Products xCELLigence RTCA Cardio
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xCELLigence® RTCA Cardio

Cardiomyocyte contractility and viability, monitored in real time. Enable evaluation of cardio toxicity during drug discovery.

xCELLigence RTCA Cardio


The xCELLigence® RTCA Cardio system uses non-invasive, label-free impedance monitoring to quantitatively evaluate cardiomyocyte health/function in real-time.  Cardiomyocytes are seeded in a 96-well electronic microtiter plate (E-Plate® Cardio 96) that contains gold microelectrode arrays fused to the bottom of each well.  Application of a low voltage (less than 20 mV) establishes an electric current between the electrodes, which is differentially modulated by the number of cells covering the electrodes, the morphology of those cells, and the strength of cell attachment (Figure 1A).  Because the cardiomyocyte contraction/relaxation cycle involves substantial changes in cell morphology and adhesion, it can be dynamically monitored using impedance (Fig. 1B).  The fast data acquisition rate (12.9 ms for the entire 96-well plate) of the xCELLigence® RTCA Cardio system provides high temporal resolution for viewing subtleties of the cardiomyocyte contraction/relaxation continuum.  Because impedance measurement is noninvasive, the millisecond time scale data can be combined with longer-term monitoring (hours/days) to study both the short- and long-term effect of compounds on cardiomyocyte health and function.

RTCA Cardio Technology Figure 1 RTCA Cardio Technology Figure

Figure 1.  Using real-time impedance monitoring to quantitatively evaluate cardiomyocyte health and function.  (A) The principle of real-time impedance monitoring. The E-Plate Cardio 96 is a 96-well microtiter plate containing gold microelectrodes integrated into the bottom of each well.  Application of a low-voltage creates a current between the electrodes. The presence of adherent cells on the surface of the electrodes impedes this current in a manner which is proportional to the number of cells inside the well and the morphologic and adhesive characteristics of the cells. The impedance signal (Z) is displayed as an arbitrary, unitless parameter called Cell Index, which is a ratio that compares the impedance value in the presence of cells vs. the absence of cells.  (B) Because the size/shape and attachment strength of cardiomyocytes fluctuate rhythmically during the contraction/relaxation cycle, impedance is capable of tracking this process.  (C) Video of beating cardiomyocytes on an E-Plate Cardio 96.


Software

xCELLigence Cardio Software Fig 1

Figure 1. Zoomed in screen shot of table for recording the contents/conditions of each well in an E-Plate.

Pre-defined protocols guide you through experimental set-up and analysis in seconds.

The RTCA Cardio Software enables facile experiment setup and execution along with powerful data analysis, while still remaining efficient and intuitive.  A general synopsis of how the software is used to run and analyze an experiment is shown below.

Step 1: Record Plate Layout
Using an intuitive graphical interface the contents/conditions of each well in the electronic microtiter plate (E-Plate®) are recorded (Figure 1).  Information fields for the wells include parameters such as cell type, cell number, drug identity, drug concentration, etc.  Table autofilling functions, similar to what are available in Excel or other spreadsheet programs, enable rapid data entry and automatic establishment of drug concentration gradients, cell number titrations, etc.  Even when multiple cell types and assay conditions are being examined, it takes just minutes to record the information for every well in a plate.

Step 2: Define Data Acquisition Parameters
Using a second table the details of data acquisition are defined.

Step 3: Running the Experiment
Press “Run” and watch as impedance data is acquired in real-time for every well in the plate.  Even as data is being acquired it can be viewed and graphically manipulated.

Step 4: Data Plotting and Analysis
Using an intuitive graphical interface the real-time impedance data for all the wells, or a subset of wells, from the E-Plate can be plotted (Figure 2A).  Data from multiple wells can be averaged and the coefficient of variation automatically calculated and plotted.  The viewing window for the x- and y-axes can be readily adjusted, and data traces can be normalized to a specific time point (immediately before drug addition, for example).  By zooming in on a short time range it is possible to view the rhythmic fluctuation in impedance resulting from cardiomyocyte beating (Figure 2B).  Built-in data analysis tools enable the real-time impedance traces to be interrogated for drug-induced effects on cardiomyocyte beating activity.  A total of 13 different parameters, including beating rate and amplitude, can be evaluated (Figure 2C).

xCELLigence Cardio Software Fig 2.1

xCELLigence Cardio Software Fig 2.2Figure 2.  Data plotting and analysis using the RTCA Cardio Software.  (A) Screen shot of data plotting/analysis window.  Here all of the curves have been normalized to the time point immediately preceding drug treatment (denoted by the bold back vertical line).  Error bars represent coefficients of variation.  (B) Viewing cardiomyocyte contraction.  By zooming in on a shorter time range (the time points inside the red box in part “A”), it is possible to view the rhythmic fluctuation of impedance resulting from cardiomyocyte beating.  (C) Built in analysis tools make it possible to identify and quantify drug-induced changes in 13 different cardiomyocyte beating parameters (including rate and amplitude).


Instrument

Description Cat. #
xCELLigence RTCA Cardio – Bundle (complete system) 00380601060
xCELLigence RTCA Cardio – Analyzer 06416993001
xCELLigence RTCA Cardio – Station 06417019001
xCELLigence RTCA Cardio – Control Unit (laptop with pre-installed software) 06200184001

Consumables

Description Cat. #
E-Plate Cardio 96 (6 plates) 06417051001
E-Plate Cardio 96 (36 plates) 06417035001

Videos

Exploring the Role of iPSC-Cardiomyocytes in Drug Discovery and Safety Assessment

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are increasingly utilized in basic biology research, drug discovery applications, and for studies of disease mechanisms. The opportunity to measure the contractility, viability, and electrophysiology of hiPSC-CMs in real time over extended periods can provide researchers unique mechanistic insights into the roles cardiomyocytes play in both normal development and cardiac disease.

In this special webinar, scientists using hiPSC-CMs will describe new approaches aimed at enhancing assessment of hiPSC-CM functionality. The speakers will also discuss how these approaches can be used to explore compounds that modulate the force of cardiomyocyte contraction or to assess the safety and efficacy of drugs and drug combinations targeting cardiac tissue.

In this webinar, you will gain insights on:

  • New instrumentation to assess cardiomyocyte contractility, viability, and electrophysiology
  • Label-free, real-time techniques to assess the “beating” of cardiomyocytes as a biologically-relevant measure of cardiomyocyte function
  • Use of electrical pacing for further maturation of cardiomyocytes
  • Techniques to detect functional cardiotoxicity

In addition, you will also be able to ask your own specific questions of the speakers during a live question-and-answer session following the presentations.

Learn More about the xCELLigence CardioECR       Click here
Featured Speaker:

Armando Lagrutta, PhD
Merck & Co. Inc.
Kristina Green, PhD
MyoKardia, Inc.

Moderator:

Patrick C.H. Lo, PhD
Senior Editor,
BioTechniques

 

 

Videos: Product Overviews

Videos: Research Presentations

Exploring the Role of iPSC-Cardiomyocytes in Drug Discovery and Safety AssessmentHuman induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are increasingly utilized in basic biology research, drug discovery applications, and for studies of disease mechanisms. The opportunity to measure the contractility, viability, and electrophysiology of hiPSC-CMs in real time over extended periods can provide researchers unique mechanistic insights into the roles cardiomyocytes play in both normal development and cardiac disease. In this ... Read More

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are increasingly utilized in basic biology research, drug discovery applications, and for studies of disease mechanisms. The opportunity to measure the contractility, viability, and electrophysiology of hiPSC-CMs in real time over extended periods can provide researchers unique mechanistic insights into the roles cardiomyocytes play in both normal development and cardiac disease.

In this special webinar, scientists using hiPSC-CMs will describe new approaches aimed at enhancing assessment of hiPSC-CM functionality. The speakers will also discuss how these approaches can be used to explore compounds that modulate the force of cardiomyocyte contraction or to assess the safety and efficacy of drugs and drug combinations targeting cardiac tissue.

In this webinar, you will gain insights on:

  • New instrumentation to assess cardiomyocyte contractility, viability, and electrophysiology
  • Label-free, real-time techniques to assess the “beating” of cardiomyocytes as a biologically-relevant measure of cardiomyocyte function
  • Use of electrical pacing for further maturation of cardiomyocytes
  • Techniques to detect functional cardiotoxicity

In addition, you will also be able to ask your own specific questions of the speakers during a live question-and-answer session following the presentations.

Learn More about the xCELLigence CardioECR       Click here
Featured Speaker:

Armando Lagrutta, PhD
Merck & Co. Inc.
Kristina Green, PhD
MyoKardia, Inc.

Moderator:

Patrick C.H. Lo, PhD
Senior Editor,
BioTechniques

 

 

Unraveling Kinase Inhibitor Cardiotoxicity with Cardiomyocyte Impedance Assays

Dr. Sarah K. Lamore
AstraZeneca Pharmaceuticals, Waltham, MA

Cardiovascular (CV) toxicity is a leading cause of drug failure. Though implementing earlier testing has successfully reduced hERG-related arrhythmias, additional assays capable of identifying other functional CV effects remain elusive. There is a pressing need to…Read More
Cardiac Toxicity Assessment Using Stem Cell-Derived Cardiomyocytes

Dr. Matthew F. Peters
AstraZeneca Pharmaceuticals, Boston, MA

Cardiac toxicity is a major hurdle in drug development. In this webinar Dr. Matthew F. Peters of AstraZeneca Pharmaceuticals (Boston, MA) discusses the utility of combining ACEA Bioscience’s xCELLigence® Cardio system with stem cell-derived cardiomyocytes...Read More

Videos: Tutorials

Videos: J.O.V.E. Video Articles

Applications Overview

With a millisecond sampling rate, the xCELLigence® RTCA Cardio system is able to monitor cardiomyocyte beating in real-time, providing a high throughput, quantitative and predictive assay for assessing of cardiac liability.

