width:119px;">TiO-96-CM</td>
			<td></td>
		</tr>
	</tbody>
</table>

use of label-free optical biosensors to detect modulation of potassium channels by g-protein coupled receptors

Ion channels control the electrical properties of neurons and other excitable cell types by selectively allowing ions to flow through the plasma membrane1. To regulate neuronal excitability, the biophysical properties of ion channels are modified by signaling proteins and molecules, which often bind to the channels themselves to form a heteromeric channel complex2,3. Traditional assays examining the interaction between channels and regulatory proteins require exogenous labels that can potentially alter the protein&#39;s behavior and decrease the physiological relevance of the target, while providing little information on the time course of interactions in living cells. Optical biosensors, such as the X-BODY Biosciences BIND Scanner system, use a novel label-free technology, resonance wavelength grating (RWG) optical biosensors, to detect changes in resonant reflected light near the biosensor. This assay allows the detection of the relative change in mass within the bottom portion of living cells adherent to the biosensor surface resulting from ligand induced changes in cell adhesion and spreading, toxicity, proliferation, and changes in protein-protein interactions near the plasma membrane. RWG optical biosensors have been used to detect changes in mass near the plasma membrane of cells following activation of G protein-coupled receptors (GPCRs), receptor tyrosine kinases, and other cell surface receptors. Ligand-induced changes in ion channel-protein interactions can also be studied using this assay. In this paper, we will describe the experimental procedure used to detect the modulation of Slack-B sodium-activated potassium (KNa) channels by GPCRs.

Slack-B stably transfected HEK-293 cells and control untransfected HEK-293 cells were seeded at 1,000&#160;cells/well on 384-well, ECM coated RWG biosensor plates. Images from the central 1.5 mm2 of the biosensor were recorded at a resolution of 3.75 &#181;m/pixel (Figure 1). Density gradient maps of mass were generated pre&#160;and 30 min post&#160;compound addition with the BIND Scan software. The BIND View software was utilized to determine the shift in PWV upon GPCR agonist addition by sub...

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Use of Label-free Optical Biosensors to Detect Modulation of Potassium Channels by G-protein Coupled Receptors

Optical biosensor techniques can detect changes in mass near the plasma membrane in living cells and allow one to follow cellular responses in both individual cells and populations of cells. This protocol will describe detection of the modulation of potassium channels by G-protein coupled receptors in intact cells using this approach.

Ion channels control the electrical properties of neurons and other excitable cell types by selectively allowing ions to flow through the plasma ...

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Research

JoVE Journal

Bioengineering

10.2K Views.  Yale School of Medicine. Optical biosensor techniques can detect changes in mass near the plasma membrane in living cells and allow one to follow cellular responses in both individual cells and populations of cells. This protocol will describe detection of the modulation of potassium channels by G-protein coupled receptors in intact cells using this approach.

Video: Use of Label-free Optical Biosensors to Detect Modulation of Potassium Channels by G-protein Coupled Receptors

Attaching Biological Probes to Silica Optical Biosensors Using Silane Coupling Agents

