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Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry

Nature Methods volume 11, pages 443–448 (2014)Cite this article

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Abstract

Cells adjust to changes in environmental conditions using complex regulatory programs. These cellular programs are the result of an intricate interplay between gene expression, cellular growth and protein degradation. Technologies that enable simultaneous and time-resolved measurements of these variables are necessary to dissect cellular homeostatic strategies. Here we report the development of an automated flow cytometry robotic setup that enables real-time measurement of precise and simultaneous relative growth and protein synthesis rates of multiplexed microbial populations across many conditions. These measurements generate quantitative profiles of dynamically evolving protein synthesis and degradation rates. We demonstrate this setup in the context of gene regulation of the unfolded protein response (UPR) of Saccharomyces cerevisiae and uncover a dynamic and complex landscape of gene expression, growth dynamics and proteolysis following perturbations.

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Figure 1: Automated high-throughput real-time flow cytometry.
Figure 2: Growth rate–corrected reporter protein dynamics by high-throughput flow cytometry.
Figure 3: Determination of two-dimensional dose responses and cell-to-cell variability by high-throughput flow cytometry.

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Acknowledgements

We thank J. DeRisi for useful conversations, engineering advice and access to equipment; J. Stewart-Ornstein (University of California, San Francisco (UCSF)) for the use of the estradiol-inducible system; and D. Pincus (UCSF) and the Walter lab for the HAC1i construct. V. Chubukov and C.-S. Chin provided early insight on reactor design and flow cytometry interfacing. This work was funded by the US National Institute of General Medical Sciences (NIGMS) system biology center (P50 GM081879), the David and Lucille Packard Foundation (H.E.-S. and H.L.) and US National Institutes of Health grants R01-GM070808 (H.L.).

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Authors and Affiliations

  1. Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California, USA

    Ignacio A Zuleta, Andrés Aranda-Díaz, Hao Li & Hana El-Samad

  2. The California Institute for Quantitative Biosciences, San Francisco, California, USA

    Ignacio A Zuleta, Andrés Aranda-Díaz, Hao Li & Hana El-Samad

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  1. Ignacio A Zuleta
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  2. Andrés Aranda-Díaz
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Contributions

I.A.Z., H.E.-S. and H.L. conceived of the hardware setup. I.A.Z. designed, implemented and characterized the hardware setup, control software and mathematical framework. I.A.Z. and A.A.-D. designed and carried over the experiments. I.A.Z., A.A.-D., H.L. and H.E.-S. analyzed and interpreted the data. A.A.-D. cloned the strains necessary for the experiments. I.A.Z., A.A.-D., H.L. and H.E.-S. prepared the manuscript.

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Correspondence to Hao Li or Hana El-Samad.

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Zuleta, I., Aranda-Díaz, A., Li, H. et al. Dynamic characterization of growth and gene expression using high-throughput automated flow cytometry. Nat Methods 11, 443–448 (2014). https://doi.org/10.1038/nmeth.2879

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