Workflow of the xCELLigence RTCA Cardio System: Cardio-Safety Testing
No cell labeling required, fully automated, physiological conditions

xCELLigence Real-Time Cell Analysis Cardio workflow

Shown in the workflow above, cryopreserved iPSC cardiomyocytes are directly plated in a 96-well microtiter E-plate® Cardio.  Post seeding, the cardiomyocytes are given sufficient time to form gap junctions and organize into a synchronized beating monolayer.  The electrode layout on the E-plate Cardio 96 facilitates visual inspection of the general health of the cardiomyocytes under a microscope. The ability to simultaneously monitor overall cell health (using cellular impedance) and cell contractile activity (using beating rate and amplitude) provides an effective means of evaluating a drug’s cardiac liability.

The RTCA Cardio System is capable of performing all xCELLigence RTCA applications, except chemotactic migration and invasion.  The most cited applications of the Cardio system are in the following in vitro cardio-safety research areas:

  1. Arrhythmia and compound validation
  2. Kinase and contractility
  3. Oncology drugs with short- and long-term toxicity
  4. iPSC and cardiac disease models
  5. Hypertrophy
  6. Structural toxicity

Click here for a list of publications, cells used and compounds tested using the xCELLigence RTCA Cardio system.

Cardiosafety: Drug-Induced Arrythmia

Between 1990 and 2006 one third of all safety-related drug withdrawals were due to cardiotoxicity, and cardiac liability continues to be a major hurdle in drug development.  Within the pharmaceutical industry, academic institutions, and regulatory agencies there are ongoing efforts to develop higher throughput and more predictive assays that can be used earlier in the drug discovery/development pipeline to minimize both cost and risk.

As described elsewhere in our technology overview, xCELLigence provides a non-invasive and label-free means of evaluating the effect of drugs on cardiomyocyte mechanical beating (Cardio system) and/or electrical activity (CardioECR system).  In the below example human iPSc-derived cardiomyocytes were exposed to a variety of compounds with known arrhythmogenic activity and impedance was subsequently monitored on the millisecond time scale.  Compared to DMSO (vehicle) and aspirin (negative control), the arrhythmogenic compounds and non-Torsade de Pointes arrhythmogenic compounds (aconitine and quabain) produce distinct impedance profiles indicative of abnormal contraction/relaxation cycles (Figure 1).

Detection of Arrhythmic Beats Induced by Known Arrhythmogenic Compounds

Figure 1.  Drug-induced arrhythmia.  Human iPS-derived cardiomyocytes (iCells) were treated with the indicated compounds and beating was monitored using impedance at millisecond time intervals.  Known arrythmogenic compounds were administered as follows: alfuzosin (10 μM), cisapride (1 μM), dofetilide (0.01 μM), erythromycin (30 μM), flecainide (3 μM), quinidine (10 μM), sotalol (100 μM), terfenadine (1 μM), and thioridazine (3 μM). Compounds associated with non-Torsade de Pointes arrhythmia, aconitine (0.03 μM) and quabain (0.03 μM), induced tachycardia- or fibrillation-like arrhythmia.  DMSO (0.1%) and 100 μM aspirin serve as vehicle and negative control, respectively. (Data and figures adapted from Guo L, et. al., 2011).

Key Benefits of Using xCELLigence for Studying Drug-induced Arryhthmia:
  1. Data display excellent correlation with known clinical arrhythmogenic risk.
  2. Monitor cardiotoxicity over short (seconds) and/or long (days/weeks) time scales.
  3. More thorough understanding of drug mechanism of action.
Drug-Induced Arrhythmia Supporting Information:

  • Cell lines Tested:
    Human iPSC iCELL® cardiomyocyte (Cellular Dynamics International), mouse ESC Cor.At® cardiomyocyte (Axiogenesis), human iPSC Cor.4U cardiomyocytes (Axiogenesis), human iPSC Pluricyte® Cardiomyocyte (Pluriomics), rat neonatal cardiomyocyte, murine ES D3 α-pig44 derived cardiomyocyte, mouse iPS derived cardiomyocyte (University of Cologne)
  • Compatible xCELLigence Systems
xCELLigence RTCA Cardio xCELLigence RTCA CardioECR
RTCA Cardio RTCA CardioECR
Throughput 1×96 wells 1×48 wells
Readout Impedance only Impedance and Field Potential
Sampling Rate Impedance: 12.9 ms Impedance: 1 ms
Field Potential: 10 kHz
  • Drug-Induced Arrhythmia Publications:
  1. Impedance-based detection of beating rhythm and proarrhythmic effects of compounds on stem cell-derived cardiomyocytes. Jonsson MK, Wang QD, Becker B. Assay Drug Dev Technol. 2011 Dec;9(6):589-99. (Roche R&D, Sweden)
  2. Functional cardiotoxicity profiling and screening using the xCELLigence RTCA Cardio System. Xi B, Wang T, Li N, Ouyang W, Zhang W, Wu J, Xu X, Wang X, Abassi YA. J Lab Autom. 2011 Dec;16(6):415-21. (ACEA Biosciences, Inc., USA)
  3. Estimating the risk of drug-induced proarrhythmia using human induced pluripotent stem cell-derived cardiomyocytes. Guo L, Abrams RM, Babiarz JE, Cohen JD, Kameoka S, Sanders MJ, Chiao E, Kolaja KL. Toxicol Sci. 2011 Sep;123(1):281-9. (Hoffmann-La Roche, Nutley, USA)
  4. In vitro model for assessing arrhythmogenic properties of drugs based on high-resolution impedance measurements. Nguemo F, Šarić T, Pfannkuche K, Watzele M, Reppel M, Hescheler J. Cell Physiol Biochem. 2012;29(5-6):819-32. (University of Cologne, Germany)
  5. Dynamic monitoring of beating periodicity of stem cell-derived cardiomyocytes as a predictive tool for preclinical safety assessment. Abassi YA, Xi B, Li N, Ouyang W, Seiler A, Watzele M, Kettenhofen R, Bohlen H, Ehlich A, Kolossov E, Wang X, Xu X. Br J Pharmacol. 2012 Mar;165(5):1424-41. (ACEA Biosciences, Inc.,USA)
  6. Drug-induced functional cardiotoxicity screening in stem cell-derived human and mouse cardiomyocytes: effects of reference compounds. Himmel HM. J Pharmacol Toxicol Methods. 2013 Jul-Aug;68(1):97-111. (Bayer Pharma AG, Germany)
  7. Refining the human iPSC cardiomyocyte arrhythmic risk assessment model. Guo L, Coyle L, Abrams RM, Kemper R, Chiao ET, Kolaja KL. Toxicol Sci. 2013 Dec;136(2):581-94. (Hoffmann-La Roche, Inc., Nutley, USA)
  8. The proliferative and chronotropic effects of Brillantaisia nitens Lindau (Acanthaceae) extracts on pluripotent stem cells and their cardiomyocytes derivatives. Nembo EN, Dimo T, Bopda OS, Hescheler J, Nguemo F. J Ethnopharmacol. 2014 Oct 28;156:73-81. (University of Cologne, Germany)
  9. Chapter 16: Label-Free Impedance Measurements for Profiling Drug- Induced Cardiotoxicity. Nguemo F, Semmler J, Hescheler J. Label-Free Biosensor Methods in Drug Discovery 2015 (University of Cologne, Germany)

 

Cardiotoxicity & Drug Screening

Is Your Current Technology Predictive?

xCELLigence® Cardio and CardioECR instruments provide the answers:

  • Superb Predictivity: Easily screen and quickly identify short-term and long-term cardiac toxicity early in drug development. (Figure 1)
  • Easy and Flexible Work Flow: Simply plate the cells, start acquiring data, and perform combination treatments and chronic dosing.
  • Powerful Multiplexing: Simultaneous readout of cardiomyocyte contractility, integrated ion channel activity (Figure 2), and viability.
  • Full Control of Beating Rate Enables Functional Maturation: Directed pacing feature improves functionality of iPSC cardiomyocytes (Figure 3) and response to inotropic compounds.
Request a Demo

 

Figure 1. Pharmacological assessment of ion channel inhibitors using iCell cardiomyocytes. iCell cardiomyocytes exhibiting consistent and robust beating activity (14 days post-seeding) were treated with multiple concentrations of each compound for up to 24 hours. Compound-induced arrhythmia was recorded by the xCELLigence RTCA Cardio instrument. 

 

Figure 2. Cardiac excitation-contraction coupling. The xCELLigence CardioECR instrument simultaneously measures electrophysiological signals and contractility. Blebbistatin, a myosin inhibitor, does not inhibit the ion-channel signal of treated cells (green), but greatly impairs the mechanical contraction and beating (red). Being able to monitor this excitation-contraction coupling relationship provides a complete picture for safety assessment of compounds during drug development.

 

Figure 3. Beating amplitude and Beating Rate Relations over time. iCell cardiomyocytes exhibiting consistent and robust beating and field potential signals were either submitted to directed progressive electrical stimulation (Paced) using the xCELLigence CardioECR instrument or cultured without electrical stimulation (Spontaneous) for 3 weeks. The Beating amplitude and Beating Rate relationship was determined weekly.

