Cooperation in microbial biotechnology 2 - … · · 2017-04-12Cooperation in microbial biotechnology 1 1 ... 23 This situation may confront the intuitive idea that ‘evolution

Cooperationinmicrobialbiotechnology

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Cooperationinmicrobialcommunitiesandtheirbiotechnologicalapplications3

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MatteoCavaliere1,SongFeng2,OrkunSoyer3andJoseI.Jimenez4*5

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1SchoolofInformatics,BBSRC/EPSRC/MRCSyntheticBiologyResearchCentre,Universityof7Edinburgh8

2CenterforNonlinearStudies,TheoreticalDivision(T-6),LosAlamosNationalLaboratory9

3SchoolofLifeSciences,BBSRC/EPSRCWarwickIntegrativeSyntheticBiologyCentre,Universityof10Warwick11

4FacultyofHealthandMedicalSciences,UniversityofSurrey12

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*Towhomcorrespondenceshouldbeaddressed:14

FacultyofHealthandMedicalSciences15

UniversityofSurrey16

Guildford,GU27XH17

UnitedKingdom18

Email:[email protected]

Phone:+440148368455720

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Statementofsignificance:22

InthisreviewwesummariseadvancesinthefieldofEvolutionaryDynamicsappliedtomicrobial23

communitiesandtheirapplicationsinbiotechnology.Wediscussdifferentkindsofcooperative24

interactions,theirpotentialmechanisticoriginsandthefactorsthatcontributetotheirstability.We25

alsoanalysetheadvantagesofcooperativebehavioursinmicrobialpopulationsandevaluatetheir26

possibleusetodeveloprobustbiotechnologicalapplications.27

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Abstract1

Microbialcommunitiesareincreasinglyutilisedinbiotechnology.Efficiencyandproductivityinmany2

oftheseapplicationsdependsonthepresenceofcooperativeinteractionsbetweenmembersofthe3

community.Twokeyprocessesunderlyingtheseinteractionsaretheproductionofpublicgoodsand4

metaboliccrossfeeding,whichcanbeunderstoodinthegeneralframeworkofecologicaland5

evolutionary(eco-evo)dynamics.Inthisreviewweillustratetherelevanceofcooperative6

interactionsinmicrobialbiotechnologicalprocesses,discusstheirmechanisticorigins,andanalyse7

theirevolutionaryresilience.Cooperativebehaviourscanbedamagedbytheemergenceof8

‘cheating’cellsthatbenefitfromthecooperativeinteractionsbutdonotcontributetothem.Despite9

this,cooperativeinteractionscanbestabilizedbyspatialsegregation,bythepresenceoffeedbacks10

betweentheevolutionarydynamicsandtheecologyofthecommunity,bytheroleofregulatory11

systemscoupledtotheenvironmentalconditionsandbytheactionofhorizontalgenetransfer.12

Cooperativeinteractionsenrichmicrobialcommunitieswithahigherdegreeofrobustnessagainst13

environmentalstressandcanfacilitatetheevolutionofmorecomplextraits.Therefore,the14

evolutionaryresilienceofmicrobialcommunitiesandtheirabilitytoconstraintdetrimentalmutants15

shouldbeconsideredinordertodesignrobustbiotechnologicalapplications.16

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Evolutionarydynamicsandcooperationinmicrobialpopulations1

Thedesignandoptimizationofmicroorganismsforbiotechnologicalpurposesoftenconsiderscells2

inisolation.Whilethisreductionistapproachaimstothriveforsimplicityintheprocess,itcreatesa3

situationthatrarelytakesplaceinNature.Intheirnaturalenvironmentmicroorganismsthrivein4

complexcommunitiesinwhichthefitnessofasinglecelldependsontheinteractionswithother5

cellsinthepopulation(Westetal.,2006).Thisscenarioalsoappliestobioprocessesinwhichthe6

efficiencyoftheprocessiscoupledtotheproductionofshared(public)goodsthatallowcellsto7

performtasksina‘cooperative’manner(Lindemannetal.,2016):agoodexampleofsharedgoods8

arethecellulasessecretedintheproductionofcellulosicethanol(ZomorrodiandSegrè,2016).9

Thepresenceofcooperativeinteractionshasasignificantimpactontheevolutionary10

dynamicsofmicrobialcommunities,representedbythechangeinthefrequenciesofcellsand11

speciesthatimplementdifferentphysiologicalstrategies(suchasproductionofpublicgoodsvs.12

not).Thus,cooperativetraitsneedtobetakenintoaccountwhenusinganevolutionaryapproach13

foroptimisingagivenbioprocess.Itispossiblethatsimpleselectionschemestargetingabioprocess-14

relatedtrait(e.g.growthrate)willnotalignwiththeselectionforthecooperativetrait(e.g.15

productionofcostlyextracellularenzymes)ultimatelyresultinginthelossofthetrait.Indeed,16

tradeoffsbetweentheoptimizationofso-calledhigh-rateandhigh-yieldarefrequentlyobservedin17

controlledevolutionaryexperiments(Bachmannetal.,2013).Thus,weadvocateconsideringthe18

interactionsbetweenthecellsandthefunctioningofcooperativetraitswhendesigningevolutionary19

optimisationandstabilisationofbioprocesses.Achievingthiswouldrequireconsideringhow‘social’20

interactionsshapemicrobialprocesses,ratherthansimplyfocusingsolelyonindividualistictraits21

suchasgrowthrate.22

Thissituationmayconfronttheintuitiveideathat‘evolutionimpliesimprovement’(i.e.the23

averagefitnessofthecommunityisexpectedtoincreaseovergenerationsasitwouldbeexpected24

formonocultures).Thekeypointisthatthepresenceofinteractionsbetweenthespeciesgivesrise25

toamorecomplicatedevolutionarypictureinwhichthefitnessofacelldependsnotonlyonits26

phenotypebutalsoontheoverallcompositionofthepopulation.Thespreadingofagiven27

phenotypictraitmaythuschangethefitnessofothermembersofthecommunityandthesechanges28

mayinturnfeedbackonthefitnessoftheindividualcells(Westetal.,2006).Theseintertwined29

selectionmechanismsareexpectedtooperateinanymicrobialpopulationwherethereispossibility30

ofdifferentcellsimplementingdifferentstrategieswithrespecttotheirphysiology,asisthecaseof31

phenotypicheterogeneity.32

Phenotypicheterogeneityariseseveninmonoculturesandsimplebioprocessesdueto33

differentreasons,suchastheuseofnon-homogenouscultureconditions,stochasticityingene34


4

expressionanddifferentialepigeneticcontrol(Enforsetal.,2001;Avery,2006;Mülleretal.,2010).1

Suchheterogeneitydoesnotrepresentastaticpicture–cellscommunicate,competeandcooperate2

andthesuccessofatraitmaybeconsequenceoftheinteractionwiththeothertraitsandofthe3

specificecologicalcontext(Carlquistetal.,2012).Therefore,itisnotsufficientforatraittobe4

successfulinonespecificsettingbutrather,itneedstobesuccessfulgiventhepresenceofother5

traitsandtheassociatedecologicalcontext.Moreover,thedilutionofatraitmayleadtochangesin6

thecommunity(bothecologicaland/orinthefrequencyofothertraits)thatcouldfeedbackonthe7

evolutionarydynamicsofthetraititself.Forinstance,atraitmaybefavouredbynaturalselection8

onlywhenrareinacomplexpopulation,becomingdisfavouredwhenitismorefrequent.These9

complexevolutionaryandecologicaldynamics,whereessentiallythesuccessofatraitdependson10

thecompositionofthecommunity,canbemathematicallyanalysedwithevolutionarygametheory11

