Use of online cell counting for micronucleus and neurite outgrowth assays on IN Cell Analyzer 2000

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1 GE Healthcare Application note AA IN Cell Analyzer 2000 Use of online cell counting for micronucleus and neurite outgrowth assays on IN Cell Analyzer 2000 Key words: IN Cell Analyzer online cell counting micronuclei analysis neurite outgrowth A critical factor in establishing robust high-content cell assays is the assurance that enough cells are imaged per treatment condition. This can be achieved on IN Cell Analyzer 2000 by automatically counting cells online as each image is acquired. In this optional acquisition mode, successive fields of view are acquired until a pre-set cell count threshold is achieved. Online cell counting has the additional advantage of reducing plate read times and the data storage burden, since no excess images are acquired once the desired number of cells has been imaged. Here we provide data demonstrating the ability of the IN Cell Analyzer 2000 online cell counting feature to improve assays containing variable cell counts. The feature is applied to increase speed and ensure robust performance of micronucleus and neurite outgrowth assays. The online cell counting feature requires that a fluorescent marker is present for cell identification. For the assays in this application, we used Hoechst nucleic acid stain to identify cell nuclei. However, other fluorescent cell markers may be substituted for this purpose. Fig 1. Online cell counting. The Image Preview window, displaying object segmentation results (yellow outlines) generated during set up of online cell counting. Segmentation outlines are a useful visual aid to help with parameter optimization. Micronucleus assay Micronucleus induction is a key characteristic of genotoxic compounds. The analysis of micronuclei formation resulting from DNA strand breakage (clastogens) or interference with chromosome segregation (aneugens) is an important component of toxicology screening of new drug candidates. Guidelines for genotoxicity testing using in vitro micronucleus assays typically recommend scoring at least 2000 cells per treatment condition for single samples, or at least 1000 cells per condition if the assay employs replicates. Online cell counting ensures that the minimum cell count is reliably achieved even when test compound toxicity results in a cell count decrease. For the examples presented here, mononucleated micronucleus assays (1,4) are configured for automated high-content analysis in 96-well format with multiple replicates per treatment condition. Neurite outgrowth assay Neurite outgrowth plays a fundamental role in embryonic development, neuronal differentiation, and nervous system function. The process is also critical in some neuropathological disorders as well as neuronal injury and regeneration. Highcontent analysis allows direct screening of the morphological effects of various treatments and can be multiplexed with additional structural and biochemical probes to increase information content. For accurate neurite measurements, cell counts of 300 or more are typically required. A confounding factor is that the differentiated neuronal phenotype is characterized not only by neurite outgrowth, but also by lack of cell proliferation. In addition, various differentiation conditions result in cell detachment and death, particularly at higher concentrations. Online cell counting minimizes the number of fields per well required to reach the desired cell count and ensures that, even at toxic doses, cells are sufficiently sampled to ensure accurate and robust data are obtained.

