No retraction, correction or concern found when last checked on Oct 21, 2026.
Comparative metagenomic and metatranscriptomic analyses of microbial communities in acid mine drainage
Lin-xing Chen, Min Hu, Li-nan Huang and 4 more
The ISME Journal · 2014 · CC BY
Abstract
The microbial communities in acid mine drainage have been extensively studied to reveal their roles in acid generation and adaption to this environment. Lacking, however, are integrated community- and organism-wide comparative gene transcriptional analyses that could reveal the response and adaptation mechanisms of these extraordinary microorganisms to different environmental conditions. In this study, comparative metagenomics and metatranscriptomics were performed on microbial assemblages collected from four geochemically distinct acid mine drainage (AMD) sites. Taxonomic analysis uncovered unexpectedly high microbial biodiversity of these extremely acidophilic communities, and the abundant taxa of Acidithiobacillus, Leptospirillum and Acidiphilium exhibited high transcriptional activities. Community-wide comparative analyses clearly showed that the AMD microorganisms adapted to the different environmental conditions via regulating the expression of genes involved in multiple in situ functional activities, including low-pH adaptation, carbon, nitrogen and phosphate assimilation, energy generation, environmental stress resistance, and other functions. Organism-wide comparative analyses of the active taxa revealed environment-dependent gene transcriptional profiles, especially the distinct strategies used by Acidithiobacillus ferrivorans and Leptospirillum ferrodiazotrophum in nutrients assimilation and energy generation for survival under different conditions. Overall, these findings demonstrate that the gene transcriptional profiles of AMD microorganisms are closely related to the site physiochemical characteristics, providing clues into the microbial response and adaptation mechanisms in the oligotrophic, extremely acidic environments.
Full text
From PubMed Central, U.S. National Library of Medicine, as current on Oct 21, 2026. Paragraph numbers are ours, so an answer can point at one.
Introduction
The Earth's extreme environments harbor a wide array of microorganisms with the ability to survive and thrive in physical extremes. Analyzing the physiological behaviors and dynamics of these extraordinary communities will reveal the mechanisms that microbes use to respond to environmental change and adapt to the harsh conditions. AMD is generated from the microbially mediated oxidative dissolution of sulfide minerals and characterized by low pH and high concentrations of sulfate and metals, representing an extreme environment for life. Two decades of 16S rRNA gene-based molecular surveys have revealed the microbial diversity and ecology of AMD environments. More recently, metagenomic analyses have successfully reconstructed complete or near-complete genomes of dominant AMD microbes directly from environmental samples, possible scenarios for carbon and nitrogen fixation and energy generation, and their potential roles in acid generation have been suggested. On the basis of metagenome-derived genomic information, subsequent metaproteomics have revealed the occurrence of proteins associated with the generation of AMD and the adaptation to extremely acidic habitats. Moreover, combined metagenomic and metaproteomic analyses have been conducted to reveal the speciation and evolution in AMD biofilms. These efforts have largely expanded our knowledge of the microbial ecology, evolution and adaptation in the extreme AMD environment.
Despite these important advances, the study of gene expression patterns of microbial populations in AMD systems has been limited. Such analyses would provide useful insights into the in situ metabolic activities and functional partitioning of microbes in these low-diversity communities. To date, the environmental transcriptomes of microbial assemblages in the Tinto River (Spain) ecosystem have been profiled using Leptospirillum ferrooxidans DNA microarrays, demonstrating the gene expression profiles of this iron oxidizer to adapt its physiology to changes in physicochemical parameters and modes of life (biofilm vs planktonic growth; ). Another report has attempted integrated community genomics, proteomics and transcriptomics to biofilms in the Richmond Mine AMD system, but, similarly, a single taxon namely the uncultivated new species ‘Leptospirillum group IV UBA BS' was targeted in the analysis. Consequently, the in situ functional activities of compositionally distinct acidophilic communities and their response to the varying environmental conditions remain unexplored.
We report here the application of combined metagenomic and metatranscriptomic approaches to four AMD microbial assemblages from three geochemically distinct mining sites (Table 1 and Supplementary Figure 1a). By simultaneously investigating the taxonomic composition, gene contents and gene expression patterns, we aimed to reveal the overall functional activities of these extremely acidophilic communities and the specific gene transcriptional behaviors of individual organisms associated with response and adaptation to different environmental conditions.
Sampling and physicochemical characteristics determination
Four AMD samples were collected from three different mine sites in Guangdong Province, China. One of the AMD samples was collected from the mining effluent of the Dabaoshan (DBS) polymetallic ore (24°31'37”N, 113°42'49”E) and another from the acidic drainage pond associated with the tailings impoundment at the Fankou (FK) Pb/Zn mine (25°04'39”N, 113°38'16”E). The other two samples were collected from the Yunfu pyrite mine (22°56'10”N, 112°02'42”E), one from the AMD Yunfu stream (YFS) draining across the surface mining area and the other from the AMD collection Yunfu pond (YFP) downstream before treatment. For DNA/RNA extraction, triplicate samples were collected on site by prefiltering through a 1.6-μm GF/A filter to remove impurities and then filtering through a 0.22-μm polyethersulfone filter using a peristaltic pump. Physicochemical characteristics were determined either on site or in the laboratory as previously described. Detailed protocols are provided in Supplementary methods.