(NowakandSigmund,2004;Frey,2010).12

Evolutionarygametheoryisamathematicalframeworkthatcomesfromclassicalgame13

theoryusedtodescribethebehaviourofrationalplayers.Classicalgametheorytriestoanalysethe14

behaviourinconflictsineconomicandsocialsettingsinwhichthesuccessofanindividualstrategy15

dependsonthestrategiesemployedbytheotherplayers.Awell-studiedexampleingametheoryis16

theprisoner’sdilemmainwhichthechoicestoeitherconfessorremainsilentdeterminewhether17

twosuspectsareconsideredguilty(Axelrod,1990).Inevolutionarygametheory,thestrategiesare18

notassociatedtorationalandcognitivechoices,butaretraitsencodedintoinheritedprogramsthat19

canbepassedtotheoffspring(forthisreason,thetermstraitandstrategiesareusedinan20

indistinguishablemanner).Traitssuchastheusageofmetabolicpathwaysortheexpressionof21

certainenzymescanbethenregardedasstrategiesandasuccessfulstrategyisthenselectedfor.22

Inamicrobialcommunitycomposedofspeciesthatcompeteusingdifferentstrategies,each23

oftheindividualcellspossessesafitnessthatdependsonitsstrategyandonthestrategyofthe24

individualswithwhomitinteracts.Individualsthatusemoresuccessfulstrategieshavehigher25

chancestopropagateandtheirfrequencyinthecommunitywillincrease.Althoughthedynamicsof26

anevolutionarygametheorymodelcanbestudiedanalyticallywhenthesetofstrategiesissmall,27

duetothelargenumberofinteractionstakingplaceinmicrobialcommunitiesmanyauthorsprefer28

tosimulatethedynamicsofthecommunityusingagent-basedmodelling.Inthesemodels,the29

replicationanddeathofindividualcells(agents)areexplicitlysimulatedusingasystemupdatedbya30

seriesofdiscreteevents(Adamietal.,2016).Thesetypesofmodelsalsoincludethepossibilityof31

addingmutationsthatcanintroducenovelstrategiesnotyetpresentinthespecies,whichcanbe32

usedtosimulaterandomevolutionofmembersofthecommunity(ErikssonandLindgren,2005).33


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Incellularpopulations,acooperativetraitisoftencharacterisedbythepresenceofashared1

publicgood,whichisafiniteresource,producedbycooperativecellsandthatisfreelyavailableto2

allothercells.Thepresenceofapublicgoodisalwaysassociatedwiththeriskofcheatingcells,3

whichexploitthepublicgoodwithoutprovidinganycontributiontoitandwhichcanspreadinthe4

population–duetotheirimprovedfitnessarisingfromnotinvestingthecostsassociatedwithpublic5

goodproduction.Althoughinthisreviewwefocusonmicrobialpopulations,thisisaverygeneral6

issueinthesustainabilityofmanyorganismsatdifferentscalesincludinghumans,justifyingwhythe7

evolution(andresilience)ofcooperationisconsideredoneofthemajoropenquestionsinbiology8

(Pennisi,2009).9

Evolutionaryconflictsbetweencooperativeandcheatingcellshavebeenstudiedinavariety10

ofmicrobialscenarios,includingtheconversionofsucroseintoglucosebytheyeastSaccharomyces11

cerevisiae(Goreetal.,2009),theproductionoftheshareableiron-scavengingsiderophore12

pyoverdineinPseudomonasaeruginosa(Kümmerlietal.,2009)andtheformationoffruitingbodies13

inMyxobacteria(VelicerandVos,2009).Giventhepotentialsimilaritieswithcelluloseandother14

polymersbiodegradation,theexamplefromyeastisworthexplainingfurther.Inthiscase,15

cooperativeandcheatingcellsonlydifferbytheproductionoftheenzymeinvertasethatconverts16

sucroseintoglucoseandfructose.Bothmonosaccharidescaneventuallydiffuseawayfromthe17

producingcellandbecomeavailabletoneighbouringcells.Inotherwords,theybecomepublic18

goods:cooperators—thecellsthat‘feed’themselvesandtheirneighboursattheexpenseof19

expressingtheenzyme—canbeexploitedbycheaters,cellsthatdonotexpresstheenzymeand20

relyoncooperatorstomakefood(Fig.1A).Inascenariolikethis,itwouldbeexpectedthatcheaters21

couldtakeoverthepopulation.However,thefitnessofthecellsisanon-linearfunctionofthe22

glucoseconcentrationand,forcertainvaluesofglucoseuptakeandmetaboliccostofenzyme23

production,itispossibletoobservetheco-existenceofthetwospeciesasanticipatedbyan24

evolutionarygametheorymodel(Goreetal.,2009).Infact,inacomplexcommunitycomposedof25

multitudeofspeciesitislikelythatsuchmechanisticpropertiesrelatingtotheimplementationof26

thedifferentstrategies,suchasregulatorymechanismscontrollingtheproductionofapublicgood,27

willaffecttheevolutionaryandecologicaldynamicsofthestrategiesandthusthewholecommunity.28

Beforediscussingfurtherthesepotentialmechanismsthatcanstabilisecooperativeinteractions,we29

willfirstdescribetypesofcooperativeinteractionsinmicrobialpopulations.30

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Microbialcooperationsbasedonpublicgoods32

Shared(public)goodsaremoleculesproducedbycertainindividualsandcanbenefittheentire33

population(Westetal.,2007).Asexplainedabove,thesemoleculesaresynthesisedatacostand,34


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therefore,aresusceptibletobeexploitedbycheatercellsthatcanbenefitfromthembutdonot1

contributetotheirproduction–henceacquiringafitnessadvantageovercooperators.Thistypeof2

cooperationisbasedonalargevarietyofsharedmolecules:siderophores,enzymes,biosurfactants,3

componentsofbiofilmmatrix,quorumsensingmolecules,bacteriocins(proteinssecretedbyone4

straintoinhibitthegrowthofacloselyrelatedstrain)andtoxinsassummarizedin(Westetal.,5

2007).Giventheirinterestinmicrobialbiotechnology,inthisreviewwewillfocusonsecretionof6

degradatoryenzymes.7

Microorganismsdigestlargemacromolecules,whicharepoorlysoluble,throughthe8

secretionofextracellularenzymes.Themacromoleculesaretypicallypolymersofbiologicalor9

syntheticorigin,suchasstarch,celluloseandpolyesters,whichconstituteanabundantsourceof10

nutrientsforbacteria,fungiandothereukaryoticmicroorganisms(Allison,2005;Richardsand11

Talbot,2013).Thesepolymersalsoconstituteaveryinterestingsubstrateforindustrialbioprocesses,12

astheyareinexpensive,biodegradableatsomeextentandoftenobtainedfromrenewablesources13

(GrossandKalra,2002).Theenzymessecretedbymicroorganismsactbydegradingthe14

macromoleculesintosimplerandsmallercomponentsthatcanthenbeassimilatedbythemicrobial15

community(Burns,2010).Inthisscenario,thedynamicsofthecooperatingandcheating16

populationsdependonparameterssuchasthecostofproducingtheenzymesandtheirdiffusibility17

