Evidence map›Paper›PMID 28471460›Full record

ArticleNature protocols2017

Using hyperLOPIT to perform high-resolution mapping of the spatial proteome.

Claire M Mulvey, Lisa M Breckels, Aikaterini Geladaki, Nina Kočevar Britovšek, Daniel J H Nightingale, Andy Christoforou, Mohamed Elzek, Michael J Deery, Laurent Gatto, Kathryn S Lilley

Abstract read
PubMed Publisher
In one paragraph

Article in Nature protocols, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
84citing papers in PubMed, 1 pooled it
7.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

84 citing papers in PubMed, 1 synthesis or guideline pooled it, 144 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Subcellular localization as a driver of protein function.Nature reviews. Molecular cell biology · 2026
    Review
  4. Mass spectrometry proteomics for studying mitostasis.Protein science : a publication of the Protein Society · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Spatial Proteomics Using S4P.Bio-protocol · 2026
    Article
  10. Article
  11. Review
  12. Review
  13. Euglena gracilis Subcellular Fractionation.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  14. Review
  15. Article
  16. Odd-Chain Dicarboxylic Acid Feeding Produces a Glutaric Aciduria Type 1-Like Metabolic Signature in Mice.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2025
    Article
  17. Article
  18. Article
  19. Article
  20. Article

24 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Claire M MulveyCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-2989-2052
Lisa M BreckelsCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
Aikaterini GeladakiCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
Nina Kočevar BritovšekCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
Daniel J H NightingaleCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
Andy ChristoforouCelgene Institute for Translational Research Europe (CITRE), Seville, Spain.
Mohamed ElzekCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
Michael J DeeryCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.
Laurent GattoCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-1520-2268
Kathryn S LilleyCambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0003-0594-6543
University of Cambridge · GB

Funding

Biotechnology and Biological Sciences Research Council BB/L002817/1Wellcome Trust 110170/Z/15/Z
6 · The paper itself

Abstract

The organization of eukaryotic cells into distinct subcompartments is vital for all functional processes, and aberrant protein localization is a hallmark of many diseases. Microscopy methods, although powerful, are usually low-throughput and dependent on the availability of fluorescent fusion proteins or highly specific and sensitive antibodies. One method that provides a global picture of the cell is localization of organelle proteins by isotope tagging (LOPIT), which combines biochemical cell fractionation using density gradient ultracentrifugation with multiplexed quantitative proteomics mass spectrometry, allowing simultaneous determination of the steady-state distribution of hundreds of proteins within organelles. Proteins are assigned to organelles based on the similarity of their gradient distribution to those of well-annotated organelle marker proteins. We have substantially re-developed our original LOPIT protocol (published by Nature Protocols in 2006) to enable the subcellular localization of thousands of proteins per experiment (hyperLOPIT), including spatial resolution at the suborganelle and large protein complex level. This Protocol Extension article integrates all elements of the hyperLOPIT pipeline, including an additional enrichment strategy for chromatin, extended multiplexing capacity of isobaric mass tags, state-of-the-art mass spectrometry methods and multivariate machine-learning approaches for analysis of spatial proteomics data. We have also created an open-source infrastructure to support analysis of quantitative mass-spectrometry-based spatial proteomics data (http://bioconductor.org/packages/pRoloc) and an accompanying interactive visualization framework (http://www. bioconductor.org/packages/pRolocGUI). The procedure we outline here is applicable to any cell culture system and requires ∼1 week to complete sample preparation steps, ∼2 d for mass spectrometry data acquisition and 1-2 d for data analysis and downstream informatics.

Indexed as

Spatial AnalysisCell FractionationCentrifugation, Density GradientEukaryotic CellsMass SpectrometryProteomeProteomicsProteome

Identifiers

PMID28471460
OpenAlexW2611725166

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.