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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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.).
The authors declare no competing financial interests.
Integrated supplementary information
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 Figure 1, Supplementary Tutorials 1 and 2 (PDF 1686 kb)
Raw transparency mask file in ‘.eps’ format. (ZIP 349 kb)
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)
A zip-compressed folder containing MATLAB scripts for image analysis as described in Supplementary Tutorial 2. (ZIP 123 kb)
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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