Cell surface proteins are major targets of biomedical research due to their utility as cellular markers and their extracellular accessibility for pharmacological intervention. However, information about the cell surface protein repertoire (the surfaceome) of individual cells is only sparsely available. Here, we applied the Cell Surface Capture (CSC) technology to 41 human and 31 mouse cell types to generate a mass-spectrometry derived Cell Surface Protein Atlas (CSPA) providing cellular surfaceome snapshots at high resolution. The CSPA is presented in form of an easy-to-navigate interactive database, a downloadable data matrix and with tools for targeted surfaceome rediscovery (http://wlab.ethz.ch/cspa). The cellular surfaceome snapshots of different cell types, including cancer cells, resulted in a combined dataset of 1492 human and 1296 mouse cell surface glycoproteins, providing experimental evidence for their cell surface expression on different cell types, including 136 G-protein coupled receptors and 75 membrane receptor tyrosine-protein kinases. Integrated analysis of the CSPA reveals that the concerted biological function of individual cell types is mainly guided by quantitative rather than qualitative surfaceome differences. The CSPA will be useful for the evaluation of drug targets, for the improved classification of cell types and for a better understanding of the surfaceome and its concerted biological functions in complex signaling microenvironments.

Complete reference maps or datasets, like the genomic map of an organism, are highly beneficial tools for biological and biomedical research. Attempts to generate such reference datasets for a proteome so far failed to reach complete proteome coverage, with saturation apparent at approximately two thirds of the proteomes tested, even for the most thoroughly characterized proteomes. Here, we used a strategy based on high-throughput peptide synthesis and mass spectrometry to generate a close to complete reference map (97% of the genome-predicted proteins) of the S. cerevisiae proteome. We generated two versions of this mass spectrometric map one supporting discovery- (shotgun) and the other hypothesis-driven (targeted) proteomic measurements. The two versions of the map, therefore, constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. The reference libraries can be browsed via a web-based repository and associated navigation tools. To demonstrate the utility of the reference libraries we applied them to a protein quantitative trait locus (pQTL) analysis, which requires measurement of the same peptides over a large number of samples with high precision. Protein measurements over a set of 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, impacting on the levels of related proteins. Our results suggest that selective pressure favors the acquisition of sets of polymorphisms that maintain the stoichiometry of protein complexes and pathways.

Precise gene expression measurement has been fundamental to developing an advanced understanding of the roles of biological networks in health and disease. To enable detection of expression signatures specific to individual cells we developed PLAYR (Proximity Ligation Assay for RNA). PLAYR enables highly multiplexed quantification of transcripts in single cells by flow- and mass-cytometry and is compatible with standard antibody staining of proteins. With mass cytometry, this currently enables simultaneous quantification of more than 40 different mRNAs and proteins. The technology was demonstrated in primary cells to be capable of quantifying multiple gene expression transcripts while the identity and the functional state of each analyzed cell was defined based on the expression of other transcripts or proteins. PLAYR now enables high throughput deep phenotyping of cells to readily expand beyond protein epitopes to include RNA expression, thereby opening a new venue on the characterization of cellular metabolism.

Many cellular responses are triggered by proteins, drugs or pathogens binding to cell-surface receptors, but it can be challenging to identify which receptors are bound by a given ligand. Here we describe TRICEPS, a chemoproteomic reagent with three moieties--one that binds ligands containing an amino group, a second that binds glycosylated receptors on living cells and a biotin tag for purifying the receptor peptides for identification by quantitative mass spectrometry. We validated this ligand-based, receptor-capture (LRC) technology using insulin, transferrin, apelin, epidermal growth factor, the therapeutic antibody trastuzumab and two DARPins targeting ErbB2. In some cases, we could also determine the approximate ligand-binding sites on the receptors. Using TRICEPS to label intact mature vaccinia viruses, we identified the cell surface proteins AXL, M6PR, DAG1, CSPG4 and CDH13 as binding factors on human cells. This technology enables the identification of receptors for many types of ligands under near-physiological conditions and without the need for genetic manipulations.