High Content Ratio Imaging for Apoptosis Detection Figure 1. Validation of caspase activity sensor probes. (A) Schematic representation of the FRET probes with corresponding caspase substrate-specific linkers. (B) The schematic representation of the default FRET between ECFP and Venus in untreated cells and its loss upon linker cleavage is shown. (C) Merged image of ECFP and FRET channels of untreated MCF7 SCAT3 cells (D) Merged image of ECFP and FRET channels of MCF7 SCAT 3 cells after treatment with staurosporine (500 nM, 12 hrs). (E) Ratio pseudo-image of the same cells untreated and (F) staurosporine treated cells. Arrows depict a representative cell showing FRET loss. (G) Histogram showing reversal of percentage of high FRET loss positive cells upon treatment with the corresponding caspase inhibitor in MCF7 SCAT3, SCAT8 and SCATcells. The cells were subjected to drug treatment in the following manner: MCF7 SCAT3 and SCAT9 cells with Staurosporine (250 nM) and SCAT8 cells with Anisomycin (2 mg/ml) for 10 hours.selected based on the maximal activity observed. Images shown in Supplementary figure S3 (H) Confocal-based FRET acceptor bleaching in MCF7 cells showing pre- bleach and post-bleach images of untreated and treated (STA 500 nM, 12 hrs) (I) FRET efficiency calculated from confocal acceptor bleaching experiments of cells expressing indicated probes with and without STA treatment. (J) Immunoblot of the drug treated HeLa SCAT3, SCAT8 and SCAT9 cells and the corresponding cleavage of endogenous caspases as well as SCAT, probed with anti-GFP (K) Percentage of cells with ECFP-EYFP FRET loss analysed for the indicated probe-expressing HeLa cells analysed by FACS after treatment for indicated time points. (L) Flow cytometry scatter plot of % cells with high ECFP- EYFP FRET ratio loss of HeLa SCAT3, SCAT8 and SCAT9 cells after 0 h, 4 h, 8 h 12 h and 24 h of Cisplatin (50 mg/ml) treatment: and graphical (M) representation. (N) Untransfected MCF7 cells and its SCAT3/SCAT8/SCAT9 transfected counterparts tested for % apoptotic nuclei after Cisplatin (50 mg/ml, 10 hrs) treatment. doi:10.1371/journal.pone.0020114.g001 multiparameter HTS results indicate that the growth inhibitory and toxic activities of Gossypol without a correspondingly massive MMP loss could be due to the massive superoxide generation and an alternate superoxide-mediated, MMP loss-independent apop- tosis signaling mechanism. To highlight the multiparameter potential of the method, chromatin condensation and FRET ratio loss channels of the same experiment have also been shown. Overall, the results highlight the potential of the platform to identify non-classical death signaling induced by chemical entities in a high throughput manner with high content multiparameter analysis. Adaptability for assaying multiparameter kinetics For assaying DEVDase activity as a function of time, HeLa SCAT3 cells were treated with a panel of 42 drugs (in duplicates) and imaged at specified time intervals over a period of 0 to 72 hours post drug treatment. Both DEVDase activity and chromatin condensation were assayed in these cells over time. Heat maps depicting the drug response helped identify 24 positive hits that showed gradational DEVDase activity over time (Figure 7). Out of these, 12 hits showed very gradual increase in both DEVDase activity and chromatin condensation kinetics, which is depicted as ‘Response group A’, while 7 showed very high activity even as early as 12 hrs after drug treatment, depicted as ‘Response Group B’. A reduction in the read out by 72 hrs in some of the populations is due to the loss of cells in the wells because of excessive cell death. A representative image set and quantitative information of the two response groups have been shown. Our results show that a similar kinetics response pattern is observed among compounds with a common mechanism of action. Hsp90 inhibitors 17AAG, 17DMAG and Radicicol showed a slow, but consistent effect in inducing DEVDase activity and chromatin condensation. Similarly, HDAC inhibitors SBHA, Apicidin and Trichostatin A as well as ER stress inducers Tunicamycin and TG also showed a similar effect. On the other hand, DNA Topoisomerase inhibitors Camptothecin and Novo- biocin that directly inhibit the DNA caused massive chromatin condensation at 12 hr itself, but with only a slower effect on the DEVDase activity over time. Translation inhibitors Cyclohexi- mide and Anisomycin, flavonoids Apigenin and Gingerol, Bcl-2 antagonist HA-14-1 as well as CK1 & CK2 inhibitor 5,6-dicloro 1,b-D ribofuranosyl benzimidazole had equal effect on inducing rapid DEVDase activity and chromatin condensation as early as 12 hr after drug treatment. Multiparameter death signaling signatures obtained with drugs of differing mechanisms of action points to the fact that apoptosis centered algorithms can be developed for profiling large chemical libraries for unknown functions. Adaptability for comparing differential drug sensitivity among cell lines Response to a particular drug varies from one cell type to another. We wanted to check the adaptability of our method to compare such differences among cell lines. For this, we generated SCAT3 transfected U251 and HeLa stable cell lines, which were treated with a panel of 37 drugs (in duplicates) and the DEVDase activity was imaged and analysed at 48 hrs post treatment. The differential response pattern showed that glioblastoma U251 cells were responsive to a greater range of compounds under the study, when compared to cervical adenocarcinoma HeLa cells (Figure 8). U251 cells were most sensitive to Trichostatin A, Sulindac, Actinomycin D, TRAIL, SBHA and Apicidin followed by Radicicol, Mevinolin, Gossypol, Camptothecin, MG132, TG and Licochalcone. HeLa cells showed most sensitivity towards Actinomycin D and Licochal- cone, moderate sensitivity towards Radicicol, Gossypol, SBHA and Apicidin, followed by Sulindac and Mimosine. Taken together, Actinomycin D was found to be inducing DEVDase activity both the cell lines under study, although with differing strengths. Our result reinforces the idea of differential sensitivity of different cell lines to a set of drugs and thereby projects itself as a useful tool in the initial screening for identifying the best set of apoptosis inducing compounds before delving into the mechanism of action in a particular cell line. Comparison of IETDase, LEHDase and DEVDase activity against MMP loss Next, we wanted to make a simultaneous comparative study of IETDase and LEHDase activity together with DEVDase activity and its correlation with Dym. For this, we generated stable clones of HeLa cells transfected with SCAT3, SCAT8 and SCAT9, which gave a direct read out of DEVDase, IETDase and LEHDase activity respectively. At 12 hrs after drug treatment, as expected, we found considerable variability in the induction of probe cleavage by different drugs (Figure 9). We found Cycloheximide, Anisomycin, 5,6-dicloro1,b-D ribofuranosyl benzimidazole (RBZ), Gossypol and Camptothecin to be most active in inducing IETDase activity and HA-14-1, 4-aminohy- droxyflavone and Apoptosis Activator I in inducing LEHDase activity. Most of the drugs induced DEVDase activity, the most prominent of those being Apigenin, Mevinolin, RBZ, Cyclohex- imide, Actinomycin D, Camptothecin, Apoptosis Activator I and Anisomycin. When comparing the probe cleavage with MMP loss, we found a good correlation of LEHDase activity with MMP loss when compared to IETDase activity that was largely not correlated with MMP loss. The DEVDase activity was always PLoS ONE | www.plosone.org 6 May 2011 | Volume 6 | Issue 5 | e20114