We thank Barbara Goricnick and Nadja Hinterreiter for their help with cell culturing and preparation of experimental solutions. The authors gratefully acknowledge financial support by the Research Training Group 1910 &#34;Medicinal chemistry of selective GPCR ligands&#34; funded by the German Research Foundation (DFG) under grant number 222125149. JAS is particularly grateful for a scholarship granted by the Bavarian Gender Equality Program.

1. Cell seeding on electrode arrays
NOTE: Selection of electrode layout is a trade-off between sensitivity and number of cells under study. The smaller the electrode, the more sensitive is the measurement but the smaller is the number of cells under study. For cells showing strong impedance fluctuations over time under baseline conditions, bigger or interdigitated electrodes are preferable.
<ol>
	<li>Pre-warm all solutions needed for standard cell passaging and seeding in a 37 &#176;C water bath. For assays with human U-373 MG cells it takes: phosphate buffered saline (PBS) without calcium and magnesium, 0.05% (w/v) trypsin, cell culture medium (Eagle&#39;s Minimum Essential Medium (EMEM) supplemented with 5% (v/v) fetal calf serum (FCS), 2 mM L-glutamine and 100 &#181;g/mL penicillin/streptomycin).</li>
	<li>Rinse the cell layer of the stock culture grown on the bottom of conventional cell culture flasks or dishes with PBS twice.</li>
	<li>Remove the PBS, add the trypsin solution (1 mL for 25 cm2) and let the cells incubate at 37 &#176;C for 5 min (applies to U-373 MG cells).</li>
	<li>Control for complete detachment of the cells from the bottom of the growth substrate by microscopy.</li>
	<li>Stop the trypsin reaction as soon as the cells are completely detached by adding 9 mL of cell culture medium per 1 mL of trypsin to the cell suspension. Carefully rinse remaining cells from the bottom of the cell culture substrate by pipetting the suspension over the substrate.</li>
	<li>Collect the cell suspension with a pipette and transfer it to a centrifugation tube (15 mL or 50 mL tube).</li>
	<li>Spin down the cells by centrifugation at 110 x g for 10 min at room temperature.</li>
	<li>Carefully remove the supernatant and thoroughly re-suspend the cell pellet in culture medium before counting the cells (e.g. by using a hemacytometer for phase contrast microscopes and manual counting).</li>
	<li>Adjust the cell suspension to the desired cell density. For experiments with U-373 MG cells, use 100 000 cells/cm2 to grow a confluent cell layer within 48 h. This translates to a cell density of 200 000 cells/mL for 8-well electrode arrays with a growth area of ~0.8 cm2 and a well volume of 400 &#181;L. 
	NOTE: For reproducible GPCR activation experiments, cells should be grown to confluent monolayers on the electrode arrays. To ensure proper receptor expression on the cell surface, cells should be seeded at least 36 h before performing the experiment. Testing different cell densities for cell seeding is often meaningful to identify the best experimental conditions.</li>
	<li>Add the cell suspension to the wells of the electrode array and let the sells settle down at room temperature for 10 &#8211; 15 min in order to ensure homogenous distribution of cells on the bottom of the wells.</li>
	<li>Grow cells for at least 36 h in a standard cell culture incubator with 5% CO2 (dependent on medium type) at 37 &#176;C and humidified atmosphere. Change cell culture medium 24 h prior to the experiment.</li>
	<li>On the day of the experiment, inspect the cell layers on the electrode arrays by (phase contrast) microscopy to ensure complete coverage of electrodes with cells.</li>
</ol>
2. Equilibration of cells in serum-free medium
<ol>
	<li>Pre-warm serum-free medium, in this study: Leibovitz&#39;s L15 medium.</li>
	<li>Remove cell culture medium from cells grown on electrode arrays and replace by pre-warmed serum-free medium. Use 200 &#181;L for 8-well format electrode arrays, and 150 &#181;L for 96-well electrode arrays.</li>
	<li>Let the cells equilibrate in serum-free medium at 37 &#176;C for at least 2 h. The equilibration time strongly depends on the cell type. For example, U-373 MG cells need 2 h, CHO cells need 4 h, BAEC may require overnight equilibration in L-15 medium. 
	NOTE: L-15 medium is CO2 independent and requires a CO2-free atmosphere. For equilibration in L-15 set the incubator to 0 % CO2. Equilibration can be monitored by impedance readings, which we recommend to do for the first experiments.</li>
</ol>
3. Monitoring cell equilibration with impedance readings
<ol>
	<li>Place the electrode array into the connecting array holder of the impedance analyzer.</li>
	<li>Ensure proper low impedance contact between electrodes and impedance analyzer. This check is individually different for different instruments. 
	NOTE: If the instrument fails to make connection to the electrodes, open the contact clamp again, readjust the electrode array for proper positioning inside the holder and retry.</li>
	<li>Select electrode type and/or multi-well format from the user interface of the software.</li>
	<li>Set up the measurement parameters. Different options are available. 
	NOTE: To select the most sensitive AC frequency, we refer to the literature and instrument manuals as it depends on electrode layout and cell type under study. Typically, the sensing frequency is in the range of 4 kHz &#8211; 50 kHz. Here, U-373 MG cells were grown on circular working electrodes of 250 &#181;m diameter and they were monitored at an AC frequency of 12 kHz.
	<ol>
		<li>If single and multiple frequency data acquisition modes are available, select the single frequency mode to ensure maximum time resolution. The measurement will be performed at this single frequency. For the most widely spread instruments, there is a number of pre-set frequencies along the available frequency window.</li>
		<li>If the number of wells under study is low or time resolution is not critical, select multiple frequency recordings instead. Impedance readings at a specified number of frequencies will be recorded for every well for later in-depth analysis. 
		NOTE: The time resolution decreases with increasing number of frequencies recorded per well and increasing number of wells. The options for frequency and data acquisition mode selection vary with instrument type and version.</li>
	</ol>
	</li>
	<li>Start acquisition of time course data.</li>
	<li>Follow the cell layer impedance (at least 2 h) until the impedance has stabilized. In the meantime, prepare the agonist solutions.</li>
	<li>When the cell layers have reached a stable impedance level, either (i) proceed to the serial agonist addition within the same experiment or (ii) terminate data acquisition and start a new dataset for monitoring agonist-induced receptor activation.</li>
</ol>
4. Preparation of agonist solutions for experiments in agonist mode
<ol>
	<li>Calculate the concentration of agonist solutions as needed for each step of serial dosing according to equation (1). n ranges from 1 to the total number of serial additions i. x denotes concentration and volume in the well at step n. y denotes concentration and volume of the &#34;solution-to-be-added&#34; in step n.</li>
</ol>
<img alt="Equation 1" src="/files/ftp_upload/60686/60686equ01.jpg" />
NOTE: Consider the number of replicates and calculate the total volume of &#34;solution-to-be-added&#34; for each concentration step. Results of a typical calculation are given in Tables 1-4. It takes a general idea about the agonist concentration range to be studied as the range defines the concentrations and number of portions to be administered during serial addition. Using the serial agonist addition protocol the agonist concentration is increased stepwise. Therefore, the amount of agonist already in the well when the next dose is added has to be taken into account. When the number of agonist molecules already present in the well is nx = cx &#8729;Vx (with the current concentration cx and volume Vx) and the number of molecules in the well after the next addition is nx+y, the number of molecules to be added ny is determined by the concentration cy and volume Vy of the solution to be applied to the well (ny = cy &#8729; Vy). After adding a portion of agonist, the new amount of agonist molecules in the well is: cx+y &#8729; Vx+y = cx &#8729; Vx + cy &#8729; Vy. This calculation applies for each subsequent step. Because of the interdependence of agonist concentration in the well and the amount of agonist in the portions to be added with each step, it is important to define final concentrations after each step in advance.
