Endocytosis is a complex process fulfilling many cellular and developmental functions. Understanding how it is regulated and integrated with other cellular processes requires a comprehensive analysis of its molecular constituents and general design principles. Here, we developed a new strategy to phenotypically profile the human genome with respect to transferrin (TF) and epidermal growth factor (EGF) endocytosis by combining RNA interference, automated high-resolution confocal microscopy, quantitative multiparametric image analysis and high-performance computing. We identified several novel components of endocytic trafficking, including genes implicated in human diseases. We found that signalling pathways such as Wnt, integrin/cell adhesion, transforming growth factor (TGF)-β and Notch regulate the endocytic system, and identified new genes involved in cargo sorting to a subset of signalling endosomes. A systems analysis by Bayesian networks further showed that the number, size, concentration of cargo and intracellular position of endosomes are not determined randomly but are subject to specific regulation, thus uncovering novel properties of the endocytic system.
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We acknowledge T. Galvez and G. Marsico, members of the Zerial group for discussions and scientific support. We are particularly indebted to K. Korn who developed transfection protocols and organized various preparatory steps and logistics before the screen and E. Krausz for the management of the HT-TDS, the MPI-CBG screening facility. We thank J. Schmitt, A. Lohmann, S. Christ, N. Tomschke, A. Niederlein, J. Wagner, M. Gierth, E. Krausz for technical, robotics and computational assistance, and M. Boes and J. Oegema for IT support that made the large-scale computational analysis possible. We acknowledge I. C. Baines, T. Galvez, J. Howard, T. Hyman, M. McShane, G. O’Sullivan and P. Tomancak for comments on the manuscript. This work was financially supported by the Max Planck Society (MPG) and by the systems biology network HepatoSys of the German Ministry for Education and Research BMBF, the DFG and the Gottlieb Daimler und Karl Benz Stiftung. This work is also part of the project ‘Endotrack’, which received research funding from the European Community’s Sixth Framework Programme.
Author Contributions C.C., Y.K. and M.Z. conceived the project and M.Z. directed it. C.C. and D.K. developed the endocytosis assay under the guidance of M.Z. and E.F.; M.S. performed the screen and image acquisition. Y.K. developed the QMPIA with the help of C.C. and J.C.R. and performed all computational analysis of the screening data. N.S. developed the clustering and pheno-score algorithms and together with C.C. performed the analysis of the clusters. C.R.B., under the supervision of B.H., performed the si/esiRNAs remapping and bioinformatics analysis. CC. and Y.K performed the Bayesian Network analysis. F.B. provided the esiRNA library. R.H., under the supervision of M.S.M. and W.E.N., provided IT support for the use of the computer cluster located at the TUD. C.C.,Y.K. and M.Z. wrote the manuscript.
The authors declare no competing financial interests.
This file contains Supplementary Materials and Methods with Supplementary Figures 11-12 with Legends, Supplementary Data and Supplementary References. (PDF 812 kb)
This file contains Supplementary Figures 1-10 with Legends. (PDF 9116 kb)
This table contains a list of parameters used in the phenotype profiling. (XLS 30 kb)
This table contains a list of known genes involved in endocytic trafficking. (XLS 20 kb)
The table contains a list of kinases having an effect on VSV virus infection. (XLS 23 kb)
This table contains the 4609 genes that were considered for further analysis. (XLS 9732 kb)
This table includes the sequences of all si/esiRNAs targeting the 4609 positive genes. (XLS 5056 kb)
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Collinet, C., Stöter, M., Bradshaw, C. et al. Systems survey of endocytosis by multiparametric image analysis. Nature 464, 243–249 (2010). https://doi.org/10.1038/nature08779
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