Alcomycete symbiotic system and application thereof in treatment of aquaculture tail water

Abstract

The invention discloses a phycomycete symbiotic system and application of the phycomycete symbiotic system in treatment of aquaculture tail water, and belongs to the technical field of tail water treatment. The phycomycete symbiotic system comprises chlorella, scenedesmus and activated sludge, and the initial inoculation dry weight ratio of the chlorella to the scenedesmus to the activated sludge is 1: 1: 6. And exogenously adding octanoyl-L-homoserine lactone or tetradecanoyl-L-homoserine lactone into the phycomycetes symbiotic system, so as to construct the phycomycetes symbiotic system with enhanced functions. On the basis of a mixed algae-bacteria symbiotic system with an optimized ratio, directional enhancement of functions is realized by virtue of quorum sensing signal molecules, the stability and resistance gene interception capability of the quorum sensing signal molecules under the stress of antibiotics are verified, and finally efficient purification of the aquaculture tail water is realized. According to the invention, the blank of the prior art in the aspects of advanced regulation and control of a phycomycete synergistic mechanism and synergistic treatment of emerging pollutants is filled up.

Description

An algae-bacteria symbiotic system and its application in treating aquaculture wastewater. Technical Field

[0001] This invention relates to the field of wastewater treatment technology, and in particular to an algae-bacteria symbiotic system and its application in treating aquaculture wastewater. Background Technology

[0002] With the rapid expansion of intensive freshwater aquaculture, aquaculture wastewater has become a significant source of nitrogen, phosphorus, and emerging pollutants in environmental water bodies. Statistics show that aquaculture production accounts for over 80% of my country's total aquatic product output, but approximately 82 cubic meters of wastewater are discharged for every kilogram of aquatic products produced. 3 The wastewater is rich in ammonia nitrogen (NH4). + -N) and phosphate (PO4) 3- Pollutants such as phosphatidylcholine (P) are present in the wastewater. Furthermore, antibiotics widely used in aquaculture (such as neomycin sulfate, enrofloxacin, and sulfadiazine) are commonly found as residues in the wastewater. These residual antibiotics not only pose a potential toxicity to aquatic organisms but also continuously screen for drug-resistant bacteria, exacerbating the risk of antibiotic resistance genes (ARGs) spreading in water bodies and posing a serious threat to regional ecological security.

[0003] Traditional physicochemical treatment methods (such as flocculation and sedimentation) can partially remove pollutants, but they suffer from high costs and the potential for secondary pollution. Meanwhile, ecological treatment technologies such as constructed wetlands face limitations, including large land areas, long hydraulic retention times, and weak resistance to shock loads. Therefore, developing new, cost-effective, and environmentally friendly wastewater treatment models has become an urgent need for the industry.

[0004] The algae-bacterial symbiotic system offers a novel approach to wastewater treatment by mimicking the mutually beneficial mechanisms of natural ecosystems: microalgae absorb carbon dioxide, nitrogen, and phosphorus nutrients from the wastewater through photosynthesis, releasing oxygen; aerobic bacteria, powered by algal oxygen, degrade organic pollutants (such as uneaten food and feces), and the released inorganic salts and carbon dioxide are reused by the algae, forming a closed loop of material cycling and synergistic degradation of pollutants. This technology can reduce energy consumption by more than 30% compared to the traditional activated sludge process and can convert waste nutrients into algae-bacterial biomass with resource recovery value.

[0005] Although algae-bacterial symbiotic systems have shown great potential in wastewater treatment, several key technical bottlenecks remain before they can be effectively applied to the treatment of aquaculture wastewater, which is characterized by complex composition and fluctuating water quality. One key challenge is the selection of algae species and the optimization of the algae-bacterial ratio. Scenedesmus sp. and Chlorella vulgaris, two common green algae in freshwater environments, possess strong environmental tolerance and rapid growth, respectively. Constructing multi-algae mixed culture systems is considered an effective strategy to improve system stability. However, mixed algae systems introduce competition for light and nutrients between algae, and the inherent dependence and constraint between microalgae and symbiotic bacteria makes the synergistic interaction between algae and bacteria a challenge. How to quickly establish a stable functional microbial community in the early stages of system startup by controlling the initial algae-bacterial inoculation ratio is a crucial factor determining treatment efficiency, but current research on this in aquaculture wastewater treatment is insufficient.

[0006] Secondly, there is the issue of regulating microbial communal behavior. In algae-microbe symbiotic micro-ecosystems, microorganisms do not exist in isolation but engage in "chemical dialogue" through quorum sensing. Acyl homoserine lactones (AHLs), commonly used by Gram-negative bacteria, exhibit different biological characteristics depending on their chain length: short-chain AHLs (such as C8-HSL) have strong diffusion capabilities and are often associated with immediate responses such as enzyme secretion and motility; long-chain AHLs (such as C14-HSL) primarily regulate communal behaviors that require long-term maintenance, such as biofilm formation. Currently, how to utilize exogenous signaling molecules to directionally optimize algae-microbe interactions in mixed algae systems and improve system purification efficiency remains a relatively unexplored new problem.

[0007] Thirdly, there is the issue of system stability under antibiotic stress. Residual antibiotics in the wastewater exert continuous selective pressure on the algae-bacteria symbiotic system. Different classes of antibiotics, due to differences in their mechanisms of action (e.g., aminoglycosides inhibit protein synthesis, quinolones inhibit DNA replication), may have significantly different effects on algae-bacteria community structure, expression of nitrogen and phosphorus conversion genes, and the accumulation and spread of ARGs. Currently, most research focuses on sulfonamides or quinolones, while our understanding of the algae-bacteria interaction mechanisms under stress from aminoglycoside antibiotics (such as neomycin sulfate), which are among the most widely used antibiotics in aquaculture, remains lacking.

[0008] In summary, there is an urgent need to systematically study the optimization of algae-bacteria ratios, the enhanced regulation of quorum sensing, and the system response mechanisms under different antibiotic stresses, so as to provide theoretical basis and technical support for developing new, efficient, stable, stress-resistant, and resource-recovery-functional aquaculture wastewater treatment processes. Summary of the Invention

[0009] The purpose of this invention is to provide an algae-bacterial symbiotic system and its application in treating aquaculture wastewater, thereby addressing the problems existing in the prior art. Based on an optimized mixed algae-bacterial symbiotic system, it utilizes quorum sensing signaling molecules to achieve targeted functional enhancement and verifies its stability under antibiotic stress and its ability to intercept resistance genes, ultimately achieving highly efficient purification of aquaculture wastewater. This invention fills the gap in existing technologies regarding the deep regulation of algae-bacterial synergistic mechanisms and the synergistic treatment of emerging pollutants.

[0010] To achieve the above objectives, the present invention provides the following solution: The present invention provides an algae-bacterial symbiotic system, which includes Chlorella, Scenedesmus and activated sludge, wherein the initial inoculation dry weight ratio of Chlorella, Scenedesmus and activated sludge is 1:1:6.

[0011] Preferably, the activated sludge is derived from aquaculture ponds.

[0012] The present invention also provides a functionally enhanced algae-bacterial symbiotic system, wherein octanoyl-L-homoserine lactone or tetradecanoyl-L-homoserine lactone is exogenously added to the algae-bacterial symbiotic system.

[0013] Preferably, the concentration of the added octanoyl-L-homoserine lactone or tetradecanoyl-L-homoserine lactone is 1 ppm.

[0014] The present invention also provides a method for treating aquaculture wastewater, including the step of contacting the aquaculture wastewater with the algae-bacteria symbiotic system or the functionally enhanced algae-bacteria symbiotic system to purify the wastewater.

[0015] The present invention also provides a method for treating aquaculture wastewater containing antibiotics, including the step of contacting the said algae-bacteria symbiotic system with the antibiotic-containing wastewater to purify the wastewater.

