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Article

Phosphorus Regulated Coordination of Carbon, Nitrogen, Sulfur and Phosphorus Cycling Genes in Sediments of a Plateau Mesotrophic Lake Erhai in Yunnan, China

by
Zhen Xie
1,
Shunzi Xiong
2,3,
Huaji Liu
2,3,
Jimeng Feng
2,3,
Xiaoyi Chen
1,
Kaiwen Yang
1,
Lei Zhang
1,
Xinze Wang
2,3 and
Xiaojun Zhang
1,4,*
1
State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
2
National Observation and Research Station of Erhai Lake Ecosystem in Yunnan, Dali 671000, China
3
Yunnan Dali Research Institute, Shanghai Jiao Tong University, Dali 671000, China
4
Technology Center for Microbial Resource, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China
*
Author to whom correspondence should be addressed.
Water 2025, 17(23), 3399; https://doi.org/10.3390/w17233399
Submission received: 27 October 2025 / Revised: 25 November 2025 / Accepted: 26 November 2025 / Published: 28 November 2025
(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)
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Abstract

Eutrophication threatens vulnerable plateau lakes, yet the gene-level microbial processes behind spatial heterogeneity of sediment carbon (C), nitrogen (N), phosphorus (P) and sulfur (S) cycling and their environmental driver remain unclear. This study first applies the high-throughput Quantitative Microbial Ecology Chip (QMEC) to quantify 71 functional genes involved in geochemical cycling in sediment of a large Chinese plateau lake, Erhai, aiming to elucidate how environmental factors shape the spatial distribution and coupling patterns of these genes. The results revealed that total functional gene abundance exhibited a pronounced south-to-north decline, with key genes (rbcL, mct, nirS, nosZ, phoD, pqqC and yedZ) being significantly higher in the southern sector (p < 0.05). Lignocellulose-degrading genes (abfA, xylA and mnp) exceeded 106 copies g−1 and were significantly enriched in the south, indicating faster organic-matter turnover. Denitrification dominated the nitrogen cycle, with nirS-type denitrifiers being overwhelmingly prevalent; genes associated with nitrate reduction (napA, narG) were also significantly more abundant in the south. Sediment total phosphorus (TP) was significantly correlated with genes involved in carbon fixation, methane production, nitrogen fixation and sulfur metabolism (Mantel test, p < 0.05), suggesting that TP is a key driver of microbial nutrient cycling in Erhai sediment. Furthermore, co-abundance of these functional genes was observed across all sites (Spearman correlation, p < 0.05), which in turn implies potential coupling of the major elemental cycles. Accordingly, the differentiation of the carbon, nitrogen, phosphorus and sulfur cycling genes and metabolic potential in the different sectors reveals heterogeneous microbial regulation of Erhai’s endogenous nutrient cycling. It highlights precision and differentiated management as a key for large lake restoration.

Graphical Abstract

1. Introduction

Eutrophication is a pervasive issue in aquatic ecosystems worldwide, leading to deteriorating water quality and frequent cyanobacterial blooms [1]. This phenomenon is particularly pronounced in plateau lakes, such as Erhai Lake in Yunnan, China, where the transition from mesotrophic to eutrophic conditions poses significant challenges for ecological management and restoration [2,3]. Even with the control of external nitrogen and phosphorus inputs, the release of nutrients from sediments can still trigger algal blooms in freshwater ecosystems, highlighting the importance of addressing internal nutrient cycling [4,5]. Understanding the mechanisms underlying nutrient cycling and the role of microbial communities in these processes is crucial for developing effective strategies to mitigate eutrophication [6].
Microbial communities are central to the biogeochemical cycling of essential elements such as carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) in aquatic ecosystems [7]. Functional genes within these communities encode specific metabolic pathways and ecological functions that drive nutrient cycling [8]. Enhancing mechanistic insights into microbial contributions to ecosystem functions requires comprehensive profiling of functional gene diversity and composition [9]. In particular, the distribution and abundance of functional genes can reveal how microbial communities respond to environmental gradients and nutrient availability [10]. In lake sediments, microbial carbon cycling involves carbon decomposition, carbon fixation, and methane metabolism. Carbon decomposition primarily includes the metabolic breakdown of organic substances. Changes in sediment nutrient content associated with lake eutrophication may lead to alterations in diverse microbial carbon fixation pathways and related functional genes. For nitrogen cycling, the availability of various nitrogen forms in both sediment and water bodies is often reflected by an increased proportion and expression of genes encoding specific processes such as nitrification, denitrification, and nitrogen fixation. For instance, the relative abundance of denitrification genes (nirK/nirS, nosZ) and nitrogen-fixation genes (nifH) governs the net internal nitrogen balance [11,12]. Functional genes involved in phosphorus uptake and release, such as those encoding phosphatases and transport proteins, are of significant importance for understanding the dynamics of phosphorus cycling in sediments [13,14]. Similarly, sulfur cycling is driven by specific functional genes, such as dsrAB involved in sulfate reduction and soxXYZ in sulfide oxidation, which play key roles in regulating sulfur cycling processes [15,16]. Therefore, the abundance and distribution of the C, N, P, and S functional genes collectively determine whether sediments act as a net sink or source of nutrients.
Previous investigations have predominantly centered on the cycling of single or paired elements. For instance, in riverine sediments, the sulfate-reducing gene (aprA) and the methanogenic gene (mcrA) were found to mediate coupled biogeochemical cycling [17]; in mangrove sediments, sulfur-driven denitrifiers modulate N2O emissions, and multiple potential coupling mechanisms between anaerobic methanotrophic oxidizers (ANMEs) and sulfate-reducing bacteria (SRB) have been proposed [18]; in a plain eutrophic lake, metabolic coupling of nitrogen and sulfur cycling has been documented [19]. However, studies that integrate the analysis of microbial functional genes (linked to key geochemical cycling elements, including carbon, nitrogen, phosphorus, and sulfur) with the physicochemical factors of lakes remain extremely scarce. This scarcity is particularly notable for mesotrophic plateau lakes—a gap that may be critical for advancing our understanding of eutrophication in freshwater lakes.
Understanding the main driving mechanisms behind differences in sediment microbial communities under eutrophic conditions can offer important insights into using sediment microbial changes as indicators of lake health or restoration. This study aims to address these knowledge gaps by investigating the distribution of functional genes associated with C, N, P, and S cycling in the sediment samples of Erhai Lake. Using a high-throughput Quantitative Microbial Ecology Chip (QMEC) [20], we quantified 71 functional genes to assess the metabolic potential of the lake concerning these essential elements. Concurrently, we examined the environmental physicochemical indicators of the sediments and water body to identify potential drivers of the observed gene distribution patterns. Our research is expected to provide insights into the internal nutrient release mechanisms in Erhai Lake, contributing to the broader understanding of highland lakes undergoing trophic transitions and for lake management and restoration.

