Cardiomyocyte contractility, viability, and electrical activity measured in real-time.
The xCELLigence® Real-Time Cell Analysis (RTCA) CardioECR instrument combines high frequency measurement of cell-induced electrical impedance with multielectrode array technology to simultaneously assess cardiomyocyte contractility, viability, and electrophysiology. This model is similar to our other xCELLigence® instruments in its use of noninvasive electrical impedance monitoring to assess cellular morphology change and attachment quality in a label-free and real-time manner. Because cell-induced electrical impedance is dependent on cell size/shape and how strongly the cell interacts with the plate bottom, the contraction-relaxation cycle of cardiomyocytes gives rise to a distinct, rhythmic fluctuation in impedance that is readily captured on the millisecond time scale. Changes in the intensity and periodicity of this “beating” pattern can be monitored in the short (seconds) to long (days) time regimes to assess cardiomyocyte contractility and viability in the presence of different drugs. The CardioECR (ExtraCellular Recording) model differs from our other xCELLigence® instruments, including the first generation Cardio model, in the following ways: (1) It has an enhanced impedance data acquisition rate (every 1 millisecond), (2) it uses a separate pair of electrodes to measure field potential at 10 kHz, (3) it provides a pacing stimulus, and (4) it uses an electronic 48-well microtiter plate (E-Plate® CardioECR 48). The simultaneous recording of impedance and field potential by the xCELLigence® RTCA CardioECR instrument provides a view of cardiomyocyte health at an unprecedented level of detail, enabling a deeper understanding of the mechanisms underlying drug-induced cardiac liability.
The xCELLigence® RTCA CardioECR instrument is placed in a standard CO2 cell culture incubator and interfaces via a cable with analysis and control units that are housed outside the incubator. User friendly software allows for real-time control and monitoring of the instrument, and includes real-time data display and analysis functions.
The xCELLigence® RTCA CardioECR instrument, regularly used in combination with human iPSC-derived cardiomyocytes, enables in vitro assays that are highly predictive of drug induced cardiac liability. It offers:
• A high-throughput method for detecting functional cardiotoxicity (effects on short-term and long-term cardio beating activity) and general toxicity in vitro
• A test of integrated ion channel activity
• Data that display excellent correlation with clinical arrhythmogenic risk
• Pacing function for more tightly controlled assays
• More thorough understanding of drug mechanism of action
Building upon the impedance-only xCELLigence® RTCA Cardio system, the new CardioECR system combines impedance recording (for evaluating contractility and viability) with both multi electrode array (MEA) technology and a pacing function (for evaluating integrated ion channel activity). Cardiomyocytes are seeded in a 48-well electronic microtiter plate (E-Plate® CardioECR 48) that contains gold microelectrode arrays fused to the bottom of each well (Figures 1A-C). 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. Because the cardiomyocyte contraction/relaxation cycle involves substantial changes in cell morphology and adhesion, it can be dynamically monitored using impedance (Figures 2A-B). The enhanced impedance measurement rate (every 1 ms) of the xCELLigence® RTCA CardioECR system provides extremely high temporal resolution for viewing subtleties of the cardiomyocyte contraction/relaxation continuum. In addition to this ability to monitor cell viability and contractile activity, additional point electrodes in the well bottoms (Figure 1C) allow for extracellular field potential (FP) measurements at 10 kHz, which can be performed in tandem with impedance recording (Figure 2B).
Figure 1. E-Plate CardioECR 48 compatible with the xCELLigence RTCA CardioECR system. (A) E-Plate CardioECR 48. The footprint of this plate complies with ANSI/SBS 1-2004 requirements, and the spacing of the wells in each column is 9 mm center-to-center as per the ANSI/SBS 4-2004 standard. (B) Zoomed in view of E-Plate CardioECR 48 wells. (C) Graphic depiction of a confluent layer of cardiomyocytes interacting with both types of recording electrodes (impedance and field potential electrodes).
Figure 2. Simultaneously using impedance and field potential to monitor cardiomyocyte health and function. (A) Comparison of the contracted vs. relaxed states of two cardiomyocytes adhered to a single electrode. The differences in cell size/shape, and the manner in which cells contact the electrode cause these two states to impede the flow of electric current differently. (B) Simultaneously monitoring cardiomyocyte contraction (red, green, blue, and pink traces) and field potential (integrated ion channel activity; black traces) in real-time. Compared to the negative control (upper set of traces), the three different drugs being evaluated here (bottom three sets of traces) have distinct effects on both contraction and field potential.
