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Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics

Author

Listed:
  • Aikaterini Geladaki

    (University of Cambridge
    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
    Cambridge Institute for Public Health)

  • Laurent Gatto

    (University of Cambridge
    de Duve Institute, UC Louvain)

  • Kathryn S. Lilley

    (University of Cambridge)

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.

Suggested Citation

  • Aikaterini Geladaki & Nina Kočevar Britovšek & Lisa M. Breckels & Tom S. Smith & Owen L. Vennard & Claire M. Mulvey & Oliver M. Crook & Laurent Gatto & Kathryn S. Lilley, 2019. "Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics," Nature Communications, Nature, vol. 10(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-018-08191-w
    DOI: 10.1038/s41467-018-08191-w
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    Cited by:

    1. Oliver M Crook & Aikaterini Geladaki & Daniel J H Nightingale & Owen L Vennard & Kathryn S Lilley & Laurent Gatto & Paul D W Kirk, 2020. "A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection," PLOS Computational Biology, Public Library of Science, vol. 16(11), pages 1-21, November.
    2. Jordan Currie & Vyshnavi Manda & Sean K. Robinson & Celine Lai & Vertica Agnihotri & Veronica Hidalgo & R. W. Ludwig & Kai Zhang & Jay Pavelka & Zhao V. Wang & June-Wha Rhee & Maggie P. Y. Lam & Edwar, 2024. "Simultaneous proteome localization and turnover analysis reveals spatiotemporal features of protein homeostasis disruptions," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    3. Yudong Gao & Daichi Shonai & Matthew Trn & Jieqing Zhao & Erik J. Soderblom & S. Alexandra Garcia-Moreno & Charles A. Gersbach & William C. Wetsel & Geraldine Dawson & Dmitry Velmeshev & Yong-hui Jian, 2024. "Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    4. Thao Nguyen & Eli J. Costa & Tim Deibert & Jose Reyes & Felix C. Keber & Miroslav Tomschik & Michael Stadlmeier & Meera Gupta & Chirag K. Kumar & Edward R. Cruz & Amanda Amodeo & Jesse C. Gatlin & Mar, 2022. "Differential nuclear import sets the timing of protein access to the embryonic genome," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    5. Ying Zhu & Kerem Can Akkaya & Julia Ruta & Nanako Yokoyama & Cong Wang & Max Ruwolt & Diogo Borges Lima & Martin Lehmann & Fan Liu, 2024. "Cross-link assisted spatial proteomics to map sub-organelle proteomes and membrane protein topologies," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    6. Michael A. Skinnider & Mopelola O. Akinlaja & Leonard J. Foster, 2023. "Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    7. Oliver M. Crook & Colin T. R. Davies & Lisa M. Breckels & Josie A. Christopher & Laurent Gatto & Paul D. W. Kirk & Kathryn S. Lilley, 2022. "Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
    8. Nicola M. Moloney & Konstantin Barylyuk & Eelco Tromer & Oliver M. Crook & Lisa M. Breckels & Kathryn S. Lilley & Ross F. Waller & Paula MacGregor, 2023. "Mapping diversity in African trypanosomes using high resolution spatial proteomics," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    9. Ana Martinez-Val & Dorte B. Bekker-Jensen & Sophia Steigerwald & Claire Koenig & Ole Østergaard & Adi Mehta & Trung Tran & Krzysztof Sikorski & Estefanía Torres-Vega & Ewa Kwasniewicz & Sólveig Hlín B, 2021. "Spatial-proteomics reveals phospho-signaling dynamics at subcellular resolution," Nature Communications, Nature, vol. 12(1), pages 1-17, December.

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