M M B TM ETHODS IN OLECULAR IOLOGY Series Editor John M. Walker School of Life Sciences University of Hertfordshire Hatfield, Hertfordshire, AL10 9AB, UK For further volumes: http://www.springer.com/series/7651 . Systems Metabolic Engineering Methods and Protocols Edited by Hal S. Alper Department of Chemical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, Texas, USA Editor HalS.Alper DepartmentofChemicalEngineering,CockrellSchoolofEngineering TheUniversityofTexasatAustin Austin,Texas,USA Additionalmaterialtothisbookcanbedownloaded fromhttp://extras.springer.com ISSN1064-3745 ISSN1940-6029(electronic) ISBN978-1-62703-298-8 ISBN978-1-62703-299-5(eBook) DOI10.1007/978-1-62703-299-5 SpringerNewYorkHeidelbergDordrechtLondon LibraryofCongressControlNumber:2012956554 ªSpringerScience+BusinessMedia,LLC2013 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartofthematerialis concerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation,broadcasting,reproduction onmicrofilmsorinanyotherphysicalway,andtransmissionorinformationstorageandretrieval,electronicadaptation, computersoftware,orbysimilarordissimilarmethodologynowknownorhereafterdeveloped.Exemptedfromthis legalreservationarebriefexcerptsinconnectionwithreviewsorscholarlyanalysisormaterialsuppliedspecificallyfor thepurposeofbeingenteredandexecutedonacomputersystem,forexclusiveusebythepurchaserofthework. DuplicationofthispublicationorpartsthereofispermittedonlyundertheprovisionsoftheCopyrightLawofthe Publisher’slocation,initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.Permissions forusemaybeobtainedthroughRightsLinkattheCopyrightClearanceCenter.Violationsareliabletoprosecution undertherespectiveCopyrightLaw. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublicationdoesnot imply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevantprotectivelawsand regulationsandthereforefreeforgeneraluse. Whiletheadviceandinformationinthisbookarebelievedtobetrueandaccurateatthedateofpublication,neitherthe authorsnortheeditorsnorthepublishercanacceptanylegalresponsibilityforanyerrorsoromissionsthatmaybe made.Thepublishermakesnowarranty,expressorimplied,withrespecttothematerialcontainedherein. Printedonacid-freepaper HumanaPressisabrandofSpringer SpringerispartofSpringerScience+BusinessMedia(www.springer.com) Preface Metabolic engineering has always been focused on using a systems-level view to analyze cellular metabolism and predict optimal rewiring of metabolic networks. Since its incep- tion,significantadvanceshavebeenmadeinourcapacitytoobtainhigh-resolutiondetails aboutcellularstate.Inresponsetothisnewfoundcapacity,SystemsMetabolicEngineering emergesasaparadigmthatconnectstheareaofsystemsbiologywithmetabolicengineer- ing goals. Specifically, this field incorporates large-scale data collection/high-throughput biology and in silico modeling efforts along with new capacities for genome-wide engi- neering to accomplish the goal of improving a cellular phenotype or pathway flux. These technologies and efforts continue to expand the global systems-level view of metabolic engineering by shifting focus away from individual pathways and toward the collective, interconnected nature of metabolism and regulation. The advances of systems biology enable high-throughput collection of genomic, transcriptomic, proteomic, metabolomic, andfluxomicdata.However,thisimmensesnapshotofcellsbringsaboutalargechallenge for data collection, integration, interpretation, synthesis, and ultimately perturbation to the cell. Moreover, the rate of data generation is also being matched by our rate of multiplexedengineeringofpathwaysandgenomes. The ultimate goal of a Systems Metabolic Engineering approach is to systematically and robustly define the specific perturbations necessary to alter a cellular phenotype. The tangible outcome of such an approach