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Probabilistic density maps to study global endomembrane organization


We developed a computational imaging approach that describes the three-dimensional spatial organization of endomembranes from micromanipulation-normalized mammalian cells with probabilistic density maps. Applied to several well-known marker proteins, this approach revealed the average steady-state organization of early endosomes, multivesicular bodies or lysosomes, endoplasmic reticulum exit sites, the Golgi apparatus and Golgi-derived transport carriers in crossbow-shaped cells. The steady-state organization of each tested endomembranous population was well-defined, unique and in some cases depended on the cellular adhesion geometry. Density maps of all endomembrane populations became stable when pooling several tens of cells only and were reproducible in independent experiments, allowing construction of a standardized cell model. We detected subtle changes in steady-state organization induced by disruption of the cellular cytoskeleton, with statistical significance observed for just 20 cells. Thus, combining micropatterning with construction of endomembrane density maps allows the systematic study of intracellular trafficking determinants.

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Figure 1: Analysis of CD63-positive endomembranes from 35 cells on crossbow-shaped patterns.
Figure 2: Analysis of Rab5-, Sec13- and Rab6-positive endomembranes on crossbow-shaped patterns.
Figure 3: Comparison of 'characteristic territories' and 'characteristic volumes' of endomembranes on crossbow-shaped patterns.
Figure 4: Analysis of CD63- and Rab6-positive endomembranes in circular cells.
Figure 5: Changes of Rab6-positive endomembranes upon cytoskeletal disruption.


  1. Bornens, M. Organelle positioning and cell polarity. Nat. Rev. Mol. Cell Biol. 9, 874–886 (2008).

    CAS  Article  Google Scholar 

  2. Caviston, J.P. & Holzbaur, E.L. Microtubule motors at the intersection of trafficking and transport. Trends Cell Biol. 16, 530–537 (2006).

    CAS  Article  Google Scholar 

  3. Lanzetti, L. Actin in membrane trafficking. Curr. Opin. Cell Biol. 19, 453–458 (2007).

    CAS  Article  Google Scholar 

  4. Ross, J.L., Ali, M.Y. & Warshaw, D.M. Cargo transport: molecular motors navigate a complex cytoskeleton. Curr. Opin. Cell Biol. 20, 41–47 (2008).

    CAS  Article  Google Scholar 

  5. Insall, R.H. & Machesky, L.M. Actin dynamics at the leading edge: from simple machinery to complex networks. Dev. Cell 17, 310–322 (2009).

    CAS  Article  Google Scholar 

  6. Schmoranzer, J. et al. Par3 and dynein associate to regulate local microtubule dynamics and centrosome orientation during migration. Curr. Biol. 19, 1065–1074 (2009).

    CAS  Article  Google Scholar 

  7. Egea, G., Lazaro-Dieguez, F. & Vilella, M. Actin dynamics at the Golgi complex in mammalian cells. Curr. Opin. Cell Biol. 18, 168–178 (2006).

    CAS  Article  Google Scholar 

  8. Rivero, S., Cardenas, J., Bornens, M. & Rios, R.M. Microtubule nucleation at the cis-side of the Golgi apparatus requires AKAP450 and GM130. EMBO J. 28, 1016–1028 (2009).

    CAS  Article  Google Scholar 

  9. Semenova, I. et al. Actin dynamics is essential for myosin-based transport of membrane organelles. Curr. Biol. 18, 1581–1586 (2008).

    CAS  Article  Google Scholar 

  10. Taunton, J. Actin filament nucleation by endosomes, lysosomes and secretory vesicles. Curr. Opin. Cell Biol. 13, 85–91 (2001).

    CAS  Article  Google Scholar 

  11. Sachs, K., Perez, O., Pe'er, D., Lauffenburger, D.A. & Nolan, G.P. Causal protein-signaling networks derived from multiparameter single-cell data. Science 308, 523–529 (2005).

    CAS  Article  Google Scholar 

  12. Sigal, A. et al. Variability and memory of protein levels in human cells. Nature 444, 643–646 (2006).

    CAS  Article  Google Scholar 

  13. Snijder, B. et al. Population context determines cell-to-cell variability in endocytosis and virus infection. Nature 461, 520–523 (2009).

    CAS  Article  Google Scholar 

  14. Liu, W.F. & Chen, C.S. Cellular and multicellular form and function. Adv. Drug Deliv. Rev. 59, 1319–1328 (2007).

    CAS  Article  Google Scholar 

  15. Thery, M., Pepin, A., Dressaire, E., Chen, Y. & Bornens, M. Cell distribution of stress fibres in response to the geometry of the adhesive environment. Cell Motil. Cytoskeleton 63, 341–355 (2006).

    CAS  Article  Google Scholar 

  16. Thery, M. et al. Anisotropy of cell adhesive microenvironment governs cell internal organization and orientation of polarity. Proc. Natl. Acad. Sci. USA 103, 19771–19776 (2006).

    CAS  Article  Google Scholar 

  17. Racine, V. et al. Visualization and quantification of vesicle trafficking on a three-dimensional cytoskeleton network in living cells. J. Microsc. 225, 214–228 (2007).

