Comparison of Trypan Blue and Fluorescence-Based Viability Detection Methods Via Morphological Observation

Comparison of Trypan Blue and Fluorescence-Based Viability Detection Methods Via Morphological Observation Nexcelom Bioscience LLC. 360 Merrimack Street, Building 9 Lawrence, MA 01843 T: 978.327.5340 F: 978.327.5341 E: info@nexcelom.com www.nexcelom.com 1001314 Rev. A

Morphological Analyses Comparing Trypan Blue and AOPI Viability Staining Methods Using Cellometer Image Cytometers Introduction All cell-based biological experiments, from standard cell culture to primary cells for evaluating pharmacological agents, require accurate determination of cell viability. The Trypan Blue (TB) exclusion assay is one of the oldest and most common methods by which to assess cell viability. (Altman et al. 1993; Louis and Siegel 2011). TB is cell membrane impermeable. Consequently, it enters cells only in the event of compromised membranes. Once inside a membrane compromised cell, TB turns the cells a blue color after it binds to intracellular proteins. The live cells within a population remain unstained. Although TB staining has long been the default method to evaluate cell viability, the method has some substantial shortcomings. Because TB itself is toxic, a short window of time exists between cell staining and counting (Tsaousis et al. 2012). Additionally, TB is prone to non-specific binding to cellular artifacts, particularly in clinical and primary cell samples, and, as of yet, there is no standardization of TB concentration to analyze cell viability. Lastly, TB staining requires manual counting under bright field illumination with a hemacytometer, a process which is laborious and introduces user-dependent errors. Fluorescent-based dyes now provide an alternative to the traditional TB method. Fluorescent viability dyes including DAPI, Hoechst 33342, ethidium bromide, propidium iodide (PI), SYTOX orange and red, acridine orange (AO), SYTO9/13, DRAQ5/7, calcein AM, and CFDA have all been used to determine viability measurements in flow or image-based cytometers (Wallen et al. 1980; Al-Rubeai et al. 1997; Foglieni et al. 2001; Chan et al. 2012). The AO and PI dual staining method is regularly implemented to assess viability of nucleated cells (Wallen et al. 1980; Darzynkiewicz et al. 1992; Mascotti et al. 2000; Foglieni et al. 2001; Ling et al. 2003; Solomon et al. 2010; Chan et al. 2012, 2013). AO can enter cell membranes, where it binds to DNA and RNA in live cells. PI is membrane impermeable and binds to DNA and RNA only when cell membranes are compromised in dying, dead, and necrotic cells. Cell viability within a given population is then determined by calculating the ratio of live cells to dead cells cells (Wallen et al. 1980). The past 20 years have seen many publications comparing TB exclusion and fluorescence-based cellular viability stains (Black and Berenbaum 1964; Jones and Senft 1985; Altman et al. 1993; Mascotti et al. 2000). 2

These studies reveal that over a time course analysis in standard cell culture, TB exclusion reports more viability in comparison to the fluorescence-based tools, although the studies did not speculate as to the reasoning behind the differences noted (Jones and Senft 1985; Mascotti et al. 2000). In this work, we perform a head-to-head comparison between cell viability as determined by TB and that determined by AO/PI using an automated imagebased cytometer, the Cellometer. Image-based cytometry allowed us to examine the morphological changes that occur in TB-stained cells, and these may explain the differences in viability counts reached by the two methods. Materials and Methods Preparation of Jurkat cells Jurkat cells were cultured in RPMI-1640 medium at 37ºC and 5% CO 2. For an analysis of naturally-dying cells, 5mL of cells (~4x10 6 cells/ml) were removed from the incubator and placed into a bench-top drawer. The sample remained at room temperature for the duration of the experiment. A small aliquot of these cells was taken and tested at the following time points: 0, 6, 12, 24, 48, 72, 96, and 168 hours. A similar experiment was run in parallel to analyze the impact of different TB concentrations on Jurkat cell viability, which was measured at time points 0, 3, 6, 9, 12, 27, and 33 hours. For the heat-killed viability comparison, 5mL of cells were placed into a tube and dropped into a boiling water bath for 15 minutes. After heat-killing, five samples were prepared at theoretical viabilities of 0, 25, 50, 75, and 100% by mixing the heat-killed with fresh Jurkat cells. Time course analysis of naturally-killed Jurkat cells Four detection methods were used to assess the naturally-dying cells: (1, 2) measuring viability with PI or AO/PI and counting with Cellometer Vision; (3) staining with 0.4% TB and counting with Cellometer Auto T4; (4) staining with 0.4% TB and manually counting with a hemacytometer. Samples of the naturally-dying cells at 0, 6, 12, 24, 48, 72, 96, and 168 hours were mixed with PI, AO/PI, or 0.4% TB and analyzed accordingly. Viability and concentration results were measured in quadruplicate for all time points. Time course analysis of naturally-killed fresh bulk murine splenocytes A lysing protocol was used to lyse the red blood cells in the splenocyte sample. Splenocyte viability was assessed at 0, 3, and 50 hours by staining with 0.4% TB, PI, or AO/PI to compare the various methods in these primary cells. TB-stained samples were measured manually by hemacytometer, while the AO/PI, and PI-stained samples were analyzed with Cellometer Vision. Again, all time point samples were assessed in quadruplicate. 3

