In Situ Recirculating Aquaculture System Improves the Growth Performance of Shrimp (Penaeus vannamei) via Shaping Diverse Bacterial Communities

Abstract

The in situ recirculating aquaculture system (IS-RAS) is regarded as an effective measure to reduce shrimp disease risks by minimizing exogenous water input and improving water quality. However, little is known about the effects of this system on bacterial communities in shrimp gut and rearing water. Here, the growth performance of shrimp and bacterial community characteristics in this culture system were assayed. The results show that the IS-RAS significantly improved rearing water quality, with a 2.2-fold reduction in turbidity, a 68.2% decrease in nitrite concentration, and enhanced hepatopancreatic digestive enzyme activities (e.g., amylase and lipase) and antioxidant capacities (e.g., superoxide dismutase and total antioxidant capacity). These improved physiological and biochemical indexes in the IS-RAS significantly increased the yield and survival rate, with increments of 23.5% and 25.9%, respectively, compared to that in CK. The IS-RAS significantly increased the bacterial diversity and enriched certain keystone taxa belonging to Roseobacteraceae, Paracoccaceae, Flavobacteriaceae, Nitrosomonadaceae, and Nitrospiraceae in both water and shrimp gut. These taxa play critical roles in maintaining bacterial network stability, and some of them were identified as potential taxa for promoting shrimp growth. Furthermore, the IS-RAS significantly upregulated functional genes associated with nitrogen metabolism (e.g., nirS, nirA, norB, napA, napB, and pmoA-amoA), thereby enhancing the nitrogen cycling potential of the bacterial community. These findings elucidate the biological mechanisms underlying IS-RAS-mediated improvements in shrimp farming productivity.

1. Introduction

The Pacific white shrimp (Penaeus vannamei) has emerged as one of the most economically valuable shrimp species in global aquaculture due to its superior genetic traits and high productivity [1]. However, with the escalating stocking density in intensive aquaculture systems, the accumulation of unconsumed feed and metabolic waste that cannot be efficiently removed leads to marked increases in toxic nitrogenous compounds (specifically ammonia-N and nitrite-N) in rearing water [2]. This deteriorating water quality significantly elevates shrimp susceptibility to disease such as acute hepatopancreatic necrosis disease (AHPND), which is closely associated with ammonia-N toxicity [3], thus ultimately resulting in substantial losses in both production yield and quality of farmed shrimp [4]. Therefore, how to rapidly and efficiently remove pollutants from aquaculture ponds has been a key issue in maintaining the healthy and sustainable development of the shrimp industry.

Among the various strategies adopted for removal of pollutants from rearing water, the recirculating aquaculture system (RAS) has been proposed as an eco-friendly alternative method to reduce the risk of water quality deterioration, and subsequently, outbreaks of disease [5,6]. However, the popularization and application of the RAS for shrimp farming in China has been hindered by its higher technical requirements, such as the engineering complexity of water treatment and system operation [7], as well as the high initial capital investment (e.g., tank retrofitting, biofiltration units, and monitoring equipment) and operating costs (e.g., water circulation, aeration, and temperature control). Furthermore, rearing water from different culture ponds is generally collected into a single water-treatment module in the RAS, which increases the risk of cross infection. Meanwhile, it is difficult to widely apply in traditional shrimp farming systems, such as traditional soil ponds and high-altitude ponds, due to its special equipment requirements [8].

Microbes in the RAS are very critical for purifying water quality. As an essential component of aquaculture systems [9], they serve as a key driver of multiple ecological processes, including nutrient cycling, organic matter decomposition, and both symbiotic and pathogenic interactions with aquatic species [10,11]. Improved environmental conditions also exert positive feedback effects on microbial community structure, primarily by enriching potential probiotic populations and depleting specific pathogens [12]. Meanwhile, emerging evidence reveals that fluctuations in key aquatic environmental parameters (temperature, salinity, pH, dissolved oxygen) dynamically modulate both the structural configuration and metabolic activity of gut microbiota in shrimp [13]. Modulating the structure of aquatic microbial communities could improve shrimp health and enhance pathogen resistance [14], and optimizing aquatic microbiota (e.g., probiotic supplementation) could also enhance colonization of beneficial gut bacteria, inhibit pathogens, and improve disease resistance [15]. However, a deeper understanding of how the RAS regulates the interactions between aquatic and gut bacterial communities remains limited.

