RESEARCH ARTICLE
High-density PhyloChip profiling of stimulated aquifer
microbial communities reveals a complex response to acetate
amendment
Kim M. Handley1, Kelly C. Wrighton1, Yvette M. Piceno2, Gary L. Andersen2, Todd Z. DeSantis2,
Kenneth H. Williams2, Michael J. Wilkins3, A. Lucie N’Guessan4, Aaron Peacock5, John Bargar6,
Philip E. Long7 & Jillian F. Banfield1,2
1
Department of Earth and Planetary Science, University of California, Berkeley, CA, USA; 2Earth Sciences Division, Lawrence Berkeley National
Laboratory, Berkeley, CA, USA; 3Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA; 4Department of
Microbiology, University of Massachusetts, Amherst, MA, USA; 5Haley & Aldrich, Oak Ridge, TN, USA; 6Molecular Environmental and Interface
Science, Stanford Synchrotron Radiation Lightsource, Menlo Park, CA, USA; and 7Energy and Environment Directorate, Pacific Northwest National
Laboratory, Richland, WA, 99353, USA
MICROBIOLOGY ECOLOGY
Correspondence: Jillian F. Banfield,
Department of Earth and Planetary Science,
University of California, Berkeley, CA 94720,
USA. Tel.: 1 510 642 9488;
fax: 1 510 643 9980;
e-mail: [email protected]
Present addresses: A. Lucie N’Guessan,
Safety, Security, Health, and Environment,
ExxonMobil Upstream Research Company,
Houston, TX, 77252, USA;
Philip E. Long, Earth Sciences Division,
Lawrence Berkeley National Laboratory,
Berkeley, CA, 94720, USA.
Received 29 October 2011; revised 27
February 2012; accepted 9 March 2012.
Final version published online 13 April 2012.
DOI: 10.1111/j.1574-6941.2012.01363.x
Editor: Tillmann Lueders
Keywords
PhyloChip; microarray; subsurface; aquifer;
acetate; bioremediation.
Abstract
There is increasing interest in harnessing the functional capacities of indigenous microbial communities to transform and remediate a wide range of environmental contaminants. Information about which community members
respond to stimulation can guide the interpretation and development of remediation approaches. To comprehensively determine community membership
and abundance patterns among a suite of samples associated with uranium
bioremediation experiments, we employed a high-density microarray (PhyloChip). Samples were unstimulated, naturally reducing, or collected during Fe
(III) (early) and sulfate reduction (late biostimulation) from an acetate reamended/amended aquifer in Rifle, Colorado, and from laboratory experiments
using field-collected materials. Deep community sampling with PhyloChip
identified hundreds-to-thousands of operational taxonomic units (OTUs) present during amendment, and revealed close similarity among highly enriched
taxa from drill core and groundwater well-deployed column sediment. Overall,
phylogenetic data suggested that stimulated community membership was most
affected by a carryover effect between annual stimulation events. Nevertheless,
OTUs within the Fe(III)- and sulfate-reducing lineages, Desulfuromonadales
and Desulfobacterales, were repeatedly stimulated. Less consistent, co-enriched
taxa represented additional lineages associated with Fe(III) and sulfate reduction (e.g. Desulfovibrionales; Syntrophobacterales; Peptococcaceae) and autotrophic sulfur oxidation (Sulfurovum; Campylobacterales). Data implies complex
membership among highly stimulated taxa and, by inference, biogeochemical
responses to acetate, a nonfermentable substrate.
Introduction
Research at the Rifle Integrated Field Research Challenge
(IFRC) site, Colorado, USA, tests the efficacy of using
indigenous microbial communities for the remediation of
low-level uranium contamination. Experiments consistently demonstrated reductive immobilization of uranium
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from groundwater during organic carbon (acetate) stimulation and Fe(III) and sulfate reduction (Anderson et al.,
2003; Williams et al., 2011), as illustrated in Fig. 1. Similar results have been reported elsewhere (e.g. Finneran
et al., 2002a, b; Akob et al., 2008). In a number of
field-scale uranium bioremediation studies, including at
Rifle, Geobacteraceae were identified as the dominant
FEMS Microbiol Ecol 81 (2012) 188–204
189
PhyloChip profiling of subsurface microbial communities
Fig. 1. Characteristic geochemical profiles of Rifle groundwater
during acetate amendment illustrating microbial Fe(III) (IR) and sulfate
(SR) reduction, forming aqueous Fe(II) and sulfide, and reductive
immobilization of aqueous U(VI). As sulfate reduction becomes
increasingly dominant, Fe(II) is partly removed from solution by sulfide
and precipitated as FeS. Curves represent geochemical data collected
over 120 days during first-time amendment. Data collected from
eight wells (D01-8, see Williams et al., 2011; Fig. 1 for a plot map)
were averaged, and time series were fitted with locally weighted
scatterplot smoothing (LOESS) curves. Note, the rate of transition
between the major TEAPs is greatly enhanced where the system has
been stimulated in the previous year.
Fe(III)-reducing bacteria (IRB) (Holmes et al., 2002;
Anderson et al., 2003; North et al., 2004) and were implicated in uranium reduction, as several Geobacter species
are known to enzymatically reduce U(VI) (e.g. Lovley
et al., 1991; Shelobolina et al., 2008). Other phylogenetically diverse bacteria, including certain sulfate-reducing
bacteria (SRB), also reduce U(VI) (Lovley & Phillips,
1992; Suzuki et al., 2004; Wall & Krumholz, 2006) and
likely contribute to U(VI) reduction in contaminated
environments (e.g. Nevin et al., 2003; North et al., 2004).
It follows that many organisms, some of which may be
present at low abundance levels, could have the potential
to reduce U(VI) in the Rifle aquifer. However, relatively
little is known about the extent and identity of these and
other stimulated taxa, or the range of biogeochemical
processes that may impact upon bioremediation at Rifle.
The PhyloChip microarray is a cost-effective, 16S rRNA
gene–based method for documenting the presence of
organisms across a wide range of abundance levels and
can provide information about between-sample relative
taxa abundances at the family level. The coverage level
provided by the PhyloChip is comparable to that obtainable with 454 pyrosequencing of amplified 16S rRNA
genes (e.g. DeAngelis et al., 2011), and phylotypes identified using the traditional clone library method have been
shown to almost exclusively represent a subset of those
identified by PhyloChip (DeSantis et al., 2007). The G2
FEMS Microbiol Ecol 81 (2012) 188–204
PhyloChip microarray has been used to investigate complex community responses to external stimuli (e.g. Tsiamis
et al., 2008; La Duc et al., 2009; Godoy-Vitorino et al.,
2010), including trends in key bacterial family abundances, such as those of Geobacteraceae, during stimulation of uranium-contaminated soil (Brodie et al., 2006).
