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Article

Red Light Enhanced Nitrogen Removal Efficiency by Bacterial–Algae Biofilm Reactor in Recirculating Aquaculture Systems

by
Wenqiang Jiang
2,†,
Qingfeng Li
2,†,
Linyuan Jiang
1,
Qunxin Huang
2,
Junneng Liang
1,
Yating Zhou
2,
Mingji Lv
2,
Luting Wen
1,
Yijian Li
1,
Qiuwei Ao
1,
Shumin Wang
2,* and
Xueming Yang
1,*
1
Guangxi Key Laboratory of Aquaculture Genetic and Breeding and Healthy Aquaculture, Guangxi Academy of Fishery Sciences, Nanning 530021, China
2
Fisheries College, Southwest University, Chongqing 400715, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Processes 2025, 13(11), 3594; https://doi.org/10.3390/pr13113594
Submission received: 23 July 2025 / Revised: 11 September 2025 / Accepted: 22 September 2025 / Published: 7 November 2025
(This article belongs to the Section Chemical Processes and Systems)
Browse Figures
Versions Notes

Abstract

This study aimed to evaluate the effects of different light wavelengths on nitrogen removal efficiency and microbial community dynamics in a bacterial–algal biofilm reactor (BABR) within recirculating aquaculture systems (RASs). Four RAS units were operated under red, blue, red–blue (1:1), and white light, and their performance in nitrogen transformation, microbial community composition, extracellular polymeric substances (EPSs), and gene abundance was systematically assessed. The results showed that red light markedly improved ammonia removal and overall nitrogen transformation stability, particularly under high nitrogen loading, by enabling faster recovery and suppressing nitrite accumulation. Microbial analyses revealed that red light enriched key algae (e.g., Scenedesmus) and functional bacteria (e.g., Bosea and Nitrospirota), supporting efficient nitrification and denitrification. Furthermore, gene annotation demonstrated that red light enhanced the abundance of photosynthetic proteins and nitrogen metabolism pathways, including biofilm formation, quorum sensing, and amino acid biosynthesis. Collectively, these findings highlight red light as a promising regulatory factor for enhancing biofilm-based nitrogen removal in RASs, providing a theoretical basis for light-assisted aquaculture wastewater treatment.

Graphical Abstract

1. Introduction

With the continuous growth of the global population, aquaculture is increasingly becoming an important means to ensure the world’s food security [1,2]. As an adaptive strategy for aquaculture, recirculating aquaculture systems (RASs) are receiving increasing interest due to their advantages in saving land and water resources, reducing labor costs, and improving yield [3,4].
Biofilters are pivotal for nitrogen removal in RASs [5]. To prevent biotoxicity, the levels of ammonia and nitrite must be strictly controlled in RASs [6,7]. Traditional methods such as biofloc and biofilm-based technologies are commonly employed in RASs for nitrogen removal. However, biofloc systems often suffer from high energy consumption and excessive sludge production [8], In addition, biofilm systems are limited by slow reaction rates and the risk of clogging, particularly when microbial growth becomes excessive or when optimal conditions for nitrification are not maintained [9,10]. Therefore, both systems exhibit notable shortcomings, which can hinder their effectiveness in long-term RAS operations [2,11,12,13]. In comparison, bacterial–algal biofilm reactors (BABRs) are a novel alternative, with higher nitrogen removal efficiency and lower CO2 and energy consumption [14,15]. Recent studies have directly compared BABRs to traditional biofilm and biofloc systems, confirming their superior nitrogen removal performance [16]. In a BABR system, microalgae fix carbon dioxide through photosynthesis, simultaneously producing oxygen and organic compounds essential for microorganisms. Concurrently, microorganisms release carbon dioxide as a byproduct of their metabolic activities. This symbiotic interaction enhances the efficiency of BABRs in nitrogen removal compared to reactors comprising only microalgae or bacteria, as photosynthesis is the key driver of the collaborative effect [17]. In addition, lighting is a cleaner and more straightforward strategy to enhance nitrogen removal compared to increasing the influent C/N ratio [18,19]. Recent studies with photo-sequencing batch reactors further confirmed that algae–bacteria consortia under illumination achieved higher nitrogen removal efficiencies than conventional aerobic granules without light [20]. However, there is limited research on the effect of supplementary lighting on nitrogen removal efficiency, with recent studies showing inconsistent results regarding the optimal wavelength [19,21,22,23,24,25]. While some studies suggest that red light significantly enhances nitrogen removal efficiency [19], others report that mixed light wavelengths or blue light yield better nutrient removal rates [26].
Light is crucial for both photosynthesis and the survival of microalgae, while bacteria are more suited to dark environments and susceptible to light inhibition, particularly nitrifying bacteria [19,27]. Recent studies have shown that nitrifying bacteria suffer from photoinhibition under strong light irradiation, primarily due to irreversible damage to ammonia monooxygenase (AMO) [28]. This effect can be further mitigated by light-shielding strategies, which protect nitrifying bacteria from photoinhibition in high-light environments [29]. The growth of microalgae and the production of specific photopigments have specific requirements in light wavelengths [30]. Consequently, optimizing directional lighting for bacterial–algal biofilms is important [31]. Our previous research demonstrated that red light is more effective than other wavelengths in enhancing nitrogen removal efficiency [19], which was confirmed in studies [32,33]. In contrast, other studies suggested that mixed light wavelengths or blue light achieved higher nutrient removal rates [34,35]. Light-enhanced nitrogen removal was primarily influenced by photosynthesis, carbon metabolism, nitrogen metabolism, glutamate metabolism, and oxidative stress [21,22,36,37]. In addition, substance absorption and extracellular environmental regulation were also involved in the nitrogen removal pathways under light illumination [38,39]. Nonetheless, how light wavelength affects the nitrogen removal routes in BABRs is still unclear.
In this study, we constructed four RASs, illuminated with different light wavelengths: red light, blue light, red–blue mixed light, and white light. The objectives of this research were as follows: (I) investigate the nitrogen removal efficiency of RASs under different light wavelengths; (II) determine the impact of light wavelengths on microbial community composition; and (III) elucidate the mechanisms by which light wavelengths affect nitrogen removal, focusing on extracellular polymeric substances (EPSs) and metabolic pathways.

