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Scientific Reports volume 16 , Article number: 29855 ( 2026 ) Cite this article
Nile tilapia ( Oreochromis niloticus ) is a commercially important freshwater fish species worldwide. The present study aims to compare the gut microbial communities of Nile tilapia O . niloticus across seven reservoirs in Sri Lanka, identify the core microbiota, and examine the environmental influences on microbial composition. Notably, the gut microbiota of O. niloticus varied significantly ( p ≤ 0.05) by gender and exhibited a distinct composition across the seven reservoirs namely, Padaviya, Yanoya, Minneriya, Kaudulla, Rathkinda, Ulhitiya, and Udawalawe. The dominant bacterial genera included Cyanobium , Clostridium sensu stricto 1, Cetobacterium , and LD29 . The richness and diversity of the intestinal microbiota were higher in the Rathkinda and Padaviya reservoirs. Genus Paracoccus and Roseomonas exhibited negative correlations with most other genera, while Romboutsia and Bacillus showed positive correlations with almost all other genera. A series of probiotic bacteria, including Bacillus and Exiguobacterium species, were isolated and are crucial for aquaculture. Some opportunistic pathogenic bacteria such as Plesiomonas , Aeromonas , Rothia and Staphylococcus were isolated from the gut of O. niloticus . The toxin-producing Cyanobium exhibited significant ( p ≤ 0.05) negative correlations with multiple water quality parameters including chloride, total hardness, calcium, total alkalinity and total dissolved solids in the studied reservoirs. Our results could provide valuable insights into the assembly of gut microbiomes and sustainable development of the O. niloticus industry in various geographical locations.
The Nile tilapia ( Oreochromis niloticus ), native to African waters, exhibits rapid growth and a range of physiological adaptations. It demonstrates resilience to diseases and robust tolerance to varying environmental conditions 1 . However, tilapia species have established themselves as the most extensively distributed invasive fish in non-native environments 2 . In contrast, the Nile tilapia has successfully formed self-sustaining populations in a majority of tropical and subtropical regions 1 . The position of an organism within the food web, known as its trophic level, plays a pivotal role in linking ecosystem dynamics to the invasion of species 3 . This tilapia has been established in over 100 nations worldwide and has risen to prominence as a key species in global aquaculture 2 , 4 . In the shallow dry-zone reservoirs of Sri Lanka, self-recruiting tilapias particularly O. niloticus and their natural hybrids have exhibited impressive adaptability to the unique environmental conditions 5 . Moreover, inland fishery in Sri Lanka is heavily reliant on a vast network of reservoirs, which makes a significant contribution to the rural economy by providing an affordable source of animal protein for rural communities 6 .
The genus Oreochromis has a diverse food habitat that helps make the wild population stronger and healthier, characteristics that led to a positive prediction for them to be labeled ‘aquatic chickens’ 7 . The diverse feeding habits of tilapia are noted for their flexibility and opportunistic omnivorous nature 8 . The diet of this organism can fluctuate significantly based on the varying temporal and spatial conditions of its environment 9 . The diversity and composition of the host gut microbiota is significantly affected by the variable availability of food resources in different geographical environments 10 . Most of the recent studies demonstrated that the environmental parameters, diet, host genetics, age, stress and disease may influence the composition and diversity of intestinal microbial communities 11 . The environmental parameters, such as water quality, temperature, and pollution, directly influence the microbial balance of fish gut 12 , 13 . Diet plays a crucial role, as the nutrients and additives in fish feed impact the composition of gut microbes 14 . Certain genetic variations can predispose individuals to specific microbiota profiles, which may affect disease susceptibility and metabolic processes 15 . As fish age, their gut microbiota evolves throughout life, generally becoming more diverse 16 , 17 . Stress, caused by handling or environmental changes, can disrupt microbial equilibrium, affecting immunity and overall health 18 . Additionally, external infections may indirectly impact gut health, and treatments like antibiotics can further disrupt microbial balance, highlighting the importance of maintaining optimal conditions for fish health and aquaculture success 19 . The variations in the structure of intestinal microbial communities are attributed to the intense selection and mutual evolution of the host and its surroundings 20 .There are limited studies on the comparison of microbial composition of the gut microbiota of O. niloticus in different environments 21 , 22 . A comprehensive investigation of O. niloticus gut microbiota is needed to identify its core gut microbes and understand their significance in host health across various ecosystems, with a particular focus on Sri Lanka. Each of the selected seven reservoirs hosts unique habitats, providing a comprehensive view of the aquatic biodiversity in the region. Variations in temperature influence the thermal layering of reservoirs, while nutrient levels, like elevated phosphorus concentrations in dry zone waters, play a crucial role in shaping aquatic environments 23 . These environmental factors significantly affect the gut microbiota of aquatic species, as shifts in water quality and nutrient abundance modify microbial diversity and balance. Additionally, temperature fluctuations can interfere with gut health, potentially impairing nutrient uptake and overall organismal well-being 24 . Meanwhile, these main reservoirs are where the fishing activities happen. On the other hand, as part of aquaculture development, it is crucial to develop better probiotics to facilitate O. niloticus industries, by unraveling gut microbial composition. Therefore, the present study aims to compare gut microbial communities of tilapia fish O . niloticus across seven reservoirs in Sri Lanka, identify core microbiota, and examine environmental influences on microbial composition. Additionally, it focuses on isolation and characterization of culturable gut bacteria with potential probiotic properties, offering insights into microbial diversity, ecological dynamics, and functional roles within host systems.
Ethical clearance (VERC-23-015) for this study was obtained from the committee for ethical clearance for research of the Faculty of Veterinary Medicine & Animal Science (FVMAS), University of Peradeniya and all experiments were carried out in accordance with relevant guidelines and regulations.
All experiments were performed in accordance with ARRIVE guidelines and regulations 25 .
Water samples from the reservoirs were collected using a column sampler to obtain composite samples from each sampling point, extending to a depth of up to 2 m below the surface. The twenty-one water samples were obtained from the seven reservoirs in an S-shaped pattern described by Boyd and Tucker 26 .
