Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics

Aikaterini Geladaki, Nina Kočevar Britovšek, Lisa M. Breckels, Tom S. Smith, Owen L. Vennard, Claire M. Mulvey, Oliver M. Crook, Laurent Gatto and Kathryn S. Lilley ()
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Aikaterini Geladaki: University of Cambridge
Nina Kočevar Britovšek: University of Cambridge
Lisa M. Breckels: University of Cambridge
Tom S. Smith: University of Cambridge
Owen L. Vennard: University of Cambridge
Claire M. Mulvey: University of Cambridge
Oliver M. Crook: University of Cambridge
Laurent Gatto: University of Cambridge
Kathryn S. Lilley: University of Cambridge

Nature Communications, 2019, vol. 10, issue 1, 1-15

Abstract: Abstract 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.

Date: 2019
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DOI: 10.1038/s41467-018-08191-w

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