Dataset Information

An NMR metabolomics analysis pipeline for human neutrophil samples with limited source material

ABSTRACT: Untargeted 1H NMR metabolomics is a robust and reproducible approach to study metabolism in biological samples, providing unprecedented insight into altered cellular processes associated with human diseases. Metabolomics is increasingly used alongside other -omics techniques, such as proteomics and transcriptomics, to detect instantaneous altered cellular function, for example the role of blood neutrophils in the inflammatory response. However, in some clinical settings e.g. pediatrics research, blood samples may be limited, restricting the amount of cellular material available for metabolomics analysis. In this study we wanted to establish the optimal 1D 1H NMR metabolomics pipeline for use with human neutrophil samples with low input material. We compared the effect of neutrophil isolation protocols using Ficoll-Paque or negative selection using antibody-labelled magnetic beads on neutrophil metabolite profiles. We also compared the effect of absolute cell counts ranging from 100,000 to 5 million neutrophils in total on the identities of metabolites that can be detected with increasing number of scans (NS) from 256 to 2,048. We found that variance in neutrophil profile was higher with N isolation method event though choice of isolation method did not significantly alter the metabolite profile of human neutrophils measured by 1D 1H NMR spectroscopy. The minimum number of cells required for detection of human metabolites was 400,000 at NS 256 for spectra acquired with a cryoprobe equipped 700MHz. Increasing the NS to 2,048 increased metabolite detection at the very lowest cell counts (<400,000 neutrophils), however this was associated with a significant increase in analysis time which would be rate-limiting for large studies. Application of a correlation reliability score (CRS) filtering method to the spectral bins preserved the essential discriminatory features of the PLS-DA models whilst improving the dataset robustness and analytical precision.

INSTRUMENT(S): Nuclear Magnetic Resonance (NMR) -

PROVIDER: MTBLS6220 | MetaboLights | 2025-11-06

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	a_MTBLS6220_NMR___metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS6220_NMR___metabolite_profiling_v2_maf.tsv	Tabular
	s_MTBLS6220.txt	Txt

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Publications

An NMR Metabolomics Analysis Pipeline for Human Neutrophil Samples with Limited Source Material.

Filbertine Grace G Abdullah Genna A GA Gill Lucy L Grosman Rudi R Phelan Marie M MM Chiewchengchol Direkrit D Hirankarn Nattiya N Wright Helen L HL

Metabolites 20250915 9

Background/Objectives: Untargeted 1H NMR metabolomics is a robust and reproducible approach used to study the metabolism in biological samples, providing unprecedented insight into altered cellular processes associated with human diseases. Metabolomics is increasingly used alongside other techniques to detect an instantaneous altered cellular function, for example, the role of neutrophils in the inflammatory response. However, in some clinical settings, blood samples may be lim ...[more]

PMID: 41002996

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Project description:Background: Neutrophil function declines with age, but little is known about the changes in neutrophil metabolism that take place in older people and people with frailty. We used 1H-NMR spectroscopy to investigate the metabolic profiles of neutrophils from healthy younger (HY) and older (HO) people and older people with frailty (FR), to identify metabolites and metabolic pathways altered with healthy ageing and ageing with frailty. We also compared FR metabolites to rheumatoid arthritis (RA) neutrophils to identify markers of inflammation in FR neutrophils. Methods: 1H-NMR spectroscopy was performed on polar and lipid metabolites extracted from blood neutrophils. Polar metabolites were annotated using Chenomx prior to univariate (ANOVA, Tukey’s adjusted p-value<0.05) and supervised (partial least square discriminant analysis, PLS-DA) multivariate analyses in R (v4.4.1). Lipid metabolites were analysed as spectral bins. Metabolite enrichment analysis was performed using Metaboanalyst (v6) against the small molecule pathway database (SMPDB).  Results: ANOVA identified 17 polar metabolites significantly different across the participant groups (adj. p<0.05). Three polar metabolites were significantly different in FR vs HO neutrophils, with NADP being higher in FR and lysine and choline being lower. NADP was uniquely elevated in FR compared to HO, HY and RA neutrophils. Seven metabolites were significantly different between HO and HY neutrophils, and only 2 metabolites were different between FR and RA neutrophils, identifying underlying similarities between FR and RA that may be driven by inflammation. Four lipid peaks were significantly different between FR and HY neutrophils. These were attributed to total cholesterol and arachidonic acid. Conclusions: This is the first study of polar and lipid metabolism in neutrophils from people with frailty. Our results provide evidence that metabolic signalling pathways involved in neutrophil activation, oxidative stress and lipid metabolism are altered during healthy ageing and ageing with frailty, and we identify NADP as a unique biomarker of altered neutrophil function in people with frailty.