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MineClosure2015–A.B.Fourie,M.Tibbett,L.SawatskyandD.vanZyl(eds)
©2015InfoMineInc.,Canada,978‐0‐9917905‐9‐3
MineClosure2015,Vancouver,Canada1
Usinggenomicsinminereclamation
L.H.FraserNaturalResourceSciences,ThompsonRiversUniversity,Canada
H.W.GarrisNaturalResourceSciences,ThompsonRiversUniversity,Canada
S.A.BaldwinChemicalandBiologicalEngineering,UniversityofBritishColumbia,Canada
J.D.VanHammeBiologicalSciences,ThompsonRiversUniversity,Canada
W.C.GardnerNaturalResourceSciences,ThompsonRiversUniversity,Canada
Abstract
Forthemajorityofmines,closuresucceedswhenhealthy,self‐sustainingecosystemsdevelopon
previouslyminedlands.InBritishColumbia,Canada,theregulationsrequirereclamationof
ecosystems;however,therearefewspecifiedtargets,andthosethatarepresentedarevague.
Genomicstechnologiesmayprovidethekeytobothunderstandingtheelementsnecessaryto
recreatefunctionalecosystemsandprovidesufficientbenchmarksforsuccess.Inthisreview,we
highlighttheuseofgenomicstomeetmineclosuregoals,enhanceecosystemdevelopmentand
optimiseecosystemservicesinherentinself‐sustainingreclaimedecosystems.Weoutlinepractical
stepsforapplyinggenomicstechnologiestocharacterisethecompositionandactivityofmicrobial
communitiesinsoilsandtreatmentsubstrates.Fromthisframework,weaddressthestateofthe
scienceandhowrecentlydevelopedtechniqueshavetransferablevaluetominereclamation.We
thendefinethreeareasinwhichgenomicstechnologieshavealreadyproveneffectiveatinforming
managementandreclamationofminesitesintheformofbioreactors,passivetreatmentsystems
andnovelgenediscovery.Finally,wespeculateonthefutureapplicationsofgenomicstechnologies
andthenecessarystepstointegratethesedataintocomprehensivemanagementofminedsites.
1Introduction
Inanidealsystem,minesoperatewithminimalenvironmentalimpactwithinandoutsideoftheoperational
footprint.Aftertheperiodofprofitableextractionisreached,adesirableconditionisrecreated,beitforest,
pastureorsuburbanneighbourhood,sothatthebiota(soilmicrobestrees,andconcernedcitizensalike)can
functionwithinanatural,self‐sustainingecosystem.Inreality,minesitesoftenleavealegacy,including
perpetuallyalteredplantcommunities(Holl,2002);elevatedcontaminantsinsurfaceandgroundwater(Cidu
etal.,2001);thin,compactsoils(Skousenetal.,2009);alteredsoilfunction(Mummeyetal.,2002);and
magnificationofcontaminantswithinthefoodchain(Allan,1995;MuscatelloandJanz,2009).
InCanada,governmentregulationsonminingoperationssetthestandardsforreclamationsuccess,andasa
result,directthefateofminedlands.TheBritishColumbiaMinesActandHealth,SafetyandReclamation
CodeforMines(theCode)specifythatreclamationmustsatisfytherequirementsofthechiefinspector
(GovernmentofBritishColumbia,2008).Thelegislationisvagueandsubjecttointerpretation(byboththe
miningcompaniesandtheinspectors),sotherehasbeenvariabilityingoalsandmeasuresofsuccess.
Historically,goalsweresetforplantproductivity,likelybecauseproductivityisrelativelyeasytomeasureand
canbeassociatedwithecosystemfunction(Britton,1998).ThecurrentCode(10.7.5)expressesagoalfor
equivalentlandcapability,whichisachallengetoachievebecausetherearenosetpredefinedtargets.There
hasbeenarecenttrendtoconsidermineclosureintermsofthewholeecosystem,withallofitsfunctions
andservices.
Ecosystemservicescanbedefinedas“theaspectsofecosystemsutilised(activelyorpassively)toproduce
humanwell‐being“(Fisheretal.,2009).Theecosystemservicesforreclaimedminedlandsmayincludeforage
UsinggenomicsinminereclamationL.H.Fraser,H.W.Garris,S.A.Baldwin,J.D.VanHammeandW.C.Gardner
2MineClosure2015,Vancouver,Canada
forcattleandwildlife,timber,cleanairandwater,carbonsequestration,biodiversityandculturally
significantnaturalproductsrelatedtotraditionalpracticesandmedicines.Canadianregulationsexistto
protecttheseservices,orensuretheircontinuation,duringandafterminingactivitiestakeplace.Despite
pervasiveeffortstomeetandimproveuponregulatoryguidelinesforecosystemservicesatpreviouslymined
sites,thereisalargedegreeofuncertaintyinminelandrestoration.Consistentapplicationofrevegetation,
soilamendmentsandregradingtreatmentscanleadtoverydifferentresults,evenonthesamesite
(Martínez‐RuizandMarrs,2007).Whysuchinconsistency?Manyauthorsattributeittovariabilityinstarting
conditions(theprevailingmineralogicalsubstrate),slope,aspectandmyriadunmeasuredfactors(Martínez‐
RuizandMarrs,2007),withoneemergingfrequently―thesoilmicrobiota(Harris,2003).