2. Materials and Methods

2.1. Study Site and Sample Collection

Erhai Lake (25°36′–25°58′N, 100°06′–100°18′E) is located in Dali City, southwest China. This lake is situated in a subtropical monsoonal climate typical of a low-latitude plateau with an elevation of 1974 m. The lake surface area is approximately 249.8 km2 and the average water depth is 10.5 m, with a maximum depth reaching 20.9 m. The lake’s reservoir capacity is about 2.8 × 109 m3. The average annual climate temperature is 15 °C. The inflowing rivers into Erhai Lake include three rivers from the north (Luoshi, Yong’an, and Miju rivers) and 18 streams from the west mountain, with the northern rivers contributing more than 60% of the lake’s inflow. The Xi’er River, located in the southwest of Erhai Lake, serves as the only outflow, thereby giving rise to a long water exchange cycle and slow currents within the lake.
Based on the spatial characteristics of water quality in Erhai Lake—with chlorophyll-a and total nitrogen (TN) both significantly higher in the northern sector (p < 0.05, Figure S1)—this study demarcated the lake into northern and southern sectors. In July 2022, a total of 19 sediment samples were collected (Figure 1), with 10 samples from the southern sector (S1-S10) and nine from the northern sector (N1-N9). With 9–10 samples per sector, lake-scale comparison was statistically feasible. These 19 locations coincide with routine water-quality monitoring stations, guaranteeing spatial coverage of the main lake regions. At each sampling site, three random surface sediment samples (0–5 cm) were collected using a gravity corer sampler (HYDRO-BIOS, Germany; 60 cm transparent acrylic tube, 70 mm inner diameter, 5.8 kg). The three random surface sediment samples were homogenized to minimize small-scale variance and placed in sterile polyethylene bags for further use. The entire procedure followed the field protocol of Hu et al. (2021) [21]. Corresponding overlying water samples were collected at 0.5 m below the water surface using plexiglass water samplers (HYDRO-BIOS, Germany; 1.0 L capacity, 56 cm length, 10 cm inner diameter). One 1.0 L aliquot per station (n = 19) was filtered through 0.45 µm cellulose acetate membranes (Bikeman Bio, Changde, China), placed in acid-rinsed polyethylene bottles (10% HCl, rinsed with ultrapure water), and stored at 4 °C without acid. Samples were transported to the laboratory at 4 °C, after which sediment samples were divided into two portions, one stored at −20 °C until molecular analysis and the other stored at 4 °C until their physicochemical properties were analyzed. Water samples were stored at 4 °C until their physicochemical properties were analyzed.

