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. 2025 Aug 19;7(4):670–681. doi: 10.1007/s42995-025-00310-z

Anammox and denitrifying bacteria and their nitrogen removal potential in lake sediments mediated by environmental changes

Mamun Abdullah Al 1,2,#, Yunfeng Wang 3, Jie Huang 4, Yuhe Yu 4, Philippe Juneau 5, Zhili He 1, Qingyun Yan 1,✉
PMCID: PMC12662983  PMID: 41322254

Abstract

Anammox and denitrification are key processes for nitrogen removal in lake sediments. However, how environmental changes mediate the community structure and functional genes of nitrogen removal bacteria in lakes remain unclear. Using metagenome and amplicon sequencing, we investigated the anammox and denitrifying bacteria and their nitrogen removing potentials in lakes experiencing significant spatiotemporal and environmental variations. The community structure of anammox and denitrifying bacteria exhibited stronger lake-wide spatial variations than that of seasonality, while only the denitrification-related functional genes showed substantial variations in both lakes. Anammox genes (e.g., hzsA/B/C and hdh) showed no significant spatial variations. However, the abundances of anammox and denitrifying genes were significantly higher in winter than in summer. The mesotrophic Lake Weishan demonstrated a greater capacity for complete denitrification in winter, while the eutrophic Lake Donghu exhibited a higher potential of anammox in summer. Differences in functional gene abundances between lakes were more pronounced than variations in phylogenetic diversity, indicating clear functional adaptations to local environments. The coupled nitrogen removal potentials also reflected ecological interactions among anammox and denitrifying genes. Importantly, anammox and denitrifying bacterial communities and their functional genes were primarily driven by dissolved organic carbon, total phosphorous and zinc (Zn). The dissimilarities of anammox and denitrifying bacterial communities increased with geographic distance, indicating a clear distance-decay effect. This study highlights the anammox and denitrifying bacteria and their nitrogen removal potentials in lake sediments that are mediated by both spatial and seasonal environmental changes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42995-025-00310-z.

Keywords: Anammox and denitrification, Eutrophic lake, Mesotrophic lake, Metagenomics, Nitrogen removal

Introduction

Nitrogen removal through denitrification and anammox is crucial for regulating nitrogen cycling in lake sediments (Myrstener et al. 2016). Denitrifying bacteria have received great attention due to their production of nitrous oxide (N2O), a potent greenhouse gas with a much higher warming potential than carbon dioxide (CO2) (Kuypers et al. 2018; Li et al. 2024). In contrast, anammox, which does not emit N2O, has received far less focus in lake sediments (Yang et al. 2021; Zhang et al. 2023). Our previous studies identified effective cooperation between anammox and denitrifying bacteria for nitrogen removal in lake sediment-associated enrichment systems (Zhang et al. 2023, 2024b). More recently, we observed differing evolutionary and ecological adaptation strategies among nirK- and nirS-type denitrifying bacteria in lake sediments due to environmental changes (Ming et al. 2024).

Numerous studies have shown that microbial functions could be significantly influenced by environmental conditions such as changes in ecosystems caused by algal blooms, nutrients and pollution (Abdullah Al et al. 2022; Zhang et al. 2024c). Furthermore, the functions and metabolites of microorganisms may also impact their surrounding environments (Yao et al. 2016; Zhang et al. 2024a), for instance, creating unfavorable conditions and creating niche differentiation for other microbes. Consequently, the response of anammox and denitrifying communities to environmental change depends on the balance of potential positive and negative interactions (Zhang et al. 2022, 2024a). Environmental changes significantly influence bacterial community structure (Abdullah Al et al. 2025; Yan et al. 2017). Pollution, for example, can enhance selective pressures on bacterial communities, leading to imbalanced ecosystem functions (Abdullah Al et al. 2022; Liu et al. 2018). Since the genetic potentials of microbial communities, shaped by various ecological processes, may affect their abundance, diversity, and activity, the feedback between environmental changes and ecological processes is crucial (Kou et al. 2021). However, little is known about how lake-wide environmental changes affect anammox and denitrifying bacteria and their nitrogen-removal functional genes in lake ecosystems.