(Allison,2005).18

Cellulasesandoxidativeenzymessecretedtocleavecellulosesuchascellobiase19

dehydrogenasescanbeconsideredasinstancesof‘publicgoods’(Dimarogonaetal.,2012)andare20

foundinthegenomeofmostwood-degradingmicrobialcommunities(Zamockyetal.,2006).Similar21

tocellulases,amylasescapableofdegradingtheglycosidiclinkagesofstarchesalsoplayan22

importantroleaspublicgoodsandhavebeenidentifiedinmanybacteriaandfungi,suchasBacillus23

subtilis(ColemanandElliott,1962),Thermomyceslanuginosus(Arnesenetal.,1998),Penicillium24

expansum(Doyleetal.,1998),andseveralspeciesofStreptomyces(El-Fallaletal.,2012).Similarly,25

enzymesresponsibleforthedigestionofothermacromoleculessuchasextracellularlipasesand26

proteasesarealsoexamplesofpublicgoods,andtheirproductioninacomplexmicrobialcommunity27

isinfluencedbytheinteractionsbetweenitsmembers(WillseyandWargo,2015).Collectively28

producedenzymesarealsoresponsibleforthedegradationofoil-derivedplasticpolymerssuchas29

poly-ethylenterephthalate(PET).Theidentificationofbacterialspeciesproducingenzymescapable30

ofPETdepolymerisation,thereforegeneratingmoleculesthatcanthenbeassimilatedbythe31

microbialcommunityinthatniche(Chenetal.,2010;Yoshidaetal.,2016)pavesthewayforthe32

remediationofPETwasteanditsuseasabioprocessingsubstrate(Wierckxetal.,2015).33

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Microbialcooperationsbasedonmetabolicinteractions1

Metabolicexchangeisanotherwayinwhichmicroorganismscaninteractcooperatively.Metabolic2

interactionsarewidespreadinnaturalmicrobialcommunitiesandarisefrommetabolitesfromone3

speciesbeingusedasenergysourcesorbuildingblocksbyotherspecies(Pacziaetal.,2012;Cooper4

andSmith,2015;Fioreetal.,2015).Theformerscenarioleadstocross-feeding,whereasthelatter5

canleadtoemergenceofauxotrophies(anorganismfullyrelyingontheenvironmentalprovisionof6

certaincompoundsrequiredforitsgrowth)(Fig1B).Themetabolitesreleasedintotheenvironment7

canbeexplainedbyeitherpassiveoractivemeans,i.e.organismsnotbeingabletomaintaincertain8

compoundsduetoleakageissuesoractivelysecretingthosecompoundsduetosomefunctional9

benefits.Whiletheformerexplanationcouldariseduetosomefundamentalbiophysicallimitations10

onbiologicalmembranes,thesecond(functional)explanationisdifficulttorationwithinasimplistic11

viewoforganismalfitness.Onecouldnaivelyarguethatsinceotherorganismsusethesecreted12

metabolitesasaresource,evolutionshouldhaveallowedthe‘secretingorganism’alsotoinnovate13

thatcapacityofusingthismetabolite(asanenergysourceorbuildingblock)ratherthansecretingit.14

Thisnaïveview,however,ignoreslimitationsarisingfromcellulartradeoffsandthermodynamics.15

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Metabolicinteractionsemergingfromthermodynamiclimitations17

Inprinciple,cross-feedingandauxotrophicinteractionscouldbeseenasanextremeformof18

cooperation(i.e.,‘altruism’)astheybenefitonlythereceivingorganisms.Undercertainconditions,19

however,secretionofinternalmetabolitescanalsobenefittheproducerleadingtoamutually-20

beneficialinteraction:iftheproductsreleasedhaveaninhibitoryeffectontheproducer,the21

presenceofanadditionalspeciesthatwouldassimilatetheseproductswouldleadtomoremild22

formsofcooperativeinteractionratherthanastraight‘altruistic’actonbehalfoftheproducer(Lilja23

andJohnson,2016).Morespecifically,thistypecross-feedinginteraction,involvingreleaseof24

inhibitionarisingfrombyproductsofmetabolismofoneorganismbyanotherisoftenreferredtoas25

syntrophy(Fig2A).Themost-wellknownexampleistheH2-mediatedsyntrophicinteractions26

betweensecondarydegradersandmethanogens(Schink,1997).Intheseinteractions,theinhibition27

ofthedegradingspeciesarisesduetoitsgrowth-supportingmetabolicreactionreachingtowards28

thermodynamicequilibriumasH2accumulates(Schink,1997;GroßkopfandSoyer,2016).This29

‘thermodynamicinhibition’isrelievedbytheconsumingofH2bythesyntrophicpartners(McInerney30

andBryant,1981;Seitzetal.,1988;ScholtenandConrad,2000),creatingasituationinwhich31

continuedgrowthisonlypossiblewhenthetwopartnersco-exist.Manyofthebiodegradation32

processesconsistofindividualsyntrophicandcross-feedinginteractionsamongdifferentspecies33

(Schink,1997),withexamplesincludingthedegradationofmonoaromaticandpolyaromatic34


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compoundsinsyntrophywithmethanogens(KnollandWinter,1989;Berdugo-Clavijoetal.,2012;1

Morrisetal.,2013).Syntrophicinteractionsarealsoimportantinoil-degradingmicrobial2

communities,althoughtheexactrolesofmanyindividualmembersinthesecommunitiesareless3

clear.Ithasbeenreported,forinstance,thatsyntrophicinteractionsbetweenDesulfatibacillum4

alkenivoransandMethanospirillumhungateiarenecessarytodegraderefractoryhydrocarbons5

(Westerholmetal.,2011;Callaghanetal.,2012).6

Theseexamplesillustratehowubiquitousandessentialsyntrophicinteractionsarefor7

completedegradationoforganiccompounds.Therefore,forfullybeingabletooptimize8

bioprocessesandbiotechnologiesaroundorganicdegradationandtransformationsweneedabetter9

understandingoftheemergenceandmaintenanceofmetaboliccooperations. Itisimportantto10

notethatsyntrophicandcross-feedinginteractionsareshowntoaltercellularmetabolicfluxes11

withinindividualspecies,aswellasinsimplecommunitiessuchthatthepresenceofadownstream12

syntrophicpartnercanresultinchangesinthemetabolicby-productsandyieldsfromupstream13

producermicroorganisms(McInerneyandBryant,1981;Seitzetal.,1988;Schink,1997;Scholten14

andConrad,2000).Inotherwords,organisms’preferredmetabolicroutes(or‘strategies’)would15

changewithlocalsubstrate/productavailabilities(aswellasinternalconstraintssuchasonuptake16

ratesorcofactoravailabilities),buttheseinturnwoulddependonwhatotherorganismswould17

choosetodometabolically.Fromatheoreticalperspective,thissituationcannotbeanalysed18

assumingasimpleindividualfitnessoptimizationunderconstantselectionpressure,butwould19

requireinsteadthecombinationofevolutionarygametheoryandecologyinordertodevelop20

theoreticalframeworksandexperimentalmodelsystemsaccountingforthedescribedcomplex21

interplays.22

Theinclusionofthermodynamicsinmodelsofmicrobialgrowthandmetabolismcould23

contributetounraveltheemergenceofmetabolicinteractions.Takingintoaccountthe24

thermodynamicconstraintsofgrowth-supportingmicrobialbiochemicalreactionswouldenable25

bettercapturingchangesintheconcentrationsofdifferentcompoundsintheenvironmentandthus26

allowdirectlinkagebetweenecologyandindividualgrowthrates.Therehavebeenseveralrecent27

attemptsinthisdirection,andmodelsincludingthethermodynamicsofmetabolicreactionshave28

beensuccessfullyemployedtodescribethedynamicsofsomebiodegradationprocesses,suchasthe29

fermentationofglucoseandthereductionofnitrate(González-Cabaleiroetal.,2013,2015;Cueto-30