[0016] Preferably, the antibiotic includes at least one of neomycin sulfate, enrofloxacin, and sulfadiazine.

[0017] The present invention also provides the application of the algae-bacteria symbiotic system in the treatment of aquaculture wastewater.

[0018] Preferably, when using the algae-bacteria symbiotic system to treat aquaculture wastewater containing antibiotics, it can remove nitrogen and phosphorus pollutants from the aquaculture wastewater while also inhibiting the spread of antibiotic-induced resistance genes; the antibiotics include at least one of neomycin sulfate, enrofloxacin, and sulfadiazine.

[0019] The present invention also provides the application of the enhanced algae-bacteria symbiotic system described above in the treatment of aquaculture wastewater.

[0020] This invention discloses the following beneficial effects: 1. It optimizes the inoculation strategy of the algae-bacterial symbiotic system, significantly improving the effluent purification efficiency. This invention, through systematic screening of the mixing ratio of Chlorella and Scenedesmus and their inoculation ratio with activated sludge, determined the optimal inoculation dry weight ratio to be 1:1:6 (Chlorella: Scenedesmus: activated sludge). Under this optimized ratio, the algae-bacterial symbiotic system exhibits synergistic purification performance: High-efficiency ammonia nitrogen removal: Complete removal of ammonia nitrogen is achieved within 12 hours (removal rate 100%); Deep total nitrogen removal: The total nitrogen (TN) removal rate is close to 100% within 72 hours, significantly better than single algae species or pure activated sludge systems; Retention of phosphorus removal potential: A good microbial foundation is preserved for the subsequent biological phosphorus removal function.

[0021] This optimized ratio solves the technical bottlenecks of algae-algae competition and algae-bacteria imbalance in traditional algae-bacteria systems, providing directly applicable process parameters for aquaculture wastewater treatment.

[0022] 2. The differential regulatory mechanism of quorum sensing signal molecules was revealed, and the targeted enhancement of system function was realized. This invention first applied acyl homoserine lactone signal molecules of different chain lengths (C8-HSL and C14-HSL) to the enhanced regulation of algal-bacterial symbiotic systems, and found that the two had different effects on the construction, stability and functional output of algal-bacterial symbiotic systems: (1) C14-HSL (long chain signal molecule): significantly enriched biofilm-forming related bacterial groups such as Pseudomonadota and Planctomycetota, activated the chemosensory system, two-component pathway, second messenger pathway and endogenous quorum sensing system, and guided the microorganisms from the free state to the biofilm state. The results were: the system stability was enhanced, and it entered the stable operation period 7 days earlier than the control group; the nitrogen removal pathway was mainly denitrification / anaerobic ammonium oxidation, and the nitrogen was completely removed in the gas phase; the total phosphorus removal rate reached 100%, which was significantly better than the control group (76.3%).

[0023] (2) C8-HSL (medium- and short-chain signaling molecules): promotes the enrichment of free bacterial communities such as Actinomycetota and Bacillota, and enhances the system's chemotactic movement and organic matter degradation capabilities. As a result, the nitrogen metabolism pathway is mainly based on nitrate reduction assimilation, which efficiently converts nitrogen resources into microbial biomass; the system's metabolic functions are diversified, and the carbon cycle and nitrogen cycle are more closely coupled.

[0024] This invention utilizes quorum sensing molecules with different properties to directionally modify and optimize the structure and function of microbial ecosystems, providing a novel technical path and theoretical support for the application of high-performance algae-bacteria symbiotic systems in environmental remediation and freshwater pond tailwater treatment.

[0025] 3. The system's tolerance and adaptability to various antibiotic stresses were verified, expanding its application scenarios. This invention systematically evaluated the effects of three commonly used aquaculture antibiotics [neomycin sulfate (aminoglycoside), enrofloxacin (quinolone), and sulfadiazine (sulfonamide)] on an algal-microbe symbiotic system. The results showed that the algal-microbe symbiotic system exhibited good stress resistance and adaptability: In the neomycin sulfate group, a stable microbial community was constructed with Pseudomonadota as the core, achieving a total nitrogen removal rate of 81%, significantly better than other antibiotic treatment groups (58%-64%). No nitrates accumulated, and the system operated stably. In the enrofloxacin and sulfadiazine groups, although some functional bacterial groups were selectively inhibited, the system maintained a certain purification function through community reconstruction (e.g., the sulfadiazine group shifted towards an actinomycete-centric model), demonstrating strong ecological resilience. Drug resistance gene analysis: The abundance of antibiotic resistance genes (such as aminoglycoside resistance genes, fluoroquinolone resistance genes, and sulfonamide resistance genes) in each treatment group was significantly higher than that in the control group, indicating that the system has the potential to enrich and intercept resistance genes in situ, effectively reducing the risk of ARGs spreading to natural water bodies.

[0026] This invention confirms that the optimized algae-bacteria symbiotic system can not only efficiently remove nitrogen and phosphorus, but also maintain functional stability under antibiotic stress and intercept the spread of resistant genes, providing key technical support for the treatment of aquaculture wastewater containing emerging pollutants.

[0027] 4. Combining resource recovery potential and environmental friendliness: The algae-bacterial symbiotic system of this invention converts nitrogen and phosphorus in effluent into algae-bacterial biomass through biological fixation, avoiding the generation of chemical sludge. The algae-bacterial biomass can be further developed, such as as a biodiesel feedstock or protein feed, achieving the dual goals of pollutant removal and resource recovery, which is in line with the concepts of circular economy and green development. Attached Figure Description

[0028] Figure 1 shows the SEM scanning electron microscope images of different algal-bacterial symbiotic systems; Figure 2 shows the purification effect of different treatment groups in the preliminary screening experiment; (A) Changes in ammonia nitrogen concentration; (B) Changes in nitrate nitrogen concentration; (C) Changes in nitrite concentration; (D) Changes in total nitrogen concentration; (E) Changes in total phosphorus concentration; Figure 3 shows the purification effect of different treatment groups in the optimization experiment; (A) Changes in ammonia nitrogen concentration in the mixed group; (B) Changes in nitrate nitrogen concentration in the mixed group; (C) Changes in nitrite concentration in the mixed group; (D) Changes in total nitrogen concentration in the mixed group; (E) Changes in total phosphorus concentration in the mixed group; Figure 4 shows the phylum-level microbial community structure of different treatment groups; Figure 5 shows the genus-level microbial community structure of different treatment groups. Figure 6 shows the functional gene prediction results from the COG database; Figure 7 shows the FAPROTAX functional prediction results; Figure 8 shows the water purification results; (A) changes in ammonia nitrogen concentration; (B) changes in nitrate nitrogen concentration; (C) changes in nitrite concentration; (D) changes in total nitrogen concentration; (E) changes in total phosphorus concentration; Figure 9 shows the results at the phylum level; Figure 10 shows the results at the genus level; In the figures, A and C represent groups C8, C14, and the control group, respectively; Figure 11 shows the results of multi-species functional difference analysis at the species level; Figure 12 shows the nitrogen metabolism pathway of the mixed algae-bacteria symbiotic system; Figure 13 shows the relative abundance of nitrogen metabolism genes. Heatmap; Figure 14 shows the cell membrane pathways related to the transition of bacteria from a free state to biofilm formation within the algae-bacterial symbiotic system after the addition of signaling molecules; Figure 15 shows the relative abundance of genes in the cell membrane pathway; Figure 16 shows the water purification results in the algae-bacterial symbiotic system with different antibiotics added; (A) Changes in ammonia nitrogen concentration; (B) Changes in nitrate nitrogen concentration; (C) Changes in nitrite concentration; (D) Changes in total nitrogen concentration; (E) Changes in total phosphorus concentration; Figure 17 shows the phylum-level analysis results in the algae-bacterial symbiotic system with different antibiotics added; Figure 18 shows the genus-level heatmap analysis results in the algae-bacterial symbiotic system with different antibiotics added; In the figures, A and D respectively... Figure 19 shows the species and functional contribution analysis results in the algae-bacterial symbiotic system with different antibiotics added; in the figure, AD represents the neomycin sulfate group, enrofloxacin group, sulfadiazine group and control group, respectively; Figure 20 shows the CADR resistance gene functional annotation in the algae-bacterial symbiotic system with different antibiotics added; (A) Neomycin sulfate group; (B) Enrofloxacin group; (C) Sulfadiazine group; (D) Control group; Figure 21 shows the effect of adding different antibiotics on nitrogen metabolism pathways; Figure 22 shows the relative abundance of nitrogen metabolism genes in the algae-bacterial symbiotic system with different antibiotics added. Detailed Implementation

[0029] Various exemplary embodiments of the present invention will now be described in detail. This detailed description should not be considered as a limitation of the present invention, but rather as a more detailed description of certain aspects, features, and embodiments of the present invention.