Mode 1: The volume in the well will increase with each step as liquid is continuously added. 
Using this mode and an 8-well format, use Vx1 = 200 &#181;L and Vy1 &#8230;. Vyi = 30 &#181;L.
Mode 2: The volume in the well is constant as the volume added with each step is removed just before the subsequent addition. 
Using this mode and a 96-well format, use Vx1 = 150 &#181;L and Vy1 &#8230;. Vyi = 75 &#181;L.
<ol start="2">
	<li>Print the data sheet with the total volume per concentration and detailed instructions for pipetting.</li>
	<li>Prepare all solutions in the required amount. Make all agonist solutions in the same serum-free medium as used for equilibration of the cells. 
	CAUTION: Histamine dihydrochloride is considered hazardous by the 2012 OSHA Hazard Communication Standard (29 CFR 1910.1200). Histamine causes skin irritation, serious eye irritation, may cause an allergic skin reaction, allergy, asthma symptoms or breathing difficulties if inhaled and may cause respiratory irritation. Please consider the safety data sheet. 
	NOTE: Make agonist solutions as fresh as possible. Stability of agonists in solution may vary considerably. Store solutions at 4 &#176;C or below until use in the experiment. For some molecules additional stabilizing additives, like BSA when using peptide-based or lipid-based molecules, may be considered to prevent adsorption to the walls of wells and tubes.</li>
	<li>If performing the experiment in 96-well format, transfer solutions to a conventional 96-well plate (no electrodes) and use an 8- (or 12-) channel pipet for quick liquid transfer to the electrode array.</li>
</ol>
5. Preparation of agonist solutions for experiment in antagonist mode
NOTE: Prepare the antagonist solution(s) with the concentration to be applied throughout. Volume and concentration of antagonist solution depend on the mode of agonist addition (1 or 2). Examples for experiments in 8-well or 96-well format in addition mode 2: (A) 8-well format (Vx1 = 200 &#181;L, VAntagonist = 200 &#181;L); (B) 96-well format (Vx1 = 150 &#181;L, VAntagonist = 75 &#181;L).
<ol>
	<li>Calculate the concentration of each agonist solution needed for each step of serial dosing as described in step 4.1.</li>
	<li>Make all agonist solutions in the same serum-free medium as used for equilibration of the cells and add the antagonist at the same final concentration as planned for the respective wells in the experiment. 
	NOTE: In this case the histamine stock solution (10 mM) is prepared in L-15 medium. When agonists are dissolved in other solvents (e.g., dimethyl sulfoxid (DMSO), ethanol) a solvent control should be included to account for the increasing solvent load with each step of addition.</li>
</ol>
6. Performing the serial addition protocol in agonist mode
<ol>
	<li>Start data acquisition as described in steps 3.1 &#8211; 3.5.</li>
	<li>Pre-warm the agonist solutions prior to use by placing them in the incubator about 10 &#8211; 15 min before addition. 
	NOTE: When using thermo-labile substances, the solutions should not be kept at 37 &#176;C for too long. If pre-warming for 10 &#8211; 15 min is considered critical, bring solutions to 37 &#176;C shortly before addition in a water bath.</li>
	<li>Run the agonist serial dosing dependent on the selected addition mode. Following mode 1 the total volume in the well increases with each addition of the next dose. In mode 2 the same volume which is added with each step is also removed again just before adding the next higher dose. 
	NOTE: Time needed for equilibration of the cell layer in between two subsequent agonist doses depends on the cells&#39; response time. An initial experiment in parallel mode (one well &#8211; one concentration) reveals (i) cell response times for different agonist concentrations and (ii) the most sensitive curve parameter (e.g., impedance maximum, impedance after time x).</li>
</ol>
A: Mode 1 / 8-well format
<ol>
	<li>Add 30 &#181;L of the first solution with the lowest concentration of agonist to the cells that were equilibrated in 200 &#181;L of serum-free medium.</li>
	<li>Let the cells respond and equilibrate for the pre-defined period of time (e.g., 15 min).</li>
	<li>Add 30 &#181;L of the second solution with the next higher concentration.</li>
	<li>Repeat steps 6.3.1-6.3.3 with the third, fourth, and so on, agonist solution. 
	NOTE: Working with 10 concentration steps will result in a total volume of 500 &#181;L in the end of the experiment, which is just below the maximum applicable volume of these wells of ~ 550 &#181;L.</li>
</ol>
B: Mode 2 / 96-well format
NOTE: Pause data acquisition during each liquid handling step (addition/removal) via the impedance instrument&#39;s software when running experiments in 96-well format. The more elaborate liquid handling may interfere with data acquisition. Use a multi-channel pipette.
<ol>
	<li>Pause data acquisition.</li>
	<li>Add 75 &#181;L of the first solution with the lowest concentration of agonist to the cells that were equilibrated in 150 &#181;L of serum-free medium.</li>
	<li>Resume data acquisition.</li>
	<li>Let the cells respond and equilibrate for the pre-defined period of time (e.g., 15 min).</li>
	<li>About 1 &#8211; 2 min before the regular equilibration time ends, pause the measurement and remove 75 &#181;L from each well. 
	NOTE: The time point at which solution should be removed depends on the number of wells monitored in parallel and the pipetting speed. Time needed for removal of the solutions should not exceed the time between subsequent steps.</li>
	<li>Add 75 &#181;L of the second solution with the next higher concentration and resume the measurement.</li>
	<li>Repeat steps 6.3.8-6.3.10 with the third, fourth, and so on, agonist solution.</li>
</ol>
7. Performing the serial addition protocol in antagonist mode
<ol>
	<li>Start the measurement as described in steps 3.1 &#8211; 3.5.</li>
	<li>During equilibration of the cell layers, prepare antagonist solution (e.g., 200 &#181;L of 1.5 &#181;M diphenhydramine hydrochloride in L15 medium). 
	CAUTION: Diphenhydramine hydrochloride has potential acute health effects. It is harmful if swallowed or inhaled, may cause eye and skin irritation. It may cause respiratory and digestive tract irritation. Please consider the safety data sheet.</li>
	<li>Pre-warm the antagonist and agonist solutions by placing them in the incubator about 10 &#8211; 15 min before addition to the cell cultures (cf. 6.2). If antagonist-free wells are included in the assay as well, also pre-warm serum-free medium.</li>
	<li>Add the antagonist solution to the designated wells. Let the cells equilibrate with antagonist for 15 &#8211; 20 min. If antagonist-free wells are included, add the same volume of serum-free medium to these wells.</li>
	<li>According to antagonist addition in mode 2, remove solution from the wells 
	(A) 8-well format (200 &#181;L) 
	(B) 96-well format (75 &#181;L)</li>
	<li>Run the agonist addition sequence as described in step 6.3.</li>
</ol>
8. Data export and analysis
<ol>
	<li>Export data using the impedance instrument&#39;s software in order to convert all recorded data from proprietary into common data formats (e.g., csv). This step allows for data re-organization and presentation with other software packages.</li>
	<li>Load the csv-formatted data to scientific data analysis software.</li>
	<li>Normalize impedance values by subtracting the impedance of the last data point before the first addition of agonist solution and by setting the time of addition to t = 0. Plot the time course of normalized impedance.</li>
	<li>Plot the individual time courses and identify the maxima in impedance after each addition step. Compose a data sheet with these values.</li>
	<li>Plot the values of maximum (or minimum, if applicable) impedance changes as a function of agonist concentration. This can be done for individual wells or for the averages (mean &#177; SD).</li>
	<li>Use a data fitting routine to determine half-maximal effective concentrations (EC50) and maximum response (EMax) by using the four parameter logistic model (equation 2):</li>
</ol>
<img alt="Equation 2" src="/files/ftp_upload/60686/60686equ02.jpg" />
NOTE: c indicates the agonist concentration, A1 is the minimum and A2 is the maximum asymptote of the sigmoidal dose-response curve (A2 = EMax). EC50 is the concentration at the inflection point of the curve, and n corresponds to the Hill slope.

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	<li>Rosenbaum, D. M., Rasmussen, S. G., Kobilka, B. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+structure+and+function+of+G-protein-coupled+receptors.">The structure and function of G-protein-coupled receptors.</a> Nature. 459, 356-363 (2009).</li><li>Sriram, K., Insel, P. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=G+Protein-Coupled+Receptors+as+Targets+for+Approved+Drugs:+How+Many+Targets+and+How+Many+Drugs.">G Protein-Coupled Receptors as Targets for Approved Drugs: How Many Targets and How Many Drugs.</a> Molecular Pharmacology. 93, 251-258 (2018).</li><li>Kaitin, K. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Deconstructing+the+drug+development+process:+The+new+face+of+innovation.">Deconstructing the drug development process: The new face of innovation.</a> Clinical Pharmacoly and Therapeutics. 87, 6 (2010).</li><li>Kenakin, T. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cellular+assays+as+portals+to+seven-transmembrane+receptor-based+drug+discovery.">Cellular assays as portals to seven-transmembrane receptor-based drug discovery.</a> Nature reviews. Drug discovery. 8, 617-626 (2009).</li><li>Zhang, R., Xie, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tools+for+GPCR+drug+discovery.">Tools for GPCR drug discovery.</a> Acta Pharmacologica Sinica. 33, 372-384 (2012).</li><li>Scott, C. W., Peters, M. F. <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+whole-cell+assays:+expanding+the+scope+of+GPCR+screening.">Label-free whole-cell assays: expanding the scope of GPCR screening.</a> Drug Discovery Today. 15, 704-716 (2010).</li><li>Giaever, I., Keese, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+fibroblast+behavior+in+tissue+culture+with+an+applied+electric+field.">Monitoring fibroblast behavior in tissue culture with an applied electric field.</a> Proceedings of the National Academy of Sciences of the United States of America. 81, 3761-3764 (1984).</li><li>Giaever, I., Keese, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+morphological+biosensor+for+mammalian+cells.">A morphological biosensor for mammalian cells.</a> Nature. 366, 591-592 (1993).</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> Biophysical Journal. 91, 16 (2006).</li><li>Stolwijk, J. A., Matrougui, K., Renken, C. W., Trebak, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impedance+analysis+of+GPCR-mediated+changes+in+endothelial+barrier+function:+overview+and+fundamental+considerations+for+stable+and+reproducible+measurements.">Impedance analysis of GPCR-mediated changes in endothelial barrier function: overview and fundamental considerations for stable and reproducible measurements.</a> Pflugers Archiv : European Journal of Physiology. 467, 2193-2218 (2015).</li><li>Lieb, S., 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+versus+conventional+cellular+assays:+Functional+investigations+on+the+human+histamine+H1+receptor.">Label-free versus conventional cellular assays: Functional investigations on the human histamine H1 receptor.</a> Pharmacological Research. 114, 13-26 (2016).</li><li>Stolwijk, J. A., 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=Increasing+the+throughput+of+label-free+cell+assays+to+study+the+activation+of+G-protein-coupled+receptors+by+using+a+serial+agonist+exposure+protocol.">Increasing the throughput of label-free cell assays to study the activation of G-protein-coupled receptors by using a serial agonist exposure protocol.</a> Integrative Biology. 11, 10 (2019).</li></ol>

The authors have nothing to disclose.