Download the Functional Maturation of iPSC Cardiomyocytes Flyer

Cardiotoxicity & Drug Screening Supporting Information:

  • Compatible xCELLigence® Systems
xCELLigence RTCA Cardio xCELLigence RTCA CardioECR
RTCA Cardio RTCA CardioECR
Throughput 1×96 wells 1×48 wells
Readout Impedance only Impedance and Field Potential
Sampling Rate Impedance: 12.9 ms Impedance: 1 ms
Field Potential: 10 kHz
  • Cardiotoxicity Publications:
  1. Estimating the Risk of Drug-induced Proarrhythmia Using Human Induced Pluripotent Stem Cell-derived Cardiomyocytes. Guo L, Abrams RM, Babiarz JE, Cohen JD, Kameoka S, Sanders MJ, Chiao E, Kolaja KL. Toxicol Sci. 2011 Sep;123(1):281-9. (Hoffmann-La Roche, Nutley, USA)
  2. Impedance-based Detection of Beating Rhythm and Proarrhythmic Effects of Compounds on Stem Cell-derived Cardiomyocytes. Jonsson MK, Wang QD, Becker B. Assay Drug Dev Technol. 2011 Dec;9(6):589-99. (Roche R&D, Sweden)
  3. Functional Cardiotoxicity Profiling and Screening Using the xCELLigence RTCA Cardio System. Xi B, Wang T, Li N, Ouyang W, Zhang W, Wu J, Xu X, Wang X, Abassi YA. J Lab Autom. 2011 Dec;16(6):415-21. (ACEA Biosciences, Inc., USA)
  4. In vitro Model for Assessing Arrhythmogenic Properties of Drugs Based on high-resolution Impedance Measurements. Nguemo F, Šarić T, Pfannkuche K, Watzele M, Reppel M, Hescheler J. Cell Physiol Biochem. 2012;29(5-6):819-32. (University of Cologne, Germany)
  5. Dynamic Monitoring of Beating Periodicity of Stem Cell-derived Cardiomyocytes as a Predictive Tool for Preclinical Safety Assessment. Abassi YA, Xi B, Li N, Ouyang W, Seiler A, Watzele M, Kettenhofen R, Bohlen H, Ehlich A, Kolossov E, Wang X, Xu X. Br J Pharmacol. 2012 Mar;165(5):1424-41. (ACEA Biosciences, Inc.,USA)
  6. Drug-induced Functional Cardiotoxicity Screening in Stem Cell-derived Human and Mouse Cardiomyocytes: Effects of Reference Compounds. Himmel HM. J Pharmacol Toxicol Methods. 2013 Jul-Aug;68(1):97-111. (Bayer Pharma AG, Germany)
  7. Refining the Human iPSC Cardiomyocyte Arrhythmic Risk Assessment Model. Guo L, Coyle L, Abrams RM, Kemper R, Chiao ET, Kolaja KL. Toxicol Sci. 2013 Dec;136(2):581-94. (Hoffmann-La Roche, Inc., Nutley, USA)
  8. The Proliferative and Chronotropic Effects of Brillantaisia Nitens Lindau (Acanthaceae) Extracts on Pluripotent Stem Cells and Their Cardiomyocytes Derivatives. Nembo EN, Dimo T, Bopda OS, Hescheler J, Nguemo F. J Ethnopharmacol. 2014 Oct 28;156:73-81. (University of Cologne, Germany)
  9. Chapter 16: Label-Free Impedance Measurements for Profiling Drug- Induced Cardiotoxicity. Nguemo F, Semmler J, Hescheler J. Label-Free Biosensor Methods in Drug Discovery 2015 (University of Cologne, Germany)

 

Cell Adhesion

Quantitative Assessment of Extracellular Matrix Effect on A549 Attachment and Spreading

The Cell Index increases proportionately as the coating concentration of collagen IV increases. (Data and figures adapted from ACEA Biosciences, unpublished data).

Mammary Stem-Like Cells Have Increased Tubulin-Dependent Initial Reattachment From Suspension

Cell Adhesion Fig 2

(A) Stem-like HMLE cells attach at signifi cantly faster rates than non-stem-like HMLE cells as determined by electrical impedance expressed as Cell Index. Stem-like HMLE and non-stem-like cells both have significantly reduced attachment when treated with the microtubule polymerization inhibitor colchicine (50µM). For all reattachment assay: lines, mean for quadruplicate wells; bars, SD; representative graph from three independent experiments is shown. (B) Phase contrast images of HMLE non-stem-like (a-d) and stem-like (e-h) subpopulations reattaching from suspension. Panels, 10x magnification; Insets, 60x magnification (Data and figures adapted from Charpentier MS, et al., 2014).

Key Benefits of Using xCELLigence to Study Cell Adhesion/Spreading:
  • Real-time monitoring of cell adhesion and spreading.
  • Label-free assay requires no fixation, staining or any other sample processing.
  • Direct, sensitive, and quantitative.
  • Easy quantification of the kinetics of adhesion and spreading.
  • Rapid optimization of cell density and extracellular matrix coating conditions.
Cell Adhesion/Spreading Supporting Information:

  • Cell Adhesion/Spreading – Compatible xCELLigence System:
xCELLigence RTCA DP xCELLigence RTCA SP xCELLigence RTCA MP xCELLigence RTCA HT xCELLigence iCELLigence
RTCA DP RTCA SP RTCA MP iCELLigence
3×16 wells 1×96 wells 6×96 wells Up to 4×384 wells 2×8 wells
  • Cell Adhesion and Spreading Publications 
  1. Using cell-substrate impedance and live cell imaging to measure real-time changes in cellular adhesion and de-adhesion induced by matrix modification. Rees, M. D., Thomas, S. R. Vis. Exp. (96), e52423, doi:10.3791/52423 (2015).
  2. Curcumin targets breast cancer stem-like cells with microtentacles that persist in mammospheres and promote reattachment. Charpentier MS, Whipple RA, Vitolo MI, Boggs AE, Slovic J, Thompson KN, Bhandary L, Martin SS. Cancer Res. 2014 Feb 15;74(4):1250-60.
  3. New blocking antibodies impede adhesion, migration and survival of ovarian cancer cells,highlighting MFGE8 as a potential therapeutic target of human ovarian carcinoma. Tibaldi L, Leyman S, Nicolas A, Notebaert S, Dewulf M, Ngo TH, Zuany-Amorim C,Amzallag N, Bernard-Pierrot I, Sastre-Garau X, Théry C. PLoS One. 2013 Aug 16;8(8):e72708.
  4. A role for adhesion and degranulation-promoting adapter protein in collagen-induced platelet activation mediated via integrin a2b1. Jarvis GE, Bihan D, Hamaia S, Pugh N, Ghevaert CJ, Pearce AC, Hughes CE, Watson SP,Ware J, Rudd CE, Farndale RW. J Thromb Haemost. 2012 Feb;10(2):268-77.
  5. Dynamic monitoring of cell adhesion and spreading on microelectronic sensor arrays. Josephine M. Atienza, Jenny Zhu, Xiaobo Wang, Xiao Xu and Yama Abassi. J Biomol Screen. 2005 Dec;10(8):795-805.

Click here to download the full list (PDF) of publications citing xCELLigence in Cell Adhesion and Spreading research

Cell-Cell Interactions: Co-Culture

Growth Factor Induced Proliferation of T47D Cells

Growth Factor Induced Proliferation of T47D Cells

Monitoring of T47D cellular response to H295R estrogen signaling. Estrogen and progesterone receptor positive T47D breast cancer cells were grown on xCELLigence E-plates. After a coculture insert containing H295R adrenal corticocarcinoma cells, known to produce estrogen and progesterone, was placed on the E-plate. The response of the T47D cells to the secreted hormones was suppressed by the application of estrogen synthesis inhibitors (A) Ketoconazole and (B) Anastrazole to the stimulatory H295R cells. (Unpublished data from ACEA Biosciences.)

Key Benefits of Using xCELLigence for Studying Cell-cell Interaction:
  1. Label free environment allows detection of responses due to stimulation of endogenous receptors
  2. Kinetic response profiles may be diagnostic for specific pathways
  3. Real time data provides comprehensive information on cell responses over long time periods
  4. E-Plate Insert offers an easy to setup co-culture platform with minimal handling
Cell-Cell Interaction Supporting Information:

  • Cell-Cell Interaction – Compatible xCELLigence System:
xCELLigence RTCA DP xCELLigence RTCA SP xCELLigence RTCA MP
RTCA DP RTCA SP RTCA MP
3×16 wells 1×96 wells 6×96 wells
  • Cell-Cell Interaction Publications:
  1. A unique co-culture model for fundamental and applied studies of human fetoplacental steroidogenesis and interference by environmental chemicals.  Thibeault AA, Deroy K, Vaillancourt C, Sanderson JT.  Environ Health Perspect. 2014 Apr;122(4):371-7.
  2. Dynamic assessment of cell viability, proliferation and migration using real time cell analyzer system (RTCA).  Roshan Moniri M, Young A, Reinheimer K, Rayat J, Dai LJ, Warnock GL.  Cytotechnology. 2015 Mar;67(2):379-86.

Cell-Response Profiling

Using the xCELLigence System for Target Identification and Validation

Application_Book_08_01
(A) HeLa cells were transfected with various concentrations of KIF11 (the gene encoding Eg5) siRNA. A time and concentration-dependent antimitotic time-dependent cell response profiles (TCRPs) was observed with higher siRNA concentrations producing more pronounced CI changes. The kinetics of the CI profiles is very similar between various concentrations of siRNAs: CI for the transfected samples started to diverge from the control samples starting 9-12 h post transfection, reaching the lowest level approximately 24 h post transfection, before starting to recover, indicating the specifi city of the TCRP. KIF11 gene express is supported with analysis of Eg5 protein expression by Western blotting (B). (Data and figures adapted from Ke N, et. al., 2010).

Using “Signature” TCRPs to Identify Compound Properties for Screening

Application_Book_08_02
Compounds with similar mechanisms of action often have similar TCRPs. (A) In A549 cells, both anti-mitotic compounds, paclitaxel and vincristine, mediated the signature anti-mitotic response profile; the DNA damaging agent 5-FU mediated a cytostatic pattern, while the topoisomerase inhibitor camptothecin mediated pronounced cytotoxicity. (B) Cell Index values are consistent with bright-fi eld imaging in the E-Plate View area. (Data and figures adapted from iCELLigence System Application Note No.2, 2012).