Water temperature and pH were measured in situ using a multiparameter (Hanna Instruments Inc., USA). floride (F), chloride (Cl − ), total alkalinity (TA), total hardness (TH), calcium (Ca), magnesium (Mg), free ammonia (NH 3 ), nitrate (NO 3 − ), iron (Fe), phosphate ( \(\:\text{P}{\text{O}}_{4}^{3-}\) ), turbidity (TUR) and total dissolved solids (TDS) were measured according to the APHA method 27 in the seven reservoirs in Sri Lanka (Table S1 ).
A total of 56 samples (adult healthy males ( n = 4) and females ( n = 4) from each reservoir), Nile tilapia O. niloticus were collected in February 2024 from the seven reservoirs of Padaviya (P, 8.834° N, 80.771° E), Yan oya (Y, 8.166° N, 80.733° E), Minneriya (M, 8.026° N, 80.871° E) and Kaudulla (K, 8.124° N, 80.904° E) reservoirs from the North-Central Province; Ulhitiya (UL, 7.453° N, 81.061° E), Rathkinda (R, 7.292° N, 80.636° E), and Udawalawe (U, 6.444° N, 80.835° E) reservoirs from the Uva Province of Sri Lanka (Fig. 1 ). Each of the selected reservoirs hosts unique habitats, providing a comprehensive view of the aquatic biodiversity in the region. Meanwhile, these main reservoirs are where the fishing activities happen. The sex identification in tilapia fish was performed by examining the genital papilla, which is located just behind the anus. In males, the papilla was a single opening (the urinary pore), while in females, there were two openings; the urinary pore and the genital pore. The total (TL) and standard length (SL) of each male and female fish were measured to the nearest cm using a calibrated measuring board (Table S2 ). The whole-body weight (500–800 g) was obtained to the nearest gram (0.1 g) using an electronic balance (KERN ALJI60-4NM, Germany). Fish were euthanized by being immersed in Tricaine Methanesulfonate (MS-222)- (250–500 mg/L) for 30 min prior to dissection. Afterward, the fish were washed with water and disinfected using 70% ethanol 21 . Euthanized fish were dissected and the posterior region (mid gut and hind gut) of the intestine were immediately collected. A portion of the intestine samples was stored at -20 °C to DNA extraction, while a portion of the sample was used for bacterial culture.
A map showing the seven sampling reservoirs in Sri Lanka. Padaviya (P), Yanoya (Y), Rathkinda (R), Ulhitiya (UL), Kaudulla (K), Minneriya (M), and Udawalawe (UD). The map was extracted from https://in.pinterest.com/pin/827325394081724887/ and satellite images were derived from google earth https://earth.google.com/web . The figure was created by the first author.
The midgut and hindgut portions of the intestine were combined, and the DNA was extracted from the gut contents using a DNA isolation kit (Omega Bio-Tek, USA) with some modifications. The quality and quantity of DNA were determined by 1% agarose gel electrophoresis and Nanodrop 2000 spectrophotometer (Thermo Scientific, USA). After extracting total DNA of samples, primers 338F (5′-ACTCCTACGGGAGGCAGCA-3′); 806R (3′-GGACTACHVGGGTWTCTAAT-5′) were designed targeting the V3-V4 region of 16S rRNA. Primers were modified by attaching sequencing adapters, followed by the amplification of the target sequences through PCR. The thermal cycling was performed with an initial denaturation at 95 °C for 5 min; followed by 25 cycles of denaturation at 95 °C for 30s, annealing at 50 °C for 30s, elongation at 72 °C for 40s min and a final extension at 72 °C for 7 min. The PCR products were purified and quantified to get a sequencing library. For the constructed library, the Illumina NovaSeq 6000 sequencing (Illumina, Santiago, CA, USA) was conducted at the BMK Cloud (Biomarker Technologies Co., Ltd., Beijing, China). The library quality control (QC) was conducted to ensure the integrity and suitability of the samples for sequencing. The high-throughput sequencing process generated original image data files, which were then converted into Sequenced Reads through Base Calling analysis, enabling further bioinformatics processing and analysis of the genetic data. The results were stored in FASTQ (referred to as fq) format file, which contains sequence information of reads and their corresponding sequencing quality information. Raw reads were firstly filtered by Trimmomatic v0.33 28 . Then the primer sequences were identified and removed by cutadapt 1.9.1, which finally generated high-quality reads without primer sequences. De-noise was processed by dada2 29 in R library in order to de-noise and remove chimeric sequences, generating non-chimeric reads. The high-quality reads generated from above steps were used in the following analysis. Sequences with similarity ≥ 97% were clustered into the same operational taxonomic unit (OTU) by USEARCH 30 (v10.0), and the OTUs with re-abundance < 0.005% were filtered. Taxonomy annotation of the OTUs was performed based on the Naive Bayes classifier in QIIME2 31 using the SILVA database 32 with a confidence threshold of 70%.
The fish abdomen was carefully opened, and the posterior region (mid gut and hind gut) of the intestine was collected under sterile conditions to avoid contamination. The intestinal contents were homogenized in a sterile distilled water to release the bacteria and culturing was carried out immediately after dissection. The bacterial isolation and selection were done by using a standard dilution plating method with the serial dilutions (10 − 1 , 10 − 2 , 10 − 3 , and 10 − 4 ) of samples plated on R2A (Reasoner’s 2 A agar) media and incubated at 28 °C for 3–4 days. Colonies were chosen based on the size, shape, color, texture, and other visible characteristics that may indicate purity or distinct bacterial types. Each selected colonies were further purified through subculturing sub culturing it on R2A media as a routine procedure 33 . The bacteria were preserved at -80 °C in 40%(v/v) glycerol. The isolated bacteria were used for further analysis.
