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Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy

Nature Protocols volume 7, pages 80–88 (2012)Cite this article

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Abstract

Quantitative single-cell time-lapse microscopy is a powerful method for analyzing gene circuit dynamics and heterogeneous cell behavior. We describe the application of this method to imaging bacteria by using an automated microscopy system. This protocol has been used to analyze sporulation and competence differentiation in Bacillus subtilis, and to quantify gene regulation and its fluctuations in individual Escherichia coli cells. The protocol involves seeding and growing bacteria on small agarose pads and imaging the resulting microcolonies. Images are then reviewed and analyzed using our laboratory's custom MATLAB analysis code, which segments and tracks cells in a frame-to-frame method. This process yields quantitative expression data on cell lineages, which can illustrate dynamic expression profiles and facilitate mathematical models of gene circuits. With fast-growing bacteria, such as E. coli or B. subtilis, image acquisition can be completed in 1 d, with an additional 1–2 d for progressing through the analysis procedure.

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Figure 1: Slide preparation.
Figure 2: Microscope station for time-lapse microscopy.
Figure 3: Analysis of time-lapse movie reveals single-cell dynamics of a B. subtilis stress response.

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Acknowledgements

We thank J. Park and additional Elowitz Lab members (former and present) for helpful comments regarding the manuscript. This research was supported by US National Institutes of Health grant R01GM07977, the National Science Foundation CAREER Award 0644463 and the Packard Foundation.

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Authors and Affiliations

  1. Division of Biology, California Institute of Technology, Pasadena, California, USA

    Jonathan W Young & James C W Locke

  2. Division of Biology, Biological Network Modeling Center, California Institute of Technology, Pasadena, California, USA

    Alphan Altinok

  3. Cancer Research UK Cambridge Research Institute, Cambridge, UK

    Nitzan Rosenfeld

  4. Moscow State Technological Institute Stankin, Moscow, Russia

    Tigran Bacarian

  5. Centre for Systems Biology at Edinburgh, University of Edinburgh, Edinburgh, Scotland, UK

    Peter S Swain

  6. Department of Computer Science, University of California, Irvine, California, USA

    Eric Mjolsness

  7. Division of Biology, Department of Bioengineering, Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California, USA

    Michael B Elowitz

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  1. Jonathan W Young
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Contributions

J.W.Y., J.C.W.L. and M.B.E. wrote and developed the protocol. A.A. helped with developing a website and modifying the Schnitzcells software package for public release. N.R., P.S.S. and M.B.E. were major original developers of Schnitzcells, and T.B. and E.M. optimized the tracking algorithm.

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Correspondence to Michael B Elowitz.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Video 1

Preparation of agarose pads. This video depicts the process of making agarose pads, as described in the Reagent Setup above, as well as illustrating how bacteria are seeded onto smaller agarose pads and transferred to the imaging dish. Some parts of the video are shown faster than real time. (MOV 25981 kb)

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Young, J., Locke, J., Altinok, A. et al. Measuring single-cell gene expression dynamics in bacteria using fluorescence time-lapse microscopy. Nat Protoc 7, 80–88 (2012). https://doi.org/10.1038/nprot.2011.432

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