2.2. DNA Extraction and QMEC Analysis

Total DNA was extracted from the sediment samples using a FastDNA SPIN Kit (MP Biomedicals, Solon, CA, USA). Following extraction, the total DNA and purity were assessed using a Qubit 4.0 (Thermo Fisher Scientific, Waltham, MA, USA) instrument. A Quantitative Microbial Ecology Chip (QMEC) analysis was performed in Magigene Biotechnology Co., Ltd. (Guangzhou, China) for the quantitative analysis of 71 functional genes associated with carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) cycling covering the major biogeochemical pathways annotated in the QMEC and previous surveys [20,22]. During the quantification process, three technical replicates and negative controls were set for each sample. Detection status and CT (cycle threshold) values for each gene were obtained using Canco software (version 1.0.0). Functional gene abundances were calculated as described previously with 16S rRNA using as an internal reference to standardize the data to obtain the relative quantification of each gene in each sample [23].

2.3. Environmental Factors Analysis

In this study, the water content (WC), total organic carbon (TOC), total nitrogen (TN), total phosphorus (TP), and total organic matter (TOM) of sediments, as well as water depth (WD), water temperature (WT), transparency (SD), dissolved oxygen (DO), pH, dissolved total nitrogen (DTN), ammonium nitrogen (NH4+), nitrate nitrogen (NO3−), nitrite nitrogen (NO2−), TN, TP, orthophosphate (PO43−), sulfate (SO42−), chemical oxygen demand (COD), and chlorophyll (Chl-a) in the overlying water (W-Chl-a) were all measured. The methods for detecting WT, SD, DO, pH, DTN, TN, TP, PO43−, COD, and Chl-a refer to our previous study [24]. NH4+ was measured by extraction with potassium chloride solution followed by spectrophotometric analysis. NO3− and NO2− were determined by the Nessler reagent spectrophotometric method. SO42− was measured using spectrophotometric methods. All physicochemical analyses followed our previous protocol [24] using spectrophotometry (Shimadzu, Japan) for lab nutrients and a portable meter (HACH, Ames, IA, USA) for field parameters; precision ≤ manufacturer specs. The ratios of TN to TP (TN/TP) in sediments and water were also calculated. The trophic state index (TSI) was calculated as described by [25].

2.4. Statistics Analysis

The functional gene abundances were calculated from the QMEC data. A violin plot, generated using the Wilcoxon rank-sum test, was used to illustrate genes with significantly different abundances between the south and north regions of Erhai Lake. The Mantel test was employed to explore the relationships between microbial functional gene abundance and environmental parameters. The Spearman correlation coefficients between functional genes involved in different elemental cycles were calculated using the ‘Hmisc’ package in the R program (version 4.4.3), and the results were visualized using the corrplot and ggplot2 packages. The spatial distribution was analyzed by interpolating the measurement data through ordinary kriging. This geostatistical procedure was performed using the gstat and ggplot2 packages within the R program (version 4.4.3).

3. Results

3.1. The Variation in Environmental Variables

Physicochemical properties of the overlying water and sediments are shown in Table S1. The Trophic State Index (TSI) ranges from 35 to 40 across all sampled sites, indicating that Erhai Lake is in a mesotrophic state. The eutrophication level of the northern sector is slightly higher than that of the southern sector, with the TSI and W-Chl-a in the former being significantly higher than those in the latter (Figure S1a). In the overlying water, the concentrations of TN and TP ranged from 0.47 to 0.55 mg/L and 0.02 to 0.04 mg/L, respectively, whereas in the sediment, these parameters ranged from 1680.00 to 7830.00 mg/kg and 370.30 to 1100.00 mg/kg. While significantly higher concentrations of TN and NO2− in the overlying water are observed in the northern sector compared to the southern sector, no significant differences were observed in the other physicochemical parameters between the two sectors (Table S1). Spatial analyses (Figure S2a–d) reveal clear north-to-south gradients in overlying-water TN, NO2− and Chl-a, while sediment TP shows a south-to-north decline, confirming heterogeneous nutrient cycling across Erhai Lake.

3.2. Distribution Patterns of Functional Genes in Erhai Lake Sediments

3.2.1. Carbon Cycling Genes

A total of 34 carbon cycling genes in the sediments were investigated by high-throughput CNPS gene q-PCR chip. The results revealed the presence of multiple carbon fixation pathways in the sediments of Erhai Lake. These included the Calvin cycle (rbcL), the Wood-Ljungdahl pathway (acsA), the 3-hydroxypropionate cycle (accA, pccA, smtA, and mct), the tricarboxylic acid cycle (frdA, aclB), and others such as acsB, korA, acsE, and cdaR in the sediment samples. Overall, the abundance of carbon fixation genes in the southern sector appears to be higher than that in the northern sector (Figure S3a). However, statistical differences were only observed for the rbcL and mct genes (p < 0.05) (Figure 2a,b,l). Similarly, the abundance of functional genes related to methane metabolism in the southern sector tends to be higher than that in the northern sector (Figure S3a). Specifically, there are significant differences in the abundance of methanotrophic functional genes (pmoA, mmoX) and methanogenic functional genes (mxaF) between the two regions (Figure 2i–k,m).
Genes related to hemicellulose degradation (abfA, xylA, and manB), starch degradation (sga), and lignin degradation (mnp) exhibited higher abundance, exceeding 1.00 × 106 copies/g (Table S2). Other carbon degradation genes detected in samples included degradation for cellulose (cex, cdh, and naglu), chitin (chiA), and pectin (pgu). Notably, with the significantly higher abundances of abfA, xylA, manB, sga, naglu, and mnp in the southern sector than in the northern sector (Figure 2c–h and Figure S3b). The overall higher gene abundance trend suggests a potential of faster carbon degradation and turnover in the southern sector of the lake relative to the northern sector.