Key Benefits of Using xCELLigence for Studying Cell-Response Profiling:  
  1. Real-time monitoring of kinetics of cell responses to treatment can reveal novel information regarding mechanism of action.
  2. Assays are performed in tissue culture incubator, allowing for detection of long-term effects.
  3. Label-free assay requires no fixation, staining or any other sample processing.
  4. Cell response profiles can allow for early identification of unexpected off-target or toxic effects of treatments.
Cell-Response Profiling Supporting Information:

  • Cell-Response Profiling Publications
  1. Identification of genomic alterations in oesophageal squamous cell cancer. Song Y, Li L, Ou Y, Gao Z, Li E, Li X, Zhang W, Wang J, Xu L, Zhou Y, Ma X, Liu L, Zhao Z,Huang X, Fan J, Dong L, Chen G, Ma L, Yang J, Chen L, He M, Li M, Zhuang X, Huang K,Qiu K, Yin G, Guo G, Feng Q, Chen P, Wu Z, Wu J, Ma L, Zhao J, Luo L, Fu M, Xu B, Chen B, Li Y, Tong T, Wang M, Liu Z, Lin D, Zhang X, Yang H, Wang J, Zhan Q. Nature. 2014 May 1;509(7498):91-5.
  2. Time-resolved human kinome RNAi screen identifies a network regulating mitotic-events as early regulators of cell proliferation. Zhang JD, Koerner C, Bechtel S, Bender C, Keklikoglou I, Schmidt C, Irsigler A, Ernst U,Sahin O, Wiemann S, Tschulena U. PLoS One. 2011;6(7):e22176. Epub 2011 Jul 13.
  3. Screening and identification of small molecule compounds perturbing mitosis using time-dependent cellular response profiles. Ke N, Xi B, Ye P, Xu W, Zheng M, Mao L, Wu MJ, Zhu J, Wu J, Zhang W, Zhang J, Irelan J, Wang X, Xu X, Abassi YA. Anal Chem. 2010 Aug 1;82(15):6495-503.
  4. RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing’s sarcoma. Arora S, Gonzales IM, Hagelstrom RT, Beaudry C, Choudhary A, Sima C, Tibes R,Mousses S, Azorsa DO. Mol Cancer. 2010 Aug 18;9:218.
  5. BH3 response profiles from neuroblastoma mitochondria predict activity of small molecule Bcl-2 family antagonists. Goldsmith KC, Lestini BJ, Gross M, Ip L, Bhumbla A, Zhang X, Zhao H, Liu X, Hogarty MD. Cell Death Differ. 2010 May;17(5):872-82.
  6. Kinetic cell-based morphological screening: prediction of mechanism of compound action and off-target effects. Abassi YA, Xi B, Zhang W, Ye P, Kirstein SL, Gaylord MR, Feinstein SC, Wang X, Xu X. Chemistry & biology. 2009 Jul 31;16(7):712-23.

Cytotoxicity Overview

Cytotoxicity is the general quality of being toxic to cells, and can be caused by chemical stimuli, exposure to other cells (NK or T cells for example), or physical/environmental conditions (radiation exposure, temperature or pressure extremes, etc.).  Cytotoxic treatment can result in one of three potential cellular fates.  Whereas necrotic cell death involves the rapid loss of membrane integrity and cell lysis, apoptotic cell death is slower, more orderly, and is genetically controlled.  Cytostasis is a special category of cytotoxicity wherein cells remain alive but fail to grow and divide.

Traditional assays for evaluating cytotoxicity typically probe membrane integrity, looking at the passage of labels into the cell or the leakage of biomolecules out of the cell.  One of the major drawbacks of these assays is the fact that they provide only endpoint data.  In contrast, xCELLigence real-time cell analysis (RTCA) allows cells to be monitored, in the absence of labels, continuously and automatically throughout the entire course of an experiment.  Besides reducing the hands-on time required to run a cytotoxicity assay, the real-time data traces generated by xCELLigence ensure that subtleties of the cytotoxic response aren’t missed.

As described in the Technology Overview, xCELLigence® real time cell analysis (RTCA) interrogates the ability of electrodes in the bottom of E-Plate® wells to conduct electric current.  Adhesion of cells to these electrodes impedes electric current, providing exquisite sensitivity to (1) the number of cells present, (2) the size/morphology of the cells, and (3) how tightly the cells are interacting with the plate surface.  Cytotoxic responses nearly always involve biochemical changes that directly, or indirectly, affect one or more of the above three parameters.  Consequently, xCELLigence is able to monitor cytotoxic responses resulting from an exceptionally wide range of molecular targets (Figure 1).

Cytotoxicity Overview Fig 1.1

For specific examples of using xCELLigence to study cytotoxicity, see:

For examples of using xCELLigence to study cell-mediated cytotoxicity for cancer immunotherapy, see:

 

Cytotoxicity: Compound-Mediated Cytotoxicity

Kinetic Response Profiles Reflect Different Cytotoxic Mechanisms
Application_Book_02_01

HepG2 cells were treated with various cytotoxic compounds and monitored in real time for cytotoxic response kinetics. Representative compounds targeting tubulin (paclitaxel), actin (cytochalasin D), DNA (doxorubicin), mitochondria (rotenone), calcium homeostasis (thapsigargin), and protein transport (brefeldin A) generated distinct response profiles. (Data and figure adapated from ACEA Biosciences, Inc. unpublished data).

Real Time Monitoring Allows Identification of Optimal Timepoints for Further Analysis​

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HeLa cells were treated with cytotoxic compounds and monitored in real time for cytotoxic response kinetics on xCELLigence. At the indicated timepoints, cells in a parallel plate were analyzed using the WST-1 cell viability assay. 5-FU or MG132 caused different dose-dependant kinetic response profiles with different optimal times for performing the WST-1 assay. (Data and figure adapted from Ke N, et. al., 2011).

Key Benefits of Using xCELLigence for Studying Compound-mediated Cytotoxicity:
  1. Kinetic responses can be predictive of mechanism of action.
  2. Continuous monitoring ensures no meaningful time points are missed.
  3. Real-time data allows identification of the optimal times for treatment and data collection.
  4. Non-invasive assay is performed in tissue culture incubator, allowing for analysis by standard viability assays at any point during the experiment.
  5. Easy quantification of the onset and kinetics of the cytotoxic response.
Compound-mediated Cytotoxicity Supporting Information:

  • Compound-Mediated Cytotoxicity Publications
  1. The xCELLigence system for real-time and label-free monitoring of cell viability. Ke N, Wang X, Xu X, Abassi Y. Methods Mol Biol. 2011;740:33-43.
  2. Kinetic cell-based morphological screening: prediction of mechanism of compound action  and off-target effects. Abassi YA, Xi B, Zhang W, Ye P, Kirstein SL, Gaylord MR, Feinstein SC, Wang X, Xu X. (2009). Chem Biol. 2009;16:712-23.
  3. Dynamic monitoring of cytotoxicity on microelectronic sensors. Xing JZ, Zhu L, Jackson JA, Gabos S, Sun XJ, Wang XB, Xu X. Chem Res Toxicol. 2005;18:154-61.

Cytotoxicity: Nanotoxicity

Nanomaterials are organic or inorganic particles whose size is less than 100 nanometers in at least one dimension.  Though nanomaterials hold tremendous promise for myriad applications, their impact on living cells in the short and long term are incompletely understood.  Numerous studies have suggested that nanomaterials, even when made of inert materials, can still display toxicity because of their physical properties (size, shape).  Moreover, nanomaterials have been shown to cause oxidative stress, cytokine production, and cell death.  Understanding the multifaceted cytotoxicity of nanoparticles is thus important to public health.  A challenge in characterizing the effect of nanoparticles on cells is that – because of their high adsorption capacity, high optical activity, redox potential, and chemical reactivity – some particle types interfere with conventional techniques for assessing cell viability/health (Figure 1).
Nantoxicity Fig 1Figure 1.  Nanoparticles can interfere with traditional toxicity/viability assays. The high adsorption capacity, high optical activity, redox potential, and/or chemical reactivity of certain types of nanoparticles make them incompatible with traditional cell viability assays.

As an alternative, label-free means of evaluating nanoparticle induced cytotoxicity, impedance-based xCELLigence real-time cell analysis (RTCA) has proven to be extremely effective.  In a study by Scott Boitano and colleagues at the University of Arizona the potential cytotoxicity of 11 different inorganic nanomaterials (Ag0, Al2O3, CeO2, Fe0, Fe2O3, HfO2, Mn2O3, SiO2, TiO2, ZnO, and ZrO2) was evaluated using the 16HBE14o- human bronchial epithelial cell line.  The effect of these different materials varied greatly (only four are shown here).  Whereas Mn2O3 was strongly cytotoxic, SiO2 and Al2O3 were moderately toxic, and CeO2 had no effect at the concentrations tested (Figure 2).
An important question is whether the results obtained by RTCA correlate with results obtained using orthogonal techniques.  As seen in Figure 3, data from a side-by-side MTT end point assay correlates extremely well with the RTCA assay.  This publication and others like it have firmly established that the accuracy and reproducibility of RTCA assays, coupled with the reduced work load and continuous data acquisition (no data points are “missed”) make the xCELLigence system an excellent means of evaluating nanotoxicity.

Nantoxicity Fig 2

Figure 2.  Real-time impedance monitoring of nanoparticle-induced cytotoxicity. At the ~17 hour time point (denoted by the dashed vertical line) 16HBE14o- human bronchial epithelial cells were exposed to different concentrations of the indicated nanoparticles, and impedance was monitored continuously for the next ~60 hours. (A) Nano-CeO2 concentrations (mg/L): 0 (—), 250 (— • —), 500 (- – -), and 1000 (•••). (B) Nano-Al2O3 concentrations (mg/L): 0 (—), 250 (— • —), 500 (- – -), and 1000 (•••). (C) Nano-SiO2 concentrations (mg/L): 0 (—), 100 (— • —), 200 (- – -), 300 (•••), and 600 (— —). (D) Nano-Mn2O3 concentrations (mg/L): 0 (—), 10 (— • —), 20 (- – -), 50 (•••), and 100 (— —).

 


Nantoxicity Fig 3
Figure 3.  Comparison of cytotoxicity measurements made using xCELLigence (•) vs. MTT (○) assay. Percent of response (relative to untreated control) is plotted as a function of nanoparticle concentration.

 

Key Benefits of Using xCELLigence for Studying Nanotoxicity:
  • Impedance detection method is not interfered with by nanoparticles.
  • Continuous monitoring ensures no meaningful data points are missed.
  • Real-time data allows identification of the optimal times for treatment and data collection.
  • Non-invasive assay is performed in tissue culture incubator, allowing for analysis by orthogonal standard viability assays at any point during the experiment.
  • Easy quantification of the onset and kinetics of the cytotoxic response.
Nanotoxicity Supporting Information:

  • Adherent cell lines tested:
    A549, SK-MES-1, CHO-K1, Calu-3, THP-1, mesenchymal stromal cells (MSCs), Hep3B, Caki-1, 16HBE14o-, HEK-293, HACAT, Chang , BEAS-2B, T98G, H9C2, PC-3, FibroGRO, EAhy926, L929, V79, HepG2, HT29, SK-BR-3, JEG-3, and HeLa
  • Nanotoxicity Publications:
  1. Application and validation of an impedance-based real time cell analyzer to measure the toxicity of nanoparticles impacting human bronchial epithelial cells. Otero-González L, Sierra-Alvarez R, Boitano S, Field JA.  Environ Sci Technol. 2012 Sep 18;46(18):10271-8.
  2. Interference of engineered nanoparticles with in vitro toxicity assays. Kroll A, Pillukat MH, Hahn D, Schnekenburger J.  Arch Toxicol. 2012 Jul;86(7):1123-36.
  3. Real-time cell-microelectronic sensing of nanoparticle-induced cytotoxic effects. Birget Moe B, Gabos S, Li X-F.  Analytica Chimica Acta 789, 2013, 83– 90.

