Methods for Quantifying the Metabolic Boundary Fluxes of Cell Cultures in Large Cohorts by High-Resolution Hydrophilic Liquid Chromatography Mass Spectrometry

Metabolomics is a mainstream approach for investigating the metabolic underpinnings of complex biological phenomena and is increasingly being applied to large-scale studies involving hundreds or thousands of samples. Although metabolomics methods are robust in smaller-scale studies, they can be chal...

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Published in:Analytical chemistry (Washington) 2022-06, Vol.94 (25), p.8874-8882
Main Authors: Groves, Ryan A., Mapar, Maryam, Aburashed, Raied, Ponce, Luis F., Bishop, Stephanie L., Rydzak, Thomas, Drikic, Marija, Bihan, Dominique G., Benediktsson, Hallgrimur, Clement, Fiona, Gregson, Daniel B., Lewis, Ian A.
Format: Article
Language:English
Subjects:
Analytical chemistry
Chemistry
Chromatography
Clinical isolates
Coefficient of variation
Fluxes
Hydrophilicity
Liquid chromatography
Mass spectrometry
Mass spectroscopy
Mathematical analysis
Metabolism
Metabolites
Metabolomics
Microorganisms
Phenotypes
Qualitative analysis
Scientific imaging
Spectroscopy
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Summary:Metabolomics is a mainstream approach for investigating the metabolic underpinnings of complex biological phenomena and is increasingly being applied to large-scale studies involving hundreds or thousands of samples. Although metabolomics methods are robust in smaller-scale studies, they can be challenging to apply to larger cohorts due to the inherent variability of liquid chromatography mass spectrometry (LC-MS). Much of this difficulty results from the time-dependent changes in the LC-MS system, which affects both the qualitative and quantitative performances of the instrument. Herein, we introduce an analytical strategy for addressing this problem in large-scale microbial studies. Our approach quantifies microbial boundary fluxes using two zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) columns that are plumbed to enable offline column equilibration. Using this strategy, we show that over 397 common metabolites can be resolved in 4.5 min per sample and that metabolites can be quantified with a median coefficient of variation of 0.127 across 1100 technical replicates. We illustrate the utility of this strategy via an analysis of 960 strains of Staphylococcus aureus isolated from bloodstream infections. These data capture the diversity of metabolic phenotypes observed in clinical isolates and provide an example of how large-scale investigations can leverage our novel analytical strategy.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.2c00078