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Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics
by
Smith, Tom S.
, Vennard, Owen L.
, Geladaki, Aikaterini
, Kočevar Britovšek, Nina
, Breckels, Lisa M.
, Mulvey, Claire M.
, Lilley, Kathryn S.
, Crook, Oliver M.
, Gatto, Laurent
in
631/1647/2067
/ 631/45/475
/ 631/80/642
/ 82/16
/ 82/58
/ Cell Fractionation
/ Cell Line, Tumor
/ Centrifugation
/ Centrifugation, Density Gradient - methods
/ Conformation
/ Crystal structure
/ Depolymerization
/ Dismantling
/ Enzymes
/ Experiments
/ Fractionation
/ Humanities and Social Sciences
/ Humans
/ Kinesin
/ Labeling
/ Localization
/ Machine learning
/ Mass Spectrometry - methods
/ Methods
/ Motor task performance
/ multidisciplinary
/ Proteins
/ Proteome - analysis
/ Proteomics
/ Proteomics - methods
/ Science
/ Science (multidisciplinary)
/ Spatial Analysis
/ Tubulin
/ Ultracentrifugation
2019
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Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics
by
Smith, Tom S.
, Vennard, Owen L.
, Geladaki, Aikaterini
, Kočevar Britovšek, Nina
, Breckels, Lisa M.
, Mulvey, Claire M.
, Lilley, Kathryn S.
, Crook, Oliver M.
, Gatto, Laurent
in
631/1647/2067
/ 631/45/475
/ 631/80/642
/ 82/16
/ 82/58
/ Cell Fractionation
/ Cell Line, Tumor
/ Centrifugation
/ Centrifugation, Density Gradient - methods
/ Conformation
/ Crystal structure
/ Depolymerization
/ Dismantling
/ Enzymes
/ Experiments
/ Fractionation
/ Humanities and Social Sciences
/ Humans
/ Kinesin
/ Labeling
/ Localization
/ Machine learning
/ Mass Spectrometry - methods
/ Methods
/ Motor task performance
/ multidisciplinary
/ Proteins
/ Proteome - analysis
/ Proteomics
/ Proteomics - methods
/ Science
/ Science (multidisciplinary)
/ Spatial Analysis
/ Tubulin
/ Ultracentrifugation
2019
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Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics
by
Smith, Tom S.
, Vennard, Owen L.
, Geladaki, Aikaterini
, Kočevar Britovšek, Nina
, Breckels, Lisa M.
, Mulvey, Claire M.
, Lilley, Kathryn S.
, Crook, Oliver M.
, Gatto, Laurent
in
631/1647/2067
/ 631/45/475
/ 631/80/642
/ 82/16
/ 82/58
/ Cell Fractionation
/ Cell Line, Tumor
/ Centrifugation
/ Centrifugation, Density Gradient - methods
/ Conformation
/ Crystal structure
/ Depolymerization
/ Dismantling
/ Enzymes
/ Experiments
/ Fractionation
/ Humanities and Social Sciences
/ Humans
/ Kinesin
/ Labeling
/ Localization
/ Machine learning
/ Mass Spectrometry - methods
/ Methods
/ Motor task performance
/ multidisciplinary
/ Proteins
/ Proteome - analysis
/ Proteomics
/ Proteomics - methods
/ Science
/ Science (multidisciplinary)
/ Spatial Analysis
/ Tubulin
/ Ultracentrifugation
2019
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Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics
Journal Article
Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics
2019
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Overview
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.
Spatial proteomics allows studying cellular protein localisations at system-wide scale. Here, the authors show that combining the previously developed hyperLOPIT method with differential centrifugation yields protein localisation maps at suborganellar resolution while reducing analysis time and input material.
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