Measuring mRNA copy number in individual Escherichia coli cells using single-molecule fluorescent in situ hybridization

Journal name:
Nature Protocols
Year published:
Published online
Corrected online


We present a protocol for measuring the absolute number of mRNA molecules from a gene of interest in individual, chemically fixed Escherichia coli cells. A set of fluorescently labeled oligonucleotide probes is hybridized to the target mRNA, such that each mRNA molecule is decorated by a known number of fluorescent dyes. Cells are then imaged using fluorescence microscopy. The copy number of the target mRNA is estimated from the total intensity of fluorescent foci in the cell, rather than from counting discrete 'spots' as in other currently available protocols. Image analysis is performed using an automated algorithm. The measured mRNA copy number distribution obtained from many individual cells can be used to extract the parameters of stochastic gene activity, namely the frequency and size of transcription bursts from the gene of interest. The experimental procedure takes 2 d, with another 2–3 d typically required for image and data analysis.

At a glance


  1. Experimental procedure.
    Figure 1: Experimental procedure.

    (a) Image acquisition. Phase-contrast and fluorescence images are acquired for each sample. Multiple focal planes (z positions) are imaged to allow precise fluorescence detection throughout the depth of the cell. (b) Cell and spot segmentation. The positions of individual cells and fluorescent foci (spots) are identified using custom MATLAB codes. Cell recognition uses as input the phase contrast images, and is performed using the Schnitzcells program (see Equipment). Fluorescent spots are identified from the stacks of fluorescence images, using the Spätzcells program developed in our laboratory. (c) Discarding false positives. False-positive spots, which are the result of probe binding to nontarget RNA, are discarded after examination of the histogram of peak height (spot intensity maximum) in a negative sample. (d) Identifying fluorescence intensity of one mRNA. The spot intensity corresponding to a single mRNA molecule is identified by examining the histogram of single spot intensities in a low-expression sample, where individual mRNAs are spatially separable. (e) Converting fluorescence intensity into mRNA numbers and extracting kinetic parameters. The one-mRNA intensity value is used to convert the total spot intensity in any cell to the number of target mRNA molecules. By measuring mRNA numbers in >1,000 cells per sample, the population mean and variance are estimated. The copy-number histogram is fitted to a simple model of transcription kinetics. The parameters of the fit are used to calculate the frequency and size of transcription bursts. Scale bars, 1 μm. a.u., arbitrary units.

  2. Preparation and use of agarose pads.
    Figure 2: Preparation and use of agarose pads.

    (a) Stack five microscope slides on a leveled surface. (b) Pour the molten agarose solution onto the slides. (c) Cover the agarose with the remaining slide, placing a weight on top. Let the agarose solidify for 45 min at room temperature. (d) Remove the four slides from the sides of the agarose pad, leaving the top and bottom slides for easy storage and handling. (e) Remove the excess agarose from the slides with a razor blade. (f) For use in imaging, carefully move the slides, exposing the agarose, and excise a 1 × 1 cm agar pad with a razor blade. (g) Pipette 2 μl of the cell suspension onto the center of a 24 × 50 mm coverslip. (h) Lay the agarose pad slowly on top of the cell suspension droplet with the razor blade. (i) Cover the pad with a 22 × 22 mm coverslip.

  3. Different smFISH samples contain spots of distinct brightness and size.
    Figure 3: Different smFISH samples contain spots of distinct brightness and size.

    Fluorescence channel images from three experimental samples (from left to right: negative control sample, low-expression control sample, high expression sample) are displayed at varying contrast levels (rows 2–4). The phase-contrast and fluorescence images were taken at a single focal plane (z position). Scale bars, 2 μm. See ANTICIPATED RESULTS for a discussion of the observed features.

Change history

Corrected online 19 August 2015
In the version of this article initially published, a component (40 µl of 50 mg ml-1 BSA) was erroneously omitted from the 'Hybridization solution' recipe in the Reagent Setup section. The error has been corrected in the HTML and PDF versions of the article.


