Evidence map›Paper›PMID 33159052›Full record

ArticleNature communications2020

Sub-nanoliter metabolomics via mass spectrometry to characterize volume-limited samples.

Yafeng Li, Marcos Bouza, Changsheng Wu, Hengyu Guo, Danning Huang, Gilad Doron, Johnna S Temenoff, Arlene A Stecenko, Zhong Lin Wang, Facundo M Fernández

Abstract readEvaluation Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  13. Machine learning-empoweredChemical science · 2023
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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

10 authors.

Yafeng LiSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Marcos BouzaSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Changsheng WuSchool of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Hengyu GuoSchool of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.ORCID 0000-0001-7133-4823
Danning HuangSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Gilad DoronW.H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.ORCID 0000-0002-3940-3574
Johnna S TemenoffW.H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.
Arlene A StecenkoEmory + Children's Center for Cystic Fibrosis and Airways Disease Research and Department of Pediatrics, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, GA, 30322, USA.
Zhong Lin WangSchool of Materials Science and Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.ORCID 0000-0002-5530-0380
Facundo M FernándezSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA, 30332, USA. facundo.fernandez@chemistry.gatech.edu.ORCID 0000-0002-0302-2534

Funding

Deep Ovarian Cancer MetabolomicsR01CA218664 · NCI · GEORGIA INSTITUTE OF TECHNOLOGY · PI Facundo Martin Fernandez, Jaeyeon Kim · 2018 to 2026
$4.3M
Portal for Open Computational Metabolomics Tools - Yr 4 U2C SupplementU2CES030167 · NIEHS · UNIVERSITY OF GEORGIA · PI SCHROEDER, FRANK CLEMENS · 2018 to 2021
$4.2M
Prevention of Cystic Fibrosis DiabetesR01FD003527 · FDA · EMORY UNIVERSITY · PI STECENKO, ARLENE A · 2009 to 2015
$908k
FDA HHS R01 FD003527NCI NIH HHS R01 CA218664NIEHS NIH HHS U2C ES030167
6 · The paper itself

Abstract

The human metabolome provides a window into the mechanisms and biomarkers of various diseases. However, because of limited availability, many sample types are still difficult to study by metabolomic analyses. Here, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter sample volumes. The approach consists of combining a customized metabolomics workflow with a pulsed MS ion generation method, known as triboelectric nanogenerator inductive nanoelectrospray ionization (TENGi nanoESI) MS. Samples tested with this approach include exhaled breath condensate collected from cystic fibrosis patients as well as in vitro-cultured human mesenchymal stromal cells. Both test samples are only available in minimum amounts. Experiments show that picoliter-volume spray pulses suffice to generate high-quality spectral fingerprints, which increase the information density produced per unit sample volume. This TENGi nanoESI strategy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analyses cannot be applied. Our method opens up avenues for future investigations into understanding metabolic changes caused by diseases or external stimuli.

Indexed as

BiomarkersCystic FibrosisHumansMass SpectrometryMesenchymal Stem CellsMetabolomicsBiomarkers

Identifiers

PMID33159052
PMCPMC7648103

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.