Analysis of inter-/intra-E-plate repeatability in the real-time cell analyzer.

Over the past decade, the real-time cell analyzer (RTCA) has provided a good tool to the cell-based in vitro assay. Unlike the traditional systems that label the target cells with luminescence, fluorescence, or light absorption, RTCA monitors cell properties using noninvasive and label-free impedance measuring. However, realization of the maximum value of RTCA for applications will require assurance of within-experiment repeatability, day-to-day repeatability, and robustness to variations in conditions that might occur from different experiments. In this article, the performance and variability of RTCA is evaluated and a novel repeatability index (RI) is proposed to analyze the intra-/inter-E-plate repeatability of RTCA. The repeatability assay involves six cell lines and two media (water [H2O] and dimethyl sulfoxide [DMSO]). First, six cell lines are exposed to the media individually, and time-dependent cellular response curves characterized as a cell index (CI) are recorded by RTCA. Then, the variations along sampling time and among repeated tests are calculated and RI values are obtained. Finally, a discriminating standard is set up to evaluate the degree of repeatability. As opposed to the standardized methodologies, it is shown that the presented index can give the quantitative evaluation for repeatability of RTCA within E-plate and variation on different days.

Mode of action classification of chemicals using multi-concentration time-dependent cellular response profiles.

In this paper, we present a new statistical pattern recognition method for classifying cytotoxic cellular responses to toxic agents. The advantage of the proposed method is to quickly assess the toxicity level of an unclassified toxic agent on human health by bringing cytotoxic cellular responses with similar patterns (mode of action, MoOA) into the same class. The proposed method is a model-based hierarchical classification approach incorporating principal component analysis (PCA) and functional data analysis (FDA). The cytotoxic cell responses are represented by multi-concentration time-dependent cellular response profiles (TCRPs) which are dynamically recorded by using the xCELLigence real-time cell analysis high-throughput (RTCA HT) system. The classification results obtained using our algorithm show satisfactory discrimination and are validated using biological facts by examining common chemical mechanisms of actions with treatment on human hepatocellular carcinoma cells (HepG2).