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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.

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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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