This protocol describes a method for label-free impedance measurements to determine the dose-response relationship of agonist-induced GPCR activation in absence or presence of specific antagonists for the same receptor. The proof of concept of this method was presented in a recent publication12. To our knowledge it is the first study describing the establishment of a full dose-response curve of agonist-mediated GPCR activation using a single cell layer in vitro. The approach inevitably requires th...

This report presents a detailed description of a serial addition protocol developed for the quantification of ligand-induced G protein-coupled receptor (GPCR) activation in adherently grown cells by label-free impedance measurements. G protein-coupled receptors (GPCRs) are involved in a multitude of physiological functions and human diseases1. Because of this and their good accessibility at the cell surface, GPCRs are one of the most important drug targets. This assessment is reflected in an estimated number of ~700 approved drugs targeting GPCRs, equivalent to a ~35% share on all marketed drugs2.
The development of new drugs comprises two central processes: (i) the identification and functional characterization of biological target molecules, and (ii) the discovery of new lead substances and their development into administrable drugs. In both processes, efficient methods are required to quantitatively evaluate drug-target interactions and the subsequent biological downstream response. Different stages of the pre-clinical drug development process make use of different methods of analysis ranging from biomolecular interaction studies between drug and target, over functional studies on cells in culture, to experiments on excised organ material or whole animals. Both, physiological significance and biological complexity increase from the former to the latter3. Although it is the overall goal to minimize animal experiments, pharmacological studies using isolated organs from laboratory animals or even whole animals are regarded inevitable to comprehensively characterize new drug candidates. In terms of analytical readout, organ pharmacology studies provide a distal, integrative &#34;holistic&#34; functional response of highest physiological relevance. A drawback of such experiments is that they are not compatible with high throughput screening for technical as well as ethical reasons and have been largely substituted by studies based on in vitro cell culture4.
Methods to quantify GPCR activation in cell cultures include different label-based chemical assays, which specifically detect second messengers, phosphorylation state of downstream signaling proteins, transcriptional activation via certain transcription factors or ligand-induced intracellular receptor trafficking4,5. A drawback of such label-based assays is the necessity to label the cells with potentially harmful dyes or radioactive markers. This often requires running the assay as an endpoint-determination for an exposure time that has to be specified a priori. Using label-based endpoint assays suffers from this very limited and biased timing of the experiment and the risk that chemical labels and probes may interfere with the regular cell physiology &#8211; potentially unnoticed by the experimenter.
In recent years, label-free assays for monitoring GPCR activation have emerged, like impedance-based techniques or optical methods applying resonant waveguide gratings5,6. Labelling of the cells is experimentally not required with these approaches. As these physical readouts operate on low amplitude signals, such methods are considered non-invasive, they allow for continuous cell monitoring potentially in real time and the observation time is only limited by the cell culture not by the readout. Similar to readouts from whole organs, label-free approaches commonly report on holistic cell responses, far downstream of receptor activation when integration along the entire signaling network leads to time-dependent but rather unspecific changes in cell morphology or mass redistribution. Whereas impedance-based assays measure the dielectric signature of changes in cell shape7,8, measurements using resonant waveguide gratings are sensitive to changes in refractive index at the cell-substrate interface arising from dynamic mass redistribution (DMR)9. The integrative character makes label-free methods extremely sensitive to receptor-mediated events regardless of the type(s) of G protein (Gq, Gi/0, Gs, G12/13) or &#946;-arrestin involved in the signaling cascade6 and well-suited for endogenous expression levels of the receptor.
In a standard label-free impedance-based assay the cells are adherently grown in multi-well plates with coplanar gold-film electrodes deposited on the bottom of each well10. These electrode arrays are connected to an impedance analyzer and the cell responses to an experimental stimulus are recorded from individual wells by time-resolved impedance readings. In a typical GPCR assay a ligand is added in individually different concentrations to each individual well. The ligand-induced changes in the impedance time course are then analyzed with respect to characteristic curve features such as maximum signal change, area under the curve, signal change within a given time interval or slope of the curve at a specified time point, in order to quantify the ligand&#39;s potency and efficacy11.