Metagenomic and metatranscriptomic sequencing and bioinformatics analyses
For the four AMD samples, DNA and RNA extraction, rRNA subtraction, RNA amplification and cDNA synthesis were performed, and the protocols are detailed in the Supplementary methods. Subsequently, the four metatranscriptomic (cDNA) libraries representing the AMD samples were individually barcoded, and those of DBS and FK, YFS and YFP were, respectively, combined. For each of the two combined cDNA libraries and each of the four metagenomic (DNA) libraries, a whole 454 Titanium run (six runs in total) was sequenced. The pyrosequencing generated a total of 3.5 million DNA and 1.3 million cDNA sequences (Supplementary Table 1). Each of the two combined cDNA libraries (DBS+FK, YFS+YFP) obtained fewer sequences than that of a DNA library (∼72%, Supplementary Table 1), likely because of the incomplete removal of poly(A) tags added for RNA amplification. By comparing these sequences against a combined 5S, 16S, 18S, 23S and 25S rRNA database from the ARB LSU and SSU databases, 0.2–0.5% of the DNA sequences and 46.7–69.1% of the cDNA sequences were identified as rRNA gene-bearing ones (Supplementary Table 1). The rRNA gene-bearing sequences were compared against the Ribosomal Database Project database (release 10; ) to identify 16S rRNA gene-bearing ones, which were further assigned to phylogenetic groups using the Ribosomal Database Project Classifier (; Figure 1a and Supplementary Figure 2). As reported in other metatranscriptomic studies, the depletion of rRNA sequences from the total RNA sample was not sufficient, this was likely due to the unsuccessful removal of archaeal rRNA sequences (Supplementary Figure 2). In each DNA and cDNA non-rRNA data set, replicate sequences sharing 100% nucleotide similarity and length were identified and removed with CD-Hit. The resulting non-rRNA, non-replicate DNA and cDNA sequences were searched for genes in the NCBI non-redundant database, and the results were parsed using the lowest common ancestor algorithm in MEGAN to obtain their taxonomic information. This obtained ∼500 000 DNA and 50 000 cDNA sequences that matched archaeal and bacterial protein-coding genes for each community, which were retained for further analyses. For functional annotation, the protein-coding sequences were compared against the extended Clusters of Orthologous Groups of proteins (COGs) database (STRING; ) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and 64.0–83.4% and 75.0–94.1% of which were, respectively, identified as COG and KEGG genes (Supplementary Table 1). See Supplementary methods for detailed protocols. The DNA and cDNA nucleotide sequences are deposited at MG-RAST under the accession numbers of 4568577.3, 4568579.3, 4568579.3, 4568581.3, 4568582.3, 4568583.3, 4568585.3 and 4568661.3.
Statistical analyses
The relative abundance of a given taxon in a community was calculated as:
where a is the number of sequences assigned to the taxon and b is the total number of sequences assigned to all the taxa in the community. Similar calculations were performed for relative abundance of a given gene, COG, COG category, KEGG pathway and KEGG subcategory.
Statistical enrichment of a given gene or COG between two data sets was determined by pairwise comparisons using two-tailed Fisher's exact test, with confidence intervals at 99% significance and Benjamini–Hochberg correction (P<0.05).
Principal component analysis was performed using the R package of ‘vegan' (version, 2.0–10). Hierarchical clustering analysis was performed with correlation distance and average-linkage method using the R package of ‘pheatmap' (version, 0.7.7).
Physicochemical characteristics of AMD samples
All AMD samples were characterized by low pH (1.9–2.7) and dissolved organic carbon (DOC) (2.9–6.8 mg l-1), and high concentrations of sulfate (6690–7931 mg l-1), total iron (520–2190 mg l-1) and heavy metals (Al, Pb, Zn, Cu, Cd, Cr and Mn) (Table 1), features typical of the acid mine environments. The AMD environments under study were physicochemically distinct as revealed by the plots (Supplementary Figure 1a). Specifically, the DBS AMD was characterized with the lowest temperature, total iron and highest dissolved oxygen, Cu concentration, whereas FK AMD was characterized by its highest temperature, DOC, Fe3+, Zn and lowest pH. In comparison, the YFS and YFP samples collected from the same mine were both characterized with relatively higher total iron and Fe2+/Fe3+ ratio, indicating a lower iron oxidation rate.