Microorganismsarecatalystsforsoilformation.Theyareresponsibleforcreatingcomplex
microenvironmentsthatleadtonutrientuptakeinplants,semi‐homeostaticwaterandchemicalregulations,
andtooverallresiliencetoerosion,contaminationandinvasionbyexoticplantspecies.Newsoilsthatform
onexposedbedrockoftenfollowapredictablesuccessionalsequence.Microbialcommunitiesformon
weatheredinorganicsubstrates,fixatmosphericnitrogenandCO2andcontributethekeyelementsoforganic
life.Multi‐cellularplantsandanimalsarerelativelatecomerstothedevelopingcommunity,arrivingwhen
soilformationprocesseshaveprovidedsufficientorganicresourcestosustainthem(seeFrouzetal.,2008,
foradiscussionofthisprocessonpreviouslyminedsites).Chronologically,thisnaturalapproachcanbe
consideredbottom‐up,withsoilorganismsandprocessesestablishingandpreparingthesubstratebefore
largerplantsandanimalsarrive.Thescienceofrestorationhasnotdevelopedamechanismforrecreating
(muchlessaccelerating)thisbottom‐upprocess.Rather,practitionersoftenattempttorecreatethedesired
ecosystemirrespectiveofthenaturalchronologicalsequencebysuperimposingsoilamendments,andwith
seedingorplantingpluggedvascularplants(Tordoffetal.,2000).Thispracticeisnotundertakenoutof
ignoranceoftherolesoilmicrobialcommunitiesplay,butbecausetoolstoobserve,quantifyandmanipulate
thesecommunitiesarenotwithinthetypicalorganisation’stoolkit.
Untilrecently,techniquesforobservingandquantifyingmicrobiotahavebeenextremelyrestrictive(Ficetola
etal.,2008).Lessthanonepercentofallsoilmicrobialorganismshavebeenculturedinalaboratorysetting
(Hugenholtzetal.,1998;Harris,2009).Asonealternative,microbiologistshavedevelopedtechniquesfor
quantifyingthemass‐actionofmicrobesinsoils,includingtherespirationandproductionratesofmetabolic
products.Genomicstechnologiesofferusanopportunitytoobservethecomplexityofmicrobial
communitiesastheyformonminedsites,andtoapplyecologicaltheorytosoilcommunityformationand
structureinawaythathasuntilveryrecentlybeenimpossible.Inrecentdecades,microbialgenomicshas
beenappliedtominesites,aswillbediscussed,butithasyettobeincorporatedintoacomprehensive
monitoringandtroubleshootingparadigmformineclosureandminesiterestoration.Inthispaper,we
provideacontextforgenomicsintheminingcommunityandhighlightspecificapplicationsofgenomicsand
metagenomicstomineclosure.
2Genomicstechniques:Fromsampletomanagementdecision
2.1Sampling
Microbialgenomicsbeginswithasource,eitheranindividualorganismorsamplematerialcomprisingmany
organisms.Soilcontainsacombinationofliving,deadanddormantorganisms,allofwhichcontributetothe
soil’sgeneticsignature.Representativesamplingofsoilsonminesitesfortheirmicrobialcommunity
structuresisachallenge,asminesitesarelarge,oftenincorporatingentirelandscapeswithvarying
geophysicalproperties.Furthermore,soilcommunitiesarenotoriouslypatchyindistribution(amonghabitat
typesandbothhorizontallyandverticallywithineachsoilstratum)(Foster,1988;RanjardandRichaume,
2001).Therefore,itisnotfeasibletosampleeveryhabitattypeandsoilstratumwithinaminedlandscape.
Rather,samplingshouldtargethabitatsandsoilstratathatmayprovidesignsofimminentdegradationof
waterquality(streamsandassociatedwetlandareaswithinandadjacenttotheminedlandcatchment),
contaminantsequestration(bioreactorsubstrates,ororganic‐richsoilsreceivingrunofffromtheminesite)
orreclamationsuccess(processedparentmaterial,organicamendmentsandunimpactedreferencesites).
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MineClosure2015,Vancouver,Canada3
Thereareafewmajorconcernstoconsiderwhendesigningasamplingprotocolforgenomicanalysis.First,
thesoilchemistryandwatercontentofsampleschangerapidlyuponcollection,possiblyleadingtoshiftsin
theactivityandabundanceofmicrobeswithinthesoil,especiallywhencollectedfromanoxicsubstrates.
