Tech Review

GPCR HTS using the xCELLigence System


Increasing evidence suggests that the cellular response to ligand-induced receptor activation is influenced by receptor expression levels and downstream signaling components that can be different amongst various cell types. There is therefore increasing interest in measuring drug target activity and the effects of target-modulating principles, such as synthetic compounds, in assays that reflect native and disease-relevant cellular environments. Sensitive label-free technologies have been recently developed for cellular applications, including optical waveguide grating, live-cell imaging or impedance (reviewed by Xi et al. 2008 and Nayler et al. 2010). Compared to standard readout technologies, one of the major advantages of these approaches is that cellular processes are measured in real-time kinetics in a non-invasive manner, and this makes them particularly suitable for the development of assays using primary cells. The impedance-based xCELL­igence RTCA System from Roche Applied Science, which was co-developed with ACEA Bioscience, uses gold electrodes at the bottom surface of microplate wells as sensors to which a low-voltage alternating current is applied. Cells that are grown as adherent monolayers on top of such electrodes influence the alternating current at the electrodes by changing the electrical resistance (impedance). The degree of change is primarily determined by the number of cells, strength of the cell-cell interactions, interactions of the cells with the microelectrodes and the overall morphology of the cells. Importantly, GPCR activation translates into quantitative changes in impedance due to induction of morphological changes, and these highly reproducible impedance changes are well-suited for the quantitative pharmacological characterization of GPCR agonists and antagonists.

Integration of RTCA HT Stations in the BioCel1200 system

Our dual BioCel1200 System from Agilent Technologies (Santa Clara, US) is an automated high-throughput screening platform with two central robots (of the “Asyst” type) and additional devices located in a radial configuration around the robots in a modular way (see Fig. 1). Agilent’s event-driven scheduler VWorks 4 is used for automation control. An updated VWorks 4 version with a newly developed driver for the RTCA HT Instrument was written and installed by Agilent. With the current set-up, test compounds and agonist were added off-line, causing a time lag of 40 seconds prior to the first impedance measurement. Due to the geometry of the E-Plate 384 lids and the grippers of the Asyst robot, the plate lids had to be removed before the impedance measurement. The overall performance and process stability of the system was tested in two reference experiments (data not shown).

Validation of Ox1 hits in

secondary impedance assays

The Ox1 receptor selectively binds and is activated by the neuropeptide orexin A (for reviews, see Gatfield et al. 2010, Tsujino et al. 2009). A high-throughput calcium flux-based screen was performed with a Fluorometric Imaging Plate Reader (FLIPR, Molecular Devices, US). 71,063 compounds were tested at 10 μM to identify potential inhibitors of orexin A-induced Ox1 receptor activation using recombinant CHO-K1 cells expressing the human Ox1 receptor. With a cutoff of >50 % inhibition, 570 initial primary hits were found, of which 263 were subsequently confirmed in the same assay. These 263 compounds were randomly placed in adjacent duplicates in a set of 1,258 compounds on eight microplates. This compound set was then measured at 10 μM in the RTCA HT assay, using the same Ox1 receptor expressing CHO-K1 cells that had been used for the FLIPR screening.
In the automated workflow, cells were seeded in the E-Plates 384 and incubated overnight in a controlled environment incubator (Cytomat, Thermo) at 37°C and 5% CO2. During this time, impedance was recorded at regular intervals by shuttling the E-plates out of the Cytomat onto the RTCA HT stations. The following morning, cells were washed with serum-free medium and equilibrated for 50 minutes in the Cyto­mat. Baseline impedance measurements were taken, compounds were then added, and impedance was recorded for five minutes before addition of 10 nM orexin A agonist. Subsequently, impedance was recorded for 25 minutes at 30 second intervals. Traces were normalized to the time point of agonist addition; data reduction was performed 25 minutes after agonist addition, and the results were exported as text files via the RTCA bridge server software (installed on the RTCA HT Control Unit). For the final analysis, said text files were imported into an Actelion proprietary HTS software suite.