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 CardioECR 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 electrical stimulation and data acquisition are defined. These include:
- Defining experimental mode: impedance only, impedance + field potential, or electrical pacing stimulus only
- Defining the pulse type and frequency of the electrical pacing stimulus
- Defining the duration of impedance and field potential data acquisition
Step 3: Running the Experiment
Press “Run” and watch as impedance and field potential data are acquired simultaneously 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 and field potential 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 and field potential associated with cardiomyocyte beating (Figure 2B). Impedance and field potential traces can be viewed individually, or can be overlaid on one another.
Figure 2. Data plotting and analysis using the CardioECR 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 (red, green, blue, and pink traces) and field potential (black traces). 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 and integrated ion channel activity associated with cardiomyocyte beating. Though shown overlapped here, the impedance and field potential traces can be viewed individually.
Built-in data analysis tools enable characterization of drug-induced early afterdepolarization (EAD) and arrhythmia, as well as calculating field potential duration (Figure 3A). Additionally, the real-time impedance trace can be interrogated to quantify cardiomyocyte beating rate and amplitude (Figure 3B) in the presence of different drugs.
Figure 3. Data analysis using the CardioECR Software. (A) Quantifying field potential duration in the presence and absence of drug. (B) Using impedance traces to quantify cardiomyocyte beating rate and amplitude in the presence and absence of drug.
|xCELLigence RTCA CardioECR – Bundle (complete system)||00380601210|
|xCELLigence RTCA CardioECR – Analyzer||00380601180|
|xCELLigence RTCA CardioECR – Station||00380601190|
|xCELLigence RTCA CardioECR – Control Unit (laptop with pre-installed software)||00380601200|
|E-Plate CardioECR 48 (6 Plates)||00300600940|
|E-Plate CardioECR 48 (36 Plates)||00300600950|
- Application Notes
- Spec Sheets
- Product Overviews
- Research Presentations
- J.O.V.E. Video Articles
- Cell Lines
Videos: Product Overviews
Videos: Research Presentations
Videos: J.O.V.E. Video Articles
- Applications Overview
- Cancer Immunotherapy Overview
- Cardiosafety: Drug-Induced Arrythmia
- Cell Adhesion
- Cell Barrier Function
- Cell-Cell Interations: Co-Culture
- Cell-Response Profiling
- Cytotoxicity Overview
- Cytotoxicity: Compound-Mediated Cytotoxicity
- Cytotoxicity: Nanotoxicity
- Functional Analysis of Genes & Proteins: siRNA
- Immune Cell Activation
- In Vitro Hypoxia Studies
- Parasitic Worm Motility and Viability
- Phenotypic Screening
- Quality Control of Cells
- Receptor Signaling Overview
- Receptor Signaling: GPCR-mediated signaling
- Receptor Signaling: Nuclear Hormone-Mediated Signaling
- Receptor Signaling: RTK-Mediated Signaling
- Stem Cell and Cell Differentiation
- Virus-Mediated Cytopathic Effect (CPE)
Building upon the impedance-only xCELLigence® RTCA Cardio system, the new CardioECR system combines impedance recording with multi electrode array (MEA) technology and a pacing function. With the ability to evaluate cardiomyocyte electrical, contractile, and structural toxicity simultaneously, the xCELLigence RTCA CardioECR system is specifically designed for comprehensive in vitro cardiotoxicity screening. The pacing function enables studies to be performed under normal vs. stressed conditions.
Workflow of the xCELLigence RTCA CardioECR System: Cardio-Safety Testing
No cell labeling required, fully automated, physiological conditions
Shown in the workflow above, cryopreserved iPSC cardiomyocytes are directly plated in a 48-well microtiter E-Plate® CardioECR. 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 CardioECR 48 facilitates visual inspection of the general health of the cardiomyocytes under a microscope. The ability to simultaneously monitor overall cell health (using cellular impedance), cell contractile activity (using beating rate and amplitude), and electrical activity (using FPD and spike amplitude) provides an extremely effective means of evaluating a drug’s cardiac liability.
The Cardio/CardioECR system is capable of performing all xCELLigence RTCA applications, except chemotactic cell migration and invasion. The most cited applications of the Cardio/CardioECR system are in the following in vitro cardio-safety research areas.