Functional Analysis of Genes & Proteins: siRNA

Using the xCELLigence System for Target Identification and Validation

Functional Analysis Fig 1.1 Functional Analysis Fig 1.2

(A) HeLa cells were transfected with various concentrations of KIF11 (the gene encoding Eg5) siRNA.  A time and concentration-dependent antimitotic time-dependent cell response profiles (TCRPs) was observed with higher siRNA concentrations producing more pronounced CI changes. The kinetics of the CI profiles is very similar between various concentrations of siRNAs: CI for the transfected samples started to diverge from the control samples starting 9-12 h post transfection, reaching the lowest level approximately 24 h post transfection, before starting to recover, indicating the specificity of the TCRP.  KIF11 gene express is supported with analysis of Eg5 protein expression by Western blotting (B).  (Data and figures adapted from Ke N, et. al., 2010).

Using “Signature” TCRPs to Identify Compound Properties for Screening

Functional Analysis Fig 2

Compounds with similar mechanisms of action often have similar TCRPs. (A) In A549 cells, both anti-mitotic compounds, paclitaxel and vincristine, mediated the signature anti-mitotic response profile; the DNA damaging agent 5-FU mediated a cytostatic pattern, while the topoisomerase inhibitor camptothecin mediated pronounced cytotoxicity. (B) Cell Index values are consistent with bright-field imaging in the E-Plate View area. (Data and figures adapted from iCELLigence System Application Note No.2, 2012).

Key Benefits of Using xCELLigence for Studying Functional Analysis of Genes and Proteins:
  1. Real-time monitoring of kinetics of cell responses to treatment can reveal novel information regarding mechanism of action
  2. Assays are performed in tissue culture incubator, allowing for detection of long-term effects
  3. Label-free assay requires no fixation, staining or any other sample processing
  4. Cell response profiles can allow for early identification of unexpected off-target or toxic effects of treatments
Functional Analysis of Genes and Proteins Supporting Information:

  • Functional Analysis of Genes and Proteins Publications:
  1. Kinetic cell-based morphological screening: prediction of mechanism of compound action and off-target effects. Abassi YA, Xi B, Zhang W, Ye P, Kirstein SL, Gaylord MR, Feinstein SC, Wang X, Xu X. Chemistry & biology. 2009 Jul 31;16(7):712-23.
  2. Time-resolved human kinome RNAi screen identifies a network regulating mitotic-events as early regulators of cell proliferation. Zhang JD, Koerner C, Bechtel S, Bender C, Keklikoglou I, Schmidt C, Irsigler A, Ernst U, Sahin O, Wiemann S, Tschulena U. PLoS One. 2011;6(7):e22176. Epub 2011 Jul 13.
  3. Screening and identification of small molecule compounds perturbing mitosis using time- dependent cellular response profiles. Ke N, Xi B, Ye P, Xu W, Zheng M, Mao L, Wu MJ, Zhu J, Wu J, Zhang W, Zhang J, Irelan J, Wang X, Xu X, Abassi YA. Anal Chem. 2010 Aug 1;82(15):6495-503.
  4. RNAi phenotype profiling of kinases identifies potential therapeutic targets in Ewing’s sarcoma. Arora S, Gonzales IM, Hagelstrom RT, Beaudry C, Choudhary A, Sima C, Tibes R, Mousses S, Azorsa DO. Mol Cancer. 2010 Aug 18;9:218
  5. BH3 response profiles from neuroblastoma mitochondria predict activity of small molecule Bcl-2 family antagonists. Goldsmith KC, Lestini BJ, Gross M, Ip L, Bhumbla A, Zhang X, Zhao H, Liu X, Hogarty MD. Cell Death Differ. 2010 May;17(5):872-82.

Immune Cell Activation

Real-Time Monitoring of Mast Cell Degranulation in RBL-2H3 Mast Cell Line

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(A) Real-time acquisition of impedance-based measurements captures immediate kinetic profi le changes of RBL-2H3 when sensitized with IgE and subsequently stimulated with DNP-BSA. (B) Rhodamine-phalloidin staining of sensitized and activated RBL-2H3 cells performed in parallel to the impedance assay indicates that stimulated cells undergo cytoskeleton rearrangements which correlate with the IgE-mediated impedance responses. (Data and figures adapated from Abassi YA., et. al., 2004).

Real-Time Monitoring of T-cell Activation by CD3 and CD28

Application_Book_13_02
Dynamic monitoring of T cell activation using the xCELLigence system. (A) Jurkat cells were seeded onto coated E-plates in the presence of indicated concentrations of anti-CD3 and anti-CD28 functional antibodies, shown as cell index (CI). (B) The dose response curve was plotted using the Cell Index Value at the time point indicated with the dotted line in panel A. (C) Effect of mixed anti-CD3 and anti-CD28 antibodies on rearrangement of actin cytoskeleton. Actin staining is shown in green and nuclear staining in blue. The left panel image shows negative control cells and the right panel image shows cells stimulated with anti-CD3 and anti-CD28 functional antibodies at 1 mg/ml. (Data and figure adapted from Guan N, et. al., 2013).

Key Benefits of Using xCELLigence for Studying Immune Cell Activation:
  • Novel assay platform to support research on allergic inflammation.
  • Sensitive and rapid real-time readout for morphology changes associated with immune cell activation.
  • Screening for modulators of IgE-function and mast cell activation.
  • Eliminate time-consuming, laborious sample processing required by the standard assay.
Immune Cell Activation Supporting Information:

  • Immune Cell Activation Publications:
  1. Label-free monitoring of T cell activation by the impedance-based xCELLigence system. Guan N, Deng J, Li T, Xu X, Irelan JT, Wang MW. Mol Biosyst. 2013 May;9(5):1035-43.
  2. Label-free, real-time monitoring of IgE-mediated mast cell activation on microelectronic cell sensor arrays. Yama A. Abassi, Jo Ann Jackson, Jenny Zhu, James O’ Connell, Xiaobo Wang, Xiao Xu. Journal of Immunological Methods. 2004;292 (1-2):195-205.

In Vitro Hypoxia Studies

Hypoxia, where the body or localized regions of the body are deprived of adequate oxygen supply, occurs during numerous acute and chronic disease states.  Examples include reduced blood flow during heart attack or stroke, and the oxygen-restricted microenvironment within a tumor.  Though cells can be studied in vitro under similar oxygen-poor conditions using a hypoxia chamber glove box, the inefficiencies of traditional endpoint assays are exacerbated by the constraints of working inside the chamber.  In contrast, an xCELLigence instrument run within a hypoxia chamber will continuously provide a real-time assessment of cell number, cell size/morphology, cell attachment quality, and cell migration/invasion without the need for intermittent manipulation/intervention by the researcher.

In the below example ACEA’s xCELLigence® RTCA DP instrument and electronic cell invasion and migration plate (CIM-Plate®) are used to monitor the ability of Ewing sarcoma cells to undergo chemotactic migration under normoxic vs. hypoxic conditions. Using the ligand SDF-1a as chemoattractant, it is first shown that CXCR4 (the most commonly expressed chemokine receptor in human cancer) promotes migration: chemical inhibition of CXCR4 with the small molecule AMD3100 causes significant reduction in the rate of migration (Figure A).  Next, the effect of exposing Ewing sarcoma cells to multiple stresses simultaneously is evaluated.  Moving serum-starved cells from a normoxic to a hypoxic atmosphere dramatically increased their rate of migration towards SDF-1a chemoattractant (Figure B).

Role of CXCR4 and Hypoxia on Chemotactic Migration of Ewing Sarcoma Cells. (A) Real-time analysis of Ewing sarcoma cell line migration. Cell index correlates linearly with the number of cells that have migrated through the pores of the CIM-Plate® toward the chemoattractant SDF-1a in the lower chamber. AMD3100 is a small molecule inhibitor of the chemokine receptor protein CXCR4. (B) Hypoxia increases the rate of migration of serum-deprived Ewing sarcoma cell line. Figures adapted from Molecular Cancer Research 2014 June, 12(6), 953-964.

Importantly, the above study highlights the flexibility and power of real-time cell analysis using xCELLigence®.  The quality and quantity of data generated in this study would be extremely difficult to match using traditional end point analyses conducted within a hypoxia chamber.

Key Benefits of Using xCELLigence for Studying In Vitro Hypoxia:
  • Data quantity: Automatic real-time data acquisition makes it possible to collect, with ease, significantly more data points than what is possible using traditional end point assays. This is especially true for hypoxia studies because manual acquisition of end points inside a hypoxia chamber is difficult and laborious.
  • Data quality and reproducibility are significantly better than what is possible using end point assays.
  • Time savings: Once cells are plated, data can be acquired continuously for anywhere from minutes to days/weeks without the need for hands-on time by the researcher.

All seven xCELLigence instruments are compatible with in vitro hypoxia studies.  To learn more about them, click here.

In Vitro Hypoxia Studies Supporting Information:

  • In Vitro Hypoxia Studies Publications:
  1. Bach1 differentially regulates distinct Nrf2-dependent genes in human venous and coronary artery endothelial cells adapted to physiological oxygen levels. Chapple SJ, Keeley TP, Mastronicola D, Arno M, Vizcay-Barrena G, Fleck R, Siow RC, Mann GE. 2015 Dec 15. pii: S0891-5849(15)01166-1.
  2. In vitro oxygen availability modulates the effect of artesunate on HeLa cells. Murray J, Gannon S, Rawe S, Murphy JE. Anticancer Res. 2014 Dec;34(12):7055-60.
  3. Stress-induced CXCR4 promotes migration and invasion of ewing sarcoma. Krook MA, Nicholls LA, Scannell CA, Chugh R, Thomas DG, Lawlor ER.  Mol Cancer Res. 2014 Jun;12(6):953-64.
  4. Hypoxia-driven cell motility reflects the interplay between JMY and HIF-1α. Coutts AS, Pires IM, Weston L, Buffa FM, Milani M, Li JL, Harris AL, Hammond EM, La Thangue NB.  2011 Dec 1;30(48):4835-42.