2. Materials and Methods

2.1. Construction and Operation of RASs

Four identical recirculating aquaculture systems (RASs) were constructed, each comprising a 36 L simulated fish tank and two 7 L bacterial–algal biofilm reactors (BABRs) arranged in series (Figure 1 and Figure S1) (laboratory-made, Chongqing, China.). Each BABR had a diameter of 100 mm, with a height-to-diameter ratio of 9:1, and was filled with 40 spherical fillers (Φ = 50 mm). Spherical fillers were chosen because their regular geometry and 50 mm size ensured a high surface-to-volume ratio, sufficient attachment area for biofilm growth, and stable hydraulic performance without clogging. Each filler consisted of a polypropylene shell with an internal polyurethane sponge (Figure S2). For biofilm sampling, the outer shell was brushed with a sterilized brush, while the sponge was brushed simultaneously with ultrasonic oscillation to detach both surface and embedded biomass.
Lighting treatments were assigned as follows: White (control), Red, Blue, and Red–Blue (1:1). The light intensity was fixed at 3000 ± 300 lx to simulate moderate illumination in aquaculture facilities, balancing photosynthesis and microbial stability, while the 12 h light/12 h dark cycle mimicked natural diel rhythms. During the high-load phase (Stage IV), the photoperiod was extended to 16 h light/8 h dark to enhance photosynthetic oxygen supply. Lighting treatments were provided by LED light strips (Model MJ-GR5050RB, Shenzhen Meijia Optoelectronic Co., Ltd., Shenzhen, Guangdong, China).
The experiment lasted for 68 days and was divided into four operating phases according to the influent total ammonia nitrogen (TAN) load (Table S1). The influent TAN concentration was stepwise increased from ~0.8 mg/L (0.03 g TAN/d, Stage I) to ~1.6 mg/L (0.06 g TAN/d, Stage II), ~4.8 mg/L (0.17 g TAN/d, Stage III), and ~8.0 mg/L (0.29 g TAN/d, Stage IV). In Stage IV, synthetic wastewater with a TAN concentration of 8.0 mg/L was freshly prepared each day and continuously fed into the system by a peristaltic pump (Model BT100-2J, Longer Precision Pump Co., Ltd., Baoding, Hebei, China) at a fixed flow rate. Due to continuous inflow and the relatively long hydraulic retention time (HRT, ~10 days), transient accumulation in the reactor occasionally led to slightly higher observed influent TAN values (~9.0 mg/L). Each system maintained a daily water renewal rate of 10% (3.6 L/d). Across all phases, nitrogen removal rates ranged from 2.11 to 19.67 g TAN/m3/d. To ensure stable operation, dissolved oxygen was controlled at ~6 mg/L, and the temperature was set to 26 ± 1 °C. A C/N ratio of 5:1 was maintained by supplementing (NH4) 2SO4 and glucose, while KH2PO4, NaHCO3, MgSO4·7H2O, and CaCl2 were used to regulate phosphorus, alkalinity, and hardness. NaHCO3 and Na2CO3 were specifically added to buffer pH within 7.0–8.5, providing suitable conditions for algae and nitrifiers. Trace elements (Text S1) were supplied daily [40].

2.2. Water Quality Measurement

Water samples were collected from the effluent of the second BABR in each system at least every three days, following the national standard methods [41]. The parameters monitored included NH4+-N, NO2−-N, NO3−-N, PO43−-P, COD, pH, and dissolved oxygen, with detection methods consistent with those described in our previous study [19]. The total daily input of ammonia nitrogen was maintained at a constant level, with the specific loading rates for each phase detailed in Table S1. Due to the high-speed water circulation within the reactor, the concentration of ammonia nitrogen in the influent could be inferred from the effluent concentrations.

2.3. Biofilm Parameters Analysis

Three carriers (Figure S2) were collected from each reactor. Biofilm samples were collected at the end of each stage by scraping the outer polypropylene shell with a sterile brush and simultaneously brushing the polyurethane sponge core, combined with ultrasound-assisted shaking. This ensured detachment of both surface and embedded biofilm layers for DNA extraction (Text S2). The mixture was then used to measure mixed liquor suspended solids (MLSS) (Text S3), chlorophyll-a (Text S4), extracellular polymeric substances (EPSs) (Text S5), and dissolved organic matter (DOM) (Text S6) [19]. Briefly, MLSS was determined by the gravimetric method, chlorophyll-a by the ethanol extraction method, EPSs by the heat extraction method, and DOM by three-dimensional fluorescence spectroscopy.

