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Article

Biochar-Enhanced Nitrogen Removal in SBBR Under PFOA Stress: The Role of Quorum Sensing

by
Zhiqi Lu
,
Mengzhe Zhao
,
Xianglong He
and
Hongjing Li
*
Department of Environmental Science & Engineering, Fudan University, Shanghai 200433, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(8), 3359; https://doi.org/10.3390/su17083359
Submission received: 9 March 2025 / Revised: 31 March 2025 / Accepted: 7 April 2025 / Published: 9 April 2025
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Abstract

:
Perfluorooctanoic acid (PFOA), an emerging organic contaminant frequently detected in wastewater, inhibits biological nitrogen removal processes, posing challenges to sustainable wastewater treatment. Mitigating the adverse effects of PFOA while enhancing total nitrogen (TN) removal efficiency remains a critical concern. In this study, three sequencing batch biofilm reactors (SBBRs) were operated under low-oxygen conditions with a C/N ratio of 4.0 to investigate enhanced nitrogen removal under PFOA stress using biochar. Compared to the 78.1% TN removal efficiency in the control reactor (SBBR-0) with an initial TN concentration of 50 mg/L, the addition of PFOA decreased TN removal by 2.3% in SBBR-1, while the combined addition of PFOA and biochar increased it by 3.2% in SBBR-2. Biochar, acting through its electron-donating surface functional groups, mitigated PFOA-induced reactive oxygen species accumulation and increased adenosine triphosphate production. These effects promoted the generation of quorum sensing (QS) signaling molecules, facilitating microbial communication and cooperation. Consequently, the relative abundance of key nitrogen-removing bacteria, such as Thauera (from 7.90% to 9.92%) and Nitrosomonas (from 1.42% to 5.75%), increased, leading to enhanced nitrogen removal efficiency. A metagenomic analysis revealed that biochar significantly reduced the production of antibiotic resistance genes without promoting their dissemination. These findings provide new insights into mitigating the negative effects of PFOA and improving TN removal through QS promotion, offering a potential approach for enhancing the sustainability of wastewater treatment systems.

1. Introduction

Biological nitrogen removal is widely recognized as a cost-effective and environmentally sustainable strategy for eliminating ammonia nitrogen from wastewater [1,2]. However, conventional biological treatment methods exhibit several limitations, including relatively low nitrogen removal efficiency and high energy consumption [3,4]. As a result, complying with the stringent total nitrogen discharge limit (TN ≤ 10 mg/L) for treated effluent, as required in environmentally sensitive areas in China, has become increasingly challenging for urban wastewater treatment plants, especially under the influence of emerging organic contaminants in the influent [5,6].
Perfluorooctanoic acid (PFOA), an emerging organic contaminant, is extensively used in industrial and consumer products such as non-stick cookware, waterproof textiles, and firefighting foams [7]. Due to its widespread application, PFOA has been frequently observed in wastewater, particularly near industrial zones, landfills, wastewater treatment plants, and firefighter training facilities [8]. The persistence, bioaccumulation, and toxicity of PFOA have been shown to adversely affect the activated sludge process [9,10]. Studies have demonstrated that the toxicity of PFOA induces microorganisms to secrete excessive extracellular polymeric substances (EPSs), leading to the formation of a protective layer [11,12]. Long-term exposure to PFOA can alter microbial community structure; for instance, the decline in the relative abundance of Chloroflexi has been associated with reduced nitrogen removal efficiency [13]. Furthermore, PFOA suppresses key functional bacteria, such as nitrifying bacteria (Nitrospira) and denitrifying bacteria (Pseudomonas), thereby disrupting nitrogen transformation pathways and significantly decreasing TN removal efficiency in constructed wetlands [14]. In addition, in one study, the presence of PFOA in a sequencing batch reactor (SBR) was found to exert an inhibitory effect on TN removal efficiency. A microbial analysis revealed that PFOA altered the dominant and functional microbial communities in an aerobic granular sludge system [15]. Denitrifying bacteria can enhance their tolerance to PFOA toxicity by upregulating efflux-type and antibiotic-inactivating resistance genes, which in turn exacerbates the risk of antibiotic resistance gene (ARG) dissemination [16,17]. While the detrimental effects of PFOA on microbial processes and nitrogen cycling have been increasingly recognized, effective and sustainable strategies to mitigate its impacts remain underexplored. Addressing this gap is vital for maintaining the stability and ecological safety of biological wastewater treatment systems, particularly in the context of growing concerns over environmental pollution and public health risks.
Sequencing batch biofilm reactor (SBBRs), which integrate biofilm processes with traditional SBRs, have been employed for the treatment of nitrogen-containing wastewater [18,19,20]. Previous studies have demonstrated that SBBRs are capable of achieving effective TN removal under various operational conditions, with key processes such as aerobic nitrification and anoxic denitrification playing essential roles [21]. These processes rely on the activity of functional microbial communities, including ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and denitrifying bacteria [22,23,24]. However, most existing research has focused on optimizing nitrogen removal under conventional conditions with relatively high energy inputs, such as high dissolved oxygen (DO) levels or high C/N ratios [25,26]. In contrast, the microbial mechanisms of nitrogen removal in SBBRs under emerging contaminant stress—particularly PFOA—remain largely unexplored. Therefore, this study aims to investigate the impact of PFOA on nitrogen removal performance and microbial community structure in SBBRs.
Biochar, characterized by its large specific surface area, well-developed porosity, and abundant functional groups, represents a cost-effective and environmentally sustainable material for use as a biological carrier in wastewater treatment systems [27,28]. Previous studies have primarily focused on its role as a carbon-based adsorbent for nitrogen removal from wastewater [29,30]. The addition of biochar significantly enhanced TN removal efficiency, likely due to its electron transfer capabilities that accelerate key biological processes involved in nitrogen transformation [31]. Additionally, biochar has been shown to promote the secretion of EPS and increase the relative abundance of Anammox bacteria, thereby further supporting the nitrogen removal process [32]. However, studies investigating the role of biochar in mitigating the adverse effects of PFOA on nitrogen removal in SBBRs remain limited. Furthermore, the influence of biochar on microbial community composition and functional gene expression under PFOA stress in biological nitrogen removal systems is still not well understood.
Quorum sensing (QS) is a widely observed communication mechanism in microbial communities that enables microorganisms to regulate population-density-dependent behaviors through the secretion and detection of specific chemical signal molecules, such as N-acyl-homoserine lactones (AHLs) and autoinducing peptides [33]. The QS mechanism encompasses the synthesis, diffusion, and receptor binding of signaling molecules, ultimately initiating collective behaviors such as biofilm formation [34,35,36]. QS systems are highly conserved in both Gram-negative bacteria (e.g., Pseudomonas) and Gram-positive bacteria (e.g., Bacillus) and play a critical role in coordinating carbon and nitrogen metabolism among environmental microorganisms [37]. In nitrogen removal processes, QS has been shown to modulate the activity of key enzymes, including nitrate reductase (Nar) and nitrite reductase (Nir), thereby enhancing electron transfer efficiency during denitrification [38]. Among various QS signals, AHLs represent the most extensively characterized molecules in Gram-negative bacteria, where they regulate gene expression and facilitate interspecies and intraspecies interactions, contributing significantly to the stability and performance of nitrogen removal systems [39,40]. Recent advances have explored the exogenous application of QS signaling compounds as a means of enhancing microbial functionality and pollutant degradation in engineered ecosystems [41,42,43]. Nevertheless, whether QS mechanisms play a critical role in the adaptation of nitrogen-removing microorganisms to PFOA stress remains unclear and warrants further investigation.
This study aims to elucidate the role of biochar in enhancing nitrogen removal under PFOA stress in SBBR, with the goal of meeting stringent discharge standards under low-energy operational conditions. Nitrogen removal performance in the presence of PFOA was evaluated under low energy consumption conditions. In addition, microbial mechanisms underlying nitrogen transformation, with particular emphasis on QS pathways, were investigated using metabolic and metagenomic analyses. Finally, the effect of biochar on mitigating the adverse impacts of PFOA in SBBRs was assessed, contributing to the development of more robust and sustainable biological nitrogen removal systems.