Assessing impact of trypan blue concentration on viability assessment To measure the impact of TB concentration of viability of naturally-killed Jurkat cells, two methods were used: (1) AO/PI staining followed by analysis with Cellometer Vision; (2) staining with various concentrations of TB and manually counting with a hemacytometer. Samples at each time point (0, 3, 6, 9, 12, 27, and 33 hours) were stained by AO/PI or by 0.4, 0.2, 0.1, 0.05, 0.025, and 0.0125% TB. All samples were analyzed in quadruplicate. Image cytometry protocol Immediately after staining, Jurkat cells were pipetted into a Nexcelom disposable counting chamber. AO was detected by optics module VB-535-402 (pseudo-color green) and PI by VB-660-502 (pseudo-color red). A color camera on the Cellometer Auto T4 was used to detect TB staining. In the case of TB-stained cells, live cells with bright centers and dark, blue-stained cells were counted. For PI analysis, total cells were determined in the bright field channel and dead cells in the fluorescent channel were counted. For AO/PI, AO-stained live cells (green) and PI-stained dead cells (orange) were counted. The viabilities were then calculated for each sample. Manual counting with the hemactyometer TB-stained Jurkat cells were pipetted into a Neubauer hemacytomter. Live and dead cells were counted under bright field from both heat-killed and naturally-dying Jurkat cells. Samples with approximately 50% viability were used for Figures 7 and 8. Phase contrast microscopy Jurkat cells stained with 0.4 and 0.1% TB were imaged under bright field using a digital camera. Both bright field and phase contrast images were captured to detect dimly diffused Jurkat cells. Results Time course analysis of naturally-killed Jurkat cells Figure 1A reports TB, PI, and AO/PI stained cells in the naturally-killed samples (0-168 hours) The bright field images report gradual morphological changes in the cell membranes. At 0-12 hours, the outer membranes were dark and quite defined. By 168 hours, cells were now grayish and undefined (green arrows in Figure 1b). TB-stained Jurkat cells showed similar morphological changes, from clearly defined to amorphous. Tight, dark cells became dim and diffuse shapes (red arrows Figure 4

1b). The number of TB-stained large dim cells rose over time, while the morphological characteristics of AO or PI-stained cells remained constant. All stained dead cells (PI, AO/PI, and TB) increased over time. In the PI-stained samples, the later time points (96 and 168 hours) also showed less clearly defined cells under bright field, which may hamper the ability of obtaining accurate cell viability with PI (Figure 1a). AO/PI was the optimal method for measuring cell viability as the labeling of both live and dead cells eliminated the chance of counting membrane-poor cells, those late apoptotic and necrotic cells, as well as eliminating the counting of cellular debris under bright field. Figure 1a and b. Bright field and fluorescent images of PI, AO/PI, and TB-stained naturally-killed Jurkat cells. (a) Time points post incubation at room temperature (0-168 hours). (b) Higher magnification of time course images illustrating dim, diffused shapes (arrows). 5