In order to interface with biological environments, biosensor platforms, such as the popular Biacore system (based on the Surface Plasmon Resonance (SPR) technique), make use of various surface modification techniques, that can, for example, prevent surface fouling, tune the hydrophobicity / hydrophilicity of the surface, adapt to a variety of electronic environments, and most frequently, induce specificity towards a target of interest.1-5 These techniques extend the functionality of otherwise highly sensitive biosensors to real-world applications in complex environments, such as blood, urine, and wastewater analysis.2,6-7 While commercial biosensing platforms, such as Biacore, have well-understood, standard techniques for performing such surface modifications, these techniques have not been translated in a standardized fashion to other label-free biosensing platforms, such as Whispering Gallery Mode (WGM) optical resonators.8-9
WGM optical resonators represent a promising technology for performing label-free detection of a wide variety of species at ultra-low concentrations.6,10-12 The high sensitivity of these platforms is a result of their unique geometric optics: WGM optical resonators confine circulating light at specific, integral resonance frequencies.13 Like the SPR platforms, the optical field is not totally confined to the sensor device, but evanesces; this "evanescent tail" can then interact with species in the surrounding environment. This interaction causes the effective refractive index of the optical field to change, resulting in a slight, but detectable, shift in the resonance frequency of the device. Because the optical field circulates, it can interact many times with the environment, resulting in an inherent amplification of the signal, and very high sensitivities to minor changes in the environment.2,14-15
To perform targeted detection in complex environments, these platforms must be paired with a probe molecule (usually one half of a binding pair, e.g. antibodies / antigens) through surface modification.2 Although WGM optical resonators can be fabricated in several geometries from a variety of material systems, the silica microsphere is the most common. These microspheres are generally fabricated on the end of an optical fiber, which provides a "stem" by which the microspheres can be handled during functionalization and detection experiments. Silica surface chemistries may be applied to attach probe molecules to their surfaces; however, traditional techniques generated for planar substrates are often not adequate for these three-dimensional structures, as any changes to the surface of the microspheres (dust, contamination, surface defects, and uneven coatings) can have severe, negative consequences on their detection capabilities. Here, we demonstrate a facile approach for the surface functionalization of silica microsphere WGM optical resonators using silane coupling agents to bridge the inorganic surface and the biological environment, by attaching biotin to the silica surface.8,16 Although we use silica microsphere WGM resonators as the sensor system in this report, the protocols are general and can be used to functionalize the surface of any silica device with biotin.

Biosensors interface with complex, biological environments and perform targeted detection by combining highly sensitive sensors with highly specific probes attached to the sensor via surface modification. Here, we demonstrate the surface functionalization of silica optical sensors with biotin using silane coupling agents to bridge the sensor and the biological environment.

In order to interface with biological environments, biosensor platforms, such as the popular Biacore system (based on the Surface Plasmon Resonance (SPR) ...

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, currently available routine methods require processing steps and alter sample integrity. Raman spectroscopy is a fast method that enables the measurement of biological samples without the need for further processing steps. This laser-based technology detects the inelastic scattering of monochromatic light.6 As every chemical vibration is assigned to a specific Raman band (wavenumber in cm-1), each biological sample features a typical spectral pattern due to their inherent biochemical composition.7-9 Within Raman spectra, the peak intensities correlate with the amount of the present molecular bonds.1 Similarities and differences of the spectral data sets can be detected by employing a multivariate analysis (e.g. principal component analysis (PCA)).10
Here, we perform Raman spectroscopy of living cells and native tissues. Cells are either seeded on glass bottom dishes or kept in suspension under normal cell culture conditions (37 &deg;C, 5% CO2) before measurement. Native tissues are dissected and stored in phosphate buffered saline (PBS) at 4 &deg;C prior measurements. Depending on our experimental set up, we then either focused on the cell nucleus or extracellular matrix (ECM) proteins such as elastin and collagen. For all studies, a minimum of 30 cells or 30 random points of interest within the ECM are measured. Data processing steps included background subtraction and normalization.

Raman spectroscopy is a suitable technique for the non-contact, label-free analysis of living cells, tissue-engineered constructs and native tissues. Source-specific spectral fingerprints can be generated and analyzed using multivariate analysis.

Non-destructive, non-contact and label-free technologies to monitor cell and tissue cultures are needed in the field of biomedical research.1-5 However, ...

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

A label-free optical biosensor based on a nanostructured porous Si is designed for rapid capture and detection of Escherichia coli K12 bacteria, as a model microorganism. The biosensor relies on direct binding of the target bacteria cells onto its surface, while no pretreatment (e.g.&#160;by cell lysis) of the studied sample is required. A mesoporous Si thin film is used as the optical transducer element of the biosensor. Under white light illumination, the porous layer displays well-resolved Fabry-P&#233;rot fringe patterns in its reflectivity spectrum. Applying a fast Fourier transform (FFT) to reflectivity data results in a single peak. Changes in the intensity of the FFT peak are monitored. Thus, target bacteria capture onto the biosensor surface, through antibody-antigen interactions, induces measurable changes in the intensity of the FFT peaks, allowing for a &#39;real time&#39; observation of bacteria attachment.
The mesoporous Si film, fabricated by an electrochemical anodization process, is conjugated with monoclonal antibodies, specific to the target bacteria. The immobilization, immunoactivity and specificity of the antibodies are confirmed by fluorescent labeling experiments. Once the biosensor is exposed to the target bacteria, the cells are directly captured onto the antibody-modified porous Si surface. These specific capturing events result in intensity changes in the thin-film optical interference spectrum of the biosensor. We demonstrate that these biosensors can detect relatively low bacteria concentrations (detection limit of 104 cells/ml) in less than an hour.