The cost of the electrode arrays may limit the application of this technique in high throughput screening (HTS) campaigns. Moreover, with increasing numbers of samples to be followed in parallel, the number of individual measurements increases and thereby reduces the available time resolution for each well gradually - even for state of the art multichannel recordings. Under such conditions fast and transient cell responses may escape the measurement. In addition, the conventional one well &#8211; one concentration approach imposes a significant time and cost factor on perfused organ-on-chip or body-on-chip developments with respect to their suitability in ligand-GPCR interaction analysis.
For this reason, we developed a stepwise dosing protocol that enables recording of full dose-response curves of ligand-induced GPCR activation in cultured cell monolayers by continuously monitoring the impedance of a single well while the agonist concentration is increased stepwise. The serial agonist addition protocol significantly increases throughput per well from one concentration to 10 or more concentrations, as shown on the current example of human U-373 MG cells, which endogenously express the histamine 1 receptor (H1R). Thus, the method has the potential to significantly improve throughput in label-free dose-response studies, while the time resolution is retained at the instrumental maximum.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>B&#252;rker counting chamber</td>
			<td>Marienfeld (Lauda-K&#246;nigshofen, Germany)</td>
			<td>640210</td>
			<td></td>
		</tr>
		<tr>
			<td>cell culture flasks 25 cm2</td>
			<td>Greiner bio-one (Frickenhausen, Germany)</td>
			<td>690175</td>
			<td></td>
		</tr>
		<tr>
			<td>Cell incubator (Heraeus Function Line BB15)</td>
			<td>Thermo Scientific (Darmstadt, Germany)</td>
			<td>\</td>
			<td></td>
		</tr>
		<tr>
			<td>Centrifuge (Heraeus 1S-R)</td>
			<td>Thermo Scientific (Darmstadt, Germany)</td>
			<td>\</td>
			<td></td>
		</tr>
		<tr>
			<td>Diphenhydramine hydrochloride</td>
			<td>Sigma Aldrich (Taufkirchen, Germany)</td>
			<td>D3630</td>
			<td></td>
		</tr>
		<tr>
			<td>Eagle&#39;s Minimum Essential Medium with 4.5 g/L D-Glucose and 2.2 g/L NaHCO3</td>
			<td>Sigma Aldrich (Taufkirchen, Germany)</td>
			<td>D5671</td>
			<td></td>
		</tr>
		<tr>
			<td>Impedance Instrument (ECIS Z&#952;)</td>
			<td>Applied BioPhysics Inc. (Troy, NY, USA)</td>
			<td>\</td>
			<td></td>
		</tr>
		<tr>
			<td>8-well electrode Arrays (8W1E PET)</td>
			<td>Applied BioPhysics Inc. (Troy, NY, USA)</td>
			<td>\</td>
			<td>PET base with 0.049 mm2 working electrode and ~50 mm2 counter electrode (gold)</td>
		</tr>
		<tr>
			<td>96-well electrode arrays (96W1E+ PET)</td>
			<td>Applied BioPhysics Inc. (Troy, NY, USA)</td>
			<td>\</td>
			<td>PET base with two electrodes (gold) with 0.256 mm2 total electrode area</td>
		</tr>
		<tr>
			<td>Fetal calf serum (FCS)</td>
			<td>Biochrom (Berlin, Germany)</td>
			<td>S0615</td>
			<td></td>
		</tr>
		<tr>
			<td>Histamine dihydrochloride</td>
			<td>Carl Roth (Karlsruhe, Germany)</td>
			<td>4017.1</td>
			<td></td>
		</tr>
		<tr>
			<td>Laminar flow hood (Herasafe, KS 12)</td>
			<td>Thermo Scientific (Darmstadt, Germany)</td>
			<td>51022515</td>
			<td>class II safety cabinet</td>
		</tr>
		<tr>
			<td>Leibovitz&#39; L-15 medium</td>
			<td>Thermo Scientific (Darmstadt, Germany)</td>
			<td>21083-027</td>
			<td></td>
		</tr>
		<tr>
			<td>L-glutamine</td>
			<td>Sigma Aldrich (Taufkirchen, Germany)</td>
			<td>G7513</td>
			<td></td>
		</tr>
		<tr>
			<td>Micropipette large (100 - 1000 &#181;L)</td>
			<td>Brandt (Wertheim, Germany)</td>
			<td>704780</td>
			<td></td>
		</tr>
		<tr>
			<td>Micropipette large (20 - 200 &#181;L)</td>
			<td>Brandt (Wertheim, Germany)</td>
			<td>704778</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope (phase contrast, Nikon Diaphot)</td>
			<td>Nikon (D&#252;sseldorf, Germany)</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Penicillin/streptomycin</td>
			<td>Sigma Aldrich (Taufkirchen, Germany)</td>
			<td>P0781</td>
			<td></td>
		</tr>
		<tr>
			<td>Phosphate buffered saline (PBS)</td>
			<td>Sigma Aldrich (Taufkirchen, Germany)</td>
			<td>D8537</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipette, serological</td>
			<td>Greiner bio-one (Frickenhausen, Germany)</td>
			<td>607 180</td>
			<td></td>
		</tr>
		<tr>
			<td>Pipettor (accu-jet pro)</td>
			<td>Brandt (Wertheim, Germany)</td>
			<td>26300</td>
			<td></td>
		</tr>
		<tr>
			<td>Trypsin</td>
			<td>Sigma Aldrich (Taufkirchen, Germany)</td>
			<td>T4174</td>
			<td>in PBS with 1 mM EDTA</td>
		</tr>
		<tr>
			<td>Tube, 15 mL</td>
			<td>Greiner bio-one (Frickenhausen, Germany)</td>
			<td>188 271</td>
			<td></td>
		</tr>
		<tr>
			<td>Tube, 50 mL</td>
			<td>Greiner bio-one (Frickenhausen, Germany)</td>
			<td>210 261</td>
			<td></td>
		</tr>
		<tr>
			<td>U-373 MG cells</td>
			<td>ATCC (Rockville, MD, USA)</td>
			<td>ATCC HTB-17</td>
			<td></td>
		</tr>
		<tr>
			<td>water bath (TW21)</td>
			<td>Julabo (Seelbach, Germany)</td>
			<td>\</td>
			<td></td>
		</tr>
	</tbody>
</table>

