Metagenomic exploration reveals high levels of microbial arsenic metabolism genes in activated sludge and coastal sediments

Lin Cai, Ke Yu, Ying Yang, Bao Wei Chen, Xiangdong Li, Tong Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

67 Citations (Scopus)

Abstract

Arsenic contamination in a water system is an urgent environmental problem that has caused severe endemic arsenicosis in south and southeast Asian countries. It is well known that microbially mediated arsenic metabolism can enhance arsenic mobility, bioavailability, and toxicity. Here, for the first time, we applied the Illumina high-throughput metagenomic and metatranscriptomic approaches to study the distribution, diversity, abundance, and expression of microbial arsenic metabolism genes in activated sludge and five coastal sediments. An average depth of ~2.6 Gb clean data for each sample was finally obtained for BLAST analysis after quality filtration and normalization. The results revealed that: (1) highly diverse arsenic metabolism-like genes were found and the overall abundance varied from 0.18 % to 0.26 % in the six metagenomic data sets; (2) arsenic metabolism-like genes were expressed with extremely low levels or no expression at all in activated sludge; and (3) the distribution, diversity, and abundance of aioA-like, arrA-like, arsB-like, ACR3-like, and arsM-like genes varied significantly in the six surveyed environments. This study provided a novel perspective on understanding the ecology of arsenic metabolism in different water environments using high-throughput sequencing technique.
Original languageEnglish
Pages (from-to)9579-9588
Number of pages10
JournalApplied Microbiology and Biotechnology
Volume97
Issue number21
DOIs
Publication statusPublished - 1 Nov 2013

Keywords

  • Arsenic
  • Arsenic metabolism
  • Arsenic metabolism genes
  • High-throughput sequencing
  • Metagenome
  • Metatranscriptome

ASJC Scopus subject areas

  • Biotechnology
  • Applied Microbiology and Biotechnology

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