3.2.2. Nitrogen Cycling Genes

A total of 22 nitrogen cycling genes in the sediments were investigated by high-throughput CNPS gene q-PCR chip. Overall, the abundance of nitrogen cycling functional genes showed an upward trend in the southern sector relative to the northern sector of the lake (Figure S3c), with the significantly higher abundance observed in the nasA, napA, narG, nirK, nirS, and nosZ genes (p < 0.05) (Figure 3a–h and Figure S3c). This result suggests that the southern sector of the lake has higher potential for assimilatory nitrate reduction (ANRA) and denitrification. The overall abundance of genes related to nitrification and anaerobic ammonium oxidation was relatively low, with the abundance of most of the related genes were at or below 103 copies/g and even absent (hzo), whereas amoB and hzsB reached 105–106 copies/g (Table S2). Notably, the abundance of genes involved in the reduction of nitrite to N2 (nirK, nirS, and nosZ) was higher than that of genes associated with dissimilatory nitrate reduction to ammonium (DNRA) and assimilatory nitrate reduction to ammonium (ANRA) (narG, napA, and nasA). Meanwhile, the abundance of nirS (ranging from 3.03 × 106 to 6.50 × 107 copies/g) was significantly higher than that of nirK (ranging from 5.97 × 104 to 9.93 × 105 copies/g), indicating a greater prevalence of nirS-type denitrifying bacteria. The abundance of the ammonification gene (ureC) and organic nitrogen mineralization gene (gdhA) showed relatively high levels (exceeding 107 copies/g), suggesting a high rate of organic nitrogen mineralization and ammonification (Table S2). The abundance of the nitrogen fixation gene (nifH) ranged from 1.10 × 107 to 1.97 × 107 copies/g, suggesting a relatively high potential for microbial nitrogen fixation in this lake.

3.2.3. Phosphorus Cycling Genes

The abundances of genes associated with inorganic phosphorus solubilization (pqqC, gcd) and organic phosphorus mineralization (phoX, phoD) were significantly higher in the southern sector of the lake relative to the northern sector (Figure 4a–e). Among the genes involved in organic phosphorus mineralization, the abundance of phoD reached an order of magnitude of 106 to 107 copies/g (Table S2). In contrast, the abundance of other organic phosphorus mineralization genes (e.g., cphy, bpp, and phoX) was relatively lower, ranging from 103 to 104 copies/g (Table S2). The abundance of the phnK gene related to the cleavage of the C-P lyase complex also showed an order of magnitude of 106 to 107 copies/g (Table S2). Both the abundance of the gcd and pqqC genes involved in inorganic phosphorus solubilization exceeded 106 copies/g. Notably, the abundance of the ppx gene (9.64 × 106 to 1.87 × 107 copies/g), which encodes a key enzyme for the hydrolysis of inorganic phosphorus compounds, was higher than that of the ppk gene (1.51 × 105 to 2.92 × 105 copies/g), a polyphosphate kinase involved in inorganic phosphorus biosynthesis. This suggests that the potential for inorganic phosphorus hydrolysis exceeds that for biosynthesis, indicating that the sediments of Erhai Lake act as an internal P reservoir that can re-release bioavailable P via internal loading. Our sediment concentration means (TN 5692 mg kg−1, TP 755 mg kg−1) are supported by the externally documented 2018 catchment supply (1576 t N yr−1, 183 t P yr−1 over 250 km2) [26], confirming that the enhanced gene-driven P-release potential operates on an anthropogenically accumulated reservoir rather than on pristine bedrock.

3.2.4. Sulfur Cycling Genes

Sulfur cycling functional gene detection included sulfur reduction genes (dsrA, dsrB, and apsA) and sulfur oxidation genes (soxY and yedZ). Similarly to the cycling of C, N, and P, the abundance of S cycling genes also exhibited a slightly higher trend in the southern sector compared to the northern sector (Figure S3d). The results showed that the abundance of sulfur reduction genes (1.12 × 107 to 3.73 × 107 copies/g) was higher than that of sulfur oxidation genes (3.28 × 106 to 8.66 × 106 copies/g) (Table S2), suggesting a more active sulfur reduction processes in these sediments. The abundance of sulfate reduction functional genes showed no significant difference between the southern and northern sectors of the lake. However, the abundance of the sulfur oxidation gene (yedZ) was significantly higher in the southern sector than in the northern sector (Figure 5a,b).
By integrating the abundance distributions of all functional genes related to C, N, P, and S cycling in the lake, we found that the abundance of these genes exhibited co-abundance characteristics across the sampling sites (Figure S3). The results of the Spearman correlation analysis show that functional genes involved in different elemental cycles are significantly positively correlated (Figure S4). These suggest the potential coupling of these elemental cycling processes.