stepwise dosing protocol for increased throughput in label-free impedance-based gpcr assays

Label-free impedance-based assays are increasingly used to non-invasively study ligand-induced GPCR activation in cell culture experiments. The approach provides real-time cell monitoring with a device-dependent time resolution down to several tens of milliseconds and it is highly automated. However, when sample numbers get high (e.g., dose-response studies for various different ligands), the cost for the disposable electrode arrays as well as the available time resolution for sequential well-by-well recordings may become limiting. Therefore, we here present a serial agonist addition protocol which has the potential to significantly increase the output of label-free GPCR assays. Using the serial agonist addition protocol, a GPCR agonist is added sequentially in increasing concentrations to a single cell layer while continuously monitoring the sample&#39;s impedance (agonist mode). With this serial approach, it is now possible to establish a full dose-response curve for a GPCR agonist from just one single cell layer. The serial agonist addition protocol is applicable to different GPCR coupling types, Gq Gi/0 or Gs and it is compatible with recombinant and endogenous expression levels of the receptor under study. Receptor blocking by GPCR antagonists is assessable as well (antagonist mode).

A typical scheme for preparing the various agonist solutions is shown for an experiment using 8-well electrode arrays with histamine as agonist in Tables 1-4. Table 1 and Table 2 present volumes and concentrations for an experiment using addition mode 1 (cf., Figure 1), while Table 3 and Table 4 present volumes and concentrations for an experiment following addition mode 2 (...

Watch this Scientific Journal Video about Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays at JoVE.com

Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays

This protocol demonstrates real-time recording of full dose-response relationships for agonist-induced GPCR activation from a single cell layer grown on a single microelectrode using label-free impedance measurements. The new dosing scheme significantly increases throughput without loss in time resolution.

Label-free impedance-based assays are increasingly used to non-invasively study ligand-induced GPCR activation in cell culture experiments. The approach ...

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6.5K Views.  University of Regensburg. This protocol demonstrates real-time recording of full dose-response relationships for agonist-induced GPCR activation from a single cell layer grown on a single microelectrode using label-free impedance measurements. The new dosing scheme significantly increases throughput without loss in time resolution.

Video: Stepwise Dosing Protocol for Increased Throughput in Label-Free Impedance-Based GPCR Assays

A Simple Method for High Throughput Chemical Screening in Caenorhabditis Elegans

Caenorhabditis elegans is a useful organism for testing chemical effects on physiology. Whole organism small molecule screens offer significant advantages for identifying biologically active chemical structures that can modify complex phenotypes such as lifespan. Described here is a simple protocol for producing hundreds of 96-well culture plates with fairly consistent numbers of C. elegans in each well. Next, we specified how to use these cultures to screen thousands of chemicals for effects on the lifespan of the nematode C. elegans. This protocol makes use of temperature sensitive sterile strains, agar plate conditions, and simple animal handling to facilitate the rapid and high throughput production of synchronized animal cultures for screening.

A Simple Method for High Throughput Chemical Screening in Caenorhabditis Elegans

Here we describe a simple protocol for rapidly producing hundreds of nematode growth media agar, 96-well culture plates with consistent numbers of Caenorhhabditis elegans per well. These cultures are useful for the phenotypic screening of whole organisms. We focus here on using these cultures to screen chemicals for pro-longevity effects.

Caenorhabditis elegans is a useful organism for testing chemical effects on physiology. Whole organism small molecule screens offer significant advantages ...

Monitoring GPCR-&#946;-arrestin1/2 Interactions in Real Time Living Systems to Accelerate Drug Discovery

Interactions between G-protein coupled receptors (GPCRs) and &#946;-arrestins are vital processes with physiological implications of great importance. Currently, the characterization of novel drugs towards their interactions with &#946;-arrestins and other cytosolic proteins is extremely valuable in the field of GPCR drug discovery particularly during the study of GPCR biased agonism. Here, we show the application of a novel structural complementation assay to accurately monitor receptor-&#946;-arrestin interactions in real time living systems. This method is simple, accurate and can be easily extended to any GPCR of interest and also it has the advantage that it overcomes unspecific interactions due to the presence of a low expression promoter present in each vector system. This structural complementation assay provides key features that allow an accurate and precise monitoring of receptor-&#946;-arrestin interactions, making it suitable in the study of biased agonism of any GPCR system as well as GPCR c-terminus &#8216;phosphorylation codes&#8217; written by different GPCR-kinases (GRKs) and post-translational modifications of arrestins that stabilize or destabilize the receptor-&#946;-arrestin complex.

GPCR-&#946;-arrestin interactions are an emerging field in GPCR drug discovery. Accurate, precise and easy to set up methods are necessary to monitor such interactions in living systems. We show a structural complementation assay to monitor GPCR-&#946;-arrestin interactions in real time living cells, and it can be extended to any GPCR.

Interactions between G-protein coupled receptors (GPCRs) and &#946;-arrestins are vital processes with physiological implications of great importance. ...

Label-Free Immunoprecipitation Mass Spectrometry Workflow for Large-scale Nuclear Interactome Profiling

Immunoaffinity purification mass spectrometry (IP-MS) has emerged as a robust quantitative method of identifying protein-protein interactions. This publication presents a complete interaction proteomics workflow designed for identifying low abundance protein-protein interactions from the nucleus that could also be applied to other subcellular compartments. This workflow includes subcellular fractionation, immunoprecipitation, sample preparation, offline cleanup, single-shot label-free mass spectrometry, and downstream computational analysis and data visualization. Our protocol is optimized for detecting compartmentalized, low abundance interactions that are difficult to identify from whole cell lysates (e.g., transcription factor interactions in the nucleus) by immunoprecipitation of endogenous proteins from fractionated subcellular compartments. The sample preparation pipeline outlined here provides detailed instructions for the preparation of HeLa cell nuclear extract, immunoaffinity purification of endogenous bait protein, and quantitative mass spectrometry analysis. We also discuss methodological considerations for performing large-scale immunoprecipitation in mass spectrometry-based interaction profiling experiments and provide guidelines for evaluating data quality to distinguish true positive protein interactions from nonspecific interactions. This approach is demonstrated here by investigating the nuclear interactome of the CMGC kinase, DYRK1A, a low abundance protein kinase with poorly defined interactions within the nucleus.

Described is a proteomics workflow for identifying protein interaction partners from a nuclear subcellular fraction using immunoaffinity enrichment of a given protein of interest and label-free mass spectrometry. The workflow includes subcellular fractionation, immunoprecipitation, filter aided sample preparation, offline cleanup, mass spectrometry, and a downstream bioinformatics pipeline.

Immunoaffinity purification mass spectrometry (IP-MS) has emerged as a robust quantitative method of identifying protein-protein interactions. This ...