2.4. Scanning Electron Microscope (SEM)

For SEM analysis, biofilm-coated carrier balls were prepared as follows: carriers with well-developed biofilms were selected, and the biofilm-covered portions were excised and fixed in 2.5% glutaraldehyde at 4 °C for 24 h. The fixative was then discarded, and the samples were washed three times with phosphate buffer (0.1 M, pH 7.0) for 15 min each. The samples were dehydrated through a graded ethanol series (30%, 50%, 70%, 80%, 90%, and 95%) for 15 min at each concentration, followed by two treatments with 100% ethanol, each lasting 20 min. The samples were then dried using a critical point dryer (Quorum K850) for three hours. Dried samples were mounted on sample holders with conductive carbon tape and coated with gold using an ion sputter coater at 10 mA for 45 s. SEM imaging was performed using a scanning electron microscope (Hitachi Reguius 8100, Hitachi High-Tech Corporation, Tokyo, Japan) to capture the surface morphology.

2.5. High-Throughput Sequencing

At the end of the fourth phase (day 69), three fillers were collected from each reactor. The bacterial–algal biofilms were scraped off and stored in 50 mL ultrapure water (Text S2). The suspension was filtered through a 0.22 μm filter membrane. The filtrate was stored at −20 °C and subjected to high-throughput sequencing. Genomic DNA was extracted from biofilm samples using commercial kits, including the Mag-Bind Soil DNA Kit (M9636-02, Omega Bio-Tek, Norcross, GA, USA), the Mag-Bind Stool DNA Kit (M9016-02, Omega Bio-Tek, USA), the MagAttract PowerSoil Pro DNA Kit (4898129, Qiagen, Hilden, Germany), and the FastDNA™ Spin Kit for Soil (6560-200, MP Biomedicals, Solon, OH, USA). DNA integrity was checked by agarose gel electrophoresis (Thermo Scientific, Agarose 75510019, Waltham, MA, USA), and high-quality DNA was used for downstream processing. Whole-genome amplification was performed with the REPLI-g Single Cell Kit (150345, Qiagen, Germany) to ensure sufficient DNA yield (Table S3).
Briefly, the paired-end Illumina reads were denoised using fastp [42]. Processed data were assembled using MEGAHIT [43]. Open reading frames (ORFs) from each assembled contig were predicted using MetaGene [44]. Representative sequences of the non-redundant gene catalog were generated by CD-HIT [45], and further aligned with the NR database with an e-value cutoff of 1 × 10−5 using Diamond [46] (http://www.diamondsearch.org/index.php, version 0.8.35, accessed on 16 October 2023.) for taxonomic annotations. Functional annotation against the cluster of orthologous groups of proteins (COG) and Kyoto Encyclopedia of Genes and Genomes database was also performed using Diamond [46] at an e-value of 10−5. Gene abundance was calculated using Reads Per Kilobase Million (RPKM) method:
R P K M i = R i ∗ 10 6 L i ∗ ∑ 1 n R j ∑ i n R j
where Ri represents the number of Reads mapped to gene i in a sample; Li represents the nucleotide length of gene i; and Rj represents the sum of all reads corresponding to all genes in the sample.

2.6. Statistical Analysis

Each light condition was represented by one independent RAS. Due to the complexity, cost, and long duration of reactor operation, biological triplicates were not feasible. Instead, continuous monitoring over multiple time points was performed, and differences among treatments were evaluated using one-way ANOVA (SPSS 24.0, IBM). Although not based on three independent replicates, the dynamic dataset across four stages and multiple sampling points provided robust evidence for treatment effects. The limitation of replication is acknowledged, and future studies will include parallel reactors to validate these findings.

3. Results and Discussion

3.1. Light Wavelengths Altered Nitrogen Removal Efficiency

3.1.1. Ammonia Removal Performance

Red light markedly improved ammonia removal and nitrogen transformation stability, especially under high loading (Figure 2a). In Stage I, all groups showed similar ammonia levels (0.66–0.73 mg/L, ANOVA p > 0.05). By Stage II, Red reduced effluent ammonia (0.70 mg/L) compared to White (0.88 mg/L), and in Stage III, it performed significantly better (0.91 mg/L vs. 2.61, 1.60, and 6.67 mg/L for Blue, Red–Blue, and White; p < 0.05). By Day 39, removal efficiency under Red reached 86.9%, while White remained at 32.8%. In Stage IV, Red enabled faster recovery (from 9.0 to 1.17 mg/L), whereas Blue, Red–Blue, and White retained higher residuals. However, the average removal efficiencies in Stage IV were markedly lower than in Stage III (Red ~52%, Red–Blue ~50%, Blue ~23%, White ~3%). This decline was mainly due to TAN accumulation under continuous inflow and extended HRT, which temporarily exceeded the nitrification and algal uptake capacities. Despite this, Red and Red–Blue maintained relatively stable performance, whereas White nearly lost its removal capacity. These observations are consistent with the recovery trends described above, indicating that red light supported faster re-stabilization under high nitrogen loading. A summary of ammonia removal efficiencies across stages, peak NO2−-N, final NO3−-N concentrations, and biofilm parameters under different light treatments is presented in Table 1.
This suggests that red light promotes more efficient nitrification and ammonia removal, potentially due to enhanced photosynthetic oxygen release, which sustains nitrifiers. Studies have shown that red light aligns with the absorption peak of chlorophyll a, enhancing oxygen release and supporting nitrifying bacteria, thus improving the ammonia → nitrite → nitrate conversion process [47,48]. In contrast, blue and white light had less pronounced effects on nitrogen removal, likely due to lower photosynthetic efficiency and/or less favorable light spectra for nitrifying bacteria [49,50].