Parasitic Worm Motility and Viability

Parasitic Worm Motility and ViabilityDespite the prevalence and expense of parasitic worm (helminth) infection worldwide, the helminth-specific pharmacopeia is extremely limited.  This is historically due, in part, to the paucity of objective high-throughput drug screening methods amenable to the life cycle of these parasites.  Though hampered by observer subjectivity and low throughput capacity, for many years the gold standard assay for anthelmintic drug screening involved manual in vitro assessment of worm motility using a microscope.  However, it was recently shown that xCELLigence® real-time impedance monitoring is able to quantify parasitic worm motility (which is a surrogate of viability).

When a helminth is placed within an E-Plate® well, its movement/writhing changes the electrode surface area being contacted, and the resultant impedance changes can be used to quantify worm motility/viability (see figure).  Since this initial discovery, xCELLigence® has been adopted within this research community for looking at multiple helminth species and different developmental stages.  The ability to quantitatively monitor multiple developmental stages is particularly important as it allows a broader net to be cast during drug screening efforts: as each stage in a parasitic worm’s life cycle may display differential drugability, being able to monitor multiple stages increases the chances of success.

Application of xCELLigence® to parasitic worm studies serves to further expound upon a theme already well established in the area of cell-based assays: the sensitivity and flexibility of real-time impedance measurement using xCELLigence® enables researchers to easily and cheaply study phenomena that were previously either inaccessible or very laborious, costly, inefficient, and poorly reproducible.

Key Benefits of Using xCELLigence for Studying Worm Motility/Viability:
  • Objective quantification: Subjective human observations of worm motility are replaced with objective real-time data.
  • Reduced workload: Once worms are placed in the wells of an E-Plate® and data acquisition has been initiated, no further involvement is required. Data is continuously recorded for anywhere from minutes to days/weeks.
  • Flexibility: A wide range of buffer compositions can be used, and multiple developmental stages of the worm can be evaluated. Moreover, the frequency of the AC current used to measure impedance can be adjusted, enabling optimization of signal to noise ratio.
Worm Motility/Viability Supporting Information:

  • Worm Motility/Viability Publications:
  1. A novel high throughput assay for anthelmintic drug screening and resistance diagnosis by real-time monitoring of parasite motility. Smout MJ, Kotze AC, McCarthy JS, Loukas A.  PLoS Negl Trop Dis. 2010 Nov 16;4(11):e885.
  2. Viability of developmental stages of Schistosoma mansoni quantified with xCELLigence worm real-time motility assay (xWORM). Rinaldi G, Loukas A, Brindley PJ, Irelan JT, Smout MJ.  (2015).  Int J Parasitol Drugs Drug Resist. 2015 Aug 6;5(3):141-8.
  3. Reversible paralysis of Schistosoma mansoni by forchlorfenuron, a phenylurea cytokinin that affects septins. Zeraik AE, Galkin VE, Rinaldi G, Garratt RC, Smout MJ, Loukas A, Mann VH, Araujo AP, DeMarco R, Brindley PJ. Int J Parasitol. 2014 Jul;44(8):523-31.
  4. Transcriptional Responses of In Vivo Praziquantel Exposure in Schistosomes Identifies a Functional Role for Calcium Signaling Pathway Member CamKII. You H, McManus DP, Hu W, Smout MJ, Brindley PJ, Gobert GN.    PLoS Pathog. 2013 Mar;9(3):e1003254.
  5. Exploration of novel in vitro assays to study drugs against Trichuris spp. Silbereisen A, Tritten L, Keiser J. J Microbiol Methods. 2011 Nov;87(2):169-75.
  6. Comparison of novel and existing tools for studying drug sensitivity against the hookworm Ancylostoma ceylanicum in vitro. Tritten L, Braissant O, Keiser J.  2012 Mar;139(3):348-57.

Phenotypic Screening

Phenotypic Screening: Probing Efficacy and Mechanism of Action Simultaneously

Because the ultimate effect of drugs are the net result of on-target and less well understood off-target interactions, the assays traditionally employed in drug discovery and development usually suffer from at least one limitation.  Due to their readout being so narrow, target-focused biochemical assays have a higher probability of failing to identify efficacious compounds.  If a drug does indeed achieve the desired phenotypic result (such as killing a cancer cell) it will still go undiscovered if it operates via a mechanism different than what is being evaluated in the biochemical assay (i.e. when the compound has an off-target activity that is beneficial).

The focused nature of biochemical assays also precludes them from being able to identify detrimental off-target activity.  In contrast, cell-based assays are less biased and can therefore effectively identify compounds with the desired phenotypic result, but usually do not provide information about the biochemical mechanism of action (MOA).  xCELLigence® real-time cell analysis (RTCA) assays provide the best of both worlds: in addition to efficiently detecting whether a drug has an effect on cell health/behavior, specific features of the cellular impedance traces and kinetics can be predictive of MOA.

Highly Effective Evaluation of Drug Efficacy

RTCA provides a quantitative readout of cell number/proliferation rate, cell size/shape, and cell-substrate attachment quality.  Because these physical properties are the product of thousands of different genes/proteins, RTCA casts a very wide net during drug screening.  Everything from endothelial barrier function and GPCR antagonism to filopodia dynamics and immune cell-mediated cytolysis have successfully been analyzed on xCELLigence instruments.  Despite the breadth of phenomena accessible with RTCA, sensitivity is in no way compromised. The gold microelectrodes used in ACEA’s E-Plates® cover ~75% of the well bottoms, enabling the simultaneous monitoring of very large numbers of cells – which provides exquisite sensitivity.

Beyond sensitivity, the efficacy of drug screening with xCELLigence is further enhanced by the continuous, real-time nature of data recording.  Drugs display a broad spectrum in the rate at which they exert their effect on target cells.  While some compounds (such as agonists of GPCRs or ion channels) cause immediate biochemical and cellular changes, other compounds display an effect at much later time points.  Moreover, some drugs display multiple and kinetically distinct effects.  For these reasons, traditional end point assays have a high probability of not identifying key features of drug responses.  The fact that xCELLigence systems interrogate cell number, cell size/shape, and cell-substrate attachment quality continuously makes them extremely adept at evaluating drug efficacy.  In short, end points are replaced by continuous data traces, so nothing is missed.

Predicting MOA

Drugs that impinge upon the same protein target or biochemical pathway typically effect similar phenotypic results.  Consistent with this, the glucocorticoid receptor agonists hydrocortisone, betamethasone, and clobetasol all produce similar RTCA data traces (Figure 1).  The same is true for the family of drugs that interfere with microtubule equilibrium/dynamics.  Importantly, even though nocodazole and paclitaxel are structurally unrelated and influence different stages of microtubule formation, their RTCA data traces are nearly identical.  This suggests that the unique impedance trace observed for this category of compounds is indicative of a common underlying global cellular response (i.e. the same cellular machinery is involved).  Drugs that act as GPCR antagonists or calcium modulators also display RTCA traces similar to one another, yet different from other drug families.  The RTCA trends highlighted in Figure 1 apply to many more compounds, and many more drug families, than just those shown here.

Phenotypic Screening 1

The mechanistic specificity of RTCA traces is highlighted by the fact that drugs which produce the same phenotypic outcome via different MOAs can readily be differentiated from one another.  Both staurosporine and 5-fluorouracil induce apoptosis, but do so via different mechanisms.  Staurosporine promiscuously inhibits protein kinases, while 5-fluorouracil inhibits DNA synthesis indirectly by blocking dTMP synthesis.  When analyzed by RTCA these two compounds cause very distinct responses (Figure 2).

Phenotypic Screening 2

The above data suggest that in contrast to traditional screening methodologies that can only reveal whether a drug is efficacious, a single RTCA data traces can be used both to evaluate efficacy and to provide strong evidence for a specific mechanism of action.  Phenotypic Screening 3This capacity for predicting MOA is highlighted in Figure 3.  While screening a 2,000 compound library for effects on the health/behavior of A549 cells, dibenzyltrisulfide was found to induce an RTCA data trace similar to that of epothilone B, which induces mitotic arrest by stabilizing microtubules.   When subjected to biochemical characterization dibenzyltrisulfide was indeed found to disrupt the microtubule cytoskeleton, and to do this specifically by inhibiting tubulin assembly into microtubules.

Identifying Off-Target Activity

The inability of target-specific drug screening approaches to identify off target activity is a major obstacle and liability.  The sensitivity of xCELLigence RTCA combined with the breadth of phenomena that it is able to observe make it possible to identify off target drug activities that previously went undetected.  Phenotypic Screening 4The long term cellular impedance response of A549 cells to s-trityl-cysteine and monastrol are nearly superimposable – which is expected in light of the fact that both compounds act as antimitotics by inhibiting the kinesin Eg5 motor protein (Figure 4).  A significant difference between these two compounds is, however, observed shortly after treatment initiation.  The monastrol-induced early/rapid drop in impedance resembles what has been observed in the RTCA profiles of compounds that modulate intracellular calcium levels.  Subsequent analyses (the details of which can be read about here) verified that, monastrol possesses a previously unknown ability to block calcium uptake through Cav1.2 channels.