Biologicalactivitymustthereforebesuspendedasquicklyaspossiblefollowingcollection,whichgenerally
involvesflashfreezingofsampleswithliquidnitrogen(−195°C)oronblocksofdryice(−79°C)whenliquid
nitrogenisnotavailableoristoodangeroustouse(e.g.onaboat).Ethanol(95%)canbesprayedonblocks
ofdryicetoaccelerateheattransfer.Thisfreezingprocesssuspendsmetabolicactivityinthesoiland
preservesinsitubacterialabundance.Second,replicationshouldbelargeenoughtoaccountforthehigh
levelofvariationinsoilmicrobialcommunitycompositionandstructure,witheachreplicaterepresentinga
homogeneousmixtureofmultiplesamples(oftensoilcores)takeninthefield.Biogeochemicalgradients
acrossphysicalinterfacesandwithinsedimentscanbeverysteep.Therefore,preservationandassessment
oflayersispreferable(seedeGruijteretal.,2006,foracomprehensivediscussionofsamplingdesignsspecific
tonaturalresourcemonitoring).Asmicrobialcommunitiesdependverystronglyonlocalconditions
(water/soilchemistryandbiologicalinteractions),sufficientmetadatashouldberecordedalongwitheach
sampletoenablethisvariationtobedescribedforaparticularcommunity.Asaminimum,thisshouldinclude
pH,temperature,dissolvedoxygen,conductivity,nitrate,nitriteandphosphorus.Finally,becauseoftheir
abilitytobringoxygenandcarbonresourcesintootherwiseanaerobicsoils,plantrootingzonescanplaya
pivotalroleindeterminingmicrobialcommunitycomposition(Marschneretal.,2001;Marschneretal.,
2004),andsamplestakenfromvegetatedsubstratesshouldaccountforthecompositionandcharacteristics
ofco‐occurringplantcommunities.
2.2Extraction
DNAextractioninvolvestwosteps:(1)breakingapartcellwallsandmembranes(celllysis)throughsome
combinationofheating,sonicationand/orchemicaltreatment,and(2)isolation/concentrationofDNAvia
filtration(Picardetal.,1992;Zhouetal.,1996).Althoughconceptuallysimilar,differentlysismethodscan
produceconflictingresults(Martin‐Laurentetal.,2001;Carriggetal.,2007).
Therearethreemajorchallengestoconsistencyintheextractionprocess.First,manymicroorganismsform
coloniesorcrustsonsubstratecomponents(sandgrainsandsmallstones).Thesecoloniescanbedifficultto
breakapart,andfundamentallyprotectmanycellsfromthelysisprocedure.Thiscanleadtodifferencesin
perceivedcommunitycompositionwhencomparingsampleswithdifferentsubstrategrainsizes.Pre‐
washingprocedureshavebeendevelopedtosuspendadheredcommunitiesinsolutionbeforebreakingapart
cells,leadingtomorerepresentativeextractions(Fortinetal.,2004;Heetal.,2005).
Second,thethicknessandmaterialpropertiesofcellwallsandmembranesarenotuniformforall
microorganisms.Developinglysisproceduresthereforeinvolvesidentifyingthemajorgroupsof
microorganismsofinteresttothestudy,andconsideringperformingparallelextractionstoisolatedistinct
groupsforcomparison.Sulphate‐reducingbacteria(SRB)andmethanogenicarchaeaareofparticularinterest
totheminingindustryfortheirprevalenceandactivityinminedsubstrates.Bacterialandarchaealcellwalls
comprisedifferentmaterials(seeKandlerandKönig,2014,forachemicalandfunctionaldescriptionofthese
differences).Asaresult,usingasinglelysisprocedurewillinvariablyunderrepresentoneofthesegroups,
andmultiplelysisproceduresshouldbeevaluatedifacomprehensiveunderstandingofmicrobialcommunity
compositionandprevalenceisdesired.
Finally,highlydegradedorganicmaterialincarbon‐richsoils(humicacids)aredifficulttoseparatefromDNA,
oftenleadingtocontaminationofDNAextractsandpoorsequencereads(Yeatesetal.,1998).Procedures
havebeendevelopedtoaccommodatesamplesrichinorganicacids;theseinvolveremovalofhumicacids
withadditionalfiltrationsteps(TsaiandOlson,1992)orionexchangechromatography(TebbeandVahjen,
1993).
UsinggenomicsinminereclamationL.H.Fraser,H.W.Garris,S.A.Baldwin,J.D.VanHammeandW.C.Gardner
4MineClosure2015,Vancouver,Canada
2.3Amplificationandsequencing
DNAextractedfromthemineenvironmentsampleprovidesinformationaboutthemicrobialcommunityand
metabolicprocessesatthatsite.Onemethodtodescribethemicrobialcommunityusesspecificcomponents
oftheDNA,suchasgenesknowntovaryamongspecies,thatareamplifiedviapolymerasechainreaction
(PCR)(Valentinietal.,2009).Thesereferencegenesfoundintheminesamplearecomparedtocurated
databasesofknownannotatedsequences(BOLD,GenBank,MG‐RAST)(RatnasinghamandHebert,2007;
Meyeretal.,2008;Bensonetal.,2013),therebyidentifyingwhichspeciesarepresentattheminesite.Early
usesofgenomicstechnologyforbacterialcommunitycharacterisationfocusedonthe16SrRNAgene,a
segmentofDNAcriticalfortheproductionofproteinsbyprokaryoticcells,andthatisgenerallyuniqueto
eachspecies(Weisburgetal.,1991).Sequencingof16SrRNAgeneshasbeenusedtoquantifymicrobial
diversitywithsufficientresolutiontodetectshiftsalongmajorecologicalgradients(Schmidtetal.,2014).
However,thisapproachislimitedtodeterminingwhichmicrobialspeciesarepresentandprovideslittle
informationabouttheactualmetabolicprocessestakingplace(Eisen,2007).Stableisotope(with13C)
probinghasbeenusedinrecentyearsincombinationwithenvironmentalDNAsequencingtoisolate
microbialcommunityfractionsinvolvedinspecificmetabolicprocesses(DumontandMurrell,2005;
Verasteguietal.,2014),whichmakestheimportantlinkbetweenbacterialcommunitycompositionand
specificmetabolicfunctions.
