Soil depth and crop determinants of bacterial communities under ten biofuel cropping systems

19 Pages·2017·4.91 MB·English

by  Bangzhou Zhang

SoilBiology&Biochemistry112(2017)140e152
ContentslistsavailableatScienceDirect
Soil Biology & Biochemistry
journal homepage: www.elsevier.com/locate/soilbio
Soil depth and crop determinants of bacterial communities under ten
biofuel cropping systems
Bangzhou Zhang a,b, C. Ryan Penton b,c, Chao Xue b,d, John F. Quensen b, Sarah S. Roleye,
Jiarong Guo b, Aaron Garoutte b, Tianling Zheng a,**, James M. Tiedje b,*
aStateKeyLabofMarineEnvironmentalScienceandKeyLaboftheMOEforCoastalandWetlandEcosystems,SchoolofLifeSciences,XiamenUniversity,
Xiamen,China
bCenterforMicrobialEcology,MichiganStateUniversity,EastLansing,MI,USA
cCollegeofLettersandSciencesandJulieAnnWrigleyGlobalInstituteofSustainability,ArizonaStateUniversity,Mesa,AZ,USA
dJiangsuCollaborativeInnovationCenterforSolidOrganicWasteUtilizationandNationalEngineeringResearchCenterforOrganic-BasedFertilizers,
DepartmentofPlantNutrition,NanjingAgriculturalUniversity,Nanjing,China
eGreatLakesBioenergyResearchCenterandW.K.KelloggBiologicalStation,MichiganStateUniversity,HickoryCorners,MI,USA
a r t i c l e i n f o a b s t r a c t
Articlehistory: Biofuel-croppingsystems,projectedforlargelandareas,canpotentiallychangetheirsoilmicrobiome
Received23October2016 and the ecosystem services they catalyze. We determined the bacterial community composition and
Receivedinrevisedform relevantsoilpropertiesforsamplescollectedafter6cropyearsat0e10cm,10e25cm,25e50cm,and50
30March2017 e100 cm under corn, switchgrass, Miscanthus, and restored prairie, as well as 0e10 cm under six
Accepted17April2017
additionalcandidatebiofuelcropsinreplicateside-bysideplots.Deepsequencingofthe16SrRNA-V4
Availableonline16May2017
regionestablishedthatsoilbacterialcommunitiesweresignificantlydifferentiatedbydepthasdeter-
minedbyproportionalOTUabundanceandcomposition,UniFracdistance,andtaxonomicandindicator
Keywords:
analyses.Thecroppingsystemsignificantlyimpactedbacterialcommunitycompositionwithinthetop
Bacterialcommunity
Soildepth three layers, with corn and switchgrass communities the most different within the 0e25 cm and 25
Biofuelcrops e50cmdepths,respectively.Theeffectsofcroptypeanddepthco-mingled,likelyattributedtodiffer-
Soilproperties encesinrootingdepthandbiomassamongcrops.Individualphylademonstratedvaryingpatternswith
depth, with significant proportional decreases of Proteobacteria, Actinobacteria, Planctomycetes, and
Bacteroidetes but proportional increases of Firmicutes from shallow to deep soils. The Acidobacteria,
Verrucomicrobia, and Chloroflexi peaked in abundance in the middle layers, whereas Thaumarchaeota
decreasedinabundance.Importantly,someclasseswithin theAcidobacteria,Verrucomicrobia,andFir-
micutes followed contrasting patterns with depth suggesting that they have different ecological spe-
cializations.Poplar,followedbysoilswithperennialcropscontainedthemostCinthesurfacesoils,with
dataindicatingthatthesedifferenceswillbecomemorepronouncedwithtime.
©2017ElsevierLtd.Allrightsreserved.
1. Introduction abundant biological component (Daniel, 2005; Gans et al., 2005;
Rodriguez and Konstantinidis, 2014). Soil bacteria play a critical
Due to spatially and temporally heterogeneous chemical and role in biogeochemical cycling and are keystones to overall
structuralproperties,soilisthemostcomplexanddiversemicro- ecosystemfunction.Itiswelldocumentedthatsoilbacterialcom-
bial environment on earth, with microorganisms as its most munity composition is influenced by soil properties, geographic
distance, plant species, land use/management, and environment
type(Daniel,2005;Acosta-Martinezetal.,2008;Ushioetal.,2010;
Caporaso et al., 2011; Rodrigues et al., 2013). However, most soil
* Corresponding author. 540 Plant and Soil Sciences Building, Michigan State microbialecologystudieshavefocusedsolelyonthesurfacehori-
University,EastLansing,MI48824,USA.
zons and were previously limited by low-resolution genetic
** Correspondingauthor.C-318,SchoolofLifeSciences,XiamenUniversity,Xia-
profiling methodologies (Muyzer et al.,1993; Fierer and Jackson,
men361102,China.
E-mail addresses: [email protected] (T. Zheng), [email protected] 2006; Hartmann and Widmer, 2006; Wakelin et al., 2008). As
(J.M.Tiedje).
http://dx.doi.org/10.1016/j.soilbio.2017.04.019
0038-0717/©2017ElsevierLtd.Allrightsreserved.
B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152 141
such, there is currentlylittle knowledge concerning soil bacterial and species are given in Table S1. These cropping systems were
communitycompositionanddiversityindeepersoillayers,wherea selectedtohavearangeofplantdiversitiesandofexternal/man-
significant proportion of microbial biomass resides (Fierer et al., agementinputs.
