Systems biology : a textbook

507 Pages·2016·82.379 MB·English

by  Klipp, Edda, Kowald, Axel, Liebermeister, Wolfram, Wierling, Christoph

EddaKlipp
WolframLiebermeister
ChristophWierling
AxelKowald
SystemsBiology

Edda Klipp
Wolfram Liebermeister
Christoph Wierling
Axel Kowald
Systems Biology
A Textbook
Second, Completely Revised
and Enlarged Edition
Authors AllbookspublishedbyWiley-VCHarecarefullyproduced.
Nevertheless,authors,editors,andpublisherdonotwarrantthe
Prof.Dr.h.c.EddaKlipp informationcontainedinthesebooks,includingthisbook,tobefreeof
TheoreticalBiophysics errors.Readersareadvisedtokeepinmindthatstatements,data,
Humboldt-UniversitätzuBerlin illustrations,proceduraldetailsorotheritemsmayinadvertentlybe
Invalidenstr.42 inaccurate.
10115Berlin
Germany LibraryofCongressCardNo.:appliedfor
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InstituteofBiochemistry AcataloguerecordforthisbookisavailablefromtheBritishLibrary.
Charité-UniversitätsmedizinBerlin
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10117Berlin
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Dr.ChristophWierling 2016Wiley-VCHVerlagGmbH&Co.KGaA,Boschstr.12,69469
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14195Berlin
Germany PrintISBN: 978-3-527-33636-4
ePDFISBN: 978-3-527-67566-1
Dr.AxelKowald ePubISBN: 978-3-527-67567-8
TheoreticalBiophysics MobiISBN: 978-3-527-67568-5
HumboldtUniversityBerlin
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Cover
CoverdesignbyWolframLiebermeister.Thecoverpicturewas
providedwithkindpermissionbyJörgBernhardt.
Contents
Preface xi 2.2.2 IllustrativeExamplesofODEModels 18
GuidetoDifferentTopicsoftheBook xiii References 21
AbouttheAuthors xv FurtherReading 21
3 StructuralModelingandAnalysisof
PartOne IntroductiontoSystemsBiology 1 BiochemicalNetworks 23
3.1 StructuralAnalysisofBiochemicalSystems 24
1 Introduction 3 3.1.1 SystemEquations 24
1.1 BiologyinTimeandSpace 3
3.1.2 InformationEncodedintheStoichiometric
1.2 ModelsandModeling 4
MatrixN 25
1.2.1 WhatIsaModel? 4 3.1.3 TheFluxCone 27
1.2.2 PurposeandAdequatenessofModels 5 3.1.4 ElementaryFluxModesandExtreme
1.2.3 AdvantagesofComputationalModeling 5 Pathways 27
1.3 BasicNotionsforComputationalModels 6 3.1.5 ConservationRelations–NullSpaceofNT 29
1.3.1 ModelScope 6 3.2 Constraint-BasedFluxOptimization 30
1.3.2 ModelStatements 6 3.2.1 FluxBalanceAnalysis 31
1.3.3 SystemState 6 3.2.2 GeometricInterpretationofFluxBalance
1.3.4 Variables,Parameters,andConstants 6 Analysis 31
1.3.5 ModelBehavior 7 3.2.3 ThermodynamicConstraints 31
1.3.6 ModelClassification 7 3.2.4 ApplicationsandTestsoftheFluxOptimization
1.3.7 SteadyStates 7 Paradigm 32
1.3.8 ModelAssignmentIsNotUnique 7 3.2.5 ExtensionsofFluxBalanceAnalysis 33
1.4 Networks 8
Exercises 35
1.5 DataIntegration 8
References 36
1.6 Standards 9
FurtherReading 37
1.7 ModelOrganisms 9
1.7.1 Escherichiacoli 9 4 KineticModelsofBiochemicalNetworks:
1.7.2 Saccharomycescerevisiae 11 Introduction 39
1.7.3 Caenorhabditiselegans 11 4.1 ReactionKineticsandThermodynamics 39
1.7.4 Drosophilamelanogaster 11 4.1.1 KineticModelingofEnzymaticReactions 39
1.7.5 Musmusculus 12 4.1.2 TheLawofMassAction 40
References 12 4.1.3 ReactionThermodynamics 40
