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The total and functional bacterial community of nitrogen removal in the SND ditches

机译:SND沟渠中氮气去除的总和功能细菌群落

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摘要

For a full understanding of microbial function in simultaneous nitrification and denitrification (SND), comprehensive genetic information in activated sludge from two parallel oxidation ditches (Ditches A and B) was investigated by high-throughput sequencing and quantitative real time PCR (q-PCR). Results showed that over 90% of the ammonia was removed by both oxidation ditches, and Ditch A had a higher average value of SND efficiency. Both ditches shared a similar bacterial composition, and Proteobacteria and Bacteroidetes were the dominant phyla. However ditch A had a microbial community with higher Shannon and Chao1 indices than Ditch B. At genus level, Nitrosomonas, Thauera, Arcobacter and Zoogloea were mainly involved in the SND of oxidation ditches. And more types and higher abundances of (de) nitrifiers were detected in Ditch A. The results were verified by q-PCR analysis. According to functional analysis, the metabolism of carbohydrates and proteins, clustering-based subsystems, as well as amino acids and derivatives were the major functions of activated sludge in oxidation ditches. SND was accomplished in oxidation ditches by means of conversion and incorporation of nitrogenous compounds. Furthermore, more types of Level 3 subsystems and higher efficiency of ammonia assimilation were found in the nitrogen metabolism of Ditch A. These findings provide an insight into genetic pattern of SND in the municipal sewage treatment plants. (C) 2017 Elsevier Ltd. All rights reserved.
机译:通过同时硝化和反硝化(SND)全面了解微生物功能,通过高通量测序和定量实时PCR(Q-PCR)研究了来自两个平行氧化沟(沟渠A和B)的综合遗传信息。通过高通量测序和定量实时PCR(Q-PCR) 。结果表明,通过氧化沟渠除去超过90%的氨,沟渠A具有更高的SND效率的平均值。这两个沟渠都分享了类似的细菌组合物,并且植物和菌株是占优势的植物。然而,沟渠A的微生物群体具有高于Shannon和Chao1指数的微生物群落,而不是沟B.在Genus,亚硝基粥,粉末,Arcobacter和Zoogloea主要涉及氧化沟渠的SND。在沟A中检测到更多类型和较高的(DE)硝化剂的丰度。结果通过Q-PCR分析验证了结果。根据功能分析,碳水化合物和蛋白质的代谢,基于聚类的子系统以及氨基酸和衍生物是氧化沟中活性污泥的主要功能。通过转化和掺入氮化合物,在氧化沟中完成SND。此外,在Ditch A的氮代谢中发现了更多类型的3级子系统和氨同化效率的效率。这些发现在市污水处理厂的SND遗传模式中提供了深入洞察。 (c)2017 Elsevier Ltd.保留所有权利。

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