3.1.2. Nitrite Accumulation Control

Nitrite accumulation was also suppressed under Red. Its Stage IV peak (0.78 mg/L) quickly declined to 0.31 mg/L, while Blue accumulated up to 1.89 mg/L (Figure 2b). Previous studies confirm that proper light stimulates AOB while Red enhances nitrite reductase, preventing nitrite build-up [51,52]. These results suggest that red light promotes nitrite reduction, likely due to enhanced photosynthetic activity under Red, which provides a continuous oxygen supply for nitrite reductase activity [47,51]. Conversely, blue light did not support such efficient nitrite reduction, possibly because of its lower photosynthetic efficiency and weaker light absorption by chlorophyll [49].

3.1.3. Nitrate Transformation Efficiency

Nitrate accumulation further demonstrated superior efficiency. At Day 19, nitrate under Red (4.06 mg/L) was lower than in other groups, and by Day 69, it remained the lowest (62.74 mg/L vs. 68.32, 66.18, and 72.61 mg/L) (Figure 2c). Red has been reported to promote NR activity and NR gene expression, enhancing nitrate assimilation [53,54]. The observed increase in CO2 uptake during photosynthesis under red light also elevated pH, which may further benefit nitrification and nitrate reduction processes. These results suggest that red light not only promotes photosynthesis and CO2 assimilation but also enhances nitrate assimilation by increasing NR expression. These findings are consistent with studies showing that red light enhances carbon fixation and nitrogen metabolism efficiency [55,56].

3.1.4. Environmental Indicators

Environmental indicators supported these findings: Red maintained higher COD/TIN ratios (>6 vs. <2 in others) (Figure 2d); elevated pH, favorable for NOB (Figure 2e) [57,58]; and the lowest phosphate levels (5.15 mg/L), reflecting stronger algal metabolism (Figure 2f) [59]. Collectively, these data suggest that red light not only enhances nitrogen removal but also enables a more balanced ammonia → nitrite → nitrate conversion under high load. The elevated pH levels observed under Red may promote the activity of nitrifiers and facilitate the conversion of ammonia to nitrate [57,58], consistent with the findings that red light enhances CO2 assimilation, improving both carbon and nitrogen metabolism [55,56]. Overall nitrogen removal efficiencies, intermediate products, and supporting biofilm parameters under different light treatments are summarized in Table 1.

3.2. Light Wavelengths Shifted the Biomass and Microbial Community Composition

3.2.1. Effects of Light Wavelengths on Biomass and Chlorophyll a Content

Biomass increased in all groups, but Red consistently maintained the highest levels, peaking at ~62 mg/ball in Stage IV, significantly higher than Blue and Red–Blue (p < 0.05, Figure 3a). This is consistent with previous studies showing that red light enhances algal biomass through improved light harvesting and photosynthetic efficiency [60,61], and by promoting CO2 utilization [62].
Chlorophyll a content showed similar trends, with the Red reaching 0.51 mg/ball in Stage IV, more than double that of the Blue. Even with a low C/N ratio (1.0), chlorophyll a in Red increased steeply, indicating that red light sustained pigment synthesis under carbon limitation. Red–Blue peaked earlier at moderate C/N ratios, suggesting that combined light only partially compensated [63,64]. These results align with reports that red light promotes efficient carbon fixation and pigment accumulation [55,65], while at low C/N ratios, photosynthetic CO2 fixation becomes critical [56,66]. Red light also enhanced carotenoid accumulation [62] and supported electron transfer balancing via phycobilisomes [67,68].

