Abstract
Metabolomics is used to reduce the complexity of plants and to understand the underlying pathways of the plant phenotype. The metabolic profile of plants can be obtained by mass spectrometry or liquid-state NMR. The extraction of metabolites from the sample is necessary for both techniques to obtain the metabolic profile. This extraction step can be eliminated by making use of high-resolution magic angle spinning (HR-MAS) NMR. In this review, an HR-MAS NMR-based workflow is described in more detail, including used pulse sequences in metabolomics. The pre-processing steps of one-dimensional HR-MAS NMR spectra are presented, including spectral alignment, baseline correction, bucketing, normalisation and scaling procedures. We also highlight some of the models which can be used to perform multivariate analysis on the HR-MAS NMR spectra. Finally, applications of HR-MAS NMR in plant metabolomics are described and show that HR-MAS NMR is a powerful tool for plant metabolomics studies.
Highlights
To understand the biological pathway underlying the phenotype of plants, a systems biology approach can be used [1,2,3]
The advantage of using high-resolution magic angle spinning (HR-MAS) nuclear magnetic resonance (NMR) spectroscopy on leaves is that experiments can be genuinely performed in vivo, which will be illustrated with selected plant metabolomics applications (Section 8)
The NMR responses of metabolites are superimposed on a broad background that does not contribute any signal of interest but affects the multivariate analysis and impedes the quantification of metabolites
Summary
To understand the biological pathway underlying the phenotype of plants, a systems biology approach can be used [1,2,3]. The information and interaction of the functional physical structure and the genetic information are integrated to provide a comprehensive model of the organism (Figure 1). Molecules 2021, 26, x FOR PEER REVIEW of the phenotype of the organisms in a general framework [22]. This requires techniques that can study metabolomics directly in native state. Biology, the information from genetic program is integrated with information mation from functional physical structures to provide a comprehensive model of plants.
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