Evidence map›Paper›PMID 31804057›Full record

ArticleAnalytical chemistry2020

Dose-Response Metabolomics To Understand Biochemical Mechanisms and Off-Target Drug Effects with the TOXcms Software.

Cong-Hui Yao, Lingjue Wang, Ethan Stancliffe, Miriam Sindelar, Kevin Cho, Weitong Yin, Yahui Wang, Gary J Patti

Abstract read
In one paragraph

Article in Analytical chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  20. Deciphering the mechanism of action of antitubercular compounds with metabolomics.Computational and structural biotechnology journal · 2021
    Review
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

8 authors.

Cong-Hui Yao
Lingjue Wang
Miriam Sindelar
Kevin Cho
Weitong YinDepartment of Mathematics and Statistics , University of North Carolina at Charlotte , Charlotte , North Carolina 28223 , United States.
Yahui Wang

Funding

Developing Metabolomic Technologies to Advance Environmental Exposure AnalysisR35ES028365 · NIEHS · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2017 to 2024
$5.9M
A COMPREHENSIVE RESOURCE FOR HIGH-THROUGHPUT PROFILING OF WORM AND ZEBRAFISH METABOLOMESR24OD024624 · OD · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2018 to 2021
$4.0M
A Comprehensive Platform for High-Throughput Profiling of the Human Reference MetabolomeU01CA235482 · NCI · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2018 to 2021
$1.8M
NCI NIH HHS U01 CA235482NIEHS NIH HHS R35 ES028365NIH HHS R24 OD024624
6 · The paper itself

Abstract

Small-molecule drugs and toxicants commonly interact with more than a single protein target, each of which may have unique effects on cellular phenotype. Although untargeted metabolomics is often applied to understand the mode of action of these chemicals, simple pairwise comparisons of treated and untreated samples are insufficient to resolve the effects of disrupting two or more independent protein targets. Here, we introduce a workflow for dose-response metabolomics to evaluate chemicals that potentially affect multiple proteins with different potencies. Our approach relies on treating samples with various concentrations of compound prior to analysis with mass spectrometry-based metabolomics. Data are then processed with software we developed called TOXcms, which statistically evaluates dose-response trends for each metabolomic signal according to user-defined tolerances and subsequently groups those that follow the same pattern. Although TOXcms was built upon the XCMS framework, it is compatible with any metabolomic data-processing software. Additionally, to enable correlation of dose responses beyond those that can be measured by metabolomics, TOXcms also accepts data from respirometry, cell death assays, other omic platforms, etc. In this work, we primarily focus on applying dose-response metabolomics to find off-target effects of drugs. Using metformin and etomoxir as examples, we demonstrate that each group of dose-response patterns identified by TOXcms signifies a metabolic response to a different protein target with a unique drug binding affinity. TOXcms is freely available on our laboratory website at http://pattilab.wustl.edu/software/toxcms .

Indexed as

AlgorithmsCarnitine O-PalmitoyltransferaseCell Line, TumorDose-Response Relationship, DrugEpoxy CompoundsGene Knockdown TechniquesHEK293 CellsHumansMetabolomicsMetforminRNA, Small InterferingRotenoneSoftwareCarnitine O-PalmitoyltransferaseCPT1A protein, humanEpoxy CompoundsetomoxirMetforminRNA, Small InterferingRotenone

Identifiers

PMID31804057
PMCPMC7354698

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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.