The phylogenetic composition and structure of soil microbial communities shifts in response to ...

14 Pages·2011·0.72 MB·English

by  Zhili He

TheISMEJournal(2012)6,259–272
&2012InternationalSocietyforMicrobialEcology Allrightsreserved1751-7362/12
www.nature.com/ismej
ORIGINAL ARTICLE
The phylogenetic composition and structure of
soil microbial communities shifts in response
to elevated carbon dioxide
Zhili He1, Yvette Piceno2, Ye Deng1, Meiying Xu1,3, Zhenmei Lu1,4, Todd DeSantis2,
Gary Andersen2, Sarah E Hobbie5, Peter B Reich6 and Jizhong Zhou1,2
1Institute for Environmental Genomics, Department of Botany and Microbiology, University of Oklahoma,
Norman, OK, USA; 2Ecology Department, Earth Sciences Division, Lawrence Berkeley National Laboratory,
Berkeley,CA, USA; 3Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application,
Guangdong Institute of Microbiology, Guangzhou, China; 4College of Life Sciences, Zhejiang University,
Hangzhou, China; 5Department of Ecology, Evolution, and Behavior, St Paul, MN, USA and 6Department
of Forest Resources, University of Minnesota, St Paul, MN, USA
One of the major factors associated with global change is the ever-increasing concentration of
atmospheric CO . Although the stimulating effects of elevated CO (eCO ) on plant growth and
2 2 2
primary productivity have been established, its impacts on the diversity and function of soil
microbialcommunitiesarepoorlyunderstood.Inthisstudy,phylogeneticmicroarrays(PhyloChip)
were used to comprehensively survey the richness, composition and structure of soil microbial
communities in a grassland experiment subjected to two CO conditions (ambient, 368 p.p.m.,
2
versuselevated,560p.p.m.)for10years.Therichnessbasedonthedetectednumberofoperational
taxonomicunits(OTUs)significantlydecreasedundereCO .PhyloChipdetected2269OTUsderived
2
from45phyla(includingtwofromArchaea),55classes,99orders,164familiesand190subfamilies.
Also, the signal intensity of five phyla (Crenarchaeota, Chloroflexi, OP10, OP9/JS1, Verrucomicro-
bia)significantlydecreasedateCO ,andsuchsignificanteffectsofeCO onmicrobialcomposition
2 2
were also observed at the class or lower taxonomic levels for most abundant phyla, such as
Proteobacteria, Firmicutes, Actinobacteria, Bacteroidetes and Acidobacteria, suggesting a shift in
microbialcommunitycompositionateCO .Additionally,statisticalanalysesshowedthattheoverall
2
taxonomicstructureofsoilmicrobialcommunitieswasalteredateCO .Manteltestsindicatedthat
2
such changes in species richness, composition and structure of soil microbial communities were
closely correlated with soil and plant properties. This study provides insights into our under-
standing of shifts in the richness, composition and structure of soil microbial communities under
eCO and environmental factorsshapingthe microbial community structure.
2
TheISME Journal(2012)6, 259–272;doi:10.1038/ismej.2011.99; published online28July 2011
SubjectCategory: microbial population and community ecology
Keywords: soil microbial community; PhyloChip; elevated CO ; microbial composition; microbial
2
community structure
Introduction plant growth and primary productivity are well-
established(Reichetal.,2001;AinsworthandLong,
The concentration of atmospheric CO has risen by
2 2005; Luo et al., 2006). For example, eCO has been
approximately 36% since the mid-19th century, 2
found to increase plant growth (Curtis and Wang,
largely because of human activities, such as fossil
1998), enhance fine root production (Hungate et al.,
fuel combustionand land use. With the current rate
1997)andaugmentsoilcarbonallocation(Zaketal.,
ofincreaseof1.9p.p.m./year,itisprojectedtoreach
1993; Hu et al., 2001). However, the influence of
700 p.p.m. by the end of this century, which may
eCO onsoil microbialcommunitiesremainspoorly
havemajorconsequencesoncarboncyclingandthe 2
understood and controversial (Walther et al., 2002;
functioning of terrestrial ecosystems (IPCC, 2007).
ParmesanandYohe,2003;Heathetal.,2005;Carney
The stimulating effects of elevated CO (eCO ) on
2 2 et al., 2007; Drigo et al., 2007, 2009, 2010; Gruber
andGalloway,2008;HeimannandReichstein,2008;
Correspondence: J Zhou, Institute for Environmental Genomics Lesaulnier etal., 2008; Austin etal., 2009; Ge et al.,
(IEG), Department of Botany and Microbiology, University of 2010; He et al., 2010b). Also, the plant growth
Oklahoma,Norman,OK73019,USA. stimulation observed under eCO may be transient
E-mail:[email protected] 2
(Drake et al., 1997; DeLucia et al., 1999) possibly
Received4January2011;revised18June2011;accepted20June
2011;publishedonline28July2011 because of the depletion of available nitrogen (N)
EffectofeCO andenvironmentalfactorsonsoilmicrobes
2
ZHeetal
260
(Luo et al., 2004; Reich et al., 2006). In addition, 2009; Rastogi et al., 2010), suggesting that Phylo-
multipleglobalchangefactors,suchaseCO ,elevated Chip provides more comprehensive surveys of
2
O , warming and/or precipitation, may interact to microbial diversity, composition and structure.