Microbial community composition and transcriptionally active taxa
Taxonomic assignment of protein-coding gene sequences in the DNA data sets revealed >100 genera in each of the four AMD communities, indicating unexpectedly high microbial diversity in these extreme environments, which hindered the sequence assembly at the current sequencing depth. The DBS community was dominated by archaeal Richmond Mine acidophilic nanoorganism, Acidithiobacillus and Leptospirillum members (Figure 1b and Supplementary Figure 1b). The FK community was with high abundance of Euryarchaeota, including archaeal Richmond Mine acidophilic nanoorganism, Thermoplasma and Ferroplasma, likely owing to the relatively high temperature of the AMD (Table 1). The two communities from the Yunfu mine showed similarity with high abundances of Acidithiobacillus spp. and AMRAN (Figure 1b and Supplementary Figure 1b), likely because of their similar environmental conditions (Supplementary Figure 1a). The taxonomic assessment based on the 16S rRNA gene-bearing sequences in the DNA data sets gave generally consistent results (Figure 1a), except that no archaeal Richmond Mine acidophilic nanoorganism-associated sequences were identified. This is likely due to the lacking representation of these lesser known archaea in the Ribosomal Database Project database. Taxonomic assignment of the cDNA protein-coding gene sequences revealed that Acidithiobacillus, Leptospirillum and Acidiphilium were the most transcriptionally active populations in the AMD communities (Figure 1c). Specifically, Acidithiobacillus and Leptospirillum and Leptospirillum and Acidiphilum were the most active populations in the DBS and FK AMD, respectively. The YFS and YFP communities harbored active populations of Leptospirillum and Acidithiobacillus, respectively. This is unexpected, as the two AMD samples shared similar environmental conditions (Supplementary Figure 1a) and microbial compositions (Figure 1a and b). Surprisingly, archaeal Richmond Mine acidophilic nanoorganism as dominant taxa across the four AMD samples showed extremely low transcriptional activity in all communities (Figure 1b and c). However, this result was consistent with a previous metaproteomic analysis of AMD biofilms, where archaeal Richmond Mine acidophilic nanoorganism showed very low activity, and indicated that the taxa with the highest abundances may not necessarily be the greatest contributors to the community functions (Figure 1).
Overview of metabolic potentials and functional activities
The non-rRNA sequences-matching genes of NCBI non-redundant, extended STRING COG and KEGG databases revealed the metabolic potentials and functional activities of the AMD communities. Genes involved in energy production and conversion, translation, ribosomal structure and biogenesis, posttranslational modification, protein turnover, chaperons, amino-acid metabolism and carbohydrate metabolism dominated the transcript pools of all analyzed communities (Supplementary Table 2 and Figure 3). The dominance of these transcripts was consistent with the results from previous metaproteomic and environmental transcriptomic analyses of other AMD systems, and even metatranscriptomic analyses of marine and soil ecosystems, indicating the uniform high abundance of transcripts for the maintenance of basic cellular machinery, enabling growth and metabolism in the normal and extreme environments. As expected, the DBS, YFS and YFP communities exhibited more similar metabolic potentials compared with that of FK (Supplementary Figure 2c), mirroring their relatively similar environmental conditions (Supplementary Figure 1a) and community composition (Figure 1b). However, the YFS community exhibited more similar overall transcriptional profiles with that of FK (Supplementary Figures 1d and 3), which was consistent with their comparable active taxa composition (Figure 1c).
Community-wide comparative gene transcriptional behaviors
Our analysis indicated that 935 out of 2731 COGs were with significantly different expression levels across the four communities (P<0.05; two-tailed Fisher's exact test; Figure 2a), suggesting distinct gene transcriptional profiles. In a given community, we define a COG with a significantly higher or lower expression level than that in all other three communities as an indicator COG (of this community), which attributes the most or the fewest transcripts for the associated function across the four communities. Accordingly, 90, 198, 64 and 106 indicator COGs (higher or lower) were, respectively, identified for the communities of DBS, FK, YFS and YFP (Figure 2b and Supplementary Table 3). The FK communities harbored a large number of higher indicator COGs in posttranslational modification, protein turnover, chaperones (COG O), energy production and conversion (COG C) and amino-acid transport and metabolism (COG E) (Figure 2b), likely owing to the much higher temperature of FK AMD (43.4 oC), for elevated temperature should upregulate the expression of proteins associated with these functions. On the basis of the functional assignment of these higher and lower indicator COGs and the dominant transcripts (see above), the associated in situ functional activities of the AMD communities will be discussed in the next several sections, taking into account the physicochemical differences of the four AMD environments.
Housekeeping functions
The expression levels of housekeeping function associated genes, including those for DNA-directed RNA polymerase, ribosomal proteins, elongation factors, cytochromes and ATP synthase, varied across the four communities (Supplementary Table 3). The lowest abundance of ribosomal protein transcripts (3.65% Figure 3) indicated that the microorganisms in FK community were likely with the lowest average growth rates. This speculation was supported by the fact that most of the archaeal taxa in this community showed very low activities (Figure 1b and c).
Low pH adaptation
AMD microorganisms are challenged to maintain a near-neutral cytoplasm and to resist the low pH. Using a cell membrane highly impermeable to protons is an important strategy to limit the influx of protons into the cell. The gene encoding hopanoids in bacteria for this strategy, that is, the squalene–hopene cyclase (sqhC), was abundant in all the cDNA data sets (Figure 3). In addition, the detection of transcripts for the ABC high-affinity potassium transport system (kdpABC) (Figure 3) indicated that the microbes may generate an inside-positive membrane potential through active influx of K+ to partially deflect the inward flow of protons. The cytoplasmic pH was also proved to be maintained by the metabolism of proton buffer molecules, like phosphate uptake (pstSCAB), and glutamate, arginine and lysine decarboxylation (gadAB, adi, speA, cadA) (Figure 3). Moreover, genes for other novel acid resistance factors as illustrated by in AMD environments, including the ClpXP (clpX, clpP) proteins, the transcriptional repressor LexA (lexA) and nucleic acid-binding proteins of Hu (hupB) and Dps (dps), were also expressed in all four communities (Figure 3). Our analyses suggested that the FK community with the lowest AMD pH (1.9) harbored the highest abundance of low pH adaptation associated transcripts that discussed above (1.14% in total), and the DBS and YFS communities with the highest pH (2.7) were, respectively, detected with clpX and hupB as a lower indicator COGs (Supplementary Table 3). These results indicated that the community-wide transcriptional behaviors for low pH adaptation were closely related to the AMD pH value, though that was not remarkably different between the AMD environment (Table 1).