3.2.2. Effect of Light Wavelengths on the Bacterial–Algal Community

Light quality strongly shaped the microbial community (Figure 4). White supported the highest overall diversity (Shannon = 6.21) [69]. At the phylum level, Chlorophyta dominated under all conditions but were most abundant in Blue, suggesting that blue light favored green algae, while Red–Blue enriched Bacillariophyta (~64%), likely due to enhanced absorption under combined spectra [70,71].
At the genus level, Scenedesmus (10–26%) was consistently present and is known for biofilm formation and ammonium removal [72]. Proteobacteria dominated among bacteria across groups, reflecting their role as algal symbionts in C and N cycling [73,74]. Red enriched Leptolyngbya and Leptodesmis, both linked to CO2 uptake and growth promotion [75,76,77]. Bosea, a denitrifier, was also most abundant under Red, supporting enhanced nitrogen removal [78,79]. Conversely, Blue enriched Rhodobacter (~3%), consistent with its high EPS production and nitrite accumulation [80,81]. White favored Microbacterium, a heterotrophic nitrifier–denitrifier [82,83], reflecting less specialized but more diverse taxa.
Nitrifiers also showed wavelength-dependent trends. Ammonia-oxidizing archaea (Nitrosopumilus and Nitrososphaera) were more abundant under Red and Red–Blue, consistent with reduced photoinhibition at longer wavelengths [28,84]. Nitrospirota (complete nitrifiers) were enriched under Red, consistent with reduced nitrite accumulation.
Overall, Red not only promoted efficient algal–bacterial symbiosis but also supported key functional groups across the nitrogen cycle. Ammonia-oxidizing archaea (Nitrosopumilus and Nitrososphaera) initiated the conversion of ammonia to nitrite, Nitrospirota (complete nitrifiers) oxidized nitrite to nitrate, while denitrifiers such as Bosea further reduced nitrate to gaseous forms [51,52,80,81]. In parallel, algal taxa such as Scenedesmus assimilated ammonium and supplied organic carbon, facilitating bacterial metabolism [68]. Together, these processes ensured a continuous ammonia → nitrite → nitrate → N2 transformation without harmful intermediate accumulation, thereby explaining the superior nitrogen removal observed under Red [85,86].

3.3. Light Wavelength Featured EPSs

3.3.1. EPS Content and Composition

EPS content increased over time, with Red and Blue reaching higher levels (~11–12 mg/ball, Figure 3c,f). Previous studies confirm that carbon stress [38,87] and red light illumination promote EPS secretion. In contrast, Red–Blue and White showed limited EPS production, likely due to reduced ROS induction under broad spectra [88]. PN/PS ratios were lower under Red and Blue, indicating higher microbial activity. Protein-rich EPSs promoted biofilm adhesion [89], while polysaccharides contributed to protection, signaling, and electron transfer [90]. Red further enhanced EPS synthesis under all ammonium conditions, whereas Blue showed positive effects only at higher loadings. Elevated PN/PS ratios hindered nitrogen storage capacity and gel-like network formation [91].

3.3.2. Dissolved Organic Matter in EPSs

Although LB-EPS and TB-EPS spectra displayed similar peaks (Figure S9), fluorescence intensities differed. Red and Blue showed stronger aromatic protein (peak B) and tryptophan-like (peak D) signals, both acting as photosensitizers and favorable niches for anammox [92,93]. This implies that light quality primarily affected DOM abundance rather than composition, thereby influencing nitrogen removal performance.

3.3.3. Surface Morphology of Carriers

SEM images (Figure S10) showed that Red–Blue promoted denser bacterial clustering around algae compared to Red, Blue, and White, which exhibited looser biofilms. Dense structures enhanced algal–bacterial synergy but limited diffusion, whereas looser biofilms facilitated cell replacement and EPS secretion, thereby sustaining nitrogen removal [94,95,96].

3.4. Light Wavelength Affected Gene Abundance and Metabolic Pathways

3.4.1. Differences in Abundance of Photosynthetic and Nitrogen Metabolism Enzymes

The abundance of genes associated with nitrogen metabolism and transformation is shown in Figure 5 and Figure S12. Nitrogen removal primarily occurred through uptake of nitrogenous compounds by the bacteria–algae system, followed by assimilation into cellular components via glutamate metabolism and nitrate reduction. Alternatively, nitrogen was converted through nitrification, anammox, or dissimilatory nitrate reduction to generate energy [97]. Among all treatments, White showed the highest overall gene abundance, consistent with its broad spectral coverage [98].
Compared to other groups, Red induced higher abundances of phycobilins, photosystem proteins, and chloroplast phosphoribulokinase, while reducing phosphoglycolate phosphatase (PGLP) expression (Figure 5). This pattern indicates that red light enhanced photosynthetic enzyme abundance, improving the efficiency of converting light to chemical energy. Similar responses have been observed in higher plants, where red light-enriched environments promoted photosynthetic enzyme activity and biomass accumulation, further confirming the metabolic advantages of red light [99]. Increased CO2 uptake during photosynthesis also elevated pH [100], consistent with findings in microalgae showing that red light enhances CO2 assimilation under nutrient-limited conditions [55]. The reduced abundance of PGLP, a key photorespiration enzyme, implied lower photorespiration intensity and more efficient substrate use [101,102,103].
Nitrogen metabolism genes were more abundant in bacteria than in algae (Figure 5a), indicating bacterial dominance in nitrogen turnover. Notably, Red enhanced the expression of genes involved in ammonia, nitrite, and nitrate transformation [36], thereby accelerating nitrogen cycling. Red also facilitated assimilation via nitrate reduction and enabled nitrate uptake without extra energy input [104]. In contrast, conventional nitrification (hao, nxr) and anammox (hzs, hdh) genes were not detected (Figure 5a). This absence, common in RASs and algal–bacterial consortia, suggests that assimilation pathways outcompeted transformation routes. Despite this, no nitrogenous compounds accumulated, confirming that assimilation exceeded conversion in maintaining stability.

