This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplemental material
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowReprints and Permissions
Right arrow Copyright Information
Right arrow Books from ASM Press
Right arrow MicrobeWorld
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mendez, M. O.
Right arrow Articles by Maier, R. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mendez, M. O.
Right arrow Articles by Maier, R. M.
Agricola
Right arrow Articles by Mendez, M. O.
Right arrow Articles by Maier, R. M.

 Previous Article  |  Next Article 

Applied and Environmental Microbiology, June 2008, p. 3899-3907, Vol. 74, No. 12
0099-2240/08/$08.00+0     doi:10.1128/AEM.02883-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.

Characterization of a Bacterial Community in an Abandoned Semiarid Lead-Zinc Mine Tailing Site{triangledown} ,{dagger}

Monica O. Mendez,{ddagger} Julia W. Neilson, and Raina M. Maier*

Department of Soil, Water and Environmental Science, University of Arizona, 429 Shantz Building No. 38, Tucson, Arizona 85721

Received 20 December 2007/ Accepted 13 April 2008


arrow
ABSTRACT
 
Bacterial diversity in mine tailing microbial communities has not been thoroughly investigated despite the correlations that have been observed between the relative microbial diversity and the success of revegetation efforts at tailing sites. This study employed phylogenetic analyses of 16S rRNA genes to compare the bacterial communities present in highly disturbed, extremely (pH 2.7) and moderately (pH 5.7) acidic lead-zinc mine tailing samples from a semiarid environment with those from a vegetated off-site (OS) control sample (pH 8). Phylotype richness in these communities decreased from 42 in the OS control to 24 in the moderately acidic samples and 8 in the extremely acidic tailing samples. The clones in the extremely acidic tailing sample were most closely related to acidophiles, none of which were detected in the OS control sample. The comparison generated by this study between the bacteria present in extremely acidic tailing and that in moderately acidic tailing communities with those in an OS control soil provides a reference point from which to evaluate the successful restoration of mine tailing disposal sites by phytostabilization.


arrow
INTRODUCTION
 
Approximately 550,000 abandoned mine sites in the United States alone have generated 45 billion tons of mine waste, including waste rock and tailing material, and many of the sites are in arid and semiarid regions (48). Mine tailings have no aggregate structure or organic matter, they are low in nutrients (N and P), they can contain high concentrations of metals (As, Cu, Fe, Mn, Ni, Pb, and Cd) ranging from 1 to 50 g kg–1, and they are often devoid of vegetation (30, 38, 49, 53). Recent interest in the reclamation of abandoned mine tailings in arid and semiarid regions focuses on revegetation, or phytostabilization, whereby tailings and their associated contaminants are sequestered in the root zone (38).

The ultimate goal of phytostabilization is not only to establish a plant cover to immobilize contaminants but also to attain the plant species richness associated with ecosystem stability and resilience (37). Long-term stability is critically important in arid and semiarid zones plagued by chronic drought. Failed revegetation efforts have been attributed to various soil parameters, including low soil pH values, low acid-neutralizing potential, acid-generating microbial activity, and high bioavailable metal concentrations (12, 36, 43, 54). A number of mine tailing reclamation studies have emphasized a strong association between the establishment of a stable plant community and the abundance and composition of soil microbiota (12, 32, 36, 37, 43, 51). While high numbers of autotrophic iron- and sulfur-oxidizing bacteria are associated with plant death in acidic mine tailings with limited acid-neutralizing potential, increases in neutrophilic heterotrophic bacteria have been shown to correlate with plant establishment (32, 35, 36, 40, 43).

The aims of this study were to conduct a comprehensive phylogenetic comparison of the microbial communities present in two semiarid mine tailing samples, one extremely (pH 2.7) and one moderately (pH 5.7) acidic, and to compare these communities to those in undisturbed off-site (OS) control soil. The relative compositions of the bacterial communities were then compared to the physicochemical characteristics of the sites.


arrow
Site description and sampling.
 
Samples were collected from the Klondyke mill site in Aravaipa Valley, Graham County, Arizona, where lead and zinc ores were processed from 1948 to 1958 (52). Approximately 100,000 metric tons of flotation tailing were deposited into two separate piles along the Aravaipa Creek, which remains completely unvegetated. Similar to tailing samples of other lead-zinc mine sites, the Klondyke tailings are iron rich and have a low acid-neutralizing-to-acid-generating (AGP) potential ratio (Table 1). As a result, they are acid-generating tailings, which prevents natural revegetation and complicates phytostabilization. In 1998, the Klondyke mill site was placed on the Arizona Water Quality Assurance Revolving Fund Registry due to levels of Pb and As that exceeded Arizona nonresidential soil remediation levels of 10 and 2,000 mg kg–1, respectively, and to elevated levels of Cd and Pb in fish sampled downstream from the site (1, 29).


View this table:
[in this window]
[in a new window]

  		TABLE 1. Physicochemical characteristics of mine tailings and OS soil samplesa

The physical and chemical heterogeneity of the Klondyke tailing piles is well documented in a site map provided by the Arizona Department of Environmental Quality (1). Two areas representing extremely acidic regions (K4, pH 2.7) and moderately acidic regions (K6, pH 5.7) of the tailing were selected for microbial analysis and phytostabilization studies. Sampling procedures, as well as physical and chemical characteristics, were reported previously, along with the analysis of the phytostabilization potential of these tailing locations (35). Briefly, 0.2-m3 tailing samples were removed from a depth of 20 to 50 cm, thoroughly mixed, and stored at 4°C for all chemical, physical, and biological analyses. An OS control sample (OS) was taken from an undisturbed vegetated area adjacent to the tailing pile. All samples were taken at depths of 20 cm or more to avoid surface contamination by blowing dust from other regions of the tailing site. Relevant chemical properties are summarized in Table 1. In addition, plant-available metals, as determined by analysis of DTPA extracts (31), were previously determined to be extremely low for As, Cu, Fe, and Pb in comparison to the total metal concentrations (0.01 to 2% of total metals), while Zn was slightly higher (13 to 18% of total metals).


arrow
Enumeration of bacteria as indicators of soil health.
 
