The authors would like to thank Dr. Charles Keese, Dr. Christian Renken, Christian Dehnert (Applied BioPhysics Inc.) and Dr. Ulf Radler (ibidi GmbH) for their advice, help and the fruitful discussions during the preparation of this manuscript. Further we would like to thank Jan van Bezu for his excellent technical support. This research was conducted with support from the Dutch Lung Foundation (Longfonds), Grant number 33.12.036.

1. Preparation of Measurement System
<ol>
	<li>Prewarm the array holder in an incubator to 37 &#176;C before starting the experiment to prevent condensation.</li>
	<li>Fill water casket of the incubator with distilled water to avoid drying of the wells.</li>
	<li>Perform all manipulations on cells and arrays in a laminar flow cabinet under sterile conditions.</li>
</ol>
2. Preparation of Arrays and Inoculation of Cells
NOTE: The ECIS arrays need to be cleaned and stabilized before an experiment to prevent electrode drift, to improve well-to-well reproducibility and signal-to-noise ratio. Therefore two options are available: A) pretreatment of the electrodes with L-cysteine and B) the stabilization function of the ECIS.
Option A: L-cysteine is recommended as the most consistent pretreatment, but might in some special cases interact with protein coatings on the electrodes. The volumes presented are used for standard 8-well arrays.
<ol>
	<li>Add 200 &#181;l/well&#160;10 mM L-cysteine. Cysteine cleans and modifies the electrode surface providing a high and reproducible electrode capacitance.</li>
	<li>Incubate 15 min at room temperature (RT).</li>
	<li>Wash twice&#160;500 &#181;l/well with ultra-pure water (type 1). Do not&#160;use phosphate buffers, which can interfere with the adsorption of some proteins. Also avoid serum-containing solutions before coating, since the gold surface will adsorb the first macromolecules brought in contact.</li>
	<li>Coat with 200 &#181;l/well warm 1% gelatin.</li>
	<li>Incubate 30 min at 37 &#176;C.</li>
	<li>Remove gelatin, but don&#39;t let surface dry. This can damage the electrodes.</li>
	<li>Wash once&#160;with ultra-pure water (type 1).</li>
	<li>Add 400 &#181;l/well complete cell culture medium (containing serum, antibiotics and all growth factors).</li>
	<li>Slide array into array holder and make sure that the array is positioned such that the nine gold square pads are properly contacted by the spring-loaded pogo pins and fix adjustment screw hand tight. Be careful with transparent arrays, the gold layer can easily be damaged.</li>
	<li>Open the measurement software and press Setup followed by Check in the &#34;Collect Data&#34; section to perform a quick impedance measurement of each individual well. The resulting values are the measurement baseline and will automatically be stored in the &#34;Comments&#34;.</li>
	<li>The well check will automatically determine the type of ECIS arrays used. Verify the selected arrays in the &#34;Well Configuration&#34; section.</li>
	<li>The array diagram lights up green for properly connected wells and red for empty or incorrect connected wells. Still, always make sure that the arrays were placed correctly in the holder. 
	NOTE: If cleaning and coating were successful the 8W1E ECIS arrays have a capacitance of about 5 nF and the 8W10E arrays of 50 nF, which results in a baseline resistance of about 2,000 and 200 &#937;, respectively.</li>
	<li>Remove array from holder.</li>
	<li>Seed cells as a single cell suspension in 400 &#181;l/well complete cell culture medium.</li>
</ol>
Option B: The stabilization function of the ECIS can be used as an alternative or in combination with the L-cysteine treatment and if problems with electrode drift or large differences in well-to-well resistance and capacitance occur.
<ol>
	<li>Perform cysteine treatment (optional) and precoat electrodes with protein (optional).</li>
	<li>Add 200 &#181;l/well of complete medium to each well and place the array in the array holder.</li>
	<li>Open measurement software and press Setup followed by Check to ascertain the array is properly connected and to measure initial Z, R, and C.</li>
	<li>Stabilize the electrodes by pressing Stabilize in the &#34;Collect Data&#34; section. The ECIS will apply a high current (ca. 3 mA), high frequency (64 kHz) pulse to clean the electrodes.</li>
	<li>Check electrodes again. Capacitance should be increased and resistance values should be in a comparable range.</li>
	<li>If capacitance and resistance values are still not satisfactory, repeat the stabilization.</li>
	<li>Remove array from the holder and inoculate cells.</li>
</ol>
3. Setting up Measurement Software and Data Acquisition
<ol>
	<li>Place the array in the array holder as described before.</li>
	<li>Open measurement software and press the Setup button in the &#34;Collect Data&#34; section to connect the ECIS software to the ECIS instrument and run another well Check.</li>
	<li>Verify the selected arrays in the &#34;Well Configuration&#34; section.</li>
	<li>Select the wells to be measured in the &#34;Well Configuration&#34; section.</li>
	<li>Select the measurement mode from the &#34;Collect Data&#34; options:
	<ol>
		<li>For a time series at a fixed frequency, select Single Freq. / Time (SFT) and choose the measurement frequency from the drop down menu.</li>
		<li>For measurement of electrode coverage and modeling of Rb and Alpha, select Multiple Freq. / Time (MFT). The ECIS device will measure automatically at all available frequencies.</li>
		<li>For micromotion (see data analysis) select Rapid Time Collect (RTC) and adjust measurement frequency and sampling frequency. Here the standard temporal resolution is one sample per sec&#160;(1 Hz), but sampling frequency can also be increased to track fast changes in impedance up to 25 Hz (for the Z-Theta). Important note: in RTC mode only a single well is measured. 
		NOTE: If micromotion need to be measured in several wells subsequently, go to Help &#62; Show expert toolbar/menu items &#62; Acquire &#62; Multi-Well RTC. Specify the Time limit (hr) in the Collect Data section; the ECIS will now measure the selected wells in numerical order. After starting the measurement the software will ask to specify the numbers of cycles. Enter the value for how often the measurement needs to be repeated.</li>
	</ol>
	</li>
	<li>For SFT and MFT, select the time Interval (sec) between measurements or if data need to be acquired as fast as possible leave this option unchecked. 
	NOTE: To acquire data the ECIS device uses a multiplexer to switch from one well to another with a minimum SFT acquisition rate of 0.25 sec and 7.5 sec for MFT. Meaning the interval is dependent on number of selected wells and frequencies. For measurements on slow proliferating cells or a simple recording of resistance vs. time, use intervals of 600 sec or more.</li>
	<li>Press Start, name the file and select location to store the data. 
	NOTE: File size should not be a problem, since ECIS data are saved in a kind of plain text format called *.abp, which never exceeds several&#160;hundred MB even with all measurement frequencies and number of wells selected.</li>
	<li>Stop run by pressing Finish.</li>
</ol>
4. Medium Change and Cell Manipulation
<ol>
	<li>Press Pause, this will stop the data acquisition, but continue to run the experimental clock.</li>
	<li>Remove the array from the holder and manipulate it under a laminar flow bench (i.e. change medium).</li>
	<li>Place array back in the holder and either click Check Connection or Resume Experiment to continue data acquisition. The measurement software will place a time mark in the data set.</li>
</ol>
5. Acute Stimulation During Data Acquisition
NOTE: A second option is to manipulate the cells during data acquisition to follow immediate changes. This is only possible&#160;when samples don&#39;t needs to be sterile in the further course of the experiment.
<ol>
	<li>Add the stimulus directly to the well and make sure to mix careful with a 200 &#181;l&#160;pipette.</li>
	<li>Mark time point manually by pressing Mark and add a comment.</li>
</ol>
6. Electrical Wounding
NOTE: Finding the right settings for the used cell type is key for electrical wounding. If wounding is too short this can result in insufficient removal of cells, whereas if wounding is too long and/or rough this can damage the electrodes (especially on the transparent arrays). Therefore, several short wounding pulses are recommended. For HUVEC cultures two 10-20 sec long wounding pulses of 5 V at 60 kHz each have been found optimal using the ECIS 1600R. In general it is recommended to use high frequencies &#62;20 kHz to maintain uniform high fields across the cells and to avoid any damage to the electrodes.
<ol>
	<li>Perform wounding during an active ECIS measurement.</li>
	<li>Enable Wound / Electroporate Setup, then click Wound and fill in the time (sec), wound voltage (V for 1,600 R) or current (&#181;A for Z and Z-Theta) and frequency (Hz). The displayed default values are based on the type of array and ECIS device.</li>
	<li>Select the wells to wound in the &#34;Well Configuration&#34; section. Only the checked wells will be wounded.</li>
	<li>Enable Delay Until Hour and fill in the delay time to activate the delay wound function. This function can be stopped at any time by pressing Stop or applying a wound manually. Only one delay command can be active at a time.</li>
	<li>Press Activate and click OK in the pop-up window to start wounding.</li>
	<li>Make sure that the resistance signal drops to the offset impedance after wounding, otherwise repeat the wounding.</li>
</ol>
7. Data Analysis
<ol>
	<li>Data representation and exporting.
	<ol>
		<li>Finish measurement or load data set via File -&#62; Open.</li>
		<li>Select wells to be displayed from the &#34;Well Configuration&#34; window. Group individual wells to present the average.</li>
		<li>Chose parameter to be displayed from the upper toolbar (Z, R or C).</li>
		<li>Select graph type from the upper toolbar (T = time, F = frequency, 3D = waterfall blot).</li>
		<li>Define graph offset and range with the sliders below the graph window or fill in the exact values in the adjacent controls.</li>
		<li>Chose from the basic &#34;Time-Series Options&#34; in the &#34;Analyze&#34; section to perform standard deviation, running average or normalization of the data.</li>
		<li>Activate Expert Toolbar in the Help menu for more advanced operations like Nyuist plot and Fourier transformation.</li>
		<li>Use &#34;Display Options&#34; in the &#34;Analyze&#34; section to define range of x- and y-axes and export graph.</li>
		<li>Export selected data to an Excel file via File -&#62; Export Data -&#62; To Excel (Selected) and use a third party software of choice for in depth analysis, statistics and representation as needed.</li>
	</ol>
	</li>
	<li>Modeling of Rb and Alpha. 
	NOTE: For modeling it is recommended to use a cell-free, medium filled well as reference.
	<ol>
		<li>Finish MFT measurement or load MFT data set.</li>
		<li>If a cell-free reference well is available press either Find to automatically select the reference value or Set to select the cell free time point manually from &#34;Freq. Scan Modeling&#34; in the &#34;Analyzing&#34; section.</li>
		<li>If there is no cell-free reference, import a reference value from another data set. Open the reference data set (make sure that the same array and medium was used) and use Find or Set to select the reference value. Then navigate to the measured data and press Get.</li>
		<li>If there is no cell-free reference data set available use the factory default.</li>
		<li>Press Model to start the calculations. Modeling might take several minutes dependent on the size of the data set.</li>
	</ol>
	</li>
	<li>Calculation of micromotion. 
	NOTE: This calculation is not part of the measurement software, but can be performed with any signal processing software.
	<ol>
		<li>Finish RTC measurement or load RTC data set.</li>
		<li>Normalize data set by the averaged resistance of the entire period.</li>
		<li>Break data set into segments with a length of 256-data points and clean each segment by a Hanning window.</li>
		<li>Run a 256-point Fourier transformation and average resulting frequency spectra to a single-sided 129-point power spectrum to minimize random noise and enhanced the biological signal.</li>
		<li>Plot frequency against amplitude in a log-log graph and apply least square linear fit.</li>
		<li>The slope of the linear fit is a measure of overall noise in the signal and thereby micromotion of the cells.</li>
	</ol>
	</li>
</ol>