FurtherReading 14 4.1.4 Michaelis–MentenKinetics 42
4.1.5 RegulationofEnzymeActivitybyEffectors 44
2 ModelingofBiochemicalSystems 15 4.1.6 GeneralizedMassActionKinetics 48
2.1 OverviewofCommonModelingApproaches
4.1.7 ApproximateKineticFormats 48
forBiochemicalSystems 15
4.1.8 ConvenienceKineticsandModularRateLaws 49
2.2 ODESystemsforBiochemicalNetworks 17 4.2 MetabolicControlAnalysis 50
2.2.1 BasicComponentsofODEModels 18 4.2.1 TheCoefficientsofControlAnalysis 51
vi
Contents
4.2.2 TheTheoremsofMetabolicControlTheory 53 6.4 CoupledSystemsandEmergent
4.2.3 MatrixExpressionsforControlCoefficients 55 Behavior 110
4.2.4 UpperGlycolysisasRealisticModelExample 58 6.4.1 ModelingofCoupledSystems 111
4.2.5 Time-DependentResponseCoefficients 59 6.4.2 CombiningRateLawsintoModels 113
Exercises 61 6.4.3 ModularResponseAnalysis 113
References 61 6.4.4 EmergentBehaviorinCoupledSystems 114
FurtherReading 62 6.4.5 CausalInteractionsandGlobalBehavior 115
Exercises 116
5 DataFormats,SimulationTechniques,and References 117
ModelingTools 63 FurtherReading 119
5.1 SimulationTechniquesandTools 63
5.1.1 DifferentialEquations 63 7 Discrete,Stochastic,andSpatialModels 121
5.1.2 StochasticSimulations 64 7.1 DiscreteModels 122
5.1.3 SimulationTools 65 7.1.1 BooleanNetworks 122
5.2 StandardsandFormatsforSystems 7.1.2 PetriNets 124
Biology 72 7.2 StochasticModelingofBiochemical
5.2.1 SystemsBiologyMarkupLanguage 72 Reactions 127
5.2.2 BioPAX 74 7.2.1 ChanceinBiochemicalReactionSystems 127
5.2.3 SystemsBiologyGraphicalNotation 74 7.2.2 TheChemicalMasterEquation 129
5.3 DataResourcesforModelingofCellular 7.2.3 StochasticSimulation 129
ReactionSystems 75 7.2.4 ChemicalLangevinEquationandChemical
5.3.1 General-PurposeDatabases 75 Noise 130
5.3.2 PathwayDatabases 76 7.2.5 DynamicFluctuations 132
5.3.3 ModelDatabases 77 7.2.6 FromStochastictoDeterministic
5.4 SustainableModelingandModel Modeling 133
Semantics 78 7.3 SpatialModels 133
5.4.1 StandardsforSystemsBiologyModels 78 7.3.1 TypesofSpatialModels 134
5.4.2 ModelSemanticsandModelComparison 78 7.3.2 CompartmentModels 135
5.4.3 ModelCombination 80 7.3.3 Reaction–DiffusionSystems 136
5.4.4 ModelValidity 82 7.3.4 RobustPatternFormationinEmbryonic
References 83 Development 138
FurtherReading 85 7.3.5 SpontaneousPatternFormation 139
7.3.6 LinearStabilityAnalysisoftheActivator–
6 ModelFitting,Reduction,andCoupling 87 InhibitorModel 140
6.1 ParameterEstimation 88 Exercises 142
6.1.1 Regression,Estimators,andMaximal References 143
Likelihood 88 FurtherReading 144
6.1.2 ParameterIdentifiability 90
6.1.3 Bootstrapping 91 8 NetworkStructure,Dynamics,and
6.1.4 BayesianParameterEstimation 92 Function 145
6.1.5 ProbabilityDistributionsforRate 8.1 StructureofBiochemicalNetworks 146
Constants 94 8.1.1 RandomGraphs 147
6.1.6 OptimizationMethods 97 8.1.2 Scale-FreeNetworks 148
6.2 ModelSelection 99 8.1.3 ConnectivityandNodeDistances 149
6.2.1 WhatIsaGoodModel? 99 8.1.4 NetworkMotifsandSignificanceTests 150
6.2.2 TheProblemofModelSelection 100 8.1.5 ExplanationsforNetworkStructures 151
6.2.3 LikelihoodRatioTest 102 8.2 RegulationNetworksandNetwork
6.2.4 SelectionCriteria 102 Motifs 152
6.2.5 BayesianModelSelection 103 8.2.1 StructureofTranscriptionNetworks 153