2. Materials and Methods

2.1. Reactor Operation and Synthetic Wastewater Composition

Three lab-scale SBBRs (2 L) were inoculated with sludge obtained from the secondary sedimentation tank of a municipal wastewater treatment plant in Shanghai, China. Resin fillers (diameter: 1.5 cm) were introduced into all SBBRs as fixed biofilm carriers to enhance microbial attachment and biofilm development, maintaining a filling ratio of approximately 0.5. These fillers remained in the reactors throughout the operation period. A schematic of the reactor configuration and filler placement is provided in Figure S1. SBBR-0 (without biochar or PFOA) served as the control, while SBBR-1 was operated with PFOA but without biochar, and SBBR-2 contained both biochar and PFOA. In SBBR-2, three packages of coconut shell biochar (5 g/L each) were suspended in the reactor. The influent C/N ratio was set to 4.0, with a COD concentration of 200 mg/L and a TN concentration of 50 mg/L (within the typical range of influent TN concentrations reported in full-scale wastewater treatment plants [44,45]). All SBBRs were kept at 21 ± 1 °C and operated in 8 h cycles under anoxic/low-oxygen conditions. Each cycle consisted of 4 h of anoxic operation (DO ≈ 0 mg/L) to promote denitrification using nitrate as the terminal electron acceptor, followed by 2 h under low-oxygen conditions (DO maintained at 0.5–1.0 mg/L) to facilitate simultaneous nitrification and denitrification. The cycle continued with 1 h of settling, 10 min for decanting, and a 50 min idle period. During the low-oxygen phase, air was introduced at a low flow rate to maintain the desired DO level. After settling, 1.0 L of supernatant was withdrawn from each reactor. Sludge properties such as biofilm dry weight and thickness in the three SBBRs are presented in Table S1. The synthetic wastewater used in this study contained 0.339 g/L sodium succinate as the carbon source (equivalent to 200 mg/L COD) and 0.191 g/L NH4Cl as the nitrogen source (equivalent to 50 mg/L NH4+-N), along with trace nutrients and minerals essential for microbial growth (detailed in Table S2) [46]. PFOA (C8HF15O2) was added to the synthetic wastewater at a concentration of 20 μg/L, which falls within the commonly reported concentration range [47,48].

2.2. Analytical Methods

2.2.1. Wastewater Quality Analysis

NH4+-N, NO3−-N, NO2−-N, TN, COD, MLSS, and MLVSS were measured according to standard procedures outlined in Standard Methods [49]. The concentrations of poly- and perfluoroalkyl substances (PFASs) were determined using liquid chromatography–tandem mass spectrometry (LC-MS/MS; Triple Quad™ 5500+, SCIEX, Framingham, MA, USA) equipped with a Poroshell 120 EC-C18 column (50 × 2.1 mm, 2.7 µm particle size; Agilent, Santa Clar, CA, USA). Detailed LC-MS/MS operating conditions are provided in Tables S7–S9.

