Evidence map›Paper›PMID 23638792›Full record

ArticleAnalytical chemistry2013

Neutron encoded labeling for peptide identification.

Christopher M Rose, Anna E Merrill, Derek J Bailey, Alexander S Hebert, Michael S Westphall, Joshua J Coon

Abstract read
In one paragraph

Article in Analytical chemistry, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
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  7. Article
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  9. Review
  10. Article
  11. Article
  12. Article
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  14. Review
  15. Peptide dimethylation: fragmentation control via distancing the dimethylamino group.Journal of the American Society for Mass Spectrometry · 2014
    Article
  16. Article
  17. Article
  18. Article
  19. 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

6 authors.

Christopher M RoseDepartment of Chemistry, University of Wisconsin, Madison, Wisconsin 53706, United States.
Anna E Merrill
Derek J Bailey
Alexander S Hebert
Michael S Westphall
Joshua J Coon

Funding

Institutional Training in the Genomic SciencesT32HG002760 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Qiongshi Lu · 2003 to 2026
$17.7M
Chemistry-Biology Interface Training ProgramT32GM008505 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI BLACKWELL, HELEN E. · 1993 to 2023
$9.8M
Sequential Ion/Ion Reactions for Large Peptide and Whole Protein CharacterizationR01GM080148 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI COON, JOSHUA J · 2007 to 2015
$3.0M
NHGRI NIH HHS 5T32HG002760NHGRI NIH HHS T32 HG002760NIGMS NIH HHS R01 GM080148NIGMS NIH HHS T32 GM008505NIGMS NIH HHS T32GM008505
6 · The paper itself

Abstract

Metabolic labeling of cells using heavy amino acids is most commonly used for relative quantitation; however, partner mass shifts also detail the number of heavy amino acids contained within the precursor species. Here, we use a recently developed metabolic labeling technique, NeuCode (neutron encoding) stable isotope labeling with amino acids in cell culture (SILAC), which produces precursor partners spaced ~40 mDa apart to enable amino acid counting. We implement large scale counting of amino acids through a program, "Amino Acid Counter", which determines the most likely combination of amino acids within a precursor based on NeuCode SILAC partner spacing and filters candidate peptide sequences during a database search using this information. Counting the number of lysine residues for precursors selected for MS/MS decreases the median number of candidate sequences from 44 to 14 as compared to an accurate mass search alone (20 ppm). Furthermore, the ability to co-isolate and fragment NeuCode SILAC partners enables counting of lysines in product ions, and when the information is used, the median number of candidates is reduced to 7. We then demonstrate counting leucine in addition to lysine results in a 6-fold decrease in search space, 43 to 7, when compared to an accurate mass search. We use this scheme to analyze a nanoLC-MS/MS experiment and demonstrate that accurate mass plus lysine and leucine counting reduces the number of candidate sequences to one for ~20% of all precursors selected, demonstrating an ability to identify precursors without MS/MS analysis.

Indexed as

NeutronsAmino Acid SequenceIsotope LabelingLeucineLysineMass SpectrometryPeptidesSaccharomyces cerevisiae ProteinsLeucineLysinePeptidesSaccharomyces cerevisiae Proteins

Identifiers

PMID23638792
PMCPMC3827945

What OpenQuestion holds

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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.