Metabolomics: Metabolites, Metabonomics, and Analytical Technologies

METABOLOMICS: METABOLITES, METABONOMICS, AND ANALYTICAL TECHNOLOGIES......Page 3
METABOLOMICS: METABOLITES, METABONOMICS, AND ANALYTICAL TECHNOLOGIES......Page 5
CONTENTS......Page 7
PREFACE......Page 9
Abstract......Page 15
I. Introduction......Page 16
II.2. Repeated Experiments for Highlighting of Metabolic States......Page 17
III.1. Classification of Metabolomic Approaches Based on Different Criteria......Page 20
III.3. Transition Matrix Based Approaches......Page 23
III.4. Stoichiometric Matrix Based Approaches......Page 24
III.5. Jacobian Matrix Based Approach......Page 26
IV. Metabolomic Approaches Based on Distance and Correlation Matrices......Page 33
IV.1. Correlation Based Approaches......Page 35
IV.1.1. Graphical Identification of Correlation Models......Page 36
IV.1.2. Data Transformation to Application of Linear Model......Page 37
IV.1.3. Correlation Coefficient Computation......Page 38
IV.1.3.1. Pearson Correlation Computation......Page 40
IV.1.3.2. Matrix Correlation Computation......Page 43
IV.1.3.3. Spearman Correlation Calculation......Page 44
IV.1.4. Origins and Interpretation of Correlations in Metabolic Systems......Page 49
IV.1.5. Scale-Dependent Interpretations of Correlations......Page 50
IV.1.6.1. Aim......Page 52
IV.1.6.3. Computation of Eigenvalues, Eigenvectors and Principle Components......Page 55
IV.1.6.5. Different Types of PCA......Page 60
IV.1.6.6. Numerical Application and Interpretation of Standardized PCA......Page 61
IV.2.1. Introduction......Page 64
IV.2.3. General Protocols in Hierarchical Cluster Analysis (HCA)......Page 65
IV.2.4.1.1. Euclidean Distance......Page 67
IV.2.4.1.2. Chi-Square Distance......Page 68
IV.2.5. Clustering Techniques......Page 71
IV.2.5.2. Complete Link-Based Clustering......Page 72
IV.2.5.5. Variance Criterion Clustering: Ward Method......Page 73
IV.2.6. Identification and Interpretation of Clusters from Dendrogram......Page 75
V.1. Introduction......Page 76
V.3. Statistical Criteria for Identification of Outliers......Page 77
V.4. Graphical Identification of Univariate Outliers......Page 78
V.5. Graphical Identification of Bivariate Outliers......Page 79
V.6. Identification of Multivariate Outliers Based on Distance Computations......Page 80
V.6.1. Standard Mahalanobis Distance Computation......Page 81
V.6.2. Jackknifed Mahalanobis Distance Computation......Page 83
V.6.3.1. General Concepts of Correspondence Analysis......Page 85
V.6.3.2 Basic Computations in Correspondence Analysis......Page 86
V.6.3.3. Graphical Interpretation of CA Results and Outlier Diagnostic......Page 88
V.6.4.3. Graphical Outlier Diagnostic Based on Andrews Curves......Page 92
References......Page 94
Abstract......Page 101
Introduction......Page 102
Metabolomics and Cancer......Page 103
Cancer Metabolism......Page 106
Metabolism and Cancer: Cause or Epiphenomenon?......Page 108
Phenotype Metabolism, Cell Shape and Microenvironment......Page 111
Cancer Cell Shape......Page 113
Cell Shape and Metabolic Phenotype......Page 116
Conclusion......Page 122
References......Page 123
Abstract......Page 135
Introduction......Page 136
Origins and Development: Looking Back......Page 138
Sample Preparation......Page 143
GC-MS Analysis......Page 144
Sample Preparation......Page 146
LC-MS Analysis......Page 147
Direct Infusion MS and MS/MS......Page 152
Desorption and Imaging MS......Page 153
Data Handling......Page 156
References......Page 158
Introduction......Page 177
Environment - Abiotic Interactions......Page 178
Nutrient Deficiency......Page 179
Drought......Page 180
Ozone......Page 181
UltraViolet Radiation......Page 182
Ecology......Page 183
Floral Scents......Page 184
Genetic versus Environmental Influences on the Metabolome......Page 185
Populations......Page 186
References......Page 187
Introduction......Page 195
The Concept of Genomics in Microbial Ecology......Page 196
Microbial Metagenomics: Major Procedural Steps......Page 197
Sampling and Microbial Nucleic Acids Extraction......Page 198
Metagenome Cloning and Targeting......Page 199
The Function-Driven Analysis......Page 200
Genomics in Mammalian Gut Microbial Diversity......Page 203
Metagenomics in Rumen Microbiome-Motives and Applications......Page 204
1. Rumen Microbes as Sources of Valuable Hydrolytic Enzymes......Page 205
3. Rumen-Originated Antimicrobial Products......Page 207
5. Determining the Protozoal Ecology of the Rumen......Page 208
Conclusion......Page 209
References......Page 210
Abstract......Page 215
Nutrigenomics Concept......Page 216
Nutrient-Gene Interaction......Page 217
Nutrigenomics in Livestock Perspective......Page 218
What is Metabolomics?......Page 219
Techniques and Data Analysis in Metabolomics......Page 220
What Is Metabonomics?......Page 222
Sample Analysis and Data Processing in Metabonomics......Page 224
References......Page 225
Abstract......Page 229
1.Introduction......Page 230
2.Metabolic Pathways......Page 232
3.The Symbolic-Statistical Framework PRISM......Page 233
4.Modeling Bisphenol A Degradation Pathway in PRISM......Page 235
5.Reconstructing Pathways from Sequences of Reactions......Page 237
7.Conclusion and Future Work......Page 239
References......Page 240
A. General Information on Metabolomics......Page 243
•  HMDB [15]......Page 244
•  PathAligner [23]......Page 245
1. Application in Oncology......Page 246
2. Application in Pharmacology......Page 247
B. Pathway Drawing......Page 248
C. Usefulness of Pathway Analysis......Page 249
3. ArrayxPath [55]......Page 251
References......Page 252
Introduction......Page 257
Imbalance in Estrogen Homeostasis......Page 258
The Mammary Gland of ERKO/Wnt-1 Mice......Page 259
The Prostate of Noble Rats......Page 260
Estrogen-Induced Mutations and Cell Transformation......Page 261
References......Page 262
INDEX......Page 267