Portions of the acidophilic iron- and sulfur-oxidizing bacterial populations and neutrophilic heterotrophs were enumerated to determine their value as bioindicators of the relative soil health of the three samples analyzed. Enumeration of iron- and sulfur-oxidizing populations in the K4, K6, and OS samples was conducted by the most probable number (MPN) technique (8), using modified 9K (pH 2.3) and modified Starkey's (pH 4.5) media as previously described (35). Neutrophilic heterotrophs were enumerated on R2A agar. Cultured iron and sulfur oxidizers present in the MPN cultures were identified by 16S rRNA gene clone library analysis of the combined 10–2 dilution tubes from each sample.


arrow
DNA extraction and 16S rRNA gene clone library analysis.
 
Total community DNA was extracted from 0.5-g subsamples taken from three bulk samples (K4, K6, and OS), using a FastDNA spin kit for soil (Qbiogene Inc., Carlsbad, CA) as specified by the manufacturer. 16S rRNA genes were amplified from the community extracts, using universal bacterial primers 27f and 1492r as described previously (25). Clone libraries were generated from the 1.5-kb 16S rRNA gene products, using a TOPO TA cloning kit (Invitrogen, San Diego, CA) according to the manufacturer's directions. One hundred sixty-six clones were screened from each tailing/soil sample, and 50 from each MPN culture (combined 10–2 dilution tubes). Clones were grouped according to restriction fragment length polymorphism patterns, using BstUI and RsaI (New England Biolabs, Mississauga, ON, Canada), and two representative clones from each group were selected for sequencing (42). Plasmid DNA was purified prior to submitting the samples to the University of Arizona Research Labs Genomic Analysis and Technology Core for quantification and sequencing with an ABI3730xl DNA analyzer (Applied Biosystems, Foster City, CA) using primers T3, 518f, 1070r, and T7. Sequences were compared to those in the GenBank database by using BLAST searches (2) using the megaBLAST option to identify the closest matches. All expected phylotypes were evaluated for chimeric sequences using NAST sequence alignment and chimera check tools from Greengenes (13, 14) and Pintail (3).


arrow
Data analysis.
 
Unique phylotypes were defined as operational taxonomic units (OTUs) with <99% 16S rRNA gene sequence similarity as determined by GCG BestFit software (18). The number of unique phylotypes (phylotype richness, S) was used for creation of rarefaction curves. Relative diversity between bacterial communities was evaluated by calculating the Shannon diversity index and evenness factor (34). Coverage (C) was used as a measurement of captured diversity (20). To estimate species richness, the nonparametric Chao 1 estimate was calculated with log-linear-transformed confidence intervals at 95% (24). Analyses were performed with EstimateS version 8.0 software (11). For the purpose of inputting data into the program, each clone or isolate was treated as a separate sample with 100 randomizations.

Community phylotypes of the cultured iron-/sulfur-oxidizing acidophiles and uncultured bacteria shared between the samples were analyzed. Sequences were aligned using Clustal X (47) and imported into DNADIST in PHYLIP version 3.6 (16) to generate distance matrices using the Jukes-Cantor correction for multiple substitutions. OTUs were assigned by distance-based OTU and richness (DOTUR [44]). A distance of 0.03 (OTU0.03) was examined to determine shared species between samples. The Sørenson (Sclass) similarity index was calculated as an estimate of the ratio of OTUs shared between two communities (e.g., K4 and K6) as follows: Sclass = (2S12)/(S1+ S2) where S1 and S2 are the numbers of OTUs observed in K4 and K6, respectively, and S12 is the number of shared OTUs between K4 and K6.

Nearly complete 16S rRNA gene sequences from the clone libraries were used to construct two separate trees (K4, K6, and OS). Putative phylogenetic groupings were determined by results from Ribosomal Database Project (RDP) Sequence Match (10) and Classifier (50) software. The sequences were aligned using Clustal X (47), and the alignments were adjusted manually using MacClade version 4.08 software (33). Rooted most-parsimonious trees based on nearly full-length sequences were generated using the maximum-parsimony analysis by heuristic search (tree bisection-reconnection branch swapping) as implemented in PAUP version 4.0 Beta (45) and described in the figure legends.


arrow
Diversity comparison of uncultured bacteria.
 
Rarefaction curves, as well as percent library coverage, indicated that the bacteria identified from the community DNA extracts from the K4, K6, and OS samples were adequately sampled (Table 2), and thus, they were analyzed further for diversity characterization. The observed phylotype and estimated Chao 1 richness of uncultured libraries increased with increasing pH (Table 2) and decreasing Fe concentration and AGP (Table 1). In terms of Chao 1 richness, the K4 (12) uncultured sample was significantly lower than that of both the K6 (25) and the OS (41) samples (P < 0.05). Although there were large differences between the phylotype and Chao 1 estimates of richness for the K6 and OS samples, the differences were not significant. Diversity, as demonstrated by the Shannon diversity index and confirmed by the Shannon evenness factor, followed the same pattern. The low Shannon evenness factor for the K4 sample (pH 2.7) provides evidence for phylotype dominance in the K4 uncultured library, which is in contrast to the OS uncultured library, for which the Shannon evenness factor approached 1, indicating little phylotype dominance. As with the Chao 1 richness estimates, the Shannon indices indicate that the diversity of the K6 (pH 5.7) sample is intermediate to those of the K4 sample and the OS control.


