Evidence map›Paper›PMID 27099342›Full record

ArticleMolecular & cellular proteomics : MCP2016

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions.

Maxim Shatsky, Ming Dong, Haichuan Liu, Lee Lisheng Yang, Megan Choi, Mary E Singer, Jil T Geller, Susan J Fisher, Steven C Hall, Terry C Hazen and 6 more

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. eLife · 2022
    Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
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

16 authors.

Maxim ShatskyFrom the ‡Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
Ming Dong§Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
Haichuan Liu¶OB/GYN Department, University of California San Francisco-Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, California 94143;
Lee Lisheng Yang‖Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
Megan Choi§Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
Mary E Singer**Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
Jil T Geller**Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
Susan J Fisher¶OB/GYN Department, University of California San Francisco-Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, California 94143;
Steven C Hall¶OB/GYN Department, University of California San Francisco-Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, California 94143;
Terry C Hazen‡‡Department of Civil and Environmental Engineering, University of Tennessee, Knoxville, Tennessee 37996; §§Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831;
Steven E BrennerFrom the ‡Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720; ¶¶Department of Plant and Microbial Biology, University of California, Berkeley, California 94720;
Gareth Butland‖‖Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720.
Jian Jin‖Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720;
H Ewa Witkowska¶OB/GYN Department, University of California San Francisco-Sandler-Moore Mass Spectrometry Core Facility, University of California, San Francisco, California 94143;
John-Marc ChandoniaFrom the ‡Physical Biosciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720; mdbiggin@lbl.gov jmchandonia@lbl.gov.
Mark D Biggin§Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720; mdbiggin@lbl.gov jmchandonia@lbl.gov.

Funding

Translational InformaticsP30CA082103 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer Leigh Clarke · 1999 to 2026
$209.7M
NCI NIH HHS P30 CA082103
6 · The paper itself

Abstract

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification of endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.

Indexed as

Bacterial ProteinsChromatography, AffinityDesulfovibrio vulgarisEscherichia coliMass SpectrometryProtein Interaction MappingProtein Interaction MapsProteomicsBacterial Proteins

Identifiers

PMID27099342
PMCPMC5083090

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.