xCELLigence RTCA SP

rtca-sp-featured

Cellular Impedance Explained

Positioned between reductionistic biochemical assays and whole organism in vivo experimentation, cell-based assays serve as an indispensable tool for basic and applied biological research. However, the utility of many cell-based assays is diminished by: (1) the need to use labels, (2) incompatibility with continuous monitoring (i.e. only end point data is produced), (3) incompatibility with orthogonal assays, and (4) the inability to provide an objective/quantitative readout. Each of these shortcomings is, however, overcome by the non-invasive, label-free, and real-time cellular impedance assay.

The functional unit of a cellular impedance assay is a set of gold microelectrodes fused to the bottom surface of a microtiter plate well (Figure 1). When submersed in an electrically conductive solution (such as buffer or standard tissue culture medium), the application of an electric potential across these electrodes causes electrons to exit the negative terminal, pass through bulk solution, and then deposit onto the positive terminal to complete the circuit. Because this phenomenon is dependent upon the electrodes interacting with bulk solution, the presence of adherent cells at the electrode-solution interface impedes electron flow. The magnitude of this impedance is dependent on the number of cells, the size and shape of the cells, and the cell-substrate attachment quality. Importantly, neither the gold microelectrode surfaces nor the applied electric potential (22 mV) have an effect on cell health or behavior.

xCELLigence Tech Overview Fig 1

Figure 1.  Overview of cellular impedance apparatus.  A side view of a single well is shown before and after cells have been added.  Neither the electrodes nor the cells are drawn to scale (they have been enlarged for clarity).  In the absence of cells electric current flows freely through culture medium, completing the circuit between the electrodes.  As cells adhere to and proliferate on the electrodes current flow is impeded, providing an extremely sensitive readout of cell number, cell size/morphology, and cell-substrate attachment quality.

Impedance Electrodes

The gold microelectrode biosensors in each well of ACEA’s electronic microtiter plates (E-Plates®) cover 70-80% of the surface area (depending if a view area is present). Rather than the simplified electrode pair depicted in Figure 1, the electrodes in each well of an E-Plate are linked into “strands” that form an interdigitating array (Figure 2). This arrangement enables populations of cells to be monitored simultaneously and thereby provides exquisite sensitivity to: the number of cells attached to the plate, the size/morphology of the cells, and the cell-substrate attachment quality.

Figure 2.  Impedance electrodes on ACEA’s E-Plates.  (A) Simplified schematic of the interdigitated electrodes used in each well of an E-Plate.  Electrodes are not drawn to scale (only a few are shown, and they have been enlarged for clarity).  Though cells can also be visualized on the gold electrode surfaces, the electrode-free region in the middle of the well facilitates microscopic imaging (brightfield, fluorescence, etc.).  (B) Photograph of a single well in a 96-well E-Plate.  (C) Zoomed in brightfield image of shadowed electrodes and unstained human cells.  (D) Gold electrodes and crystal violet stained human cells, as viewed in a compound microscope.

Real-Time Impedance Traces Explained

The impedance of electron flow caused by adherent cells is reported using a unitless parameter called Cell Index (CI), where CI = (impedance at time point n – impedance in the absence of cells)/nominal impedance value. Figure 3 provides a generic example of a real-time impedance trace throughout the course of setting up and running an apoptosis experiment. For the first few hours after cells have been added to a well there is a rapid increase in impedance. This is caused by cells falling out of suspension, depositing onto the electrodes, and forming focal adhesions. If the initial number of added cells is low and there is empty space on the well bottom cells will proliferate, causing a gradual yet steady increase in CI. When cells reach confluence the CI value plateaus, reflecting the fact that the electrode surface area that is accessible to bulk media is no longer changing. The addition of an apoptosis inducer at this point causes a decrease in CI back down to zero. This is the result of cells rounding and then detaching from the well bottom. While this generic example involves drug addition when cells are confluent, impedance-based assays are extremely flexible and can also evaluate the rate and extent of initial cell adhesion to the electrodes, or the rate and extent of cell proliferation.

Figure 3.  Generic real-time impedance trace for setting up and running an apoptosis assay.  Each phase of the impedance trace, and the cellular behavior it arises from, is explained in the text.

Moving beyond the generic example shown above, Figure 4 shows actual real-time impedance data acquired using E-Plates in ACEA’s xCELLigence® real-time cell analysis (RTCA) instruments. Figure 4A shows impedance traces for the first two hours after A549 cells have been added to an E-Plate, the wells of which were previously coated with differing concentrations of collagen IV. While Figure 4B demonstrates the change in cell index that occurs within the first few minutes of exposing HeLa cells to the GPCR agonist dopamine, Figure 4C evaluates NK cell-mediated cytolysis of cancer cells over the course of 20 hours. Figure 4D highlights the variety of changes that can occur in cell index depending on a drug’s mechanism of action.

Figure 4.  Examples of real-time impedance traces obtained using E-Plates and xCELLigence RTCA instruments.  (A) Real-time monitoring of A549 cell adhesion to E-Plate wells that had been pre-coated with different concentrations of collagen IV.  Note the correlation between impedance values (Cell Index) and the number of adherent cells visible in the microscope.  (B) Real-time impedance traces for HeLa cells exposed to different concentrations of the GPCR agonist dopamine.  The black arrow indicates the time of dopamine addition.  (C) Real-time impedance traces for NK 92 cell-mediated cytolysis of MCF7 breast cancer cells.  (D) Real-time impedance traces for A549 cells exposed to drugs displaying a variety of mechanisms of action.

Correlating Impedance with Cellular Phenomena

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 can provide an extremely wide field of view on cell health and behavior. Everything from endothelial barrier function and chemotaxis to filopodia dynamics and immune cell-mediated cytolysis have successfully been analyzed on xCELLigence instruments. Despite the breadth of their reach, xCELLigence assays are still capable of interrogating very specific biochemical and cellular phenomena. Appropriate use of controls and/or orthogonal techniques make it possible to correlate the features of an impedance trace with specific cellular/molecular phenomena. To learn more about how this is done, and to witness the sensitivity and versatility of the xCELLigence RTCA technology, peruse the many specific applications that are highlighted here.

