SILAS G. VILLAS-BÔAS, PHD, is a Research Scientist at AgResearch Limited in New Zealand. UTE ROESSNER, PHD, is a Post-Doctoral Fellow at the Australian Centre for Plant Functional Genomics at the University of Melbourne, Australia.?MICHAEL A. E. HANSEN, PHD, is a Post-Doctoral Fellow at BioCentrum-DTU, Technical University of Denmark.JØRN SMEDSGAARD, PHD, is an Associate Professor at the Center for Microbial Biotechnology, BioCentrum-DTU?at the Technical University of Denmark.JENS NIELSEN, PROFESSOR, Dr. techn., PHD, is the Director of the Center for Microbial Biotechnology at the Technical University of Denmark.

"Overall, this book provides a great introduction to metabolomics and at a retail price of approximately $75, it has great value. The intended audience for this book includes new metabolomics practitioners and undergraduate/graduate students." (J Am Soc Mass Spectrom, 2007)

• Preface xiiiList of Contributors xvPart I: Concepts and Methodology1 Metabolomics in Functional Genomics and Systems Biology 31.1 From genomic sequencing to functional genomics 31.2 Systems biology and metabolic models 61.3 Metabolomics 81.4 Future perspectives 112 The Chemical Challenge of the Metabolome 152.1 Metabolites and metabolism 152.2 The structural diversity of metabolites 182.2.1 The chemical and physical properties 182.2.2 Metabolite abundance 232.2.3 Primary and secondary metabolism 242.3 The number of metabolites in a biological system 252.4 Controlling rates and levels 262.4.1 Control by substrate level 272.4.2 Feedback and feedforward control 272.4.3 Control by “pathway independent” regulatory molecules 272.4.4 Allosteric control 282.4.5 Control by compartmentalization 302.4.6 The dynamics of the metabolism—the mass flow 312.4.7 Control by hormones 332.5 Metabolic channeling or metabolons 332.6 Metabolites are arranged in networks that are part of a cellular interactome 353 Sampling and Sample Preparation 393.1 Introduction 393.2 Quenching—the first step 413.2.1 Overview on metabolite turnover 413.2.2 Different methods for quenching 443.2.3 Quenching microbial and cell cultures 443.2.4 Quenching plant and animal tissues 503.3 Obtaining metabolites from biological samples 523.3.1 Release of intracellular metabolites 523.3.2 Structure of the cell envelopes—the main barrier to be broken 523.3.3 Cell disruption methods 583.3.4 Nonmechanical disruption of cell envelopes 593.3.5 Mechanical disruption of cell envelopes 663.4 Metabolites in the extracellular medium 713.4.1 Metabolites in solution 723.4.2 Metabolites in the gas phase 753.5 Improving detection via sample concentration 764 Analytical Tools 834.1 Introduction 834.2 Choosing a methodology 844.3 Starting point—samples 864.4 Principles of chromatography 874.4.1 Basics of chromatography 874.4.2 The chromatogram and terms in chromatography 904.5 Chromatographic systems 934.5.1 Gas chromatography 944.5.2 HPLC systems 1024.6 Mass spectrometry 1064.6.1 The mass spectrometer—an overview 1074.6.2 GC-MS—the EI ion source 1094.6.3 LC-MS—the ESI ion source 1114.6.4 Mass analyzer—the quadrupole 1154.6.5 Mass analyzer—the ion-trap 1174.6.6 Mass analyzer—the time-of-flight 1194.6.7 Detection and computing in MS 1214.7 The analytical work-flow 1254.7.1 Separation by chromatography 1254.7.2 Mass spectrometry 1284.7.3 General analytical considerations 1294.8 Data evaluation 1294.8.1 Structure of data 1294.8.2 The chromatographic separation 1324.8.3 Mass spectral data 1334.8.4 Exporting data for processing 1354.9 Beyond the core methods 1364.9.1 Developments in chromatography 1374.9.2 Capillary electrophoresis 1394.9.3 Tandem MS and advanced scanning techniques 1414.9.4 NMR spectrometry 1434.10 Further reading 1445 Data Analysis 1465.1 Organizing the data 1465.2 Scales of