Pathway Analysis and Optimization in Metabolic Engineering

Facility in the targeted manipulation of the genetic and metabolic composition of organisms, combined with unprecedented computational power, is forging a niche for a new subspecialty of biotechnology called metabolic engineering. First published in 2002, this book introduces researchers and advanced students in biology and engineering to methods of optimizing biochemical systems of biotechnological relevance. It examines the development of strategies for manipulating metabolic pathways, demonstrates the need for effective systems models, and discusses their design and analysis, while placing special emphasis on optimization. The authors propose power-law models and methods of biochemical systems theory toward these ends. All concepts are derived from first principles, and the text is richly illustrated with numerous graphs and examples throughout. Special features include: nontechnical and technical introductions to models of biochemical systems; a review of basic methods of model design and analysis; concepts of optimization; and detailed case studies. Contents......Page 8 Preface......Page 10 CRITERIA FOR MODEL SELECTION......Page 16 MODELS OF BIOCHEMICAL PROCESSES......Page 21 SUMMARY......Page 50 2 Methods of Biochemical Systems Theory......Page 57 MODEL DESIGN......Page 58 DESIGN OF EQUATIONS IN BST......Page 61 PARAMETER ESTIMATION......Page 63 DYNAMIC ANALYSIS......Page 71 STEADY-STATE ANALYSIS......Page 75 STABILITY ANALYSIS......Page 79 EVALUATION AND INTERPRETATION......Page 82 INTRODUCTION......Page 90 BASIC CHEMISTRY AND BIOCHEMISTRY OF CITRIC ACID......Page 91 A FIRST MATHEMATICAL MODEL......Page 94 REVISED MODEL......Page 120 QUALITY ASSESSMENT OF THE REVISED MODEL......Page 141 4 Optimization Methods......Page 149 ANALYTICAL METHODS......Page 150 SEARCH ALGORITHMS......Page 168 INTRODUCTION......Page 177 ARE NONLINEARITIES REALLY NECESSARY?......Page 181 SEARCHING FOR EXTREMA OF LINEAR FUNCTIONS WITH MANY VARIABLES......Page 184 OPTIMIZATION OF STOICHIOMETRIC NETWORKS......Page 190 OPTIMIZATION OF S-SYSTEMS......Page 192 OPTIMIZATION OF GMA SYSTEMS......Page 195 MULTIPLE CRITERIA OPTIMIZATION......Page 197 OPTIMIZATION OF STRUCTURE......Page 204 INTRODUCTION......Page 212 A LINEAR PROGRAM FOR OPTIMIZED CITRIC ACID PRODUCTION IN......Page 214 OPTIMAL SOLUTIONS......Page 222 SYSTEMATIC SEARCH FOR THE BEST SEQUENCE OF STEPS TOWARD THE OPTIMAL SOLUTION......Page 225 ANALYSIS OF THE EFFECTS OF IMPRECISION DURING IMPLEMENTATION......Page 229 CONCLUSIONS......Page 237 INTRODUCTION......Page 242 BACKGROUND......Page 244 KINETIC MODEL......Page 246 S-SYSTEM MODEL......Page 249 QUALITY ASSESSMENT OF THE MODEL......Page 250 OPTIMIZATION: THE INDIRECT OPTIMIZATION METHOD (IOM)......Page 253 RESULTS......Page 259 QUALITY ASSESSMENT OF THE INDIRECT OPTIMIZATION METHOD......Page 267 MULTI-OBJECTIVE OPTIMIZATION......Page 273 DISCUSSION......Page 282 8 Conclusions......Page 288 L-CARNITINE PRODUCTION IN HIGH-DENSITY CULTURES OF......Page 289 TRYPTOPHAN BIOSYNTHESIS IN......Page 292 TRENDS IN PATHWAY ANALYSIS AND THE ROLE OF GENE TECHNOLOGY AND GENOMICS......Page 294 THE FUTURE HAS BEGUN......Page 301 Author Index......Page 306 Subject Index......Page 314 This book, first published in 2002, introduces methods of optimizing biochemical systems of biotechnological relevance. It examines the development of strategies for manipulating metabolic pathways and discusses the design and analysis of systems models. All concepts are derived from first principles and the well-illustrated text is accompanied by two detailed case studies. This book introduces methods of optimizing biochemical systems of biotechnological relevance. It examines the development of strategies for manipulating metabolic pathways and discusses the design and analysis of systems models. All concepts are derived from first principles, the text is illustrated with graphs and examples, and two detailed case studies are presented Before we get lost in the technical details of manipulating functions, approximating complicated phenomena, or designing and analyzing models, it is useful to establish more clearly what exactly our target is.