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Detection of nucleic acid–protein interactions in plant leaves using fluorescence lifetime imaging microscopy

Nature Protocols volume 12, pages 1933–1950 (2017)Cite this article

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Abstract

DNA-binding proteins (DNA-BPs) and RNA-binding proteins (RNA-BPs) have critical roles in living cells in all kingdoms of life. Various experimental approaches exist for the study of nucleic acid–protein interactions in vitro and in vivo, but the detection of such interactions at the subcellular level remains challenging. Here we describe how to detect nucleic acid–protein interactions in plant leaves by using a fluorescence resonance energy transfer (FRET) approach coupled to fluorescence lifetime imaging microscopy (FLIM). Proteins of interest (POI) are tagged with a GFP and transiently expressed in plant cells to serve as donor fluorophore. After sample fixation and cell wall permeabilization, leaves are treated with Sytox Orange, a nucleic acid dye that can function as a FRET acceptor. Upon close association of the GFP-tagged POI with Sytox-Orange-stained nucleic acids, a substantial decrease of the GFP lifetime due to FRET between the donor and the acceptor can be monitored. Treatment with RNase before FRET–FLIM measurements allows determination of whether the POI associates with DNA and/or RNA. A step-by-step protocol is provided for sample preparation, data acquisition and analysis. We describe how to calibrate the equipment and include a tutorial explaining the use of the FLIM software. To illustrate our approach, we provide experimental procedures to detect the interaction between plant DNA and two proteins (the AeCRN13 effector from the oomycete Aphanomyces euteiches and the AtWRKY22 defensive transcription factor from Arabidopsis). This protocol allows the detection of protein–nucleic acid interactions in plant cells and can be completed in <2 d.

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Figure 1: General view of the FLIM setup.
Figure 2: Visualization of the fluorescence decay in live mode.
Figure 3: GFP fluorescence observed in Nicotiana leaves that express GFP-tagged proteins.
Figure 4: Synchronization of the FLIM system.
Figure 5: Process from the acquired streak images to the extraction of the raw decay curve.
Figure 6: Extraction of the estimated parameters.
Figure 7: Lifetime image.
Figure 8: GFP lifetime distribution of GFP:AeCRN13 and GFP:AeCRN13AAA fusion proteins in plant nuclei.
Figure 9: NSR-b:GFP binds RNA in N. benthamiana leaves.
Figure 10: GFP lifetime distribution within a nucleus.

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Acknowledgements

We thank the Région Midi-Pyrénées, the Université Paul Sabatier Toulouse III and the GIS-IBiSA ('Groupement d'Intérêt Scientifique-Infrastructure Biologie Santé Agronomie') for financial support for the FLIM equipment. We are grateful to F. Esteveny for his contribution to the development of the FLIM software. The research was carried out using the core facilities of the TRI-Genotoul Imagery Platform of Toulouse (France) and in the Laboratoire de Recherche en Sciences Végétales and the Laboratory of Plant-Microbe Interactions, part of the French Laboratory of Excellence 'TULIP' (ANR-10-LABX-41; ANR-11-IDEX-0002-02). L.D. was supported by an Agence Nationale de la Recherche (ANR) grant (RADAR, ANR-15-CE20-0016-01). E.G. was supported by an ANR Jeunes Chercheuses/Jeunes Chercheurs grant (APHANO-Effect, ANR-12-JSV6-0004-01).

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Author notes

  1. Laurent Camborde and Alain Jauneau: These authors contributed equally to this work.

Authors and Affiliations

  1. Laboratoire de Recherche en Sciences Végétales, Université de Toulouse, CNRS–Université Toulouse, Castanet-Tolosan, France

    Laurent Camborde, Christian Brière, Bernard Dumas & Elodie Gaulin

  2. CNRS, Plateforme Imagerie-Microscopie, Fédération de Recherche FR3450, Castanet-Tolosan, France

    Alain Jauneau

  3. LIPM, Université de Toulouse, INRA, CNRS–Université Toulouse, Castanet-Tolosan, France

    Laurent Deslandes

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Contributions

L.C. designed the experimental procedures for N. benthamiana leaves, improved the FRET–FLIM method and performed data acquisition; A.J. acquired and analyzed FLIM data and contributed to the development of the FLIM software and its guidelines; C.B. contributed to the development of the FLIM software and its guidelines; L.D. performed the experiment with AtWRKY22 and contributed to the improvement of the FRET–FLIM technique; B.D. contributed to the guidelines of the FLIM software and the design of the experimental procedures; and E.G. managed this collaborative work. All the authors wrote the manuscript.

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Correspondence to Elodie Gaulin.

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Integrated supplementary information

Supplementary Figure 1 Examples of invalid decay curves

A: This picture illustrates a noisy curve that can be obtained when the incorrect focus is used or upon a too short time for data acquisition. B: This curve shows a rapid decrease in the fluorescence intensity, likely due to the fluorescence of chlorophyll (chloroplasts close to the nucleus) or to the use of altered solutions that damaged the samples. C: Incorrect synchronization of the system leads to noisy curve associated with two peaks (arrows).

Supplementary Figure 2 NLE versus MLE

Comparison of the distribution of τ values of 20,000 pixels using the NLE (orange) or MLE (green) estimation model obtained from an image of fluorescein standard solution, Imax being higher than 103 (panel A) or lower than 103 (panel B). When the Imax is higher than 103 the results are similar; the histograms obtained using either NLE or MLE are centred around 4.3 ns (mean value of 4.30 +/- 0.08 and 4.34 +/-0.07 with NLE and MLE respectively). In B, the values are clearly underestimated using the NLE estimation model (value centred on 4.0 +/-0.14 ns). Using the MLE model, the histogram is centred around 4.31 +/-0.21 ns. We have to note the higher dispersion of the values in B than in A. Ensure not to underestimate the value and carefully interpret the different values inside an object compared to the standard error.

Supplementary Figure 3 Efficiency of RNase A treatment on N. benthamiana tissues

A: Subnuclear localization of NSR-b:GFP in Nicotiana benthamiama cells. Top-left (a): NSR-b:GFP is localized in subnuclear speckles in the absence of RNase treatment. Other panels illustrated RNaseA treated tissues. Top-right (b): speckles are still present but a weak GFP fluorescence is detected in the nucleus. Bottom-left (c): speckles are strongly destabilized and GFP fluorescence is observed in the entire nucleus. Bottom-right (d): speckles seem to be intact, suggesting that RNase treatment was inefficient in this nucleus. Scale bar: 10μm B: Overview of the fluorescence of Acridine Orange stained nuclei after RNase treatment. Green fluorescence is due to DNA binding ability of Acridine Orange. Presence of RNA allows Acridine Orange to emit red fluorescence. White arrows show green and red fluorescence in treated nuclei, indicating incomplete RNA degradation. Scale bar: 10 μm.

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Camborde, L., Jauneau, A., Brière, C. et al. Detection of nucleic acid–protein interactions in plant leaves using fluorescence lifetime imaging microscopy. Nat Protoc 12, 1933–1950 (2017). https://doi.org/10.1038/nprot.2017.076

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