[0030] The terms “include,” “including,” “have,” “contain,” etc., used in this article are all open-ended terms, meaning that they include but are not limited to.

[0031] Example 1: Effect of Algae-Bacterial Inoculation Ratio on the Efficiency of Symbiotic System in Treating Aquaculture Wastewater 1. Methods and Materials 1.1 Experimental Materials The *Chlorella vulgaris* (FACHB-8) and *Scenedesmus* (FACHB-489) used in the experiment were purchased from the Institute of Hydrobiology, Chinese Academy of Sciences. Before inoculation, the algal culture solution was washed three times with ultrapure water. The algal culture and culture medium were cultured on BG11 medium and placed in a constant temperature and light incubator. The incubator conditions were set at 25℃, 4000 lux light intensity, and a light-to-dark ratio of 12:12. Shaking was performed for 3 minutes at 9:00, 15:00, and 21:00 daily, with a rotation speed of 600 r / min to 1000 r / min (600 r / min was used as an example in this example). The culture medium was changed every two weeks during the culture period.

[0032] Before the experiment, the BG11 medium was sterilized using an autoclave at 121°C for 30 minutes. After cooling to room temperature, the pH was adjusted to the optimal level using NaOH and HCl. Algae were inoculated into 500mL Erlenmeyer flasks at a volume ratio of algae solution to BG11 medium of 1:5 for propagation.

[0033] 1.2 Absorbance-Algal Biomass Relationship Algae in the logarithmic growth phase were diluted in 50 mL centrifuge tubes at different ratios (2x, 3x, 4x, 5x, 6x, 7x, 8x, 9x, 10x). Spectrophotometers were used to read the absorbance of the algal dilutions at different dilution ratios. The algal solution was filtered onto a 0.45 μm filter membrane that had been baked to constant weight (110℃, 8h; the constant weight of the baked filter paper was accurately measured as B0). The filtered filter paper was then baked to constant weight (110℃, 8h). After cooling, the mass of the filter paper and algae was weighed as B1. The formula for calculating the absorbance-algal biomass relationship is: Chlorella: Y = 1.1263x + 0.0140 (R... 2 =0.9993); Scenedesmus: Y=1.6763x+0.0003 (R 2 =0.9991); Y is the dry weight of algal biomass (g / L), and x is the absorbance (OD). 680 ).

[0034] 1.3 Sludge treatment and testing (1) Sludge treatment: Activated sludge was taken from the largemouth bass breeding pond. The sampled activated sludge was placed in a 3000mL conical flask for aeration for 24h. Then, sludge impurities were removed using a 60-mesh sieve. The sludge with impurities removed was temporarily kept in simulated aquaculture tailwater.

[0035] (2) Activated sludge testing: The dry weight of activated sludge, i.e., the mass of activated sludge obtained by drying at 103℃ to constant weight, is determined by the gravimetric method: a certain volume (V) of activated sludge is filtered through a pre-dried quantitative filter paper with a known mass (M0), and then dried in an oven (103℃) to constant weight. The mass of the filter paper and the activated sludge (M1) is then weighed, and the mass of the sludge (W) is obtained by the difference method. The mixed liquor suspended solids (MLSS) concentration is calculated by the following formula: W (dry weight, g) = M1 - M0; MLSS (g / L) = W / V = (M1 - M0) / V.

[0036] 1.4 Experimental Methods Two experiments were conducted. Preliminary screening experiment: The effects of different algae and bacteria species and ratios on the purification effect of aquaculture wastewater were preliminarily analyzed. Optimization experiment: Based on the results of the preliminary screening experiment, the algae and bacteria ratio was further optimized. The preliminary screening experiment consisted of 10 experimental groups (AJ), and the optimization experiment consisted of 5 experimental groups (KO), with 3 replicates for each experiment.

[0037] The influent concentrations were: ammonia nitrogen 5 mg / L, nitrate nitrogen 10 mg / L, organic nitrogen 5 mg / L, total phosphorus 2 mg / L, and C / N ratio of 5. The experimental design is shown in Tables 1 and 2. The experiment was conducted in a light incubator at 25℃, with a light intensity of 5000 lux and a light-to-dark ratio of 12:12. Algae and bacteria were added to 500 mL Erlenmeyer flasks according to the experimental design, and the water was not changed during the experiment. To ensure sufficient contact between the simulated effluent and the microalgae and activated sludge, the flasks were shaken daily at 8:00, 14:00, and 20:00. At the beginning of the experiment, supernatant was collected at 0h, 4h, 8h, 12h, and 24h for water quality testing. Subsequently, supernatant was collected daily after sedimentation. Water quality analysis was performed according to "Methods for Detection and Analysis of Water and Wastewater (Fourth Edition)". Nitrite nitrogen (NO2) was measured after filtration using a 0.45µm aqueous polyethersulfone membrane. - -N), nitrate nitrogen (NO3) - -N), ammonia nitrogen (NH4) + The concentrations of NO2- and NH3-N, NO2- - -N, NO3 - -N and ammonia nitrogen were determined using the modified N-(1-naphthyl)ethylenediamine spectrophotometric method, phenol disulfonic acid method, and salicylic acid spectrophotometric method, respectively; total nitrogen (TN) and total phosphorus (TP) were determined by alkaline potassium persulfate digestion and ultraviolet spectrophotometry. After the experiment, the mixture at the bottom of the conical flasks of groups BD and FJ was collected and scanned by SEM electron microscopy.

[0038] Table 1. Algae-bacteria ratio in different treatment groups during preliminary screening experiment (dry weight / mg) Table 2. Algae-bacteria ratio for different treatment groups in the optimized experiment (dry weight / mg) 1.5 Microbial Diversity Analysis After the experiment, the algae and bacteria mixture at the bottom of the conical flask was collected, and the microbial community was analyzed using high-throughput sequencing technology. Microbial sequencing was performed by Majorbio Biopharmaceuticals Co., Ltd. (Shanghai, China). The basic sequencing workflow included sample DNA extraction, PCR amplification, PCR product quantification, sequencing library construction, and paired-end sequencing. The bacterial V3-V4 16sRNA region was targeted and amplified using primers 338F (5'-ACTCCTACGGGAGGCAGCAG-3', SEQ ID NO.1) and 806R (5'-GGACTACHVGGGTWTCTAAT-3', SEQ ID NO.2). The amplified PCR products were sequenced on the Illumina MiSeq platform. The sequencing results were analyzed using the Majorbio cloud platform.