2003). Three 2.5-cm diameter intact soil cores weretaken fromeach
Biofuelsareasustainablealternativetofossilfuelsandhavethe plotwithaGeoprobe540MT(GeoprobeSystems,Salinas,KS)and
potential to address emerging energy demands while providing transportedtoa4(cid:3)Ccoolerwithin3hofcollectionandstoredthere
otherecosystemservices,suchascarbonsequestration,enhanced until processing, which usually occurred within one week of
biodiversity, and reduced greenhouse gas emissions (Lemus and collection. Upon processing, soil cores were sectioned into
Lal, 2005; Hill et al., 2006; Robertson et al., 2008; Gelfand et al., 0e10cm,10e25cm,25e50cm,and50e100cmslicesfromG1,G5,
2013; Werling et al., 2014; Oates et al., 2015). Biofuel crops are G6 and G10. Soils of the other systems were collected only at
projectedtocoverlargeareasoflesser-studiedlandscapesunsuited 0e10cm.Eachcoresectionwassieved(4mm)toremoverootsand
for food crop production (Gelfand et al., 2013), with ensuing stonesandthenthethreesamplesfromthesameplotanddepth
changes in the soil microbiome. Meanwhile, soil microbes can were combined into a single composite sample. Each composite
promote biofuel feedstock yields directly or indirectly by fixing samplewasdivided,withportionsfrozenforlaterDNAextraction,
atmosphericnitrogen,increasingphosphorusacquisition,recycling air-dried for nutrient analysis, and oven-dried at 60 (cid:3)C for total
nutrients, improving soil aggregation, and suppressing plant dis- carbon(C)andnitrogen(N)analysis.Intotal,110compositesam-
ease(Swiftetal., 2004;TiedjeandDonohue,2008). Near-surface ples((4treatments(cid:1)4depthsþ6treatments(cid:1)1depth)(cid:1)5plots)
and root zone soil microbial community composition is influ- werecollected.
enced by plant type due to the annual/perennial nature of the
plants, root depth, differing root exudates, plant residue decom- 2.2. Soilproperties
posability, and active recruitment of specific microbial taxa. In
contrast, sub-surface soil microbial communities are likely more TodeterminethetotalCandNcontent,sub-samplesfromeach
relatedtolong-termCsequestrationbecausesubsoilorganicmat- depthofeachcropthathadbeenoven-driedwerepulverizedand
terischaracterizedbyhighmeanresidencetimesandenrichedin combusted in a Costech Elemental Combustion System 4010
microbially-derived carbon compounds (Rumpel and Kogel- (Costech Analytical Technologies, Valencia CA). To determine soil
Knabner, 2011; Liang et al., 2012a). Thus characterizing the im- pH,potassium (K),phosphorus(P),calcium(Ca),andmagnesium
pactsofbiofuelcroppingsystemsonbothsurfaceandsub-surface (Mg) concentrations, sub-samples that had been air-dried were
microbial communities is important in understanding long-term analyzedatMichiganStateUniversitySoilandPlantNutrientLab-
systemsustainabilityandenvironmentalimpacts. oratory using standard methods (http://extension.missouri.edu/
Our objectives were to: i) determine shifts in the microbial explorepdf/specialb/sb1001.pdf).
community structure and diversity due to crop and depth, ii)
determine taxonomic patterns, especially with depth since that 2.3. DNAextraction,PCRamplification,andMiSeqsequencing
presumably reflects the physiologies of the favored taxa, iii)
determineindicatorspeciesforcropanddepthandthedriversthat Soil samples were thawed and total DNA was extracted from
correlatewiththem,andiv)wherepossible,inferpotentialfunc- 0.3 gportionsofeachsoil sampleusing theMoBioPowerSoil Kit
tionoftheselectedtaxa.Todothis,wedeterminedsoilmicrobial (MoBio, Carlsbad, CA), according to the manufacturer's protocol.
community composition after 6 crop years by Illumina MiSeq TheresultingDNAyieldandqualitywerecheckedwithanND1000
sequencingof16S-V4rRNAgenesatfoursoildepthsthatcovered device(NanoDrop,Wilmington,DE),followedbyre-extractionand
the rooting zone and beyond of four primary candidate biofuel pooling of some samples with lower yields, which occurred for
crops:corn,switchgrass,Miscanthus,andrestoredprairieaswellas some50e100cmsamples.
thesurfacesoilsfromthreeothercorn-basedcroppingsystemsand Bacterial 16S rRNA PCR amplification using a dual-index
threeotherperennialbiofuelcrops. sequencing strategy (Kozich et al., 2013) was conducted to
generate the amplicon library for MiSeq sequencing. Briefly,
2. Methods ampliconsweregeneratedinthereactionsystemconsistingof17ml
of AccuPrime Pfx SuperMix (Invitrogen, CA, USA), 1 ml of DNA
2.1. Samplecollection (around20ng/ml),and1mlofeachbarcodedprimer(10mM).The
fusionprimersetwithIlluminaadapterandbarcodestargetedthe
Samples were collected post-harvest in November 2013 from hypervariable V4 region with specific forward primer 50-
ten biofuel cropping systems (G1 - G10) of the Great Lakes Bio- GTGCCAGCMGCCGCGGTAA and reverse primer 50-GGAC-
energyResearchCenter(GLBRC)BiofuelsCroppingSystemExper- TACHVGGGTWTCTAAT (Caporaso et al., 2011). The cycling condi-
iment (BCSE) at Kellogg Biological Station in southwest MI, USA. tionswere95(cid:3)Cfor2min,30cyclesof95(cid:3)Cfor20s,55(cid:3)Cfor15s,
Firstestablishedin2008,theBCSEexperimentaldesignutilizesa 72(cid:3)Cfor1min,and72(cid:3)Cfor10min.PCRproductswerepurified
randomized complete block design with 5 replicate blocks and normalized using the SequalPrep Normalization Plate Kit
(30(cid:1)40m).Thesitehadthesameorverysimilarcroppinghistory (Invitrogen,CA,USA),followedbypoolingof5mlofeachsampleto
prior to establishing the current plot design in 2008. The soil is produce a sample library. Sequencing was performed by the
predominantly Kalamazoo loam (Fine-Loamy, Mixed, Semiactive, ResearchTechnologySupportFacility,MSU,forMiSeqpaired-ends
Mesic Type Hapludalf), a sandy loam with 47e56% sand. These sequencing with the 250 bp kit (Standard v2 flow cell with 500
cropping systems are continuous corn (G1), continuous cycles).RawsequencesweredepositedintheNCBISequenceRead
cornþcovercrop(G2),soybeaninasoybean-cornrotationþcover ArchiveunderaccessionnumberPRJNA296796.