<ol>
	<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 (6455), 591-592 (1993).</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=Micromotion+of+mammalian+cells+measured+electrically.">Micromotion of mammalian cells measured electrically.</a> Proc. Natl. Acad. Sci. U.S.A. 88 (17), 7896-7900 (1991).</li><li>Lo, C. M., Keese, C. R., Giaever, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cell-substrate+contact:+another+factor+may+influence+transepithelial+electrical+resistance+of+cell+layers+cultured+on+permeable+filters.">Cell-substrate contact: another factor may influence transepithelial electrical resistance of cell layers cultured on permeable filters.</a> Exp. Cell Res. 250 (2), 576-580 (1999).</li><li>Wegener, J., Sieber, M., Galla, H. J. <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+epithelial+and+endothelial+cell+monolayers+cultured+on+gold+surfaces.">Impedance analysis of epithelial and endothelial cell monolayers cultured on gold surfaces.</a> J. Biochem. Biophys. Methods. 32 (3), 151-170 (1996).</li><li>P&#228;nke, O., Balkenhohl, T., Kafka, J., Sch&#228;fer, D., Lisdat, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impedance+spectroscopy+and+biosensing.">Impedance spectroscopy and biosensing.</a> Adv. Biochem. Eng. Biotechnol. 109 (11/2007), 195-237 (2008).</li><li>Wegener, J., Zink, S., R&#246;sen, P., Galla, H. <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+electrochemical+impedance+measurements+to+monitor+beta-adrenergic+stimulation+of+bovine+aortic+endothelial+cells.">Use of electrochemical impedance measurements to monitor beta-adrenergic stimulation of bovine aortic endothelial cells.</a> Pflugers Arch. 437 (6), 925-934 (1999).</li><li>Eker, B., Meissner, R., Bertsch, A., Mehta, K., Renaud, P. <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+recognition+of+drug+resistance+via+impedimetric+screening+of+breast+cancer+cells.">Label-free recognition of drug resistance via impedimetric screening of breast cancer cells.</a> PloS ONE. 8 (3), (2013).</li><li>Nacke, T., Anhalt, M., Frense, D., Beckmann, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anwendungsm&#246;glichkeiten+der+Impedanzspektroskopie+in+der+Biotechnologie+(Application+of+the+Impedance+Spectroscopy+in+the+Biotechnology).">Anwendungsm&#246;glichkeiten der Impedanzspektroskopie in der Biotechnologie (Application of the Impedance Spectroscopy in the Biotechnology).</a> Technisches Messen. 69 (1/2002), 12-18 (2002).</li><li>DePaola, , 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=Electrical+impedance+of+cultured+endothelium+under+fluid+flow.">Electrical impedance of cultured endothelium under fluid flow.</a> Ann. Biomed. Eng. 29 (8), 648-656 (2001).</li><li>Pietrosimone, K. M., Yin, X., Knecht, D. A., Lynes, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measurement+of+Cellular+Chemotaxis+with+ECIS/Taxis.">Measurement of Cellular Chemotaxis with ECIS/Taxis.</a> J. Vis. Exp. (62), (2012).</li><li>Wegener, J., Keese, C. R., Giaever, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electric+cell-substrate+impedance+sensing+(ECIS)+as+a+noninvasive+means+to+monitor+the+kinetics+of+cell+spreading+to+artificial+surfaces.">Electric cell-substrate impedance sensing (ECIS) as a noninvasive means to monitor the kinetics of cell spreading to artificial surfaces.</a> Exp. Cell Res. 259 (1), 158-166 (2000).</li><li>Lo, C. M., Keese, C. R., Giaever, I. <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+MDCK+cells+measured+by+electric+cell-substrate+impedance+sensing.">Impedance analysis of MDCK cells measured by electric cell-substrate impedance sensing.</a> Biophys. J. 69 (6), 2800-2807 (1995).</li><li>Lo, C. M., Keese, C. R., Giaever, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Monitoring+motion+of+confluent+cells+in+tissue+culture.">Monitoring motion of confluent cells in tissue culture.</a> Exp. Cell Res. 204 (1), 102-109 (1993).</li><li>Opp, D., Wafula, B., Lim, J., Huang, E., Lo, J. C., Lo, C. M. <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+electric+cell-substrate+impedance+sensing+to+assess+in+vitro+cytotoxicity.">Use of electric cell-substrate impedance sensing to assess in vitro cytotoxicity.</a> Biosens. Bioelectron. 24 (8), 2625-2629 (2009).</li><li>Szulcek, R., Beckers, C. M. L., 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=Localized+RhoA+GTPase+activity+regulates+dynamics+of+endothelial+monolayer+integrity.">Localized RhoA GTPase activity regulates dynamics of endothelial monolayer integrity.</a> Cardiovasc. Res. 99 (3), 471-482 (2013).</li><li>Liang, C. -. C., Park, A. Y., Guan, J. -. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=In+vitro+scratch+assay:+a+convenient+and+inexpensive+method+for+analysis+of+cell+migration+in+vitro.">In vitro scratch assay: a convenient and inexpensive method for analysis of cell migration in vitro.</a> Nat. Protoc. 2 (2), 329-333 (2007).</li><li>Keese, C. R., Wegener, J., Walker, S. R., Giaever, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrical+wound-healing+assay+for+cells+in+vitro.">Electrical wound-healing assay for cells in vitro.</a> Proc. Natl. Acad. Sci. U.S.A. 101 (6), 1554-1559 (2004).</li><li>Krishnan, R., Klumpers, D. 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=Substrate+stiffening+promotes+endothelial+monolayer+disruption+through+enhanced+physical+forces.">Substrate stiffening promotes endothelial monolayer disruption through enhanced physical forces.</a> Am. J. Physiol., Cell Physiol. 300 (1), 146-154 (2011).</li><li>Van Nieuw Amerongen, P. G., van Delft, S., Ma Vermeer, M., Collard, J. G., van Hinsbergh, V. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Activation+of+RhoA+by+thrombin+in+endothelial+hyperpermeability:+role+of+Rho+kinase+and+protein+tyrosine+kinases.">Activation of RhoA by thrombin in endothelial hyperpermeability: role of Rho kinase and protein tyrosine kinases.</a> Circ. Res. 87 (4), 335-340 (2000).</li><li>Aman, J., 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=Effective+treatment+of+edema+and+endothelial+barrier+dysfunction+with+imatinib.">Effective treatment of edema and endothelial barrier dysfunction with imatinib.</a> Circulation. 126 (23), 2728-2738 (2012).</li></ol>

Applied BioPhysics Inc. covered the open access fees, whereas structure and content of the article remained full responsibility of the authors.

