Metabolomics

by Nielsen, Jens; Jewett, Michael C.

• ISBN13: 9783540747185
• ISBN10: 3540747184
• Edition: 1st
• Format: Hardcover
• Copyright: 2007-12-04
• Publisher: Springer Verlag

Summary

The metabolome comprises the complete set of metabolites, the non-genetically encoded substrates, intermediates, and products of metabolic pathways, associated with a cell. Given the increasing demand to quantitatively identify the metabolome and understand how trafficking of metabolites through the metabolic network impact cellular behavior, metabolomics has emerged as an important complementary technology to the cell-wide measurements of mRNA, proteins, fluxes, and interactions (e.g., protein-DNA). Metabolomics is already a powerful tool in drug discovery and development and in metabolic engineering. While maintaining these strengths, the field promises to play a heightened role in systems biology research, which is transforming the practice of medicine and our ability to engineer living organisms. This book brings together the latest results in the field of metabolomics. It comprehensively presents the current state of the metabolomics field by underscoring experimental methods, analysis techniques, standardization practices, and advances in specific model systems. As a result, it significantly broadens our perspective on the principles and strategies underpinning this emerging field.

Table of Contents

The role of metabolomics in systems biology	p. 1
Abstract	p. 1
Metabolomics	p. 1
Applications of metabolomics	p. 3
The role of metabolomics in systems biology	p. 4
Outline of this book	p. 6
References	p. 8
Analytical methods from the perspective of method standardization	p. 11
Abstract	p. 11
Introduction	p. 11
Pre-analytical variability	p. 13
Biological variability	p. 13
Variability introduced during sampling	p. 14
Variability introduced during sample processing	p. 19
Intra-analytical variability	p. 28
GC-MS	p. 29
ESI-MS	p. 37
Conclusions	p. 43
Post-analytical issues	p. 43
Final remarks	p. 44
Acknowledgments	p. 45
References	p. 45
Abbreviations	p. 51
Reporting standards	p. 53
Abstract	p. 53
Introduction	p. 53
Data handling in metabolomics	p. 54
Standards, models, and formats	p. 56
Initiatives in metabolomics data standards	p. 60
MIAMI IT	p. 60
ArMet	p. 61
SMRS	p. 61
MSI	p. 62
Reporting standards in other fields	p. 62
Transcriptomics	p. 62
Proteomics	p. 64
Cross-domain standards	p. 64
Issues in metabolomics standards	p. 66
The detailed nature of standards	p. 66
Controlled vocabularies and ontologies	p. 68
Chemical identity	p. 69
Conclusions	p. 70
References	p. 70
The Golm Metabolome Database: a database for GC-MS based metabolite profiling	p. 75
Abstract	p. 75
Introduction	p. 75
Pathway databases	p. 77
Cheminformatics databases	p. 78
Databases dedicated to metabolite profiling	p. 79
The Golm Metabolome Database (GMD)	p. 80
Database objects	p. 80
Information exchange between databases	p. 81
The main work flows of metabolite profiling	p. 82
The metabolite profiling work flow: from sample to metabolite fingerprint and profile	p. 83
The metabolite mapping work flow: from metabolite to specific and selective GC-MS mass fragment	p. 85
The main database objects	p. 87
Modelling the "MST" database object	p. 87
Modelling the "chemical substance" database object	p. 88
Outlook	p. 90
References	p. 91
List of abbreviations	p. 95
Reconstruction of dynamic network models from metabolite measurements	p. 97
Abstract	p. 97
Introduction	p. 97
Quantitative measurements of intracellular metabolites	p. 99
Use of metabolite measurements for identification of dynamic models	p. 103
Modular decomposition of the network	p. 103
In silico identification of whole cell metabolite dynamics through evolutionary algorithms and parallel computing	p. 118
Identification of kinetic rate expression from series of steady state observations	p. 122
Summary and outlook	p. 123
