Accepted Article
Submission Date: 09-Oct-2013 Accept Date: 19-Mar-2014
Disturbed subsurface microbial communities follow equivalent trajectories despite different structural starting points
1
Kim M. Handley1,2,a, Kelly C. Wrighton1,b, Christopher S. Miller1,c, Michael J. Wilkins3,d, Rose S. Kantor4, Brian C. Thomas1, Kenneth H. Williams5, Jack A. Gilbert2,6, Philip E. Long5, Jillian F. Banfield1
1
Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; 2Department of
Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA; 3Biological Sciences Division, Pacific Northwest National Laboratory, PNNL, Richland, WA 99353, USA; 4Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA; 5Earth Sciences Division, Lawrence Berkeley National Laboratory, LBNL, Berkeley, CA 94720, USA; 6Biosciences Division, Argonne National Laboratory, Lemont, IL 60439, USA.
Manuscript prepared for submission to Environmental Microbiology: October 2013
Running title: Microbial community succession and disturbance
a
Corresponding author (contact details): Department of Ecology and Evolution, University of
Chicago, Chicago, IL 60637, USA; ph +1-630-252-5007; fax +1-773-834-2877; email: [email protected]. b
Current address: Department of Microbiology, Ohio State University, Columbus, OH 43210, USA.
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/1462-2920.12467
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Current address: Department of Integrative Biology, University of Colorado Denver, Denver, CO
Accepted Article
c
80217, USA. d
Current address: School of Earth Sciences, Ohio State University, Columbus, OH 43210, USA.
2
This article is protected by copyright. All rights reserved.
Summary
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Microbial community structure, and niche and neutral processes can all influence response to
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disturbance. Here, we provide experimental evidence for niche versus neutral and founding
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community effects during a bioremediation-related organic carbon disturbance. Subsurface sediment,
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partitioned into 22 flow-through columns, was stimulated in situ by the addition of acetate as a carbon
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and electron donor source. This drove the system into a new transient biogeochemical state
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characterized by iron reduction, and enriched Desulfuromonadales, Comamonadaceae and
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Bacteroidetes lineages. After approximately one month conditions favored sulfate reduction, and were
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accompanied by a substantial increase in the relative abundance of Desulfobulbus, Desulfosporosinus,
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Desulfitobacterium and Desulfotomaculum. Two subsets of four-to-five columns each were switched
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from acetate to lactate amendment during either iron (earlier) or sulfate (later) reduction. Hence,
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subsets had significantly different founding communities. All lactate treatments exhibited lower
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relative abundances of Desulfotomaculum and Bacteroidetes, enrichments of Clostridiales and
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Psychrosinus species, and a temporal succession from highly abundant Clostridium sensu stricto to
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Psychrosinus. Regardless of starting point, lactate-switch communities followed comparable
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structural trajectories whereby convergence was evident 9-16 days after each switch, and significant
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after 29-34 days of lactate addition. Results imply that neither the founding community nor neutral
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processes influenced succession following perturbation.
Accepted Article
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Accepted Article
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Introduction
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Ecosystem disturbance has the power to reshape both living systems and the abiotic environment.
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Response to disturbance is a central concern in ecological theory, which aims to predict species
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survival, community resilience and stability, trajectories, and ecosystem function (Holling, 1973).
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Microbial community response to perturbations can significantly alter biogeochemical cycles and
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ecosystem processes (Gadd, 2009). This phenomenon can be exploited in indigenous microbial
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communities to cost-effectively remediate environmental contaminants (Lloyd, 2002). However,
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despite their importance, microorganisms are largely overlooked in ecosystem process modeling, with
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still relatively few studies investigating the range of microbial responses to disturbance (Allison and
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Martiny, 2008; Shade et al., 2012).
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Disturbance, as used here, is a natural or engineered perturbation, which causes a change in
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community membership, structure and/or ecosystem function relative to a reference state (Rykiel,
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1985), whereby structure refers to “the composition (membership) of a community and the abundance
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of individual members” (Little et al., 2008). Studies into community succession following disturbance
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have a long history in macroecology (Cowles, 1899; Clements, 1916). The trajectory that disturbance-
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induced succession follows can be orderly or complex, subject to heterogeneity, and reliant on various
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inputs, including species, resource availability, and interactions (e.g., facilitating or inhibitory)
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between organisms and the environment (Sousa, 1979; McCook, 1994; Pickett, 2011). Moreover,
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ecosystem interactions involved in disturbance are susceptible to reciprocity, whereby composition or
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diversity, for example, can influence disturbance outcomes and vice versa (Agrawal et al., 2007;
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Hughes et al., 2007).
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Intrinsic to factors influencing community disturbance response are the concepts of niche
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(deterministic) and neutral (stochastic) processes. Several recent environmental and literature surveys
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and animal experiments have investigated the relative contributions of these processes in structuring
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microbial communities. Conclusions tend to suggest a concert of niche and neutral effects. Some
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studies found the strongest selective pressure was exerted by niche factors in animal guts, open soil
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mycorrhizal fungi and subsurface systems (Dumbrell et al., 2010; Jeraldo et al., 2012; Stegen et al., 4
This article is protected by copyright. All rights reserved.
2012). In other contexts (mouse guts, open wastewater system, and widely-sampled mycorrhizal fungi
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communities) neutral processes appeared to dominate, notably, but not always, those pertaining to
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open systems or where disturbance magnitude or spatiotemporal heterogeneity overwhelmed dispersal
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limitation (Ofiteru et al., 2010; Caruso et al., 2012; McCafferty et al., 2013). Niche and neutral
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effects can be further controlled or mitigated by other factors, such as the founding community
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composition (McCafferty et al., 2013), and the ratio of community generalists and specialists
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(Langenheder and Székely, 2011).
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Given the uncertain influence of niche versus neutral selective pressures, and the potential for
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reciprocity (disturbed communities in turn influencing the outcomes of disturbance), we queried
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whether a change in the nature of an ‘organic carbon’ disturbance would impact community
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trajectories within a shallow, unconfined aquifer (Rifle, Colorado, USA). The Rifle aquifer has been
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the subject of ongoing uranium and vanadium bioremediation studies, based primarily on acetate
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amendment, as it is respired completely to CO2 and (excluding in methanogenesis) not fermented (e.g.
