- Apply the preset ROI (step 4) to the filtered stack by selecting
it from the ROI manager. The ROI should appear in each slice
of the image sequence. - Identify single spots within the ROI by selecting Plugins>
Macros>FindStackMaxima. Find the local maxima in each
slice by selecting Find Maxima and setting the Noise Tolerance
to 10, Output Types to Single Points and Exclude Edge Max-
ima (seeNotes 18and 19 ). - Invert the local maxima stack by selecting Edit>Invert. Select
“Yes” to process all images (seeNote 20). - Repeatsteps 1– 10 for the second fluorescence channel using
the same ROI saved in the ROI manager. - In each processed stack, use a custom MATLAB program to
identify which 2D local maxima are 3D local maxima to remove
overcounted maxima and for 3D colocalization analysis (see
Notes 21and 22 ). Representative fluorescence images and
analysis results are shown in Figs.2 and 3.
Fig. 2Fluorescent images and analysis of engineered RNA transcripts in cells following RBMB delivery and
smFISH. Five hours following microporation of HT1080-d2EGFP-96mer cells with 0.8μM RBMBs, the cells
were then fixed and smFISH was performed. (a) GFP, (b) DAPI, (c) RBMB-reference dye (Alexa 750), (d)
smFISH probes (TMR) and (e) RBMB-reporter dye (CF640R) were acquired. Images (a) and (b) are widefield
fluorescence images. Images (c), (d) and (e) are maximum intensity projection images. (f) A merged image of
(b), (d) and (e). Individual spots in the smFISH and RBMB-reporter channels were identified and used to
calculate the percent colocalization between the two signals using custom a MATLAB program. (g) Example
MATLAB analysis that identifies smFISH (green) and RBMB-reporter (red) signals within the region outlined by
awhite boxin panel (f). Identified colocalization events are enclosed withinblack circles.(h) MATLAB output
overlaid on the source micrograph (Reproduced from [6] with permission from Oxford University Press)
238 Yantao Yang et al.