3
alter soil microbial community diversity, composi- Theobjectivesofthisstudywereto:(i)surveythe
tion,structureandfunction(Chungetal.,2006;Castro richness and composition of soil microbial commu-
et al., 2010). Therefore, understanding the diversity, nities; (ii) examine the effects of eCO on the
2
composition and structure of soil microbial commu- richness, composition and structure of soil micro-
nitiesisnecessaryforustoassesshoweCO modifies bial communities and (iii) link soil geochemistry
2
ecosystem properties and functional processes. and plant properties with the microbial community
Soil may be the most complex of all microbial composition and structure using PhyloChip (Brodie
communities with extremely high diversity. For et al., 2006, 2007). For these purposes, this study
example, 1g of soil contains thousands to millions wasconductedinaconstructedgrasslandecosystem
of different bacterial, archaeal and eukaryotic spe- subjectedtoCO manipulationfor10yearsbyusing
2
cies (Torsvik et al., 2002; Gans et al., 2005) thefree-air CO enrichment (FACE) technology.The
2
interwoven in extremely complex food webs. results showed that eCO significantly altered the
2
Furthermore, most (499%) of those microbes are richness, composition and structure of soil micro-
as-yet uncultured (Whitman et al., 1998). Thus, bialcommunities,especiallyforparticularmicrobial
characterizing the phylogenetic diversity of soil populations, at the operational taxonomic unit (OTU)
microbialcommunitiesandtheirresponsestoglobal level.Suchmicrobialpopulationchangeswereclosely
change (for example, eCO ) will make a significant correlated with soil and plant properties.
2
contribution to understanding soil ecosystems.
Conventional molecular biology approaches
Materials and methods
have demonstrated that soil microbial diversity
generally increased (Mitchell et al., 2003; Janus The following is a summary of the methods used in
et al., 2005; Sonnemann and Wolters, 2005; Jossi thisstudy.Moredetailedinformationisprovidedin
etal.,2006;Lesaulnieretal.,2008),decreased(Horz Supplementary Data-A.
et al., 2004) or remained unchanged (Barnard et al.,
2004; Ebersberger et al., 2004; Loy et al., 2004;
Chung et al., 2006; Gruter et al., 2006; Lipson et al., Site and sampling
This study was conducted within the BioCON
2006; Drigo et al., 2007, 2009; Austin et al., 2009;
Ge et al., 2010) in response to eCO2. The apparent (Biodiversity, CO2 and Nitrogen) experiment site
(http://www.biocon.umn.edu/) located at the Cedar
discrepancy of microbial responses to eCO could
2
Creek Ecosystem Science Reserve in Minnesota,
be partially due to real differences among various
ecosystems, but could also be due to differences in USA. The main BioCON field experiment has a
total of 296 plots with three treatments: CO
the methodologies used, such as terminal restric- 2
(ambient (aCO ), 368 p.p.m. versus elevated, 560
tion-fragment length polymorphism, denaturing 2
gradient gel electrophoresis, 16S rRNA-based se- p.p.m.),N(ambientversus4gNperm2peryear)and
quencing, enzyme activities and phospholipid fatty plant diversity (1, 4, 9 or 16 species) (Reich et al.,
2001). In this study, soil samples from 24 plots (12
acids.Forexample,itispossiblethatsomemethods
replicates from aCO , 12 replicates from eCO and
may not be sensitive enough to resolve the differ- 2 2
ences caused by eCO at the community level. all with 16 species and ambient N supply) were
2
collected in July 2007 when they had been exposed
Recently, 16S rRNA gene-based microarray tech-
to aCO or eCO for 10 years, and each sample was
nologieshavebeenusedtoobtainmorecomprehen- 2 2
sive information on microbial community diversity, composited from five soil cores at a depth of
0–15cm for analysis of soil properties or DNA
composition, structure and dynamics. PhyloChip
extraction. Additional information about the Bio-
(G2) consists of 506944 probe features, and of these
features, 297851 are oligonucleotide perfect match CON experimental site, and plant groups and
species, is provided in Supplementary Data-A.
(PM)ormismatchmatch(MM)probesfor16SrRNA
genes (Brodie et al., 2006, 2007). PhyloChip has
been used to detect microorganisms in a variety of
Plant and soil analyses
environments, such as contaminated sites (Brodie
The aboveground and belowground biomass, plant
et al., 2006; Rastogi et al., 2010), air (Brodie et al.,
C and N concentrations, soil pH, volumetric soil
2007), water (Hery et al., 2010), soil (Cruz-Martinez
moisture, total soil C and N concentrations, and
et al., 2009; DeAngelis et al., 2009; Yergeau et al.,
in situ net N mineralization and net nitrification
2009; Teixeira et al., 2010), microbial fuel cell
weremeasuredasdescribedpreviously(Reichetal.,
(Wrighton et al., 2008) and Huanglongbing patho-
2001, 2006; He et al., 2010b).
gen-infected citrus (Sagaram et al., 2009). In addi-
tion, several studies demonstrated that PhyloChip
could detect many more bacterial taxa as compared DNA extraction, purification and quantitation
with the 16S rRNA gene-based clone library Soil DNAwas extracted by freeze-grinding mechan-
approach (DeSantis et al., 2007; La Duc et al., icallysisasdescribedpreviously(Zhouetal.,1996).
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DNAqualitywasassessedbytheratiosof260/280and Results
260/230nm and final DNA concentrations were
Effects of eCO on plant and soil properties
quantifiedbythePicoGreenmethod(Ahnetal.,1996). 2
The plant productivity measured by biomass of
aboveground, roots and fine roots was significantly
(Po0.05) stimulated by eCO (Supplementary Table
PhyloChip analysis 2
S1), which is consistent with previous studies in
ThesecondgenerationofthePhyloChip(PhyloTech,
thissite(Reichetal.,2001;Adairetal.,2009).Also,
SanFrancisco,CA,USA),whichhas8741OTUsand
the whole-plot total N (gm(cid:2)2) and legume biomass
842 subfamilies with 297851 probes, was used for
significantly (Po0.05) increased at eCO , but the
this study (Brodie et al., 2006). PhyloChip analysis 2
percentages of nitrogen (N) in the whole-plot plant
included three major steps: (i) Amplification of 24
biomass, aboveground biomass and belowground
soil genomic DNAs using universal 16S rRNA
biomass significantly (Po0.05) decreased (Supple-
primers (27F/1492R for bacteria and 4Fa/1492R for
mentary Table S1). In addition, the aboveground
archaea);(ii)500ngofbacterialand30ngofarchaeal
carbon/nitrogen (C/N) ratio significantly (Po0.05)
PCR products were hybridized to each PhyloChip
increased (Supplementary Table S1), probably be-
(Brodie et al., 2006, 2007) and (iii) hybridization
causeofanincreaseinplantbiomassandadecrease
data were preprocessed prior to statistical analysis
intheabovegroundNconcentration.Similarly,eCO
asdetailedinSupplementaryData-A.Foreightof12 2
significantly (Po0.05) increased soil pH and soil
eCO samples with less than 30ng of archaeal PCR
2 moisture (at depths of 0–17, 42–59 and 83–100cm).