crop (G3), corn in a corn-soybean rotation þ cover crop (G4),
switchgrass (Panicum virgatum, G5), Miscanthus (Miscanthus x 2.4. Bioinformaticanalyses
giganteus,G6),nativegrassmix(G7),hybridpoplar(Populusnigrax
Populus maximowiczii, G8), early successional (G9), and restored Rawpaired-endreadswereassembledusingtheRDPAssembler
prairie(G10).Previously,G2,G3,andG4wereinacorn-soybean- (Cole et al., 2014) with a read Q score cutoff of 28. Primers were
canola rotation from 2008 to 2011. Details on cropping histories trimmedandtheresultingreads(averaging253bp)werechimera
142 B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152
checkedusingUCHIME(Edgaretal.,2011)indenovomode.OTU (ANOVA,p<0.001),whileCaandMgfirstincreasedwithdepthand
clustering was performed by UPARSE Following the pipeline, all thendecreased(highestat25e50cm,ANOVA,p <0.001).More-
chimera-freereads weredemultiplexed intoone file, clusteredat over,continuouscorn(G1)generallyhadsignificantlylowerC,N,
97% similarity, representative sequences generated, singletons pH,Ca,andMgthantheotherbiofuelcropsystems(especiallythe
removed, and a final OTU table was created. Representative se- poplar, G8) at 0e10 cm depth (Table 1), while switchgrass (G5),
quences of OTUs were submitted for taxonomic classification by Miscanthus(G6),nativegrassmix(G7),andrestoredprairie(G10)
RDP Classifier at a confidence of 50% (Wang et al., 2007). OTUs containedsignificantlylowerKthancorn-relatedsoils(especially
classified as chloroplasts or unclassified at the domain level as thecontinuouscorn,G1).Therewerenosignificantdifferencesin
Bacteria or Archaea were removed (For simplicity, “bacterial” is soil characteristics among the continuous corn, switchgrass, Mis-
used throughout since Archaea accounted for less than 3% of the canthusandtherestoredprairieinthedeeperlayers.
sequences). This did leave OTUs unclassified to a bacterial or
archaealphylum.Allsampleswerere-sampledto25,000sequences 3.2. Diversitymeasures
per sample for downstream analyses. All bioinformatic analyses
wereperformedusingtheHighPerformanceComputationalCenter Atotalof5,006,088highqualityreadswereobtainedafteras-
facilitiesatMichiganStateUniversity.Alldatafileswereorganized sembly which produced 20,179 unique OTUs at a 97% sequence
usingRpackagephyloseq(McMurdieandHolmes,2013). similaritycutoff,18,354ofwhichoccurredinsamplesfromG1,G5,
G6,andG10(Fig.S1).Shared“universal”OTUs(foundinsamples
2.5. Statisticalanalyses fromallfourof thesecropsat all fourdepths)accountedfor 31%
(5655) of the total (Fig. S1). Surface soils contained the highest
Differences in communitystructure werevisualized using db- proportion(12%)ofexclusiveOTUs,followedbythebottomlayer
RDA based on generalized UniFrac distances (a ¼ 0.5), which (8%),whiletheintermediatelayersaccountedfortheleast(5and
weregeneratedfromrepresentativesequencesofOTUsbyFastTree 6%each).
andtheRpackageGUniFrac(Chenetal.,2012a).Thesignificance Forthefourcropssampledoverdepth,bacterialdiversity(H0),
was tested by PERMANOVA with 999 permutations (using the observednumberofspecies(Sobs),andevenness(J’)werehighestin
function adonis in R package vegan), and the correlations of soil the top 10 cm of soil and decreased significantly in each deeper
propertiestothedb-RDApatternswerecalculatedusingtheenvfit layer(Fig.2,leftpanels,ANOVA,a<0.05).Comparingcropswithin
functionintheRpackage vegan(Oksanenetal.,2015).Alphadi- eachsoillayer,bacterialdiversityindexesweresignificantlylower
versity indexes, including observed richness (Sobs), Shannon di- incornsoilsthanswitchgrassinthe10e25cmlayer(Fig.2,right
versity(H0),andPielou'sevenness(J0),werecomputedbasedonthe panels), butotherwise no marked differences were found among
OTU table using the vegan package as well. Shared OTUs were crops(Fig.2andFig.S2).Foralldatacombined,bacterialdiversity
calculated and plotted using the R package VennDiagram (Chen, indexes were strongly associated with soil total C and N content
2014). The indicator analysis based on genera (singleton and (Fig.S3).