3.3. Correlation of Environmental Factors and Functional Genes

The Mantel test analysis revealed that the content of total phosphorus in the sediments (S-TP) was significantly correlated with the abundance of carbon fixation genes and methane production genes (Figure 6a). This suggests that sedimentary total phosphorus (S-TP) may play a crucial role in regulating these microbial processes. Additionally, water temperature (WT), chemical oxygen demand (COD), and concentration of phosphate in the overlying water (W-PO43−) were significantly associated with methane metabolism-related genes (Figure 6a).
For the nitrogen cycling, S-TP content was significantly associated with the abundance of genes involved in nitrogen fixation, organic nitrogen mineralization, assimilatory nitrate reduction (ANRA) and ammonification (Figure 6b). In addition, nitrite (NO2−) concentration in the overlying water was primarily positively correlated with the processes of ANRA and dissimilatory nitrate reduction (DNRA) (Figure 6b). The ANRA was also significantly influenced by multiple environmental factors, including water temperature (WT), overlying water pH (W-pH), phosphate concentration in the overlying water (W-PO4−), and chemical oxygen demand (COD) (Figure 6b). These factors collectively affect the distribution and abundance of nitrogen-cycling functional genes.
Additionally, S-TP was found to be significantly correlated with the abundance of functional genes involved in sulfur metabolism (Figure 6c). In contrast, the phosphorus cycling process did not exhibit significant correlations with the environmental factors analyzed (Figure 6c). To visualize the spatial basis of the TP-gene correlation, we produced an interpolated map of sediment total phosphorus (Figure S2d), which displays a clear south-to-north gradient consis tent with the functional gene patterns reported above.

4. Discussion

4.1. Spatial Variability in Functional Gene Abundance and Associated Metabolic Potential

In sediments from the southern and northern sectors of Erhai Lake, most functional genes associated with carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) cycling exhibit a pronounced south-to-north decreasing trend in abundance. This pattern underscores the spatial heterogeneity of microbial metabolic potential within the lake. The enrichment of genes in the southern sector of the lake—specifically those mediating the degradation of complex organic matter (e.g., starch, hemicellulose, lignin) and those involved in methanogenesis/methanotrophy—implies a higher capacity for organic-matter turnover and endogenous nutrient release. Carbon fixation in the lake is dominated by the Wood-Ljungdahl pathway (key functional gene: acsA) and the 3-hydroxypropionate (3-HP) cycle (key functional genes: accA, pccA, smtA, mct). However, the relative contributions of the Calvin cycle (key functional gene: rbcL) and the 3-HP cycle (key functional gene: mct) differ between the southern and northern sectors, indicating region-specific constraints on microbial carbon acquisition. Such metabolic pathway plasticity highlights carbon metabolism as the metabolic backbone of the sediment bacterial communities—a role supported by the fact that the key functional genes of these communities not only drive carbon fixation but also modulate downstream biogeochemical interactions among carbon (C), nitrogen (N), phosphorus (P), and sulfur (S). These north–south contrasts in the intrinsic microbial functional potential of sediments, likely reflecting the influence of local environmental factors on sediment-dwelling microbial communities [27,28], stem from key differences between the two sectors, including hydrodynamic regime and external nutrient input patterns.
Nitrogen-cycle functional genes were dominated by denitrification markers, rather than those associated with dissimilatory nitrate reduction to ammonia (DNRA) or anaerobic ammonium oxidation (ANRA). This pattern indicates intrinsically low nitrogen retention capacity in the system, driven by the loss of nitrogen as gaseous nitrogen into the atmosphere. We found that the NO2− pool was processed almost exclusively by the nirS-type community, whose abundance exceeded that of nirK by 1–2 orders of magnitude (Table S2), consistent with the preference of nirS-type denitrifiers for the low-oxygen to anoxic conditions typical of surficial sediments [29]. Although functional genes associated with nitrate reduction (key genes: napA, narG) were more abundant in the south sector, the north sector exhibited higher nitrite (NO2−) concentrations—likely driven by greater external nitrogen loads. This discrepancy highlights that functional gene abundance alone cannot reliably predict in situ nitrogen cycling flux. Future studies should therefore integrate transcriptomic quantification with isotope-tracing or incubation-based flux measurements to clarify the dynamics of in situ nitrogen cycling.