would be a complete cell model capable of (1) simulatingcellandmetabolicfunctionand(2)predictingphenotypicresponsetochanges in media, gene knockouts/overexpressions, or incorporation of heterologous pathways. Whilethefieldisnotyetatthispoint,itisclearlyonatrajectorytowardsuchcapacity.The fieldofSystemsMetabolicEngineeringhasalreadyproventobeasuccessfulparadigmfor improvingpathwayperformanceforsmallmoleculesinboththelaboratoryandindustrial setting.Astechniques continueto improve,thedesigncycleforengineeringacellwillbe greatlyreduced. Asstatedabove,greatstrideshavebeenmadeinadvancingthekeyaspectsofaSystems MetabolicEngineeringapproach.Thus,theaimofthisbookistodescribethemethodol- ogiesandapproachesintheareaofSystemsMetabolicEngineeringandprovideastep-by- stepguidefortheirimplementation.Inparticular,fourmajortenantsofthisapproachwill be discussed: (1) modeling and simulation, (2) multiplexed genome engineering, (3) ‘omics technologies, and (4) large data-set incorporation and synthesis. Each of these four capacities plays an important role in the design cycle for strain improvement. Tools andprotocolswithineachofthesetenetswillbedescribedtoenablefacileimplementation of a Systems Metabolic Engineering approach using model host organisms. This book is designedespeciallyformetabolicengineers,molecularbiologists,andmicrobiologistswho are proficient in the genetic manipulation of organisms. The coverage of this material is quite broad to allow for accessibility by novices and experts alike. It is hopeful that this book will serve as a guide to implementing the most recent approaches in Systems MetabolicEngineering. Austin,Texas,USA HalS.Alper v Contents Preface.................................................................... v Contributors............................................................... ix PART I MODELING AND SIMULATION TOOLS 1 Genome-ScaleModelManagementandComparison......................... 3 StephanPabingerandZlatkoTrajanoski 2 AutomatedGenomeAnnotationandMetabolicModelReconstruction intheSEEDandModelSEED........................................... 17 ScottDevoid,RossOverbeek,MatthewDeJongh,VeronikaVonstein, AaronA.Best,andChristopherHenry 3 MetabolicModelRefinementUsingPhenotypicMicroarrayData.............. 47 PratishGawand,LaurenceYang,WilliamR.Cluett, andRadhakrishnanMahadevan 4 LinkingGenome-ScaleMetabolicModelingandGenomeAnnotation.......... 61 EdikM.Blais,ArvindK.Chavali,andJasonA.Papin 5 ResolvingCellCompositionThroughSimpleMeasurements, Genome-ScaleModeling,andaGeneticAlgorithm.......................... 85 RyanS.SengerandHadiNazem-Bokaee 6 AGuidetoIntegratingTranscriptionalRegulatoryandMetabolic NetworksUsingPROM(ProbabilisticRegulationofMetabolism) ............. 103 EvangelosSimeonidis,SriramChandrasekaran,andNathanD.Price 7 KineticModelingofMetabolicPathways:Application toSerineBiosynthesis................................................... 113 KieranSmallboneandNatalieJ.Stanford 8 ComputationalToolsforGuidedDiscoveryandEngineering ofMetabolicPathways .................................................. 123 MatthewMoura,LindaBroadbelt,andKeithTyo 9 RetrosyntheticDesignofHeterologousPathways ........................... 149 PabloCarbonell,Anne-Ga¨ellePlanson,andJean-LoupFaulon PART II GENOME ENGINEERING TOOLS 10 CustomizedOptimizationofMetabolicPathways byCombinatorialTranscriptionalEngineering.............................. 177 YongboYuan,JingDu,andHuiminZhao 11 AdaptiveLaboratoryEvolutionforStrainEngineering ....................... 211 JamesWinkler,LuisH.Reyes,andKatyC.Kao 12 TrackableMultiplexRecombineeringforGene-TraitMappinginE.coli......... 223 ThomasJ.Mansell,JosephR.Warner,andRyanT.Gill vii viii Contents PART III SYSTEMS-LEVEL ‘OMICS TOOLS 13 IdentificationofMutationsinEvolvedBacterialGenomes .................... 