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Edinburgh Research Explorer
Cooperation in microbial communities and their biotechnologicalapplications
Citation for published version:Cavaliere, M, Feng, S, Soyer, O & Jimenez, JI 2017, 'Cooperation in microbial communities and theirbiotechnological applications', Environmental Microbiology, pp. 1-30. https://doi.org/10.1111/1462-2920.13767
Digital Object Identifier (DOI):10.1111/1462-2920.13767
Link:Link to publication record in Edinburgh Research Explorer
Document Version:Peer reviewed version
Published In:Environmental Microbiology
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Download date: 22. Jun. 2020
Cooperationinmicrobialbiotechnology
1
1
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Cooperationinmicrobialcommunitiesandtheirbiotechnologicalapplications3
4
MatteoCavaliere1,SongFeng2,OrkunSoyer3andJoseI.Jimenez4*5
6
1SchoolofInformatics,BBSRC/EPSRC/MRCSyntheticBiologyResearchCentre,Universityof7Edinburgh8
2CenterforNonlinearStudies,TheoreticalDivision(T-6),LosAlamosNationalLaboratory9
3SchoolofLifeSciences,BBSRC/EPSRCWarwickIntegrativeSyntheticBiologyCentre,Universityof10Warwick11
4FacultyofHealthandMedicalSciences,UniversityofSurrey12
13
*Towhomcorrespondenceshouldbeaddressed:14
FacultyofHealthandMedicalSciences15
UniversityofSurrey16
Guildford,GU27XH17
UnitedKingdom18
Email:[email protected]
Phone:+440148368455720
21
Statementofsignificance:22
InthisreviewwesummariseadvancesinthefieldofEvolutionaryDynamicsappliedtomicrobial23
communitiesandtheirapplicationsinbiotechnology.Wediscussdifferentkindsofcooperative24
interactions,theirpotentialmechanisticoriginsandthefactorsthatcontributetotheirstability.We25
alsoanalysetheadvantagesofcooperativebehavioursinmicrobialpopulationsandevaluatetheir26
possibleusetodeveloprobustbiotechnologicalapplications.27
28
Cooperationinmicrobialbiotechnology
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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
17
Cooperationinmicrobialbiotechnology
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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
Cooperationinmicrobialbiotechnology
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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
Cooperationinmicrobialbiotechnology
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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
31
Microbialcooperationsbasedonpublicgoods32
Shared(public)goodsaremoleculesproducedbycertainindividualsandcanbenefittheentire33
population(Westetal.,2007).Asexplainedabove,thesemoleculesaresynthesisedatacostand,34
Cooperationinmicrobialbiotechnology
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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
34
Cooperationinmicrobialbiotechnology
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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
16
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
Cooperationinmicrobialbiotechnology
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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
Cooperationinmicrobialbiotechnology
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microbialcommunitiesunderconditionswherethermodynamics-drivenmetabolicinteractions1
dominate.2
3
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
18
1
Figure1.(A)Interactionsbasedonsharedpublicgoods.Somecells(cooperators,showninblack2
edge)produceanenzymerequiredtosplitasubstrateintodigestibleproducts.Othercells(cheats,3
showningrey),donotproducetheenzymebuttakeadvantageofthepublicgoodsproducedbythe4
others.(B)Interactionsbasedoncross-feeding.Somecellsinthecommunityexcretemetabolites5
thatcanbetakenupbyothercellsgivingrisetoawebofinteractions.6
7
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
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
Cooperationinmicrobialbiotechnology
23
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