Lake ecosystems are globally threatened by various human activities, particularly excessive fertilizer use, mineralization of soil organic matter, land use changes, dam construction, and agricultural runoff (Li et al. 2024; Woolway et al. 2020; Wu et al. 2022). These human impacts further compromise ecosystem function (Yue et al. 2024; Zhang et al. 2024a). Increasing attention has been devoted toward the interventional removal of excess nitrogen to control lake eutrophication (Zhang et al. 2023, 2024b). The cooperation between anammox and denitrifying bacteria can effectively lower nitrogen levels, thereby aiding nitrogen removal in eutrophic lakes (Wu et al. 2019; Zhang et al. 2023). However, the mechanisms by which environmental factors influence gene regulation of anammox and denitrification in lakes remain poorly understood, potentially limiting microbially-driven nitrogen removal in these ecosystems.

One of the greatest threats to lake ecosystems worldwide is excessive nitrogen input, which can lead to seasonal cyanobacterial blooms and significantly affect microbial activities involved in nitrogen removal (Abdullah Al et al. 2025; Woolway et al. 2020; Wu et al. 2022). Therefore, clarifying the mechanisms that control the diversity and functions of nitrogen removal bacterial communities is central to enhancing our understanding of lake ecosystems (Abdullah Al et al. 2025; Lin et al. 2020). We hypothesized that lake-wide changes in levels of nutrients and heavy metals would critically impact the community structure of anammox and denitrifying bacteria and their associated nitrogen removal genes in lake sediments. To address this hypothesis, we collected sediment samples from two lakes with different trophic states (i.e., mesotrophic Lake Weishan and eutrophic Lake Donghu) characterized by strong seasonal dynamics of nutrients and heavy metals. We employed metagenome and amplicon sequencing to investigate the environmental influences of anammox and denitrifying bacteria, as well as their potential function in nitrogen removal across lakes and seasons. This study is ecologically important for understanding the dynamics of anammox and denitrifying bacteria and the underlying mechanisms to improve our knowledge of microbial nitrogen removal potentials in lake ecosystems.

Materials and methods

Study area and sample collection

To investigate the nitrogen-removing bacterial communities in lakes with different trophic status, we selected the largest freshwater lake in northern China, namely the mesotrophic Lake Weishan, and the second-largest urban lake in China, namely the eutrophic Lake Donghu (Fig. 1A). The water environments in these lakes have been significantly affected by the continuous influx of agricultural and urban wastewater discharges (Ding et al. 2022; Yan et al. 2017).

Fig. 1.

Fig. 1

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Sampling sites in Lake Weishan and Lake Donghu showing the variationsof environmental factors between summer and winter in lake sediments. A Location of the sampling sites. B Environmental variables of Lake Donghu. C Environmental variables of Lake Weishan. DO, dissolved oxygen; EC, electrical conductivity; NO2−, nitrite; NO3−, nitrate; NH4+, ammonium; PO43−, phosphate; DOC, dissolved organic carbon; TN, total nitrogen; TP, total phosphorus; Cd, cadmium; Cr, chromium; Cu, copper; Fe, iron; Pb, plumbum; Zn, zinc

Surface sediment samples (0–10 cm) were collected from three sampling sites in each lake in January (winter) and July (summer) 2021 (Fig. 1A). At each site, three sediment replicates (~ 2 kg each) were collected and mixed into a single sample, resulting in a total of 12 surface sediment samples (six from Lake Weishan and six from Lake Donghu). The samples were immediately stored in sterile bags, placed on dry ice in an incubator, and transported to the laboratory for further analysis. Each sample was divided into two portions: one was kept at − 80 °C for DNA extraction, and the other was stored at 4 °C for physicochemical analysis.