products, 10mL of concentrated archaeal amplicons
However, no significant (P40.05) changes in soil
were used. A mixture of amplicons at known
carbon, nitrogen, C/N ratio, or rates of ammonifica-
concentrations was added to each sample prior to
tion, nitrification or net N mineralization, were
fragmentation, which allows for standardization/
observed (Supplementary Table S2). The significant
normalization of PhyloChip data. Data obtained
differences in plant characteristics and soil proper-
from the CEL files (produced from GeneChip
ties suggest that the diversity, composition and
Microarray Analysis Suite, version 5.1) were scaled
structure of soil bacterial communities may be
by setting the mixture of internal standards (spike
shifted in response to eCO .
mix)meanintensityto2500tocompensateforslight 2
differences in probe responses on different chips.
OTU reports were generated as described in Sup- Richness of soil microbial communities in response
plementary Data-A. Because setting a positive frac- to eCO2
tion (pf) cut-off can vary the number of passing The richness of soil microbial communities was
OTUs (and hence affect the reported number of examinedbyPhyloChip.Atotalof2269 OTUswere
OTUs for each sample), several pf cut-off values detected at least in three samples, accounting for
(0.86,0.88,0.90,0.92,0.94)wereevaluatedbyusing 26% OTUs on the PhyloChip. An average of 1916
the PhyloChip data analysis pipeline PhyloTrac OTUs were detected at aCO2, which was signifi-
(http://www.phylotrac.org/Home.html)andstatistical cantly (P¼0.0281) higher than an average of 1864
methods as described under Materials and methods OTUsdetectedateCO2(Table1).AlldetectedOTUs
and Supplementary Data-A. A pf cut-off of 0.9 was were taxonomically derived from two archaeal
determined to be a reasonable choice and used to phyla and 43 bacterial phyla, 55 classes, 99 orders,
generate the final OTU report used in this study. 164 families and 190 subfamilies; most phylotypes
were detected at both aCO and eCO , with few
2 2
detected only at aCO or eCO (Table 2). At the
2 2
Statistical analysis phylumlevel,amongatotalof2269OTUsdetected,
Pre-processedPhyloChipdatawerefurtheranalyzed 1002 OTUs were derived from Proteobacteria, a
by different statistical methods: (i) Response ratio phylum with the highest number of detectable
(Luo et al., 2006); (ii) detrended correspondence OTUs, followed by Firmicutes with 384, Actinobac-
analysis of the microbial community structure; (iii) teria with 289, Bacteroidetes with 162 and Acid-
analysis of similarities (Clarke, 1993), non-para- obacteriawith76OTUs(Table1).Also,basedonthe
metric multivariate analysis of variance (ADONIS) number of OTUs detected in each phylum, two
(Anderson, 2001) and multi-response permutation phyla had significantly (Po0.05) lower numbers of
procedure (Mielke and Berry, 2001; McCune and OTUs detected at eCO2 than at aCO2, including
Grace, 2002) were used to analyze differences of Chloroflexi (P¼0.003) and OP10 (P¼0.007)
microbialcommunitiesbyusingtheBinomialindex (Table 1). The results indicate that the richness of
(Anderson and Millar, 2004); (iv) Mantel test and soil microbial communities was decreased at eCO2.
canonical correspondence analysis for linking the
functional structure of microbial communities to Overall taxonomic composition and structure of soil
plant or soil variables; and (v) partial Mantel test microbial communities in response to eCO
2
and partial canonical correspondence analysis for To examine if eCO affects the taxonomic composi-
2
co-variation analysis of soil and plant variables tion and structure of soil microbial communities,
(Zhou et al., 2008; He et al., 2010b). detrended correspondence analysis was performed
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Table1 NumbersofOTUsdetectedbyPhyloChipinmajorphylaunderaCO andeCO conditions
2 2
Phylum OTUsonPhyloChip No.ofOTUsdetectedbyPhyloChip
Total(%) aCO eCO P(t-test)
2 2
Crenarchaeota 79 12(15.1) 12.00±0.00 12.00±0.00 1.000
Euryarchaeota 224 2(0.9) 1.00±0.00 1.00±0.00 1.000
Acidobacteria 98 76(77.6) 67.67±6.56 64.25±5.96 0.195
Actinobacteria 810 289(35.6) 233.17±20.32 225.92±17.24 0.356
Bacteroidetes 880 162(18.4) 123.42±14.39 119.67±20.00 0.603
Chlorobi 21 11(52.4) 9.42±1.78 8.83±1.59 0.406
Chloroflexi 117 44(37.6) 37.58±4.58 31.33±4.75 0.003
Cyanobacteria 202 51(25.2) 45.42±3.37 43.00±3.19 0.085
Firmicutes 2012 384(19.1) 312.25±30.54 300.75±25.39 0.327
Gemmatimonadetes 15 9(60.0) 8.67±0.49 8.58±0.51 0.689
Natronoanaerobium 7 5(71.4) 4.00±0.74 3.42±0.79 0.076
Nitrospira 29 8(27.6) 7.3±0.98 6.5±1.73 0.161
OP10 12 7(58.3) 5.67±1.07 4.58±0.67 0.007
OP9/JS1 12 5(41.6) 4.25±1.14 3.5±1.17 0.125
Planctomycetes 182 26(14.3) 20.00±4.09 17.25±2.22 0.053
Proteobacteria 3170 1002(31.6) 849.75±70.62 837.58±85.72 0.708
Spirochaetes 150 36(24.0) 33.75±2.93 32.67±2.99 0.380
Synergistes 19 5(26.3) 5.00±0.00 5.00±0.00 1.000
TM7 45 9(20.0) 8.83±0.58 8.25±1.29 0.166
Verrucomicrobia 78 36(46.1) 28.33±3.92 25.75±3.05 0.085
Others(o5OTUs) 250 53(21.2) 46.35±9.37 37.67±6.35 0.173
Unclassified 329 37(11.2) 32.92±1.83 31.25±3.14 0.126
Total 8741 2269(26.0) 1916.6±52.03 1864.1±57.25 0.028
Abbreviations:aCO,ambientCO;eCO,elevatedCO;OTU,operationaltaxonomicunit.