249 LiamRoyce,ErinBoggess,TaoJin,JulieDickerson,andLauraJarboe 14 DiscoveryofPosttranscriptionalRegulatoryRNAsUsing NextGenerationSequencingTechnologies................................. 269 GrantGeldermanandLydiaM.Contreras 15 13C-BasedMetabolicFluxAnalysis:FundamentalsandPractice................ 297 TaeHoonYang 16 NuclearMagneticResonanceMethodsforMetabolicFluxomics............... 335 ShilpaNargund,MaxE.Joffe,DennisTran,VitaliTugarinov, andGaneshSriram 17 UsingMultipleTracersfor13CMetabolicFluxAnalysis ...................... 353 MaciekR.Antoniewicz 18 IsotopicallyNonstationary13CMetabolicFluxAnalysis ...................... 367 LaraJ.JazminandJameyD.Young 19 SamplePreparationandBiostatisticsforIntegratedGenomicsApproaches ...... 391 HeinStam,MichielAkeroyd,HillyMenke,RengerH.Jellema, FredoenValianpour,WilbertH.M.Heijne,MaurienM.A.Olsthoorn, SabineMetzelaar,ViktorM.Boer,CarlosM.F.M.Ribeiro, PhilippeGaudin,andCeesM.J.Sagt PART IV INTEGRATING LARGE DATASETS FOR MODELING AND ENGINEERING APPLICATIONS 20 TargetedMetabolicEngineeringGuidedbyComputationalAnalysis ofSingle-NucleotidePolymorphisms(SNPs) ............................... 409 D.B.R.K.GuptaUdatha,SimonRasmussen,ThomasSicheritz-Ponte´n, andGianniPanagiotou 21 LinkingRNAMeasurementsandProteomicswithGenome-ScaleModels....... 429 ChristopherM.GowenandStephenS.Fong 22 ComparativeTranscriptomeAnalysisforMetabolicEngineering............... 447 ShuoboShi,TaoChen,andXuemingZhao 23 MergingMultipleOmicsDatasetsInSilico:StatisticalAnalyses andDataInterpretation................................................. 459 KazuharuArakawaandMasaruTomita Index..................................................................... 471 Contributors MICHIEL AKEROYD (cid:1) DSM Biotechnology Center, Delft, The Netherlands MACIEK R. ANTONIEWICZ (cid:1) Metabolic Engineering and Systems Biology Laboratory, Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, DE, USA KAZUHARU ARAKAWA (cid:1) Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa, Japan AARON A. BEST (cid:1) Department of Biology, Hope College, Holland, MI, USA EDIK M. BLAIS (cid:1) Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA VIKTOR M. BOER (cid:1) DSM Biotechnology Center, Delft, The Netherlands ERIN BOGGESS (cid:1) Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA LINDA BROADBELT (cid:1) Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA PABLO CARBONELL (cid:1) Institute of Systems & Synthetic Biology (ISSB), Evry, France SRIRAM CHANDRASEKARAN (cid:1) Institute for Systems Biology, Seattle, WA, USA; Center for Biophysics and Computational Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA ARVIND K. CHAVALI (cid:1) Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA TAO CHEN (cid:1) Key Laboratory of Systems Bioengineering, Ministry of Education, Tianjin University, Tianjin, China; Department of Biological Engineering, SchoolofChemicalEngineeringandTechnology,TianjinUniversity,Tianjin,China WILLIAM R. CLUETT (cid:1) Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada LYDIA M. CONTRERAS (cid:1) Department of Chemical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, USA MATTHEW DEJONGH (cid:1) Department of Computer Science, Hope College, Holland, MI, USA SCOTT DEVOID (cid:1) Argonne National Laboratory, MCS Division, Argonne, IL, USA JULIE DICKERSON (cid:1) Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA JING DU (cid:1) Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA JEAN-LOUP FAULON (cid:1) Institute of Systems & Synthetic Biology (ISSB), Evry, France STEPHEN S. FONG (cid:1) Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, USA PHILIPPE GAUDIN (cid:1) DSM Biotechnology Center, Delft, The Netherlands PRATISH GAWAND (cid:1) Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON, Canada GRANT GELDERMAN (cid:1) Department of Chemical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, USA ix