Outline placeholder......Page 0
Copyright......Page 2
Contributors......Page 3
Preface......Page 11
A Fundamental Definition of Systems Biology......Page 43
The Importance of the Integration of In Vivo and In Vitro Analyses......Page 45
Alternative Definitions of Systems Biology......Page 47
Different Types of Systems Biology......Page 48
References......Page 49
Mass Spectrometry in Systems Biology: An Introduction......Page 52
What is Mass Spectrometry?......Page 53
Mass Spectrometer Configurations......Page 54
Sample introduction......Page 56
Ionization sources......Page 58
Electron impact ionization......Page 59
Matrix-assisted laser desorption ionization......Page 60
Triple quadrupole mass analyzers......Page 61
Time-of-flight mass analyzers......Page 62
Quadrupole-time-of-flight hybrid systems......Page 63
Ion trap......Page 64
Fourier transform ion cyclotron resonance mass analyzers......Page 65
Ion mobility spectrometry......Page 66
The Benefits of Mass Spectrometry......Page 67
Structural characterization and identification......Page 68
Profiling of metabolomes and proteomes......Page 69
Acknowledgments......Page 70
References......Page 71
Abstract......Page 73
Arrays of plasmids coding for fluorescent fusion proteins......Page 74
Preparation of cell arrays......Page 78
Cell array stimulation......Page 79
Labeling of the PY72 antibody......Page 80
Automated FLIM......Page 81
Assessment of positives......Page 83
Arrays of plasmids coding for fluorescent fusion proteins......Page 84
FLIM and FLIM image processing......Page 85
Conclusion: Why Use CA-FLIM?......Page 86
General principles......Page 87
FLIM instrumentation......Page 88
Global Analysis of FRET-FLIM Data......Page 90
Materials......Page 91
References......Page 93
Absorption Spectroscopy......Page 95
Origins of spectra......Page 96
The Beer-Lambert law......Page 99
Instrumentation for absorption spectroscopy......Page 100
Estimation of protein concentration at 280nm (A280)......Page 102
Estimation of DNA melting temperature by absorption spectroscopy......Page 103
Enzyme kinetics......Page 104
Quenching and extraction of intracellular metabolites......Page 106
Metabolite extraction protocol......Page 107
Enzymatic rate assay for metabolite concentrations......Page 108
Acknowledgments......Page 110
References......Page 111
A Strand-Specific Library Preparation Protocol for RNA Sequencing......Page 112
NGS......Page 113
RNA sequencing......Page 114
ssRNA-Seq Protocol......Page 116
Selection of fragmentation approach......Page 117
Purification of polyA+RNA......Page 119
Isolation of polyA+RNA......Page 120
RNA fragmentation......Page 122
First-strand synthesis......Page 123
Removal of dNTPs......Page 124
ssRNA-Seq library preparation......Page 125
Required materials......Page 126
Adapter ligation......Page 127
Real-time quality check......Page 128
Amplification of the library......Page 129
References......Page 130
Quantitative Real-Time PCR-Based Analysis of Gene Expression......Page 132
Introduction......Page 133
Primer Validation Experiments......Page 134
Cell Culture-Based Isolation and Quantification of RNA......Page 135
Reverse Transcription......Page 136
Comparative gene expression experiments......Page 137
Required materials......Page 140
References......Page 142
Quantification of Proteins and Their Modifications Using QconCAT Technology......Page 143
Isotope-labeled peptides for absolute protein quantification......Page 144
Design for posttranslational modification quantification......Page 148
Transformation of expression E. coli strain with QconCAT plasmid......Page 149
Analysis of expressed QconCAT......Page 150
Extraction and purification of QconCAT protein......Page 151
Yeast......Page 153
Mammalian cells......Page 154
Considerations for the quantification of posttranslational modifications......Page 155
Defining transitions......Page 156
Software for data analysis......Page 157
Quantification of Posttranslational Modifications......Page 158
Replicate Analysis-Biological Versus Technical Replicates......Page 159
References......Page 160
Mass Spectrometric-Based Quantitative Proteomics Using SILAC......Page 162
Introduction......Page 163
Metabolic labeling of the cellular proteome......Page 164
General overview......Page 165
Experimental design......Page 168
SILAC media......Page 169
Determining the degree of incorporation of SILAC amino acids......Page 170
Analysis of SILAC-labeled cell extracts......Page 172
Quantification of SILAC peptides......Page 174
Relative quantification......Page 175
Studies of posttranslational modifications......Page 176
References......Page 177
Nucleic Acid Programmable Protein Array......Page 180
Introduction......Page 181
Overview of NAPPA Chemistry......Page 183
Array Production......Page 184
Preparation of nucleobond anion exchange resin plate for DNA preparation......Page 185
Preparation of plasmid DNA......Page 186
Production of arrays......Page 188
Expression of proteins......Page 189
Detection of captured proteins......Page 190
