Chapter 20
Untargeted Metabolomics of Arabidopsis Stomatal
Immunity
Lisa David, Jianing Kang, and Sixue Chen
Abstract
Although untargeted metabolomic approaches hold great promise for global identification of low molecular weight metabolites in biological samples, deep coverage and confident identification of the metabolites
remains challenging due to the great diversity and number of chemical structures, especially in plants.
Additionally, there is a need to employ a cell-specific research approach to many physiological and biological
responses to specific environmental stimuli. Here, we report an untargeted metabolomic method using
Arabidopsis thaliana guard cell samples during response to systemic signals of pathogen attack. We
employed a new Acquire X MS
n data acquisition technology, which uses an iterative fragmentation process
to increase level-2 identification of unknown metabolites. We were able to increase the number of identified
metabolites and thus the metabolome coverage in Arabidopsis guard cells. This method can be applied to
studying metabolomes of other cell types and tissues.
Key words Arabidopsis, Metabolomics, Acquire X, Guard cells, Systemic acquired resistance
1 Introduction
Plants have complex metabolomes that are estimated to be composed of more than one million endogenous metabolites from
more than 200,000 plant species [1]. These compounds vary in
their complexities, solubilities, and thermolabilities. This can make
extraction and identification by chromatography and mass spectrometry methods challenging. Technological improvements for
enhanced instrument sensitivity, ionization techniques, and
increased scan speed can increase metabolite coverage. However,
identification of metabolites requires software capable of processing, integrating, interpreting, and verifying the metabolomic data.
Currently, there are four levels of metabolite identifications in the
published literature [2]. Level 1 identified compounds are the most
confident because there are authentic standards, which have often
been reported in literature. However, the number of these level
1 metabolites is small, since not many plant metabolites have
Jose J. Sanchez-Serrano and Julio Salinas (eds.), Arabidopsis Protocols, Methods in Molecular Biology, vol. 2200,
https://doi.org/10.1007/978-1-0716-0880-7_20, © Springer Science+Business Media, LLC, part of Springer Nature 2021
413
Untargeted Metabolomics of Arabidopsis Stomatal
Immunity
Lisa David, Jianing Kang, and Sixue Chen
Abstract
Although untargeted metabolomic approaches hold great promise for global identification of low molecular weight metabolites in biological samples, deep coverage and confident identification of the metabolites
remains challenging due to the great diversity and number of chemical structures, especially in plants.
Additionally, there is a need to employ a cell-specific research approach to many physiological and biological
responses to specific environmental stimuli. Here, we report an untargeted metabolomic method using
Arabidopsis thaliana guard cell samples during response to systemic signals of pathogen attack. We
employed a new Acquire X MS
n data acquisition technology, which uses an iterative fragmentation process
to increase level-2 identification of unknown metabolites. We were able to increase the number of identified
metabolites and thus the metabolome coverage in Arabidopsis guard cells. This method can be applied to
studying metabolomes of other cell types and tissues.
Key words Arabidopsis, Metabolomics, Acquire X, Guard cells, Systemic acquired resistance
1 Introduction
Plants have complex metabolomes that are estimated to be composed of more than one million endogenous metabolites from
more than 200,000 plant species [1]. These compounds vary in
their complexities, solubilities, and thermolabilities. This can make
extraction and identification by chromatography and mass spectrometry methods challenging. Technological improvements for
enhanced instrument sensitivity, ionization techniques, and
increased scan speed can increase metabolite coverage. However,
identification of metabolites requires software capable of processing, integrating, interpreting, and verifying the metabolomic data.
Currently, there are four levels of metabolite identifications in the
published literature [2]. Level 1 identified compounds are the most
confident because there are authentic standards, which have often
been reported in literature. However, the number of these level
1 metabolites is small, since not many plant metabolites have
Jose J. Sanchez-Serrano and Julio Salinas (eds.), Arabidopsis Protocols, Methods in Molecular Biology, vol. 2200,
https://doi.org/10.1007/978-1-0716-0880-7_20, © Springer Science+Business Media, LLC, part of Springer Nature 2021
413