3.4.2. Alterations in Key Metabolic Pathways

Level 3 pathways provided insights into the synergistic metabolism of the system [105]. Sixteen pathways were identified (Figure 5b), with nitrogen removal mainly supported by bacterial–algal cooperation in amino acid biosynthesis and nutrient uptake via ATP-binding cassette (ABC) transporters. Carbon metabolism and oxidative phosphorylation were also critical [106,107].
Compared to other groups, Red significantly increased gene abundances associated with biofilm formation, quorum sensing, ABC transporters, amino acid biosynthesis, and carbon metabolism (Figure 5b). These enhancements indicate that Red not only improved nutrient assimilation but also reinforced microbial cooperation. Specifically, Red promoted substance exchange within biofilms [95,108], stimulated quorum sensing to enhance EPS secretion [109] facilitated substrate transport via ABC transporters [110,111], and supported amino acid biosynthesis through intracellular nitrogen conversion [112]. Collectively, these mechanisms strengthened metabolic coupling between algae and bacteria. In addition, recent studies highlighted that red light-driven mitochondrial redox signaling modulates transcriptional networks, linking ROS signaling with enhanced carbon metabolism and nitrogen turnover [113]. Together, these findings confirm that Red reinforced multi-pathway cooperation in bacteria–algae symbiosis, thereby achieving higher nitrogen removal efficiency.

3.5. Reconstruction of Nitrogen Metabolism Pathways

3.5.1. Enhanced Photosynthesis Efficiency by Supplementary Light

Bacteria and algae collaboratively removed ammonium nitrogen in water via a shared metabolic pathway within the biofilm. A metabolic interaction model was proposed by integrating photosynthesis, nitrogen metabolism, and EPSs (Figure 6).
Consistent with previous studies, Red showed superior performance in promoting photosynthesis compared to Blue or White. Specifically, algae converted light energy into ATP and NADPH, which were subsequently transformed into stable chemical energy and used to drive nitrogen removal. The higher efficiency under red light may be attributed to its wavelength alignment with the absorption peaks of chlorophyll a (~660–680 nm), which directly excites both Photosystem II and Photosystem I reaction centers, thereby improving excitation efficiency [48,114]. In contrast, blue light is mainly absorbed by chlorophyll b and carotenoids and requires energy transfer to chlorophyll a before being utilized by PSI and PSII, which involves additional steps and is generally less efficient [47]. Supporting this, recent work has shown that blue light leads to lower photosynthetic efficiency in cyanobacteria due to limitations in phycobilisome-mediated light capture [49]. Through the Calvin cycle, the fixed CO2 was further assimilated into organic compounds, providing carbon skeletons for nitrogen assimilation. Red also significantly boosted the expression of genes related to CO2 fixation, thereby enhancing the efficiency of the Calvin cycle and promoting the coupling between carbon fixation and nitrogen metabolism [115,116]. This implies that the superior photosynthetic efficiency under red light contributed directly to higher nitrogen removal performance.

3.5.2. Impact of Lighting on Bacterial Nitrogen Metabolism

Light exposure affected the microbial community of nitrifying bacteria, with a common inhibition of AOB. However, NOB were enriched under Red in this study, which enabled a rapid conversion of nitrite to nitrate. Additionally, genes linked to nitrogen metabolism in bacteria exhibited a higher abundance level. For example, an abundant ammonia nitrogen metabolic pathway was observed in bacteria compared to microalgae (Figure S12), indicating that bacterial assimilation of ammonium nitrogen was the primary nitrogen removal pathway, with a small amount of ammonium nitrogen being converted to nitrite and nitrate.

3.5.3. Role of EPSs in Substrate Exchange and Biofilm Formation

EPSs served as a critical medium for bacterial–algal interactions, facilitating biofilm formation and initiating nitrogen removal [39]. Composed primarily of polysaccharides and proteins, EPSs promoted electron transfer, gas exchange with the external environment, and protection of the microbial consortium against pollutants in RASs [38,117]. Additionally, EPSs provided supplementary carbon sources and electron donors under low C/N conditions [89], which alleviated the stress of limited organic carbon and reduced potential light-induced damage. The structural properties of EPSs also enhanced mass transfer efficiency and supported biomass accumulation, thereby improving carrier utilization and stabilizing nitrogen removal [118,119]. These findings highlight that EPSs not only mediated substrate exchange but also created a favorable microenvironment for both microbial activity and long-term biofilm stability.

4. Conclusions

This study systematically investigated the influence of different light wavelengths on nitrogen removal, microbial community composition, and functional gene expression in bacterial–algal biofilm reactors (BABRs) within recirculating aquaculture systems (RASs). The major findings are summarized as follows:
(1)
Nitrogen removal performance: Red consistently enhanced ammonia removal efficiency and stabilized the nitrification pathway, particularly under high nitrogen loading, by enabling faster recovery and suppressing nitrite accumulation.
(2)
Microbial community structure: Red enriched functional algal and bacterial groups such as Scenedesmus, Bosea, and Nitrospirota, which supported efficient carbon fixation, nitrification, and denitrification.
(3)
EPS and gene regulation: Red promoted EPS secretion and increased the abundance of genes related to photosynthesis, biofilm formation, and nitrogen metabolism, thereby strengthening microbial cooperation and system stability.
(4)
Mechanistic insight: The superiority of red light was attributed to its spectral alignment with chlorophyll a, enhancing oxygen release, supporting nitrifiers, and maintaining balanced ammonia → nitrite → nitrate conversion.
Limitations and future directions—This study used single-system experiments without biological triplicates, and photosynthetic parameters such as oxygen evolution were not directly measured. These limitations may reduce the robustness of statistical comparisons. Future work will include replicated reactor trials, direct monitoring of photosynthetic activity, and pilot-scale applications to further validate the role of red light in enhancing nitrogen removal efficiency in RASs.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/pr13113594/s1.

Author Contributions

W.J. and Q.L. organized the framework of the paper. Q.H., Y.Z., and M.L. contributed to the collection and analysis of experimental data and participated in the writing of this paper. J.L., Y.L., Q.A., and L.W. took part in data analysis. L.J., S.W., and X.Y. proposed the study idea and revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was financially supported by the open fund of “China (Guangxi)-ASEAN Key Laboratory of Comprehensive Exploitation and Utilization of Aquatic Germplasm Resources, Ministry of Agriculture” (No. GXKEYLA-2023-01-3), “Chongqing Municipality Fisheries Science and Technology Innovation Alliance Project”(No. CQFTIU202502-2), “Fundamental Research Funds for the Central Universities” (No. SWU-KR22006), and Project 202310635031 supported by National Training Program of Innovation and Entrepreneurship for Undergraduates.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

Authors Linyuan Jiang, Junneng Liang, Luting Wen, Yijian Li, Qiuwei Ao and Xueming Yang were employed by the company Guangxi Academy of Fishery Sciences. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Processes 13 03594 g001
Figure 1. A schematic diagram of the BABR setup. Four series of BABRs were established, each was exposed to different light conditions: red, blue, a mixture of red and blue, and white light, at an intensity of 3000 lux. Each BABR comprises two 7 L fixed-bed reactors arranged in series, with each reactor filled with 40 polyethylene carrier balls. The dark blue, green, and light blue lines represent the influent, effluent, and post-filtered effluent, respectively. Simulated wastewater was pumped into four aquaculture tanks at a constant flow rate of 3.6 L/day using a peristaltic pump. After the two reactors, the processed water was recirculated back to the aquaculture tanks through a plankton screen at a pore size of 0.064 mm.
Figure 1. A schematic diagram of the BABR setup. Four series of BABRs were established, each was exposed to different light conditions: red, blue, a mixture of red and blue, and white light, at an intensity of 3000 lux. Each BABR comprises two 7 L fixed-bed reactors arranged in series, with each reactor filled with 40 polyethylene carrier balls. The dark blue, green, and light blue lines represent the influent, effluent, and post-filtered effluent, respectively. Simulated wastewater was pumped into four aquaculture tanks at a constant flow rate of 3.6 L/day using a peristaltic pump. After the two reactors, the processed water was recirculated back to the aquaculture tanks through a plankton screen at a pore size of 0.064 mm.
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Figure 2. Variations in water quality parameters throughout the experimental period: (a) ammonia nitrogen (NH4+-N), (b) nitrite nitrogen (NO2−-N), (c) nitrate nitrogen (NO3−-N), (d) COD/TIN ratio, (e) pH, and (f) phosphate (PO43−-P). The vertical black line indicates the division of experimental phases, which are delineated based on the gradient of ammonia concentrations as described in Table S1. The dashed line marks the time of alkalinity addition, as detailed in Text S7.
Figure 2. Variations in water quality parameters throughout the experimental period: (a) ammonia nitrogen (NH4+-N), (b) nitrite nitrogen (NO2−-N), (c) nitrate nitrogen (NO3−-N), (d) COD/TIN ratio, (e) pH, and (f) phosphate (PO43−-P). The vertical black line indicates the division of experimental phases, which are delineated based on the gradient of ammonia concentrations as described in Table S1. The dashed line marks the time of alkalinity addition, as detailed in Text S7.
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Figure 3. Biomass and EPSs of bacterial–algal biofilm at each experimental stage: (a) bacterial–algal biomass, (b) chlorophyll-a content, and EPS features (including TB-composition and PN/PS ratios) under (c) red light, (d) blue light, (e) red and blue mixed light, and (f) white light. TB, LB, PN, and PS represent tightly bound EPSs, loosely bound EPSs, protein, and polysaccharide, respectively.
Figure 3. Biomass and EPSs of bacterial–algal biofilm at each experimental stage: (a) bacterial–algal biomass, (b) chlorophyll-a content, and EPS features (including TB-composition and PN/PS ratios) under (c) red light, (d) blue light, (e) red and blue mixed light, and (f) white light. TB, LB, PN, and PS represent tightly bound EPSs, loosely bound EPSs, protein, and polysaccharide, respectively.
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Figure 4. Community composition of microorganisms within biofilms. Microorganisms in the three main domains (algae, bacteria, and archaea) were investigated. The pie charts were constructed at the phylum level, and only phyla with a relative abundance greater than 1% were shown. Genera with a relative abundance greater than 1% were visualized as dot plots, where dot color represents the phylum level and dot size indicates relative abundance. Unclassified taxa at the respective classification level were labeled as ‘unclassified,’ and those with a relative abundance less than 1% were grouped as ‘others’.
Figure 4. Community composition of microorganisms within biofilms. Microorganisms in the three main domains (algae, bacteria, and archaea) were investigated. The pie charts were constructed at the phylum level, and only phyla with a relative abundance greater than 1% were shown. Genera with a relative abundance greater than 1% were visualized as dot plots, where dot color represents the phylum level and dot size indicates relative abundance. Unclassified taxa at the respective classification level were labeled as ‘unclassified,’ and those with a relative abundance less than 1% were grouped as ‘others’.
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Figure 5. Key nitrogen removal genes and metabolic pathways in the bacteria–algae biofilm. The gene abundance was calculated using the Reads Per Kilobase per Million mapped reads (RPKM) method. (a) Gene expression profiles related to nitrogen metabolism and photosynthesis. (b) Metabolic pathways of bacteria–algae consortia identified at KEGG Level 3.
Figure 5. Key nitrogen removal genes and metabolic pathways in the bacteria–algae biofilm. The gene abundance was calculated using the Reads Per Kilobase per Million mapped reads (RPKM) method. (a) Gene expression profiles related to nitrogen metabolism and photosynthesis. (b) Metabolic pathways of bacteria–algae consortia identified at KEGG Level 3.
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Figure 6. Proposed nitrogen removal mechanism in the bacteria–algae biofilm with arrows indicating material and energy flow and process interactions. Microalgae remove nitrogen through assimilation. Meanwhile, bacteria convert ammonia nitrogen directly into nitrate. EPS mediates this process by facilitating metabolic pathways such as photosynthesis, material exchange, carbon metabolism, and nitrogen metabolism.
Figure 6. Proposed nitrogen removal mechanism in the bacteria–algae biofilm with arrows indicating material and energy flow and process interactions. Microalgae remove nitrogen through assimilation. Meanwhile, bacteria convert ammonia nitrogen directly into nitrate. EPS mediates this process by facilitating metabolic pathways such as photosynthesis, material exchange, carbon metabolism, and nitrogen metabolism.
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Table 1. Summary of nitrogen removal performance, intermediate products, and biomass parameters under different light treatments in RAS-BABRs.
Table 1. Summary of nitrogen removal performance, intermediate products, and biomass parameters under different light treatments in RAS-BABRs.
MetricRedBlueRed–BlueWhite
NH4+-N removal (Stage III, %)82.8 ± 6.6 a47.0 ± 30.6 b74.0 ± 17.0 a46.5 ± 24.8 b
NH4+-N removal (Stage IV, %)52.2 ± 41.1 a22.7 ± 56.8 b50.1 ± 44.2 a3.4 ± 75.1 c
Peak NO2−-N (Stage III mg·L−1)0.120 a0.8310.3340.387
Peak NO2−-N (Stage IV mg·L−1)0.775 a5.3175.0482.843
Final NO3−-N (Stage III mg·L−1)14.7720.7415.1922.22
Final NO3−-N (Stage IV mg·L−1)62.7470.4768.3270.61
Biomass (Stage IV mg·ball−1)61.6732.6731.6740.67
Chl-a (Stage IV mg·ball−1)0.5060.2010.2260.278
Notes: Different superscript letters (a–c) indicate significant differences among treatments within the same stage (p < 0.05). Ammonia removal efficiency is expressed as the mean ± SD across each operating stage. Peak NO2−-N and final NO3−-N values represent the highest and last-day observations, respectively, and are shown as single-point values without statistical testing. Biomass and chlorophyll a were measured at the end of Stage IV.
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MDPI and ACS Style

