smiFISH and FISH-quant - a flexible single RNA detection approach with super-resolution capability

Abstract

Single molecule FISH (smFISH) allows studying transcription and RNA localization by imaging individual mRNAs in single cells. We present smiFISH (single molecule inexpensive FISH), an easy to use and flexible RNA visualization and quantification approach that uses unlabelled primary probes and a fluorescently labelled secondary detector oligonucleotide. The gene-specific probes are unlabelled and can therefore be synthesized at low cost, thus allowing to use more probes per mRNA resulting in a substantial increase in detection efficiency. smiFISH is also flexible since differently labelled secondary detector probes can be used with the same primary probes. We demonstrate that this flexibility allows multicolor labelling without the need to synthesize new probe sets. We further demonstrate that the use of a specific acrydite detector oligonucleotide allows smiFISH to be combined with expansion microscopy, enabling the resolution of transcripts in 3D below the diffraction limit on a standard microscope. Lastly, we provide improved, fully automated software tools from probe-design to quantitative analysis of smFISH images. In short, we provide a complete workflow to obtain automatically counts of individual RNA molecules in single cells.

Figure 1.

mRNA detection using smiFISH. (A) Principle of smiFISH. 24 primary probes are pre-hybridized in vitro with the secondary probe via the FLAP sequence. Resulting duplexes are subsequently hybridized in cells. Length (nt: nucleotides) and ΔG_37°C are indicated. Red circles: Cy3 moieties. (B and C) Dual-colour labelling of HIV transcripts with smiFISH-Cy3 and MS2-GFP in HeLa-HIV-MS2-GFP cells and parental HeLa cells (negative control). (B) Red arrows indicate examples of individual mRNA molecules. Blue arrows indicate active transcription site. (C) Percentage of smiFISH spots that co-localized with a MS2 spot. Each dot corresponds to one cell, plotted as a function of the number of smiFISH spots per cell (N = 50 cells). (D) Androgenetic (AK2) and parthenogenetic (PR8) mouse embryonic stem cells mES cells were hybridized with smiFISH probes targeting either Grb10 or Peg3. Red arrows indicate examples of individual mRNA molecules. Number of detected mRNAs are reported for each image. Nuclei manually drawn from DAPI images (not shown) are outlined in blue.

Figure 2.

Comparison of smiFISH and standard smFISH against a GFP-tagged version of ING3. Negative control is a cell line not expressing the tagged ING3. (A) Representative images for smFISH and smiFISH performed with varying numbers of probes. Images were rescaled such that cellular background is comparable. The granular background in the negative control likely stems from non-specifically bound stray probes. Same scale bar for all images. (B) Number of (normalized) detected spots shown as a function of different (normalized) intensity thresholds. The number of detected spots were renormalized such that the actually detected number is 1, in order to compare cells with different numbers of detected mRNAs. The tested intensity thresholds are not listed with their intensity values, but with an increasing index, in order to compare images with different intensity values. (C) Number of detected spots as a function of different tested intensity thresholds for smiFISH with 24 probes. Panel on the left shows results for 5 cells with different expression levels for ING3, panel on the right for 5 cells of the negative control. Gray vertical bar indicates manually determined plateau for mRNA detection. Note that in the negative control no spots are detected with this threshold. (D) Estimated parameters after fitting detected spots with a 3D Gaussian function (mean ±/- standard deviation). For each experiment, 5 cells with a total of 500± spots were considered. Increasing the probe number leads to brighter amplitude but also more background. Estimated width of the Gaussian stays, however, unchanged. Signal-to-noise ratio (SNR) relates the intensity of the mRNA molecules to fluctuations in background intensity. SNR was calculated as μ/σ, where μ is the average estimated amplitude after fitting individual mRNA molecules with a Gaussian function with FISH-quant (5), σ is the standard deviation of the background intensity (measured in parts of the cells with no mRNA molecules). Reported values are the mean ±/- standard deviation for the same cells used in (C). Using increasing probe numbers leads to a higher SNR for smiFISH and smFISH.

Figure 3.

