Evidence map›Paper›PMID 30638535›Full record

ArticleMethods in enzymology2019

Identification of Unknown Metabolomics Mixture Compounds by Combining NMR, MS, and Cheminformatics.

Abigail Leggett, Cheng Wang, Da-Wei Li, Arpad Somogyi, Lei Bruschweiler-Li, Rafael Brüschweiler

Abstract read
In one paragraph

Article in Methods in enzymology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. NMR Studies on Protein-Ligand Interactions.International journal of molecular sciences · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. Applications of chromatographic methods in metabolomics: A review.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2024
    Review
  6. Multiplatform untargeted metabolomics.Magnetic resonance in chemistry : MRC · 2023
    Review
  7. Practical Aspects of NMR-Based Metabolomics.Handbook of experimental pharmacology · 2023
    Article
  8. Advances in Microbial NMR Metabolomics.Advances in experimental medicine and biology · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Cadaverine Is a Switch in the Lysine Degradation Pathway inFrontiers in cellular and infection microbiology · 2022
    Article
  13. Review
  14. Review
  15. NMR-TS: de novo molecule identification from NMR spectra.Science and technology of advanced materials · 2020
    Article
  16. 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.

Abigail LeggettOhio State Biochemistry Program, The Ohio State University, Columbus, OH, United States.
Cheng WangDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, United States.
Da-Wei LiCampus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, OH, United States.
Arpad SomogyiCampus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, OH, United States.
Lei Bruschweiler-LiCampus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, OH, United States.
Rafael BrüschweilerOhio State Biochemistry Program, The Ohio State University, Columbus, OH, United States; Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, United States; Campus Chemical Instrument Center (CCIC), The Ohio State University, Columbus, OH, United States; Department of Biological Chemistry and Pharmacology, The Ohio State University, Columbus, OH, United States. Electronic address: bruschweiler.1@osu.edu.

Funding

Southeast Resource Center for Integrated Metabolomics (SECIM)U24DK097209 · NIDDK · UNIVERSITY OF FLORIDA · PI EDISON, ARTHUR S, YOST, RICHARD A. · 2013 to 2017
$9.2M
New hybrid methods for the improved and integrated analysis of complex metabolomics mixturesR01GM066041 · NIGMS · OHIO STATE UNIVERSITY · PI BRUSCHWEILER, RAFAEL · 2002 to 2019
$3.3M
NIDDK NIH HHS U24 DK097209NIGMS NIH HHS R01 GM066041
6 · The paper itself

Abstract

Metabolomics aims at the comprehensive identification of metabolites in complex mixtures to characterize the state of a biological system and elucidate their roles in biochemical pathways. For many biological samples, a large number of spectral features observed by NMR spectroscopy and mass spectrometry (MS) belong to unknowns, i.e., these features do not belong to metabolites that have been previously identified, and their spectral information is not available in databases. By combining NMR, MS, and combinatorial cheminformatics, the analysis of unknowns can be pursued in complex mixtures requiring minimal purification. This chapter describes the SUMMIT MS/NMR approach covering sample preparation, NMR and MS data collection and processing, and the identification of likely unknowns with the use of cheminformatics tools and the prediction of NMR spectral properties.

Indexed as

Computational BiologyMagnetic Resonance SpectroscopyMass SpectrometryMetabolomics3D NMR HSQC-TOCSYCOLMAR databaseFT-ICR MSMetabolite structure elucidationMetabolomicsNMR-MS hybrid approachSUMMIT MS/NMRUnknown metabolite identificationUnknowns

Identifiers

PMID30638535
PMCPMC6953983

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.