doubleton genera removed first) was conducted using R package
indicspecies(DeCaceresandLegendre,2009)with999permuta- 3.3. Communitystructures
tionsandallowingforcombinationsofdepthsandcrops,andtheP-
values were corrected for multiple comparison using R package There were significant differences in microbial community
qvalue(DabneyandStorey,2015)withafalsediscoveryrateof10% structure among the ten crops in the 0e10 cm layer (p < 0.001,
(q (cid:4) 0.1). Other measurements, including soil properties, were Table 2). On ordination, annual corn treatments were separated
analyzed and plotted using the R package ggplot2 (Wickham, from the perennial crop treatments by the first db-RDA axis
2009), while NMDS of soil properties was performed using the (Fig.3A).Continuouscorn(G1)wasseparatedfromcorntreatments
veganpackage.Allone-wayANOVAtestswereconductedbyone- withcovercropbyaxis2(Fig.3A),andcontinuouscornwithcover
way.test and pairwise.t.test with P-value adjustment method of crop(G2)wasseparatedfromcornwithcovercropinrotation(G3
“BH” for multiple comparisons. Data were square-root- or log- andG4)byaxis3(Fig.3B).Similarly,twoclusterswereobserved
transformed to meet normality and homogeneity of variance. within the six perennial systems: monocultures G5, G6, and G8
Otherwise,kruskalinRpackageargicolae(Mendiburu,2015)was (switchgrass,Miscanthus,poplar)andpolyculturesG7,G9,andG10
used. Pearson's correlations and their significances of a-diversity (nativegrassmix,earlysuccessional,andrestoredprairie)(Fig.3A).
indexes, abundances of individual phyla and classes to soil prop- Furthermore, G8 was separated from the other monocultures by
ertieswerecalculatedbyfunctionsofcorandcor.testinRpackage axis3(Fig.3B).Thus,sixgroups intotalare distinguishable. Cor-
stats(RCoreTeam,2014).TheseanalyseswereperformedusingR relations between site scores and environmental variables were
3.1.2(RCoreTeam,2014). relativelyweakbutstatisticallysignificantexceptforK;valuesfor
allbutPwerelowerforthecornsites(Fig.3andTableS2).
3. Results Ordinationofallsamplesforthefourcropssampledwithdepth
(G1,G5,G6,andG10)indicatedthattheirmicrobialcommunities
3.1. Soilproperties wereshapedprimarilybyfactorsassociatedwithdepth(Fig.4A).
Site scores were significantly correlated with all measured envi-
Soilchemicalpropertiesdifferedwithdepthandamongcrop- ronmental variables, especially C (r2 ¼ 0.91) and N (r2 ¼ 0.88)
pingsystems(Fig.1andTable1).NMDSordination(Fig.1)showed (TableS2).Whilesuchdepthrelatedfactorsplayedadominantrole
that samples separated primarily by depth (PERMANOVA, in shaping communities, PERMANOVA revealed a significant
P<0.001).Cropwasaminorfactor(PERMANOVA,P¼0.037),and interactionbetweendepthandcrops(Table2),leadingustomake
there was no significant interaction between crop and depth furthertestsforeachseparatesoillayer.Theseresultsindicatedthat
(PERMANOVA,P¼0.750).Fromthesurfacesoil(0e10cm)tothe cropsaffectedsoilcommunitiesforallbutthedeepest(50e100cm)
bottom (50e100 cm), soil total C and total N contents decreased layer(Table2).
(ANOVA,p<0.001)by12and7times,respectively.ThepHwasalso Forthe0e10cmlayer,ordinationseparatedsamplesforthefour
significantlylowerinthebottomlayer(ANOVA,p<0.01).SoilKand cropsinthesamewayaswhenall10cropswereincluded.G5and
P concentrations were significantly higher in the surface soil G6clusteredtogether,G1andG10separately(Fig.4B).Onlyfourof
B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152 143
Fig.1. Comparisonsofsoilchemicalpropertiesamongdepthsunderfourcrops(G1,G5,G6,andG10),andNMDSordinationbasedontheseproperties.Thebottomandtopofabox
arethe25thand75thquartiles,thehorizontallinewithinaboxisthemedian,andtheendsofthewhiskersarethelimitsofthedistributionasinferredfromtheupperandlower
quartiles.Dotsareoutliers.Blackstarsaremeans.LettersindicatetheANOVAgroupingamongdepths.BothsoilCandNareinunitsofg/100g(weight%),whileP,K,Ca,andMgare
allinunitsofmg/g(ppm).
Table1
Comparisonsofsoilchemicalpropertiesamongcropsat0e10cm.LettersindicatetheANOVAgroupingamongcrops.
Crops# C* N** pH** P K** Ca Mg***
G1 1.148±0.118b 0.111±0.009c 5.9±0.2c 57±43 173±56a 748±148 85±11c
G2 1.265±0.172ab 0.120±0.013bc 6.4±0.7ab 48±24 148±35ab 992±248 131±40abc
G3 1.208±0.115b 0.117±0.013bc 6.2±0.3abc 45±16 140±42abc 914±159 126±24ab
G4 1.195±0.172b 0.116±0.015bc 6.2±0.2abc 50±15 149±26ab 938±163 125±12b
G5 1.141±0.170b 0.110±0.013c 6.3±0.1abc 33±13 97±17c 863±167 124±12b
G6 1.257±0.152ab 0.114±0.013bc 6.1±0.1bc 40±9 111±62c 935±83 126±15b
G7 1.292±0.126ab 0.124±0.011bc 6.4±0.5abc 33±7 111±22bc 1056±57 156±16a
G8 1.558±0.295a 0.148±0.024a 6.4±0.1ab 54±10 182±45a 1000±107 145±3ab
G9 1.365±0.135ab 0.136±0.010ab 6.5±0.2ab 47±30 169±51a 996±225 172±17a
G10 1.208±0.109b 0.116±0.012bc 6.5±0.1a 35±12 110±29bc 915±138 154±37ab
#G1andG2areannuallycontinuouscornandcontinuouscornþcovercrop,respectively;whileG3andG4aresoybeanþcovercropandcornþcovercrop,respectively,ina
soybean-cornrotation.G5-G10areperenniallyswitchgrass,Miscanthus,nativegrassmix,poplar,earlysuccessional,andrestoredprairie,respectively.Significance:*P<0.05,
**P<0.01,***P<0.001.
the environmental variables were significantly (a (cid:4) 0.05) associ- distinctinthetopthreelayers(0e50cm), andbecamemoreho-
atedwiththesitescores.Kwaspositivelyassociatedwiththecorn mogeneous(withlessvariation)atthe50e100cmdepth(Fig.S4B).
