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  English.dicp.cas.cn    Posted:2018-11-19
Lecture: The in silico Human Surfaceome & Technologies for the Elucidation of the Surfaceome Nanoscale Organization

Time: Nov. 19th, 2018, 09:30 am
Venue: Academic Hall, Biotechnology Buiding
Lecturer: Bernd Wollscheid, Institute of Molecular Systems Biology & Department of Health Sciences and Technology, ETH Zurich, Switzerland


Cell surface proteins are of great biomedical importance as demonstrated by the fact that 66% of approved human drugs listed in the DrugBank database target a cell surface protein. Despite this biomedical relevance, there has been no comprehensive assessment of the human surfaceome, and only a fraction of the predicted 5,000 human transmembrane proteins have been shown to be located at the plasma membrane (http://wlab.ethz.ch/protter). To enable analysis of the human surfaceome, we developed the surfaceome predictor SURFY, based on machine learning. As a training set, we used experimentally verified high-confidence cell surface proteins from the Cell Surface Protein Atlas (CSPA, http://wlab.ethz.ch/CSPA) and trained a random forest classifier on 131 features per protein and specifically, per topological domain. SURFY was used to predict a human surfaceome of 2,886 proteins with an accuracy of 93.5%, which shows excellent overlap with known cell surface protein classes (i.e., receptors). In deposited mRNA data, we found that between 543 to 1,100 surfaceome genes were expressed in cancer cell lines and maximally 1,700 surfaceome genes were expressed in embryonic stem cells and derivative lines. Thus, the surfaceome diversity depends on cell type and appears to be more dynamic than the non-surface proteome. To make the predicted surfaceome readily accessible to the research community, we provide visualization tools for intuitive interrogation (http://wlab.ethz.ch/surfaceome). The in silico surfaceome enables the filtering of data generated by multi-omics screens and supports the elucidation of the surfaceome nanoscale organization using proximity-based tagging strategies. Proximity Radical Tagging (PRT) and Lux-MS technology are two new chemical proteomics-based strategies which enable the identification of ligand-receptor interactions, but also the elucidation of lateral/cis interactions within the surfaceome. Proximity-tagging by Lux-MS and PRT provide new molecular spatial relationship information which could be exploited for drug targeting.


Bernd Wollscheid is a Professor for Chemical and Systems Biology at the Swiss Federal Institute of Technology in Zürich, Switzerland. After studying chemistry in Freiburg and Boston he obtained his PhD in Molecular Immunology from the Max-Planck Institute for Immunobiology. His postdoctoral research took him to the Institute of Systems Biology in Seattle where he developed and applied chemoproteomic technologies to elucidate cell surface protein biology. As a group leader and PI at the Institute for Molecular Systems Biology at ETH Zurich he developed a research program focusing on a systems biology understanding of the cell surface as a cellular information gateway and on the identification of cell surface glycoproteins as diagnostic and therapeutic clinical targets. Now at the Department of Health Sciences and Technology of ETH his team developed and applied chemoproteomic technologies which enable the decoding of the extracellular interactome.

Contact: YE Mingliang
Phone: 84379610




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