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Anderson et al., 2003; Holmes et al., 2007; Williams et al., 2011; Handley et al., 2013). The aquifer
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harbors phylogenetically diverse communities (this study; Handley et al., 2012) that are functionally
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redundant with respect to electron acceptor utilization (Barlett et al., 2012), reflecting findings
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elsewhere in contaminated subsurface sediment (North et al., 2004). While primary perturbation of
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the aquifer with a substrate such as acetate produces predictable responses with respect to community
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composition and structure (e.g., Handley et al., 2012), it was unclear how predictable responses would
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be if communities where subjected to a secondary disturbance, and at difference stages in
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amendment-promoted community succession.
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To address this uncertainty, we exposed aquifer communities in an open system experiment to
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a continuous ‘press’ disturbance (as opposed to a transient ‘pulse’ disturbance, Bender et al., 1984;
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Shade et al., 2012) by incubating flow-through subsurface sediment columns with acetate. In situ
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acetate amendment promoted community succession through two well-characterized biogeochemical
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regimes, iron reduction (IR) followed by sulfate reduction (SR) (Anderson et al., 2003; Williams et
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al., 2011). The organic carbon and electron donor source was switched from acetate to lactate during
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either the IR or SR phase in a subset of columns, generating distinct founding communities for each 5
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lactate press disturbance. Substantial differences in community composition, and the timing and
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efficiency of terminal electron accepting processes (TEAPs) can be achieved by amending subsurface
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sediments with different electron donors, such as simple (acetate, lactate, ethanol, glucose) and
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complex (hydrogen-release compound, vegetable oil) (Akob et al., 2008; Barlett et al., 2012). The
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electron donor and carbon sources we employed (acetate and lactate) are common metabolic
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byproducts respired by diverse anaerobic bacteria. Both can be coupled to the reduction of inorganic
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species such as Fe(III) or sulfate (e.g., Equations 1-4; Lovley et al., 2004). However, in contrast with
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acetate, lactate may be fermented to acetate and propionate, or completely or partially respired to CO2
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or acetate, respectively. Sulfate-reducing bacteria, for example, can be complete or incomplete
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respirers (Gibson, 1990). Lactate therefore has a greater potential for complex outcomes in terms of
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metabolites, and the functional microbial groups supported by lactate and its degradation products.
Accepted Article
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(1) CH 3COO- + 8Fe(OH)3 + 15H+ ¾Acetate ¾¾¾¾¾¾¾¾ ® 8Fe 2+ + 2HCO-3 + 20H 2O dependant Fe(III) reduction
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(2) CH 3 -CHOH-COO- + 12Fe(OH)3 + 22H + ¾Lactate ¾¾¾¾¾¾¾¾ ® 12Fe 2+ + 3HCO-3 + 30H 2O dependant Fe(III) reduction (3) 2CH 3COO- + 2SO2-4 + H + ¾Acetate ¾¾¾¾¾¾¾¾ ® HS- + H 2S + 4HCO-3 dependant sulfate reduction (4) 4CH 3 -CHOH-COO- + 2SO2-4 ¾Lactate ¾¾¾¾¾¾¾¾ ® 4CH 3COO- + HS- + H 2S + 4HCO-3 + H + dependant sulfate reduction
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The experiment evaluates whether communities subject to a large organic carbon disturbance
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follow the same trajectory when introduced to a secondary press disturbance at different stages of
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community succession, and tests the hypothesis that niche selection, determined by taxa-specific
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affinities to a given substrate, will prevail over founding community effects, neutral processes or
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functional redundancy, ultimately yielding community convergence. Results are likely to be most
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relevant to sites undergoing large disturbances, such as encountered during bioremediation or owing
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to anthropogenic contamination.
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Results and discussion
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Biogeochemical response to amendment and disturbance
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Over the duration of the 63-day experiment acetate and lactate concentrations in column effluents
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were variable, but were detected in excess (Table S1; see Fig. 1 for column set-up). Consistent with
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previous studies, acetate addition to columns was followed by Fe(II) accumulation in groundwater
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effluent within 7 days (Fig. 2). A ~91% reduction in readily-bioavailable Fe(III) was also detected in
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column sediments sampled after 7-10 days of acetate amendment (Fig. S1). These changes are
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indicative of microbial reduction of Fe(III) minerals, and have previously been attributed to the
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activity of enriched Geobacter species (e.g., Anderson et al., 2003; Wilkins et al., 2009; Holmes et
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al., 2009; Williams et al., 2011). Fe(II) concentrations decreased after 11 days of acetate amendment,
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owing to either a decrease in the activity of dissimilatory Fe(III)-reducing bacteria and/or co-
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precipitation with sulfide generated by incipient sulfate reduction. Aqueous sulfate reduction and
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sulfide accumulation were manifest after approximately one month.
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Comparable results were obtained in columns receiving lactate, regardless of whether lactate
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was substituted for acetate when Fe(II) was increasing (lactate switch ‘early’, LE; dominant iron
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reduction) or sulfate was decreasing (lactate switch ‘late’, LL; dominant sulfate reduction). One
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exception was an unexplained high secondary spike in Fe(II) concentrations during the dominant
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sulfate reduction period in 3 lactate samples (Fig. 2b and Table S1). Differences in sulfate and sulfide
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concentrations between the averaged acetate and lactate-switch columns (Fig. 2) can be attributed to a
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well-specific effect, rather than the nature of the electron donor. In general, columns in one of two
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dedicated acetate wells (well 5 versus 1, Fig. 1) exhibited less sulfate loss, presumably due to lower
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levels of additional well-derived acetate in that region of the aquifer (Fig. S2). During peak sulfate
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reduction, average column sulfate millimolar concentrations per well were: 6.3 ± 1.4 (1 s.d., well 1),
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4.5 ± 1.7 (well 2), 6.5 ± 2.4 (well 3), and 7.3 ± 2.1 (well 5). In contrast, average column Fe(II)
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micromolar concentrations during peak iron reduction were not notably lower in well 5: 58 ± 50 (well
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1); 39 ± 37 (well 2), 33 ± 47 (well 2), and 33 ± 32 (well 5).
