Cell Indices Research Articles

Real-Time Monitoring of Photocytotoxicity in Nanoparticles-Based Photodynamic Therapy: A Model-Based Approach

Nanoparticles are widely suggested as targeted drug-delivery systems. In photodynamic therapy (PDT), the use of multifunctional nanoparticles as photoactivatable drug carriers is a promising approach for improving treatment efficiency and selectivity. However, the conventional cytotoxicity assays are not well adapted to characterize nanoparticles cytotoxic effects and to discriminate early and late cell responses. In this work, we evaluated a real-time label-free cell analysis system as a tool to investigate in vitro cyto- and photocyto-toxicity of nanoparticles-based photosensitizers compared with classical metabolic assays. To do so, we introduced a dynamic approach based on real-time cell impedance monitoring and a mathematical model-based analysis to characterize the measured dynamic cell response. Analysis of real-time cell responses requires indeed new modeling approaches able to describe suited use of dynamic models. In a first step, a multivariate analysis of variance associated with a canonical analysis of the obtained normalized cell index (NCI) values allowed us to identify different relevant time periods following nanoparticles exposure. After light irradiation, we evidenced discriminant profiles of cell index (CI) kinetics in a concentration- and light dose-dependent manner. In a second step, we proposed a full factorial design of experiments associated with a mixed effect kinetic model of the CI time responses. The estimated model parameters led to a new characterization of the dynamic cell responses such as the magnitude and the time constant of the transient phase in response to the photo-induced dynamic effects. These parameters allowed us to characterize totally the in vitro photodynamic response according to nanoparticle-grafted photosensitizer concentration and light dose. They also let us estimate the strength of the synergic photodynamic effect. This dynamic approach based on statistical modeling furnishes new insights for in vitro characterization of nanoparticles-mediated effects on cell proliferation with or without light irradiation.

Abstract 4300: Comparative assessment of cell viability and motility kinetics by novel real-time technology and classic endpoint assays

Abstract Background Elucidation of biological mechanisms underlying deregulated proliferation and motility of cancer cells and identification of potential therapeutic targets require accurate cell-based monitoring. The xCELLigence Real Time Cell Analysis (RTCA) technology (Roche Applied Science) constitutes a non-invasive and label-free approach to assess cell viability and motility in real time, hereby countering key features of classic label-based endpoint detection methods. Here we show results of in vitro detection of cell viability and migration on 2 cancer cell lines using xCELLigence RTCA DP and correlate these with data obtained from parallel experiments carried out using established assessment methods for each process. Methods and results Kinetic viability and migration measurements were carried out on the MDA-MB-231 (breast cancer) and A549 (lung cancer) cell lines using the xCELLigence RTCA DP instrument. Cell viability was assessed during 10 days of incubation using modified 16-well plates (E-plate) containing microelectrodes at the well bottoms for impedance-based detection of attachment, spreading and proliferation, expressed as a Cell Index (CI) value. Cell migration was measured during 38 hours using 16-well plates (CIM16-plate) consisting of an upper and a lower chamber separated by a microporous membrane equipped with a similar detection system at the bottom side. The Sulforhodamine B (SRB) assay and a 24-well Transwell system served as reference tools to assess viability and migratory kinetics. Viability was estimated by optical density (OD) reading (540 nm) of solubilized cells that were fixed and stained with SRB at a rate of 1 plate per day. Good correlations were observed between SRB and RTCA CI for 5x103 and 104 MDA-MB-231 cells/mL (Spearman's ≤ = 0.79 and 0.84 resp) and similar doubling times (p = 0.459). The experimental Transwell design allowed dynamic quantitation of cancer cell migration by fixing and staining of the insert membranes in methanol and crystal violet in duplicates at 10 time points during a 24 hour-incubation. Pixel area quantitation showed strong correlation with xCELLigence CI (Spearman's ≤ = 0.90 for both cell lines). However, OD measurements (590 nm) correlated even stronger with CI (Spearman's ≤ = 0.96 and 1.00 for MDA-MB-231 and A549). Moreover, analysis of random migration indicated a significant difference between RTCA CI and area / OD (p < 0.001) implying reduced detection limits of the xCELLigence system. Conclusions The similarity between observations as performed with conventional approaches and xCELLigence makes both methods interchangeable. Added with results indicating reduced detection limits, xCELLigence provides an accurate detection platform for high-throughput kinetic screenings and for determination of time-dependent cell proliferation and motility dynamics. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4300. doi:1538-7445.AM2012-4300

Killing Effects of Different Physical Factors on Extracorporeal HepG2 Human Hepatoma Cells

