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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. [ABSTRACT FROM AUTHOR]

High-throughput sequencing is expanding our knowledge of microbial diversity in the environment. Still, understanding the metabolic potentials and ecological roles of rare and uncultured microbes in natural communities remains a major challenge. To this end, we applied a 'divide and conquer' strategy that partitioned a massive metagenomic data set (>100 Gbp) into subsets based on K-mer frequency in sequence assembly to a low-diversity acid mine drainage (AMD) microbial community and, by integrating with an additional metatranscriptomic assembly, successfully obtained 11 draft genomes most of which represent yet uncultured and/or rare taxa (relative abundance <1%). We report the first genome of a naturally occurring Ferrovum population (relative abundance >90%) and its metabolic potentials and gene expression profile, providing initial molecular insights into the ecological role of these lesser known, but potentially important, microorganisms in the AMD environment. Gene transcriptional analysis of the active taxa revealed major metabolic capabilities executed in situ, including carbon- and nitrogen-related metabolisms associated with syntrophic interactions, iron and sulfur oxidation, which are key in energy conservation and AMD generation, and the mechanisms of adaptation and response to the environmental stresses (heavy metals, low pH and oxidative stress). Remarkably, nitrogen fixation and sulfur oxidation were performed by the rare taxa, indicating their critical roles in the overall functioning and assembly of the AMD community. Our study demonstrates the potential of the 'divide and conquer' strategy in high-throughput sequencing data assembly for genome reconstruction and functional partitioning analysis of both dominant and rare species in natural microbial assemblages. [ABSTRACT FROM AUTHOR]

A wide array of microorganisms survive and thrive in extreme environments. However, we know little about the patterns of, and controls over, their large-scale ecological distribution. To this end, we have applied a bar-coded 16S rRNA pyrosequencing technology to explore the phylogenetic differentiation among 59 microbial communities from physically and geochemically diverse acid mine drainage (AMD) sites across Southeast China, revealing for the first time environmental variation as the major factor explaining community differences in these harsh environments. Our data showed that overall microbial diversity estimates, including phylogenetic diversity, phylotype richness and pairwise UniFrac distance, were largely correlated with pH conditions. Furthermore, multivariate regression tree analysis also identified solution pH as a strong predictor of relative lineage abundance. Betaproteobacteria, mostly affiliated with the 'Ferrovum' genus, were explicitly predominant in assemblages under moderate pH conditions, whereas Alphaproteobacteria, Euryarchaeota, Gammaproteobacteria and Nitrospira exhibited a strong adaptation to more acidic environments. Strikingly, such pH-dependent patterns could also be observed in a subsequent comprehensive analysis of the environmental distribution of acidophilic microorganisms based on 16S rRNA gene sequences previously retrieved from globally distributed AMD and associated environments, regardless of the long-distance isolation and the distinct substrate types. Collectively, our results suggest that microbial diversity patterns are better predicted by contemporary environmental variation rather than geographical distance in extreme AMD systems. [ABSTRACT FROM AUTHOR]