[0039] 2. Results and Analysis 2.1 Preliminary Screening of Microstructure of Algal-Bacterial Symbionts The scanning electron microscopy results of each group of algal-bacterial symbionts are shown in Figure 1. R1 represents group I, and R2-R8 represent groups BD, FH, and J. R1 is the pure activated sludge group, whose bottom sediments exhibit a sheet-like accumulation structure and have not formed a complete three-dimensional structure. Figures R2-R4 show group BD, where the microalgae in the algal-bacterial symbiotic system is Chlorella vulgaris. The symbionts in each group are spherical. With the increase of the added activated sludge concentration, under the stirring action of the water, the spherical structures of the Chlorella vulgaris groups show more obvious sheet-like accumulation. R5-R7 represent group FG, where the microalgae in the algal-bacterial symbiotic system is Scenedesmus, and the sediments are boat-shaped. R8 is the mixed algae group, with sediments in both circular and boat-shaped shapes, and the resulting symbiotic structure is more rounded. Compared to R1, a significant difference in shape was observed between the algae and bacteria groups. The pure activated sludge group only had a sheet-like structure, while the groups with added microalgae exhibited a three-dimensional structure, and the shape was related to the type of microalgae added, indicating that the microalgae and bacteria had combined. As the concentration of added sludge increased, the grooves on the surface of the algae and bacteria particles formed under the action of horizontal shear force in the water body decreased.

[0040] 2.2 Preliminary Screening of Algae-Bacterial Ratio The changes in water quality indicators of each treatment group in the preliminary screening experiment are shown in Figure 2. Each algae-bacterial symbiotic group exhibited a strong removal efficiency for nitrogen. All groups achieved 100% ammonia nitrogen removal rate after 72 hours. Among them, the treatment group with algae:activated sludge = 1:3 (groups C, G, and J) completely removed ammonia nitrogen after 12 hours of experimentation, indicating that this inoculation ratio had a superior effect on ammonia nitrogen treatment (Figure 2, A).

[0041] Regarding nitrate nitrogen removal, at 72 hours, the algae:activated sludge ratio of 1:3 treatment group was superior to other groups. Group C achieved a nitrate nitrogen removal rate of 99.17% (10 mg / L → 0.083 mg / L), Group J achieved 98.04% (10 mg / L → 0.196 mg / L), and Group G achieved 38.3% (10 mg / L → 6.17 mg / L) (Figure 2, B). Figure 2, C, shows the nitrite nitrogen purification effect. The algae:activated sludge ratio of 1:3 treatment group was superior to other treatment groups. The mixed algae group J achieved a nitrite removal rate of 80.8% (0.24 mg / L → 0.046 mg / L), which was superior to the other two single algae groups (Group G: 0.19 mg / L → 0.05 mg / L, Group C: 0.163 mg / L → 0.11 mg / L). Figure 2D shows the total nitrogen removal efficiency of each group. The treatment group with algae:activated sludge = 1:3 was better than the other treatment groups. Among them, the mixed algae group J had almost complete TN removal after 72 h, with the highest denitrification efficiency, which was 33.3%~90% higher than the other groups. Figure 2E shows the phosphorus removal pattern in the symbiotic system. The overall removal efficiency of total phosphorus in each treatment group was not good. Although the total phosphorus removal rate of the mixed algae group J was the highest, it was only 7.5% (2 mg / L → 1.85 mg / L).

[0042] 2.3 Optimization of Algae-Bacteria Ratio: Preliminary screening experiments revealed that the algae-bacteria symbiotic system achieved a high purification efficiency when the algae:activated sludge ratio was 1:3, with mixed algae group J showing the best purification effect. To further determine the optimal ratio of mixed algae, optimization experiments were conducted, and the purification results of each mixed algae group are shown in Figure 3. At 216 h, nitrite, nitrate nitrogen, and total nitrogen in group M (Chlorella vulgaris to Scenedesmus ratio of 1:1) were almost completely removed, with a removal efficiency significantly better than other groups. After 74 h, the nitrite concentration fluctuated between 0 mg / L and 0.2 mg / L. After 48 h, all groups achieved 100% removal rate for ammonia nitrogen, while the removal effect of total phosphorus was poor in each group.

[0043] 2.4 Microbial Analysis of the Algae-Bacterial Symbiotic System 2.4.1 Phylum-Level Microbial Community Structure Phylum-level microbial community structure analysis of different experimental groups revealed the profound impact of algae type and activated sludge addition on the microbial composition of the symbiotic system. As shown in Figure 4, there were significant differences in the relative abundance distribution at the phylum level among the experimental groups. Pseudomonas was the absolutely dominant phylum in all experimental groups, and its relative abundance differed significantly among groups with different proportions. With the increase of activated sludge addition ratio, the abundance of Pseudomonas generally showed an upward trend, reaching a high level at an algae-sludge ratio of 1:3. Bacteroidetes and Planctomycetes had relatively high abundance in groups with a moderate algae-bacterial ratio, while their abundance decreased significantly in pure algae or pure sludge groups. In different proportion groups, the abundance of cyanobacteria increased with the increase of Chlorella proportion, becoming a secondary dominant bacterial group in groups with a high algal content (such as groups A and E). The pure algae groups (such as A and E) or pure sludge group (I) showed a clear trend towards a homogeneous community structure, with high concentration of dominant bacterial groups and decreased species diversity. The relative abundance of Bacillota in the mixed groups was significantly higher than that in the mono-algae groups. The community structure in group M (Chlorella: Scenedesmus: activated sludge dry weight ratio of 1:1:6) was more balanced, with a reasonable distribution of dominant bacterial groups and potential for multifunctional synergy.

[0044] 2.4.2 Genus-level Microbial Community Structure The genus-level microbial community structure is shown in Figure 5. Analysis shows that in the Chlorella algae-bacterial symbiotic system, the abundance of Cyanobacteria-related genera (such as Unclassified Cyanobacteria) was high in the pure Chlorella group without sludge. After the addition of activated sludge, the abundance of Gram-negative bacteria genera (such as Pseudomonas and Bacillus) and Proteobacteria-related genera (such as Unclassified Proteobacteria) gradually increased in the Chlorella algae-bacterial symbiotic system (groups B, C, and D), especially in group D (high sludge concentration).

[0045] In the *Scenedesmus* algae-bacterial symbiotic system, certain unclassified cyanobacteria were dominant in the pure *Scenedesmus* group E (without sludge). The abundance of *Exiguobacterium* and *Paracossus* was significantly increased in the algae-bacterial symbiotic systems (groups F, G, and H), especially in group H. Compared to the *Scenedesmus* group, the *Chlorella* group showed a higher abundance of *Rubirtepida* at the same sludge concentration. With the activated sludge concentration fixed at 150 mg in all mixed algae groups, the microbial community structure varied with changes in the ratio of *Chlorella* to *Scenedesmus*.

[0046] 2.4.3 Functional Gene Prediction and Classification Based on COG Database: COG prediction of microbial community metagenomic functions based on 16S rRNA gene sequences revealed the functional potential profile of communities under different treatments from a functional genomics perspective. Figure 6 shows the results, demonstrating high functional redundancy and targeted niche adaptation strategies. In the pure algae groups (A, E) and the optimized experimental groups with a high proportion of single algae (K, O), the energy production and conversion (C-type) function was relatively abundant, which is related to the active photosynthetic autotrophic energy metabolism pathway dominated by algae. In the groups with added activated sludge, all groups showed high levels of carbohydrate (G-type) and lipid (I-type) transport and metabolism functions, which co-occurred with translation, ribosome structure and biosynthesis (J-type) and replication, recombination and repair (L-type) functions, especially in the C, D, G, and H groups with a high proportion of sludge. Amino acid transport and metabolism (Type E) functions were present in high proportions across all groups, particularly in groups with a high proportion of sludge (C, D, G, H) and the mixed algae-bacteria groups (J, M). Inorganic ion transport and metabolism (Type P) functions were more abundant in the activated sludge groups, while their abundance was lower in the pure algae groups (A, E). Type P functions were relatively more abundant in groups with a high proportion of activated sludge (e.g., D, H) and the mixed algae-bacteria groups (J, M). Furthermore, cell cycle regulation (Type D) and cell wall / membrane biosynthesis (Type M) functions were also enhanced in the high sludge groups, demonstrating higher microbial growth activity.