DNA extraction of isolated bacteria was performed using DNA isolation kit (Omega Bio-Tek, USA) with some modifications. The quality and quantity of DNA were determined by 1% agarose gel electrophoresis and Nanodrop 2000 spectrophotometer (Thermo Scientific, USA). The 16S rRNA genes were partially amplified using universal primers 27F (5′- AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′) 34 and a 25µL polymerase chain reaction (PCR), including 11 µL ddH 2 O, 0.5 µL of each forward and reverse primers (10mmol/L), 11µL 2×SYBR Prime-Script™ Master Mix (TaKaRa, Japan) and 2µL of template DNA. The thermal cycling process began with an initial denaturation at 95 °C for 10 min; followed by 32 cycles of denaturation at 95 °C for 30s, annealing at 55 °C for 30s, elongation at 72 °C for 1 min and a final extension at 72 °C for 10 min. The PCR-amplified products were analyzed on agarose gels stained with ethidium bromide, visualized using a gel documentation system (Bio- Rad) and sent for sequencing. The sequencing analysis involved 19 culturable intestinal bacterial species. All sequenced data was checked using the Basic Local Alignment Search Tool (BLAST) and sequences were aligned using the ClustalW program in gene studio software. The phylogenetic tree was constructed using the MEGA 11 software package, which used the p- distance method to calculate genetic distances 35 .
The alpha diversity of the intestinal microbiota in male and female O. niloticus across the seven reservoirs was assessed using several metrics, including Chao1, ACE (Abundance-based Coverage Estimator), Shannon, and Simpson, to evaluate the richness and diversity based on OTUs using QIIME2 31 software. The two-way ANOVA was chosen as default for difference significance test with Tukey’s HSD (Honestly Significant Difference) applied for post hoc analysis. Beta diversity was examined using unweighted and weighted UniFrac distances, with principal coordinate analysis (PCoA) for visualization in QIIME 36 . Analysis of similarities (ANOSIM) and Permutational multivariate analysis of variance (PERMANOVA) were used to assess the significance of differences in the intestinal microbiota of O. niloticus across seven reservoirs in Sri Lanka. Spearman rank correlation analysis identified correlations (coefficient > 0.1, p ≤ 0.05), which were used for network construction. Canonical Correspondence Analysis (CCA) at the genus level and Redundancy Analysis (RDA) at the phylum level were conducted to analyze the interplay between community composition and environmental factors. The heatmaps were generated by R package according to microbial composition and relative abundance at level of phylum and genus. All data analysis was performed using SPSS software (Ver. 26.0) 37 and a P-value less than 0.05 ( p ≤ 0.05) was considered as significantly different.
In the present study, we examined the microbial community composition of the intestine of 56 Nile tilapia, O. niloticus , in seven reservoirs of Sri Lanka. A total of 4,273,317 PE reads were generated from 56 samples and among these, 2,166,811 PE reads for females and 2,106,506 PE reads for males were obtained after PE reads quality control and assembly. Minimum of 48,504 and average of 76,309 clean reads were generated for each sample. The findings of the present study revealed significant variation in gut microbiota across the locations and gender of O. niloticus in reservoirs of Sri Lanka. A total of 1491 genera; 1097 genera in females and 1288 genera in males were observed in the intestinal microbiota of O. niloticus in Sri Lanka. Among the 43 represent phyla, 39 phyla in females and 42 phyla in male samples were observed in the intestinal microbiota of O. niloticus .
A Venn diagram illustrates both the shared and unique characteristics among samples and helps pinpoint common microbes between groups. The Venn diagram displayed the number of common and distinct operational taxonomic units (OTUs). The findings revealed that 65 OTUs were shared across all the reservoirs in Sri Lanka and major genera were Cyanobium PCC 6307, Clostridium sensu stricto 1 , Cetobacterium , unclassified Peptostreptococcaceae unclassified Cyanobacteriia , Turicibacter , Romboutsia , and Bacillus. There were 2764 shared OTUs between male and female samples in Sri Lanka, with 9467 and 12,871 OTUs being unique to females and males, respectively. The composition of gut contents may lean toward flora associated with food particles rather than flora intrinsically tied to the gut. Consequently, the observed floral diversity is likely to arise predominantly from food-related sources, which may not represent an accurate depiction of gut-associated bacterial diversity.
Among the most abundant gut microbial genera in Sri Lankan reservoirs, Cyanobium PCC 6307, Clostridium sensu stricto 1 , Cetobacterium , LD29 , Romboutsia , unclassified Cyanobacteria , Turicibacter , Paeniclostridium , Bacillus , unclassified Clostridiaceae , and Methylocystis showed a significant difference ( p ≤ 0.05) across the seven reservoirs in Sri Lanka while unclassified Peptostreptococcaceae , unclassified Cyanobacteriales and Paracoccus showed no significant difference in relative abundance (Table S3). Among the most abundant phyla, the relative abundance of Firmicutes, Cyanobacteria, Proteobacteria, Fusobacteriota, Verrucomicrobiota, Actinobacteriota, unclassified bacteria, Planctomycetota, Chloroflexi, Patescibacteria, Bacteroidota, Bdellovibrionota, and Dependentiae showed a significant difference ( p ≤ 0.05) in the intestinal microbiota of O. niloticus across seven reservoirs in Sri Lanka. Conversely, the relative abundance of Acidobacteriota and Campylobacterota did not show a significant difference among the reservoirs (Table S4).
Remarkably, the relative abundance of gut microbiota of O. niloticus exhibited significant differences between males and females in the reservoirs of Sri Lanka. Interestingly, males showed significant ( p ≤ 0.05) higher relative abundance of genus Methylocystis than females. Other bacterial communities did not exhibit a significant difference in relative abundance ( p ≤ 0.05) between the sexes (Fig. 2 A). Besides, gut microbiota of male O. niloticus showed a significantly higher relative abundance ( p ≤ 0.05) of the phyla Bdellovibrionota, Campylobacterota, and Myxococcota compared to females. A noteworthy observation from this study was that the gut microbiota revealed phyla Abditibacteriota, Aenigmarchaeota, Crenarchaeota, and Entotheonellaeota exclusively present in males, while the phylum Euryarchaeota was found solely in females (Fig. 2 B).
Relative abundance of intestinal microbiota in O. niloticus across seven reservoirs in Sri Lanka ( A ) Bar-plots showing the most abundant genera ( B ) Bar-plots showing the most abundant phyla, M-Male, F-Female R-Rathkinda reservoir, P-Padaviya reservoir, M-Minneriya reservoir, K-Kaudulla reservoir, Y-Yanoya reservoir, UL-Ulhitiya reservoir, and UD-Udawalawe reservoir.
Alpha diversity was assessed using the ACE (Fig. 3 A), Chao1 (Fig. 3 B), Shannon (Fig. 3 C), and Simpson (Fig. 3 D) indices to examine the bacterial community of male and female O. niloticus across the seven reservoirs. Both ACE ( p = 0.001) and Chao 1 ( p = 0.001) indices revealed that the intestinal microbiota of O. niloticus in the Rathkinda reservoir exhibited significantly (Two-way ANOVA, p ≤ 0.05) higher microbial richness compared to those in other reservoirs, while the intestinal microbiota of O. niloticus from the Yanoya reservoir exhibited the least microbial richness. All indices showed no significant difference (Two-way ANOVA, p ≤ 0.05) between the intestinal microbial community of male and female O. niloticus (Table S5).
Alpha diversity of intestinal microbiota of O. niloticus across seven reservoirs by OTUs. ( A ) ACE, ( B ) Chao1, ( C ) Shannon and ( D ) Simpson indices. M-Male, F-Female, R-Rathkinda reservoir, P-Padaviya reservoir, M-Minneriya reservoir, K-Kaudulla reservoir, Y-Yanoya reservoir, UL-Ulhitiya reservoir, and UD-Udawalawe reservoir.
PCoA was performed using weighted and unweighted unifrac distance method at the genus level. Weighted unifrac considers the abundance of species, while unweighted unifrac only considers their presence or absence. If the differences in the data are more related to species presence rather than abundance, unweighted unifrac explains more variance. Weighted unifrac distance (Fig. 4 A and B), PC1% variation accounted for 14.38% and PC2 for 28.26%, while unweighted unifrac distance (Fig. 4 C and D) was observed a percent variation, PC1 for 11.05% and PC2 for 12.97% of the total differences. Further, ANOSIM and PERMANOVA were performed for both weighted and unweighted unifrac distance results. Based on the analysis of O. niloticus intestinal microbiota among reservoirs, the ANOSIM ( R = 0.303; p = 0.001) and PERMANOVA (R 2 = 0.324; p = 0.001) for weighted unifrac distance, while ANOSIM ( R = 0.347; p = 0.001) and PERMANOVA (R 2 = 0.222; p = 0.001) for unweighted unifrac distance. The results of ANOSIM and PERMANOVA indicate significant differences of intestinal microbiota of O. niloticus across the seven reservoirs at the genus level.
Principal coordinate analysis based on ( A ) ANOSIM and ( B ) PERMANOVA of weighted unifrac and ( C ) ANOSIM ( D ) PERMANOVA of unweighted unifrac distance of the intestinal microbiota of O. niloticus across seven reservoirs in Sri Lanka at the genus level. R-Rathkinda reservoir, P-Padaviya reservoir, M-Minneriya reservoir, K-Kaudulla reservoir, Y-Yanoya reservoir, UL-Ulhitiya reservoir, and UD-Udawalawe reservoir.
Spearman’s rank correlation analysis (spearman’s rank correlation coefficients-ρ) was used to identify the association of intestinal microbial communities of O. niloticus in seven reservoirs in Sri Lanka. Genus Paracoccus (ρ ranged from − 0.373 to 0.134) and Roseomonas (ρ ranged from − 0.480 to 0.242) also exhibited negative correlations with most other genera. Whereas, Romboutsia (ρ ranged from − 0.284 to 0.556) and Bacillus (ρ ranged from − 0.270 to 0.566) showed positive correlations with almost all other genera. Genus Paeniclostridium had a strong negative correlation (ρ=-0.5, p ≤ 0.05) with Paracoccus and unclassified Beijerinckiaceae had a strong positive correlation (ρ = 0.77, p ≤ 0.05) with unclassified Bacteria compared to other genera (Fig. 5 A). Moreover, Phylum Fusobacteriota (ρ ranged from − 0.52 to 0.58) and Bacteroidota (ρ ranged from − 0.62 to 0.58) exhibited inverse associations with nearly all other phyla. Bdellovibrionota (ρ ranged from − 0.61 to 0.699) and Dependentiae (ρ ranged from − 0.445 to 0.657) showed positive correlations with almost all other phyla. Further, Phylum Planctomycetota (ρ=-0.629, p ≤ 0.05) had a strongly negative correlation with Bacteroidota, while Chloroflexi showed relatively strong positive correlations with Desulfobacterota (ρ = 0.78, p ≤ 0.05) compared to other phyla (Fig. 5 B).
Correlation network of core gut microbiota composed of 20 bacteria in O. niloticus in seven reservoirs in Sri Lanka using the Spearman rank test ( A ) at the genus level ( B ) at the Phylum level.
CCA and RDA were performed at the genus and phylum level, respectively. CCA analysis for water quality parameters at the genus level showed that CCA1 and CCA2 were accounted for 5.06% and 4.67% of the variation in the data, respectively. CCA analysis revealed that Cyanobium was negatively associated with TDS, TA, TH and T. Clostridium sensu stricto 1 , Bacillus and unclassified Cyanobacteria showed positive association with the same parameters Conversely, it showed positive correlations with phosphate \(\:\text{P}{\text{O}}_{4}^{3-}\) and \(\:\text{N}{\text{O}}_{3}^{-}\) (Fig. 6 A).
Further, The RDA analysis for water quality parameters at the phylum level showed that RDA1 and RDA2, which accounted for 7.44% and 5.43% of the variation in the data, respectively. Patescibacteria and Verrucomicrobiota were positively correlated with TDS, TA and TH, while Cyanobacteria was negatively associated with the same parameters. Further, Firmicutes positively associated with TA and TH. Planctomycetota, Chloroflexi, Actinobacteriota, Proteobacteria and unclassified Bacteria were positively associated with \(\:\text{P}{\text{O}}_{4}^{3-}\) and \(\:\text{N}{\text{O}}_{3}^{-}\) (Fig. 6 B).
Canonical correspondence analysis (CCA) and Redundancy analysis (RDA) for the relationships between bacterial community compositions and water quality parameters ( A ) At the genus and ( B ) At the phylum level. Water quality parameters were water temperature (T), total alkalinity (TA), total hardness (TH), nitrate (NO 3 − ), phosphate ( \(\:\text{P}{\text{O}}_{4}^{3-}\) ), and total dissolved solids (TDS). R-Rathkinda reservoir, P-Padaviya reservoir, M-Minneriya reservoir, K-Kaudulla reservoir, Y- Yanoya reservoir, UL-Ulhitiya reservoir, and UD-Udawalawe reservoir
The correlation heatmap illustrated the relationship between bacterial community composition and water quality parameters. Among the prevalent bacterial genera, Cyanobium exhibited a pronounced negative correlation with several parameters, including TH, TA, and TDS. Conversely, Clostridium sensu stricto 1 and unclassified Clostridiaceae demonstrated a significant positive correlation with the same parameters. Notably, genus LD29 displayed a strong negative correlation with T, TUR, and NH 3 , while Cetobacterium and Turicibacter exhibited robust positive correlations with these parameters (Fig. 7 A). Regarding the most abundant phyla, Firmicutes showed positive associations with T, Cl − , TA, TH and Ca. In contrast, Cyanobacteria displayed negative correlations with the same parameters. Furthermore, Patescibacteria and Verrucomicrobiota exhibited strong negative correlations with T, free NH 3 , Fe and TUR while TA and TDS showed robust positive correlations with these genera (Fig. 7 B).
Spearman correlation heatmap of the water quality parameters with top 15 microbes ( A ) At the genus level and ( B ) at the phylum level. X- and Y-axis represent water quality parameters and different phyla and genus, respectively. Significant results are indicated by * P < 0.05, ** P < 0.01, *** P < 0.001. Water quality parameters were temperature (T), pH, Floride (F), Chloride (Cl − ), Total Alkalinity (TA), Total Hardness (TH), Calcium (Ca), Magnesium (Mg), Free Ammonia (NH 3 ), Nitrate (NO 3 − ), Iron (Fe), Phosphate ( \(\:\text{P}{\text{O}}_{4}^{3-}\) ), Turbidity (TUR) and Total Dissolved Solids (TDS)
The phylogenetic analysis was performed based on 16S rRNA gene sequences from nineteen bacterial strains isolated from the intestine of O. niloticus . Among these culturable intestinal bacterial species, the predominant phyla were Firmicutes, Proteobacteria, Deinococcota, and Actinobacteria (Fig. 8 ). Notably, our high-throughput results aligned with the outcomes obtained through 16S rRNA sequencing. We identified various bacteria using high-throughput sequencing, including opportunistic pathogens such as, 0.0006% of Aeromonas , 0.0001% of Rothia , 0.0006% of Staphylococcus , and 0.003% of Plesiomonas . According to the literature evidence, we found bacteria with potential probiotic properties, including 0.02% of Bacillus. Moreover 0.002% of Paenibacillus , 0.01% of Acinetobacter , and 0.0003% of Psychrobacter . The 16S rRNA sequences were deposited to the NCBI repository.
Maximum likelihood phylogenetic tree based on comparing their 16S rRNA gene sequences of isolated bacteria from the intestinal microbiota of O. niloticus in the seven reservoirs in Sri Lanka. Bootstrap values (expressed as percentages of 1000 replications) and evolutionary distances were computed using the TN93 + G (Tamura and Nei 1993) model by MEGA 11.
Fish gut microbiome is crucial for maintaining host health by promoting immune system development, aiding nutrient acquisition, and outcompeting opportunistic pathogens 38 . In Sri Lanka, the gut microbiota of O. niloticus exhibited marked variations across the seven reservoirs studied. The fish samples collected from reservoirs contained food matter in their guts, and their microbial diversity was studied without washing off the gut contents. Interestingly, the primary bacterial genera within the core gut microbiota of O. niloticus are Cyanobium , Clostridium sensu stricto 1 , Cetobacterium , LD29 , and Romboutsia . Additionally, the dominant bacterial phyla in the core gut microbiota across all studied reservoirs are Firmicutes, Cyanobacteria, Proteobacteria, Fusobacteriota and Verrucomicrobiota. Furthermore, the gut microbiota of O. niloticus in the Rathkinda reservoir exhibited a higher number of OTUs (5385) compared to the Yanoya reservoir, which showed fewer OTUs (1977). Thus, the gut microbiota of O. niloticus across seven reservoirs in Sri Lanka harbored distinct bacterial genera, O. niloticus in the Udawalawe reservoir is predominantly inhabited by Cyanobium , a phylum of Cyanobacteria. Further, O. niloticus in the Yanoya reservoir had a high abundance of Clostridium sensu stricto 1 , while O. niloticus in the Kaudulla reservoir had a high abundance of Turicibacter. Both Clostridium sensu stricto 1 and Turicibacter belong to the phylum Firmicutes. Cetobacterium , a Fusobacteriota, was the dominant genus in O. niloticus in both Ulhitiya and Minneriya reservoirs. Genus LD29 , belonging to the phylum Verrucomicrobiota, was in high abundance in O. niloticus in the Padaviya reservoir. Moreover, the alpha and beta diversity outcomes confirmed that the intestinal microbial community of O. niloticus exhibited high richness and diversity in the Rathkinda and Padaviya reservoirs, respectively. The variations in bacterial community richness and diversity evident across different sampling locations. Previous research has consistently shown that Firmicutes, Cyanobacteria, Proteobacteria, and Fusobacteriota are the prevailing microbiota in freshwater fish 39 , 40 , 41 . Bereded et al. (2022) found that Firmicutes were the predominant phylum in samples from Lake Awassa and Lake Chamo, whereas Fusobacteriota were more prevalent in samples from Lake Hashengie and Lake Tana. In the intestines of Nile tilapia raised in aquaculture ponds in Bangladesh, Cyanobacteria were identified as the dominant and bacterial phyla with Proteobacteria, Actinobacteria, and Fusobacteria also being detected 42 . Whereas, Fusobacteria are widely observed as a prominent component of microbiomes in farmed O. niloticus within the Aiyura valley, located in the Eastern Highlands of Papua New Guinea 43 . Tilapia fed the plant based dry food diet exhibited a rise in microbial communities that ferment digestible carbohydrates under anaerobic conditions within the intestine of O. niloticus commercial freshwater fish in China. Likewise, at the genus level, Gemmobacter , Pirellula , and Planctomyces were notably more abundant in fish consuming the plant based dry diet. These microbes, belonging to the Planctomycetes group, have been recognized for their ability to ferment carbohydrates. Whereas, before feeding, the primary intestinal microbiota of tilapia larvae, at the phylum level, consisted of Proteobacteria, Firmicutes, Actinobacteria, Planctomycetes, Fusobacteria, and Bacteroidetes 44 . These findings suggest that the consistency of gut microbiota may be influenced by geographic locations, potentially due to varying environmental conditions across different regions.