Optical Detection of E. coli Bacteria by Mesoporous Silicon Biosensors

A label-free optical biosensor for rapid bacteria detection is introduced. The biosensor is based on a nanostructured porous Si, which is designed to directly capture the target bacteria cells onto its surface. We use monoclonal antibodies, immobilized onto the porous transducer, as the capture probes. Our studies demonstrate the applicability of these biosensors for the detection of low bacterial concentrations within minutes with no prior sample processing (such as cell lysis).

A label-free optical biosensor based on a nanostructured porous Si is designed for rapid capture and detection of Escherichia coli K12 bacteria, as a ...

Nanomanipulation of Single RNA Molecules by Optical Tweezers

A large portion of the human genome is transcribed but not translated. In this post genomic era, regulatory functions of RNA have been shown to be increasingly important. As RNA function often depends on its ability to adopt alternative structures, it is difficult to predict RNA three-dimensional structures directly from sequence. Single-molecule approaches show potentials to solve the problem of RNA structural polymorphism by monitoring molecular structures one molecule at a time. This work presents a method to precisely manipulate the folding and structure of single RNA molecules using optical tweezers. First, methods to synthesize molecules suitable for single-molecule mechanical work are described. Next, various calibration procedures to ensure the proper operations of the optical tweezers are discussed. Next, various experiments are explained. To demonstrate the utility of the technique, results of mechanically unfolding RNA hairpins and a single RNA kissing complex are used as evidence. In these examples, the nanomanipulation technique was used to study folding of each structural domain, including secondary and tertiary, independently. Lastly, the limitations and future applications of the method are discussed.

Optical tweezers have been used to study RNA folding by stretching individual molecules from their 5&#8217; and 3&#8217; ends. Here common procedures are described to synthesize RNA molecules for tweezing, calibration of the instrument, and methods to manipulate single molecules.

A large portion of the human genome is transcribed but not translated. In this post genomic era, regulatory functions of RNA have been shown to be ...

A Microfluidic-based Electrochemical Biochip for Label-free DNA Hybridization Analysis

Miniaturization of analytical benchtop procedures into the micro-scale provides significant advantages in regards to reaction time, cost, and integration of pre-processing steps. Utilizing these devices towards the analysis of DNA hybridization events is important because it offers a technology for real time assessment of biomarkers at the point-of-care for various diseases. However, when the device footprint decreases the dominance of various physical phenomena increases. These phenomena influence the fabrication precision and operation reliability of the device. Therefore, there is a great need to accurately fabricate and operate these devices in a reproducible manner in order to improve the overall performance. Here, we describe the protocols and the methods used for the fabrication and the operation of a microfluidic-based electrochemical biochip for accurate analysis of DNA hybridization events. The biochip is composed of two parts: a microfluidic chip with three parallel micro-channels made of polydimethylsiloxane (PDMS), and a 3 x 3 arrayed electrochemical micro-chip. The DNA hybridization events are detected using electrochemical impedance spectroscopy (EIS) analysis. The EIS analysis enables monitoring variations of the properties of the electrochemical system that are dominant at these length scales. With the ability to monitor changes of both charge transfer and diffusional resistance with the biosensor, we demonstrate the selectivity to complementary ssDNA targets, a calculated detection limit of 3.8 nM, and a 13% cross-reactivity with other non-complementary ssDNA following 20 min&#160;of incubation. This methodology can improve the performance of miniaturized devices by elucidating on the behavior of diffusion at the micro-scale regime and by enabling the study of DNA hybridization events.