Rojasetal.,2015),toexplainmicrobialdiversity(GroßkopfandSoyer,2016),aswellastomodel31

individualspeciesgrowth(HohandCord-Ruwisch,1996;JinandBethke,2007).Additionalworksin32

thisdirectionwillallowbetterpredictivemodelstoexplainevolutionaryandecologicaldynamicsof33


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microbialcommunitiesunderconditionswherethermodynamics-drivenmetabolicinteractions1

dominate.2

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Metabolicinteractionsemergingfromcellulartradeoffs4

Asdiscussedabove,fitnessoptimizationisacomplexfunctionofmultipletraitsanditissubjectto5

intrinsictradeoffsthatcouldreadilyexplainmetabolicsecretions.Inparticular,theoptimizationof6

ATP-generatingpathwaysunderlimitationsonenzymeinvestmentandinternalmetabolic7

concentrationsisshowntoleadtotheevolutionofimpartialpathwaysandmetaboliteexcretion8

(PfeifferandBonhoeffer,2004).Similarly,limitationsonmembranespaceandinternalresources9

suchasenzymesandconservedmoietiescancausetradeoffsinsubstrateuptakeratesandinternal10

metabolicfluxes,resultingindifferentgenotypesthatdifferentiallyutilizerespiratory(i.e.pathways11

endingwithinorganicterminalelectronacceptors)andfermentation(i.e.pathwaysendingwith12

organicterminalelectronacceptors)pathways(MajewskiandDomach,1990;Vemurietal.,2006;13

Molenaaretal.,2009;Zhuangetal.,2011;vanHoekandMerks,2012;Flamholzetal.,2013;Basan14

etal.,2015).Sincetheendproductsoffermentativepathwaysareusuallystillabletosustainfurther15

microbialgrowth,thiscouldagainexplainthefirststageofformationofmetabolicinteractions16

throughmetabolicexcretions.Subsequently,limitationsonsubstrateuptakearepredictedtoactas17

aforcetodrivemetabolicspecializationonsuchexcretedcompounds(Doebeli,2002;Spenceretal.,18

2007).19

Theideaofcellulartradeoffsdrivingtheemergenceofmetaboliccross-feedinghasrecently20

beenevaluatedinacombinedinsilicoandexperimentalevolutionstudy(Großkopfetal.,2016).In21

thatstudy,theauthorshaveincorporatedtradeoffsinastoichiometricmetabolicmodelofE.coliby22

imposingglobalconstraintsonthetotaluptakerates.Thismodelwasthensimulatedusing23

dynamicalfluxbalanceanalysis,whichallowsmodellingofbothmicrobialgrowthandenvironmental24

substrateconcentrations,andmutations,whichcanalterthedistributionoftotaluptakefluxamong25

differentsubstrates.Inotherwords,thisapproachcombinedsimulationofecologicaland26

evolutionarydynamicsatthesametime;startingfromasinglemodel,theinsilicosimulationscan27

leadtoalterationsbothintheenvironmentalconditionsandmutantmodels(Fig.2B).The28

applicationofthisapproachtothemodellingoftheexperimentallong-termevolutionofEscherichia29

colirevealedthatthecombinationoftradeoffsandecological/evolutionarydynamicsresultsinthe30

emergenceoftwodominantmodels(Fig.2C).Thesetwomodelshavedistinctuptakefluxes31

suggestiveofacross-feedinginteraction;onemodelhadincreasedglucoseuptakeandacetate32

excretionrateandtheotherhadincreasedacetateuptakerate(Großkopfetal.,2016).Further33

experimentalanalysesrevealedthatthetwomodelsshowmetabolicfluxpatternsthatqualitatively34


10

matchexperimentallyobservedgenotypesinonelineageofthelong-termexperiments,indicating1

thatthisapproachmightprovideusefulinsightsintohowecologicalandevolutionarydynamicscan2

shapemetabolicsystems.Indeed,anemergingtrendintheanalysisofcommunitydynamicsisto3

increasinglycombinemulti-speciesecologicalsimulationswithstoichiometricmodelsdescribingthe4

metabolismofthoseinteractingspeciesinanattempttogenerateinsightsintoecology–5

evolutionaryinterplay(LoucaandDoebeli,2015;Widderetal.,2016;ZomorrodiandSegrè,2016).6

7

Factorscontributingtothestabilizationofcooperativeinteractionsinmicrobialpopulations8

9

Structuredenvironments10

Oneofthebasicmechanismsthataffecttheresilienceofcooperationisthepresenceofspatial11

structure.Structurewouldultimatelyfacilitatetheresilienceofcooperationasitallowsthe12

‘segregation’ofcooperativefromcheatingcells(Nowak,2006)(i.e.,cooperativecellscanthenshare13

theproducedpublicgoodwiththesimilartrait,excludingcheatingcells)(Fig3A).14

Thereareseveraltheoreticalstudiesandexperimentalevidencesofspatialsegregationin15

cellularpopulations(VanDykenetal.,2013),withbiofilmsbeingaparadigmaticexampleofbacterial16

communitiesexhibitingstablecooperationduetothesegregationinstructuredenvironments17

(Nadelletal.,2009).Thestructureandcompositionofbiofilmscanfeedbackonthehighlydynamic18

competitionbetweensub-populationsofcooperators(i.e.,contributingtothebiofilmassembly)and19

cheaters.Inthesecircumstances,thespatialarrangementsofthedistinctgenotypescruciallyaffect20

thedegreeofcooperationandcompetitionpresentinthebiofilm(Nadelletal.,2016).21

Abroadernotionofstructurecanalsorefertothecaseofhavingapopulationdistributed22

intodifferentheterogeneoussub-populationsthatmaybespatiallysegregated(e.g.forming23

colonies).Inthiscasethestructureofthepopulationcanleadtoacharacteristicissueofmulti-level24

selectionknownasSimpson’sparadox.Simpson’sparadoxisastatisticalphenomenomthatcan25

emergewhencomparinggroupsofdata;groupscandisplayatrendwhenanalysingthem26

individually,butthistrendisreversedwhenthegroupsarecombined.Afamousexampleof27

Simpson’sparadoxistheonebehindthegenderdiscriminationaccusationagainsttheUniversityof28

Berkeleyinearly1970s.Inthatcase,44%ofthetotalmaleapplicationstothegraduateschoolwere29

acceptedagainstthe35%ofthefemaleapplicantssuggestingabiasagainstfemaleapplicants.30

Lookingintohowtheapplicationsweredistributedamongthedifferentdepartments,however,it31

becameclearthattherewasnobias,andthedifferencesintheratesweretheresultofamajorityof32

womenhavingappliedtothemostcompetitivedepartments,whichdecreasedthesuccessrateof33

thefemaleapplicants.Inotherwords,theapparentbiasisonlytheresultofthewaysthe34


11

applicationsareaggregatedtogether(Bickeletal.,1975).Inthecontextofmicrobialcommunities,1

