Evidence map›Paper›PMID 39460701›Full record

ArticleAnalytical chemistry2024

Single-Cell Lipidomics: An Automated and Accessible Microfluidic Workflow Validated by Capillary Sampling.

Anastasia Kontiza, Johanna von Gerichten, Kyle D G Saunders, Matt Spick, Anthony D Whetton, Carla F Newman, Melanie J Bailey

Abstract read
In one paragraph

Article in Analytical chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

7 authors.

Anastasia KontizaSchool of Chemistry and Chemical Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.ORCID 0000-0003-0097-3358
Johanna von GerichtenSchool of Chemistry and Chemical Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.ORCID 0000-0002-9224-5296
Kyle D G SaundersSchool of Chemistry and Chemical Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.ORCID 0000-0002-5615-5322
Matt SpickSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.ORCID 0000-0002-9417-6511
Anthony D WhettonvHive, School of Veterinary Medicine, School of Biosciences and Medicine, University of Surrey, Guildford GU2 7XH, United Kingdom.
Carla F NewmanCellular Imaging and Dynamics, GlaxoSmithKline, Stevenage SG1 2NY, United Kingdom.ORCID 0000-0003-3659-0156
Melanie J BaileySchool of Chemistry and Chemical Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, United Kingdom.ORCID 0000-0001-9050-7910

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We report the first demonstration of a microfluidics-based approach to measure lipids in single living cells using widely available liquid chromatography mass spectrometry (LC-MS) instrumentation. The method enables the rapid sorting of live cells into liquid chambers formed on standard Petri dishes and their subsequent dispensing into vials for analysis using LC-MS. This approach facilitates automated sampling, data acquisition, and analysis and carries the additional advantage of chromatographic separation, aimed at reducing matrix effects present in shotgun lipidomics approaches. We demonstrate that our method detects comparable numbers of features at around 200 lipids in populations of single cells versus established live single-cell capillary sampling methods and with greater throughput, albeit with the loss of spatial resolution. We also show the importance of optimization steps in addressing challenges from lipid contamination, especially in blanks, and demonstrate a 75% increase in the number of lipids identified. This work opens up a novel, accessible, and high-throughput way to obtain single-cell lipid profiles and also serves as an important validation of single-cell lipidomics through the use of different sampling methods.

Indexed as

LipidomicsLipidsSingle-Cell AnalysisAutomationChromatography, LiquidHumansMass SpectrometryMicrofluidic Analytical TechniquesWorkflowLipids

Identifiers

PMID39460701
PMCPMC11541894

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.