View this table:
[in this window]
[in a new window]

  		TABLE 2. Summary of clone libraries of uncultured bacteria and bacteria cultured in autotroph media


arrow
Phylogenetic structure of uncultured bacterial communities.
 
Results from the phylogenetic analysis are similar to those from the diversity analyses in that the number of phylogenetic groups increased as a function of pH from 4 to 7 to 11 in the microbial communities extracted from the K4, K6, and OS tailing samples, respectively (Fig. 1). The K4 tailing sample contained eight unique phylotypes (Table 2); three belonged to Firmicutes, two to Actinobacteria, two to Gammaproteobacteria, and one to Nitrospira (Fig. 2; Table 3). Twenty-four unique phylotypes were identified from the K6 sample, 75% of which belonged to the four phyla identified above for the K4 sample (Fig. 2; Table 3). The remaining K6 phylotypes were associated with Acidobacteria, Alphaproteobacteria, and Betaproteobacteria. The diversity of phylotypes associated with the groups common to both samples, Actinobacteria, Firmicutes, and Gammaproteobacteria, was greater in the K6 sample than in the K4 sample.


Figure 1
View larger version (16K):
[in this window]
[in a new window]

  		FIG. 1. Distribution of phylotypes in uncultured libraries from mine tailing samples. Diagrams show the relative abundance of 16S rRNA phylotypes of clones from the K4 (A), K6 (B), and OS (C) samples, with a total of 8, 24, and 42 unique phylotypes, respectively.


Figure 2
View larger version (32K):
[in this window]
[in a new window]

  		FIG. 2. Most-parsimonious tree generated from 16S rRNA gene sequences from reference bacterial strains (GenBank) and unique phylotypes of both cultured and uncultured bacteria in K4 (indicated by •) and K6 (indicated by ••) mine tailings. Two members of the phylum Bacteroidetes (Bacteroides fragilis and Bacteroides uniformis) were used as the outgroup. Bootstrap values (1,000 replicates) are given for nodes with ≥50% support. Accession numbers for reference strains are shown in parentheses, and type strains (T) are indicated where possible; accession numbers for 16S rRNA gene sequences from this study are included in Tables 3 and 4.


View this table:
[in this window]
[in a new window]

  		TABLE 3. Identities of 16S rRNA gene sequences from K4 and K6 uncultured bacteria

The OS control sample contained 42 unique phylotypes. Phyla represented in this sample and not present in the K4 and K6 samples included Gemmatimonadetes, Bacteroidetes, Planctomycetes, Deltaproteobacteria, and Verrucomicrobia. In comparison to the K6 sample phylotypes, the relative percentages of Acidobacteria, Actinobacteria, Alphaproteobacteria, and Betaproteobacteria increased, while the percentage of Gammaproteobacteria phylotypes decreased significantly, and Firmicutes phylotypes were not detected at all (Fig. 1 and see Fig. S1 and Table S1 in the supplemental material).


arrow
Characterization of cultured autotrophs and neutrophilic heterotrophs.
 
Culturable populations of iron- and sulfur-oxidizing acidophiles and neutrophilic heterotrophs were enumerated as potential bioindicators of relative soil health. Comparable numbers of iron and sulfur oxidizers were cultured from the K4 and K6 tailing samples, but none was detected in the OS control soil (Table 2). The diversity of the acidophilic iron and sulfur oxidizers cultured in 9K and Starkey's media was greater at pH 6 than at pH 4 (Table 2). The single K4 cultured iron oxidizer belonged to the class Nitrospira, while the K6 iron oxidizers belonged to the Alphaproteobacteria and Gammaproteobacteria. The K4 sulfur oxidizer was a member of the Gammaproteobacteria subphylum, while the K6 oxidizers included members of both Betaproteobacteria and Gammaproteobacteria (Table 4; Fig. 2). With the exception of one sulfur oxidizer (strain S-K6-C04), all of the cultured iron and sulfur oxidizer phylotypes were also identified from the uncultured clone libraries (≥99% identity), indicating that these cultured organisms represented viable populations in their respective communities (Table 4). Populations common to both cultured and uncultured clone libraries belonged to the Nitrospira, Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria phylotypes (Table 4; Fig. 2).


View this table:
[in this window]
[in a new window]

  		TABLE 4. Identities of 16S rRNA gene sequences from bacteria cultured in iron- and sulfur-oxidizer mediaa

Neutrophilic heterotroph counts were significantly lower in both tailing samples than in the OS sample (F2,6 = 555.53, P < 0.0001). The K4 (pH 2.7) tailing sample had remarkably low counts, 30 ± 17 CFU g–1, while the K6 (pH 5.7) tailing sample count, 1.5 x 105 ± 1.1 x 104 CFU g–1, was only 10-fold lower than that of the OS (pH 7.7) sample, 2.5 x 106 ± 5.2 x 105 CFU g–1. These results suggest that the relative presence of culturable neutrophilic heterotrophs may serve as a bioindicator of the degree of site disturbance, where low numbers correspond to mine tailings with low levels of bacterial diversity and a low potential for plant establishment. Previously published work (35) demonstrated that unamended K6 tailing samples could support plant growth, while the unamended K4 tailing sample could not. Although plants grown in the K6 tailing were severely stunted when harvested after 3 months, postharvest neutrophilic heterotroph counts were significantly higher in the bulk and rhizosphere soils than in the initial bulk tailing. Likewise, the presence of quantifiable culturable populations of acidophilic iron and sulfur oxidizers may be a secondary indicator of site disturbance. Final numbers of acidophilic autotrophic iron and sulfur oxidizers were significantly lower than the initial counts in the K6 tailing sample after the plant harvest.


arrow
Comparison of clone libraries.
 
