A metagenomic approach to decipher the indigenous microbial communities of arsenic contaminated groundwater of Assam

• Published in: Genomics data Vol. 12; no. C; pp. 89 - 96
• Main Authors: Das, Saurav, Bora, Sudipta Sankar, Yadav, R.N.S., Barooah, Madhumita
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.06.2017; Elsevier
• Subjects: Actinobacteria; aquifers; arsenates; Arsenic; Assam; Bacteria; Bacteroidetes; biochemical pathways; data collection; Firmicutes; functional diversity; Groundwater; India; iron; metabolism; Metagenomic; metagenomics; microbial communities; open reading frames; operon; Planctomycetes; proteins; Proteobacteria; quality control; Regular; river deltas; Siderophore; Verrucomicrobia; India; Proteobacteria; Arsenic; Assam; Groundwater; Siderophore; Metagenomic; Bacteria
• ISSN: 2213-5960; 2213-5960
• DOI: 10.1016/j.gdata.2017.03.013

Metagenomic approach was used to understand the structural and functional diversity present in arsenic contaminated groundwater of the Ganges Brahmaputra Delta aquifer system. A metagene dataset (coded as TTGW1) of 89,171 sequences (totaling 125,449,864 base pairs) with an average length of 1406bps was annotated. About 74,478 sequences containing 101,948 predicted protein coding regions passed the quality control. Taxonomical classification revealed abundance of bacteria that accounted for 98.3% of the microbial population of the metagenome. Eukaryota had an abundance of 1.1% followed by archea that showed 0.4% abundance. In phylum based classification, Proteobacteria was dominant (62.6%) followed by Bacteroidetes (11.7%), Planctomycetes (7.7%), Verrucomicrobia (5.6%), Actinobacteria (3.7%) and Firmicutes (1.9%). The Clusters of Orthologous Groups (COGs) analysis indicated that the protein regulating the metabolic functions constituted a high percentage (18,199 reads; 39.3%) of the whole metagenome followed by the proteins regulating the cellular processes (22.3%). About 0.07% sequences of the whole metagenome were related to genes coding for arsenic resistant mechanisms. Nearly 50% sequences of these coded for the arsenate reductase enzyme (EC. 1.20.4.1), the dominant enzyme of ars operon. Proteins associated with iron acquisition and metabolism were coded by 2% of the metagenome as revealed through SEED analysis. Our study reveals the microbial diversity and provides an insight into the functional aspect of the genes that might play crucial role in arsenic geocycle in contaminated ground water of Assam.