Evidence map›Paper›PMID 28669031›Full record

ReviewCellular and molecular life sciences : CMLS2017

Experimental design and reporting standards for metabolomics studies of mammalian cell lines.

Sarah Hayton, Garth L Maker, Ian Mullaney, Robert D Trengove

Abstract readReview
In one paragraph

Review in Cellular and molecular life sciences : CMLS, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Paclitaxel resistance-associated metabolic events in ovarian cancer cells.Metabolomics : Official journal of the Metabolomic Society · 2025
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  5. Metabolomics in asthma: A platform for discovery.Molecular aspects of medicine · 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

4 authors.

Sarah HaytonSeparation Sciences and Metabolomics Laboratories, Murdoch University, Perth, WA, Australia.
Garth L MakerSeparation Sciences and Metabolomics Laboratories, Murdoch University, Perth, WA, Australia. g.maker@murdoch.edu.au.
Ian MullaneySchool of Veterinary and Life Sciences, Murdoch University, 90 South St, Murdoch, WA, 6150, Australia.
Robert D TrengoveSeparation Sciences and Metabolomics Laboratories, Murdoch University, Perth, WA, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Indexed as

AnimalsCell LineHumansMammalsMetabolomeMetabolomicsResearch DesignCell cultureExperimental designIn vitroMetabolomicsMethodsStandardisation

Identifiers

PMID28669031
PMCPMC11107723

What OpenQuestion holds

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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.