  1. Femino, A.M., Fay, F.S., Fogarty, K. & Singer, R.H. Visualization of single RNA transcripts in situ. Science 280, 585590 (1998).
  2. Raj, A., Peskin, C.S., Tranchina, D., Vargas, D.Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).
  3. Zenklusen, D., Larson, D.R. & Singer, R.H. Single-RNA counting reveals alternative modes of gene expression in yeast. Nat. Struct. Mol. Biol. 15, 12631271 (2008).
  4. Raj, A., van den Bogaard, P., Rifkin, S.A., van Oudenaarden, A. & Tyagi, S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 5, 877879 (2008).
  5. Taniguchi, Y. et al. Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science 329, 533538 (2010).
  6. Trcek, T. et al. Single-mRNA counting using fluorescent in situ hybridization in budding yeast. Nat. Protoc. 7, 408419 (2012).
  7. Zenklusen, D. & Singer, R.H. Analyzing mRNA expression using single mRNA resolution fluorescent in situ hybridization. Methods Enzymol. 470, 641659 (2010).
  8. Zong, C., So, L.H., Sepulveda, L.A., Skinner, S.O. & Golding, I. Lysogen stability is determined by the frequency of activity bursts from the fate-determining gene. Mol. Syst. Biol. 6, 440 (2010).
  9. So, L.H. et al. General properties of transcriptional time series in Escherichia coli. Nat. Genet. 43, 554560 (2011).
  10. Golding, I., Paulsson, J., Zawilski, S.M. & Cox, E.C. Real-time kinetics of gene activity in individual bacteria. Cell 123, 10251036 (2005).
  11. Thompson, R.E., Larson, D.R. & Webb, W.W. Precise nanometer localization analysis for individual fluorescent probes. Biophys. J. 82, 27752283 (2002).
  12. Lubeck, E. & Cai, L. Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat. Methods 9, 743748 (2012).
  13. Golding, I. & Cox, E.C. Chapter 8: Spatiotemporal dynamics in bacterial cells: real-time studies with single-event resolution. Methods Cell Biol. 89, 223251 (2008).
  14. Maamar, H., Raj, A. & Dubnau, D. Noise in gene expression determines cell fate in Bacillus subtilis. Science 317, 526529 (2007).
  15. Kafri, R. et al. Dynamics extracted from fixed cells reveal feedback linking cell growth to cell cycle. Nature 494, 480483 (2013).
  16. Peccoud, J. & Ycart, B. Markovian modeling of gene-product synthesis. Theor. Popul. Biol. 48, 222234 (1995).
  17. Shahrezaei, V. & Swain, P.S. Analytical distributions for stochastic gene expression. Proc. Natl. Acad. Sci. USA 105, 1725617261 (2008).
  18. Levsky, J.M., Shenoy, S.M., Pezo, R.C. & Singer, R.H. Single-cell gene expression profiling. Science 297, 836840 (2002).
  19. Long, R.M. et al. Mating type switching in yeast controlled by asymmetric localization of ASH1 mRNA. Science 277, 383387 (1997).
  20. Golding, I. & Cox, E.C. RNA dynamics in live Escherichia coli cells. Proc. Natl. Acad. Sci. USA 101, 1131011315 (2004).
  21. Montero Llopis, P. et al. Spatial organization of the flow of genetic information in bacteria. Nature 466, 7781 (2010).
  22. Nevo-Dinur, K., Nussbaum-Shochat, A., Ben-Yehuda, S. & Amster-Choder, O. Translation-independent localization of mRNA in E. coli. Science 331, 10811084 (2011).
  23. Bakshi, S., Siryaporn, A., Goulian, M. & Weisshaar, J.C. Superresolution imaging of ribosomes and RNA polymerase in live Escherichia coli cells. Mol. Microbiol. 85, 2138 (2012).
  24. Kuhlman, T.E. & Cox, E.C. Gene location and DNA density determine transcription factor distributions in Escherichia coli. Mol. Syst. Biol. 8, 610 (2012).