2 2 2 2
BoldfaceindicatessignificantlychangedphylotypesoralldetectedOTUs.
Table2 PhylotypesdetectedbyPhyloChipatdifferenttaxonomiclevels
Domain Phylum Class Order Family Subfamily
Totalno.detectedphylotypes 2 45 55 99 164 190
SharedataCO andeCO 2 44 52 97 163 188
2 2
OnlydetectedataCO 0 1 2 1 1 2
2
OnlydetectedateCO 0 0 1 1 1 0
2
for PhyloChip signal intensity data. Overall, the
majority of the samples from eCO and aCO were
2 2
distributed in different parts of the data space,
although there was some overlap. Eight of 12 aCO
2
sampleswereseparatedwellfromtheeCO samples,
2
but four other aCO samples seemed to be clustered
2
closertotheeCO thantheaCO samples(Figure1).
2 2
Based on the Binomial index (Anderson and Millar,
2004), three non-parametric, multivariate statistical
tests, analysis of similarities, ADONIS and multi-
response permutation procedure, showed signifi-
cant (P¼0.007, 0.046 and 0.018, respectively)
differences between microbial communities at
aCO and eCO . The results indicated that the
2 2
overall taxonomic composition and structure of soil
microbial communities was altered at eCO .
2
Relationshipsbetweenmicrobialcommunitiesandsoil
Figure1 DetrendedcorrespondenceanalysisofPhyloChipdata
and plant properties
for both aCO and eCO samples. Only OTUs (a total of 2269)
To link the taxonomic structure of microbial com- 2 2
detectedinthreeormoresamplesoutof12ataCO oreCO were
2 2
munitieswithsoilandplantproperties,Manteltests analyzed.
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Table3 Relationshipsofmicrobialphylotypes(OTUs)detectedattheclasslevelbyPhyloChiptosoilandplantvariablesrevealedby
partialManteltest
Inassociationwith:Controlling Soila Plantb
Plantb Soila
Phylum Class OTUno. M P M P
r r
Alldetected 2269 0.166 0.091 0.082 0.227
Acidobacteria Acidobacteria-4 10 0.075 0.272 0.283 0.046
Bacteroidetes KSA1 1 0.083 0.262 0.230 0.071
Unclassified 8 0.039 0.306 0.144 0.053
Caldithrix Unclassified 2 0.122 0.187 0.271 0.040
Chlamydiae Chlamydiae 2 0.069 0.058 (cid:2)0.003 0.478
Chlorobi Chlorobia 11 0.143 0.088 0.096 0.195
Chloroflexi Chloroflexi-3 2 0.168 0.106 0.192 0.069
Chloroflexi-4 2 0.138 0.127 0.213 0.063
Dehalococcoidetes 7 0.062 0.289 0.243 0.065
Unclassified 6 (cid:2)0.022 0.495 0.309 0.059
Coprothermobacteria Unclassified 1 0.112 0.196 0.194 0.07
Crenarchaeota C1 12 0.077 0.258 0.455 0.012
Thermoprotei 2 0.085 0.261 0.455 0.009
Cyanobacteria Cyanobacteria 48 0.147 0.145 0.315 0.027
Deferribacteres Deferribacer 1 0.053 0.098 (cid:2)0.057 0.919
Dictyoglomi Dictyoglomi 1 0.158 0.174 0.423 0.029
DSS1 Unclassified 1 0.174 0.095 0.213 0.067
Firmicutes Catabacter 7 0.131 0.162 0.249 0.060
Symbiobacteria 2 0.154 0.144 0.354 0.023
Unclassified 17 0.124 0.220 0.245 0.063
Lentisphaerae Unclassified 3 0.178 0.084 0.212 0.065
Marinegroup-A mgA-1 2 0.299 0.054 0.555 0.014
OD1 OP11-5 1 0.172 0.038 0.111 0.152
OP10 Unclassified 4 0.316 0.015 0.049 0.298
OP3 Unclassified 3 0.132 0.076 0.040 0.282
OP8 Unclassified 1 (cid:2)0.177 0.920 0.329 0.039
OP9JS1 OP9 2 0.121 0.138 0.195 0.064
Proteobacteria Gammaproteobacteria 330 0.326 0.002 0.031 0.357
Unclassified 9 0.027 0.392 0.181 0.060
Spirochaetes Spirochaetes 36 0.092 0.212 0.257 0.045
SR1 Unclassified 1 0.072 0.265 0.452 0.020
Synergistes Unclassified 5 0.085 0.218 0.260 0.030
Thermodesulfobacteria Thermodesulfobacteria 1 0.049 0.349 0.249 0.056
Thermotogae Thermotogae 1 0.182 0.078 0.103 0.184
TM6 Unclassified 1 0.090 0.264 0.416 0.035
TM7 Unclassified 4 0.161 0.101 0.227 0.068
Unclassified Unclassified 37 0.160 0.150 0.218 0.068
WS3 Unclassified 2 0.055 0.303 0.166 0.089
Abbreviation:OTU,operationaltaxonomicunit.
aSelectedsoilvariablesincludesoil%Natadepthof10–20cm(N10–20),soil%CandNatadepthof10–20cm(SCN10–20),soilpH,nitrification
(mgkg(cid:2)1day(cid:2)1)andnetNmineralization(mgkg(cid:2)1day(cid:2)1).
bSelectedplantvariablesincludetotalrootbiomass(TRB),speciescountfrom%cover(SCFPC),abovegroundpercentagecarbon(APC),fineroots
atadepthof0–20cm(FR0–20)andtotalbiomass(TB).
