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Metabolically active eukaryotic communities in extremely acidic mine drainage.

ABSTRACT: Acid mine drainage (AMD) microbial communities contain microbial eukaryotes (both fungi and protists) that confer a biofilm structure and impact the abundance of bacteria and archaea and the community composition via grazing and other mechanisms. Since prokaryotes impact iron oxidation rates and thus regulate AMD generation rates, it is important to analyze the fungal and protistan populations. We utilized 18S rRNA and beta-tubulin gene phylogenies and fluorescent rRNA-specific probes to characterize the eukaryotic diversity and distribution in extremely acidic (pHs 0.8 to 1.38), warm (30 to 50 degrees C), metal-rich (up to 269 mM Fe(2+), 16.8 mM Zn, 8.5 mM As, and 4.1 mM Cu) AMD solutions from the Richmond Mine at Iron Mountain, Calif. A Rhodophyta (red algae) lineage and organisms from the Vahlkampfiidae family were identified. The fungal 18S rRNA and tubulin gene sequences formed two distinct phylogenetic groups associated with the classes Dothideomycetes and Eurotiomycetes. Three fungal isolates that were closely related to the Dothideomycetes clones were obtained. We suggest the name "Acidomyces richmondensis" for these isolates. Since these ascomycete fungi were morphologically indistinguishable, rRNA-specific oligonucleotide probes were designed to target the Dothideomycetes and Eurotiomycetes via fluorescent in situ hybridization (FISH). FISH analyses indicated that Eurotiomycetes are generally more abundant than Dothideomycetes in all of the seven locations studied within the Richmond Mine system. This is the first study to combine the culture-independent detection of fungi with in situ detection and a demonstration of activity in an acidic environment. The results expand our understanding of the subsurface AMD microbial community structure.

SUBMITTER: Baker BJ

PROVIDER: S-EPMC522060 | biostudies-literature | 2004 Oct

REPOSITORIES: biostudies-literature

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Metabolically active eukaryotic communities in extremely acidic mine drainage.

Baker Brett J BJ Lutz Michelle A MA Dawson Scott C SC Bond Philip L PL Banfield Jillian F JF

Applied and environmental microbiology 20041001 10

Acid mine drainage (AMD) microbial communities contain microbial eukaryotes (both fungi and protists) that confer a biofilm structure and impact the abundance of bacteria and archaea and the community composition via grazing and other mechanisms. Since prokaryotes impact iron oxidation rates and thus regulate AMD generation rates, it is important to analyze the fungal and protistan populations. We utilized 18S rRNA and beta-tubulin gene phylogenies and fluorescent rRNA-specific probes to charact ...[more]

PMID: 15466574

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Project description:The microbial community of acid mine drainage (AMD) fascinates researchers by their adaption and roles in shaping the environment. Molecular surveys have recently helped to enhance the understanding of the distribution, adaption strategy, and ecological function of microbial communities in extreme AMD environments. However, the interactions between the environment and microbial community of extremely acidic AMD (pH <3) from different mining areas kept unanswered questions. Here, we measured physicochemical parameters and profiled the microbial community of AMD collected from four mining areas with different mineral types to provide a better understanding of biogeochemical processes within the extremely acidic water environment. The prominent physicochemical differences across the four mining areas were in SO4 2-, metal ions, and temperature, and distinct microbial diversity and community assemblages were also discovered in these areas. Mg2+ and SO4 2- were the predominant factors determining the microbial structure and prevalence of dominant taxa in AMD. Leptospirillum, Ferroplasma, and Acidithiobacillus were abundant but showed different occurrence patterns in AMD from different mining areas. More diverse communities and functional redundancy were identified in AMD of polymetallic mining areas compared with AMD of copper mining areas. Functional prediction revealed iron, sulfur, nitrogen, and carbon metabolisms driven by microorganisms were significantly correlated with Mg2+ and SO4 2-, Ca2+, temperature, and Fe2+, which distinguish microbial communities of copper mine AMD from that of polymetallic mine AMD. In summary, microbial diversity, composition, and metabolic potential were mainly shaped by Mg2+ and SO4 2- concentrations of AMD, suggesting that the substrate concentrations may contribute to the distinct microbiological profiles of AMD from different mining areas. These findings highlight the microbial community structure in extremely acidic AMD forming by types of minerals and the interactions of physicochemical parameters and microbiology, providing more clues of the microbial ecological function and adaptation mechanisms in the extremely acidic environment.

Project description:Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic ?-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

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Metabolically active eukaryotic communities in extremely acidic mine drainage.

Publications

Metabolically active eukaryotic communities in extremely acidic mine drainage.

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