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. 2025 Apr 14;13(4):899.
doi: 10.3390/microorganisms13040899.

Dynamic Response Mechanisms of Anammox Reactors Under Nitrogen-Loading Fluctuations: Nitrogen Removal Performance, Microbial Community Succession, and Metabolic Functions

Xuemei Liu  1   2 , Kai Wan  1 , Chunqiao Xiao  1 , Jingang Hu  1 , Xiangyi Deng  1 , Ruan Chi  1
Affiliations

Dynamic Response Mechanisms of Anammox Reactors Under Nitrogen-Loading Fluctuations: Nitrogen Removal Performance, Microbial Community Succession, and Metabolic Functions

Xuemei Liu et al. Microorganisms. .

Abstract

The leachate from ion-adsorbed rare earth tailings poses challenges to the application of the anaerobic ammonium oxidation (anammox) process in this field due to its large fluctuations in ammonia nitrogen concentration (50-300 mg/L) and high flow rate (4000-10,000 m3/d). This study investigated the effects of nitrogen-loading rate (NLR) regulation on denitrification performance through reactor operation and elucidated the mechanisms of NLR impacts on anammox processes via microbial community analysis and metabolic profiling. The results revealed a nonlinear relationship between nitrogen loading and system performance. As NLR increased, both denitrification efficiency and anammox bacterial abundance (rising from 5.85% in phase P1 to 11.43% in P3) showed synchronous enhancement. However, excessive nitrogen loading (>3.68 kg/m3·d) or nitrogen starvation led to performance deterioration and reduced anammox bacterial abundance. Microbial communities adopted modular collaboration to counteract loading stress, with modularity indices of 0.563 and 0.545 observed in the inhibition phase (P2) and starvation phase (P4), respectively. Zi-Pi plot analysis demonstrated a significant increase in inter-module connectivity, indicating reinforced interspecies interactions among microorganisms to resist nitrogen-loading fluctuations.

Keywords: anaerobic ammonia oxidation; co-occurrence network; metabolic pathways; microbial community structure; rare earth tailings; substrate fluctuations.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Schematic diagram of anammox reactor.
Figure 2
Figure 2
Performance variations of anammox bioreactor at different stages (P1–P5). (a) Ammonia nitrogen removal (ANR), nitrite removal (NR), total nitrogen (TN), and total nitrogen removal efficiency (NRE). (b) Changes in nitrogen removal rate (NRR), nitrogen-loading rate (NLR), stoichiometric ratios (Rs and Rp), and nitrogen removal contribution. (c) Changes in reactor pH and free ammonia (FA) and free nitrite (FNA) content.
Figure 2
Figure 2
Performance variations of anammox bioreactor at different stages (P1–P5). (a) Ammonia nitrogen removal (ANR), nitrite removal (NR), total nitrogen (TN), and total nitrogen removal efficiency (NRE). (b) Changes in nitrogen removal rate (NRR), nitrogen-loading rate (NLR), stoichiometric ratios (Rs and Rp), and nitrogen removal contribution. (c) Changes in reactor pH and free ammonia (FA) and free nitrite (FNA) content.
Figure 3
Figure 3
Composition of microorganisms and changes in their relative abundance in the reactor. (a) Phylum level. (b) Genus level.
Figure 4
Figure 4
Analysis of microbial community differences. (a) PcoA analysis of microbial communities at different stages. (b) Venn diagram of genus-level distribution of microbes in samples at different stages (colors represent samples at different stages, numbers represent species contained in the samples). (c) LEfSe analysis of genus-level microbial communities in different run stages (LDA scores > 3.5).
Figure 5
Figure 5
Correlation analysis of physicochemical properties with microorganisms.
Figure 6
Figure 6
PICRUSt2 analysis of changes in microbial KEGG function during reactor operation. (a) KEGG secondary metabolic pathway (Kruskal–Wallis test, * p < 0.05, ** p < 0.01). (b) Key tertiary metabolic pathways for energy metabolism and membrane transport (Different letters indicate significant differences before and after composting.).
Figure 7
Figure 7
Microbial co-occurrence network analysis with network connectivity analysis. (a–e) Network diagram of microbial contribution at P1–P5 stages. (f–j) show the results of co-occurrence network connectivity for stages P1–P5. Calculated according to the SparCC correlation algorithm, the red edges between nodes correspond to a significant positive correlation (r > 0.8, p < 0.05), while the green edges correspond to a significant negative correlation (r < −0.8, p < 0.05). Node size was correlated with connectivity between microbes. zi-Pi plots show key node microbes in the co-occurrence network.
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