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Exploring microbiome from sediments of River Ganga using a metagenomic approach

机译:使用宏基因组学方法探索恒河沉积物中的微生物组

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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.
机译:恒河是印度的主要河流系统,为数百万家庭提供生态系统服务。然而,由于各种人为活动,这条河承受着压力。河流沉积物中含有多种微生物,对河流健康有巨大影响。本研究采用宏基因组方法对法拉卡河段恒河采集的三个沉积物样本进行微生物群落表征。使用高通量下一代测序平台对沉积物样品进行测序。分类学分类研究表明,细菌的发生率高于其他微生物类群。细菌类,如Betaproteobacteria、Deltaproteobacteria、Gammaproteobacteria和古菌门、Thaumarchaeota和Crenarchaeota等,相对高于其他群落。对3个样本的KEGG通路分析显示,与Farakka拦河坝和Dhulian样本相比,Lalbag样本中与环境信息处理相关的基因数量更高。使用SEED分析通过功能分类对微生物群落进行分类。COG和SEED分析均显示,与碳水化合物代谢相关的基因高于其他功能类别。属级研究证实了假单胞菌的发生率较高,这与集体沐浴等人为活动相对应。细菌属 Nitrospira 和古细菌门 Thaumarchaeota 的存在证实了环境中健康的氮循环。此外,生成的信息将有助于理解微生物群落的重要性及其在维持河流生态系统健康方面的重要作用。

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