Remarkably, the O. niloticus population in the Udawalawe Reservoir within Sri Lanka displayed a markedly higher occurrence of this particular cyanobacterium (relative abundance: 0.31 ± 0.04%) compared to other studied reservoirs in Sri Lanka. Specially, we found Cyanobium gracile in the gut microbiota of O. niloticus from the seven reservoirs, and Cyanobium water blooms appeared to be more widespread. These freshwater cyanobacteria have the potential to cause harmful algal blooms, which can have significant economic and ecological consequences 45 . Whereas, ingestion and digestion of noxious cyanobacteria, cyanotoxins are liberated and tend to amass within the liver, muscles, and other internal organs of fish 46 . Further, we observed the presence of genus Cetobacterium in the gut microbiome, particularly Cetobacterium somerae . This bacterium plays a critical role in vitamin B12 production, which is essential for synthesizing haem, a key component of hemoglobin and myoglobin 47 . In this study, Clostridium butyricum , a genus Clostridium was identified in the gut samples. Notably, various strains of Clostridium butyricum have been observed in diverse ecological contexts as commensal bacteria in the intestines of both humans and animals 48 . Research studies have emphasized the probiotic properties of distinct Clostridium butyricum strains, which have been successfully commercialized in different countries 49 , 50 . Our high-throughput findings align with the results from 16S rRNA sequencing. Among the confirmed bacterial phyla, Firmicutes, Proteobacteria, Deinococcota, and Actinobacteria were isolated. Notably, the isolated bacteria, Paenibacillus polysaccharolyticus and Acinetobacter oryzae have the capacity to enter the gut through their food, which originates from plants. Specifically, Paenibacillus polysaccharolyticus has been identified in Bamboo plant leaves 51 . The presence of hemicellulose, a polymer abundant in various plant systems, containing substantial amounts of xylan 52 . Interestingly, within different plant-associated bacterial genera, certain species of the genus Paenibacillus have been identified as potential xylan degraders 51 . This has the potential to aid in the digestion of plant material within the gastrointestinal tract of O. niloticus . Further, Deinococcus actinosclerus and Deinococcus seoulensis , originally from soil on a rocky hillside and sediment areas, respectively 53 , 54 were also detected in the gut microbiome of O. niloticus in Sri Lanka. This implies that these bacteria found their way into the intestines of O. niloticus via the sedimentary debris present in the reservoir. The study identified several bacterial species associated with opportunistic pathogenesis. The isolated bacterium Rothia aerolata , genus Rothia is increasingly recognized as an opportunistic pathogen associated with infections in humans 55 . Further, Aeromonas hydrophila and Aeromonas veronii , which may inhabit the gut of O. niloticus , are known pathogens affecting fish 56 . Additionally, Staphylococcus warneri and Staphylococcus pasteuri were isolated, with the latter also identified as a human pathogen 57 , 58 , 59 , 60 . Plesiomonas , a bacterium, was isolated in the gut microbiota of O. niloticus in the seven reservoirs. Notably, Plesiomonas shigelloides has caused substantial mortality in rainbow trout 61 and largemouth bass ( Micropterus salmoides ) 62 . Moreover, it is increasingly recognized as a causative agent of diarrheal disease in humans 63 . These findings highlight the potential pathogenic impact on O. niloticus and the role of specific bacterial species in gut microbiota establishment.
Nile tilapia exhibits an omnivorous diet, consuming a diverse array of food sources such as phytoplankton, macrophytes, insects, detritus, and zooplankton. Their dietary preferences evolve as they grow and are influenced by the availability of food in their surroundings. Typically, juvenile tilapia tends to consume more animal-based food, while adult tilapia shifts towards a predominantly plant-based diet including plant materials, algae, and detritus 64 . This diet is rich in complex carbohydrates and fibers, which are more challenging to digest. As these materials pass through the long intestine, they undergo fermentation by gut microbes. The fermentation process in the gut, particularly in herbivores, tends to deplete oxygen quickly. As the plant material ferments, the oxygen levels decrease, creating anaerobic conditions. On the other hand, tilapia is known for their ability to thrive in environments with low levels of dissolved oxygen, which could create conditions conducive to the establishment of true anoxia within their gut 65 . These conditions favor the growth of anaerobic bacteria, which do not require oxygen to thrive. Particularly, Bacillus proteolyticus , Bacillus tropicus , Paenibacillus polysaccharolyticus , Plesiomonas shigelloides , and Staphylococcus pasteuri were isolated from the tilapia gut, and these species are facultative anaerobes. They can grow in the presence of oxygen; they can also thrive in anaerobic conditions. This adaptability likely contributes to their prevalence in the oxygen-variable environment of the tilapia gut. Moreover, the genus Cetobacterium is recognized as a major group of gut bacteria in many freshwater fish species, contributing significantly to anaerobic metabolic processes 66 . Our current investigation involves the isolation of beneficial bacterial strains tailored for the aquaculture industry. Specially, this study isolated multiple Bacillus species, including Bacillus proteolyticus , Bacillus pseudomycoides , Bacillus tropicus , Bacillus altitudinis , Bacillus aerius , and Bacillus stercoris. These Bacillus strains serve as probiotics, promoting growth and disease resistance in tilapia and other species 67 . Additionally, we detected Exiguobacterium indicum and Exiguobacterium acetylicum bacteria in water samples from reservoirs in Sri Lanka (unpublished results). It’s plausible that these bacteria could enter the intestines of O. niloticus through water exposure. Furthermore, existing research suggests that the Exiguobacterium genus holds promise for probiotic production in aquaculture 68 .
Certainly, in the context of correlation analysis in reservoirs in Sri Lanka, among the genera, Paracoccus and Roseomonas exhibited predominantly negative correlations with other genera, suggesting potential competitive interactions or distinct ecological niches. On the other hand, Romboutsia and Bacillus showed positive correlations with nearly all other genera, indicating potential synergistic relationships or shared environmental preferences. Notably, the genus Paeniclostridium had a strong negative correlation with Paracoccus , suggesting a significant antagonistic relationship. Additionally, an unclassified genus from the family Beijerinckiaceae showed a robust positive correlation with unclassified bacteria, emphasizing specific inter-genus associations within the microbial community. At the phylum level, Fusobacteriota and Bacteroidota exhibited inverse associations with most other phyla, indicating their unique ecological roles or competitive exclusion dynamics. In contrast, Bdellovibrionota and Dependentiae demonstrated positive correlations with almost all other phyla, hinting at their potential role in fostering microbial diversity or stability. Particularly noteworthy is the strong negative correlation between Planctomycetota and Bacteroidota, highlighting significant interactions that might influence microbial community structure. Similarly, Chloroflexi showed strong positive correlations with Desulfobacterota, suggesting a closely linked ecological or metabolic relationship between these two phyla. These findings highlight the crucial role of core taxa in maintaining gut microbiota stability. The study found that most of the core bacterial genera in O. niloticus exhibit positive correlations, indicating a symbiotic interaction among themselves. Moreover, these findings underscore the intricate network of associations within the intestinal microbiota of O. niloticus , providing a foundational understanding of the microbial interactions that could influence the health and functioning of these aquatic organisms. Further research is needed to unravel the underlying mechanisms driving these correlations and their ecological implications.
The heatmap reveals a nuanced interplay between water quality parameters and the bacterial community composition. For instance, the pronounced negative correlation of toxin-producing Cyanobium with TH, TA, and TDS suggests that these parameters might create an unfavorable environment for Cyanobium growth. This could be due to the potential inhibitory effects of high mineral content and alkalinity on Cyanobium . On the other hand, Clostridium sensu stricto 1 and unclassified Clostridiaceae show significant positive correlations with TH, TA, and TDS. These genera may possess adaptive mechanisms that allow them to thrive in harder and more alkaline water, possibly benefiting from the increased mineral availability for their metabolic processes. The study also highlights a strong negative correlation of genus LD29 with T, TUR, and NH 3 . This suggests that LD29 might favor cooler, clearer waters with lower ammonia levels, possibly due to their preference for stable and less polluted environments in Padaviya and Minneriya reservoirs. Conversely, Cetobacterium and Turicibacter exhibit robust positive correlations with T, TUR, and NH 3 , indicating that these genera may thrive in warmer, more turbid, and ammonia-rich conditions. This could be due to their ability to utilize ammonia as a nutrient source and tolerate higher temperatures and turbidity. Regarding the most abundant phyla, Firmicutes display positive associations with T, Cl − , TA, TH, and Ca, suggesting that these bacteria thrive in warmer, more mineral-rich environments. This might be attributed to their resilience and adaptability to varied conditions. In contrast, Cyanobacteria exhibit negative correlations with the same parameters, indicating that these conditions might not be conducive to their growth. This could be due to the potential stress caused by high mineral content and alkalinity on Cyanobacteria. Interestingly, male O. niloticus demonstrated distinct microbial associations, with the genus Methylocystis exhibiting a significantly positive correlation with pH, suggesting that alkaline conditions may favor the presence of specific methane-oxidizing bacteria in males. Phyla Bdellovibrionota showed a significant positive correlation with PO₄³⁻, which thrive in oxygen-limited environments, possibly linked to higher metabolic activity or territorial behavior. Campylobacterota displayed a significant positive correlation with temperature and turbidity, reflecting adaptations to warmer and murkier environments often linked to territorial defense behaviors. Additionally, Myxococcota exhibited a significant positive correlation with PO₄³⁻, indicating a potential role in nutrient cycling within male microbiomes. The correlation heatmap provides valuable insights into the intricate relationships between water quality parameters and microbial diversity. However, to fully understand the mechanisms driving these correlations, further investigation is needed.
Among the seven reservoirs examined, the Methylocystis genus showed a marked significant difference in the gut microbiota of male O. niloticus . The presence of Methylocystis in the gut suggests a symbiotic relationship where these bacteria benefit from the nutrients available in the male fish gut environment, while potentially aiding in the host’s digestion and overall health by mitigating methane production. Moreover, this interaction may be significant because Methylocystis plays a role in methane oxidation, which helps reduce methane emissions from aquatic environments 69 , 70 . However, the exact mechanisms of this interaction and its impact on male tilapia health and the surrounding ecosystem require further research. These findings suggest that gender might have a relatively more significant role in shaping the gut microbiota as well as environmental factors. However, previous studies have shown that variations in the structure and composition of gut microbiota between male and female fish could be attributed to their metabolic differences 71 . Further investigation is warranted to comprehend the mechanisms and implications of this noteworthy finding. Although the abundance of gut microbiota varied across the sampling reservoirs, several microbial communities are believed to be crucial for maintaining the health of the host by performing various functions of the gut microbiome. Based on these findings, we hypothesized that there may be variations in the functional activity of intestinal microbiota with the environmental conditions. Our study highlights that the gut microbiota of O. niloticus may be more affected by environmental factors than by gender. Further research is required to understand the functional importance of gut microbiota variations in relation to the geographic environment.