We present a microfluidic-based electrochemical biochip for DNA hybridization detection. Following ssDNA probe functionalization, the specificity, sensitivity, and detection limit are studied with complementary and non-complementary ssDNA targets. Results illustrate the influence of the DNA hybridization events on the electrochemical system, with a detection limit of 3.8 nM.

Miniaturization of analytical benchtop procedures into the micro-scale provides significant advantages in regards to reaction time, cost, and integration ...

A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning of such signaling can lead to many disorders. To understand cell-to-cell signaling, it is essential to study the spatial and temporal nature of the secreted molecules from the cell without disturbing the local environment. Various assays have been developed to study protein secretion, however, these methods are typically based on fluorescent probes which disrupt the relevant signaling pathways. To overcome this limitation, a label-free technique is required.
In this paper, we describe the fabrication and application of a label-free localized surface plasmon resonance imaging (LSPRi) technology capable of detecting protein secretions from a single cell. The plasmonic nanostructures are lithographically patterned onto a standard glass coverslip and can be excited using visible light on commercially available light microscopes. Only a small fraction of the coverslip is covered by the nanostructures and hence this technique is well suited for combining common techniques such as fluorescence and bright-field imaging.
A multidisciplinary approach is used in this protocol which incorporates sensor nanofabrication and subsequent biofunctionalization, binding kinetics characterization of ligand and analyte, the integration of the chip and live cells, and the analysis of the measured signal. As a whole, this technology enables a general label-free approach towards mapping cellular secretions and correlating them with the responses of nearby cells.

Inter-cellular communication is critical for controlling various physiological activities within and outside the cell. This paper describes a protocol for measuring the spatio-temporal nature of single cell secretions. To achieve this, a multidisciplinary approach is used which integrates label-free nanoplasmonic sensing with live cell imaging.

Inter-cellular communication is an integral part of a complex system that helps in maintaining basic cellular activities. As a result, the malfunctioning ...

Label-free Single Molecule Detection Using Microtoroid Optical Resonators

Detecting small concentrations of molecules down to the single molecule limit has impact on areas such as early detection of disease, and fundamental studies on the behavior of molecules. Single molecule detection techniques commonly utilize labels such as fluorescent tags or quantum dots, however, labels are not always available, increase cost and complexity, and can perturb the events being studied. Optical resonators have emerged as a promising means to detect single molecules without the use of labels. Currently the smallest particle detected by a non-plasmonically-enhanced bare optical resonator system in solution is a 25 nm polystyrene sphere1. We have developed a technique known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that can surpass this limit and achieve label-free single molecule detection in aqueous solution2. As signal strength scales with particle volume, our work represents a &#62; 100x improvement in the signal to noise ratio (SNR) over the current state of the art. Here the procedures behind FLOWER are presented in an effort to increase its usage in the field.

We have developed a label-free biosensing system based on optical resonator technology known as Frequency Locking Optical Whispering Evanescent Resonator (FLOWER) that is capable of detecting single molecules in solution. Here the procedures behind this work are described and presented.

Detecting small concentrations of molecules down to the single molecule limit has impact on areas such as early detection of disease, and fundamental ...

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

Biosensors are becoming increasingly important and implemented in various fields such as pathogen detection, molecular diagnosis, environmental monitoring, and food safety control. In this context, we used &#946;-lactamases as efficient reporter enzymes in several protein-protein interaction studies. Furthermore, their ability to accept insertions of peptides or structured proteins/domains strongly encourages the use of these enzymes to generate chimeric proteins. In a recent study, we inserted a single-domain antibody fragment into the Bacillus licheniformis BlaP &#946;-lactamase. These small domains, also called nanobodies, are defined as the antigen-binding domains of single chain antibodies from camelids. Like common double chain antibodies, they show high affinities and specificities for their targets. The resulting chimeric protein exhibited a high affinity against its target while retaining the &#946;-lactamase activity. This suggests that the nanobody and &#946;-lactamase moieties remain functional. In the present work, we report a detailed protocol that combines our hybrid &#946;-lactamase system to the biosensor technology. The specific binding of the nanobody to its target can be detected thanks to a conductimetric measurement of the protons released by the catalytic activity of the enzyme.