- Arrhythmia and compound validation (e.g., CiPA studies)
- Kinase and contractility
- Oncology drugs with short- and long-term toxicity
- iPSC and cardiac disease models
- Structural toxicity
Cancer Immunotherapy Overview
What is cancer immunotherapy?
Cancer immunotherapy consists of multiple approaches that focus on harnessing and enhancing the innate powers of the immune system to fight cancer. While traditional small molecule chemotherapy continues to play a critical role in cancer treatment, immunotherapy is rapidly gaining traction; in 2014 immunotherapies constituted ~50% of the overall oncology pharmacopeia. Cancer immunotherapies can be divided into three major categories: (1) cytokines/immunomodulation agents, (2) monoclonal antibodies, and (3) cell-based therapies. Though monoclonal antibodies currently represent the largest class of commercialized cancer immunotherapies, cell-based therapies are rapidly making headway. This class of patient-specific therapies involve collecting immune cells from a cancer patient, engineering them (via genetic manipulation or peptide/adjuvant stimulation) to recognize and kill cancer cells, growing large numbers of these and reintroducing them into the same patient.
What are the different ways the immune system can be harnessed to target tumors?
As shown in the figure below, immune cell-mediated tumor cell killing can involve the following:
- Antibody-Dependent Cell-Mediated Cytotoxicity (ADCC)
- Bispecific T Cell Engagers (BiTEs) and Bispecific Antibodies Mediated Cytotoxicity
- Genetically Engineered T Cell-Mediated Cell Killing
- Macrophage-mediated phagocytosis
- NK Cell-Mediated Cytotoxicity
- T Cell-Mediated Cytotoxicity
What assays are used to study immune cell killing?
Many in vitro assays have been developed to screen and evaluate the efficacy of immune cell-mediated killing. The most common of these is the release assay where effector cell-mediated disruption of the target cell membrane results in leakage of its cytoplasmic contents into the culture medium. Endogenous biomolecules (such as lactate dehydrogenase) or previously added exogenous labels (such as the radioisotopes 51Cr or 111In) that leak into the media are then measured as an indirect readout of the damage caused by effector cells. Alternative endpoint methods include flow cytometry, ELISA-based granzyme measurement, and morphometric analyses by microscopy. Although traditional end-point assays still serve as important tools for evaluating the efficacy of immune cell-mediated killing, there is a critical need for more efficient, homogeneous, automated assays (requiring less hands-on time) that aren’t hampered by the artifacts and hassle of using labels and that can provide quantitative results.
What is the xCELLigence RTCA assay principle?
ACEA’s xCELLigence® Real-Time Cell Analysis (RTCA) instruments utilize gold microelectrodes embedded in the bottom of microtiter wells to non-invasively monitor cell status including cell number, shape/size and attachment. The major distinguishing features of this technology include enhanced sensitivity, the preclusion of labels and, importantly, kinetic measurement of cell health/behavior.
Step 1: Adherent target cells (i.e. tumor cells) are first seeded in the wells of an electronic microtiter plate (E-Plate®). Adhesion of cells to the gold microelectrodes impedes the flow of electric current between electrodes. This impedance value, plotted as a unitless parameter called “Cell Index”, increases as cells proliferate and then plateaus as cells approach 100% confluence.
Step 2: When added subsequently, non-adherent effector cells (i.e. immune cells) in suspension do not cause impedance changes in and of themselves (due to lack of adherence to the gold microelectrodes).
Step 3: If effector cells induce the destruction of the target adherent tumor cells, the corresponding cytolytic activity can be sensitively and precisely detected. The continuous acquisition of impedance data for each well of an E-Plate enables the generation of real-time killing curves for multiple conditions simultaneously.
Key benefits of using xCELLigence to monitor immune cell-mediated killing:
- Label-Free: Allowing for more physiological assay conditions; labeling or secondary assays aren’t required.
- Real-Time: Quantitative monitoring of both fast (hours) and slow (days) killing kinetics.
- Sensitive: Capable of evaluating low effector cell to target cell ratios that are physiologically relevant.
- Simple Workflow: Requires only the addition of effector cells to target cells (in the presence or absence of antibodies); homogeneous assay without additional sample handling.
- Automatic Data Plotting: RTCA software enables facile data display and objective analysis, precluding the subjective data vetting that is common to imaging-based assays.
Featured xCELLigence RTCA systems for immune cell killing assays:
|xCELLigence RTCA DP||xCELLigence RTCA SP||xCELLigence RTCA MP||xCELLigence RTCA HT|
|3×16 wells||1×96 wells||6×96 wells||Up to 4×384 wells|
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).