A similarity comparison of the cultured and uncultured bacterial libraries showed that the extremely acidic K4 and moderately acidic K6 mine tailing communities were related, with a Sørenson similarity index of 0.28 (Sclass) (Table 3) at an OTU0.03 definition, but neither sample was similar to the OS sample (Sclass = 0) (see Table S1 in the supplemental material). Approximately 57% of the K4 phylotypes were shared with the K6 sample, and 18% of the K6 phylotypes were found in the K4 sample (Table 3). In the K4 uncultured library, four of the eight K4 phylotypes were ≥99.7% similar to the K6 clones (Gammaproteobacteria, K4-C03 and K6-C12; Actinobacteria, K4-C160 and K6-C16; Firmicutes, K4-C26 and K6-C156; Nitrospira, K4-C86 and K6-C22). Clones K4-C93 and K6-C156, belonging to the Firmicutes group, had 98.8% sequence identity.


arrow
Characterization of K4 bacterial populations.
 
All phylotypes identified from the K4 sample were acidophiles closely related to clones or isolates previously identified from acid mine drainage (AMD) ecosystems (4). Clones K4-C03 and K4-C116, affiliated with Gammaproteobacteria, are closely related (99.5% and 98%) to clone ff5 from the extremely acidic Tinto River in southwestern Spain (17) and have 98% and 97% similarity, respectively, to the iron- and sulfur-oxidizing bacteria Acidithiobacillus ferrooxidans. Clone K4-C03 is also 99.1% similar to strain S-K4-C38 cultured in the sulfur-oxidizing medium. Clone K4-C86 belongs to the phylum Nitrospira and is 99.9% similar to the iron oxidizer cultured from this sample (Fe-K4-C09). This cultured Fe oxidizer was 98% similar to the autotrophic Fe oxidizer Leptospirillum ferriphilum ATCC strain 49881 (4, 6, 19, 46). Optimal growth conditions for L. ferriphilum have been characterized at pH 1 to 2, with a temperature range of 30 to 40°C, which is a higher temperature range than the optimum for Leptospirillum ferrooxidans, another common AMD iron oxidizer (4). Interestingly, a summer soil temperature of 40°C is not uncommon in the semiarid regions of southern Arizona, where these tailings are located.

The three phylotypes belonging to the phylum Firmicutes are 100% likely to be Sulfobacillus species (RDP classifier) with remote similarity to S. yellowstonensis YTF-1 (K4-C26, 94%; K4-C93, 92%) and S. thermosulfidooxidans DSM9293T (K4-C07, 95%). Clone K4-C41, placed within the Actinobacteria group, is highly similar to Acidimicrobium clones identified from the Richmond mine in Iron Mountain, CA, as follows: 99.7% similar to the Acidimicrobium ferrooxidans AMD clone BA46 identified by Bond et al. (6) and 99.3% similar to clone ASL4 identified by Baker and Banfield (4). In addition, K4-C41 is 99.2% similar to the heterotrophic iron oxidizer Ferrimicrobium acidiphilum (AF251436). The second actinobacterium clone, K4-C160, has no close association with any cultured organism. It is 98% similar to a clone extracted from biogenic iron oxide nodules (AB254793). Sulfobacillus- and Acidimicrobium-related phylotypes are frequent components of acid mine drainage. Sulfobacillus organisms are facultative autotrophs comprising 6 to 8% of extremely acidic AMD communities (4, 39). They are iron and sulfur oxidizers, as well as iron reducers, using ferric iron as an electron acceptor. Bridge and Johnson (7) have shown that strains of Sulfobacillus spp. actively dissolve ferric iron-containing minerals such as jarosite, which is a primary mineral constituent of these tailings. Iron oxidation by mixed populations of Sulfobacillus spp. and Acidithiobacillus ferrooxidans was actually shown to be more extensive than that by pure cultures of either isolate, which has been attributed to the mixotrophic growth of Sulfobacillus, allowing it to remove organic carbon. (4). The Acidimicrobium-related species have also been characterized as iron-oxidizing, acidophilic, facultative autotrophs (6).

Thus, according to the phylogenetic analysis, the K4 tailing community appears to be composed of both autotrophic and heterotrophic acidophiles typical of populations identified from extremely acidic AMD locations. These acidophiles are closely related to cultured bacteria capable of iron and sulfur oxidation/reduction and carbon oxidation/fixation (4, 9, 22). The jarosite mineralogy of these tailings may explain the presence of iron reducers along with the iron-oxidizing populations. The distribution of extreme acidophiles observed for the K4 sample reflects the low pH which may result from an AGP which is 2.6 times that of the K6 tailing.


arrow
Characterization of K6 bacterial populations.
 
Populations identified in the K6 tailing (pH 5.7) sample represent the same categories of mutualistic heterotrophic and autotrophic bacteria described for the K4 sample but with a higher degree of diversity, implying the existence of a more complex community with the potential for a broader range of physiological activities. While the Chao 1 estimate for the K4 sample showed a high degree of phylotype dominance, the estimate for the K6 sample was not significantly different from that of the OS control. The K6 microbial community contained 14 acidophiles not found in the K4 tailing sample and 6 phylotypes with no close relationships to known acidophiles.

The acidophiles unique to the K6 sample included the K6-C83 clone, which was cultured as Fe-K6-C47, has been placed in the Alphaproteobacteria group, and was assigned to the Acidiphilium genus by the RDP classifier (100%). This clone has 98% sequence identity with Acidiphilium acidophilum, which is unique among the Acidiphilium spp. in that it can grow heterotrophically, autotrophically, or mixotrophically (27) and is the only known Acidiphilium sp. to grow autotrophically on sulfur. Acidiphilium spp. are also capable of ferric iron reduction (15, 41). K6-C83 is nearly identical to the Acidiphilium isolates CH3 (99.6%) isolated from the La Andina copper mine tailing, Chile (15), and Acidiphilium sp. PK40 (99.4%), isolated from acid streamers from abandoned copper mines in north Wales, United Kingdom (22). The clone K6-C101, affiliated with the Betaproteobacteria subphylum, was also identified from the S oxidizer culture medium (S-K6-C18). These strains were 99.9 and 99.7% similar to the arsenite-oxidizing Thiomonas arsenivorans strain B6 (5) isolated from AMD in France and 98% similar to Thiomonas sp. strain PK44 isolated on heterotrophic medium from the acid mine streamers referred to above (22). Thiomonas sp. strain PK44 was further characterized as a thiosulfate, ferrous iron, and arsenite oxidizer. Bruneel et al. (9) cultured Thiomonas from subsurface waters of the Carnoulès Pb-Zn mine tailing impoundment and found that the numbers enumerated increased with pH, suggesting a neutrophilic growth preference.

The K6 community included three times as many Gammaproteobacteria phylotypes as that of the K4 tailing. Two Gammaproteobacteria clones unique to the K6 sample (K6-C19 and K6-C79) were included in the Acidithiobacillus cluster (Fig. 2), and three clones were related to novel acidophiles. Phylotype K6-C13 and cultured sulfur oxidizer S-K6-C04 were 98.6% and 99.8% similar, respectively, to isolate WJ2 from the Wheal Jane mine in England, characterized as a moderate heterotrophic acidophile capable of Fe oxidation (21). The second novel phylotype, K6-C11, cultured as Fe oxidizer Fe-K6-C35, was 99.5% similar to the Fe-oxidizing autotrophic acidophile m-1 (AF387301). The m-1 strain was isolated from coal strip mine refuse in Calloway County, Missouri; is capable of growth at 35 to 40°C; and is an extreme acidophile capable of growth at pH of <3 (23).

As with the Gammaproteobacteria, there were twice as many K6 Sulfobacillus spp. with only one phylotype common (sequence similarity of ≥99%) to those of the K4 tailing samples. Like the K4 sulfobacilli, six of the K6 phylotypes were distantly related (91 to 94%) to Sulfobacillus yellowstonensis or S. thermosulfidooxidans. A seventh Firmicutes phylotype, K6-C31, was remotely similar (94%) to the gram-positive iron-oxidizing acidophile G1 (AY529492) (28). Finally, the closely related phylotypes K6-C55 and K6-C86, identified by the RDP Classifier (10) as belonging to the genus GP1 in the family Acidobacteriaceae, were 97% similar to the heterotrophic acidophile CH1 cultured from the La Andina, Chile, copper mine tailing (15). The Acidobacteria are characterized as moderately acidophilic heterotrophs, preferring a pH of 3 to 6. Recent research has shown that the capacity to reduce iron is also widespread among these bacteria (41).

The existence of a more complex microbial community at a moderately acidic pH level is further demonstrated by the presence of five K6 phylotypes with no association to known acidophiles. Specifically, two K6 Alphaproteobacteria phylotypes, K6-C56 and K6-C124, were similar to rhizosphere clones, with the latter having 99.3% sequence identity with the N2-fixing Bradyrhizobium elkanii strain SEMIA 6101, an elite rhizobial strain used in Brazilian commercial inoculants.


arrow
Characterization of OS bacterial populations.
 
The phylogenetic diversity observed in the OS control is typical of an average healthy soil as defined by Janssen (26) and thus can serve as a benchmark of comparison for the two disturbed tailing microbial communities. In a survey of 32 clone libraries from a broad range of soils, Janssen found that average soil communities are dominated by Proteobacteria (39%, including 19% Alphaproteobacteria, 10% Betaproteobacteria, and 8% Gammaproteobacteria), followed by Acidobacteria (20%), and Actinobacteria (13%). The remaining phyla representing 2 to 7% of the clones were Verrucomicrobia, Bacteroidetes, Chloroflexi, Planctomycetes, and Gemmatimonadetes. The OS sample was similarly dominated by Alphaproteobacteria (21%) followed by Gemmatimonadetes (19%), Betaproteobacteria (14%), Acidobacteria (12%), and Actinobacteria (12%), with representatives also identified from each of the less dominant phyla listed above, with the exception of the phylum Chloroflexi (Fig. 1). Janssen's five dominant phyla or subphyla were each represented by 4 to 25% of the clones in the K6 library (Fig. 1), but only the Actinobacteria and Gammaproteobacteria were represented by clones in the K4 tailing bacterial community. The K4 community was dominated by members of the Firmicutes group, which was not detected in the OS sample nor listed as a principle component in Janssen's survey. These results suggest that moderately acidic mine tailings not only have a much more diverse acidophilic community but may be able to sustain some populations associated with a healthier soil.


arrow
Summary.
 
This report offers a comprehensive characterization of the phylogenetic composition and structure of uncultured bacterial communities from both extremely and moderately acidic tailing samples and from a parallel OS control in a semiarid environment. Much of the focus on the acidophiles implicated in reducing the pH of mine waste sites has been from the perspective of communities associated with AMD drainage or collection water. The results presented here reveal that seven of the eight phylogenetic groups described by Baker and Banfield (4) in their review of AMD microbial communities were represented in the K4 and K6 mine tailing communities and that the majority of clones had strong similarities to bacteria previously identified or cultured from AMD sites that are well characterized. Thus, strong similarities exist between the structure of various AMD bacterial communities and the microbial communities characterized from these semiarid mine tailings.

The Chao 1 estimates and Shannon diversity indices for the three microbial communities increased with increasing pH and decreasing AGP and Fe concentration. The significance of these three variables to the relative community diversity of the K4 and K6 tailings was reinforced by the fact that all other chemical properties including total organic carbon, total nitrogen, and plant-available metals were similar for both tailing samples, with the exception that plant-available Zn was actually 10 times higher in the K6 sample than in the K4 sample.

This characterization of the K4 and K6 bacterial communities provides a basis for further study of microbial communities dominating semiarid acidic tailing piles that are inhospitable to plant growth. In addition, we propose that inventories of bacterial populations present in soils or tailings that are capable of sustaining plant growth, but absent from tailing sites where plants cannot survive, provide information concerning potential biomarkers to be used for reclamation evaluation. Currently, the permanent success of phytostabilization of mine tailings is unknown. Most studies monitor only plant growth, ignoring the microbial community and the potential effects that they may have on future ecosystem function or metal speciation. Restoration ecology is dependent on establishing a reference point for comparison to restoration outcomes, and microbial population biomarkers may be useful reference points for phytostabilization of mine tailing disposal sites.


arrow
Nucleotide sequence accession numbers.
 
Sequence accession numbers were deposited in the GenBank database under accession numbers EF612352 to EF612425 for the K4, K6, and OS uncultured clones and EF612426 to EF612433 and EU014795 for the cultured Fe and S oxidizer isolates.


arrow
ACKNOWLEDGMENTS
 
This research was supported by grant 2 P42 ES04940-11 from the National Institute of Environmental Health Sciences Superfund Basic Research Program, NIH.

We thank Edwin Pond and Scott D. Goodwin from the Arizona Department of Environmental Quality for providing access to the Klondyke site and existing site characterization data.


arrow
FOOTNOTES
 
* Corresponding author. Mailing address: Department of Soil, Water and Environmental Science, University of Arizona, 429 Shantz Building No. 38, Tucson, AZ 85721. Phone: (520) 621-7231. Fax: (520) 621-1647. E-mail: rmaier{at}ag.arizona.edu Back

{triangledown} Published ahead of print on 18 April 2008. Back

{dagger} Supplemental material for this article may be found at http://aem.asm.org/. Back

