Comparison and Interpretation of Taxonomical Structure of Bacterial Communities in Two Types of Lakes on Yun-Gui plateau of China

Sci Rep. 2016 Jul 27:6:30616. doi: 10.1038/srep30616.

Abstract

Bacterial communities from freshwater lakes are shaped by various factors such as nutrients, pH value, temperature, etc. Their compositions and relative abundances would undergo changes to adapt the changing environments, and in turn could affect the environments of freshwater lakes. Analyses of the freshwater lake's bacterial communities under different environments would be of pivotal importance to monitor the condition of waterbody. In this study, we have collected freshwater samples from two lakes on Yun-Gui plateau of China, Lake Dianchi and Lake Haixihai, and analyzed the bacterial community structures from these samples based on 16S rRNA sequencing. Results have shown that: Firstly, the bacterial community of these samples have very different taxonomical structures, not only between two lakes but also among the intra-groups for samples collected from Dianchi. Secondly, the differences between samples from two lakes are highly associated with the chemical-geographical properties of the two lakes. Thirdly, for samples of Dianchi and Haixihai, analytical results of physicochemical, taxonomical structure and relative abundance of community revealed that extreme physicochemical factors caused by human activities have strongly affected the bacterial ecosystem in Dianchi. These results have clearly indicated the importance of combining biological profiling and chemical-geographical properties for monitoring Chinese plateau freshwater bacterial ecosystem, which could provide clues for Chinese freshwater ecosystem remediation on plateau.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacteria / genetics*
  • Biodiversity
  • China
  • Ecosystem
  • Lakes / microbiology*
  • Microbiota* / genetics
  • Microbiota* / physiology
  • RNA, Ribosomal, 16S
  • Water Microbiology

Substances

  • RNA, Ribosomal, 16S