A more recent version of the PhyloChip, G3, expands
upon the range of operational taxonomic units (OTUs)
identifiable from just fewer than 9000 to almost 60 000
(Hazen et al., 2010).
Prior to this research, stimulated Rifle groundwater
and sediment bacterial community composition has been
characterized by clone library analysis (using up to 100
clones) and denaturing gradient gel electrophoresis
(DGGE) (Anderson et al., 2003; Chang et al., 2005; Vrionis
et al., 2005; Holmes et al., 2007), which while identifying
the most dominant organisms may have failed to capture
the underlying community structure or flanking (lessabundant) community composition. To further our
understanding of bacterial populations important to bioremediation, we used the G3 PhyloChip microarray to
assess trends in microbial community diversity across a
collection of Rifle sediment and groundwater samples that
had been biostimulated to differing extents and lengths of
time, and to establish the efficacy of bench-top (ex situ)
and field-based (in situ, down-well) incubation experiments as a proxy for biostimulated subsurface sediment.
Specifically, we sought (1) to define the range of taxa
enriched during remediation efforts, in particular those
that may impact on the biogeochemical cycling of Fe, S
and U, and (2) to characterize the similarity and stability
of microbial community composition and structure
across experimental conditions.
Materials and methods
Sample descriptions
The samples used in this study are listed in Table 1 and
represent a collection from various in situ or ex situ
experiments conducted in 2008 and 2009 within, or
using material from, the Rifle aquifer (see site description in Anderson et al., 2003). Samples consist of unamended ‘background’ sediments (BGS08/09); naturally
reduced (NR) and acetate-amended drill-core sediments
(LAS, MAS, HAS); laboratory- and field-based flowthrough column sediments (ECS/Q, ICS/Q); enrichment
cultures of SRB derived from sediment (ECA/L); and
groundwater samples collected during acetate amendment (GW). Each sample type is described below. All
samples were flash-frozen immediately upon collection
and stored at 80 °C. The well gallery used for the 2008
and 2009 stimulation experiments was first amended
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K.M. Handley et al.
190
Table 1. Description of samples analyzed
Sample ID
Sample location
Sample type
Major
TEAP
TEAP Progress
Y
Amendment
Amount of
e donor
Date
BGS08
BGS09
GW T1-3
GW T4-6
NR
LAS
MAS
HAS
ICS
ICQ
ECS T1-3
ECQ T1-3
ECA 1-6
ECL 1-2
Background (UG)
Background (UG)
Well D04
Well D04
Core LQ112 16-18′
Core P106 10′
Core P105 16′
Core P104 19′
Well P104
Well P104
Bench top
Bench top
Bench top
Bench top
Subsurface sediment
Subsurface sediment
Groundwater
Groundwater
Subsurface sediment
Subsurface sediment
Subsurface sediment
Subsurface sediment
In situ sediment column
In situ quartz column
Ex situ sediment column
Ex situ quartz column
Enrichment culture
Enrichment culture
–
–
IR
IR
SR
SR
SR
SR
SR
SR
SR
SR
SR
SR
–
–
Early
Late
Prolonged
Prolonged
Prolonged
Prolonged
Prolonged
Prolonged
Early prolonged
Early prolonged
–
–
–
–
2
2
–
2
2
2
3
3
1
1
1
1
Unamended
Unamended
5–10 days acetate
13–23 days acetate
Ongoing NOM
4 months acetate
4 months acetate
4 months acetate
1 month acetate
1 month acetate
1–3 months acetate
1–3 months acetate
Acetate
Lactate
–
–
Excess, H
Excess, H
–
Limited, L
Limited, M
Excess, H
Excess, H
Excess, H
Excess, H
Excess, H
Excess, H
Excess, H
2008
2009
2008
2008
2009
2008
2008
2008
2009
2009
2009
2009
2009
2009
Background (control) sediments were collected up-gradient, UG, of amendment.
T, time point; IR, Fe(III) reduction; SR, sulfate reduction; NOM, naturally occurring organic matter; L, low; M, moderate; H, high. The year (Y) of
stimulation denotes whether experiments were conducted in portions of the aquifer, or using aquifer materials, that were as follows: 1, pristine
(first-year amendment); 2, stimulated during the previous summer (second-year amendment); 3, stimulated during the last two summers (thirdyear amendment).
during the summer in 2007, and as such constitutes a
prestimulated gallery.
Background sediments were collected in 2008 (BGS08)
and 2009 (BGS09) up-gradient of injection wells from
saturated portions of the aquifer using a backhoe. Acetate
was employed in bench-top and subsurface experiments
to stimulate microbial growth. Concentrations were typically in excess of microbial rates of consumption
throughout the course of field and laboratory stimulation
experiments (see Table 1).
Acetate-stimulated groundwater samples (GW T1-6)
were obtained along a 6-point time course spanning from
early Fe(III) reduction to the onset of sulfate reduction in
2008. Specifically, samples were collected 5, 7, 10, 13, 20,
and 23 days after the addition of acetate to the subsurface
was commenced in July 2008. Acetate was injected continuously from a 50-mM stock solution, which underwent
a dilution of approximately 1 : 10 in groundwater. The
injection process is described in detail by Williams et al.
(2011). Samples were pumped from well D04 and filtered
as described by Wilkins et al. (2009).
Following 110 days of near-continuous acetate injection during the 2008 experiment (Williams et al., 2011),
sediment samples dominated by sulfate reduction were
collected from drill cores (L-HAS). The injected concentration of acetate was increased to 150 mM during sulfate
reduction from days 38 to 110. The subsurface sample
P104-19′ (well ID P104, sample depth 19′) was collected
0.5 m down-gradient; P105-16′, 5 m down-gradient; and
P106-10′, 9 m down-gradient of injection wells. The
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amount of acetate received by these samples decreased
with increasing distance from injection wells.
Further acetate-stimulated sediment samples were
obtained from the aquifer after incubating flow-through
columns in situ (ICS-Q) within well P104, for 1 month
(July–August 2009). During this period, acetate was
injected into the aquifer up-gradient of P104 from a 150mM stock solution, attaining approximately 1 : 10 dilution in groundwater. Cylindrical columns (either 2.5 cm
wide 9 20.3 cm long or 5.1 wide 9 10.2 cm long) were
packed with either fine-grained (< 2 mm) freshly collected background Rifle sediment (BGS09) or dithionite–
citrate–bicarbonate washed (Chang & Jackson, 1957)
quartz sand underlain by a 2-cm-thick layer of fresh Rife
background sediment for microbial inoculation. Flow was
achieved by pumping (acetate-amended) groundwater up
through the column using peristaltic pumps located at
the ground surface. Flow rates corresponded to a pore
water velocity of approximately 1 m day 1, approximately twice the rate of groundwater within the aquifer.
Sediment and quartz were collected from columns upon
sacrifice.
Drilling in 2009 also recovered subsurface sediment
(well ID LQ112, sample depth 16-18′) from a NR sulfidic
region of the aquifer that was putatively stimulated by
autochthonous organic matter. The core was obtained
outside areas previously impacted by acetate amendment.
Laboratory experiments, emulating field studies, utilized ex situ ‘bench-top’ flow-through cylindrical columns
(ECS-Q) (2.5 cm wide 9 15 cm long) that were packed
FEMS Microbiol Ecol 81 (2012) 188–204
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PhyloChip profiling of subsurface microbial communities
with clean quartz sand, underlain by an inoculum of
background (BGS08) Rifle sediment (~ 10% column
volume, < 2 mm fraction) mixed 50 : 50 with quartz
sand. Columns were flushed continuously with anoxic
(99 : 1 N2/CO2) Rifle groundwater that contained
~ 10 mM of naturally occurring sulfate and 15 mM of
added acetate. Flow rates corresponded to a pore water
velocity of 0.5 m day 1. Columns were sacrificed at the
onset of sulfate reduction, after 31 days of incubation,
and during ongoing sulfate reduction, after 56 and
78 days. Both sediment and quartz were collected from
each column.
Fast-growing SRB, as might be expected to occur in
the field in the presence of excess electron donor, were
enriched using a modified minimal (no yeast extract)
Postgate B medium (Postgate, 1984) or Rifle groundwater, both with added vitamins and with minerals (see
Handley et al., 2009 and references therein) and 10 mM
acetate (ECA) or 20 mM lactate (ECL). Media were inoculated with 10% w/v Rifle background sediment, incubated at 30 °C, and subcultured 4–6 times.
DNA extraction and amplification
Genomic DNA was extracted in duplicate from sediments
using the PowerSoilTM DNA Isolation kit (Mo Bio Laboratories, Inc, Carlsbad, CA) and from groundwater and
cultures using the FastDNA® SPIN Kit for Soil (MP Biomedicals, Solon, OH). Near full 16S rRNA gene amplification was undertaken using 8-gradient (annealing
temperatures, 48–58 °C) 25-cycle PCR in order to minimize PCR bias, as described by DeSantis et al. (2007).
Reactions were performed using the general bacterial
primers 27f (5′-AGAGTTTGATCCTGGCTCAG-3′) and
1492r (5′-GGT
TACCTTGTTACGACTT-3′) (Lane, 1991) and Clonetech
Titanium taq (Mountain View, CA), and uracil was
incorporated during fragment synthesis (2 : 1 dTTP/
dUTP). The primers used span the 16S rRNA gene region
used for probe creation (DeSantis et al., 2007). Pooled
products were concentrated to 20 lL by ethanol precipitation with glycogen, and fragment size and quality were
checked by gel electrophoresis.
Probe fragmentation and hybridization
PCR products were fragmented to 50–200 bp using uracil-DNA glycosylase and apurinic/apyrimidinic endonuclease 1 (Affymetrix, Santa Clara, CA). Reaction mixes
were spiked with amplicons from prokaryotic metabolic
genes, yeast genes, and Arabidopsis genes of known concentration (final concentration range: 4.62–651.9 pM) to
serve as internal controls, and contained 500 ng of samFEMS Microbiol Ecol 81 (2012) 188–204
ple amplicons (or between 225 and 372 ng for samples
NR and ECQ T2 r1). Reactions were carried out at 37 °C
for 60 min and inactivated at 93 °C for 2 min. Fragmentation products were terminally biotinylated using the Affymetrix GeneChip DNA Labeling Reagent kit, following
the manufacturer’s instructions. Labeled products were
hybridized to 25-mer 16S rRNA gene probes on custommade GeneChip chips (G3 PhyloChip) using the Hybridization Module (Affymetrix). Reactions were performed
according to the manufacturer’s protocol, with DNA
denaturation at 99 °C for 5 min and hybridization overnight at 48 °C while chips rotated at 60 r.p.m. Hybridized chips were washed and stained in the automated
Affymetrix fluidics station, and fluorescence was measured using the Affymetrix GeneChip Scanner 3000 7G
(see DeSantis et al., 2007). Chip design is described by
DeSantis et al. (2007) and Hazen et al. (2010).
Data treatment
Chip OTUs comprised 37 ± 9.6 SD (or between 2–50)
probe pairs targeting closely related organisms with
97.5% 16S rRNA gene similarity (Hazen et al., 2010).
Following amplicon hybridization to chip, the mean
intensities of all spiked in DNA controls were averaged
for each chip and scaled to 10 000 in the initial treatment
of the data. Background hybridization intensities were
subtracted from probe intensities as follows. Probe pairs
comprised one perfectly matching (PM) probe and one
mismatching (MM) probe with a substitution at central
base number 13 along the 25-mer probe length (Hazen
et al., 2010). Threshold criteria for scoring OTUs as positive are described in detail by Hazen et al. (2010) and are
outlined here. The difference between PM and MM
hybridization intensities, the d score, was determined.
The likelihood that the difference in intensities (d score)
of a given OTU came from a distribution more similar to
positive rather than negative controls was then calculated,
yielding the r score. An OTU was considered present if
(1) at least 18 probe pair signals were counted and (2)
the quartiles of ranked r scores were at least 0.7, 0.95,
and 0.98 for the first, second, and third quartiles, respectively.
OTUs were then assessed against a stringent secondary
criteria that penalized any OTUs likely to be positive
because of probe cross-hybridization. Potentially, crosshybridizing probes were deemed to be those sharing perfect identity among their central 17-mer. Adjusted r
scores (rx) were generated by dividing the number of
external subfamilies that passed the first threshold by the
number of external subfamilies that potentially crosshybridize with specific probes. Subfamilies with a third
quartile rx value of 0.48 were accepted. Subfamilies
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192
were demarcated as OTU groups with 72% similar
heptamers. The means of PM probe hybridization scores,
minus the highest and lowest scores, were used for analyses. Corrected hybridization scores and presence–absence data
are given in the Supporting Information, Data S1.
In analyses comparing the relative abundances of taxa,
OTUs were discounted if probe scores fell below the secondary threshold across all samples. Hybridization scores
were then normalized to total array intensity to adjust for
differences in sample intensities, attributed to differences
in taxa diversity owing to the loss of available hybridization sites for highly abundant taxa in samples with less
even, and typically less rich, communities (a negative
linear trend is observed between summed chip intensities
and maximum intensity values, R2 = 0.92, prior to
normalization to total array intensity). For diversity measures, including presence–absence data, the hybridization
scores of OTUs within individual samples were set to zero
if below the threshold. As zero is a nonstandard hybridization score value, when extraction replicate data were
averaged, if a value was present for only one replicate, the
nonzeroed value was used.
Hybridization scores in PhyloChip have been shown to
directly relate to gene abundance through a positive linear
relationship (DeSantis et al., 2005; Brodie et al., 2007).
However, scores are not quantitative within a sample,
owing to differences in the hybridization efficiencies of
probes. Even so, the relative abundances of individual
taxa are comparable across samples.
Community analyses
Differences in community diversity among samples were
examined with rank abundance curves (rank of OTU vs.
hybridization scores), which graphically portray observed
sample community richness (S = total number of OTUs)
and evenness (slope of line as a representation of the distribution of OTU abundance). Key information from the
curves was summarized as richness and maximum
hybridization score data and portrayed relative to average
background scores (score - average background sediment
score).
Unamended background sediment is used as a baseline
throughout the study to gauge changes in diversity and
the enrichment of taxa-stimulated communities. While
unamended sediment cannot be considered an exact
proxy for unamended groundwater, by applying the same
baseline uniformly, we are still able to compare differences and similarities across stimulated sample types and
determine whether similar taxa are highly abundant in
stimulated sediment and groundwater communities.
Hierarchical clustering and nonmetric multidimensional scaling (NMDS), in PRIMER 6 (PRIMER-E Ltd,
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K.M. Handley et al.
Plymouth, UK), were used to assess clustering patterns
among samples. Both methods utilized Bray–Curtis dissimilarity matrices. Hierarchical clustering was performed
using the group average method. Stress values of 0.1
indicate that NMDS plots are a good representation of
sample relationships in two-dimensional space. Stress is
determined in PRIMER 6 by the goodness of fit of a regression line to samples plotted according to pairwise
distance in the ordination vs. percent similarity in the
Bray–Curtis matrix.
Analysis of similarity (ANOSIM), in PRIMER 6, was used to
test the alternate hypothesis that there are differences
between sample groups. R statistics were calculated using
999 permutations to determine the difference in average
rank dissimilarities between and within groups, based on
Bray–Curtis similarity matrices. Communities were considered different if the R statistic (on a 0–1 scale)
approached 1, moderately overlapping for R statistics near
0.5 and highly overlapping for R statistics near 0. Permutational ANOVA (PERMANOVA) was used to determine the
similarity of extraction replicates by comparing the average dissimilarities between extraction replicates and samples (http://www.stat.auckland.ac.nz/~mja/Programs.htm#
Mine; Anderson, 2001; McArdle & Anderson, 2001). Bray
–Curtis dissimilarities were used for the analysis.
The similarity percentage method, SIMPER, in PRIMER 6
was used to determine the contribution of each OTU to
differences between groups based on average Bray–Curtis
dissimilarities. For comparison, the standard deviations
(SD) of OTU hybridization scores between sample groups
or relative to background were also calculated to gauge
the variation in abundances (as employed by Brodie
et al., 2006). Key taxa were taken as those occurring in
the top 10% of SIMPER contributions and top 100 SDs.
The relative abundances of all taxa, and key taxa determined by SIMPER and SDs, were rendered visually as
heatmaps using the MADE4 v1.22 package (Culhane et al.,
2005) in R (http://www.r-project.org/; Ihaka & Gentleman, 1996). Hybridization scores were scaled by row
(OTU) across all samples, according to the default settings. Specifically, scores for each OTU were adjusted to
values spanning the range of ±3. Samples were grouped
using a correlation metric distance and average linkage
cluster analysis. This method enables comparisons among
samples (columns) for each OTU, but not comparisons
among taxa (rows). The OTU accession numbers for
probe-targeted sequences are given in Table S1.
Given the large number of probes on the PhyloChip,
the phylogenetic assignment of OTUs examined in the
‘key taxa’ heatmap was re-verified by BLAST matches
(Altschul et al., 1990), and by the construction of neighbor-joining and maximum-likelihood phylogenetic trees
with 1000 boot-strap replicates using MEGA v5.0 software
FEMS Microbiol Ecol 81 (2012) 188–204
193
PhyloChip profiling of subsurface microbial communities
(http://www.megasoftware.net; Tamura et al., 2011). Trees
were created using OTU probe-targeted sequences from
GenBank. Neighbor-joining trees employed evolutionary
distances estimated with the maximum composite likelihood method (Tamura et al., 2004). The highest log-likelihood (maximum-likelihood) tree was obtained using the
maximum parsimony method when the number of common sites was < 100 or < 1/4 of the total number of sites,
or using the BIONJ method with MCL distance matrix
when the number of common sites was greater than this
(Tamura & Nei, 1993).
Results
Similarities in bacterial composition and
abundance patterns
OTUs were detected across a range of different phyla in
both stimulated and unstimulated samples, including the
seven major chip targeted phyla (Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Firmicutes, Planctomycetes, and Proteobacteria) and Candidate Divisions
(heatmap in Fig. S1). The heatmap shows that background sediment communities were diverse, with relatively abundant members widely distributed across these
phylogenetic groups, especially in the 2009 collected sediment community (BGS09). Some heterogeneity in the
community compositions of these two samples, which
were collected from different locations within the aquifer,
is evident. Drill-core sediments collected after acetate
amendment (L-HAS), and NR sediment communities,
grouped closely with the background communities, and
displayed a similar broad distribution of enrichment
across the phylogenetic groups. Communities in enrichment cultures were also broadly enriched and clustered
with the HAS and NR. Both acetate and lactate resulted
in enrichment communities with very similar profiles,
although relative abundances were generally much higher
with lactate. In contrast, community abundance patterns
appear to have been much less evenly distributed across
phylogenetic groups in acetate-amended column sediments/quartz (IC and ECS/Q) and groundwater samples.