To determine the killing effects on extracorporeal HepG2 cells under different temperatures, pressures of permeability and lengths of treatment time. According to different temperatures, pressures of permeability and lengths of treating time, extracorporeal HepG2 cells of human hepatoma cell-line were grouped to 80 groups. Cell index (CI) as the measurement of killing effect were calculated by monotetrazolium (MTT) methods, i.e., CI = 1 - (the OD value in treated group - the OD value in blank control group)/(mean of untreated control group - mean of blank control group). According to the factorial design, data were fed into SPSS 10.0 and analyzed by three-way ANOVA (analysis of variance). Temperature, pressure of permeability and length of treating time all had effects on the CI (cell index) level. Length of treating time was the most influential factor of the three. Additionally, any two of them all had statistically significant interactive effects on the CI level. When treated for 5-30 min, destilled water at 46 degrees C stably generated the highest CI. The "46 degrees C-destilled water-60 min" was considered as the optimal combination of conditions which lead to highest CI. We suggest exerting celiac lavage for 15 min with stilled water at 40 degrees C-43 degrees C in surgical practice as a hyperthermia treatment to achieve ideal killing effects on free cancer cells, which is feasible, practical, and clinically effective.

Recognition of chemical compounds in contaminated water using time-dependent multiple dose cellular responses

An early determination of toxicant compounds of water contaminations can gain critical time to protect citizens’ health and save substantial amounts of medical costs. To determine toxins in real time, a multi-dose classification algorithm using cellular state variable identification (CSVID) is developed in this paper. First, the dynamic cytotoxicity response profiles of living cells are measured using a real-time cell electronic sensing (RT-CES) system. Changes in cell number expressed as cell index (CI) are recorded on-line as time series. Then CSVID, which reflects the cell killing, cell lysis and certain cellular pathological changes, is extracted from those dynamic cellular responses. Finally, a support vector machine (SVM) algorithm based on CSVID is employed to classify chemical compounds and determine their analogous cellular response pathway. In order to increase the classification accuracy, a majority vote of the class labels is also proposed. Several validation studies demonstrate that CSVID-based classification algorithm has great potential in distinguishing the cytotoxicity response of the cells in the presence of toxins.

Real-time profiling of NK cell killing of human astrocytes using xCELLigence technology

We have conducted the first profiling of human Natural Killer (NK) cell mediated killing of astrocytes using xCELLigence technology. The sensitivity and applicability of xCELLigence was compared to lactate dehydrogenase (LDH) release and time-lapsed microscopy to validate the killing events. The xCELLigence technology uses electrical impedance measurements from adherent cells and converts into Cell Index (CI). NK cells did not register any Cell Index signal directly, therefore all changes in Cell Index are a direct measure of astrocyte responses. Astrocytes are insensitive to basal NK cells (non-activated NKs). Whereas NK cells activated by IL-2 prior to culture with targets rapidly kill astrocytes. This observation was supported by all methods of analysis. Using the xCELLigence we were able to monitor the longer term killing profile. This demonstrated that at all NK ratios, death was achieved if given long enough. In addition, the development of the killing phenotype was investigated by inducing lymphokine activated killing with IL-2 in the presence of the target astrocytes. In this paradigm of killing, the xCELLigence was the only assay suitable due to the prolonged time-course required for killing, which required 4–5 days to achieve maximal killing (100%). This suggested that the astrocytes can directly suppress the killing activity of the NK cells. These data highlight the sensitivity, applicability and profiling power of the xCELLigence system and support its use for further investigation of NK-killing of healthy and/or tumourogenic astrocytic cells.

Data-based modeling and prediction of cytotoxicity induced by contaminants in water resources

Abstract This paper is concerned with dynamic modeling, prediction and analysis of cell cytotoxicity induced by water contaminants. A real-time cell electronic sensing (RT-CES) system has been used for continuously monitoring dynamic cytotoxicity responses of living cells. Cells are grown onto the surfaces of the microelectronic sensors. Changes in cell number expressed as cell index (CI) have been recorded on-line as time series. The CI data are used to develop dynamic prediction models for cell cytotoxicity process. We consider support vector regression (SVR) algorithm to implement data-based system identification for dynamic modeling and prediction of cytotoxicity. Through several validation studies, multi-step-ahead predictions are calculated and compared with the actual CI obtained from experiments. It is shown that SVR-based dynamic modeling has great potential in predicting the cytotoxicity response of the cells in the presence of toxicant.