References	p. 124
Toward metabolome-based 13C flux analysis: a universal tool for measuring in vivo metabolic activity	p. 129
Abstract	p. 129
Introduction	p. 129
Fundamentals of metabolic flux analysis	p. 132
Principles of labeling experiments	p. 133
Current practice of stationary 13C flux analysis	p. 135
Experimental design	p. 135
From analytes to 13C labeling patterns	p. 136
From 13C labeling patterns to fluxes	p. 138
Toward metabolome-based 13C flux analysis	p. 144
Experimental proof-of-concept	p. 144
Analytics: lessons from metabolomics	p. 145
Current developments	p. 147
Conclusions	p. 151
Acknowledgements	p. 151
References	p. 151
List of abbreviations	p. 157
Data acquisition, analysis, and mining: Integrative tools for discerning metabolic function in Saccharomyces cerevisiae	p. 159
Abstract	p. 159
Yeast as a model system for metabolomics	p. 159
Metabolite analysis workflow	p. 161
Chemical analysis	p. 162
Quenching	p. 162
Extraction	p. 162
Analytical methods	p. 163
Standardization	p. 165
Data analysis	p. 165
Pre-processing	p. 166
Statistical analysis	p. 169
Classification	p. 175
Genetic programming	p. 175
SpectConnect	p. 176
Data integration	p. 177
Future outlook	p. 180
Acknowledgements	p. 180
References	p. 180
E. coli metabolomics: capturing the complexity of a "simple" model	p. 189
Abstract	p. 189
Introduction	p. 189
Experimental methods	p. 190
Quenching of metabolism and metabolite extraction	p. 191
Main analytical methods tested with E. coli	p. 193
Groundwork	p. 198
Combining concentration data with enzyme activity and flux measurements	p. 201
Emerging metabolomic studies in E. coli	p. 202
Evaluating the size of the E. coli metabolome	p. 203
Hints from genome-based models	p. 203
Experimental clues	p. 203
Improving metabolite identification	p. 204
Architecture/anatomy of the E. coli metabolome	p. 206
Metabolite architecture	p. 206
Pathway architecture	p. 206
E. coli metabolomics as a powerful tool for functional genomics	p. 207
Metabolic footprinting	p. 208
Enzyme discovery using non-targeted metabolomics	p. 208
Deorphanizing enzymatic activities and filling-in metabolic pathway holes	p. 212
Phenotype microarrays as reporters of metabolic phenotype	p. 212
Metabolomics to facilitate metabolic engineering of E. coli	p. 213
Metabolomics in flux analysis	p. 215
Adaptive evolution in E. coli, metabolomics, and metabolic phenotype	p. 215
Metabolic models of E. coli: the role of metabolomics	p. 216
Databases and resources	p. 218
Data integration and visualization	p. 221
Future prospects and developments	p. 222
Concluding remarks	p. 223
Acknowledgement	p. 223
References	p. 224
Abbreviations	p. 234
The exo-metabolome in filamentous fungi	p. 235
Abstract	p. 235
Introduction	p. 235
Exo-metabolome and taxonomy	p. 236
Exo-metabolome and fungal growth	p. 237
Visualisation of the exo-metabolome	p. 239
Extraction of the exo-metabolome	p. 240
Analysis of the exo-metabolome by high performance liquid chromatography	p. 242
Direct infusion electrospray mass spectrometry for profiling	p. 247
Outlook - a polyphasic approach	p. 248
Acknowledgements	p. 249
References	p. 249
The importance of anatomy and physiology in plant metabolomics	p. 253
Abstract	p. 253
Introduction	p. 253
Importance of plants	p. 253
Plant metabolomics	p. 254
Plant anatomy	p. 255
Whole plant anatomy	p. 255
Cell anatomy	p. 256
Plant physiology - Challenges for plant metabolomics	p. 260
Photosynthesis	p. 260
Photorespiration	p. 260
Transpiration	p. 262
Starch and other storage products	p. 262
Cell wall synthesis	p. 263
Secondary metabolites	p. 266
Unique aspects of plant research	p. 267
Functional genomics	p. 267
Breeding and QTL analysis	p. 268
Genetic engineering	p. 270
Recent, current and future of plant metabolomics	p. 272
Successful applications	p. 272
Future	p. 274
References	p. 274
Index	p. 279
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