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

<b>Background/Objectives:</b> Untargeted <sup>1</sup>H 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 limited, restricting the amount of cellular material available for a metabolomic analysis. In this study, we wanted to establish an optimal 1D <sup>1</sup>H NMR metabolomic pipeline for use with human neutrophil samples with low amounts of input material. <b>Methods</b>: We compared the effect of different neutrophil isolation protocols on metabolite profiles. We also compared the effect of the absolute cell counts (100,000 to 5,000,000) on the identities of metabolites that were detected with an increasing number of scans (NS) from 256 to 2048. <b>Results/Conclusions</b>: The variance in the neutrophil profile was equivalent between the isolation methods, and the choice of isolation method did not significantly alter the metabolite profile. The minimum number of cells required for the detection of neutrophil metabolites was 400,000 at an NS of 256 for the spectra acquired with a cryoprobe (700 MHz). Increasing the NS to 2048 increased metabolite detection at the very lowest cell counts (<400,000 neutrophils); however, this was associated with a significant increase in the analysis time, which would be rate-limiting for large studies. The application of a correlation-reliability-score-filtering method to the spectral bins preserved the essential discriminatory features of the PLS-DA models whilst improving the dataset robustness and analytical precision.

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Publication Details

Journal
Metabolites
Published
2025-09-15
DOI
https://doi.org/10.3390/metabo15090612
Citations
2
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
1.61
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article

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

Marie M. Phelan, Rudi Grosman, Direkrit Chiewchengchol, Grace Filbertine et al.
2 citations
Metabolites
Metabolomics and Mass Spectrometry Studies
1.61
article

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

Marie M. Phelan, Rudi Grosman, Direkrit Chiewchengchol, Grace Filbertine, Nattiya Hirankarn, Lucy Gill, Helen L. Wright, Genna Ali Abdullah
article en
2 citations

Abstract

<b>Background/Objectives:</b> Untargeted <sup>1</sup>H 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 limited, restricting the amount of cellular material available for a metabolomic analysis. In this study, we wanted to establish an optimal 1D <sup>1</sup>H NMR metabolomic pipeline for use with human neutrophil samples with low amounts of input material. <b>Methods</b>: We compared the effect of different neutrophil isolation protocols on metabolite profiles. We also compared the effect of the absolute cell counts (100,000 to 5,000,000) on the identities of metabolites that were detected with an increasing number of scans (NS) from 256 to 2048. <b>Results/Conclusions</b>: The variance in the neutrophil profile was equivalent between the isolation methods, and the choice of isolation method did not significantly alter the metabolite profile. The minimum number of cells required for the detection of neutrophil metabolites was 400,000 at an NS of 256 for the spectra acquired with a cryoprobe (700 MHz). Increasing the NS to 2048 increased metabolite detection at the very lowest cell counts (<400,000 neutrophils); however, this was associated with a significant increase in the analysis time, which would be rate-limiting for large studies. The application of a correlation-reliability-score-filtering method to the spectral bins preserved the essential discriminatory features of the PLS-DA models whilst improving the dataset robustness and analytical precision.

MetabolitesVol. 15(9)
University of Liverpool (GB), Chulalongkorn University (TH)
Openalex Percentile: Top 15%
Metabolomics and Mass Spectrometry Studies
1.61
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