2 Materials Products used IN Cell Analyzer 2000, standard chip CCD camera IN Cell Analyzer 2000, large chip CCD camera IN Cell Investigator, single seat license well Matriplate (0.72 mm glass bottom thickness) G1S Cell Cycle Phase Marker Assay, Screening Mouse IgG Cy5 -Linked (from goat), 1 mg PA45002 Other materials used µclear plates, 96-well tissue culture treated, black Greiner Bio-One, CHO-K1 cells (Hamster Chinese Ovary epithelial) ECACC, Neuroblastoma neuro-2a cells ATCC, CCL-131 McCoys 5A media Sigma, M8403 Nutrient Mixture F12 HAM Sigma, N4888 Eagle s Minimum Essential Medium (EMEM) ATCC, Fetal Bovine Serum Gold PAA, A Penicillin-streptomycin, 100 Sigma, P4333 L-glutamine, 200 mm solution Sigma, G7513 Mitomycin C *, 2 mg Sigma, M4287 Etoposide *, 25 mg Sigma, E1383 FITC, 10 mg Invitrogen, F1906 Hoechst (16.2 mm stock) Invitrogen, H3570 Ethanol 100% Hayman chemicals PBS Sigma, D8537 DMSO Sigma, D2650 Sterile water Fresenius Kabi, Retinoic acid Sigma, R2625 Geneticin Sigma G8168 Triton X-100 Sigma, T8787 Monoclonal anti-α-tubulin antibody, clone DM1A Sigma, T9026 * Mitomycin C and etoposide are classified as toxic. Handle in accordance with MSDS and local laboratory safety guidelines. Retinoic acid and Triton X-100 are classified as harmful. Handle in accordance with MSDS and local laboratory safety guidelines. Methods Unless indicated otherwise, media formulations for the cell lines were as recommended by the supplier. Variable cell count assay Two cell lines were used to assess performance of the online cell counting function in cases of variable cell count: CHO-K1, a Chinese hamster ovary-derived cell line lacking the gene for proline synthesis; and G1S Cell Cycle Phase Marker, derived from the U2-OS human osteosarcoma cell line and engineered to express an EGFP-tagged cell cycle phase reporter. Cells were seeded onto 96-well µclear plates at 20, 15, 10, 5, 2.5, and cells/well (n = 16 wells of each dilution). Plates were incubated overnight under standard tissue culture conditions and then fixed using 2% formaldehyde. Cells were then stained with Hoechst and imaged on IN Cell Analyzer 2000 configured with the standard chip CCD camera and a 20 /0.45 NA objective. Micronucleus assay CHO-K1 cells seeded onto 96 well Matriplate microplates were incubated with mitomycin C (clastogen) or etoposide (aneugen) to induce micronuclei formation for 48 h, fixed at room temperature for 30 min with ethanol, and stained with FITC and Hoechst (1). With the online cell count threshold set to 1000 cells/well, plates were imaged on IN Cell Analyzer 2000 with the 20 /0.45 NA objective. Neurite outgrowth assay Neuro-2a murine neuroblastoma-derived cells were seeded onto a 96-well µclear plate in media containing 2% FBS, and incubated for 6 h. Retinoic acid at concentrations ranging from 5 to 50 µm were then added to the cells and the plate incubated for 18 h at 37ºC/5% CO 2 in a humidified incubator. The cells were fixed with 4% formaldehyde for 2 h and then permeabilized with Triton X-100 detergent in PBS. The cells were then incubated with monoclonal anti-α-tubulin antibody to identify cell bodies and neurites, followed by a Cy5-conjugated mouse anti-igg secondary antibody. Nuclei were then stained with Hoechst (2). With the online cell count threshold set to 300 cells/ well, plates were imaged on an IN Cell Analyzer 2000 configured with the large chip CCD camera, which has a field of view 4 that of the standard chip CCD camera. Analysis and data processing To assess performance of the online cell counting feature in variable cell count assays, results were benchmarked against those obtained using an offline analysis protocol developed using the IN Cell Investigator Multi-Target Analysis module as described in the product user manual. Cell count data and the number of fields per well obtained with IN Cell Analyzer 2000 acquisition were retrieved from the IN Cell Analyzer session log and processed using Microsoft Excel. 2 12/ AA

3 For micronuclei formation assay analysis, the IN Cell Investigator Micronuclei Analysis Module was used as described in the product user manual. Proliferation index was calculated (Fig 4). To obtain cell count for calculation of the proliferation index in assays employing the online cell count feature, total cell count per well was divided by the number of fields acquired per well. For neurite outgrowth assays, IN Cell Developer Toolbox was used to create an analysis protocol to analyze cells and associated neurites. The analysis routine was designed to identify neurites by subtracting a binary image of cell bodies (derived by eroding a whole-cell binary image to exclude neurites) from a binary image of the entire