Physicochemical parameter analysis

Water temperature, electrical conductivity (EC), dissolved oxygen concentration (DO), and pH were measured in situ using a multi-parameter water quality sonde (YSI, USA). The concentrations of NO3–, NO2–, NH4+, and PO43– were measured in a soil suspension using ion chromatography with a soil-to-water ratio of 1:5 (w/v). Total nitrogen (TN), total phosphorus (TP), and dissolved organic carbon (DOC) were determined as described previously (Liu et al. 2024). The contents of cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), plumbum (Pb) and zinc (Zn) were quantified using inductively coupled plasma mass spectrometry (ICP-MS), while Fe concentrations were determined using inductively coupled plasma optical emission spectrometry (ICP-OES) following the protocol of Han et al. (2021).

DNA extraction and sequencing

DNA was extracted using the FastDNA® Spin Kit for Soil (MP Biomedicals, USA) according to the manufacturer’s instructions. Three representative functional genes (nirS and nirK for denitrifying communities, and hzsB for anammox communities) were selected to explore the nitrogen removal bacteria. The nirS gene (~ 400 bp) was amplified using primers cd3aF and R3cdR. The nirK gene (~ 450 bp) was amplified using primers 1aCuF and R3CuR (Abdullah Al et al. 2025). The hzsB gene (~ 350 bp) was amplified with primers 396F and 742R (Cai et al. 2020; Zhang et al. 2022, 2023; Zhou et al. 2018).

PCR reactions were performed in 20-μL volumes containing 10 μL of 2 × Pro Taq, 0.8 μL of each primer (5 μmol/L), and 10 ng of template DNA (Zhang et al. 2023). Annealing temperatures used in PCR amplifications of nirS/nirK and hzsB genes were 60 °C and 55 °C, respectively. Amplicon libraries were sequenced using a 2 × 300 bp paired-end Illumina sequencing kit on the MiSeq platform (Majorbio, Shanghai, China). Metagenome libraries were sequenced using a 2 × 150 bp paired-end Illumina sequencing kit on the NovaSeq platform (Majorbio, Shanghai, China).

Sequences analyses

Amplicon sequences were analyzed according to our previous study (Zhang et al. 2023). Briefly, paired-end reads were merged using FLASH and trimmed with Trimmomatic (Bolger et al. 2014; Magoč and Salzberg 2011). The sequences were then filtered using Qiime2, and chimeric sequences were removed based on the Chimera UCHIME algorithm (Caporaso et al. 2010; Edgar et al. 2011). Quality-filtered sequences were clustered into operational taxonomic units (OTUs) at 97% identity using UPARSE (Edgar 2013). The representative sequences of the nirS/K and hzsB genes were taxonomically annotated against FunGene (http://fungene.cme.msu.edu/) and NCBI Sequence Read Archive (https://ncbi.nlm.nih.gov/), respectively.

High-quality paired-end reads of metagenome sequences were assembled into contigs using MEGAHIT (v1.2.9) (Li et al. 2015). The open reading frames (ORFs) of assembled contigs from each sample were predicted using Prodigal (v2.6.3) and translated into amino acid sequences (Hyatt et al. 2010). All predicted ORFs were clustered into a non-redundant gene catalog using CD-HIT (v4.8.1) with 95% identity and 90% coverage (Li and Godzik 2006). The non-redundant gene catalogs were then aligned against the Kyoto Encyclopedia of Genes and Genomes (KEGG) using DIAMOND (v2.0.15) with a cutoff of 1e − 5 for functional annotation (Buchfink et al. 2015; Kanehisa et al. 2016). Gene abundances were normalized to transcripts per million (TPM) and calculated using Salmon (Patro et al. 2017). The high-quality paired-end reads were further assembled by PEAR (v0.9.6) and then annotated via DIAMOND (v2.0.15) against the KEGG database with a cutoff of 1e − 5 (Zhang et al. 2014).

