Synergistic effects of soybean oligosaccharides and Chlorella pyrenoidosa on water quality and microbial community structure in biofloc system

Synergistic effects of soybean oligosaccharides and Chlorella pyrenoidosa on water quality and microbial community structure in biofloc system | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Synergistic effects of soybean oligosaccharides and Chlorella pyrenoidosa on water quality and microbial community structure in biofloc system Hangxian Zhou, Mengsha Lou, Cruz Clement de, Jie Wei, Mingwei Tao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6527949/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract This study explored the synergistic effects of soybean oligosaccharides (SBOS) and Chlorella pyrenoidosa on water quality and microbial community structure of aquaculture effluent in a biofloc system. Five experimental treatments were designed including CON group (control, no treatment), GLU group (glucose), SBOS group (2.5% SBOS and 97.5% glucose), CP group (glucose and Chlorella pyrenoidosa ), and CS group (2.5% SBOS, 97.5% glucose and Chlorella pyrenoidosa ). Chlorella pyrenoidosa were included at a concentration of 5.37×10⁵ cells/mL for selected treatments. Each treatment had 5 replicates, and C/N ratio was 15. Over the nine-day experimental period, combination of SBOS and Chlorella pyrenoidosa demonstrated significant synergistic effects on water quality improvement and biofloc formation ( P < 0.05). Specifically, in CS group, nitrate concentrations were significantly reduced on day 1, nitrite nitrogen concentrations exhibited a marked reduction on day 5, and both nitrite and total nitrogen concentrations showed significant reductions on day 7 compared to GLU group ( P < 0.05). Biofloc volume (FV) in CS group showed a significant increase on day 3 compared to both CON and GLU groups ( P < 0.05). Turbidity (NTU) was significantly lower in all experimental groups compared to CON group ( P < 0.05). Compared with other experimental groups, the abundance of Aeromonasaceae decreased significantly, and Bacillus and Mycobacteria increased significantly in CS group, which contributed to the enhanced nitrogen cycling and degradation of organic matter degradation pathway ( P < 0.05). These findings suggest that SBOS and Chlorella pyrenoidosa exhibit synergistic effects in treatment of effluent in biofloc system, and efficiently remove nitrogen and optimize microbial community structure. soybean oligosaccharides Chlorella pyrenoidosa microflora synergistic effects biofloc Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 1. Introduction In recent years, the escalation of high-nitrogen wastewater sourced from industry and agriculture has intensified challenges in water management and has posed a serious threat to aquatic ecosystems (Conley et al., 2009 ). Biofloc technology (BFT), a microbial-based water purification technique, is extensively utilized in aquaculture due to its efficient nitrogen processing and cost-effectiveness (Avnimelech, 2009 ). This technology enhances the proliferation of heterotrophic bacteria through the addition of carbon sources (Avnimelech, 1999 ), effectively reduces excess nitrogen while ensuring the safety of aquatic life (Huang et al., 2023 ). BFT is widely recognized as a sustainable and effective method for treating aquaculture effluents (Wandana et al., 2024 ). The health and growth of aquatic animal are directly influenced by microorganisms (Li et al., 2024 ), with changes in the microbial community structure in the water environment being closely linked to their overall health(Bruno et al., 2023 ). The immune system of aquatic animals can be activated by the complex interactions among microorganisms in the BFT system (Rajeev et al., 2023 ) with numerous studies consistently demonstrating its significant positive effects on the immune performance and overall health of aquatic animals ((El-Hawarry et al., 2021 ; Flores-Valenzuela et al., 2021 ; Yu et al., 2023 ). Functional oligosaccharides, serving as prebiotics, effectively enhance intestinal morphology and improve the microbial community structure in aquatic animals (Rajeev et al., 2021 ). Moreover, the incorporation of oligosaccharides into feed has been extensively reported to modulate the intestinal microbial community structure (Jia et al., 2017 ), enhanced intestinal functionality (Yang et al., 2018 ), and boost immune performance (Hahor et al., 2019 ). Microorganism regulation in BFT systems is facilitated by addition of organic carbon sources, with oligosaccharides emerging as a viable option. Research has demostrasted that incorporating oligosaccharides as a carbon source in BFT systems enhances the intestinal microbiota of cultured aquatic animals by increasing beneficial bacteria and reducing harmful ones (Kishawy et al., 2020 ). Substituting 1%-5% of glucose with soybean oligosaccharides (SBOS) in BFT systems significantly improve the growth of Carassius auratus and promoted the proliferation of beneficial intestinal bacteria such as Actinobacteria (Qiu et al., 2023 ). Furthermore, replacing glucose with 2.5% SBOS in high-nitrogen water effectively optimized the microbial community structure, fostering the growth of beneficial bacteria (Zhou et al., 2024a ). These findings indicate that oligosaccharides not only optimize bacterial communities in aquatic systems but also enhance the proliferation of beneficial bacteria growth (Zhou et al., 2024b ). Therefore, the addition of SBOS may exert a positive influence on bacterial communities in aquaculture environments. Microalgae possess a notable ability to reduce ammonia nitrogen (NH 4 + -N) and nitrite nitrogen (NO 2 − -N) in water, similar to heterotrophic bacteria (Nie et al., 2020 ), while also lowering the phosphate levels (Holanda et al., 2022 ). Additionally, polysaccharides from microalgae are metabolized and utilized as binders to facilitate flocculation (Watanabe et al., 2008 ). Yun et al. ( 2022 ) demonstrated that algal populations exhibited significantly greater proliferation compared to bacterial populations in shrimp farming systems, with algae being more profoundly affected by interactions with zooplankton and other associated organisms. These findings align with the recommendation by Ramanan et al. ( 2016 ) that algae-based BFT systems are more suitable for shrimp farming due to their enhanced ecological interactions and functional advantages over bacteria-based systems. Similarly, studies had demonstrated that nitrates and phosphates in high nitrogen effluents can be effectively reduced by using Chlorella vulgaris alone, highlighting the significant potential of microalgae treatment in mitigating water eutrophication (Pekkoh et al., 2022 ). Currently, research on BFT systems predominantly emphasizes bacterial interactions, while the functional role and contributions of algae remain insufficiently studied. This disparity highlights the need for a more balanced investigation to understand the underlying synergistic interactions between bacteria and algae within these systems. Symbiotic interactions between microalgae and bacteria, both direct and indirect, accelerate microalgae growth, enhance wastewater removal, and promote microalgal flocculation (Ramanan et al., 2016 ). Several studies have indicated that bacteria in aerobic-activated sludge secrete abundant extracellular polysaccharides whose viscosity and rheological properties facilitate the capture of microalgae, thereby forming microalgae-bacteria bio-communities that effectively enhance the system’s capacity to adsorb nitrogen and phosphorus from the water (Seviour et al., 2012 , 2009 ; Wang et al., 2022 ). The polysaccharides secreted by microalgae promote the production of extracellular polymeric substances (EPS), a mixture composed of proteins, polysaccharides, humic-like substances, and nucleic acids (Wingender et al., 1999 ), which significantly influence the flocculating, settling, and dewatering properties of flocs (Dai et al., 2020 ; Kang et al., 2023 ; Meng et al., 2023 ). Therefore, the interactions between microalgae and bacteria are now regarded as a sustainable and more commercially viable approach (Subashchandrabose et al., 2011 ). The competitive or synergistic interactions among different bacteria play an important role in influencing water quality. The addition of SBOS has been shown to significantly increase the abundance of specific bacterial communities, thereby optimizing the microbial structure of the water and enhancing bacterial-microalgal interactions. However, research focusing on optimizing bacterial community structures in water through the synergistic effects of carbon sources (particularly oligosaccharides) and algae remains limited. To address this gap, the present study aims to enhance the efficiency and practical application of BFT by investigating the combined effects of SBOS and Chlorella pyrenoidosa on high-nitrogen effluent purification and their influence on the microbial community in the water. 2. Materials and methods 2.1. Experimental Materials The water effluent was collected from an aquaculture farm in Huzhou (China). The water contained 10.24 mg/L of total nitrogen (TN), 1.34 mg/L of NH 4 + -N, 0.54 mg/L of NO 2 -N, and 8.12 mg/L of nitrate nitrogen (NO 3 − -N). Anhydrous glucose (AR, 99%) was purchased from China National Pharmaceutical Group Chemical Reagent Co., Ltd. SBOS (BR, 99%) was obtained from Shanghai Yuanye Bio-Technology Co., Ltd. The Chlorella pyrenoidosa algal liquid (8.6×10 7 cell/mL) was sourced from Hainan Yuanquan Biotechnology Co., Ltd. Thirty high-density polyethylene (HDPE) tanks with a capacity of 300 L were used, each initially filled with 150 L of aquaculture effluent. No water exchange was performed during the 9-day experimental period, which was conducted under natural light. Five treatments were established: control group (Control), with no carbon source added; glucose group (GLU), receiving glucose; SBOS group (SBOS), receiving 2.5% SBOS and 97.5% glucose; Chlorella pyrenoidosa group (CP), receiving glucose and Chlorella pyrenoidosa at 5.37×10 5 cells/mL; Chlorella pyrenoidosa + SBOS group (CS), receiving 2.5% SBOS and 97.5% glucose, along with Chlorella pyrenoidosa at 5.37×10 5 cells/mL. In all treatments except the control, these additions served as carbon sources, with the C/N ratio adjusted to 15:1 (Avnimelech, 1999 ) and each treatment had 5 replicates. 2.3. Water quality parameters Key water quality parameters, including water temperature, pH, and dissolved oxygen (DO) of the water were monitored daily throughout the experimental using a YSI Pro Plus portable multi-parameter. Water samples (100 mL) were collected at the start of the experiment (day 0) and subsequently at two-day intervals (days 1, 3, 5, 7, and 9). Each water samples were filtered through a 0.45 µm membrane filter and nutrient concentrations, including NH 4 + -N, NO 2 − -N, NO 3 − -N, and TN in the water were measured using a QC8500 flow injection water quality analyzer. Biofloc volume (FV) was quantified using an Imhoff cone according to the method described by Avnimelech and Kochba ( 2009 ). A 1,000 mL water sample was allowed to settle naturally for 30 minutes in the Imhoff cone, which was positioned on a perfectly level surface, and the settled biofloc volume was recorded. Water Turbidity (NTU) was measured using a WTW 430 turbidity meter. 2.4. Microbial community analysis At the start of the experiment (designated as the F0 group) and on day 9, 100 mL water samples were collected from 5 experimental tanks, filtered through a 0.22 µm membrane until visible particulates adhered to the membrane surface. The membranes were then placed in sterile centrifuge tubes and stored at -80 ℃ for microbial diversity analysis. The DNA extraction and amplification were performed by Shanghai Meiji Bio-Pharmaceuticals Technology Co., Ltd., which conducted the 16S rDNA gene abundance sequencing analysis using Illumina sequencing. Specific kits and methods refer to previous studies (Deng et al., 2023 ). Primers 799F (5′-AACMGGATTAGATACCCKG-3′) and 1193R (5′-ACGTCATCCCCACCTTCC-3′) were used to amplify the hypervariable regions V5-V7, thereby avoiding the excessive influence of chloroplasts on the sequencing results in the V3-V4 regions. In phylogenetic and population genetic studies, Operational Taxonomic Unit (OTU) refers to a standard unit of classification, used to simplify the classification labeling process during analysis. The experimental results are presented at the phylum and genus levels, with OTUs clustered using a 97% similarity threshold. Community richness was reflected by ACE and Chao indices, community diversity was indicated by Shannon and Simpson indices, and community coverage was represented by the coverage index. 2.5. Statistical Analysis IBM SPSS Statistics 26.0 was used for data analysis. One-way ANOVA was used to analyze the experimental data first, and then the synergistic effects of SBOS and Chlorella pyrenoidosa were analyzed by two-way ANOVA. A result is considered significant only both analysis methods show significance. Experimental results were expressed as mean ± standard deviation (mean ± SD). For high-throughput sequencing data, the Kruskal-Wallis rank-sum test was used for multiple comparisons. P < 0.05 was considered statistically significant. 