A green Kodak Wratten filter #58 (Edmund Optics, Barrington, NJ) and a 130 µm pinhole were affixed to a stabilizing cardboard frame. These were placed directly on the cell culture plate and positioned to achieve an even illumination of the viewing field (Figure 1A, B).
The image was then defocused by lowering the objective until image contrast was maximal. Best results were achieved by lowering the focus by 50–200 µm, corresponding to 0.5–2 turns of the fine z-focus drive. An image was then taken using an 80 ms exposure. Exposure times for fluorescence and pinhole images were kept constant throughout the measurements.
The pinhole aperture was formed by punching a hole into heavy-duty (0.9 mil) aluminum foil with the point of a fine needle. The size of the pinhole was determined to be 130 ± 10 µm by placing the aperture on the bed of an optical scanner (MFC 7460, Brother, Bridgewater, NJ) and scanning the pinhole at 9600 dpi (n = 4).Cell counting
Cells were counted using the ITCN (Image-based tool for counting nuclei) Plugin for ImageJ developed by Thomas Kuo andJiyun Byun at the Center for Bio-image Informatics at UC Santa Barbara (11). Its algorithm assumes nuclei to be blob-like structures with roughly convex local intensity distributions whose iso-level contour is approximately ellipsoidal; nuclei are fitted by an inverted Laplacian of Gaussian filter (11). The plugin can be downloaded without charge from www.bioimage.ucsb.edu/automatic-nuclei-counter-plug-in-for-imagej. Images were converted to eight-bit greyscale and inverted before using ITCN. Cell detection was performed by detecting dark peaks with the following parameters: cell width = 7, minimum distance = 7, threshold = 2, mask image: use selected ROI.
Alternatively, cells were counted using the CellC image analysis software (available for download at: https://sites.google.com/site/cellcsoftware/), which identifies cells by global thresholding combined with a watershed segmentation algorithm (12). Eight-bit images were loaded into the CellC software. The Automatic Intensity Threshold was adjusted to between 0.4 and 0.5. The number of cells was evaluated by counting the number of isolated pixel groups that exceeded the intensity threshold. As a reference, cells were also counted manually from brightfield images using the ImageJ cell counter plugin.
Image contrast and brightness have been optimized for publication in panels shown in (Figures 1–3), but all cell counting data were calculated from unprocessed microscopy images.
Results and Discussion Counting of neuroblastoma cells by pinhole illumination and fluorescence microscopy
Bright-field images, particularly those of adherent cells, lack contrast, which makes them ill-suited for automated cell counting algorithms. By placing a tiny pinhole aperture directly between the condenser lamp and experimental surface (Figure 1A, B) and by defocusing the image, bright-field images of very high contrast could be generated since each cell body produced a bright spot in a plane below the cells. We found that contrast could be further increased by placing a monochromatic filter in the beam path (Figure 1C). Image contrast was largely unchanged by altering the z-position of either the condenser or the pinhole assembly (data not shown).
SH-EP cells expressing GFP-tagged nuclear histone H2B (SHEP-GFP) were imaged using identical fields with pinhole illumination, GFP fluorescence, and conventional phase-contrast bright-field microscopy (Figure 1C, D, E). Three different regions in three independent wells were examined and cells were identified from fluorescence images and pinhole illuminated images using the ITCN plugin (Figure 1F, G).
We found that uniform ITCN variable settings (width, minimum distance, and threshold) could be used for all fluorescence images, while threshold values varying between 2 and 4 optimized imaging in the pinhole method. The latter effect resulted from slight differences in the overall brightness of images gathered from different microscope sessions. Width and minimum distance variables were kept constant for all pinhole images. We tested the influence of the z-focus position on counting accuracy by recording a stack of images while lowering the focal plane from −50µm to −700µm (Figure 1H). Cell counts were stable over a wide range of focus positions. While defocusing by ~50 µm produced the highest contrast, focal positions from −100 to −400 µm were more tolerant to variations in thickness of the cell culture plates and produced robust counting results (Figure 1H).