Effects of dietary β-glucans on the productive performance, blood parameters, and intestinal microbiota of angelfish (Pterophyllum scalare) juveniles

Abstract

Among the potential feed additives, β-glucans are known to positively affect the growth performance, blood parameters, and intestinal microbiota of fish, even the ornamental species. Therefore, the present study evaluated the effects of the dietary supplementation of different Saccharomyces cerevisiae β-glucans concentrations (0, 0.05, 0.1, and 0.2%) in juvenile angelfish (Pterophyllum scalare) over a 42-day period. Regarding growth performance, no effects were observed on most parameters. However, 0.2% β-glucans supplementation produced higher condition factor values, indicating a better nutritional status. Furthermore, β-glucans supplementation did not affect blood parameters. Regarding intestinal microbiota, β-glucans supplementation increased the abundance of the potentially beneficial bacterial genus Phascolarctobacterium. The high abundance of bacteria from the phylum Bacteroidetes, which can degrade β-glucans, may be attributed to the increased abundance of Phascolarctobacterium spp. In addition, 0.2% β-glucans supplementation produced more operational taxonomic units and higher Sobs (observed species richness), indicating effects on the overall bacterial community structure. These results demonstrate the potential application of β-glucans as a dietary supplement to improve the performance and modulate the intestinal microbiota of angelfish.

Key words
Freshwater angelfish; Immunostimulants; Ornamental fish; Phascolarctobacterium; Prebiotics; Saccharomyces cerevisiae

INTRODUCTION

In the overall global trade of live fish, the trade of ornamental fish involves smaller quantities but higher economic value than the trade of fish destined for human consumption (FAO 2016). Furthermore, the aquarium industry is a rapidly developing sector, and aquarium keeping is no longer simply a hobby (Karadal et al. 2017). In this context, freshwater angelfish (Pterophyllum scalare), a cichlid native to the Amazon Basin, is one of the most popular ornamental fish species worldwide, mainly because of the body and fin shape, availability of several varieties, peaceful behavior, relative rusticity, excellent adaptability to captivity, easy reproduction, omnivorous eating habit, and acceptance of artificial foods (Azimirad et al. 2016, Ikeda et al. 2011, Fujimoto et al. 2006, Ribeiro et al. 2007). Regarding nutritional management in aquaculture, the use of feed additives can optimize productivity and increase profitability. For this purpose, immunostimulants, such as β-glucans, can be supplied.

β-glucans are polysaccharides composed of glucose linked by β-glycosidic bonds, which are found in the cell wall of several plants, yeasts, mushrooms, seaweeds, and bacteria (Meena et al. 2013). In particular, among the best studied and most applied are β-glucans derived from the cell wall of yeast Saccharomyces cerevisiae (Petit & Wiegertjes 2016). Although studies in fish have demonstrated the efficiency of β-glucans administration through water (Souza et al. 2020a, Zhang et al. 2009) and injection (Rodríguez et al. 2009, Selvaraj et al. 2005), dietary supplementation is a more practical route of administration (Petit & Wiegertjes 2016). However, only a few studies have explored the dietary inclusion of β-glucans in ornamental fish and demonstrated its positive effects on stress resistance, pathogen resistance, immunity, and hematologic response (Abreu et al. 2014, Lin et al. 2011, Russo et al. 2006, Türnal et al. 2000).

Although most previous studies primarily focused on the use of β-glucans for improving immunity and pathogen resistance (Meena et al. 2013, Petit & Wiegertjes 2016), these polysaccharides can also improve growth and other aspects related to productive performance. As such, previous studies have reported the positive effects of dietary β-glucans on parameters related to growth and feed utilization in fish (Ji et al. 2017, Liranço et al. 2013, Talpur et al. 2014, Welker et al. 2012), including ornamental species (Lin et al. 2011). Additionally, there is evidence of the efficacy of β-glucans in modulating the intestinal microbiota of fish (Carda-Diéguez et al. 2014, Harris et al. 2020, Jung-Schroers et al. 2016), including ornamental species (Jung-Schroers et al. 2019). Based on these reports, β-glucans show a great potential for application in commercial fish farming intended for human consumption and ornamental purposes.

To date, however, no study has evaluated the effectiveness of dietary β-glucans supplementation in Pterophyllum scalare. There is only one study evaluating the effectiveness of β-glucans in P. scalare larvae cultivation water (Sushila et al. 2022). Therefore, the present study evaluated the effects of dietary supplementation of different β-glucans concentrations on the growth, feed utilization, blood parameters (hematological, immunological, and biochemical), and intestinal microbiota of angelfish juveniles.

MATERIALS AND METHODS

Animals and experimental conditions

The procedures performed in the present study were approved by the Ethics Committee on the Use of Animals at the Universidade Estadual de Londrina (CEUA/UEL) (protocol CEUA no. 13903.2018.86).

