一种宏基因组方法来破译阿萨姆邦砷污染地下水的本地微生物群落

Saurav Das , Sudipta Sankar Bora , R.N.S. Yadav , Madhumita Barooah
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引用次数: 42

摘要

采用宏基因组方法研究了恒河-雅鲁藏布江三角洲含水层系统砷污染地下水的结构和功能多样性。对平均长度为1406 bps的89,171个序列(总计125,449,864个碱基对)的metagene数据集(编码为TTGW1)进行了注释。共有74,478个序列包含101,948个预测蛋白编码区通过了质量控制。分类显示细菌丰度占宏基因组微生物种群的98.3%。真核生物的丰度为1.1%,其次是古生物,丰度为0.4%。在门分类中,变形菌门占优势(62.6%),其次是拟杆菌门(11.7%)、植物菌门(7.7%)、Verrucomicrobia(5.6%)、放线菌门(3.7%)和厚壁菌门(1.9%)。COGs分析表明,调节代谢功能的蛋白占较高的比例(18,199 reads;39.3%),其次是调节细胞过程的蛋白(22.3%)。整个宏基因组中约有0.07%的序列与抗砷机制相关。其中近50%的序列编码砷酸盐还原酶(EC)。1.20.4.1),是ars操纵子的优势酶。通过SEED分析发现,与铁获取和代谢相关的蛋白质被2%的宏基因组编码。我们的研究揭示了微生物多样性,并提供了可能在阿萨姆邦污染地下水中砷地质循环中发挥关键作用的基因功能方面的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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

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 1406 bps 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.

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