{ddagger} Present address: 423 Harcourt, San Antonio, TX 78223. Back


arrow
REFERENCES
 
    1
  1. ADEQ. 2001. Geochemistry static test results for Klondyke Tailings WQARF Site. Arizona Department of Environmental Quality, Phoenix, AZ.
    2. 2
  2. Altschul, S. F., T. L. Madden, A. A. Schaffer, J. H. Zhang, Z. Zhang, W. Miller, and D. J. Lipman. 1997. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25:3389-3402.[Abstract/Free Full Text]
    3. 3
  3. Ashelford, K. E., N. A. Chuzhanova, J. C. Fry, A. J. Jones, and A. J. Weightman. 2005. At least 1 in 20 16S rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies. Appl. Environ. Microbiol. 71:7724-7736.[Abstract/Free Full Text]
    4. 4
  4. Baker, B. J., and J. F. Banfield. 2003. Microbial communities in acid mine drainage. FEMS Microbiol. Ecol. 44:139-152.[CrossRef]
    5. 5
  5. Battaglia-Brunet, F., C. Joulian, F. Garrido, M. C. Dictor, D. Morin, K. Couplan, D. B. Johnson, K. B. Hallberg, and P. Baranger. 2006. Oxidation of arsenite by Thiomonas strains and characterization of Thiomonas arsenivorans sp. nov. Antonie van Leeuwenhoek 89:99-108.[CrossRef][Medline]
    6. 6
  6. Bond, P. L., S. P. Smriga, and J. F. Banfield. 2000. Phylogeny of microorganisms populating a thick, subaerial, predominantly lithotrophic biofilm at an extreme acid mine drainage site. Appl. Environ. Microbiol. 66:3842-3849.[Abstract/Free Full Text]
    7. 7
  7. Bridge, T. A. M., and D. B. Johnson. 1998. Reduction of soluble iron and reductive dissolution of ferric iron-containing minerals by moderately thermophilic iron-oxidizing bacteria. Appl. Environ. Microbiol. 64:2181-2186.[Abstract/Free Full Text]
    8. 8
  8. Briones, A. M., and W. Reichardt. 1999. Estimating microbial population counts by ‘most probable number’ using Microsoft Excel. J. Microbiol. Methods 35:157-161.[CrossRef][Medline]
    9. 9
  9. Bruneel, O., R. Duran, K. Koffi, C. Casiot, A. Fourcans, F. Elbaz-Poulichet, and J. C. Personne. 2005. Microbial diversity in a pyrite-rich tailings impoundment (Carnoulés, France). Geomicrobiol. J. 22:249-257.[CrossRef]
    10. 10
  10. Cole, J. R., B. Chai, R. J. Farris, Q. Wang, S. A. Kulam, D. M. McGarrell, G. M. Garrity, and J. M. Tiedje. 2005. The Ribosomal Database Project (RDP-II): sequences and tools for high-throughput rRNA analysis. Nucleic Acids Res. 33:D294-D296.[Abstract/Free Full Text]
    11. 11
  11. Colwell, R. K., C. X. Mao, and J. Chang. 2004. Interpolating, extrapolating, and comparing incidence-based species accumulation curves. Ecology 85:2717-2727.[CrossRef]
    12. 12
  12. de La Iglesia, R., D. Castro, R. Ginocchio, D. Van Der Lelie, and B. Gonzalez. 2006. Factors influencing the composition of bacterial communities found at abandoned copper-tailings dumps. J. Appl. Microbiol. 100:537-544.[CrossRef][Medline]
    13. 13
  13. DeSantis, T. Z., P. Hugenholtz, K. Keller, E. L. Brodie, N. Larsen, Y. M. Piceno, R. Phan, and G. L. Andersen. 2006. NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes. Nucleic Acids Res. 34:W394-W399.[Abstract/Free Full Text]
    14. 14
  14. DeSantis, T. Z., P. Hugenholtz, N. Larsen, M. Rojas, E. L. Brodie, K. Keller, T. Huber, D. Dalevi, P. Hu, and G. L. Andersen. 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72:5069-5072.[Abstract/Free Full Text]
    15. 15
  15. Diaby, N., B. Dold, H. Pfeifer, C. Holliger, D. B. Johnson, and K. B. Hallberg. 2007. Microbial communities in a porphyry copper tailings impoundment and their impact on the geochemical dynamics of the mine waste. Environ. Microbiol. 9:298-307.[CrossRef][Medline]
    16. 16
  16. Felsenstein, J. 2004. PHYLIP (Phylogeny Inference Package) version 3.6. Department of Genome Sciences, University of Washington, Seattle, WA.
    17. 17
  17. García-Moyano, A., E. González-Toril, A. Aguilera, and R. Amils. 2007. Prokaryotic community composition and ecology of floating macroscopic filaments from an extreme acidic environment, Río Tinto (SW, Spain). Syst. Appl. Microbiol. 30:601-614.[CrossRef][Medline]
    18. 18
  18. Genetics Computer Group. 2002. GCG, Wisconsin package, version 10.3. Accelrys, Inc., San Diego, CA.
    19. 19
  19. Goebel, B. M., and E. Stackebrandt. 1994. Cultural and phylogenetic analysis of mixed microbial populations found in natural and commercial bioleaching environments. Appl. Environ. Microbiol. 60:1614-1621.[Abstract/Free Full Text]
    20. 20
  20. Good, I. J. 1953. The population frequencies of species and the estimation of population parameters. Biometrics 40:237-264.
    21. 21
  21. Hallberg, K. B., and D. B. Johnson. 2003. Novel acidophiles isolated from moderately acidic mine drainage waters. Hydrometallurgy 71:139-148.[CrossRef]
    22. 22
  22. Hallberg, K. B., K. Coupland, S. Kimura, and D. B. Johnson. 2006. Macroscopic streamer growths in acidic, metal-rich mine waters in North Wales consist of novel and remarkably simple bacterial communities. Appl. Environ. Microbiol. 72:2022-2030.[Abstract/Free Full Text]
    23. 23
  23. Harrison, A. P., Jr. 1982. Genomic and physiological diversity amongst strains of Thiobacillus ferrooxidans and genomic comparison with Thiobacillus thiooxidans. Arch. Microbiol. 131:68-76.[CrossRef]
    24. 24
  24. Hughes, J. B., J. J. Hellmann, T. H. Ricketts, and B. J. M. Bohannan. 2001. Counting the uncountable: statistical approaches to estimating microbial diversity. Appl. Environ. Microbiol. 67:4399-4406.[Free Full Text]
    25. 25
  25. Ikner, L. A., R. S. Toomey, G. Nolan, J. W. Neilson, B. M. Pryor, and R. M. Maier. 2007. Culturable microbial diversity and the impact of tourism in Kartchner Caverns, Arizona. Microbial Ecol. 53:30-42.[CrossRef][Medline]
    26. 26
  26. Janssen, P. H. 2006. Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA genes. Appl. Environ. Microbiol. 72:1719-1728.[Free Full Text]
    27. 27
  27. Johnson, D. B., and T. A. M. Bridge. 2002. Reduction of ferric iron by acidophilic heterotrophic bacteria: evidence for constitutive and inducible enzyme systems in Acidiphilium spp. J. Appl. Microbiol. 92:315-321.[CrossRef][Medline]
    28. 28
  28. Johnson, B. D., N. Okibe, and K. B. Hallberg. 2005. Differentiation and identification of iron-oxidizing acidophilic bacteria using cultivation techniques and amplified ribosomal DNA restriction enzyme analysis. J. Microbiol. Methods 60:299-313.[CrossRef][Medline]
    29. 29
  29. King, A. K., and M. Martinez. 1998. Metals in fish collected from Aravaipa Creek. Report prepared for U. S. Fish and Wildlife Service, Arizona Ecological Services Field Office, Phoenix, AZ.
    30. 30
  30. Krzaklewski, W., and M. Pietrzykowski. 2002. Selected physico-chemical properties of zinc and lead ore tailings and their biological stabilisation. Water Air Soil Pollut. 141:125-142.[CrossRef]
    31. 31
  31. Lindsay, W. L., and W. A. Norvell. 1978. Development of a DTPA soil test for zinc, iron, manganese, and copper. Soil Sci. Soc. Am. J. 42:421-428.[Abstract/Free Full Text]
    32. 32
  32. Londry, K., and B. Sherriff. 2005. Comparison of microbial biomass, biodiversity, and biogeochemistry in three contrasting gold mine tailings deposit. Geomicrobiol. J. 22:237-247.[CrossRef]
    33. 33
  33. Maddison, D. R., and W. P. Maddison. 2001. MacClade4: analysis of phylogeny and character evolution. Sinauer Associates, Sunderland, MA.
    34. 34
  34. Magurran, A. E. 1988. Ecological diversity and its measurement. Chapman and Hall, London, United Kingdom.
    35. 35
  35. Mendez, M. O., E. P. Glenn, and R. M. Maier. 2007. Phytostabilization potential of quailbush for mine tailings: growth, metal accumulation, and microbial community changes. J. Environ. Qual. 36:245-253.[Abstract/Free Full Text]
    36. 36
  36. Moynahan, O. S., C. A. Zabinski, and J. E. Gannon. 2002. Microbial community structure and carbon-utilization diversity in a mine tailings revegetation study. Restor. Ecol. 10:77-87.[CrossRef]
    37. 37
  37. Mummey, D. L., P. D. Stahl, and J. S. Buyer. 2002. Microbial biomarkers as an indicator of ecosystem recovery following surface mine reclamation. Appl. Soil Ecol. 21:251-259.[CrossRef]
    38. 38
  38. Munshower, F. F. 1994. Practical handbook of disturbed land revegetation. Lewis Publishing, Boca Raton, FL.
    39. 39
  39. Okibe, N., and D. B. Johnson. 2004. Biooxidation of pyrite by defined mixed cultures of moderately thermophilic acidophiles in pH-controlled bioreactors: significance of microbial interactions. Biotechnol. Bioeng. 87:574-583.[CrossRef][Medline]
    40. 40
  40. Rosario, K., S. L. Iverson, D. A. Henderson, S. Chartrand, C. McKeon, E. P. Glenn, and R. M. Maier. Bacterial community changes during plant establishment at the San Pedro River mine tailings site. J. Environ. Qual. 36:1249-1259.
    41. 41
  41. Rowe, O. F., J. Sánchez-España, K. B. Hallberg, and D. B. Johnson. 2007. Microbial communities and geochemical dynamics in an extremely acidic, metal-rich stream at an abandoned sulfide mine (Huelva, Spain) underpinned by two functional primary production systems. Environ. Microbiol. 9:1761-1771.[CrossRef][Medline]
    42. 42
  42. Sambrook, J., E. F. Fritsch, and T. Maniatis. 1989. Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory Press, Plainview, NY.
    43. 43
  43. Schippers, A., P. G. Jozsa, W. Sand, Z. M. Kovacs, and M. Jelea. 2000. Microbiological pyrite oxidation in a mine tailings heap and its relevance to the death of vegetation. Geomicrobiol. J. 17:151-162.[CrossRef]
    44. 44
  44. Schloss, P. D., and J. Handelsman. 2005. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Appl. Environ. Microbiol. 71:1501-1506.[Abstract/Free Full Text]
    45. 45
  45. Swofford, D. L. 2006. PAUP*: phylogenetic analysis using parsimony. Macintosh Beta v. 10.0. Sinauer Associates, Sunderland, MA.
    46. 46
  46. Tan, G., W. Whu, K. B. Hallberg, F. Li, C. Lan, and L. Huang. 2007. Cultivation-dependent and cultivation-independent characterization of the microbial community in acid mine drainage associated with acidic Pb/Zn mine tailing at Lechang, Guangdong, China. FEMS Microbiol. Ecol. 59:118-126.[CrossRef][Medline]
    47. 47
  47. Thompson, J. D., T. J. Gibson, F. Plewniak, F. Jeanmougin, and D. G. Higgins. 1997. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 25:4876-4882.[Abstract/Free Full Text]
    48. 48
  48. U. S. Environmental Protection Agency (USEPA). 2004. Abandoned mine lands team: reference notebook. www.epa.gov/aml/tech/amlref.pdf.
    49. 49
  49. Walder, I. F., and W. X. Chavez. 1995. Mineralogical and geochemical behavior of mill tailing material produced from lead-zinc skarn mineralization, Hanover, Grant County, New Mexico, USA. Environ. Geol. 26:1-18.[CrossRef]
    50. 50
  50. Wang, Q., G. M. Garrity, J. M. Tiedje, and J. R. Cole. 2007. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73:5261-5267.[Abstract/Free Full Text]
    51. 51
  51. Wielinga, B., J. K. Lucy, J. N. Moore, O. F. Seastone, and J. E. Gannon. 1999. Microbiological and geochemical characterization of fluvially deposited sulfidic mine tailings. Appl. Environ. Microbiol. 65:1548-1555.[Abstract/Free Full Text]
    52. 52
  52. Wilson, E. D. 1959. Aravaipa district, p. 51-62. In Arizona zinc and lead deposits. Part 1. Arizona Bureau of Mines, geological series no. 18, bulletin no. 156. University of Arizona, Tucson, AZ.
    53. 53
  53. Wong, J. W. C., C. M. Ip, and M. H. Wong. 1998. Acid-forming capacity of lead-zinc mine tailings and its implications for mine rehabilitation. Environ. Geochem. Health 20:149-155.[CrossRef]
    54. 54
  54. Ye, Z. H., W. S. Shu, Z. Q. Zhang, C. Y. Lan, and M. H. Wong. 2002. Evaluation of major constraints to revegetation of lead/zinc mine tailings using bioassay techniques. Chemosphere 47:1103-1111.[Medline]

