Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Brief Communication
  • Published:

Integrated genetic and computation methods for in planta cytometry

Nature Methods volume 9, pages 483–485 (2012)Cite this article

Subjects

Abstract

We present the coupled use of specifically localized fluorescent gene markers and image processing for automated quantitative analysis of cell growth and genetic activity across living plant tissues. We used fluorescent protein markers to identify cells, create seeds and boundaries for the automatic segmentation of cell geometries and ratiometrically measure gene expression cell by cell in Arabidopsis thaliana.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Automated segmentation of cells in Arabidopsis.
Figure 2: Nuclear ratiometric measurements for in planta cytometry.

Similar content being viewed by others

References

  1. Caselles, V., Kimmel, R. & Sapiro, G. Int. J. Comput. Vis. 22, 61–79 (1997).

    Article  Google Scholar 

  2. Otsu, N. IEEE Trans. Syst. Man Cybern. 9, 62–66 (1979).

    Article  Google Scholar 

  3. Kapur, J.N., Sahoo, P.K. & Wong, A.K.C. Comput. Vis. Graph. Image Process 29, 273–285 (1985).

    Article  Google Scholar 

  4. Rittscher, J. Ann. Rev. Biomed. Eng. 12, 315–344 (2010).

    Article  CAS  Google Scholar 

  5. Makowski, P. et al. Comput. Med. Imaging Graph. 26, 9–17 (2002).

    Article  Google Scholar 

  6. Beemster, G.T. & Baskin, T.I. Plant Physiol. 116, 1515–1526 (1998).

    Article  CAS  Google Scholar 

  7. Laskowski, M. et al. PLoS Biol. 6, 307 (2008).

    Article  Google Scholar 

  8. Ottenschläger, I. et al. Proc. Natl. Acad. Sci. USA 100, 2987–2991 (2003).

    Article  Google Scholar 

  9. Jones, A.R. et al. Nat. Cell Biol. 11, 78–84 (2009).

    Article  CAS  Google Scholar 

  10. Kass, M., Witkin, A. & Terzopoulos, D. Int. J. Computer Vision 1, 321–331 (1988).

    Article  Google Scholar 

  11. Mace, D.L. et al. Bioinformatics 22, e323–e331 (2006).

    Article  CAS  Google Scholar 

  12. Jönsson, H. et al. Bioinformatics 21 (suppl. 1), i232–i240 (2005).

    Article  Google Scholar 

  13. Kelly, J.R. et al. J. Biol. Eng. 3, 4 (2009).

    Article  Google Scholar 

  14. Boisnard-Lorig, C. et al. Plant Cell 13, 495–509 (2001).

    Article  CAS  Google Scholar 

  15. Kurup, S. et al. Plant J. 42, 444–453 (2005).

    Article  CAS  Google Scholar 

  16. Boresi, A.P. & Chong, K.P. Elasticity in Engineering Mechanics (Wiley-IEEE, New York, 2000).

  17. Sage, D., Neumann, F.R., Hediger, F., Gasser, S.M. & Unser, M. IEEE Trans. Image Process. 14, 1372–1383 (2005).

    Article  Google Scholar 

  18. Bao, Z. et al. Proc. Natl. Acad. Sci. USA 103, 2707–2712 (2006).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was supported by the Biotechnology and Biological Sciences Research Council, and Engineering and Physical Sciences Research Council research grants (BBS/B/16720 and BEP/17053 to J.H.), Institut de Recherche pour le Développement (L.L). F.F.'s PhD scholarship was supported by the Bill and Melinda Gates foundation (Gates Cambridge Trust). The Scottish Crop Research Institute receives grant-in-aid support from the Scottish Government Rural and Environment Research and Analysis Directorate (Workpackage 1.7). M.H. acknowledges the Australian Research Council for funding. We thank B. Scheres and H. Hofhuis (Utrecht University) for DR5rev∷3×Venus-N7 seeds and R.Y. Tsien (University of California, San Diego) for the mRFP1 cassette.

Author information

Author notes

  1. Fernán Federici and Lionel Dupuy: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Plant Sciences, University of Cambridge, Cambridge, UK

    Fernán Federici & Jim Haseloff

  2. The James Hutton Institute, Invergowrie, Dundee, Scotland, UK

    Lionel Dupuy

  3. Institut de Recherche pour le Développement, Unité Mixte de Recherche, Diversité Adaptation Développement, EÉquipe Rhizogenèse, Montpellier, France

    Laurent Laplaze

  4. Developmental Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Marcus Heisler

  5. School of Biological Sciences, University of Sydney, Sydney, Australia

    Marcus Heisler

Authors
  1. Fernán Federici
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lionel Dupuy
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Laurent Laplaze
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Marcus Heisler
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jim Haseloff
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

F.F. generated the transgenic lines, analyzed the data and performed experiments. L.D. created the computational tools and plugin for ImageJ, and analyzed the data. J.H. provided instructions and supervision. M.H. performed confocal imaging of shoot apical meristem shown in Figure 2 and Supplementary Figure 1. L.L. generated the pBI 35S∷H2B-RFP binary vector and the Arabidopsis 35S∷H2B-RFP transgenic line.

Corresponding author

Correspondence to Jim Haseloff.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4 (PDF 14667 kb)

Supplementary Movie 1

Time-lapse movie of 35S::GFPLTI6b and 35S::mCherry-H2B in the root apical meristem. Images were acquired every 3 min. This video is shown with illustrative purposes, and it was not used for data analysis owing to its short duration (1 h 24 min). (MOV 726 kb)

Supplementary Movie 2

Time-lapse imaging of 35S::GFPLTI6b and 35S::mCherry-H2B to automate cell tracking in the root apical meristem. Images were acquired every 3 min. Nuclei tracking used SpotTracker to extract nuclei trajectories and to initiate balloon positions. This video is shown with illustrative purposes, and it was not used for data analysis owing to its short duration (1 h 24 min). (MOV 809 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Federici, F., Dupuy, L., Laplaze, L. et al. Integrated genetic and computation methods for in planta cytometry. Nat Methods 9, 483–485 (2012). https://doi.org/10.1038/nmeth.1940

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.1940

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing