Effects of the photovoltaic fishery breeding model on intestinal microbiota structure and diversity in Litopenaeus vannamei

Effects of the photovoltaic fishery breeding model on intestinal microbiota structure and diversity in Litopenaeus vannamei | 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 Article Effects of the photovoltaic fishery breeding model on intestinal microbiota structure and diversity in Litopenaeus vannamei Zhongmeng Zhao, Xingyu Chen, Yongshuang Wang, Han Zhao, Huadong Li, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7881803/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 9 You are reading this latest preprint version Abstract The photovoltaic (PV) fishery breeding model integrates the generation of solar energy with aquaculture, yet its impacts on aquatic organisms remain poorly understood. This study investigated how PV panel shading affects the intestinal microbial ecosystem of Litopenaeus vannamei . We conducted a controlled 80-day experiment comparing shrimp reared under PV panels (ZG group) versus those reared in traditional open ponds (CK group), with quadruplicate 800 m² ponds per group under standardized conditions (80 shrimp/m², salinity 15–18‰). High-throughput 16S rRNA sequencing was employed to analyze microbial composition, diversity, and predicted functional profiles. The growth data revealed that the ZG group exhibited significantly shorter body length than the CK group after 20 days of culture ( P < 0.05), while body weight was significantly less after 16 days ( P < 0.05).‌ The results of the intestinal microbiota analysis showed that Proteobacteria and Firmicutes were the main components of the intestinal microbiota in the CK and ZG groups, while Oceanobacillus and Candidatus_Electronema were present as indicator species in the CK and ZG groups, respectively. Higher Chao1 and Shannon indices indicated that the ZG group improved the richness and uniformity of the L. vannamei intestinal flora. In addition, significant differences between the groups were detected by the β-diversity analysis. A predicted bacterial function analysis also revealed significant differences in functional abundance between the two groups. This study provides critical insight into how PV shading alters shrimp microbiota and growth performance, offering practical guidance for optimizing sustainable PV-aquaculture integrated systems. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Biological sciences/Microbiology Earth and environmental sciences/Ocean sciences Litopenaeus vannamei The photovoltaic fishery breeding model Intestinal microbiota Structural composition Diversity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Integrating photovoltaic (PV) systems with aquaculture is a promising approach for sustainable development, as it simultaneously addresses energy production and food security challenges. The PV fishery breeding model achieves clean energy and aquatic products while improving land-use efficiency 1 – 3 . However, the shading effect of PV panels significantly changes the light conditions in the aquaculture environment 4 , which influences physiology 5 , 6 . Current research has demonstrated the profound effects of light intensity on crustaceans. Studies on Jasus edwardsii and Scylla paramamosain have shown that low light levels during culture significantly enhance growth rate 7 , 8 . Wang et al. reported significant differences in the growth and exuviation of Fenneropenaeus chinensis under different light intensities, with optimal growth observed at light intensities ranging from 50 to 300 lx 8 . Gardner et al. showed that low light intensity promotes molting in Pseudocarcinus gigas larvae and reduces the rate of residual feeding 9 . In addition, Oreochromis niloticus and Paralichthys dentatus have lower plasma cortisol concentrations in darker environments 10 . Melanogrammus aeglefinus exhibits higher locomotor activity at 100 lx compared to 30 lx 11 . Despite these findings, a critical knowledge gap remains regarding how PV-induced light modulation affects the homeostasis of intestinal microbiota in commercially important species, such as Litopenaeus vannamei . L. vannamei belongs to the phylum Arthropoda, family Penaeidae, and is native to the tropical Pacific coast of western Latin America 12 . It is characterized by rapid growth, large size, broad salinity tolerance, and strong disease resistance. It is one of the most commonly cultured species in PV fishery breeding facilities in China. L. vannamei is prized for its delicious meat, high protein content, and low-fat levels, making it an ideal choice for a healthy nutritious diet 13 . The intestinal microbiota plays pivotal roles in nutrient absorption, immune function, and pathogen resistance 14 – 17 . We wanted to determine if the lower light induced by PV significantly changes the characteristics of the intestinal microbiota of shrimp, thereby promoting growth performance compared to a traditional pond system. Given the limited research on the dynamics of microbiota in PV aquaculture systems 18 , we analyzed the effect of a PV aquaculture system on the composition, with supplementary growth performance measurements (body length/weight) of L. vannamei . This study primarily elucidates how PV shading drives microbial composition/diversity shifts, while the growth data provide ancillary evidence for evaluating system productivity. The findings offer an empirical basis for optimizing PV-aquaculture practices and deepen our understanding of environment-microbiota interactions in commercially important species. 2. Methods 2.1 Animal materials L. vannamei were collected from Wenchun Town, Taishan City, Guangdong Province, China. Four ponds each were allocated to the experimental group (ZG) and the control group (CK), respectively. All ponds were standardized cement pools, with a single pool area of 800 m 2 (40 × 20 m), a water depth of 1.2 m, and equipped with an oxygen generator and a water-circulating system. The ZG was equipped with an overhead PV panel system covering 50% of the pond surface, whereas the CK was cultured in a traditional open-air aquaculture pond structure. The water source for the two groups was the same (salinity, 15–18‰, and 80 shrimp/m 2 stocking density; body length 1.2 ± 0.3 cm). The water-circulating system maintained a partial water exchange rate of 10% daily, with complete water replacement every 10 days to ensure stability of the microbial community. This protocol was applied to the ZG and CK groups to eliminate water renewal frequency as a confounding variable. The water temperature was measured using a HOBO U22-001 high-precision temperature recorder (± 0.2℃). Fixed monitoring points were set at two depths: the surface layer (0.2 m) and the bottom layer (1.0 m) of the breeding pool (the ZG group was placed under the PV panels). The temperature was automatically recorded every 10 minutes. Continuous monitoring was conducted from 08:00 to 18:00 every day, and a YSI Pro2030 handheld water quality analyzer was used for manual calibration (3 times per week) simultaneously. All data were verified by the NIST standard temperature source and averaged daily for analysis. A standardized diet (30% crude protein, 08:00/20:00) was administered throughout the trial. Residual feed was quantified daily by feeding observation logs, and feeding regimens were adjusted accordingly. Morphometric measurements ‌(including body length and body weight) of L. vannamei were made during the culture period. Sampling frequency was daily for the initial 20 days and every fifth day thereafter. Measurements were performed between 08:00 and 10:00 hours. Five individuals were randomly selected from each culture pond. Body length (postorbital carapace to the telson tip) was measured using a digital caliper (precision: ±0.01 mm) and recorded. Body weight (wet weight) was determined using an electronic balance (precision: ±0.01 g) following a 12-hour postprandial fasting period. Due to the small size of the shrimp during the first 20 days, weight data were obtained via pooled weighing of ten shrimp per sample, with individual weights calculated subsequently. Shrimp were weighed separately after 20 days of culture. Five replicates per sampling event were performed for weight measurements within each pond. After the 80-day culture experiment, 16 L. vannamei with a healthy appearance, intact appendages, and consistent size were randomly selected from the two groups. Specifically, the body length and weight of L. vannamei in the ZG were (10.54 ± 0.37) cm and (20.00 ± 1.15) g, respectively. The body length and weight of shrimp in the CK were (12.32 ± 0.54) cm and (22.98 ± 0.64) g, respectively. Four L. vannamei were collected from each breeding pool to constitute one biological sample. Four such samples were collected from each culture model as experimental replicates. The intestinal contents were collected under sterile conditions and immediately flash-frozen in liquid nitrogen for the intestinal microbiota analysis. 2.2 Intestinal microbiota DNA was extracted using the HiPure Stool DNA Kit(D5625-01) (Magen, Guangzhou, China) kit. Primers 338F (5'- CCTACGGGNGGCWGCAG − 3') and 806R (5'- GGACTACHVGGGTATCTAAT − 3') were used to amplify the V3-V4 region of 16S rRNA. Paired-end sequencing (2×250 bp) was performed on an Illumina NovaSeq 6000 platform using the NovaSeq 6000 SP Reagent Kit (500 cycles). The primers used were taken from Guo et al. (2017) 2 . The resulting amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions, and quantified using the ABI StepOnePlus Real-Time PCR System (Life Technologies, Foster City, CA, USA). The purified amplicons were pooled in equimolar quantities and pair-end sequenced (PE250) on the Illumina platform according to the standard protocol. 2.3 Data analysis The operational taxonomic units (OTUs) were classified at the species level through taxonomic classification and annotation against the database. Stacked bar charts of the microbial species distribution for each group were generated at the phylum and genus levels 19 – 21 . The labdsv package in R (The R Foundation for Statistical Computing, Vienna, Austria) was used to calculate the indicator values for each species across the different groups. A 10-fold cross-validation approach was applied to assess species differentiation 22 , 23 . The Chao1 and Shannon indices were calculated in QIIME (version 1.9.1) 24 . The OTU rarefaction and rank abundance curves were plotted in R using the ggplot2 package (version 2.2.1). The alpha index comparison between groups was calculated using Welch’s t -test and the Wilcoxon rank test using the vegan package in R (version 2.5.3) 25 . The bacterial community compositions were ordinated by principal coordinate analysis (PCoA) based on the Bray-Curtis dissimilarity values. Permutational multivariate analysis of variance was performed to examine the differences in microbial community composition among the different groups based on the Bray-Curtis dissimilarities using the ‘adonis’ function in the vegan package 25 , 26 . The KEGG pathway analysis of the OTUs was inferred using Tax4Fun (version 1.0) or PICRUSt 27 , 28 . The analysis of functional differences between groups was calculated by Tukey’s HSD test in R using the vegan package (version 2.5.3) 25 . The network was constructed with a Pearson’s correlation coefficient exceeding 0.9 and a significance level of p -value less than 0.05. The network was visualized using igraph 29 . 3. Results 3.1 The growth conditions of L. vannamei under different light conditions Water temperature monitoring revealed significantly higher mean values in the CK than the ZG group over the 80-day culture period. The CK group exhibited an average surface water temperature increase of 0.85°C and an average bottom water temperature increase of 0.76°C relative to the ZG group (Fig. S1 ).‌ ‌Morphometric analysis of L. vannamei indicated significant growth differences between the groups. The body length of L. vannamei was significantly shorter in the ZG group than that in the CK group on day 20 of culture (Fig. 2 A). Similarly, body weight measurements indicated significantly lower values in the ZG group starting on day 16 post-stocking (Fig. 2 B). 3.2 The 16S rRNA sequencing data of the L. vannamei intestinal microbiota under different light conditions We obtained 1,033,325 raw tags and 1,032,822 clean tags from the intestines of eight L. vannamei . After removing the chimeric tags detected in the clustered analog pairs, 960,147 valid tags were obtained. Additionally, we calculated the number of OTUs and the coverage rate of each sample exceeded 99.94% (Table 1 ). Rank abundance curves were generated for all samples based on the OTU abundance and ranking to illustrate species richness and evenness. Figure 3 provides an overview of the species composition in each sample. Table 1 Number of raw tags, clean tags, effective tags, OTUs, and Good’s coverage for the 16S rRNA libraries from the L. vannamei samples. Samplings Raw Tags Clean Tags Effective Tags OTUs Good’s Coverage (%) CK1 125121 124714 119001 1105 99.95 CK-2 123694 123218 115327 1260 99.96 CK-3 134894 134280 126682 1156 99.95 CK-4 122882 122392 117873 845 99.95 ZG-1 130490 129767 121486 1379 99.94 ZG-2 128480 127935 119562 1354 99.96 ZG-3 127698 127113 120977 1019 99.95 ZG-4 132074 131421 119239 1613 99.95 3.3 Differences in the L. vannamei intestinal microbiota composition under different light conditions The cumulative abundance of the top ten bacterial phyla in the intestinal microbiota of the treatment groups exceeded 94%, and Proteobacteria was the most dominant. The abundance of Proteobacteria and Firmicutes decreased, whereas Verrucomicrobiota increased in the ZG group compared with the control group (Fig. 4 A). Aeromonas and Vibrio were the dominant genera in the treatment groups. The abundance of Aeromonas , Vibrio , Bacillus , and Staphylococcus decreased in the ZG, while LD29 , Thioclava , and Rhodobacter increased (Fig. 4 B). Additionally, 244 bacterial genera were shared between the two treatment groups (Fig. 4 C). The indicator species analysis, based on species abundance and occurrence frequency, revealed that Oceanobacillus had the highest indicator value in the CK, whereas C._Electronema had the highest indicator value in the ZG. This result indicates that Oceanobacillus and C._Electronema could serve as indicator species for the CK and ZG groups, respectively (Fig. 4 D). 3.4 Diversity analysis of the L. vannamei intestinal microbiota under different light conditions The Chao1 and Shannon alpha diversity indices (Fig. 5 A-B) increased in the ZG group, indicating that the PV fishery model enhanced the richness and evenness of the L. vannamei intestinal microbiota. Closer samples had more similar microbiomes. The PcoA based on OTU abundance revealed clear separation between the groups, while samples within each group clustered closely together (Fig. 5 D). The Adonis analysis revealed a significant overall difference in the intestinal microbiota between the ZG and CK groups (Fig. 5 C). Additionally, bacterial phylogenetic tree analysis of L. vannamei indicated that the abundance of Fimbriiglobus , Butyrivibrio , Desulfomicrobrio , Bdellovibrio , and Chryseolinea was significantly higher in the ZG than the CK. In contrast, the abundance of Mariniradius , Muribaculum , Parabacteroides , Nonomuraea , and Cloacibacillus was significantly lower in the ZG than in the CK (Fig. 5 G). 3.5 Predicting L. vannamei intestinal microbiota function under different light conditions To further investigate the effect of light on the intestinal microbiota of L. vannamei , we predicted bacterial functions and assessed whether the light treatments affected the functionality of the intestinal microbiota. The predictive functional analysis revealed that metabolism and cellular processes were dominant across all groups. Using analysis of variance and Tukey’s HSD test, we detected the significant differences among the eight most abundant bacterial functions in the groups. The results indicated that the functional abundances of bacterial chemotaxis, the bacterial secretion system, cysteine and methionine metabolism, riboflavin metabolism, nitrogen metabolism, cyanoamino acid metabolism, the phosphotransferase system, and plant-pathogen interactions decreased significantly under the PV fishery breeding model (Fig. 6 A). Furthermore, the bacterial interaction analysis revealed distinct topological architectures, including differences in node connectivity and edge distribution, between CK and ZG groups. The CK network consisted of 227 nodes and 2,497 edges, whereas the ZG network contained 192 nodes and 1,379 edges. These results indicated significantly higher connectivity in the CK network (Fig. 6 B and 6 C). Specifically, in the CK network, the strongest interactions were observed between Firmicutes and Proteobacteria, within Firmicutes (intra-phylum), and between Actinobacteriota and Firmicutes (Fig. 6 B). In contrast, the strongest interactions in the ZG network occurred between Firmicutes and Proteobacteria, within Proteobacteria (intra-phylum), and between Actinobacteriota and Proteobacteria associations (Fig. 6 C). 4. Discussion Photoperiod was first studied in plants, where it affects physiological activities such as flowering and fruiting 30 . However, light is an important environmental factor that cannot be ignored for the health and development of aquatic animals 31 . Wang et al. reported that the most suitable growth environment for the intensive farming of Marsupenaeus japonicas is total darkness 32 . Wu et al. showed that Cherax quadricarinatus shrimp have the lowest survival rate and the slowest growth rate under full darkness 33 . In this study, measurements of body length and body weight indicated that the growth rate of L. vannamei in the PV fishery model was slower than that in the traditional pond culture model. This result sugges ts that light availability under the PV panels may adversely affect the growth of L. vannamei . Previous studies have showed that light environment variations can influence the growth of aquatic organism by modulating digestive enzymes activity 34 – 36 . For instance, protease facilitates proteins hydrolysis into amino acids, thereby promoting nutrient absorption in aquatic organisms 34 . Specifically, α-amylase (AMS) primarily catalyzes the hydrolysis of starch and glycogen 35 , and lipse (LPS) catalyzes lipid hydrolysis of aquatic organisms, converting it into energy substrates to support growth 36 . Reduced light conditions under PV panels may suppress the activity of these enzymes, thereby impairing digestive efficiency and overall growth in L. vannamei . Meanwhile, light exposure may also affect the growth of L. vannamei by influencing its feeding behavior, and future studies could incorporate continuous feeding monitoring to better characterize this relationship 37 . For crustaceans, temperature is an especially crucial environmental factor. Due to their unique molting-based growth and developmental mechanism, crustaceans exhibit high sensitivity to temperature throughout their entire life cycle. Within the optimal thermal range, the growth and development rates of species, including L. vannamei and Penaeus japonicus , exhibit a positive correlation with water temperature 38 , 39 . In this study, recorded aquaculture water temperatures revealed that the average water temperature in the PV fishery model was lower than that in the traditional pond culture model, which may account for the observed differences in the growth performance of L. vannamei between the two models. However, when water temperature exceeds the physiological tolerance threshold of shrimp, their metabolic rate may exceed their assimilation rate. Under such conditions, energy is expended rapidly and cannot be stored, ultimately adversely affecting growth. Moreover, excessively high temperatures can cause tissue damage and disrupt normal physiological functions, leading to growth inhibition and reduced survival rates 40 . In addition, a large number of research indicates that water temperature affects the antioxidant defense systems of both fish and crustaceans. Adverse water temperature conditions and abrupt temperature fluctuations can induce oxidative stress responses 41 . In the present study, the composition and structure of the L. vannamei intestinal microbiota were significantly different between the PV fishery model and the traditional pond culture model. Although the relative intestinal abundance of Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes varied between the two culture modes, these phyla consistently dominated the bacterial community. This is similar to the results of studies in Scophthalmus maximus 42 , hybrid grouper 43 , Eriocheir sinensis 44 , Penaeus monodon 45 and Macrobrachium rosenbergii 46 . Under the PV fishery model, reduced light availability caused by shading is likely to suppress primary production, thereby driving a compositional shift in the microbial community toward K-strategists (e.g., Verrucomicrobiota). These bacteria are characterized by slow growth rates and strong competitiveness, typically adapting to relatively stable environments. In contrast, frequent water disturbances of traditional aquaculture models may promote the proliferation of r-strategists (e.g., Proteobacteria), which exhibit high reproductive rates but lower competitive ability 47 . This structural change may have originated from two aspects of light regulatory mechanisms. One is that shading reduces the intensity of photosynthesis in water, inhibits the proliferation of light-dependent bacteria (such as Rhodobacter ), and simultaneously promotes expansion of the ecological niche of anaerobic bacteria (such as Microphylum acuminatum ) 48 . Second, changes in light intensity regulate the secretion of immune factors through the opsin pathway in shrimp, indirectly affecting the colonization environment 49 – 51 . The number of Aeromonas in the L. vannamei intestine decreased after shading, and some species of Aeromonas promote digestion, absorption and metabolism in the host 52 . Notably, the abundance of opportunistic pathogenic bacteria, such as Aeromonas and Vibrio , decreased in the PV aquaculture mode, which was consistent with the correlation between pathogenic bacteria and the Macrobrachium rosenbergii culture environment 53 – 56 . The nitrogen cycling function of Thioclava and the photosynthetic oxygen production characteristics of Rhodobacter may together improve the microenvironment of the culture water, but further data on dissolved oxygen and ammonia nitrogen levels are needed for support 57 , 58 . Although the ecological functions of Vibrio and related genera have been previously documented 59 , this study is the first to report a negative correlation between their temporal dynamics of Vibrio and the abundance of photosynthetic bacteria ( Rhodobacter ) in water column under the PV model. This finding suggests that reduced light availability may influence microbial community interactions and implies a potential regulatory mechanism through which light conditions could be manipulated to suppress opportunistic pathogens. Alpha diversity provides a comprehensive assessment of intestinal microbiota by measuring richness, diversity, and evenness 60 , while beta diversity reflects variations in microbial composition among different groups 60 . In this study, the alpha diversity analysis revealed that the Chao1and Shannon indices of the intestinal microbiota in L. vannamei cultured in the PV fishery model were higher than those in the traditional pond aquaculture model. The higher Shannon index suggests a more balanced composition, which may help suppress the competitive advantage of opportunistic pathogens 48 , 61 . Additionally, the higher Chao1 index suggests a higher proportion of rare species, which, despite being less abundant, may contribute to functional redundancy and enhance the stability of the microbiota under stress conditions 62 , 63 . However, although the α-diversity index increased in the PV farming model, higher diversity does not necessarily directly equate to improved health; it may reflect the recombination of the microbiota caused by an environmental disturbance 64 . This study demonstrates that the PV fishery model induces significant alterations in the intestinal microbiota of L. vannamei , characterized by increased α-diversity and altered community structure. Although these microbial changes are initially associated with reduced growth rates, they appear to promote the establishment of a more stable and pathogen-resistant gut ecosystem, as indicated by the suppression of Vibrio populations and the enrichment of functional taxa like Verrucomicrobiota 65 , 66 . This trade-off between short-term growth performance and long-term health benefits reflects ecological adaptation strategies, where environmental stressors trigger adaptive microbial reorganization. Future research should prioritize the development of optimized light regimes to balance these ecological trade-offs, potentially through intermittent illumination protocols that maintain beneficial microbial functions while minimizing growth inhibition 67 . These findings offer valuable insights into the development of ecologically sustainable aquaculture practices by leveraging light-microbiota-host interactions. 5. Conclusion This 80-day aquaculture experiment systematically evaluated the effects of photovoltaic shading on L. vannamei . This results showed that the PV fishery breeding model (ZG) exhibited lower water temperatures compared to the traditional pond culture model (CK), leading to reduced growth in body length and weight. However, it significantly enhanced the α-diversity of the shrimp’s intestinal microbiota. Microbial profiling demonstrated substantial declines in potential pathogens ( Vibrio and Aeromonas ), increased abundance of beneficial taxa ( Thioclava and Verrucomicrobiota ), and specific enrichment of C._Electronema as a biomarker in the PV model. While 244 core genera with essential ecological functions were shared between both models, the observed reductions in Proteobacteria and Firmicutes abundance under the PV model suggest that light-induced changes in water temperature may modulate shrimp energy allocation though temperature-microbiota interactions. These findings imply that a moderate trade-off growth performance may be compensated by enhanced microbial stability and disease resistance, providing a critical ecological rationale for the adoption of integrated PV fishery breeding model. Declarations Author contributions Z.Z.M., and L.Q. conceived and designed research. Z.Z.M., Z.H., W.Y.S, and C.X.Y. conducted experiments. Z.Z.M., Z.H., L. H. D., D.Y.L., H.Z.P., Z.L., and Z.J. analyzed data. Z.Z.M., C.X.Y., and L.Q. wrote the manuscript. All authors read and approved the manuscript. Funding This research was supported by Innovation of High Quality Fish Breeding Materials and Methods and Selection of New Varieties (Breeding Research Project) (2021YFYZ0015) and Sichuan Freshwater Fish Innovation Team of the National Modern Agricultural Industrial Technology System (SCCXTD-2025-15). In addition, We would like to thank Tongwei New Energy Co., Ltd. For their financial support in this study. Data availability The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (CRA024106) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa. Ethical approval. All animal handling procedures were approved by the Animal Care and Use Committee of the Fisheries Research Institute, Sichuan Academy of Agricultural Sciences (20220323002A), following the recommendations in the U.K. Animals (Scientific Procedures) Act, 1986. At the same time, all methods were carried out by relevant guidelines and regulations. Competing interests The authors declare no competing interests. References Jingwen, B. "Integrating fishing and light" to create a new model of industrial development. Solar Energy , 67+69 (2016). Mengjiao, G. et al. Bacillus subtilis Improves Immunity and Disease Resistance in Rabbits. Frontiers in Immunology 8 , 354 (2017). Duo, H. “Integration of fish and light” to promote the transformation and upgrading of aquaculture. China Fishery News , 106-108 (2016). Gilles Boeuf & Bail, P.-Y. L. Does light have an influence on fish growth? Aquaculture 177 , 129-152 (1999). Blaxter, J. H. S. Visual Thresholds and Spectral Sensitivity of Herring Larvae. Journal of Experimental Biology 51 , 39-53 (1968). Mcfarland, W. N. Light in the Sea-Correlations with Behaviors of Fishes and Invertebrates. American Zoologist 26 , 389-401 (1986). Moss, G. A., Tong, L. J. & Illingworth, J. Effects of light intensity and food density on the growth and survival of early-stage phyllosoma larvae of the rock lobster Jasus edwardsii . Marine Freshwater Research 50 , 129-134 (1999). Wang, F. et al. The effect of light intensity on the growth of Chinese shrimp Fenneropenaeus chinensis . Aquaculture 234 , 475-483 (2004). Gardner, C. & Maguire, G. B. Effect of photoperiod and light intensity on survival, development and cannibalism of larvae of the Australian giant crab Pseudocarcinus gigas (Lamarck). Aquaculture 165 , 51-63 (1998). Mclean, E., Cotter, P., Thain, C. & King, N. Tank color impacts performance of cultured fish. Ribarstvo 2 , 43-54 (2008). Wei Hui et al. Effects of light intensity on phototaxis, growth, antioxidant and stress of juvenile gibel carp (Carassius auratus gibelio). Aquaculture 501 , 39-47 (2019). Kr, M., Sunar, M. C., Topuz, M. & Saripek, M. Thermal acclimation capacity and standard metabolism of the Pacific white shrimp Litopenaeus vannamei (Boone, 1931) at different temperature and salinity combinations. Journal of Thermal Biology 112 , 103429 (2023). Dong, X., Wang, J. & Raghavan, V. Impact of microwave processing on the secondary structure, in-vitro protein digestibility and allergenicity of shrimp ( Litopenaeus vannamei ) proteins-ScienceDirect. Food Chemistry 337 , 127811 (2021). Rawls, J. F., Samuel, B. S. & Gordon, J. I. Gnotobiotic zebrafish reveal evolutionarily conserved responses to the gut microbiota. Proceedings of the National Academy of Sciences of the United States of America 101 , 6 (2004). Xuemei, L. et al. Gut Microbiota Contributes to the Growth of Fast-Growing Transgenic Common Carp ( Cyprinus carpio L. ). Plos One 8 , e64577-e64577 (2013). Luan, Y. et al. The fish microbiota: research progress and potential applications. Engineering 29 , 137-146 (2023). Rubio-Portillo, Josefa Sanchez Jerez & Pablo. Exploring changes in bacterial communities to assess the influence of fish farming on marine sediments. Aquaculture 506 , 459-464 (2019). Toni, M. et al. Review: Assessing fish welfare in research and aquaculture, with a focus on European directives. Cambridge University Press 13 , 161-170 (2019). Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol 73 , 5261-5267 (2007). Elmar, P. et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35 , 7188-7196 (2007). Ondov, B. D., Bergman, N. H. & Phillippy, A. M. Interactive metagenomic visualization in a Web browser. Bmc Bioinformatics 12 , 385 (2011). Chen, H. B. & Boutros, P. C. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. Bmc Bioinformatics 12 , 35 (2011). Conway, J. R., Lex, A. & Gehlenborg, N. UpSetR: an R package for the visualization of intersecting sets and their properties. Bioinformatics 33 , 2938-2940 (2017). Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature methods 7 , 335-336 (2010). Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P. & Stevens, W. H. H.(2010): Vegan: Community Ecology Package. R package, version 1.17-4. http://cran . r-project. org>. Acesso em , 2010 (2010). Wickham, H. ggplot2. Wiley Interdisciplinary Reviews: Computational Statistics 3 , 180-185 (2011). Aßhauer, K. P., Wemheuer, B., Daniel, R. & Meinicke, P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. Bioinformatics 31 , 2882-2884 (2015). Langille et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature biotechnology 31 , 814-821 (2013). Shen, W. et al. The impact of microplastic and sulfanilamide co-exposure on soil microbiota. Ecotoxicology Environmental Safety 292 , 117968 (2025). Liu Li & Pengfang, Z. Relationship between photoperiod and plant floral induction. Liaoning Agricultural Sciences , 26-27 (2004). Adair, K. L. & Douglas, A. E. Making a microbiome: the many determinants of host-associated microbial community composition. Current Opinion in Microbiology 35 , 23-29 (2017). Wang Xiang, Ren Xianyun, Sheng Xiuzhen, Li Cuiping & Jian, L. Effects of different photoperiods on growth, molting and glucose metabolism of Marsupenaeus japonicus . Progress in Fishery Sciences 41 , 66-73, doi:10.19663/j.issn2095-9869.20190902001 (2020). Wu Zhixin, Chen Xiaoxuan, Liu Xiaoling, Mei Xiaohua & Xiqun, C. Effects of different photoperiods on reproduction and growth of Cherax quadricarinatus . Freshwater Fisheries 30 , 4-5 (2000). Shukun, Y. The latest research and application progress of feed protease. Feed Industry 40 , 22-26, doi:10.13302/j.cnki.fi.2019.10.005 (2019). Chunlei;, L. & Yutuo, W. Research progress on classi fication and application of amylase. Guangxi Science 25 , 248-252, doi:10.13656/j.cnki.gxkx.20180531.002 (2018). Zishe;, W., Ji;, Z., Junyi;, M. & Rui, S. Research and application progress of lipase. Journal of Anhui Agri cultural Sciences 39 , 3798-3800+3855, doi:10.13989/j.cnki.0517-6611.2011.07.004 (2011). Yanling, T. et al. The influence of light intensity and shelter on habitat and feeding behavior of the spiny lobster ( Panulirus homarus ). Journal OF Dalian Ocean University 40 , 382-389, doi:10.16535/j.cnki.dlhyxb.2024-285 (2025). Jesus;, P.-P., A., M.-P. C., and & G., R. L. The effects of salinity and temperature on the growth and survival rates of juvenile white shrimp, Penaeus vannamei , Boone, 1931. Aquaculture 157 , 107-115 (1997). Coman G J, Crocos P J & P, P. N. The effects of temperature on the growth, survival and biomass of different families of juvenile Penaeus japonicus Bate. Aquaculture 214 , 185-199 (2002). Zhiguo;, L., Chengsong;, Z., Yan;, Z., Fuhua;, L. & Jianhai, X. Effects of temperature on embryonic and larval development of the Exopalaemon carinicauda (Holthuis) Repopts 37 , 9-16 (2013). Bowden, T. J. Modulation of the immune system of fish by their environment. Fish Shellfish Immunology 25 , 373-383 (2008). Li, Y. et al. Effects of dietary glycinin on the growth performance, digestion, intestinal morphology and bacterial community of juvenile turbot, Scophthalmus maximus L. Aquacultur , 125-133 (2017). He, Y. et al. Glutamine improves growth and intestinal health in juvenile hybrid groupers fed high-dose glycinin. Fish Shellfish Immunology , 141 (2023). A, F. H. et al. Sodium butyrate can improve intestinal integrity and immunity in juvenile Chinese mitten crab ( Eriocheir sinensis ) fed glycinin-ScienceDirect. Fish Shellfish Immunology , 400-411 (2020). Rungrassamee, W., Klanchui, A., Maibunkaew, S., Chaiyapechara, S. & Karoonuthaisiri, N. Characterization of Intestinal bacteria in wild and domesticated adult black Tiger Shrimp ( Penaeus monodon ). PLoS ONE 9 , e91853 (2014). Jingfeng, Y. The study on immune effects, feeding physiology and intestinal health of soybean antigen protein on giant freshwater prawn (Macrobrachium rosenbergii) , Shanghai Ocean University, (2018). Chaiyapechara, S., Uengwetwanit, T., Arayamethakorn, S., Bunphimpapha, P. & Rungrassamee, W. Understanding the host-microbe-environment interactions: Intestinal microbiota and transcriptomes of black tiger shrimp Penaeus monodon at different salinity levels. Aquaculture 546 , 737371 (2021). Kolda, A., Gavrilovi, A., Jug-Dujakovi, J., Ljubei, Z. & Kapetanovi, D. Profiling of bacterial assemblages in the marine cage farm environment, with implications on fish, human and ecosystem health. Ecological Indicators 118 , 106785 (2020). Suhn, K. & Hyeyoung, K. Inhibitory effect of astaxanthin on oxidative stress-induced mitochondrial Dysfunction-A Mini-Review. Nutrients 10 , E1137 (2018). Bendich & Adrianne. Physiological role of antioxidants in the immune system. Journal of Dairy Science 76 , 2789-2794 (1993). Vazquez, L., Alpuche, J., Maldonado, G., Agundis, C. & Zenteno, E. Review: Immunity mechanisms in crustaceans. Innate Immunity 15 , 179-188 (2009). Koca S B, Yigit N Ö & I, D. B. Effects of enzyme-producing probiotic bacteria isolated from the gastrointestinal tract of trout on the growth performance, survival, and digestive enzyme activity of rainbow trout fry ( Oncorhynchus mykiss ). Israeli Journal of Aquaculture-Bamidgeh 352 , 1-9 (2015). B., V., Sai, P. G., P., R. & G., B. Antibacterial activity of Allium sativum against multidrug-resistant Vibrio harveyi isolated from black gill–diseased Fenneropenaeus indicus. Aquaculture International 19 , 531-539 (2011). Kuebutornye, F. K. A., Abarike, E. D. & Lu, Y. A review on the application of Bacillus as probiotics in aquaculture. Fish & Shellfish Immunology 87 , 820-828 (2019). Huttenhower, C., Gevers, D., Knight, R., Abubucker, S. & Badger, J. H. Structure, function and diversity of the healthy human microbiome. Progress in Molecular Biology and Translational Science 191 , 53-82 (2012). Green, T. J. et al. Simulated marine heat wave alters abundance and structure of Vibrio populations associated with the pacific oyster resulting in a mass mortality event. Microbial Ecology 77 , 736-747 (2018). Sorokin D Y & P., T. T. Thioclava pacifica gen. nov., sp. nov., a novel facultatively autotrophic, marine, sulfur-oxidizing bacterium from a near-shore sulfidic hydrothermal area. International Journal of Systematic and Evolutionary Microbiology 55 , 1069-1075 (2005). Cao Haipeng, Zhang Shuying, Yu Jingjing & Jian, A. Isolation, identification and detoxification of a trichlorphon-tolerant Rhodobacter Sphaeroides XR12. Acta Hydrobiologica Sinica 44 , 59-66 (2020). Dai, L. et al. Pathogenicity and transcriptomic exploration of Vibrio fortis in Penaeus monodon . Fish Shellfish Immunology 142 , 109097 (2023). Willis, K. J. & Whittaker, R. J. Ecology. Species diversity--scale matters. Science 295 , 1245-1248 (2002). Suo, Y. et al. Response of gut health and microbiota to sulfide exposure in Pacific white shrimp Litopenaeus vannamei . Fish Shellfish Immunology 63 , 87-96 (2017). Fergus, S. Probiotics in perspective. Gastroenterology 139 (2010). Quero, G. M., Ape, F., Manini, E., Mirto, S. & Luna, G. M. Temporal changes in mcrobial communities beneath fish farm sediments are related to organic enrichment and fish biomass over a production cycle. Frontiers in Marine Science 7 , 524 (2020). Xiong, J., Wang, K., Wu, J., Qiuqian, L. & Zhang, D. Changes in intestinal bacterial communities are closely associated with shrimp disease severity. Applied Microbiology Biotechnology 99 , 6911-6919 (2015). Qu Biao et al. Effect of“Fishing light complementary”on plankton in catfish pond. Journal of Aquaculture 36 , 6-9 (2015). Kyle F. Edwards, Mridul K. Thomas, Christopher A & Elena, K. Phytoplankton growth and the interaction of light and temperature: A synthesis at the species and community level. Limnology Oceanography 61 , 1232-1244 (2016). Wang, Y. B., Li, J. R. & Lin, J. Probiotics in aquaculture: Challenges and outlook. Aquaculture 281 , 1-4 (2008). Additional Declarations No competing interests reported. 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08:54:08","extension":"png","order_by":26,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":397139,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig.5.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/b6743158973ba84f56f750e0.png"},{"id":96979172,"identity":"b844cde3-0de3-4e24-b370-ff6046544877","added_by":"auto","created_at":"2025-11-28 08:54:12","extension":"png","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":269769,"visible":true,"origin":"","legend":"","description":"","filename":"OnlineFig.6.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/7073600465ec1ad5988636d6.png"},{"id":96979240,"identity":"c49d26b5-e34a-4a02-a5c6-da92a04c0e3e","added_by":"auto","created_at":"2025-11-28 08:54:16","extension":"png","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66839,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/2256272cb7d46e176c11184d.png"},{"id":96979125,"identity":"ae7c7edf-7957-4aa4-8832-52b1675ef25c","added_by":"auto","created_at":"2025-11-28 08:54:10","extension":"png","order_by":29,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":38162,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/dec3e0cc0900a860f5dd6bb1.png"},{"id":96979126,"identity":"bbfc06ef-38d7-450b-a475-9f7cb886f5e4","added_by":"auto","created_at":"2025-11-28 08:54:10","extension":"png","order_by":30,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":82604,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/d2f9dc63baa042b631c76988.png"},{"id":96979054,"identity":"db4bf2b2-4b39-451c-b8d5-885b34e2c690","added_by":"auto","created_at":"2025-11-28 08:54:07","extension":"png","order_by":31,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":44938,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/c7de525742cff66db4ce5cce.png"},{"id":96979158,"identity":"5e018d0b-0d5f-44f5-bf59-7fd8d0480fc5","added_by":"auto","created_at":"2025-11-28 08:54:11","extension":"png","order_by":32,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":445992,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/e9e09f9f4a47182cc092c404.png"},{"id":96979177,"identity":"95386d17-5303-4c55-8fb0-a7e6a2a12dc2","added_by":"auto","created_at":"2025-11-28 08:54:12","extension":"png","order_by":33,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":293816,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/ea83040be2271b8406fbf461.png"},{"id":96979229,"identity":"19dfd6a8-5e81-42c8-aa29-5535bfc91bfc","added_by":"auto","created_at":"2025-11-28 08:54:14","extension":"xml","order_by":34,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":135059,"visible":true,"origin":"","legend":"","description":"","filename":"f732bd0269b040e6a0aa0a41786790c41structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/761b9f17c756a16bd4bf63d7.xml"},{"id":96979254,"identity":"9a1ec25d-472b-421f-a470-c31ac8907643","added_by":"auto","created_at":"2025-11-28 08:54:17","extension":"html","order_by":35,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":149866,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/3217bbb195b5d16e11b053f3.html"},{"id":96979225,"identity":"68efff2d-fb12-482c-af9d-4727debaf36e","added_by":"auto","created_at":"2025-11-28 08:54:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":191255,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental procedure. The \u003cem\u003eL. vannamei\u003c/em\u003e were placed in the ponds of the photovoltaic fishery model and the ordinary pond culture model, and their intestinal tracts were excised for analysis after 80 days. \u003cem\u003eL. vannamei\u003c/em\u003e growth performance and water temperature data were recorded during the culture period.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/964ca8d29c2a4770bcec8fc8.png"},{"id":96979222,"identity":"d3e1e8b4-295f-4b56-ad22-1dc22b9e6587","added_by":"auto","created_at":"2025-11-28 08:54:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":94873,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in body length and weight of \u003cem\u003eL. vannamei\u003c/em\u003e after 80 days of culture. A. Curve of the body length changes. B. Curve of the body weight changes.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/5a9ce40068bbe15e92c8b67c.png"},{"id":96979176,"identity":"494295b8-cc9f-48f6-aeb4-56bde5885466","added_by":"auto","created_at":"2025-11-28 08:54:12","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":107027,"visible":true,"origin":"","legend":"\u003cp\u003eDilution curves for the Sob index of the 16S rRNA gene MiSeq sequences from the different light condition samples. Different colored lines represent different samples. The horizontal and vertical coordinates represent the number of tags extracted and the number of tags extracted corresponding to the calculation of the diversity index value, respectively. CK: control group, ZG: 24-hour shading treatment.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/5785f9f92b1ed15238cd7655.png"},{"id":96979122,"identity":"f2cef5d2-e737-4af5-8273-6c5e0117a231","added_by":"auto","created_at":"2025-11-28 08:54:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":163275,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in the intestinal microbiota composition under the different light treatments. \u003cstrong\u003eA\u003c/strong\u003eDistribution of intestinal bacterial phyla in each sample of the experimental and control groups. \u003cstrong\u003eB\u003c/strong\u003e Distribution of intestinal bacteria genera in the treatment and control groups. \u003cstrong\u003eC\u003c/strong\u003eUpset plot of species composition between the treatment groups. \u003cstrong\u003eD\u003c/strong\u003eIndicator analysis between the treatment groups.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/eb10d04ff327d55062acf917.png"},{"id":96979179,"identity":"f7d0b43c-606c-434d-a53e-1fd7cbdc420a","added_by":"auto","created_at":"2025-11-28 08:54:12","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":391785,"visible":true,"origin":"","legend":"\u003cp\u003eDiversity of the gut bacteria in the treatment groups. \u003cstrong\u003eA\u003c/strong\u003e Box chart of the inter-group differences in the Chao 1 index. \u003cstrong\u003eB\u003c/strong\u003e Box chart of the inter-group differences in the Shannon index. \u003cstrong\u003eC\u003c/strong\u003e Adonis analyzed the explanatory power of the groups for sample differences and used the permutation test to detect differences between the groups. \u003cstrong\u003eD\u003c/strong\u003e Principal coordinates analysis between samples from the treatment groups. \u003cstrong\u003eE\u003c/strong\u003e Phylogenetic relationship among the genera of the horizontal species. A phylogenetic tree was constructed with representative sequences of the genera of the horizontal species. The colors of the branches and the fan-shaped branches represent the corresponding gates, and the stacking histogram outside the fan ring represents the abundance of the genus in the samples.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/57f3d32be787d8b068b7f441.png"},{"id":96979226,"identity":"236a8532-c47a-4d14-9792-df6a4a9063cb","added_by":"auto","created_at":"2025-11-28 08:54:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":260826,"visible":true,"origin":"","legend":"\u003cp\u003eFunctional prediction of the intestinal microbiota. A Tukey’s Honestly Significant Difference rank-sum test of the significance differences in functions between the groups. The eight functions predicted to have the highest abundance were compared for differences between the groups, with an asterisk indicating a difference. \u003cstrong\u003eB \u003c/strong\u003eNetwork diagram of the microbial community structure of Group CK. \u003cstrong\u003eC\u003c/strong\u003e Network diagram of the microbial community structure of Group ZG.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/f104f89458eff68eff4c85bc.png"},{"id":99545329,"identity":"ceb87f71-e4d3-497c-9aac-28e4f8320246","added_by":"auto","created_at":"2026-01-05 16:05:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2057274,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/7d11070d-e1dc-457a-9c9c-d03e615b5473.pdf"},{"id":97138184,"identity":"4c605ea3-f182-435c-9d5a-f7b39b858574","added_by":"auto","created_at":"2025-12-01 09:58:34","extension":"jpg","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":116266,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7881803/v1/28871952ab132f6ce02531c6.jpg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of the photovoltaic fishery breeding model on intestinal microbiota structure and diversity in Litopenaeus vannamei","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eIntegrating photovoltaic (PV) systems with aquaculture is a promising approach for sustainable development, as it simultaneously addresses energy production and food security challenges. The PV fishery breeding model achieves clean energy and aquatic products while improving land-use efficiency\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, the shading effect of PV panels significantly changes the light conditions in the aquaculture environment\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, which influences physiology\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCurrent research has demonstrated the profound effects of light intensity on crustaceans. Studies on \u003cem\u003eJasus edwardsii\u003c/em\u003e and \u003cem\u003eScylla paramamosain\u003c/em\u003e have shown that low light levels during culture significantly enhance growth rate\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Wang et al. reported significant differences in the growth and exuviation of \u003cem\u003eFenneropenaeus chinensis\u003c/em\u003e under different light intensities, with optimal growth observed at light intensities ranging from 50 to 300 lx\u003csup\u003e8\u003c/sup\u003e. Gardner et al. showed that low light intensity promotes molting in \u003cem\u003ePseudocarcinus gigas\u003c/em\u003e larvae and reduces the rate of residual feeding\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In addition, \u003cem\u003eOreochromis niloticus\u003c/em\u003e and \u003cem\u003eParalichthys dentatus\u003c/em\u003e have lower plasma cortisol concentrations in darker environments\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. \u003cem\u003eMelanogrammus aeglefinus exhibits higher locomotor activity at 100 lx compared to 30 lx\u003c/em\u003e\u003csup\u003e11\u003c/sup\u003e. Despite these findings, a critical knowledge gap remains regarding how PV-induced light modulation affects the homeostasis of intestinal microbiota in commercially important species, such as \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e. \u003cem\u003eL. vannamei\u003c/em\u003e belongs to the phylum Arthropoda, family Penaeidae, and is native to the tropical Pacific coast of western Latin America\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. It is characterized by rapid growth, large size, broad salinity tolerance, and strong disease resistance. It is one of the most commonly cultured species in PV fishery breeding facilities in China. \u003cem\u003eL. vannamei\u003c/em\u003e is prized for its delicious meat, high protein content, and low-fat levels, making it an ideal choice for a healthy nutritious diet\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe intestinal microbiota plays pivotal roles in nutrient absorption, immune function, and pathogen resistance\u003csup\u003e\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. We wanted to determine if the lower light induced by PV significantly changes the characteristics of the intestinal microbiota of shrimp, thereby promoting growth performance compared to a traditional pond system. Given the limited research on the dynamics of microbiota in PV aquaculture systems\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, we analyzed the effect of a PV aquaculture system on the composition, with supplementary growth performance measurements (body length/weight) of \u003cem\u003eL. vannamei\u003c/em\u003e. This study primarily elucidates how PV shading drives microbial composition/diversity shifts, while the growth data provide ancillary evidence for evaluating system productivity. The findings offer an empirical basis for optimizing PV-aquaculture practices and deepen our understanding of environment-microbiota interactions in commercially important species.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Animal materials\u003c/h2\u003e\u003cp\u003e\u003cem\u003eL. vannamei\u003c/em\u003e were collected from Wenchun Town, Taishan City, Guangdong Province, China. Four ponds each were allocated to the experimental group (ZG) and the control group (CK), respectively. All ponds were standardized cement pools, with a single pool area of 800 m\u003csup\u003e2\u003c/sup\u003e (40 \u0026times; 20 m), a water depth of 1.2 m, and equipped with an oxygen generator and a water-circulating system. The ZG was equipped with an overhead PV panel system covering 50% of the pond surface, whereas the CK was cultured in a traditional open-air aquaculture pond structure. The water source for the two groups was the same (salinity, 15\u0026ndash;18\u0026permil;, and 80 shrimp/m\u003csup\u003e2\u003c/sup\u003e stocking density; body length 1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 cm). The water-circulating system maintained a partial water exchange rate of 10% daily, with complete water replacement every 10 days to ensure stability of the microbial community. This protocol was applied to the ZG and CK groups to eliminate water renewal frequency as a confounding variable. The water temperature was measured using a HOBO U22-001 high-precision temperature recorder (\u0026plusmn;\u0026thinsp;0.2℃). Fixed monitoring points were set at two depths: the surface layer (0.2 m) and the bottom layer (1.0 m) of the breeding pool (the ZG group was placed under the PV panels). The temperature was automatically recorded every 10 minutes. Continuous monitoring was conducted from 08:00 to 18:00 every day, and a YSI Pro2030 handheld water quality analyzer was used for manual calibration (3 times per week) simultaneously. All data were verified by the NIST standard temperature source and averaged daily for analysis.\u003c/p\u003e\u003cp\u003eA standardized diet (30% crude protein, 08:00/20:00) was administered throughout the trial. Residual feed was quantified daily by feeding observation logs, and feeding regimens were adjusted accordingly. Morphometric measurements \u0026zwnj;(including body length and body weight) of \u003cem\u003eL. vannamei\u003c/em\u003e were made during the culture period. Sampling frequency was daily for the initial 20 days and every fifth day thereafter. Measurements were performed between 08:00 and 10:00 hours. Five individuals were randomly selected from each culture pond. Body length (postorbital carapace to the telson tip) was measured using a digital caliper (precision: \u0026plusmn;0.01 mm) and recorded. Body weight (wet weight) was determined using an electronic balance (precision: \u0026plusmn;0.01 g) following a 12-hour postprandial fasting period. Due to the small size of the shrimp during the first 20 days, weight data were obtained via pooled weighing of ten shrimp per sample, with individual weights calculated subsequently. Shrimp were weighed separately after 20 days of culture. Five replicates per sampling event were performed for weight measurements within each pond. After the 80-day culture experiment, 16 \u003cem\u003eL. vannamei\u003c/em\u003e with a healthy appearance, intact appendages, and consistent size were randomly selected from the two groups. Specifically, the body length and weight of \u003cem\u003eL. vannamei\u003c/em\u003e in the ZG were (10.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37) cm and (20.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15) g, respectively. The body length and weight of shrimp in the CK were (12.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54) cm and (22.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64) g, respectively. Four \u003cem\u003eL. vannamei\u003c/em\u003e were collected from each breeding pool to constitute one biological sample. Four such samples were collected from each culture model as experimental replicates. The intestinal contents were collected under sterile conditions and immediately flash-frozen in liquid nitrogen for the intestinal microbiota analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Intestinal microbiota\u003c/h2\u003e\u003cp\u003eDNA was extracted using the HiPure Stool DNA Kit(D5625-01) (Magen, Guangzhou, China) kit. Primers 338F (5'- CCTACGGGNGGCWGCAG \u0026minus;\u0026thinsp;3') and 806R (5'- GGACTACHVGGGTATCTAAT \u0026minus;\u0026thinsp;3') were used to amplify the V3-V4 region of 16S rRNA. Paired-end sequencing (2\u0026times;250 bp) was performed on an Illumina NovaSeq 6000 platform using the NovaSeq 6000 SP Reagent Kit (500 cycles). The primers used were taken from Guo et al. (2017)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The resulting amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer\u0026rsquo;s instructions, and quantified using the ABI StepOnePlus Real-Time PCR System (Life Technologies, Foster City, CA, USA). The purified amplicons were pooled in equimolar quantities and pair-end sequenced (PE250) on the Illumina platform according to the standard protocol.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data analysis\u003c/h2\u003e\u003cp\u003eThe operational taxonomic units (OTUs) were classified at the species level through taxonomic classification and annotation against the database. Stacked bar charts of the microbial species distribution for each group were generated at the phylum and genus levels\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The labdsv package in R (The R Foundation for Statistical Computing, Vienna, Austria) was used to calculate the indicator values for each species across the different groups. A 10-fold cross-validation approach was applied to assess species differentiation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. The Chao1 and Shannon indices were calculated in QIIME (version 1.9.1)\u003csup\u003e24\u003c/sup\u003e. The OTU rarefaction and rank abundance curves were plotted in R using the ggplot2 package (version 2.2.1). The alpha index comparison between groups was calculated using Welch\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test and the Wilcoxon rank test using the vegan package in R (version 2.5.3)\u003csup\u003e25\u003c/sup\u003e. The bacterial community compositions were ordinated by principal coordinate analysis (PCoA) based on the Bray-Curtis dissimilarity values. Permutational multivariate analysis of variance was performed to examine the differences in microbial community composition among the different groups based on the Bray-Curtis dissimilarities using the \u0026lsquo;adonis\u0026rsquo; function in the vegan package\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The KEGG pathway analysis of the OTUs was inferred using Tax4Fun (version 1.0) or PICRUSt\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The analysis of functional differences between groups was calculated by Tukey\u0026rsquo;s HSD test in R using the vegan package (version 2.5.3)\u003csup\u003e25\u003c/sup\u003e. The network was constructed with a Pearson\u0026rsquo;s correlation coefficient exceeding 0.9 and a significance level of \u003cem\u003ep\u003c/em\u003e-value less than 0.05. The network was visualized using igraph\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.1 The growth conditions of \u003cem\u003eL. vannamei\u003c/em\u003e under different light conditions\u003c/h2\u003e\u003cp\u003eWater temperature monitoring revealed significantly higher mean values in the CK than the ZG group over the 80-day culture period. The CK group exhibited an average surface water temperature increase of 0.85\u0026deg;C and an average bottom water temperature increase of 0.76\u0026deg;C relative to the ZG group (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u0026zwnj;\u003c/p\u003e\u003cp\u003e\u0026zwnj;Morphometric analysis of \u003cem\u003eL. vannamei\u003c/em\u003e indicated significant growth differences between the groups. The body length of \u003cem\u003eL. vannamei\u003c/em\u003e was significantly shorter in the ZG group than that in the CK group on day 20 of culture (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Similarly, body weight measurements indicated significantly lower values in the ZG group starting on day 16 post-stocking (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.2 The 16S rRNA sequencing data of the \u003cem\u003eL. vannamei\u003c/em\u003e intestinal microbiota under different light conditions\u003c/h2\u003e\u003cp\u003eWe obtained 1,033,325 raw tags and 1,032,822 clean tags from the intestines of eight \u003cem\u003eL. vannamei\u003c/em\u003e. After removing the chimeric tags detected in the clustered analog pairs, 960,147 valid tags were obtained. Additionally, we calculated the number of OTUs and the coverage rate of each sample exceeded 99.94% (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Rank abundance curves were generated for all samples based on the OTU abundance and ranking to illustrate species richness and evenness. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides an overview of the species composition in each sample.\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\u003eNumber of raw tags, clean tags, effective tags, OTUs, and Good\u0026rsquo;s coverage for the 16S rRNA libraries from the \u003cem\u003eL. vannamei\u003c/em\u003e samples.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSamplings\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRaw Tags\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eClean Tags\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEffective Tags\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOTUs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGood\u0026rsquo;s Coverage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e125121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e124714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e119001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCK-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e123694\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e123218\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e115327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCK-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e134894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e134280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e126682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCK-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e122882\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e122392\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e117873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e845\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZG-1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e130490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e129767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e121486\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZG-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e128480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e127935\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e119562\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.96\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZG-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e127698\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e127113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e120977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZG-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e132074\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e131421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e119239\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e99.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Differences in the \u003cem\u003eL. vannamei\u003c/em\u003e intestinal microbiota composition under different light conditions\u003c/h2\u003e\u003cp\u003eThe cumulative abundance of the top ten bacterial phyla in the intestinal microbiota of the treatment groups exceeded 94%, and Proteobacteria was the most dominant. The abundance of Proteobacteria and Firmicutes decreased, whereas Verrucomicrobiota increased in the ZG group compared with the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003cem\u003eAeromonas\u003c/em\u003e and \u003cem\u003eVibrio\u003c/em\u003e were the dominant genera in the treatment groups. The abundance of \u003cem\u003eAeromonas\u003c/em\u003e, \u003cem\u003eVibrio\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, and \u003cem\u003eStaphylococcus\u003c/em\u003e decreased in the ZG, while \u003cem\u003eLD29\u003c/em\u003e, \u003cem\u003eThioclava\u003c/em\u003e, and \u003cem\u003eRhodobacter\u003c/em\u003e increased (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Additionally, 244 bacterial genera were shared between the two treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eThe indicator species analysis, based on species abundance and occurrence frequency, revealed that \u003cem\u003eOceanobacillus\u003c/em\u003e had the highest indicator value in the CK, whereas \u003cem\u003eC._Electronema\u003c/em\u003e had the highest indicator value in the ZG. This result indicates that \u003cem\u003eOceanobacillus\u003c/em\u003e and \u003cem\u003eC._Electronema\u003c/em\u003e could serve as indicator species for the CK and ZG groups, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.4 Diversity analysis of the \u003cem\u003eL. vannamei\u003c/em\u003e intestinal microbiota under different light conditions\u003c/h2\u003e\u003cp\u003eThe Chao1 and Shannon alpha diversity indices (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B) increased in the ZG group, indicating that the PV fishery model enhanced the richness and evenness of the \u003cem\u003eL. vannamei\u003c/em\u003e intestinal microbiota. Closer samples had more similar microbiomes. The PcoA based on OTU abundance revealed clear separation between the groups, while samples within each group clustered closely together (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). The Adonis analysis revealed a significant overall difference in the intestinal microbiota between the ZG and CK groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003eAdditionally, bacterial phylogenetic tree analysis of \u003cem\u003eL. vannamei\u003c/em\u003e indicated that the abundance of \u003cem\u003eFimbriiglobus\u003c/em\u003e, \u003cem\u003eButyrivibrio\u003c/em\u003e, \u003cem\u003eDesulfomicrobrio\u003c/em\u003e, \u003cem\u003eBdellovibrio\u003c/em\u003e, and \u003cem\u003eChryseolinea\u003c/em\u003e was significantly higher in the ZG than the CK. In contrast, the abundance of \u003cem\u003eMariniradius\u003c/em\u003e, \u003cem\u003eMuribaculum\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, \u003cem\u003eNonomuraea\u003c/em\u003e, and \u003cem\u003eCloacibacillus\u003c/em\u003e was significantly lower in the ZG than in the CK (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Predicting \u003cem\u003eL. vannamei\u003c/em\u003e intestinal microbiota function under different light conditions\u003c/h2\u003e\u003cp\u003eTo further investigate the effect of light on the intestinal microbiota of \u003cem\u003eL. vannamei\u003c/em\u003e, we predicted bacterial functions and assessed whether the light treatments affected the functionality of the intestinal microbiota. The predictive functional analysis revealed that metabolism and cellular processes were dominant across all groups. Using analysis of variance and Tukey\u0026rsquo;s HSD test, we detected the significant differences among the eight most abundant bacterial functions in the groups. The results indicated that the functional abundances of bacterial chemotaxis, the bacterial secretion system, cysteine and methionine metabolism, riboflavin metabolism, nitrogen metabolism, cyanoamino acid metabolism, the phosphotransferase system, and plant-pathogen interactions decreased significantly under the PV fishery breeding model (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Furthermore, the bacterial interaction analysis revealed distinct topological architectures, including differences in node connectivity and edge distribution, between CK and ZG groups. The CK network consisted of 227 nodes and 2,497 edges, whereas the ZG network contained 192 nodes and 1,379 edges. These results indicated significantly higher connectivity in the CK network (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Specifically, in the CK network, the strongest interactions were observed between Firmicutes and Proteobacteria, within Firmicutes (intra-phylum), and between Actinobacteriota and Firmicutes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). In contrast, the strongest interactions in the ZG network occurred between Firmicutes and Proteobacteria, within Proteobacteria (intra-phylum), and between Actinobacteriota and Proteobacteria associations (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003ePhotoperiod was first studied in plants, where it affects physiological activities such as flowering and fruiting\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. However, light is an important environmental factor that cannot be ignored for the health and development of aquatic animals\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Wang et al. reported that the most suitable growth environment for the intensive farming of \u003cem\u003eMarsupenaeus japonicas\u003c/em\u003e is total darkness\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Wu et al. showed that \u003cem\u003eCherax quadricarinatus\u003c/em\u003e shrimp have the lowest survival rate and the slowest growth rate under full darkness\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In this study, measurements of body length and body weight indicated that the growth rate of \u003cem\u003eL. vannamei\u003c/em\u003e in the PV fishery model was slower than that in the traditional pond culture model. This result sugges\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ets\u003c/span\u003e that light availability under the PV panels may adversely affect the growth of \u003cem\u003eL. vannamei\u003c/em\u003e. Previous studies have showed that light environment variations can influence the growth of aquatic organism by modulating digestive enzymes activity\u003csup\u003e\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. For instance, protease facilitates proteins hydrolysis into amino acids, thereby promoting nutrient absorption in aquatic organisms\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Specifically, \u003cem\u003eα-amylase\u003c/em\u003e (AMS) primarily catalyzes the hydrolysis of starch and glycogen\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e, and \u003cem\u003elipse\u003c/em\u003e (LPS) catalyzes lipid hydrolysis of aquatic organisms, converting it into energy substrates to support growth\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Reduced light conditions under PV panels may suppress the activity of these enzymes, thereby impairing digestive efficiency and overall growth in \u003cem\u003eL. vannamei\u003c/em\u003e. Meanwhile, light exposure may also affect the growth of \u003cem\u003eL. vannamei\u003c/em\u003e by influencing its feeding behavior, and future studies could incorporate continuous feeding monitoring to better characterize this relationship\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFor crustaceans, temperature is an especially crucial environmental factor. Due to their unique molting-based growth and developmental mechanism, crustaceans exhibit high sensitivity to temperature throughout their entire life cycle. Within the optimal thermal range, the growth and development rates of species, including \u003cem\u003eL. vannamei\u003c/em\u003e and \u003cem\u003ePenaeus japonicus\u003c/em\u003e, exhibit a positive correlation with water temperature\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In this study, recorded aquaculture water temperatures revealed that the average water temperature in the PV fishery model was lower than that in the traditional pond culture model, which may account for the observed differences in the growth performance of \u003cem\u003eL. vannamei\u003c/em\u003e between the two models. However, when water temperature exceeds the physiological tolerance threshold of shrimp, their metabolic rate may exceed their assimilation rate. Under such conditions, energy is expended rapidly and cannot be stored, ultimately adversely affecting growth. Moreover, excessively high temperatures can cause tissue damage and disrupt normal physiological functions, leading to growth inhibition and reduced survival rates\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. In addition, a large number of research indicates that water temperature affects the antioxidant defense systems of both fish and crustaceans. Adverse water temperature conditions and abrupt temperature fluctuations can induce oxidative stress responses\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn the present study, the composition and structure of the \u003cem\u003eL. vannamei\u003c/em\u003e intestinal microbiota were significantly different between the PV fishery model and the traditional pond culture model. Although the relative intestinal abundance of Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes varied between the two culture modes, these phyla consistently dominated the bacterial community. This is similar to the results of studies in \u003cem\u003eScophthalmus maximus\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e, hybrid grouper\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eEriocheir sinensis\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003ePenaeus monodon\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e and \u003cem\u003eMacrobrachium rosenbergii\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Under the PV fishery model, reduced light availability caused by shading is likely to suppress primary production, thereby driving a compositional shift in the microbial community toward K-strategists (e.g., Verrucomicrobiota). These bacteria are characterized by slow growth rates and strong competitiveness, typically adapting to relatively stable environments. In contrast, frequent water disturbances of traditional aquaculture models may promote the proliferation of r-strategists (e.g., Proteobacteria), which exhibit high reproductive rates but lower competitive ability\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. This structural change may have originated from two aspects of light regulatory mechanisms. One is that shading reduces the intensity of photosynthesis in water, inhibits the proliferation of light-dependent bacteria (such as \u003cem\u003eRhodobacter\u003c/em\u003e), and simultaneously promotes expansion of the ecological niche of anaerobic bacteria (such as \u003cem\u003eMicrophylum acuminatum\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Second, changes in light intensity regulate the secretion of immune factors through the opsin pathway in shrimp, indirectly affecting the colonization environment\u003csup\u003e\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. The number of \u003cem\u003eAeromonas\u003c/em\u003e in the \u003cem\u003eL. vannamei\u003c/em\u003e intestine decreased after shading, and some species of \u003cem\u003eAeromonas\u003c/em\u003e promote digestion, absorption and metabolism in the host\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Notably, the abundance of opportunistic pathogenic bacteria, such as \u003cem\u003eAeromonas\u003c/em\u003e and \u003cem\u003eVibrio\u003c/em\u003e, decreased in the PV aquaculture mode, which was consistent with the correlation between pathogenic bacteria and the \u003cem\u003eMacrobrachium rosenbergii\u003c/em\u003e culture environment\u003csup\u003e\u003cspan additionalcitationids=\"CR54 CR55\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. The nitrogen cycling function of \u003cem\u003eThioclava\u003c/em\u003e and the photosynthetic oxygen production characteristics of \u003cem\u003eRhodobacter\u003c/em\u003e may together improve the microenvironment of the culture water, but further data on dissolved oxygen and ammonia nitrogen levels are needed for support\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. Although the ecological functions of \u003cem\u003eVibrio\u003c/em\u003e and related genera have been previously documented\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e, this study is the first to report a negative correlation between their temporal dynamics of \u003cem\u003eVibrio\u003c/em\u003e and the abundance of photosynthetic bacteria (\u003cem\u003eRhodobacter\u003c/em\u003e) in water column under the PV model. This finding suggests that reduced light availability may influence microbial community interactions and implies a potential regulatory mechanism through which light conditions could be manipulated to suppress opportunistic pathogens.\u003c/p\u003e\u003cp\u003eAlpha diversity provides a comprehensive assessment of intestinal microbiota by measuring richness, diversity, and evenness\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, while beta diversity reflects variations in microbial composition among different groups\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. In this study, the alpha diversity analysis revealed that the Chao1and Shannon indices of the intestinal microbiota in \u003cem\u003eL. vannamei\u003c/em\u003e cultured in the PV fishery model were higher than those in the traditional pond aquaculture model. The higher Shannon index suggests a more balanced composition, which may help suppress the competitive advantage of opportunistic pathogens\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Additionally, the higher Chao1 index suggests a higher proportion of rare species, which, despite being less abundant, may contribute to functional redundancy and enhance the stability of the microbiota under stress conditions\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. However, although the α-diversity index increased in the PV farming model, higher diversity does not necessarily directly equate to improved health; it may reflect the recombination of the microbiota caused by an environmental disturbance\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study demonstrates that the PV fishery model induces significant alterations in the intestinal microbiota of \u003cem\u003eL. vannamei\u003c/em\u003e, characterized by increased α-diversity and altered community structure. Although these microbial changes are initially associated with reduced growth rates, they appear to promote the establishment of a more stable and pathogen-resistant gut ecosystem, as indicated by the suppression of \u003cem\u003eVibrio\u003c/em\u003e populations and the enrichment of functional taxa like \u003cem\u003eVerrucomicrobiota\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. This trade-off between short-term growth performance and long-term health benefits reflects ecological adaptation strategies, where environmental stressors trigger adaptive microbial reorganization. Future research should prioritize the development of optimized light regimes to balance these ecological trade-offs, potentially through intermittent illumination protocols that maintain beneficial microbial functions while minimizing growth inhibition\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. These findings offer valuable insights into the development of ecologically sustainable aquaculture practices by leveraging light-microbiota-host interactions.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis 80-day aquaculture experiment systematically evaluated the effects of photovoltaic shading on \u003cem\u003eL. vannamei\u003c/em\u003e. This results showed that the PV fishery breeding model (ZG) exhibited lower water temperatures compared to the traditional pond culture model (CK), leading to reduced growth in body length and weight. However, it significantly enhanced the α-diversity of the shrimp\u0026rsquo;s intestinal microbiota. Microbial profiling demonstrated substantial declines in potential pathogens (\u003cem\u003eVibrio\u003c/em\u003e and \u003cem\u003eAeromonas\u003c/em\u003e), increased abundance of beneficial taxa (\u003cem\u003eThioclava\u003c/em\u003e and \u003cem\u003eVerrucomicrobiota\u003c/em\u003e), and specific enrichment of \u003cem\u003eC._Electronema\u003c/em\u003e as a biomarker in the PV model. While 244 core genera with essential ecological functions were shared between both models, the observed reductions in Proteobacteria and Firmicutes abundance under the PV model suggest that light-induced changes in water temperature may modulate shrimp energy allocation though temperature-microbiota interactions. These findings imply that a moderate trade-off growth performance may be compensated by enhanced microbial stability and disease resistance, providing a critical ecological rationale for the adoption of integrated PV fishery breeding model.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ.Z.M., and L.Q. conceived and designed research. Z.Z.M., Z.H., W.Y.S, and C.X.Y. conducted experiments. Z.Z.M., Z.H., L. H. D., D.Y.L., H.Z.P., Z.L., and Z.J. analyzed data. Z.Z.M., C.X.Y., and L.Q. wrote the manuscript. All authors read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by Innovation of High Quality Fish Breeding Materials and Methods and Selection of New Varieties (Breeding Research Project) (2021YFYZ0015) and Sichuan Freshwater Fish Innovation Team of the National Modern Agricultural Industrial Technology System (SCCXTD-2025-15). In addition, We would like to thank Tongwei New Energy Co., Ltd. For their financial support in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation / Beijing Institute of Genomics, Chinese Academy of Sciences (CRA024106) that are publicly accessible at https://ngdc.cncb.ac.cn/gsa.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval.\u003c/strong\u003e All animal handling procedures were approved by the Animal Care and Use Committee of the Fisheries Research Institute, Sichuan Academy of Agricultural Sciences (20220323002A), following the recommendations in the U.K. Animals (Scientific Procedures) Act, 1986. At the same time, all methods were carried out by relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJingwen, B. \u0026quot;Integrating fishing and light\u0026quot; to create a new model of industrial development. \u003cem\u003eSolar Energy\u003c/em\u003e, 67+69 (2016).\u003c/li\u003e\n\u003cli\u003eMengjiao, G.\u003cem\u003e et al.\u003c/em\u003e Bacillus subtilis Improves Immunity and Disease Resistance in Rabbits. \u003cem\u003eFrontiers in Immunology\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 354 (2017).\u003c/li\u003e\n\u003cli\u003eDuo, H. \u0026ldquo;Integration of fish and light\u0026rdquo; to promote the transformation and upgrading of aquaculture. \u003cem\u003eChina Fishery News\u003c/em\u003e, 106-108 (2016).\u003c/li\u003e\n\u003cli\u003eGilles Boeuf \u0026amp; Bail, P.-Y. L. Does light have an influence on fish growth? \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e177\u003c/strong\u003e, 129-152 (1999).\u003c/li\u003e\n\u003cli\u003eBlaxter, J. H. S. Visual Thresholds and Spectral Sensitivity of Herring Larvae. \u003cem\u003eJournal of Experimental Biology\u003c/em\u003e \u003cstrong\u003e51\u003c/strong\u003e, 39-53 (1968).\u003c/li\u003e\n\u003cli\u003eMcfarland, W. N. Light in the Sea-Correlations with Behaviors of Fishes and Invertebrates. \u003cem\u003eAmerican Zoologist\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 389-401 (1986).\u003c/li\u003e\n\u003cli\u003eMoss, G. A., Tong, L. J. \u0026amp; Illingworth, J. Effects of light intensity and food density on the growth and survival of early-stage phyllosoma larvae of the rock lobster \u003cem\u003eJasus edwardsii\u003c/em\u003e. \u003cem\u003eMarine Freshwater Research\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 129-134 (1999).\u003c/li\u003e\n\u003cli\u003eWang, F.\u003cem\u003e et al.\u003c/em\u003e The effect of light intensity on the growth of Chinese shrimp \u003cem\u003eFenneropenaeus chinensis\u003c/em\u003e. \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e234\u003c/strong\u003e, 475-483 (2004).\u003c/li\u003e\n\u003cli\u003eGardner, C. \u0026amp; Maguire, G. B. Effect of photoperiod and light intensity on survival, development and cannibalism of larvae of the Australian giant crab \u003cem\u003ePseudocarcinus gigas\u003c/em\u003e (Lamarck). \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e165\u003c/strong\u003e, 51-63 (1998).\u003c/li\u003e\n\u003cli\u003eMclean, E., Cotter, P., Thain, C. \u0026amp; King, N. Tank color impacts performance of cultured fish. \u003cem\u003eRibarstvo\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 43-54 (2008).\u003c/li\u003e\n\u003cli\u003eWei Hui\u003cem\u003e et al.\u003c/em\u003e Effects of light intensity on phototaxis, growth, antioxidant and stress of juvenile gibel carp (Carassius auratus gibelio). \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e501\u003c/strong\u003e, 39-47 (2019).\u003c/li\u003e\n\u003cli\u003eKr, M., Sunar, M. C., Topuz, M. \u0026amp; Saripek, M. Thermal acclimation capacity and standard metabolism of the Pacific white shrimp \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e (Boone, 1931) at different temperature and salinity combinations. \u003cem\u003eJournal of Thermal Biology\u003c/em\u003e \u003cstrong\u003e112\u003c/strong\u003e, 103429 (2023).\u003c/li\u003e\n\u003cli\u003eDong, X., Wang, J. \u0026amp; Raghavan, V. Impact of microwave processing on the secondary structure, in-vitro protein digestibility and allergenicity of shrimp (\u003cem\u003eLitopenaeus vannamei\u003c/em\u003e) proteins-ScienceDirect. \u003cem\u003eFood Chemistry\u003c/em\u003e \u003cstrong\u003e337\u003c/strong\u003e, 127811 (2021).\u003c/li\u003e\n\u003cli\u003eRawls, J. F., Samuel, B. S. \u0026amp; Gordon, J. I. Gnotobiotic zebrafish reveal evolutionarily conserved responses to the gut microbiota.\u003cem\u003e Proceedings of the National Academy of Sciences of the United States of America\u003c/em\u003e \u003cstrong\u003e101\u003c/strong\u003e, 6 (2004).\u003c/li\u003e\n\u003cli\u003eXuemei, L.\u003cem\u003e et al.\u003c/em\u003e Gut Microbiota Contributes to the Growth of Fast-Growing Transgenic Common Carp (\u003cem\u003eCyprinus carpio L.\u003c/em\u003e). \u003cem\u003ePlos One\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, e64577-e64577 (2013).\u003c/li\u003e\n\u003cli\u003eLuan, Y.\u003cem\u003e et al.\u003c/em\u003e The fish microbiota: research progress and potential applications. \u003cem\u003eEngineering\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 137-146 (2023).\u003c/li\u003e\n\u003cli\u003eRubio-Portillo, Josefa Sanchez Jerez \u0026amp; Pablo. Exploring changes in bacterial communities to assess the influence of fish farming on marine sediments. \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e506\u003c/strong\u003e, 459-464 (2019).\u003c/li\u003e\n\u003cli\u003eToni, M.\u003cem\u003e et al.\u003c/em\u003e Review: Assessing fish welfare in research and aquaculture, with a focus on European directives. \u003cem\u003eCambridge University Press\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 161-170 (2019).\u003c/li\u003e\n\u003cli\u003eWang, Q., Garrity, G. M., Tiedje, J. M. \u0026amp; Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. \u003cem\u003eAppl. Environ. Microbiol\u003c/em\u003e \u003cstrong\u003e73\u003c/strong\u003e, 5261-5267 (2007).\u003c/li\u003e\n\u003cli\u003eElmar, P.\u003cem\u003e et al.\u003c/em\u003e SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. \u003cem\u003eNucleic Acids Res\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 7188-7196 (2007).\u003c/li\u003e\n\u003cli\u003eOndov, B. D., Bergman, N. H. \u0026amp; Phillippy, A. M. Interactive metagenomic visualization in a Web browser. \u003cem\u003eBmc Bioinformatics\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 385 (2011).\u003c/li\u003e\n\u003cli\u003eChen, H. B. \u0026amp; Boutros, P. C. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R.\u003cem\u003e Bmc Bioinformatics\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 35 (2011).\u003c/li\u003e\n\u003cli\u003eConway, J. R., Lex, A. \u0026amp; Gehlenborg, N. UpSetR: an R package for the visualization of intersecting sets and their properties. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e33\u003c/strong\u003e, 2938-2940 (2017).\u003c/li\u003e\n\u003cli\u003eCaporaso, J. G.\u003cem\u003e et al.\u003c/em\u003e QIIME allows analysis of high-throughput community sequencing data. \u003cem\u003eNature methods\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 335-336 (2010).\u003c/li\u003e\n\u003cli\u003eOksanen, J., Blanchet, F. G., Kindt, R., Legendre, P. \u0026amp; Stevens, W. H. H.(2010): Vegan: Community Ecology Package. R package, version 1.17-4. \u003cem\u003ehttp://cran\u003c/em\u003e\u003cem\u003e. r-project. org\u0026gt;. Acesso em\u003c/em\u003e, 2010 (2010).\u003c/li\u003e\n\u003cli\u003eWickham, H. ggplot2. \u003cem\u003eWiley Interdisciplinary Reviews: Computational Statistics\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 180-185 (2011).\u003c/li\u003e\n\u003cli\u003eA\u0026szlig;hauer, K. P., Wemheuer, B., Daniel, R. \u0026amp; Meinicke, P. Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data. \u003cem\u003eBioinformatics\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 2882-2884 (2015).\u003c/li\u003e\n\u003cli\u003eLangille\u003cem\u003e et al.\u003c/em\u003e Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. \u003cem\u003eNature biotechnology\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 814-821 (2013).\u003c/li\u003e\n\u003cli\u003eShen, W.\u003cem\u003e et al.\u003c/em\u003e The impact of microplastic and sulfanilamide co-exposure on soil microbiota.\u003cem\u003e Ecotoxicology Environmental Safety\u003c/em\u003e \u003cstrong\u003e292\u003c/strong\u003e, 117968 (2025).\u003c/li\u003e\n\u003cli\u003eLiu Li \u0026amp; Pengfang, Z. Relationship between photoperiod and plant floral induction. \u003cem\u003eLiaoning Agricultural Sciences\u003c/em\u003e, 26-27 (2004).\u003c/li\u003e\n\u003cli\u003eAdair, K. L. \u0026amp; Douglas, A. E. Making a microbiome: the many determinants of host-associated microbial community composition.\u003cem\u003e Current Opinion in Microbiology\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 23-29 (2017).\u003c/li\u003e\n\u003cli\u003eWang Xiang, Ren Xianyun, Sheng Xiuzhen, Li Cuiping \u0026amp; Jian, L. Effects of different photoperiods on growth, molting and glucose metabolism of \u003cem\u003eMarsupenaeus japonicus\u003c/em\u003e. \u003cem\u003eProgress in Fishery Sciences\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 66-73, doi:10.19663/j.issn2095-9869.20190902001 (2020).\u003c/li\u003e\n\u003cli\u003eWu Zhixin, Chen Xiaoxuan, Liu Xiaoling, Mei Xiaohua \u0026amp; Xiqun, C. Effects of different photoperiods on reproduction and growth of \u003cem\u003eCherax quadricarinatus\u003c/em\u003e. \u003cem\u003eFreshwater Fisheries\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 4-5 (2000).\u003c/li\u003e\n\u003cli\u003eShukun, Y. The latest research and application progress of feed protease. \u003cem\u003eFeed Industry\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 22-26, doi:10.13302/j.cnki.fi.2019.10.005 (2019).\u003c/li\u003e\n\u003cli\u003eChunlei;, L. \u0026amp; Yutuo, W. Research progress on classi fication and application of amylase. \u003cem\u003eGuangxi Science\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 248-252, doi:10.13656/j.cnki.gxkx.20180531.002 (2018).\u003c/li\u003e\n\u003cli\u003eZishe;, W., Ji;, Z., Junyi;, M. \u0026amp; Rui, S. Research and application progress of lipase.\u003cem\u003e Journal of Anhui Agri cultural Sciences\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, 3798-3800+3855, doi:10.13989/j.cnki.0517-6611.2011.07.004 (2011).\u003c/li\u003e\n\u003cli\u003eYanling, T.\u003cem\u003e et al.\u003c/em\u003e The influence of light intensity and shelter on habitat and feeding behavior of the spiny lobster (\u003cem\u003ePanulirus homarus\u003c/em\u003e). \u003cem\u003eJournal OF Dalian Ocean University\u003c/em\u003e \u003cstrong\u003e40\u003c/strong\u003e, 382-389, doi:10.16535/j.cnki.dlhyxb.2024-285 (2025).\u003c/li\u003e\n\u003cli\u003eJesus;, P.-P., A., M.-P. C., and \u0026amp; G., R. L. The effects of salinity and temperature on the growth and survival rates of juvenile white shrimp, \u003cem\u003ePenaeus vannamei\u003c/em\u003e, Boone, 1931. \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e157\u003c/strong\u003e, 107-115 (1997).\u003c/li\u003e\n\u003cli\u003eComan G J, Crocos P J \u0026amp; P, P. N. The effects of temperature on the growth, survival and biomass of different families of juvenile \u003cem\u003ePenaeus japonicus \u003c/em\u003eBate. \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e214\u003c/strong\u003e, 185-199 (2002).\u003c/li\u003e\n\u003cli\u003eZhiguo;, L., Chengsong;, Z., Yan;, Z., Fuhua;, L. \u0026amp; Jianhai, X. Effects of temperature on embryonic and larval development of the \u003cem\u003eExopalaemon carinicauda\u003c/em\u003e (Holthuis) \u003cem\u003eRepopts\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 9-16 (2013).\u003c/li\u003e\n\u003cli\u003eBowden, T. J. Modulation of the immune system of fish by their environment. \u003cem\u003eFish Shellfish Immunology\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 373-383 (2008).\u003c/li\u003e\n\u003cli\u003eLi, Y.\u003cem\u003e et al.\u003c/em\u003e Effects of dietary glycinin on the growth performance, digestion, intestinal morphology and bacterial community of juvenile turbot, \u003cem\u003eScophthalmus maximus\u003c/em\u003e L. \u003cem\u003eAquacultur\u003c/em\u003e, 125-133 (2017).\u003c/li\u003e\n\u003cli\u003eHe, Y.\u003cem\u003e et al.\u003c/em\u003e Glutamine improves growth and intestinal health in juvenile hybrid groupers fed high-dose glycinin. \u003cem\u003eFish Shellfish Immunology\u003c/em\u003e, 141 (2023).\u003c/li\u003e\n\u003cli\u003eA, F. H.\u003cem\u003e et al.\u003c/em\u003e Sodium butyrate can improve intestinal integrity and immunity in juvenile Chinese mitten crab (\u003cem\u003eEriocheir sinensis\u003c/em\u003e) fed glycinin-ScienceDirect.\u003cem\u003e Fish Shellfish Immunology\u003c/em\u003e, 400-411 (2020).\u003c/li\u003e\n\u003cli\u003eRungrassamee, W., Klanchui, A., Maibunkaew, S., Chaiyapechara, S. \u0026amp; Karoonuthaisiri, N. Characterization of Intestinal bacteria in wild and domesticated adult black Tiger Shrimp (\u003cem\u003ePenaeus monodon\u003c/em\u003e). \u003cem\u003ePLoS ONE\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, e91853 (2014).\u003c/li\u003e\n\u003cli\u003eJingfeng, Y. \u003cem\u003eThe study on immune effects, feeding physiology and intestinal health of soybean antigen protein on giant freshwater prawn (Macrobrachium rosenbergii)\u003c/em\u003e, Shanghai Ocean University, (2018).\u003c/li\u003e\n\u003cli\u003eChaiyapechara, S., Uengwetwanit, T., Arayamethakorn, S., Bunphimpapha, P. \u0026amp; Rungrassamee, W. Understanding the host-microbe-environment interactions: Intestinal microbiota and transcriptomes of black tiger shrimp \u003cem\u003ePenaeus monodon\u003c/em\u003e at different salinity levels. \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e546\u003c/strong\u003e, 737371 (2021).\u003c/li\u003e\n\u003cli\u003eKolda, A., Gavrilovi, A., Jug-Dujakovi, J., Ljubei, Z. \u0026amp; Kapetanovi, D. Profiling of bacterial assemblages in the marine cage farm environment, with implications on fish, human and ecosystem health. \u003cem\u003eEcological Indicators\u003c/em\u003e \u003cstrong\u003e118\u003c/strong\u003e, 106785 (2020).\u003c/li\u003e\n\u003cli\u003eSuhn, K. \u0026amp; Hyeyoung, K. Inhibitory effect of astaxanthin on oxidative stress-induced mitochondrial Dysfunction-A Mini-Review. \u003cem\u003eNutrients\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, E1137 (2018).\u003c/li\u003e\n\u003cli\u003eBendich \u0026amp; Adrianne. Physiological role of antioxidants in the immune system. \u003cem\u003eJournal of Dairy Science\u003c/em\u003e \u003cstrong\u003e76\u003c/strong\u003e, 2789-2794 (1993).\u003c/li\u003e\n\u003cli\u003eVazquez, L., Alpuche, J., Maldonado, G., Agundis, C. \u0026amp; Zenteno, E. Review: Immunity mechanisms in crustaceans. \u003cem\u003eInnate Immunity\u003c/em\u003e \u003cstrong\u003e15\u003c/strong\u003e, 179-188 (2009).\u003c/li\u003e\n\u003cli\u003eKoca S B, Yigit N \u0026Ouml; \u0026amp; I, D. B. Effects of enzyme-producing probiotic bacteria isolated from the gastrointestinal tract of trout on the growth performance, survival, and digestive enzyme activity of rainbow trout fry (\u003cem\u003eOncorhynchus mykiss\u003c/em\u003e). \u003cem\u003eIsraeli Journal of Aquaculture-Bamidgeh\u003c/em\u003e \u003cstrong\u003e352\u003c/strong\u003e, 1-9 (2015).\u003c/li\u003e\n\u003cli\u003eB., V., Sai, P. G., P., R. \u0026amp; G., B. Antibacterial activity of \u003cem\u003eAllium sativum\u003c/em\u003e against multidrug-resistant \u003cem\u003eVibrio harveyi\u003c/em\u003e isolated from black gill\u0026ndash;diseased Fenneropenaeus indicus. \u003cem\u003eAquaculture International\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 531-539 (2011).\u003c/li\u003e\n\u003cli\u003eKuebutornye, F. K. A., Abarike, E. D. \u0026amp; Lu, Y. A review on the application of \u003cem\u003eBacillus\u003c/em\u003e as probiotics in aquaculture. \u003cem\u003eFish \u0026amp; Shellfish Immunology\u003c/em\u003e \u003cstrong\u003e87\u003c/strong\u003e, 820-828 (2019).\u003c/li\u003e\n\u003cli\u003eHuttenhower, C., Gevers, D., Knight, R., Abubucker, S. \u0026amp; Badger, J. H. Structure, function and diversity of the healthy human microbiome. \u003cem\u003eProgress in Molecular Biology and Translational Science\u003c/em\u003e \u003cstrong\u003e191\u003c/strong\u003e, 53-82 (2012).\u003c/li\u003e\n\u003cli\u003eGreen, T. J.\u003cem\u003e et al.\u003c/em\u003e Simulated marine heat wave alters abundance and structure of \u003cem\u003eVibrio\u003c/em\u003e populations associated with the pacific oyster resulting in a mass mortality event.\u003cem\u003e Microbial Ecology\u003c/em\u003e \u003cstrong\u003e77\u003c/strong\u003e, 736-747 (2018).\u003c/li\u003e\n\u003cli\u003eSorokin D Y \u0026amp; P., T. T. \u003cem\u003eThioclava pacifica\u003c/em\u003e gen. nov., sp. nov., a novel facultatively autotrophic, marine, sulfur-oxidizing bacterium from a near-shore sulfidic hydrothermal area. \u003cem\u003eInternational Journal of Systematic and Evolutionary Microbiology\u003c/em\u003e \u003cstrong\u003e55\u003c/strong\u003e, 1069-1075 (2005).\u003c/li\u003e\n\u003cli\u003eCao Haipeng, Zhang Shuying, Yu Jingjing \u0026amp; Jian, A. Isolation, identification and detoxification of a trichlorphon-tolerant \u003cem\u003eRhodobacter Sphaeroides\u003c/em\u003e XR12. \u003cem\u003eActa Hydrobiologica Sinica\u003c/em\u003e \u003cstrong\u003e44\u003c/strong\u003e, 59-66 (2020).\u003c/li\u003e\n\u003cli\u003eDai, L.\u003cem\u003e et al.\u003c/em\u003e Pathogenicity and transcriptomic exploration of \u003cem\u003eVibrio fortis\u003c/em\u003e in \u003cem\u003ePenaeus monodon\u003c/em\u003e. \u003cem\u003eFish Shellfish Immunology\u003c/em\u003e \u003cstrong\u003e142\u003c/strong\u003e, 109097 (2023).\u003c/li\u003e\n\u003cli\u003eWillis, K. J. \u0026amp; Whittaker, R. J. Ecology. Species diversity--scale matters. \u003cem\u003eScience\u003c/em\u003e \u003cstrong\u003e295\u003c/strong\u003e, 1245-1248 (2002).\u003c/li\u003e\n\u003cli\u003eSuo, Y.\u003cem\u003e et al.\u003c/em\u003e Response of gut health and microbiota to sulfide exposure in Pacific white shrimp \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e. \u003cem\u003eFish Shellfish Immunology\u003c/em\u003e \u003cstrong\u003e63\u003c/strong\u003e, 87-96 (2017).\u003c/li\u003e\n\u003cli\u003eFergus, S. Probiotics in perspective. \u003cem\u003eGastroenterology\u003c/em\u003e \u003cstrong\u003e139\u003c/strong\u003e (2010).\u003c/li\u003e\n\u003cli\u003eQuero, G. M., Ape, F., Manini, E., Mirto, S. \u0026amp; Luna, G. M. Temporal changes in mcrobial communities beneath fish farm sediments are related to organic enrichment and fish biomass over a production cycle. \u003cem\u003eFrontiers in Marine Science\u003c/em\u003e \u003cstrong\u003e7\u003c/strong\u003e, 524 (2020).\u003c/li\u003e\n\u003cli\u003eXiong, J., Wang, K., Wu, J., Qiuqian, L. \u0026amp; Zhang, D. Changes in intestinal bacterial communities are closely associated with shrimp disease severity. \u003cem\u003eApplied Microbiology Biotechnology\u003c/em\u003e \u003cstrong\u003e99\u003c/strong\u003e, 6911-6919 (2015).\u003c/li\u003e\n\u003cli\u003eQu Biao\u003cem\u003e et al.\u003c/em\u003e Effect of\u0026ldquo;Fishing light complementary\u0026rdquo;on plankton in catfish pond. \u003cem\u003eJournal of Aquaculture\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 6-9 (2015).\u003c/li\u003e\n\u003cli\u003eKyle F. Edwards, Mridul K. Thomas, Christopher A \u0026amp; Elena, K. Phytoplankton growth and the interaction of light and temperature: A synthesis at the species and community level. \u003cem\u003eLimnology Oceanography\u003c/em\u003e \u003cstrong\u003e61\u003c/strong\u003e, 1232-1244 (2016).\u003c/li\u003e\n\u003cli\u003eWang, Y. B., Li, J. R. \u0026amp; Lin, J. Probiotics in aquaculture: Challenges and outlook. \u003cem\u003eAquaculture\u003c/em\u003e \u003cstrong\u003e281\u003c/strong\u003e, 1-4 (2008).\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":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Litopenaeus vannamei, The photovoltaic fishery breeding model, Intestinal microbiota, Structural composition, Diversity","lastPublishedDoi":"10.21203/rs.3.rs-7881803/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7881803/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe photovoltaic (PV) fishery breeding model integrates the generation of solar energy with aquaculture, yet its impacts on aquatic organisms remain poorly understood. This study investigated how PV panel shading affects the intestinal microbial ecosystem of \u003cem\u003eLitopenaeus vannamei\u003c/em\u003e. We conducted a controlled 80-day experiment comparing shrimp reared under PV panels (ZG group) versus those reared in traditional open ponds (CK group), with quadruplicate 800 m\u0026sup2; ponds per group under standardized conditions (80 shrimp/m\u0026sup2;, salinity 15\u0026ndash;18\u0026permil;). High-throughput 16S rRNA sequencing was employed to analyze microbial composition, diversity, and predicted functional profiles. The growth data revealed that the ZG group exhibited significantly shorter body length than the CK group after 20 days of culture (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while body weight was significantly less after 16 days (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u0026zwnj; The results of the intestinal microbiota analysis showed that Proteobacteria and Firmicutes were the main components of the intestinal microbiota in the CK and ZG groups, while \u003cem\u003eOceanobacillus\u003c/em\u003e and \u003cem\u003eCandidatus_Electronema\u003c/em\u003e were present as indicator species in the CK and ZG groups, respectively. Higher Chao1 and Shannon indices indicated that the ZG group improved the richness and uniformity of the \u003cem\u003eL. vannamei\u003c/em\u003e intestinal flora. In addition, significant differences between the groups were detected by the β-diversity analysis. A predicted bacterial function analysis also revealed significant differences in functional abundance between the two groups. This study provides critical insight into how PV shading alters shrimp microbiota and growth performance, offering practical guidance for optimizing sustainable PV-aquaculture integrated systems.\u003c/p\u003e","manuscriptTitle":"Effects of the photovoltaic fishery breeding model on intestinal microbiota structure and diversity in Litopenaeus vannamei","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-28 08:53:23","doi":"10.21203/rs.3.rs-7881803/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-08T05:37:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-07T22:09:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-06T13:02:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"279018720753137860618414856988397103603","date":"2025-11-26T00:29:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229472610803729724541818059987390490253","date":"2025-11-24T19:32:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-24T11:10:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-27T09:01:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-24T02:05:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-24T02:02:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"116aca82-544e-4800-9260-b7299db99d22","owner":[],"postedDate":"November 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":58611819,"name":"Biological sciences/Ecology"},{"id":58611820,"name":"Earth and environmental sciences/Ecology"},{"id":58611821,"name":"Earth and environmental sciences/Environmental sciences"},{"id":58611822,"name":"Biological sciences/Microbiology"},{"id":58611823,"name":"Earth and environmental sciences/Ocean sciences"}],"tags":[],"updatedAt":"2026-01-05T16:01:06+00:00","versionOfRecord":{"articleIdentity":"rs-7881803","link":"https://doi.org/10.1038/s41598-025-34429-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-04 15:57:03","publishedOnDateReadable":"January 4th, 2026"},"versionCreatedAt":"2025-11-28 08:53:23","video":"","vorDoi":"10.1038/s41598-025-34429-x","vorDoiUrl":"https://doi.org/10.1038/s41598-025-34429-x","workflowStages":[]},"version":"v1","identity":"rs-7881803","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7881803","identity":"rs-7881803","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}