Here, an in situ recirculating aquaculture system (IS-RAS) was built to evaluate its effects on water purification and aquaculture biological health through continuous monitoring of key water quality indicators and shrimp growth parameters. High-throughput sequencing technology was used to analyze the characteristics of bacterial communities and to evaluate the specific effects of the IS-RAS on bacterial ecological balance.

2. Materials and Methods

2.1. Experimental Design and Sample Collection

The experiment was performed at the pilot base of Ningbo University (Meishan campus). The IS-RAS system was constructed in a 1500 L polyethylene culture tank and consists of an in situ return pipe (0.3 m in diameter and 0.7 m in height), an airlift device, a gravity backwash system, a filtration system with an 80-mesh screen, and moving bed biofilm reactor (MBBR) packing (Figure 1a,b). Healthy shrimp (P15) were obtained from Xiangda Seedling Co., Ltd. (Xiamen, China) and were acclimatized to the experimental conditions for 7 d. Then, the shrimp were randomly distributed into the eight modified tanks containing 1200 L of sanitized seawater, with a density of 1000 shrimp per tank. The shrimp were fed thrice per day (at 09:00, 14:00, and 20:00), and the feeding amount was set at 5% of the body weight of shrimp. The experiment was divided into two groups: the control group (CK), which had a 30% water exchange and pollution discharge three times per day; and the in situ recirculating aquaculture system (IS-RAS) group, where 10% of the water was exchanged daily, and the recirculating water system was started one hour after feeding (Figure 1b). Each group had four biological replicates (n = 4). Samples of water and gut of shrimp were collected at days of 21, 42, 56, 70 and 84. For the water samples, 200 mL of water was collected from each tank and filtered through a 0.22 μm membrane to retain microorganisms, and the filtrate was used for water quality analysis. For the shrimp samples, 20 shrimp were randomly selected from each tank for the collection of gut and hepatopancreatic tissues on day 21, and 10 shrimp were randomly selected for tissue sampling on days 42, 56, 70 and 84. All collected samples were stored in an ultra-low-temperature freezer at −80 °C for subsequent DNA extraction and enzyme activity analyses.

2.2. Water Quality Parameter Analysis

Water temperature, dissolved oxygen, pH, and salinity in each tank were monitored daily between 7:00 and 8:00 a.m. using a portable water quality analyzer (YSI Pro Plus, Yellow Springs, OH, USA). Concentrations of ammonia nitrogen, nitrite, nitrate, and reactive phosphate were determined according to the National Standard of China (GB 17378.4-2007) [16]. Turbidity was measured with a portable turbidimeter (WGZ-1B, Shanghai Xinrui Instrumentation Co., Ltd., Shanghai, China).

2.3. Shrimp Growth and Enzyme Activity Analysis

After the experiment, the numbers and weights of shrimp in each tank were recorded. The survival rate, yield, feed conversion ratio and specific growth rate were calculated according to the following formulas: Survival rate (%) = (Harvested shrimp number/Initial stocked shrimp number) × 100; Production yield (kg/m³) = Total harvested shrimp weight/Aquaculture water volume; Feed conversion ratio = Total feed consumption/Shrimp weight gain (wet weight); and Specific growth rate (%) = [ln(Final individual weight) − ln(Initial individual weight)]/Culture days × 100.

Hepatopancreas tissues of shrimp were used for enzyme activity analysis. Before measurement, the tissues were freeze-dried by vacuum freeze dryer (EYELA, Tokyo, Japan) for 48 h, and then grounded into powder. For each sample, 0.1 g of powder was accurately weighed and added to 10 times its volume (v/w) of pre-cooled normal saline. Then, the mixture was homogenized with a homogenizer at 2500 rpm for 10 min under an ice bath, and the supernatant was used to measure the enzyme activities (amylase, lipase, cellulase, trypsin, superoxide dismutase, glutathione peroxidase, catalase) and total antioxidant capacity (T-AOC) following the instructions of assay kits (Nanjing Jiancheng Biotechnology Co., Ltd., Nanjing, China).

2.4. DNA Extraction, 16S rRNA Gene Sequencing and Data Processing

Total DNA was extracted from water samples and shrimp gut samples using the Power Soil^® DNA kit (MOBIO, Carlsbad, CA, USA) and QIAamp^® DNA Stool Mini Kit (Qiagen, Hilden, Germany), respectively, following the manufacturers’ protocols. The concentration and purity of DNA were measured with a NanoDrop ND-2000 spectrophotometer (Thermo Scientific, Waltham, MA, USA), and DNA was stored at −80 °C for subsequent analysis. The V4 region of the 16S rRNA gene was amplified using specific primers 515F-Y (5′-GTGYCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTCANVGGGTWTC TAAT-3′), followed by sequencing on the Illumina MiSeq platform (Illumina, San Diego, CA, USA).