2.2.2. Extraction and Determination of AHLs

AHLs were extracted using the solid-phase extraction (SPE) procedure, as previously described [50]. Mixed liquor samples collected from the SBBRs were first centrifuged at 10,000 rpm for 10 min. A 50 mL aliquot of the supernatant was then filtered through a GF/B glass fiber membrane (47 mm, Whatman, Leeds, UK). The resulting filtrate was subjected to SPE using a hydrophilic–lipophilic balance cartridge (HLB, 6 cm3/200 mg, JIEDAO, Taizhou, China), which had been preconditioned with 6 mL of methanol followed by 6 mL of acidified ultrapure water (pH 2.5). The sample was loaded onto the cartridge at a flow rate of 1 mL/min over 50 min. Subsequently, the cartridge was washed with 6 mL of acidified ultrapure water and dried under a gentle stream of N2 for 1 min. Retained compounds were eluted with 5 mL of methanol. The eluate was evaporated to dryness under a N2 stream, reconstituted to less than 1 mL, and then diluted to a final volume of 1 mL with methanol for LC-MS/MS analysis [51,52].
SPE extracts were analyzed by an advanced LC/TQ system (Agilent Technologies, USA). The mass spectrometer employed was the Triple Quadrupole MS equipped with Agilent Jet Stream Technology (Model G6470A). Detailed LC–MS/MS operating conditions are provided in Tables S4–S6. The AHLs (>97%) quantified in this study included N-butyryl-DL-homoserine lactone (C4-HSL), N-octanoyl-DL-homoserine lactone (C8-HSL), and N-decanoyl-DL-homoserine lactone (C10-HSL) (Aladdin, Shanghai, China); N-hexanoyl-DL-homo-serine lactone (C6-HSL), N-(3-Oxohexanoyl-DL-homoserine lactone (3OC6-HSL), and N-dodecanoyl-DL-homoserine lactone (C12-HSL) (MCE, Shanghai, China); and N-tetradecanoyl-DL-homoserine lactone (C14-HSL) (Macklin, Shanghai, China). Their CAS numbers, abbreviations, molecular weights, and molecular formulas are listed in Table S3.

2.2.3. Morphology and Spectroscopy Analysis of Biochar and Metabolic Analysis

The raw biochar and the used biochar samples from the SBBR were characterized using Fourier Transform Infrared Spectroscopy (FTIR), X-ray Photoelectron Spectroscopy (XPS), and Scanning Electron Microscopy (SEM). To assess the biomass attached to the biochar, Excitation–Emission Matrix (EEM) Fluorescence Spectroscopy was employed. Biochar samples were collected and resuspended in a phosphate buffer solution (pH 7.0) followed by incubation in a water bath at 80 °C for 30 min. The suspension was then centrifuged at 6000 rpm for 15 min, and the supernatant was collected for EEM analysis. The scanning range was set with excitation and emission wavelengths from 220 to 500 nm, with a 2 nm increment. The fluorescence regional integration method was used to analyze the major biomass components based on the EEM spectra [53]. Five distinct fluorescence regions were identified using consistent excitation and emission boundaries (Figure S2). Quantification of intracellular reactive oxygen species (ROS) and adenosine triphosphate (ATP) was conducted using ELISA reagent kits (MLBIO, Shanghai, China).

2.2.4. Batch Experiments

To evaluate the contribution of AHLs to TN removal, batch experiments were conducted using sludge collected from the three SBBRs. The experimental procedure was as follows: At the end of the reaction cycle, 140 mL of mixed liquor was sampled from each reactor and centrifuged to separate the sludge. The recovered sludge was evenly divided into seven portions, with each portion resuspended in 20 mL of culture medium containing different types of AHLs. The experimental setup included one control group (without AHL addition) and six experimental groups, each supplemented with a specific type of AHL at a concentration of 100 ng/L. The mixtures were transferred into 50 mL Erlenmeyer flasks and incubated on a shaker at room temperature for 8 h. After incubation, water samples were collected for analysis, and the changes in TN removal efficiency were calculated.

2.2.5. Metagenomic Analysis

DNA samples was extracted using the E.Z.N.A.Soil DNA Kit (Omega, M5635-02, San Francisco, CA, USA) and sequenced on the Illumina Miseq platform by Sangon Biotech Co., Ltd. (Shanghai, China). After assembly of the clean reads, gene sets were aligned against NCBI, the Kyoto Encyclopedia of Genes and Genomes (KEGG), and other databases to obtain species annotation information and functional annotation information of genes using DIAMOND (version 0.8.20), with screening parameters set at an E-value < 1 × 10−5 and a Score > 60. QS regulatory genes (e.g., luxR) associated with AHL synthesis, as well as nitrogen-cycle-related functional genes (nirS, nxrB, amoA, hao, nosZ, etc.), were identified through the KEGG annotation results [54].
For the qualitative and quantitative analysis of ARGs, UBLAST was employed to screen potential ARG sequences and 16S rRNA sequences from the dataset using the following thresholds: E-value < 1 × 10−7 and sequence identity ≥ 80%. Two sequence classification methods (similarity search and keyword search) were applied to identify ARGs, and redundant sequences were removed by merging with the SARG database [55]. To address differences in sequencing depth across samples, normalization procedures were applied. ARG abundance was quantified using read-based normalization, with results expressed in parts per million (ppm), defined as the number of ARG-like sequences per million reads. To predict the phylogenetic origins of the ARGs, predicted genes were aligned to the NCBI database, and the corresponding host microorganisms were identified as potential antibiotic-resistant bacteria (ARBs) [56]. Circos plots [57] were generated to visualize ARG subtypes and their association with denitrifying bacteria across the three samples. A co-occurrence network analysis was conducted to explore the correlations between ARGs and microorganisms using IBM SPSS Statistics (version 20.0), focusing on strong and significant correlations (Spearman’s r ≥ 0.8, Pearson’s r ≥ 0.8, p ≤ 0.01). Network visualization was performed using Gephi (version 0.10.1).

