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Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise

Nature volume 441, pages 840846 (15 June 2006) | Download Citation

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Abstract

A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.

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Acknowledgements

The authors acknowledge M. Bigos, P. Dezain and S. Elmes for their help with cytometry; K. Uffenheimer and A. Carroll (A.C.) for assistance with automation; W. Wickner for an anti-GFP antibody; R. Tsien for a construct encoding tdTomato; A.C., W.-K. Huh, M. Jonikas, V. Zapeda and E. Griffis for experimental assistance; A. H. DePace for graphical assistance; S. Collins, V. Denic, H. El Samad, V. L. Newman, E. K. O'Shea and members of the Weissman laboratory for insightful comments; and the Hertz Foundation, the NIH, DARPA and HHMI for funding.

Author information

Author notes

    • Sina Ghaemmaghami

    †Present address: Institute for Neurodegenerative Diseases, PO Box 0518, University of California, San Francisco, San Francisco, California 94143-0518, USA

Affiliations

  1. Howard Hughes Medical Institute,

    • John R. S. Newman
    • , Sina Ghaemmaghami
    • , Jan Ihmels
    • , David K. Breslow
    • , Matthew Noble
    • , Joseph L. DeRisi
    •  & Jonathan S. Weissman
  2. Department of Cellular and Molecular Pharmacology, and

    • John R. S. Newman
    • , Sina Ghaemmaghami
    • , Jan Ihmels
    • , David K. Breslow
    •  & Jonathan S. Weissman
  3. Department of Biochemistry and Biophysics, University of California, San Francisco, and the California Institute for Quantitative Biomedical Research, 1700 4th Street, San Francisco, California 94107, USA

    • Joseph L. DeRisi

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Competing interests

Reprints and permissions information is available at npg.nature.com/reprintsandpermissions. The authors declare no competing financial interests.

Corresponding authors

Correspondence to John R. S. Newman or Jonathan S. Weissman.

Supplementary information

PDF files

  1. 1.

    Supplementary Notes 1

    Instruction manual for custom software described in the main text. Instructions on how to use ‘HTSPro’ to control the delivery of samples to a flow cytometer, as well as to control the software that runs the cytometer. As noted in the Supplementary Text, the software is available to academic users from the Authors.

  2. 2.

    Supplementary Notes 2

    Supplementary information about experimental design, execution and interpretation. Also provided is a supplementary discussion and supplementary figures that support the Main Text.

  3. 3.

    Supplementary Table 3

    Statistics for calculating the number of false positive and false negative strains.

  4. 4.

    Supplementary Table 4

    Primers Used for Tagging and Deletion of ORFs

  5. 5.

    Supplementary Table 5

    Organization of GO-Term, transcription factor and transcription module correlations associated with low or high variation

  6. 6.

    Supplementary Table 6

    References for data used for P-value calculations

Excel files

  1. 1.

    Supplementary Table 1

    Abundance and variation measurements for strains grown in YEPD and SD.

  2. 2.

    Supplementary Table 2

    Supplementary Table 2 nature04785-s04.xls Changes in protein and mRNA levels for strains grown in YEPD and SD.

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DOI

https://doi.org/10.1038/nature04785

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