Evidence map›Paper›PMID 28546536›Full record

ArticleScientific reports2017

A sensitive mass spectrometry platform identifies metabolic changes of life history traits in C. elegans.

Arwen W Gao, Iliana A Chatzispyrou, Rashmi Kamble, Yasmine J Liu, Katharina Herzog, Reuben L Smith, Henk van Lenthe, Martin A T Vervaart, Arno van Cruchten, Angela C Luyf and 4 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

45 citing papers in PubMed, 79 citations in OpenAlex.

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  19. AFrontiers in microbiology · 2022
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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

14 authors at 1 institution in 1 country.

Arwen W GaoLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Iliana A ChatzispyrouLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Rashmi KambleLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Yasmine J LiuLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Katharina HerzogLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Reuben L SmithLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Henk van LentheLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Martin A T VervaartLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Arno van CruchtenLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Angela C LuyfDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Antoine van KampenDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.ORCID 0000-0003-1025-7232
Mia L Pras-RavesLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Frédéric M VazLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands.
Riekelt H HoutkooperLaboratory Genetic Metabolic Diseases, Academic Medical Center, 1105 AZ, Amsterdam, The Netherlands. r.h.houtkooper@amc.nl.ORCID 0000-0001-9961-0842
Amsterdam UMC Location University of Amsterdam · NL

Funding

Enhancing and expanding the CGC Strain CollectionP40OD010440 · OD · UNIVERSITY OF MINNESOTA · PI Ann E. Rougvie · 2012 to 2026
$7.5M
European Research Council 638290NIH HHS P40 OD010440
6 · The paper itself

Abstract

Abnormal nutrient metabolism is a hallmark of aging, and the underlying genetic and nutritional framework is rapidly being uncovered, particularly using C. elegans as a model. However, the direct metabolic consequences of perturbations in life history of C. elegans remain to be clarified. Based on recent advances in the metabolomics field, we optimized and validated a sensitive mass spectrometry (MS) platform for identification of major metabolite classes in worms and applied it to study age and diet related changes. Using this platform that allowed detection of over 600 metabolites in a sample of 2500 worms, we observed marked changes in fatty acids, amino acids and phospholipids during worm life history, which were independent from the germ-line. Worms underwent a striking shift in lipid metabolism after early adulthood that was at least partly controlled by the metabolic regulator AAK-2/AMPK. Most amino acids peaked during development, except aspartic acid and glycine, which accumulated in aged worms. Dietary intervention also influenced worm metabolite profiles and the regulation was highly specific depending on the metabolite class. Altogether, these MS-based methods are powerful tools to perform worm metabolomics for aging and metabolism-oriented studies.

Indexed as

Life History TraitsMetabolomeMetabolomicsAge FactorsAmino AcidsAnimalsCaenorhabditis elegansCaenorhabditis elegans ProteinsChromatography, High Pressure LiquidComputational BiologyDietFatty AcidsLipid MetabolismMass SpectrometryMutationPhosphorylationAmino AcidsCaenorhabditis elegans ProteinsFatty Acids

Identifiers

PMID28546536
PMCPMC5445081
OpenAlexW2615592869

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.