Oral Presentation HUPO 2019 - 18th Human Proteome Organization World Congress

LUX-MS enables the light-controlled elucidation of ligand-receptor interactions and functional surfaceome nanoscale organization on living cells (#50)

Maik Mueller 1 2 , Stefan Vetterli 3 , Milon Mondal 3 , Andy Kong 4 , Yannik Severin 5 , Fabienne Graebnitz 6 , Niculo Barandun 6 , James Prudent 7 , Annette Oxenius 6 , John Robinson 3 , Berend Snijder 5 , Alexey Nesvizhskii 4 , Bernd Wollscheid 1 2
  1. Institute of Molecular Systems Biology & Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
  2. Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
  3. Chemistry Department, University of Zurich, Zurich, Switzerland
  4. Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
  5. Institute of Molecular Systems Biology & Department of Biology, ETH Zurich, Zurich, Switzerland
  6. Institute of Microbiology & Department of Biology, ETH Zurich, Zurich, Switzerland
  7. Centrose, Madison, Wisconsin, USA

Similar to intracellular proteins cell surface proteins engage in dynamic protein interactions to confer function. However, there is limited knowledge of how cell surface residing proteins within the surfaceome of human and microbial cells are organized into functional complexes and interact with extracellular ligands due to analytical limitations. Defining functional surfaceome synapses and dynamic interactions in cis and trans would enable the development of rational strategies to manipulate cellular signaling in health and disease. Here, we developed LUX-MS which enables light-mediated proximity detection of ligand-receptor interactions and cell surface protein neighborhoods on living cells.

LUX-MS uses small molecule Singlet Oxygen Generators (SOGs) that produce spatially restricted reactive oxygen species upon illumination. SOGs can be coupled to a ligand of choice such as pathogens, antibodies or even small molecules enabling the light-controlled photo-oxidation of ligand-proximal proteins in nanometer vicinity. Using FragPipe we found bioorthogonal amino acid modifications and boosted their yield for highly-efficient chemical labeling. Combined with a tailored quantitative DDA/DIA-MS-based workflow such an optoproteomic strategy can be used to reveal acute ligand-receptor interactions and cell surface protein neighborhoods in a discovery-driven fashion.

We used LUX-MS technology within four scenarios in order to highlight its versatile application space: First, we applied LUX-MS in human peripheral blood mononuclear cells and identified the binding target of the therapeutic antibody Rituximab. Next, we decoded ligand-receptor interactions in microbes by revealing interaction of a novel class of antibiotics with an essential outer-membrane biogenesis complex. On cancer cells, we mapped surfaceome neighborhoods targeted by a small molecule ion channel inhibitor revealing candidates for extracellular-drug-conjugate targeting (EDCs). Finally, we used LUX-MS to investigate dynamic protein interactions implicated in the formation of functional immune synapses between T-cells and antigen-presenting cells.

Taken together, LUX-MS enables light-controlled proximity-detection of dynamic protein interactions to decode the extracellular interactome across organisms.



  1. Bausch-Fluck, D., Milani, E. S. & Wollscheid, B. Surfaceome nanoscale organization and extracellular interaction networks. Curr. Opin. Chem. Biol. 48, 26–33 (2019)
  2. Sobotzki, N. et al. HATRIC-based identification of receptors for orphan ligands. Nat. Commun. 9, 1519 (2018)
  3. Frei, A. P. et al. Direct identification of ligand-receptor interactions on living cells and tissues. Nat. Biotechnol. 30, 997–1001 (2012)
  4. Kuimova, M. K., Yahioglu, G. & Ogilby, P. R. Singlet oxygen in a cell: spatially dependent lifetimes and quenching rate constants. J. Am. Chem. Soc. 131, 332–340 (2009)
  5. Glasgow, H. L. et al. Laminin targeting of a peripheral nerve-highlighting peptide enables degenerated nerve visualization. Proc. Natl. Acad. Sci. U. S. A. (2016). doi:10.1073/pnas.1611642113
  6. Kong, A. T., Leprevost, F. V., Avtonomov, D. M., Mellacheruvu, D. & Nesvizhskii, A. I. MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics. Nat. Methods 14, 513–520 (2017)
  7. Marshall, D. J. et al. Extracellular Antibody Drug Conjugates Exploiting the Proximity of Two Proteins. Mol. Ther. (2016). doi:10.1038/mt.2016.119
  8. van Oostrum, M. et al. ‘De novo Classification of Mouse B Cell Types using Surfaceome Proteotype Maps’. bioRxiv 620344 (2019). doi:10.1101/620344