Spatial proteomics in neurons at single-protein resolution
Center for NanoScience · Max Planck Institute of Biochemistry · +8 more institutions
Abstract
To understand biological processes, it is necessary to reveal the molecular heterogeneity of cells by gaining access to the location and interaction of all biomolecules. Significant advances were achieved by super-resolution microscopy, but such methods are still far from reaching the multiplexing capacity of proteomics. Here, we introduce secondary label-based unlimited multiplexed DNA-PAINT (SUM-PAINT), a high-throughput imaging method that is capable of achieving virtually unlimited multiplexing at better than 15 nm resolution. Using SUM-PAINT, we generated 30-plex single-molecule resolved datasets in neurons and adapted omics-inspired analysis for data exploration. This allowed us to reveal the complexity…
Citation impact
- FWCI
- 81.55
- Percentile
- 100%
- References
- 65
Authors
14- EMEduard M. Unterauer
Center for NanoScience, Max Planck Institute of Biochemistry, Ludwig-Maximilians-Universität München
- SSSayedali Shetab Boushehri
Technical University of Munich, Helmholtz Zentrum München, Roche Pharma AG (Germany)
- KJKristina Jevdokimenko
Universitätsmedizin Göttingen, University of Göttingen
- LALuciano A. Masullo
Max Planck Institute of Biochemistry
- MGMahipal Ganji
Max Planck Institute of Biochemistry, Indian Institute of Science Bangalore
Topics & keywords
- Proteomics
- Biology
- Computational biology
- Workflow
- Multiplexing
- Resolution (logic)
- Computer science
- Artificial intelligence
Funding
- FHF. Hoffmann-La Roche
- MMax-Planck-Förderstiftung
- ECEuropean CommissionAwards: 101003275, 101065980, 796606, 866411
- DFDeutsche ForschungsgemeinschaftAwards: SFB1286, FO 1342/1-3
- BFBundesministerium für Bildung und ForschungAward: 13N15990
- MMax-Planck-Gesellschaft
- BFBundesministerium für Bildung, Wissenschaft, Forschung und Technologie
- IMInternational Max Planck Research School for Advanced Methods in Process and Systems Engineering
- HEH2020 European Research Council