Even so, removing the enrichment cultures from the heatmap (data not shown) caused HAS to group with the
in situ column communities owing to discernable similarities in composition.
Overall, total community compositions differed primarily by sample type and, to a lesser extent, by time (or
degree of stimulation). Hierarchical clustering (Fig. 2a)
revealed that, at similarities > 96%, communities were separated into four distinct clusters according to the sample
type, similar to the groups observed in the full community
heatmap (Fig. S1). ANOSIM results demark significantly
FEMS Microbiol Ecol 81 (2012) 188–204
different clusters on the NMDS plot (Fig. 2b). The fourth
cluster is not shown in Fig. 2 to better resolve clusters 1–3.
Cluster 4 represents a dominant, but poorly constrained
group of enrichment culture communities and is shown in
Fig. S2. Removing this cluster does not alter the character
of the remaining clusters. ANOSIM global and pairwise R statistics were between 0.841 and 0.959 (P-values < 0.001)
differentiating all four clusters.
Specifically, cluster 1 groups well-sourced samples,
namely GW and field-deployed column (ICQ-S) communities collected during dominant phases of Fe(III) reduction and sulfate reduction, respectively. Communities in
groundwater differ according to earlier and later time
points (GW T1-3 vs. T4-6), while the composition of in
situ column communities differs based on quartz or sediment column matrix. Within cluster 2, ex situ (benchtop) column communities group with the inoculating
background sediment (BGS08) and exhibit a temporal
and column matrix cluster effect. However, the duration
of sulfate reduction appears to be a stronger driver for
clustering than matrix (quartz vs. sediment). In cluster 3,
background (BGS09) and low and moderately stimulated
subsurface sediments (L-MAS) group closely, while NR
and more highly stimulated subsurface communities are
less similar. Cluster 4 comprises sulfate-reducing enrichment culture communities grown with acetate or lactate,
but does not cluster expressly based on electron donor.
To dampen the effect of highly abundant taxa, cluster
analysis using square-root-transformed hybridization
scores was also performed, but results differed only by
slightly higher overall similarity values (data not shown).
Agreement between DNA extraction replicates evident
from hierarchical clustering (Fig. 2a) was confirmed by
average dissimilarity scores between these replicates and
samples, generated by PERMANOVA. Dissimilarity scores
were, on average, 0.48 (±0.1 SD) between replicates and
2.41 (±0.7 SD) between samples.
Community richness and diversity
Overall community diversity was lower in stimulated communities relative to background sediment, reflected by
decreases in taxa number (richness) and decreases in the
evenness of taxa abundance (Fig. 3; for rank abundance
curves, see Fig. S3). Fe(III)-reducing groundwater and sulfate-reducing sediment communities shared a similar
range of richness values, with over twofold lower richness
values relative to background in some samples. Interestingly, diversity increased somewhat in groundwater communities collected in late Fe(III) reduction (T5-6), as
conditions approached the transition to sulfate reduction.
Quartz-colonized communities exhibited lower overall
richness than sediment-associated column communities;
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K.M. Handley et al.
194
(a)
(b)
Fig. 2. Community cluster analysis. (a) Group average hierarchical clustering of OTU data into distinct groups (1–4). Abbreviations: Earlier (E) or
later (L) time points; lower (LA) or higher (HA) acetate; number of years (Y) of amendment the aquifer or aquifer-derived material has undergone
(see Table 1). (b) NMDS of OTU hybridization score data from groups 1–3, depicting two-dimensional separation of samples based on overall
community composition. Shaded areas demark clusters in (a) that differ significantly from one another based on ANOSIM results. Extraction
replicate data are averaged in the NMDS plot, but display identical clustering patterns to unaveraged data.
however, the in situ quartz community exhibited greater
diversity than that of an analogous drill-core sediment
(HAS). As expected, the lowest community richness and
evenness occurred in SRB enrichment cultures.
Richness values for the NR sediment community were
low (319 and 346). This may be partly due to the loading
of less than an optimal amount of DNA onto the chips. As
such, these data were excluded from comparisons in Fig. 3.
Nevertheless, total array hybridization scores were within
the range of other samples, suggesting high abundance of
detected OTUs. Owing to lower DNA, total array-normalized values may overestimate NR OTU relative abundances, but this would not affect the community structure,
nor the identification of dominant taxa (see below).
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Identity of key bacterial taxa enriched during
biostimulation
In order to ascertain the bacteria most responsive to acetate amendment or natural attenuation, changes in OTU
abundances were compared to background communities
and between-sample groups. Results were approximately
comparable using SIMPER and SD methods (Table 2),
and no difference was noted between SIMPER analyses
using untransformed or square-root-transformed data.
The relative abundances of OTUs from enriched lineages
are portrayed within a cluster heatmap (Fig. 4). Results
indicated a notable increase over background and lowacetate sediment levels in OTUs representing or very
FEMS Microbiol Ecol 81 (2012) 188–204
PhyloChip profiling of subsurface microbial communities
195
Fig. 3. Bar chart, with staggered bars showing average richness (S) data and maximum hybridization scores (MHS) relative to (minus)
average background (BGS08/09) values (S = 3497 ± 335; MHS = 14563 ± 47). S and MHS values summarize rank abundance curves. Negative
S and MHS values are indicative of values lower than those in the background sediment communities. The table gives the range of original S
values.
closely related to genera known to reduce Fe(III) and/or
be involved in sulfur redox cycling (Fig. 5).
In particular, OTUs, representing or closely related to
Epsilonproteobacteria known to oxidize (Sulfurovum and
Helicobacteraceae) and/or reduce (Sulfurospirillum) sulfur,
were highly increased in acetate-amended sediment and
groundwater communities over background (Fig. 4).
These bacteria were most enriched in the in situ columns,
which were incubated in a well gallery subject to a third
summer of acetate amendment. The heatmap also shows
fairly abundant Sulfurovum-like OTUs in the 2009, but
not 2008, background sediment.