cell (including neurites). In conjunction, information from the nuclear channel was used to derive individual cell data. Details of the analysis protocol can be found in a separate application note (3). For assays employing online cell counting, mean cell count data was derived by dividing the total cell count per well by the number of fields acquired in the well. Note: The online cell counting feature is easily implemented during set up of an imaging run. Within Protocol Designer, select the cell counting function and then specify the wavelength to be used for counting, the minimum nuclear area parameter used to optimize object identification, and the cell count threshold. During set up, the object identification (segmentation) results and cell count are displayed to help with assessment and optimization of the settings (Fig 1). Results Assays with variable cell count Various cell culture conditions and treatments can result in decreases in cell number within sample wells. In many cases, the total cell number following treatment is unpredictable, which can present a challenge to ensuring data are captured from a statistically significant population of cells in each case. Typically, this problem is addressed by acquiring an excess number of fields of view from all sample wells in order to accommodate the worst-case conditions. By contrast, the IN Cell Analyzer 2000 online cell counting feature automatically acquires the minimum number of fields required to achieve a user-set count threshold. To investigate the utility of the online cell counting feature in rendering variable cell counts, two cell lines were seeded at a range of densities across separate sample plates. Online cell counting was then applied, with the cell count threshold set to 500 for a hamster (CHO-derived) cell line and to 300 for a slowergrowing human (U2-OS-derived) cell line. As shown in Figure 2, the number of cells acquired was consistently above the set threshold for all seeding densities and the number of fields required to achieve the threshold decreased with increasing cell density. The online cell counting feature thus saved time and storage space for the imaging run by acquiring only the minimum number of images required to capture data from a statistically acceptable number of cells for each well. (a) (b) Fig 2. Online cell counting to achieve sufficient cell count with a minimum number of fields. Cell count and number of fields acquired for (a) CHO-derived and (b) U2-OS-derived cell lines seeded at increasing densities across the plate. Cells were imaged using the standard chip CCD camera with the 20 /0.45 NA objective. Points and error bars represent the mean +/- 1 standard deviation for 16 replicate wells. Micronucleus assays For micronucleus assays configured with multiple replicates per treatment condition, a minimum cell count of 1000 cells/well is recommended. Without online cell counting, 34 fields of view needed to be acquired from each well to ensure a sufficient cell count was achieved (based on the maximum field count obtained when online cell counting was applied). This resulted in a plate acquisition time of 80 min with the standard chip camera, compared to an acquisition time of 37 min when online cell counting was applied under comparable conditions. As summarized in Table 1, the use of online cell counting significantly decreased plate acquisition times for the assay. To maximize acquisition rate for micronuclei formation assays, the large chip CCD camera is preferable to the standard chip size. With a pixel array, the large chip camera acquires a field of view approximately four times that of the standard chip camera (Fig 3). Consequently, fewer fields of view are required to obtain the desired cell count. In addition, capture rate with the large chip camera configuration is significantly more rapid than with the standard chip camera in place. Both of these factors contribute to increased speed of acquisition. For dose-response assays with etoposide and mitomycin C as test compounds, the online cell count threshold was set to The number of fields imaged per well to achieve the threshold ranged from 1 to 34 using the standard chip CCD camera and 1 to 16 using the large chip CCD camera. Use of the large chip camera reduced plate acquisition times by ~50% compared to those achieved with the standard chip camera under comparable conditions (Table 1). 12/ AA 3