OnlyclasseswithP-valueso0.10tosoilorplantvariableshavebeenlisted.
BoldfaceindicatessignificantlychangedphylotypesoralldetectedOTUs.
and canonical correspondence analysis were per- (mgkg(cid:2)1day(cid:2)1) were selected from 20 soil para-
formed.ByusingtheBioENVprocedure(Clarkeand meters (Supplementary Table S2).
Ainsworth, 1993), five plant variables, including Based on the above selected sets of plant and soil
total root biomass (TRB), species count from % variables, partial Mantel tests were initially
cover (SCFPC), aboveground percentage carbon performed to correlate the microbial community
(APC), fine roots at a depth of 0–20cm (FR0–20) measuredbythesignalintensityofalldetected2269
and total biomass (TB), were selected from 24 plant OTUswiththoseenvironmentalfactors,andsuchan
parameters (Supplementary Table S1). Similarly, analysis showed that the microbial community on
five soil variables, including soil %N at a depth of the whole was not correlated significantly with the
10–20cm (N10–20), soil C/N ratio at a depth of soil variables (P¼0.091) or plant variables
10–20cm (SCN10–20), soil pH, nitrification rate (P¼0.227) (Table 3). Then, we examined the
(mgkg(cid:2)1day(cid:2)1) and net N mineralization rate correlations of the plant or soil properties with
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specific microbial populations at different taxo-
nomic levels (phylum, class, order, family and
subfamily). At the phylum level, 14 phylotypes
significantly (Po0.05) correlated with the soil
or/and plant properties. For example, there was a
significant (P¼0.011) correlation between Cre-
narchaeota and the selected plant variables, and a
significant (P¼0.037) correlation between Proteo-
bacteriaandtheselectedsoilvariables(Supplemen-
tary Table S3). At the class level, 16 classes were
significantly (Po0.05) correlated with the soil or/
and plant characteristics. For example, g-Proteobac-
teria and OP10 were significantly (P¼0.002 and
0.015,respectively)correlatedwiththeselectedsoil
variables, whereas Cyanobacteria and Spirochaetes Figure 2 Variation partition analysis of the effects of CO, soil
2
were significantly (P¼0.027 and 0.045, respec- andplantvariablesonthephylogeneticstructureofsoilmicrobial
tively) correlated with the selected plant variables communities. The BioENV procedure was used to identify
common sets of soil and plant variables important to the
(Table3).Also,thereweresignificant(P¼0.012and
microbial community. The same sets of soil or plant variables
0.009) correlations between the microbial commu-
wereusedforvariationpartitionanalysisandpartialManteltests
nity and the selected plant properties for both (Table3;SupplementaryTableS3andSupplementaryTableS4).
archaeal classes, C1 and Thermoprotei, respectively The concentrations of CO are 368 p.p.m. for ambient and 560
2
(Table 3). Similarly, 48 families were detected to be p.p.m.forelevatedenvironments;soilvariablesincludedsoil%N
atadepthof10–20cm(N10–20),soilCandNratioatadepthof
correlated with the plant or soil properties (Supple-
10–20cm (SCN10–20), soil pH, nitrification rate (mgkg(cid:2)1day(cid:2)1)
mentary Table S4). For example, the signal inten- and net N mineralization rate (mgkg(cid:2)1day(cid:2)1); plant variables
sitiesofAnaplasmataceaefroma-Proteobacteriaand included total root biomass (TRB), species count from % cover
Spirochaetaceae from Spirochaetes had significant (SCFPC), aboveground percentage carbon (APC), fine roots at a
depthof0–20cm(FR0–20)andtotalbiomass(TB).
(P¼0.019and 0.046,respectively) correlationswith
the selected plant variables, and those of Entero-
bacteriaceaeandVibrionaceaefromg-Proteobacteria tionsbetweenCO andsoilvariables,CO andplant
2 2
had significant (P¼0.001 and 0.004, respectively) variables, and soil and plant variables, and among
correlations with the selected soil variables, CO , soil and plant variables, were 0.1%, 2.4%,
2
whereas Erysipelotrichaceae from Mollicutes was 0.0%and2.8%,respectively(Figure2).Inaddition,
significantly correlated with both soil (P¼0.038) 45.3% of the variation remained unexplained
and plant (P¼0.025) properties (Supplementary (Figure 2). The above statistical analyses suggest
Table S4). In addition, five unclassified classes and that CO has a direct effect on the microbial
2
29unclassifiedfamiliesweresignificantly(Po0.05) community, and that both soil and plant properties
correlated with the selected soil or plant variables, are almost equally important for shaping microbial
respectively, suggesting that soil and plant factors communities through indirect CO effects in this
2
may also largely shape taxonomically uncharacter- grassland ecosystem.
ized microorganisms (Table 3 and Supplementary
Table S4).
Variation partition analysis (Ramette and Tiedje, Significantly changed and unique OTUs
2007) was then used to assess the contribution of ToexamineeffectsofeCO onmicrobialcommunity
2
CO , soil and plant properties to the taxonomic composition,bothsignificantlychangedandunique
2
structure of microbial communities with the same OTUs were identified. Among 2269 OTUs detected,
selected variables (Figure 2). When the plant and 2075 were shared by aCO and eCO samples, and
2 2
soil variables were held constant, there was a 194 unique OTUs were only detected at aCO (123)
2
significant (P¼0.037) correlation between commu- oreCO (71),respectively.For those shared OTUs,a
2
nity structure and CO ; when plant variables and responseratiowascalculatedforeachOTUbasedon
2
CO were held constant, there was a significant its signal intensity. A total of 194 OTUs were
2
(P¼0.048) correlation between community struc- significantly (Po0.05) decreased and only 13 were
ture and soil variables; and when soil variables and significantly (Po0.05) increased at eCO (Table 4).