3. Results and Discussions

3.1. Profiles of Three SBBRs

As shown in Figure 1a,b, the initial TN in the three SBBRs was 50 mg/L, which gradually decreased as the reaction progressed. After 4 h of the anoxic phase, no accumulation of NO3−-N was observed in SBBR-0 and SBBR-2, whereas approximately 0.5 mg/L of NO3−-N was detected in SBBR-1. Simultaneously, the residual NH4+-N concentrations in SBBR-0, SBBR-1, and SBBR-2 were 17.1, 17.8, and 16.1 mg/L, respectively. No NO2−-N accumulation was detected in any of the reactors, likely due to the rapid oxidation of nitrite to nitrate by active nitrite-oxidizing bacteria, indicating complete nitrification without intermediate buildup. At the end of the low-oxygen phase, the residual NO3−-N and TN concentrations were 10.2 mg/L and 11.0 mg/L in SBBR-0, 11.0 mg/L and 12.2 mg/L in SBBR-1, and 8.7 mg/L and 9.4 mg/L in SBBR-2, respectively. The corresponding TN removal efficiencies were 78.1% for SBBR-0, 75.8% for SBBR-1, and 81.3% for SBBR-2 (Figure 1c). These results indicated that TN removal efficiency declined under PFOA stress, likely due to its inhibitory effects on microbial nitrogen metabolism. The slight accumulation of NO3−-N in SBBR-1 suggested that PFOA may have affected denitrification efficiency, potentially by disrupting electron transfer or altering metabolic pathways. However, the addition of biochar in SBBR-2 mitigated some of the negative impacts of PFOA, possibly by enhancing electron transfer or supporting microbial activity, thereby improving TN removal performance.
The initial COD concentrations in the three SBBRs were approximately 200 mg/L and decreased noticeably during the anoxic phase. By the end of this phase, COD levels had dropped to 51.4 mg/L in SBBR-0, 54.2 mg/L in SBBR-1, and 37.6 mg/L in SBBR-2. After 6 h of operation, COD concentrations further declined to 30.6 mg/L in SBBR-0, 36.1 mg/L in SBBR-1, and 27.9 mg/L in SBBR-2. Corresponding COD removal efficiencies were 84.7% for SBBR-0, 81.9% for SBBR-1, and 86.1% for SBBR-2.
The initial PFOA concentrations in SBBR-1 and SBBR-2 were approximately 20 μg/L and remained relatively stable throughout the reaction period. Five PFOA byproducts were detected in the effluent, with concentrations ranging from 0 to 167 ng/L (Table S10). These byproducts could have originated from partial microbial degradation by specific microbial communities or from trace impurities introduced via chemical reagents used in the experiment. This observation was consistent with the findings of Liou et al. [58], who reported that PFOA is recalcitrant to microbial degradation in conventional SBBRs and imposes persistent stress on the microbial system. The degradation of PFOA in bioreactors primarily occurred through adsorption onto activated sludge rather than through biodegradation [12]. In this study, the minimal difference in PFOA concentrations between influent and effluent suggested that the adsorption capacity for PFOA had reached saturation in both SBBRs.

3.2. Characterization of Biochar

In our study, the removal efficiencies of TN and COD in SBBR-2 were significantly higher than those observed in SBBR-1. The SEM image of the raw biochar (Figure 2a) revealed a highly porous and rough surface, which likely facilitated microbial attachment by providing extensive surface area and protective microenvironments, thereby enhancing microbial retention. The SEM analysis of the used biochar (Figure 2a–d) showed abundant microbial colonization on the surface, forming a complex and dense microbial community. To further characterize the biomass associated with the biochar, EEM fluorescence spectroscopy was performed (Figure S2). Compared to the spectra of the raw biochar, a distinct peak with an emission wavelength of 305–345 nm and an excitation wavelength near 280 nm was observed in the used biochar. This peak was attributed to soluble microbial products (SMPs), which are organic compounds released by microorganisms during substrate metabolism and biomass decay [59]. These results indicated that microorganisms attached to the biochar in SBBR-2 were metabolically active and contributed to the observed SMP production.
The FTIR spectra of the raw biochar and used biochar (Figure 2e) exhibited a characteristic absorption peak at 3440 cm−1, corresponding to O–H stretching vibrations, which could be attributed to hydroxyl groups or adsorbed water molecules. The band at 2928 cm−1 was associated with C–H stretching vibrations, potentially originating from alkyl groups on the biochar surface [60]. A prominent band near 1600 cm−1 may be attributed to C=O stretching vibrations, which may have shifted to a lower wavenumber due to conjugation with aromatic rings, representing carbonyl (–C=O) or carboxyl (–COOH) groups [61]. Additionally, this band may have partially resulted from C=C skeletal vibrations within aromatic structures. To further investigate changes in oxygen-containing functional groups on the biochar, XPS analysis was performed (Figure 2f). Compared to raw biochar, the intensity of the –OH peak decreased in the used biochar, possibly due to the oxidation of hydroxyl groups. In contrast, the –COOH peak intensity increased, likely resulting from further oxidation of carbonyl (–C=O) groups. These changes suggested that hydroxyl groups on the biochar surface were oxidized during microbial activity in SBBR-2, while carbonyl groups (–C=O) were further transformed into carboxyl groups (–COOH). These observations implied that biochar functioned as an electron donor during microbial metabolism, thereby facilitating microbial metabolic activities through electron provision and enhancing pollutant removal efficiency.

3.3. Metabolic Analysis

To further investigate the effects of PFOA and biochar on cellular activity, ROS and ATP levels in the activated sludge from the three SBBRs were measured. As shown in Figure 2g, ROS levels followed the order SBBR-1 > SBBR-2 > SBBR-0, indicating that PFOA exposure led to increased oxidative stress, while the presence of biochar significantly reduced ROS accumulation. ROS are primarily generated as byproducts of intracellular metabolic activities and are normally regulated by the cellular antioxidant defense system to maintain redox homeostasis. When ROS levels exceed the neutralizing capacity of the antioxidant system, oxidative stress occurs, leading to cellular damage [62]. Previous studies have demonstrated that excessive ROS could oxidize lipids, damage cellular structures, and inhibit key enzymatic activities and ATP synthesis through protein interactions, thereby suppressing microbial metabolic activity [63,64]. PFOA has been shown to disrupt the mitochondrial electron transport chain (ETC) and impair antioxidant system functionality, resulting in elevated ROS levels. In contrast, biochar supplementation effectively mitigated the PFOA-induced oxidative stress, maintaining ROS concentrations at relatively lower levels. As shown in Figure 2h, ATP levels followed the order SBBR-2 > SBBR-1 > SBBR-0, suggesting that ROS-induced mitochondrial damage triggered a self-reinforcing cycle of reduced ATP synthesis. Insufficient ATP further weakened the antioxidant defense system, thereby exacerbating ROS accumulation. Since ATP levels reflected both mitochondrial function and overall cellular activity, the observed increase in SBBR-2 indicates that the biochar enhanced cellular energy metabolism and alleviated the inhibitory effects of PFOA on sludge performance.

