Evidence map›Paper›PMID 28119711›Full record

ArticleFrontiers in plant science2016

Comprehensive Proteomic Profiling of Wheat Gluten Using a Combination of Data-Independent and Data-Dependent Acquisition.

Sophie N L Bromilow, Lee A Gethings, James I Langridge, Peter R Shewry, Michael Buckley, Michael J Bromley, E N Clare Mills

Abstract read
In one paragraph

Article in Frontiers in plant science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Gluten-degrading bacteria: availability and applications.Applied microbiology and biotechnology · 2021
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. What Is Gluten-Why Is It Special?Frontiers in nutrition · 2019
    Review
  14. Review
  15. Article
  16. Article
  17. 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

7 authors.

Sophie N L BromilowFaculty of Biology, Medicine and Health, Infection, Immunity and Respiratory Medicine, Manchester Academic Health Sciences Centre, Manchester Institute of Biotechnology, University of Manchester Manchester, UK.
Lee A GethingsWaters Corporation Wilmslow, UK.
James I LangridgeWaters Corporation Wilmslow, UK.
Peter R ShewryRothamsted Research Harpenden, UK.
Michael BuckleySchool of Chemistry, Manchester Institute of Biotechnology, University of Manchester Manchester, UK.
Michael J BromleySynergy Health Hebden Bridge, UK.
E N Clare MillsFaculty of Biology, Medicine and Health, Infection, Immunity and Respiratory Medicine, Manchester Academic Health Sciences Centre, Manchester Institute of Biotechnology, University of Manchester Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wheat is the most important food crop in the world, the unique physiochemical properties of wheat gluten enabling a diverse range of food products to be manufactured. However, genetic and environmental factors affect the technological properties of gluten in unpredictable ways. Although newer proteomic methods have the potential to offer much greater levels of information, it is the older gel-based methods that remain most commonly used to identify compositional differences responsible for the variation in gluten functionality, in part due to the nature of their primary sequences. A combination of platforms were investigated for comprehensive gluten profiling: a QTOF with a data independent schema, which incorporated ion mobility (DIA-IM-MS) and a data dependent acquisition (DDA) workflow using a linear ion trap quadrupole (LTQ) instrument. In conjunction with a manually curated gluten sequence database a total of 2736 gluten peptides were identified with only 157 peptides identified by both platforms. These data showed 127 and 63 gluten protein accessions to be inferred with a minimum of one and three unique peptides respectively. Of the 63 rigorously identified proteins, 26 were gliadin species (4 ω-, 14 α-, and 8 γ-gliadins) and 37 glutenins (including 29 LMW glutenin and 8 HMW glutenins). Of the HMW glutenins, three were 1Dx type and five were 1Bx type illustrating the challenge of unambiguous identification of highly polymorphic proteins without cultivar specific gene sequences. The capacity of the platforms to sequence longer peptides was crucial to achieving the number of identifications, the combination of QTOF-LTQ technology being more important than extraction method to obtain a comprehensive profile. Widespread glutamine deamidation, a post-translational modification, was observed adding complexity to an already highly polymorphic mixture of proteins, with numerous insertions, deletions and substitutions. The data shown is the most comprehensive and detailed proteomic profile of gluten to date.

Indexed as

chymotrypsincoeliac diseaseglutenLTQ-Orbitrapmass spectrometryplant proteomicsproteomicsQTOF-MS/MS

Identifiers

PMID28119711
PMCPMC5223596

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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.