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.

FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images

Nature Protocols volume 9, pages 457–463 (2014)Cite this article

Subjects

Abstract

Cell biology heavily relies on the behavior of fibrillar structures, such as the cytoskeleton, yet the analysis of their behavior in tissues often remains qualitative. Image analysis tools have been developed to quantify this behavior, but they often involve an image pre-processing stage that may bias the output and/or they require specific software. Here we describe FibrilTool, an ImageJ plug-in based on the concept of nematic tensor, which can provide a quantitative description of the anisotropy of fiber arrays and their average orientation in cells, directly from raw images obtained by any form of microscopy. FibrilTool has been validated on microtubules, actin and cellulose microfibrils, but it may also help analyze other fibrillar structures, such as collagen, or the texture of various materials. The tool is ImageJ-based, and it is therefore freely accessible to the scientific community and does not require specific computational setup. The tool provides the average orientation and anisotropy of fiber arrays in a given region of interest (ROI) in a few seconds.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

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

Figure 1: Presentation of FibrilTool.
Figure 2: Effect of image quality and ROI selection on the FibrilTool output.
Figure 3: Test of FibrilTool on images with different types of fibrillar structures.

References

  1. Lippincott-Schwartz, J. & Manley, S. Putting super-resolution fluorescence microscopy to work. Nat. Methods 6, 21–23 (2009).

    Article  CAS  Google Scholar 

  2. Gerlich, D., Mattes, J. & Eils, R. Quantitative motion analysis and visualization of cellular structures. Methods 29, 3–13 (2003).

    Article  CAS  Google Scholar 

  3. Axelrod, D. Total internal reflection fluorescence microscopy in cell biology. Traffic 2, 764–774 (2001).

    Article  CAS  Google Scholar 

  4. Green, P.B. Multinet growth in the cell wall of Nitella. J. Biophys. Biochem. Cytol. 7, 289–296 (1960).

    Article  CAS  Google Scholar 

  5. Tower, T.T., Neidert, M.R. & Tranquillo, R.T. Fiber alignment imaging during mechanical testing of soft tissues. Ann. Biomed. Eng. 30, 1221–1233 (2002).

    Article  Google Scholar 

  6. Sander, E.A., Stylianopoulos, T., Tranquillo, R.T. & Barocas, V.H. Image-based multiscale modeling predicts tissue-level and network-level fiber reorganization in stretched cell-compacted collagen gels. Proc. Natl. Acad. Sci. USA 106, 17675–17680 (2009).

    Article  CAS  Google Scholar 

  7. Pijanka, J.K. et al. Quantitative mapping of collagen fiber orientation in non-glaucoma and glaucoma posterior human sclerae. Invest. Ophthalmol. Vis. Sci. 53, 5258–5270 (2012).

    Article  CAS  Google Scholar 

  8. Yi, Q. & Coppolino, M.G. Automated classification and quantification of F-actin-containing ruffles in confocal micrographs. Biotechniques 40, 745–746, 748, 750 passim (2006).

    Article  CAS  Google Scholar 

  9. Higaki, T., Kutsuna, N., Sano, T., Kondo, N. & Hasezawa, S. Quantification and cluster analysis of actin cytoskeletal structures in plant cells: role of actin bundling in stomatal movement during diurnal cycles in Arabidopsis guard cells. Plant. J. 61, 156–165 (2010).

    Article  CAS  Google Scholar 

  10. Jacques, E. et al. MicroFilament Analyzer, an image analysis tool for quantifying fibrillar orientation, reveals changes in microtubule organization during gravitropism. Plant. J. 74, 1045–1058 (2013).

    Article  CAS  Google Scholar 

  11. Rubbens, M.P. et al. Quantification of the temporal evolution of collagen orientation in mechanically conditioned engineered cardiovascular tissues. Ann. Biomed. Eng. 37, 1263–1272 (2009).

    Article  Google Scholar 

  12. Sander, E.A. & Barocas, V.H. Comparison of 2D fiber network orientation measurement methods. J. Biomed. Mater. Res. A 88, 322–331 (2009).

    Article  CAS  Google Scholar 

  13. Schriefl, A.J., Wolinski, H., Regitnig, P., Kohlwein, S.D. & Holzapfel, G.A. An automated approach for three-dimensional quantification of fibrillar structures in optically cleared soft biological tissues. J. R. Soc. Interface 10, 20120760 (2013).

    Article  Google Scholar 

  14. Karlon, W.J., Covell, J.W., McCulloch, A.D., Hunter, J.J. & Omens, J.H. Automated measurement of myofiber disarray in transgenic mice with ventricular expression of ras. Anatomical Record 252, 612–625 (1998).