Applications Overview

The xCELLigence® RTCA SP system is compatible with the 96-well microtitor E-Plate®.  This format/throughput is popular for dose dependent studies. The SP system is capable of performing all xCELLigence RTCA applications, except cell migration and invasion assays (using ACEA’s CIM-Plate®) and cardio specific assays (analyzing cardiomyocyte contractile and electrical activities).

Workflow of the xCELLigence RTCA SP System
No cell labeling required, fully automated, physiological conditions

xCELLigence Real-Time Cell Analysis SP workflow

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 components of both the innate and adaptive immune systems including: (1) natural killer (NK) cells, (2) cytotoxic T cells (MHC-dependent), (3) antibodies secreted by B lymphocytes, (4) engineered antibodies such as bispecific antibodies and bispecific T cell engagers (BiTEs), (5) genetically engineered T cells targeting specific tumor antigens (e.g., CAR-T; MHC-independent), and (6) macrophage-mediated phagocytosis.

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:
  1. Label-Free: Allowing for more physiological assay conditions; labeling or secondary assays aren’t required.
  2. Real-Time: Quantitative monitoring of both fast (hours) and slow (days) killing kinetics.
  3. Sensitive: Capable of evaluating low effector cell to target cell ratios that are physiologically relevant.
  4. 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.
  5. 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:

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Cancer Immunotherapy: Antibody-Dependent Cell-Mediated Cytolysis (ADCC)

What is ADCC?

Though the innate and adaptive branches of the immune system are typically described as being distinct and separate from one another, they often work in concert to afford protection and combat disease. Upon encountering a pathogen, cells of the innate immune system typically release cytokines that cross-talk with components of the adaptive immune system, causing them to expand and become activated. Moreover, many cells involved in the innate immune response (including NK cells, neutrophils and eosinophils) also express CD16 (Fc receptor), which is a low affinity receptor for immunoglobulins such as IgG. Immunoglobulin binding by CD16 targets innate immune cells to the immunonglobulin-bound target cell, and triggers target cell destruction. This prophylactic mechanism is known as antibody-dependent cell-mediated cytolysis (ADCC) and is the basis of many current monoclonal antibody therapies.

Application Highlight: Erbitux-Mediated NK Cell Killing

Erbitux (Cetuximab) is a therapeutic monoclonal antibody that binds specifically to the human epidermal growth factor receptor (EGFR) that is overexpressed in many tumor types. In the example shown here, real-time impedance monitoring with xCELLigence was used to evaluate the efficacy of Erbitux-mediated NK cell killing. A431 human epidermoid carcinoma cells, which express high levels of human EGFR, were first seeded in the wells of an ACEA electronic microtiter plate (E-Plate). 22 hours post seeding, Erbitux was added at different concentrations. One hour after antibody addition, interleukin 2-activated NK cells were added at an effector:target cell ratio of 20:1. Neither Erbitux nor medium alone have a substantial effect on the real-time impedance trace of the A431 cells (left panel). While NK cell addition alone induces a decrease in the number, size, and/or attachment quality of the adherent A431 cells, the prior addition of Erbitux substantially increases, in a dose-dependent manner, this effect. The fact that MabThera (a monoclonal antibody against the CD20 protein which is not expressed in A431 cells) is ineffective highlights the specific role being played by Erbitux in directing NK cell-mediated killing (left panel). By plotting the Cell Index value (10 hours after NK cell addition) as a function of Erbitux concentration, a dose–response curve was generated and the EC50 of Erbitux calculated (right panel).

Antibody-dependent NK cell-mediated killing of A431 cells. Adherent A431 epidermoid carcinoma cells were incubated with or without the Erbitux monoclonal antibody before being exposed to interleukin 2-activated NK cells. Real-time impedance traces clearly show that the cytolytic activity of the NK cells is accentuated by Erbitux in a dose-dependent manner (left panel). The “Ab” and “NK” arrows denote the times of antibody and NK cell addition, respectively. Plotting the Cell Index, 10 hours after NK cell addition, as a function of antibody concentration yields a dose-response curve and the EC50 of Erbitux (right panel). Figure adapted from Assay Drug Dev Technol. 2006 Oct;4(5):555-63.

Key Benefits of Using xCELLigence to Monitor ADCC:
  1. Label-Free: Allowing for more physiological assay conditions; labeling or secondary assays aren’t required.
  2. Real-Time: Quantitative monitoring of both fast (hours) and slow (days) killing kinetics.
  3. Sensitive: Capable of evaluating low effector cell to target cell ratios that are physiologically relevant.
  4. 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.
  5. Automatic Data Plotting: RTCA software enables facile data display and objective analysis, precluding the subjective data vetting that is common to imaging-based assays.

ADCC Supporting Information:

  • Adherent target cells tested:
    MCF-7, A431, BT-474, NCI-N87, SKOV3, PC8, PC9, PC11, PC12, PC13, HD9, HD10, HD11, H322, MCF-7-CD19tm, Colo38, MDA-MB435
  • ADCC – Compatible xCELLigence Systems:
    Screenshot_120715_021555_PM
  • ADCC Publications:
  1. Dynamic detection of natural killer cell-mediated cytotoxicity and cell adhesion by electrical impedance measurements. Glamann J, Hansen AJ. Assay Drug Dev Technol. 2006 Oct;4(5):555-63. (Novo Nordisk, Denmark)
  2. Breast tumor cells isolated from in vitro resistance to trastuzumab remain sensitive to trastuzumab anti-tumor effects in vivo and to ADCC killing. Kute TE, Savage L, Stehle JR Jr, Kim-Shapiro JW, Blanks MJ, Wood J, Vaughn JP. Cancer Immunol Immunother. 2009 Nov;58(11):1887-96. (Wake Forest University School of Medicine, USA)
  3. Pertuzumab in combination with trastuzumab shows significantly enhanced antitumor activity in HER2-positive human gastric cancer xenograft models. Yamashita-Kashima Y, Iijima S, Yorozu K, Furugaki K, Kurasawa M, Ohta M, Fujimoto-Ouchi K. Clin Cancer Res. 2011 Aug 1;17(15):5060-70. (Chugai Pharmaceutical, Japan)
  4. Isolation and characterization of IgG1 with asymmetrical Fc glycosylation. Ha S, Ou Y, Vlasak J, Li Y, Wang S, Vo K, Du Y, Mach A, Fang Y, Zhang N. Glycobiology. 2011 Aug;21(8):1087-96. (Merck Research, USA)
  5. Understanding key assay parameters that affect measurements of trastuzumab-mediated ADCC against Her2 positive breast cancer cells. Kute T, Stehle Jr JR, Ornelles D, Walker N, Delbono O, Vaughn JP. Oncoimmunology. 2012 Sep 1;1(6):810-821. (Wake Forest University School of Medicine, USA)
  6. A novel glycoengineered bispecific antibody format for targeted inhibition of epidermal growth factor receptor (EGFR) and insulin-like growth factor receptor type I (IGF-1R) demonstrating unique molecular properties. Schanzer JM, Wartha K, Croasdale R, Moser S, Künkele KP, Ries C, Scheuer W, Duerr H, Pompiati S, Pollman J, Stracke J, Lau W, Ries S, Brinkmann U, Klein C, Umana P. J Biol Chem. 2014 Jul 4;289(27):18693-706. (Roche Diagnostics, Germany)
  7. γδ T cell-mediated antibody-dependent cellular cytotoxicity with CD19 antibodies assessed by an impedance-based label-free real-time cytotoxicity assay. Seidel UJ, Vogt F, Grosse-Hovest L, Jung G, Handgretinger R, Lang P. Front Immunol. 2014 Dec 2;5:618. (University Children’s Hospital Tübingen, Germany)
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Cancer Immunotherapy: Bispecific T Cell Engagers (BiTEs) and Bispecific Antibodies

What are Bispecific Antibodies/Bispecific T Cell Engagers (BiTEs)?

The therapeutic efficacy of the antibody-dependent cell-mediated cytotoxicity (ADCC) technique is mitigated by the fact that not all immune cells express the CD16 antibody receptor. In particular, cytotoxic and helper T lymphocytes don’t express CD16 and therefore aren’t recruited to antibody-coated cells.

In order to circumvent this constraint and mobilize the full capacity of the adaptive immune response against tumors, bispecific antibodies have been engineered which simultaneously (1) bind to specific antigens on the surface of tumor cells, and (2) tether and activate cytotoxic and helper T cells by binding the CD3 receptor that is expressed on their surface. This approach has the advantage of bypassing MHC-mediated activation of T cells, and has the potential to target any antigen that is expressed on the surface of tumor cells. Though multiple variations of bispecific antibodies have been studied, one type stands out as being especially promising. Bispecific T cell engagers (BiTEs), which target the CD19 antigen on B cell malignancies, have recently been awarded “Breakthrough Therapy” status by the FDA.

Application Highlight: Analyzing a BiTE Targeting the EpCAM Receptor

To evaluate the utility of xCELLigence RTCA for characterizing BiTEs, killing of adherent PC3 prostate cancer cells by PBMCs was studied in the presence of a BiTE that targets the EpCAM receptor (which is expressed on the surface of most cancer cells of epithelial origin, including PC3 cells). At a PBMC:PC3 ratio of 20, EpCAM/CD3 BiTE increases killing efficacy in a dose dependent manner (left panel). Though PC3 cell killing is still stimulated at the lowest BiTE concentration, complete killing of the PC3 cells is delayed.

As a means of quantifying the time-dependent cytolysis activity of PBMCs towards PC3 cells in the presence of BiTE, the effective time for reduction of Cell Index by 50% (ET50) was plotted (right panel). As expected, ET50 values demonstrate PC3 lysis to be more efficient at higher effector:target cell ratios and at higher BiTE concentrations. The ability of xCELLigence RTCA to assess the effect of BiTEs on the cytolytic activity of effector cells in a continuous manner elucidates killing kinetics that would be impossible to capture with end point assays.

Screenshot_120715_022759_PM

Analyzing the efficacy of a BiTE targeting PC3 prostate cancer cells.  Killing of adherent PC3 prostate cancer cells by PBMCs (effector:target ratio = 20) was evaluated in the presence of a BiTE with specificity for both EpCAM (present on PC3 cells) and CD3 (present on PBMCs).  At all BiTE concentrations examined, simultaneous addition of the BiTE and PBMCs causes the destruction of PC3 cells, leading to reduced impedance signal (left panel). Plotting the effective time for reduction of Cell Index by 50% (ET50) enables quantitative evaluation of the differential effects of effector:target ratio and BiTE concentration (right panel). Unpublished data from ACEA Biosciences, Inc.

Key Benefits of Using xCELLigence To Study Bispecific Antibodies/BiTEs:
  1. Label-Free: Allowing for more physiological assay conditions; labeling or secondary assays aren’t required.
  2. Real-Time: Quantitative monitoring of both fast (hours) and slow (days) killing kinetics.
  3. Sensitive: Capable of evaluating low effector cell to target cell ratios that are physiologically relevant.
  4. 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.
  5. Automatic Data Plotting: RTCA software enables facile data display and objective analysis, precluding the subjective data vetting that is common to imaging-based assays.
Bispecific Antibody/BiTE Supporting information:

  • Adherent target cells tested:
    PC3 prostate cancer cells, Panc89, Colo357, PancTu-I, PDAC, Colo38, MDA-MB435, HBV-transfected HuH7-S
  • Bispecific Antibody/BiTE – Compatible xCELLigence Systems:
    Screenshot_120715_021555_PM
  • Bispecific Antibody/BiTE Publications:
  1. Novel bispecific antibodies increase γδ T-cell cytotoxicity against pancreatic cancer cells. Oberg HH, Peipp M, Kellner C, Sebens S, Krause S, Petrick D, Adam-Klages S, Röcken C, Becker T, Vogel I, Weisner D, Freitag-Wolf S, Gramatzki M, Kabelitz D, Wesch D. Cancer Res. 2014 Mar 1;74(5):1349-60. (Christian-Albrechts-University Kiel, Germany)
  2. Committing cytomegalovirus-specific CD8 T cells to eliminate tumor cells by bifunctional major histocompatibility class I antibody fusion molecules. Schmittnaegel M, Levitsky V, Hoffmann E, Georges G, Mundigl O, Klein C, Knoetgen H. Cancer Immunol Res. 2015 Jul;3(7):764-76. (Roche Pharma Research and Early Development, Germany)

 

Cancer Immunotherapy: Genetically Engineered T Cell-Mediated Cell Killing

Genetically Engineered T Cells

T cells can be genetically engineered to express a modified T cell receptor (TCR; specific for a tumor antigen) or a chimeric antigen receptor (CAR; composed of an intracellular signaling domain that is linked to an extracellular domain derived from a tumor-specific antibody).

