The Handbook of Plant Metabolomics

Edited by

Wolfram Weckwerth

and Günter Kahl

The Handbook of Plant

Metabolomics

Titles of the Series “Molecular Plant Biology Handbook Series”

Kahl, G., Meksem, K. (eds.)

The Handbook of Plant Functional Genomics

Concepts and Protocols

2008

ISBN: 978-3-527-31885-8

Meksem, K., Kahl, G. (eds.)

The Handbook of Plant Mutation Screening

Mining of Natural and Induced Alleles

2010

ISBN: 978-3-527-32604-4

Meksem, K., Kahl, G. (eds.)

The Handbook of Plant Genome Mapping

Genetic and Physical Mapping

2005

ISBN: 978-3-527-31116-3

Related Titles

Harbers, M., Kahl, G. (eds.)

Tag-based Next Generation Sequencing

2012

ISBN: 978-3-527-32819-2

Hirt, H. (ed.)

Plant Stress Biology

From Genomics to Systems Biology

2010

ISBN: 978-3-527-32290-9

Hayat, S., Mori, M., Pichtel, J., Ahmad, A. (eds.)

Nitric Oxide in Plant Physiology

2010

ISBN: 978-3-527-32519-1

Kahl, G.

The Dictionary of Genomics, Transcriptomics and Proteomics

2009

ISBN: 978-3-527-32073-8

Edited by Wolfram Weckwerth and Günter Kahl

The Handbook of Plant Metabolomics

The Editors

Prof. Dr. Wolfram Weckwerth

Universität Wien

Molekulare Systembiologie

Althanstr. 14

1090 Wien

Austria

Prof. Dr. Günter Kahl

Mohrmühlgasse 3

63500 Seligenstadt

Germany

Cover Legend

The cover picture presents some structures of

representative phytochemicals and

biosynthetic pathways and enzymes of

Arabidopsis thaliana, referred to in the chapter

“Integrative analysis of secondary metabolism

and transcript regulation in Arabidopsis

thaliana” by Fumio Matsuda and Kazuki Saito

(for further details see Chapter 9, Fig. 4). The

figure was originally published in “Matsuda,

F., et al. (2010) AtMeteEpress development: A

phytochemical atlas of Arabidopsis

development. Plant Physiol, 152, 566–578),

www.plantphysiol.org, # American Society of

Plant Biologists. The permission of the authors

to partly use their figure in a changed format

is greatly appreciated. Foto of Arabidopsis:

# Vasiliy Koval, Fotolia.com

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and author have used their best efforts in preparing this

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respect to the accuracy or completeness of the contents of

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warranty can be created or extended by sales representatives

or written sales materials. The Advice and strategies

contained herein may not be suitable for your situation. You

should consult with a professional where appropriate.

Neither the publisher nor authors shall be liable for any loss

of profit or any other commercial damages, including but not

limited to special, incidental, consequential, or other

damages.

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Library.

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Nationalbibliothek

The Deutsche Nationalbibliothek lists this publication in the

Deutsche Nationalbibliografie; detailed bibliographic data

are available on the Internet at <http://dnb.d-nb.de>.

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Print ISBN: 978-3-527-32777-5