6.3 ModelReduction 104 8.2.2 RegulationEdgesandTheirSteady-State
6.3.1 ModelSimplification 104 Response 156
6.3.2 ReductionofFastProcesses 105 8.2.3 NegativeFeedback 156
6.3.3 Quasi-EquilibriumandQuasi-SteadyState 107 8.2.4 AdaptationMotif 157
6.3.4 GlobalModelReduction 108 8.2.5 Feed-ForwardLoops 158
vii
Contents
8.3 ModularityandGeneFunctions 160 10 Variability,Robustness,andInformation 209
8.3.1 CellFunctionsAreReflectedinStructure, 10.1 VariabilityandBiochemicalModels 210
Dynamics,Regulation,andGenetics 160 10.1.1 VariabilityandUncertaintyAnalysis 210
8.3.2 MetabolicsPathwaysandElementary 10.1.2 FluxSampling 212
Modes 162 10.1.3 ElasticitySampling 213
8.3.3 EpistasisCanIndicateFunctionalModules 163 10.1.4 PropagationofParameterVariabilityinKinetic
8.3.4 EvolutionofFunctionandModules 163 Models 214
8.3.5 IndependentSystemsasaTacitModel 10.1.5 ModelswithParameterFluctuations 216
Assumption 165 10.2 RobustnessMechanismsandScaling
8.3.6 ModularityandBiologicalFunctionAre Laws 217
ConceptualAbstractions 165 10.2.1 RobustnessinBiochemicalSystems 218
Exercises 166 10.2.2 RobustnessbyBackupElements 219
References 167 10.2.3 FeedbackControl 219
FurtherReading 169 10.2.4 PerfectRobustnessbyStructure 222
10.2.5 ScalingLaws 224
9 GeneExpressionModels 171 10.2.6 TimeScaling,SummationLaws,and
9.1 MechanismsofGeneExpression Robustness 227
Regulation 171 10.2.7 TheRoleofRobustnessinEvolutionand
9.1.1 TranscriptionFactor-InitiatedGene Modeling 228
Regulation 171 10.3 AdaptationandExplorationStrategies 229
9.1.2 GeneralPromoterStructure 173 10.3.1 InformationTransmissioninSignaling
9.1.3 PredictionandAnalysisofPromoter Pathways 230
Elements 174 10.3.2 AdaptationandFold-ChangeDetection 230
9.1.4 PosttranscriptionalRegulationthrough 10.3.3 TwoAdaptationMechanisms:Sensingand
microRNAs 176 RandomSwitching 231
9.2 DynamicModelsofGeneRegulation 180 10.3.4 ShannonInformationandtheValueof
9.2.1 ABasicModelofGeneExpressionand Information 232
Regulation 180 10.3.5 MetabolicShiftsandAnticipation 233
9.2.2 NaturalandSyntheticGeneRegulatory 10.3.6 ExplorationStrategies 234
Networks 183 Exercises 236
9.2.3 GeneExpressionModelingwithStochastic References 237
Equations 186 FurtherReading 239
9.3 GeneRegulationFunctions 187
9.3.1 TheLacOperoninE.coli 187 11 OptimalityandEvolution 241
9.3.2 GeneRegulationFunctionsDerivedfrom 11.1 OptimalityinSystemsBiologyModels 243
EquilibriumBinding 188 11.1.1 MathematicalConceptsforOptimalityand
9.3.3 ThermodynamicModelsofPromoter Compromise 245
Occupancy 189 11.1.2 MetabolismIsShapedbyOptimality 248
9.3.4 GeneRegulationFunctionoftheLac 11.1.3 OptimalityApproachesinMetabolic
Promoter 191 Modeling 250
9.3.5 InferringTranscriptionFactorActivitiesfrom 11.1.4 MetabolicStrategies 252
TranscriptionData 192 11.1.5 OptimalMetabolicAdaptation 253
9.3.6 NetworkComponentAnalysis 194 11.2 OptimalEnzymeConcentrations 255
9.3.7 CorrespondencesbetweenmRNAandProtein 11.2.1 OptimizationofCatalyticPropertiesofSingle
Levels 196 Enzymes 255
9.4 FluctuationsinGeneExpression 196 11.2.2 OptimalDistributionofEnzymeConcentrations
9.4.1 StochasticModelofTranscriptionand inaMetabolicPathway 257
Translation 197 11.2.3 TemporalTranscriptionPrograms 259
9.4.2 IntrinsicandExtrinsicVariability 200 11.3 EvolutionandSelf-Organization 261