Simpson’sparadoxisshowntoemergewhenthedifferentsub-groupsaresufficiently2

heterogeneousintheircompositiontoguaranteethatintheaggregatepopulationthecooperative3

individualshaveanadvantageoverthecheatingcells(despiteineachofthecolonies–the4

disaggregatedpopulation–cheatersarefavoured)(Chuangetal.,2009).Thisfindingsuggeststhat5

theopportunedesignoftheorganizationofamicrobialcommunityinsub-populations(and6

subsequentcoalescenceofthosesub-populations)maybeusefultoimproveitsresilienceto7

detrimentalmutants.Ingeneral,othermorecomplexnotionsofstructuredpopulationsfrom8

ecology(e.g.,meta-populationdynamics)couldalsoberelevanttounderstandandcontrolthe9

evolutionarydynamicsofcooperativeinteractions(Dattaetal.,2013).10

11

Interplaybetweenecologicalandevolutionarydynamics12

Anotherstabilisinganddrivingfactorbeyondcooperativeinteractionsinmicrobialcommunitiesis13

theinterplaybetweenecologicalandevolutionarydynamicsthatresultsinchangesinthe14

compositionofthecommunityovertime.Thishappenswhen,duetotheinteractionsina15

community,certaintraits(suchascheatingandcooperation)areselectedfororagainst,resultingin16

rapidchangesinthefrequencyoftheindividualscarryingthetraitthataffecttheecologyofthe17

globalcommunity.Thechangesintheecologycanthenfeed-backontheselectiveadvantageofthe18

differenttraits(asdiscussedabove),leadingtoaneco-evolutionaryfeedback(Fig.3B)(Lennonand19

Denef,2015).Thisaspecthasbecomeofrecentinterestduetoseveraltheoreticalandexperimental20

studiesshowingthenon-trivialeffectsofthetime-scalesoverlapbetweenecologyandevolutionin21

whatarecalledeco-evofeedbacks(Schoener,2011).Thereareseveralexamplesofeco-evo22

feedbacksinmicrobialpopulationsinvestigatedexperimentally(FiegnaandVelicer,2003;Ross-23

Gillespieetal.,2009;Moreno-Fenolletal.,2017)withthemostknownexamplebeingtheinterplay24

betweenpopulationdensityandfitness(SanchezandGore,2013).Forinstance,intheyeast25

communitiesdiscussedabove,cooperativecellshavehigherfitnessthancheatingcellsonlyatlower26

populationdensity.This,coupledtothefactthatcheatersleadtolowerpopulationgrowth,27

facilitatestheobservedco-existencebetweenthetwotraits,i.e.thestabilisationofcooperation28

(SanchezandGore,2013).Eco-evofeedbackscanbemodelledbyaddingnotionsofpopulation29

dynamicstoevolutionarygametheory,leadingtotheframeworkofecologicalpublicgoodgames30

(Hauertetal.,2008)thatextendthestandardevolutionarygametheory(inwhich,usually,thefocus31

oftheanalysisisthechangeinfrequencyofacertaintrait).Combinationofpopulationdynamics32

withmetabolicmodelsatthelevelofindividualspeciesorgenotypes(Harcombeetal.,2014)with33


12

evolutionarydynamics(Großkopfetal.,2016)isanotherpromisingroutetowardscapturingeco-1

evolutionarydynamics,especiallywhencooperativeinteractionsinvolvemetabolitesecretions.2

3

Regulatorymechanisms4

Anotherpotentialfactorforthestabilisationofcooperationthathasrecentlyattractedattentionis5

cellularregulatorymechanisms.Animals,includinghumans,havedevelopedcomplexsocial6

strategiestocontrolcheaters,andthereisgreatinterestindeterminingtowhichextentsinglecell7

organismscouldemploysimilarmechanismstofightdetrimentalmutants(TravisanoandVelicer,8

2004).9

Oneoftheseregulatorymechanismsisknownas‘reciprocity’.Inthiscasetheamount10

contributedofapublicgooddependsontheenvironmentalconditions,whichinturnmaydepend11

onthecontributionsmadebyothers.ThisisforinstancethecaseofironuptakeinP.aeruginosa12

whereironscavengingsiderophores(thepublicgood)arereleasedingreaterorsmallerquantities13

dependingontheamountofironintheenvironment(Kümmerlietal.,2009).Recentexperiments14

usingthissystemhaveconfirmedthatcellsuseatypeof‘reciprocity’thatfacilitatesthecontrolof15

cheaters:thecellulardecisionofproducingpublicgoodismadeonlyinanenvironmentwithmany16

producers.Inotherwords,thecellsseemtoimplementarulestating‘cooperatewhensurrounded17

bymostlycooperators’.Coupledtoquorumsensing,thisruleallowsbacteriatomatchtheir18

investmentatlowerlevelsofpopulationstructuringanditisaneffectivewaytorepresscheaters19

(Allenetal.,2016).Inyeast,asimilarmechanismhappensintheproductionofinvertase.Another20

regulatorymechanismthatcouldbeinterpretedasafunctional‘decision’tolimitthespreadof21

cheatersistoincreasethenoiseintheexpressionofgenesencodingforpublicgoods(Goreetal.,22

2009).Thisisthecaseofself-destructivecooperation,inwhichcooperativecellsdiewhilehelping23

others,forexample,asithappensduringthesecretionoftoxinsthatenhancethecolonizationof24

tissuesbycertainbacterialpathogens(Ackermannetal.,2008).Sincethetoxinisgenetically25

encoded,itisonlyexpressedbyafractionofthepopulationorthewholemicrobialpopulation26

woulddie.The‘decision’onwhichcellsmaketheultimatesacrificeisgivenbythestochastic27

expressionofthegeneencodingthetoxin.Similarly,cell-cellvariabilityintheproductionofother28

kindsofpublicgoodsmayallowcooperativecellstotemporarilyswitchofftheproductionofapublic29

good,thereforelimitingitscostandallowingforenhancedcompetitionagainstthecheatingcells.30

Thesetypesofcellulardecision-makingmechanismscaninterplaywithanunderlyingeco-31

evodynamics(HarringtonandSanchez,2014)andcruciallyaffecttheresilienceofcooperation,as32

shownintheoreticalmodels(CavaliereandPoyatos,2013)(Fig.3C).Thus,itisplausibletopropose33

thecontrolofpublicgoodproductionforsuccessfulbioprocesses(suchasthedescribedcellulose34


13

degradation)throughexistinggeneregulatorymechanismsorbyengineeringsuchmechanismsde1

novo.2

3

Horizontalgenetransferofcooperativetraits4

Mobilegeneticelements(plasmids,bacteriophages,transposons,etc.)transmittedviahorizontal5

genetransferareoneofthemainfactorscontributingtoshapingmicrobialevolution.Apartfromthe6

genesessentialforthereplicationandtransmissionessentialforthemobileelements,theyoften7

carrymultipletraitstheenablesocialinteractionsinmicrobialcommunitiesandmakethemactive8

agentsdefiningtheevolutionarydynamicsofthesecommunities(Rankinetal.,2011).9

Cooperativetraitssuchaspublicgoodproducingexoenzymesarecommonlyacquireddueto10

thetransferenceofmobileelements.Infact,agenomicanalysisinsomebacterialspeciesshowthat11

thefrequencyofgenesencodingextracellularproteinsissignificantlyhigherinchromosomal12

locationsknowntobetransferred(e.g.transposons)comparedtoregionsthatarenot,andthe13

frequencyisevenhigherinplasmids,whichwerethemostmobileelementspresentintheanalysis14