3.4. Microbial Community Structure Analysis

3.4.1. Community Composition Analysis

Figure 3 illustrates the microbial community composition in the three SBBRs, with the four dominant phyla identified as Pseudomonadota, Bacteroidota, Chloroflexota, and Acidobacteriota (Figure 3a). These phyla were commonly detected in soil and surface water environments contaminated with PFOA and PFOS [65]. Pseudomonadota, which includes genera such as Pseudomonas and Paracoccus, plays a key role in nitrogen cycling and the degradation of organic pollutants through processes such as nitrification and denitrification [66]. Bacteroidota, represented by Bacteroides and Flavobacterium, contributes to the hydrolysis and fermentation of organic matter [67]. Chloroflexota, including Chloroflexus and Roseiflexus, is involved in biofilm formation and sludge aggregation, thereby enhancing microbial stability [68]. Acidobacteriota, comprising genera such as Acidobacterium and Granulicella, is associated with carbon cycling and microbial resilience under stress conditions [69]. Under PFOA stress, microorganisms often secrete large quantities of proteins to cope with toxic environmental conditions, while Bacteroidetes can decompose proteins and glucose to produce volatile acids [70]. A previous study showed that elevated PFOA concentrations can stimulate the growth and proliferation of Bacteroidetes, enhancing their adaptability to harsh environments [13]. In this study, the relative abundance of Bacteroidetes in SBBR-2 was lower than that in SBBR-1, suggesting that biochar effectively alleviated PFOA-induced stress. This reduction in environmental pressure may have diminished the microbial community’s need to develop high stress tolerance, resulting in a more balanced microbial community structure and improved TN removal efficiency.
Seventeen major genera identified across the three SBBRs are presented in Figure 3b. In SBBR-0, the four most abundant genera were unclassified_Anaerolineales (6.08%), unclassified_Flavobacteriales (4.71%), Thauera (4.48%), and unclassified_Betaproteobacteria (4.23%). Under PFOA stress in SBBR-1, the dominant genera shifted to Thauera (7.90%), unclassified_Pseudomonadota (5.16%), unclassified_Anaerolineae (4.69%), and unclassified_Betaproteobacteria (4.42%), indicating significant alteration in the dominance hierarchy. In SBBR-2, the addition of biochar further altered the microbial community structure, with the top four genera being Thauera (9.92%), unclassified_Pseudomonadota (6.29%), Nitrosomonas (5.75%), and unclassified_Burkholderiales (5.29%). The dominant bacteria across the three SBBRs included Thauera, Nitrosomonas, and Nitrospira, consistent with microbial communities reported in other wastewater treatment systems [71,72]. These genera were pivotal in biological nitrogen removal, with Thauera primarily responsible for denitrification, as well as Nitrosomonas and Nitrospira involved in ammonia and nitrite oxidation, respectively. Although nitrification was not the limiting step in nitrogen removal, the increased abundance of Nitrosomonas and Nitrospira in SBBR-2 likely contributed to enhanced nitrification–denitrification synergy, indirectly promoting total nitrogen removal [73,74]. Compared to SBBR-0, the abundance of Nitrospira and Nitrosomonas in SBBR-1 decreased, while Thauera increased. Denitrifying bacteria, as the main hosts of ARGs, would be stimulated to produce tolerance in the presence of PFOA, promoting the proliferation [16]. In contrast, the abundance of nitrifying bacteria was suppressed under PFOA exposure due to harsher living conditions and intensified substrate competition.
In our study, the introduction of biochar not only altered the dominant microbial genera but also significantly increased the relative abundance of key functional genera. Specifically, Thauera abundance increased by 25.6%, while Nitrosomonas showed a 305% increase compared to SBBR-1. Thauera, a member of the Comamonadaceae family within the β-Proteobacteria, is involved in denitrification processes [75,76]. Nitrosomonas, an ammonia-oxidizing bacterium, is essential for the conversion of ammonia to nitrite, a key step in nitrification [77]. Additionally, Burkholderiales, the fourth most dominant genus in SBBR-2, accounted for 5.30% of the microbial community, representing a 55.9% increase compared to SBBR-1. Certain members of Burkholderiales are known for their ability to degrade aromatic compounds, including high-priority pollutants such as pentachlorophenol [78,79]. Microorganisms responded differently to PFOA exposure, and the introduction of biochar helped optimize the microbial community under PFOA stress. The increased abundance of functional genera such as Thauera contributed to enhanced partial nitrification–denitrification performance in SBBR-2. Moreover, the overall rise in denitrifying bacteria supported improved TN removal efficiency. These shifts in microbial community structure were consistent with the observed differences in nitrogen removal performance among the three SBBRs.