ePDF ISBN: 978-3-527-66989-9

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Dedicated to

Ulrich and Hannelore Weckwerth

for their endless sympathy, patience and guidance

Contents

Preface XVII

List of Contributors XIX

Part I Central Metabolism 1

1 Metabolic Profiling of Plants by GC–MS 3

Camilla B. Hill and Ute Roessner

1.1 Introduction 3

1.2 Methods and Protocols 7

1.2.1 Sample Preparation 7

1.2.1.1 Sampling 7

1.2.1.2 Homogenization and Extraction 7

1.2.1.3 Procedure for Polar Extraction of Metabolites 8

1.2.2 Chemical Derivatization: Methoxymation and Silylation 9

1.2.2.1 Procedure for the Chemical Derivatization of Plant Extracts 9

1.2.3 GC–MS Analysis 10

1.2.3.1 Procedure to Acquire GC–MS Data 11

1.2.4 Data Preprocessing and Export 12

1.2.4.1 Procedure for Postacquisition Data Preprocessing 12

1.2.4.2 Data Analysis and Statistics 14

1.2.4.3 Procedure for Postacquisition Data Analysis 15

1.3 Applications of the Technology 15

1.4 Perspectives 17

References 18

2 Isotopologue Profiling – Toward a Better Understanding

of Metabolic Pathways 25

Wolfgang Eisenreich, Claudia Huber, Erika Kutzner, Nihat Knispel,

and Nicholas Schramek

2.1 Introduction 25

2.2 Methods and Protocols to Determine Isotopologues 31

2.2.1 Mass Spectrometry 31

2.2.2 Protocols for Isotopologue Profiling by GC–MS 36

jVII

2.2.2.1 Protein-Bound Amino Acids 36

2.2.2.2 Metabolic Intermediates and Polar Products 37

2.2.2.3 Carbohydrates 37

2.2.3 NMR Spectroscopy 38

2.2.4 Protocols for Isotopologue Profiling by NMR 41

2.2.5 Deconvolution of Isotopologue Data 43

2.2.6 Expanding the Metabolic Space by Retrobiosynthetic Analysis 45

2.3 Applications 46

2.3.1 Experiments Using ½U-13C6Glucose 46

2.3.2 Experiments Using 13CO2 47

2.4 Perspectives 53

References 54

3 Nuclear Magnetic Resonance Spectroscopy for Plant

Metabolite Profiling 57

Sonia van der Sar, Hye Kyong Kim, Axel Meissner, Robert Verpoorte,

and Young Hae Choi

3.1 Introduction 57

3.2 Methods and Protocols 59

3.2.1 Sample Preparation 59

3.2.1.1 Harvesting Plant Material 60

3.2.1.2 Drying 60

3.2.1.3 Extraction 60

3.2.2 Data Acquisition 60

3.2.3 Standard 1

H-NMR Spectroscopy 61

3.2.4 J-Resolved Spectroscopy 61

3.2.5 Data Analysis 61

3.3 Applications 62

3.3.1 1D 1

H-NMR Spectroscopy 62

3.3.2 2D NMR Spectroscopy 63

3.3.2.1 J-Resolved Spectroscopy 65

3.3.2.2 COSY and TOCSY 67

3.3.2.3 HMBC and HMQC/HSQC 68

3.3.2.4 NOESY or ROESY (CAMELSPIN) 69

3.3.2.5 DOSY 69

3.3.3 Magic Angle Spinning 70

3.4 Perspectives 71

References 72

4 Comprehensive Two-Dimensional Gas Chromatography

for Metabolomics 77

Katja Dettmer, Martin F. Almstetter, Christian J. Wachsmuth,

and Peter J. Oefner

4.1 Introduction 77

4.2 Methods and Protocols 81

VIIIj Contents

4.2.1 Instrumentation 81

4.2.2 Sample Preparation and Analysis 82

4.2.3 Data Processing 83

4.2.4 Metabolic Fingerprinting 83

4.2.5 Quantitative Analysis of Selected Metabolites 84

4.3 Applications of the Technology 85

4.3.1 Data Analysis 85

4.3.2 Literature 88

4.4 Perspectives 89

References 90

5 MALDI Mass Spectrometric Imaging of Plants 93

Ale9s Svato9s and Hans-Peter Mock