References......Page 191
Systems Biology of Recombinant Protein Production Using Bacillus megaterium......Page 193
Introduction......Page 194
Plasmids for recombinant protein production in B. megaterium......Page 195
Materials......Page 196
Recombinant protein production in B. megaterium in shaking flask scale......Page 197
Recombinant protein production in B. megaterium using high cell density conditions in a bioreactor......Page 199
Purification of recombinantly produced intra- and extracellular proteins......Page 200
Materials......Page 202
Preparation of protoplasts......Page 203
Test of protoplast transformation......Page 204
Transconjugation as genetic tool for B. megaterium......Page 205
Preparation of B. megaterium and E. coli cells for transconjugation......Page 206
Counter selection by the sacB suicide system......Page 209
Protocol......Page 210
Counter selection......Page 211
Genome sequence of B. megaterium......Page 212
Transcriptomics......Page 213
RNA preparation for microarray analysis of B. megaterium......Page 214
Materials......Page 216
Metabolome analysis via GC/MS of B. megaterium......Page 217
Fluxome analysis of B. megaterium......Page 218
Acknowledgments......Page 219
References......Page 220
Protein Production in Saccharomyces cerevisiae for Systems Biology Studies......Page 224
Introduction......Page 225
Comprehensive Libraries for Protein Production in S. cerevisiae......Page 226
Protocols for Protein Expression and Purification from Tagged Collections of S. cerevisiae......Page 229
Cell growth and protein expression......Page 230
Protein purification......Page 232
Protein Analysis and Quantification......Page 234
Acknowledgments......Page 236
References......Page 237
Towards a Full Quantitative Description of Yeast Metabolism......Page 240
Introduction......Page 241
Enzyme Kinetics for Systems Biology......Page 243
Production and Purification of Isoenzymes......Page 244
Towards high-throughput measurements of enzymatic activities......Page 245
Management of enzyme kinetics data......Page 247
Determination of the absolute levels of isoenzymes......Page 249
Hexokinase (EC 2.7.1.1) and glucokinase (2.7.1.2)......Page 250
Fructose-1,6-biphosphate aldolase (EC 4.1.2.13)......Page 251
Phosphoglycerate kinase (EC 2.7.2.3)......Page 252
Alcohol dehydrogenase (EC 1.1.1.1)......Page 253
References......Page 254
Enzyme Kinetics for Systems Biology......Page 257
Enzyme Kinetics for Systems Biology: Five Variations on the Theme......Page 258
Enzymology......Page 259
The in vitro lysate approach......Page 260
The ex vivo approach......Page 261
The bottom-up approach......Page 263
Three System Biology Approaches that Use Different Enzyme Kinetics......Page 264
Hierarchical regulation analysis......Page 265
Metabolic regulation analysis......Page 267
Biological Material......Page 268
Preparation of yeast cell-free extracts by homogenization......Page 270
Enzyme capacities (Vmax) in submilliliter reaction volumes: Hexokinase as example......Page 271
Reagents......Page 272
Toward further protocols for ex vivo enzymatic assays......Page 275
Perspectives......Page 276
References......Page 277
The Use of Continuous Culture in Systems Biology Investigations......Page 282
Introduction......Page 283
Chemostat......Page 284
Turbidostat......Page 286
Experimental Considerations......Page 287
Media......Page 288
Selection of biomass set point......Page 289
Off-line measurements......Page 290
Preparation of bioreactor......Page 291
Preparation of media......Page 292
Setting up of the biomass monitor......Page 293
Sampling of Biomass for Proteome and Metabolome Analyses......Page 294
References......Page 295
Sample Preparation Related to the Intracellular Metabolome of Yeast......Page 297
Introduction......Page 298
Sample Collection from Batch Cultures with Quenching of Intracellular Metabolism......Page 300
Materials and instruments......Page 302
Method for quenching of metabolism and sample collection from batch cultures......Page 303
Extraction of Polar and Nonpolar Metabolites from the Intracellular Metabolome......Page 304
Materials and instruments......Page 306
Method for combined extraction of polar and non polar metabolites......Page 307
Targeted Quantification of Organic Acids Applying Gas Chromatography-Mass Spectrometry......Page 308
Materials and instruments......Page 310
Methods for quantitation of organic acids......Page 311
References......Page 315
Plant Metabolomics and Its Potential for Systems Biology Research......Page 318
Fields of application......Page 320
Sampling: From whole plant to single cell......Page 321
Metabolite profiling technologies......Page 322