[0047] 2.4.4 FAPROTAX Functional Prediction The FAPROTAX functional prediction results are shown in Figure 7. Carbon removal mainly depends on the system's ability to decompose and transform organic matter. Functions related to organic carbon degradation, such as "reductive acetogenesis," "fermentation," and "urea hydrolysis," generally showed high abundance in the activated sludge group (Group I) and the algae-bacteria symbiotic group containing activated sludge. These functions showed extremely low abundance in the pure algae system. With the addition of activated sludge, the abundance of fermentation function in each group significantly increased. The pure activated sludge group showed extremely high abundance of functional genes in both "nitrification" and "denitrification" pathways, indicating that activated sludge has strong traditional biological nitrogen removal potential. In the Chlorella system (Group AD), with the increase of sludge dosage, the abundance of "reductive acetogenesis" and "nitrate reduction" functions gradually increased, but the abundance of "manganese oxidation" function in Group AC was lower than that in Group I. A similar trend was observed in the Scenedesmus system (Group EH).

[0048] The mixed algae symbiotic system exhibited unique advantages. It showed significantly higher abundance in nitrogen fixation, nitrite respiration, and chloroplasts than most other groups. Group J maintained a high activity level in nitrate respiration similar to that of high sludge volume groups (such as groups D and H), while its nitrification function was also maintained at a certain level.

[0049] The algae-bacterial inoculation ratio significantly modulated the treatment efficiency of the symbiotic system in removing freshwater effluent. When Chlorella:Scenedesmus:activated sludge = 1:1:6, the algae-bacterial symbiotic system exhibited optimal purification performance: ammonia nitrogen removal reached 100% within 12 hours, and nitrate nitrogen, nitrite nitrogen, and total nitrogen were nearly completely removed within 72 hours. Its overall denitrification effect was significantly better than the control groups and other algae-bacterial ratio systems. Microbial community structure analysis revealed that algal species dominated the construction of the "algal intermicrobial community"; compared with single algae or single-bacterial systems, the algae-bacterial symbiotic system significantly enriched bacteria with denitrification functions, such as Pseudomonas and Bacillus. Functional prediction analysis further showed that the mixed algae system enhanced related metabolic functions such as ammonia oxidation and nitrate reduction, forming a more diverse and functionally complex microbial community, thereby supporting the system to achieve more efficient, complete, and stable pollutant removal performance. This invention provides a theoretical basis and data support for optimizing the inoculation strategy of ABSS in aquaculture effluent treatment.

[0050] Example 2: Enhanced Algal-Bacterial Symbiotic System Based on C8 and C14 Quorum Sensing Signaling Molecules 1. Experimental Methods Three cylindrical reactors with an effective volume of 2L were used: C8 group [1 ppm of C8-HSL (octanoyl-L-homoserine lactone) added daily], C14 group [1 ppm of C14-HSL (tetradecanoyl-L-homoserine lactone) added daily], and control group, with 3 replicates for each group.

[0051] Chlorella, Scenedesmus, and activated sludge were inoculated into the reactor according to the optimal algae-sludge ratio (dry weight ratio 1:1:6) selected in Example 1.

[0052] The reactor was a continuous flow reactor with a hydraulic retention time (HRT) of 24 h. The influent concentrations were 5 mg / L ammonia nitrogen, 20 mg / L nitrate nitrogen, and 2 mg / L total phosphorus, with a C / N ratio of 5. During the initial acclimatization phase, no water exchange was performed. Acclimatization was considered complete when all water quality indicators within the reactor approached 0 mg / L, marking the start of the stable phase and continuous flow water exchange. Water samples were collected daily for purification testing. After the experiment, bottom algae and bacteria particles were collected for metagenomic sequencing.

[0053] 2. Testing Indicators (1) Water Purification Efficiency: Monitoring NH4 in influent and effluent + -N, NO2 - -N, NO3 - -N and TP concentrations were used to calculate nitrogen and phosphorus removal efficiency.

[0054] (2) Sludge characteristics: extracellular polymeric substances (EPS) content (protein PN, polysaccharide PS) and PN / PS ratio.

[0055] (3) Microbial Analysis: Microorganisms collected after the experiment were subjected to metagenomic sequencing (KEGG annotation). The microbial sequencing work was completed by Majorbio Biopharmaceutical Technology Co., Ltd. (Shanghai, China). The basic sequencing process included sample DNA extraction, PE library construction, bridge PCR, and sequencing. Metagenomic analysis was completed on the Meiji Bio Cloud Platform, mainly to analyze the microbial community structure, nitrogen metabolism and amino acid metabolism, and changes in QS-related genes and pathways, and to analyze the effects of adding different HSLs on the microbial community structure.

[0056] 3. Results and Analysis 3.1 Water Purification Efficiency The ammonia nitrogen removal efficiency is shown in Figure 8A. The ammonia nitrogen removal rate in the treatment groups was significantly higher than that in the control group. In group C8, the ammonia nitrogen removal rate decreased from 5.94 mg / L to 0.52 mg / L (removal rate 91.2%), and in group C14, it decreased from 4.92 mg / L to 0.47 mg / L (removal rate 90.4%), while in the control group, it only decreased from 6.57 mg / L to 0.76 mg / L (removal rate 88.4%). In terms of ammonia nitrogen removal, group C14 was slightly better than group C8.

[0057] The nitrate nitrogen removal efficiency is shown in Figure 8B. All groups achieved near-complete nitrate nitrogen removal, with the treatment groups showing a slightly higher nitrate nitrogen removal rate than the control group. The treatment groups entered the stable removal phase 7 days earlier than the control group. The overall removal trend was consistent across the treatment groups, with group C14 showing a slightly higher removal efficiency than group C8.

[0058] The nitrite removal efficiency is shown in Figure 8C. The overall concentration in the control group fluctuated significantly, with nitrite increasing from 0.103 mg / L to 0.287 mg / L. In contrast, the overall concentration fluctuation in the treatment group was smaller. The treatment group (C8 / C14) completely decreased to 0 mg / L from 0.080 / 0.059 mg / L on day 1, with a nitrite accumulation rate of 0%.

[0059] The total nitrogen removal efficiency is shown in Figure 8D. In group C8, the total nitrogen decreased from 27.20 mg / L to 0.52 mg / L (removal rate 98.1%), in group C14 from 26.84 mg / L to 0.58 mg / L (removal rate 97.8%), and in the control group from 25.94 mg / L to 0.79 mg / L (removal rate 97.0%). The difference in removal rate between group C8 and group C14 was only 0.3%; on day 40, the residual total nitrogen concentration in the treated groups was 30.4% lower than that in the control group (0.55 / 0.79 mg / L).

[0060] The total phosphorus removal efficiency is shown in Figure 8E. From day 1 to day 40, the total phosphorus concentration in group C8 decreased from 2.51 mg / L to 0 mg / L, and in group C14 it decreased from 2.13 mg / L to 0 mg / L, both achieving 100% complete removal. The control group decreased from 2.62 mg / L to 0.62 mg / L, with a removal rate of 76.3%, and significant residues were observed in the control group.

[0061] 3.2 Microbial Metagenomic Analysis 3.2.1 Phylogenetic Results Based on bar chart analysis of phylum-level community composition, the significant impact of adding signaling molecules with different acyl chain lengths on the macroscopic structure of the algal-microbe symbiotic system was revealed, as shown in Figure 9. The core microbial flora of each group was dominated by Pseudomonadota, Actinomycetota, and Bacteroidota. The addition of exogenous signaling molecules altered the relative proportions of the core phyla and community diversity. Compared to group C14, the relative abundance of Actinomycetota increased in group C8, while the abundance of Pseudomonadota decreased accordingly. Simultaneously, the abundance of secondary dominant phyla such as Bacillota and Chloroflexota also slightly increased in group C8. In contrast, group C14 exhibited a distinctly different community structure. Compared with the control group, the relative abundance of Pseudomonadota, Planctomycetota, Bacteroidota, and Bdellovibrionota was further increased in group C14, with Pseudomonadota becoming the dominant phylum. The abundance of Actinomycetota, however, was relatively decreased. Furthermore, the relative abundance of several rare phyla, including Verrucomicrobiota and Myxococcota, was significantly reduced in group C14. Compared with the control group, the relative abundance of Actinomycetota and Chloroflexota was lower in both treatment groups.