5.1 Introduction 93

5.1.1 Sample Preparation 96

5.1.2 Data Acquisition 98

5.1.3 Data Processing 98

5.2 Methods and Protocols 99

5.2.1 Sample Preparation and Handling 99

5.2.1.1 Intact Tissues 99

5.2.1.2 Cryosectioning 99

5.2.2 Matrix Deposition 100

5.2.2.1 Paintbrush (Figure 5.2) 100

5.2.2.2 Sublimation (Figure 5.3) 102

5.2.3 MALDI-MS Imaging Measurement 103

5.2.3.1 Bruker Ultraflex Instruments 103

5.2.3.2 Waters MALDI Micro MX 104

5.3 Imaging Intact Tissues and Objects 105

5.4 Future Perspectives 109

References 109

6 Medicago truncatula Root and Shoot Metabolomics: Protocol

for the Investigation of the Primary Carbon and Nitrogen Metabolism

Based on GC–MS 111

Vlora Mehmeti, Lena Fragner, and Stefanie Wienkoop

6.1 Introduction 111

6.2 Methods and Protocols 112

6.2.1 Equipment and Software 112

6.2.2 Buffers and Chemicals 112

6.2.3 Plant Material and Harvest 113

6.2.4 Extraction 114

6.2.5 Derivatization 115

6.2.6 GC–MS Setup for the Analysis 115

6.2.7 Metabolite Identification and Quantification: Data Matrix

Processing 116

Contents jIX

6.2.8 Data Mining 119

6.3 Applications of the Technology 119

6.4 Perspectives 121

References 123

Part II Secondary and Lipid Metabolism 125

7 Study of the Volatile Metabolome in Plant–Insect Interactions 127

Georg J.F. Weingart, Nora C. Lawo, Astrid Forneck, Rudolf Krska,

and Rainer Schuhmacher

7.1 Introduction 127

7.1.1 Plant–Insect Interactions 127

7.1.2 Significance of Volatile Plant Metabolites 128

7.1.3 Study of the Plant Volatile Metabolome in Plant–Insect Interactions 128

7.1.3.1 Setting Up of Biological Experiments 129

7.1.3.2 Sampling, Quenching, and Sample Preparation 130

7.1.3.3 Headspace Extraction and Measurement by GC–MS 131

7.1.3.4 Data Handling 134

7.1.3.5 Biological Interpretation 135

7.2 Methods and Protocols 135

7.2.1 Permanent Breed of Insects 135

7.2.2 Cultivation of Grapevine Plants and Inoculation with Phylloxera 136

7.2.2.1 Materials 136

7.2.2.2 Procedures 136

7.2.3 Sampling and Quenching of Plant Tissue (Roots and Leaves) 138

7.2.3.1 Sampling and Quenching of Root Tips 138

7.2.3.2 Sampling and Quenching of Grapevine Leaves 139

7.2.4 Milling and Weighing of Plant Tissue (Roots and Leaves) 140

7.2.4.1 Milling and Weighing of Root Samples 140

7.2.4.2 Milling and Weighing of Leaf Samples 141

7.2.5 Measurement – Automated HS-SPME Extraction

and GC–MS Analysis 143

7.2.5.1 Materials 143

7.2.5.2 SPME Method 143

7.2.5.3 GC Method 144

7.2.5.4 MS Settings 144

7.2.6 Data Processing with AMDIS 145

7.2.6.1 An In-House Reference Library Has to be Established in Advance 145

7.2.6.2 Generation of RI Calibration File 146

7.2.6.3 Batch Job Analysis for the Simultaneous Processing of Multiple

Sample Chromatograms 146

7.2.7 Statistics/Chemometrics 147

7.2.7.1 Univariate Statistics 147

7.2.7.2 Multivariate Statistics 148

Xj Contents

7.3 Applications of the Technology 148

7.4 Perspectives 149

References 150

8 Metabolomics in Herbal Medicine Research 155

Lie-Fen Shyur, Chiu-Ping Liu, and Shih-Chang Chien

8.1 Introduction 155

8.2 Methods and Protocols 158

8.2.1 Materials 158

8.2.1.1 Reagents 158