Carbon assimilation
As typical of other AMD environments, all the four AMD samples contained limited DOC (2.9–6.8 mg l-1; Table 1). Our analysis indicated that Acidithiobacillus spp. and/or Leptospirillum spp. were the main carbon fixers in the analyzed AMD communities, as the genes encoding the key enzymes for Calvin–Benson–Bassham cycle and reductive tricarboxylic acid cycle were highly expressed (Figure 3 and Supplementary Table 2), supporting the findings from previous transcriptomic or metaproteomic analyses of other AMD environments. Notably, the collective transcriptional activities of carbon fixing genes were much lower in the FK community (Supplementary Figures 4b and c), which harbored multiple higher indicator COGs for DOC assimilation and metabolism (Supplementary Table 3), including sugar and amino-acid transporters and glucose and alcohol dehydrogenases. Our analysis indicated that the microbes in FK AMD, especially the active heterotrophic Acidiphilium spp., likely obtain carbon resources from the environment (DOC=6.8 mg l-1; Table 1).
Nitrogen assimilation
As reported for other AMD environment, the concentration of nitrogen resources (for example, ammonium, nitrate, nitrite) was under detection limits (<0.05 mg l-1) in all analyzed AMD samples. Therefore, the knowledge of nitrogen fixation and assimilation mechanisms used by the AMD microorganisms is critical to the understanding of how they respond and adapt to the nitrogen-limited conditions. Atmospheric N2, ammonium, nitrite and nitrate are important inorganic nitrogen resources for microorganisms. Direct observation of nitrogen fixation in low pH conditions has not been made, and expression of the nitrogen-fixing genes were not identified in previous studies of AMD communities. However, our transcriptional analysis detected nitrogen-fixation transcripts (including nifD, nifK and nifH) in all the four communities (Figure 3), which were associated with L. ferrooxidans (group I), L. ferrodiazotrophum (group III), At. ferrivorans and Acidithiobacillus sp. GGI-221. This result indicated the key role of these taxa in nitrogen fixation of the communities, despite the relatively low abundance of the nitrogen-fixation transcripts (5–27 transcripts). The genes for ammonium transporter (amt) showed high transcriptional activities in all communities (Figure 3). Likewise, genes encoding the glutamine synthetase (glnA) and glutamate synthase (gltBD), which would permit the incorporation of ammonium into glutamine and then to glutamate for utilization, were also highly expressed (Figure 3), as reported by in other AMD environments. The glnA was identified as a higher indicator COG of YFS community (Supplementary Table 3), indicating a high need of nitrogen resources for the populated microorganism. However, the genes encoding enzymes for the utilization of nitrate and nitrite (for example, narK, nasA, nasB, nirA, nirB) exhibited very low transcriptional activities (Figure 3). Together, these results indicated that the AMD communities likely obtained nitrogen resources via nitrogen fixation and ammonium assimilation. This scenario is reasonable, as the analyzed samples were from open AMD environments where external ammonium inputs are highly possible.
Phosphate assimilation
Phosphate is vital for the synthesis of many biomacromolecules, and could also help to deal with the low pH stress via cytoplasmic buffering of H+. The genes of phosphate transport system (pstSCAB) were highly abundant in our cDNA data sets (Figure 3), which were with the transcriptionally active taxa of Acidithiobacillus, Leptospirillum and Acidiphilium and other less active taxa. These results indicated the ubiquitous behavior of phosphate uptake for the AMD microorganisms, especially the active taxa, which was supported by the transcription of the putative phosphate regulon response regulator gene of phoB in them (Figure 3; ). Furthermore, previous studies have found that the expression of these genes seemed to be upregulated under phosphate starvation for AMD microorganisms like Acidithiobacillus and Leptospirillum spp.. Although the concentration of phosphate could not be determined in our AMD environments because of its low content, it is reasonable to speculate (based on the high expression of pstSCAB and phoB) that the AMD communities, especially that of YFP, which exhibited the highest expression levels of these genes (Figure 3; pstS and pstC were higher indicator COGs of YFP, Supplementary Table 3), may encounter a phosphate limited condition. The coprecipitation of phosphate with Fe3+ and Al3+, which were also with high concentrations in the YFP AMD (Table 1), may partially account for this scenario. Meanwhile, the transcripts for transporters of phosphonate and polyphosphate were also detected (phnE and ppk; Figure 3), indicating multiple strategies for phosphorus resources and further supporting the speculated phosphate limited condition.