4.2. Coupling of Biogeochemical Cycles in the Sediments of Erhai Lake

Our results reveal that, while the absolute abundances of functional genes linked to C, N, P, and S cycling differ between the southern and northern sectors, their relative proportions remain remarkably constant across all sampling sites. This pattern exhibits a typical co-abundance pattern, consistent with previous findings from shallow lake sediment studies [30], and is likely closely linked to the environmental properties of the sediments. Despite Erhai Lake being a deep lake (max. depth 20.9 m), the surficial 0–5 cm layer shows synchronous deposition-remobilization of C, N, and P [31] and maintains a millimeter-scale oxic-anoxic interface [32], creating microenvironments that may favor the observed microbial assemblage [33].
Moreover, this cooccurrence pattern likely reflects microbial communities’ coordinated regulation of different elemental cycles. Specifically, microbes couple elemental transformations through either cross-species syntrophy or genomic coordination of multiple genes within a single organism [34]. Functional gene correlations identified in the Huaihe River Basin sediment study provide a robust proxy for inferring coupled C, N, and S cycles systems [17]. Within methane-nitrogen cycle coupling, processes including aerobic methane oxidation coupled to denitrification (AME-D), anaerobic methane oxidation linked to denitrification (n-damo), and denitrification-associated methanogenesis have been validated [35,36,37]. This demonstrates microbial mediation of methane and nitrogen compound transformations. Similarly, in N-P coupling, elevated phosphorus concentrations in shallow lake sediments have been shown to enhance the coupling of nitrification and denitrification by increasing functional gene abundance, thereby accelerating nitrogen removal while promoting phosphorus release. Notably, the concurrent release of dissolved organic nitrogen (DON) helps balance the N/P ratio in the water column [38]. Collectively, in natural ecosystems, microbes maximize their efficiency in utilizing external nutritional resources to fuel self-generated energy acquisition and sustain growth. Therefore, the coordinated utilization of carbon, nitrogen, phosphorus, and sulfur (C-N-P-S) may represent a key adaptive strategy employed by microbial communities to adapt to environmental conditions.

4.3. Phosphorus as a Key Driver of Functional Gene Distribution

In this study, the key steps of C, N, and S cycles were found to be correlated with the concentration of TP in sediments, indicating that TP plays a crucial role in regulating biogeochemical cycles in Erhai Lake. Phosphorus bioavailability sustains microbial growth, thus rendering the microbially driven aquatic phosphorus cycle the most active component of the global phosphorus cycle [13]. Microbes regulate phosphorus turnover by adjusting the abundance of organic-phosphorus-mineralizing (phoX, phoD) and inorganic-phosphorus-solubilizing (pqqC, gcd) genes, thereby influencing P bioavailability and the cycling of other elements. It has been reported that in areas with higher flow velocities and finer sediments, lower concentrations of bioavailable phosphorus (bio-P) lead to increased microbial diversity and enhanced capabilities for organic phosphorus (OP) mineralization and inorganic phosphorus (IP) dissolution [39]. This could account for the elevated abundance of organic phosphorus mineralization genes and inorganic phosphorus dissolution genes in the southern versus the northern part of Erhai Lake. The southern sector of Erhai Lake, as the lake’s sole outflow area, likely generates more dynamic hydrological conditions—an environment that further fosters the proliferation of these genes. In Erhai Lake sediments, iron/aluminum (Fe/Al)-bound and fulvic/humic-associated P dominate TP, indicating abundant Fe(III) surfaces and organic matter [40,41]; thus, resuspension pulses simultaneously activate C, N, S, and P-cycling pathways.
Phosphorus (P) is intricately intertwined with the biogeochemical cycling of carbon and other essential elements. Notably, the microbially mediated marine phosphorus cycle exhibits covariation with the cycles of C, N, and metals on ocean-basin spatial scales [13,42]. In freshwater lake ecosystems, the TP content in sediments may regulate the cycling of C, N, and S by influencing the structure and function of microbial communities. In heavily eutrophic lakes, specifically Honghu Lake [23] and Taihu Lake [43], total phosphorus (TP) concentrations not only serve as a reliable predictor of the abundance of the genes of carbon, nitrogen, phosphorus, and sulfur cycling but also drive the succession of sediment microbial communities. Likewise, studies on riverine and wetland sediments have revealed that phosphorus concentration gradients directly modulate N-cycling gene pools and indirectly alter the environmental sensitivity of these genes. Specifically, elevated P levels help stabilize community structure and synchronize the responses of genes involved in C/N/P metabolism [44,45].
Furthermore, previous studies have documented that microbial communities in different lakes vary substantially in their diversity, abundance, and functional traits [23,24,46]. This variability reflects the interplay between abiotic factors (e.g., light intensity, dissolved oxygen) and biotic interactions (e.g., competition, predation), underscoring the complexity of microbial ecology in lake systems. Therefore, the targeted studies focusing on the unique microenvironments of individual lakes are essential for formulating effective strategies to regulate nutrient cycling and improve water quality in a given lake.