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 ARRHYTHMIA:
- Data display excellent correlation with known clinical arrhythmogenic risk.
- Monitor cardiotoxicity over short (seconds) and/or long (days/weeks) time scales.
- More thorough understanding of drug mechanism of action.
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
(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).
- 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 Barrier Function
Comparison of Conventional Methods with the Dynamic Impedance-Based Method for Monitoring Ethanol-Induced Epithelial Barrier Dysfunction
(A) The reversible barrier dysfunction induced by 7.5% ethanol was assessed by measuring phenol red permeability (control: untreated Caco-2 cell monolayer; EtOH: Caco-2 exposed in ethanol for 3 h; EtOH removal: Caco-2 exposed in ethanol for 3 h followed by replacing ethanol with fresh medium for another 3 h) and (B) TEER assay. (C) Dynamic impedance-based monitoring of ethanol (7.5%) induced epithelial barrier dysfunction, which was reversed after ethanol was removed. Black arrow: ethanol was added; gray arrow: ethanol was removed. (Data and figures adapted from Sun M, et. al., 2012).
Co-Culture of Astrocytes Enhanced the Barrier Function of Brain Microvascular Endothelial Cells (BMEC)
(A) Schematic of assembly of the inverted blood brain barrier model. Astrocytes and BMEC were grown on the transwell membrane in the upper chambers and on the gold electrode in lower chambers the CIM device, respectively. (B) Astrocytes (seeding densities were 0, 1000, 4000 and 8000/well) increased the CI of BMEC in a dose-dependent manner. (Data and figures adapted from Sansing HA, et. al., 2012).
- A label-free alternative to solute permeability and transendothelial electrical resistance (TEER) assays.
- Direct, sensitive, and quantitative.
- Real-time assay is conducted under normal tissue culture conditions, allowing for monitoring of barrier function disruption as well as recovery.
- Noninvasive nature of the readout allows for orthogonal assays conducted on the same device, including visual monitoring of cell density by microscopy.
Cell-Cell Interations: Co-Culture
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.)
- Label free environment allows detection of responses due to stimulation of endogenous receptors
- Kinetic response profiles may be diagnostic for specific pathways
- Real time data provides comprehensive information on cell responses over long time periods
- E-Plate Insert offers an easy to setup co-culture platform with minimal handling
Using the xCELLigence System for Target Identification and Validation
(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
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).
- Real-time monitoring of kinetics of cell responses to treatment can reveal novel information regarding mechanism of action.
- Assays are performed in tissue culture incubator, allowing for detection of long-term effects.
- Label-free assay requires no fixation, staining or any other sample processing.
- Cell response profiles can allow for early identification of unexpected off-target or toxic effects of treatments.
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).
For specific examples of using xCELLigence to study cytotoxicity, see:
- Cytotoxicity: Compound-Mediated Cytotoxicity
- Cytotoxicity: Irradiation-Induced Cytotoxicity
- Cytotoxicity: Nanotoxicity
For examples of using xCELLigence to study cell-mediated cytotoxicity for cancer immunotherapy, see:
- Cancer Immunotherapy: Antibody-Dependent Cell-Mediated Cytolysis (ADCC)
- Cancer Immunotherapy: Bispecific T Cell Engagers (BiTEs) and Bispecific Antibodies
- Cancer Immunotherapy: Genetically Engineered T Cell-Mediated Cell Killing
- Cancer Immunotherapy: Macrophage-Mediated Phagocytosis
- Cancer Immunotherapy: NK Cell-Mediated Cytolysis
- Cancer Immunotherapy: T Cell-Mediated Cytolysis
Cytotoxicity: Compound-Mediated Cytotoxicity
Kinetic Response Profiles Reflect Different Cytotoxic Mechanisms
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
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).
- Kinetic responses can be predictive of mechanism of action.
- Continuous monitoring ensures no meaningful time 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 standard viability assays at any point during the experiment.
- Easy quantification of the onset and kinetics of the cytotoxic response.
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).
Figure 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.
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 (— —).
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.
- 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.
Functional Analysis of Genes & Proteins: siRNA
Using the xCELLigence System for Target Identification and Validation
(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
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).