sampleswhilepH,Mg,andCawerepositivelyassociatedwiththe
othercrops.Clusteringofcropswasdifferentforthedeeperdepths. 3.4. Taxonabundances
Inthe10e25cmlayer,G5andG10clusteredtogetherwhileG1and
G6 formed separate clusters (Fig. 4C). In the 25e50 cm layer, G5 OTUswereclassifiedto10majorphyla(eachmorethan1%of
formed a separate cluster, and while the other crops showsome thetotalsequences,Table3)thattogetheraccountedfor81.0%of
separation in Fig. 4D, no differences among themwere found by the total sequences, and 22 minor phyla accounting for an addi-
PERMANOVA(datanotshown).Therewerenosignificantcorrela- tional3.7%.Atotalof14.2%ofthesequenceswereunclassifiedat
tionsbetweenenvironmentalvariablesandsitescoresfordepths the phylum level (unclassified_Bacteria, Table 3). Relative abun-
otherthan0e10cm,andnosignificantdifferencesamongcropsfor dances of individual phyla were highly variable with depth and
the50e100cmlayer(Table2). among cropping systems, and were significantly correlated with
Generalized UniFrac distances between pairs of soil layers soil properties (Table 3, Fig. 5, Tables S3 and S4). Proteobacteria,
increased with the distance between the layers being compared Actinobacteria,Planctomycetes,Bacteroidetes,andcandidateWPS-2
(Fig. S4A). Pairwise comparisons of distances between cropping decreased from the surface to deeper soils, while Firmicutes and
systems also showed that bacterial communities were more unclassified Bacteria increased. The most abundant phylum,
144 B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152
andTableS5).Thesecontrastingpatternsofclasseswithinthesame
phylawith soil depth were also observed in Verrumicrobia (Spar-
tobacteriavsSubdivision3)andChoroflexi(KtedonobacteriavsCal-
dilineae)andevenintheconsistently-increasingphylumFirmicutes
(ClostridiavsBacilli)(TableS5),butwerenotdetectedinclassesof
consistently-decreasing phyla Proteobacteria and Bacteroidetes.
Similarly,corn-relatedsoilshadlowerabundancesofGp6andGp17
butgreaterabundancesofGp1andGp3at0e10cm.Switchgrass
soilsaccumulatedmoreDelta-andGamma-butlessAlpha-proteo-
bacteriaat25e50cm,aswellashigherpercentageofsubdivision3
and Verrucomicrobiae but lower Spartobacteria of Verrucomicrobia
(Fig.5andTableS6).
3.5. Indicators
Indicator analysis identified 271 genera significantly (q < 0.1)
associated with a specific depth or a combination of depths
(Table S7), of which 91 genera were clearly classified and had
relativeabundancesover0.005%(Fig.7).Usingthesameanalysis,
20, 5, and 7 indicator generawere characteristic (q < 0.1) of one
crop or a combination of crops at 0e10 cm, 10e25 cm, and
25e50cm,respectively(TableS8).Ofthese,27generawereunique
and clearly classified (Fig. 8). Indicator genera characteristic of
0e10cmand10e25cmwererelativelysimilar(moreshared),but
differentfromthoseatthetwodeeperlayersthatweresimilarto
each other as well. Corn-related soils were characterized by in-
dicators different from those associated with perennial crops at
0e10 cm and 10e25 cm, while switchgrass soils had more
distinctive indicators at 25e50 cm. Overall, most of indicator
Fig.2. Comparisonsofbacterialdiversityindexesamongsoildepthsandamongcrops generabelongedtoProteobacteriaandActinobacteria,followedby
atthedepthof10e25cm.ThefourcropabbreviationsaredefinedinTable1.Letters BacteroidetesandAcidobacteria.
indicatetheANOVAgroupingamongdepthsandcrops(a¼0.05).Explanationofboxes
andstarsasforFig.1.Sobs,observednumberofOTUs;H0,Shannondiversityindex;J0
Pielou'sevennessindex. 4. Discussion
In this study, we observed significant differences in soil pro-
Table2 karyotic communities and soil properties among four soil depths
Effectofsoildepth,crop,andtheirinteractionsonbacterialcommunitystructures
(down to 100 cm) under four different biofuel crop systems and
basedonPERMANOVAandgeneralizedUniFracdistances(a¼0.5).
among10cropsinnearsurfacesoilsafter6cropgrowingseasons.
Depth Crop Depth(cid:1)Crop Asaproxyforchangingsoiledaphicfactors,especiallytotalCandN,
F R2 F R2 F R2 soil depth was a major driver of bacterial community structure
0-10cm,10crops e e 1.64*** 0.28 e e among thefourcropping systemsexamined overdepth, whereas
4depths(cid:1)4crops 19.51*** 0.42 2.43** 0.05 1.47* 0.10 crop effects were secondary and significantly correlated with
0-10cm,4crops 2.14*** 0.31 severalsoilvariablesat0e10cm(Fig.3).Moreover,ourindicator
10-25cm,4crops e e 1.39** 0.24 e e analyses identified exclusive and shared genera characteristic of
25-50cm,4crops e e 2.20*** 0.29 e e
soilsindifferentlayersandsoilsunderdifferentcropsatthesame
50-100cm,4crops e e 1.24ns 0.19 e e
depth,whichsuggestspatternstobetestedmorebroadlyaswellas
Significance:*P<0.05,**P<0.01,***P<0.001. forconsistencyoftheirdrivingecologicalfeatures.
