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Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors

Tomáš Lukeš, Jakub Pospíšil, Karel Fliegel, Theo Lasser, View ORCID ProfileGuy M. Hagen
doi: https://doi.org/10.1101/246488
Tomáš Lukeš
1Laboratoire d’Optique Biomédicale, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
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Jakub Pospíšil
2Department of Radioelectronics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 16627 Prague 6, Czech Republic
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Karel Fliegel
2Department of Radioelectronics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 16627 Prague 6, Czech Republic
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Theo Lasser
1Laboratoire d’Optique Biomédicale, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
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Guy M. Hagen
3UCCS center for the Biofrontiers Institute, University of Colorado at Colorado Springs, 1420 Austin Bluffs Parkway, Colorado Springs, Colorado, 80918, USA
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  • ORCID record for Guy M. Hagen
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Abstract

Background Super-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared to organic dyes which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms.

Findings Four complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM data sets using a different method: super-resolution optical fluctuation imaging (SOFI). The two modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes.

Conclusion This dataset has potential for extensive reuse. Complete raw data from SMLM experiments has typically not been published. The YFP data exhibits low signal to noise ratios, making data analysis a challenge. These data sets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.

Footnotes

  • Tomáš Lukeš, tomas.lukes{at}epfl.ch, Guy M. Hagen, ghagen{at}uccs.edu

  • Abbreviations

    (d)STORM
    (direct) stochastic optical reconstruction microscopy
    FWHM
    full width at half maximum
    GFP
    green fluorescent protein
    NA
    numerical aperture
    PALM
    photoactivated localization microscopy
    PSF
    point spread function
    SMLM
    single molecule localization microscopy
    SOFI
    stochastic optical fluctuation imaging
    WF
    wide field
    YFP
    yellow fluorescent protein
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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    Posted January 11, 2018.
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    Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors
    Tomáš Lukeš, Jakub Pospíšil, Karel Fliegel, Theo Lasser, Guy M. Hagen
    bioRxiv 246488; doi: https://doi.org/10.1101/246488
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    Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors
    Tomáš Lukeš, Jakub Pospíšil, Karel Fliegel, Theo Lasser, Guy M. Hagen
    bioRxiv 246488; doi: https://doi.org/10.1101/246488

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