Raw reads were demultiplexed, primer-stripped, and merged by the sequencing provider (Biozeron Biotechnology Co., Ltd., Shanghai, China) using cutadapt (v4.1) and FLASH (v2.2.00). The resulting valid reads were then imported into QIIME 2 (v2024.2) for downstream processing. Valid reads were denoised into zOTUs (zero-radius operational taxonomic units) using the “denoise-no-primer-pooled” method implemented in the q2-usearch plugin. Taxonomic classification of zOTUs was performed using the “classify-sklearn” method in the q2-feature-classifier plugin against a pre-trained classifier based on the SILVA 138.2 reference database generated using standard procedures (q2-rescript). After removing zOTUs classified as chloroplast or mitochondrial sequences, as well as any unassigned or unclassified zOTUs, a de novo phylogenetic tree was constructed using the “align-to-mafft-fasttree” pipeline in the q2-phylogeny plugin. Finally, the zOTU table was rarefied to a depth of 19,030, resulting in a total of 9804 zOTUs for downstream analysis.

2.5. Data Analysis

2.5.1. Diversity and Taxonomic Analysis

The indices of richness (observed species), Pielou’s evenness and phylogenetic diversity were calculated by QIIME 2. All subsequent analyses were performed in R v4.3.3. Principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity was conducted using the “microeco v1.3.0” package to visualize differences in bacterial community structure between the CK and IS-RAS groups, followed by permutational multivariate analysis of variance (PERMANOVA) to assess the statistical significance of community variation. Discriminative taxa across groups were identified through LEfSe analysis combined with the Kruskal–Wallis rank-sum test (α = 0.05). To further investigate period-specific taxa in the aquaculture system, specificity and occupancy were calculated according to the method described by Dufrene and Legendre [17]. A Venn diagram was generated using the online platform (http://cloudtutu.com./, accessed on 5 May 2025) to identify time-specific discriminative taxa between the two experimental groups.

2.5.2. Co-Occurrence Network

A SparCC network was constructed using the “SpiecEasi” package (v1.99.3) [18] with parameters (median = 20,100 bootstraps) to calculate correlations and pseudo p-values. Significant correlations (|ρ| ≥ 0.6, p < 0.05) were retained to build the network, visualized in Gephi (v0.10). Topological and stability metrics (natural connectivity, robustness, vulnerability) were analyzed via the “igraph” R package (version 2.2.1) by evaluating connectivity decline after node removal and the negative-to-positive cohesion ratio [19].

2.5.3. Functional Potential Evaluation

Prediction of functional gene abundance was carried out using PICRUSt2 based on 16S rRNA amplicon sequencing data from cultured water bacterial communities [20]. Annotation of microbial metabolic pathways was conducted through the KEGG database. The focus was on genes related to nitrogen metabolism, including nitrate reduction: narH, nasA, napA; nitrite reduction: nirB, nirD, nirK, nrfA; nitric oxide reduction: norB, norC; nitrous oxide reduction: nosZ. Using the OmicStudio platform (https://www.omicstudio.cn/tool, accessed on 5 May 2025) and ggplot2 enrichment visual function, the correlation between functional genes and physicochemical factors in water was analyzed by Pearson correlation.

2.6. Statistical Analyses

Statistical analysis was performed to assess the significant differences between groups based on Student’s t-test using the “VEGAN” package in R 4.0.3.

3. Results

3.1. Water Quality and Shrimp Growth Performance in the IS-RAS Group

The water quality parameters at each culture stage, such as temperature, inorganic nutrients (ammonia nitrogen, nitrite, nitrate), turbidity, dissolved oxygen (DO), and salinity, were measured. The results show no significant differences in water temperature or salinity between the in situ recirculating aquaculture system (IS-RAS) and the control (CK) groups (Figure S1). The DO and pH exhibited dynamic variations: the IS-RAS group showed significantly higher DO levels than the CK group during the mid-late culture stages (D56–D84, p < 0.01), while the pH value in the CK group was progressively decreased to 7.3 from 7.7 in the IS-RAS group (p < 0.05). Furthermore, the CK group exhibited 2.2-fold higher turbidity than the IS-RAS group (31.1 vs. 14.1 NTU). The IS-RAS group demonstrated a 68.2% reduction in nitrite concentration compared to CK (4.9 vs. 15.4 mg/L), and about a 2-fold increase in nitrate levels (Figure S1).