  25. Phillips, R., Kondev, J., Theriot, J. & Garcia, H. Physical Biology of the Cell (Garland Science, 2012).
  26. Yu, J., Xiao, J., Ren, X., Lao, K. & Xie, X.S. Probing gene expression in live cells, one protein molecule at a time. Science 311, 16001603 (2006).
  27. Hebenstreit, D. et al. RNA sequencing reveals two major classes of gene expression levels in metazoan cells. Mol. Syst. Biol. 7, 497 (2011).
  28. Bertrand, E. et al. Localization of ASH1 mRNA particles in living yeast. Mol. Cell 2, 437445 (1998).
  29. Fusco, D. et al. Single mRNA molecules demonstrate probabilistic movement in living mammalian cells. Curr. Biol. 13, 161167 (2003).
  30. Young, J.W. et al. Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat. Protoc. 7, 8088 (2012).
  31. Cohen, A.A. et al. Dynamic proteomics of individual cancer cells in response to a drug. Science 322, 15111516 (2008).
  32. Geva-Zatorsky, N. et al. Protein dynamics in drug combinations: a linear superposition of individual-drug responses. Cell 140, 643651 (2010).
  33. Neidhardt, F.C. (ed.) Escherichia coli and Salmonella: Cellular and Molecular Biology (ASM Press, 1996).
  34. Bates, D. & Kleckner, N. Chromosome and replisome dynamics in E. coli: loss of sister cohesion triggers global chromosome movement and mediates chromosome segregation. Cell 121, 899911 (2005).
  35. Kuhlman, T., Zhang, Z., Saier, M.H. Jr. & Hwa, T. Combinatorial transcriptional control of the lactose operon of Escherichia coli. Proc. Natl. Acad. Sci. USA 104, 60436048 (2007).
  36. Yakovleva, G.M., Kim, S.K. & Wanner, B.L. Phosphate-independent expression of the carbon-phosphorus lyase activity of Escherichia coli. Appl. Microbiol. Biotechnol. 49, 573588 (1998).
  37. Raj, A. & Tyagi, S. Detection of individual endogenous RNA transcripts in situ using multiple singly labeled probes. Methods Enzymol. 472, 365386 (2010).
  38. Batish, M., Raj, A. & Tyagi, S. Single molecule imaging of RNA in situ. Methods Mol. Biol. 714, 313 (2010).
  39. Sliusarenko, O., Heinritz, J., Emonet, T. & Jacobs-Wagner, C. High-throughput, subpixel precision analysis of bacterial morphogenesis and intracellular spatio-temporal dynamics. Mol. Microbiol. 80, 612627 (2011).
  40. Paulsson, J. & Ehrenberg, M. Random signal fluctuations can reduce random fluctuations in regulated components of chemical regulatory networks. Phys. Rev. Lett. 84, 54475450 (2000).

Download references

Author information

  1. These authors contributed equally to this work.

    • Samuel O Skinner &
    • Leonardo A Sepúlveda


  1. Verna and Marrs McLean Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, Texas, USA.

    • Samuel O Skinner,
    • Leonardo A Sepúlveda,
    • Heng Xu &
    • Ido Golding
  2. Department of Physics, University of Illinois, Urbana, Illinois, USA.

    • Samuel O Skinner &
    • Ido Golding
  3. Center for Biophysics and Computational Biology, University of Illinois, Urbana, Illinois, USA.

    • Leonardo A Sepúlveda &
    • Ido Golding
  4. Center for the Physics of Living Cells, University of Illinois, Urbana, Illinois, USA.

    • Heng Xu &
    • Ido Golding


I.G. supervised the project. S.O.S., L.A.S. and H.X. developed the protocol. S.O.S., L.A.S. and I.G. wrote the paper.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Author details

Additional data