Figure 2 compares the image cytometry and hemacytometer measurements. Clear differences between the fluorescence-based and TB assays were seen (2a). AO/PI and PI reported sharp declines in Jurkat viability at 12 hours. A 2-sample T-test at 12 hours comparing AO/PI to PI and AO/PI to TB showed that AO/PI was comparable to PI staining (p>0.05) but significantly different than TB counting (p<0.05). Even though AO/PI reported 70% viability, the TB method reported a measurement of 82.8% viability. These data confirm earlier studies which report that TB-stained cell samples lower than 80% typically overestimate cell viability (Mascotti et al. 2000). The fluorescence-based methods reported consistent total cell concentrations over the duration of the experiment, but the TB method showed a gradual decrease in cell concentration (Figure 2b) Figure 2c, d shows a plotting of measured live cell concentration (c) and measured dead cell population (d). All methods reported similar concentration measurements 6

over time for the live cells (c). The dead cell concentrations varied significantly, however. By the end of the time course, both the manual and TB-derived concentrations were greater than two times lower than the fluorescence-based detection methods. The initial differences in dead cell count by TB began at 12 hours which coincides with the time when AO/PI-measured cell viability decreased to ~70%. These data suggest that as viability declines, TB undercounts the number of dead cells, producing an inflated viability measurement. Figure 2a-d. Time course analysis (0-168 hours) of viability (a), total cell concentration (b), live cell count (c), and dead cell count (d) for TB, PI, and AO/PIstained, naturally-killed Jurkat cells. 7

Time course analysis of naturally-killed fresh bulk murine splenocytes Viability data in splenocytes were similar to those reported for Jurkat cells Figure 3 shows the AO/PI and PI viability data gradually decreasing from ~80% at time point 0 to ~65% at 50 hours post incubation. TB-stained samples at 0.4 and 0.1% concentrations showed a decrease in viability of only ~5%. Again, a 2-sample T-test revealed that there was a significantly difference in the viability between AO/PI and TB (p<0.05), whereas AO/PI was not significantly different than PI (p>0.05). Figure 3. Time course analysis (0, 33, 50 hours) of viability for TB, PI, and AO/PIstained primary murine splenocytes. Assessing impact of trypan blue concentration on viability assessment Figure 4 shows the images of cells stained with 0.4, 0.1, and 0.025% TB as well a those stained with AO/PI. High concentrations of TB (0.4%) stained more cells but also produced more large, dimly diffused shapes (red arrows). Lower TB concentrations (0.1 and 0.05%) stained fewer cells but those that were stained were tighter, dark shapes, unlike the ones seen at the higher TB concentrations, especially at 12 hours and beyond. AO/PI staining was consistent with previous results, reporting an increase in PIpositive cells over the time course. 8

Figure 4. Image from the time course analysis (0-33 hours) of varying concentrations of TB in naturally-killed Jurkat cells. Figure 5a shows that the viability results produced a trend similar to that scene in the time-course assay. Again, viabilities from each TB concentration were higher than from those derived from the AO/PI cells. Because this experiment had a lower initial viability (~80%), the differences were immediately noticeable with the TB viability counts always higher than the AO/PI counts. Again, a 2-sample T-test report that AO/PI viability counts were significantly different than all the TB concentrations (p<0.05). The measured concentration of dead cells for each parameter was significantly different (p<0.05) for AO/PI against all TB concentrations (Figure 5b, c), the largest difference occurring between AO/PI and 0.025% TB, likely due to the low concentration of TB. Even at higher concentrations of TB, lower than expected number of dead cells are reported, which confirms our previous findings that TB routinely overestimates viability and demonstrates that this phenomenon occurs at every TB concentration tested here. 9

Figure 5a-c. Time course analysis (0-33 hours) of concentration and viability with different concentrations of TB (0.4-0.025%). Viability is shown in a, live cell count in b, and dead cell count in c. Heat-killed viability comparison This experiment aimed to demonstrate that morphological differences between cells killed by heat and cells killed naturally impact how those cells are counted. Figure 6 shows clear morphological differences between heat-killed and non-heatkilled cells. Heat-killed cells did not undergo natural death by apoptosis or necrosis and so the cells are consistent in shape, color, circularity, and TB-staining pattern. The cells are tight and dark blue in color, and the viability counts of these cells between TB and PI were highly correlated (Figure 7). PI was used with these cells as heat-killed cells generate little debris. The non-heat-killed cells, however, did undergo apoptosis and necrosis. Therefore, they demonstrated a non-uniform morphology and TB-staining pattern. These cells did generate significant amounts of cellular debris and so AO/PI was required to accurately determine the viability without interference by the debris (Chan et al. 2013). 10

Figure 6. Bright field and fluorescent images of TB and PI-stained heat-killed Jurkat cells at various theoretical viability percentages (0-100%). 11

