ABSTRACT
Metagenomic approach permits us to obtain the latent resources from culturable and unculturable microorganisms in ecosystem. In this study, high-throughput sequencing was practiced to comprehensively probe prokaryotic community within extreme acidic environment of Baiyin open-pit mine stope, which varied in pH and other physicochemical parameters. Bioinformatics analysis was further accomplished to process millions of Illumina reads and analyzed alpha and beta diversities, and prokaryotic community profile in different samples obtained from the acidic mine stope. Diversity indices such as ACE, Chao, Shannon, and Simpson were varied among samples. Both taxon richness and evenness were significantly higher in the solid samples than that of the water samples. Taxonomic diversity was unexpectedly higher within confined pit ecosystem. Most of the sequences were assigned to phyla Proteobacteria, Firmicutes, and Acidobacteria. In archaea, Euryarchaeota and Thaumarchaeota were major phyla reported, however, archaea occupied very little share in the metagenome. At class level, variation in community structure was higher within samples. Among iron- and sulfur-related acidophiles, 30.8% of the sequences were unidentified at genera level, while the remaining were dominated by sulfur and/or iron oxidizing Acidithiobacillus and heterotrophic Acidiphilum related groups. The community profile of solid and water groups was different and metagenomic biomarkers were higher in solid, while acidophiles and archaea were reported only in water group by using LEfSe. Among samples, community structure and abundance was varied in terms of OTUs abundance, which clearly indicates spatial variation and proposed the influence of physicochemical and geochemical properties on phylogenetic diversity. This study offers numerous treasured datasets for better understanding the community composition under the influence of geochemical and physicochemical factors and possible novelty in terms of taxonomic/phylogenetic diversity in acidic ecosystem.
Acknowledgment
We are thankful to Xiaolan Zhao, Tinzhu Lei, and Shengyin Zhang for ICP-OES analysis.