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Community alpha diversity
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Subsampled 16S rRNA amplicon reads from each column sediment community were reconstructed
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into sequences representing approximately 1,000-4,000 OTUs (Table 1), with up to ~30,000 times 7
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sequence coverage per OTU per sample. The steep slopes of rank abundance curves (Fig. S3) indicate
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high unevenness across treatment groups (Table 1), which are not clearly differentiated by Shannon’s
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and Pielou’s indices (Table 1). Observed OTU richness in unfiltered sequence data (with rare taxa
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preserved; Fig. S3) was on average 46% lower in amended communities compared with time zero
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(Table 1), and equivalent to PhyloChip-based estimates reported previously for Rifle aquifer
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communities (Handley et al., 2012). Decreased diversity following amendment is further suggested
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by lower Simpson’s indices (1-D) compared with those for the no-treatment T0 community (Table 1).
Accepted Article
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Treatment response and beta diversity
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Lactate-switch founding communities. Use of a press disturbance promoted a successional change in
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acetate-amended communities, such that these communities did not attain an altered stable state, as
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may otherwise occur during a press disturbance (Shade et al., 2012). Acetate induced a clear
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distinction in the composition and structure of column communities corresponding to periods of iron
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reduction (IR) or sulfate reduction (SR) (see ordinations and dendrograms in Figs 3-4 and S4). These
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two community groupings, iron-reducing acetate-only (IR-AO) and sulfate-reducing acetate-only
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(SR-AO), respectively constituted the early and late founding communities for the lactate switch
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experiment. Pairwise weighted-UniFrac significance tests indicate the difference between IR-AO and
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SR-AO was statistically significant, and the two groups are differentiated according to mean within-
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and between-group Bray-Curtis dissimilarities (Table 2; Fig. S4d).
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Lactate-switch communities. Results show that despite the difference in the lactate-switch
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founding communities (IR-AO and SR-AO), addition of lactate promoted equivalent trajectories for
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both the early and late lactate-switch (LE and LL) communities, which were distinct from those
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promoted by acetate alone (Figs 3-4 and S4, Table 2). As lactate duration progressed in both the
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earlier and later switches (from LE1 and LL1 to LE2 and LL2), communities increasingly diverged
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from AO communities (Figs 3-4, Table 2). The trajectories of lactate-switch communities converged
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over the course of the experiment, such that mature lactate communities (LE2 and LL2) clustered
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tightly with one another, while less mature communities clustered loosely and inconsistently together
8
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(Figs 3-4). Consistent results were obtained for all distance and dissimilarity metrics used to evaluate
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community response to treatment (i.e., un/weighted UniFrac, chi-squared, Bray-Curtis).
Accepted Article
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Explanatory or predictive variables. Duration of the acetate and lactate press disturbances
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was the primary factor contributing to variation among communities, as evidenced by the distribution
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of samples along PCoA1 and NMDS1 in approximate order of collection date, and the separation of
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IR-AO and SR-AO communities into two groups along these same axes (Figs 3 and S4c). Distinct
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separation of sulfate-reducing communities receiving acetate or lactate along PCoA2 and NMDS2
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suggests the second greatest amount of inter-community variation is explained by substrate type
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within communities amended for longer.
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To further explore these relationships, we performed canonical correspondence analysis
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(CCA), and constructed a time-constrained predictive multivariate regression tree (MRT). Sulfate and
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Fe(II) concentrations and amendment durations were all determined to be significant explanatory
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variables in CCA, contributing to separation of IR-AO and SR-AO treatment groups (Fig. 4b).
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Separation of lactate amendment groups are explained by lactate duration, and higher Fe(II)
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concentrations associated with LE1 (Fig. 4b). In MRT, when constraining treatment group clustering
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by either total or lactate amendment duration, lactate duration was determined to be the most
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important predictor (Fig. 4c, and summarized in Fig. 4d). The addition of sulfate or Fe(II)
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concentrations as a third constraint altered only the major internal clustering pattern of the distinct AO
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branch (Fig. 4c and S5b-c), indicating amendment duration was also more important than electron
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acceptors in predicting lactate-treated community associations.
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Community membership and structure
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Almost one tenth (9.1%) of sequences were identical across samples, and just over one third (33.5%)
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were shared across samples at ≥97% sequence similarity. At the phylum-level communities were
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dominated by Proteobacteria, Firmicutes and Bacteroidetes (Figs 5a and S6, Table S3). Treatments
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were distinguished by a higher relative abundance of Proteobacteria in the iron-reducing acetate (IR-
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AO) communities, and more abundant Firmicutes in lactate-amended communities.
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IR-AO communities. Abundant Exiguobacterium, Acinetobacter and Bacillus in the
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unamended sediment decreased upon addition of acetate from 13-20% average relative abundance
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(ARA) to ≤4% (Exiguobacterium) and 10-fold estimated sequence coverage (Supporting Information), and typically no gaps.
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Further sequences were removed if they had gaps, or were putative chimeras. Chimeras were detected
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using UCHIME v6.0 (Edgar et al., 2011) searched against the Greengenes 2011 database (McDonald
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et al., 2012) and DECIPHER (Wright et al., 2012). Filtering resulted in 204 to 492 OTUs per sample.
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Taxonomy
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Taxonomy was assigned to OTUs using RDP classifier v2.2 with a bootstrap cutoff of 80% (Wang et
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al., 2007), and for detailed analyses, the USEARCH algorithm (v5; Edgar, 2010) by generating global 17
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alignments against the SILVA database, and BLAST searches against GenBank sequences (Altschul
404
et al., 1990).
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Community analysis
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Alpha diversity was interrogated via rank abundance and rarefaction curves (Supporting Information),
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and diversity indices (Shannon, 1948; Simpson, 1949; Pielou, 1966) calculated using the vegan v2.0.5
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package in R v. 2.15.1 (R Core Team, 2012; Oksanen et al., 2012).
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To compare treatment groups (defined in Table S1 based on electron donor type, switch
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timing, and duration/biogeochemical response), Principal Coordinate Analysis (PCoA) was performed
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using the abundance-weighted and unweighted UniFrac phylogenetic distance metric, with and
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without jackknifing (153 sampling size), and Unweighted Pair Group Method with Arithmetic mean
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(UPGMA) hierarchical clustering (Luzupone and Knight, 2005; Lozupone et al., 2011). For UniFrac,
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filtered
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http://selab.janelia.org/software.html) with Thermus thermophilus supplied as the out-group. A
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phylogenetic tree was constructed with FastTree (Price et al., 2009), and the root designated with the
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Newick utility (Junier and Zdobnov, 2010). UniFrac PCoA plots were generated using the QIIME
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v1.5.0 pipeline (Caporaso et al., 2010) with the user supplied tree and OTU abundance table. The
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OTU table was created by first clustering existing OTUs at 100% identity using UCLUST v6.0
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(Edgar, 2010). OTU abundances were scaled to a value of greater than one, and converted to BIOM
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format with RDP taxonomic classifications via the convert_biom.py Python script (http://biom-
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format.org).
sequences
were
first
aligned
using
SSU-align
(Nawrocki
et
al.,
2009;
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Statistical significant differences between treatment groups were determined via the QIIME
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pipeline by pairwise comparisons among treatments based on the weighted UniFrac significance test
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after 1,000 permutations (Lozupone and Knight, 2005).
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Beta diversity was further interrogated using Bray-Curtis dissimilarities (Bray and Curtis,
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1957; Supporting Information). Mean within- and between-group Bray-Curtis dissimilarities were
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determined using the vegan function meandist. The relationship between treatments groups,
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geochemistry and length of amendment were evaluated in R by canonical correspondence analysis 18
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(CCA; vegan package 2.0-5) and multivariate regression trees (MRT; mvpart 1.6-0 and
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MVPARTwrap 0.1-8 packages; De’ath, 2002; Ouellette, 2013; Therneau and Atkinson, 2013). MRT
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size was chosen as the smallest within one standard error of the minimum cross-validated relative
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error.
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Identification of taxa contributing to differences among treatment groups was determined by
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analysis of similarity percentages (SIMPER; Clarke, 1993) using Bray-Curtis dissimilarities and the
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vegan package. Highly abundant taxa were also plotted on the UniFrac PCoA using a QIIME Python
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script for biplots. Specific differences in community composition/structure were further visualized in
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heatmaps made using the heatmap.2 function in the R gplots v2.11.0 package (Warnes, 2012) on log-
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normalized and un-normalized abundance data. Heatmaps at the phylum-level used RDP
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classifications, and all filtered data. At the genus-level (by RDP classification) heatmaps included
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only taxa at ≥1% relative abundance in at least two samples or technical replicates. Hierarchical
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clustering of sample communities was based on Euclidean distances.
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Accession numbers
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Reconstructed 16S rRNA gene data is accessible via the GenBank accession numbers KC716084-
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KC731398.
448 449
Acknowledgements
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Funding was provided through the IFRC, Subsurface Biogeochemical Research Program, Office of
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Science, Biological and Environmental Research, the US Department of Energy (DOE). J.A. Gilbert
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was funded through the DOE under contract DE-AC02-06CH11357. We thank A.P. Yelton
453
(University of California, Berkeley, UCB), D.R. Lovley (University of Massachusetts), and J.D.
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Coates (UCB) for experiment support/preparation; A.P. Montgomery (LBNL) for well-bore
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geochemical data; K.R. Frischkorn (UCB) for sequencing support; and H. O’Geen (DNA
456
Technologies Core Facility) for sequencing.
457 458
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web-site.
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Figure Legends
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Fig. 1 Schematic illustrating the experimental setup. Columns were incubated in four newly drilled
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groundwater wells. Acetate-amended columns were distributed among all four wells and lactate-
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switch columns were distributed between wells one and three. Influent and effluent tubes were unique
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for each column. Before column collection all on/off values on influent and effluent tubes for a well
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were closed and pumps were stopped to prevent fluid flow through columns prior to the common
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column support pole being raised. Un-sampled columns were returned to the well within 5 minutes
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and flow was restored. Disturbance was negligible.
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Fig. 2 (a) Sampling and disturbance timelines for each sample, indicated by bars colored by sample
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groups: light and dark blue (Acetate Only), yellow and orange (Lactate Early, LE, sampling intervals
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1 and 2), light and dark green (Lactate Late, LL, sampling intervals 1 and 2). Dark grey bars represent
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acetate amendment preceding lactate addition. Arrows indicate the start of acetate and lactate
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amendment periods. (b) Plots of aqueous geochemical data (averaged) collected from column effluent
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throughout the experiment. Error bars indicate ± 1 standard deviation. In the sulfide plot, one
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abnormally high outlier in the LL group was excluded: 1 mM at day 34 (Oct 4th, 2010). (a and b)
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Shaded pink and grey areas demark periods characterized by iron reduction (IR) and sulfate reduction
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(SR), respectively.
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Fig. 3 (a) Abundance weighted UniFrac PCoA. Pink enclosures represent statistically significant
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groups according to a weighted UniFrac significance test after Bonferroni correction (Table 2).
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Arrows are qualitative and indicate direction of transitions according to biogeochemistry (iron
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reduction, IR versus sulfate reduction, SR) and treatment. Numbers indicate total days of amendment
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for corresponding community data points. (b) Unweighted UniFrac PCoA biplot displaying the 25
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most abundant taxa. Circles sizes reflect taxa relative abundances. Inset shows points without taxa.
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Communities are generally separated along PC1 by time, and along PC2 by electron donor treatment.
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Technical replicates group closely in both ordinations. 31
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Accepted Article
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Fig. 4 (a) Tree representing UPGMA hierarchical clustering of the weighted UniFrac distance matrix
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based on 1,000 sub-samplings. Samples cluster into 4 distinct groups, with key subgroups indicated.
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Branch colors represent levels of jackknife support: red=75-100%, yellow=50-75%, green=25-50%,
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and blue is
Submission Date: 09-Oct-2013 Accept Date: 19-Mar-2014
Disturbed subsurface microbial communities follow equivalent trajectories despite different structural starting points
1
Kim M. Handley1,2,a, Kelly C. Wrighton1,b, Christopher S. Miller1,c, Michael J. Wilkins3,d, Rose S. Kantor4, Brian C. Thomas1, Kenneth H. Williams5, Jack A. Gilbert2,6, Philip E. Long5, Jillian F. Banfield1
1
Earth & Planetary Science, University of California, Berkeley, CA 94720, USA; 2Department of
Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA; 3Biological Sciences Division, Pacific Northwest National Laboratory, PNNL, Richland, WA 99353, USA; 4Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA; 5Earth Sciences Division, Lawrence Berkeley National Laboratory, LBNL, Berkeley, CA 94720, USA; 6Biosciences Division, Argonne National Laboratory, Lemont, IL 60439, USA.