[0062] 3.2.2 Community-level results: Based on metagenomic data, the microbial community structure of the algae-microbe symbiotic system was reshaped by adding different signaling molecules, as shown in Figure 10. Brevundimonas, Hyphomonas, and Pirellula were abundant in all samples. Compared to the control group, the abundance of Flavihumibacter, Acetoanaerobium, Magnetospirillum, and Leptonema was higher in both treatment groups, while the abundance of Truepera, Microbacterium, Chryseobacterium, and Dietzia was lower in the treatment groups.

[0063] The abundance of *Sandaracinus*, *Flavihumibacter*, and *Reyranella* (a member of the Proteobacteria phylum) was higher in group C8 than in the control group. Compared with group C14, the abundance of *Rhizobium*, *Pirellula*, *Magnetospirillum*, *Comamonas*, and *Agrobacterium* was lower in group C8 than in group C14, while the abundance of *Prosthecobacter*, *Leptonema*, *Microcella*, and *Pseudoxanthomonas* was higher in group C8 than in group C14.

[0064] 3.2.3 Species-Level Analysis of Functional Differences At the species level, the Kruskak-Wallis rank-sum test (P=0.05) was used to analyze the significant differences in the relative abundance of species and functions among the groups, and FDR was used for multiple test correction. The results are shown in Figure 11. In group C8, the relative abundance of *Hyphomonas* was 4.1% higher than in group C14 and 5.8% higher than in the control group; the relative abundance of *Flavihumibacter* was 1.01% higher than in group C14 and 1.2% higher than in the control group. In group C14, the relative abundance of *Brevundimonas* was 3.8% higher than in group C8 and 1.4% higher than in the control group; the relative abundance of *Pirellula* was 2.9% higher than in group C8 and 1.2% higher than in the control group; and the relative abundance of *Rhizobium* was 2.3% higher than in group C8.

[0065] 3.2.4 Effects of Adding Different Signaling Molecules on Nitrogen Metabolism Pathways As shown in Figure 12, metagenomic predictions based on KEGG nitrogen metabolism (ko00910) related genes revealed nitrogen transformation pathways in the mixed algae-bacteria symbiotic system, including heterotrophic nitrate reduction (NapA / B (EC 1.9.6.1), NriBD (EC 1.7.1.15), NrfAH (EC 1.7.2.2)), assimilated nitrate reduction (Narb (EC 1.7.7.2), NR (EC 1.7.1.1, EC 1.7.1.2, EC 1.7.1.3), NIT-6 (EC 1.7.1.4), NirA (EC 1.7.7.1), NasBDE (EC 1.7.1.4)), and denitrification (NapA / B (EC 1.9.6.1), Nirk (EC 1.7.2.1), Nirs (EC 1.7.1.4)). There are a total of 5 nitrogen transformation pathways: nitrogen fixation (NifDKH (EC 1.18.6.1), AnfG (EC 1.18.6.1)) and anaerobic ammonia oxidation (Nirk (EC 1.7.2.1), Nirs (EC 1.7.2.1), Hzs (EC 1.7.2.7)). As shown in the nitrogen metabolism gene relative abundance heatmap in Figure 13, the relative abundance of glutamate dehydrogenase (EC 1.4.1.4), nitrite reductase (EC 1.7.2.2), glutamine synthase (EC 6.3.1.2), and nitrate reductase (EC 1.7.7.2) in group C8 was higher than that in group C14 and the control group. In contrast, the relative abundance of glutamate synthase (EC 1.4.1.14), hydroxylamine reductase (EC 1.7.99.1), carbonic acid acylase (EC 4.2.1.1), glutamate dehydrogenase [NAD(P+)] (EC 1.4.1.3), nitrase (EC 3.5.5.1), and nitric oxide reductase (EC 1.7.1.14) in group C14 was higher than that in group C8 and the control group. In the control group, the relative abundance of assimilatory nitrite reductase (EC 1.7.1.4), nitrous oxide reductase (EC 1.7.2.4), and nitrate reductase A (EC 1.7.5.1) was higher than that in the two treatment groups.

[0066] 3.2.5 The effect of adding different signaling molecules on cell membrane formation is shown in Figure 14. Based on metagenomic analysis of KEGG and cell membrane formation (ko02025) related metabolic pathways, four pathways related to the formation of biofilms from free state of bacteria in the algae-bacterial symbiotic system were found after the addition of signaling molecules. The cAMP / Vfr signaling pathway is regulated by the chemosensory system (Pij (motor protein), Pili (motor protein), chpa (chemosensory villous system protein), and chpc (fimbriae chemosensory system protein) to regulate the expression of PiIH (bacterial motor protein) and PiIG (two-component system response regulator). PiIH and PiIG further regulate Cyab (adenylate cyclase), CpdA (3',5'-cyclic AMP phosphodiesterase), and cAMP (cyclic adenosine monophosphate). Finally, it regulates the flagellar assembly system (FleQ (flagellate regulatory protein)), type III secretion system (AraC family transcriptional regulatory protein), type IV villous system (T4P), and type II secretion system by controlling the expression of Vfr (CRP / FNR family transcriptional regulator).

[0067] QS quorum sensing comprises the PQS system, the RhI system, and the Las system. The PQS system primarily consists of Phna (anthracycline synthase component I), Phnb (anthracycline synthase component II), Pqse (2-aminobenzoylacetyl-CoA thioesterase), and Pqsh (2-heptayl-3-hydroxy-4(1H)-quinolone synthase). The RhI system regulates C4-HSL secretion via RHII (acylisochromolactone synthase). The Las system controls the synthesis of 3-Oxo-C12-HSL by Lasl (acylisochromolactone synthase), further controlling the function of LasR (family transcription regulator), a regulator of the quorum sensing system, thereby controlling bacterial quorum movement and twitching. LasR is also regulated by Vfr in the cAMP / Vfr signaling pathway.

[0068] The Gac / Rsm pathway is primarily regulated by two networks that control sRNA expression. RsmA (carbon storage regulator) controls the secretion of HSI-I (serine), further regulating the function of the type VI secretion system. RsmA is regulated by the Las system from the quorum sensing system. One part of the regulatory network involves enzymes and proteins, including three sensor histidine kinases (Sags, PA1611, PA1976), Hptb (histidine phosphotransferase), HSbr (HptB-dependent secretion and biomembrane response regulator), HSbA (biomembrane anti-oxidation factor), flgM (negative regulator of flagellin synthesis), and flia (RNA polymerase σ factor). The other part mainly includes two sensor histidine kinases (Lads, Rets), Gacs (NarL family), and Gaca (invasion response regulator).

[0069] The c-dI-GMP (second messenger molecule) signaling pathway primarily controls WspA (methyl acceptor chemokine), WspB / D (chemotaxis-associated proteins), and WspE (response regulators) downregulates WspF (chemotactic family) through the bacterial surface post-contact pathway. Within the c-dI-GMP signaling pathway, c-dI-GMP is regulated by GTP (signal transduction protein), which in turn regulates pGpG (phosphatidylglycerol) by controlling Bifa (second messenger phosphodiesterase). c-dI-GMP is further regulated by six guanosine cyclases: WspR, Sadc, SiaD, TpbB, RoeA, and Mucr, which in turn regulate functions such as PSL, Pel polysaccharide biosynthesis, Alg44 (mannitone synthase), alginate biosynthesis, type IV villi (T4P), and goblet hyphae biosynthesis within the pathway.