Nitrogen removal potentials of anammox and denitrifying bacteria

To further investigate the genomic characteristics and nitrogen removal potentials of microbiomes, genome binning was performed using the MetaWRAP pipeline (Uritskiy et al. 2018). The assembled contigs were clustered into bins based on MetaBat2 and MaxBin2 (Wu et al. 2016). The original bins were then consolidated and improved using the Bin_refinement and Reassemble_bins modules to generate metagenome-assembled genomes (MAGs). The MAGs were dereplicated across assemblies using dRep (v3.4.3) (Olm et al. 2017). The completeness and contamination of MAGs were estimated with CheckM (v1.0.12), retaining only those with completeness > 50% and contamination < 10% for subsequent analyses (Parks et al. 2015). The relative abundance of each MAG was assessed using the Quant_bins module. Taxonomic assignments of MAGs were made using GTDB-Tk (v2.3.2) with the classify_wf module (Chaumeil et al. 2019). The functional potentials of MAGs were predicted and annotated using METABOLIC (v4.0) (Zhou et al. 2022). The spatial and seasonal variations were represented using alluvial (e.g., season) or chord (e.g., spatial) diagrams created with OriginPro 2021 (https://www.originlab.com).

Statistical analyses

Environmental factors were tested using permutational multivariate analysis of variance (PERMANOVA). Principal coordinate analysis (PCoA) and cluster analysis with similarity profile (SIMPROF) were utilized to show the variations. Seasonal and spatial variations of each environmental variable were tested using one-way ANOVA. The analysis of similarity (ANOSIM) was performed to test whether functional gene abundances differed significantly using PRIMER v7.0.24.

The phylogenetic trees for anammox and denitrifying genes were constructed using QIIME 2, and phylogenetic diversity was measured with the ‘vegan/picante’ package in R. Significant variations in phylogenetic diversity and OTU richness were tested using the Mann–Whitney U test with IBM SPSS v24. The contribution of different taxa to the total bacterial communities was calculated using similarity percentage analyses (SIMPER). Mantel tests were conducted to show the significant correlations between environmental variables and bacterial communities using R packages ggplot2 and ggcor.

Distance-based linear models (DistLM) with redundancy biplot (dbRDA) were employed to determine significant predictors of microbial variations using the best selection procedure. The adjusted R2 with 9999 permutations was applied to identify the most potential predictive drivers using PERMANOVA in PRIMER v7.0.24. In addition, incorporating geographic location as a spatial factor, we partitioned physicochemical parameters, heavy metals, and spatial factors to explain community variation by adjusted R2.

Results

Environmental conditions of Lake Weishan and Lake Donghu

With the exception of DO and Pb, all measured environmental variables in Lake Donghu were higher in winter than in summer (Fig. 1B). SIMPROF-based clustering analysis indicated that environmental conditions in winter differed significantly from those in summer in both lakes (P < 0.05) (Supplementary Fig. S1A). Generally, significant differences were observed among sites (P < 0.05), except for site 3 at Lake Donghu during winter (P > 0.05). Specifically, temperature, DO, EC, pH, NO3–, NH4+, and PO43− showed significant seasonal variations in Lake Donghu, while Cd and Cr showed significant spatial variations among sites (P < 0.05).

In Lake Weishan, DO, TN, PO43−, TP, Cr, Cu, Pb, and Fe were higher in winter (Fig. 1C). Significant seasonal variations were observed in temperature, DO, NO2–, NO3–, Cr, Fe, and Pb. However, PO43– and Zn demonstrated significant spatial variations (P < 0.05) among sites at Lake Weishan (Supplementary Fig. S1A). There was significant (P < 0.05) seasonal variation detected for all environmental variables by the PERMANOVA test in both lakes, while the first two axes of PCoA accounted for 70.1% of the total variation in Lake Donghu and 68.6% in Lake Weishan (Supplementary Fig. S1B).