After culturing, the final survival rates and body weights of shrimp in the CK and IS-RAS groups were 67.8% and 85.3% and 8.32 g and 8.25 g/individual, respectively, which led to a significant increase in yield with a ratio of 23.5% in the IS-RAS group (Figure 1c and Table S1). In addition, the feed conversion ratio (FCR) in the IS-RAS group was significantly decreased by 25%, compared to that in the CK group (Figure 1c). Although there was no significant difference in specific growth rates (SGRs) between the groups, digestive enzyme activities, such AMS, LPS, and trypsin, were 1.3, 2.6, and 1.9-fold higher in the IS-RAS than in the CK group at certain time points, respectively (Figure 1c and Figure S2). Meanwhile, the IS-RAS group displayed 5.35-fold higher total antioxidant capacity (T-AOC) than CK, accompanied by a 14.35% increase in superoxide dismutase (SOD) activity (Figure S2).

3.2. Bacterial Community Composition of Water and Shrimp Gut in the IS-RAS Group

The bacterial communities of water and shrimp gut in the CK and IS-RAS groups significantly differed along with culture time. On day 21, the bacterial community diversity parameters of water, including Pielou’s evenness index (0.66 vs. 0.55), richness (1089 vs. 837 ASVs), and phylogenetic diversity (44.1 vs. 37.5 PD_whole_tree) in the IS-RAS group were significantly higher than in CK (p < 0.05, Figure S3). The shrimp gut bacterial community of the IS-RAS group exhibited a significantly lower Pielou’s evenness index compared to that of CK at D42 (0.54 vs. 0.62; p < 0.05). However, significantly elevated richness (33.75% higher) and phylogenetic diversity (34.87% increase) were observed in the IS-RAS group during the mid-late culture stages (D56–D84, Figure S3). To evaluate similarity patterns of bacterial communities in the aquaculture system across culture stages, Bray–Curtis distance-based principal coordinates analysis (PCoA) was conducted to comparatively analyze microbial assemblages in both the rearing water and shrimp gut. The aquatic bacterial communities between the two groups exhibited significant structural divergence prior to D42 (R² = 0.18, p = 0.001), whereas shrimp gut bacterial community disparities persisted from D21 through experimental termination (R² = 0.24, p = 0.002, Figure 2a,b).

The dominant bacterial taxa at the genus level exhibited significant compositional divergences between both groups across culture stages (Figure 3 and Figures S4 and S5). The most abundant taxa in the rearing water were Marivita, Actinobacteria_PeM15, Flavobacteriaceae, Roseobacteraceae, Catenococcus, and Paracoccaceae, but no statistically significant differences were observed between the groups overall (Figure 3a). Temporal shifts in aquatic bacterial communities exhibited more pronounced and visually striking dynamics across culture stages. For examples, CK demonstrated significantly higher proportions of Algoriphagus at D56 (18.1% vs. 7.63%; p < 0.01), Vibrio at D56 (7.32% vs. 0.07%; p < 0.001), and Vibrionaceae at D70 (7.69% vs. 2.22%; p < 0.05) compared to the IS-RAS group (Figures S4 and S5a). The shrimp gut bacterial community was dominated by Flavobacteriaceae (IS-RAS 28.13% vs. CK 14.17%), Roseobacteraceae (IS-RAS 7.02% vs. CK 6.50%), Paracoccaceae (IS-RAS 6.63% vs. CK 6.15%), Tenacibaculum (IS-RAS 2.90% vs. CK 7.82%), and Sungkyunkwania (IS-RAS 5.46% vs. CK 5.18%) (Figure 3b). In contrast to the rearing water bacterial communities, shrimp gut bacterial assemblages demonstrated marked disparities within the groups in dominant taxa. For examples, the IS-RAS group exhibited significantly higher proportions of Flavobacteriaceae (26.28%), Xanthomarina (3.80%), Vibrionimonas (2.61%), and Marivita (1.65%) and demonstrated reduced proportions of Sungkyunkwania (7.73%), Catenococcus (4.06%), Lysobacter (3.10%), Halieaceae (2.21%), and Pseudoalteromonas (1.81%) compared to CK throughout most culture stages (Figure 3b and Figures S4 and S5b). These findings collectively indicate that while both groups shared similar dominant taxa in planktonic communities, the CK group exhibited significant increases in Algoriphagus, Vibrio, and Vibrionaceae during the mid-late culture stages.