ECIS is an excellent tool for the screening of cell properties and behavior as well as for the quantification of the effects of known and unknown substances. Thereby the cells are held under standard culture conditions, impedance can continuously be monitored with a high temporal resolution and correlated to optical signals. That way the optimal time point for cell manipulations can be chosen on the basis of the morphological and functional cell status. Unfortunately, this high measurement resolution comes with the price that small changes in temperature, pH or mechanical stimulation of cells (medium change) will influence the impedance signal immediately.
The application of the small measurement current to the cells makes the ECIS measurement noninvasive, nondestructive, and label-free, but as a result only passive bioelectrical properties can be measured (no action potentials). A key feature is that a number of parameters can be derived from a single measurement, combining the information from several classical assays, like permeability or wound healing assays. Here the particular interesting aspect is that mathematically modeled data can be used to explore changes in resistance and capacitance and refer them to distinct cellular structures (e.g. cell-contacts or cell membrane). Important to note is that impedance spectroscopy always provides an averaged signal from all cells on the sensing electrode, which does not allow for studies on single cells and also the mathematical model is only valid in confluent cell layers. Therefore endothelial cells should be held in the confluent state for at least one day before used for modeling to ensure mature cell-adhesions and quiescent cells. Equally, electrical wounds should only be applied to confluent cell layers using multiple short wounding pulses with high frequencies, to achieve optimal wounding efficiency and prevent damage of the electrodes.
To get the maximal amount of information from an ECIS measurement, as in every assay, several parameters such as the combination of array substrate, coating and seeding density for the individual cell type need to be tested and optimized before an experiment.
A major limitation of ECIS is that the measurement does not provide direct information on the molecular level. Thus ECIS measurements are usually most informative at the beginning of an experimental series to help associate a scientific problem with cellular structures or properties and provide significant input for the generation of a testable hypothesis. Therefore the modular design of ECIS provides a wide spectrum of applications with the possibility for tailor made arrays. The latest array developments indicate a future focus on high throughput impedance screenings for cell proliferation and electrical wounding and the advance of special flow arrays for the simulation of in vivo shear stress with different flow profiles.
Further literature 
Please also refer to the webpage of Applied BioPhysics (www.biophysics.com) for application notes, webinars and a detailed list of publications covering the entire ECIS spectrum.

&#937;&#937;&#937;Here we present Electric Cell-substrate Impedance Sensing, known as ECIS, a specific method to measure and analyze the impedance spectrum of adherent cells in culture1. The aim of this protocol is to offer a generally applicable guide for the usage of this particular type of impedance based cellular assays and provide protocols for some of the key functions from the constantly growing number of applications. The focus will be on the study of cell proliferation, barrier function, cell junctions, and cell motility.
Since ECIS and its associated model to transform the impedance spectroscopy data in biologically relevant parameters was introduced in its current form to the scientific community by Giaever and Keese in 19912, it has often been referred to as a system for the measurement of TEER (trans-epithelial electrical resistance), which is not accurate. The differences seem marginal at first, but are important for the data interpretation. For classical TEER measurements, cells are grown on permeable filters to characterize paracellular transport mechanisms, which are dominated by epithelial tight junctions or endothelial adherens junctions3. Commonly, two electrodes positioned above and below the filter are used to apply a direct current (DC) flow over the cell layer and two other electrodes to measure the resulting voltage drop4. The electrical resistance is calculated using Ohm&#39;s law, which allows a numerical description of the quality of the cell barrier.
ECIS follows this basic principle and extends it. In the ECIS system, cells are grown on opposing, circular gold electrodes that are embedded in the bottom of special cell culture dishes. The number of electrodes per culture well is variable, dependent on the application and the electrodes have a standard diameter of 250 &#181;m; in some cases a larger counter electrode is used to complete the circuit. ECIS uses a constant alternating current (AC) of 1 &#181;A with a given frequency instead of a direct current. The impedance is calculated from the corresponding changes in voltage (in mV) between electrodes. ECIS offers the possibility to measure the impedance over a range of frequencies to study frequency dependent cellular properties, which has several advantages over TEER and will be explained in detail in this article. First, measuring complex impedance allows separating the overall impedance into cell barrier resistance and cell capacitance. In addition, by taking data at multiple frequencies and applying a mathematical model, one can differentiate between junctional impedance (tightness of cell-cell contacts) and impedance caused by cell-substrate interactions (distance of basal cell membrane to underlying matrix) as well as the contribution of the cell membrane capacitance. Second, cell proliferation and motility can be assessed, since the cells are in direct contact with the electrodes. Third, substrate and electrodes are sufficiently thin to allow for bright field and phase contrast microscopy.
Basis of impedance measurements: The complex impedance
The basis for the measurement of the electrical impedance of biological objects (e.g. cells) is&#160;Ohm&#39;s law, a basic electro-technical principle, which describes the relation between resistance (R), current (I) and voltage (U) in an electrical circuit at a given time (t). 
Applicable in DC circuit: R(t) = U(t)/I(t)
When working in the AC system, current and voltage not only differ in their amplitude, but also in their phase (&#966;). Now, resistance is no longer sufficient to describe these relations. Instead, the complex impedance (Z) or in most cases the magnitude of the impedance (|Z|) are used, containing the previously described ohmic resistance plus reactance (X), which results from AC flow through capacitors and inductors driving the phase shift between voltage and current5. 
Applicable in AC circuit: |Z(f)| = &#8730;(R2+X(f)2) 
&#966; = arctan(X/R)
When performing impedance measurements on intact cells, due to the characteristics of their membrane, cells act as a parallel connection of resistor and capacitor. Here, resistance represents the opposition to current flow, whereas capacitance (C) describes the separation of electric carriers at the insulating bi-layer of the cell membrane that causes polarization of the cell. Thereby X is dominated by the capacitive properties of the cell membrane. 
X(f) &#8776; (2*Pi*f*CCell)-1
Since X is frequency dependent, variation of the measurement frequency enables study of different functional and structural properties of the cell. The ECIS device measures both R and X, allowing calculation of |Z|, C and &#966;.
Quantifying entire cell layers with impedance spectroscopy: The electrical equivalent circuit.
As previously explained, when a cell is brought into an electrical field, it shows properties of passive electronic components. If now, instead of a single cell, an entire cell layer grown on top of electrodes and supplemented with cell culture medium is investigated, the simple model of resistor and capacitor needs to be extended to an entire electrical network. In this so-called equivalent circuit, resistance of the culture medium (RMed) as well as capacitance (CElectr) and resistance (RElectr) characterizing the electrode/electrolyte interaction need to be considered3,6.
A simplified, general example of such an equivalent circuit for an adherent growing cell layer can be found in Figure 1. The advantage of such a mathematical approach to describe a biological system is that those circuits can be refined ad libitum and adjusted to the specific experimental questions, e.g. by considering impedance caused by intra-cellular organelles or to distinguish influences of cell-cell (RJunc) and cell-substrate adhesions (RSub) on overall impedance7,8. Nevertheless the aim for the modeling should always be to use the smallest number of elements describing all features of the measured impedance spectrum to allow meaningful correlations.
<img alt="Figure 1" fo:content-width="5in" src="/files/ftp_upload/51300/51300fig1highres.jpg" width="500" /> 
Figure 1.&#160;Schematic of the ECIS system and representative equivalent circuit for an adherent growing cells layer. A) Cross section of an ECIS culture well. The cells are growing on top of sensing and counter electrode and are covered with culture medium. The electrodes are connected to a lock-in amplifier and an AC signal is applied via a 1 M&#937;&#160;resistor to create a constant current source. Stimuli can be added directly to the culture medium at any point in time. B) ECIS measures the sum of all individual contributions to the impedance. Resistance of the culture medium (RMed) as well as impedance caused by the electrode/electrolyte interface, which is for simplicity presented as a parallel combination of a resistor (RElectr) and a capacitor (CElectr), and also the electrical properties of the cell membrane, described by a parallel connection of resistance (RCell) and capacitance (CMem), all need to be considered. RCell is variable, since it is dependent on the cell permeability towards the current. The equivalent circuit can be extended and refined ad libitum. As an example junctional (RJunc) as well as subendothelial (RSub) resistance were added to the circuit. <a href="https://www.jove.com/files/ftp_upload/51300/51300fig1highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Impedance parameters and their biological meaning
The two most direct parameters derived from impedance measurements are resistance and capacitance of cells. Resistance represents quality and function of the cell barrier and therefore takes into consideration the resistance towards para- and trans-cellular current flow. Capacitance provides an overall measure of electrode coverage. The distinctive feature of the ECIS is that with the help of equivalent circuits and modeling those global parameters provide insights on many more cellular properties, including cell-cell and cell-substrate adhesions, which will be discussed later in this article.
Before starting: Experimental considerations
Measurement setup - The setup consists of several separate components: ECIS device with measurement electronics; PC for data acquisition; array holder for the 8- or 96-well system; ECIS arrays and the cell culture of choice. The array holder must be placed in an incubator and connected to the ECIS device outside the incubator. The PC needs to be equipped with the ECIS software (1.2.123.0 14th February 2013) and connected to the ECIS device.
Array selection - There is a continuously growing variety of ECIS arrays, designed for multiple applications. The standard arrays are the 8W1E and the 8W10E arrays, which are composed of 8 culture wells (indicated by W) comprising 1 or 10 measurement electrodes (indicated by E), respectively. A large counter electrode completes the circuit, but its impedance is essentially negligible in the actual measurement6. The standard 8-well array holder can host two arrays, resulting in a total number of 16 culture wells. The gold electrodes are 50&#160;nm thick, delineated with an insulating film and mounted on either an optically clear Lexan polycarbonate substrate or a printed circuit board (PCB). The PCB arrays are more robust and cost efficient. The transparent slides allow for light and immunofluorescence microscopy. What must be considered is that the 1E array enhances fluctuations in the resistance signal caused by cell motions and is needed for wound healing studies. In addition, single electrodes allow correlation of electrical and optical signals. In the multi electrode arrays, the signal is averaged over several electrodes, which due to the increased measurement area includes more cells in the measurement, limits bias of the data by uneven inoculation and growth of the cells and reduces blurring of the signal due to cell motions. Therefore, the multi electrode arrays are useful to study cell proliferation and barrier formation. Next to standard arrays there are special arrays available for the application of shear stress9, to study chemotaxis10, cell migration, and proliferation as well as 96-well plates for high throughput screenings. To conclude, the array to be used is strongly dependent on scientific question and cell type and should be selected and tested carefully.
Measurement frequency - The modeling of Rb and alpha (see data analysis) requires multi frequency measurements (MFT). Otherwise impedance can be measured over time at one cell type specific frequency (SFT), with the advantage that data can be collected with a higher temporal resolution. The most sensitive measurement frequency for a specific cell type can be found by frequency scans. When plotting impedance respectively resistance vs. frequency in a log-log graph the frequency where the difference between cell-free and cell-covered electrode is biggest is the frequency where the cells block the current most effectively. In case of endothelial cells (EC) this frequency is at about 4 kHz.
Seeding density - As in every regular cell-based experiment seeding density depends on the scientific problem. When studying adhesion and spreading or barrier formation, endothelial cells should be seeded with a high density of 40,000-60,000 cells/cm2 to guarantee a confluent, stable barrier after 48 hr. If the focus of the experiment is on proliferation, endothelial cells should be seeded with a low density of about 2,000-10,000 cells/cm2.