- Real-time monitoring of kinetics of cell responses to treatment can reveal novel information regarding mechanism of action
- Assays are performed in tissue culture incubator, allowing for detection of long-term effects
- Label-free assay requires no fixation, staining or any other sample processing
- Cell response profiles can allow for early identification of unexpected off-target or toxic effects of treatments
Immune Cell Activation
Real-Time Monitoring of Mast Cell Degranulation in RBL-2H3 Mast Cell Line
(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
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).
- 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.
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 xCELLigence®
- 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.
Parasitic Worm Motility and Viability
Despite 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 xCELLigence®
- 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.
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.
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.
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).
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. This 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. The 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.
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.
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.
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).
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 xCELLigence®
- 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.
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).
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
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. Here 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.
Key Benefits of xCELLigence®
- 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.
Receptor Signaling: Nuclear Hormone-Mediated Signaling
Estrogen Specific Response Monitored on xCELLigence System
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
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).
- Label-free nature allows for sensitive detection of endogenous receptor activity.
- Kinetic response profiles may be diagnostic for specific pathways.
- Ability to differentiate cytotoxicity and proliferation with a single experiment.
- Real time data can identify the optimal time to monitor different ligand effects with standard assay.
Receptor Signaling: RTK-Mediated Signaling
Endogenous Receptor Tyrosine Kinase Short Term Response
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
(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).
- The integrated, global response of cells to RTK modulation can be monitored.
- Rapid responses involving cell morphology and attachment changes may be assayed on a minute timescale.
- Slower responses involving cell proliferation and viability may be assayed over days or weeks.
- Receptor activity can often be assessed in the endogenous context, in a disease-relevant cell type.
Stem Cell and Cell Differentiation
Real-Time Monitoring and Image Analysis of Human Skin-Derived Precursor (SKPs) Cell Differentiation
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-β31 (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
(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).
- Real time data reveals the kinetics of cell differentiation.
- Label-free nature minimizes the need for staining with fluorescent markers involving multiple handling steps for fixation and staining.
- 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.
Virus-Mediated Cytopathic Effect (CPE)
Virus infection of a host cell typically includes the selective suppression of host cell functions and redirection of resources towards viral replication and assembly, ultimately leading to host cell lysis and dissemination of new virus. While host cell rounding, detachment from the plate surface and/or lysis are readily detected by real-time impedance monitoring, more subtle changes in host cell morphology occurring during earlier phases of viral infection can also be monitored. This sensitivity to virus-induced changes in host cell morphology and behavior makes the xCELLigence technology very well suited for a wide array of virology applications, including: differentiating between virus strains/isolates based on the kinetics of replication and cytopathic effect, determining viral titers, determining neutralizing antibody titers, and studying virus-host cell interactions using physiologically relevant cell types that cannot typically be used because they aren’t compatible with traditional assay techniques.
APPLICATION HIGHLIGHT: DETERMINING VIRUS TITER
Citing the fact that traditional plaque assays are labor intensive and time consuming, Reisen and colleagues evaluated the efficacy of xCELLigence real-time cell analysis (RTCA) for determining virus titers. Vero cells in suspension were incubated with serial dilutions of a known concentration of West Nile virus (WNV) for 30 minutes at 37°C, followed by immediate addition of the cell/virus suspension to wells of ACEA’s electronic microtiter plates (E-Plates®). In contrast to uninfected control cells which grew to confluency and maintained a plateaued Cell Index (CI), virus-infected cells displayed a time-dependent decrease of CI down to zero, indicating complete cell lysis (Figure 1A). Importantly, the time at which this cytopathic effect occurred correlated extremely well with the known titer of the virus. This is highlighted by plotting the CIT50 (time required for the CI to decrease by 50%) as a function of virus titer (Figure 1B). Using this type of standard curve, it is possible to determine the viral titer in samples of unknown concentration.
Figure 1. Real-time monitoring of West Nile virus cytopathic effect. (A) The timing of West Nile virus (WNV)-induced cytopathic effect is dependent on virus titer. After being incubated with serial dilutions of WNV, Vero cells were seeded in the wells of an E-Plate and impedance was monitored for 200 hours. The thin horizontal line denotes CIT50 (time required for the Cell Index to decrease by 50%). (B) The time dependence of WNV-induced cytopathic effect correlates with virus titer. Plotting CIT50 as a function of known virus concentration demonstrates the strength of this correlation. Data have been adapted from J Virol Methods. 2011 May;173(2):251-8.