4 Table 1. Plate acquisition times achieved for 96-well micronuclei formation dose-response assays Run Camera chip Test compound Online cell count threshold Objective Exposure(s) Number of fields required Plate acquisition time* (min) 1 Standard Etoposide Feature not applied Large Mitomycin C Feature not applied Standard Etoposide Variable 37 4 Large Etoposide Variable 18 5 Standard Mitomycin C Variable 69 6 Large Mitomycin C Variable 30 * Acquisition rates required to ensure 1000 cells/well without (Runs 1 and 2) or with (Runs 3 to 6) online cell counting. (c) For dose-response assays, percentage maximum cell count and percentage of cells with micronuclei were plotted against drug concentration (Fig 4). As indicated in the plots, micronuclei count increases with drug treatment until toxic doses are reached and cells begin to detach from the plate. Percentage maximum cell count relative to untreated controls can be used as a crude index of cell proliferation (PI), which typically decreases with increasing exposure to genotoxins. Drug concentration at half maximal proliferation (PI 50 ) was determined to be 127 nm for mitomycin C and 176 nm for etoposide (Table 2). These values are within the 95% confidence intervals of values obtained with the standard chip camera, and correspond well with those reported in the literature (198 and 216 nm respectively) during validation of an automated micronucleus screening assay using IN Cell Analyzer 1000 (4). The percentage of cells presenting with micronuclei at PI 50 was also determined for each assay. Table 2 shows that values obtained with the standard and large chip cameras were comparable to each other as well as to the values reported by Ovechkina et al (4). (a) (a) (b) Fig 3. Micronuclei formation assay. Following treatment of CHO-K1 cells with 250 µm etoposide, and staining with Hoechst 33342, cells were imaged with (a) the large chip CCD camera or (b) the standard chip CCD camera. Relative size of images from the two cameras is as shown. (c) Enlargement of the region of interest outlined in white in (a). Arrow: micronucleus formed at the periphery of a nucleus. Cell count for the standard chip camera image is 70 for field 1, compared with a cell count of 386 for field 1 for the large chip camera. (b) Fig 4. Dose-response micronuclei formation assays. CHO K1 cells were treated with increasing doses of (a) etoposide, or (b) mitomycin C, and imaged on IN Cell Analyzer 2000 using the large chip camera. Data points represent mean +/- 1 SEM, n = 8 wells per concentration. Percentage maximum cell count was calculated as [100 (mean field cell count of treated sample)/(mean field cell count of untreated control sample)]. 4 12/ AA

5 Table 2. Dose-response micronuclei formation assays imaged with the large and standard chip cameras Mitomycin C Etoposide PI 50 * (nm) PI 50 95% CI % cells with micronuclei at PI 50 PI 50 (nm) PI 50 95% CI % cells with micronuclei at PI 50 Standard chip camera to to Large chip camera to to Reported Value * PI 50 = drug concentration at 50% maximum cell proliferation. CI = Confidence interval. PI 50 is taken to be analogous to published GI 50 values, where the growth index (GI) is calculated as a ratio of the change in cell count for treated and untreated sample populations during the treatment time period (4). Neurite outgrowth assays Retinoic acid treatment induces Neuro-2a cell differentiation to a neuronal phenotype (Fig 5), which is characterized by formation of neurites and lack of cell proliferation. At higher drug concentrations, cell detachment and death can also occur. Consequently, to ensure robust assay results, the use of online cell counting to achieve counts exceeding 300 per well is recommended. Since neurites can extend up to tens or even hundreds of microns in length, use of the large chip camera configuration ensures the most accurate neurite segmentation results. As shown in Figure 5, many more neurites can be captured in their entirety with the large chip camera, compared to the standard chip camera. Alternatively, if the assay is run with the standard chip camera, image stitching can be performed post-acquisition using IN Cell Investigator software. (a) (b) Fig 5. Neurite outgrowth in populations of differentiated neuroblastoma cells. Serum-starved neuro-2a cells were treated for 18 h with retinoic acid, stained, and imaged with (a) the large chip camera, or (b) the standard chip camera. Images shown were acquired in the green channel (tubulin staining) with the 10 /0.45 NA objective. Cells were co-stained with Hoechst to identify nuclei (blue channel image not shown). 12/ AA 5