3. Results 3.1. Changes in Water Quality Throughout the experiment, the temperature range from 27°C to 29°C (Fig. 1 ). The DO content in the experimental groups fluctuated significantly at the beginning of the experiment, dropping rapidly to its lowest point on day 1, which was significantly lower than that of the CON group ( P < 0.05). The content of ammonia nitrogen (NH 4 + -N) initially decreased, then increased, peaking on day 3, and subsequently decreased again. In contrast, the ammonia nitrogen content of the control group (CON) decreased and then stabilized (Fig. 2 -a). On day 1, all groups experienced a rapid decline in NH 4 + -N levels. By day 3, differences among the experimental groups were not statistically significant ( P > 0.05), though the NH 4 + -N remained significantly higher than the CON group ( P < 0.05) (Table 1 , Table S1 ). By day 5, the NH 4 + -N content in the CS group was notably lower than those in the SBOS and GLU groups, with the latter showing higher content than the CP group ( P < 0.05). A Significant synergistic effect between the SBOS and Chlorella pyrenoidosa on day 7, the NH 4 + -N content in CS group was significantly higher than GLU group on days 7 and 9 ( P < 0.05). However, NH 4 + -N levels in all experimental groups were already in the healthy range. Table 1 The effects of chlorella pyrenoidosa and soybean oligosaccharide on ammonia nitrogen Algae Carbon source Groups Day 1 Day 3 Day 5 Day 7 Day 9 - GLU GLU 0.17 ± 0.07 1.70 ± 0.21 0.24 ± 0.06 Aa 0.02 ± 0.00 b 0.08 ± 0.00 B - GLU + SBOS SBOS 0.21 ± 0.08 1.86 ± 0.36 0.17 ± 0.02 Ab 0.03 ± 0.01 a 0.08 ± 0.00 B Chlorella pyrenoidosa GLU CP 0.15 ± 0.06 1.66 ± 0.32 0.17 ± 0.08 Ba 0.03 ± 0.00 b 0.10 ± 0.01 A Chlorella pyrenoidosa GLU + SBOS CS 0.19 ± 0.12 1.58 ± 0.35 0.12 ± 0.04 Bb 0.03 ± 0.01 a 0.09 ± 0.01 A P -value Soybean oligosaccharide 0.31 0.78 0.04 0.05 0.81 Chlorella pyrenoidosa 0.64 0.28 0.03 0.47 0.00 S×C 0.99 0.41 0.61 0.01 0.41 Notes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. A, B, a, b Mean values with different letters were significantly different ( P < 0.05). The content of nitrite nitrogen (NO 2 − -N) followed a similar fluctuating pattern to NH 4 + -N, with periods of increase and decrease observed throughout the experiment (Fig. 2 -b). On day 3, NO 2 − -N content in the GLU and SBOS groups was significantly lower than CP and CS groups ( P < 0.05) (Table 2 , Table S2). A distinct interaction between the SBOS and Chlorella pyrenoidosa significantly altered NO 2 − -N concentrations on day 5, which significantly reduced the NO₂⁻-N content in the SBOS group ( P < 0.05). By day 7, the NO 2 − -N content in the SBOS group remained higher than that GLU group, while all experimental groups recorded higher levels than the control group ( P < 0.05). Table 2 The effects of chlorella pyrenoidosa and soybean oligosaccharide on Nitrite Nitrogen Algae Carbon source Groups Day 1 Day 3 Day 5 Day 7 Day 9 - GLU GLU 0.59 ± 0.20 0.15 ± 0.07 B 1.18 ± 0.24 A 0.17 ± 0.05 Ab 0.05 ± 0.03 - GLU+ SBOS SBOS 0.52 ± 0.31 0.16 ± 0.03 B 1.56 ± 0.18 A 0.29 ± 0.07 Aa 0.06 ± 0.03 Chlorella pyrenoidosa GLU CP 0.55 ± 0.39 0.34 ± 0.05 A 0.77 ± 0.24 B 0.17 ± 0.04 Bb 0.07 ± 0.02 Chlorella pyrenoidosa GLU+ SBOS CS 0.44 ± 0.45 0.25 ± 0.06 A 0.63 ± 0.34 B 0.15 ± 0.05 Ba 0.06 ± 0.02 P -value Soybean oligosaccharide 0.57 0.17 0.32 0.04 0.87 Chlorella pyrenoidosa 0.70 0.00 0.00 0.01 0.51 S×C 0.92 0.06 0.04 0.01 0.26 Notes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. A, B, a, b Mean values with different letters were significantly different ( P < 0.05). The content of nitrate nitrogen (NO 3 − -N) initially decreased and then increased (Fig. 2 -c, Table 3 , Table S3). The NO 3 − -N content remained relatively stable in the CON group, consistently higher than in the experimental groups ( P < 0.05). A significant synergistic effect between SBOS and Chlorella pyrenoidosa was observed in reducing NO 3 − -N levels on day 1, with the concentration in CS group significantly lower than other experimental groups ( P < 0.05). By day 5, the CP and CS groups exhibited higher NO 3 − -N content compared to the GLU and SBOS groups ( P 0.05). Table 3 The effects of chlorella pyrenoidosa and soybean oligosaccharide on Nitrate Nitrogen Algae Carbon source Groups Day 1 Day 3 Day 5 Day 7 Day 9 - GLU GLU 1.47 ± 0.10 Aa 0.35 ± 0.06 B 2.84 ± 0.72 B 5.37 ± 0.81 6.03 ± 0.44 - GLU+ SBOS SBOS 1.43 ± 0.05 Ab 0.28 ± 0.06 B 2.13 ± 0.42 B 4.92 ± 0.73 5.66 ± 0.82 Chlorella pyrenoidosa GLU CP 0.58 ± 0.06 Ba 0.53 ± 0.24 A 3.68 ± 0.95 A 5.60 ± 0.96 5.89 ± 0.90 Chlorella pyrenoidosa GLU+ SBOS CS 0.26 ± 0.04 Bb 0.46 ± 0.18 A 3.19 ± 1.03 A 5.03 ± 0.60 5.70 ± 0.66 P -value Soybean oligosaccharide 0.00 0.35 0.12 0.16 0.40 Chlorella pyrenoidosa 0.00 0.02 0.02 0.63 0.87 S×C 0.00 0.94 0.77 0.87 0.79 Notes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. A, B, a, b Mean values with different letters were significantly different ( P < 0.05). The content of total nitrogen (TN) showed a similar trend to NO 3 − -N, with an initial decrease followed by an increase (Fig. 2 -d, Table 4 , Table S4). The TN content in the CON group remained relatively stable and was significantly higher than that in the experimental groups throughout the experiment ( P < 0.05). On day 1, the TN content was significantly higher in the GLU group compared to the SBOS group, and the CP group recorded higher content than the CS group ( P 0.05). Table 4 The effects of chlorella pyrenoidosa and soybean oligosaccharide on Total Nitrogen Algae Carbon source Groups Day 1 Day 3 Day 5 Day 7 Day 9 - GLU GLU 5.07 ± 0.69 Aa 3.30 ± 0.37 4.60 ± 0.52 7.15 ± 0.86 B 8.43 ± 0.30 - GLU+ SBOS SBOS 3.63 ± 1.17 Ab 3.41 ± 0.47 4.24 ± 0.33 8.71 ± 1.10 B 8.18 ± 0.80 Chlorella pyrenoidosa GLU CP 3.71 ± 0.51 Ba 3.29 ± 0.60 4.53 ± 0.46 9.40 ± 1.15 A 8.08 ± 1.05 Chlorella pyrenoidosa GLU+ SBOS CS 3.41 ± 0.57 Bb 3.05 ± 0.21 4.53 ± 0.32 8.59 ± 0.88 A 8.18 ± 0.95 P -value Soybean oligosaccharide 0.02 0.73 0.35 0.42 0.84 Chlorella pyrenoidosa 0.04 0.37 0.56 0.03 0.63 S×C 0.12 0.38 0.35 0.02 0.64 Notes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. A, B, a, b Mean values with different letters were significantly different ( P < 0.05). 3.2. Changes in the biofloc formation Biofloc was not observed in the CON group during the experiment. Biofloc formation began in all experimental groups on day 2. The volume of the bioflocs gradually increased, reaching a peak on day 3 and then decreased (Fig. 3 -a). On day 3, there was a significant interaction between SBOS and Chlorella pyrenoidosa ( P < 0.05) (Table 5 , Table S5). Additionally, the results on days 3 and 9 were similar, the FV content in each experimental group was significantly higher than that in control group ( P < 0.05). The FV content in SBOS group was significantly higher than in GLU group ( P 0.05). Table 5 The effects of chlorella pyrenoidosa and soybean oligosaccharide on Floc Volume Algae Carbon source Groups Day 1 Day 3 Day 5 Day 7 Day 9 - GLU GLU - 35.00 ± 12.37 Ab 8.40 ± 2.88 3.26 ± 0.73 2.38 ± 0.19 Ab - GLU+ SBOS SBOS - 79.00 ± 11.92 Aa 10.80 ± 1.79 3.13 ± 0.38 3.20 ± 0.39 Aa Chlorella pyrenoidosa GLU CP - 44.80 ± 3.42 Bb 7.76 ± 3.27 3.75 ± 0.48 1.69 ± 0.19 Bb Chlorella pyrenoidosa GLU+ SBOS CS - 47.40 ± 11.61 Ba 8.00 ± 4.69 3.30 ± 0.67 2.85 ± 0.23 Ba P -value Soybean oligosaccharide - 0.00 0.39 0.28 0.00 Chlorella pyrenoidosa - 0.03 0.26 0.23 0.00 S×C - 0.00 0.48 0.56 0.17 Notes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. A, B, a, b Mean values with different letters were significantly different ( P < 0.05). The NTU in each group initially increased and then decreased, with the control group showing a smaller decrease (Fig. 3 -b). On day 1, the NTU in the SBOS group was significantly higher than GLU group ( P 0.05), but all groups exhibited significantly lower NTU compared to the control group ( P < 0.05). Table 6 The effects of chlorella pyrenoidosa and soybean oligosaccharide on Turbidity Algae Carbon source Groups Day 1 Day 3 Day 5 Day 7 Day 9 - GLU GLU 45.74 ± 6.38 b 34.1 ± 13.25 9.65 ± 4.00 4.35 ± 0.87 5.82 ± 1.60 - GLU+ SBOS SBOS 67.84 ± 7.99 a 35.64 ± 17.98 9.02 ± 1.77 3.95 ± 1.53 5.71 ± 1.54 Chlorella pyrenoidosa GLU CP 54.82 ± 9.92 b 37.17 ± 21.28 8.95 ± 1.71 3.51 ± 1.18 4.48 ± 0.41 Chlorella pyrenoidosa GLU+ SBOS CS 55.4 ± 9.18 a 27.99 ± 3.88 5.47 ± 2.07 3.67 ± 1.98 7.22 ± 2.14 P -value Soybean oligosaccharide 0.01 0.59 0.09 0.86 0.08 Chlorella pyrenoidosa 0.66 0.75 0.08 0.40 0.91 S×C 0.01 0.45 0.23 0.67 0.06 Notes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. A, B, a, b Mean values with different letters were significantly different ( P < 0.05). 3.3. The microbial diversity and abundance in the water of BFT system The results of microbial community diversity index for each group are shown in Table 7 . Compared to the control group, the community diversity (Simpson index) was significantly increased, and community richness (OTU) was decreased in GLU group ( P < 0.05). The community richness (ACE and Chao indexes) was significantly reduced in SBOS group compared to the control group ( P < 0.05). The community diversity (Shannon index) was significantly lowered in CP group compared to the control group ( P < 0.05). Both the CS and CP groups significantly enhanced community diversity (Shannon indexes) compared to the GLU and SBOS groups ( P < 0.05). These results indicate that the experimental groups effectively modulated bacterial community diversity and impacted the microbial community structure. The Venn diagram also showed that the control group had more unique bacterial communities compared to the experimental groups (Fig. 4 ). Table 7 Microbial diversity and abundance in bioflocs Groups ace chao shannon coverage OTU F0 1379.00±78.91 1311.00±67.16 4.66±0.07* 0.99±0.00 1166.00±63.04 CON 1606.00±359.50 1538.00±331.20 4.30±0.38 a 0.99±0.00 1364.00±328.50 a GLU 1238.00±205.00 1186.00±196.10 3.17±0.37 cd 0.99±0.00 1014.00±172.90 b SBOS 1168.00±203.90 1128.00±187.50 2.96±0.39 d 0.99±0.00 945.60±164.20 b CP 1426.00±136.80 1358.00±136.10 3.63±0.38 bc 0.99±0.00 1176.00±129.00 ab CS 1448.00±91.87 1383.00±80.60 3.78±0.29 b 0.99±0.00 1195.00±61.22 ab Algae Carbon source Groups ace chao coverage shannon OTU - GLU GLU 1238.00±205.00 1186.00±196.10 0.99±0.00 3.17±0.37 b 1014.00±172.90 - GLU+SBOS SBOS 1168.00±203.90 1128.00±187.50 0.99±0.00 2.96±0.39 b 945.60±164.20 Chlorella pyrenoidosa GLU CP 1426.00±136.80 1358.00±136.10 0.99±0.00 3.63±0.38 a 1176.00±129.00 Chlorella pyrenoidosa GLU+SBOS CS 1448.00±91.87 1383.00±80.60 0.99±0.00 3.78±0.29 a 1195.00±61.22 P -value Soybean oligosaccharide 0.93 0.86 0.77 0.90 0.79 Chlorella pyrenoidosa 0.09 0.15 0.77 0.00 0.07 S×C 0.64 0.74 0.81 0.23 0.70 Notes: The upper section presents the pairwise comparison results between the CON and F0 groups, the middle section shows the results of Kruskal-Wallis rank-sum test, and the lower section displays the interaction effects between SBOS and Chlorella pyrenoidosa . F0: original water sample collected before the experiment started; CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and Chlorella pyrenoidosa added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and Chlorella pyrenoidosa added. S×C: the interaction between soybean oligosaccharide and Chlorella pyrenoidosa . Data are presented as means ± SD, n = 5. a, b Mean values with different letters were significantly different ( P < 0.05). * indicates a significant difference between CON group and F0 group. 3.4. The microbial community composition in the BFT system Compared to the F0 group, the abundance of Actinobacteriota increased in the CON group, with an overall similar structural proportion. The microbial community structures in all experimental groups were effectively altered in comparison to the CON group. At the phylum level, Actinobacteriota and Proteobacteria dominated in the CON group. In the experimental groups, the top five dominant bacteria were Bacteroidota, Firmicutes, Actinobacteriota, and Proteo (Fig. 5 ). Additionally, the GLU and SBOS groups had a higher abundance of Bacteroidota and a lower abundance of Actinobacteriota when compared to the CP and CS groups. At the genus level, all experimental groups effectively increased the abundance of Flavobacterium and Bacillus while decreasing the abundance of hgel_clade and unclassified_o__Saccharimonadales (Fig. 6 ). 3.5. Differences in Bacterial Community Composition in BFT Systems In this experiment, the microbial community structure of the experimental group was significantly different from CON group ( P < 0.01), suggesting that the experimental groups significantly altered the bacterial community structure in the water (Fig. 7 -a). Similarly, significant differences were observed among the microbial communities of the experimental groups ( P < 0.05), with the CS group exhibiting a greater degree of divergence from the other groups (Fig. 7 -b). The microbial community structure in the water was significantly affected by different treatments in the experimental groups. At the phylum level, the abundance of Bacteroidota was significantly increased in GLU, SBOS, and CP treatments compared to the CON group ( P < 0.05) (Fig. 8 -a). The abundance of Actinobacteriota was significantly reduced in all experimental groups ( P < 0.05) (Fig. 8 -b), while the abundance of Firmicutes was significantly increased ( P < 0.05) (Fig. 8 -c). At the genus level, the abundance of Flavobacterium and Bacillus increased, and the abundance of hgel_clade decreased in experimental groups generally ( P < 0.05) (Fig. 8 -d). The abundance of Terrimonas was significantly increased and the abundance of Chryseobacterium , Parvibaculum , and Neochlamydia was significantly decreased in the SBOS group compared to the GLU group ( P < 0.05) (Fig. 8 -e). The abundance of Saprospiraceae , Pseudomonas , and Chlamydiales was significantly increased and the abundance of Chryseobacterium was significantly decreased in the CP group compared to the GLU group ( P < 0.05) (Fig. 8 -f). The abundance of Saprospiraceae , norank_f__ 67 − 14, and Limnobacter was significantly increased and the abundance of Flavobacterium decreased in the CS group compared to the GLU group ( P < 0.05) (Fig. 8 -g). Significant community differences were also observed among experimental groups. The abundance of Hydrogenophaga , Mycobacterium , Saprospiraceae , and NS9_marine_group were significantly increased in the CP group compared to the SBOS group ( P < 0.05) (Fig. 8 -h). Similarly, the abundance of Phenylobacterium , Pseudomonas , Hyphomicrobium , and Acidibacter was significantly increased in the CS group compared to the SBOS group ( P < 0.05) (Fig. 8 -i). A significant increase in the abundance of Roseomonas , Phenylobacterium , Sphingomonas , and Solimonadaceae in CS group compared to the CP group ( P < 0.05) (Fig. 8 -j). Linear Discriminant Analysis Effect Size (LefSe) analysis showed that Myxococcota was significantly enriched in the GLU group. The Bacteroidota was significantly enriched in the SBOS group, and Firmicutes was significantly enriched in CS group ( P < 0.05) (Fig. 9 -a). At the genus level, LDA value of 3.5 was used. Flavobacterium was significantly enriched in the SBOS group, Hydrogenophaga was significantly enriched in CP group, and Bacillus and Mycobacterium were significantly enriched in CS group ( P < 0.05) (Fig. 9 -b). 3.6. FAPROTAX prediction FAPROTAX, a manually constructed database, is considered one of the most reliable methods for predicting microbial ecological functions (Zhang et al., 2023 ). Microbial function predictions based on the experimental results showed that the functional structure of the microorganisms was significantly altered in the experimental groups. The function involved in degrading aromatic hydrocarbons was significantly increased in the SBOS group compared to the GLU group ( P < 0.05) (Fig. 10 -a). The function related to nitrogen cycle conversion was significantly increased in the CP group ( P < 0.05) (Figs. 10 -b), while functions related to symbionts and nitrogen cycle conversion were significantly upregulated in the CS group ( P < 0.05) (Fig. 10 -c). The function of chemoheterotrophy was significantly increased in the SBOS group compared to the CP group ( P < 0.05) (Fig. 10 -d). The nitrogen cycle conversion ability was significantly increased in the CS group compared to the SBOS group ( P < 0.05) (Fig. 10 -e), and the abilities for nitrogen fixation and cellulolysis were significantly increased in the CS group compared to the CP group ( P < 0.05) (Fig. 10 -f). 