Data quality

Data quality obtained in the RTCA HT Instrument screen was assessed in several ways (see also Fig. 2): First we looked at the quality of the E-Plates 384: within the whole test phase, a total of 101 E-Plates 384 were screened. 39 wells failed electronically, corresponding to a single-well failure rate of 0.4 well/plate (0.1%). Second, on the basis of 16 high controls (with 10 nM agonist) and 16 low controls (no agonist) on each E-Plate 384 of the Ox1 screen, the Z’ factor and coefficient of variation (CV) values were calculated. At an average window size of 1.38, the average Z’ factor was 0.46±0.09; CV values were 3.4% for high and 3.4% for low controls (Fig. 2). Third, as a further control, a dilution series of the agonist and a reference antagonist were added to each plate. There was very little variation across plates in the EC50 and IC50 values (9.5nM±4.0nM and 13.3nM±3.2nM, respectively). The correlation coefficient (Bravais-Pearson) of adjacent duplicates – a measure of intra-assay reproducibility – was calculated as 0.96. Finally, the same screen was repeated on a different day under identical conditions. The correlation coefficient of 0.87 was calculated for the average of the duplicates in the two independent runs (Fig 2). In summary, the RTCA HT Instrument delivered a high-quality data set with very high intra-assay and inter-assay reproducibility.

Hit confirmation rates in RTCA HT Instrument assays

It is important to note that the calcium flux FLIPR assay and the RTCA HT Instrument assay produced very similar EC50 values for orexin A and IC50 values for a reference antagonist (data not shown). It therefore appeared reasonable to apply a similar inhibition threshold for the RTCA assay (40%). In addition, an upper threshold of <120% inhibition for impedance data was used, as inhibition >120% might be due to cytotoxicity. 170 compounds of the 263 FLIPR hits were confirmed in the RTCA HT Instrument assay, corresponding to a confirmation rate of 65% (Fig. 3). The remaining 93 compounds were then investigated in more detail, and were measured in a calcium flux FLIPR using an unrelated G protein-coupled receptor. 40 of the 93 compounds (43%) showed >30% inhibition in this specificity assay, and are therefore considered false positive FLIPR hits.


The integration of two RTCA HT Stations into an automated dual BioCel1200 system from Agilent Technologies was successfully performed in a single day. Fully automated runs worked well: on average, less than 0.5 wells per E-Plate 384 failed electronically to deliver data. During this pilot study, Z’ factors around 0.5 and coefficients of variation (CV) below 5% were obtained. Intra-assay and inter-assay data reproducibility were high. Consistent with this, the EC50 and IC50 values of reference substances showed very little variation from plate to plate or screen to screen. 170 compounds of 263 calcium flux FLIPR hits were confirmed with RTCA HT Instrument assays as secondary assays (65%). Compounds that were non-specific in the FLIPR assay were not confirmed by impedance technology, so that impedance was able to distinguish between specific and non-specific hits. In the set-up with two RTCA HT Stations and with our assay protocol, the throughput was about 20 plates per day. We conclude that the RTCA HT Instrument is well suited as a secondary screening technology and complements classical GPCR assay formats.D

1 Abassi et al. (2009). Chem Biol. 16 (7): 712-23.
2 Atienza et al. (2006). Assay Drug Dev Technol. 4(5): 597-607. Review.
3 Gatfield et. al. (2010). ChemMedChem. 5(8):1197-214. Review.
4 Nayler, Birker-Robaczewska, Gatfield (2010). Integration of label-free detection methods in GPCR Drug Discovery. GPCR Molecular Pharmacology and Drug Targeting. Wiley&Sons. Edited by Annette Gilchrist. Chapter 11.
5 Tsujino et al. (2009). Pharmacol Rev. 61(2):162-76. Review.
6 Xi et al. (2008). Biotechnol J. 3(4):484-95. Review.

Urs Lüthi, John Gatfield
Actelion Pharmaceuticals Ltd.
Gewerbestrasse 16, CH-4123 Allschwil, Switzerland

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