6 Following treatment of serum-starved cells with increasing doses of retinoic acid for 18 h, samples were imaged with the online cell count threshold set to 300. Cell count per field and number of fields acquired per well were plotted against retinoic acid concentration. As shown in Figure 6, cell count decreases with increasing retinoic acid concentration. This is consistent with decreased cell proliferation associated with differentiation and indicative of toxic effects occuring at higher doses. The data also indicate an inverse relationship between field count and drug concentration, demonstrating that the online cell counting feature minimizes the number of required fields needed to obtain the desired cell count. The effect of online cell counting on dose-response assay performance was examined by comparing the mean per field cell counts obtained with online cell counting to the cell counts obtained from a single field of view per well. In each case, four replicate wells were imaged per treatment condition. As shown in Figure 7, a clear retinoic acid-dependent decrease in cell number is observed when online cell counting is applied. By contrast, the dose-response relationship is much less apparent when data are acquired from a single field of view per replicate well. The standard errors of the means are also significantly larger in the absence of online cell counting, demonstrating that cell proliferation data are more robust with online cell counting applied. Fig 6. Effect of retinoic acid treatment on cell count. Cell count per field and number of fields acquired per well are plotted against retinoic acid concentration. Plates were imaged with the large chip camera. The minimum cell count threshold was set to 300 cells/well with a maximum field limit set to 9. Data points represent the mean +/- 1 SD, n = 4 wells per treatment condition. The data in Table 3 demonstrate the significant time savings achieved by applying online cell counting for the 10-point (40 well) dose-response assay. The read-time required to ensure capture of at least 300 cells per well was reduced from 17 min without online cell counting to 7 min with online cell counting applied. Fig 7. Comparison of cell count data with and without online cell counting. Cell count was obtained by dividing the total cell count per well by the number of fields acquired in the well. Data points represent the mean +/- 1 SEM, n = 4 wells per concentration of retinoic acid. Table 3. Reduction in assay read-time using online cell counting Camera chip Objective Hoechst channel exposure(s) Cy5 channel exposure(s) Online cell count threshold Number of fields required Acquisition time for 40 wells (min) Large Feature not applied 7 17 Large Variable / AA

7 Similarly, Figure 8 demonstrates the improvement in robustness of neurite length measurements for the assay. The doseresponse relationship between neurite length and retinoic acid concentration is more pronounced when online cell counting is applied, reflecting the fact that data are derived from a sufficiently large cell sample at each dose. Fig 8. Comparison of neurite length data with and without online cell counting. Data points represent the mean +/- 1 SEM, n = 4 wells per concentration of retinoic acid. Conclusions Acquisition of data from a sufficiently large cell population can be critical to the performance of high-content assays, yet this can result in prohibitively long plate read times in the absence of an online cell counting functionality. The data presented here clearly demonstrate that application of the IN Cell Analyzer 2000 online cell counting feature provides significant time savings during image acquisition, at the same time reducing file size by minimizing the number of required images. This can be a major advantage in screening applications, such as analysis of micronucleus formation, where assays must be both robust and rapid. Use of the large chip camera option enables even faster results, with plate read times reduced by as much as 50%. Measurement accuracy is essential to interpreting data from dose-response and other drug characterization assays. Comparative data obtained from the neurite outgrowth assay demonstrate a clear improvement in the quality of pharmacodynamic data, together with substantial improvements in imaging speed, when online cell counting is applied. References 1. Application Note: Online cell counting in a micronuclei formation assay using the IN Cell Analyzer GE Healthcare, , Edition AA (2009). 2. Application Note: A high-content assay for neurite outgrowth using the IN Cell Analyzer GE Healthcare, , Edition AA (2009). 3. Application note: Neurite outgrowth cell-by-cell analysis using the IN Cell Developer Toolbox, GE Healthcare, , Edition AA (2005). 4. Ovechkina Y et al.; Development and validation of automated in vitro mammalian micronucleus screening assay using IN Cell Analyzer 1000, poster presented at SBS 12 th Annual Conference and Exhibition (2006). 12/ AA 7

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