Withtheadventofhighthroughputsequencingtechnologies,targetingonlyspecificregionswithinDNAhas
givenwayto“shotgun”andwhole‐genome/metagenomesequencingusingalloftheDNAinthesample
(Tringeetal.,2005).Thetermmetagenomeisusedwhenthesamplecontainsmanyorganisms(andthus
genomes),asisthecaseinsoils.Shotgunsequencinginvolvesbreakingthemetagenomeintomanysmall
fragmentsviaphysicalshearingorenzymaticprocesses(Sharpton,2014).Aftersequencing,thesefragments
canbeusedtoreconstructentiregenomesfortheorganismspresentatthesitebyaligningthesequences
wheretheyoverlap.Themetagenomeincludesbothfunctionalinformation(genemarkerslinkedtospecific
metabolicproducts)andcompositionalinformation(e.g.16Sandotherspecies‐specificreferencesequences)
(Xiaetal.,2011).Thecomputationaltechniquesrequiredtocompile,alignandinterpretthesemillionsof
basesofgeneticcodearrangedintoshortfragmentsistermedbioinformatics(discussedinthenextsection).
AnadditionaluseofenvironmentalDNAfragmentsisfunctionalscreening.Cloningofthesefragmentsinto
livehostssuchasthebacteriumE.coliortheyeastP.pastorisenablesexpressionoftheproteinproducts
andtheirfunctionalscreening.Forexample,growingofE.colicellscontainingenvironmentalDNAon
mediumcontainingcelluloseallowedfordirectidentificationofnovelcellulaseenzymes(Mewisetal.,2013)
fromamineremediationenvironment.
2.4Bioinformatics
Bioinformaticsreferstothecomputationalproceduresusedtoextractmeaningfulinformationfromthevery
largedatasetsproducedinmetagenomicstudies.Bioinformaticspipelinesrequireconsiderable
computationalpoweranduniquealgorithmstocarryoutthestepsfromqualitycontrolofthesequencesto
assemblingfunctionalcomponents(i.e.sequencescodingforproteinsusedincellularfunctionscalledopen
readingframesorORFs)thatyieldinformationaboutthemetabolicpotentialoftheorganismspresentatthe
site.Bioinformaticsformetagenomicsarecomplex,ascompositionalaswellasfunctionalreconstructionis
required.Toidentifycompositionalstructure,themarkergenes(i.e.16SrRNA)arebinned,basedontheir
similarity,intooperationaltaxonomicunits(OTUs)thatarelikelytobederivedfromthesamespecies.
Assembledfunctionalcomponents(theORFs)andOTUsareinterrogatedagainstproteinandgenedatabases
inbioinformaticspipelinesusingtheblasttools(Altschuletal.,1990)inordertoassignputativefunctions
andidentitiestothemicrobialcommunityfoundintheminesitesample(seeSharpton,2014,fora
comprehensivediscussionofprocessingandinterpretationofshotgun‐derivedsequences).
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MineClosure2015,Vancouver,Canada5
3Applications
3.1DNAbarcoding
Giventhemuchlarger,morecomplexgenomesfoundinplantandanimalspecies,themoleculartoolsfor
identifyingthemhavedevelopedmoreslowlythanthoseformicroorganisms.Whereasthe16SrRNAgeneis
foundinallbacteriaandarchaea,thecorresponding18SrRNAgeneinhighereukarya,andevenfungi,isnot
asreliableasaspeciesidentifier.Assuch,mucheffortisbeingputintofindingsignaturegenes,called“DNA
barcodes,”fordifferentgroupsofplants,invertebratesandvertebrates(Hebertetal.,2003).Eachspecies
collectedcanberapidlyandcost‐effectivelyidentified,andwiththepropersamplingprotocols,quantifiedin
termsofrelativeabundanceanddiversitybysite.
NewGold’sNewAftonMinenearKamloops,BritishColumbia,Canada,beganoperationin2012.Although
themineisinitsearlydaysofoperation,ithastakenaproactiveapproachtofuturemineclosureplansby
implementingapartnershipwiththeBiodiversityInstituteofOntariotoimplementDNAbarcodingfor
environmentalimpactassessments.Thepilotprograminvolvedfoursites:twograsslandsites(disturbedand
undisturbed)andtwowetlandsites(disturbedandundisturbed).Invertebratesamplesfromthesefoursites
werecollectedinthesummerof2013,andDNAbarcodeanalyseswerecompletedinAugust2014.Between
294and5,560individualinvertebrateswerecapturedinMalaisetrapseachweek,and3,956specieswere
identified(D.WilsonandS.Davidson,personalcommunication8May,2015).Differenceswereobserved
betweenhabitattypessuchthatwetlandscontainedmorespeciesthangrasslands,andthenaturalgrassland
hadmorespeciesthanthedisturbedgrassland.Theintentionistocontinuemonitoringonafour‐tofive‐
yeartimescale.Suchbaselinedataprovideinvaluableinformationforfuturemineclosureandsite
reclamation.