The significant decrease in alpha diversity with depth is
Acidobacteria, as well as Verrucomicrobia and Chloroflexi were mirrored in previous studies using pyrosequencing (Will et al.,
2010; Eilers et al., 2012; Tsitko et al., 2014), clone libraries
generallymoreabundantinthemiddlelayers.Therelativeabun-
(Hansel et al., 2008), and fingerprinting approaches (Fiereret al.,
danceofThaumarchaeota,themostabundantArchaea,showedabi-
2003; Agnelli et al., 2004). Eilers et al. (2012) observed that mi-
modal distribution with depth. Among cropping systems, corn-
crobialcommunitiesbasedonweightedUniFracdistancesamong
relatedsoilsharboredmoreProteobacteria(especiallyAlpha-)and
Chloroflexi, but less Acidobacteria than perennial crop soils at sites were most variable in the near-surface horizons, relatively
0e10 cm. Less abundant Actinobacteria and Planctomycetes but uniformatintermediatedepths,andagainhighlyvariableatdeep
moreunclassifiedBacteriawerepresentincornsoilsat10e25cm. layers.Indeed,inourstudysamplevariabilitywithinthesamelayer
basedongeneralizedUniFracdistanceswashighestinthesurface
SwitchgrasssoilscontainedmoreBacteroidetesinlayersfrom25to
100cm,andmoreunclassifiedBacteriabutlessThaumarchaeotaat anddeepestsoilsformostcases(Fig.S4B).Thesoildepthassociated
25e50cmaswellaslessSpartobacteriabutmoresubdivision3of withcommunitychangeappearstoextendtoapproximately50cm,
with communities becoming less similar (greater phylogenetic
theVerrucomicrobiathantheotherthreecrops.
distance) with increasing physical distance. Indicator analyses
Although the predominant classes of Acidobacteria (Gp6, Gp4,
revealedmanyspecificgeneraforsoildepthswithdiverseputative
Gp16,Gp17)displayedsimilartrendsasthephylumwithsoildepth,
functions: for example, biodegradation/decomposition (Actino-
someclasses(Gp7,Gp1,Gp2)wereproportionallymoreabundant
planes(GoodfellowandWilliams,1983),Cellvibrio(Mergaertetal.,
withsoildepth,whileGp3remainedquitestablewithdepth(Fig.6
2003)) and nitrogen-fixation (Microvirga (Ardley et al., 2012),
B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152 145
Fig.3. Differencesinsoilbacterialcommunitystructuresamongcropsforthe0e10cmlayer.db-RDAconstrainedoncropswasfittedwithsignificantlycorrelatedsoilproperties.
Fig.4. Differencesinsoilbacterialcommunitystructuresamongdepths(A)andundercropsatthesamedepth(BeD).Thevariationsexplainedbydepthsorcropsandstatistics
frompermutationtestsaregiveninTable2db-RDAsconstrainedbydepthsorcropswerethenfittedwithsignificantlycorrelatedsoilproperties.Thereisnoplotforthe50e100cm
layerbecausetherewerenosignificantdifferencesinsoilbacterialcommunitiesamongcrops(Table2).Datawerebasedonthe4cropswithdepth.
Azoarcus(Reinhold-Hureketal.,1993))inshallowsoils,aswellas waterholdingcapacity,andredoxstatuscanvaryamongsoilho-
denitrification(Microvirgula(Patureauetal.,1998))andutilization rizons and also impact which species thrive or senesce at each
of recalcitrant compounds (Rubrobacter (Carreto et al., 1996)) in depth.Paststudiesingrasslands(Willetal.,2010)andpeat(Tsitko
deeperlayers.WhileCandNwerehighlycorrelatedtomicrobial etal.,2014)havealsodocumentedastrongcorrelationtosoiltotal
communitychanges, other soil properties such as aggregate size, C and N. Microbial biomass is well known to decline with depth
146 B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152
Table3
Relativeabundancesofmajorphyla(>1%)andtheirchangeswithsoildepthandcorrelationstosoilproperties.MoredetailsinTableS3.
Phylum Abundance F-value Changes Correlationto soil variables
with depth
C N pH P K Ca Mg
Acidobacteria 28.68±4.57 24.21*** 0.47*** 0.43*** 0.59*** -0.09 0.09 0.26* 0.15
Proteobacteria 14.28±3.82 118.24*** 0.89*** 0.88*** 0.38*** 0.44*** 056*** -0.01 -0.161
unclassified_Bacteria 14.24±4.34 106.22*** -0.89*** -0.88*** -0.30** -0.32*** -0.51*** -0.13 -0.04
Verrucomicrobia 9.49±2.01 17.08*** -0.46*** -0.49*** -0.37*** -0.27* -0.09 0.22 0.39***
Actinobacteria 6.86±1.85 9.53*** 0.45*** 0.47*** 0.31** 0.35** 0.27* 0.03 -0.04
Firmicutes 5.42±4.57 75.10*** -0.73*** -0.70*** -0.53*** -0.17 -0.35** -0.21 -0.02
Chloroflexi 4.91±2.39 27.32*** -0.60*** -0.65*** -0.42*** -0.24* -0.14 0.31** 0.36**
Planctomycetes 4.58±1.18 46.49*** 0.74*** 0.77*** 0.33** 0.33** 0.38*** 0.09 -0.15
Bacteroidetes 2.90±1.84 60.72*** 0.81*** 0.81*** 0.38*** 0.26* 0.48*** 0.01 -0.07
Thaumarchaeota 2.26±0.92 25.41*** 0.50*** 0.55*** -0.02 0.32** 0.15 -0.36** -0.40***
candidateWPS-2 1.64±0.93 248.30*** 0.90*** 0.91*** 0.40*** 0.25* 0.46*** 0.12 -0.08
Significance: *P<0.05,**P<0.01,***P<0.001.
