The Handbook of Plant Metabolomics

Wolfram Weckwerth, Guenter Kahl, Wolfram Weckwerth, Guenter Kahl

• Publisher: Wiley-Blackwell
• Year: 2013
• Print ISBN: 9783527327775
• eBook ISBN: 9783527669905
• Edition: 1
• Topic: Biological Sciences
• Subtopic: Botany
• Index: Biological Sciences

This is the newest title in the successful Molecular Plant Biology Handbook Series. Just like the other titles in the series this new book presents an excellent overview of different approaches and techniques in Metabolomics. Contributors are either from ivy-league research institutions or from companies developing new technologies in this dynamic and fast-growing field. With its approach to introduce current techniques in plant metabolomics to a wider audience and with many labs and companies considering to introduce metabolomics for their research, the title meets a growing market. The Kahl books are in addition a trusted brand for the plant science community and have always sold above expectations.

Part I

Central Metabolism

1

Metabolic Profiling of Plants by GC–MS

Camilla B. Hill and Ute Roessner

1.1 Introduction

For numerous organisms, complete genomes have been sequenced [1–3] and transcriptome [4–6] and proteome studies [7–9] have been described, but only recently have metabolome analyses using mass spectrometry (MS)-based platforms attracted attention. Recent advances in analytical technologies have now allowed the analysis of complex metabolic structures in an organism.

Metabolomics is currently a very powerful tool for characterizing metabolites and metabolic pathways and aims to provide a “snapshot” of the biochemical state of a biological sample. The number of metabolites is expected to be significantly lower than the number of genes, proteins, or mRNAs, which reduces the complexity of the sample. However, the total number of metabolites in the plant kingdom is estimated to be between 100 000 and 200 000, which makes cataloging of all metabolites a challenging task [10, 11]. The metabolic composition of plants is likely to be altered during different physiological and environmental conditions and can also reflect different genetic backgrounds. Metabolomics aims to provide a comprehensive and unbiased analysis of all metabolites with a low molecular weight present in a biological sample, such as an organism, a specific tissue, or a cell, under certain conditions [12].

Analytical strategies for plant metabolite analysis include metabolic profiling, metabolite target analysis, and metabolic fingerprinting and are chosen according to either the focus of the research or the research question [12–14]. Metabolite profiling aims to detect as many metabolites as possible within a structurally related predefined group, for example, organic acids, amino acids, and carbohydrates. Metabolic profiling does not necessarily aim to determine absolute concentrations of metabolites but rather their comparative levels. In contrast, the aim of targeted metabolite analysis is to determine pool sizes (e.g., absolute concentrations) of metabolites involved in a particular pathway by utilizing specialized extraction protocols and adapted separation and detection methods. A third conceptual approach in metabolome analysis is metabolic fingerprinting, which generally is not intended to identify individual metabolites, but rather provides a fingerprint of all chemicals measurable for sample comparison and discrimination analysis by nonspecific rapid analysis of crude metabolite mixtures. Depending on the analytical strategy, a number of different instrumental platforms with different configurations may need to be utilized to ensure optimal data acquisition [15].

Because of the diversity of structural classes of metabolites, ranging from primary metabolites such as carbohydrates, amino acids, and organic acids to very complex secondary metabolites such as phenolics, alkaloids, and terpenoids, there is no single methodology that can measure the complete metabolome in one step. It is necessary to combine different techniques to detect all metabolites in a complex mixture [13]. It is possible that two samples, although very different, may show the same metabolite profile using one strategy. Therefore, only by employing a combination of different instrument platforms and techniques can the suite of differences in the metabolite profiles be revealed.

Several extraction methods and instrument platforms have been established to analyze highly complex mixtures, and each has to be chosen according to particular interests. These include nuclear magnetic resonance (NMR), Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS or FT-MS), and mass spectrometry (MS) coupled with liquid chromatography (LC) [liquid chromatography–mass spectrometry (LC–MS)] or gas chromatography (GC) [gas chromatography–mass spectrometry (GC–MS)]. Section 1.2 focuses on the application of GC–MS to plant metabolomics studies; the advantages and disadvantages of other instrument platforms for metabolomics were discussed in Refs. [16–19].

The coupling of GC to electron impact ionization (EI) MS is possibly the oldest hybrid technique in analytical chemistry and is considered to be one of the most developed, robust, and highly sensitive instrument platforms for metabolite analysis [20–22]. GC–MS offers high chromatographic separation power, robust quantification methods, and the capability to identify metabolites with high fidelity, and is therefore often referred to as the “gold standard” in metabolomics [23]. GC–MS-based methodologies were among the first to be applied to metabolite profiling and target analysis, thus offering established protocols for machine setup, data mining, and interpretation. Compared with other instrument platforms, it offers the lowest acquisition, operating, and maintenance expenses [24]. Furthermore, both commercially and publicly available EI spectral libraries facilitate the use of GC–MS as a metabolomics platform [25].

Historically, the first chromatographic separation techniques were developed between 1940 and 1950 by Martin and Synge, who won the 1952 Nobel Prize for their invention of partition chromatography [26, 27]. They further contributed substantially to the development of GC and high-performance liquid chromatography (HPLC). During the 1970s, the term “metabolite profiling” was coined and was first applied in studies of steroid and steroid derivatives, amino acids, and drug metabolites [28, 29] in 1971. In the following years, metabolite research developed toward the utilization of metabolic profiling by GC–MS as a diagnostic technique in medicine to monitor metabolites present in urine [30]. But it was not until the 1990s that metabolomics found its way into plant research. In the late 1990s, Oliver et al. were the first to introduce the terms metabolome and metabolomics [31]. About a decade ago, one of the first approaches for high-throughput, large-scale, and comprehensive plant metabolite analysis was conducted by Roessner et al. [21, 32, 33], who analyzed more than 150 compounds simultaneously within a single potato (Solanum tuberosum) tuber sample using GC–MS, and Fiehn et al. [20], who analyzed 326 distinct compounds from Arabidopsis thaliana leaf extracts of four genotypes by GC–MS, and identified ~50% of these compounds. Several studies have now implemented this approach, and it has been applied to various plant species and tissues, including A. thaliana leaf tissue [13], phloem exudates of buttercup squash (Cucubita maxima) [34], tomato leaves and fruit (Solanum lycopersicum) [35, 36], and barley leaf and root tissue (Hordeum vulgare) [37]. GC–MS applications include studies that associate certain metabolites with biotic [38] and abiotic stress responses [39–42], define metabolic differences of genetically modified plants [32, 33, 35, 43, 44], or integrate genetic ...

Table of contents

• Cover
• Titles of the Series “Molecular Plant Biology Handbook Series”
• Title Page
• Copyright
• Dedication
• Preface
• List of Contributors
• Part I: Central Metabolism
• Part II: Secondary and Lipid Metabolism
• Part III: Metabolomics and Genomics
• Part IV: Metabolomics and Bioinformatics
• Glossary
• Index