3.2Meta‐omics
Thankstotheconservednatureof,andrelativelylonghistoryofcollectingsequencedatafor,the16SrRNA
geneinbacteriaandarchaeaand,toalesserextent,the18SrRNAgeneinfungi,researchersinterestedin
microbialcommunities(e.g.environment,health,industry)havereachedastagewhereusingthese
referencegenestodescribemicrobialcommunitycompositionanddiversityisnowroutine(Schmidtetal.,
2014).Ashortnumberofyearsago,publicationswouldbebasedsolelyon16SrRNAgenesurveysof
microbialcommunities,whereastodaythesesurveysareconsideredoneofmanystandardanalyticaltools
forscanningmicrobiallandscapes.While16Sand18SrRNAgenesurveyswillcontinuetobepowerfultools,
microbiologistshaverealisedthatthesereferencegenesdonotuniversallyreflectthemetabolicpotential
andbiochemicalactivitiesofindividualmicroorganisms,letalonecomplexmicrobialcommunities.This
realisationcontinuestomotivatethedevelopmentof“meta”toolstoqualifyandquantifyalloftheDNA,
mRNAandproteinsinmicrobialcommunities(metagenomics,metatranscriptomicsandmetaproteomics)
andtorelatethesedatatobiochemicalfluxes(metabolomics)and,ultimately,ecosystemfunctions(Krause
etal.,2014).
Atthepresenttime,therearegoodgenomicdatabasesforpurebacterialculturesgrownunderlaboratory
conditions.Generatinggooddraftsofmicrobialgenomescannowbedoneindaysratherthanyears,by
individualsratherthanteams,forhundredsratherthanmillionsofdollars.Thisisamajorshiftfromlessthan
adecadeago(Kyrpidesetal.,2014).Highthroughputtranscriptomicandproteomictoolshavecomeonline
andarebeingincreasinglyusedforpureculturablemicroorganismsaswell.Thetoolsareavailableto
characterisenaturalmicrobialcommunities,butanalysingdatafromevenafewsamplesinameaningfulway
stillrequirestheuseofsupercomputersorpowerfulcomputerclusters,andisbasedonimperfectdatabases
establishedintheearlydaysofgenomics(Howeetal.,2014).A“meta‐omics”studyisnotforthefaintof
heart,butthefieldisshiftingrapidly,andthesetypesofstudiesarebecomingmorecommondespitethe
needforlargemonetaryandpersonnelinvestments.Majorbreakthroughsarecurrentlybeingmadeto
advanceourunderstandingofthedominantrolesmicroorganismsplayinthemetabolismandlifestylesofall
macroorganisms.Further,biotechnologicalapplicationsarebeingrealisedinanarrayoffields,including
UsinggenomicsinminereclamationL.H.Fraser,H.W.Garris,S.A.Baldwin,J.D.VanHammeandW.C.Gardner
6MineClosure2015,Vancouver,Canada
forestry,agriculture,animalhusbandry,humanhealth,andfood,beverageandfuelproduction(Ekkersetal.,
2012).
Giventherichliteratureonmetal‐microbeinteractions(Gadd,2010),thereistremendousscopeforapplying
meta‐omicstominereclamation,particularlygiventhesmallbutsolidfoundationofgenomicworkbeing
doneinphytoremediation(Baietal.,2014),metal‐plantinteractions(HanikenneandNouet,2011;Bhargava
etal.,2012)andsoilecology(Howeetal.,2014)onwhichtobuild.Lookingtothefuture,oncecurrentmeta‐
omicstoolshavesufficientlymaturedformicrobialcommunities,thegene,transcript,proteinandmetabolic
signaturesfromplantsandothermacroorganismsmustbeintegratedinholisticmodelsinordertobetter
appreciatetheholobionts(macroorganismsandtheirassociatedmicrobialandviralcommunities)essential
tohealthyecosystems.
3.3Stateofthescience
3.3.1 Example 1: Bioreactors
Seepagefromminetailingsstoragefacilities,wasterockpiles,openpitsandundergroundworkings,aswell
asexcessprocesswater,containsmetalssuchasselenium,copper,molybdenum,zincandarsenic,often
alongwithsulphateandnitrate(McDonaldandStrosher,1998;WangandMulligan,2006).High‐density
sludgetreatmentisusedatmanyminesitestotreatthismine‐influencedwater,butthischemicalprocess
consumeslargequantitiesofreagentsandproduceshighvolumesoftoxicsludgerequiringlong‐termsafe
storage(ZinckandGriffith,2013).Bioreactorsofferasustainable,cost‐effectivealternativetoreagent‐based
watertreatmenttechnologies.
Biologicalprocessesusenaturalmicroorganismstotreatmine‐influencedwater.Somebioreactorsreduce
sulphatetoproducesulphide,whichchemicallybindswithmetalions,causingthemtoprecipitateoutof
solutionasstablemetalsulphides(Barnesetal.,1994).Additionally,bioreactorshavebeendesignedto
selectivelyremovespecificvaluablemetals,suchascopperandzinc,thatcanberecycledtothemetal
extractionfacility(ZinckandGriffith,2013).Bioreactorsareusedtoremovenitrate,whichishighinsome
mine‐influencedwaterowingtotheuseofexplosivesonminesites(Korenetal.,2000).Seleniumandarsenic
aremetalsthatoccurasanions,andtherearenaturalmicroorganismsthattransformthesecompoundsin
ordertogainenergyforgrowth.Biologicalreactorsusingtheseorganismssuccessfullyremoveseleniumand
arsenicfrommine‐influencedwater(Moritaetal.,2007).