Avoiding the immune tolerance issues associated with non-autologous therapies, and producing T cells that efficiently target tumors without the need for de novo activation in the patient, are primary motivations for genetically modifying T cells. The efficacy of this approach is highlighted by the convincing clinical data that has emerged in recent years (as one example, see: Clin Transl Immunology. 2014;3(5):e16.)

Application Highlight: Measuring the Targeting Efficacy of Engineered TCR vs. CAR

In the example below, multiple assays are used to evaluate the killing efficiency of T cells when they are directed at cancer cells using either an engineered TCR or a CAR. To facilitate this comparison, CD8+ T cells were engineered to express both a TCR (recognizing the OVA257 epitope of ovalbumin) and a CAR (recognizing HER2). At different effector:target cell ratios, these T cells were incubated with adherent MC57 mouse fibrosarcoma cells that expressed the OVA257 epitope, HER2, or no exogenous protein.

After 18 hours of co-incubation, T cell-mediated cytolysis was analyzed using a traditional 51Cr release assay (left panel). Though the engineered T cells are able to kill MC57 cells, killing efficiency increases dramatically when the MC57 cells are expressing either OVA57 or HER2 (as expected). At all effector:target cell ratios analysed, activating these T cells via their TCR or their CAR results in similar killing efficiency (left panel). When the same assay is repeated using xCELLigence real-time impedance monitoring, after 18 hours of co-incubation killing via OVA257 targeting and HER2 targeting are very similar. Importantly, however, when analysed over a longer time period there are substantial differences in the killing efficiencies of these two targeting approaches (right panel).

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Targeting T cells using an engineered TCR vs. CAR results in different killing efficiency. T cells engineered to simultaneously express a TCR against the OVA257 epitope of ovalbumin and a CAR against the HER2 protein were co-incubated with adherent mouse fibrosarcoma cells.  Killing efficiency was analyzed by both a traditional 51Cr release assay (left panel) and xCELLigence RTCA impedance monitoring (right panel; here data are plotted in arbitrary units, comparing the cell index value at each time point to the cell index value of the same sample prior to T cell addition).  Both assays show that MC57 cells are killed more efficiently when they express OVA257 or HER2 (as expected).  In the 51Cr release assay (conducted after 18 hours of co-incubation) both targeting approaches produce similar killing efficiencies.  In contrast, real-time monitoring of impedance over a longer time period reveals that in this context the TCR targeting approach results in more robust cell killing.  Figure adopted from Cancer Immunol Res. 2015; 3(5):483-94.

Genetically Engineered T Cell-Mediated Cell Killing Supporting Information:

  • Adherent target cells tested:
    A375, SW480, MC57, MC57-HER2, U-251MG, 13-06-MG
  • Genetically Engineered T Cell-Mediated Cell Killing – Compatible xCELLigence Systems:
    Screenshot_120715_021555_PM
  • Genetically Engineered T Cell-Mediated Cell Killing References:
  1. Epigenetic modulation to enable antigen-specific T-cell therapy of colorectal cancer. Chou J, Voong LN, Mortales CL, Towlerton AM, Pollack SM, Chen X, Yee C, Robbins PF, Warren EH. J Immunother. 2012 Feb-Mar;35(2):131-41. (Fred Hutchinson Cancer Research Center, USA)
  2. CAR-T cells inflict sequential killing of multiple tumor target cells. Davenport AJ, Jenkins MR, Cross RS, Yong CS, Prince HM, Ritchie DS, Trapani JA, Kershaw MH, Darcy PK, Neeson PJ. Cancer Immunol Res. 2015 May;3(5):483-94. (Peter MacCallum Cancer Center, Australia)
  3. Serial killers and mass murderers: engineered T cells are up to the task. June CH. Cancer Immunol Res. 2015 May;3(5):470-2. (University of Pennsylvania, USA)
  4. Efficacy of systemic adoptive transfer immunotherapy targeting NY-ESO-1 for glioblastoma. Everson RG, Antonios JP, Lisiero DN, Soto H, Scharnweber R, Garrett MC, Yong WH, Li N, Li G, Kruse CA, Liau LM, Prins RM. Neuro Oncol. 2015 Sep 1. pii: nov153. [Epub ahead of print] (University of California, Los Angeles, USA)

Cancer Immunotherapy: Macrophage-Mediated Phagocytosis

Tumor Associated Macrophages

Macrophages are important effector cells of innate immunity. Depending on the tissue microenvironment, tumor-associated macrophages (TAM) can differentiate into either cytotoxic (M1) or tumor-promoting (M2) states. While cytotoxic M1 macrophages are typically induced by IFN-γ alone or in concert with microbial products, tumor promoting M2 macrophages are induced by IL-4 or IL-13, IL-10, IL-21, TGFβ, immune complexes, and glucocorticoids.

Application Highlight: M1 Macrophage-Mediated Tumor Cell Killing

In a recent study the secreted glycoprotein thrombospondin 1 (TSP1) was shown to be a positive modulator of innate antitumor immunity by increasing M1 macrophage recruitment and stimulating reactive oxygen species (ROS)-mediated tumor cell killing. These conclusions were drawn, in part, by using xCELLigence RTCA impedance monitoring to evaluate the effect of TSP1 on macrophage/monocyte activity when co-cultured with MDA-MB-231 breast adenocarcinoma target cells. The % cytolysis data clearly indicate that the tumoricidal activity of both differentiated U937 human monocytes (left panel) and activated ANA-1 murine macrophages (right panel) are enhanced in the presence of TSP1.

Secreted glycoprotein TSP1 increases macrophage/monocyte-mediated tumoricidal activity.  MDA-MB-231 breast adenocarcinoma target cells were seeded in ACEA’s electronic microtiter plates (E-Plates) and incubated for up to 24 hours. Differentiated U937 human monocytes (left panel) or activated ANA-1 murine macrophages (right panel) were then added in the presence or absence of soluble TSP1. Figure adapted from Cancer Res. 2008;68(17):7090-9.  Note that the RT-CES® described in this publication was ACEA’s first generation real-time cell analysis (RTCA) system, and has subsequently been rebranded as xCELLigence RTCA.

Macrophage-mediated phagocytosis – Supporting Information:
  • Adherent target cells tested:
    MDA-MB-231, MDA-MB-435, MCF-7
  • Macrophage-Mediated Phagocytosis – Compatible xCELLigence Systems:
  • Screenshot_120715_021555_PMReferences:
  1. Thrombospondin 1 promotes tumor macrophage recruitment and enhances tumor cell cytotoxicity of differentiated U937 cells. Martin-Manso G, Galli S, Ridnour LA, Tsokos M, Wink DA, Roberts DD. Cancer Res. 2008 Sep 1;68(17):7090-9. (National Institutes of Health, USA)
  2. Hydroxychloroquine inhibits autophagy to potentiate antiestrogen responsiveness in ER+ breast cancer. Cook KL, Wärri A, Soto-Pantoja DR, Clarke PA, Cruz MI, Zwart A, Clarke R. Clin Cancer Res. 2014 Jun 15;20(12):3222-32. (Georgetown University Medical Center, USA)

Cancer Immunotherapy: NK Cell-Mediated Cytolysis

Natural killer (NK) cells are a type of cytotoxic lymphocyte that play a critical role in the innate immune system, primarily by recognizing and destroying virus-infected cells. NK cells express a number of activation and inhibitory receptors that work in concert to distinguish infected or diseased cells from normal cells. In close proximity to a target cell slated for killing, NK cells are activated and secrete a membrane permeabilizing protein (perforin) and proteases (granzymes) which collectively cause target cell death via apoptosis or osmotic lysis. These mechanisms employed by NK cells to recognize and destroy infected cells are also critical to killing cancer cells.

Unlike T cells which must be educated by antigen-presenting cells before they recognize tumors, NK cells spontaneously lyse certain types of tumor cells in vivo and in vitro without requiring immunization or pre-activation. Similar to virally infected cells, tumor cells also down-regulate their MHC-1 expression. Recognizing this change in expression, NK cells destroy cancer cells through perforin/granzyme mediated lysis. Owing to this capacity, NK cells are being investigated for the purposes of immunotherapy.

Application Highlight: NK-92 Cell-Mediated Cytolysis of MCF7 Breast Cancer Cells

In the experiment shown below, xCELLigence RTCA was used to quantitatively measure the cytolytic activity of NK cells in real-time. After growing adherent breast cancer MCF7 cells in the bottom of E-Plate wells, NK-92 cells were added at different effector to target (E:T) ratios. The data clearly demonstrate NK-92 cell-mediated lysis of the MCF7 cells in a dose- and time-dependent manner (left and right panels).

Importantly, real-time impedance monitoring by the xCELLigence system is sensitive enough to detect target cell killing even at low E:T ratios. For plotting purposes, the percentage of cytolysis is readily calculated using a simple formula: Percentage of cytolysis = ((Cell Index no effector – Cell Index effector)/Cell Index no effector) X 100

Real-time monitoring of NK-92 cell-mediated cytolysis of MCF7 breast cancer cells. Adherent MCF7 target cells were grown in multiple wells of an E-Plate. Different quantities of NK-92 cells were added to each well and impedance was monitored continuously for the next ~20 hours (left panel). The time-dependent cytolytic activity of NK-92 cells at different E:T ratios (right panel) was calculated as described above. Figures adapted from ACEA’s Application Note entitled “Label-Free Assay for NK Cell-Mediated Cytolysis”.

Key Benefits Of Using xCELLigence For Studying NK Cell-mediated Cytolysis:
  1. Label-Free: Allowing for more physiological assay conditions; labeling or secondary assays aren’t required.
  2. Real-Time: Quantitative monitoring of both fast (hours) and slow (days) killing kinetics.
  3. Sensitive: Capable of evaluating low effector cell to target cell ratios that are physiologically relevant.
  4. 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.
  5. Automatic Data Plotting: RTCA software enables facile data display and objective analysis, precluding the subjective data vetting that is common to imaging-based assays.

NK Cell-mediated Cytolysis – Supporting Information:

  • Adherent cell lines tested:
    HT1080, H460, HepG2, MCF-7, A549, HeLa, MDA-MB-231, NIH3T3, MelC, MelS, astrocyte-like cell (NT2A), RCC6, RCC4, mesenchymal stromal cells (MSCs)
  • NK Cell-mediated Cytolysis – Compatible xCELLigence Systems:
    Screenshot_120715_021555_PM
  • NK Cell-mediated Cytolysis References:
  1. Dynamic and label-free monitoring of natural killer cell cytotoxic activity using electronic cell sensor arrays. Zhu J, Wang X, Xu X, Abassi YA. J Immunol Methods. 2006 Feb 20;309(1-2):25-33. (ACEA Biosciences, USA)
  2. Unique functional status of natural killer cells in metastatic stage IV melanoma patients and its modulation by chemotherapy. Fregni G, Perier A, Pittari G, Jacobelli S, Sastre X, Gervois N, Allard M, Bercovici N, Avril MF, Caignard A. Clin Cancer Res. 2011 May 1;17(9):2628-37. (INSERM, France)
  3. Real-time profiling of NK cell killing of human astrocytes using xCELLigence technology. Moodley K, Angel CE, Glass M, Graham ES. J Neurosci Methods. 2011 Sep 15;200(2):173-80. (University of Auckland, Australia)
  4. Mutations of the von Hippel-Lindau gene confer increased susceptibility to natural killer cells of clear-cell renal cell carcinoma. Perier A, Fregni G, Wittnebel S, Gad S, Allard M, Gervois N, Escudier B, Azzarone B, Caignard A. Oncogene. 2011 Jun 9;30(23):2622-32. (INSERM, France)
  5. Evaluation of NK cell function by flowcytometric measurement and impedance based assay using real-time cell electronic sensing system. Park KH, Park H, Kim M, Kim Y, Han K, Oh EJ. Biomed Res Int. 2013;2013:210726. (Catholic University of Korea, South Korea)
  6. Mature cytotoxic CD56(bright)/CD16(+) natural killer cells can infiltrate lymph nodes adjacent to metastatic melanoma. Messaoudene M, Fregni G, Fourmentraux-Neves E, Chanal J, Maubec E, Mazouz-Dorval S, Couturaud B, Girod A, Sastre-Garau X, Albert S, Guédon C, Deschamps L, Mitilian D, Cremer I, Jacquelot N, Rusakiewicz S, Zitvogel L, Avril MF, Caignard A. Cancer Res. 2014 Jan 1;74(1):81-92. (Institut Cochin, France)
  7. Phenotypic and functional characteristics of blood natural killer cells from melanoma patients at different clinical stages. Fregni G, Messaoudene M, Fourmentraux-Neves E, Mazouz-Dorval S, Chanal J, Maubec E, Marinho E, Scheer-Senyarich I, Cremer I, Avril MF, Caignard A. PLoS One. 2013 Oct 18;8(10):e76928. (University of Lausanne, Switzerland)
  8. Inhibition of mesenchymal stromal cells by pre-activated lymphocytes and their culture media. Valencic E, Loganes C, Cesana S, Piscianz E, Gaipa G, Biagi E, Tommasini A. Stem Cell Res Ther. 2014 Jan 9;5(1):3. (Institute of Maternal and Child Health IRCCS Burlo Garofolo, Italy)