Energy generation
Energy generation is crucial for microorganisms to drive physiologically important processes and thus survive in extreme environments. Genes for ATPase (F-type), which makes use of pH gradient (pH is typically 104–106 times higher outside of the cell in AMD) to uptake protons to generate ATP, were abundantly detected in the cDNA data sets (Figure 3 and Supplementary Table 2). The obtained protons are usually coupled with O2 to generate H2O with the consumption of electrons from ferrous iron (Fe2+) and/or sulfur oxidation. Our data showed that genes encoding the key proteins for Fe2+ oxidation, including the rusticyanin of Acidithiobacillus spp. and cytochrome 572 and cytochrome 579 of Leptospirillum spp., were highly expressed (Figure 3 and Supplementary Table 2), indicating that these active populations may generate energy through iron oxidation in the AMD communities. The FK community contributed the fewest transcripts in Fe2+ oxidation, the low availability of Fe2+ (characterized by low Fe2+/Fe3+ ratio; Table 1) and dissolved oxygen of the FK AMD may partially account for this scenario. Also, multiple sulfur oxidation transcripts were detected (Figure 3), including those for sulfur oxidation multienzyme complex, sulfide:quinone oxidoreductase, thiosulfate:quinone oxidoreductase, and tetrathionate hydrolase, indicating the activity of sulfur oxidizing-based energy metabolisms. Notably, our analyses showed that sulfur oxidation was mainly executed by the less active taxa of At. thiooxidans and At. caldus, although the active taxa of At. ferrivorans and L. ferrodiazotrophum may also execute this function.
Environmental stress
Molecular chaperones are capable of helping with protein folding and refolding for stress resistance, multiple associated transcripts were detected with high abundances (Figure 3 and Supplementary Table 2). The DBS community harbored three lower indicator COGs for chaperons, whereas the FK, YFS and YFP communities were detected with 1, 3 and 2 chaperones associated higher indicator COGs (Supplementary Table 3), likely indicating a relatively benign environment of the DBS AMD compared with the other three. However, the DBS community harbored the most transcripts for heavy metal resistance, including those for Cd, Cr, Zn, Co, As, Ag, Mn and Hg (Figure 3). Notably, DBS community was detected with three higher indicator COGs (czcA, czcB, czcD; Figure 3), which were responsible for Co2+/Zn2+/Cd2+ efflux (Supplementary Table 3), this may be due to the high concentrations of Zn and Cd in DBS AMD (Table 1). Moreover, genes involved in defense against oxidative stress were also highly expressed (Figure 3), including those encoding the peroxiredoxin (ahpC), superoxide dismutase (sodA) and hydroperoxide reductase (dnaX), with the majority of which was associated with the active taxa (Figure 1c), supporting their ecological success in the AMD. Collectively, our analyses thus confirmed the diverse stress resistance mechanisms that is used by AMD microorganisms to survive and thrive in the extreme environments.
Other functional activities
Four and six transposase associated with higher indicator COGs were, respectively, detected in the communities of DBS and FK, where one lower indicator COG for transposase was identified in both YFS and YFP communities (Supplementary Table 3). This result indicated higher activities of the former communities in genomic material rearrangement for environmental adaptation. In addition, the DBS community harbored one higher indicator COG for S-adenosylmethionine decarboxylase associated with At. ferrivorans and At. ferrooxidans, two for pilus assembly proteins associated with At. ferrivorans, and two for type II and III secretion system proteins associated with At. ferrooxidans (Supplementary Table 3), indicating a highly active behavior of quorum sensing and biofilm formation for microorganisms in this environment.
Organism-wide comparative gene transcriptional behaviors
The phylogenetically divergent taxa in natural communities may exhibit distinct transcriptional profiles in response and adaptation to different biotic or abiotic factors. Hierarchical clustering analysis of the top three most active taxa in each AMD community (Supplementary Figure 4) based on their DNA and cDNA COGs abundances showed that the same taxa harbored similar metabolic potentials in different communities as expected but generally exhibited varying transcriptional behaviors (Supplementary Figure 5), indicating distinct response and adaptation mechanisms under different environmental conditions (Table 1). To further reveal this, detailed analyses were conducted for the organisms of At. ferrivorans and L. ferrodiazotrophum, both of which were among the most active taxa in three of the four AMD communities (Supplementary Figure 4).
Case study of At. ferrivorans. The psychrotolerant acidophile At. ferrivorans was highly active in DBS, YFS and YFP (Supplementary Figure 4) but with low abundance and activity in FK, likely due to the high solution temperature (43.3 oC; Table 1). Our analyses detected 211 genes (1831 in total) of At. ferrivorans with significantly different transcriptional levels across the three communities (P<0.05, two-tailed Fisher's exact test), although those in DBS and YFP exhibited generally more similar activities (Figure 4a). Functional analysis of these transcripts indicated that At. Ferrivorans in these communities exhibited different activities spanning a broad range of functions.
Thirty eight significantly different transcripts were associated with information storage and processing, especially those for translation, ribosomal structure and biogenesis (COG J; Figure 4b). These transcripts mainly were for ribosomal proteins, which could indicate the high growth rates of At. ferrivorans in these communities as was further supported by the high expression of genes for RNA polymerase (Figure 4c). Forty eight significant transcripts were involved in cellular processes and signaling (Figure 4b). Notably, the three genes for chaperonins of GroEL (Hsp60), dnaK and htpG (Hsp90) all exhibited a significant upregulation in YFS and YFP (Figure 4c). This was likely due to the much higher temperatures of these two samples compared with DBS (Table 1), as these chaperonins are well-known proteins, responding to heat-shock, although they could also deal with other environmental stresses.