3.4.2. Quorum Sensing Analysis

To evaluate the impact of biochar on QS activity within microbial communities, the concentrations of seven representative AHLs were quantified. The total AHL concentrations served as indicators of QS activity in the three SBBRs. As shown in Figure 4a, not all AHL types were detected in the mixed liquor of the reactors. The overall AHL concentrations followed the order SBBR-2 > SBBR-1 > SBBR-0 (Figure 4b), indicating a positive correlation between QS signaling, microbial community structure, and TN removal efficiency. During bacterial growth, AHLs are continuously produced to mediate intercellular communication. Among the three SBBRs, four types of AHLs were identified: C4-HSL, C8-HSL, C12-HSL, and C14-HSL. In SBBR-2, short-chain AHLs (C4-HSL: 118 ng/L) accounted for approximately 26.2% of the total AHL content, while the remainder comprised medium- and long-chain AHLs (e.g., C8-HSL to C14-HSL). AHL concentrations were consistently higher across all detected types in SBBR-2, with particularly notable increases observed in long-chain AHLs compared to SBBR-1. The binding of AHLs to their cognate cytoplasmic receptor proteins, specifically LuxR-type transcriptional regulators, is a concentration-dependent process. Consequently, bacterial community behavior is closely regulated by the concentration of these signaling molecules. At low AHL concentrations, QS pathways are weakly activated or remain inactive; in contrast, elevated concentrations effectively initiate QS responses, thereby facilitating coordinated microbial communication and cooperative behavior [80].
The results of the batch experiments are presented in Figure 4c. The bar graph illustrates the variations in TN removal capacity among the experimental groups relative to the control group, following the addition of various AHLs. The accompanying scatter plot depicts the standard deviations of AHL concentrations across the three SBBRs, with higher values indicating a greater influence of PFOA and biochar on AHL dynamics. An analysis of the signaling molecules associated with nitrogen removal revealed that four types of AHLs enhanced TN removal to varying degrees in SBBR-0, while six types were effective in SBBR-2. In contrast, only two AHL types contributed to improved TN removal in SBBR-1, which was exposed to PFOA. The presence of PFOA likely imposed stress on the microbial community, leading to reduced secretion of specific signaling molecules. This disruption may have impaired QS pathways and consequently weakened the regulatory effects of these molecules on TN removal processes.
The addition of C4-HSL and C14-HSL enhanced the TN removal efficiency of PFOA-acclimated activated sludge. Previous studies have shown that C4-HSL promotes regulation, transportation, and decomposition functions in the QS process [81], while C14-HSL is specifically involved in regulating Anammox [82]. As illustrated in Figure 4a, the concentration of C14-HSL in SBBR-1 decreased markedly following PFOA addition, whereas its level in SBBR-2 increased significantly after the introduction of biochar. Among all the tested AHLs at the same concentration (100 ng/L), C14-HSL had the most pronounced effect on enhancing TN removal efficiency, which was consistent with its pronounced variation in response to PFOA exposure and biochar addition. The decline in QS levels following PFOA exposure may be attributed to the compound’s hydrophobic and lipophilic characteristics. PFOA tends to accumulate on microbial cell surfaces within activated sludge, potentially disrupting normal cellular functions and interfering with substance transport and metabolic processes [83]. In biological wastewater treatment systems, microbial cooperation through metabolite exchange is essential for maintaining system performance; thus, the presence of PFOA may destabilize these interactions. In contrast, biochar addition in SBBR-2 elevated QS activity, likely due to its electron transfer capabilities, which enhanced microbial activity and accelerated metabolic processes, thereby promoting the synthesis and secretion of QS signaling molecules as metabolic byproducts. These findings further demonstrated a significant correlation among QS activity, microbial community composition, and TN removal efficiency in SBBRs, as supported by our metabolic analysis.
As illustrated in Figure 5, the addition of PFOA led to elevated intracellular ROS levels and a reduction in ATP concentrations, ultimately resulting in diminished cellular activity. In contrast, the introduction of biochar effectively mitigated these adverse effects. This mitigation is attributed to the abundant oxygen-containing functional groups on the biochar surface, which acted as electron donors and participated in the mitochondrial ETC, thereby enhancing cellular metabolism. Consequently, the secretion of AHLs—as metabolic byproducts—was increased, leading to enhanced QS activity. Previous studies have demonstrated that microorganisms such as Thauera, Pseudomonas, Agrobacterium, Acinetobacter, and Burkholderia are capable of producing AHLs [84,85]. In the present study, the relative abundances of Thauera, Burkholderia, and Pseudomonas increased following biochar addition, which corresponded with the observed elevation in AHL concentrations. This enhancement in microbial communication improved cooperative interactions within the community, thereby contributing to increased nitrogen removal efficiency. Furthermore, biochar addition promoted microbial community restructuring and significantly elevated AHL concentrations. The increase in AHLs was facilitated by the enrichment of QS-active bacteria, which subsequently promoted the proliferation of functional nitrogen-removing genera such as Thauera, Nitrospira, and Nitrosomonas. The enrichment of these functional bacteria strengthened nitrogen transformation processes, ultimately resulting in improved TN removal performance.

3.5. Metagenomics Analysis

3.5.1. Quorum Sensing Genes

Figure 6 illustrates the total relative abundance (log scale) of LuxR family genes—associated with AHLs sensing and synthesis—across the top 17 most abundant genera in samples from SBBR-0, SBBR-1, and SBBR-2. Thauera exhibited the highest proportion of LuxR family genes among the three SBBRs, accounting for 0.32%, 0.42%, and 0.58% in SBBR-0, SBBR-1, and SBBR-2, respectively. Genera such as Thauera, Alicycliphilus, and Comamonas showed relatively high abundances of QS-related genes, while the abundance of QS genes in genera such as Candidatus_Accumulibacter and Brevundimonas was lower in SBBR-1 compared to SBBR-0. This variation was likely attributed to the addition of PFOA, which induced tolerance and promoted the proliferation of Thauera, Alicycliphilus, and Comamonas, while reducing the abundance of more sensitive and intolerant bacteria. Consequently, these changes led to corresponding alterations in QS gene abundance, thereby affecting QS mechanisms within the microbial community.
Compared to SBBR-1, an increase in the relative abundance of functional bacterial genera involved in AHL sensing and synthesis was observed in SBBR-2. For instance, the relative abundance of Thauera increased from 7.9% to 9.9%. These findings indicated that the introduction of biochar influenced microbial genetic composition by enhancing the abundance of genes associated with AHL sensing and synthesis. Detailed data on relative abundances are provided in Table S11.