Diversity and structure of anammox and denitrifying bacteria

The phylogenetic diversity and OTU richness, as depicted by amplicon sequencing, revealed higher diversity of anammox bacteria (hzsB) compared to denitrifying bacteria (nirK and S-type) (Supplementary Fig. S2). The anammox and nirK-type denitrifying bacteria differed significantly between the two lakes (P < 0.05), although the nirS-type denitrifying bacteria did not show any significant differences (P > 0.05). Furthermore, these variations in the community composition were validated by ANOSIM tests (Table 1) and revealed by PCoA biplot (Fig. 2B). Our results showed strong community compositional variation of anammox and denitrifying bacteria in the sediments of both lakes (Table 1).

Table 1.

The analysis of similarity (ANOSIM) showing the variations of anammox and denitrifying genes as depicted by metagenome and amplicon sequencing

Approach Category Between lakes Lake × Site Lake × Season
R P R P R P
Amplicon hzsB 0.77 0.002 0.86 0.001 0.41 0.040
nirK 1.00 0.002 0.81 0.001 0.65 0.003
nirS 1.00 0.002 0.81 0.001 0.72 0.003
Metagenome Anammox 0.01 0.420 0.12 0.300 0.05 0.360
nirK 0.45 0.019 0.70 0.007 0.21 0.140
nirS − 0.08 0.680 0.13 0.290 -0.04 0.480
Others 0.66 0.002 0.36 0.040 0.60 0.003
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R indicates global R in the ANOSIM tests suggesting the degree of separation between samples. Anammox contains hzsA/B/C and hdh genes. Others indicate denitrifying genes norB/C and nosZ

Fig. 2.

Fig. 2

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Principal coordinate analysis (PCoA) showing the variations in anammox and denitrifying bacterial community compositions and their potential functional genes in Lake Donghu and Lake Weishan. A Anammox and denitrifying functional gene abundances revealed by metagenome sequencing. B Community compositions of anammox (hzsB) and denitrifying (nirK/S) communities as depicted by amplicon sequencing. DH, Lake Donghu; WS, Lake Weishan; Sum, summer; Win, winter; 1, 2 and 3 indicate sampling site 1, site 2 and site 3, respectively

The detected anammox genera included Thiobacillus, Isosphaera, and Magnetospirillum in Lake Donghu, while Lake Weishan hosted Thiobacillus, Croceicoccus, Rhizobium, and Solimonas as the major genera. The dominant denitrifying genera in Lake Donghu were Nitrosospira, Paracoccus, Rubrivivax, and Zoogloea, while Lake Weishan was characterized by Azospira and Rubrivivax. SIMPER analysis revealed that 11 anammox genera accounted for 52.40% of the dissimilarity in the anammox bacterial communities, while seven nirS- and 4 nirK-type denitrifying genera accounted for 44.16% and 6.23% of the dissimilarity in denitrifying bacterial communities, respectively (Supplementary Table S1).

Functional dynamics of anammox and denitrifying bacteria

The results of abundance variation by PCoA for potential functional genes of anammox and denitrification (Fig. 2A), as well as bacterial communities (Fig. 2B) showed significant variation in the sediments of both lakes (Fig. 2). Further gene specific variation was validated by ANOSIM tests and revealed that denitrification functional genes nirK and other denitrifying genes, i.e., norB/C and nosZ, showed lake-wide spatio-temporal variations (Table 1). There were no significant differences for anammox and nirS genes among lakes, seasons, and sites.

The results of SIMPROF based cluster analyses from metagenome sequencing data showed significant seasonal variations in anammox and denitrifying genes in both lakes (Fig. 3). Significant variations were also noted between sites 2 and 3 in Lake Donghu, and between sites 1 and 2 in Lake Weishan. The total abundances of denitrifying genes (e.g., nirK/S, norB/C, and nosZ) and anammox genes (e.g., hzsA/B/C and hdh) exhibited considerable lake-wide variation and strong seasonality (Fig. 4). Notably, denitrifying gene abundances in Lake Donghu were higher in summer than in winter, while in Lake Weishan, they were higher in winter than in summer. Spatially, denitrifying genes (e.g., nap, nar, and nor) were most abundant at sites 1 and 3 in Lake Donghu, with the nir gene showing the highest abundance at site 2 (Fig. 4A). In Lake Weishan, all denitrifying genes reached their highest abundance at site 1, while anammox genes were more abundant at site 3 compared to other sites (Fig. 4B).