8.2.1.2 Equipment 159

8.2.2 Procedures 160

8.2.2.1 Sample Handling for Medicinal Plants 160

8.2.2.2 Sample Preparation for LC–MS Analysis 160

8.2.2.3 LC–MS Analysis 161

8.2.2.4 HPLC–Photodiode Array (PDA) MS Setup and Analysis 161

8.2.2.5 GC–MS Analysis 162

8.2.2.6 Plant Extract Preparation for GC–MS Analysis 163

8.2.2.7 GC–MS Parameters and Analysis 164

8.2.2.8 LC–MS and GC–MS Data Analysis 165

8.2.2.9 LC–SPE–NMR Analysis 166

8.2.2.10 Sample Preparation and LC–SPE–NMR Analysis 167

8.2.2.11 HPLC–SPE–NMR Data Analysis 168

8.3 Applications 168

8.4 Perspectives 169

References 170

9 Integrative Analysis of Secondary Metabolism and Transcript

Regulation in Arabidopsis thaliana 175

Fumio Matsuda and Kazuki Saito

9.1 Introduction 175

9.2 Methods and Protocols 177

9.2.1 Metabolome Analysis of Plant Secondary Metabolites 177

9.2.1.1 Sample Preparation 177

9.2.1.2 Data Acquisition 178

9.2.1.3 Preparation of Metabolite Accumulation Data from the Raw

Chromatogram Data 179

9.2.2 Preparation of Combined Data Matrix 180

9.2.2.1 Preparation of Gene Expression Data 180

9.2.2.2 Combination of Data Matrices 180

9.2.3 Data Mining 180

9.2.3.1 BL-SOM Analysis 180

9.2.3.2 Correlation Analysis 181

9.2.3.3 Principal Component Analysis and Application of Other

Data Mining Techniques 183

Contents jXI

9.3 Applications of the Technology 183

9.4 Perspectives 187

References 190

10 Liquid Chromatographic–Mass Spectrometric Analysis of

Flavonoids 197

Maciej Stobiecki and Piotr Kachlicki

10.1 Introduction 197

10.1.1 Role of Flavonoids and Their Derivatives in Biological Systems 197

10.1.2 Preparation of Biological Material for Metabolomic Analysis and/or

Metabolite Profiling 199

10.1.3 Instrumental Considerations 201

10.2 Methods and Protocols: Liquid Chromatography–Mass

Spectrometry of Flavonoids 206

10.2.1 General Remarks 206

10.2.2 Plant Cultivation Conditions 208

10.2.3 Preparation of Biological Material with Biotechnological Methods

(Callus, Cell, or Hairy Root Cultures) 208

10.2.4 Extraction of Plant Tissue or Biotechnologically Prepared Material 208

10.2.4.1 Extraction Procedure 209

10.2.5 Solid-Phase Extraction of Culture Medium or Apoplastic Fluids 209

10.2.6 Preparation of Samples for LC–MS Analyses 210

10.2.7 Chromatographic Protocols for Separation of Flavonoid

Glyconjugates 210

10.2.8 Control of Ionization Parameters During Mass Spectrometric

Analysis and Identification of Compounds During LC–MS

Metabolite Profiling 211

10.3 Applications of the Technology 211

10.4 Perspectives 211

References 212

11 Introduction to Lipid (FAME) Analysis in Algae Using Gas

Chromatography–Mass Spectrometry 215

Takeshi Furuhashi and Wolfram Weckwerth

11.1 Introduction 215

11.2 Methods and Experimental Protocol 216

11.2.1 Extraction 216

11.2.2 Bound and Free Fatty Acids 217

11.2.3 Pigments 217

11.2.4 Contaminants 219

11.2.5 Derivatization 219

11.2.6 GC–MS System 220

11.2.7 Identification 220

11.2.8 Protocols 221

11.2.8.1 Protocol I 221

XIIj Contents

11.2.8.2 Protocol II 221

11.2.9 GC–MS Instrument and Conditions 223

11.3 Application and Perspective 223

References 224

