A two-stage biological contact oxidation reactor with an effective volume of ~6 L was set up in Figure 1, which is composed of two identical rectangular chambers (125 × 125 × 200 mm). The influent was pumped (BT101s, Lead Fluid, China) into the inlet and flowed to the outlet downward and upwardly through the overflow ports on both sides of the bottom in the middle baffle of the two chambers. The microporous aeration disc (LZB-3WB, Xiangjin, China) was fixed at the bottom of each chamber with dissolved oxygen (DO) of 3–4 mg/L. The acrylic zigzag circle frame with top and bottom inner diameters of 50 and 60 mm was suspended and fixed at 50–100 mm above the aeration disc in each chamber through its four serrations. Furthermore, the mixed polyethylene carrier (Teijin, Japan), which has a compact and porous fiber structure with a filling capacity yield of 3.5 g/L carriers, was wrapped around the zigzag circle frame to serve as a filter that absorbed the activated sludge and formed an efficient biofilm.

Seed sludge was gathered from the secondary sedimentation tank of the Wulongkou Municipal Wastewater Treatment Plant (MWTP). The original mixed liquor-suspended solids (MLSS) of the two chambers were maintained at ~4.0 g/L. After aerating for 3 days, the sludge was almost adsorbed onto the carrier surface, and the liquid was clarified. Afterward, the microorganisms were inhabited at a high density in the activated sludge, which is beneficial to forming a biofilm and realizing the selective distribution and natural differentiation of microorganisms in space and function through synergy and antagonism.

Initially, 0.05 g of standard SMZ was dissolved in a small amount of 50 mL of acetonitrile (HPLC grade) and then stored in amber-colored vials at −20°C. After the completion of biofilm incubation, the synthetic SMZ wastewater was prepared based on the previous study (Shi et al., 2018; Wan et al., 2018), with the main composition of CH₃COONa 1.15 g/L, NH₄Cl 0.34 g/L, K₂HPO₄ 0.10 g/L, and trace elements of 1 mL/L (1.50 g/L FeCl₃·6H₂O, 0.15 g/L H₃BO₃, 0.03 g/L CuSO₄·5H₂O, 0.12 g/L MnCl₄·H₂O, 0.06 g/L NaMoO₄·2H₂O, 0.12 g/L ZnSO₄·7H₂O, 0.15 g/L CoCl₂·6H₂O). It was pumped into the reactor continuously at room temperature (25–30°C) for 80 days. The flow rate of the peristaltic pump was 4.25 mL/min to maintain the hydraulic retention time (HRT) of 24 h. The operation process could be generally divided into three phases based on SMZ shocks in the influent, which gradually increased from 0.10 to 1 mg/L and 3 mg/L, according to previous studies (Yang et al., 2015; Li et al., 2019).

The influent and effluent samples were collected daily and centrifuged at 10,000 rpm for 10 min, and the supernatant was taken to determine COD, NH4+-N, and PO43− levels as previously described (Zhou et al., 2022). The DO and pH values were measured using a DO meter (YSI 550A, USA) and a pH meter (HQ30d, HACH, America). The supernatant samples were filtrated using a 0.22-μm filter membrane (PTFE) for SMZ quantification using an analytical liquid chromatograph (LC-2030C, Shimadzu, Japan), equipped with the SB-C18 chromatographic column (Agilent ZORBAX, 150 × 4.6 mm, 5 μm) at a detection wavelength of 270 nm, an injection volume of 20 μL, and a flow rate of 1 mL/min. A combination of two mobile stages was programmed with pure water (A) and acetonitrile (B), and the mobile stage elution gradient was 0–2 min 60% A, 2–4 min 70% A, and 4–6 min 75% A.

The seed sludge (CK) biofilm samples obtained from the carrier in the reactor at the end of stages 2 (Z1) and 3 (Z3) were used to extract the EPS using thermal extraction. First, 25 mL of the sludge mixture was centrifuged at 4,000 r/min for 5 min at 4°C to remove the supernatant. Then, the sludge was replenished to its original volume with PBS buffer (NaCl 8.5%, Na₂HPO₄ 2.2%, NaH₂PO₄ 0.4%, distilled water 100 mL, pH 7), heated to 70°C, mixed well, and centrifuged at 4,000 r/min for 10 min at 4°C to obtain the supernatant (LB-EPS). The supernatant was then supplemented with PBS buffer to its original volume and heated in a water bath at 70°C for 30 min. Then, it was centrifuged at 4,000 r/min for 15 min at 4°C to obtain the supernatant (TB-EPS). Afterward, solutions of LB-EPS and TB-EPS were filtered through a 0.45-μm membrane.

The protein (PN) and polysaccharide (PS) concentrations were determined using the Bradford method and the phenol-sulfuric acid method (Peng et al., 2022). The organic compositions and fluorescence characteristics in EPS were determined using three-dimensional excitation and emission matrix fluorescence (3D-EEM). The excitation wavelength (Ex) was scanned from 200 to 400 nm, and the emission wavelength (Em) was scanned from 300 to 500 nm, both in 5 nm increments (Zhang et al., 2022a).