Giventhebenefitsineconomicsandeffectivenesspromisedbybiologicaltreatment,itissurprisingthatuse
ofbioreactorsisnotwidespreadonminesites.Afewreasonsforthishavebeenrevealedthroughthe
applicationofmetagenomics.Bioreactorscontainconsortiaofmicroorganisms,ratherthanonesingletype
(Baldwinetal.,2012),andtheperformanceofthesebioreactorsdependsonthetypesofmicroorganisms
usedtoinoculatethem(Prudenetal.,2007).Microbialcommunitiesaredynamic,andtheirmembers
fluctuateinabundanceandactivityinresponsetochangesintheinfluentwateroroperatingconditions(Dar
etal.,2008).Shiftsinmicrobialcommunitycompositioncanleadtofailuretomeetwaterquality
specifications,ultimatelyputtingthereceivingenvironmentatrisk(MirjafariandBaldwin,2011).To
overcomethislimitationofbiologicaltreatment,itisnecessarytomonitormicrobialcommunitycomposition
inbioreactorsandcorrelatethistooperationalsettingsandperformancemetrics.Themicrobialcommunity
inmine‐basedbioreactorscanbemonitoredusingthemetagenomicstechniques,suchasthosetargetingthe
16SrRNA,describedinSection2.3(SchmidtovaandBaldwin,2011;Baldwinetal.,2015).
High‐throughputsequencingcangenerateenoughinformationtocharacterisetheentiremicrobial
communityincludingveryraremembers.Oftentheimportantfunctionalgroupsformetalremovalin
bioreactorsarerare,eventhoughtheiractionachievessuccessfultreatment(Rezadehbashietal.,2012).
Someothermicrobespresentfacilitatetheactivityofthesedesiredgroups,orsomemightcompetefor
nutrientsandhindertheiractivity.Nutrientconsumptionisoneofthemajorcostsinrunningabioreactor,
andwhenundesiredmicrobescompetesuccessfullyformostofthenutrients,thedesiredorganismsdecline
innumberandbioreactorperformancefails(Silvaetal.,2012).
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MineClosure2015,Vancouver,Canada7
Muchoftheworkdonetodateonmicrobialcommunitiesinbioreactors,especiallythoserelatedtomine
remediation,hasfocusedonmicrobialcommunitycompositionbasedonsurveysofthe16SrRNAgene.
Thesesurveyshaverevealedthatmicrobialgroupsassociatedwithmetal‐richenvironmentsareunknown
anduncharacterised,suchthatnewtaxonomicgroupshavebeeninventedtoclassifythem(Khoshnoodiet
al.,2013).Thus,metagenomicstudiesareneededtodiscoverthepotentialfunctionsofthesenovel
organisms(Ellisetal.,2012).
SequencingofDNAprovidesinformationonmetabolicpotentialonly,anddoesnotrevealwhichofthegenes
arebeingactivelyexpressed.Activemetabolicprocessescanbedetectedbysequencingthetranscribed
genesusingatechniquereferredtoastranscriptomics(Luoetal.,2014).Althoughveryrecentlydeveloped
formicrobialcommunitiesinbioreactors(Luoetal.,2014),microbialtranscriptomicsispossiblebutrequires
carefulsamplingtopreservetheactivestateofthemicrobes.
Giventheaffordabilityofhigh‐throughputsequencing,useofmetagenomicsandtranscriptomicsfor
bioreactormonitoringisboundtoincrease.Sincethesedatasetsarenew,correlationofmicrobial
communitycomposition,metagenomicsandtranscriptomicswithbioreactoroperationandperformanceis
stillbeinginvestigated.Asthebioinformaticsimproves,thesemetagenomicstoolsshowpromiseforfuture
processcontrolofbioreactors.
3.3.2 Example 2: Passive treatment systems
Thebenefitofusingbioreactorsformineremediationisthattheycanbecontrolledusingtanks,pumps,
valves,instrumentationanddefinednutrientstoachievejusttherightconditionsandrapidkineticsfor
treatinglargeflowrates(ZinckandGriffith,2013).However,theircapitalandoperatingcostsaddtothe
expenseofmineoperationandclosure.Inaddition,althoughtheyarehighlyautomated,operatorsare
needed.
Thevastarrayofnaturalprocessesforbiogeochemicalcyclingofmetalsandnutrientscanbeharnessedin
so‐calledpassiveorsemi‐passivetreatmentsystems(Ziemkiewiczetal.,2003).Thesetypicallytaketheform
ofconstructedwetlands,eithersub‐surfaceflowanaerobic,surfaceflowaerobicor,mostcommonly,
combinationsthereof.Insteadofdefinednutrients,mixturesofwasteorganicmaterialssuchaswooddebris,
hay,compost,pulpandpapermillbiosolidsareused.Thesecomplexorganicmaterialsaredecomposedinto
thesmallercarboncompoundsneededforthesulphate‐andmetal‐reducingbacteria.