3.7. The interactions of microorganisms in BFT systems and their impact on the environment The distribution of samples and species was illustrated by the collinearity network (Fig. 11 -a). The results showed that the proportion of shared bacteria between the experimental groups and the CON group was low. The microbial compositions of GLU and SBOS groups were quite comparable, whereas those of CS and CP groups also shared similarities. Flavobacterium and Bacillus were connected with every experimental group. Rhizobiales was connected only with SBOS group, and Mycobacterium was connected only with CS group. The univariate network diagram demonstrates the positive and negative correlations between bacterial communities, with red lines indicating positive correlations, green lines indicating negative correlations, and the thickness of the lines representing the correlation coefficient (Fig. 11 -b). The results denoted a strong degree of correlation among bacteria in the BFT system. All lines connected to Flavobacterium were green, indicating negative correlations with bacteria such as Mycobacterium . In contrast, most lines linked to Bacillus were red, representing positive correlations, except for a single green line, which highlighted a negative correlation with hgcl_clade . Overall, the red lines predominated over the green ones, suggesting a general trend of mutual promotion among bacterial communities within the system. The correlation between experimental bacterial communities and various environmental factors was also demonstrated (Fig. 12 ), with FV showing positive correlations with NH 4 + -N and NO 2 − -N, and negative correlations with NO 3 − -N, TN, and NTU. Flavobacterium showed a significant positive correlation with FV ( P < 0.01) and significant negative correlations with NO 3 − -N, TN, and NTU ( P < 0.05). Bacillus exibited significant positive correlations with NH 4 + -N and FV, and significant neagitve correlation with NO 3 − -N, TN, and NTU ( P < 0.05). Hgel_clade was significantly negatively correlated with FV and pH, while showing a significant positive correlation with NTU ( P < 0.05). 4. Discussion Bacteria and microalgae are crucial components of aquatic ecosystems, playing a crucial role in enhancing system stability (Vale et al., 2023 ). This stability is particularly important in BFT systems, where maintaining stable and healthy bacterial communities can effectively reduce harmful nitrogen levels in the water and positively influence the growth of aquatic animals (Lu et al., 2014 ). Harmful nitrogen in water can be effectively reduced by the combined action of microalgae and heterotrophic bacteria (Mahari et al., 2024 ). Additionally, various types of aquaculture effluents can be effectively treated through synergistic interaction of algae and bacteria (Lee et al., 2015 ; Li et al., 2023 ; Zhang et al., 2020 ), which also establishes symbiotic relationships within the water (Bhatt et al., 2024 ). In this symbiosis, bacteria supply nutrients such as nitrogen to algae, while algae provide fixed organic carbon to bacteria (Cho et al., 2015 ). Although microalgae and carbon sources are often used independently, their simultaneous application can overcome the limitations of individual use, optimizing bacterial communities and improving water purification(Shi et al., 2024 ). During the experiment, DO and pH were observed to decline rapidly on day 1, followed by a sharp increase on day 3. Simultaneously, NH 4 + -N content increased on day 3 before decreasing, whereas NO 2 − -N nitrogen content increased on the day 5 and subsequently decline. These fluctuation may be attributed to the growth and proliferation of bacteria in the water. Following the addition of carbon sources, heterotrophic bacteria proliferate rapidly and metabolize, consuming large amounts of DO and producing acidic substances (Deng et al., 2021 ). This process creates a temporary hypoxic environment and causes rapid drop in pH. Under these conditions, the activity of nitrifying bacteria was inhibited, leading to the accumulation of NH 4 + -N and NO 2 − -N (Crab et al., 2012 ). Subsequently, as the biofloc system stabilizes, DO levels gradually recover, allowing the nitrification process to resume. Simultaneously, as the carbon is gradually depleted, bacterial metabolites transition from acidic to neutral or alkaline, resulting in a gradual increase in pH (Espeleta et al., 2017 ). Additionally, the results indicate that the CS group outperformed the SBOS and CP groups in reducing nitrogen, suggesting that the combined use of SBOS and Chlorella pyrenoidosa may be more effective in removing nitrogen compared to their separate use. The CS group consistently maintained a relatively low content of nitrogen and NTU levels while sustaining high FV content. In contrast, the CP group was found to be less effective than the CS group in reducing nitrogen content and maintaining system stability. This may be attributed to the partial digestion absorption of SBOS by beneficial bacteria using specialized enzymes (Roberfroid et al., 2010 ). This process increases the abundance of beneficial and core bacteria while reducing harmful bacteria through bacterial competition, which promotes microalgae-bacteria interactions. The types of bacteria are crucial for microalgae-bacteria interactions (Crespo et al., 2023 ). For instance, the growth rate of microalgae ( Chlorella sorokiniana ) is significantly enhanced by Azospirillum brasilense and Bacillus pumilus through the secretion of growth hormones or the provision of essential nutrients (Amavizca et al., 2017 ). This demonstrates that the yield and quality of biomass can be significantly improved by specific bacteria in aquaculture systems (Kang et al., 2021 ). Conversely, c bacteria may inhibit the growth of specific microalgae; forexample, the growth of Nannochloropsis gaditana is significantly inhibited by Muricauda sp., likely due to bacterial density and the chemical substances they release (Han et al., 2016 ). Previous studies also highlighted that an optimized bacterial community can enhance algal-bacterial symbiosis (Kim et al., 2014 ), thereby enhancing the overall productivity of aquatic systems. In this experiment, α-diversity index in the experimental groups was lower than CON group. This reduction in diversity and richness of the microbial community may be due to the addition of carbon sources. Microbial diversity and richness were observed to decrease in high-carbon environments, and heterotrophic bacteria were found to rapidly adapt to the high-carbon conditions and proliferate quickly (Chen et al., 2023 ). The abundance of Terrimonas , a bacterium with a unique nitrogen fixation system belonging to the Rhizobiales , was found to be significantly increased by the addition of SBOS (Huang et al., 2022 ). Meanwhile, the abundance of the harmful bacterium Chryseobacterium was significantly decreased by SBOS (Zamora et al., 2012 ). This is consistent with previous findings, where the number of harmful bacteria such as Vibrio in the intestines of crucian carp was effectively reduced by a small amount of SBOS as a carbon source (Qiu et al., 2023 ), and the abundance of harmful bacteria like Aeromonadaceae in the water was also reduced by a small amount of fructooligosaccharides as a carbon source (Zhou et al., 2024b ). Similarly, the abundance of beneficial bacteria such as Bacillus in the intestines of Nile Tilapia ( Oreochromis niloticus ) was significantly increased by using mannanoligosaccharides as a carbon source in BFT, while the abundance of harmful bacteria such as Vibrio and Aeromonas was reduced (Kishawy et al., 2020 ). This aligns with the previous hypothesis that the addition of a small amount of SBOS as a carbon source can effectively increase the abundance of beneficial bacteria in the water while reducing the abundance of harmful bacteria. A previous study also demonstrated that the addition of Chlorella pyrenoidosa significantly increased the abundance of Saprospiraceae and Pseudomonas . Saprospiraceae , a core genus in activated sludge, is known for its ability to metabolize glucose, galactose, and specific proteins (Wu et al., 2019 ). Free-living Pseudomonas has also been shown to effectively remove nitrogen from the water (Yi et al., 2023 ). Chlorella pyrenoidosa may supply these microorganisms with glucose, galactose, or specific amino acids and proteins (Ummat et al., 2024 ), thereby promoting their growth. The abundance of bacteria that can effectively degrade nitrogen in the water, such as Hydrogenophaga (Fan et al., 2023 ), Mycobacterium (Dong et al., 2022 ), and Saprospiraceae (McIlroy and Nielsen, 2014 ), was significantly increased in the CP group compared to the SBOS group. Nitrogen accumulation was more effectively reduced under low C/N conditions by a BFT system with algal-bacterial symbiosis compared to a system dominated solely by bacteria (Markou et al., 2023 ). Similarly, the CS group exhibited the same increase in Pseudomonas and Hydrogenophaga as seen in the CP group compared to the SBOS group, while a significant increase in the abundance of Roseomonas and Sphingomonas was observed in the CS group compared to the CP group. Research has shown that an inverse relationship exists between Roseomonas and nitrite content, indicating that nitrite reduction is positively influence by Roseomonas (Mang et al., 2024 ). Sphingomonas has also been found to effectively reduce the accumulation of NH 4 + -N and nitrite in aquaculture (Yun et al., 2019 ). The significant increase in Solimonadaceae may be related to the presence of HDPE materials (Nguyen et al., 2021 ), and the combined effects of SBOS and Chlorella pyrenoidosa on the microbial community may drive this change, although the underlying mechanisms remain unclear. LEfSe analysis revealed that differentially enriched bacteria were present in each experimental group. The observed changes in bacterial communities may have been influenced by these differentially enriched bacteria. Flavobacterium was found to be significantly enriched in the SBOS group, Hydrogenophaga was significantly enriched in the CP group, and Bacillus was significantly enriched in the CS group. This result is consistent with the environmental factor analysis, where nitrogen transformation in the water was significantly influenced by the bacteria affected by each experimental group. Additionally, the overall functionality of the microbial community was considerably impacted by the significantly enriched bacteria helping maintain its balance and stability (Guo et al., 2022 ). The microbial function prediction results for each experimental group showed that nitrite-related metabolism was significantly increased in the CP group, which can reduce toxic nitrite levels (Wang et al., 2020 ). The ability for nitrogen fixation was significantly increased in the CS group compared to the CP group, possibly due to the significant enrichment and high abundance of Mycobacterium in the CS group. Mycobacterium has been found to have a positive impact on nitrogen fixation (Pajares and Bohannan, 2016 ). Compared to the SBOS group, nitrite-related metabolism was significantly increased in the CS group, likely due to the symbiosis between Chlorella pyrenoidosa and many denitrifying bacteria, greatly enhancing this function. The correlation between environmental factors and bacterial communities shows that Flavobacterium , as a core genus, was negatively correlated with NH 4 + -N and NO 3 − -N, and positively correlated with NO 2 − -N. This suggests that NH 4 + -N is effectively converted by Flavobacterium , and the positive correlation between Flavobacterium and FV indicates that harmful nitrogen in the water is efficiently converted into biofloc. These findings aligns with previous research, where NO 3 − -N is effectively converted to NO 2 − -N by Flavobacterium , a denitrifying bacterium (Bernardet and Bowman, 2006 ). A significant positive correlation was observed between Bacillus and NH 4 + -N and FV, and a significant negative correlation was found between Bacillus and NO 3 − -N. This may be due to sufficient organic matter for Bacillus growth being provided by NH 4 + -N, and biofloc formation being promoted by the physiological activities of Bacillus , effectively reducing NO 3 − -N content (He et al., 2023 ). HgcI_clade , a bacterium used to gauge water quality (Tong et al., 2023 ), shows no significant differences with the three forms of nitrogen but is significantly negatively correlated with FV. This may be due to substances such as nitrogen being removed from the water by biofloc, inhibiting the growth of hgcI_clade . The changes in microbial community structure caused by SBOS and Chlorella pyrenoidosa indicate that microbial activity and water quality are closely linked. 5. Conclusion The research demonstrates that both SBOS and Chlorella pyrenoidosa , whether used individually or in combination, effectively promote the growth of heterotrophic bacteria, facilitating nitrogen absorption and biofloc formation. The addition of SBOS significantly increases the abundance of Flavobacterium , while the addition of Chlorella pyrenoidosa significantly increases the abundance of Hydrogenophaga . When used together, they further boosted the abundance of Bacillus and Mycobacterium , promoting the expression of nitrogen cycle-related functional genes. This highlights a synergistic effect between SBOS and Chlorella pyrenoidosa in promoting the growth of beneficial bacteria, enhancing nitrogen absorption, and contributing positively to the reduction of nitrogen accumulation and the stability of the aquatic ecosystem in aquaculture environments. Declarations Funding This work was supported by Zhejiang Province Agricultural Major Technology Cooperative Promotion Plan ( 2022XTTGSC01 ); The Project Supported by Zhejiang Provincial Natural Science Foundation of China ( LTGN23C190002 ). Competing interests The authors declare no competing interests Author Contributions Hangxian Zhou : Conceptualization, Methodology, Formal analysis, Resources, Data curation, Writing – original draft. Mengsha Lou : Conceptualization, Methodology, Writing – original draft. Clement de Cruz : Writing – review & editing. Jie Wei : Conceptualization, Methodology, Writing – original draft. Mingwei Tao : Conceptualization, Methodology, Writing – original draft. Jianhua Zhao : Formal analysis. Rongfei Zhang : Formal analysis. Qiyou Xu : Conceptualization, Writing – review & editing, Supervision. Data availability statement The data that support the findings of this study are available from the corresponding author, upon reasonable request. 