Detection of CTNNA1 and TPX2 mRNA by two-colour smiFISH in HeLa cells. Single-colour smiFISH performed with Cy3 against either gene. Dual-colour smiFISH performed with Cy3 against TPX2, and Cy5 against CTNNA1. Both probe-sets contain FLAP-Y, and were prehybridized separately with the secondary probes before the actual experiment. (A and B) Maximum intensity projections of representative smiFISH images for (A) single-colour and (B) dual-colour experiments. For automated segmentation, nuclei were marked with DAPI, and cells with HCS CellMask^TM Green (Molecular Probes). Segmentation was performed on focus-projected images (see last section of results) with CellCognition (10): nuclei shown with dashed blue lines, cells with solid blue lines. (C) Left: estimated mRNA number per cell. Reported P-value from Wilcoxon rank sum test for equal medians (Matlab function ranksum). Right: amplitude of 3D Gaussian fit to each detected mRNA molecule. TPX2 mRNA detection was similar in single-colour and dual-colour experiments with respect to estimated mRNA counts and mRNA spot intensity. Labelling of CTNNA1 mRNA with Cy5 leads to substantially dimmer spots, which makes mRNA detection more challenging and leads to a lower P-value for the comparison of mRNA counts. Number of cells per condition: NCTTNA1 = 143, NTPX2 = 115; NCTTNA1,TPX2 = 150. (D) Dual-colour smiFISH (TPX2 in red, and CTNNA1 in white). Images are zoom-ins indicated by red rectangles in (B). For better visualization, images were background corrected with the Subtract Background function in Fiji (Rolling ball radius of 50 pixels). (E) Co-localization analysis for dual-colour smiFISH experiment in (C). mRNAs were detected in 3D images with FISH-quant (5) and co-localization determined with the Matlab function munkres using the Hungarian Algorithm for linear assignment problems, which is available on Matlab File Exchange. Plots show the co-localization percentage for TPX2 (blue, 27 178 mRNAs) and CTNNA1 (red, 35 623 mRNAs) as a function of the maximum allowed distance between spots to be still considered to be co-localized. For distances smaller than 500 nm, co-localization is smaller than 5%. Larger allowed distances lead to a significant increase of co-localization percentage, since neighbouring spots are erroneously considered to co-localize (especially in denser area such as zoom-in 4).

Figure 4.

Expansion microscopy with smiFISH. (A) Principle of ExM with smiFISH. Secondary probes carry an acrydite modification that anchors them into the polymer. After addition of water, the polymer swells and the cell will physically increase in size. Close spots (green rectangle) will be separated more, and can be distinguished under a regular microscope. Grey rectangles show zoom-in to illustrate how the secondary probes get anchored in the polymer network. (B) smiFISH against CRM1 before (left) and after (right) ExM. Numbers in plot after ExM indicate estimated number of mature mRNA molecules. In the image before ExM 186±/-70 mRNAs were detected (Supplementary Figure S8). Images show entire field of view (220 × 220 μm). (C) Bar plots show estimated background and amplitude after fitting detected mRNAs with FISH-quant. N = 5 cells. Black bar shows imaging background without cells. (D) Bar plot shows SNR with standard deviation before and after ExM. (E) As in (B), but for GAPDH. (F) Intensity profile through two mRNA spots after ExM highlighted in inset of (E). Scaled distance obtained by dividing by estimated expansion factor. (G) Estimated mRNA number with FISH-quant before and after ExM with identical detection settings. Boxplot generated with Matlab. Central mark indicates the median, the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. The whiskers extend to the most extreme data points not considered outliers (indicated by crosses).

Figure 5.

Improved image segmentation with focus projection. (A) Images show maximum intensity projections of smFISH against KIF5B in HeLa cells along the indicated axis. Plot on the right shows averaged pixel intensity along the dashed blue line. (B) Schematic of focus based projection. Out-of-focus slices are removed based on a global focus calculation. Local focus measurements are done on remaining images and a projection is performed by choosing for each XY position the pixel-intensity in Z with the maximum focus value. Focus is calculated with HELM operator (27), which computes the intensity ratio between pixels and their neighbourhood. (C) 2D cell segmentation after focus-projection (see also Supplementary Note 3). Eighteen cells were segmented in this image, please note that cells whose nucleus touches the image border were automatically excluded. Yellow rectangle indicate protrusions that were only properly segmented after focus-projection but not maximum intensity projection (See Supplementary Note 3, Figure 5). (D and E) Evaluation of segmentation quality by comparing automatic segmentation to manually segmented ground truth for cell area and cell border. Used abbreviations: TP = true positives, FP = false positives, FN = false negatives, FP = false positives. Sensitivity = TP/(TP±FN), or the proportion of ground truth area (or border) that is correctly segmented. Precision = TP/(TP±FP), or the proportion of the automatically segmented area (or border) belonging to the ground truth. A confidence zone of 36 pixels width is used when comparing cell borders.