APPLICATION HIGHLIGHT: EVALUATING FITNESS AND IDENTIFYING DIFFERENT VIRUS STRAINS/ISOLATES
Evaluating the relative fitness of different virus strains/isolates, and determining the identity of a virus isolate can involve a large number of techniques, including: ELISA, PCR, RT-PCR, Western blotting, plaque assays, immunofluorescence, etc. Owing to its ability to kinetically characterize a virus-induced cytopathic effect, xCELLigence real-time cell analysis (RTCA) can be used in place of, or in addition to, some of these traditional assays for characterizing virus fitness and/or identity. In the below example RTCA traces were acquired for Vero cells infected with West Nile virus (WNV) or St. Louis encephalitis virus (SLEV) at the same multiplicity of infection. As seen in Figure 2, the cytopathic effect induced by these two viruses begins at different times post infection and takes different amounts of time to complete (i.e. to reach complete cell lysis). This type of RTCA-based kinetic comparison can be used for assessing the relative fitness/virulence of different virus isolates/strains, or to help identify a virus using RTCA traces from known standards.
Figure 2. Real-time monitoring of cytopathic effects induced by West Nile virus (WNV) and St. Louis encephalitis virus (SLEV). Vero cells in suspension were incubated with either WNV or SLEV at an identical multiplicity of infection. Subsequently the cell/virus suspension was added to a well of an E-Plate. Despite being closely related viruses within the same serocomplex, WNV and SLEV show marked differences in the time at which they begin causing a detectable cytopathic effect: the CIT50 (time required for the Cell Index to decrease by 50%) for SLEV lags behind that of WNV by 55 hours. Moreover, the rate at which these two viruses effect complete cell lysis (i.e. the temporal duration of the cytopathic effect) differs. Data have been adapted from J Virol Methods. 2011 May;173(2):251-8.
APPLICATION HIGHLIGHT: DETERMINING NEUTRALIZING ANTIBODY TITER
Besides being used for therapeutic or prophylactic purposes, neutralizing antibodies also serve as a diagnostic hallmark of infection. One means of determining the presence and/or concentration of antibody in a sample is to evaluate the sample’s ability to neutralize infection by a virus. The automated continuous data acquisition of xCELLigence real-time cell analysis (RTCA), combined with its high reproducibility and minimal hands-on time, make it extremely well suited for this type of assay. In Figure 3A, Vero cell were incubated with a fixed amount of West Nile virus (WNV) that had previously been treated with different dilutions of antisera containing a known concentration of WNV neutralizing antibody. The time at which cells displayed a cytopathic effect (with Cell Index dropping to zero) varied dramatically between the different samples. As expected, at higher dilutions the neutralizing capacity of the antisera decreased. By plotting the CIT50 (time required for the Cell Index to decrease by 50%) as a function of the known neutralizing antibody titer a standard curve can be constructed (Figure 3B). This type of curve can be used for determining neutralizing antibody titer in samples of unknown concentration.
Figure 3. Quantitation of neutralizing antibody titer. (A) Vero cells were treated with West Nile virus (WNV) that had previously been incubated with different dilutions of House finch antisera containing a known WNV neutralizing antibody titer. Whereas the negative control (not exposed to virus) displays a plateaued cell index, the positive control (exposed to virus that was not pretreated with antisera) displays a rapid onset of cytopathic effect (CPE). Pretreatment of WNV with antisera delays the onset of CPE. (B) Correlation between antisera/neutralizing antibody titer and time of CPE onset. Plotting the CIT50 (time required for the Cell Index to decrease by 50%) as a function of antisera/neutralizing antibody titer demonstrates the strength of this correlation. Data have been adapted from J Virol Methods. 2011 May;173(2):251-8.
- Quantify virus titer: An automated, simple, reduced workload alternative to plaque assays.
- Evaluate the fitness of different strains/isolates: The relative fitness of different viruses (natural isolates, engineered mutants, etc.) are readily evaluated using the onset and kinetics of virus-mediated cytopathic effects.
- Determine/confirm virus identity: Real-time kinetic traces of virus-mediated cytopathic effects can be compared to those of characterized viruses to help determine/confirm the identity of a virus.
- Quantify neutralizing antibody titer: Because the time of cytopathic effect onset correlates with neutralizing antibody concentration, standard curves are easy to generate. These can be used for quantifying neutralizing antibody in samples of unknown concentration.
- Rapid assay optimization: Quickly identify the optimal viral titer and assay time point for subsequent screening of inhibitory compounds, neutralizing antibodies and neutralizing serums.