3.3. Identification of Discriminatory Bacterial Taxa in the IS-RAS Group

Given the distinct dynamics of bacterial community composition in both rearing water and shrimp gut, LEfSe analysis (LDA score > 2.5) was subsequently employed to identify stage-specific discriminatory planktonic bacterial taxa across culture stages (Figure S6a). The IS-RAS group demonstrated higher discriminatory zOTU numbers in water communities predominantly during the early and late culture stages compared to CK, while shrimp gut communities exhibited increased differential zOTU abundance in the IS-RAS group at D56 and D84 (Figure S6a). Differential zOTUs were predominantly affiliated with Alphaproteobacteria, Bacteroidia, and Gammaproteobacteria, and the IS-RAS group exhibited a greater diversity of additional discriminatory zOTUs, including Bdellovibrionia, Bacilli, and Nitrospiria, compared to CK during the late culture stages (D70–D84) (Figure S6b). The SPEC-OCCU plot further demonstrated uniform zOTU occupancy across different culture stages and habitats, with comparable zOTU numbers observed at all sampling points (Figure S6c). To identify habitat-specific indicator species, zOTUs with specificity and occupancy rates ≥ 0.7 were selected (dotted boxes in Figure S6b). Notably, the IS-RAS group exhibited fewer unique taxa in rearing water than CK at D56 (22 vs. 45) and D70 (51 vs. 72), but surpassed CK at D84 (136 vs. 104). A similar temporal pattern was observed in the shrimp gut bacterial community, and the IS-RAS group demonstrated significantly higher values (71) compared to CK (55) at D56 (Figure S6c). Notably, class-level analysis of these discriminatory zOTU compositions revealed that D70-specific zOTUs in the CK group were predominantly affiliated with Gammaproteobacteria (Figure S6d).

To identify IS-RAS-enriched specific taxa, shared IS-RAS-discriminatory bacterial taxa at each sampling point were determined through the LEfSe (LDA score > 2.5), and SPEC-OCCU (specificity and occupancy ≥ 0.7) analyses (Figure 4 and Figure S6). Venn diagram and heatmap analyses revealed that the IS-RAS group exhibited 73 and 23 discriminatory taxa in the rearing water and shrimp gut bacterial communities, respectively (Figure 4a), and both the numbers and relative abundances of these taxa were significantly higher than those in the CK group (Figure 4b). Among these water-enriched zOTUs, the majority were primarily classified into multiple taxonomic groups within Roseobacteraceae, Flavobacteriaceae, and Bacteroidia. Notably, the following zOTUs exhibited higher relative abundances at specific time points, such as the at day 21: zOTU21 (Tenacibaculum, 2.75%), zOTU172 (Paracoccus, 0.84%), zOTU103 (Haloferula, 0.68%), zOTU92 and zOTU38 (Gammaproteobacteria_others, 0.65% and 0.52%); day 42: zOTU790 (Roseobacteraceae, 0.18%), zOTU1744 (Cryomorphaceae_others, 0.10%); day 56: zOTU687 (Roseobacteraceae, 0.25%); D70: zOTU1498 (Flavobacteriales NS9_marine group, 0.09%); day 84: zOTU177 (Marinicella, 2.87%), zOTU236 (Paracoccaceae, 0.89%) (Figure 5). The enriched zOTUs in the shrimp gut predominantly belonged to Roseobacteraceae and Paracoccaceae, as well as certain taxa from Bdellovibrionia, Bacteroidia, Acidimicrobiia, and Nitrospiria. Notably, the following zOTUs exhibited elevated relative abundances: on day 21, zOTU437 (Algoriphagus, 1.27%); on day 56, zOTU65 (PeM15, 0.12%); on day 84, zOTU212 (Roseobacteraceae, 0.61%), zOTU397 and zOTU1096 (Paracoccaceae, 0.43% and 0.12%), and zOTU610 (Babeliales, 0.29%) (Figure 5).

3.4. Bacterial Co-Occurrence Networks in the IS-RAS Group

For aquatic bacterial co-occurrence networks, the IS-RAS group exhibited significantly more edges and nodes than the control group (CK) during the initial 42-day culture period (Figure 6). For shrimp gut bacterial co-occurrence networks, the IS-RAS group demonstrated superior edge and node connectivity metrics compared to CK throughout the trial duration (excluding day 70) (Figure 6). For the stable parameters of bacterial networks, at day 21 of the experiment, the bacterial co-occurrence networks in both water and gut of the IS-RAS group all demonstrated significantly enhanced robustness compared to the CK group (Figure 7a). Moreover, the absolute value ratio of negative to positive cohesion in the IS-RAS group demonstrated statistically significant elevation compared to the CK group (Figure 7b).

