Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics.
Kočevar Britovšek, Nina
Breckels, Lisa M
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Geladaki, A., Kočevar Britovšek, N., Breckels, L. M., Smith, T., Vennard, O. L., Mulvey, C. M., Crook, O., et al. (2019). Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics.. Nature communications, 10 (1), 331. https://doi.org/10.1038/s41467-018-08191-w
The study of protein localisation has greatly benefited from high-throughput methods utilising cellular fractionation and proteomic profiling. Hyperplexed Localisation of Organelle Proteins by Isotope Tagging (hyperLOPIT) is a well-established method in this area. It achieves high-resolution separation of organelles and subcellular compartments but is relatively time- and resource-intensive. As a simpler alternative, we here develop Localisation of Organelle Proteins by Isotope Tagging after Differential ultraCentrifugation (LOPIT-DC) and compare this method to the density gradient-based hyperLOPIT approach. We confirm that high-resolution maps can be obtained using differential centrifugation down to the suborganellar and protein complex level. HyperLOPIT and LOPIT-DC yield highly similar results, facilitating the identification of isoform-specific localisations and high-confidence localisation assignment for proteins in suborganellar structures, protein complexes and signalling pathways. By combining both approaches, we present a comprehensive high-resolution dataset of human protein localisations and deliver a flexible set of protocols for subcellular proteomics.
Cell Line, Tumor, Humans, Proteome, Ultracentrifugation, Centrifugation, Density Gradient, Cell Fractionation, Proteomics, Mass Spectrometry, Spatial Analysis
Wellcome Trust BBSRC
WELLCOME TRUST (110170/Z/15/Z)
WELLCOME TRUST (108467/Z/15/Z)
External DOI: https://doi.org/10.1038/s41467-018-08191-w
This record's URL: https://www.repository.cam.ac.uk/handle/1810/288535
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/