Manuscript prepared for submission to Environmental Microbiology: October 2013
Running title: Microbial community succession and disturbance
a
Corresponding author (contact details): Department of Ecology and Evolution, University of
Chicago, Chicago, IL 60637, USA; ph +1-630-252-5007; fax +1-773-834-2877; email: [email protected]. b
Current address: Department of Microbiology, Ohio State University, Columbus, OH 43210, USA.
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/1462-2920.12467
This article is protected by copyright. All rights reserved.
Current address: Department of Integrative Biology, University of Colorado Denver, Denver, CO
Accepted Article
c
80217, USA. d
Current address: School of Earth Sciences, Ohio State University, Columbus, OH 43210, USA.
2
This article is protected by copyright. All rights reserved.
Summary
2
Microbial community structure, and niche and neutral processes can all influence response to
3
disturbance. Here, we provide experimental evidence for niche versus neutral and founding
4
community effects during a bioremediation-related organic carbon disturbance. Subsurface sediment,
5
partitioned into 22 flow-through columns, was stimulated in situ by the addition of acetate as a carbon
6
and electron donor source. This drove the system into a new transient biogeochemical state
7
characterized by iron reduction, and enriched Desulfuromonadales, Comamonadaceae and
8
Bacteroidetes lineages. After approximately one month conditions favored sulfate reduction, and were
9
accompanied by a substantial increase in the relative abundance of Desulfobulbus, Desulfosporosinus,
10
Desulfitobacterium and Desulfotomaculum. Two subsets of four-to-five columns each were switched
11
from acetate to lactate amendment during either iron (earlier) or sulfate (later) reduction. Hence,
12
subsets had significantly different founding communities. All lactate treatments exhibited lower
13
relative abundances of Desulfotomaculum and Bacteroidetes, enrichments of Clostridiales and
14
Psychrosinus species, and a temporal succession from highly abundant Clostridium sensu stricto to
15
Psychrosinus. Regardless of starting point, lactate-switch communities followed comparable
16
structural trajectories whereby convergence was evident 9-16 days after each switch, and significant
17
after 29-34 days of lactate addition. Results imply that neither the founding community nor neutral
18
processes influenced succession following perturbation.
Accepted Article
1
19
3
This article is protected by copyright. All rights reserved.
Accepted Article
20 21
Introduction
22
Ecosystem disturbance has the power to reshape both living systems and the abiotic environment.
23
Response to disturbance is a central concern in ecological theory, which aims to predict species
24
survival, community resilience and stability, trajectories, and ecosystem function (Holling, 1973).
25
Microbial community response to perturbations can significantly alter biogeochemical cycles and
26
ecosystem processes (Gadd, 2009). This phenomenon can be exploited in indigenous microbial
27
communities to cost-effectively remediate environmental contaminants (Lloyd, 2002). However,
28
despite their importance, microorganisms are largely overlooked in ecosystem process modeling, with
29
still relatively few studies investigating the range of microbial responses to disturbance (Allison and
30
Martiny, 2008; Shade et al., 2012).
31
Disturbance, as used here, is a natural or engineered perturbation, which causes a change in
32
community membership, structure and/or ecosystem function relative to a reference state (Rykiel,
33
1985), whereby structure refers to “the composition (membership) of a community and the abundance
34
of individual members” (Little et al., 2008). Studies into community succession following disturbance
35
have a long history in macroecology (Cowles, 1899; Clements, 1916). The trajectory that disturbance-
36
induced succession follows can be orderly or complex, subject to heterogeneity, and reliant on various
37
inputs, including species, resource availability, and interactions (e.g., facilitating or inhibitory)
38
between organisms and the environment (Sousa, 1979; McCook, 1994; Pickett, 2011). Moreover,
39
ecosystem interactions involved in disturbance are susceptible to reciprocity, whereby composition or
40
diversity, for example, can influence disturbance outcomes and vice versa (Agrawal et al., 2007;
41
Hughes et al., 2007).
42
Intrinsic to factors influencing community disturbance response are the concepts of niche
43
(deterministic) and neutral (stochastic) processes. Several recent environmental and literature surveys
44
and animal experiments have investigated the relative contributions of these processes in structuring
45
microbial communities. Conclusions tend to suggest a concert of niche and neutral effects. Some
46
studies found the strongest selective pressure was exerted by niche factors in animal guts, open soil
47
mycorrhizal fungi and subsurface systems (Dumbrell et al., 2010; Jeraldo et al., 2012; Stegen et al., 4
This article is protected by copyright. All rights reserved.
2012). In other contexts (mouse guts, open wastewater system, and widely-sampled mycorrhizal fungi
49
communities) neutral processes appeared to dominate, notably, but not always, those pertaining to
50
open systems or where disturbance magnitude or spatiotemporal heterogeneity overwhelmed dispersal
51
limitation (Ofiteru et al., 2010; Caruso et al., 2012; McCafferty et al., 2013). Niche and neutral
52
effects can be further controlled or mitigated by other factors, such as the founding community
53
composition (McCafferty et al., 2013), and the ratio of community generalists and specialists
54
(Langenheder and Székely, 2011).
Accepted Article
48
55
Given the uncertain influence of niche versus neutral selective pressures, and the potential for
56
reciprocity (disturbed communities in turn influencing the outcomes of disturbance), we queried
57
whether a change in the nature of an ‘organic carbon’ disturbance would impact community
58
trajectories within a shallow, unconfined aquifer (Rifle, Colorado, USA). The Rifle aquifer has been
59
the subject of ongoing uranium and vanadium bioremediation studies, based primarily on acetate
60
amendment, as it is respired completely to CO2 and (excluding in methanogenesis) not fermented (e.g.