4.4. Implications for Eutrophication Management and Restoration

The Chlorophyll a (Chl-a) concentration in northern Erhai Lake was markedly higher than that in the southern part, which indicates a stronger degree of eutrophication [47]. Although TSI did not differ significantly, it followed the same trend. At sites N1 and N2 the N:P ratio approached the Redfield N:P ratio value (16:1) (Table S1), implying nitrogen limitation and favoring N-fixing cyanobacteria [48]. The elevated total nitrogen (TN) levels in northern Erhai suggest that the earlier nitrogen interception measures implemented in this region were less effective. This ineffectiveness can be attributed to the characteristics of the northern catchment—larger in scale, more complex in structure, and featuring longer hydrological flow paths—which collectively result in its contribution of over 60% to the lake’s external total nitrogen (TN) and total phosphorus (TP) inputs. Targeted, location-specific management is therefore urgent for the north, while the south—although exhibiting lower Chl-a and better water quality—may face greater internal nutrient release from sediments, as suggested by the higher abundances of functional genes observed in this sector.

5. Conclusions

This study provides a gene-level spatial survey of C, N, P, and S-cycling genes in the mesotrophic, deep plateau Erhai Lake, revealing three main findings:
(1)
Gene abundances follow a consistent south-to-north gradient and exhibit co-abundance characteristics across sampling sites; their positive correlation with sediment TP indicates that total phosphorus acts simultaneously as a deterministic filter for C-N-S-cycling genes and as a proxy for redox-driven coupling of all four elements, offering a single-variable management lever.
(2)
The combination of high gene abundances with a large, gene-accessible P pool positions the southern sector as the lake’s dominant internal loading hotspot; effective eutrophication control must therefore pair external-nutrient reduction in the north with active internal-P mitigation in the south.
(3)
The integrated gene-geochemistry survey establishes the first functional-gene baseline for the surficial sediment layer of Erhai Lake, providing a quantitative reference for future monitoring and for evaluating management effectiveness.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17233399/s1, Table S1. Physicochemical characteristics of surface sediments and overlying water in Erhai Lake. Table S2. Summary of functional gene abundances in Erhai Lake sediments. Figure S1. Violin plots illustrating physicochemical variables that differed significantly between the southern and northern sectors of Erhai Lake. (a) Chlorophyll-a concentration in overlying water (W-Chl-a); (b) total nitrogen concentration (W-TN); (c) nitrite concentration (W-NO2−). Variables without significant differences are omitted. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01; *** p < 0.001. Figure S2. Spatial distribution of (a) Chlorophyll-a concentration in overlying water (W-Chl-a); (b) total nitrogen concentration (W-TN); (c) nitrite concentration (W-NO2−); and (d) sediment total phosphorus concentration (TP) in Erhai Lake. Data were interpolated by ordinary kriging using the gstat and ggplot2 packages in R (v4.4.3). The color scale indicates concentration. Figure S3. Bubble charts showing the relative abundance of functional genes involved in C, N, P, and S cycling across all sampling sites in Erhai Lake. (a) Carbon-fixation and methane-metabolism genes; (b) Carbon-degradation genes; (c) Nitrogen-cycling genes; (d) Phosphorus- and sulfur-cycling genes. Bubble size is proportional to relative abundance (copies/g). Figure S4. Heatmap of Spearman correlation coefficients among the abundances of C, N, P, and S cycling functional genes.

Author Contributions

Writing—original draft, methodology, investigation, visualization, data curation, Z.X.; visualization, investigation, J.F., H.L. and X.C.; visualization, data curation, K.Y. and L.Z.; visualization, investigation, X.W.; writing—original draft, methodology, investigation, visualization, S.X.; writing–review and editing, supervision, project administration, funding acquisition, conceptualization, X.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This study was financially supported by the National Observation and Research Station of Erhai Lake Ecosystem in Yunnan (2022), and Natural Science Foundation of China (NSFC 42577128 and 31971526).

Data Availability Statement

All high-throughput Quantitative Microbial Ecology Chip (QMEC) data generated in this study are included in this article and its Supplementary Materials.

Acknowledgments

We thank Wei Li (National Observation and Research Station for Erhai Lake Ecosystem, Dali, China) for his assistance in field sampling. We acknowledge the assistance of Doubao, an AI-powered language tool developed by ByteDance. During the preparation of this manuscript, Doubao was exclusively used for language polishing, specifically to refine the clarity, coherence, and grammatical accuracy of the English text.

Conflicts of Interest

The authors declare no conflicts of interest.