(Nogueiraetal.,2009).Horizontalgenetransferisalsoresponsibleforthetransmissionof15

exoenzymesineukaryoticmicroorganisms,asrevealedbyasimilaranalysiscarriedoutin16

osmotrophicfungi,inwhichitbecameevidentthatnotonlytheenzymes,butalsothetransporters17

requiredfortheuptakeoftheproductsresultingfromtheactivityoftheenzymesonlargepolymers,18

wereencodedinmobilegeneticelements(RichardsandTalbot,2013).19

Theseobservationsareconsistentwiththeideaofmobileelementsenablingcooperationin20

acommunityowingtotheinvasionofmobileelementstransmittingcooperativetraits.However,the21

mobileelementsalsogenerateacosttothecellsharbouringthemand,therefore,canpotentiallybe22

lostoroutcompetedby‘cheat’geneticelements(Rankinetal.,2011).Recentexperimental23

evidencesshowneverthelessthathorizontalgenetransferhelpstomaintaintheproductionof24

publicgoodsdespitethepotentialpresenceofnon-cooperativeorganismsandnon-cooperative25

mobileelements(Dimitriuetal.,2015)owing,amongotherfactors,totheincreaseingenetic26

relatednessduetothepresenceofthemobileelements(McGintyetal.,2013).Inotherwords,27

transmissiblemobileelementsallowforthelocalenrichmentincooperativeinteractions,which28

may,inthelongterm,leadtothespecializationofsub-populationsincooperativenichesspeciallyin29

thepresenceofstrongstructure(Niehusetal.,2015).30

31

Therelevanceofcooperationforbiotechnologicalapplications32

Thepresenceofcooperativeinteractionsfacilitatesthedevelopmentofcomplexfunctionsthat33

wouldbeotherwisedifficultorimpossible(Nowak,2006).34


14

Cooperativemicrooorganismscanexhibitdistributionoflabour:alargecollectionofdistinct1

phenotypicbehaviours,organizedinsubpopulations,cancoordinatetofulfilsomecomplextasksina2

collectiveway(Fig4A).Shareddiffusiblemoleculesallowcellstocommunicateandspatially3

distributethelabour.Examplesofcomplextasksrangefromthecontrolledgrowthofbiofilms4

dependingonenvironmentalconditions(Liuetal.,2015;Kimetal.,2016)tothedistributed5

computationofBooleanfunctions(Regotetal.,2011).6

Thistypeofinteractioniscommonlyobservedinbiodegradativeprocessescarriedoutby7

interspeciesbiofilms.Forinstance,thepresenceofaalgaeinamicrobialconsortiumwithmorethan8

ninebacterialspeciesenhancesthedegradationofthepesticidediclofopmethyl(Wolfaardtetal.,9

1994).Anotherinterestingexampleisthesyntrophicinteractionbetweenthenon-cellulolytic10

speciesTreponemabryantii,andthecellulolyticspeciesRuminococcusflavefaciens,toenhancethe11

rateofcellulosedegradation.TheslowlygrowingculturesofR.flavefaciensbenefitsfromT.bryantii12

removingthecellulolyticproduct,whichresultsinhigherpopulationdensityanddegradationrates13

(Jamesetal.,1995).14

Distributionoflabouris,however,notrestrictedtospatiallystructuredpopulationsor15

populationscomposedbymorethanonespecies,butcanalsoapplytootherbiologicalprocesses16

likethebiochemicalpathwaysforthedegradationofaromaticsinpopulationscomposedofone17

strain(Nikeletal.,2014).Thesepathwaysaresometimesorganisedintotwodistinctgeneoperons,18

oneencodingfortheactivitiesrequiredtofunnelthearomaticsubstrateintoamoreaffordable19

aromaticcarbonsourceandasecondrequiredtotransformthisaromaticcompoundintocentral20

metabolites.Forinstance,theTOLpathwayofPseudomonasputidaresponsiblefortolueneand21

xylenedegradationcontainsan‘upper’partthatconvertstolueneintobenzoate,anda‘lower’22

segmentresponsibleforthedegradationofbenzoate(Franklinetal.,1981).Inprinciple,itwouldbe23

expectedthatallcellsexpressbothoperonswhenaclonalpopulationofP.putidaisculturedinthe24

presenceoftoluenebut,surprisingly,manyofthecellsdisplayanearbimodaldistribution25

expressingeitheroneoperonortheother(Nikeletal.,2014).Themechanisticexplanationofthis26

behaviourisunknownalthoughaplausibleexplanationofthephenotypicdistributionmayarise27

fromtheintricatetranscriptionalcontroloftheoperons(Silva-RochaanddeLorenzo,2012).28

Distributionoflabouralsoappearsintheanaerobicmetabolismofaromaticcompoundsin29

Rhodopseudomonaspalustris.Monoculturesofthisspeciesorganiseinthreedifferent30

subpopulationswhenusingp-coumarateorbenzoateasthecarbonsource.Eachofthese31

subpopulationsisresponsiblefortheutilizationofeitherthearomaticcompound,CO2andH2or,32

whengrowingonbenzoate,N2andformate,formingasyntrophicconsortiadefactocomposedofa33

singlespecies(Karpinetsetal.,2009).However,whetherthisparticulartypeofcooperativecross-34


15

feedinginteractionisadvantageoustopreventwasteofresourcesoraccumulationoftoxic1

intermediatesisanopenquestion.2

Distributionoflabourcanalsobeengineeredtogetherwithcooperativetraitsin‘synthetic’3

communities(Fig.4B).Thisisthecaseofco-culturingengineeredstrainsofthebacteriumE.coliand4

theyeastS.cerevisiaethatareartificiallymutualistic.Eachofthesestrainsismodifiedtoexpressone5

moduleofthebiosyntheticpathwayofanantitumoralcompoundofinterest(theacetylateddiol6

paclitaxelprecursor).Thecooperationbetweenthesespeciesallowsproductionoftaxaneswith7

higheryieldsthanusingE.colialone.ThemixedculturecombinesthecapabilitiesofE.colifor8

producingtheintermediatetaxadienewiththesuperiorpropertiesofS.cerevisiaecomparedtoE.9

colitocatalysetheoxygenationreactionsrequiredtorenderthefinalcompound(Zhouetal.,2015).10

Syntheticconsortiacanbeusedinbioprocessesevenintheabsenceofmutualismasexplainedin11

theprevioussections(e.g.ifeco-evofeedbackstakeplace).Thisisthecaseofanartificial12

communitydesignedtoproduceisobutanolfromcellulosicbiomasscomposedbythefungus13

TrichodermareeseiandanengineeredstrainofE.coli.InthisconsortiumT.reseeiactsasa14

cooperatorsecretingcellulasesrequiredtodegradelignocellulosicpolymersandtheresulting15

saccharidesareusedtofeedtheE.colistrainthatdeliversthefinalproduct(Mintyetal.,2013).16

Syntheticcommunitiescanalsoimprovebiodegradationprocessescomparedtomonocultures.17