The utopia´´ of a systems level understanding......Page 323<br>Experimental design and plant growth......Page 324<br>Harvest......Page 325<br>Sampling......Page 326<br>Sample storage......Page 327<br>An introduction to GC-TOF/MS metabolite profiling......Page 328<br>GC-TOF/MS plant metabolite profiling: Recommended experimental procedures......Page 329<br>Data preprocessing and metabolite classification in plant GC-TOF/MS profiling......Page 330<br>An introduction to LC-MS metabolite profiling......Page 333<br>Data preprocessing of plant LC-MS profiling experiments......Page 334<br>Extraction of polar metabolites......Page 336<br>Extraction with deuterated solvents......Page 337<br>Extraction with nondeuterated solvents......Page 339<br>Acquisition......Page 340<br>Metabolite identification or spectral assignment......Page 343<br>Concluding Remarks......Page 345<br>References......Page 346<br>The Study of Mammalian Metabolism through NMR-based Metabolomics......Page 356<br>Introduction......Page 357<br>Perchloric acid extraction......Page 358<br>Tissue extraction procedure......Page 359<br>Tissue extraction procedure......Page 360<br>NMR spectroscopy of tissue extracts......Page 361<br>Protocol......Page 362<br>Protocol......Page 363<br>Protocol......Page 364<br>A Brief Overview of Directly Measuring Metabolites in Mammalian Tissues by High-Resolution Magic Angle Spinning 1H NMR Spec......Page 365<br>Protocol......Page 366<br>Data Processing......Page 368<br>References......Page 369<br>Building a Kinetic Model of Trehalose Biosynthesis in Saccharomyces cerevisiae......Page 371<br>Introduction......Page 372<br>Biological Background......Page 373<br>Response to stress......Page 374<br>Interaction with glycolysis......Page 376<br>Hexokinase......Page 379<br>T6P synthase......Page 380<br>Vmax......Page 381<br>TPS1 mutant......Page 382<br>Discussion......Page 383<br>References......Page 384<br>Sustainable Model Building......Page 387<br>Sustainable Model Building......Page 388<br>The bottom-up modeling paradigm......Page 389<br>Guidelines for creating reusable models......Page 390<br>Systems Biology Markup Language......Page 391<br>Systems Biology Graphical Notation......Page 392<br>Modeling tools and model repositories......Page 393<br>Controlled vocabularies, taxonomies, and ontologies......Page 395<br>MIRIAM-compliant annotations in SBML models......Page 397<br>Web services......Page 398<br>Workflow engines......Page 400<br>Tools for managing biochemical names and identifiers......Page 401<br>Model creation......Page 404<br>Annotations in Genome-Scale Network Reconstructions......Page 405<br>Acknowledgments......Page 408<br>References......Page 409<br>From Reaction Networks to Information Flow-Using Modular Response Analysis to Track Information in Signaling Netw......Page 412<br>Introduction......Page 413<br>Modular Response Analysis......Page 414<br>Conservation Analysis......Page 417<br>From Reaction Schemes to Influence Networks Using a Monte Carlo Approach......Page 419<br>Acknowledgments......Page 423<br>References......Page 424<br>Whole-Genome Metabolic Network Reconstruction and Constraint-Based Modeling......Page 425<br>Introduction......Page 426<br>Genome annotation......Page 427<br>Automated network reconstruction......Page 428<br>Key organizational tools......Page 431<br>Organism-specific curation......Page 432<br>In vitro experimentation and validation......Page 433<br>Constraint-Based Modeling Methods......Page 434<br>GENRE-to-model implementation......Page 435<br>Flux balance analysis......Page 436<br>Flux variability analysis......Page 438<br>Minimization of metabolic adjustment......Page 439<br>Regulatory on/off minimization......Page 440<br>ObjFind......Page 441<br>Bayesian discrimination......Page 442<br>Multiple metabolic objectives......Page 443<br>Summary......Page 444<br>References......Page 445<br>Hands-on Metabolism......Page 448<br>Elementary Flux Modes......Page 449<br>Mathematical background......Page 451<br>Network reconstruction......Page 454<br>Application to photosynthate metabolism......Page 455<br>Overview of further applications of EFM analysis......Page 460<br>Pathway analysis in genome-scale metabolic networks......Page 462<br>Acknowledgments......Page 463<br>References......Page 465<br>How to Obtain True and Accurate Rate-Values......Page 468<br>Introduction......Page 469<br>Problems in measuring the broth total volume V or broth mass M......Page 470<br>Calculation of V using a volume balance is a wrong approach......Page 471<br>The broth total mass balance in (fed) batch provides a calculated M......Page 472<br>Reformulating individual compound balances on total mass and not volume basis......Page 477<br>Introduction......Page 478<br>Viability staining, leads to kd......Page 480<br>Due to cell death mu changes, muD......Page 481<br>Product degradation influences the calculation of qp......Page 482<br>Evaporation of volatile compounds influences the calculation of qp, qs......Page 483<br>Principles of element conservation......Page 484<br>O2 and CO2 balances to calculate RO2 and RCO2......Page 485<br>Using conservation of C and degree of reduction to detect forgotten processes......Page 488<br>Examples on the use of conservation principles to detect forgotten processes......Page 489<br>Statistical error propagation in compound balance based Ri......Page 493<br>Statistical error propagation in element balances derived Ri......Page 495<br>Setting up the equations to calculate Ri......Page 497<br>Stage 1: Select measurement effort with minimal error propagation for element balance derived Ri......Page 499<br>Stage 3: Create redundancy to check for forgotten processes to eliminate systematic errors......Page 502<br>Calculation ofmeasured´´ rate, Ri......Page 504