2
CO were held constant, the plant variables did not Most phyla, including relatively abundant ones (for
2
show a significant (P¼0.082) correlation with example,Crenarchaeota,Acidobacteria,Chloroflexi,
microbial community. The single variable CO was Planctomycetes, Verrucomicrobia), did not have
2
able to independently explain 5.8% of the variation OTUs detected with increased signal intensities at
observed, which was the second largest contributor eCO , and only a few phyla (for example, Actino-
2
based on all 11 individual variables. Five soil bacteria, Bacteroidetes, Firmicutes, Proteobacteria)
variables could independently explain 22.1% of hadOTUswithbothincreasedanddecreasedsignal
the variation, and five plant variables could explain intensities at eCO (Table 4), which is consistent
2
21.5% of the variation (Figure 2). Also, the interac- withthegeneraltrendthattherichnessdecreasedat
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Table 4 Numbers of shared OTUs detected at both aCO and five phyla, including one archaeal phylum
2
eCO2 based on the hybridization signal intensity and unique (Crenarchaeota) and four bacterial phyla (Chloroflexi,
OTUsdetectedonlyataCO2oreCO2 OP10, OP9/JS1, Verrucomicrobia), showed signifi-
cantly (Po0.05) decreased signal intensities, but
Phylum SharedOTUs UniqueOTUs
most abundant phyla (for example, Proteobacteria,
Firmicutes, Actinobacteria, Bacteroidetes, Acido-
Decrese–eCO Increase–eCO aCO eCO
2 2 2 2
bacteria) remained unchanged at eCO (Figure 4).
2
A further examination of those significantly chan-
Crenarchaeota 12 0 0 0
Euryarchaeota 1 1 1 1 ged phyla showed that those changes occurred in
Acidobacteria 15 0 3 2 some specific microbial groups at the class or lower
Actinobacteria 10 1 26 17 levels. In the phylum of Chloroflexi, a significant
Bacteroidetes 4 2 8 9
decrease of signal intensities at eCO was observed
Chlorobi 1 0 0 0 2
Chloroflexi 11 0 5 0 in three orders (Chloroflexi-1a, 1b, 1f) of the class
Cyanobacteria 4 1 4 0 Anaerolineae, and the class of Dehalococcoidetes,
Firmicutes 29 2 25 11 whereas the signal intensities of other classes (for
Gemmatimonadetes 2 0 0 0
example, Chloroflexi-3, Chloroflexi-4, Thermomi-
Natronoanaerobium 0 0 1 0
crobia)didnotchangesignificantly(Supplementary
Nitrospira 4 0 0 0
OP10 2 0 2 0 Figure S2A). In the phylum of Verrucomicrobia, all
OP9/JS1 3 0 0 0 significantchangesappearedtooccurintheorderof
Planctomycetes 9 0 6 1 Verrucomicrobiales from the class of Verrucomicro-
Proteobacteria 55 6 33 29
biae, in which three families (Verrucomicrobiaceae,
Spirochaetes 2 0 0 0
Synergistes 1 0 0 0 Verrucomicrobia subdivision-3, Verrucomicrobia
TM7 0 0 0 0 subdivision-7) and an unclassified phylotype had
Verrucomicrobia 16 0 4 1 significantly (Po0.01) decreased signal intensities,
Others(o5OTUs) 6 0 3 0
although the other two families (Verrucomicrobia
Unclassified 7 0 2 0
subdivision-5 and Xiphinematobacteraceae) de-
Total 194 13 123 71
tected did not show significant changes in signal
Abbreviations: aCO, ambient CO; eCO, elevated CO; OTU, intensity at eCO (Supplementary Figure S2B).
2 2 2 2 2
operationaltaxonomicunit. Crenarchaeota is an archaeal phylum showing
Increase–CO or Decrease–eCO indicates the signal intensity of an
2 2 significantly (Po0.01) decreased signal intensities
OTUwassignificantlyhigherorlowerateCO,respectively.
2 at eCO , and such decreases were observed in three
2
orders (C1a, C1b, Cenarchaeales) from two classes
eCO . The signal intensities of 6 and 56 OTUs were (C1 and Thermoprotei) (Supplementary Figure
2
significantly (Po0.05) increased and decreased, S3A). In addition, significant decreases of signal
respectively, in Proteobacteria. Specifically, two intensity were seen in two less characterized phyla
OTUs were increased and 12 decreased in (OP10 and OP9/JS1), with one from an unclassified
a-Proteobacteria, 2 and 2 in b-Proteobacteria, 1 and class in OP10 (Supplementary Figure S3B) and the
2ine-Proteobacteria,and1and7ing-Proteobacteria, other from an unclassifiedorderof JS1classinOP9/
respectively, but all 31 OTUs derived from JS1 (Supplementary Figure S3C).
d-Proteobacteria were decreased at eCO (Figure 3). Althoughsignificantchangeswerenotobservedat
2
Similarly, 29 and 2 (OTU3497 and OTU3254) OTUs eCO for the most abundant phyla at the phylum
2
were significantly (Po0.05) decreased and in- level based on summed intensities, such signifi-
creased, respectively, in Firmicutes, which were cancesweredetectedattheclassorlowertaxonomic
mostly derived from two classes, Clostridia and levelsforsomephyla.InthephylumProteobacteria,
Bacilli (Supplementary Figure S1). Among 194 the signal intensity of the AMD clone order of
unique OTUs, 123 and 71 were from aCO and d-Proteobacteria was significantly (Po0.05) de-
2
eCO , respectively, and those OTUs were largely creased although no significant changes were de-
2
derived from the most abundant phyla, such as tected at the class level (Supplementary Figure S4).
