Systems Metabolic Engineering: Methods and Protocols

487 Pages·2013·6.514 MB·English

by  Stephan Pabinger, Zlatko Trajanoski (auth.), Hal S. Alper (eds.)

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
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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
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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
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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