[0070] Figure 15 shows a heatmap of the relative abundance of genes in the cell membrane pathway. Compared with the control group, the relative abundance of 15 genes in group C8 was upregulated. Among them, the main functions involved include flagellin synthesis regulator K02398, response regulators K02657 and K02658, chemosensory trichophyton system protein K06598, sensor histidine kinases K13061 and K13490, response regulator K13491, 2-heptayl-3-hydroxy-4(1H)-quinolone synthase K17940, glycosyltransferase K18101, polysaccharide biosynthesis protein K21006, diguanylate cyclase K21021, and putative membrane domain protein K21023 involved in signal transduction. Compared with the control group, the C14 group showed an upregulation of the relative abundance of 20 genes, including those involved in major functions such as chemosensory villonyl system protein K06596, invasion response regulator K07689, quorum sensing system regulator K18304, glycosyltransferase K12990, acyl isochrome lactone synthase K13060, alginate biosynthesis protein K19291, thioesterase K20257, sensor histidine kinase K20971, histidine kinase K20974, and GGDEF domain-containing protein K21022. Compared with the control group, the treatment group showed a downregulation of the relative abundance of 8 genes, such as flagellar regulatory protein K10941 and serine protein kinase K11912.

[0071] The experimental results above demonstrate that this invention, through a systematic investigation of the regulatory effects of exogenously added QS signaling molecules (C8-HSL and C14-HSL) of different chain lengths on the water purification efficiency, microbial community structure, and functional pathways of an algae-bacterial symbiotic system, yields the following conclusions: In terms of water purification, the addition of both C8-HSL and C14-HSL significantly improves the system's removal efficiency for nitrogen and phosphorus pollutants. Both signaling molecules achieve complete removal of total phosphorus (100%), and the treatment group reaches the stable removal stage 7 days earlier than the control group. The chain length specificity of the signaling molecules significantly affects the composition and functional differentiation of the bacterial community. C14-HSL significantly enriches bacteria related to biofilm formation and denitrification, such as Proteobacteria and Planctomycetes, while C8-HSL tends to promote the growth of free bacteria such as Actinobacteria and Firmicutes, enhancing the system's organic matter degradation capacity. At the genus level, the abundance of biofilm-associated bacteria such as *Shortwave Monota* and *Rhizobium* was significantly increased in group C14, further enhancing its nitrogen removal function. At the functional gene regulation level, C8-HSL guided nitrogen flow towards biomass synthesis by upregulating the expression of genes such as assimilatory nitrate reductase (e.g., EC1.7.2.2) and glutamine synthase (EC6.3.1.2); while C14-HSL enriched key enzymes in the denitrification pathway (e.g., nitric oxide reductase EC1.7.1.14) and genes related to anaerobic ammonia oxidation, promoting gas-phase nitrogen removal.

[0072] In summary, QS signaling molecules achieve differentiated enhancement of water purification efficiency in algae-bacteria symbiotic systems by precisely regulating microbial community building, metabolic pathways, and collective behavior. This invention provides a theoretical basis for optimizing microbial community function in wastewater treatment through the targeted addition of signaling molecules and also offers a new strategy for developing intelligent and controllable wastewater treatment technologies.

[0073] Example 3: Application of Algae-Bacteria Symbiotic System in Removing Commonly Used Antibiotics in Aquaculture Production 1. Experimental Methods Three cylindrical reactors with an effective volume of 2L were used: neomycin sulfate group (1 ppm neomycin sulfate stock solution was added daily), enrofloxacin group (7 ppm enrofloxacin stock solution was added daily), sulfadiazine group (5 ppm sulfadiazine stock solution was added daily), and control group, with 3 replicates for each group.

[0074] Chlorella, Scenedesmus, and activated sludge were inoculated into the reactor according to the optimal algae-sludge ratio (dry weight ratio 1:1:6) selected in Example 1.

[0075] The reactor was a continuous flow reactor with a hydraulic retention time (HRT) of 24 h. The influent concentrations were 5 mg / L ammonia nitrogen, 15 mg / L nitrate nitrogen, 2 mg / L total phosphorus, and a C / N ratio of 5. Water samples were collected daily for water quality purification testing. After the experiment, bottom algae and bacteria particles were collected for metagenomic sequencing.

[0076] 2. Testing Indicators (1) Water Purification Efficiency: Monitoring NH4 in influent and effluent + -N, NO2 - -N, NO3 - -N and TP concentrations were used to calculate nitrogen and phosphorus removal efficiency.

[0077] (2) Changes in antibiotic concentration: Every 7 days, water samples were collected from the reactor to detect antibiotic concentration.

[0078] (3) Microbial analysis: metagenomic sequencing (KEGG annotation) was used to analyze changes in nitrogen metabolism, amino acid metabolism and QS-related genes and pathways, and to analyze the effects of adding different antibiotics on the microbial community structure.

[0079] 3. Results and Analysis 3.1 Water Purification Efficiency The ammonia nitrogen purification index is shown in Figure 16A. The sulfadiazine group achieved a 100% removal rate on day 12, reaching a stable period faster than other treatment groups. Compared to the sulfadiazine group, the enrofloxacin group showed greater fluctuations in ammonia nitrogen concentration during the middle of the experiment, increasing after day 15 and stabilizing after day 27. Compared to the control group, the neomycin sulfate group showed significant residual ammonia nitrogen concentration, with an overall removal rate of 75%–80%.

[0080] The changes in nitrate nitrogen concentration are shown in Figure 16B. The concentration fluctuation in the sulfadiazine group was more significant, with the nitrate nitrogen removal rate ranging from 66.6% to 73.4% in the later stages of the experiment. The removal rate in the enrofloxacin group gradually decreased, from an initial 98% to 66.4%. The nitrate nitrogen removal rate in the neomycin sulfate group was 83.3%, which was better than the other two treatment groups by 8% to 17%.

[0081] The changes in nitrite concentration are shown in Figure 16C. The nitrite concentration in the neomycin sulfate group remained stable, with a concentration below 0.5 mg / L throughout the entire experimental period. Compared with the control group, the sulfadiazine and enrofloxacin groups showed significant nitrite accumulation. In the sulfadiazine group, the rate of nitrite accumulation began to increase after day 15, and the overall nitrite concentration remained at 4–4.5 mg / L after day 18. In the enrofloxacin group, the nitrite concentration ranged from 3.8 to 4.3 mg / L after day 27.

[0082] The changes in total nitrogen concentration are shown in Figure 16D. The total nitrogen removal rate was 58% in the sulfadiazine group, 64% in the enrofloxacin group, and 81% in the neomycin sulfate group, which were significantly higher than the other two treatment groups by 17% to 23%. Compared with the control group, the total nitrogen removal rate of the neomycin sulfate group was 9% lower.

[0083] The changes in total phosphorus concentration are shown in E of Figure 16. Compared with the control group, there was no significant difference between the enrofloxacin group and the neomycin sulfate group, while the total phosphorus removal rate of the sulfadiazine group was 10% lower than that of other groups.

[0084] 3.2 Metagenomic-Based Microbial Community Phylogenetic Results Figure 17 shows the phylum-level results of the microbial community in the neomycin sulfate group. The microbial community structure in the neomycin sulfate group was constructed with Pseudomonadota as its core. The relative abundance of Chloroflexota, Bacteroidetes, Gemmatimonadota, Bacillota, and Cyanobacteriota was higher in the neomycin sulfate group than in other groups. The microbial community structure in the enrofloxacin group was similar to that in the neomycin sulfate group, also with Pseudomonadota as its core. However, the relative abundance of Pseudomonadota and Armatimonadota was significantly higher in the enrofloxacin group than in other groups. The relative abundance of Gemmatimonadota was the lowest in the treatment group, similar to that in the control group. Unlike the other two treatment groups, the sulfadiazine group had a core microbial structure centered on the phylum Actinomycetota, with a significantly higher relative abundance of Actinomycetota than the other groups, while the relative abundance of Pseudomonas was significantly lower than the other groups.