Key Benefits of xCELLigence for Phenotypic Screening
  • The integrated, global response of cells to treatment is monitored – enabling a very wide net to be cast during drug screening. Cell number, size/shape, and attachment quality are the products of thousands of different genes and proteins. Monitoring these physical parameters simultaneously enables xCELLigence to efficiently identify compounds with biological activity.
  • The kinetics of cellular responses can be predictive of compound mechanism of action.
  • RTCA impedance traces can provide an early alert to possible off-target or toxic effects of a compound.
  • Since real-time impedance assays are non-invasive and conducted under standard tissue culture conditions, at any time during an assay cells can still be harvested and analyzed by orthogonal methods to verify phenotype.
Phenotypic Screening Supporting Information:

  • Phenotypic Screening Publications:
  1. Screening and identification of small molecule compounds perturbing mitosis using time-dependent cellular response profiles. Ke N, Xi B, Ye P, Xu W, Zheng M, Mao L, Wu MJ, Zhu J, Wu J, Zhang W, Zhang J, Irelan J, Wang X, Xu X, Abassi YA.  Chem. 2010, 82, 6495-6503.
  2. Kinetic cell-based morphological screening: prediction of mechanism of compound action and off-target effects. Abassi YA, Xi B, Zhang W, Ye P, Kirstein SL, Gaylord MR, Feinstein SC, Wang X, Xu X.  Biol. 2009, 16, 712-723.
 

Quality Control of Cells

Though a great deal of attention is typically paid to optimizing the conditions and reagents used in cell-based assays, quality control of the cells themselves is frequently overlooked.  Human errors such as mislabeling or cross contaminating cell lines can lead to researchers working with cells of unintended identity.

QC 1

Moreover, even in the absence of errors/contamination, the inherent genetic instability of many cell lines and the epigenetic modifications resulting from culture conditions/passage number can have an effect on cellular phenotype – confounding fundamental research or drug screening efforts.  Genotyping methods such as short tandem repeat profiling can verify cellular identity but do not exhaustively prove the absence of genetic modification and cannot elucidate changes in cell behavior resulting from epigenetic modification.  By providing information about phenotype (cell-substrate attachment quality, cell size and morphology, and the kinetics of cell proliferation) xCELLigence® real-time cell analysis (RTCA™) using impedance measurement provides a quick, easy, and cost effective means of validating cell identity and health.

As proof of principle consider the below impedance traces for three different cell lines.  A549 (adenocarcinomic human alveolar basal epithelial cell line), GTL16 (gastric carcinoma cell line), and SHSY5Y (neuroblastoma cell line) cells display markedly different real-time impedance traces for cell attachment and growth (Figure 1) – validating xCELLigence as a means of differentiating between cell types.

QC 2

As a more subtle RTCA analysis requiring quantitative comparison between different cell sources, an xCELLigence® instrument was used to monitor the real time growth of HeLa cell lines obtained from the American Type Culture Collection (ATCC), three academic labs, and two biotech labs.  Though visual inspection revealed some morphological heterogeneity within and between these six cell lines, “none showed morphologies that were unambiguously outside the range of normal HeLa cells” (Figure 2A).  Despite this, real-time impedance curves revealed the cell line from lab 5 to have attachment and growth characteristics dramatically different from the other cell lines (Figures 2B and C).

QC 3

For a more thorough examination of how xCELLigence® can be used for cell quality control, and why this is superior to other methods, please see the following Application Note and the publications listed at the bottom of this page.

Key Benefits of Using xCELLigence for Quality Control of Cells:
  • Cell identity validation: Using the RTCA trace of a reference cell type, the identity of new stocks of the same cell type can be readily validated.
  • Cell quality assessment: The health of cells subjected to different culture conditions or passage number can be evaluated by comparing their substrate/surface attachment quality, size/morphology, and growth properties to naïve/young reference cells. Cell quality issues – including cell line mix-ups, genetic and epigenetic changes, contamination, and passage number effects – result in distinct impedance profile changes.
  • Ease of use: Cellular properties/phenotype can be rapidly and quantitatively assessed with minimal hands-on time or effort by the researcher. Once cells have been plated and data acquisition initiated no further involvement is required.
Quality Control of Cells Supporting Information:

  • Compatible Instruments:
    All seven xCELLigence instruments are compatible with cell quality control applications.  To learn more about these instruments, click here.
  • Quality Control of Cells Publications
  1. Rapid and quantitative assessment of cell quality, identity, and functionality for cell-based assays using real-time cellular analysis. Irelan JT, Wu MJ, Morgan J, Ke N, Xi B, Wang X, Xu X, Abassi YA.  J Biomol Screen. 2011 March, 16(3), 313-322.
  2. ATCC technology assessment of Roche xCELLigence System: an electronic impedance-based cell sensing unit.
    Langenbach K.  2010 October, 49(4), 757-758.
  3. Live cell quality control and utility of real-time cell electronic sensing for assay development. Kirstein SL, Atienza JM, Xi B, Zhu J, Yu N, Wang X, Xu X, Abassi YA.  Biochemical and Assay Drug Dev. Technol. 2006 October, 4(5), 545-553.

Receptor Signaling Overview

Critical to all forms of life is the ability to temporally regulate cellular processes based on environment/circumstance.  Whereas the downstream regulatory processes can involve biochemical modification (phosphorylation, allosteric inhibition, etc.) and/or changes to transcription/translation profiles, the initial “sensing” event occurs predominantly through membrane receptor signaling (Figure 1).

Receptor Signaling Overview Fig 1

Figure 1.  Membrane receptor signaling.  Extracellular stimuli are initially “sensed” predominantly through membrane receptors.  Transmission of the signal inside the cell can result in regulation via biochemical modifications and or changes to transcription/translation.

As described in the Technology Overview, xCELLigence real time cell analysis (RTCA) interrogates the ability of electrodes in the bottom of E-Plate wells to conduct electric current.  Adhesion of cells to these electrodes impedes electric current, providing exquisite sensitivity to (1) the number of cells present, (2) the size/morphology of the cells, and (3) how tightly the cells are interacting with the plate surface.  Membrane receptor signaling very often results in biochemical changes that directly, or indirectly, affect one or more of the above three parameters.  Real-time impedance monitoring by xCELLigence makes it possible to capture everything from size/shape changes occurring in the first two minutes after GPCR ligand addition to changes in proliferation rate over the 48 hours following growth factor addition.  For specific examples of using xCELLigence to study receptor signaling, see:

Receptor Signaling: GPCR-mediated signaling

GPCR-Mediated Signaling

G protein-coupled receptors (GPCRs) are the most abundant family of cell surface receptors and represent the largest class of therapeutic targets.  Responding to a wide range of stimuli, GPCRs elicit diverse signaling events ranging from phosphorylation cascades and transcription regulation to ion channel activity and secondary messenger production.  Either directly or indirectly these signaling events usually lead to changes in at least one of the following: cell size/shape, cell-substrate attachment quality, or the kinetics of cell proliferation.  Because xCELLigence® real-time cell analysis (RTCA) instruments are exquisitely sensitive to these physical phenomena, they excel at quantitatively monitoring GPCR-mediated signaling.  The efficacy of RTCA for studying diverse GPCRs is illustrated in Figure 1.  GPCR 1Here Chinese hamster ovary cells expressing human receptors for histamine, dopamine, or serotonin are exposed to their respective ligands.  Histamine receptor, dopamine receptor, and serotonin receptor (which act through the Gaq, Gas, and Gai classes of G proteins, respectively) all show distinct, robust, and titratable impedance responses to their respective ligands.  GPCR antagonists can block these ligand-induced responses (data not shown), indicating that the phenomena being observed reflect bona fide GPCR activation.  By plotting the amplitude of the impedance trace (at a given time point) as a function of ligand concentration it is possible to calculate EC50 values.  Importantly, EC50 values calculated from RTCA traces match extremely well the values determined by alternative methodologies.

It has long been known that a single GPCR can impinge upon multiple signaling pathways.  A more recent finding is that drugs targeting a single GPCR can differentially modulate distinct subsets of that receptor’s signaling repertoire2.  This phenomenon, known as “ligand-biased signaling” or “functional selectivity”, presents the potential for achieving extremely specific biochemical modulation with therapeutic drugs.

The phenomenon of GPCR functional selectivity presents a technical challenge in drug discovery and development because it makes it difficult to comprehensively evaluate the biochemical effects of a given GPCR-ligand interaction.  A unique assay may be required for evaluating how a compound influences each of a GPCR’s downstream pathways.  Moreover, the complete signaling repertoire of most GPCRs is unknown.  Accordingly, an assay of broader scope – capable of evaluating all of a GPCR’s output channels simultaneously – is needed.  Enter xCELLigence.  As one example of how RTCA meets this need, consider stimulation of the b2-adrenergic receptor (b2AR).  In HEK293S cells b2AR was known to elicit at least two distinct signaling events: activation of the MEK pathway and accumulation of cAMP via adenylyl cyclase stimulation.  Stimulation of b2AR with the ligand isoproterenol gives rise to the distinct impedance trace shown in Figure 2. Inhibition of adenylyl cyclase (AC) or MEK similarly reduce the impedance in the 5-100 minute time regime, but have no impact on the first (negatively sloped) phase of the response profile (0-5 minutes).  This suggests that the first phase is caused by a signaling pathway other than those mediated by AC or MEK.  Stallaert and coworkers used this new, holistic view of b2AR activation to hypothesize and then prove the existence of a novel b2AR–promoted Ca2+ mobilization event.