12 Multi-Gene Transformation for Pathway Engineering of Secondary

Metabolites 227

Hideyuki Suzuki, Eiji Takita, Kiyoshi Ohyama, Satoru Sawai, Hikaru Seki,

Nozomu Sakurai, Toshiya Muranaka, Masao Ishimoto, Hiroshi Sudo,

Kazuki Saito, and Daisuke Shibata

12.1 Introduction 227

12.2 Methods and Protocols 233

12.2.1 Chemicals 233

12.2.2 Plasmid Construction of Multi-Gene Transformation 233

12.2.3 Preparation of Dual Terminator (DT) Fragment by PCR-Based

Overlap Extension Method 233

12.2.4 Plasmid Construction of pUHR KS CSPS Thsp 236

12.2.5 Construction of pHSG299 CSPS 35S-CYP88-DT (Figure 12.2a) 236

12.2.6 Construction of pHSG299 CSPS 35S-CYP72-DT2 (Figure 12.2a) 237

12.2.7 Construction of pHSG299-CYP93(RNAi)-DT (Figure 12.2a) 238

12.2.8 Construction of pUHR KS CSPS Thsp-CYP88-CYP72-CYP93

(RNAi) 239

12.2.9 Transformation of Soybean by Particle Bombardment 239

12.2.9.1 Preparation of Embryogenic Suspension Tissue Culture 239

12.2.9.2 Preparation of Plasmid DNA for Particle Bombardment 240

12.2.9.3 Conditions of Particle Bombardment 240

12.2.9.4 Selection and Generation of Transgenic Soybean Plants 240

12.2.10 GC-MS Analysis for Triterpene Glycone 241

12.2.10.1 Extraction of Metabolite 241

12.2.10.2 Acid Treatment of Extracted Metabolites 241

12.2.10.3 Derivatization of Metabolites 242

12.2.11 GC-MS Conditions 242

12.3 Application of Technology 242

12.4 Perspectives 243

References 243

Part III Metabolomics and Genomics 245

13 Metabolomics-Assisted Plant Breeding 247

Alexander Herrmann and Nicolas Schauer

13.1 Introduction 247

13.2 Method 249

13.3 Applications of the Technology 251

13.4 Perspective 253

References 254

Contents jXIII

14 Conducting Genome-Wide Association Mapping of Metabolites 255

Susanna Atwell and Daniel J. Kliebenstein

14.1 Introduction 255

14.2 Methods and Protocols 256

14.2.1 Biological Question to Be Addressed 256

14.2.2 Chemistry to Study 256

14.2.2.1 Chemical Class 256

14.2.2.2 Extraction and Detection Platform 257

14.2.3 Species Choice 258

14.2.3.1 Genotypic Choices 258

14.2.3.2 GWA Populations Available 259

14.2.3.3 Domestication Status 260

14.2.3.4 Ability to Conduct Appropriate Follow-Up Experiments 260

14.2.4 Should I Utilize an Additional Perturbation? 260

14.2.5 Conducting the Phenotype Measurements 261

14.2.6 Computational Platform to Use for Analysis 261

14.2.6.1 Single Marker Analysis 262

14.2.6.2 Population Structure Modification 262

14.2.6.3 Resulting GWA Plots 262

14.2.6.4 Gene-Based Approaches 263

14.2.6.5 What Should I Use and How Do I Use It? 263

14.2.7 Candidate Gene Selection 265

14.2.8 Candidate Gene Validation 266

14.2.8.1 Validate That the Gene Influences the Phenotype? 267

14.2.8.2 Validate That Natural Variation in the Gene Influences the

Phenotype 267

14.3 Applications 267

14.4 Perspectives 268

References 268

Part IV Metabolomics and Bioinformatics 273

15 Metabolite Clustering and Visualization of Mass Spectrometry Data

Using One-Dimensional Self-Organizing Maps 275

Alexander Kaever, Manuel Landesfeind, Kirstin Feussner, Ivo Feussner,

and Peter Meinicke

15.1 Introduction 275

15.2 Methods and Protocols 276