(Agnellietal.,2004;Eilersetal.,2012),consistentwithourlowDNA 2010;Shietal.,2011).
extraction yield, especially at 50e100 cm. Overall, the effects of Differencesinmicrobialcommunitystructureamongcropshave
depth(0e10cmvs.10e25cm)hadagreaterinfluenceonbacterial alsobeenattributedtotheperennialnatureandrootingsystemsof
communities than selective pressures from different cropping the crops. Corn has a shorter photosynthetic life cycle, shallower
systemsat0e10cm.Similarly,itwasreportedthatthedeptheffects rooting depth, lower root densities, and less root biomass than
onmicrobialcommunities,evenas littleas10e20cmwithin the perennial grasslands, including switchgrass (Jackson et al.,1996;
samecore,canreachasimilarextentasthatofsurfacesoilssepa- Tufekcioglu et al.,1999; Culman et al., 2010). Indeed, we identi-
rated by thousands of kilometers (Eilers et al., 2012). Together, fiedabundantrootsinswitchgrasssoildownto100cm,butalmost
these results suggest that soil depth integrates environmental norootsincornsoildeeperthan25cm.Furthermore,arecentstudy
gradientsalongsoilprofilesandformsastrongecologicalfilterfor demonstratedthatswitchgrassrootlengthdensitiesandrootdry
selecting/shapingmicrobialcommunitieswithin different depths, weight (both peaking at 30e45 cm) are much higher than Mis-
asproposedbyEilersetal.(2012). canthus(peakingat0e10cm,90%concentratinginthetop35cm)
In addition to the overwhelming depth influences, we also inrelativelydeepersoil(MontiandZatta,2009),althoughwehave
identifiedsignificanteffectsofcropsonsoilmicrobialcommunities. notobservedsuchdifferenceshere(Sprungeretal.,unpublished).
These crop effects were constrained within the top 50 cm, pre- Together,theseobservationssuggestthatswitchgrassmaypossess
sumablyduetorhizosphericinfluencessuchasplantrootexudates, themostuniquerootstructureand/orqualityandquantityofroot
root cap sloughing, and root turnover (Acosta-Martinez et al., exudatesandhencesupportthehighestuniquenessoftheassoci-
2008).Perennialplantsareknowntoproducemoreabundantmi- atedsoilmicrobialcommunitiesatthe25e50cmdepthasseenin
crobial resources through rhizodeposition and root turnover and thisstudy.Switchgrassaccumulatesgreatermicrobialbiomassthan
can thus accommodate a larger population of more diverse mi- corn and this influence of resource availability can move deeper
croorganisms(Liangetal.,2012b).Inaddition,croprotation,tillage within the soil over time (to 30 cm after 9 years) (Stewart et al.,
(including annual planting), and other management influences 2015). We detected significantly higher diversity in switchgrass
(suchasfertilizationandherbicides)servetodifferentiateperen- thancontinuouscornat10e25cmafter6croppingyears.There-
nial from annual crops. The distant grouping of continuous corn fore,giventheinherentlydifferentrootingsystems,wepredictthat
awayfromtheotherthreecorn-basedsystemsandtheseparation switchgrasswilleventuallysignificantlyshapemicrobialcommu-
of perennial monocultures from multispecies grasses can infer nities as deep as 100 cm over time through root-mediated C
these impacts (Fig. 4). Specifically, corn soils harbored the most allocation.
distinct communities,compared totheperennial biofuel cropsin ThedominancesofAcidobacteria,Proteobacteria,Verrucomicro-
thetop25cm,similartoresultscomparingcorn,switchgrass,and bia,Actinobacteria,Firmicutes,andChloroflexiobservedinthisstudy
Miscanthussurfacesoils(downto24cmdepth)(Liangetal.,2012b; havebeendetectedinvarioussoiltypes,biomes,anddepths(Jesus
Mao et al., 2013; Jesus et al., 2016). This microbial pattern under etal.,2010;Willetal.,2010;Eilersetal.,2012;Liangetal.,2012b;
differentcropswasalsoreflectedinindicatorgenera.Forexample, Tsitko et al., 2014), which indicates the ubiquity and important
continuous corn soils at 0e10 cm, which were lower in pH than rolesofthesephyla.However,therelativeabundancesofthesetaxa
othercropsoils(Table1),werecharacterizedbyRhodanobacterthat changed distinctly with soil depth and among cropping systems.
