Evidence map›Paper›PMID 24895383›Full record

ArticleMolecular & cellular proteomics : MCP2014

Analytical utility of mass spectral binning in proteomic experiments by SPectral Immonium Ion Detection (SPIID).

Christian D Kelstrup, Christian Frese, Albert J R Heck, Jesper V Olsen, Michael L Nielsen

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Signature Fragment Ions of Biotinylated Peptides.Journal of the American Society for Mass Spectrometry · 2020
    Article
  6. Article
  7. Review
  8. Article
  9. Review
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

5 authors.

Christian D KelstrupFrom the ‡Department of Proteomics, The Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Faculty of Health Sciences, DK-2200 Copenhagen, Denmark;
Christian Frese§Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584CH Utrecht, The Netherlands.
Albert J R Heck§Biomolecular Mass Spectrometry and Proteomics Group, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, 3584CH Utrecht, The Netherlands.
Jesper V OlsenFrom the ‡Department of Proteomics, The Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Faculty of Health Sciences, DK-2200 Copenhagen, Denmark;
Michael L NielsenFrom the ‡Department of Proteomics, The Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Faculty of Health Sciences, DK-2200 Copenhagen, Denmark; michael.lund.nielsen@cpr.ku.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unambiguous identification of tandem mass spectra is a cornerstone in mass-spectrometry-based proteomics. As the study of post-translational modifications (PTMs) by means of shotgun proteomics progresses in depth and coverage, the ability to correctly identify PTM-bearing peptides is essential, increasing the demand for advanced data interpretation. Several PTMs are known to generate unique fragment ions during tandem mass spectrometry, the so-called diagnostic ions, which unequivocally identify a given mass spectrum as related to a specific PTM. Although such ions offer tremendous analytical advantages, algorithms to decipher MS/MS spectra for the presence of diagnostic ions in an unbiased manner are currently lacking. Here, we present a systematic spectral-pattern-based approach for the discovery of diagnostic ions and new fragmentation mechanisms in shotgun proteomics datasets. The developed software tool is designed to analyze large sets of high-resolution peptide fragmentation spectra independent of the fragmentation method, instrument type, or protease employed. To benchmark the software tool, we analyzed large higher-energy collisional activation dissociation datasets of samples containing phosphorylation, ubiquitylation, SUMOylation, formylation, and lysine acetylation. Using the developed software tool, we were able to identify known diagnostic ions by comparing histograms of modified and unmodified peptide spectra. Because the investigated tandem mass spectra data were acquired with high mass accuracy, unambiguous interpretation and determination of the chemical composition for the majority of detected fragment ions was feasible. Collectively we present a freely available software tool that allows for comprehensive and automatic analysis of analogous product ions in tandem mass spectra and systematic mapping of fragmentation mechanisms related to common amino acids.

Indexed as

AlgorithmsDatabases, ProteinIonsPeptidesProtein Processing, Post-TranslationalProteomicsSoftwareTandem Mass SpectrometryIonsPeptides

Identifiers

PMID24895383
PMCPMC4125726

What OpenQuestion holds

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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.