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Metatranscriptomic and metagenomic description of the bacterial nitrogen metabolism in waste water wet oxidation effluents

机译:废水湿氧化废水中细菌氮代谢的转录组学和宏基因组学描述

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摘要

Anaerobic digestion is a common method for reducing the amount of sludge solids in used waters and enabling biogas production. The wet oxidation process (WOX) improves anaerobic digestion by converting carbon into methane through oxidation of organic compounds. WOX produces effluents rich in ammonia, which must be removed to maintain the activity of methanogens. Ammonia removal from WOX could be biologically operated by aerobic granules. To this end, granulation experiments were conducted in 2 bioreactors containing an activated sludge (AS). For the first time, the dynamics of the microbial community structure and the expression levels of 7 enzymes of the nitrogen metabolism in such active microbial communities were followed in regard to time by metagenomics and metatranscriptomics. It was shown that bacterial communities adapt to the wet oxidation effluent by increasing the expression level of the nitrogen metabolism, suggesting that these biological activities could be a less costly alternative for the elimination of ammonia, resulting in a reduction of the use of chemicals and energy consumption in sewage plants. This study reached a strong sequencing depth (from 4.4 to 7.6 Gb) and enlightened a yet unknown diversity of the microorganisms involved in the nitrogen pathway. Moreover, this approach revealed the abundance and expression levels of specialised enzymes involved in nitrification, denitrification, ammonification, dissimilatory nitrate reduction to ammonium (DNRA) and nitrogen fixation processes in AS.
机译:厌氧消化是减少废水中污泥固体含量并使沼气生产的常用方法。湿式氧化工艺(WOX)通过有机化合物的氧化将碳转化为甲烷来改善厌氧消化。 WOX产生的废水富含氨,必须将其除去以保持产甲烷菌的活性。从WOX去除氨气可以通过好氧颗粒进行生物操作。为此,在2个含有活性污泥(AS)的生物反应器中进行了制粒实验。第一次,在时间上通过宏基因组学和元转录组学研究了微生物群落结构的动态和这种活性微生物群落中氮代谢的7种酶的表达水平。结果表明,细菌群落通过增加氮代谢的表达水平来适应湿氧化废水,这表明这些生物活性可能是消除氨的成本较低的替代方法,从而减少了化学物质和能源的使用。污水处理厂的消耗。这项研究达到了很强的测序深度(从4.4到7.6 Gb),并启发了氮途径中涉及的微生物的未知多样性。此外,该方法揭示了AS中硝化,反硝化,氨化,异化硝酸盐还原为铵盐(DNRA)和固氮过程中涉及的特殊酶的丰度和表达水平。

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