Jiang, W.; Li, Q.; Jiang, L.; Huang, Q.; Liang, J.; Zhou, Y.; Lv, M.; Wen, L.; Li, Y.; Ao, Q.; et al. Red Light Enhanced Nitrogen Removal Efficiency by Bacterial–Algae Biofilm Reactor in Recirculating Aquaculture Systems. Processes 2025, 13, 3594. https://doi.org/10.3390/pr13113594

AMA Style

Jiang W, Li Q, Jiang L, Huang Q, Liang J, Zhou Y, Lv M, Wen L, Li Y, Ao Q, et al. Red Light Enhanced Nitrogen Removal Efficiency by Bacterial–Algae Biofilm Reactor in Recirculating Aquaculture Systems. Processes. 2025; 13(11):3594. https://doi.org/10.3390/pr13113594

Chicago/Turabian Style

Jiang, Wenqiang, Qingfeng Li, Linyuan Jiang, Qunxin Huang, Junneng Liang, Yating Zhou, Mingji Lv, Luting Wen, Yijian Li, Qiuwei Ao, and et al. 2025. "Red Light Enhanced Nitrogen Removal Efficiency by Bacterial–Algae Biofilm Reactor in Recirculating Aquaculture Systems" Processes 13, no. 11: 3594. https://doi.org/10.3390/pr13113594

APA Style

Jiang, W., Li, Q., Jiang, L., Huang, Q., Liang, J., Zhou, Y., Lv, M., Wen, L., Li, Y., Ao, Q., Wang, S., & Yang, X. (2025). Red Light Enhanced Nitrogen Removal Efficiency by Bacterial–Algae Biofilm Reactor in Recirculating Aquaculture Systems. Processes, 13(11), 3594. https://doi.org/10.3390/pr13113594

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