Deltaproteobacteria lineages known to reduce sulfate
were increased in all stimulated samples (Fig. 4). Of
these, Desulfobacterales were consistently enriched across
all amended samples, excluding enrichment cultures
(Fig. 4 and Table 2). A high degree of enrichment in Desulfobulbaceae, Desulfomicrobiaceae, and Syntrophobacterales
appeared to be less consistent among samples. The Firmicute family, Peptococcaceae, were common only to NR
sediment and communities stimulated under pristine conditions (first-year amendment), in ex situ columns and
enrichment cultures. Peptococcaceae are highly enriched in
cultures using either acetate or lactate as electron donor.
OTUs in the Desulfuromonadales, an order well known
for dissimilatory Fe(III) reduction, were highly increased
in groundwater and column sediments (ICS and ECS T2
FEMS Microbiol Ecol 81 (2012) 188–204
and 3), but decreased in groundwater collected during
late-stage Fe(III) reduction (Fig. 4). Curiously, Desulfuromonadales became increasingly enriched alongside that of
SRB lineages (i.e. Desulfobacterales and Peptococaceae) in
ex situ columns sediments, which were harvested during
early-stage to late-stage sulfate reduction. SIMPER results
suggest that within the Desulfuromonadales, Geobacteraceae and Desulfuromonadaceae were differently enriched,
being each more highly enriched in Fe(III)-reducing
groundwater or sulfate-reducing sediments, respectively
(Table 2). In general, Desulfuromonadales appeared to be
poor colonizers of the quartz matrix in ex situ, but not
in situ columns.
SIMPER and SD analyses (data not shown) indicate
that the 2008 background sediment had higher abundance
of Pseudomonaceae than the 2009 sediment, likely explaining why these communities do not cluster together in full
community dendrogram and NMDS plots (Fig. 2).
Clustering of samples based on highly enriched taxa
(Fig. 4) differs in certain respects to that based on full
community data (Fig. 2 and Fig. S1). In terms of enriched
taxa, moderate- and high-acetate subsurface drill-core sediments more closely resemble in situ columns and groundwater, owing to overall similarities among highly enriched
S-cycling and Fe(III)-reducing lineages. Moreover, ex situ
columns cluster with enrichment cultures, apparently
owing to shared high abundances of Peptococcaceae.
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K.M. Handley et al.
196
Table 2. Elevated taxa in sample groups relative to background sediment communities
Discussion
Observed richness, diversity, and
co-enrichment of IRB and SRB
Use of high-density PhyloChip expanded our estimation
of community richness within the Rifle aquifer over
10-fold, with large numbers of observed bacterial OTUs
(795–3132) still detected after the addition of excess acetate
to subsurface Rifle sediment and groundwater. The
observed richness for the Rifle background sediment was
also up to four times greater than that determined
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by Brodie et al. (2006) for unamended U-contaminated
sediment from Oak Ridge, TN, using an earlier version of
the PhyloChip with fewer probes (1000 OTUs identified).
However, to what extent the observed richness values in
this study approximate actual richness values, in terms of
reaching saturation, is not known.
Consistent with previous clone library and DGGE studies conducted at the site, PhyloChip data indicate that
Desulfuromonadales (dissimilatory IRB) and Desulfobacterales (SRB) were enriched during acetate-stimulated Fe
(III) and sulfate reduction (Anderson et al., 2003; Chang
et al., 2005; Vrionis et al., 2005; Holmes et al., 2007).
FEMS Microbiol Ecol 81 (2012) 188–204
PhyloChip profiling of subsurface microbial communities
197
Fig. 4. Heatmap depicting the relative abundances of highly stimulated lineages known to reduce/oxidize sulfur species and/or reduce Fe(III). Ep,
Epsilonproteobacteria; Dp, Deltaproteobacteria; F, Firmicutes; N, Nitrospira; Gp, Gammaproteobacteria. Colors in the bar at the top of the
heatmap distinguish sample groups (NR, yellow; BGS, black; L-HAS, brown; GW, dark blue; IC, pale blue; EC, red; ECS, pale gray; ECQ, dark
gray). Extraction replicate and culture data are averaged. No difference was evident between heatmap results for replicates, and few differences
were apparent among cultures.
Deeper community sampling with PhyloChip data clearly
shows that the enrichment of these lineages was not
mutually exclusive, even in the very early stages of acetate-induced Fe(III) reduction (Fig. 4). Desulfobacterales
enrichments occur early in the Fe(III)-reducing stage of
biostimulation, and Desulfuromonadales continue to be
enriched throughout sulfate reduction.
FEMS Microbiol Ecol 81 (2012) 188–204
The co-enrichment of Fe(III)- and sulfate-reducing lineages, and evidence of their concurrent activity in Riflerelated laboratory and field studies (Komlos et al., 2008a;
Miletto et al., 2011; Williams et al., 2011), may be
explained by the mixture of easily reducible and recalcitrant iron minerals within the aquifer (Postma & Jakobsen, 1996; Komlos et al., 2008b). It seems likely that once
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198
K.M. Handley et al.
Fig. 5. 16S rRNA gene neighbor-joining
phylogenetic tree of key highly enriched taxa
identified by SIMPER and SD analyses
(boldface with black circles). One
representative (probe-targeted) sequence per
OTU was used. The tree does not represent
actual sequences from Rifle aquifer material,
but is an close approximation based on probe
matches. All sequences were obtained from
GenBank. Reference taxa are shown in regular
font. Bootstrap values 50 are shown.
easily reducible, poorly crystalline Fe(III) sources are
expended within the aquifer, Desulfuromonadales colonize
and slowly reduce more recalcitrant forms of Fe(III), such
as goethite. The enrichment of Desulfuromonadales in Fe
(III)-bearing Rifle sediment, but not in quartz sand
matrices in ex situ column experiments, suggests a need
for attachment to consumable Fe(III) oxides. Attachment
to quartz in the in situ columns may have been due to
the presence of suspended Fe(III) oxides in the aquifer.