Degradationofcrudeoilisagoodexampleinwhichmicrobialcommunitiescanexhibitcooperative18

interactionsinNatureincludingmetaboliccross-talkandsharedgoodsthatmaycontributetothe19

formationofinterspeciesbiofilms(McGenityetal.,2012).Moreover,theseinteractionscanbe20

harnessedtoproduceartificialcommunitieswithenhanceddegradationcapabilitiessuitableforoil21

removal(Gallegoetal.,2007).Anotherexampleisthedesulphurizationofdibenzothiophene(DBT)22

toformsulphur-free2-hydroxybiphenyl.Inarecentwork,DBTdesulphurizationwascarriedout23

usingeitheranengineeredP.putidastrainexpressingallthedszABCDgenesrequiredintheprocess,24

oramixedcultureofthesamestrainexpressingonlysomeofthegenes.Inthisexperiment,25

desulphurationofDBTwashigherwhencombiningmultiplecells‘specialising’inonestepofthe26

biochemicalpathwaycomparedtothecaseofhavingallreactionstakingplaceinthesameorganism27

(Martínezetal.,2016).28

Cooperativeinteractionsinmicrobialcommunitiescanalsoleadtohigherresistanceto29

environmentalandecologicalstress.Empiricalobservationsusingartificialcommunitiesofyeast30

showthatthisresistancetakesplaceoverawiderangeofconditions(Goreetal.,2009).Inaddition,31

experimentscarriedoutwithengineeredpopulationsofBacillussubtilislackingtheabilitytoform32

biofilmsshowthattheyneverthelesstendtoformclustersthat,althoughcanhavereducedgrowth33

duetolimitedmobility,allowthecellstoendureharshenvironmentalconditions(RatzkeandGore,34


16

2016).Inthiscase,cooperativeindividualstendtoaggregateleadingtothe‘privatization’ofpublic1

goodsandtotheexclusionofcheatingindividuals(Pandeetal.,2016).Ontheotherhand,thelossof2

cooperationmakescellularcommunitiesmorefragile(SanchezandGore,2013)andmorevulnerable3

tocompositionalshiftsarising,forexample,fromantibiotictreatments(Liuetal.,2015).Thefact4

thatthesebehavioursareobservedinexperimentswithdifferentmanipulatedspeciessuggeststhat5

thesemechanismsaregeneralandcouldbecommonplaceinNature.6

Thepresenceofmechanismsthatfacilitatecooperationcanalsoleadtocomplexco-7

evolutionarydynamicswiththeconsequentemergenceofnovelsocialinteractions.Themost8

significantexampleinthisrespectisthemechanismofquorumsensing(QS)thatisinvolvedin9

controllingtheinvestmentin‘publicgoods’(Allenetal.,2016).AlthoughtheoriginalroleofQSis10

unknown,itsabilitytofacilitatethe(beneficial)presenceofcooperativeinteractionsmayhaveledto11

theselectionofcomplexfunctionalities,e.g.,coordinatingtheexpressionofgenesinvolvedin12

multiplecooperativestrategies,oftenco-evolvingwiththem(Popatetal.,2015).Thisexample13

suggeststhepossibilityofusingthepresenceofcooperativeinteractionstodirecttheevolutionof14

thecommunitiestowardsotherpropertiesofinterest.15

16

Conclusion17

Thekeypointofevolutionarygametheoryisthatthefitnessofindividualsdependsnotonlyonthe18

environmentbutalsoonothermembersinthepopulation.Thistheoryprovidesaframeworkto19

understandthedynamicsofmanybioprocessesinvolvingcomplexmicrobialpopulations(natural20

andsynthetic)inwhichthefitnessofanindividualcellisinfactaffectedbytheenvironmentandby21

thepresenceofothercells.Aparticularcaseofthisscenarioconcernsthepresenceofcooperative22

interactionsbasedonpublicgoodsandmetabolicinteractionsandthathavebeenthemainfocusof23

thisreview.Wehavealsodiscussedsomeofthefactorsshapingtheseinteractionssuchascellular24

andthermodynamicconstraints,aswellasfactorsstabilisingthemsuchasstructuredenvironments,25

feedbacksarisingfromtheecologyofthepopulation,cellularregulatorymechanismsimplementing26

certainbehaviouralstrategiesandtheroleofmobilegeneticelements.Thesepropertiesendow27

cooperativemicrobialpopulationswiththepossibilitytoresistcheatersinvasionsandthecapability28

ofperformingmoresophisticatedtasks.29

Despiteitsgrowingusetostudytheevolutionofcooperation,evolutionarygametheoryhas30

hadsofaraverylimitedimpactinfieldorindustrialbiotechnologicalapplicationsinwhichthe31

environmentalconditionsaregenerallynotwell-definedandmayaffectthemicrobialcommunities32

(Bouchezetal.,2000;SaylerandRipp,2000;CasesanddeLorenzo,2005).Infact,wehave33

presentedseveralexamplessuggestingthatcooperativeinteractionsbasedoncross-feedingand34


17

publicgoodsareatthecoreofmanyprocessesrelevantforindustrialbiotechnologyincludingfood,1

energyandenvironmentalapplicationsofmicroorganisms.2

Therefore,theyaresuitableofimprovementbyincorporatingthemechanismsinvestigated3

inthelargeliteratureoftheevolutionofcooperation.Aswehavediscussed,populationscouldbe4

manipulatedbasedonthermodynamicconstrainstopromotecertainmetabolic(cooperative)5

interactions.Similarly,bioprocesses,includingbioreactordesign,couldbeengineeredtoaccount6

(andexploit)foreco-evofeedbacksandspatialorganizations.7

Understandinghowsyntrophyandcooperationendowthemicrobialpopulationswith8

resistanceandresilienceagainstecologicalandenvironmentaldisturbanceslikecompositionalshifts9

intheenvironmentorantibioticshockscouldbeusedtoengineerrobustmicrobialcommunities10

withenhancedperformanceandpredictabledynamics(BrionesandRaskin,2003;Allisonand11

Martiny,2008;Sözenetal.,2014).Overall,webelievethatthemigrationofresultsand12

methodologiesfromtheareaofevolutionarygametheoryintothedesignofmicrobialconsortia13

wouldfacilitatetheengineeringofevolutionaryresilientcommunitieswithabetterperformancein14

awiderangeofbiotechnologicalapplications.15

16

Acknowledgements17

JJwouldliketoacknowledgethesupportreceivedfromtheEuropeanUnion'sHorizon2020research18

andinnovationprogrammeundergrantagreementno.633962fortheprojectP4SBandthesupport19

fromtheBiotechnologyandBiologicalSciencesResearchCouncil(BBSRC)(grantBB/M009769/1).20

