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High-throughput microfluidics to control and measure signaling dynamics in single yeast cells

Nature Protocols volume 10, pages 1181–1197 (2015)Cite this article

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Abstract

Microfluidics coupled to quantitative time-lapse fluorescence microscopy is transforming our ability to control, measure and understand signaling dynamics in single living cells. Here we describe a pipeline that incorporates multiplexed microfluidic cell culture, automated programmable fluid handling for cell perturbation, quantitative time-lapse microscopy and computational analysis of time-lapse movies. We illustrate how this setup can be used to control the nuclear localization of the budding yeast transcription factor Msn2. By using this protocol, we generate oscillations of Msn2 localization and measure the dynamic gene expression response of individual genes in single cells. The protocol allows a single researcher to perform up to 20 different experiments in a single day, while collecting data for thousands of single cells. Compared with other protocols, the present protocol is relatively easy to adopt and of higher throughput. The protocol can be widely used to control and monitor single-cell signaling dynamics in other signal transduction systems in microorganisms.

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Figure 1: Overview of the microfluidic setup.
Figure 2: A typical experiment.
Figure 3: Device design.
Figure 4: Photolithography and soft lithography overview.
Figure 5: Photolithography steps: fabrication of silicon wafer master mold.
Figure 6: Soft lithography steps: fabrication of microfluidic device.
Figure 7: Time-lapse microscopy experiments.

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Acknowledgements

We thank M. McClean and S. Ramanathan for their help with setting up the original Y-channel microfluidic device. We thank D. MacLaurin and E. Zwiebach-Cohen for discussions. We thank the O'Shea laboratory for discussions and comments on the manuscript. This work was performed in part at the Center for Nanoscale Systems at Harvard University, a member of the National Nanotechnology Infrastructure Network, which is supported by the National Science Foundation under NSF award no. ECS-0335765. This work was supported by the Howard Hughes Medical Institute (to E.K.O'S.) and the US National Institutes of Health grant R01 GM111458 (to N.H.).

Author information

Authors and Affiliations

  1. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA

    Anders S Hansen & Erin K O'Shea

  2. Howard Hughes Medical Institute, Harvard University, Northwest Laboratory, Cambridge, Massachusetts, USA

    Anders S Hansen & Erin K O'Shea

  3. Faculty of Arts and Sciences Center for Systems Biology, Harvard University, Northwest Laboratory, Cambridge, Massachusetts, USA

    Anders S Hansen & Erin K O'Shea

  4. Division of Biological Sciences, Section of Molecular Biology, University of California San Diego, La Jolla, California, USA

    Nan Hao

  5. Department of Molecular and Cellular Biology, Harvard University, Northwest Laboratory, Cambridge, Massachusetts, USA

    Erin K O'Shea

Authors
  1. Anders S Hansen
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  3. Erin K O'Shea
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Contributions

A.S.H. developed the multiplexed microfluidic device, the automated fluid control system, developed MATLAB code and wrote the protocol. N.H. developed the original method of using microfluidics to control analog-sensitive kinases and Msn2 localization. E.K.O'S. supervised the projects. A.S.H., N.H. and E.K.O'S. wrote the manuscript.

Corresponding author

Correspondence to Erin K O'Shea.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Control experiment for Figure 2.

Figure 2 shows a typical experiment for strain EY2967/ASH189 in response to six 5-min pulses of 690 nM 1-NM-PP1 separated by 10- min intervals. This figure shows the same plots with the same axes for a control experiment without 1-NM-PP1 treatment. As can be seen, in the absence of 1-NM-PP1 treatment, no gene expression is observed.

a) Msn2 translocation dynamics. In this control experiment, no 1-NM-PP1 is added, so no Msn2-mCherry activation is observed. Raw data (black dots) and errorbars (standard deviation) are from 101 single cells and the red line shows a fit to the data.

b)-c) Single cell time traces of the YFP (b) and CFP (c) gene expression reporters. Raw, unsmoothed data is shown. As can be seen, in the absence of 1-NM-PP1 treatment, no gene expression is observed.

d) By following both CFP and YFP gene expression dynamics in the same single cell, their co-variance can be computed. Each dot in the scatterplot is the max CFP and YFP from the same single cell.

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1, Supplementary Tutorials 1 and 2 (PDF 1686 kb)

Supplementary Data 1: Transparency mask

Raw transparency mask file in ‘.eps’ format. (ZIP 349 kb)

Supplementary Data 2: Valve control scripts

A zip-compressed folder containing MATLAB scripts for controlling and interfacing with solenoid electrovalves as described in Box 1 and Supplementary Tutorial 1. (ZIP 3 kb)

Supplementary Data 3: Image analysis scripts

A zip-compressed folder containing MATLAB scripts for image analysis as described in Supplementary Tutorial 2. (ZIP 123 kb)

Supplementary Data 4: Microscope holder

Microscope holder sketch in ‘PDF’ format. (PDF 264 kb)

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Hansen, A., Hao, N. & O'Shea, E. High-throughput microfluidics to control and measure signaling dynamics in single yeast cells. Nat Protoc 10, 1181–1197 (2015). https://doi.org/10.1038/nprot.2015.079

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