Cancer Immunotherapy: T Cell-Mediated Cytolysis

What are T Cells?

By seeking out and destroying infected cells directly, the CD8+ subgroup of T cells play a critical role in the adaptive immune response. Every CD8+ T cell clone expresses a unique variant of a specialized receptor, the T cell receptor (TCR), that can recognize and bind to a specific antigenic peptide presented by MHC class I (MHC-I) molecules on the surface of target cells. Engaging infected or cancerous cells through this antigen:MHC-I complex causes CD8+ cells to secrete perforin and granzymes, leading to lysis of the target cell.

Tumor cells typically acquire extensive mutations in their genomes, including the genes of key regulatory and signaling proteins. When cleaved, processed and presented by the MHC-I molecule on the surface of antigen presenting cells, these mutated proteins can elicit a cellular immune response.

It is for this reason that T lymphocytes can be found inside tumors. Some cancer vaccines exploit this tumor targeting capacity of T cells by priming the cellular arm of the adaptive immune response to target cancer cells that are expressing proteins that are either mutated or expressed at abnormal levels.

Application Highlight: Detecting Cytolytic Activity of CD8+ T Cells Against Breast Cancer Cells

While in some contexts it is useful to quantify the number of antigen-specific CD8+ T cells in samples using assays such as ELISpot or flow cytometry, it is often critical to assess the functional cytotoxicity of these cells via killing assays. Measuring cytolytic activity via the chromium-51 release assay has long been the gold standard for evaluating CD8+ T cell responses.

In the assay shown below, SKBR-3 breast cancer cells expressing the HER2/Neu protein are pre-labeled with 51Cr. They are subsequently co-incubated with increasing amounts of a CD8+ T cell clone that expresses a TCR targeting an antigenic peptide of HER2/Neu, and target cell killing is detected by release of 51Cr into the medium.

This same assay is concurrently performed using the xCELLigence RTCA system without pre-labeling of the target cells. The RTCA system quantitatively detects the cytolytic activity of CD8+ T cells against the SKBR-3 target cells in a manner that is dependent on both time and number of CD8+ T cells added (left panel).

Side by side comparison with the 51Cr release assay shows that the sensitivity and dynamic range of the xCELLigence RTCA assay surpasses that of 51Cr (right panel). Moreover, the preclusion of radio-labeling, and the kinetic data provided by RTCA (including both the onset of cytolysis and the rate of tumor cell killing) make this assay especially attractive.

t ce

CD8+ T cell-mediated cytolysis of SKBR3 tumor cells. Upon CD8+ T cell addition, real-time impedance traces show a distinct drop in the number, size/shape, and/or attachment quality of SKBR3 tumor cells (left panel). This response is dose-dependent, with high effector:target cell ratios yielding the most substantial decrease (left panel). Plotting the percentage of tumor cell lysis, as determined by xCELLigence RTCA vs. a standard 51Cr release assay, demonstrates RTCA to be the more sensitive method (right panel). Figure adapted from J Vis Exp. 2012 Aug 8;(66):e3683.

KEY BENEFITS OF USING xCELLigence FOR STUDYING T Cell-mediated Cytolysis:
  1. Label-Free: Allowing for more physiological assay conditions; labeling or secondary assays aren’t required.
  2. Real-Time: Quantitative monitoring of both fast (hours) and slow (days) killing kinetics.
  3. Sensitive: Capable of evaluating low effector cell to target cell ratios that are physiologically relevant.
  4. 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.
  5. Automatic Data Plotting: RTCA software enables facile data display and objective analysis, precluding the subjective data vetting that is common to imaging-based assays.
T Cell-mediated Cytolysis – Supporting information:

  • Adherent target cells tested:
    TIII melanoma, SK-BR3, HCC1419, MCF-7, BT20, 15-12RM, OAW42, HLA-negative NCI-ADR-RES cells, murine 4T1 mammary gland tumor cells, BCSC (breast cancer stem cell), MSC (mesenchymal stem cell), BT20, HCC1419
  • T Cell-mediated Cytolysis – Compatible xCELLigence Systems:
    Screenshot_120715_021555_PM

 