A Rapidly Incremented Tethered-Swimming Maximal Protocol for Cardiorespiratory Assessment of Swimmers

Incremental exercise testing is the standard means of assessing cardiorespiratory capacity of endurance athletes. While the maximal rate of oxygen consumption is typically used as the criterion measurement in this regard, two metabolic breakpoints that reflect changes in the dynamics of lactate production/consumption as the work rate is increased are perhaps more relevant for endurance athletes from a functional standpoint. Exercise economy, which represents the rate of oxygen consumption relative to performance of submaximal work, is also an important parameter to measure for endurance-athlete assessment. Ramp incremental tests comprising a gradual but rapid increase in work rate until the limit of exercise tolerance is reached are useful for determining these parameters. This type of test is typically performed on a cycle ergometer or treadmill because there is a need for precision with respect to work-rate incrementation. However, athletes should be tested while performing the mode of exercise required for their sport. Consequently, swimmers are typically assessed during free-swimming incremental tests where such precision is difficult to achieve. We have recently suggested that stationary swimming against a load that is progressively increased (incremental tethered swimming) can serve as a &#34;swim ergometer&#34; by allowing sufficient precision to accommodate a gradual but rapid loading pattern that reveals the aforementioned metabolic breakpoints and exercise economy. However, the degree to which the peak rate of oxygen consumption achieved during such a protocol approximates the maximal rate that is measured during free swimming remains to be determined. In the present article, we explain how this rapidly incremented tethered-swimming protocol can be employed to assess the cardiorespiratory capacity of a swimmer. Specifically, we explain how assessment of a short-distance competitive swimmer using this protocol revealed that his rate of oxygen uptake was 30.3 and 34.8 mL&#8729;min-1&#8729;kg-1BM at his gas-exchange threshold and respiratory compensation point, respectively.

As opposed to measurement during free swimming, which presents inherent challenges and limitations, determination of important parameters of cardiorespiratory function for swimmers can be made using a more feasible and easier to administer tethered-swimming rapidly incremented protocol with gas exchange and ventilatory data collection.

Incremental exercise testing is the standard means of assessing cardiorespiratory capacity of endurance athletes. While the maximal rate of oxygen ...

Creating Highly Specific Chemically Induced Protein Dimerization Systems by Stepwise Phage Selection of a Combinatorial Single-Domain Antibody Library

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the dissection and manipulation of biological pathways. Currently, only a limited number of chemically induced dimerization (CID) systems exist and engineering new ones with desired sensitivity and selectivity for specific small-molecule ligands remains a challenge in the field of protein engineering. We here describe a high throughput screening method, combinatorial binders-enabled selection of CID (COMBINES-CID), for the de novo engineering of CID systems applicable to a large variety of ligands. This method uses the two-step selection of a phage-displayed combinatorial nanobody library to obtain 1) &#34;anchor binders&#34; that first bind to a ligand of interest and then 2) &#34;dimerization binders&#34; that only bind to anchor binder-ligand complexes. To select anchor binders, a combinatorial library of over 109 complementarity-determining region (CDR)-randomized nanobodies is screened with a biotinylated ligand and hits are validated with the unlabeled ligand by bio-layer interferometry (BLI). To obtain dimerization binders, the nanobody library is screened with anchor binder-ligand complexes as targets for positive screening and the unbound anchor binders for negative screening. COMBINES-CID is broadly applicable to select CID binders with other immunoglobulin, non-immunoglobulin, or computationally designed scaffolds to create biosensors for in vitro and in vivo detection of drugs, metabolites, signaling molecules, etc.

Creating chemically induced protein dimerization systems with desired affinity and specificity for any given small molecule ligand would have many biological sensing and actuation applications. Here, we describe an efficient, generalizable method for de novo engineering of chemically induced dimerization systems via the stepwise selection of a phage-displayed combinatorial single-domain antibody library.

Protein dimerization events that occur only in the presence of a small-molecule ligand enable the development of small-molecule biosensors for the ...

Strategic Screening and Characterization of the Visual GPCR-mini-G Protein Signaling Complex for Successful Crystallization

The key to determining crystal structures of membrane protein complexes is the quality of the sample prior to crystallization. In particular, the choice of detergent is critical, because it affects both the stability and monodispersity of the complex. We recently determined the crystal structure of an active state of bovine rhodopsin coupled to an engineered G protein, mini-Go, at 3.1 &#197; resolution. Here, we detail the procedure for optimizing the preparation of the rhodopsin&#8211;mini-Go complex. Dark-state rhodopsin was prepared in classical and neopentyl glycol (NPG) detergents, followed by complex formation with mini-Go under light exposure. The stability of the rhodopsin was assessed by ultraviolet-visible (UV-VIS) spectroscopy, which monitors the reconstitution into rhodopsin of the light-sensitive ligand, 9-cis retinal. Automated size-exclusion chromatography (SEC) was used to characterize the monodispersity of rhodopsin and the rhodopsin&#8211;mini-Go complex. SDS-polyacrylamide electrophoresis (SDS-PAGE) confirmed the formation of the complex by identifying a 1:1 molar ratio between rhodopsin and mini-Go after staining the gel with Coomassie blue. After cross-validating all this analytical data, we eliminated unsuitable detergents and continued with the best candidate detergent for large-scale preparation and crystallization. An additional problem arose from the heterogeneity of N-glycosylation. Heterologously-expressed rhodopsin was observed on SDS-PAGE to have two different N-glycosylated populations, which would probably have hindered crystallogenesis. Therefore, different deglycosylation enzymes were tested, and endoglycosidase F1 (EndoF1) produced rhodopsin with a single species of N-glycosylation. With this strategic pipeline for characterizing protein quality, preparation of the rhodopsin&#8211;mini-Go complex was optimized to deliver the crystal structure. This was only the third crystal structure of a GPCR&#8211;G protein signaling complex. This approach can also be generalized for other membrane proteins and their complexes to facilitate sample preparation and structure determination.

This report describes screening of different detergents for preparing the visual GPCR, rhodopsin, and its complex with mini-Go. Biochemical methods characterizing the quality of the complex at different stages during purification are demonstrated. This protocol can be generalized to other membrane protein complexes for their future structural studies.

The key to determining crystal structures of membrane protein complexes is the quality of the sample prior to crystallization. In particular, the choice ...

