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Full Description
Providing information on the main approaches for the analysis of metabolites, this textbook:
Covers basic methodologies in sample preparation and separation techniques, as well as the most recent techniques of mass spectrometry.
Differentiates between primary and secondary metabolites.
Includes four chapters discussing successful metabolome studies of different organisms.
Highlights the analytical challenges of studying metabolites.
Illustrates applications of metabolome analysis through the use of case studies.
Contents
Preface xiii
List of Contributors xv
Part I: Concepts and Methodology
1 Metabolomics in Functional Genomics and Systems Biology 3
1.1 From genomic sequencing to functional genomics 3
1.2 Systems biology and metabolic models 6
1.3 Metabolomics 8
1.4 Future perspectives 11
2 The Chemical Challenge of the Metabolome 15
2.1 Metabolites and metabolism 15
2.2 The structural diversity of metabolites 18
2.2.1 The chemical and physical properties 18
2.2.2 Metabolite abundance 23
2.2.3 Primary and secondary metabolism 24
2.3 The number of metabolites in a biological system 25
2.4 Controlling rates and levels 26
2.4.1 Control by substrate level 27
2.4.2 Feedback and feedforward control 27
2.4.3 Control by "pathway independent" regulatory molecules 27
2.4.4 Allosteric control 28
2.4.5 Control by compartmentalization 30
2.4.6 The dynamics of the metabolism—the mass flow 31
2.4.7 Control by hormones 33
2.5 Metabolic channeling or metabolons 33
2.6 Metabolites are arranged in networks that are part of a cellular interactome 35
3 Sampling and Sample Preparation 39
3.1 Introduction 39
3.2 Quenching—the first step 41
3.2.1 Overview on metabolite turnover 41
3.2.2 Different methods for quenching 44
3.2.3 Quenching microbial and cell cultures 44
3.2.4 Quenching plant and animal tissues 50
3.3 Obtaining metabolites from biological samples 52
3.3.1 Release of intracellular metabolites 52
3.3.2 Structure of the cell envelopes—the main barrier to be broken 52
3.3.3 Cell disruption methods 58
3.3.4 Nonmechanical disruption of cell envelopes 59
3.3.5 Mechanical disruption of cell envelopes 66
3.4 Metabolites in the extracellular medium 71
3.4.1 Metabolites in solution 72
3.4.2 Metabolites in the gas phase 75
3.5 Improving detection via sample concentration 76
4 Analytical Tools 83
4.1 Introduction 83
4.2 Choosing a methodology 84
4.3 Starting point—samples 86
4.4 Principles of chromatography 87
4.4.1 Basics of chromatography 87
4.4.2 The chromatogram and terms in chromatography 90
4.5 Chromatographic systems 93
4.5.1 Gas chromatography 94
4.5.2 HPLC systems 102
4.6 Mass spectrometry 106
4.6.1 The mass spectrometer—an overview 107
4.6.2 GC-MS—the EI ion source 109
4.6.3 LC-MS—the ESI ion source 111
4.6.4 Mass analyzer—the quadrupole 115
4.6.5 Mass analyzer—the ion-trap 117
4.6.6 Mass analyzer—the time-of-flight 119
4.6.7 Detection and computing in MS 121
4.7 The analytical work-flow 125
4.7.1 Separation by chromatography 125
4.7.2 Mass spectrometry 128
4.7.3 General analytical considerations 129
4.8 Data evaluation 129
4.8.1 Structure of data 129
4.8.2 The chromatographic separation 132
4.8.3 Mass spectral data 133
4.8.4 Exporting data for processing 135
4.9 Beyond the core methods 136
4.9.1 Developments in chromatography 137
4.9.2 Capillary electrophoresis 139
4.9.3 Tandem MS and advanced scanning techniques 141
4.9.4 NMR spectrometry 143
4.10 Further reading 144
5 Data Analysis 146
5.1 Organizing the data 146
5.2 Scales of measurement 147
5.2.1 Qualitative data 148
5.2.2 Quantitative data 148
5.3 Data structures 148
5.4 Preprocessing of data 150
5.4.1 Calibration of data 150