  • T Cell-mediated Cytolysis Publications:
  1. T cells contribute to tumor progression by favoring pro-tumoral properties of intra-tumoral myeloid cells in a mouse model for spontaneous melanoma. Lengagne R, Pommier A, Caron J, Douguet L, Garcette M, Kato M, Avril MF, Abastado JP, Bercovici N,Lucas B, Prévost-Blondel A. PLoS One. 2011;6(5):e20235. (INSERM, France)
  2. Determining optimal cytotoxic activity of human Her2neu specific CD8 T cells by comparing the Cr51 release assay to the xCELLigence system. Erskine CL, Henle AM, Knutson KL. J Vis Exp. 2012 Aug 8;(66):e3683. (Mayo Clinic, USA)
  3. Enzymatic discovery of a HER-2/neu epitope that generates cross-reactive T cells. Henle AM, Erskine CL, Benson LM, Clynes R, Knutson KL. J Immunol. 2013 Jan 1;190(1):479-88. (Mayo Clinic, USA)
  4. CD47 in the tumor microenvironment limits cooperation between antitumor T-cell immunity and radiotherapy. Soto-Pantoja DR, Terabe M, Ghosh A, Ridnour LA, DeGraff WG, Wink DA, Berzofsky JA, Roberts DD. Cancer Res. 2014 Dec 1;74(23):6771-83. (National Institutes of Health, USA)
  5. An impedance-based cytotoxicity assay for real-time and label-free assessment of T-cell-mediated killing of adherent cells. Peper JK, Schuster H, Löffler MW, Schmid-Horch B, Rammensee HG, Stevanović S. J Immunol Methods. 2014 Mar;405:192-8. (University of Tübingen, Auf derMorgenstelle, Germany)
  6. Targeting specificity of dendritic cells on breast cancer stem cells: in vitro and in vivo evaluations. Nguyen ST, Nguyen HL, Pham VQ, Nguyen GT, Tran CD, Phan NK, Pham PV. Onco Targets Ther. 2015 Jan 30;8:323-34. (Vietnam National University, Vietnam)
  7. A simple in vitro method for evaluating dendritic cell-based vaccinations. Pham PV, Nguyen NT, Nguyen HM, Khuat LT, Le PM, Pham VQ, Nguyen ST, Phan NK. Onco Targets Ther. 2014 Aug 18;7:1455-64. (Vietnam National University, Vietnam)

Cell Adhesion

Quantitative Assessment of Extracellular Matrix Effect on A549 Attachment and Spreading

Cell Adhesion Fig 1

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 
  • 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 and Spreading Publications 
  1. 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.
  2. 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.
  3. 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.
  4. 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.
 

Cell Barrier Function

Comparison of Conventional Methods with the Dynamic Impedance-Based Method for Monitoring Ethanol-Induced Epithelial Barrier Dysfunction

Application_Book_10_01(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)

Application_Book_10_02
(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).

Key Benefits 
  • 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 Barrier Function Supporting Information:

  • Cell Barrier Function Publications:
  1. Apolipoprotein E Receptor 2 Mediates Activated Protein C–Induced Endothelial Akt Activation and Endothelial Barrier Stabilization. Sinha RK, Yang XV, Fernández JA, Xu X, Mosnier LO, Griffin JH. 2016 Jan 21. pii: ATVBAHA.115.306795.
  2. CCM1–ICAP-1 complex controls β1 integrin–dependent endothelial contractility and fibronectin remodeling. Faurobert E, Rome C, Lisowska J, Manet-Dupé S, Boulday G, Malbouyres M, Balland M, Bouin AP,Kéramidas M, Bouvard D, Coll JL, Ruggiero F, Tournier-Lasserve E, Albiges-Rizo C. J Cell Biol. 2013 Aug 5;202(3):545-61.
  3. Vinculin-dependent Cadherin mechanosensing regulates efficient epithelial barrier formation. Twiss F, Le Duc Q, Van Der Horst S, Tabdili H, Van Der Krogt G, Wang N, Rehmann H, Huveneers S,Leckband DE, De Rooij J. Biology Open. 2012; doi:10.1242/bio.20122428
  4. An inverted blood-brain barrier model that permits interactions between glia and inflammatory stimuli. Sansing HA, Renner NA, MacLean AG. Journal of neuroscience methods. 2012;207(1):91–6.
  5. A dynamic real-time method for monitoring epithelial barrier function in vitro. Sun M, Fu H, Cheng H, Cao Q, Zhao Y, Mou X, Zhang X, Liu X, Ke Y. Analytical biochemistry. 2012;425(2):96–103.

Cell-Cell Interations: 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:
  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 Publications:
  1. 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. 2011; 32:(03_MeetingAbstracts): P1-107
  2. Dynamic and label-free monitoring of natural killer cell cytotoxic activity using electronic cell sensor arrays. Zhu J, Wang X, Xu X, Abassi YA. Journal of Immunological Methods. 2006 Feb 20;309(1-2):25-33.
  3. Dynamic detection of natural killer cell-mediated cytotoxicity and cell adhesion by electrical impedance measurements. Glamann J, Hansen AJ. Assay and Drug Development Technologies. 2006 Oct;4(5):555-63.
  4. Real-time profiling of NK cell killing of human astrocytes using xCELLigence technology. Moodley K, Angel CE, Glass M, Graham ES. Journal of Neuroscience Methods. 2011 Sep 15;200(2):173-80.
  5. T cells contribute to tumor progression by favoring pro-tumoral properties of intra- tumoral myeloid cells in a mouse model for spontaneous melanoma. Lengagne R, Pommier A, Caron J, Douguet L, Garcette M, Avril MF, Abastado JP, Bercovici N, Lucas B, Prévost-Blondel A. Public Library of Science One. 2011;6(5):e200235.

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 
  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​

Application_Book_02_02
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 
  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 
  • 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 – Compatible xCELLigence Systems:
    Nanotoxicity Compatible xCELLigence Systems
  • 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:
  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

Application_Book_13_01
(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
  • 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).

In Vitro Hypoxia Studies

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.

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 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.
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 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.
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 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.
GPCR-Mediated Signaling Supporting Information:

  • 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.

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 
  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 
  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
  1. Real time data reveals the kinetics of cell differentiation.
  2. Label-free nature minimizes the need for staining with fluorescent marketings 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.

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.

Virus mediated cytopathic effect Figure 3

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.

Virus mediated cytopathic effect Figure 2

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.

