Protocol | Published:

Quantitative mapping of fluorescently tagged cellular proteins using FCS-calibrated four-dimensional imaging

Nature Protocols volume 13, pages 14451464 (2018) | Download Citation

Abstract

The ability to tag a protein at its endogenous locus with a fluorescent protein (FP) enables quantitative understanding of protein dynamics at the physiological level. Genome-editing technology has now made this powerful approach routinely applicable to mammalian cells and many other model systems, thereby opening up the possibility to systematically and quantitatively map the cellular proteome in four dimensions. 3D time-lapse confocal microscopy (4D imaging) is an essential tool for investigating spatial and temporal protein dynamics; however, it lacks the required quantitative power to make the kind of absolute and comparable measurements required for systems analysis. In contrast, fluorescence correlation spectroscopy (FCS) provides quantitative proteomic and biophysical parameters such as protein concentration, hydrodynamic radius, and oligomerization but lacks the capability for high-throughput application in 4D spatial and temporal imaging. Here we present an automated experimental and computational workflow that integrates both methods and delivers quantitative 4D imaging data in high throughput. These data are processed to yield a calibration curve relating the fluorescence intensities (FIs) of image voxels to the absolute protein abundance. The calibration curve allows the conversion of the arbitrary FIs to protein amounts for all voxels of 4D imaging stacks. Using our workflow, users can acquire and analyze hundreds of FCS-calibrated image series to map their proteins of interest in four dimensions. Compared with other protocols, the current protocol does not require additional calibration standards and provides an automated acquisition pipeline for FCS and imaging data. The protocol can be completed in 1 d.

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Acknowledgements

We thank the mechanical and electronics workshops of EMBL for custom hardware, the Advanced Light Microscopy Facility of EMBL for microscopy support, and the Flow Cytometry Core Facility of EMBL for cell sorting. We gratefully acknowledge B. Nijmeijer, S. Alexander, and A. Rybina for critical reading of the manuscript. We thank T. Ohrt (Zeiss) for support in the hardware control. This work was supported by grants to J.E. from the European Commission EU-FP7-Systems Microscopy NoE (grant agreement 258068), EU-FP7-MitoSys (grant agreement 241548), and iNEXT (grant agreement 653706), as well as by EMBL (A.Z.P., Y.C., N.W., M.J.H., B.K., M.W., and J.E.). Y.C. and N.W. were supported by the EMBL International PhD Programme (EIPP).

Author information

Author notes

    • Yin Cai
    • , Birgit Koch
    •  & Malte Wachsmuth

    Present addresses: Roche Diagnostics, Waiblingen, Germany (Y.C.); Max Planck Institute for Medical Research, Heidelberg, Germany (B.K.); Luxendo, Heidelberg, Germany (M.W.).

Affiliations

  1. EMBL, Heidelberg, Germany.

    • Antonio Z Politi
    • , Yin Cai
    • , Nike Walther
    • , M Julius Hossain
    • , Birgit Koch
    • , Malte Wachsmuth
    •  & Jan Ellenberg

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Contributions

A.Z.P. performed the experiments and analysis, and designed the software packages. A.Z.P. developed the protocol with the help of Y.C. and M.W. N.W. tested the protocol and helped in writing the software manuals. B.K. created the homozygous cell line and provided the dextran-labeling protocol. M.J.H. provided the code to segment the cells. A.Z.P. wrote the protocol with the help of N.W., B.K., and J.E.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Jan Ellenberg.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary figures 1–3, Supplementary Tables 1–2 and Supplementary Notes 1–6

Zip files

  1. 1.

    Supplementary Software 1

    The FCSRunner software to manually acquire FCS and imaging data.

  2. 2.

    Supplementary Software 2

    The MyPiC software to automatically acquire FCS and imaging data using adaptive-feedback microscopy.

  3. 3.

    Supplementary Software 3

    A FiJi software package to automatically acquire FCS and imaging data using adaptive-feedback microscopy; to be used in combination with Supplementary Software 2.

  4. 4.

    Supplementary Software 4

    FiJi and R tools to analyze the FCS and imaging data and compute image calibration coefficients.

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DOI

https://doi.org/10.1038/nprot.2018.040

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