Donor-Graft Compatibility Tests in Pig-to-Primate Xenotransplantation Model: Serum Versus Plasma in Real-Time Cell Analyzer Trials

Introduction Various strategies have been designed to assess in vitro donor-graft compatibility in pig-to-primate xenotransplantation models. Most of them are based on a cytolysis assessment by exposing donor tissue to host serum with investigations by flow cytometry, and photocolorimetric levels. The aim of this study was to analyze the difference in cytolysis produced by sera and plasma obtained using various anticoagulants, or containing high versus low levels of platelets. Methods The cytolysis trials were performed using an xCELLigence real-time cell analyzer (RTCA) in a cell model involving transgenic pig fibroblasts exposed to sera (S) or plasma obtained using EDTA, Li-heparin, or Na-heparin in combination with plasma containing high versus low content of platelets. Samples were obtained from two baboons and five volunteer human donors. Evolution of fibroblast cell growth was assessed by RTCA as the cell index (CI). After 9 hours of growth, cells were exposed to 20 μL of each sample. The minimum CI (CImin), time to CImin (TCImin), and time to reach the CI observed before compound addition (Trec) were recorded for each microwell. Results The lowest CImin, highest TCImin, and Trec observed for EDTA plasma showed significant differences from other samples ( P < .001). Discussion On the basis of this study, using the RTCA assay, heparinized plasma produced complement inhibition and with undervaluation of the cytolysis reaction. EDTA plasma produced total death of most of cultures. The most accurate sample matrix seems to be serum.

Cellular impedance measurement as a new tool for poxvirus titration, antibody neutralization testing and evaluation of antiviral substances

Impedance-based biosensing known as real-time cell electronic sensing (RT-CES) belongs to an emerging technology for analyzing the status of cells in vitro. In the present study protocols were developed for an RT-CES-based system (xCELLigence™, Roche Applied Science, ACEA Biosciences Inc.) to supplement conventional techniques in pox virology. First, proliferation of cells susceptible to orthopoxviruses was monitored. For virus titration cells were infected with vaccinia virus and cell status, represented by the dimensionless impedance-based cell index (CI), was monitored. A virus-dose dependent decrease in electrical impedance could be shown. Calculation of calibration curves at a suitable CI covering a dynamic range of 4 log enabled the quantification of virus titers in unknown samples. Similarly, antiviral effects could be determined as shown for anti-poxviral agents ST-246 and Cidofovir. Published values for the in vitro concentration that inhibited virus replication by 50% (IC 50) could be confirmed while cytotoxicity in effective concentrations was excluded in long-term incubation experiments. Finally, an RT-CES-based virus neutralization test was established. Various poxvirus-specific antibodies were examined for their neutralizing activity and a calculation mode for the neutralizing antibody titer was introduced. In summary, the presented RT-CES-based methods outmatch end-point assays by observing the cell population throughout the entire experiment while workload and time to result are reduced.

&lt;I&gt;In Vitro&lt;/I&gt; Study of Silica Nanoparticle-Induced Cytotoxicity Based on Real-Time Cell Electronic Sensing System

The biological fate and potential toxicity of nanoparticles have become hot topics since the use of nanoparticles was extended to the biomedical and biotechnological field. In this paper, an in vitro study of silica (SiO2) nanoparticle-induced cytotoxicity was presented mainly by real-time cell electronic sensing (RT-CES) system, which could be used for label-free, dynamic measurement of cell responses to cytotoxicants. The cytotoxicity of both 20-nm silica nanoparticles and microscale SiO2 powder in cultured RAW264.7 cells at dosage levels from 31.25 to 8000 microg/ml was evaluated comparatively. The experimental results showed that the cell index (CI) decrease induced by SiO2 nanoparticles appeared earlier than that by the microscale SiO2 powder at the same dose. The nanoparticles in the dose of 500 micdrog/ml had the toxic effect by the Cell Index Curves of RT-CES, while the microscale SiO2 powders in the same dose did not show obvious effect. The above experimental results were compared with the experiments of a tetrazolium compound-based colorimetric method (MTT assay) and LDH activity in medium. The results showed that the RT-CES assay displayed equal sensitivity and correlation to MTT assay. LDH activity caused by SiO2 nanoparticles at dose of 250 and 500 microg/ml was higher than that by microscale SiO2 particles, which indicated that the exposure to SiO2 nanoparticles could result in a dose-dependent cytotoxicity in cultured RAW264.7 cells due to cell membrane injury. The RT-CES system allows a realtime, continuous monitoring and quantitative recording of the whole assay process and provides a new insight into the cell-toxicant interaction.