<table border="0" cellpadding="0" cellspacing="0" style="width:1269px;" width="1269">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Name of Material/Equipment</td>
			<td style="width:320px;">Company</td>
			<td style="width:247px;">Distributor Europe</td>
			<td style="width:119px;">Catalog Number</td>
			<td style="width:329px;">Comments/Description</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">ECIS Z&#952;</td>
			<td style="width:320px;">Applied Biophysics Inc., Troy, NY, USA</td>
			<td style="width:247px;">ibidi GmbH, Munich, Germany</td>
			<td>71617</td>
			<td><a href="http://www.biophysics.com/products-ecisz0.php">http://www.biophysics.com/products-ecisz0.php</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">8W1E PCB Electrode Array</td>
			<td style="width:320px;">Applied Biophysics Inc., Troy, NY, USA</td>
			<td style="width:247px;">ibidi GmbH, Munich, Germany</td>
			<td>70004</td>
			<td><a href="http://www.biophysics.com/cultureware.php">http://www.biophysics.com/cultureware.php</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">8W1E Lexan Electrode Array</td>
			<td style="width:320px;">Applied Biophysics Inc., Troy, NY, USA</td>
			<td style="width:247px;">ibidi GmbH, Munich, Germany</td>
			<td>70001</td>
			<td>http://www.biophysics.com/cultureware.php</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">8W10E PCB Electrode Array</td>
			<td style="width:320px;">Applied Biophysics Inc., Troy, NY, USA</td>
			<td style="width:247px;">ibidi GmbH, Munich, Germany</td>
			<td>70010</td>
			<td>http://www.biophysics.com/cultureware.php</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">L-Cystein</td>
			<td style="width:320px;">Merck Millipore</td>
			<td style="width:247px;">-</td>
			<td>102838</td>
			<td><a href="http://www.merckmillipore.com/germany/chemicals/l-cystein/MDA_CHEM-102838/p_GLOb.s1L7V8AAAEWL.EfVhTl?WFSimpleSearch_NameOrID=L-cystein&amp;BackButtonText=search+results">http://www.merckmillipore.com/germany/chemicals/l-cystein/MDA_CHEM-102838/p_GLOb.s1L7V8AAAEWL.EfVhTl?WFSimpleSearch_NameOrID=L-cystein&#38;BackButtonText=search+results</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Gelatin</td>
			<td style="width:320px;">Merck Millipore</td>
			<td style="width:247px;">-</td>
			<td>104070</td>
			<td><a href="http://www.merckmillipore.com/germany/chemicals/gelatine/MDA_CHEM-104070/p_S7Wb.s1LadYAAAEWaOEfVhTl?WFSimpleSearch_NameOrID=gelatine&amp;BackButtonText=search+results">http://www.merckmillipore.com/germany/chemicals/gelatine/MDA_CHEM-104070/p_S7Wb.s1LadYAAAEWaOEfVhTl?WFSimpleSearch_NameOrID=gelatine&#38;BackButtonText=search+results</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Bovine Thrombin</td>
			<td style="width:320px;">Merck Millipore</td>
			<td style="width:247px;">-</td>
			<td>604980</td>
			<td><a href="http://www.merckmillipore.com/germany/life-science-research/thrombin-bovine-high-activity/EMD_BIO-604980/p__pmb.s1LNsYAAAEWS2IfVhTm?PortalCatalogID=merck4biosciences">http://www.merckmillipore.com/germany/life-science-research/thrombin-bovine-high-activity/EMD_BIO-604980/p__pmb.s1LNsYAAAEWS2IfVhTm?PortalCatalogID=merck4biosciences</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Albuman (Human Serum Albumin)</td>
			<td style="width:320px;">Sanquin</td>
			<td style="width:247px;">-</td>
			<td></td>
			<td><a href="http://www.sanquin.nl/en/products-services/plasma-products/">http://www.sanquin.nl/en/products-services/plasma-products/</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Y-27632</td>
			<td style="width:320px;">Tocris Biosciences</td>
			<td style="width:247px;">-</td>
			<td>1254</td>
			<td><a href="http://www.tocris.com/dispprod.php?ItemId=1382#.UbiFNNish8E">http://www.tocris.com/dispprod.php?ItemId=1382#.UbiFNNish8E</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">EGM-2 BulletKit&#160;</td>
			<td style="width:320px;">Lonza</td>
			<td style="width:247px;">-</td>
			<td>CC-3162</td>
			<td><a href="http://www.lonza.com/products-services/bio-research/primary-and-stem-cells/human-cells-and-media/endothelial-cells-and-media/endothelial-cell-growth-media-kits.aspx">http://www.lonza.com/products-services/bio-research/primary-and-stem-cells/human-cells-and-media/endothelial-cells-and-media/endothelial-cell-growth-media-kits.aspx</a></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Pen/Strep</td>
			<td style="width:320px;">Lonza</td>
			<td style="width:247px;">-</td>
			<td>17-602E</td>
			<td><a href="http://www.lonza.com/products-services/bio-research/cell-culture-products/reagents/antibiotics-antimycotics/penicillin-streptomycin.aspx">http://www.lonza.com/products-services/bio-research/cell-culture-products/reagents/antibiotics-antimycotics/penicillin-streptomycin.aspx</a></td>
		</tr>
	</tbody>
</table>

electric cell-substrate impedance sensing for the quantification of endothelial proliferation, barrier function, and motility

