Abstract
mRNA Fluorescence In Situ Hybridization (FISH) is a technique commonly used to profile the distribution of transcripts in cells. When combined with the common single molecule technique Fluorescence Resonance Energy Transfer (FRET), FISH can also be used to profile the co-expression of nearby sequences in the transcript to measure processes such as alternate initiation or splicing variation of the transcript. Unlike in a conventional FISH method using multiple probes to target a single transcript, FRET is limited to the use of two probes labeled with matched dyes and requires the use of sensitized emission. Any widefield microscope capable of sensitive single molecule detection of Cy3 and Cy5 should be able to measure FRET in yeast cells. Alternatively, a FRET-FISH method can be used to unambiguously ascertain identity of the transcript without the use of a guide probe set used in other FISH techniques.
Keywords: RNA FISH, Fluorescence In Situ Hybridization, Saccharomyces cerevisiae, Budding yeast, Transcription, Single molecule
Background
Quantification of the transcript distribution of single cells is typically accomplished by targeting mRNA with multiple probes to achieve a bright signal that can be distinguished from non-specifically bound probes (Raj and Tyagi, 2010). However, in some instances, there are features on the transcript such as splicing variants or alternative initiation sites that would be indistinguishable to a conventional FISH probe set. These isoform sequences can have short 50 nt uniquely identifying sequences. Using two probes, one can target either side of the junction with a FRET pair and quantify up to three classifications of mRNA isoform simultaneously, e.g., the isoform with both probes (FRET), the isoform with probe 1 only, and the isoform with probe 2 only. The reliance on a single fluorophore or pair of fluorophores requires sensitive detection through an EMCCD. Also, the detection efficiency of a probe for a sequence without other isoforms can be estimated using a FRET pair (Wadsworth et al., 2017).
Materials and Reagents
Equipment
Software
Procedure
Data analysis
The Matlab Image Processing Toolbox was used to analyze the three-dimensional images. In cases where the researcher is unfamiliar with coding we recommend FISH-quant for its rigor and user friendly GUI. For systems with very non- uniform illumination Corrected Intensity Distributions using Regularized Energy minimization (CIDRE) (Smith et al., 2015) can be used to flatten the images. Many functions in the Image Processing Toolbox can be accelerated by simply converting them to a gpuArray () in Matlab with a compatible graphics card (e.g., Nvidia Geforce 1080). An outline of the algorithm used to locate cells and spots is as follows:
Notes
Recipes
Acknowledgments
Parts of this protocol have been adapted from Raj et al. (2010). This work was supported by Georgia Institute of Technology startup funds, GAANN Molecular Biophysics and Biotechnology Fellowship, and the National Institutes of Health grant (R01-GM112882).
Competing interests
The authors declare no conflicts of interests or competing interests.
References
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