Virus mediated cytopathic effect Figure 1

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

Key Benefits 
  1. Quantify virus titer: An automated, simple, reduced workload alternative to plaque assays.
  2. 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.
  3. 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.
  4. 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.
  5. Rapid assay optimization: Quickly identify the optimal viral titer and assay time point for subsequent screening of inhibitory compounds, neutralizing antibodies and neutralizing serums.
Virus-Mediated CPE Supporting Information:

  • Compatible xCELLigence Systems
    Virus mediated cytopathic effect Compatible xCELLigence Systems
  • Virus-Mediated CPE  Publications
  1. Real-time cell analysis–a new method for dynamic, quantitative measurement of infectious viruses and antiserum neutralizing activity Teng Z, Kuang X, Wang J, Zhang X. J Virol Methods. 2013 Nov;193(2):364-70. doi: 10.1016/j.jviromet.2013.06.034.
  2. Novel, real-time cell analysis for measuring viral cytopathogenesis and the efficacy of neutralizing antibodies to the 2009 influenza A (H1N1) virus. Tian, D., Zhang, W., He, J., Liu, Y., Song, Z., Zhou, Z., Zheng, M., et al. PloS One. 2012;7(2), e31965. doi:10.1371/journal.pone.0031965.
  3. Real-time monitoring of flavivirus induced cytopathogenesis using cell electric impedance technology. Fang, Y., Ye, P., Wang, X., Xu, X., & Reisen, W. Journal of virological methods. 2011;173(2), 251–8. doi:10.1016/j.jviromet.2011.02.013.

Videos: Product Overviews

Videos: Research Presentations

Identifying a Novel Diagnostic and Therapeutic Target for Metastatic Breast Cancer

Dr. Michele I. Vitolo
University of Maryland, Baltimore, MD

With metastasis posing the primary challenge in the clinical management of breast cancer, there is high demand for effective diagnostic and therapeutic strategies focused on this facet of the disease. In this webinar, Dr. Michele Vitolo from…Read More
Bispecific Antibody Constructs Mediate Immunotherapeutic Retargeting of Effector Cells Towards HBV Infected Target Cells

Dr. Felix Bohne
Institute of Virology, German Research Center for Environmental Health, Helmholtz Zentrum München

Chronic viral hepatitis is a major public health threat. Current strategies for eradicating the virus and treating virus-induced liver disease and hepatocellular carcinoma are very limited. Novel therapeutic strategies are in urgent need. Immunotherapeutic retargeting of effector cells is a promising approach to… Read More
Targeting the Reattachment of Circulating Breast Tumor Stem Cells to Reduce Metastasis

Dr. Stuart Martin
University of Maryland School of Medicine, Baltimore, MD

Breast tumor stem cells that are circulating in the bloodstream can invade distant tissues and lie dormant for long periods of time. Reemergence of these disseminated stem cells as metastatic tumors is a primary cause of patient death. In this webinar… Read More
Advances in Toxicity Bioassays – Unleashing the Power of Real-Time Cell Analysis for Health Risk Assessment

Dr. Stephan Gabos
University of Alberta, Edmonton, AB (Canada)

Modern public health protection requires ongoing surveillance of environmental media (water, air, food and soil) for potentially harmful chemicals. There is currently an unmet need for in vitro toxicity assays with higher sensitivity, lower interference, and better… Read More
A Novel in vitro Approach to Study Biocompatibility and Wound Healing

Dr. Sandra N. Garcia
Kinetic Concepts Inc., San Antonio, TX

Negative Pressure Wound Therapy (NPWT), where a vacuum is applied to an acute or chronic wound, has proven extremely effective for promoting would healing. The success of NPWT lies in its ability to draw the edges of a wound together, to promote granulation,…Read More

 

Using Impedance-Based Approaches for Measuring Antigen-Specific Cytotoxic T cell Activity

Dr. Keith L. Knutson
Mayo Clinic, Jacksonville, FL
The Vaccine & Gene Therapy Institute of Florida, Port Saint Lucie, FL

Immunotherapy, where the immune system is harnessed to treat and/or prevent disease, holds great promise in the fight against cancer. One noteworthy facet of cancer immunotherapy is the development of cancer-specific vaccines. In this webinar Dr. Keith L…Read More
Identifying Novel Combination Therapeutic Targets for Pancreatic Cancer

Dr. Melissa L. Fishel
Indiana University School of Medicine, Indianapolis, IN

Pancreatic cancer is presently a largely incurable disease. Increasing evidence suggests that effective treatment strategies will need to simultaneously target multiple molecular mediators of critical functions in pancreatic ductal adenocarcinoma cells (PDAC)…Read More

Videos: Testimonials

Software

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

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

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

For the xCELLigence RTCA DP, SP, and MP instruments experiments are programed and executed, and data is analyzed, using the RTCA 2.0 Software.  This 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 all the wells of a plate.

Step 2: Define Data Acquisition Parameters
Using a second table the details of data acquisition are defined.  These include the frequency of impedance recording and the experiment duration.

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, graphically manipulated, analyzed, and exported.

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).  Lastly, curve fitting functionalities enable calculation of rates of change, EC50 values, etc. (Figure 2B).

A.xCELLigence RTCA 2.0 Software Fig 2.1B.xCELLigence RTCA 2.0 Software Fig 2.2

Figure 2.  Data plotting and analysis using the RTCA 2.0 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) Dose-response curve.  Plotting cell index values (at a specific time post drug treatment) as a function of drug concentration enables determination of an EC50 value.  These types of calculations are readily performed using built in data analysis functions.

Instrument

Description Cat. #
xCELLigence RTCA SP – Bundle (complete system) 00380601030
xCELLigence RTCA SP – Analyzer (model W380) 05228972001
xCELLigence RTCA SP – Station 05229057001
xCELLigence RTCA SP – Control Unit (laptop with pre-installed software) 05454417001

Consumables

Description Cat. #
E-Plate 96 (6 plates) 05232368001
E-Plate 96 (36 plates) 05232376001
E-Plate VIEW 96 (6 plates) 06472451001
E-Plate VIEW 96 (36 plates) 06472460001
E-Plate VIEW 96 PET (6 plates) 00300600910
E-Plate VIEW 96 PET (36 plates) 00300600900
E-Plate Insert 16 (16 well insert, 6 of these) 06465382001
E-Plate Insert 96 (16 well insert; 6 of these are housed in a 96 well Receiver Plate that contains a lid; 6 of these assemblies are included)

  • (Inserts can be cultured in the non-electronic Receiver Plate prior to being transferred
    to an E-Plate for real-time cell analysis.)
06465412001
E-Plate Insert 96 (16 well insert; 6 of these are housed in a 96 well Receiver Plate that contains a lid; 6 of these assemblies are included)

  • (Inserts can be cultured in the non-electronic Receiver Plate prior to being transferred to an E-Plate for real-time cell analysis.)
06465455001