A unique terrace with sharp gradient of environmental conditions was selected to study the microbial response and survival strategies to the extreme environments introduced by acid mine drainage (AMD) contamination. A combination of geochemical analyses, metagenomic sequencing, ex-situ microcosm setups, and statistical analyses were used to investigate the environment-microbe interactions. The microbial communities and metabolic potentials along the terrace were studied by focusing on the genes associated with important biogeochemical processes (i.e., C, N, S cycling and metal resistance). Results show that the variations of geochemical parameters substantially shaped the indigenous microbial communities. Sharp environmental gradients also impacted the microbial metabolic potentials, especially for C, N, and S cycling. Although the relative abundances of carbon fixing genes did not significantly vary along the environmental gradients, the taxa for carbon fixation varied significantly in more contaminated fields versus less contaminated fields, indicating the effects of AMD contamination on the autotrophic microbial communities. AMD input also influenced the N cycling, especially for nitrogen fixation and dissimilatory nitrate reduction to ammonium (DNRA). In addition, ex situ experiments were undertaken to evaluate the effects of AMD contamination on nitrogen fixation rates. Random Forest (RF) analysis indicated that nitrate, pH, total N, TOC exhibited positive correlations with the rates of nitrogen fixation while total Fe, Fe(III), and sulfate showed negative effects. Two co-occurrence networks at taxonomic and genomic levels indicated that geochemical parameters such as pH, TOC, total N, total S, and total Fe substantially influenced the innate microbial communities and their metabolic potentials. The current study provides an understanding for microbial response to AMD contamination and lays the foundation for future potential AMD bioremediation.
All Science Journal Classification (ASJC) codes
- Environmental Science(all)
- Co-occurrence network
- Nitrogen fixation
- Random Forest