iscapableofdenitrificationanddominateatlowpH(Greenetal., The most striking of these changes was associated with Proteo-
2012; Kostka et al., 2012). In contrast, perennial switchgrass and bacteria,whoserelativeabundancedecreasedwithdepth,atrend
Miscanthus soils were strongly associated with lignin-degrading observedinotherstudiesaswell(Eilersetal.,2012;Tsitkoetal.,
Sphingobacterium (Wang et al., 2013), while switchgrass soils 2014). Given the strong correlation to soil C (Table 3), the
were also characterized by lignin-degrading Novosphingobium decreaseofproteobacterialabundanceswithdepthislikelydueto
(Chen et al., 2012b) at 10e50 cm. The plant growth-promoting their lifestyle, as they are more abundant in soil with higher C
Acinetobacter, an indicator at lower depth layers, especially in availability (Fierer et al., 2007; Eilers et al., 2010; Goldfarb et al.,
switchgrass soils might provide benefits by fixing nitrogen, solu- 2011). This decreasing trend was consistent for all four proteo-
bilizing P, producing siderophores and indole-3-acetic acid, and bacterialclasses.Croptype,possiblyinconjunctionwithsampling
promoting root-growth (Huddedar et al., 2002; Sachdev et al., time,alsoinfluencedProteobacteria,withAlphaproteobacteriaand
B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152 147
Fig.5. Differencesinrelativeabundancesofmajorphyla(>1%)undercropsatthesamedepths.Starsanderrorbarsarethemeansandstandarddeviations,respectively.Firstletters
ofthephylumnameswereusedtosavespace.LettersindicatetheANOVAgroupingamongdepthsandcrops.Moredetailsandmorephylaaswellastheircorrelationstosoil
propertiesareinTableS4.
Gammaproteobacteria more abundant in corn-based soil at Granulicellaat0e10cm,whichhydrolyzesawiderangeofsugars
0e10cm.ThismayreflectmorelabileorganicCinthesurfacesoil, andcomplexpolysaccharides(Rawatetal.,2013).Additionally,this
perhapsduetothedegradationofdeadcornroots,asthesampling ecologicallifestyle-basedhypothesisexplainsthedeclinesofActi-
timewasapproximatelyonemonthafterharvest.Moredeadroots nobacteria and Bacteroidetes (Fierer et al., 2007) with depth.
in corn soils were also supported by the observed indicator Planctomycetes(IvanovaandDedysh,2012)andcandidatedivision
148 B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152
Fig.6. Relativeabundancesofbacterialclasseswithinthesamephylumwithsoildepth.Starsanderrorbarsarethemeansandstandarddeviations,respectively.Lettersindicate
theANOVAgroupingamongdepthsandcrops.MoredetailsandmoreclassesaswellastheircorrelationstosoilpropertiesareinTableS5.
WPS-2(Tsitkoetal.,2014)havealsobeenreportedtodecreasewith abundant in the four corn systems than in the perennial ones,
depth, consistent with our observation. Recently, Planctomycetes suggestingthatpossiblyCquality,soilproperties(e.g.significantly
wereshowntobecapableofaerobicdegradationofplantsaccha- positive correlation to pH, Table S6), or other management prac-
rides (Erbilgin et al., 2014), which agrees with their decreasing ticesmayimpacttheirstatus.Moreover,acidobacterialabundances
abundanceswithdepth. have been found to be negatively correlated with pH (Hartman
Otherbacteriallineagesincreasedwithdepthorpeakedinthe etal.,2008;Jonesetal.,2009).Thiscorrelationwasnotobserved
middlelayers.Acidobacteria(themostabundant),Verrucomicrobia, at the phylum level in this study. Rather we found some classes
andChloroflexipeakedatmid-layers,whileFirmicutesandunclas- (especiallyGp1 and Gp2) werenegativelycorrelatedtopH while
sifiedBacteriaconsistentlyincreasedwithdepth.Acidobacteriaare some(e.g.Gp6,Gp4)werepositivelycorrelatedwithpH,similarto
wellknowntobewidelydistributedalongthesoilprofiles(Hansel earlier findings (Jones et al., 2009). Distinct genera within Acid-
etal.,2008;Eilersetal.,2012),andareconsideredtobeoligotrophs obacteriaidentifiedas indicatorsassociated with different depths
withhigherabundancesassociatedwithlesserCresources(Fierer canalsobeexplainedbytheirvariousphysiologies.
et al., 2007). This may explain increases in relative abundances The peak in Verrucomicrobia abundance in the middle depths
fromthesurfacetothemid-layer(higherCtolowerC).However,it wasalsoshownpreviously,andwassuggestedtobepartiallylinked
is not clear what drives a decrease in relative abundance in the totheiroligotrophicclassification(Eilersetal.,2012).Similartothe
deeper layers. Although this is an overall trend at the coarse Acidobacteria, we also observed variations in trends between the
phylumlevel,subgrouppopulationsmaypossessvaryingphysiol- twomajorclasses,SpartobacteriaandSubdivison3,withthelatter
ogies(Fiereretal.,2007)thatdrivevariationswithsoildepthand more abundant in switchgrass soil at 25e50 cm. The Firmicutes
edaphic properties. For example, most subgroups (e.g. Gp7, Gp1, werepredominatelyrepresentedbytheobligatelyanaerobicClos-
and Gp2) increased with depth, reflecting oligotrophic status. In tridiainthisstudy.Theirincreasingproportionswithdepthwere
contrast,themostabundantGp6decreasedwithdepth,appearing notexpectedsincethesearewell-drained,sandysoils,andlimited
toexhibitamorecopiotrophic-likephysiology.However,asimple oxygenwouldnotbeexpected.However,theabilityofClostridiato
C-based impact on Gp6 abundance is unlikely as they were less sporulate as well as restricted metabolism due to substrate
B.Zhangetal./SoilBiology&Biochemistry112(2017)140e152 149
Fig.7. Indicatorgenerasignificantly(q<0.1)associatedwithonesoildepthoracombinationofsoildepths.Thebarindicatestherelativeabundanceofeachindicatorgenus,while
thesizeofeachcirclerepresentstheindicatorvalue(associationstrength)ofaspecificgenuswiththedifferentsoildepths:0e0.25,notcharacteristic;0.25e0.5,weaklychar-
acteristic;0.5e0.75,characteristic;and0.75e1.0,stronglycharacteristic.Taxonomicinformation,indicatorvalues,P-values,andq-valuesofallindicatorgeneraaregiveninTableS7.
Datawerebasedon4cropswithdepth.