[0085] 3.3 Metagenomic-based genus-level results of microbial communities: Heatmap analysis was performed using the NR-origin annotation table of the origin-GENESET gene set in the NR species database. The genus-level results of the top 50 communities by total abundance at the taxonomic level for each group are shown in Figure 18. In the neomycin sulfate group, the relative abundance of *Gemmatimonas*, *Pirellula*, and *Candidatus_Flexicrinis* was higher than that of other groups. In the enrofloxacin group, the relative abundance of *Brevundimonas*, *Hyphomicrobium*, *Pseudomonas*, and *Bosea* was higher than that of other groups. In the sulfadiazine group, the relative abundance of *Rhodococcus* and *Paramicrosporidium* was significantly higher than that of other groups. In the control group, the relative abundance of Sphingopyxis, Caldilinea, Oligoflexus, and Gemmata was higher than that in the treatment group.

[0086] 3.4 Species and Functional Contribution Analysis At the genus level, the association between the top 10 species by relative abundance and the top 3 functions was analyzed using the NR species annotation table. The results are shown in Figure 19. The top three functions were metabolism, cellular processes and signal transduction, and information storage and processing. The distribution of the top 10 species in each function was basically consistent. In the neomycin sulfate group, other bacterial genera were mainly the core functional framework, and the relative abundance of Gemmatimonas, Pirellula, and Candidatus_Flexicrinis was significantly higher than in other groups. The relative abundance of Brevundimonas was higher than in the sulfadiazine group and the control group. Similar to the neomycin sulfate group, the relative abundance of other bacterial genera was highly correlated with function in the enrofloxacin group. The relative abundance of Brevundimonas and Hyphomicrobium was significantly higher in the enrofloxacin group than in other groups. The sulfadiazine group was dominated by Rhodococcus, with a significantly higher relative abundance of Rhodococcus than other groups. There were no significant differences in the relative abundance of rhizobia among the treatment groups. However, compared to the control group, the relative abundance of Caldilinea and Oligoflexus in the treatment groups was lower.

[0087] 3.5 CADR Resistance Gene Functional Annotation By comparing with the CADR database, the number of genes in the top 35 categories related to drug resistance in each group was statistically analyzed. The results are shown in Figure 20. The number of multidrug resistance genes (19,510) and aminoglycoside resistance genes (1,911) in the neomycin sulfate group was significantly higher than in other groups, while the number of functional genes related to amino acid metabolism, such as peptides (5,619), was 567 more than in the control group (5,052). The enrofloxacin group had 17,576 multidrug resistance genes, and 1,634 enrofloxacin-related resistance genes (fluoroquinolones), 180 more than the control group (1,454). The sulfadiazine group had fewer drug resistance genes (16,139) than the other two treatment groups, and 114 sulfadiazine-related resistance genes, 21 more than the control group (93). A number of tetracycline resistance genes were present in all groups, with the tetracycline resistance gene count in the neomycin sulfate group being significantly higher than that in other groups.

[0088] 3.6 Effects of different antibiotics on nitrogen metabolism pathways. As shown in Figures 21-22, metagenomic predictions based on KEGG nitrogen metabolism (ko00910) related genes revealed nitrogen transformation pathways in the mixed algae-bacteria symbiotic system, including heterotrophic nitrate reduction (NapA / B (EC 1.9.6.1), NriBD (EC 1.7.1.15), NrfAH (EC 1.7.2.2)), assimilated nitrate reduction (Narb (EC 1.7.7.2), NR (EC 1.7.1.1, EC 1.7.1.2, EC 1.7.1.3), NIT-6 (EC 1.7.1.4), NirA (EC 1.7.7.1), NasBDE (EC 1.7.1.4)), and nitrification (AmoCAB (EC 1.14.18.3), Hao (EC 1.14.18.3)). There are a total of 6 nitrogen transformation pathways, including nitrogen conversion (1.7.2.6), denitrification (NapA / B (EC1.9.6.1), Nirk (EC 1.7.2.1), Nirs (EC 1.7.2.1, EC 1.7.99.1), nitrogen fixation (NifDKH (EC1.18.6.1), AnfG (EC 1.18.6.1)), and anaerobic ammonia oxidation (Nirk (EC 1.7.2.1), Nirs (EC 1.7.2.1), Hzs (EC 1.7.2.7)). Among the nitrogen metabolism genes in each group, the relative abundance of nitrite monooxygenase EC 1.13.12.16, glutamate synthase EC 1.4.1.13, homologous dehydrogenase EC 1.1.1.3, EC 1.7.1.4, nitrite reductase EC 1.7.2.2, nitrite reductase EC 1.7.5.1, hydroxylamine reductase EC 1.7.99.1, 3-dehydroquinoline dehydratase EC 4.2.1.10, and glutamine synthase EC 6.3.1.2 was significantly higher in the neomycin sulfate group than in other groups. Conversely, the relative abundance of nitrogenase EC 1.18.6.1, glutamate dehydrogenase EC 1.4.1.2, glutamate dehydrogenase EC 1.4.1.4, hydroxylamine dehydrogenase EC 1.7.2.6, hydrazine synthase EC 1.7.2.7, and nitrate reductase EC 1.7.2.7 was significantly higher in the enrofloxacin group than in other groups. 1.9.6.1 was higher than other groups. In the sulfadiazine group, only the aminoacyl-phosphosynthase EC 6.3.4.16 was higher than other groups.

[0089] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. An algae-bacteria symbiotic system, characterized in that, The algae-bacteria symbiotic system includes Chlorella, Scenedesmus and activated sludge, wherein the initial inoculation dry weight ratio of Chlorella, Scenedesmus and activated sludge is 1:1:

6.

2. The algae-bacteria symbiotic system as described in claim 1, characterized in that, The activated sludge comes from aquaculture ponds.

3. A functionally enhanced algae-bacterial symbiotic system, characterized in that, Add octanoyl-L-homoserine lactone or tetradecanoyl-L-homoserine lactone exogenously to the algae-bacterial symbiosis system of claim 1 or 2.

4. The functionally enhanced algae-bacteria symbiotic system as described in claim 3, characterized in that, The concentration of the added octanoyl-L-homoserine lactone or tetradecanoyl-L-homoserine lactone is 1 ppm.

5. A method for treating aquaculture wastewater, characterized in that, The method includes the step of contacting the aquaculture wastewater with the algae-bacterial symbiotic system as described in claim 1 or 2, or the functionally enhanced algae-bacterial symbiotic system as described in claim 3 or 4, to purify the wastewater.

6. A method for treating aquaculture wastewater containing antibiotics, characterized in that, The method includes the step of contacting the algae-bacteria symbiotic system described in claim 1 or 2 with the effluent containing antibiotics to purify the effluent.

7. The method as described in claim 6, characterized in that, The antibiotics include at least one of neomycin sulfate, enrofloxacin, and sulfadiazine.

8. The application of the algae-bacteria symbiotic system as described in claim 1 or 2 in the treatment of aquaculture wastewater.

9. The application as described in claim 8, characterized in that, When using the algae-bacteria symbiotic system to treat aquaculture wastewater containing antibiotics, nitrogen and phosphorus pollutants in the wastewater can be removed while the spread of antibiotic-induced resistance genes can be inhibited; the antibiotics include at least one of neomycin sulfate, enrofloxacin, and sulfadiazine.

10. The application of the enhanced algae-bacteria symbiotic system as described in claim 3 or 4 in the treatment of aquaculture wastewater.

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