Figure 7. Comparison of viability measurements between manual, Cellometer Auto T4 with TB, and automated PI analysis of heat-killed Jurkat cells. The y-axis shows experimentally-derived viability percentages, while the x-axis indicates the 0-100% theoretical viability mixtures. Phase contrast microscopy Figure 8 shows the bright field and phase contrast images of TB-stained Jurkat cells. At a concentration of 0.4% TB, Jurkat cells were observed and identified as a dim, diffuse dead cell in the bright field image but was too dim to be detected in the PC image (red arrow). At 0.1% TB, dark cellular morphology in the bright field image was also detected in the PC image. These results underscore the importance of choosing appropriate TB dye concentrations and detection methods. 12

Figure 8. Phase contrast and bright field images at 0.4% and 0.1% TB. Red arrows indicate dim, diffused cell in TB-stained image that is not also seen under phase contrast. Green arrows indicate dark, dead cell seen in TB image that was also seen under phase contrast. Results/Discussion The aim of this study was to ascertain the variations in viability measurements between the TB exclusion assay and fluorescence-based viability labels. We uncovered two main reasons for variations in cellular morphology that contribute to variations in viability analysis: the concentration of TB used and the manner by which the cells died. Morphological differences occurred in cells stained with TB at different viability ranges. This is not surprising as naturally-killed Jurkat cells undergo extreme shape changes during cell death. High viability samples showed cells with uniform shape characteristics, suggesting that cell membranes remained whole enough to retain the TB dye. Low viability samples showed large, dim, non-uniform cells, suggesting a loss of membrane integrity. 13

Furthermore, we noted that dim, diffuse shapes can vary greatly in brightness. This may complicate analysis when using a hemacytometer as TB staining may yield higher viability counts because of unintended exclusion of dead cells. The difference between the staining methods reached as high as 30%, confirming the findings of other studies (Mascotti et al. 2000). The overestimation of viability is also observed in primary murine bulk splenocytes. Between the AO/PI, PI, and TB methods there were significant differences (p 0.05), which further underlines the overestimation seen in TB manual counting, particularly when cultured or primary cell samples are at or below 70% viability. High concentrations of TB ( 0.4%) produced large, dim circles (Figure 9) that we termed balloons. These balloons can be seen under a light microscope and the Cellometer. The balloon cells are comprised of different sizes and brightness, with some more diffuse than others. Balloons formed within the first 30 seconds of staining at the high TB concentration. More balloons formed in the next 60 seconds, although at a slower rate. At low TB concentrations (0.025%), no balloon-like cells were seen, although this dye concentration may be too low to accurately stain all dead cells in the sample. The concentrations within each population are shown in Figure 10. At 33 hours, there were significantly more diffused balloon cells at 0.4 and 0.1% concentrations of TB (p 0.05). At 0.025% TB, there was a reversal in the number of counted balloons versus the number of counted dead cells (p 0.05), as well as a lower number of total counted cells, which we attribute to the low dye concentration. From these results, we conclude that at high TB concentrations, there is a morphological effect on the membranes of compromised dead cells, thereby producing the balloon-like cells. Lower concentrations of TB did not show the same morphological anomalies. The balloon structures are difficult to see and count, prompting an overestimation of viability. Other reasons for the differences between TB and fluorescence-based viability measurements may include: o Differences in the molecular sizes of the dyes which impacts how quickly the dyes enter the cells; o The fact that TB is a cytoplasmic dye and so when membranes degrade, the dye may be more easily lost, resulting in fewer dead cells being counted. As PI binds to nucleic acids, it is more readily retained regardless of membrane integrity which is why it s the dye of choice for late apoptotic and necrotic cell studies (Denecker et al. 2000; Yedjou et al. 2012). 14

Image cytometry allowed for the visualization of the morphological differences seen in high and low viability samples and in response to various concentrations of TB stain. Future studies will examine the impact of TB incubation time on cellular morphology, as well as a video analysis to show a time lapse of the morphological changes induced by TB Figure 9. Image cytometry analysis of morphological changes in TB concentration series. White arrows illustrate dead cells that have expanded to become dim, diffuse shapes. Black arrows illustrate dead cells that remain the dark and tight morphology. Figure 10a-d. Time course analysis (0-33 hours) of varying TB concentrations (0.4% a, 0.1% b, 0.025% c) quantifying the large, dim balloon-like Jurkat cells and the dark, tight Jurkat cells. Cell counts of balloon-like cells and dark, tight cells at 33 hours post incubation at the various concentrations of TB (d). 15

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