Exploring the ecological niche of comammox Nitrospira by in-situ enrichment within mainstream nitrification systems

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Xiaochuan Ran , Mingda Zhou , Tong Wang , Yanren Wang , Han Wang , Yayi Wang
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Abstract

Complete-ammonia-oxidization bacteria (Comammox Nitrospira) hold promising potential for reducing carbon footprint in mainstream wastewater treatment. However, the inadequate understanding of comammox Nitrospira within wastewater systems has greatly hindered the utilization of these novel microbial resources. This study explored the ecological niche of comammox Nitrospira within mainstream nitrification systems by enriching them under varied operational conditions. The joint analysis of multiple linear regression and random forest model have identified in-situ ammonium concentration and pH as the two most important parameters influencing the growth of comammox Nitrospira, followed by nitrogen loading rate, nitrogen source type, and dissolved oxygen (DO). Meanwhile, the ecological niche preference of comammox Nitrospira was revealed. The optimal ranges of in-situ ammonium concentration and pH for comammox Nitrospira was found below 0.5 mg NH4+-N/L and 6.5–7.5, respectively, indicating that low free ammonia conditions favor their growth. Furthermore, comammox Nitrospira exhibited a competitive advantage over Nitrosomonas under weakly acidic pH (6.0–6.5), and adapted to DO fluctuations by interspecies shifts, whereas Nitrosomonas preferred relatively high DO (1.5–2 mg O2/L). Comparative genomics further confirmed the above niche differentiation of two groups from reconstructed comammox Nitrospira and Nitrosomonas genomes. Overall, these findings provide guidance for the application of comammox process in wastewater treatment, thereby supporting the transition of mainstream nitrification process toward a more sustainable and energy-efficient pathway.

Abstract Image

主流硝化系统原位富集法研究硝化螺旋菌生态位
完全氨氧化细菌(Comammox Nitrospira)在主流废水处理中具有减少碳足迹的巨大潜力。然而,由于对废水系统中硝化梭菌的认识不足,极大地阻碍了这些新型微生物资源的利用。本研究通过在不同操作条件下对主流硝化系统中comammox硝化螺旋菌进行富集,探索其生态位。通过多元线性回归和随机森林模型的联合分析,发现原位铵态氮浓度和pH值是影响comammox硝化螺旋藻生长的两个最重要的参数,其次是氮负荷速率、氮源类型和溶解氧(DO)。同时,揭示了硝螺旋藻的生态位偏好。铵态氮浓度为0.5 mg NH4+-N/L以下,pH值为6.5 ~ 7.5,说明低游离氨条件有利于硝化毛菌的生长。此外,在弱酸性pH值(6.0 ~ 6.5)下,硝化螺旋菌比亚硝化单胞菌表现出竞争优势,并能适应物种间的DO波动,而亚硝化单胞菌更倾向于较高的DO (1.5 ~ 2 mg O2/L)。比较基因组学进一步证实了上述两个群体在硝化螺旋菌和亚硝化单胞菌基因组重构中的生态位分化。总的来说,这些发现为comammox工艺在废水处理中的应用提供了指导,从而支持主流硝化工艺向更可持续和节能的途径过渡。
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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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