3.5. Assessment of Nitrogen Metabolic Functional Potential in the IS-RAS Group

The nitrogen metabolism-related functional genes in bacterial communities of aquaculture water were predicted using PICRUSt2, and homologous gene alignment was conducted with the KEGG database to identify multiple genes related to nitrogen metabolic functions (Figure 8a). From day 21 to 84, the nitrogen metabolic functions of water bacterial community were significantly increased, mainly including K15864 (nirS), K00366 (nirA), K02591 (nifK), K2588 (nifH), K2586 (nifD), K04561 (norB), K03385 (nrfA), K02568 (napB), K02567 (napA), K00368 (nirK), K10944 (pmoA-amoA), K10945 (pmoB-amoB), and K10946 (pmoC-amoC) in the IS-RAS group, compared to that in the CK group (Figure 8a). The relative abundances of nirS and nirA were increased by more than 2-fold at certain time points in the IS-RAS group, compared to that in CK, and the relative abundances of norB, napA, napB, and pmoA-amoA at day 21 were 79.7%, 393.3%, 283.1%, and 628% higher in the IS-RAS group than CK, respectively (Figure 8b). These metabolic functional genes were primarily associated with denitrification, nitrite reduction, nitrogen fixation, and nitrification, which showed stronger expression in the IS-RAS group than CK, showing increases of 4.2%, 5.5%, 12.6%, and 100.7%, respectively (Figure 8c). These findings are similar to the concentrations of ammonia nitrogen and nitrite in water (Figure S1). The correlation analysis indicated that the abundances of specific nitrate/nitrite reduction functional genes (e.g., nrfA, napA, napB, nifH, nifD, nifK, nirB, nirD, nasA) were positively associated with water temperature and nitrate concentration, and nitrogen fixation genes (e.g., nifH, nifD, nifK) were positively correlated with water temperature, nitrate concentration, T-AOC, and trypsin activity, while ammonia oxidation genes exhibited negative correlations with water temperature, ammonia concentration, and GSH-Px activity (Figure S7). Furthermore, partial nitric oxide/nitrate/nitrite reduction genes (e.g., nirS, nirK, nirA, anfG, norB, norC, narB) were predominantly positively correlated with water temperature and pH but negatively correlated with nitrate and total phosphorus concentrations (Figure S7).

4. Discussion

4.1. IS-RAS Improved Water Quality and Shrimp Physiological Performance

Water quality management plays an important role in the process of aquaculture and directly affects the health status of shrimp [21,22]. In traditional shrimp culture models, such as small ponds and high-level pond culture models, water quality problems are mainly caused by the accumulation of solid waste from feces and residual food, as well as their microbial decomposition in the culture process [2]. In the process of culture, only a small amount of nitrogen and phosphorus in the feed are converted into shrimp biomass, and the rest remain in culture ponds in non-soluble and soluble forms, which seriously affects the water quality of the culture system [23]. For example, it has been reported that about 70% of ammonia nitrogen in aquaculture wastewater comes from the degradation of organic particles [24]. The ammonia and nitrite produced by the decomposition of these residues seriously affects the growth of shrimp [25], becoming the main factor restricting the development of the intensive shrimp industry [26]. RAS could greatly improve water quality through both removing non-soluble solid waste and transferring soluble nitrogen and phosphorus waste, thus maintaining the health growth of culture animals [27]. In this study, the IS-RAS significantly reduced the turbidity of water and the contents of ammonia and nitrite (Figure S1) Meanwhile, the IS-RAS also significantly enhanced the yield and survival rate of shrimp and reduced the feed conversion rate (Figure 1c; Table S1), indicating that it could significantly improve the water quality of aquaculture.