The seed sludge (CK) and the biofilm sludge samples collected at the end of stages 2 (Z1) and 3 (Z3) were used for metagenomics analysis on an Illumina HiSeq 4000 platform (Majorbio, China). The raw reads were used to generate clean reads using fastp (Chen et al., 2018) on the Majorbio Cloud Platform (cloud.majorbio.com). A non-redundant gene catalog was constructed using CD-HIT (Fu et al., 2012). The species abundance was calculated from the sum of gene abundances corresponding to the species. Representative sequences from the non-redundant gene catalog were annotated by Blastp based on the NCBI NR database, using DIAMOND for taxonomic annotation with an e-value cutoff of 1e⁻⁵. Antibiotic resistance gene annotation was conducted using DIAMOND (Buchfink et al., 2015) against the CARD database with an e-value cutoff of 1e⁻⁵. Network analysis was used to explore the potential correlations between bacteria and ARGs based on Spearman's correlation coefficient > 0.6 (P < 0.05). The data were deposited into the NCBI Sequence Read Archive (SRA) database under accession number PRJNA838398.

The performance of the two-stage biological contact oxidation reactor for the treatment of SMZ wastewater is shown in Figure 2. The SMZ shocks in stages 1–2 barely influenced the performance of BCOR in COD removal (Figure 2A), and the average COD removal efficiency was 86.93 and 88.04%, respectively. However, the obvious fluctuation of COD removal efficiency appeared in stage 3, and it reduced to 66.39%, mainly attributed to the increasing SMZ stress. In addition, NH4+-N removal efficiency kept relatively stable at 83.87–90.03% when the SMZ concentration increased from 0.10 to 1 mg/L (Figure 2B), indicating that the nitrifying bacteria still had strong activity even under the increasing SMZ pressure. However, the NH4+-N removal efficiency illustrated a decreasing tendency when the SMZ concentration in the influent increased to 3 mg/L. The high SMZ concentration (3 mg/L) in the present research could impact the removal of organic matter and the process of ammonia oxidization.

Moreover, there was no significant difference in the effect of different SMZ concentrations on PO43− removal efficiency (Figure 2C), which always fluctuated around 42.12%. The pH of the effluent is higher than that of the influent (Figure 2D). It has been reported that pH affects phosphorus removal by the microbial community. With effluent pH exceeding 8, phosphorus precipitation tends to form in the system (Wang et al., 2022), affecting phosphorus utilization by microorganisms and reducing phosphorus removal efficiency. Overall, the two-stage biological contact oxidation reactor had a limited effect on the removal of PO43− during the SMZ wastewater treatment.

Afterward, SMZ was undetectable in the effluents during stage 1 (Figure 2E), indicating that activated sludge completely adsorbed or degraded the dosed SMZ. Afterward, the SMZ removal efficiency was above 90% in stage 2. In stage 3, the average removal efficiency of SMZ decreased to 39.36% with 3 mg/L SMZ added to the influent. The gradient concentrations of SMZ resulted in a significant reduction in the performance of the two-stage biological contact oxidation reactor during SMZ wastewater treatment.

Biofilms are complex structures composed of microorganisms, and EPS, as the main component of biofilms, is a key factor affecting the performance of reactors (Xiong et al., 2020). EPS content is strongly influenced by SMZ in Figure 3. The addition of SMZ to the influent inhibited the secretion of LB-EPS (Figure 3A), which was reduced from 73.53 mg/(g VSS) in CK to 42.04 mg/(g VSS) in Z3. On the contrary, the production of TB-EPS substantially increased after each SMZ shock to 44.33 mg/(g VSS) in Z1 and 53.79 mg/(g VSS) in Z3, respectively (Figure 3B), which was significantly higher than the 10.34 mg/(g VSS) in CK. It has been reported that EPS can resist antibiotic stress by the adsorption of antibiotics through the hydrophobic region and functional groups of PN (Fan et al., 2021). The pronounced increase in PN yield mainly contributed to the elevated TB-EPS production, reaching 41.97 mg/(g VSS) and 47.79 mg/(g VSS) in Z1 and Z3, respectively. Its production was promoted to protect microbial cells against SMZ shocks. In particular, SMZ is positively correlated with TB-EPS and TB-PN content and negatively correlated with LB-EPS content, while TB-EPS is also positively correlated with PN content (Figure 3).

The chemical composition of EPS was further investigated at different SMZ concentrations by the 3D-EEM fluorescence spectra in Figures 3D–F. The I-peak (250 nm < Ex < 400 nm, 200 nm < Em < 380 nm) was associated with aromatic protein-like substances, according to Zhu et al. (2022). The I-peak appeared at all SMZ concentrations, while its intensity significantly decreased with increasing SMZ concentrations. Compared to 0 mg/L SMZ, the location of the I-peak in TB-EPS was shifted by 20/20 nm and 25/25 nm along the excitation/emission scale at 1 and 3 mg/L SMZ, respectively. Additionally, the fluorescence shift further illustrated that SMZ could affect the chemical composition of EPS.