9.4.3 TemporalFluctuationsinGene 11.3.1 Introduction 261
Cascades 202 11.3.2 SelectionEquationsforBiological
Exercises 203 Macromolecules 263
References 205 11.3.3 TheQuasispeciesModel:Self-Replicationwith
FurtherReading 207 Mutations 265
viii
Contents
11.3.4 TheHypercycle 267 13.2.1 ChemicalBondsandForcesImportantin
11.3.5 OtherMathematicalModelsofEvolution:Spin BiologicalMolecules 336
GlassModel 269 13.2.2 FunctionalGroupsinBiologicalMolecules 338
11.3.6 TheNeutralTheoryofMolecular 13.2.3 MajorClassesofBiologicalMolecules 338
Evolution 270 13.3 StructuralCellBiology 345
11.4 EvolutionaryGameTheory 271 13.3.1 StructureandFunctionofBiological
11.4.1 SocialInteractions 272 Membranes 347
11.4.2 GameTheory 273 13.3.2 Nucleus 349
11.4.3 EvolutionaryGameTheory 274 13.3.3 Cytosol 349
11.4.4 ReplicatorEquationforPopulationDynamics 274 13.3.4 Mitochondria 350
11.4.5 EvolutionarilyStableStrategies 275 13.3.5 EndoplasmicReticulumandGolgi
11.4.6 DynamicalBehaviorintheRock–Scissors–Paper Complex 350
Game 276 13.3.6 OtherOrganelles 351
11.4.7 EvolutionofCooperativeBehavior 276 13.4 ExpressionofGenes 351
11.4.8 CompromisesbetweenMetabolicYieldand 13.4.1 Transcription 351
Efficiency 278 13.4.2 ProcessingofthemRNA 353
Exercises 279 13.4.3 Translation 353
References 280 13.4.4 ProteinSortingandPosttranslational
FurtherReading 283 Modifications 355
13.4.5 RegulationofGeneExpression 355
12 ModelsofBiochemicalSystems 285 Exercises 356
12.1 MetabolicSystems 285 References 356
12.1.1 BasicElementsofMetabolicModeling 286 FurtherReading 356
12.1.2 ToyModelofUpperGlycolysis 286
12.1.3 ThreonineSynthesisPathwayModel 289 14 ExperimentalTechniques 357
12.2 SignalingPathways 291 14.1 RestrictionEnzymesandGel
12.2.1 FunctionandStructureofIntra-andIntercellular Electrophoresis 358
Communication 292 14.2 CloningVectorsandDNALibraries 359
12.2.2 Receptor–LigandInteractions 293 14.3 1Dand2DProteinGels 361
12.2.3 StructuralComponentsofSignaling 14.4 HybridizationandBlottingTechniques 362
Pathways 295 14.4.1 SouthernBlotting 363
12.2.4 AnalysisofDynamicandRegulatoryFeatures 14.4.2 NorthernBlotting 363
ofSignalingPathways 304 14.4.3 WesternBlotting 363
12.3 TheCellCycle 307 14.4.4 InSituHybridization 364
12.3.1 StepsintheCycle 309 14.5 FurtherProteinSeparationTechniques 364
12.3.2 MinimalCascadeModelofaMitotic 14.5.1 Centrifugation 364
Oscillator 310 14.5.2 ColumnChromatography 364
12.3.3 ModelsofBuddingYeastCellCycle 311 14.6 PolymeraseChainReaction 365
12.4 TheAgingProcess 314 14.7 Next-GenerationSequencing 366
12.4.1 EvolutionoftheAgingProcess 316 14.8 DNAandProteinChips 367
12.4.2 UsingStochasticSimulationstoStudy 14.8.1 DNAChips 367
MitochondrialDamage 318 14.8.2 ProteinChips 367
12.4.3 UsingDelayDifferentialEquationstoStudy 14.9 RNA-Seq 368
MitochondrialDamage 323 14.10 YeastTwo-HybridSystem 368
Exercises 327 14.11 MassSpectrometry 369
References 327 14.12 TransgenicAnimals 370
14.12.1 MicroinjectionandESCells 370
14.12.2 GenomeEditingUsingZFN,TALENs,and
PartTwo ReferenceSection 331 CRISPR 370
14.13 RNAInterference 371
13 CellBiology 333 14.14 ChIP-on-ChipandChIP-PET 372
13.1 TheOriginofLife 334 14.15 GreenFluorescentProtein 374
13.2 MolecularBiologyoftheCell 336 14.16 Single-CellExperiments 375