61
Anderson et al., 2003; Holmes et al., 2007; Williams et al., 2011; Handley et al., 2013). The aquifer
62
harbors phylogenetically diverse communities (this study; Handley et al., 2012) that are functionally
63
redundant with respect to electron acceptor utilization (Barlett et al., 2012), reflecting findings
64
elsewhere in contaminated subsurface sediment (North et al., 2004). While primary perturbation of
65
the aquifer with a substrate such as acetate produces predictable responses with respect to community
66
composition and structure (e.g., Handley et al., 2012), it was unclear how predictable responses would
67
be if communities where subjected to a secondary disturbance, and at difference stages in
68
amendment-promoted community succession.
69
To address this uncertainty, we exposed aquifer communities in an open system experiment to
70
a continuous ‘press’ disturbance (as opposed to a transient ‘pulse’ disturbance, Bender et al., 1984;
71
Shade et al., 2012) by incubating flow-through subsurface sediment columns with acetate. In situ
72
acetate amendment promoted community succession through two well-characterized biogeochemical
73
regimes, iron reduction (IR) followed by sulfate reduction (SR) (Anderson et al., 2003; Williams et
74
al., 2011). The organic carbon and electron donor source was switched from acetate to lactate during
75
either the IR or SR phase in a subset of columns, generating distinct founding communities for each 5
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lactate press disturbance. Substantial differences in community composition, and the timing and
77
efficiency of terminal electron accepting processes (TEAPs) can be achieved by amending subsurface
78
sediments with different electron donors, such as simple (acetate, lactate, ethanol, glucose) and
79
complex (hydrogen-release compound, vegetable oil) (Akob et al., 2008; Barlett et al., 2012). The
80
electron donor and carbon sources we employed (acetate and lactate) are common metabolic
81
byproducts respired by diverse anaerobic bacteria. Both can be coupled to the reduction of inorganic
82
species such as Fe(III) or sulfate (e.g., Equations 1-4; Lovley et al., 2004). However, in contrast with
83
acetate, lactate may be fermented to acetate and propionate, or completely or partially respired to CO2
84
or acetate, respectively. Sulfate-reducing bacteria, for example, can be complete or incomplete
85
respirers (Gibson, 1990). Lactate therefore has a greater potential for complex outcomes in terms of
86
metabolites, and the functional microbial groups supported by lactate and its degradation products.
Accepted Article
76
87
(1) CH 3COO- + 8Fe(OH)3 + 15H+ ¾Acetate ¾¾¾¾¾¾¾¾ ® 8Fe 2+ + 2HCO-3 + 20H 2O dependant Fe(III) reduction
88
(2) CH 3 -CHOH-COO- + 12Fe(OH)3 + 22H + ¾Lactate ¾¾¾¾¾¾¾¾ ® 12Fe 2+ + 3HCO-3 + 30H 2O dependant Fe(III) reduction (3) 2CH 3COO- + 2SO2-4 + H + ¾Acetate ¾¾¾¾¾¾¾¾ ® HS- + H 2S + 4HCO-3 dependant sulfate reduction (4) 4CH 3 -CHOH-COO- + 2SO2-4 ¾Lactate ¾¾¾¾¾¾¾¾ ® 4CH 3COO- + HS- + H 2S + 4HCO-3 + H + dependant sulfate reduction
89 90
The experiment evaluates whether communities subject to a large organic carbon disturbance
91
follow the same trajectory when introduced to a secondary press disturbance at different stages of
92
community succession, and tests the hypothesis that niche selection, determined by taxa-specific
93
affinities to a given substrate, will prevail over founding community effects, neutral processes or
94
functional redundancy, ultimately yielding community convergence. Results are likely to be most
95
relevant to sites undergoing large disturbances, such as encountered during bioremediation or owing
96
to anthropogenic contamination.
97 98
Results and discussion
99
Biogeochemical response to amendment and disturbance
6
This article is protected by copyright. All rights reserved.
Over the duration of the 63-day experiment acetate and lactate concentrations in column effluents
101
were variable, but were detected in excess (Table S1; see Fig. 1 for column set-up). Consistent with
102
previous studies, acetate addition to columns was followed by Fe(II) accumulation in groundwater
103
effluent within 7 days (Fig. 2). A ~91% reduction in readily-bioavailable Fe(III) was also detected in
104
column sediments sampled after 7-10 days of acetate amendment (Fig. S1). These changes are
105
indicative of microbial reduction of Fe(III) minerals, and have previously been attributed to the
106
activity of enriched Geobacter species (e.g., Anderson et al., 2003; Wilkins et al., 2009; Holmes et
107
al., 2009; Williams et al., 2011). Fe(II) concentrations decreased after 11 days of acetate amendment,
108
owing to either a decrease in the activity of dissimilatory Fe(III)-reducing bacteria and/or co-
109
precipitation with sulfide generated by incipient sulfate reduction. Aqueous sulfate reduction and
110
sulfide accumulation were manifest after approximately one month.
Accepted Article
100
111
Comparable results were obtained in columns receiving lactate, regardless of whether lactate
112
was substituted for acetate when Fe(II) was increasing (lactate switch ‘early’, LE; dominant iron
113
reduction) or sulfate was decreasing (lactate switch ‘late’, LL; dominant sulfate reduction). One
114
exception was an unexplained high secondary spike in Fe(II) concentrations during the dominant
115
sulfate reduction period in 3 lactate samples (Fig. 2b and Table S1). Differences in sulfate and sulfide
116
concentrations between the averaged acetate and lactate-switch columns (Fig. 2) can be attributed to a
117
well-specific effect, rather than the nature of the electron donor. In general, columns in one of two
118
dedicated acetate wells (well 5 versus 1, Fig. 1) exhibited less sulfate loss, presumably due to lower
119
levels of additional well-derived acetate in that region of the aquifer (Fig. S2). During peak sulfate
120
reduction, average column sulfate millimolar concentrations per well were: 6.3 ± 1.4 (1 s.d., well 1),
121
4.5 ± 1.7 (well 2), 6.5 ± 2.4 (well 3), and 7.3 ± 2.1 (well 5). In contrast, average column Fe(II)
122
micromolar concentrations during peak iron reduction were not notably lower in well 5: 58 ± 50 (well
123
1); 39 ± 37 (well 2), 33 ± 47 (well 2), and 33 ± 32 (well 5).