Real-time xCELLigence impedance analysis of the cytotoxicity of dental composite components on human gingival fibroblasts

Aim of this study was by continuous monitoring to assay the proliferative capacity of human gingival fibroblasts (HGFs), to investigate cytotoxicity of the most common monomers/comonomers in dental resin composites: bisphenol-A-glycidylmethacrylate (BisGMA), hydroxyethylenemethacrylate (HEMA), triethyleneglycoldimethacrylate (TEGDMA), and urethanedimethacrylate (UDMA) in HGFs during 24h exposure using the xCELLigence system. xCELLigence cell index (CI) impedance measurements were performed according to the instructions of the supplier. HGFs were resuspended in medium and subsequently adjusted to 400,000, 200,000, 100,000, and 50,000 cells/mL. After seeding 100 microL of the cell suspensions into the wells of the E-plate 96, HGFs were monitored every 15 min for a period of up to 18 h by the xCELLigence system. Half maximum effect concentrations (EC(50)) were determined based on the dose-response curves derived by xCELLigence measurements. Following real-time analysis, significantly increased EC(50) values of HGFs exposed for 24h to the following substances were obtained: HEMA(a), TEGDMA(b), UDMA(c). The EC(50) values (mean [mmol/L]+/-S.E.M.; n=5) were: HEMA 11.20+/-0.3, TEGDMA(a) 3.61+/-0.2, UDMA(a,b) 0.20+/-0.1, and BisGMA(a,b,c) 0.08+/-0.1. These results are similar to the EC(50) values previously observed with the XTT end-point assay. Our data suggests that the xCELLigence live cell analysis system offers dynamic live cell monitoring and combines high data acquisition rates with ease of handling. Therefore, the xCELLigence system can be used as a rapid monitoring tool for cellular viability and be applied in toxicity testing of xenobiotics using in vitro cell cultures.

Dynamic Detection of Natural Killer Cell-Mediated Cytotoxicity and Cell Adhesion by Electrical Impedance Measurements

Measurement of electrical impedance is a relatively new real-time and label-free method for monitoring cell adhesive properties. Impedance measurements are performed in tissue culture wells in which the bottom is equipped with gold electrodes. The extent of electrode coverage by living cells as well as the strength of the bond between the cell membrane and the electrode surface determines the impedance, which in real-time cell electrical sensing (RT-CES, ACEA Biosciences, San Diego, CA) is measured as the cell index (CI). We showed for carcinoma cells that CI was linearly correlated to the number of cells and that CI also was related to the amount of coating (laminin-5) of the wells. When natural killer (NK) cells were added to adherent carcinoma cells (target cells) CI declined rapidly dependent on the NK cell:target cell ratio. The initial decrease of CI was much more pronounced than target cell death as measured by [(3)H]thymidine incorporation assay. Such a rapid fall of CI was due to changes in the adhesion and morphology of target cell undergoing apoptosis. It took more than 6 h before the extent of cell death and fall of CI were comparable. We also showed using A431 cells and an antibody specific for the human epidermal growth factor receptor (Erbitux, manufactured by Merck KGaA, Darmstadt, Germany) that RT-CES could be used to monitor antibody-dependent cellular cytotoxicity. Thus RT-CES is a convenient way to continuously determine cell number and cell adhesion and may offer early detection of NK cell-mediated cytotoxic effects.

Dynamic Modelling and Prediction of Cytotoxicity on Microelectronic cell Sensor Array

AbstractA real‐time cell electronic sensing (RT‐CES) system has been used for label‐free dynamic measurements of cell responses to toxicant. Cells are grown onto the surfaces of the microelectronic sensors. Changes in cell number expressed as cell index (CI) have been recorded on‐line as time series. The CI data are used for dynamic modelling or parameter estimation for cell cytotoxicity process. We consider two dynamic modelling approaches, namely data‐based system identification and first principle modelling. It is shown that data‐based system identification can provide a quick solution for the cytotoxicity dynamic models and is effective for short‐term predictions. It, however, can be poor for long‐term predictions, particularly if there is no output correction, i.e., when the model is used for simulation. In view of this, the first principle modelling approach by considering fundamental physical principles such as toxicant transport is explored. For long‐term prediction or simulation, the prediction performance for some of cytotoxicity process is dramatically improved using the models obtained from the latter approach. This happens only if the underlying mechanism is truly understood. Through several cytotoxicity modelling and validation studies, it is shown that the black box modelling and first principle modelling both should be considered in challenging modelling problems such as the cytotoxicity. Pros and cons of the two modelling approaches are discussed.