Exploring microbiome from sediments of River Ganga using a metagenomic approach

γ蛋白杆菌 基因组 塔玛丘塔 Β-变形菌 生物 克雷纳恰奥塔 生态学 酸杆菌 操作分类学单元 变形菌纲 微生物种群生物学 生态系统 拟杆菌 古细菌 16S核糖体RNA 细菌 放线菌门 基因 生物化学 遗传学
作者
Bijay Kumar Behera,Parameswar Sahu,Ajaya Kumar Rout,Pranaya Kumar Parida,Dhruba Jyoti Sarkar,Nagendra Kumar Kaushik,A. R. Rao,Anil Rai,Basanta Kumar Das,Trilochan Mohapatra
出处
期刊:Aquatic Ecosystem Health & Management [Taylor & Francis]
卷期号:24 (4): 12-22 被引量:19
标识
DOI:10.14321/aehm.024.04.04
摘要

Abstract The Ganga is a major riverine system of India providing ecosystem services to millions of households. However, this river is under stress due to various anthropogenic activities. River sediment harbours a variety of microorganisms which has a tremendous influence on river health. In the present study, metagenomic approach for microbial community characterization of three sediment samples collected from River Ganga at Farakka stretch was carried out. The sediment samples were sequenced using a high-throughput Next Generation Sequencing platform. Taxonomical classification study showed that the occurrence of bacteria is higher than other groups of microbes. The bacterial classes, such as Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and archaeal phylum, Thaumarchaeota, and Crenarchaeota were relatively higher than other communities. KEGG pathway analysis of three samples revealed that the number of genes associated with environmental information processing is higher in the Lalbag sample in comparison to Farakka barrage and Dhulian samples. The microbial community was categorized by functional classification using SEED analysis. Both COG and SEED analysis revealed that genes associated with carbohydrate metabolism are higher than other functional categories. The genus-level study confirms the higher occurrence of Pseudomonas, which corresponds to anthropogenic activities like mass bathing. The presence of bacterial genus Nitrospira and archaeal phylum Thaumarchaeota confirms a healthy nitrogen cycle in the environment. Moreover, the generated information would help in understanding the importance of microbial communities and their imperative function in maintaining the riverine ecosystem health.

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