Parallel Interrogation of &#946;-Arrestin2 Recruitment for Ligand Screening on a GPCR-Wide Scale using PRESTO-Tango Assay

As the largest and most versatile gene superfamily and mediators of a gamut of cellular signaling pathways, G-protein-coupled receptors (GPCRs) represent one of the most promising targets for the pharmaceutical industry. Ergo, the design, implementation, and optimization of GPCR ligand screening assays is crucial, as they represent remote-control tools for drug discovery and for manipulating GPCR pharmacology and outcomes. In the past, G-protein dependent assays typified this area of research, detecting ligand-induced events and quantifying the generation of secondary messengers. However, since the advent of functional selectivity, as well as an increased awareness of several other G protein-independent pathways and the limitations associated with G-protein dependent assays, there is a greater push towards the creation of alternative GPCR ligand screening assays. Towards this endeavor, we describe the application of one such resource, the PRESTO-Tango platform, a luciferase reporter-based system that enables the parallel and simultaneous interrogation of the human GPCR-ome, a feat which was previously considered technically and economically unfeasible. Based on a G-protein independent &#946;-arrestin2 recruitment assay, the universality of &#946;-arrestin2-mediated trafficking and signaling at GPCRs makes PRESTO-TANGO an apt tool for studying approximately 300 non-olfactory human GPCRs, including approximately 100 orphan receptors. PRESTO-Tango&#39;s sensitivity and robustness make it suitable for primary high-throughput screens using compound libraries, employed to uncover new GPCR targets for known drugs or to discover new ligands for orphan receptors.

Given that GPCRs are attractive druggable targets, GPCR ligand screening is thus indispensable for the identification of lead compounds and for deorphanization studies. Towards these efforts, we describe PRESTO-Tango, an open-source resource platform used for simultaneous profiling of transient &#946;-arrestin2 recruitment at approximately 300 GPCRs using a TEV-based reporter assay.

As the largest and most versatile gene superfamily and mediators of a gamut of cellular signaling pathways, G-protein-coupled receptors (GPCRs) represent ...

High-Throughput Screening for Protein Crystallization

High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography

X-ray crystallography is the most commonly employed technique to discern macromolecular structures, but the crucial step of crystallizing a protein into an ordered lattice amenable to diffraction remains challenging. The crystallization of biomolecules is largely experimentally defined, and this process can be labor-intensive and prohibitive to researchers at resource-limited institutions. At the National High-Throughput Crystallization (HTX) Center, highly reproducible methods have been implemented to facilitate crystal growth, including an automated high-throughput 1,536-well microbatch-under-oil plate setup designed to sample a wide breadth of crystallization parameters. Plates are monitored using state-of-the-art imaging modalities over the course of 6 weeks to provide insight into crystal growth, as well as to accurately distinguish valuable crystal hits. Furthermore, the implementation of a trained artificial intelligence scoring algorithm for identifying crystal hits, coupled with an open-source, user-friendly interface for viewing experimental images, streamlines the process of analyzing crystal growth images. Here, the key procedures and instrumentation are described for the preparation of the cocktails and crystallization plates, imaging the plates, and identifying hits in a way that ensures reproducibility and increases the likelihood of successful crystallization.

Author Spotlight: High-Throughput Screening to Obtain Crystal Hits for Protein Crystallography  

This protocol details high-throughput crystallization screening, ranging from the 1,536 microassay plate preparation to the end of a 6 week experimental time window. Details are included about the sample setup, the imaging obtained, and how users can perform analyses using an artificial intelligence-enabled graphical user interface to quickly and efficiently identify macromolecular crystallization conditions.

X-ray crystallography is the most commonly employed technique to discern macromolecular structures, but the crucial step of crystallizing a protein into ...

"Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome

Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of applications. The cell surface proteome ("surfaceome") in human disease is of significant interest, as plasma membrane proteins are the primary target of most clinically approved therapeutics, as well as a key feature by which to diagnostically distinguish diseased cells from healthy tissues. However, focused characterization of membrane and surface proteins of the cell has remained challenging, primarily due to the complexity of cellular lysates, which mask proteins of interest by other high-abundance proteins. To overcome this technical barrier and accurately define the cell surface proteome of various cell types using mass spectrometry proteomics, it is necessary to enrich the cell lysate for cell surface proteins prior to analysis on the mass spectrometer. This paper presents a detailed workflow for labeling cell surface proteins from cancer cells, enriching these proteins out of the cell lysate, and subsequent sample preparation for mass spectrometry analysis.

Here, we describe a proteomics workflow for characterization of the cell surface proteome of various cell types. This workflow includes cell surface protein enrichment, subsequent sample preparation, analysis using an LC-MS/MS platform, and data processing with specialized software.

Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of ...

High-Throughput Quantification of the Synthesis and Distribution of mtDNA

High-Throughput Image-Based Quantification of Mitochondrial DNA Synthesis and Distribution

The vast majority of cellular processes require a continuous supply of energy, the most common carrier of which is the ATP molecule. Eukaryotic cells produce most of their ATP in the mitochondria by oxidative phosphorylation. Mitochondria are unique organelles because they have their own genome that is replicated and passed on to the next generation of cells. In contrast to the nuclear genome, there are multiple copies of the mitochondrial genome in the cell. The detailed study of the mechanisms responsible for the replication, repair, and maintenance of the mitochondrial genome is essential for understanding the proper functioning of mitochondria and whole cells under both normal and disease conditions. Here, a method that allows the high-throughput quantification of the synthesis and distribution of mitochondrial DNA (mtDNA) in human cells cultured in vitro is presented. This approach is based on the immunofluorescence detection of actively synthesized DNA molecules labeled by 5-bromo-2'-deoxyuridine (BrdU) incorporation and the concurrent detection of all the mtDNA molecules with anti-DNA antibodies. Additionally, the mitochondria are visualized with specific dyes or antibodies. The culturing of cells in a multi-well format and the utilization of an automated fluorescence microscope make it easier to study the dynamics of mtDNA and the morphology of mitochondria under a variety of experimental conditions in a relatively short time.

Author Spotlight: High-Throughput Image-Based Quantification of Mitochondrial DNA Synthesis and Distribution  

A procedure for studying the dynamics of mitochondrial DNA (mtDNA) metabolism in cells using a multi-well plate format and automated immunofluorescence imaging to detect and quantify mtDNA synthesis and distribution is described. This can be further used to investigate the effects of various inhibitors, cellular stresses, and gene silencing on mtDNA metabolism.

The vast majority of cellular processes require a continuous supply of energy, the most common carrier of which is the ATP molecule. Eukaryotic cells ...