OSSacknowledgessupportfromBBSRC(grantsBB/K003240/1andBB/M017982/1).M.C.21

acknowledgesthesupportfromtheEngineeringandPhysicalSciencesResearchCouncil(EPSRC)22

grantEP/J02175X/1andfromUKResearchCouncils'SyntheticBiologyforGrowthprogramme.S.F.23

acknowledgesthesupportbyLaboratoryDirectedResearch&Development(LDRD)grant24

XWJX00/3000FENGfromLosAlamosNationalLaboratory.Theauthorsdonotahaveconflictof25

interesttodeclare.26

27


18

1

Figure1.(A)Interactionsbasedonsharedpublicgoods.Somecells(cooperators,showninblack2

edge)produceanenzymerequiredtosplitasubstrateintodigestibleproducts.Othercells(cheats,3

showningrey),donotproducetheenzymebuttakeadvantageofthepublicgoodsproducedbythe4

others.(B)Interactionsbasedoncross-feeding.Somecellsinthecommunityexcretemetabolites5

thatcanbetakenupbyothercellsgivingrisetoawebofinteractions.6

7


19

1Figure2.(A)Metabolicinteractionsthatcantakeplaceinapopulation.Cellscanexchangemetabolitesthat2

arerequiredtosupporteachother’sgrowthinamutualisticinteraction(left).Oneofthecellscanusea3

metaboliteexcretedbyanothercell,favouringinthiswaythemetabolismoftheproducerthroughthe4

pathwaysleadingtotheexcretion(centre).Whenthemetabolitesexcretedhaveaninhibitoryeffectonthe5

producer(e.g.becausetheyleadtothermodynamicequilibrium),therelationshipwithadegradercellofthe6

inhibitorymetaboliteismutuallybeneficialandknownassyntrophy(right).(B)Dynamicmodellingofthe7

evolutionofFBAmodels.Cellscanbemodelledasmetabolicnetworksexchangingmetaboliteswithother8

cellsinthepopulation.InthisabstractioneachcellisrepresentedbyaFluxBalanceAnalysismodel.These9

modelscanreplicateovertimeandalsoevolve,producingpopulationscomposedbymodelswithdifferent10

constrainsforuptakeandsecretionofmetabolites.(C)Dynamicanalysisofmodelgenealogy.Thefrequency11

ofeachmodelinthepopulationchangesovertimebeingthedarkestbarsthemostabundantmodels.Dueto12

mutations,newmodelsariseandtheyarerepresentedasnewbranchesinthephylogeny.Plotredrawnfrom13

(Großkopfetal.,2016).14

15

Mutualism Cross-Feeding Synthrophy

A

B

FBA1

FBA2FBA3

FBA4

Generation n

FBA1

FBA1*

Generation IGenerations

Mod

els

C


20

1Figure3.MechanismstoPreserveCooperationinCellularCommunities.(A):Astructuredenvironmentcan2

facilitatecooperation.Thefigureshowsthegrowthoffluorescentlylabeledcolonies(cooperatorsinred,3

cheatersingreen)ofS.cerevisiae(Figurefrom(VanDykenetal.,2013)).Cooperativecellsproduceinvertase4

thatbreaksdownsucroseintodigestibleglucoseandfructose.Non-producerscells(cheaters)haveafitness5

advantagebecausetheydonotproduceinvertasebutcanaccessglucose.Inunstructuredenvironment(liquid6

culture)cooperatorsdecline.However,inaspatialenvironment(obtainedbyspottingadropletofmixed7

cooperator/cheaterculturesontosolidmedium)cooperatorscanspreadovercheaters.Thediffusionofcells8

leadtotheformationofdiscretesectors-cooperatorsectorsaremoreproductivethancheatersectorsand9

willexpandradiallyfaster.(B):Eco-evodynamicscanpreservecooperationincommunitiesofS.cerevisiae10

(redrawnfrom(SanchezandGore,2013)).Redcirclesrepresentcooperativecells(invertaseproducers),green11

circlesrepresentcheaters(non-producers).Belowacertaincooperatordensity,thereislittleglucoseavailable.12

Cooperativecellsgrowataslowrateonthelittleamountofglucosetheycanretain,whilecheatercellsgrow13

moreslowly(itiscrucialthatcooperatorshavepreferentialaccesstotheglucose).Aboveacertaincooperator14

density,bothcooperatorsandcheatersgrowatafastratebecauseofthelargepoolofavailableglucose,but15

cheatersgrowfasterastheydonothavetheburdenofproducinginvertase.Suchdensity-dependent16

selectionfavorscooperatorsatlowdensitiesandcheatersathighdensities,whichleadstothestableco-17

existenceofcooperativeandcheatingyeastcells.(C):Regulationofpublicgoodproductioncanpreserve18

cooperationinameta-populationmodelinwhichthepopulationistransientlydividedinsub-populations19

A

C

B

Population density

Frac

tion

of c

oope

rativ

e ce

lls


21

(figurefrom(CavaliereandPoyatos,2013)).In-silicosimulationspresenttwopossiblesuccessfultypesof1

regulationagainstcheaters:positiveplasticity(toprow)inwhichcooperatorsconstraintcheatersbystopping2

theproductionofpublicgoodwhencheatersappear(a)andfullyrestartingonlywhencheatershave3

disappeared(b)andnegativeplasticity(bottomrow)inwhichcooperatorsproducepermanentlylow4

amountsofpublicgoodwhichhelpscontrollingcheatersinvasion(c).Thickarrowsdenotethecellulardecision5

toproduce(P)ornotproduce(nP)thepublicgood.Thesuccessoftheregulationiscoupledtothe6

heterogeneity(variance)ofthesub-populations,i.e.,positiveplasticitytransientlymodifiesthevariancewhile7

negativeplasticitykeepsarelativelyconstantheterogeneity(varianceshownin(d)correspondto8

trajectories(b)and(c),respectively).9

10


22

12

Figure4.(A)Divisionoflabourinmicrobialpopulations.ColoniesofPseudomonasfluorescensP0-1are3

composedbycellswithtwodifferentmorphologiesknownasmucoidanddrythatcanevolvefromeachother4

duetoasinglemutation(leftpicture).Coloniescomposedbyamixtureofthetwophenotypesexpandfaster5

allowingcellstocoloniselargerregionsinshorterperiodsoftimecomparedtocoloniescomposedbyeachof6

theindividualphenotypes.Thetwomorphotypesoccupydifferentregionsofthecolonyasshownwhen7

labelledwithfluorescentreporters(centre).Drycells(inred)exhibitaradialdistributiongrowingontopofthe8

mucoid(ingreen).Confocalmicroscopyrevealsthattheedgeofthecolony(rightpicture)displaysadistinct9

spatialorganizationinwhichmucoidcellsformathinstripattheveryedge.Thedifferentiationandspatial10

segregationallowsthedistributionoflabourinthepopulation:Mucoidcellsproducealubricantpolymerat11

theedge,whereasdrycellssitbehindandpushbothofthemalong.Thecooperationofthesetwophenotypes12

resultsinafastgrowingcolony.Pictureshavebeenreproducedfrom(Kimetal.,2016).(B)Engineered13

populationscanimprovebioprocesses.Twostrainsarecombinedtocarryoutthesynthesisofaproductof14

interest(redpentagons)thatcannotbeproducedusingeachofthestrainsindividually.Theprocessinvolves15

thatoneofproducesanintermediate(theyellowpentagon)thatisusedbytheothertosynthesizethefinal16

product.Ifthetwocellscompeteforthesameresources(e.g.carbonsourceshownbythebluehexagon;left17

panel)thepopulationwiththelowerfitnessunderthoseconditionswilleventuallycollapse.However,when18

thetwopopulationsareengineeredsothatonegrowsattheexpensesoftheother(e.g.throughcross-feedor19

syntrophyshownbythepurpletriangle),thetwopopulationscooperate(centrepanel)andthesynthesisof20

theproductofinteresttakesplaceforalongerperiodoftimeresultinginhigheryields(rightpanel).Panels21

inspiredby(Zhouetal.,2015).22

time

A

B

Competition Cooperationprod

uct

competitioncooperation


23

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Cooperation in microbial biotechnology 2 - … · · 2017-04-12Cooperation in microbial biotechnology 1 1 ... 23 This situation may confront the intuitive idea that ‘evolution