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. 2021 Jul 23:12:659302.
doi: 10.3389/fmicb.2021.659302. eCollection 2021.

Lipidomics of Environmental Microbial Communities. I: Visualization of Component Distributions Using Untargeted Analysis of High-Resolution Mass Spectrometry Data

Nicole J Bale  1 , Su Ding  1 , Ellen C Hopmans  1 , Milou G I Arts  1 , Laura Villanueva  1   2 , Christine Boschman  1 , Andreas F Haas  1 , Stefan Schouten  1   2 , Jaap S Sinninghe Damsté  1   2
Affiliations

Lipidomics of Environmental Microbial Communities. I: Visualization of Component Distributions Using Untargeted Analysis of High-Resolution Mass Spectrometry Data

Nicole J Bale et al. Front Microbiol. .

Abstract

Lipids, as one of the main building blocks of cells, can provide valuable information on microorganisms in the environment. Traditionally, gas or liquid chromatography coupled to mass spectrometry (MS) has been used to analyze environmental lipids. The resulting spectra were then processed through individual peak identification and comparison with previously published mass spectra. Here, we present an untargeted analysis of MS1 spectral data generated by ultra-high-pressure liquid chromatography coupled with high-resolution mass spectrometry of environmental microbial communities. Rather than attempting to relate each mass spectrum to a specific compound, we have treated each mass spectrum as a component, which can be clustered together with other components based on similarity in their abundance depth profiles through the water column. We present this untargeted data visualization method on lipids of suspended particles from the water column of the Black Sea, which included >14,000 components. These components form clusters that correspond with distinct microbial communities driven by the highly stratified water column. The clusters include both known and unknown compounds, predominantly lipids, demonstrating the value of this rapid approach to visualize component distributions and identify novel lipid biomarkers.

Keywords: Black Sea; MZmine; lipidome; lipidomics; lipids; liquid chromatography mass spectrometry.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
A preliminary analysis, using average-neighbor hierarchical clustering (Ward method) of the 38 UHPLC-HRMS analyses (Black Sea water column SPM from 2013) and associated extraction blanks. Clustered by similarity in distribution of lipidome components (n = 14,648), as extracted by MZmine software. Red annotations show the water column redox zones, as given in Table 1.
FIGURE 2
FIGURE 2
Heat map of the peak areas of 14,648 component in Black Sea SPM from June 2013 as extracted by MZmine software. Color scheme represents component’s depth profile, red, highest abundance; and blue, lowest abundance. SPM extracts clustered by similarity in component distribution on the vertical axis and components clustered by similarity of depth profile through water column on the horizontal axis. Red annotations show the water column redox zones, as given in Table 1.
FIGURE 3
FIGURE 3
Heat map of the peak area of 12,372 components in Black Sea SPM from March 2017 as extracted by MZmine software. Color scheme represents component’s depth profile, red, highest abundance; and blue, lowest abundance. SPM extracts clustered by similarity in component distribution on the vertical axis and components clustered by similarity of depth profile through water column on the horizontal axis. Red annotations show the water column redox zones, as given in Table 1.
See this image and copyright information in PMC

References

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