    Article  CAS  Google Scholar 

  15. Uyttewaal, M. et al. Mechanical stress acts via Katanin to amplify differences in growth rate between adjacent cells in Arabidopsis. Cell 149, 439–451 (2012).

    Article  CAS  Google Scholar 

  16. Lucas, J.R. & Shaw, S.L. MAP65-1 and MAP65-2 promote cell proliferation and axial growth in Arabidopsis roots. Plant J. 71, 454–463 (2012).

    CAS  PubMed  Google Scholar 

  17. Martin, A.C., Kaschube, M. & Wieschaus, E.F. Pulsed contractions of an actin-myosin network drive apical constriction. Nature 457, 495–499 (2009).

    Article  CAS  Google Scholar 

  18. Burian, A. et al. A correlative microscopy approach relates microtubule behavior, local organ geometry, and cell growth at the Arabidopsis shoot apical meristem. J. Exp. Bot. 64, 5753–5767 (2013).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This research was supported by a bilateral grant from Institut National de la Recherche Agronomique (INRA), France; by the Ministry of Science and Higher Education, Poland; by the MAESTRO research grant no. 2011/02/A/NZ3/00079 from the National Science Centre, Poland; and by a grant from Agence Nationale de la Recherche ANR-10-BLAN-1516 'Mechastem'. We thank Platim (UMS 3444 Biosciences Gerland-Lyon Sud) for help with imaging.

Author information

Authors and Affiliations

  1. Laboratoire de Reproduction et Développement des Plantes, Institut National de la Recherche Agronomique (INRA), Centre National de la Recherche Scientifique (CNRS), Ecole Normale Supérieure de Lyon (ENS), Université de Lyon, Lyon, France

    Arezki Boudaoud, Magalie Uyttewaal & Olivier Hamant

  2. Laboratoire Joliot Curie, CNRS, ENS Lyon, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France

    Arezki Boudaoud & Olivier Hamant

  3. Department of Biophysics and Morphogenesis of Plants, University of Silesia, Katowice, Poland

    Agata Burian, Dorota Borowska-Wykręt & Dorota Kwiatkowska

  4. Institut Jean-Pierre Bourgin, UMR1318 INRA-AgroParisTech, Centre de Versailles, Versailles, France

    Magalie Uyttewaal

  5. August Chełkowski Institute of Physics, University of Silesia, Katowice, Poland

    Roman Wrzalik

Authors
  1. Arezki Boudaoud
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Agata Burian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dorota Borowska-Wykręt
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Magalie Uyttewaal
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Roman Wrzalik
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dorota Kwiatkowska
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Olivier Hamant
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

The protocol was initiated and first tested by A. Boudaoud, M.U. and O.H. A. Boudaoud designed the ImageJ macros and supervised the formulation of the protocol. A. Burian, D.B.-W., R.W. and D.K. obtained images of fibrillar structures and used them to further test the macros. A. Boudaoud and O.H. wrote the manuscript with input from the other authors.

Corresponding author

Correspondence to Arezki Boudaoud.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Validation of FibrilTool with artificial images.

a-d. Examples of artificial images (372x372 pixels) obtained by generating 50 random segments (black segments, width 2 pixels) with (a,b) or with no (c,d) directional bias; the images in (a,c) were “degraded” by applying a Gaussian blur of radius 5 pixels (b,d); the theoretical orientation and anisotropy score can be computed directly from the distribution of segments, while the output of FibrilTool is shown in blue. e,f. Results of the analysis of a set of 10x3 such images with FibrilTool: raw images (continuous lines), moderately degraded images (blur of radius 3, dashed lines), and degraded images (blur of radius 5, dot-dashed lines). Data are plotted as a function of the theoretical anisotropy score: anisotropy score measured with FibrilTool (e); difference in degrees between orientation measured with FibrilTool and theoretical orientation (f).

Supplementary information

Supplementary Figure 1

Validation of FibrilTool with artificial images. (PDF 370 kb)

Supplementary Table 1

Sample excel file that can be used to copy-paste the contents of the Log file. (XLS 27 kb)

Supplementary Data 1

Source file of FibrilTool. (TXT 6 kb)

Supplementary Data 2

Source file of the DirectionPrinting macro. (TXT 0 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Boudaoud, A., Burian, A., Borowska-Wykręt, D. et al. FibrilTool, an ImageJ plug-in to quantify fibrillar structures in raw microscopy images. Nat Protoc 9, 457–463 (2014). https://doi.org/10.1038/nprot.2014.024

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2014.024

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

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