124 125
Community alpha diversity
126
Subsampled 16S rRNA amplicon reads from each column sediment community were reconstructed
127
into sequences representing approximately 1,000-4,000 OTUs (Table 1), with up to ~30,000 times 7
This article is protected by copyright. All rights reserved.
sequence coverage per OTU per sample. The steep slopes of rank abundance curves (Fig. S3) indicate
129
high unevenness across treatment groups (Table 1), which are not clearly differentiated by Shannon’s
130
and Pielou’s indices (Table 1). Observed OTU richness in unfiltered sequence data (with rare taxa
131
preserved; Fig. S3) was on average 46% lower in amended communities compared with time zero
132
(Table 1), and equivalent to PhyloChip-based estimates reported previously for Rifle aquifer
133
communities (Handley et al., 2012). Decreased diversity following amendment is further suggested
134
by lower Simpson’s indices (1-D) compared with those for the no-treatment T0 community (Table 1).
Accepted Article
128
135 136
Treatment response and beta diversity
137
Lactate-switch founding communities. Use of a press disturbance promoted a successional change in
138
acetate-amended communities, such that these communities did not attain an altered stable state, as
139
may otherwise occur during a press disturbance (Shade et al., 2012). Acetate induced a clear
140
distinction in the composition and structure of column communities corresponding to periods of iron
141
reduction (IR) or sulfate reduction (SR) (see ordinations and dendrograms in Figs 3-4 and S4). These
142
two community groupings, iron-reducing acetate-only (IR-AO) and sulfate-reducing acetate-only
143
(SR-AO), respectively constituted the early and late founding communities for the lactate switch
144
experiment. Pairwise weighted-UniFrac significance tests indicate the difference between IR-AO and
145
SR-AO was statistically significant, and the two groups are differentiated according to mean within-
146
and between-group Bray-Curtis dissimilarities (Table 2; Fig. S4d).
147
Lactate-switch communities. Results show that despite the difference in the lactate-switch
148
founding communities (IR-AO and SR-AO), addition of lactate promoted equivalent trajectories for
149
both the early and late lactate-switch (LE and LL) communities, which were distinct from those
150
promoted by acetate alone (Figs 3-4 and S4, Table 2). As lactate duration progressed in both the
151
earlier and later switches (from LE1 and LL1 to LE2 and LL2), communities increasingly diverged
152
from AO communities (Figs 3-4, Table 2). The trajectories of lactate-switch communities converged
153
over the course of the experiment, such that mature lactate communities (LE2 and LL2) clustered
154
tightly with one another, while less mature communities clustered loosely and inconsistently together
8
This article is protected by copyright. All rights reserved.
(Figs 3-4). Consistent results were obtained for all distance and dissimilarity metrics used to evaluate
156
community response to treatment (i.e., un/weighted UniFrac, chi-squared, Bray-Curtis).
Accepted Article
155
157
Explanatory or predictive variables. Duration of the acetate and lactate press disturbances
158
was the primary factor contributing to variation among communities, as evidenced by the distribution
159
of samples along PCoA1 and NMDS1 in approximate order of collection date, and the separation of
160
IR-AO and SR-AO communities into two groups along these same axes (Figs 3 and S4c). Distinct
161
separation of sulfate-reducing communities receiving acetate or lactate along PCoA2 and NMDS2
162
suggests the second greatest amount of inter-community variation is explained by substrate type
163
within communities amended for longer.
164
To further explore these relationships, we performed canonical correspondence analysis
165
(CCA), and constructed a time-constrained predictive multivariate regression tree (MRT). Sulfate and
166
Fe(II) concentrations and amendment durations were all determined to be significant explanatory
167
variables in CCA, contributing to separation of IR-AO and SR-AO treatment groups (Fig. 4b).
168
Separation of lactate amendment groups are explained by lactate duration, and higher Fe(II)
169
concentrations associated with LE1 (Fig. 4b). In MRT, when constraining treatment group clustering
170
by either total or lactate amendment duration, lactate duration was determined to be the most
171
important predictor (Fig. 4c, and summarized in Fig. 4d). The addition of sulfate or Fe(II)
172
concentrations as a third constraint altered only the major internal clustering pattern of the distinct AO
173
branch (Fig. 4c and S5b-c), indicating amendment duration was also more important than electron
174
acceptors in predicting lactate-treated community associations.
175 176
Community membership and structure
177
Almost one tenth (9.1%) of sequences were identical across samples, and just over one third (33.5%)
178
were shared across samples at ≥97% sequence similarity. At the phylum-level communities were
179
dominated by Proteobacteria, Firmicutes and Bacteroidetes (Figs 5a and S6, Table S3). Treatments
180
were distinguished by a higher relative abundance of Proteobacteria in the iron-reducing acetate (IR-
181
AO) communities, and more abundant Firmicutes in lactate-amended communities.
9
This article is protected by copyright. All rights reserved.
IR-AO communities. Abundant Exiguobacterium, Acinetobacter and Bacillus in the
183
unamended sediment decreased upon addition of acetate from 13-20% average relative abundance
184
(ARA) to ≤4% (Exiguobacterium) and 10-fold estimated sequence coverage (Supporting Information), and typically no gaps.
396
Further sequences were removed if they had gaps, or were putative chimeras. Chimeras were detected
397
using UCHIME v6.0 (Edgar et al., 2011) searched against the Greengenes 2011 database (McDonald
398
et al., 2012) and DECIPHER (Wright et al., 2012). Filtering resulted in 204 to 492 OTUs per sample.
399 400
Taxonomy
401
Taxonomy was assigned to OTUs using RDP classifier v2.2 with a bootstrap cutoff of 80% (Wang et
402
al., 2007), and for detailed analyses, the USEARCH algorithm (v5; Edgar, 2010) by generating global 17
This article is protected by copyright. All rights reserved.
alignments against the SILVA database, and BLAST searches against GenBank sequences (Altschul
404
et al., 1990).
Accepted Article
403
405 406
Community analysis
407
Alpha diversity was interrogated via rank abundance and rarefaction curves (Supporting Information),
408
and diversity indices (Shannon, 1948; Simpson, 1949; Pielou, 1966) calculated using the vegan v2.0.5
409
package in R v. 2.15.1 (R Core Team, 2012; Oksanen et al., 2012).