3.5.2. Nitrogen Cycle Genes

Microorganisms play a pivotal role in the nitrogen cycle, which is regulated by a range of functional genes involved in distinct nitrogen transformation processes [86]. As shown in Figure 7a,b, the relative abundances of all nitrogen-cycle-related functional genes increased significantly, consistent with the enrichment of functional microbial genera. The most notable increase was observed for the hao gene, which encodes hydroxylamine oxidase. Furthermore, the abundances of nosZ (encoding nitrous oxide reductase) and nxrB (encoding nitrite oxidoreductase) were higher in SBBR-2 than in SBBR-1, indicating enhanced denitrification and nitrification activities in the biochar-amended reactor.
The increased abundance of hao, nir, nor, and nos genes indicated an enhancement of partial nitrification–denitrification processes in SBBR-2. This pathway facilitated rapid nitrogen removal, improved energy utilization, and reduced overall energy consumption [87]. The performance difference between SBBR-1 and -2 was highlighted by nitrate accumulation at the end of the anoxic and low-oxygen phases. After 4 h of anoxic treatment, no nitrate accumulation was observed in SBBR-2, whereas approximately 0.5 mg/L of nitrate accumulated in SBBR-1. These findings underscored the higher nitrogen removal efficiency of SBBR-2, which corresponded with the elevated abundance of hao, nir, nor, and nos genes. A host analysis of the genes encoding nitrogen-cycle-related functional enzymes further corroborated the relationship between microbial community structure and nitrogen cycling activity. This observation was consistent with the results shown in Figure 3, which demonstrated that shifts in microbial community composition contributed to the enhanced nitrogen removal performance observed in SBBR-2.

3.5.3. ARG Analysis

A co-occurrence network analysis was employed to identify the taxonomic hosts of ARGs (Figure 7c). In the network diagram, bacterial genera are represented in red and ARGs in black. Distinct modules, indicated by different colors, reflect specific ARGs and their associated host microorganisms. The size of each node represents the number of ARG subtypes associated with each genus, with larger nodes indicating greater ARG diversity. A network analysis revealed that the primary ARG hosts were not the key nitrogen-removing functional microorganisms in the reactors. Instead, ARGs were predominantly associated with genera such as Ignavibacterium, Rhodobacter, Azohydromonas, and Rubrivivax, which are not directly involved in nitrogen removal. Moreover, the enrichment of key nitrogen-removing microorganisms did not lead to a significant accumulation of ARGs, thereby reducing the potential risk of ARG proliferation and environmental dissemination.
Previous studies have shown that PFOA can induce denitrifying bacteria to produce ARGs [16]. To compare ARG carriage and production by denitrifiers under PFOA stress across the three SBBRs, fourteen representative denitrifying genera were selected from nearly eighty identified taxa, including Thauera, Pseudomonas, Azoarcux, etc. The taxonomic hosts of ARGs were identified by mapping ARG sequences to the NCBI database [56]. The qualitative and quantitative relationships between ARG subtypes and denitrifying bacteria in SBBR-1 and SBBR-2 were visualized using Circos diagrams (Figure S3), providing a clear overview of ARG distribution among key denitrifying bacteria. The addition of biochar appeared to moderate ARG expression under PFOA stress.
As illustrated in Figure S3, differences in both the subtypes and abundances of ARGs carried by denitrifying bacteria were observed across the three reactors. Compared to SBBR-0, the presence of PFOA in SBBR-1 increased the ARG-to-denitrifying-bacteria ratio, while biochar addition in SBBR-2 significantly reduced this ratio. These results suggested that PFOA imposed stress on denitrifying bacteria, stimulating ARG production, whereas biochar alleviated this stress and suppressed ARG expression. From a sustainability perspective, this effect is particularly important, as it indicates that biochar addition can serve as an effective strategy to control ARG emergence and reduce ecological risks associated with emerging contaminants. In addition to microbial composition, variations in QS could also influence ARG dynamics. QS regulates cell membrane permeability [88], and its enhancement may facilitate intercellular genetic communication, potentially promoting ARG transfer [89,90]. However, despite the observed increase in QS activity in SBBR-2, the overall ARG levels were reduced. This finding indicated that biochar not only mitigated the negative effects of PFOA but also reduced ARG production and did not promote ARG dissemination, highlighting its potential as a sustainable remediation strategy in PFOA-stressed biological treatment systems.

4. Conclusions

This study demonstrated that TN removal under PFOA stress was enhanced by introducing biochar into the SBBR operated with DO concentrations of 0.5–1.0 mg/L and a C/N ratio of 4.0. The metabolic analysis revealed that intracellular ROS levels increased under PFOA pressure, while oxygen-containing functional groups on the biochar surface—serving as electron donors—significantly reduced ROS accumulation and promoted ATP production. The improvement in cellular metabolism further stimulated QS, leading to increased synthesis of QS signaling molecules. The analysis of AHL concentrations confirmed that biochar restored QS activity suppressed by PFOA stress, enhancing microbial communication and cooperation. The relative abundance of key nitrogen-removing bacteria, such as Thauera and Nitrosomonas, increased, contributing to improved nitrogen removal efficiency. Furthermore, the metagenomic analysis revealed that biochar introduction significantly suppressed the production of ARGs and did not promote their dissemination, thereby mitigating the adverse effects of PFOA. These findings highlight the potential of biochar to enhance QS, counteract PFOA-induced inhibition, and improve TN removal performance in SBBRs. This study provides novel insights into the development of sustainable strategies to enhance biological nitrogen removal performance under the stress of emerging organic contaminants, supporting efforts to meet the stringent TN discharge standard for urban wastewater treatment.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/su17083359/s1, Table S1: The parameters of the three SBBRs; Table S2: Nutrient profile of synthetic wastewater; Table S3: Detailed properties of the typical AHLs; Table S4: LC-MS/MS conditions for AHL measurements; Table S5: Parameters for procedure of gradient elution (AHL measurements); Table S6: Multiple reaction monitoring (MRM) and MS/MS parameters for AHL measurements; Table S7: LC-MS/MS conditions for PFAS measurements; Table S8: Parameters for procedure of gradient elution (PFAS measurements); Table S9: Multiple reaction monitoring (MRM) and MS/MS parameters for PFAS measurements; Table S10: PFOA degradation products in the effluent from two SBBRs; Table S11: Relative abundance (% and log) of LuxR family genes in 14 genera; Figure S1: The schematic diagram of the SBBRs; Figure S2: EEM images of the biomass on the biochar. (a) The raw biochar. (b) The used biochar; Figure S3: Circos plot of the top 30 abundant ARG subtypes and taxonomic origin in (a) SBBR-0, (b) SBBR-1, and (c) SBBR-2. (d) The ratio of ARG relative abundance to denitrifying bacteria relative abundance in SBBR-0, SBBR-1, and SBBR-2.