Previous studies have reported that the activities of digestive enzymes and antioxidant enzymes in the hepatopancreas of shrimp are very important for feed digestion, nutrient absorption, growth and disease resistance [28,29]. For example, shrimp growth performance is closely associated with the activities of digestive enzymes such as amylase (AMS), lipase (LPS), and trypsin, which catalyze the breakdown of carbohydrates, lipids, and proteins in feed into smaller molecules, thereby facilitating nutrient digestion and absorption and being associated with improved growth performance [29,30]. Additionally, studies indicate that enhancing SOD and T-AOC enzyme activities in shrimp can strengthen their antioxidant defense and immune systems, thereby improving disease resistance, increasing aquaculture survival rates, and supporting healthy growth [29]. In this study, we found that the IS-RAS significantly improved the activities of digestive enzymes (AMS, LPS and trypsin), and antioxidant enzymes (T-AOC and SOD) in the hepatopancreas of shrimp (Figure S2), indicating that the improved survival rate and growth performance might be associated with the enhancement in digestive and antioxidant capacities in the IS-RAS group.

4.2. IS-RAS Enhanced Bacterial Community Stability via Enriching Certain Special Taxa

The stability of the gut bacterial community is responsible for host health, as it ensures that beneficial taxa and their mediated functions can be well maintained over time [31]. A large number of studies have shown that the diversity of bacterial communities directly affects community stability and reflects overall host health [11]. Bacterial α-diversity is considered to be a key indicator of community stability, and high α-diversity is more resistant to pathogens [32]. Here, although the IS-RAS could significantly change the bacterial communities of both water and shrimp gut, the responding pattern differed. The water bacterial community was rapidly affected in the IS-RAS group, which led to an increase in α-diversity and specific taxa’s abundance, especially at the early culture stage. Meanwhile, the gut bacterial community was gradually affected along with the culture time (Figure 2 and Figure S3). These results indicate that the IS-RAS might help to maintain a more diverse bacterial community in both water and shrimp gut.

Bacterial community composition is also crucial for probiotic function. Here, the IS-RAS promoted the rapid convergence of water and gut bacterial communities, which were mainly composed of Rhodobacteraceae and Flavobacteriaceae. Previous studies have reported that Rhodobacteraceae is dominant in shrimp culture systems, and certain taxa in this family can not only synthesize vitamin B12 but also produce TDA to inhibit pathogens such as Vibrio spp., showing their potential as probiotic bacterial taxa [33,34]. Some members of Flavobacteriaceae are good at degrading polymeric organic matter and removing nitrogen, and are thus also being considered as a potential probiotic group [35]. In this study, the relative abundances of zOTUs from the above bacterial taxa, like zOTU21, zOTU113, zOTU737, zOTU1955, zOTU2142, and zOTU707, were significantly increased by the IS-RAS in both water and shrimp gut (Figure 5). This increase corresponded with reduced ammonia and nitrite levels and increased shrimp yield and survival rate, highlighting their potential importance in improving water quality and shrimp growth performance. In addition, our previous studies indicated that the enrichment of taxa from Rhodobacteraceae and Flavobacteriaceae was positively associated with the stability of bacterial communities in shrimp culture systems [11]. Here, the IS-RAS significantly increased the abundances of these taxa, indicating that the stability of bacterial communities might be enhanced.

Bacterial co-occurrence network properties, such as degree, cohesion and robustness values, have been used to estimate bacterial community stability in culture systems [36,37,38]. In this study, the numbers of nodes, edges and cohesion, and the robustness of the co-occurrence network in the IS-RAS group were significantly higher than those in the control group, especially at the early stage of culture (Figure 6). Meanwhile, the network robustness values in the IS-RAS group were significantly higher than in CK in both water and shrimp (Figure 7a). The absolute ratio of negative to positive cohesion was higher in the IS-RAS group in both the water and the gut (Figure 7b), indicating that the IS-RAS was beneficial to maintain the network stability. Previous studies have reported that there are complex interactions among microorganisms, which are crucial for ecosystem function, material circulation and biological evolution [39]. These interactions significantly affect the growth and development and physiological and biochemical characteristics of the host, as well as its adaptability to environmental disturbances, disease resistance and stress resistance [40]. We found that the bacterial community networks in the IS-RAS group had much more complex interactions, which might help to maintain community linkages through more alternative routes when network balance is disrupted, thus improving the stability of bacterial communities [41].