    Article  Google Scholar 

  18. Bowman, A.W. & Foster, P. Density based exploration of bivariate data. Stat. Comput. 3, 171–177 (1993).

    Article  Google Scholar 

  19. Hyndman, R. Computing and graphing highest density regions. Am. Stat. 50, 120–126 (1996).

    Google Scholar 

  20. Pols, M.S. & Klumperman, J. Trafficking and function of the tetraspanin CD63. Exp. Cell Res. 315, 1584–1592 (2009).

    CAS  Article  Google Scholar 

  21. Chavrier, P., Parton, R.G., Hauri, H.P., Simons, K. & Zerial, M. Localization of low molecular weight GTP binding proteins to exocytic and endocytic compartments. Cell 62, 317–329 (1990).

    CAS  Article  Google Scholar 

  22. Tang, B.L. et al. The mammalian homolog of yeast Sec13p is enriched in the intermediate compartment and is essential for protein transport from the endoplasmic reticulum to the Golgi apparatus. Mol. Cell. Biol. 17, 256–266 (1997).

    CAS  Article  Google Scholar 

  23. Antony, C. et al. The small GTP-binding protein rab6p is distributed from medial Golgi to the trans-Golgi network as determined by a confocal microscopic approach. J. Cell Sci. 103, 785–796 (1992).

    CAS  PubMed  Google Scholar 

  24. Grigoriev, I. et al. Rab6 regulates transport and targeting of exocytotic carriers. Dev. Cell 13, 305–314 (2007).

    CAS  Article  Google Scholar 

  25. White, J. et al. Rab6 coordinates a novel Golgi to ER retrograde transport pathway in live cells. J. Cell Biol. 147, 743–760 (1999).

    CAS  Article  Google Scholar 

  26. Gretton, A., Borgwardt, K.M., Rasch, M.J., Schoelkopf, B. & Smola, A. A kernel method for the two-sample problem. Advances in Neural Information Processing Systems 19: Proceedings of the 2006 Conference 513–520 (MIT Press, Cambridge, Masssachusetts, USA, 2007).

  27. Wodarz, A. & Näthke, I. Cell polarity in development and cancer. Nat. Cell Biol. 9, 1016–1024 (2007).

    CAS  Article  Google Scholar 

  28. Rodriguez Boulan, E. & Sabatini, D.D. Asymmetric budding of viruses in epithelial monlayers: a model system for study of epithelial polarity. Proc. Natl. Acad. Sci. USA 75, 5071–5075 (1978).

    CAS  Article  Google Scholar 

  29. Snider, J. et al. Intracellular actin-based transport: how far you go depends on how often you switch. Proc. Natl. Acad. Sci. USA 101, 13204–13209 (2004).

    CAS  Article  Google Scholar 

  30. Azioune, A., Storch, M., Bornens, M., Théry, M. & Piel, M. Simple and rapid process for single cell micro-patterning. Lab Chip 9, 1640–1642 (2009).

    CAS  Article  Google Scholar 

  31. Sibarita, J.B. Deconvolution microscopy. Adv. Biochem. Eng. Biotechnol. 95, 201–243 (2005).

    PubMed  Google Scholar 

  32. Simonoff, J.S. Smoothing Methods for Statistics. (Springer, New York, 1996).

    Book  Google Scholar 

  33. Duong, T. & Hazelton, M.L. Plug-in bandwidth matrices for bivariate kernel density estimations. J. Nonparametr. Stat. 17, 17–30 (2003).

    Article  Google Scholar 

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We acknowledge L. Sengmanivong of the Nikon Imaging Centre at Institut Curie–Centre National de la Recherche Scientifique and V. Fraisier of the Plate-forme Imagerie Cellulaire et Tissulaire–Infrastructures en Biologie Santé et Agronomie Imaging Facility for their extensive help with microscopes and in particular their help using the deconvolution service of the facility. We thank J.-B. Sibarita for advice on image analysis including use of the multidimensional image analysis program and fruitful discussion during early phases of the project; I. Brito for statistical advice; W. Hong (Institute of Molecular and Cell Biology, Singapore) for providing the Sec13 antibody; M. Piel, A. Azioune and J. Fink for help with microprinting; and G. Egea, S. Miserey, A. Echard and J. Enninga for critical reading of the manuscript. K.S. received funding from the Fondation pour la Recherche Médicale en France and Association pour la Recherche sur le Cancer. This project was supported by grants from the Centre National de la Recherche Scientifique and Institut Curie.

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Authors and Affiliations



K.S. and B.G. designed the research, K.S. performed the experiments and analysis and wrote the manuscript, T.D. developed the density calculation, K.B. developed the statistical analysis and edited the manuscript, S.B. adjusted patterning techniques and M.B. contributed to the conception of the work.

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Correspondence to Kristine Schauer or Bruno Goud.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Table 1 and Supplementary Notes 1–2 (PDF 2412 kb)

Supplementary Video 1

Maximum intensity projection of the deconvolved fluorescence of GFP-Rab6-positive cells (n = 82) under control conditions. (AVI 2507 kb)

Supplementary Video 2

Maximum intensity projection of the deconvolved fluorescence of GFP-Rab6-positive cells (n = 47) after nocodazole treatment. (AVI 1383 kb)

Supplementary Video 3

Maximum intensity projection of the deconvolved fluorescence of GFP-Rab6-positive cells (n = 50) after cytochalasin D treatment. (AVI 1667 kb)

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Schauer, K., Duong, T., Bleakley, K. et al. Probabilistic density maps to study global endomembrane organization. Nat Methods 7, 560–566 (2010).

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