Fig. 3.

Fig. 3

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Metagenome sequence-based KEGG predictive functions of anammox and denitrifying bacteria in Lake Donghu and Lake Weishan. Dissimilarity (%) indicates Bray–Curtis dissimilarity of functional genes. Red lines in the cluster indicate significant differences (P < 0.05). S1–S3, sampling site; Win and Sum, winter and summer, respectively

Fig. 4.

Fig. 4

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Distribution of anammox and denitrifying genes in lake sediments during winter and summer among sites. A Lake Danghu. B Lake Weishan. Anammox genes including hzsA, hzsB, hzsC and hdh; denitrifying genes including nirK/S, norB/C and nosZ

The hzsC gene was not detected in Lake Donghu, and the hdh gene was not detected in Lake Weishan (Fig. 5). In addition, the nirK/S, norB/C, and nosZ genes had stronger contributions to the denitrification pathway in winter, except for K00368, the contribution of which was stronger in summer. Similarly, the hzsA gene had a greater contribution to the anammox pathway in summer, while other hzs genes were more prominent in winter (Fig. 5A).

Fig. 5.

Fig. 5

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Dynamics of anammox and denitrifying genes and their correlations with environmental factors. A Anammox and denitrifying functional gene abundances calculated from KEGG pathways by homogenization and normalized into transcripts per million counts. Pie charts represent the gene abundance variation between winter and summer. B Mantel test showing the significant correlations (* P < 0.05 and ** P < 0.01) between anammox and denitrifying functional genes and environmental factors. Tem, temperature; DO, dissolved oxygen concentration; EC, electrical conductivity; NO2−, nitrite; NO3−, nitrate; NH4+, ammonium; PO43−, phosphate; DOC, dissolved organic carbon; TN, total nitrogen; TP, total phosphorus; Cd, cadmium; Cr, chromium; Cu, copper; Fe, iron; Pb, plumbum; Zn, zinc

Influencing factors on anammox and denitrifying bacteria in lake sediments

Our results revealed that only NO2– and Cr had significant correlations with the anammox and denitrifying bacterial community composition (Supplementary Fig. S3). The abundances of anammox and denitrifying genes were strongly correlated with seasonal changes in environmental factors (Fig. 5B). In Lake Donghu, nirK gene showed significant correlation with DOC, Cr and Pb, while hzsA gene significantly correlated with DOC, Cr and Fe. WT, DO and NO2− were significantly correlated with norB and nosZ genes. EC was significantly correlated with nirS and hdh genes. TN and Cd were significantly correlated with norC and hdh genes (Fig. 5B). In Lake Weishan, Cu was significantly correlated with nirK gene while Zn was significantly correlated with norC and hzsB genes. DO and pH were significantly correlated with norB gene whereas hzsA gene was significantly correlated with DO, NO2− and TN (Fig. 5B). The significant correlations were also detected among anammox and denitrification functional genes (Supplementary Table S2).

The distLM results revealed different influences of environmental factors on the nitrogen removal potentials (Fig. 6A) and community composition of anammox and denitrifying bacteria (Fig. 6B). Physicochemical variables (i.e., pH, temperature, DO, NO2–, NO3–, TN, and TP) and heavy metals (i.e., Cd, Cu, Cr, Fe, Pb, and Zn) were the primary factors influencing nitrogen removal bacterial communities and their functional genes (Supplementary Table S3). The taxonomic composition of bacteria might have been affected by a combination of physicochemical variables, heavy metals, and geographic location, explaining 50%, 78%, and 79% of the variations, respectively (Fig. 6C). The abundances of functional genes were primarily affected by physicochemical variables and heavy metals (Fig. 6C), and the model roughly explained 26% to 50% of variation, respectively. Our results clearly showed that the effect of geographic distance on anammox and denitrifying bacterial communities, rather than their functional genes, indicating a strong distance-decay process on these bacterial communities.