4.3. IS-RAS Augmented Nitrogen Metabolic Function of Water Bacterial Communities

The capacity for nitrogen removal relies on the specific bacterial community present in the rearing water. Here, rearing water of the IS-RAS group possessed significantly higher proportions of habitat-specific zOTUs, which mainly belonged to Roseobacteraceae, Paracoccaceae, Flavobacteriaceae, Nitrosomonadaceae and Nitrospiraceae, etc. Many members of Nitrosomonas, Nitrospira and Flavobacteriaceae have been confirmed to be closely related to water nitrification and nitrogen removal pathways [42]. The Nitrospiria group can oxidize nitrite to nitrate, which helps to reduce the concentration of toxic ammonia and nitrite in water [43]. Taxa from Flavobacteriaceae have been reported to have the ability to remove nitrogen and phosphorus, and they have been reported to be the dominant group in activated sludge treatment systems [44]. Enrichment of these taxa might indicate that the bacterial communities in IS-RAS have a stronger ability to degrade various pollutions, thus improving water quality. Functional analysis provides greater insight into biological value than individual species composition analysis, and PICRUSt2 has been used to predict the functional potential of aquaculture systems at a low cost [45]. The results indicated that the IS-RAS might significantly enhance the expression of functional genes in nitrification, complete nitrification, nitrogen fixation and assimilative nitrate reduction (Figure 8). Nitrification is a two-step oxidation process that converts ammonia to nitrate. First, ammonia-oxidizing bacteria (e.g., Nitrosomonas) transform ammonia into nitrite via ammonia monooxygenase encoded by the amoA gene; second, nitrite-oxidizing bacteria (e.g., Nitrospira) further oxidize nitrite to nitrate using nitrite oxidoreductase encoded by the nxrA gene. This process effectively reduces toxic accumulation of ammonia and nitrite in water [46]. Here, the gene abundances of pmoA-amoA were six-fold higher in the IS-RAS group than that in CK (Figure 8b), which indicates that ammonia oxidation activity was enhanced. In addition, the gene numbers of nxrA and nxrB were increased by 234% and 247.5% in the IS-RAS group (Figure 8b), likely suggesting that the complete nitrification capacity was enhanced, thereby mitigating nitrite toxicity. Complete nitrification is mediated by a single microbial species (e.g., the complete ammonia oxidizer Comammox Nitrospira), which directly oxidizes ammonia to nitrate, avoiding accumulation of nitrite intermediates [47]. Assimilatory nitrate reduction refers to the microbial reduction of nitrate to ammonium (NH₄⁺) via genes like nirA for protein and nucleic acid synthesis [48]. This process mitigates nitrate accumulation in water bodies and suppresses algal blooms. In the IS-RAS group, nirA gene expression increased by 109~345% (Figure 8b), which likely indicates enhanced microbial nitrate utilization, reduced nitrate concentration, and alleviated eutrophication risks. Concurrently, the synergy between nitrification and denitrification (e.g., doubled nirS expression in the IS-RAS group) maintains nitrogen cycle balance and prevents excessive oxygen consumption during nitrification [49]. These functional improvements might facilitate the efficient transformation of ammonia and nitrite in the water, associated with better water quality and lower stress levels in shrimp.

It is important to acknowledge several limitations associated with the functional predictions presented in this study. First, the functional profiles of microbial communities were inferred using PICRUSt2 based on 16S rRNA gene sequences, which provide only potential functions and may not accurately reflect actual metabolic activities or gene expression in situ. Second, the absence of complementary validation using quantitative PCR (qPCR) or shotgun metagenomic sequencing limits the confidence in both taxonomic and functional assignments. Third, although correlations were observed between the abundance of specific microbial taxa, functional gene predictions, and shrimp health parameters, these associations do not establish causality. Further experimental validation is needed to determine whether the observed microbial shifts and functional potentials directly influence shrimp growth performance, antioxidant capacity, or nitrogen metabolism. Despite these limitations, PICRUSt2-based functional predictions still provide valuable insights into the potential functional pathways associated with nitrogen cycling in the IS-RAS system, offering preliminary understanding of how it may maintain water quality stability and promote shrimp health.

5. Conclusions

In conclusion, this study indicated that the IS-RAS could significantly improve the rearing water quality and growth performance of shrimp, resulting in 23.5% higher yield and 25.9% higher survival rate. The stabilities of bacterial communities in both rearing water and shrimp gut in the IS-RAS group were significantly increased via enriching certain specific bacterial taxa in both water and shrimp gut, which were identified as Roseobacteraceae, Paracoccaceae, Flavobacteriaceae, Nitrosomonadaceae, and Nitrospiraceae. Furthermore, the IS-RAS increased the functional potential of bacterial nitrogen metabolism pathways, such as denitrification, nitrite reduction, nitrogen fixation, and nitrification, which were closely associated with the water quality parameters. This study indicated that the IS-RAS has the potential to improve the rearing water environment and enhance shrimp production at a low cost, providing guidance for the more effective use of the IS-RAS.