Ifsuccessful,passivetreatmentcanremovemetalsatseepsdistributedacrosstheminesiteforafractionof
thecostofactivebioreactortreatment(ZinckandGriffith,2013,p.14).Themetalresidualsarecapturedand
securedinsidetheorganicmatrix,mostoftenassparinglysolublemetalsulphides(Khoshnoodietal.,2013).
Theecosystemofapassiveremediationsystemisascomplicatedasthatofsoils(Baldwinetal.,2015).Like
bioreactors,theyareconsortiaofinteractingspeciesthatshiftincompositionwithgeochemicalgradients,
seasonsandtheageofthesystem(vanderLelieetal.,2012).Theirperformancemaydeclineastheorganic
materialdecomposes,evolvingtowardsmicrobialcommunitieswithcompletelydifferentmetabolic
potentialthanatthestart(Mirjafari,2014).Preliminarystudiesofthemicrobialcommunitiesinthese
systemsrevealthatthemetabolicpotentialformetalremovalinthemismuchwiderthanpreviouslythought
(Baldwinetal.,2015).Theycontainspeciesthattoleratehighmetalconcentrations,manynovelunclassified
candidatedivisiongroupsfoundinothermetal‐contaminatedenvironmentsandspeciescapableofusing
usuallyrecalcitrantaromaticcompoundsforgrowth.
SuccessfulmetalremovaloccurseveninplaceswhereSRBareextremelyrare,meaningeitherthatmany
othergroupsoforganismswedonotknowaboutarecapableofsulphatereductionand/ormetal
precipitation,orthatonlyafewsulphatereducersareneededforsuccessfultreatment(Khoshnoodietal.,
2013;Baldwinetal.,2015).Chartingofmicrobialcommunitiesinpassiveremediationbioreactorshas
revealedthattheyarenotstatic,butfluctuatecyclically(Baldwin,unpublisheddata).Usingmetagenomics
andmetatranscriptomics,wecanlearnmoreaboutthedynamicsoftheseecosystemsastheyrespondto
changingconditionsandusethisknowledgetodesignbettersystemsordiagnoseperformanceissues.
UsinggenomicsinminereclamationL.H.Fraser,H.W.Garris,S.A.Baldwin,J.D.VanHammeandW.C.Gardner
8MineClosure2015,Vancouver,Canada
3.3.3 Example 3: Novel gene discovery
Metal‐richecosystemsareconsideredextremeenvironments.Theyharbourhighlyspecialised
microorganismsthathaveevolveduniquemetabolismstotransform,sequesterordetoxifymetalsinorder
tosurvive.Examplesincludesulphatereducers’overproductionofextracellularpolymericmaterialtobind
upcopperions,therebycreatingnucleationsitesforprecipitation(JalaliandBaldwin,2000),intracellular
mineralisationoftelluriumtosequesterthishighlytoxicmetal(AmoozegarandKhoshnoodi,2012),and
methylationandvolatilisationofarsenicbyMethanocorpusculumlabreanum,suggestingthatitmaybea
significantcontributortometalcyclinginanaerobicenvironments(Khoshnoodietal.,2012).
Enzymesinvolvedinmetalcycling,orbiochemicalcompoundswiththeabilitytosequesterspecificmetal
ions,canbeusedinfuturebiotechnologiestoimprovebioremediation,andevendevelopmethodsforinsitu
mining.Thefieldoffunctionalmetagenomics,firstmentionedinSection2.3,isbeingusedtoscreenlarge
DNAfragmentsfromminesites(Mewisetal.,2011).TheselargefragmentsofenvironmentalDNAmay
containnovelgenesformetalcycling,and,usingselectivemediainthelaboratory,wecanscreentheE.coli
clonesformetalresistance.Itmaybepossibleinthefuturetoconstructbiochemicalpathwaysformetal
removalusingsimpleandeasy‐to‐groworganismsandsyntheticbiology.
3.4Futureofthescience
3.4.1 Site-specific pre-assessments for closure targets
Theminingindustryhasrecognisedforsometimethatplanningformineclosurebeginsevenbefore
overburdenisremovedfromthesite(Thirgood,1986inPolster1989).Untilrecently,thishasnotincludeda
significantconsiderationofthepre‐impactcommunityofplants,animalsandmicroorganismsresidinginthe
unalteredsubstrate,butseeMorrisonetal.(2005)andJasper(2007).Inthefuture,suchassessmentsshould
includeevaluationofbothunimpactedoverburdensoilcommunitiesandstockpilesofsuchmaterialfor
eventualrecoveringofthesite.Microbialgenomicsmayplayakeyroleinexpeditingminelandrestoration
byprovidinginformationonsoilcommunitydynamicsinoverburdenstockpiles,allowingmanagersto
maintainthesecommunitiesinawaythatexpeditesrecoveryoncethesesubstratesareusedtorecoverthe
minedsite.
Microbialgenomicsmayalsoserveasanindicatorforsuccessinthesesystems,providingadditionalevidence
ofsoilcommunityformationandecosystemtrajectory.Tobeabletosetobjectivesforeffectivemine
reclamationandevaluatewhatissuccessful,themeaningof“equivalentlandcapacity”needstobedefined
foreveryminesite.