Applied and Environmental Microbiology, June 2008, p. 3899-3907, Vol. 74, No. 12
0099-2240/08/$08.00+0     doi:10.1128/AEM.02883-07
Copyright © 2008, American Society for Microbiology. All Rights Reserved.



This article has been cited by other articles:

  • Lauber, C. L., Hamady, M., Knight, R., Fierer, N. (2009). Pyrosequencing-Based Assessment of Soil pH as a Predictor of Soil Bacterial Community Structure at the Continental Scale. Appl. Environ. Microbiol. 75: 5111-5120 [Abstract] [Full Text]  
  • Iverson, S. L., Maier, R. M. (2009). Effects of Compost on Colonization of Roots of Plants Grown in Metalliferous Mine Tailings, as Examined by Fluorescence In Situ Hybridization. Appl. Environ. Microbiol. 75: 842-847 [Abstract] [Full Text]  

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Supplemental material
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowReprints and Permissions
Right arrow Copyright Information
Right arrow Books from ASM Press
Right arrow MicrobeWorld
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Mendez, M. O.
Right arrow Articles by Maier, R. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Mendez, M. O.
Right arrow Articles by Maier, R. M.
Agricola
Right arrow Articles by Mendez, M. O.
Right arrow Articles by Maier, R. M.

Copyright © 2009 by the American Society for Microbiology.   For an alternate route to Journals.ASM.org, visit: http://intl-journals.asm.org | More Info»