Electric Cell-substrate Impedance Sensing (ECIS) is an in vitro impedance measuring system to quantify the behavior of cells within adherent cell layers. To this end, cells are grown in special culture chambers on top of opposing, circular gold electrodes. A constant small alternating current is applied between the electrodes and the potential across is measured. The insulating properties of the cell membrane create a resistance towards the electrical current flow resulting in an increased electrical potential between the electrodes. Measuring cellular impedance in this manner allows the automated study of cell attachment, growth, morphology, function, and motility. Although the ECIS measurement itself is straightforward and easy to learn, the underlying theory is complex and selection of the right settings and correct analysis and interpretation of the data is not self-evident. Yet, a clear protocol describing the individual steps from the experimental design to preparation, realization, and analysis of the experiment is not available. In this article the basic measurement principle as well as possible applications, experimental considerations, advantages and limitations of the ECIS system are discussed. A guide is provided for the study of cell attachment, spreading and proliferation; quantification of cell behavior in a confluent layer, with regard to barrier function, cell motility, quality of cell-cell and cell-substrate adhesions; and quantification of wound healing and cellular responses to vasoactive stimuli. Representative results are discussed based on human microvascular (MVEC) and human umbilical vein endothelial cells (HUVEC), but are applicable to all adherent growing cells.

Setting up an experiment is fairly simple and the measurement itself is fully automatic, but as is often the case, correct analysis and interpretation of the data are crucial. In the representative data section a guide is provided for the interpretation of the most important parameters provided by impedance spectroscopy with ECIS. This will be helpful to decide for which kind of scientific problem an ECIS measurement can be useful and which parameters should be recorded.
A typical experimental read-out can generally be divided in a growth-phase after cell inoculation and a plateau-phase when cells reach confluence. Each of these phases yields information on different cellular properties. A representative measurement is shown in Figure 2 and divided into four subphases to analyze A) cell adhesion, spreading and proliferation; B) formation of a maturation EC barrier; C) cell migration after the generation of an electrical wound; and D) the cellular response to stimulation with the vasoactive agent thrombin. Phase-contrast and immunofluorescence images were acquired directly from the measurement electrode during the different subphases to illustrate the link between electrode coverage, cell status, and recorded impedance signal.
Adhesion, spreading and proliferation
Every cell type has its characteristic adhesion and growth curve that can be manipulated by varying seeding density, coating with extracellular matrix proteins or other stimuli. One of the major difficulties to study those processes is to differentiate between adhesion, spreading and proliferation. Wegener et al.11 gave a detailed description for the use of a combination of resistance and capacitance to distinguish between those parameters and in Figure 3 it becomes obvious how resistance and capacitance can complement each other. It is important for the study of adhesion and spreading to understand the influence of the measurement frequency, because here the electrical field causes a polarization of the cell membrane of the cells in suspension8, which forces the current to flow exclusively around the cells. When the cells attach they start to restrict the current flow by spreading over the electrode and capacitance decreases in a linear fashion with the percentage of open area on the electrode (fractional area). Hence, adhesion, spreading and proliferation can be quantified best, when recording capacitance at a frequency higher than 40 kHz (Figure 3B), where the decrease in capacitance is direct proportional to the electrode coverage. Alternatively resistance at its most sensitive measurement frequency is a direct measure for the differentiation and maturation of cells into a confluent barrier (Figure 3A). In addition to the fractional area, Wegener et al. introduced two other parameters to quantify adhesion and electrode coverage: t1/2 (half maximum capacitance), which is the time until 50% of the electrode is covered with cells (Figure 3B, insertion), and the slope of the capacitance curve (s, not shown) as the rate of cell spreading and proliferation.
Resistance as a measure of barrier quality
Resistance is the part of impedance that describes barrier quality and function best, because it neglects capacitive components from membrane, electrode and medium. Here the term barrier quality and not permeability is used, since permeability is per definition only dependent on cell-cell contacts. Resistance however is determined by the ability of cells and their cell-cell and cell-matrix interactions to block the current flow. Accordingly different cell types (clones and passages) have their specific resistance values (Figure 4A). Although resistance gives a much clearer idea about the cell barrier, the impedance signal should always be taken into consideration.
Modeling of Rb and Alpha
The ECIS software harbors a particular feature, the ability to model two parameters, which distinguish between cell-cell and cell-matrix adhesions (Figures 4B and 4C). Rb (in cm2 x ohm), is the resistivity of cell-cell contacts to the current flow and thereby an inverse measure of classical permeability. High Rb implies low permeability towards the current flow. Alpha (in cm x ohm0.5), is a measure for the impedance contributions arising from the cell-electrode junctions. The model to quantify cell-cell and cell-matrix contacts was introduced 1991 by Giaever and Keese and is based on the assumption that cells are circular, disc shaped objects that have an insulating membrane, hover over the electrode and are filled with conducting electrolyte2. The insulating property of the cell membrane leaves only three pathways for the current: a) between ventral surface of the cells and electrode, b) between the cell-cell contacts, and c) through the cells (only likely when a high measurement frequency is used). A more detailed derivation and explanation can be found in the papers of Lo et al3,12.
Micromotion
It has been shown that small fluctuations in the resistance signal (Figure 4A) are due to subtle, random cell movements in confluent cell layers as well as cells moving on and off the electrode in sparse cultures2. This aspect of ECIS time-course data described by Lo and Opp et al.13,14&#160;is often overlooked and best seen when measuring with the 1E arrays and at the most sensitive frequency to account for para- and subcellular current-paths. The calculation of this cell caused noise (micromotion) is not part of the standard measurement software, although in the newest version Fast Fourier Transformation (FFT) is integrated. Recording RTC data with a sampling frequency of 1 Hz for 1 hr at 4 kHz provides sufficient resolution for the calculation of EC micromotion. This calculation provides one single value and can be directly used for statistical analysis. An extended discussion on the use of frequency analysis for micromotion can be found elsewhere15. Alternatively to FFT other analysis strategies can be used, like variance of the increments. Variance is more sensitive towards small changes in micromotion, but because of this sensitivity the comparison of individual experiments becomes difficult. The slopes of the power spectrum are a more robust measurement of micromotion (Figure 4D). Here the area under the curve can be seen as the amount of micromotion or noise the cells create. Hence, the steeper the slope of the power spectrum the smaller the area under the curve and the smaller the micromotion.
Electric wound healing assay
To study migration of cells, usually mechanical wounds are applied by scratching cells off the culture plate with pipette tips, cell scrapers or specific stamps and follow their remigration microscopically16. This method has the obvious disadvantage that the size of the scratch varies and is usually too big to neglect the influence of cell proliferation on the wound healing process. The wounding function of the ECIS uses a high voltage, high frequency pulse to get a cell free electrode and subsequently follows remigration of neighboring cells to replace the death cells (Figure 5A). An advantage of this automated method over standard, labor intensive scratch assays is that the ECIS produces a highly reproducible wound with a precise diameter of 250 &#181;m, that closes within a few hours, to study pure migration. Further, the electrical pulse does not remove protein coating and secreted extracellular matrix. Under the assumption that the cells remigrate on the electrode from all sides, the migration rate can easily be calculated by dividing wound radius by time required for wound closure17. As an alternative to electrical wounding, recently the so-called electric fence method was introduced (not shown). Here high current pulses prevent attachment and migration of cells on the electrodes after inoculation. The cells will grow around the measurement electrode and start migrating inwards as soon as the electric pulses are turned off. The advantage of the electric fence over the electric wounding is that the electrode surface hasn&#39;t been altered by cell growth or cell removal, which is important to measure influences of different coatings on cell migration.
Cell stimulation
In addition to the study of cell migration, impedance spectroscopy is perfectly suited to measure the effects of drugs and toxins on cells. Figure 5B presents a classical stimulation/inhibition experiment, where thrombin was used to induce hyper-permeability in the confluent EC barrier by contraction and gap formation of cells, which manifests as a transient drop in resistance. By preincubation with the Rho kinase inhibitor Y-27632 most of the thrombin response is diminished by lowering basal cell tension18 and blocking stress fiber formation19. Then the Rho kinase blocker was used at different time points after thrombin addition, leading to an immediate and total recovery of the EC barrier. Here the advantage of a continuous impedance measurement system to study acute cellular responses becomes obvious. In regular endpoint assays (e.g. immunofluorescence staining or macromolecule passage), this acute response to the used blocker would be very difficult if not impossible to detect and quantify. Important to note is that with impedance measurements the permeability towards ions is described and not towards macromolecules. Please refer to Aman et al.20, where an excellent comparison between ECIS measurements and macromolecule passage experiments is provided.
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/51300/51300fig2highres.jpg" src="/files/ftp_upload/51300/51300fig2.jpg" /> 
Figure 2.&#160;Representative measurement. MVEC were grown on a gelatin coated 8W1E arrays with a low seeding density of 5,000 cells/cm2 and MFT recording was performed over 10 days. The measurement illustrates the different read-outs of an ECIS experiment: A) adhesion, spreading and proliferation; B) formation and maturation of a confluent cell barrier; C) wound healing after the application of an electrical wound; D) stimulation with the vasoactive agent thrombin. The two arrows indicate medium refreshments, which were performed in intervals of 4 days and give an idea about the sensitivity of the measurements towards mechanical stimuli and changes in temperature and pH. The images in the top panel correspond to the measurement and were acquired directly from the measurement electrode. The phase-contrast image on the left shows the endothelial cells 24 hr&#160;after inoculation, starting to cover the electrode. The immunofluorescence pictures in the center and on the right present F-actin staining of the confluent endothelial layer before and after stimulation with thrombin (1 U/ml). Thrombin causes contraction of endothelial cells by formation of so called stress fibers and the transient opening of inter-endothelial gaps (arrows and image inserts), recognizable in the ECIS signal by a drop in resistance to baseline. Here the sensitivity of the measurement becomes obvious and how changes in the cell layer correlate with the impedance signal. <a href="https://www.jove.com/files/ftp_upload/51300/51300fig2highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/51300/51300fig3highres.jpg" src="/files/ftp_upload/51300/51300fig3.jpg" /> 
Figure 3.&#160;Cell attachment and growth. MVEC from the same donor were seeded with three different densities on gelatin coated 8W10E arrays and cell growth was recorded at multiple frequencies for 60 hr. A) Resistance values for the three conditions at their optimal frequency of 4 kHz to measure barrier formation. All three seeding densities established a confluent barrier of ca. 1,200 &#937; at the end of the measurement; the proliferation rates however (slopes of the curves) differ markedly. B) Measurement of capacitance at 64 kHz provides insights on adhesion and spreading. Adhesion is the initial plateau phase in the capacitance curve (between 2-8 hr). Spreading, which is in linear relation to the electrode coverage, is represented by the slope of the curve and is completed after 10-30 hr&#160;depending on the seeding density. The time point t1/2 (half maximal coverage) can be used for statistical analysis. <a href="https://www.jove.com/files/ftp_upload/51300/51300fig3highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" fo:content-width="5in" fo:src="/files/ftp_upload/51300/51300fig4highres.jpg" src="/files/ftp_upload/51300/51300fig4.jpg" /> 
Figure 4.&#160;Characterization of the confluent barrier. Two MVEC donors with different passage numbers (passage 3 and 6) were seeded on gelatin coated 8W1E arrays and a MFT measurement was performed for 30 hr&#160;to characterize the EC barrier. A) Resistance measurements reveal that the younger donor 1 has a higher resistance of ca. 11,000 &#937; in comparison to the ca. 7,500 &#937; of the older donor 2. B-C) The modeling capabilities of the ECIS have been used to find the cause for the lower resistance. Modeling revealed a comparable cell-cell interaction Rb and indicated a weakened cell-matrix interaction Alpha as a possible cause. D) RTC was performed to quantify micromotion within the confluent cell layer by Fourier transformation, where the area under the curve is proportional to micromotion. Analyses of the spectra shows less micromotion of the older donor 2 and thereby support what can already be assumed from the resistance signal (less variance). <a href="https://www.jove.com/files/ftp_upload/51300/51300fig4highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" fo:content-width="5in" fo:src="/files/ftp_upload/51300/51300fig5highres.jpg" src="/files/ftp_upload/51300/51300fig5.jpg" /> 
Figure 5.&#160;Cell migration after electric wounding and effects of thrombin stimulation. Impedance recordings were performed at 4 kHz with maximal temporal resolution. A) MVEC donor 1 was used in passage 3 and donor 2 in passage 6 on gelatin coated 8W1E arrays and grown to confluence. Then an electrical wound was created by application of two 5 V pulses at 60 kHz with a duration of 20 sec each. The younger donor 1 showed better wound healing capabilities based on a faster wound closure (migration, slopes of the curves) and a higher resistance after wounding in comparison to the older donor 2. B) HUVEC were grown on gelatin coated 8W10E arrays. Upon confluence the cells have been serum starved for 1.5 hr&#160;by replacing the complete culture medium with basal medium plus 1% human serum albumin (HSA). Usage of plain medium with HSA is a critical step, since serum components block the thrombin response. As soon as a stable resistance plateau was detected, thrombin was added directly to the wells and mixed carefully with a 200&#160;&#181;l&#160;pipette. The maximal thrombin effect is visible after 30 min, characterized by a transient drop in resistance to baseline and a ca. 30-50% lower resistance after recovery. The cells were either preincubated with the Rho kinase blocker Y-27632 for 30 min or the blocker was added 20, 30, or 40 min after thrombin addition, which diminished the thrombin effect immediately. <a href="https://www.jove.com/files/ftp_upload/51300/51300fig5highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Electric Cell-substrate Impedance Sensing for the Quantification of Endothelial Proliferation, Barrier Function, and Motility at JoVE.com