Barcodingandmetagenomicscanbeincorporatedintomethodsforevaluatingecosystemservices.Microbial
communityanalysisprovidesvaluableinformationaboutnutrient(carbon,nitrogenandsulphur)cycling,
greenhousegasemissionsandmetaltransformationsthatcanbefedintodeterminingpre‐miningland
capacityassessment.Thiswillallowtargetstobespecifiedforpost‐minereclamation,andthesesametools
canbeusedtoevaluatewhetherremediationstrategiesareworking.
3.4.2 Whole-ecosystem modelling
Microbialgenomicsfillsacriticalgapineffortstosimulatetheformationofmetabolicnetworksin
ecosystems.Thepresenceorabsenceofkeymicrobialcommunitiesmaymeanthedifferencebetweena
successfullyremediatedsiteandpersistentdegradationofwaterquality(e.g.acidificationandmetal
leaching).Effortsareunderwaytodevelopcomprehensivepredictivenetworksforminesites,inwhich
environmentalgenomicsaretiedtoenvironmentalmonitoringdatatogenerateacomprehensive
understandingofecosystemfunction.Probabilisticmodellingframeworksmayverywellprovideearly
warningsignsofacidgenerationinminedsubstrates,andgenomicsdatamayyieldthenecessaryevidence
todeterminewhatremediationoptionswillbemostlikelytosucceedinboththeshortandlongterm.
KeynotesandPlenaries
MineClosure2015,Vancouver,Canada9
3.4.4 Defining benchmarks
Definingbenchmarksmayverywellbethekeycomponentnecessarytoleveragegenomicstoolsformine‐
sitemanagement.Bioinformaticsdataprocessingworkflows(pipelines)exist(sometimesincorporated
directlyintosequencinghardware)thatprovideforrapidprocessingandinterpretationofsequencingruns.
Thegreatquestionsfortheminingindustrycanbeputquitesimply:(1)Whatdowesequence?,and(2)How
doweusetheresultingdatatoimprovemanagement,reclamationandcontainment?
Section2.1providesguidelinesforsamplingofthesesites,buttheindustryrequiresawealthofcontext‐
dependentvalidationoftheseapproachestobecomewidespread.Therefore,researchanddevelopment
resources(bothacademicandindustrial)shouldbeleveragedinsuchawaythatsamplingprocedurescanbe
standardisedtothesortsofquestionsofinterestatminesites(e.g.Howdosoilmicrobialcommunitiesform
onminedsubstrate?Whatsoilconditionspromoterecoveryofnativespecies?).
Ultimately,withstandardsamplingprocedures,bioinformaticspipelinescanbetailoredtoindustry‐specific
questions.Forexample,asamplingprotocolmightbedevelopedtoevaluatediffuseleachateexposurein
ripariansubstrates,withthequestion:Doesexposuretoleachateaffectmicrobialcommunitycomposition
anddynamicsinawaythatcouldlimitcontainmentinthefuture?Fieldsamplingandsequencingfollowing
establishedprotocolswouldbeprocessedthroughatailoredbioinformaticspipelinethatyieldsthefollowing
outputs:
1. Communitycompositionmatricesandplannedcomparisons(diversity,similarity,etc.)
2. Compositionaldifferencesandknownassociations(i.e.variationsingroupsoforganismsknown
tobeinvolvedincertaingeochemicalpathways)
3. Managementrecommendationsandreferencestosimilarscenarios/responses.
4Conclusions
Wehaveoutlinedarangeofgenomicsapplicationstomineclosure,fromcharacterisingnaturalsubstrates
beforeoverburdenremoval,towatertreatment,tobioremediationandmonitoringofhealthyreclaimed
ecosystems.Inperformingthisreview,weidentifiedtwokeyconstraintsonthewidespreadapplicationof
genomicsformineclosure.First,industry‐widestandardoperatingprotocolsneedtobedevelopedformine
closure,includingsamplingproceduresdesignedforrepresentativenessandcomparability(spatialextent,
replication,temporalfrequency).Second,sequencinganddatainterpretationpipelinesmustbeestablished
inparallelwiththedevelopmentofthesestandards,allowingminemanagerstomoreeasilydiscoverwhat
worksinagivensystemandtoestablishbenchmarksforreclamationsuccess.Miningisakeyglobalindustry
fordevelopmentandforqualityoflife.Theintegrationofgenomicstechnologiesintomineclosureplanning
andimplementationmaydrasticallyimprovethestabilityandreliabilityofecosystemreclamation.
Acknowledgements
WewouldliketothankJonTaylor(UniversityofBritishColumbia)forhelpfultroubleshootingandadvisement
onsamplingdesignformine‐siteapplications.WewouldliketothankGenomeBC,GenomeCanada,NSERC
EngageandMitacsAccelerateforfundingtosupportpreliminaryR&Donmetagenomicstechnologies.We
wouldalsoliketothankDennisWilsonandScottDavidsonofNewGoldforprovidingdetailsabouttheir
project.Finally,wewouldliketothankMountPolleyMineCorporationandparticularlyKatieMcMahon,
ColleenHughes,LukeMogerandArtFryefortheirpartnershipinprojectsaimedataddressingmanyofthe
questionsaddressedinthisreview.
UsinggenomicsinminereclamationL.H.Fraser,H.W.Garris,S.A.Baldwin,J.D.VanHammeandW.C.Gardner
10MineClosure2015,Vancouver,Canada
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