Diversity and functional profile of bacterial communities at Lancaster acid mine drainage dam, South Africa as revealed by 16S rRNA gene high-throughput sequencing analysis

  • Thabile Lukhele
  • Ramganesh Selvarajan
  • Hlengilizwe Nyoni
  • Bheki Brilliance Mamba
  • Titus Alfred Makudali MsagatiEmail author
Original Paper


This study surveyed physicochemical properties and bacterial community structure of water and sediments from an acid mine drainage (AMD) dam in South Africa. High-throughput sequence analysis revealed low diversity bacterial communities affiliated within 8 dominant phyla; Acidobacteria, Actinobacteria, Chloroflexi, Firmicutes, Nitrospirae, Proteobacteria, Saccharibacteria, and ca. TM6_(Dependentiae). Acidiphilium spp. which are common AMD inhabitants but rarely occur as dominant taxa, were the most abundant in both AMD water and sediments. Other groups making up the community are less common AMD inhabitants; Acidibacillus, Acidibacter, Acidobacterium, Acidothermus, Legionella, Metallibacterium, Mycobacterium, as well as elusive taxa (Saccharibacteria, ca. TM6_(Dependentiae) and ca. JG37-AG-4). Although most of the taxa are shared between sediment and water communities, alpha diversity indices indicate a higher species richness in the sediments. From canonical correspondence analysis, DOC, Mn, Cu, Cr, Al, Fe, Ca were identified as important determinants of community structure in water, compared to DOC, Ca, Cu, Fe, Zn, Mg, K, Mn, Al, sulfates, and nitrates in sediments. Predictive functional profiling recovered genes associated with bacterial growth and those related to survival and adaptation to the harsh environmental conditions. Overall, the study reports on a distinct AMD bacterial community and highlights sediments as microhabitats with higher species richness than water.


Acid mine drainage 16S rRNA gene High-throughput sequencing Bacterial diversity 



The work was supported by the University of South Africa and the National Research Foundation of South Africa through a Grant (SFH170705248759), also authors would like to acknowledge Center for High Performance (CHPC), Pretoria for providing computational support for Metagenomic analysis.

Supplementary material

792_2019_1130_MOESM1_ESM.docx (116 kb)
Supplementary material 1 (DOCX 115 kb)


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© Springer Japan KK, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Nanotechnology and Water Sustainability Research Unit, College of Science Engineering and TechnologyUniversity of South AfricaJohannesburgSouth Africa
  2. 2.College of Agriculture and Environmental SciencesUniversity of South AfricaJohannesburgSouth Africa
  3. 3.State Key Laboratory of Separation and Membranes, Membrane ProcessesNational Center for International Joint Research on Membrane Science and TechnologyTianjinPeople’s Republic of China

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