Electric Cell-substrate Impedance Sensing for the Quantification of Endothelial Proliferation, Barrier Function, and Motility

This protocol reviews Electric Cell-substrate Impedance Sensing, a method to record and analyze the impedance spectrum of adherent cells for the quantification of cell attachment, proliferation, motility, and cellular responses to pharmacological and toxic stimuli. Detection of endothelial permeability and assessment of cell-cell and cell-substrate contacts are emphasized.

Electric Cell-substrate Impedance Sensing (ECIS) is an in vitro impedance measuring system to quantify the behavior of cells within adherent cell layers. ...

electric-cell-substrate-impedance-sensing-for-quantification

Research

Education

JoVE Journal

JoVE Core

Electrical Engineering

Physics

Bioengineering

Unit 1

Three-Phase Circuits

Alternating-Current Circuits

SCIENTISTS IN ACTION

57.1K vistas.  Institute for Cardiovascular Research, VU University Medical Center.  Este protocolo revisa eléctrico de la célula-sustrato Impedancia de detección, un método para registrar y analizar el espectro de impedancia de las células adherentes para la cuantificación de la unión celular, la proliferación, motilidad, y las respuestas celulares a estímulos farmacológicos y tóxicos. La detección de la permeabilidad endotelial y la evaluación de los contactos célula-célula y célula-sustrato que se obtienen. 

Video: Electric Cell-substrate Impedance Sensing for the Quantification of Endothelial Proliferation, Barrier Function, and Motility

Hollow Microneedle-based Sensor for Multiplexed Transdermal Electrochemical Sensing

The development of a minimally invasive multiplexed monitoring system for rapid analysis of biologically-relevant molecules could offer individuals suffering from chronic medical conditions facile assessment of their immediate physiological state. Furthermore, it could serve as a research tool for analysis of complex, multifactorial medical conditions. In order for such a multianalyte sensor to be realized, it must be minimally invasive, sampling of interstitial fluid must occur without pain or harm to the user, and analysis must be rapid as well as selective.
Initially developed for pain-free drug delivery, microneedles have been used to deliver vaccines and pharmacologic agents (e.g., insulin) through the skin.1-2 Since these devices access the interstitial space, microneedles that are integrated with microelectrodes can be used as transdermal electrochemical sensors. Selective detection of glucose, glutamate, lactate, hydrogen peroxide, and ascorbic acid has been demonstrated using integrated microneedle-electrode devices with carbon fibers, modified carbon pastes, and platinum-coated polymer microneedles serving as transducing elements.3-7,8
This microneedle sensor technology has enabled a novel and sophisticated analytical approach for in situ and simultaneous detection of multiple analytes. Multiplexing offers the possibility of monitoring complex microenvironments, which are otherwise difficult to characterize in a rapid and minimally invasive manner. For example, this technology could be utilized for simultaneous monitoring of extracellular levels of, glucose, lactate and pH,9 which are important metabolic indicators of disease states7,10-14 (e.g., cancer proliferation) and exercise-induced acidosis.15

This article details the construction of a multiplexed microneedle-based sensor. The device is being developed for in situ sampling and electrochemical analysis of multiple analytes in a rapid and selective manner. We envision clinical medicine and biomedical research uses for these microneedle-based sensors.