Proteobacteria, Firmicutes and Actinobacteria In the phylum Firmicutes, the signal intensities of
(Table4andSupplementaryTableS5).Theanalysis the family Syntrophomonadaceae in the order of
of significantly changed and unique OTUs further Clostridiales and an unclassified order in the class
confirms that the phylogenetic composition of soil of Clostridia significantly (Po0.05) decreased at
microbial communities changed in response to eCO . eCO , as did an unclassified phylotype (Po0.01),
2 2
although no significant changes were observed in
Significantly changed microbial populations at eCO other phytolypes (for example, Bacilli, Mollicutes)
2
To understand what specific microbial populations (Supplementary Figure S5). Also, three groups of
maybeaffectedbyeCO ,wemappedOTUsdetected Actinobacteria showed significantly decreased
2
to microbial populations at the phylum or lower signal intensities at eCO , which included the
2
levels, and significantly changed populations were order Acidimicrobiaceae and an unclassified
identified by response ratio based on PhyloChip phylotype in the class Acidimicrobiales; the order
hybridization signal intensity. At the phylum level, BifidobacteriaceaeintheclassBifidobacterialesand
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Figure3 SignificantlychangedOTUsinthephylumofProteobacteriaateCO byusingtheresponseratiomethod(Luoetal.,2006)at
2
95%confidenceinterval.
an unclassified phylotype at the phylum level, and Discussion
interestingly, no significant changes in signal in-
tensity were observed in the largest class Actino- The long-term sustainability of ecosystem produc-
mycetales (Supplementary Figure S6). In addition, tivityrequiresdetailedknowledgeofitsbiodiversity
nosignificantchangeswereobservedinthephylum coupled to profound understanding of its function-
of Bacteroidetes (Supplementary Figure S7) or ing. To better understand the implications of eCO
2
Acidobacteria even at the class, order or family on microbial communities, we used PhyloChip to
level (Supplementary Figure S8). Those results comprehensively survey the richness, composition
indicate that eCO significantly affected some and structure of soil microbial communities in the
2
specific microbial populations at different taxo- BioCON grassland. Our results showed that eCO
2
nomic levels, such as phylum, class, order and significantly altered the microbial community
family, and those phylotypes generally appeared to diversity, composition and structure, especially for
have decreased signal intensities at eCO . particular microbial populations at the OTU level.
2
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Figure4 AveragePhyloChiphybridizationsignalintensitiesforaCO andeCO samplesatthephylumlevel.Significancewastestedby
2 2
responseratios(Luoetal.,2006).***Po0.01;**Po0.05.
Such microbial population changes were signifi- altered the Actinobacterial community structure
cantly correlated with soil and plant properties. butnotitsdiversity(Piaoetal.,2008).Bacteroidetes
This study provides a comprehensive survey of are the fourth most prevalent group of bacteria
themicrobialrichnessandcompositionofgrassland detected in this study, with three major classes
soil microbial communities. Previous studies with (Bacteroidetes, Flavobacteria, Sphingobacteria).
16S rRNA-based analyses using clone libraries Acidobacteria are among the most dominant phyla
(Janssen, 2006; Lesaulnier et al., 2008), microarrays in soil-borne microbial communities, and generally
(for example, PhyloChip) (Cruz-Martinez et al., areclassifiedintoeightclasses(Handelsman,2004).
2009; DeAngelis et al., 2009; Yergeau et al., 2009), The diversity of Acidobacteria in soil was recently
pyrosequencing (Roesch et al., 2007; Fulthorpe examined using different approaches, and a higher
et al., 2008; Campbell et al., 2010; Eilers et al., proportion of Acidobacteria was observed in bulk
2010;Urozetal.,2010)andotherapproaches(Drigo soil than in rhizosphere soil (Kielak et al., 2008).
et al., 2007, 2008, 2009, 2010; Feng et al., 2009) Therefore, this study provides a comprehensive
show that soil microbial communities are highly survey of the richness and composition of soil
diverse and complex. In this study, 2269 OTUs microbial communities at this grassland ecosystem.
affiliated 45 phyla, 55 classes, 99 orders, 164 Elevated atmospheric CO may affect soil micro-
2
families and 190 subfamilies were detected. Proteo- bial communities in both direct and indirect ways.
bacteria was the most well-represented phylum, In a previous study, soil CO flux increased
2
with a-, b-, d-, g- and e-Proteobacteria, as well as 0.57mmolm(cid:2)2s(cid:2)1 or 16% on average at eCO
2
unclassifiedclasses,detected.Thisgroupofbacteria conditions as compared with aCO conditions in
2
has considerable morphological, physiological and the BioCON site (Craine et al., 2001). Also, a recent
metabolicdiversity,whichareofgreatimportanceto studyinthesamesiteshowedthattheabundanceof
global carbon, nitrogen and sulfur cycling (Kersters key genes involved in microbial C and N fixation,
etal.,2006).Firmicutesweredetectedasthesecond and labile C degradation, was significantly in-
most prevalent phylum in terms of the number of creased at eCO (He et al., 2010b). Those results
2
OTUs, and Bacilli, Clostridia and Mollicutes were suggestthateCO maydirectlyimpactsoilmicrobial
2
found to be major classes in this grassland ecosys- communitystructureandfunction.However,asCO
2
tem. Some previous cloning analyses may under- concentrationsintheporespaceofsoilgenerallyare
estimate this group as cells or spores are known to between 2000 and 38000 p.p.m., much higher than
be difficult to lyse during DNA extraction (Janssen, thoseintheatmosphereevenunderaCO condition,
2
2006). The members of the Actinobacteria phylum the direct effects of eCO on soil microbial commu-
2
are a group of Gram-positive bacteria that have an nities may be negligible compared with potential
important role in organic matter turnover and indirect effects, such as increased plant carbon
carbon cycling, such as decomposition of cellulose inputs to soil and changes in soil properties (Drigo
and chitin, and Actinomycetales and Acidimicro- et al., 2008). The data presented here reflect this
bialeswerefoundtobemajorclassesintheBioCON idea:CO aloneexplained5.8%ofthetotalvariation
2
site. A previous study showed that long-term of microbial community structure, compared with
organic and inorganic amendments significantly soilvariablesat22.1%andplantvariablesat21.5%.