The majority of the significantly different transcripts (106 genes; Figure 4b) were associated with metabolism, especially for energy production and conversion (COG C; 25 transcripts). At. Ferrivorans could generate energy via both iron and sulfur oxidation. Twelve out of the 14 genes in the rus operon for iron oxidation and nine genes for sulfur oxidation were expressed. Interestingly, At. ferrivorans in YFS contributed more transcripts for sulfur oxidation, and fewer for iron oxidation, compared with that in DBS and YFP (Figure 4c). This may be associated with the carbon-fixation activity (via the Calvin–Benson–Bassham pathway), which was most active for At. ferrivorans in YFS. This activity requires electrons for the reduction of NAD+ to NADH, the significant upregulation of carbon fixing genes in At. ferrivorans of YFS was supported by the significant upregulation of genes encoding NADH dehydrogenase complex, and sulfur oxidation is a more effective strategy to provide electrons compared with Fe2+ oxidation; on the other hand, carboxysomes may be produced in At. ferrivorans of YFS, as indicated by the significant higher expression of involved genes, suggesting a carbon-limiting condition, as reported in other Acidithiobacillus spp.; moreover, it seemed that the more energetic substrate of sulfur tended to need for more cellular carbon during growth, as suggested for At. ferrooxidans. At. ferrivorans in all three communities could fix nitrogen, whereas that in YFS showed significantly higher activities of glutamine synthetase and glutamate synthase (Figure 4c), indicating a much need for nitrogen resources. In addition, At. ferrivorans in all three communities (especially in YFS) showed high activities in the uptake of phosphate. Moreover, At. ferrivorans in DBS and YFP may execute assimilatory sulfur reduction for the utility of sulfur as indicated by the upregulation of sulfite reductase genes of cysI, cysJ and cysH. Collectively, these lines of evidence indicate that At. ferrivorans in YFS contributed more for carbon, nitrogen and phosphate assimilation, whereas those in DBS and YFP were likely active in sulfur assimilation.
Case study of L. ferrodiazotrophum. The recently characterized iron-oxidizing and free-living nitrogen fixer L. ferrodiazotrophum represented >5% of the total transcripts of the DBS, FK and YFS communities (Supplementary Figure 4). A total of 1997 transcripts were identified, 223 of which exhibited significantly different expression levels among the three communities (Figure 5a).
Similar to those of At. ferrivorans, the majority of these transcripts (117 transcripts; Figure 5b) were associated with metabolism-related functions. L. ferrodiazotrophum was considered as a keystone species in the Richmond Mine AMD ecosystems for the ability of nitrogen fixation; however, no proteins involved in nitrogen fixation were detected in previous metaproteomics studies. Seven of the 16 genes of the nif operon of L. ferrodiazotrophum were expressed in the three AMD communities (Figure 5c), with a total of 17 transcripts. L. ferrodiazotrophum in YFS contributed the most in nitrogen fixation, with >10 times of associated transcripts in abundance (0.26%) compared with those in DBS and FK. For the carbon-fixation activity, all genes of the reductive tricarboxylic acid cycle in L. ferrodiazotrophum were expressed (Figure 5c), and those in YFS accounted for a total abundance of 10.9%, as compared with 4.6% and 4.2% for those in DBS and FK (Supplementary Table 5). The genes for Fe2+ and sulfur oxidation (that is, sulfide-quinone reductase) were also detected, with the highest expression levels in YFS. These results suggest that this organism in YFS contributed much in the fixation of carbon and nitrogen via Fe2+ and sulfur oxidation, as At. ferrivorans did in the same community (see above). We further identified the genes for proteasome, which collectively accounted for a transcript abundance of 0.44%, 1.45% and 0.93% in DBS, FK and YFS, respectively (Supplementary Table 5). Within the Bacteria, proteasome has only been found in actinobacteria and Leptospirillum group II and III, and this molecular machine is involved in defence against environmental stress via degrading the unneeded or damaged proteins. It is reasonable to speculate that the degraded proteins could be further utilized (as organic nitrogen resources) by both L. ferrodiazotrophum and other microorganisms in the AMD communities. Also detected for L. ferrodiazotrophum in all three communities were several transcripts involved in stress response to phage or virus, including those for clustered regularly interspaced short palindromic repeats associated (Cas) proteins and phage integrase proteins (Supplementary Table 5), implying the biotic stress in the extreme AMD environments.
Conclusions and perspectives
Our comparative metagenomic and metatranscriptomic analyses have provided a detailed gene transcriptional blueprint for the naturally occurring, low diversity microbial communities in the extreme AMD environments, demonstrating how these extraordinary microorganisms respond and adapt to the different physicochemical conditions at both community- and organism-level. The transcriptional analyses of dominant transcripts and indicator COGs revealed a high diversity of transcripts harbored by these acidophilic assemblages. These transcripts were associated with a wide range of functions, the expression levels of which were closely related to the physicochemical characteristics of the AMD systems. In particular, the detection of nitrogen-fixation transcripts provided clues for nitrogen-fixing activities in AMD communities. Detailed analysis of the transcriptional behaviors of the most active organisms revealed differential gene expression patterns, likely reflecting their distinct roles and life state in different communities. For example, both At. ferrivorans and L. ferrodiazotrophum in YFS contributed more transcripts for carbon and nitrogen assimilation than their counterparts in other communities. The ecological significance of less active taxa, including their irreplaceable role for the whole-community function as well as their contribution in community assembly and dynamics, has been documented in marine environment. However, with the current sequencing depth of 454 pyrosequencing and the inefficient removal of rRNA sequences from total RNA, we failed to obtain sufficient transcriptional information for the less active populations in the AMD communities, hindering the understanding of their response and adaptation mechanisms at gene transcription level. With the benefit of more efficient and unbiased rRNA-depletion approaches and the development of higher-throughput sequencing technologies (for example, Illumina HiSeq, ABI Solid), future studies could be designed to explore gene transcription profiles along environmental gradients or through time series for both dominant and rare taxa, and to reveal the transcriptional dynamics of microbial communities in response and adaptation to the changing environmental conditions or associated with sequential development stages.
