We compared counts obtained through several cell counting procedures. First, we automatically counted cells in identical pinhole illuminated images using ITCN and CellC cell counting software and compared those results with automated counts of fluorescence images. We also compared the results with manual cell counts (Figure 1I). Average counts for all methods diverged by less than 5%. Cells counted from fluorescence microscopy matched the manual count most closely (3% variation at 50,000 cells per well), whereas pinhole illumination resulted in a somewhat higher standard deviation (7%–8%). This is likely due to the presence of highly elongated cells that lowered contrast in pinhole images. In these images, diminished contrast sometimes prevented correct cell identification or led to double-counting of cells. Analysis of cells plated at a widely divergent densities (50,000–500,000 per well) confirmed that pinhole-based counts and counts generated from fluorescence images were highly correlated (R2 > 0.98) (Figure 1J); likewise these counts on average differed by less than 5%.Brief cell swelling in PBS improves contrast and counting accuracy
We found that variability of cell counts from pinhole illumination images could be reduced by briefly removing growth media from the wells and replacing it with 1× PBS. Cells incubated in PBS for 15 min experienced overall swelling of the cell body, resulting in increased contrast during pinhole imaging (Figure 2A, B). After imaging, growth media was returned to the cell cultures. Re-counting cells after 24 h did not reveal any differences in cell number between PBS-treated and untreated cells; that is, the PBS treatment did not affect SH-EP cell viability. The increased contrast of PBS-treated cells resulted in substantially more accurate cell detection by the ITCN ImageJ plugin, decreasing the average standard deviation of cell counts from 10% in untreated cells to 5% after PBS treatment when benchmarked against fluorescence-based counting (Figure 2C).Counting of freshly seeded cells
Often it is desirable to control for varied cell densities when cells are grown under different conditions (e.g., siRNA treatment) and re-seeded onto a new culture plate. When cells are round and have not fully spread out, they should be particularly good targets for pinhole illumination cell counting. To test the accuracy of the method under these conditions, we plated cells at different densities (50,000–500,000 per well). Freshly seeded cells were permitted to settle for three hours. Fluorescence and pinhole images from three independent wells were taken for each density (Figure 3A, B). Cells were imaged in their original growth media. Counts from fluorescence and pinhole images show a strong correlation (R2 > 0.98) (Figure 3C). Cell counts from pinhole images are almost identical to those from nucleus fluorescence (95 ± 6%, Figure 3D). Cells were slightly undercounted in pinhole illuminated images at higher densities, likely due to clumping of cells under these conditions.Counting of dense cell layers
To test the limitations of pinhole illumination counting of dense-to-overgrown cell layers, cells from the prior experiment were allowed to grow for an additional 24–48 h. This resulted in overgrown cell cultures where cells started to form a second overlapping layer. Overgrowth was a challenge for this method of automated cell counting since it was not possible to get all cells simultaneously into focus. Fluorescence and pinhole images were taken with and without treating the cells with PBS for 15 min. Cell counts were normalized against fluorescence imaging (Figure 4). Under these conditions, cell counts from pinhole images with and without PBS treatment were virtually identical to those obtained by fluorescence imaging, 101 ± 7% and 97 ± 2%, respectively. PBS treatment of cells substantially decreased the counting errors observed previously with lower cell densities.
Generally, brightfield microscopy can visualize differences in opacity (amplitude objects) while failing to resolve transparent objects that differ only in refractive index (phase objects), which are better viewed using phase contrast microscopy (13). However, phase objects can be made visible in brightfield microscopy by defocusing the microscope (14). Defocusing translates phase differences into intensity differences in microscopic imaging (15). However, phase information deteriorates with decreasing spatial coherence of the light source (16). The combination of pinhole and monochromatic filter produces a quasi-coherent wave front, thereby strongly improving phase contrast in defocused images. Our results show that pinhole illumination combined with defocused image acquisition results in bright-field images with high contrast. This can be conceptualized as each cell body acting as a miniature lens to produce a bright, central spot below the cell layer. Such spots can easily be identified through threshold analysis and used for cell counting.