5.4.2 Combining profile scans 151
5.4.3 Filtering 152
5.4.4 Centroid calculation 156
5.4.5 Internal mass scale correction 156
5.4.6 Binning 157
5.4.7 Baseline correction 157
5.4.8 Chromatographic profile matching 163
5.5 Deconvolution of spectroscopic data 166
5.6 Data standardization (normalization) 167
5.7 Data transformations 168
5.7.1 Principal component analysis 168
5.7.2 Fisher discriminant analysis 171
5.8 Similarities and distances between data 173
5.8.1 Continuous functions 173
5.8.2 Binary functions 176
5.9 Clustering techniques 178
5.9.1 Hierarchical clustering 178
5.9.2 k-means clustering 181
5.10 Classification techniques 182
5.10.1 Decision theory 183
5.10.2 k-nearest neighbor 184
5.10.3 Tree-based classification 184
5.11 Integrated tools for automation libraries and data evaluation 185
Part II—case Studies and Reviews
6 Yeast Metabolomics: The Discovery of New Metabolic Pathways in Saccharomyces cerevisiae 191
6.1 Introduction 191
6.2 Brief description of the methodology used 192
6.2.1 Sample preparation 192
6.2.2 The analysis 194
6.3 Early discoveries 194
6.4 Yeast stress response gives evidence of alternative pathway for glyoxylate biosynthesis in S. cerevisiae 195
6.5 Biosynthesis of glyoxylate from glycine in S. cerevisiae 196
6.5.1 Stable isotope labeling experiment to investigate glycine catabolism in S. cerevisiae 198
6.5.2 Data leveraged for speculation 201
7 Microbial Metabolomics: Rapid Sampling Techniques to Investigate Intracellular Metabolite Dynamics—An Overview 203
7.1 Introduction 203
7.2 Starting with a simple sampling device proposed by Theobald et al. (1993) 204
7.3 An improved device reported by Lange et al. (2001) 205
7.4 Sampling tube device by Weuster-Botz (1997) 207
7.5 Fully automated device by Schaefer et al. (1999) 209
7.6 The stopped-flow technique by Buziol et al. (2002) 209
7.7 The BioScope: a system for continuous-pulse experiments 212
7.8 Conclusions and perspectives 213
8 Plant Metabolomics 215
8.1 Introduction 215
8.2 History of plant metabolomics 217
8.3 Plants their metabolism and metabolomics 219
8.3.1 Plant structures 219
8.3.2 Plant metabolism 222
8.4 Specific challenges in plant metabolomics 223
8.4.1 Light dependency of plant metabolism 223
8.4.2 Extraction of plant metabolites 225
8.4.3 Many cell types in one tissue 225
8.4.4 The dynamical range of plant metabolites 226
8.4.5 Complexity of the plant metabolome 226
8.4.6 Development of databases for metabolomics-derived data in plant science 228
8.5 Applications of metabolomics approaches in plant research 229
8.5.1 Phenotyping 229
8.5.2 Functional genomics 231
8.5.3 Fluxomics 232
8.5.4 Metabolic trait analysis 232
8.5.5 Systems biology 234
8.6 Future perspectives 234
9 Mass Profiling of Fungal Extract from Penicillium Species 239
9.1 Introduction 239
9.2 Methodology for screening of fungi by DiMS 242
9.2.1 Cultures 243
9.2.2 Extraction 243
9.2.3 Analysis by direct infusion mass spectrometry 244
9.3 Discussion 245
9.3.1 Initial data processing 245
9.3.2 Metabolite prediction 246
9.3.3 Chemical diversity and similarity 248
9.4 Conclusion 252
10 Metabolomics in Humans and Other Mammals 253
10.1 Introduction 253
10.2 A brief history of mammalian metabolomics 257
10.3 Sample preparation for mammalian metabolomics studies 260
10.3.1 Working with blood 262
10.3.2 Working with urine 263
10.3.3 Working with cerebrospinal fluid 264
10.3.4 Working with cells and tissues 267
10.4 Sample analysis 268
10.4.1 GC-MS analysis of urine plasma and CSF 269
10.4.2 LC-MS analysis of urine blood and CFS 271
10.4.3 NMR analysis of CSF urine and blood 274
10.5 Applications 277
10.5.1 Identification and classification of metabolic disorders 278
10.6 Future outlook 283
Index 289