The development of a minimally invasive multiplexed monitoring system for rapid analysis of biologically-relevant molecules could offer individuals ...

Sensing of Barrier Tissue Disruption with an Organic Electrochemical Transistor

The gastrointestinal tract is an example of barrier tissue that provides a physical barrier against entry of pathogens and toxins, while allowing the passage of necessary ions and molecules. A breach in this barrier can be caused by a reduction in the extracellular calcium concentration. This reduction in calcium concentration causes a conformational change in proteins involved in the sealing of the barrier, leading to an increase of the paracellular flux. To mimic this effect the calcium chelator ethylene glycol-bis(beta-aminoethyl ether)-N,N,N&#39;,N&#39;-tetra acetic acid (EGTA) was used on a monolayer of cells known to be representative of the gastrointestinal tract. Different methods to detect the disruption of the barrier tissue already exist, such as immunofluorescence and&#160;permeability assays. However, these methods are time-consuming and costly and not suited to dynamic or high-throughput measurements. Electronic methods for measuring barrier tissue integrity also exist for measurement of the transepithelial resistance (TER), however these are often costly and complex. The development of rapid, cheap, and sensitive methods is urgently needed as the integrity of barrier tissue is a key parameter in drug discovery and pathogen/toxin diagnostics. The organic electrochemical transistor (OECT) integrated with barrier tissue forming cells has been shown as a new device capable of dynamically monitoring barrier tissue integrity. The device is able to measure minute variations in ionic flux with unprecedented temporal resolution and sensitivity, in real time, as an indicator of barrier tissue integrity. This new method is based on a simple device that can be compatible with high throughput screening applications and fabricated at low cost.

The Organic Electrochemical Transistor is integrated with live cells and used to monitor ion flux across the gastrointestinal epithelial barrier. In this study, an increase in ion flux, related to disruption of tight junctions, induced by the presence of the calcium chelator EGTA (ethylene glycol-bis(beta-aminoethyl ether)-N,N,N',N'-tetra acetic acid), is measured.

The gastrointestinal tract is an example of barrier tissue that provides a physical barrier against entry of pathogens and toxins, while allowing the ...

Quantification and Size-profiling of Extracellular Vesicles Using Tunable Resistive Pulse Sensing

Extracellular vesicles (EVs), including &#8216;microvesicles&#8217; and &#8216;exosomes&#8217;, are highly abundant in bodily fluids. Recent years have witnessed a tremendous increase in interest in EVs. EVs have been shown to play important roles in various physiological and pathological processes, including coagulation, immune responses, and cancer. In addition, EVs have potential as therapeutic agents, for instance as drug delivery vehicles or as regenerative medicine. Because of their small size (50 to 1,000 nm) accurate quantification and size profiling of EVs is technically challenging.
This protocol describes how tunable resistive pulse sensing (tRPS) technology, using the qNano system, can be used to determine the concentration and size of EVs. The method, which relies on the detection of EVs upon their transfer through a nano sized pore, is relatively fast, suffices the use of small sample volumes and does not require the purification and concentration of EVs. Next to the regular operation protocol an alternative approach is described using samples spiked with polystyrene beads of known size and concentration. This real-time calibration technique can be used to overcome technical hurdles encountered when measuring EVs directly in biological fluids.

Extracellular vesicles play important roles in physiological and pathological processes, including coagulation, immune responses, and cancer or as potential therapeutic agents in drug delivery or regenerative medicine. This protocol presents methods for the quantification and size characterization of isolated and non-isolated extracellular vesicles in various fluids using tunable resistive pulse sensing.

Extracellular vesicles (EVs), including &#8216;microvesicles&#8217; and &#8216;exosomes&#8217;, are highly abundant in bodily fluids. Recent years have ...

Using Cell-substrate Impedance and Live Cell Imaging to Measure Real-time Changes in Cellular Adhesion and De-adhesion Induced by Matrix Modification

Cell-matrix adhesion plays a key role in controlling cell morphology and signaling. Stimuli that disrupt cell-matrix adhesion (e.g., myeloperoxidase and other matrix-modifying oxidants/enzymes released during inflammation) are implicated in triggering pathological changes in cellular function, phenotype and viability in a number of diseases. Here, we describe how cell-substrate impedance and live cell imaging approaches can be readily employed to accurately quantify real-time changes in cell adhesion and de-adhesion induced by matrix modification (using endothelial cells and myeloperoxidase as a pathophysiological matrix-modifying stimulus) with high temporal resolution and in a non-invasive manner. The xCELLigence cell-substrate impedance system continuously quantifies the area of cell-matrix adhesion by measuring the electrical impedance at the cell-substrate interface in cells grown on gold microelectrode arrays. Image analysis of time-lapse differential interference contrast movies quantifies changes in the projected area of individual cells over time, representing changes in the area of cell-matrix contact. Both techniques accurately quantify rapid changes to cellular adhesion and de-adhesion processes. Cell-substrate impedance on microelectrode biosensor arrays provides a platform for robust, high-throughput measurements. Live cell imaging analyses provide additional detail regarding the nature and dynamics of the morphological changes quantified by cell-substrate impedance measurements. These complementary approaches provide valuable new insights into how myeloperoxidase-catalyzed oxidative modification of subcellular extracellular matrix components triggers rapid changes in cell adhesion, morphology and signaling in endothelial cells. These approaches are also applicable for studying cellular adhesion dynamics in response to other matrix-modifying stimuli and in related adherent cells (e.g., epithelial cells).

Here, we present a protocol to continuously quantify cell adhesion and de-adhesion processes with high temporal resolution in a non-invasive manner by cell-substrate impedance and live cell imaging analyses. These approaches reveal the dynamics of cell adhesion/de-adhesion processes triggered by matrix modification and their temporal relationship to adhesion-dependent signaling events.

Cell-matrix adhesion plays a key role in controlling cell morphology and signaling. Stimuli that disrupt cell-matrix adhesion (e.g., myeloperoxidase and ...

Fabricating Multi-Component Lipid Nanotube Networks Using the Gliding Kinesin Motility Assay

Lipid nanotube (LNT) networks represent an in vitro model system for studying molecular transport and lipid biophysics with relevance to the ubiquitous lipid tubules found in eukaryotic cells. However, in vivo LNTs are highly non-equilibrium structures that require chemical energy and molecular motors to be assembled, maintained, and reorganized. Furthermore, the composition of in vivo LNTs is complex, comprising of multiple different lipid species. Typical methods to extrude LNTs are both time- and labor-intensive, and they require optical tweezers, microbeads, and micropipettes to forcibly pull nanotubes from giant lipid vesicles. Presented here is a protocol for the gliding motility assay (GMA), in which large scale LNT networks are rapidly generated from giant unilamellar vesicles (GUVs) using kinesin-powered microtubule motility. Using this method, LNT networks are formed from a wide array of lipid formulations that mimic the complexity of biological LNTs, making them increasingly useful for in vitro studies of lipid biophysics and membrane-associated transport. Additionally, this method is capable of reliably producing LNT networks in a short time (&#60;30 min) using commonly used laboratory equipment. LNT network characteristics such as length, width, and lipid partitioning are also tunable by altering the lipid composition of the GUVs used for fabricating the networks.

This protocol describes a process for fabricating lipid nanotube networks using gliding kinesin motility in conjunction with giant unilamellar lipid vesicles.

Lipid nanotube (LNT) networks represent an in vitro model system for studying molecular transport and lipid biophysics with relevance to the ubiquitous ...