References 62
- 1.
Appia-Ayme C Quatrini R Denis Y Denizot F Silver S Roberto F 2006 Microarray and bioinformatic analyses suggest models for carbon metabolism in the autotroph Acidithiobacillus ferrooxidansHydrometallurgy83273280
Not in our library
- 2.
Amaral-Zettler LA Zettler ER Theroux SM Palacios C Aguilera A Amils R 2011 Microbial community structure across the tree of life in the extreme Rio TintoISME J54250
Not in our library10.1038/ismej.2010.101
- 3.
Arrigo K 2004 Marine microorganisms and global nutrient cyclesNature437349355
Not in our library10.1038/nature04159
- 4.
Baker B Banfield J 2003 Microbial communities in acid mine drainageFEMS Microbiol Rev44139152
Not in our library10.1016/s0168-6496(03)00028-x
- 5.
Baker BJ Comolli LR Dick GJ Hauser LJ Hyatt D Dill BD 2010 Enigmatic, ultrasmall, uncultivated archaeaProc Natl Acad Sci USA10788068811
Not in our library10.1073/pnas.0914470107
- 6.
Baker BJ Tyson GW Webb RI Flanagan J Hugenholtz P Allen EE 2006 Lineages of acidophilic archaea revealed by community genomic analysisScience31419331935
Not in our library10.1126/science.1132690
- 7.
Baker-Austin C Dopson M 2007 Life in acid: pH homeostasis in acidophilesTrends Microbiol15165171
Not in our library10.1016/j.tim.2007.02.005
- 8.
Bertin PN Heinrich-Salmeron A Pelletier E Goulhen-Chollet F Arsène-Ploetze F Gallien S 2011 Metabolic diversity among main microorganisms inside an arsenic-rich ecosystem revealed by meta- and proteo-genomicsISME J517351747
Not in our library10.1038/ismej.2011.51
- 9.
Bird LJ Bonnefoy V Newman DK 2011 Bioenergetic challenges of microbial iron metabolismTrends Microbiol19330340
Not in our library10.1016/j.tim.2011.05.001
- 10.
Chen LX Li JT Chen YT Huang LN Hua ZS Hu M 2013 Shifts in microbial community composition and function in the acidification of a lead/zinc mine tailingsEnviron Microbiol1524312444
Not in our library10.1111/1462-2920.12114
- 11.
Cole JR Wang Q Cardenas E Fish J Chai B Farris RJ 2009 The Ribosomal Database Project: improved alignments and new tools for rRNA analysisNucleic Acids Res37d141d145
Not in our library10.1093/nar/gkn879
- 12.
De Mot R 2007 Actinomycete-like proteasomes in a gram-negative bacteriumTrends Microbiol15335338
Not in our library10.1016/j.tim.2007.06.002
- 13.
De Mot R Schoofs G Nagy I 2007 Proteome analysis of Streptomyces coelicolor mutants affected in the proteasome system reveals changes in stress-responsive proteinsArch Microbiol188257271
Not in our library10.1007/s00203-007-0243-8
- 14.
Denef VJ Banfield JF 2012 In situ evolutionary rate measurements show ecological success of recently emerged bacterial hybridsScience336462466
Not in our library10.1126/science.1218389
- 15.
Denef VJ Mueller RS Banfield JF 2010 AMD biofilms: using model communities to study microbial evolution and ecological complexity in natureISME J4599610
Not in our library10.1038/ismej.2009.158
- 16.
Franceschini A Szklarczyk D Frankild S Kuhn M Simonovic M Roth A 2013 STRING v9.1: protein-protein interaction networks, with increased coverage and integrationNucleic Acids Res41D808D815
Not in our library10.1093/nar/gks1094
- 17.
Frias-Lopez J Shi Y Tyson GW Coleman ML Schuster SC Chisholm SW 2008 Microbial community gene expression in ocean surface watersProc Natl Acad Sci USA10538053810
Not in our library10.1073/pnas.0708897105
- 18.
Galand PE Casamayor EO Kirchman DL Lovejoy C 2009 Ecology of the rare microbial biosphere of the Arctic OceanProc Natl Acad Sci1062242722432
Not in our library10.1073/pnas.0908284106
- 19.
Gifford SM Sharma S Booth M Moran MA 2013 Expression patterns reveal niche diversification in a marine microbial assemblageISME J7281198
Not in our library10.1038/ismej.2012.96
- 20.
Goebel BM Stackebrandt E 1994 Cultural and phylogenetic analysis of mixed microbial populations found in natural and commercial bioleaching environmentsAppl Environ Microbiol6016141621
Not in our library10.1128/aem.60.5.1614-1621.1994
- 21.
