Evidence map›Paper›PMID 35713879›Full record

ArticleAnalytical chemistry2022

Single-Cell Metabolic Profiling of Macrophages Using 3D OrbiSIMS: Correlations with Phenotype.

Waraporn Suvannapruk, Max K Edney, Dong-Hyun Kim, David J Scurr, Amir M Ghaemmaghami, Morgan R Alexander

Open access · hybridAbstract read
In one paragraph

Article in Analytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

15 citing papers in PubMed, 33 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Waraporn SuvannaprukAdvanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.ORCID 0000-0001-9138-9418
Max K EdneyDepartment of Chemical and Environmental Engineering, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.ORCID 0000-0003-3438-5060
Dong-Hyun KimAdvanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.ORCID 0000-0002-3689-2130
David J ScurrAdvanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.ORCID 0000-0003-0859-3886
Amir M GhaemmaghamiImmunology & Immuno-bioengineering Group, School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.ORCID 0000-0003-3160-8759
Morgan R AlexanderAdvanced Materials and Healthcare Technologies Division, School of Pharmacy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.ORCID 0000-0001-5182-493X
University of Nottingham · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macrophages are important immune cells that respond to environmental cues acquiring a range of activation statuses represented by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at each end of their spectrum. Characterizing the metabolic signature (metabolic profiling) of different macrophage subsets is a powerful tool to understand the response of the human immune system to different stimuli. Here, the recently developed 3D OrbiSIMS instrument is applied to yield useful insight into the metabolome from individual cells after in vitro differentiation of macrophages into naïve, M1, and M2 phenotypes using different cytokines. This analysis strategy not only requires more than 6 orders of magnitude less sample than traditional mass spectrometry approaches but also allows the study of cell-to-cell variance. Characteristic metabolites in macrophage subsets are identified using a targeted lipid and data-driven multivariate approach highlighting amino acids and other small molecules. The diamino acids alanylasparagine and lipid sphingomyelin SM(d18/16:0) are uniquely found in M1 macrophages, while pyridine and pyrimidine are observed at increased intensity in M2 macrophages, findings which link to known biological pathways. The first demonstration of this capability illustrates the great potential of direct cell analysis for in situ metabolite profiling with the 3D OrbiSIMS to probe functional phenotype at the single-cell level using molecular signatures and to understand the response of the human body to implanted devices and immune diseases.

Indexed as

MacrophagesMetabolomicsCytokinesLipidsPhenotypeCytokinesLipids

Identifiers

PMID35713879
PMCPMC9260720
OpenAlexW4283017080

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Registered trials

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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.