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BMC Vet Res 8, 77. https://doi.org/10.1186/1746-6148-8-77 Zhang, B., Li, W., Guo, Y., Zhang, Z., Shi, W., Cui, F., Lens, P.N.L., Tay, J.H., 2020. Microalgal-bacterial consortia: From interspecies interactions to biotechnological applications. Renewable and Sustainable Energy Reviews 118, 109563. https://doi.org/10.1016/j.rser.2019.109563 Zhang, J., Xiao, Z., Li, D., Wang, X., Lu, C., Du, Z., Li, B., Wang, Jinhua, Wang, Jun, Zhu, L., 2023. Effect of flumetsulam alone and coexistence with polyethylene microplastics on soil microbial carbon and nitrogen cycles: Elucidation of bacterial community structure, functional gene expression, and enzyme activity. Journal of Hazardous Materials 460, 132367. https://doi.org/10.1016/j.jhazmat.2023.132367 Zhou, H., Tao, M., Wei, J., Zhao, J., Xu, Q., 2024a. Effect of replacing glucose with soybean oligosaccharides on microbial community structure in biofloc system (in Chinese). 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GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/39f5b88c12f59a9ca86b1faa.jpg"},{"id":82035938,"identity":"4e3ee9b5-fa6e-4aff-bf78-37f781a82479","added_by":"auto","created_at":"2025-05-06 08:09:41","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66318,"visible":true,"origin":"","legend":"\u003cp\u003eThe variations in Ammonia Nitrogen (a), Nitrite Nitrogen (b), Nitrate Nitrogen (c), and Total Nitrogen (d)\u003c/p\u003e\n\u003cp\u003eNote: CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/cad10f1d0337df54507dbeac.jpg"},{"id":82035939,"identity":"b4738a79-605d-41e0-ab32-1978c8b1b56f","added_by":"auto","created_at":"2025-05-06 08:09:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33599,"visible":true,"origin":"","legend":"\u003cp\u003eThe variations in Floc Volume (a) and Turbidity (b)\u003c/p\u003e\n\u003cp\u003eNote: CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/c924d0dfb22abf54c2e4d888.jpg"},{"id":82034979,"identity":"6abf844f-c381-49e8-bc51-03e3d14b6cd6","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":34648,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagram of microbial OTU in water\u003c/p\u003e\n\u003cp\u003eNote: F0: original water sample collected before the experiment started; CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/6199860a78232519272faa7e.jpg"},{"id":82034974,"identity":"b587e8a0-185d-46a3-9805-5202f1ef0e68","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":63013,"visible":true,"origin":"","legend":"\u003cp\u003eCommunity structure histogram at phylum level\u003c/p\u003e\n\u003cp\u003eNote: F0: original water sample collected before the experiment started; CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003eadded; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/66f38d097904a97f97ba50af.jpg"},{"id":82034978,"identity":"7764f8b2-7545-4b10-be15-0f1ab131b618","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":54084,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of community structure at genus level\u003c/p\u003e\n\u003cp\u003eNote: F0: original water sample collected before the experiment started; CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/eb4005a9b731b773dc003471.jpg"},{"id":82035940,"identity":"7d9f65b5-a281-49b8-81a9-e1ac0337d911","added_by":"auto","created_at":"2025-05-06 08:09:41","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":67102,"visible":true,"origin":"","legend":"\u003cp\u003ePCoA analysis of bacterial community (a): PCoA analysis of all treatment groups and initial samples; (b): PCoA analysis of all experimental groups\u003c/p\u003e\n\u003cp\u003eNote: F0: original water sample collected before the experiment started; CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/9357bd6561fc5b0985cdee3b.jpg"},{"id":82034982,"identity":"c28f38eb-b437-4b22-b4ae-9e6434908c85","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":156178,"visible":true,"origin":"","legend":"\u003cp\u003eDifferences of bacterial community at gene level\u003c/p\u003e\n\u003cp\u003eNote: CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. (a), (b), (c): The most abundant bacterial phylum with significant differences at the phylum level (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). (d), (e), (f), (g), (h), (i), (j): The most abundant bacterial genera with significant differences at the genus level in pairwise comparison (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/e88a8672dcdbc41b73a9f711.jpg"},{"id":82034981,"identity":"fb775e2b-4407-4474-b1c0-3f3b9bc81a15","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":242908,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial community taxa with significant intergroup differences were identified through LEfSe analysis. (a): LEfSe analysis the differential bacteria between phylum to genus level. (b): histogram of LDA values at the genus level (LDA \u0026gt; 3.5)\u003c/p\u003e\n\u003cp\u003eNote: CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. (a): The most abundant bacterial phylum with significant differences at the phylum level (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). (d), (e), (f), (g), (h), (i), (j): The most abundant bacterial genera with significant differences at the genus level in pairwise comparison (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/b3432752fa9a4d49f6ee0de0.jpg"},{"id":82035941,"identity":"08866c6e-5ed7-4512-911c-ef9360fbc5a1","added_by":"auto","created_at":"2025-05-06 08:09:41","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":96378,"visible":true,"origin":"","legend":"\u003cp\u003eThe most abundant functional differences in bacterial communities in pairwise comparison\u003c/p\u003e\n\u003cp\u003eNote: CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added.\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/b733c5f2832ca98c7d3956f3.jpg"},{"id":82034985,"identity":"a3d8265c-6f22-4c73-be50-63d84c9c7b8b","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":196857,"visible":true,"origin":"","legend":"\u003cp\u003eBacterial Community Correlation Network. (a) The collinear network between bacteria in different groups (b): Interactions between bacteria and bacteria in all experimental groups and the red line represents a positive impact, the green line represents a negative impact\u003c/p\u003e","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/624979a79dba3ecf3f8c538c.jpg"},{"id":82036403,"identity":"1570e2b9-1672-4944-becf-cc2b073662d9","added_by":"auto","created_at":"2025-05-06 08:17:41","extension":"jpg","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":60857,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of correlation between environmental factors and bacterial community\u003c/p\u003e","description":"","filename":"12.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/e2cb3983ccf1e6e8acaf1212.jpg"},{"id":82037430,"identity":"431aa72c-61c1-43dc-87c4-6ba26054cb69","added_by":"auto","created_at":"2025-05-06 08:25:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2559340,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/bbb6ae77-1fa7-4825-99db-e3bb626914f7.pdf"},{"id":82034977,"identity":"0059c727-0e5a-4ac7-bc3f-b49eeb358d13","added_by":"auto","created_at":"2025-05-06 08:01:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27079,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable.docx","url":"https://assets-eu.researchsquare.com/files/rs-6527949/v1/4ad0432edbd0ce5eebd7b8b1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Synergistic effects of soybean oligosaccharides and Chlorella pyrenoidosa on water quality and microbial community structure in biofloc system","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIn recent years, the escalation of high-nitrogen wastewater sourced from industry and agriculture has intensified challenges in water management and has posed a serious threat to aquatic ecosystems (Conley et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Biofloc technology (BFT), a microbial-based water purification technique, is extensively utilized in aquaculture due to its efficient nitrogen processing and cost-effectiveness (Avnimelech, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). This technology enhances the proliferation of heterotrophic bacteria through the addition of carbon sources (Avnimelech, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), effectively reduces excess nitrogen while ensuring the safety of aquatic life (Huang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). BFT is widely recognized as a sustainable and effective method for treating aquaculture effluents (Wandana et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe health and growth of aquatic animal are directly influenced by microorganisms (Li et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), with changes in the microbial community structure in the water environment being closely linked to their overall health(Bruno et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The immune system of aquatic animals can be activated by the complex interactions among microorganisms in the BFT system (Rajeev et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) with numerous studies consistently demonstrating its significant positive effects on the immune performance and overall health of aquatic animals ((El-Hawarry et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Flores-Valenzuela et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Functional oligosaccharides, serving as prebiotics, effectively enhance intestinal morphology and improve the microbial community structure in aquatic animals (Rajeev et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Moreover, the incorporation of oligosaccharides into feed has been extensively reported to modulate the intestinal microbial community structure (Jia et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), enhanced intestinal functionality (Yang et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and boost immune performance (Hahor et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMicroorganism regulation in BFT systems is facilitated by addition of organic carbon sources, with oligosaccharides emerging as a viable option. Research has demostrasted that incorporating oligosaccharides as a carbon source in BFT systems enhances the intestinal microbiota of cultured aquatic animals by increasing beneficial bacteria and reducing harmful ones (Kishawy et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Substituting 1%-5% of glucose with soybean oligosaccharides (SBOS) in BFT systems significantly improve the growth of \u003cem\u003eCarassius auratus\u003c/em\u003e and promoted the proliferation of beneficial intestinal bacteria such as \u003cem\u003eActinobacteria\u003c/em\u003e (Qiu et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, replacing glucose with 2.5% SBOS in high-nitrogen water effectively optimized the microbial community structure, fostering the growth of beneficial bacteria (Zhou et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024a\u003c/span\u003e). These findings indicate that oligosaccharides not only optimize bacterial communities in aquatic systems but also enhance the proliferation of beneficial bacteria growth (Zhou et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). Therefore, the addition of SBOS may exert a positive influence on bacterial communities in aquaculture environments.\u003c/p\u003e \u003cp\u003eMicroalgae possess a notable ability to reduce ammonia nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) and nitrite nitrogen (NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) in water, similar to heterotrophic bacteria (Nie et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), while also lowering the phosphate levels (Holanda et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, polysaccharides from microalgae are metabolized and utilized as binders to facilitate flocculation (Watanabe et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Yun et al. (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) demonstrated that algal populations exhibited significantly greater proliferation compared to bacterial populations in shrimp farming systems, with algae being more profoundly affected by interactions with zooplankton and other associated organisms. These findings align with the recommendation by Ramanan et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) that algae-based BFT systems are more suitable for shrimp farming due to their enhanced ecological interactions and functional advantages over bacteria-based systems. Similarly, studies had demonstrated that nitrates and phosphates in high nitrogen effluents can be effectively reduced by using \u003cem\u003eChlorella vulgaris\u003c/em\u003e alone, highlighting the significant potential of microalgae treatment in mitigating water eutrophication (Pekkoh et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Currently, research on BFT systems predominantly emphasizes bacterial interactions, while the functional role and contributions of algae remain insufficiently studied. This disparity highlights the need for a more balanced investigation to understand the underlying synergistic interactions between bacteria and algae within these systems.\u003c/p\u003e \u003cp\u003eSymbiotic interactions between microalgae and bacteria, both direct and indirect, accelerate microalgae growth, enhance wastewater removal, and promote microalgal flocculation (Ramanan et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Several studies have indicated that bacteria in aerobic-activated sludge secrete abundant extracellular polysaccharides whose viscosity and rheological properties facilitate the capture of microalgae, thereby forming microalgae-bacteria bio-communities that effectively enhance the system\u0026rsquo;s capacity to adsorb nitrogen and phosphorus from the water (Seviour et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The polysaccharides secreted by microalgae promote the production of extracellular polymeric substances (EPS), a mixture composed of proteins, polysaccharides, humic-like substances, and nucleic acids (Wingender et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), which significantly influence the flocculating, settling, and dewatering properties of flocs (Dai et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kang et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Meng et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, the interactions between microalgae and bacteria are now regarded as a sustainable and more commercially viable approach (Subashchandrabose et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe competitive or synergistic interactions among different bacteria play an important role in influencing water quality. The addition of SBOS has been shown to significantly increase the abundance of specific bacterial communities, thereby optimizing the microbial structure of the water and enhancing bacterial-microalgal interactions. However, research focusing on optimizing bacterial community structures in water through the synergistic effects of carbon sources (particularly oligosaccharides) and algae remains limited. To address this gap, the present study aims to enhance the efficiency and practical application of BFT by investigating the combined effects of SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e on high-nitrogen effluent purification and their influence on the microbial community in the water.