Abstract
The development of improved mass spectrometers and supporting computational tools is expected to enable the rapid annotation of whole metabolomes. Essential for the progress is the identification of strengths and weaknesses of novel instrumentation in direct comparison to previous instruments. Orbitrap liquid chromatography (LC)–mass spectrometry (MS) technology is now widely in use, while Orbitrap gas chromatography (GC)–MS introduced in 2015 has remained fairly unexplored in its potential for metabolomics research. This study aims to evaluate the additional knowledge gained in a metabolomics experiment when using the high-resolution Orbitrap GC–MS in comparison to a commonly used unit-mass resolution single-quadrupole GC–MS. Samples from an osmotic stress treatment of a non-model organism, the microalga Skeletonema costatum, were investigated using comparative metabolomics with low- and high-resolution methods. Resulting datasets were compared on a statistical level and on the level of individual compound annotation. Both MS approaches resulted in successful classification of stressed vs. non-stressed microalgae but did so using different sets of significantly dysregulated metabolites. High-resolution data only slightly improved conventional library matching but enabled the correct annotation of an unknown. While computational support that utilizes high-resolution GC–MS data is still underdeveloped, clear benefits in terms of sensitivity, metabolic coverage, and support in structure elucidation of the Orbitrap GC–MS technology for metabolomics studies are shown here.
Highlights
Metabolite annotation is an important step in any untargeted mass spectrometry (MS)-based metabolomics study, allowing for chemically and biologically sound interpretation of analytical data [1].In current studies, usually less than 30% of compounds are identified because the coverage of existing molecules in mass spectral libraries is limited [2]
The Orbitrap mass spectrometer coupled with liquid chromatography (LC) has contributed to this development by providing high mass resolving power combined with tandem MS capabilities [5]
We investigated the response of a non-model organism, the diatom Skeletonema costatum, to osmotic stress compared to a control
Summary
Metabolite annotation is an important step in any untargeted mass spectrometry (MS)-based metabolomics study, allowing for chemically and biologically sound interpretation of analytical data [1]. Usually less than 30% of compounds are identified because the coverage of existing molecules in mass spectral libraries is limited [2]. The identification of an unknown, either by MS experiments or alternative techniques such as nuclear magnetic resonance spectroscopy (NMR), has been the most time-consuming step of metabolomics research for more than a decade, requiring labor-intensive manual interpretation of spectral data by an expert [3]. The field is currently entering a new era of metabolite annotation, where novel analytical technologies, computational algorithms and community driven open database resources will enable the rapid annotation of whole metabolomes [4].
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