Evidence map›Paper›PMID 29521506›Full record

ArticleJournal of proteome research2018

Systematic Analysis of Fatty Acids in Human Cells with a Multiplexed Isobaric Tag (TMT)-Based Method.

Fangxu Sun, Alexander A Choi, Ronghu Wu

Abstract read
In one paragraph

Article in Journal of proteome research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

12 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. 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

3 authors at 1 institution in 1 country.

Fangxu SunSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.
Alexander A ChoiSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.
Ronghu WuSchool of Chemistry and Biochemistry and the Petit Institute for Bioengineering and Bioscience , Georgia Institute of Technology , Atlanta , Georgia 30332 , United States.ORCID 0000-0001-9493-9462
Georgia Institute of Technology · US

Funding

Effective MS-Based Methods for Unraveling Cell Surface Protein InteractionsR01GM118803 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI WU, RONGHU · 2017 to 2024
$2.4M
NIGMS NIH HHS R01 GM118803
6 · The paper itself

Abstract

Fatty acids (FAs) are essential components in cells and are involved in many cellular activities. Abnormal FA metabolism has been reported to be related to human diseases such as cancer and cardiovascular diseases. Identification and quantification of FAs provide insights into their functions in biological systems, but it is very challenging to analyze them due to their structures and properties. In this work, we developed a novel method by integrating FAs tagged with stable isotope labeled aminoxy tandem mass tags (aminoxyTMTs) and mass spectrometric analysis in the positive mode. On the basis of their structures, the aminoxyTMT reagents reacted with the carboxylic acid group of the FAs, resulting in an amine group with high proton affinity covalently attached to the analytes. This enabled the analysis of FAs under the positive electrospray ionization-mass spectrometry (ESI-MS) mode, which is normally more popular and sensitive compared to the negative mode. More importantly, the multiplexed TMT tags allowed us to quantify FAs from several samples simultaneously, which increased the experimental throughput and quantification accuracy. FAs extracted from three types of breast cells, i.e., MCF 10A (normal), MCF7 (minimally invasive) and MDA-MB-231 (highly invasive) cells, were labeled with the six-plexed aminoxyTMTs and quantified by LC-MS/MS. The results demonstrated that the abundances of some FAs, such as C22:5 and C20:3, were markedly increased in MCF7 and MDA-MB-231 cancer cells compared to normal MCF 10A cells. For the first time, aminoxyTMT reagents were exploited to label FAs for their identification and quantification in complex biological samples in the positive MS mode. The current method enabled us to confidently identify FAs and to accurately quantify them from several samples simultaneously. Because this method does not have sample restrictions, it can be extensively applied for biological and biomedical research.

Indexed as

Breast NeoplasmsCell Line, TumorChromatography, LiquidFatty AcidsHumansIsotope LabelingMetabolomicsMethodsSpectrometry, Mass, Electrospray IonizationTandem Mass SpectrometryFatty AcidsaminoxyTMTcancer cellsfatty acidsidentification and quantificationLC−MS/MS

Identifiers

PMID29521506
PMCPMC5937127
OpenAlexW2793808545

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.