Author Contributions

Z.L.: methodology, data curation, formal analysis, investigation, writing—original draft, visualization. M.Z.: methodology, data curation, investigation. X.H.: methodology, formal analysis, validation. H.L.: funding acquisition, conceptualization, validation, writing—review and editing, supervision, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by the National Key Research and Development Program (2024YFA0918901), the National Natural Science Foundation of China (22276039), and the Shanghai Natural Science Foundation (22ZR1405400). The authors gratefully acknowledge the reviewers for valuable insights and suggestions.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analyzed during this study are included in this manuscript and its Supplementary Information file.

Acknowledgments

The authors are extremely appreciative of their teacher’s advice and the assistance of the research group’s pupils.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Variations in NH4+-N, NO2−-N, NO3−-N, TN, and COD concentrations over a single operational cycle in the three SBBRs: (a) comparison of overall removal performance; (b) variation in nitrogen concentration at different time points within a single treatment cycle; (c) comparison of TN removal efficiencies among reactors.
Figure 1. Variations in NH4+-N, NO2−-N, NO3−-N, TN, and COD concentrations over a single operational cycle in the three SBBRs: (a) comparison of overall removal performance; (b) variation in nitrogen concentration at different time points within a single treatment cycle; (c) comparison of TN removal efficiencies among reactors.
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Figure 2. SEM images of raw biochar at (a) 50 µm and (b) 10 µm scale. SEM images of used biochar at (c) 50 µm and (d) 10 µm scale. (e) FTIR spectra and (f) XPS spectra of raw and used biochar. (g) ROS levels and (h) ATP levels in the three SBBRs.
Figure 2. SEM images of raw biochar at (a) 50 µm and (b) 10 µm scale. SEM images of used biochar at (c) 50 µm and (d) 10 µm scale. (e) FTIR spectra and (f) XPS spectra of raw and used biochar. (g) ROS levels and (h) ATP levels in the three SBBRs.
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Figure 3. Microbial community composition in the three SBBRs at the (a) phylum and (b) genus levels.
Figure 3. Microbial community composition in the three SBBRs at the (a) phylum and (b) genus levels.
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Figure 4. AHL profiles in mixed liquor samples from SBBR-0, SBBR-1, and SBBR-2: (a) comparison of individual AHL types across the three SBBRs; (b) total AHL concentrations in each SBBR; (c) effects of different AHL types on TN removal.
Figure 4. AHL profiles in mixed liquor samples from SBBR-0, SBBR-1, and SBBR-2: (a) comparison of individual AHL types across the three SBBRs; (b) total AHL concentrations in each SBBR; (c) effects of different AHL types on TN removal.
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Figure 5. Proposed mechanism of enhanced TN removal under PFOA stress in SBBR with biochar addition.
Figure 5. Proposed mechanism of enhanced TN removal under PFOA stress in SBBR with biochar addition.
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Figure 6. Total relative abundance (log scale) of LuxR family genes across different genera in samples from SBBR-0, SBBR-1, and SBBR-2. The top 17 genera, ranked by relative abundance, are displayed and quantified.
Figure 6. Total relative abundance (log scale) of LuxR family genes across different genera in samples from SBBR-0, SBBR-1, and SBBR-2. The top 17 genera, ranked by relative abundance, are displayed and quantified.
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Figure 7. (a) Heat map showing the relative abundance (log scale) of nitrogen-cycle-related genes across different microbial genera in samples from SBBR-0, SBBR-1, and SBBR-2. Darker colors indicate higher abundance. The top 30 genera by relative abundance are displayed and quantified. (b) Radar plot illustrating the relative abundance of total genes involved in various nitrogen cycle pathways. (c) Co-occurrence network analysis of the top 30 bacterial genera and the top 70 ARGs based on abundance.
Figure 7. (a) Heat map showing the relative abundance (log scale) of nitrogen-cycle-related genes across different microbial genera in samples from SBBR-0, SBBR-1, and SBBR-2. Darker colors indicate higher abundance. The top 30 genera by relative abundance are displayed and quantified. (b) Radar plot illustrating the relative abundance of total genes involved in various nitrogen cycle pathways. (c) Co-occurrence network analysis of the top 30 bacterial genera and the top 70 ARGs based on abundance.
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MDPI and ACS Style

Lu, Z.; Zhao, M.; He, X.; Li, H. Biochar-Enhanced Nitrogen Removal in SBBR Under PFOA Stress: The Role of Quorum Sensing. Sustainability 2025, 17, 3359. https://doi.org/10.3390/su17083359

AMA Style

Lu Z, Zhao M, He X, Li H. Biochar-Enhanced Nitrogen Removal in SBBR Under PFOA Stress: The Role of Quorum Sensing. Sustainability. 2025; 17(8):3359. https://doi.org/10.3390/su17083359

Chicago/Turabian Style

Lu, Zhiqi, Mengzhe Zhao, Xianglong He, and Hongjing Li. 2025. "Biochar-Enhanced Nitrogen Removal in SBBR Under PFOA Stress: The Role of Quorum Sensing" Sustainability 17, no. 8: 3359. https://doi.org/10.3390/su17083359

APA Style

Lu, Z., Zhao, M., He, X., & Li, H. (2025). Biochar-Enhanced Nitrogen Removal in SBBR Under PFOA Stress: The Role of Quorum Sensing. Sustainability, 17(8), 3359. https://doi.org/10.3390/su17083359

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