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Experimental Materials\u003c/h2\u003e \u003cp\u003eThe water effluent was collected from an aquaculture farm in Huzhou (China). The water contained 10.24 mg/L of total nitrogen (TN), 1.34 mg/L of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, 0.54 mg/L of NO\u003csub\u003e2\u003c/sub\u003e-N, and 8.12 mg/L of nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N). Anhydrous glucose (AR, 99%) was purchased from China National Pharmaceutical Group Chemical Reagent Co., Ltd. SBOS (BR, 99%) was obtained from Shanghai Yuanye Bio-Technology Co., Ltd. The \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e algal liquid (8.6\u0026times;10\u003csup\u003e7\u003c/sup\u003ecell/mL) was sourced from Hainan Yuanquan Biotechnology Co., Ltd.\u003c/p\u003e \u003cp\u003eThirty high-density polyethylene (HDPE) tanks with a capacity of 300 L were used, each initially filled with 150 L of aquaculture effluent. No water exchange was performed during the 9-day experimental period, which was conducted under natural light. Five treatments were established: control group (Control), with no carbon source added; glucose group (GLU), receiving glucose; SBOS group (SBOS), receiving 2.5% SBOS and 97.5% glucose; \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e group (CP), receiving glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e at 5.37\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/mL; \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u0026thinsp;+\u0026thinsp;SBOS group (CS), receiving 2.5% SBOS and 97.5% glucose, along with \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e at 5.37\u0026times;10\u003csup\u003e5\u003c/sup\u003e cells/mL. In all treatments except the control, these additions served as carbon sources, with the C/N ratio adjusted to 15:1 (Avnimelech, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and each treatment had 5 replicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Water quality parameters\u003c/h2\u003e \u003cp\u003eKey water quality parameters, including water temperature, pH, and dissolved oxygen (DO) of the water were monitored daily throughout the experimental using a YSI Pro Plus portable multi-parameter. Water samples (100 mL) were collected at the start of the experiment (day 0) and subsequently at two-day intervals (days 1, 3, 5, 7, and 9). Each water samples were filtered through a 0.45 \u0026micro;m membrane filter and nutrient concentrations, including NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and TN in the water were measured using a QC8500 flow injection water quality analyzer. Biofloc volume (FV) was quantified using an Imhoff cone according to the method described by Avnimelech and Kochba (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). A 1,000 mL water sample was allowed to settle naturally for 30 minutes in the Imhoff cone, which was positioned on a perfectly level surface, and the settled biofloc volume was recorded. Water Turbidity (NTU) was measured using a WTW 430 turbidity meter.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Microbial community analysis\u003c/h2\u003e \u003cp\u003eAt the start of the experiment (designated as the F0 group) and on day 9, 100 mL water samples were collected from 5 experimental tanks, filtered through a 0.22 \u0026micro;m membrane until visible particulates adhered to the membrane surface. The membranes were then placed in sterile centrifuge tubes and stored at -80 ℃ for microbial diversity analysis. The DNA extraction and amplification were performed by Shanghai Meiji Bio-Pharmaceuticals Technology Co., Ltd., which conducted the 16S rDNA gene abundance sequencing analysis using Illumina sequencing. Specific kits and methods refer to previous studies (Deng et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Primers 799F (5\u0026prime;-AACMGGATTAGATACCCKG-3\u0026prime;) and 1193R (5\u0026prime;-ACGTCATCCCCACCTTCC-3\u0026prime;) were used to amplify the hypervariable regions V5-V7, thereby avoiding the excessive influence of chloroplasts on the sequencing results in the V3-V4 regions. In phylogenetic and population genetic studies, Operational Taxonomic Unit (OTU) refers to a standard unit of classification, used to simplify the classification labeling process during analysis. The experimental results are presented at the phylum and genus levels, with OTUs clustered using a 97% similarity threshold. Community richness was reflected by ACE and Chao indices, community diversity was indicated by Shannon and Simpson indices, and community coverage was represented by the coverage index.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical Analysis\u003c/h2\u003e \u003cp\u003eIBM SPSS Statistics 26.0 was used for data analysis. One-way ANOVA was used to analyze the experimental data first, and then the synergistic effects of SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e were analyzed by two-way ANOVA. A result is considered significant only both analysis methods show significance. Experimental results were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). For high-throughput sequencing data, the Kruskal-Wallis rank-sum test was used for multiple comparisons. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Changes in Water Quality\u003c/h2\u003e \u003cp\u003eThroughout the experiment, the temperature range from 27\u0026deg;C to 29\u0026deg;C (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The DO content in the experimental groups fluctuated significantly at the beginning of the experiment, dropping rapidly to its lowest point on day 1, which was significantly lower than that of the CON group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThe content of ammonia nitrogen (NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N) initially decreased, then increased, peaking on day 3, and subsequently decreased again. In contrast, the ammonia nitrogen content of the control group (CON) decreased and then stabilized (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-a). On day 1, all groups experienced a rapid decline in NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N levels. By day 3, differences among the experimental groups were not statistically significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), though the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N remained significantly higher than the CON group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). By day 5, the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N content in the CS group was notably lower than those in the SBOS and GLU groups, with the latter showing higher content than the CP group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A Significant synergistic effect between the SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e on day 7, the NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N content in CS group was significantly higher than GLU group on days 7 and 9 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N levels in all experimental groups were already in the healthy range.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effects of \u003cem\u003echlorella pyrenoidosa\u003c/em\u003e and soybean oligosaccharide on ammonia nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003esource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDay 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDay 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDay 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDay 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDay 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eAa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u0026thinsp;+\u0026thinsp;SBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003eAb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003eBa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u0026thinsp;+\u0026thinsp;SBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eBb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eS\u0026times;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand Chlorella pyrenoidosa\u003c/em\u003e. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;5. A, B, a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe content of nitrite nitrogen (NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) followed a similar fluctuating pattern to NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, with periods of increase and decrease observed throughout the experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-b). On day 3, NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content in the GLU and SBOS groups was significantly lower than CP and CS groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S2). A distinct interaction between the SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e significantly altered NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N concentrations on day 5, which significantly reduced the NO₂⁻-N content in the SBOS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). By day 7, the NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content in the SBOS group remained higher than that GLU group, while all experimental groups recorded higher levels than the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effects of \u003cem\u003echlorella pyrenoidosa\u003c/em\u003e and soybean oligosaccharide on Nitrite Nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003esource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDay 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDay 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDay 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDay 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDay 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eAb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003csup\u003eAa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eBb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eBa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eS\u0026times;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand Chlorella pyrenoidosa\u003c/em\u003e. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;5. A, B, a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe content of nitrate nitrogen (NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N) initially decreased and then increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-c, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S3). The NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content remained relatively stable in the CON group, consistently higher than in the experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A significant synergistic effect between SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e was observed in reducing NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N levels on day 1, with the concentration in CS group significantly lower than other experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). By day 5, the CP and CS groups exhibited higher NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content compared to the GLU and SBOS groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), although no significant differences were observed on days 7 and 9 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effects of \u003cem\u003echlorella pyrenoidosa\u003c/em\u003e and soybean oligosaccharide on Nitrate Nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003esource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDay 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDay 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDay 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDay 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDay 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003csup\u003eAa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003csup\u003eAb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003csup\u003eBa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003eBb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eS\u0026times;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand Chlorella pyrenoidosa\u003c/em\u003e. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;5. A, B, a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe content of total nitrogen (TN) showed a similar trend to NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, with an initial decrease followed by an increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e-d, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table S4). The TN content in the CON group remained relatively stable and was significantly higher than that in the experimental groups throughout the experiment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). On day 1, the TN content was significantly higher in the GLU group compared to the SBOS group, and the CP group recorded higher content than the CS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The content of TN on days 3, 5, and 9 showed no significant differences among the experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effects of \u003cem\u003echlorella pyrenoidosa\u003c/em\u003e and soybean oligosaccharide on Total Nitrogen\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003esource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDay 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDay 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDay 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDay 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDay 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003csup\u003eAa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003csup\u003eAb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.10\u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003csup\u003eBa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.40\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.57\u003csup\u003eBb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eS\u0026times;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand Chlorella pyrenoidosa\u003c/em\u003e. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;5. A, B, a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Changes in the biofloc formation\u003c/h2\u003e \u003cp\u003eBiofloc was not observed in the CON group during the experiment. Biofloc formation began in all experimental groups on day 2. The volume of the bioflocs gradually increased, reaching a peak on day 3 and then decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-a). On day 3, there was a significant interaction between SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table S5). Additionally, the results on days 3 and 9 were similar, the FV content in each experimental group was significantly higher than that in control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The FV content in SBOS group was significantly higher than in GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). On day 5, no significant differences were observed among the experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effects of \u003cem\u003echlorella pyrenoidosa\u003c/em\u003e and soybean oligosaccharide on Floc Volume\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003esource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDay 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDay 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDay 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDay 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDay 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.37\u003csup\u003eAb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.40\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eAb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.00\u0026thinsp;\u0026plusmn;\u0026thinsp;11.92\u003csup\u003eAa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003csup\u003eAa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.80\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003csup\u003eBb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.76\u0026thinsp;\u0026plusmn;\u0026thinsp;3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003eBb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.40\u0026thinsp;\u0026plusmn;\u0026thinsp;11.61\u003csup\u003eBa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003csup\u003eBa\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eS\u0026times;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand Chlorella pyrenoidosa\u003c/em\u003e. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;5. A, B, a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe NTU in each group initially increased and then decreased, with the control group showing a smaller decrease (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e-b). On day 1, the NTU in the SBOS group was significantly higher than GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table S6). In the following days, there were no significant differences in NTU among the groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but all groups exhibited significantly lower NTU compared to the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effects of \u003cem\u003echlorella pyrenoidosa\u003c/em\u003e and soybean oligosaccharide on Turbidity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlgae\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbon\u003c/p\u003e \u003cp\u003esource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDay 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDay 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDay 5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDay 7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDay 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.74\u0026thinsp;\u0026plusmn;\u0026thinsp;6.38\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.65\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.84\u0026thinsp;\u0026plusmn;\u0026thinsp;7.99\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.64\u0026thinsp;\u0026plusmn;\u0026thinsp;17.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.82\u0026thinsp;\u0026plusmn;\u0026thinsp;9.92\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.17\u0026thinsp;\u0026plusmn;\u0026thinsp;21.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGLU+\u003c/p\u003e \u003cp\u003eSBOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.18\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.47\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.22\u0026thinsp;\u0026plusmn;\u0026thinsp;2.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eS\u0026times;C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eNotes: GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand Chlorella pyrenoidosa\u003c/em\u003e. Data are presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;5. A, B, a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3. The microbial diversity and abundance in the water of BFT system\u003c/h2\u003e \u003cp\u003eThe results of microbial community diversity index for each group are shown in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. Compared to the control group, the community diversity (Simpson index) was significantly increased, and community richness (OTU) was decreased in GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The community richness (ACE and Chao indexes) was significantly reduced in SBOS group compared to the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The community diversity (Shannon index) was significantly lowered in CP group compared to the control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Both the CS and CP groups significantly enhanced community diversity (Shannon indexes) compared to the GLU and SBOS groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These results indicate that the experimental groups effectively modulated bacterial community diversity and impacted the microbial community structure. The Venn diagram also showed that the control group had more unique bacterial communities compared to the experimental groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \n\u003cp\u003e\u003cstrong\u003eTable 7\u0026nbsp;\u003c/strong\u003eMicrobial diversity and abundance in bioflocs\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003eace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003echao\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003eshannon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003ecoverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003eOTU\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eF0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003e1379.00\u0026plusmn;78.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003e1311.00\u0026plusmn;67.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003e4.66\u0026plusmn;0.07*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003e1166.00\u0026plusmn;63.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eCON\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003e1606.00\u0026plusmn;359.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003e1538.00\u0026plusmn;331.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003e4.30\u0026plusmn;0.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003e1364.00\u0026plusmn;328.50\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eGLU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003e1238.00\u0026plusmn;205.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003e1186.00\u0026plusmn;196.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003e3.17\u0026plusmn;0.37\u003csup\u003ecd\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003e1014.00\u0026plusmn;172.90\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eSBOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003e1168.00\u0026plusmn;203.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003e1128.00\u0026plusmn;187.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003e2.96\u0026plusmn;0.39\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003e945.60\u0026plusmn;164.20\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eCP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003e1426.00\u0026plusmn;136.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003e1358.00\u0026plusmn;136.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003e3.63\u0026plusmn;0.38\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003e1176.00\u0026plusmn;129.00\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.2735%;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.1977%;\"\u003e\n \u003cp\u003e1448.00\u0026plusmn;91.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 6.4695%;\"\u003e\n \u003cp\u003e1383.00\u0026plusmn;80.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.6326%;\"\u003e\n \u003cp\u003e3.78\u0026plusmn;0.29\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 6.2521%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 6.5239%;\"\u003e\n \u003cp\u003e1195.00\u0026plusmn;61.22\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.6211%;\"\u003e\n \u003cp\u003eAlgae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.0017%;\"\u003e\n \u003cp\u003eCarbon source\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 2.9901%;\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003eace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003echao\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003ecoverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003eshannon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003eOTU\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.6211%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.0017%;\"\u003e\n \u003cp\u003eGLU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 2.9901%;\"\u003e\n \u003cp\u003eGLU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1238.00\u0026plusmn;205.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1186.00\u0026plusmn;196.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e3.17\u0026plusmn;0.37\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e1014.00\u0026plusmn;172.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.6211%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.0017%;\"\u003e\n \u003cp\u003eGLU+SBOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 2.9901%;\"\u003e\n \u003cp\u003eSBOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1168.00\u0026plusmn;203.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1128.00\u0026plusmn;187.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e2.96\u0026plusmn;0.39\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e945.60\u0026plusmn;164.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.6211%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.0017%;\"\u003e\n \u003cp\u003eGLU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 2.9901%;\"\u003e\n \u003cp\u003eCP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1426.00\u0026plusmn;136.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1358.00\u0026plusmn;136.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e3.63\u0026plusmn;0.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e1176.00\u0026plusmn;129.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.6211%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.0017%;\"\u003e\n \u003cp\u003eGLU+SBOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 2.9901%;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1448.00\u0026plusmn;91.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e1383.00\u0026plusmn;80.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.99\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e3.78\u0026plusmn;0.29\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e1195.00\u0026plusmn;61.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 12.6673%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 12.6673%;\"\u003e\n \u003cp\u003eSoybean oligosaccharide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 12.6673%;\"\u003e\n \u003cp\u003e\u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 12.6673%;\"\u003e\n \u003cp\u003eS\u0026times;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.7628%;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 3.5881%;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 4.1318%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 5.8171%;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: The upper section presents the pairwise comparison results between the CON and F0 groups, the middle section shows the results of Kruskal-Wallis rank-sum test, and the lower section displays the interaction effects between SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e. F0: original water sample collected before the experiment started; CON: control group without additives; GLU: glucose added; SBOS: 97.5% glucose and 2.5% soybean oligosaccharide added; CP: glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added; CS: 97.5% glucose, 2.5% soybean oligosaccharide, and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e added. S\u0026times;C: the interaction between soybean oligosaccharide \u003cem\u003eand\u003c/em\u003e \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e. Data are presented as means \u0026plusmn; SD, n = 5. a, b Mean values with different letters were significantly different (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). * indicates a significant difference between CON group and F0 group.