Miletto et al. (2011) recently demonstrated that dissimilatory sulfite reductase (dsrB) genes used in sulfate
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reduction were expressed predominantly by Desulfobacteraceae and, to a lesser extent, by Desulfobulbaceae and
Syntrophaceae, in a second-year Rifle biostimulation
experiment. Although samples analyzed in this study represent a diverse collection of nonreplicated time course or
single time point experiments, and different amendment
time points, PhyloChip data indicate that enrichment of
these SRB lineages, particularly Desulfobacteraceae, was
typical during acetate amendment experiments and largely
independent of sample type. Desulfobacteraceae and/or
other Desulfobacterales became enriched in samples
FEMS Microbiol Ecol 81 (2012) 188–204
199
PhyloChip profiling of subsurface microbial communities
regardless of (1) sample incubation and collection procedure, that is, whether in situ or ex situ column, drill core,
or groundwater; (2) whether samples were acetate-stimulated or from a NR part of the aquifer; or (3) the
progress of stimulation, that is, dominant terminal
electron–accepting process (TEAP), or with or without
prestimulation (first- to third-year amendments).
In addition, other enriched OTUs were detected using
PhyloChip that belong to phyla known to include sulfate
reducers (Desulfovibrionales and Peptococcaceae) and Fe
(III) reducers (Shewanellaceae, Aeromonadaceae, Peptococcaceae, and Sulfurospirillum). Among likely SRB candidates, Peptococcaceae were the most variable, and their
detection in past studies has appeared transitory (Anderson et al., 2003) or atypical (Vrionis et al., 2005). In
Anderson et al.’s study (2003), this study, and further
experiments within the Rifle aquifer (K.M. Handley, K.W.
Wrighton, C.S. Miller, J.F. Banfield., unpublished data),
Peptococcaceae were abundant exclusively in experiments
using pristine (not previously stimulated) aquifer material
or in NR sediment, suggesting that they may represent an
early-stimulation SRB group when exposed to high levels
of added acetate.
Mixed sulfate-reducing communities
Although several SRB groups are co-enriched, the prevalence of Desulfobacterales in the acetate-amended field
sediments is not surprising. Many genera from this family, most notably Desulfobacter, can grow using acetate as
a sole electron donor and carbon source while reducing
sulfate (e.g. Bak & Widdel, 1986; Platen et al., 1990; Lien
& Beeder, 1997; Purdy et al., 1997; Kuever et al., 2001).
Certain species within other detected SRB lineages,
namely Syntrophobacterales and Desulfotomaculum (in the
Peptococcaceae), can also couple sole acetate oxidation to
sulfate reduction (e.g. Widdel & Pfennig, 1977; Oude
Elferink et al., 1999). How competitive these bacteria are
during bioremediation likely depends upon their concentration-specific affinity for acetate and sulfate (Laanbroek
et al., 1984), in addition to the availability of other limiting nutrients. The ability of Peptococcaceae to form spores
(Campbell & Postgate, 1965; Stackebrandt et al., 1997)
may also account for the apparent dominance of this
group in first-time stimulated sediments, although alternative possibilities cannot be excluded.
Aside from Desulfotomaculum, other Peptococcaceae
genera, Desulfovibrionales, or Desulfobulbaceae species are
not known to couple acetate oxidation with sulfate reduction, although some species can reduce sulfate mixotrophically when using small amounts of acetate as a carbon
source and H2 as an electron donor (e.g. Lien et al.,
1998; Dias et al., 2008). Alternatively, their presence may
FEMS Microbiol Ecol 81 (2012) 188–204
be result from cryptic growth supported by the acetatefed biomass. Competition for acetate by acetoclastic
methanogenesis is unlikely to be important at the high
sulfate concentration present in the Rifle groundwater
(Dar et al., 2008), until very low sulfate/acetate ratios are
attained during peak sulfate reduction (Williams et al.,
2011).
Interestingly, diverse SRB appear to coexist in the NR
sediment, where sulfate reducers from all of the identified
taxonomic groups (Desulfobacterales, Desulfovibrionales,
Syntrophobacterales, and Peptococcaceae) were abundant
relative to nonreduced background sediment. Most of
these lineages (Desulfobacterales, Desulfovibrionaceae, and
Peptococcaceae) also include species capable of Fe(III)
reduction (Lovley et al., 1993; Ramamoorthy et al., 2006;
Haouari et al., 2008). Both groups may be implicated in
the formation of uranium-enriched framboidal pyrite
associated with these NR zones in the Rifle aquifer
(Qafoku et al., 2009).
Phylogenetic evidence for sulfur cycling
Among the most highly enriched OTUs in acetate-stimulated samples, in addition to SRB, were those associated
with lineages of chemolithoautotrophic Epsilonproteobacteria. These bacteria – Sulfurovum, Helicobacteraceae (Sulfuricurvum or Sulfurimonas), and Campylobacteraceae
(Sulfurospirillum deleyianum) – are known to couple
nitrate or oxygen reduction to the oxidation of sulfide to
S0, or S0 and thiosulfate to sulfate (Hoor, 1975; Eisenmann et al., 1995; Inagaki et al., 2004; Kodama & Watanabe, 2004). While 16S rRNA gene phylogeny is not
necessarily congruent with physiology, the well-characterized nature of these organisms lends strong evidence
toward their potential activity in the Rifle aquifer.
Indeed, the aquifer contains approximately 6–10 mM
of sulfate in the groundwater, which is largely consumed
during periods of high acetate loading (e.g. 10 mM).
Equimolar concentrations of H2S produced during sulfate
reduction are capable of generating a large supply of
reduced sulfur, such as FeS and S0 (Williams et al., 2011),
that may fuel cyclic oxidation and reduction. Microbial
oxidation of elemental or reduced sulfur species could be
supported by small amounts of dissolved oxygen or
nitrate present in micromolar concentrations in the
groundwater (Williams et al., 2011). In fact, high ammonium-to-nitrate ratios detected during a previous stimulation experiment in the aquifer (Mouser et al., 2009) may
indicate the occurrence of denitrification.
Other notable OTUs enriched during amendment that
may also have the potential to contribute to sulfur redox
cycling are Sulfurospirillum, Desulfuromonadales (Geobacteraceae, Desulfuromonadaceae, Pelobacteraceae), and
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K.M. Handley et al.
200
Shewanellaceae – all of which include species capable of
reducing thiosulfate, S0, nitrate, or nitrite (Lovley et al.,
2004). The nature of abundant Nitrospiraceae OTUs,
however, is largely enigmatic, although sequence identity
indicates that the OTUs are most closely related to sulfate-reducing Thermodesulfovibrio (Henry et al., 1994)
and putatively sulfur-oxidizing Magnetobacterium (Jogler
et al., 2010) species.