The study identified the intestinal microbiota of O. niloticus from seven reservoirs in Sri Lanka. The gut microbes varied significantly by reservoir and gender, with different bacterial genera dominating in each location. Among the most abundant intestinal microbial genera of O. niloticus , Cyanobium PCC 6307, Clostridium sensu stricto 1 , Cetobacterium , LD29 , Romboutsia , unclassified Cyanobacteria , Turicibacter , Paeniclostridium , Bacillus , unclassified Clostridiaceae , and Methylocystis showed a significant difference across the seven reservoirs in Sri Lanka. At the phylum level, Firmicutes, Cyanobacteria, Proteobacteria, Fusobacteriota, Verrucomicrobiota, Actinobacteriota, unclassified bacteria, Planctomycetota, Chloroflexi, Patescibacteria, Bacteroidota, Bdellovibrionota, and Dependentiae also showed significant differences in the intestinal microbiota of O. niloticus across these reservoirs. Interestingly, alpha diversity was exhibited that the intestinal microbiota of O. niloticus in the Rathkinda reservoir exhibited significantly higher microbial richness compared to those in other reservoirs, while the intestinal microbiota of O. niloticus from the Yanoya reservoir exhibited the least microbial richness. Whereas, the beta diversity analysis indicates significant differences of intestinal microbiota of O. niloticus across the seven reservoirs at the genus level. On the other hand, the toxin-producing Cyanobium exhibited significant negative correlations with multiple water quality parameters including chloride, total hardness, calcium, total alkalinity and total dissolved solids in the studied reservoirs. Moreover, the study indicates that specific bacterial species found in the gut microbiota of O. niloticus from Sri Lanka have potential for commercial applications, especially in probiotics. Whereas, some identified bacteria could pose pathogenic risks to O. niloticus . Further, the data generated from this study on the gut microbiota of O. niloticus provides valuable insights for sustainable aquaculture development across different geographic locations.
Sequence data that support the findings of this study have been deposited in the National Center for Biotechnology Information (NCBI) with the primary accession numbers were Aeromonas hydrophila ON 22 (PQ358617), Acinetobacter oryzae ON-31 (PQ363040), Bacillus aerius ON-33 (PQ363064), Bacillus altitudinis ON-26 (PQ363143), Bacillus proteolyticus ON-29 (PQ363174), Bacillus pseudomycoides ON-37 (PQ363176), Bacillus stercoris ON-34 (PQ363177), Bacillus tropicus ON-25 (PQ363271), Deinococcus seoulensis ON-23 (PQ367392), Exiguobacterium acetylicum ON-30 (PQ367518), Exiguobacterium indicum ON-24 (PQ367797), Plesiomonas shigelloides ON-38 (PQ367921), Paenibacillus polysaccharolyticus (PQ367833), Psychrobacter alimentarius ON-36 (PQ368076), Rothia aerolata ON-39 (PQ368167), Staphylococcus pasteuri ON-27 (PQ368250), Staphylococcus warneri ON-32 (PQ368251), Deinococcus actinosclerus ON-28 (PQ368306), and Aeromonas veronii bv. veronii ON-40 (PQ368327).The high-throughput sequencing data can be accessed through the NCBI with the BioProject identifier PRJNA1217125. The corresponding BioSample and SRA accession numbers range from SAMN46479457 to SAMN46479512.The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request (Professor Dongru Qiu, Email: qiu@ihb.ac.cn).
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The first author was sponsored by TWAS President’s Fellowship Programme of the World Academy of Sciences. Further, we would like to acknowledge the fishing community of Yanoya, Padaviya, Kaudulla, Minneriya, Udawalawe, Ulhitiya and Rathkinda reservoirs for providing fish samples for this research.
This work was funded by the Program of China-Sri Lanka Joint Research and Demonstration Center for Water Technology and the China-Sri Lanka Joint Center for Education and Research, Chinese Academy of Sciences (Award Y72Z261).
National Key Laboratory of Breeding Biotechnology and Sustainable Aquaculture (CAS), Institute of Hydrobiology, Chinese Academy of Sciences, Wuhan, 430072, China
W. M. Lakshani Anuradha Wanasinghe, Siliang Yuan & Dongru Qiu
University of Chinese Academy of Sciences, Beijing, 100049, China
Department of Animal Science, Faculty of Animal Science and Export Agriculture, Uva Wellassa University of Sri Lanka, Passara Road, Badulla, 90000, Sri Lanka
Department of Farm Animal Production & Health, Faculty of Veterinary Medicine & Animal Science, University of Peradeniya, Peradeniya, 20400, Sri Lanka
Department of Basic Veterinary Sciences, Faculty of Veterinary Medicine & Animal Science, University of Peradeniya, Peradeniya, 20400, Sri Lanka
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W. M. L. A. W.- Conceptualization, Methodology, Software, Investigation, Data curation, Formal analysis, Writing – original draft, Writing – review & editing. S. Y.- Writing – review & editing, Formal analysis. M. N. M. F.- Writing –review & editing, Resources. L. G. S. L.- Writing – review & editing, Resources. D. Q.- Supervision, Investigation, Project administration, Writing – review & editing, Resources, Funding acquisition.
Correspondence to W. M. Lakshani Anuradha Wanasinghe or Dongru Qiu .
Ethical approval (VERC-23-015) for this study was obtained from the committee for ethical clearance for research of the Faculty of Veterinary Medicine & Animal Science (FVMAS), University of Peradeniya and all experiments were carried out in accordance with relevant guidelines and regulations. All experiments were performed in accordance with ARRIVE guidelines and regulations.
The authors declare no competing interests.
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Wanasinghe, W.M.L.A., Yuan, S., Fouzi, M.N.M. et al. Comparative analysis of the gut microbiota of the wild nile tilapia ( Oreochromis niloticus ) across the seven reservoirs in Sri Lanka. Sci Rep 16 , 29855 (2026). https://doi.org/10.1038/s41598-025-09867-2
Version of record : 25 September 2026
DOI : https://doi.org/10.1038/s41598-025-09867-2
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