Testing for errors and forgotten processes using residues of the redundancy equations (node analysis)......Page 506
Reconciliation......Page 509
q-Values: Best estimates and errors......Page 510
Formulating the equations......Page 513
Formulation of the nonlinear optimization problem......Page 514
Statistical aspects......Page 515
Conclusion......Page 518
References......Page 519
A Practical Guide to Genome-Scale Metabolic Models and Their Analysis......Page 520
Introduction......Page 521
Bottom-up (kinetic) models versus genome-scale metabolic models......Page 525
Top-down (biostatistical) models versus genome-scale metabolic models......Page 529
Generating a draft reconstruction based on the genome sequence......Page 531
Define external metabolites and the biomass equation......Page 532
Applications of Genome-Scale Metabolic Models......Page 534
Flux balance analysis: The work horse of constraint based modeling......Page 535
FBA predicts rates only through yield maximization......Page 536
Using constraint-based modeling for discovery and interpretation: Sensitivity analysis......Page 538
References......Page 539
Supply-Demand Analysis......Page 544
Introduction......Page 545
Quantitative Analysis of Supply-Demand Systems......Page 546
Generalized Supply-Demand Analysis......Page 553
Differences in rate characteristic shapes......Page 557
Comparison of elasticities and response coefficients......Page 558
Requirements for and limitations of the approach......Page 559
Double modulation......Page 560
Selected examples of experimental supply-demand analysis......Page 561
References......Page 563
Introduction......Page 566
Nomenclature and link with metabolic control analysis......Page 567
The single-intermediate input-output system......Page 571
Multi-intermediates, multimodule systems......Page 572
Response analysis......Page 576
Mitchondrial respiration and oxidative phosphorylation......Page 577
References......Page 579
Quantitative Analysis of Flux Regulation Through Hierarchical Regulation Analysis......Page 582
Introduction......Page 583
Gene-expression regulation......Page 584
Metabolic regulation......Page 586
Theory of Regulation Analysis......Page 587
Time-dependent regulation analysis......Page 589
Dissection of the regulation of Vmax......Page 590
Cooperative regulation......Page 592
Experimental Tools for Regulation Analysis......Page 593
Metabolic flux analysis......Page 594
Strategies of Flux Regulation......Page 595
How are changes in fluxes regulated in practice?......Page 596
References......Page 602
Origins of Stochastic Intracellular Processes and Consequences for Cell-to-Cell Variability and Cellular Survival......Page 607
Cell-to-Cell Heterogeneity and Measurement Techniques......Page 608
Noise in mRNA numbers at steady state......Page 610
A switching-gene model that captures many experimental findings......Page 614
Eukaryotic translation bursts and eukaryotic protein noise......Page 620
Noise propagation in molecular networks......Page 623
Changing and uncertain environments: Stochastic phenotype switching by microorganisms......Page 625
Bistable switches in cellular decision making......Page 626
Eukaryotic signaling and cell-to-cell variability......Page 628
Noisy decision making in eukaryotic development......Page 629
Conclusion......Page 630
References......Page 631
The SEEK: A Platform for Sharing Data and Models in Systems Biology......Page 636
Introduction......Page 637
The SEEK Platform......Page 639
The Yellow Pages......Page 640
The SEEK assets catalog......Page 641
Access to external resources......Page 642
The Challenges of Data Management......Page 643
Biological object identity......Page 644
Data in context......Page 645
JERM harvesters and extractors......Page 648
The SEEK and model management......Page 649
Protocols for informatics experiments......Page 651
Data annotation and RightField......Page 652
Tools for model annotation......Page 654
Linking data and models......Page 656
Incentives for Sharing Data......Page 657
Credit and attribution......Page 658
The SEEK: Experiences......Page 659
References......Page 661
Crossing the Boundaries: Delivering Trans-disciplinary Science in a Disciplinary World......Page 663
Introduction......Page 664
Theoretical Management Strategies......Page 665
Project-based organizations......Page 666
Matrix organization structure......Page 667
The challenge of knowledge creation and management in systems biology......Page 668
Application to CISBs-Mixed organizational structures......Page 670
MCISB......Page 671
Centre for Systems Biology at Edinburgh......Page 673
Conclusions......Page 676
References......Page 677