Evidence map›Paper›PMID 35000038›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2022

Integrating in vitro metabolomics with a 96-well high-throughput screening platform.

Julia M Malinowska, Taina Palosaari, Jukka Sund, Donatella Carpi, Mounir Bouhifd, Ralf J M Weber, Maurice Whelan, Mark R Viant

Open access · hybridAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

16 citing papers in PubMed, 25 citations in OpenAlex.

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  13. The use of NAMs and omics data in risk assessment.EFSA journal. European Food Safety Authority · 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

8 authors at 3 institutions in 3 countries.

Julia M MalinowskaSchool of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK.ORCID 0000-0001-6565-2980
Taina PalosaariEuropean Commission, Joint Research Centre (JRC), 21027, Ispra, Italy.
Jukka SundEuropean Commission, Joint Research Centre (JRC), 21027, Ispra, Italy.
Donatella CarpiEuropean Commission, Joint Research Centre (JRC), 21027, Ispra, Italy.
Mounir BouhifdEuropean Commission, Joint Research Centre (JRC), 21027, Ispra, Italy.
Ralf J M WeberSchool of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK.
Maurice WhelanEuropean Commission, Joint Research Centre (JRC), 21027, Ispra, Italy.
Mark R ViantSchool of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK. m.viant@bham.ac.uk.
Joint Research Centre · ITUniversity of Birmingham · GBFinnish Safety and Chemicals Agency · FI

Funding

Medical Research Council MR/M009157/1
6 · The paper itself

Abstract

introductionHigh-throughput screening (HTS) is emerging as an approach to support decision-making in chemical safety assessments. In parallel, in vitro metabolomics is a promising approach that can help accelerate the transition from animal models to high-throughput cell-based models in toxicity testing.

objectiveIn this study we establish and evaluate a high-throughput metabolomics workflow that is compatible with a 96-well HTS platform employing 50,000 hepatocytes of HepaRG per well.

methodsLow biomass cell samples were extracted for metabolomics analyses using a newly established semi-automated protocol, and the intracellular metabolites were analysed using a high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) method that was modified for low sample biomass.

resultsThe method was assessed with respect to sensitivity and repeatability of the entire workflow from cell culturing and sampling to measurement of the metabolic phenotype, demonstrating sufficient sensitivity (> 3000 features in hepatocyte extracts) and intra- and inter-plate repeatability for polar nESI-DIMS assays (median relative standard deviation < 30%). The assays were employed for a proof-of-principle toxicological study with a model toxicant, cadmium chloride, revealing changes in the metabolome across five sampling times in the 48-h exposure period. To allow the option for lipidomics analyses, the solvent system was extended by establishing separate extraction methods for polar metabolites and lipids.

conclusionsExperimental, analytical and informatics workflows reported here met pre-defined criteria in terms of sensitivity, repeatability and ability to detect metabolome changes induced by a toxicant and are ready for application in metabolomics-driven toxicity testing to complement HTS assays.

Indexed as

High-Throughput Screening AssaysMetabolomicsAnimalsMass SpectrometryMetabolomeSpecimen HandlingChemical risk assessmentDirect infusion mass spectrometryHepaRGHigh-throughput screeningIn vitro metabolomicsToxicology

Identifiers

PMID35000038
PMCPMC8743266
OpenAlexW4205820995

What Socratic 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 Socratic graph.