Evidence map›Paper›PMID 26837423›Full record

ArticleAnalytical chemistry2016

Bar Coding MS(2) Spectra for Metabolite Identification.

Jonathan L Spalding, Kevin Cho, Nathaniel G Mahieu, Igor Nikolskiy, Elizabeth M Llufrio, Stephen L Johnson, Gary J Patti

Abstract readLetter
In one paragraph

Article in Analytical chemistry, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. A robust, single-injection method for targeted, broad-spectrum plasma metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2017
    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.

Jonathan L SpaldingDepartment of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.
Kevin ChoDepartment of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.
Nathaniel G MahieuDepartment of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.
Igor NikolskiyDepartment of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.
Elizabeth M LlufrioDepartment of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.
Stephen L JohnsonDepartment of Genetics, Washington University School of Medicine , St. Louis, Missouri 63110, United States.
Gary J PattiDepartment of Chemistry, Washington University in St. Louis , St. Louis, Missouri 63130, United States.

Funding

DEVELOPING THE UNTARGETED METABOLOMIC WORKFLOW FOR HIGH-THROUGHPUT ANALYSESR01ES022181 · NIEHS · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2012 to 2016
$1.8M
CELL-SPECIFIC ISOTOPE LABELING TO TRACK INTERCELLULAR METABOLITE EXCHANGE IN CANCERR21CA191097 · NCI · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2015 to 2017
$663k
TISSUE IN SITU METABOLITE PROFILING IN ZEBRAFISHR21HD081531 · NICHD · WASHINGTON UNIVERSITY · PI JOHNSON, STEPHEN L · 2014 to 2015
$414k
NCI NIH HHS R21 CA191097NICHD NIH HHS R21 HD081531NIEHS NIH HHS R01 ES022181
6 · The paper itself

Abstract

Metabolite identifications are most frequently achieved in untargeted metabolomics by matching precursor mass and full, high-resolution MS(2) spectra to metabolite databases and standards. Here we considered an alternative approach for establishing metabolite identifications that does not rely on full, high-resolution MS(2) spectra. First, we select mass-to-charge regions containing the most informative metabolite fragments and designate them as bins. We then translate each metabolite fragmentation pattern into a binary code by assigning 1's to bins containing fragments and 0's to bins without fragments. With 20 bins, this binary-code system is capable of distinguishing 96% of the compounds in the METLIN MS(2) library. A major advantage of the approach is that it extends untargeted metabolomics to low-resolution triple quadrupole (QqQ) instruments, which are typically less expensive and more robust than other types of mass spectrometers. We demonstrate a method of acquiring MS(2) data in which the third quadrupole of a QqQ instrument cycles over 20 wide isolation windows (coinciding with the location and width of our bins) for each precursor mass selected by the first quadrupole. Operating the QqQ instrument in this mode yields diagnostic bar codes for each precursor mass that can be matched to the bar codes of metabolite standards. Furthermore, our data suggest that using low-resolution bar codes enables QqQ instruments to make MS(2)-based identifications in untargeted metabolomics with a specificity and sensitivity that is competitive to high-resolution time-of-flight technologies.

Indexed as

MetabolomeElectronic Data ProcessingLimit of DetectionMass SpectrometryMetabolomics

Identifiers

PMID26837423
PMCPMC4869618

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.