Fig. 6.

Fig. 6

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Distance-based linear model (distLM) and redundancy analysis (dbRDA) showing the significant predictive environmental factors for variations in anammox and denitrifying bacterial communities and their potential functional genes in lake sediments. A Anammox and denitrifying functional gene abundances based on metagenome sequencing. B Anammox and denitrifying bacterial communities based on amplicon sequencing. C Proportion of explained variations by different environmental factors on taxonomic composition of anammox and denitrifying bacterial communities (right panel) and functional genes (left panel). Temp, temperature; DO, dissolved oxygen concentration; EC, electrical conductivity; NO2−, nitrite; NO3−, nitrate; NH4+, ammonium; DOC, dissolved organic carbon; TP, total phosphorus; Cd, cadmium; Cr, chromium; Cu, copper; Fe, iron; Pb, plumbum; Zn, zinc. PF, physicochemical factors; HM, heavy metals

Discussion

Understanding the community structure and potential functions of anammox and denitrifying communities is crucial for clarifying microbe-mediated nitrogen removal in lake ecosystems. Ecological health has significant implications for effective lake management due to its direct effects on water quality and microbial communities (Li et al. 2024; Wu et al. 2022). We found that environmental conditions in both lakes exhibited significant seasonal variations. However, high levels of DOC may lead to lower abundances of anammox bacteria and their potential functions. Anammox bacteria are generally limited by abundant organic matters (Yao et al. 2018). Our previous studies indicated that anammox and denitrifying bacteria work synergistically to remove nitrogen from eutrophic lake sediments (Zhang et al. 2023, 2024b). Nonetheless, the influence of seasonal environmental variations on anammox and denitrifying bacterial communities and their potential functional genes remains unclear.

Clarifying the mechanisms that control community diversity and functions is a central issue in microbial ecology (Ning et al. 2020). Our results indicate that community composition and phylogenetic diversity of anammox and denitrifying bacteria in the sediments of both lakes exhibited clear seasonal and spatial variations. Previous studies found that changes in environmental conditions due to water pollution in freshwater resulted in significant variations of bacterial communities (Abdullah Al et al. 2022; Zhou and Ning 2017). Consistently, we likewise found NO2− and Cr were significantly correlated with anammox and denitrifying bacterial communities. A recent study in the eutrophic Lake Taihu confirmed that excessive nutrients and algal blooms affect the structure of denitrifying communities (Abdullah Al et al. 2025). Furthermore, environmental filtering has a profound effect on microbial community succession (Chen et al. 2023; Stegen et al. 2012; Yuan et al. 2020). The present study revealed significant correlations between nitrogen removal functional genes and the concentration of Cr in lake sediments. This is consistent with previous research indicating that heavy metals can diminish the activities of microorganisms (Gui et al. 2017; Gutwinski et al. 2021). The positive correlation between Cr and hzsB-/nirK-type bacteria further suggests that heavy metals may negatively impact microbially driven nitrogen removal (Yang et al. 2021). Therefore, our findings confirm that heavy metals inhibit anammox and denitrification processes in lake sediments. A pioneer study in Lake Donghu revealed that denitrification and anammox are responsible for NO2− reduction (Zhang et al. 2023). Consistently, our results showed that nirK/S-type denitrifying bacteria in Lake Donghu, and anammox bacteria in Lake Weishan, were significantly correlated with NO2−, suggesting effective nitrogen capabilities of anammox and denitrifying bacterial communities.