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

In this work, we report a new method to study protein-protein interactions using a conductimetric biosensor based on the hybrid &#946;-lactamase technology. This method relies on release of protons upon hydrolysis of &#946;-lactams.

Biosensors are becoming increasingly important and implemented in various fields such as pathogen detection, molecular diagnosis, environmental ...

PIP-on-a-chip: A Label-free Study of Protein-phosphoinositide Interactions

Numerous cellular proteins interact with membrane surfaces to affect essential cellular processes. These interactions can be directed towards a specific lipid component within a membrane, as in the case of phosphoinositides (PIPs), to ensure specific subcellular localization and/or activation. PIPs and cellular PIP-binding domains have been studied extensively to better understand their role in cellular physiology. We applied a pH modulation assay on supported lipid bilayers (SLBs) as a tool to study protein-PIP interactions. In these studies, pH sensitive ortho-Sulforhodamine B conjugated phosphatidylethanolamine is used to detect protein-PIP interactions. Upon binding of a protein to a PIP-containing membrane surface, the interfacial potential is modulated (i.e. change in local pH), shifting the protonation state of the probe. A case study of the successful usage of the pH modulation assay is presented by using phospholipase C delta1 Pleckstrin Homology (PLC-&#948;1 PH) domain and phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) interaction as an example. The apparent dissociation constant (Kd,app) for this interaction was 0.39 &#177; 0.05 &#181;M, similar to Kd,app values obtained by others. As previously observed, the PLC-&#948;1 PH domain is PI(4,5)P2 specific, shows weaker binding towards phosphatidylinositol 4-phosphate, and no binding to pure phosphatidylcholine SLBs. The PIP-on-a-chip assay is advantageous over traditional PIP-binding assays, including but not limited to low sample volume and no ligand/receptor labeling requirements, the ability to test high- and low-affinity membrane interactions with both small and large molecules, and improved signal to noise ratio. Accordingly, the usage of the PIP-on-a-chip approach will facilitate the elucidation of mechanisms of a wide range of membrane interactions. Furthermore, this method could potentially be used in identifying therapeutics that modulate protein&#39;s capacity to interact with membranes.

Here we present a supported lipid bilayer in the context of a microfluidic platform to study protein-phosphoinositide interactions using a label-free method based on pH modulation.

Numerous cellular proteins interact with membrane surfaces to affect essential cellular processes. These interactions can be directed towards a specific ...

Assessing Collagen and Elastin Pressure-dependent Microarchitectures in Live, Human Resistance Arteries by Label-free Fluorescence Microscopy

The pathogenic contribution of resistance artery remodeling is documented in essential hypertension, diabetes and the metabolic syndrome. Investigations and development of microstructurally motivated mathematical models for understanding the mechanical properties of human resistance arteries in health and disease have the potential to aid understanding how disease and medical treatments affect the human microcirculation. To develop these mathematical models, it is essential to decipher the relationship between the mechanical and microarchitectural properties of the microvascular wall. In this work, we describe an ex vivo method for passive mechanical testing and simultaneous label-free three-dimensional imaging of the microarchitecture of elastin and collagen in the arterial wall of isolated human resistance arteries. The imaging protocol can be applied to resistance arteries of any species of interest. Image analyses are described for quantifying i) pressure-induced changes in internal elastic lamina branching angles and adventitial collagen straightness using Fiji and ii) collagen and elastin volume densities determined using Ilastik software. Preferably all mechanical and imaging measurements are performed on live, perfused arteries, however, an alternative approach using standard video-microscopy pressure myography in combination with post-fixation imaging of re-pressurized vessels is discussed. This alternative method provides users with different options for analysis approaches. The inclusion of the mechanical and imaging data in mathematical models of the arterial wall mechanics is discussed, and future development and additions to the protocol are proposed.

We describe simultaneous mechanical testing and 3D-imaging of the arterial wall of isolated, live human resistance arteries, and Fiji and Ilastik image analyses for the quantification of elastin and collagen spatial organization and volume densities. We discuss the use of these data in mathematical models of arterial wall mechanics.

The pathogenic contribution of resistance artery remodeling is documented in essential hypertension, diabetes and the metabolic syndrome. Investigations ...