15.2.1 Data Import 277

15.2.2 Clustering 277

15.2.3 Cluster Analysis 280

15.3 Applications of the Technology 281

15.4 Perspectives 286

References 286

XIVj Contents

16 Metabolite Identification and Computational Mass Spectrometry 289

Steffen Neumann, Florian Rasche, Sebastian Wolf, and Sebastian B€ocker

16.1 Introduction 289

16.2 Annotation and Identification of Metabolites 290

16.2.1 Exact Mass Search in Compound Libraries 291

16.2.2 Deriving the Elemental Composition from MS1 292

16.2.3 Elemental Composition from MS2 and MSn 293

16.2.4 In Silico Library Search with MetFrag 294

16.2.5 Reference Spectral Library Lookup 299

16.3 Perspectives 302

References 303

17 Using COVAIN to Analyze Metabolomics Data 305

Xiaoliang Sun and Wolfram Weckwerth

17.1 Introduction 305

17.2 Methods 308

17.2.1 Data Preprocessing 308

17.2.1.1 Imputation of Missing Values 308

17.2.1.2 Transformations to Satisfy Prerequisites of Statistical Methods 310

17.2.1.3 Adjusting Outliers 310

17.2.1.4 Scaling 310

17.2.1.5 Filtering by Statistical Features 310

17.2.2 Uni- and Bivariate Statistical Methods for Individual

Metabolite-Level Analysis 311

17.2.2.1 ANOVA Compares Single Metabolite Levels 311

17.2.2.2 Correlation Coefficients Interpret the Relationships Between

Pairwise Two Metabolites 311

17.2.2.3 Granger Causality Analysis Identifies the Causation Between

Pairwise Two Metabolites in Time-Series Data 311

17.2.3 Multivariate Statistical Methods for Group-Level Analysis 312

17.2.3.1 PCA Distinguishes Phenotypes and Finds Most Influencing

Metabolites 312

17.2.3.2 Independent Component Analysis Distinguishes Phenotypes

and Finds the Latent Sources of Metabolites in Time-Series Data 312

17.2.3.3 Clustering Classifies Data Into Groups 312

17.2.4 Network-Level Analysis 313

17.2.4.1 Network Mapping 313

17.2.4.2 Network Inference 313

17.2.5 Influences of Data Preprocessing on Statistical Analysis Results 313

17.2.5.1 On the Mean Values: ANOVA, Correlation Coefficient, Granger

Analysis, and Clustering 313

17.2.5.2 On the Variance and Covariance: ANOVA, PCA, and ICA 314

17.3 Application 314

17.4 Perspective 320

References 320

Contents jXV

18 Mass Spectral Search and Analysis Using the Golm Metabolome

Database 321

Jan Hummel, Nadine Strehmel, Christian B€olling, Stefanie Schmidt,

Dirk Walther, and Joachim Kopka

18.1 Introduction 321

18.2 Methods and Protocols: the GMD and Supported Data Analysis

Workflows 322

18.2.1 The GMD Data Entities 322

18.2.2 The Text Search Queries 325

18.2.3 The Mass Spectrum Query Submission and Analysis Options 325

18.2.3.1 Mass Spectral Matching 326

18.2.3.2 Decision Tree (DT)-Supported Substructure Prediction 329

18.2.4 Interpreting the Mass Spectral Analysis Results 329

18.2.4.1 The Mass Spectral Matching Results 329

18.2.4.2 The Substructure Prediction Results 332

18.2.4.3 Interpreting Decision Trees 333

18.2.5 The Web Services at GMD 336

18.2.5.1 General Considerations 336

18.2.5.2 The GMD Web Service Modules 337

18.2.6 The GMD Download Options 338

18.3 Applications and Perspectives 341

References 342

Glossary 345

Index 415

XVIj Contents