GPCR 2

Key Benefits of Using xCELLigence for Studying GPCR-Mediated Signaling:
  • Flexibility: Capable of probing activation of GPCRs of wide structural and functional diversity.
  • Broad Scope: Simultaneously screen GPCR function across all coupling classes: Gs, Gq, as well as Gi and G12/13 (which are traditionally difficult).
  • Global Observation: Detection of functional selectivity.
  • Cell Variety: Assay endogenous GPCRs in primary cells, stem cells, or disease relevant cell lines.
GPCR-Mediated Signaling Supporting Information:

  • Application Notes:
  1. RTCA iCELLigence Systsem: Dynamic Monitoring of G-Protein-Coupled Receptor Activation in Living Cells
  2. xCELLigence System RTCA SP Instrument: Dynamic Monitoring of G-Protein-Coupled Receptor Activation in Living Cells
  3. xCELLigence System RTCA SP Instrument:: From Classical to Online Monitoring of G-Protein- Coupled Receptor Stimulation in Living Cells
  4. xCELLigence System RTCA HT Instrument: High-Throughput GPCR Assay Development
  5. xCELLigence System RTCA HT Instrument: High-Throughput GPCR Screening
  • GPCR-Mediated Signaling – Compatible xCELLigence System:
xCELLigence RTCA DP xCELLigence RTCA SP xCELLigence RTCA MP xCELLigence RTCA HT xCELLigence iCELLigence
RTCA DP RTCA SP RTCA MP iCELLigence
3×16 wells 1×96 wells 6×96 wells Up to 4×384 wells 2×8 wells
  • GPCR-Mediated Signaling Publications
  1. Label-free impedance responses of endogenous and synthetic chemokine receptor CXCR3 agonists correlate with Gi-protein pathway activation.  Anne O. Watts, Danny J. Scholten, Laura H. Heitman, Henry F. Vischer, and Rob Leurs.  Biochem Biophys Res Commun. 2012 Mar 9;419(2):412-8.
  2. Impedance responses reveal β2-adrenergic receptor signaling pluridimensionality and allow classification of ligands with distinct signaling profiles.  Stallaert W, Dorn JF, van der Westhuizen E, Audet M, Bouvier M.  PLoS One. 2012;7(1):e29420.
  3. Impedance measurement: A new method to detect ligand-biased receptor signaling. Kammermann, A. Denelavas, A. Imbach, U. Grether, H. Dehmlow, C.M. Apfel, C. Hertel.  Biochem Biophys Res Commun. 2011 Sep 2;412(3):419-24.
  4. Neurokinin 1 receptor mediates nembrane blebbing in HEK293 cells through a Rho/Rho-associated coiled-coil kinase-dependent mechanism.  Meshki J, Douglas SD, Lai JP, Schwartz L, Kilpatrick LE, Tuluc F.  J Biol Chem. 2009 Apr 3;284(14):9280-9.
  5. Real-time monitoring of morphological changes in living cells by electronic cell sensor arrays: an approach to study G protein coupled receptors. Yu N, Atienza JM, Bernard J, Blanc S, Zhu J, Wang X, Xu X, Abassi YA.  Anal Chem. 2006 Jan 1;78(1):35-43.

Click here to download the full list (PDF) of publications citing xCELLigence in GPCR research

Receptor Signaling: Nuclear Hormone-Mediated Signaling

Estrogen Specific Response Monitored on xCELLigence System

Application_Book_07_01
The estrogen receptor agonist 17β-estradiol (E2) induced a unique kinetic response profile with delayed cell index growth in the human breast cancer cell line T-47D. Such response was abolished by the estrogen receptor antagonist ICI182780 (A). The progesterone antagonist mifepristone cannot abolish E2 response (B), but rather had a synergistic effect with E2 on T-47D cells. (Data and figures adapted from Jin C, et. al., 2011).

Progesterone Specific Response Monitored on xCELLigence System

Application_Book_07_02
Progesterone induced unique kinetic response profile with a biphasic cell index curve in the human breast cancer cell line T-47D. This response was blocked by the progesterone antagonist mifepristone (A), but could not be abolished by the estrogen receptor antagonist ICI182780 (B). (Data and figures adapted from Jin C, et. al., 2011).

Key Benefits of Using xCELLigence for Studying Nuclear Hormone Receptors: 
  1. Label-free nature allows for sensitive detection of endogenous receptor activity.
  2. Kinetic response profiles may be diagnostic for specific pathways.
  3. Ability to differentiate cytotoxicity and proliferation with a single experiment.
  4. Real time data can identify the optimal time to monitor different ligand effects with standard assay.
Nuclear Hormone Receptor Supporting Information:

  • Nuclear Hormone Receptor Publications 
  1. Real-Time Growth Kinetics Measuring Hormone Mimicry for ToxCast Chemicals in T-47D Human Ductal Carcinoma Cell. Daniel M. Rotroff, David J. Dix, Keith A. Houck, Robert J. Kavlock, Thomas B. Knudsen,Matthew T. Martin, David M. Reif, Ann M. Richard, Nisha S. Sipes, Yama A. Abassi, Can Jin, Melinda Stampfl, and Richard S. Judson. Chem. Res. Toxicol. 2013;26(7):1097–1107.
  2. The Aryl Hydrocarbon Receptor Mediates Leflunomide- Induced Growth Inhibition of Melanoma Cells. Edmond F. O’Donnell, Prasad Rao Kopparapu, Daniel C. Koch, Hyo Sang Jang, Jessica Lynne Phillips, Robert L. Tanguay, Nancy I. Kerkvliet, Siva Kumar Kollur.
    PLoS One. 2012;7(7):e40926.
  3. A Novel Sensitive and Selective Real-time Cellular Assay for Detection of Endocrine Disruptors Using Native Endocrine Signaling Pathways. Jin, C., Abassi, Y., Xu, X. & Wang X. Endocr Rev. 2001;Vol. 32 (03_MeetingAbstracts):1-107.

Receptor Signaling: RTK-Mediated Signaling

Endogenous Receptor Tyrosine Kinase Short Term Response

Application_Book_06_01
Cells expressing recombinant PDGFRb were seeded on an E-plate 96 at 20,000 cells per well and after overnight growth the medium was replaced with serum free medium (not shown). (A) After 2 hours cells were treated with increasing doses of the PDGF nhibitor Imatinib, incubated for one hour, then stimulated with 10 ng/ml PDGF BB. (B) Imatinib showed a dose-responsive inhibition of the morphology change resulting from PDGF stimulation, with an IC50 value of 135 nM as determined using the xCELLigence software (Data and figures adapted from ACEA Biosciences, unpublished data).

Endogenous Receptor Tyrosine Kinase Expressing Cell Line Response to Inhibitor

Application_Book_06_02(A) Cells expressing constitutively active cMET were seeded on an E-plate 384 at 10,000 cells per well and after overnight growth cells were treated with increasing doses of the cMET inhibitor Crizotinib. (B) Crizotinib showed a doseresponsive morphology change resulting from blocking the constitutive cMET signal, with an IC50 value of 87.5 nM as determined using the xCELLigence software (Data and figures adapted from ACEA Biosciences, unpublished data).

Key Benefits of Using xCELLigence for Studying RTK-Mediated Cell Signaling: 
  1. The integrated, global response of cells to RTK modulation can be monitored.
  2. Rapid responses involving cell morphology and attachment changes may be assayed on a minute timescale.
  3. Slower responses involving cell proliferation and viability may be assayed over days or weeks.
  4. Receptor activity can often be assessed in the endogenous context, in a disease-relevant cell type.
RTK-Mediated Cell Signaling Supporting Information:

  • RTK-Mediated Cell Signaling Publications
  1. Benzothiophene containing Rho kinase inhibitors: Efficacy in an animal model of glaucoma. Davis RL, Kahraman M, Prins TJ, Beaver Y, Cook TG, Cramp J, Cayanan CS, Gardiner EM,McLaughlin MA, Clark AF, Hellberg MR, Shiau AK, Noble SA, Borchardt AJ. Bioorganic & Medicinal Chemistry Letters. 2010 Jun 1;20(11):3361-6.
  2. Modeling ERBB receptor-regulated G1/S transition to find novel targets for de novo trastuzumab resistance. Sahin O, Fröhlich H, Löbke C, Korf U, Burmester S, Majety M, Mattern J, Schupp I,Chaouiya C, Thieffry D, Poustka A, Wiemann S, Beissbarth T, Arlt D. BMC Syst Biol. 2009 Jan 1;3:1.
  3. Label-free and real-time cell-based kinase assay for screening selective and potent receptor tyrosine kinase inhibitors using microelectronic sensor array. Atienza JM, Yu N, Wang X, Xu X, Abassi Y. J Biomol Screen. 2006 Sep;11(6):634-43.

Stem Cell and Cell Differentiation

Real-Time Monitoring and Image Analysis of Human Skin-Derived Precursor (SKPs) Cell Differentiation

Application_Book_12_01
Differentiation of human skin-derived precursors (SKPs) into smooth muscle cells (SMCSs) and undifferentiated SKPs (C) with or without the application of transforming growth factor (TGF)-β1 (A) or TGF-β3(B) and subsequently fixed and stained to display a-smooth actin, calponin, and SM22a. Real-time analysis correlates the increase in Cell Index with that of morphological differences between the differentiated and undifferentiated SKPs (D). (Data and figures adapted from Steinbach SK, et. al., 2011).

Morphological Changes of Keratinocytes During Terminal Differentiation

Application_Book_12_02
(A) Calcium-dependent morphological changes of keratinocytes during terminal differentiation can be exhibited using the RTCA xCELLigence system. (B) The increase in Cell Index correlates with image-based morphological analysis. (Data and figures adapted from Spörl F, et. al., 2010).

Key Benefits of Using xCELLigence for Studying Stem Cells and Cell Differentiation:
  1. Real time data reveals the kinetics of cell differentiation.
  2. Label-free nature minimizes the need for staining with fluorescent markers involving multiple handling steps for fixation and staining.
  3. The non-invasive nature of the assay, in combination with the E-Plate VIEW area allows for correlation of real time data with imaging assays.
Stem Cells and Cell Differentiation Supporting Information:

  • Stem Cells and Cell Differentiation Publications
  1. Optimization and scale-up culture of human endometrial multipotent mesenchymal stromal cells: potential for clinical application. Rajaraman G, White J, Tan KS, Ulrich D, Rosamilia A, Werkmeister J, Gargett CE. Tissue Engineering Part C Methods. 2013 Jan;19(1):80–92.
  2. Comparison of long-term retinoic acid-based neural induction methods of bone marrow in human mesenchymal stem cells. Mammadov B, Karakas N, Isik S. In Vitro Cellular and Developmental Biology. 2011 Aug;47(7):484-91.
  3. Directed differentiation of skin-derived precursors into functional vascular smooth muscle cells. Steinbach SK, El-Mounayri O, DaCosta RS, Frontini MJ, Nong Z, Maeda A, Pickering JG,Miller FD, Husain M. Arteriosclerosis, Thrombosis, and Vascular Biol. 2011 Dec;31(12):2938-48.
  4. Real-time monitoring of membrane cholesterol reveals new insights into epidermal differentiation. Spörl F, Wunderskirchner M, Ullrich O, Bömke G, Breitenbach U, Blatt T, Wenck H, Wittern KP, Schrader A. Journal of Investigative Dermatology. 2010 May;130(5):1268-78.