Microbial diversity and community structure dynamics in acid mine drainage: Acidic fire with dissolved heavy metals

Abstract

Acid mine drainage (AMD) is one of the leading causes of environmental pollution and is linked to public health and ecological consequences. Microbes-mineral interaction generates AMD, but microorganisms can also remedy AMD pollution. Exploring the microbial response to AMD effluents may reveal survival strategies in extreme ecosystems. Three distinct sites across a mine (inside the mine, the entrance of the mine, and outside) were selected to study their heavy metal concentrations due to significant variations in pH and physicochemical characteristics, and high-throughput sequencing was carried out to investigate the microbial diversity. The metal and ion concentrations followed the order SO42−, Fe, Cu, Zn, Mg, Pb, Co, Cr, and Ni from highest to lowest, respectively. Maximum sequences were allocated to Proteobacteria and Firmicutes. Among archaea, the abundance of Thaumarchaeota and Euryarchaeota was higher outside of mine. Most of the genera (23.12 %) were unclassified and unknown. The average OTUs (operational taxonomic units) were significantly higher outside the mine; however, diversity indices were not significantly different across the mine sites. Hierarchical clustering of selective genera and nMDS ordination of OTUs displayed greater segregation resolution inside and outside of mine, whereas the entrance samples clustered with greater similarity. Heterogeneous selection might be the main driver of community composition outside the mine, whereas stochastic processes became prominent inside the mine. However, the ANOSIM test shows a relatively even distribution of community composition within and between the groups. Microbial phyla showed both positive and negative correlations with physicochemical factors. A greater number of biomarkers were reported outside of the mine. Predictive functional investigation revealed the existence of putative degradative, metabolic, and biosynthetic pathways. This study presents a rare dataset in our understanding of microbial diversity and distribution as shaped by the ecological gradient and potential novelty in phylogenetic/taxonomic diversity in AMD, with potential biotechnological applications.