The impact of SMZ pressure on the microbial composition and distribution was investigated by the metagenomics sequencing technology in Figure 4. The bacterial community composition and abundance differed significantly with an increase in SMZ concentration, and the flora with poor environmental adaptability were gradually eliminated. At the phylum level, the abundance of Chloroflexi increased from 19.25% (CK) to 20.12% (Z1) and 41.75% (Z3) with an increase in SMZ concentration (Figure 4A). Moreover, the abundance of Proteobacteria reached 39.54% in Z1, while it decreased to 28.62% in Z3. In contrast, the abundance of Actinobacteria had an obvious decrease from 44.22% (CK) to 8% (Z3) under the selection pressure of SMZ in the environment.

At the genus level (Figure 4B), Candidatus_Microthrix and unclassified_c__Actinobacteria were the most prevalent genera in CK, accounting for 22.6% of all observed sequences. However, their abundances showed a downward trend and reduced to 0.5 and 1.9% in Z3, respectively, with the increased SMZ concentration, probably because the SMZ concentrations exceeded these bacteria' tolerance levels. In contrast, the abundances of unclassified_d__Bacteria, unclassified_c__Betaproteobacteria, unclassified_c__Anaerolineae, Candidatus_Promineofilum, and unclassified_p__Chloroflexi increased with the increased SMZ concentration, especially for Candidatus_Promineofilum, whose abundance increased from 1.4% in CK to 11.6% in Z3, indicating higher levels of adaptation for SMZ. Furthermore, the SMZ was significantly correlated with Candidatus_Promineofilum (P < 0.05), followed by unclassified_c__Anaerolineae, unclassified_c__Betaproteobacteria, and unclassified_f__Anaerolineaceae (P < 0.05) (Figure 4C). Meanwhile, the relative abundances of genera Candidatus_Promineofilum, unclassified_c__Betaproteobacteria, and unclassified_f__Anaerolineaceae exhibited an increasing trend in the SMZ wastewater treatment system (Figure 4B), further demonstrating their powerful tolerance to SMZ.

The presence of SMZ not only affects the microbial community but also leads to the development, migration, and transformation of diverse ARGs. Therefore, the correlation between the abundance of ARGs and the microbial community has been further explored in Figure 5. During the SMZ wastewater treatment system, the types of antibiotics with higher abundance in the sludge samples from CK, Z1, and Z3 were bacteriocins and sulfonamides. The abundance of sulfonamide antibiotics increased substantially from 12% (CK) to 31% (Z1) and 56% (Z3), respectively (Figure 5A). This phenomenon indicated that the SMZ concentration in the influent serves as a crucial factor for enriching its corresponding sulfonamide antibiotics. Among these ARGs (Figure 5B), bacA, sul1, and sul2 were the top three dominant genes across the three samples. sul1 and sul2 are the sulfonamide resistance genes, and their abundances increased with the increasing SMZ concentration, which enhanced the propagation and transformation of ARGs among bacteria. Afterward, AAN60217, ABG36700, and ACJ39691 associated with sul1, and YP_001969930 associated with sul2 also exhibited an increasing trend during the SMZ wastewater treatment (Figure 5C), further revealing that the selection pressure imposed by increased SMZ promoted the occurrence of these associated bacteria. The co-occurrence pattern of sul1, sul2, and microbial communities revealed that the 19 bacterial genera were speculated as possible hosts (Figure 5D). The microorganisms positively associated with sul1 and sul2 were mainly attributed to Chloroflexi and Proteobacteria, especially Candidatus_Promineofilum. It was not only strongly correlated with sul1 and sul2, but it was also the most enriched genus associated with the removal of SMZ in this system.

Antibiotics exert selective pressure on microbial communities and promote the emergence of ARGs. Sulfonamide antibiotics were dissipated and driven by microbes mainly through the initial ipso-hydroxylation (Chen et al., 2022). To analyze the factors that contribute to the mechanism of resistance of biota to SMZ, it is crucial to understand the mechanism of action of antibiotics. During the SMZ wastewater treatment system, the antibiotic target alteration was persistently prevalent in different SMZ concentrations (Figure 6A), which was considered a primary resistance mechanism for bacterial resistance to SMZ, among which the relative contribution of Candidatus_Promineofilum, unclassified_f__Anaerolineaceae, Hyphomicrobium, unclassified_c__Anaerolineae, and unclassified_p__Chloroflexi to this resistance mechanism gradually increased with the increased SMZ concentration (Figure 6B), indicating that the members of these genera could resist the adverse environment of SMZ pressure through antibiotic target alteration mechanisms (Figure 6C).