The mesotrophic Lake Weishan exhibited stronger denitrification in winter than that of the eutrophic Lake Donghu. However, Lake Donghu showed higher anammox potential in summer than Lake Weishan. Seasonal variations in nitrogen cycling genes have been found to correlate with environmental changes such as temperature and surface runoff (Myrstener et al. 2016; Yue et al. 2024; Zhang et al. 2024b). Our results supported the assertion that temperature significantly influences denitrification in lake sediments. Both anammox and denitrification rates in lake sediments appear to be affected by changes in organic matter content (Lin et al. 2020; Yue et al. 2024). We also found a significant correlation between anammox and denitrifying functional genes and DOC, suggesting that seasonal changes in DOC may regulate the coupling of anammox and denitrification in lake sediments. Previous studies found ecological interactions between anammox and denitrifying bacteria through niche differentiation and cooperation (Baumann et al. 2022; Zhang et al. 2023). This is in agreement with our results showing strong correlations among the anammox and denitrification functional genes. We found WT, EC, DO, and TN/TP were the key factors affecting anammox and denitrifying functional genes. Furthermore, Fe, Pb, Zn, Cu and Cr showed significant influences on the abundances of anammox and denitrification functional genes. Although anammox and denitrifying bacteria can utilize different metals as electron acceptors (Liu et al. 2022; Yang et al. 2021), they are sensitive to toxic substances (Zhao et al. 2022). Thus, anammox and denitrification functional dynamics in freshwater lake sediments could be influenced by seasonally varying physicochemical properties and metal concentrations.

We also found that geographic distance had a stronger influence on the composition of anammox and denitrifying bacterial communities than on functional genes. This supports the idea that functional adaptation to environmental changes may occur through the selective loss of genes or acquisition of traits from other bacteria (Ming et al. 2024). This could explain the relatively lower variation in gene abundances compared to community composition. On the other hand, the significant geographic effects on the composition of anammox and denitrifying bacterial communities further confirm the distance-decay relationship (Broman et al. 2022). The two lakes investigated are geographically distant and exhibit highly heterogeneous environmental conditions. As a result, the anammox and denitrifying bacterial communities are highly dissimilar with varied nitrogen removal potentials.

Conclusions

The mesotrophic Lake Weishan is dominated by anammox bacteria and their functional genes, while the eutrophic Lake Donghu exhibits abundant denitrifying bacteria and their functional genes. A clear distance-decay process was observed in structuring anammox and denitrifying bacterial communities. The nitrogen removal functional genes in these bacterial communities showed a strong significant correlation with each other. Moreover, a coupling between anammox and denitrification was detected in lake sediments, and these nitrogen removal processes were significantly influenced by seasonal variations in dissolved organic carbon, total phosphorous and Zn content. This study sheds light on the effects of environmental changes on anammox and denitrifying bacterial communities and their nitrogen removal potentials in freshwater lakes, providing valuable insights for predicting the response and evolution of nitrogen removal microorganisms in lake ecosystems.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 4865 kb) (4.8MB, docx)

Acknowledgements

We are grateful to Dr. Weibo Song (Ocean University of China, China) for helpful suggestions on experimental design and insightful discussions on the results. The authors thank Dr. Alan Warren (Natural History Museum, UK) for English editing and helpful suggestions. This work was supported by the National Natural Science Foundation of China (32030015, W2433059, 42377111), and the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (SML2024SP002, SML2024SP022).

Authors contributions

JH, QY and YW conceived the study. YW performed the experiments. MAA and YW analyzed the data. MAA and YW wrote the manuscript. JH, YY, PJ, ZH and QY reviewed and edited the manuscript. All authors read and approved the final version of the manuscript.

Data availability

All amplicon and metagenome sequencing data are available at National Center for Biotechnology Information (NCBI) under the accession numbers PRJNA1150883 and PRJNA1151834, respectively.

Declarations

Conflict of interest

The authors declare no competing interests. Author Qingyun Yan is a member of the Editorial Board, but he was not involved in the journal’s review of, or decision related to, this manuscript.

Animal and human rights statement

This article does not contain any studies with human participants or animals performed by any of the authors.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Mamun Abdullah Al and Yunfeng Wang have contributed equally to this work.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary file1 (DOCX 4865 kb) (4.8MB, docx)

Data Availability Statement

All amplicon and metagenome sequencing data are available at National Center for Biotechnology Information (NCBI) under the accession numbers PRJNA1150883 and PRJNA1151834, respectively.

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