Finite Element Modelling of a Cellular Electric Microenvironment

Clinical studies show electrical stimulation (ES) to be a potential therapy for the healing and regeneration of various tissues. Understanding the mechanisms of cell response when exposed to electrical fields can therefore guide the optimization of clinical applications. In vitro experiments aim to help uncover those, offering the advantage of wider input and output ranges that can be ethically and effectively assessed. However, the advancements in in vitro experiments are difficult to reproduce directly in clinical settings. Mainly, that is because the ES devices used in vitro differ significantly from the ones suitable for patient use, and the path from the electrodes to the targeted cells is different. Translating the in vitro results into in vivo procedures is therefore not straightforward. We emphasize that the cellular microenvironment's structure and physical properties play a determining role in the actual experimental testing conditions and suggest that measures of charge distribution can be used to bridge the gap between in vitro and in vivo. Considering this, we show how in silico finite element modelling (FEM) can be used to describe the cellular microenvironment and the changes generated by electric field (EF) exposure. We highlight how the EF couples with geometric structure to determine charge distribution. We then show the impact of time dependent inputs on charge movement. Finally, we demonstrate the relevance of our new in silico model methodology using two case studies: (i) in vitro fibrous Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT-PSS) scaffolds and (ii) in vivo collagen in extracellular matrix (ECM).

This paper presents a strategy for building finite element models of fibrous conductive materials exposed to an electric field (EF). The models can be used to estimate the electrical input that cells seeded in such materials receive and assess the impact of changing the scaffold's constituent material properties, structure or orientation.

Clinical studies show electrical stimulation (ES) to be a potential therapy for the healing and regeneration of various tissues. Understanding the ...

Electric and Magnetic Field Devices for Stimulation of Biological Tissues

Electric fields (EFs) and magnetic fields (MFs) have been widely used by tissue engineering to improve cell dynamics such as proliferation, migration, differentiation, morphology, and molecular synthesis. However, variables such stimuli strength and stimulation times need to be considered when stimulating either cells, tissues or scaffolds. Given that EFs and MFs vary according to cellular response, it remains unclear how to build devices that generate adequate biophysical stimuli to stimulate biological samples. In fact, there is a lack of evidence regarding the calculation and distribution when biophysical stimuli are applied. This protocol is focused on the design and manufacture of devices to generate EFs and MFs and implementation of a computational methodology to predict biophysical stimuli distribution inside and outside of biological samples. The EF device was composed of two parallel stainless-steel electrodes located at the top and bottom of biological cultures. Electrodes were connected to an oscillator to generate voltages (50, 100, 150 and 200 Vp-p) at 60 kHz. The MF device was composed of a coil, which was energized with a transformer to generate a current (1 A) and voltage (6 V) at 60 Hz. A polymethyl methacrylate support was built to locate the biological cultures in the middle of the coil. The computational simulation elucidated the homogeneous distribution of EFs and MFs inside and outside of biological tissues. This computational model is a promising tool that can modify parameters such as voltages, frequencies, tissue morphologies, well plate types, electrodes and coil size to estimate the EFs and MFs to achieve a cellular response.

This protocol describes the step-by-step process to build both electrical and magnetic stimulators used to stimulate biological tissues. The protocol includes a guideline to simulate computationally electric and magnetic fields and manufacture of stimulator devices.

Electric fields (EFs) and magnetic fields (MFs) have been widely used by tissue engineering to improve cell dynamics such as proliferation, migration, ...

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations result in pathology, and how myocardial diseases may be treated. Cardiovascular magnetic resonance imaging (CMR) has become an indispensable tool for a comprehensive in vivo assessment of cardiac anatomy and function. This protocol shows detailed measurements of mouse heart left ventricular function, myocardial strain, and hemodynamic forces using 7-Tesla CMR. First, animal preparation and positioning in the scanner are demonstrated. Survey scans are performed for planning imaging slices in various short- and long-axis views. A series of prospective ECG-triggered short-axis (SA) movies (or CINE images) are acquired covering the heart from apex to base, capturing end-systolic and end-diastolic phases. Subsequently, single-slice, retrospectively gated CINE images are acquired in a midventricular SA view, and in 2-, 3-, and 4-chamber views, to be reconstructed into high-temporal resolution CINE images using custom-built and open-source software. CINE images are subsequently analyzed using dedicated CMR image analysis software.
Delineating endomyocardial and epicardial borders in SA end-systolic and end-diastolic CINE images allows for the calculation of end-systolic and end-diastolic volumes, ejection fraction, and cardiac output. The midventricular SA CINE images are delineated for all cardiac time frames to extract a detailed volume-time curve. Its time derivative allows for the calculation of the diastolic function as the ratio of the early filling and atrial contraction waves. Finally, left ventricular endocardial walls in the 2-, 3-, and 4-chamber views are delineated using feature-tracking, from which longitudinal myocardial strain parameters and left ventricular hemodynamic forces are calculated. In conclusion, this protocol provides detailed in vivo quantification of the mouse cardiac parameters, which can be used to study temporal alterations in cardiac function in various mouse models of heart disease.

This study describes a comprehensive cardiovascular magnetic resonance imaging (CMR) protocol to quantify the left ventricular functional parameters of the mouse heart. The protocol describes the acquisition, post-processing, and analysis of the CMR images as well as assessment of different cardiac functional parameters.

Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations ...

Layer Microdissection of Tricuspid Valve Leaflets for Biaxial Mechanical Characterization and Microstructural Quantification

The tricuspid valve (TV) regulates the unidirectional flow of unoxygenated blood from the right atrium to the right ventricle. The TV consists of three leaflets, each with unique mechanical behaviors. These variations among the three TV leaflets can be further understood by examining their four anatomical layers, which are the atrialis (A), spongiosa (S), fibrosa (F), and ventricularis (V). While these layers are present in all three TV leaflets, there are differences in their thicknesses and microstructural constituents that further influence their respective mechanical behaviors. 
This protocol includes four steps to elucidate the layer-specific differences: (i) characterize the mechanical and collagen fiber architectural behaviors of the intact TV leaflet, (ii) separate the composite layers (A/S and F/V) of the TV leaflet, (iii) carry out the same characterizations for the composite layers, and (iv) perform post-hoc histology assessment. This experimental framework uniquely allows the direct comparison of the intact TV tissue to each of its composite layers. As a result, detailed information regarding the microstructure and biomechanical function of the TV leaflets can be collected with this protocol. Such information can potentially be used to develop TV computational models that seek to provide guidance for the clinical treatment of TV disease.

This protocol describes the biaxial mechanical characterization, polarized spatial frequency domain imaging-based collagen quantification, and microdissection of tricuspid valve leaflets. The provided method elucidates how the leaflet layers contribute to the holistic leaflet behaviors.

The tricuspid valve (TV) regulates the unidirectional flow of unoxygenated blood from the right atrium to the right ventricle. The TV consists of three ...

Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation

A major component of designing drug delivery systems concerns how to amplify or attenuate interactions with specific cell types. For instance, a chemotherapeutic might be functionalized with an antibody to enhance binding to cancer cells (&#34;targeting&#34;) or functionalized with polyethylene glycol to help evade immune cell recognition (&#34;stealth&#34;). Even at a cellular level, optimizing the binding and uptake of a drug carrier is a complex biological design problem. Thus, it is valuable to separate how strongly a new carrier interacts with a cell from the functional efficacy of a carrier&#39;s cargo once delivered to that cell.
To continue the chemotherapeutic example, &#34;how well it binds to a cancer cell&#34; is a separate problem from &#34;how well it kills a cancer cell&#34;. Quantitative in vitro assays for the latter are well established and usually rely on measuring viability. However, most published research on cell-carrier interactions is qualitative or semiquantitative. Generally, these measurements rely on fluorescent labeling of the carrier and, consequently, report interactions with cells in relative or arbitrary units. However, this work can be standardized and be made absolutely quantitative with a small number of characterization experiments. Such absolute quantification is valuable, as it facilitates rational, inter- and intra-class comparisons of various drug delivery systems-nanoparticles, microparticles, viruses, antibody-drug conjugates, engineered therapeutic cells, or extracellular vesicles.
Furthermore, quantification is a prerequisite for subsequent meta-analyses or in silico modeling approaches. In this article, video guides, as well as a decision tree for how to achieve in vitro quantification for carrier drug delivery systems, are presented, which take into account differences in carrier size and labeling modality. Additionally, further considerations for the quantitative assessment of advanced drug delivery systems are discussed. This is intended to serve as a valuable resource to improve rational evaluation and design for the next generation of medicine.

Experimental Quantification of Interactions Between Drug Delivery Systems and Cells In Vitro: A Guide for Preclinical Nanomedicine Evaluation

A workflow is demonstrated for the absolute quantification of drug carrier-cell interactions using flow cytometry to allow better rational evaluation of novel drug delivery systems. This workflow is applicable to drug carriers of any type.