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Also, eCO significantly increased plant productiv- populations, such as Chloroflexis and Cyanobacteria.
2
ity, whole-plot total N, soil pH and soil moisture, Indeed, a decrease in the signal intensity of those
anddecreasedwhole-plotplantN,abovegroundand phyla was observed in this study. pH has been
belowground N concentrations. The results suggest considered an important factor affecting the diver-
eCO may directly and indirectly affect soil micro- sity and structure of soil microbial communities
2
bial communities, and the indirect effects appear to (Fierer and Jackson, 2006), and our Mantel analysis
make more of a contribution to shaping the soil showed a significant correlation between soil prop-
microbial communities. erties, including pH and g-Proteobacteria or OP10.
Effects of eCO on plant and soil properties are In this study, soil pH was B6.2 in aCO plots and it
2 2
expectedtomodifytaxonomicmicrobialcommunity significantly increased to B6.5 in eCO plots,
2
composition and structure, and regulate ecosystem suggesting a possible shift of microbial community
functioning. First, it is indicated by differential composition and structure. Therefore, our results
responses of soil microbial populations to eCO . indicate that both soil and plant properties, such as
2
Increases in soil carbon, coupled to an increase in soil pH, moisture and plant biomass, significantly
cellulolyticandchitinolyticactivities,werenotedto affect the microbial richness, composition and
alter the availability of soil substrates for microbial structure, which may determine or modify ecosys-
metabolism (Larson et al., 2002; Phillips et al., tem functioning.
2002). Previous studies showed increases in the The central hypothesis of this study was that, at
abundance of Actinobacteria and Bacteroidetes at eCO , an increase in plant biomass (Reich et al.,
2
eCO (Sait et al., 2006; Lesaulnier et al., 2008). 2006)andsoilcarboninputs(Adairetal.,2009),and
2
However, we did not see significant changes in the associated microenvironmental changes (Reich,
total signal intensities for Actinobacteria, Bacteroi- 2009; He et al., 2010b), would stimulate microbial,
detes or other most abundant phyla at the phylum especially bacterial growth, which would lead to
level in response to eCO . In a-Proteobacteria, a significant changes in the richness, composition,
2
significant increase in the abundance of OTUs structure and function of soil microbial commu-
related to Rhodobium and a significant decrease in nities. Previous studies of effects of eCO on soil
2
the abundance of OTUs related to Bradyrhizobium microbial communities showed variable responses.
were detected in the trembling aspen FACE study Forexample,astudyconductedatatremblingaspen
(Lesaulnier et al., 2008), and a recent study showed FACE experiment site in Wisconsin, USA, showed
a stimulation of purple phototrophic a- and b- an increase in heterotrophic decomposers and a
Proteobacteria in a flooded paddy soil by eCO decrease in nitrate reducers of the domain bacteria
2
(Feng et al., 2009), which are generally consistent and archaea, although the total bacterial abundance
withthisstudy.Also,thepreferenceofAcidobacter- didnotchange(Lesaulnieretal.,2008).Bycontrast,
iainbulksoilhasbeensuggestedtobearesultofthe no detectable effects on microbial community
oligotrophic lifestyle for many members of this structure, microbial activity, potential soil N miner-
phylum (Fierer et al., 2007). A higher input of alization or nitrification rates were observed at a
organicmatterintosoilateCO maybefavorablefor sweetgum FACE experiment in Tennessee, USA
2
carbon polymer-degrading or fast-growing microor- (Austinetal.,2009).Fortestingourcorehypothesis,
ganisms, which presumably outcompete Acidobac- thisstudyhadseveralstrengths:(i)Itwasconducted
teria. If true, the signal intensity of Acidobacteria at a well-designed BioCON experimental site, with
may remain unchanged or decrease at eCO , which 12 replicates for each CO condition, so that the
2 2
wasobservedinthisstudy.Inaddition,adecreasein effectsofeCO onsoilmicrobialcommunitiescould
2
the abundance of Crenarchaea and Verrucomicrobia berobustlyexamined;(ii)PhyloChipisconsidereda
at eCO was observed previously (Lesaulnier et al., powerful tool for a comprehensive survey of micro-
2
2008), which is consistent with our observation in bial richness and composition (DeAngelis et al.,
thisstudy.MembersofVerrucomicrobiaarereported 2009;Rastogietal.,2010),whichmayovercomethe
to be negatively impacted by soil moisture (Buckley limitations of cloning-based approaches and (iii)
and Schmidt, 2001), which has been shown to this study was conducted in a grassland ecosystem
increase at eCO in the BioCON site (Reich et al., with defined plant species, which minimizes the
2
2001; He et al., 2010b) and other sites (Zavaleta effects of plant diversity and composition on soil
et al., 2003), which is largely due to reduced microbial communities. Indeed, consistently with
stomatal conductance of plants (Kandeler et al., some previous studies in grasslands (Schortemeyer
2008). Second, significant correlations are observed et al., 1996; Drissner et al., 2007), our results
between environmental factors and microbial indicated that eCO had significant effects on the
2
communities. A negative impact of increased con- richness, composition and structure of soil micro-
centrations of organic matter on the growth of bial communities. First, such changes are reflected
Acidobacteria was observed previously (Stevenson in a decrease in richness, which generally agrees
et al., 2004), and consistently, Acidobacteria-4 with previous studies (Begon et al., 1996; Hughes
populations were found to be correlated signifi- et al., 2001). Similarly, a significant decrease in
cantlywithplantvariablesinthisstudy.Also,more richness was observed in some phyla (for example,
carbon input into soil may affect autotrophic Chloroflexi,OP10).Second,more OTUswere found
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