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. The microbial community composition in the BFT system\u003c/h2\u003e \u003cp\u003eCompared to the F0 group, the abundance of \u003cem\u003eActinobacteriota\u003c/em\u003e increased in the CON group, with an overall similar structural proportion. The microbial community structures in all experimental groups were effectively altered in comparison to the CON group. At the phylum level, Actinobacteriota and Proteobacteria dominated in the CON group. In the experimental groups, the top five dominant bacteria were Bacteroidota, Firmicutes, Actinobacteriota, and Proteo (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Additionally, the GLU and SBOS groups had a higher abundance of Bacteroidota and a lower abundance of Actinobacteriota when compared to the CP and CS groups. At the genus level, all experimental groups effectively increased the abundance of \u003cem\u003eFlavobacterium\u003c/em\u003e and \u003cem\u003eBacillus\u003c/em\u003e while decreasing the abundance of \u003cem\u003ehgel_clade\u003c/em\u003e and \u003cem\u003eunclassified_o__Saccharimonadales\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Differences in Bacterial Community Composition in BFT Systems\u003c/h2\u003e \u003cp\u003eIn this experiment, the microbial community structure of the experimental group was significantly different from CON group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting that the experimental groups significantly altered the bacterial community structure in the water (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e-a). Similarly, significant differences were observed among the microbial communities of the experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with the CS group exhibiting a greater degree of divergence from the other groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e-b). The microbial community structure in the water was significantly affected by different treatments in the experimental groups. At the phylum level, the abundance of Bacteroidota was significantly increased in GLU, SBOS, and CP treatments compared to the CON group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-a). The abundance of Actinobacteriota was significantly reduced in all experimental groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-b), while the abundance of Firmicutes was significantly increased (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-c). At the genus level, the abundance of \u003cem\u003eFlavobacterium\u003c/em\u003e and \u003cem\u003eBacillus\u003c/em\u003e increased, and the abundance of \u003cem\u003ehgel_clade\u003c/em\u003e decreased in experimental groups generally (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-d). The abundance of \u003cem\u003eTerrimonas\u003c/em\u003e was significantly increased and the abundance of \u003cem\u003eChryseobacterium\u003c/em\u003e, \u003cem\u003eParvibaculum\u003c/em\u003e, and \u003cem\u003eNeochlamydia\u003c/em\u003e was significantly decreased in the SBOS group compared to the GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-e). The abundance of \u003cem\u003eSaprospiraceae\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, and \u003cem\u003eChlamydiales\u003c/em\u003e was significantly increased and the abundance of \u003cem\u003eChryseobacterium\u003c/em\u003e was significantly decreased in the CP group compared to the GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-f). The abundance of \u003cem\u003eSaprospiraceae\u003c/em\u003e, \u003cem\u003enorank_f__\u003c/em\u003e67\u0026thinsp;\u0026minus;\u0026thinsp;14, and \u003cem\u003eLimnobacter\u003c/em\u003e was significantly increased and the abundance of \u003cem\u003eFlavobacterium\u003c/em\u003e decreased in the CS group compared to the GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-g). Significant community differences were also observed among experimental groups. The abundance of \u003cem\u003eHydrogenophaga\u003c/em\u003e, \u003cem\u003eMycobacterium\u003c/em\u003e, \u003cem\u003eSaprospiraceae\u003c/em\u003e, and \u003cem\u003eNS9_marine_group\u003c/em\u003e were significantly increased in the CP group compared to the SBOS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-h). Similarly, the abundance of \u003cem\u003ePhenylobacterium\u003c/em\u003e, \u003cem\u003ePseudomonas\u003c/em\u003e, \u003cem\u003eHyphomicrobium\u003c/em\u003e, and \u003cem\u003eAcidibacter\u003c/em\u003e was significantly increased in the CS group compared to the SBOS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-i). A significant increase in the abundance of \u003cem\u003eRoseomonas\u003c/em\u003e, \u003cem\u003ePhenylobacterium\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e, and \u003cem\u003eSolimonadaceae\u003c/em\u003e in CS group compared to the CP group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e-j). Linear Discriminant Analysis Effect Size (LefSe) analysis showed that Myxococcota was significantly enriched in the GLU group. The Bacteroidota was significantly enriched in the SBOS group, and Firmicutes was significantly enriched in CS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e-a). At the genus level, LDA value of 3.5 was used. \u003cem\u003eFlavobacterium\u003c/em\u003e was significantly enriched in the SBOS group, \u003cem\u003eHydrogenophaga\u003c/em\u003e was significantly enriched in CP group, and \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003eMycobacterium\u003c/em\u003e were significantly enriched in CS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e-b).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.6. FAPROTAX prediction\u003c/h2\u003e \u003cp\u003eFAPROTAX, a manually constructed database, is considered one of the most reliable methods for predicting microbial ecological functions (Zhang et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Microbial function predictions based on the experimental results showed that the functional structure of the microorganisms was significantly altered in the experimental groups. The function involved in degrading aromatic hydrocarbons was significantly increased in the SBOS group compared to the GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-a). The function related to nitrogen cycle conversion was significantly increased in the CP group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Figs.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-b), while functions related to symbionts and nitrogen cycle conversion were significantly upregulated in the CS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-c). The function of chemoheterotrophy was significantly increased in the SBOS group compared to the CP group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-d). The nitrogen cycle conversion ability was significantly increased in the CS group compared to the SBOS group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-e), and the abilities for nitrogen fixation and cellulolysis were significantly increased in the CS group compared to the CP group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e-f).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.7. The interactions of microorganisms in BFT systems and their impact on the environment\u003c/h2\u003e \u003cp\u003eThe distribution of samples and species was illustrated by the collinearity network (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e-a). The results showed that the proportion of shared bacteria between the experimental groups and the CON group was low. The microbial compositions of GLU and SBOS groups were quite comparable, whereas those of CS and CP groups also shared similarities. \u003cem\u003eFlavobacterium\u003c/em\u003e and \u003cem\u003eBacillus\u003c/em\u003e were connected with every experimental group. \u003cem\u003eRhizobiales\u003c/em\u003e was connected only with SBOS group, and \u003cem\u003eMycobacterium\u003c/em\u003e was connected only with CS group. The univariate network diagram demonstrates the positive and negative correlations between bacterial communities, with red lines indicating positive correlations, green lines indicating negative correlations, and the thickness of the lines representing the correlation coefficient (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e11\u003c/span\u003e-b). The results denoted a strong degree of correlation among bacteria in the BFT system. All lines connected to \u003cem\u003eFlavobacterium\u003c/em\u003e were green, indicating negative correlations with bacteria such as \u003cem\u003eMycobacterium\u003c/em\u003e. In contrast, most lines linked to \u003cem\u003eBacillus\u003c/em\u003e were red, representing positive correlations, except for a single green line, which highlighted a negative correlation with \u003cem\u003ehgcl_clade\u003c/em\u003e. Overall, the red lines predominated over the green ones, suggesting a general trend of mutual promotion among bacterial communities within the system. The correlation between experimental bacterial communities and various environmental factors was also demonstrated (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e12\u003c/span\u003e), with FV showing positive correlations with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and negative correlations with NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, TN, and NTU. \u003cem\u003eFlavobacterium\u003c/em\u003e showed a significant positive correlation with FV (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and significant negative correlations with NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, TN, and NTU (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eBacillus\u003c/em\u003e exibited significant positive correlations with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and FV, and significant neagitve correlation with NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, TN, and NTU (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eHgel_clade\u003c/em\u003e was significantly negatively correlated with FV and pH, while showing a significant positive correlation with NTU (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eBacteria and microalgae are crucial components of aquatic ecosystems, playing a crucial role in enhancing system stability (Vale et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This stability is particularly important in BFT systems, where maintaining stable and healthy bacterial communities can effectively reduce harmful nitrogen levels in the water and positively influence the growth of aquatic animals (Lu et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Harmful nitrogen in water can be effectively reduced by the combined action of microalgae and heterotrophic bacteria (Mahari et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, various types of aquaculture effluents can be effectively treated through synergistic interaction of algae and bacteria (Lee et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhang et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which also establishes symbiotic relationships within the water (Bhatt et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this symbiosis, bacteria supply nutrients such as nitrogen to algae, while algae provide fixed organic carbon to bacteria (Cho et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although microalgae and carbon sources are often used independently, their simultaneous application can overcome the limitations of individual use, optimizing bacterial communities and improving water purification(Shi et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDuring the experiment, DO and pH were observed to decline rapidly on day 1, followed by a sharp increase on day 3. Simultaneously, NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N content increased on day 3 before decreasing, whereas NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N nitrogen content increased on the day 5 and subsequently decline. These fluctuation may be attributed to the growth and proliferation of bacteria in the water. Following the addition of carbon sources, heterotrophic bacteria proliferate rapidly and metabolize, consuming large amounts of DO and producing acidic substances (Deng et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This process creates a temporary hypoxic environment and causes rapid drop in pH. Under these conditions, the activity of nitrifying bacteria was inhibited, leading to the accumulation of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N (Crab et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Subsequently, as the biofloc system stabilizes, DO levels gradually recover, allowing the nitrification process to resume. Simultaneously, as the carbon is gradually depleted, bacterial metabolites transition from acidic to neutral or alkaline, resulting in a gradual increase in pH (Espeleta et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Additionally, the results indicate that the CS group outperformed the SBOS and CP groups in reducing nitrogen, suggesting that the combined use of SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e may be more effective in removing nitrogen compared to their separate use. The CS group consistently maintained a relatively low content of nitrogen and NTU levels while sustaining high FV content. In contrast, the CP group was found to be less effective than the CS group in reducing nitrogen content and maintaining system stability. This may be attributed to the partial digestion absorption of SBOS by beneficial bacteria using specialized enzymes (Roberfroid et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). This process increases the abundance of beneficial and core bacteria while reducing harmful bacteria through bacterial competition, which promotes microalgae-bacteria interactions. The types of bacteria are crucial for microalgae-bacteria interactions (Crespo et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For instance, the growth rate of microalgae (\u003cem\u003eChlorella sorokiniana\u003c/em\u003e) is significantly enhanced by \u003cem\u003eAzospirillum brasilense\u003c/em\u003e and \u003cem\u003eBacillus pumilus\u003c/em\u003e through the secretion of growth hormones or the provision of essential nutrients (Amavizca et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This demonstrates that the yield and quality of biomass can be significantly improved by specific bacteria in aquaculture systems (Kang et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Conversely, c bacteria may inhibit the growth of specific microalgae; forexample, the growth of \u003cem\u003eNannochloropsis gaditana\u003c/em\u003e is significantly inhibited by \u003cem\u003eMuricauda\u003c/em\u003e sp., likely due to bacterial density and the chemical substances they release (Han et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Previous studies also highlighted that an optimized bacterial community can enhance algal-bacterial symbiosis (Kim et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), thereby enhancing the overall productivity of aquatic systems.\u003c/p\u003e \u003cp\u003eIn this experiment, α-diversity index in the experimental groups was lower than CON group. This reduction in diversity and richness of the microbial community may be due to the addition of carbon sources. Microbial diversity and richness were observed to decrease in high-carbon environments, and heterotrophic bacteria were found to rapidly adapt to the high-carbon conditions and proliferate quickly (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The abundance of \u003cem\u003eTerrimonas\u003c/em\u003e, a bacterium with a unique nitrogen fixation system belonging to the \u003cem\u003eRhizobiales\u003c/em\u003e, was found to be significantly increased by the addition of SBOS (Huang et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Meanwhile, the abundance of the harmful bacterium \u003cem\u003eChryseobacterium\u003c/em\u003e was significantly decreased by SBOS (Zamora et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This is consistent with previous findings, where the number of harmful bacteria such as \u003cem\u003eVibrio\u003c/em\u003e in the intestines of crucian carp was effectively reduced by a small amount of SBOS as a carbon source (Qiu et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and the abundance of harmful bacteria like \u003cem\u003eAeromonadaceae\u003c/em\u003e in the water was also reduced by a small amount of fructooligosaccharides as a carbon source (Zhou et al., \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2024b\u003c/span\u003e). Similarly, the abundance of beneficial bacteria such as \u003cem\u003eBacillus\u003c/em\u003e in the intestines of Nile Tilapia (\u003cem\u003eOreochromis niloticus\u003c/em\u003e) was significantly increased by using mannanoligosaccharides as a carbon source in BFT, while the abundance of harmful bacteria such as \u003cem\u003eVibrio\u003c/em\u003e and \u003cem\u003eAeromonas\u003c/em\u003e was reduced (Kishawy et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This aligns with the previous hypothesis that the addition of a small amount of SBOS as a carbon source can effectively increase the abundance of beneficial bacteria in the water while reducing the abundance of harmful bacteria. A previous study also demonstrated that the addition of \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e significantly increased the abundance of \u003cem\u003eSaprospiraceae\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e. \u003cem\u003eSaprospiraceae\u003c/em\u003e, a core genus in activated sludge, is known for its ability to metabolize glucose, galactose, and specific proteins (Wu et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Free-living \u003cem\u003ePseudomonas\u003c/em\u003e has also been shown to effectively remove nitrogen from the water (Yi et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e may supply these microorganisms with glucose, galactose, or specific amino acids and proteins (Ummat et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), thereby promoting their growth. The abundance of bacteria that can effectively degrade nitrogen in the water, such as \u003cem\u003eHydrogenophaga\u003c/em\u003e (Fan et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), \u003cem\u003eMycobacterium\u003c/em\u003e (Dong et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and \u003cem\u003eSaprospiraceae\u003c/em\u003e (McIlroy and Nielsen, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), was significantly increased in the CP group compared to the SBOS group. Nitrogen accumulation was more effectively reduced under low C/N conditions by a BFT system with algal-bacterial symbiosis compared to a system dominated solely by bacteria (Markou et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, the CS group exhibited the same increase in \u003cem\u003ePseudomonas\u003c/em\u003e and \u003cem\u003eHydrogenophaga\u003c/em\u003e as seen in the CP group compared to the SBOS group, while a significant increase in the abundance of \u003cem\u003eRoseomonas\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e was observed in the CS group compared to the CP group. Research has shown that an inverse relationship exists between \u003cem\u003eRoseomonas\u003c/em\u003e and nitrite content, indicating that nitrite reduction is positively influence by \u003cem\u003eRoseomonas\u003c/em\u003e (Mang et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). \u003cem\u003eSphingomonas\u003c/em\u003e has also been found to effectively reduce the accumulation of NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and nitrite in aquaculture (Yun et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The significant increase in \u003cem\u003eSolimonadaceae\u003c/em\u003e may be related to the presence of HDPE materials (Nguyen et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and the combined effects of SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e on the microbial community may drive this change, although the underlying mechanisms remain unclear.\u003c/p\u003e \u003cp\u003eLEfSe analysis revealed that differentially enriched bacteria were present in each experimental group. The observed changes in bacterial communities may have been influenced by these differentially enriched bacteria. \u003cem\u003eFlavobacterium\u003c/em\u003e was found to be significantly enriched in the SBOS group, \u003cem\u003eHydrogenophaga\u003c/em\u003e was significantly enriched in the CP group, and \u003cem\u003eBacillus\u003c/em\u003e was significantly enriched in the CS group. This result is consistent with the environmental factor analysis, where nitrogen transformation in the water was significantly influenced by the bacteria affected by each experimental group. Additionally, the overall functionality of the microbial community was considerably impacted by the significantly enriched bacteria helping maintain its balance and stability (Guo et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The microbial function prediction results for each experimental group showed that nitrite-related metabolism was significantly increased in the CP group, which can reduce toxic nitrite levels (Wang et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The ability for nitrogen fixation was significantly increased in the CS group compared to the CP group, possibly due to the significant enrichment and high abundance of \u003cem\u003eMycobacterium\u003c/em\u003e in the CS group. \u003cem\u003eMycobacterium\u003c/em\u003e has been found to have a positive impact on nitrogen fixation (Pajares and Bohannan, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Compared to the SBOS group, nitrite-related metabolism was significantly increased in the CS group, likely due to the symbiosis between \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e and many denitrifying bacteria, greatly enhancing this function.\u003c/p\u003e \u003cp\u003eThe correlation between environmental factors and bacterial communities shows that \u003cem\u003eFlavobacterium\u003c/em\u003e, as a core genus, was negatively correlated with NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N, and positively correlated with NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N. This suggests that NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N is effectively converted by \u003cem\u003eFlavobacterium\u003c/em\u003e, and the positive correlation between \u003cem\u003eFlavobacterium\u003c/em\u003e and FV indicates that harmful nitrogen in the water is efficiently converted into biofloc. These findings aligns with previous research, where NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N is effectively converted to NO\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N by \u003cem\u003eFlavobacterium\u003c/em\u003e, a denitrifying bacterium (Bernardet and Bowman, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). A significant positive correlation was observed between \u003cem\u003eBacillus\u003c/em\u003e and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N and FV, and a significant negative correlation was found between \u003cem\u003eBacillus\u003c/em\u003e and NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N. This may be due to sufficient organic matter for \u003cem\u003eBacillus\u003c/em\u003e growth being provided by NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e-N, and biofloc formation being promoted by the physiological activities of \u003cem\u003eBacillus\u003c/em\u003e, effectively reducing NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e-N content (He et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). \u003cem\u003eHgcI_clade\u003c/em\u003e, a bacterium used to gauge water quality (Tong et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), shows no significant differences with the three forms of nitrogen but is significantly negatively correlated with FV. This may be due to substances such as nitrogen being removed from the water by biofloc, inhibiting the growth of \u003cem\u003ehgcI_clade\u003c/em\u003e. The changes in microbial community structure caused by SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e indicate that microbial activity and water quality are closely linked.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThe research demonstrates that both SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e, whether used individually or in combination, effectively promote the growth of heterotrophic bacteria, facilitating nitrogen absorption and biofloc formation. The addition of SBOS significantly increases the abundance of \u003cem\u003eFlavobacterium\u003c/em\u003e, while the addition of \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e significantly increases the abundance of \u003cem\u003eHydrogenophaga\u003c/em\u003e. When used together, they further boosted the abundance of \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003eMycobacterium\u003c/em\u003e, promoting the expression of nitrogen cycle-related functional genes. This highlights a synergistic effect between SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e in promoting the growth of beneficial bacteria, enhancing nitrogen absorption, and contributing positively to the reduction of nitrogen accumulation and the stability of the aquatic ecosystem in aquaculture environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Zhejiang Province Agricultural Major Technology Cooperative Promotion Plan ( 2022XTTGSC01 ); The Project Supported by Zhejiang Provincial Natural Science Foundation of China ( LTGN23C190002 ).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHangxian Zhou\u003c/strong\u003e: Conceptualization, Methodology, Formal analysis, Resources, Data curation, Writing – original draft. \u003cstrong\u003eMengsha Lou\u003c/strong\u003e: Conceptualization, Methodology, Writing – original draft.\u003cstrong\u003e\u0026nbsp;Clement de Cruz\u003c/strong\u003e: Writing – review \u0026amp; editing. \u003cstrong\u003eJie Wei\u003c/strong\u003e: Conceptualization, Methodology, Writing – original draft. \u003cstrong\u003eMingwei Tao\u003c/strong\u003e: Conceptualization, Methodology, Writing – original draft. \u003cstrong\u003eJianhua Zhao\u003c/strong\u003e: Formal analysis. \u003cstrong\u003eRongfei Zhang\u003c/strong\u003e: Formal analysis. \u003cstrong\u003eQiyou Xu\u003c/strong\u003e: Conceptualization, Writing – review \u0026amp; editing, Supervision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author, upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmavizca, E., Bashan, Y., Ryu, C.-M., Farag, M.A., Bebout, B.M., de-Bashan, L.E., 2017. 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Int. 32, 8417\u0026ndash;8436. https://doi.org/10.1007/s10499-024-01572-7\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"","identity":"aquaculture-international","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"10499","submissionUrl":"https://submission.nature.com/new-submission/10499/3","title":"Aquaculture International","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"soybean oligosaccharides, Chlorella pyrenoidosa, microflora, synergistic effects, biofloc","lastPublishedDoi":"10.21203/rs.3.rs-6527949/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6527949/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study explored the synergistic effects of soybean oligosaccharides (SBOS) and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e on water quality and microbial community structure of aquaculture effluent in a biofloc system. Five experimental treatments were designed including CON group (control, no treatment), GLU group (glucose), SBOS group (2.5% SBOS and 97.5% glucose), CP group (glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e), and CS group (2.5% SBOS, 97.5% glucose and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e). \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e were included at a concentration of 5.37\u0026times;10⁵ cells/mL for selected treatments. Each treatment had 5 replicates, and C/N ratio was 15. Over the nine-day experimental period, combination of SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e demonstrated significant synergistic effects on water quality improvement and biofloc formation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Specifically, in CS group, nitrate concentrations were significantly reduced on day 1, nitrite nitrogen concentrations exhibited a marked reduction on day 5, and both nitrite and total nitrogen concentrations showed significant reductions on day 7 compared to GLU group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Biofloc volume (FV) in CS group showed a significant increase on day 3 compared to both CON and GLU groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Turbidity (NTU) was significantly lower in all experimental groups compared to CON group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Compared with other experimental groups, the abundance of \u003cem\u003eAeromonasaceae\u003c/em\u003e decreased significantly, and \u003cem\u003eBacillus\u003c/em\u003e and \u003cem\u003eMycobacteria\u003c/em\u003e increased significantly in CS group, which contributed to the enhanced nitrogen cycling and degradation of organic matter degradation pathway (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings suggest that SBOS and \u003cem\u003eChlorella pyrenoidosa\u003c/em\u003e exhibit synergistic effects in treatment of effluent in biofloc system, and efficiently remove nitrogen and optimize microbial community structure.\u003c/p\u003e","manuscriptTitle":"Synergistic effects of soybean oligosaccharides and Chlorella pyrenoidosa on water quality and microbial community structure in biofloc system","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 08:01:36","doi":"10.21203/rs.3.rs-6527949/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-21T07:44:56+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-21T03:50:34+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-16T13:11:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-12T02:58:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54518489517778517232696733999734404507","date":"2025-05-09T08:08:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6063651723720677747147105645738097288","date":"2025-05-07T13:37:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11817255622599417872269218523988398342","date":"2025-05-04T15:18:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257310199894276158072086880058340322566","date":"2025-05-02T02:10:00+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-30T15:32:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-28T06:00:45+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-28T02:00:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aquaculture International","date":"2025-04-25T10:08:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"","identity":"aquaculture-international","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"10499","submissionUrl":"https://submission.nature.com/new-submission/10499/3","title":"Aquaculture International","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"","reportingPortfolio":"VoR Journals","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b2018803-3fe4-4ff6-bd09-2a4c3163aa09","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-06-04T18:53:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-06 08:01:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6527949","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6527949","identity":"rs-6527949","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}