Goltsman DSA Denef VJ Singer SW VerBerkmoes NC Lefsrud M Mueller R 2009 Community genomic and proteomic analyses of chemoautotrophic iron-oxidizing “Leptospirillum rubarum” (Group II) and “Leptospirillum ferrodiazotrophum” (Group III) bacteria in acid mine drainage biofilmsAppl Environ Microbiol7545994615
Not in our library10.1128/aem.02943-08
- 22.
Goltsman DSA Dasari M Thomas BC Shah MB VerBerkmoes NC Hettich RL 2013 New group in the Leptospirillum clade-cultivation-independent community genomics, proteomics, and transcriptomics of the new species “Leptospirillum group IV UBA BS”Appl Environ Microbiol7953845393
Not in our library10.1128/aem.00202-13
- 23.
Grzmil B Wronkowski J 2006 Removal of phosphates and fluorides from industrial wastewaterDesalination189261268
Not in our library
- 24.
Guazzaroni ME Morgante V Mirete S Gonzalez-Pastor JE 2013 Novel acid resistance genes from the metagenome of the Tinto River, an extremely acidic environmentEnviron Microbiol1510881102
Not in our library10.1111/1462-2920.12021
- 25.
Hallberg KB Gonzalez-Toril E Johnson DB 2010 Acidithiobacillus ferrivorans, sp. nov.; facultatively anaerobic, psychrotolerant iron-, and sulfur-oxidizing acidophiles isolated from metal mine-impacted environmentsExtremophiles14919
Not in our library10.1007/s00792-009-0282-y
- 26.
He S Wurtzel O Singh K Froula JL Yilmaz S Tringe SG 2010 Validation of two ribosomal RNA removal methods for microbial metatranscriptomicsNat Methods7807812
Not in our library10.1038/nmeth.1507
- 27.
Huson DH Auch AF Qi J Schuster SC 2007 MEGAN analysis of metagenomic dataGenome Res17377386
Not in our library10.1101/gr.5969107
- 28.
Johnson DB Hallberg KB 2003 The microbiology of acidic mine watersRes Microbiol154466473
Not in our library10.1016/s0923-2508(03)00114-1
- 29.
Johnson DB Hallberg KB 2008 Carbon, iron and sulfur metabolism in acidophilic micro-organismsAdv Microb Physiol54201255
Not in our library10.1016/s0065-2911(08)00003-9
- 30.
Konings WN Albers S-J Koning S Driessen AJM 2002 The cell membrane plays a crucial role in survival of bacteria and archaea in extreme environmentsAntonie van Leeuwenhoek816172
Not in our library10.1023/a:1020573408652
- 31.
Kuang JL Huang LN Chen LX Hua ZS Li SJ Hu M 2012 Contemporary environmental variation determines microbial diversity patterns in acid mine drainageISME J710381050
Not in our library10.1038/ismej.2012.139
- 32.
Lamarche MG Wanner BL Crepin S Harel J 2008 The phosphate regulon and bacterial virulence: a regulatory network connecting phosphate homeostasis and pathogenesisFEMS Microbiol Rev32461473
Not in our library10.1111/j.1574-6976.2008.00101.x
- 33.
Lee J Sperandio V Frantz DE Longgood J Camilli A Phillips MA 2009 An alternative polyamine biosynthetic pathway is widespread in bacteria and essential for biofilm formation in Vibrio choleraeJ Biol Chem28498999907
Not in our library10.1074/jbc.m900110200
- 34.
Leigh JA Dodsworth JA 2007 Nitrogen regulation in bacteria and archaeaAnnu Rev Microbiol61349377
Not in our library10.1146/annurev.micro.61.080706.093409
- 35.
Li W Godzik A 2006 Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequencesBioinformatics2216581659
Not in our library10.1093/bioinformatics/btl158
- 36.
Liljeqvist M Rzhepishevska OI Dopson M 2013 Gene identification and substrate regulation provide insights into sulfur accumulation during bioleaching with the psychrotolerant acidophile Acidithiobacillus ferrivoransAppl Environ Microbiol79951957
Not in our library10.1128/aem.02989-12
- 37.
Liu Z Klatt CG Wood JM Rusch DB Ludwig M Wittekindt N 2011 Metatranscriptomic analyses of chlorophototrophs of a hot-spring microbial matISME J512791290
Not in our library10.1038/ismej.2011.37
- 38.
Méndez-García C Mesa V Sprenger RR Richter M Diez MS Solano J 2014 Microbial stratification in low pH oxic and suboxic macroscopic growths along an acid mine drainageISME J812591274
Not in our library10.1038/ismej.2013.242
- 39.
Musat N Halm H Winterholler B Hoppe P Peduzzi S Hillion F 2008 A single-cell view on the ecophysiology of anaerobic phototrophic bacteriaProc Natl Acad Sci1051786117866
Not in our library10.1073/pnas.0809329105
- 40.
Mogk A Deuerling E Vorderwülbecke S Vierling E Bukau B 2003 Small heat shock proteins, ClpB and the DnaK system form a functional triad in reversing protein aggregationMol Microbiol50585595
Not in our library10.1046/j.1365-2958.2003.03710.x
Cited by papers we hold 1
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.