410
To compare treatment groups (defined in Table S1 based on electron donor type, switch
411
timing, and duration/biogeochemical response), Principal Coordinate Analysis (PCoA) was performed
412
using the abundance-weighted and unweighted UniFrac phylogenetic distance metric, with and
413
without jackknifing (153 sampling size), and Unweighted Pair Group Method with Arithmetic mean
414
(UPGMA) hierarchical clustering (Luzupone and Knight, 2005; Lozupone et al., 2011). For UniFrac,
415
filtered
416
http://selab.janelia.org/software.html) with Thermus thermophilus supplied as the out-group. A
417
phylogenetic tree was constructed with FastTree (Price et al., 2009), and the root designated with the
418
Newick utility (Junier and Zdobnov, 2010). UniFrac PCoA plots were generated using the QIIME
419
v1.5.0 pipeline (Caporaso et al., 2010) with the user supplied tree and OTU abundance table. The
420
OTU table was created by first clustering existing OTUs at 100% identity using UCLUST v6.0
421
(Edgar, 2010). OTU abundances were scaled to a value of greater than one, and converted to BIOM
422
format with RDP taxonomic classifications via the convert_biom.py Python script (http://biom-
423
format.org).
sequences
were
first
aligned
using
SSU-align
(Nawrocki
et
al.,
2009;
424
Statistical significant differences between treatment groups were determined via the QIIME
425
pipeline by pairwise comparisons among treatments based on the weighted UniFrac significance test
426
after 1,000 permutations (Lozupone and Knight, 2005).
427
Beta diversity was further interrogated using Bray-Curtis dissimilarities (Bray and Curtis,
428
1957; Supporting Information). Mean within- and between-group Bray-Curtis dissimilarities were
429
determined using the vegan function meandist. The relationship between treatments groups,
430
geochemistry and length of amendment were evaluated in R by canonical correspondence analysis 18
This article is protected by copyright. All rights reserved.
(CCA; vegan package 2.0-5) and multivariate regression trees (MRT; mvpart 1.6-0 and
432
MVPARTwrap 0.1-8 packages; De’ath, 2002; Ouellette, 2013; Therneau and Atkinson, 2013). MRT
433
size was chosen as the smallest within one standard error of the minimum cross-validated relative
434
error.
Accepted Article
431
435
Identification of taxa contributing to differences among treatment groups was determined by
436
analysis of similarity percentages (SIMPER; Clarke, 1993) using Bray-Curtis dissimilarities and the
437
vegan package. Highly abundant taxa were also plotted on the UniFrac PCoA using a QIIME Python
438
script for biplots. Specific differences in community composition/structure were further visualized in
439
heatmaps made using the heatmap.2 function in the R gplots v2.11.0 package (Warnes, 2012) on log-
440
normalized and un-normalized abundance data. Heatmaps at the phylum-level used RDP
441
classifications, and all filtered data. At the genus-level (by RDP classification) heatmaps included
442
only taxa at ≥1% relative abundance in at least two samples or technical replicates. Hierarchical
443
clustering of sample communities was based on Euclidean distances.
444 445
Accession numbers
446
Reconstructed 16S rRNA gene data is accessible via the GenBank accession numbers KC716084-
447
KC731398.
448 449
Acknowledgements
450
Funding was provided through the IFRC, Subsurface Biogeochemical Research Program, Office of
451
Science, Biological and Environmental Research, the US Department of Energy (DOE). J.A. Gilbert
452
was funded through the DOE under contract DE-AC02-06CH11357. We thank A.P. Yelton
453
(University of California, Berkeley, UCB), D.R. Lovley (University of Massachusetts), and J.D.
454
Coates (UCB) for experiment support/preparation; A.P. Montgomery (LBNL) for well-bore
455
geochemical data; K.R. Frischkorn (UCB) for sequencing support; and H. O’Geen (DNA
456
Technologies Core Facility) for sequencing.
457 458
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Supporting information
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Additional Supporting Information may be found in the online version of this article at the publisher’s
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web-site.
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30
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Figure Legends
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Fig. 1 Schematic illustrating the experimental setup. Columns were incubated in four newly drilled
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groundwater wells. Acetate-amended columns were distributed among all four wells and lactate-
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switch columns were distributed between wells one and three. Influent and effluent tubes were unique
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for each column. Before column collection all on/off values on influent and effluent tubes for a well
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were closed and pumps were stopped to prevent fluid flow through columns prior to the common
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column support pole being raised. Un-sampled columns were returned to the well within 5 minutes
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and flow was restored. Disturbance was negligible.
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Fig. 2 (a) Sampling and disturbance timelines for each sample, indicated by bars colored by sample
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groups: light and dark blue (Acetate Only), yellow and orange (Lactate Early, LE, sampling intervals
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1 and 2), light and dark green (Lactate Late, LL, sampling intervals 1 and 2). Dark grey bars represent
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acetate amendment preceding lactate addition. Arrows indicate the start of acetate and lactate
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amendment periods. (b) Plots of aqueous geochemical data (averaged) collected from column effluent
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throughout the experiment. Error bars indicate ± 1 standard deviation. In the sulfide plot, one
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abnormally high outlier in the LL group was excluded: 1 mM at day 34 (Oct 4th, 2010). (a and b)
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Shaded pink and grey areas demark periods characterized by iron reduction (IR) and sulfate reduction
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(SR), respectively.
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Fig. 3 (a) Abundance weighted UniFrac PCoA. Pink enclosures represent statistically significant
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groups according to a weighted UniFrac significance test after Bonferroni correction (Table 2).
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Arrows are qualitative and indicate direction of transitions according to biogeochemistry (iron
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reduction, IR versus sulfate reduction, SR) and treatment. Numbers indicate total days of amendment
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for corresponding community data points. (b) Unweighted UniFrac PCoA biplot displaying the 25
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most abundant taxa. Circles sizes reflect taxa relative abundances. Inset shows points without taxa.
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Communities are generally separated along PC1 by time, and along PC2 by electron donor treatment.
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Technical replicates group closely in both ordinations. 31
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Accepted Article
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Fig. 4 (a) Tree representing UPGMA hierarchical clustering of the weighted UniFrac distance matrix
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based on 1,000 sub-samplings. Samples cluster into 4 distinct groups, with key subgroups indicated.
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Branch colors represent levels of jackknife support: red=75-100%, yellow=50-75%, green=25-50%,
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and blue is