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Water 17 03399 g001
Figure 1. Sampling sites in Erhai Lake, China. Red dots denote sites S1–S10 in the southern sector, and orange dots indicate sites N1–N9 in the northern sector.
Figure 1. Sampling sites in Erhai Lake, China. Red dots denote sites S1–S10 in the southern sector, and orange dots indicate sites N1–N9 in the northern sector.
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Figure 2. Relative abundance of key functional genes and processes involved in carbon cycle in sediments of Erhai Lake, China. (a–k) Violin plots illustrating genes with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (l,m) Depiction of the carbon fixation steps and methane metabolism, with the associated genes indicated. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01. Note: Prefix “S” and “N” denote southern and northern sectors, respectively; this convention applies to all subsequent figures.
Figure 2. Relative abundance of key functional genes and processes involved in carbon cycle in sediments of Erhai Lake, China. (a–k) Violin plots illustrating genes with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (l,m) Depiction of the carbon fixation steps and methane metabolism, with the associated genes indicated. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01. Note: Prefix “S” and “N” denote southern and northern sectors, respectively; this convention applies to all subsequent figures.
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Figure 3. Relative abundance of key functional genes and processes involved in nitrogen cycle in sediments of Erhai Lake, China. (a–g) Violin plots illustrating genes with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (h) Depiction of steps of the nitrogen cycle, with the associated genes indicated. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01; *** p < 0.001.
Figure 3. Relative abundance of key functional genes and processes involved in nitrogen cycle in sediments of Erhai Lake, China. (a–g) Violin plots illustrating genes with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (h) Depiction of steps of the nitrogen cycle, with the associated genes indicated. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01; *** p < 0.001.
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Figure 4. Relative abundance of key functional genes and processes involved in the phosphorus cycle in sediments of Erhai Lake, China. (a–d) Violin plots illustrating genes with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (e) Depiction of steps of the phosphorus cycle, with the associated genes indicated. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01.
Figure 4. Relative abundance of key functional genes and processes involved in the phosphorus cycle in sediments of Erhai Lake, China. (a–d) Violin plots illustrating genes with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (e) Depiction of steps of the phosphorus cycle, with the associated genes indicated. Asterisks denote Wilcoxon test significance: * p < 0.05; ** p < 0.01.
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Figure 5. Relative abundance of key functional genes and processes involved in sulfur cycle in sediments of Erhai Lake, China. (a) Violin plots illustrating S oxidation gene (yedZ) with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (b) Depiction of the sulfur cycling steps with the genes involved. Asterisks denote Wilcoxon test significance: * p < 0.05.
Figure 5. Relative abundance of key functional genes and processes involved in sulfur cycle in sediments of Erhai Lake, China. (a) Violin plots illustrating S oxidation gene (yedZ) with significantly different abundances between the southern and northern sectors of Erhai Lake; genes without significant differences are omitted. (b) Depiction of the sulfur cycling steps with the genes involved. Asterisks denote Wilcoxon test significance: * p < 0.05.
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Figure 6. Mantel test results between functional-gene matrices and environmental variables. (a) Carbon cycling; (b) Nitrogen cycling; (c) Phosphorus and sulfur cycling. Line colors: green denotes 0.01 ≤ p < 0.05, orange denotes p < 0.01, and gray denotes p ≥ 0.05. Line thickness scales with Mantel’s r (correlation coefficient). Asterisks indicate Spearman correlation significance: * p < 0.05; ** p < 0.01; *** p < 0.001.
Figure 6. Mantel test results between functional-gene matrices and environmental variables. (a) Carbon cycling; (b) Nitrogen cycling; (c) Phosphorus and sulfur cycling. Line colors: green denotes 0.01 ≤ p < 0.05, orange denotes p < 0.01, and gray denotes p ≥ 0.05. Line thickness scales with Mantel’s r (correlation coefficient). Asterisks indicate Spearman correlation significance: * p < 0.05; ** p < 0.01; *** p < 0.001.
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MDPI and ACS Style

Xie, Z.; Xiong, S.; Liu, H.; Feng, J.; Chen, X.; Yang, K.; Zhang, L.; Wang, X.; Zhang, X. Phosphorus Regulated Coordination of Carbon, Nitrogen, Sulfur and Phosphorus Cycling Genes in Sediments of a Plateau Mesotrophic Lake Erhai in Yunnan, China. Water 2025, 17, 3399. https://doi.org/10.3390/w17233399

AMA Style

Xie Z, Xiong S, Liu H, Feng J, Chen X, Yang K, Zhang L, Wang X, Zhang X. Phosphorus Regulated Coordination of Carbon, Nitrogen, Sulfur and Phosphorus Cycling Genes in Sediments of a Plateau Mesotrophic Lake Erhai in Yunnan, China. Water. 2025; 17(23):3399. https://doi.org/10.3390/w17233399

Chicago/Turabian Style

Xie, Zhen, Shunzi Xiong, Huaji Liu, Jimeng Feng, Xiaoyi Chen, Kaiwen Yang, Lei Zhang, Xinze Wang, and Xiaojun Zhang. 2025. "Phosphorus Regulated Coordination of Carbon, Nitrogen, Sulfur and Phosphorus Cycling Genes in Sediments of a Plateau Mesotrophic Lake Erhai in Yunnan, China" Water 17, no. 23: 3399. https://doi.org/10.3390/w17233399

APA Style

Xie, Z., Xiong, S., Liu, H., Feng, J., Chen, X., Yang, K., Zhang, L., Wang, X., & Zhang, X. (2025). Phosphorus Regulated Coordination of Carbon, Nitrogen, Sulfur and Phosphorus Cycling Genes in Sediments of a Plateau Mesotrophic Lake Erhai in Yunnan, China. Water, 17(23), 3399. https://doi.org/10.3390/w17233399

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