Phylogenetic diversity of bacteria potentially
capable of uranium reduction
Direct microbial enzymatic reduction of U(VI) yields similar energy as that for the reduction of crystalline Fe(III)
minerals (Finneran et al., 2002a, b) and occurs in the presence of Fe(II) and sulfide without interference by abiotic
reduction (Lovley et al., 1991; Finneran et al., 2002a, b).
Geobacter is an obvious candidate for U(VI) reduction
during acetate stimulation in the Rifle aquifer owing to its
ability to grow using uranium as an electron acceptor
(Lovley et al., 1991), and its high abundance, even during
sulfate reduction (Williams et al., 2011). Nevertheless, we
also observed an increase in the abundance of other lineages that, in addition to Fe(III) and sulfate reduction,
include species that are able to reduce U(VI). It is possible
that these lineages (Shewanellaceae, Desulfovibrionaceae,
and Peptococcaceae) may also account for some portion of
the U(VI) reduced during biostimulation (Caccavo et al.,
1992; Lovley & Phillips, 1992; Tebo & Obraztsova, 1998;
Suzuki et al., 2004). With the presence of multiple candidates for U(VI) reduction with different electron donor
and nutrient affinities, it is difficult not to speculate that
stimulated biological uranium reduction at the site may be
robust against shifts in community composition.
Similarities and differences among stimulated
communities
In acetate amendment experiments, it made little difference to the enrichment of Desulfuromonadales and Desulfobacterales whether samples were collected during
dominant Fe(III)- or sulfate-reducing phases, from
groundwater, column, or drill-core sediments, or from
first-, second-, or third-year stimulation experiments.
Only the degree of enrichment altered, evidently owing to
either the length of incubation or whether previous stimulations had occurred. Re-amendment of the Rifle aquifer
from 1 year to another is known to cause a legacy effect,
inducing a more rapid community response and transition through dominant TEAPs (Callister et al., 2010).
Results here also suggest that community composition is
affected and that while experiments involving a section of
nonpristine, previously stimulated aquifer may fail to capª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
ture the enrichment of Peptococcaceae, the use of pristine
sediments could underestimate the importance of Desulfobacterales, particularly with respect to long-term amendment. Enrichment cultures, in particular, missed the
progression from Peptococcaceae to Desulfobacterales.
Experimental approaches clearly yielded differences in
OTU abundance across diverse phylogenetic groups.
Communities from amended columns and groundwater
samples appeared depleted in OTUs from a number of
phyla relative to amended drill-core sediment communities. However, considering the similarity in the composition of highly enriched taxa from column, groundwater,
and drill-core samples (all from second- or third-year
aquifer stimulations), it is uncertain whether observed
differences in total community diversity would have any
implications for remediation processes or major community function.
It is not within the scope of this study to determine
whether or how groundwater communities collected during experiments at Rifle might differ from coupled sediment communities; however, it is notable that although
groundwater and sediment samples from field-based
experiments represent different time points during
stimulation or successive stimulation events (second-vs.
third-year stimulations), PhyloChip results show that
groundwater communities can be at least as diverse as
those in subsurface sediments (HAS and ICS in Fig. 3),
and share strong similarities in highly stimulated taxa
composition (Fig. 4). Groundwater sampling is commonly used to study subsurface communities (e.g. Anderson et al., 2003; Fields et al., 2005; Holmes et al., 2007;
Miletto et al., 2011), even though planktonic and sediment-attached aquifer communities are expected to differ
somewhat in composition (Alfreider et al., 1997; Lehman
et al., 2001; Flynn et al., 2008; Anneser et al., 2010).
Regardless of potential biases in groundwater sampling,
data also suggest that down-well, flow-through column
incubations may provide a convenient alternative, permitting sampling of the whole (planktonic and attached) wet
sediment communities.
Conclusions
PhyloChip-based analysis yields an in-depth view of community phylogenetic affiliation and richness, providing
evidence for both compositional complexity among acetate-stimulated taxa and reproducibility in key taxa
among experiments. We consistently detected the same
highly stimulated lineages (Desulfuromonadales and Desulfobacterales) throughout acetate-promoted Fe(III) and sulfate reduction, accompanied by a less consistently
enriched contingent of other lineages. Of the differences
observed among experimental approaches, year of aquifer
FEMS Microbiol Ecol 81 (2012) 188–204
PhyloChip profiling of subsurface microbial communities
stimulation (i.e. first, second, or third) appears to be
the largest factor affecting the composition of highly
stimulated taxa. Compositional similarities among drillcore and in situ flow-through column communities, particularly among highly stimulated taxa, indicate that the
latter may serve as a suitable proxy and tractable method
for studying subsurface stimulation. The phylogenetic
affiliations of taxa, enriched during amendment, suggest
that many may share the ability to use the same electron
donors and acceptors, such as Fe(III), sulfate, and potentially also U(VI). Phylogenetic data also provide evidence
for other biogeochemical processes, in particular re-oxidation of sulfur or reduced sulfur species. We speculate
therefore that the presence of multiple lineages that able
to compete for resources may increase the functional efficiency of the system and the variety of niches exploited.
Acknowledgements
Funding was provided by the Environmental and Remediation Sciences Program, Office of Science, Biological and
Environmental Research, US Department of Energy. We
thank Kate Campbell (US Geological Survey, Menlo Park)
for her help with column design and Shuk Chan (University of California, Los Angeles) for help with field implementation. We also thank our anonymous reviewers for
their helpful comments.
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Supporting Information
Additional Supporting Information may be found in the
online version of this article:
Fig. S1. Heatmap depicting the relative abundances of
OTUs among samples.
Fig. S2. Nonmetric multidimensional scaling (NMDS) of
OTU hybridization score data from groups 1–4, depicting
two-dimensional separation of samples based on overall
community composition.
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
K.M. Handley et al.
Fig. S3. Rank abundance curves depicting community
richness (x-axis) and abundance (y-axis). Insets show
curves with logged ranks to better resolve the differences
in community abundances.
Table S1. Representative GenBank accession numbers for
OTUs of highly stimulated lineages, shown in Fig. 4.
Data S1. Total array normalized hybridization scores post
cross-hybridization correction, and presence-absence data.
Please note: Wiley-Blackwell is not responsible for the
content or functionality of any supporting materials supplied by the authors. Any queries (other than missing
material) should be directed to the corresponding author
for the article.
FEMS Microbiol Ecol 81 (2012) 188–204