measurement 1475.2.1 Qualitative data 1485.2.2 Quantitative data 1485.3 Data structures 1485.4 Preprocessing of data 1505.4.1 Calibration of data 1505.4.2 Combining profile scans 1515.4.3 Filtering 1525.4.4 Centroid calculation 1565.4.5 Internal mass scale correction 1565.4.6 Binning 1575.4.7 Baseline correction 1575.4.8 Chromatographic profile matching 1635.5 Deconvolution of spectroscopic data 1665.6 Data standardization (normalization) 1675.7 Data transformations 1685.7.1 Principal component analysis 1685.7.2 Fisher discriminant analysis 1715.8 Similarities and distances between data 1735.8.1 Continuous functions 1735.8.2 Binary functions 1765.9 Clustering techniques 1785.9.1 Hierarchical clustering 1785.9.2 k-means clustering 1815.10 Classification techniques 1825.10.1 Decision theory 1835.10.2 k-nearest neighbor 1845.10.3 Tree-based classification 1845.11 Integrated tools for automation libraries and data evaluation 185Part II—case Studies and Reviews6 Yeast Metabolomics: The Discovery of New Metabolic Pathways in Saccharomyces cerevisiae 1916.1 Introduction 1916.2 Brief description of the methodology used 1926.2.1 Sample preparation 1926.2.2 The analysis 1946.3 Early discoveries 1946.4 Yeast stress response gives evidence of alternative pathway for glyoxylate biosynthesis in S. cerevisiae 1956.5 Biosynthesis of glyoxylate from glycine in S. cerevisiae 1966.5.1 Stable isotope labeling experiment to investigate glycine catabolism in S. cerevisiae 1986.5.2 Data leveraged for speculation 2017 Microbial Metabolomics: Rapid Sampling Techniques to Investigate Intracellular Metabolite Dynamics—An Overview 2037.1 Introduction 2037.2 Starting with a simple sampling device proposed by Theobald et al. (1993) 2047.3 An improved device reported by Lange et al. (2001) 2057.4 Sampling tube device by Weuster-Botz (1997) 2077.5 Fully automated device by Schaefer et al. (1999) 2097.6 The stopped-flow technique by Buziol et al. (2002) 2097.7 The BioScope: a system for continuous-pulse experiments 2127.8 Conclusions and perspectives 2138 Plant Metabolomics 2158.1 Introduction 2158.2 History of plant metabolomics 2178.3 Plants their metabolism and metabolomics 2198.3.1 Plant structures 2198.3.2 Plant metabolism 2228.4 Specific challenges in plant metabolomics 2238.4.1 Light dependency of plant metabolism 2238.4.2 Extraction of plant metabolites 2258.4.3 Many cell types in one tissue 2258.4.4 The dynamical range of plant metabolites 2268.4.5 Complexity of the plant metabolome 2268.4.6 Development of databases for metabolomics-derived data in plant science 2288.5 Applications of metabolomics approaches in plant research 2298.5.1 Phenotyping 2298.5.2 Functional genomics 2318.5.3 Fluxomics 2328.5.4 Metabolic trait analysis 2328.5.5 Systems biology 2348.6 Future perspectives 2349 Mass Profiling of Fungal Extract from Penicillium Species 2399.1 Introduction 2399.2 Methodology for screening of fungi by DiMS 2429.2.1 Cultures 2439.2.2 Extraction 2439.2.3 Analysis by direct infusion mass spectrometry 2449.3 Discussion 2459.3.1 Initial data processing 2459.3.2 Metabolite prediction 2469.3.3 Chemical diversity and similarity 2489.4 Conclusion 25210 Metabolomics in Humans and Other Mammals 25310.1 Introduction 25310.2 A brief history of mammalian metabolomics 25710.3 Sample preparation for mammalian metabolomics studies 26010.3.1 Working with blood 26210.3.2 Working with urine 26310.3.3 Working with cerebrospinal fluid 26410.3.4 Working with cells and tissues 26710.4 Sample analysis 26810.4.1 GC-MS analysis of urine plasma and CSF 26910.4.2 LC-MS analysis of urine blood and CFS 27110.4.3 NMR analysis of CSF urine and blood 27410.5 Applications 27710.5.1 Identification and classification of metabolic disorders 27810.6 Future outlook 283Index 289