The experiment was performed in the laboratory of the Núcleo de Estudos e Pesquisa em Aquicultura e Genética (NEPAG) at the Universidade Estadual de Londrina (UEL). Angelfish (Pterophyllum scalare) juveniles of the marble strain were purchased from local suppliers and housed in laboratory facilities. Prior to the initiation of the experiment, the fish were acclimatized to the experimental conditions for 28 days. The experimental units were aquariums with a total volume of 60 L, connected to a recirculation system, with additional aeration performed directly at the filter. Adequate temperature was maintained using a space heater and a thermostat in the filtration system. The fish were fed to apparent satiation twice a day at 09:00 and 16:00. To maintain water quality, feces and feed remains were removed daily, and 25% of the system volume was renovated twice a week. Temperature (°C), pH, and dissolved oxygen (DO) (mg L^-1) were measured daily using an oximeter (Hanna Instruments, Barueri, SP, Brazil) and a pH meter (Akso, São Leopoldo, RS, Brazil). Total ammonia levels were measured three times a week with a colorimetric kit (Labcon Tests, Camboriu, Brazil). During the experimental period, the values of temperature, DO, and pH were 27.51 ± 0.70°C, 9.54 ± 0.83 mg·L^-1, and 6.94 ± 0.10 (mean ± standard deviation), respectively. Total ammonia levels ranged from 0.0 to 0.25 mg L^-1. The photoperiod was maintained at 12 h of light and 12 h of dark. All procedures were performed during the acclimatization and the experimental period. Prior to the beginning of the experiment, all fish were individually weighed to obtain the initial weight (mean weight ± standard deviation: 5.28 ± 0.91 g).

Diet preparation

To evaluate the effects of dietary inclusion of β-glucans, a specific commercial diet for discus fish (Symphysodon spp.) and angelfish (Nutricon, Araçoiaba da Serra, SP, Brazil) (12% moisture, 38% protein, 3.5% lipids, 2.5% fiber, and 12% minerals) was used; all feed additives that could compromise the effects of β-glucans (sugar-cane yeast, spirulina, yeast extract, multienzyme additive, prebiotic, canthaxanthin, and yucca extract) were removed from the feed formulation and manufacturing process by the manufacturer at the request of our research group. The same commercial feed was used during the acclimatization period. As the source, a commercial product (MacroGard®, Biorigin, Lençóis Paulista, Brazil) containing a minimum of 60% β-1,3/1,6-glucans extracted from S. cerevisiae was used. As additives, the respective concentrations of MacroGard® for each diet (0.0, 0.05, 0.1, and 0.2%) were diluted in distilled water, homogenized, and distributed evenly over the feed. Then, the mixture was blended to ensure a homogeneous distribution. To ensure β-glucans fixation, 40 mL of an agglutinating feed additive (Vansil Saúde Animal, Descalvado, São Paulo, Brazil) was added per kilogram of feed, which was also evenly distributed. Thereafter, the feeds were dried at room temperature under ventilation for 24 h. The control diet (0.0%) was prepared using the same procedures, except for the addition of MacroGard®. The concentrations of MacroGard® used were chosen because research using these concentrations has already obtained positive effects on productive performance, hematological, immunological, blood biochemical, and intestinal microbiota parameters (Aramli et al. 2015, Do-Huu et al. 2016, Ghaedi et al. 2015, Harris et al. 2020, Talpur et al. 2014). The fixation of the additive in the feed was carried out based on the methodologies proposed by Furlan-Murari et al. (2022) and Siwicki et al. (2015).

Experimental design and performance evaluation

The juvenile fish were distributed in 16 aquariums (n = 10 fish each) following a completely randomized design, comprising four treatments (β-glucans concentrations) with four replicates each. The experimental diets were provided until apparent satiety twice a day at 09:00 and 16:00 h. The amount of feed consumed in each aquarium throughout the experimental period was recorded.

Following 42 days of feeding the diets containing different β-glucans concentrations, biometrics of all fish were obtained after fasting for 24 h to assess growth and other zootechnical parameters. To minimize stress during the measurements and as a prerequisite for subsequent procedures, the fish were anesthetized with benzocaine (0.1 g L ^-1) (Souza et al. 2020a) and then immobilized with wet towels. All fish were weighed and measured individually to obtain the final weight (g), total length (from the anterior end of the head to the end of the caudal fin) (cm), and standard length (from the anterior end of the head to the beginning of caudal fin insertion) (cm). Based on these data, the following parameters were calculated: weight gain (g): mean final weight − mean initial weight; weight gain (%): (mean final weight − mean initial weight/mean initial weight) × 100; specific growth rate (% day ^-1): [(ln mean final weight − ln mean initial weight)/experimental period (days)] × 100; feed intake (g): amount of feed consumed per aquarium/number of fish; feed conversion ratio: feed intake (g)/weight gain (g); protein efficiency ratio: weight gain (g)/protein intake (g); and survival rate (%): (final fish number/initial fish number) × 100. The condition factor (CF) was calculated using both total length (TL) [CF (TL) = (final weight/total length³) × 100)] and standard length (SL) [CF (SL) = (final weight /standard length³) × 100)], as described in other studies on Pterophyllum scalare (Nagata et al. 2010, Ribeiro et al. 2008).

Blood parameter analyses

Following anesthesia administration with benzocaine (0.1 g L^-1), blood samples were collected from the caudal vein. For analyses using whole blood, samples were collected with 3 mL syringes containing ethylenediaminetetraacetic acid (EDTA) for preservation (two fish per aquarium and eight fish per treatment). To obtain serum samples, blood was collected using 3 mL syringes without EDTA (pool of blood from three fishes, two pools per aquarium and eight pools per treatment) and centrifuged for 10 min at 1400 ×g for serum separation.

Red blood cells (RBC, 10⁶ μL^-1) were counted using Neubauer chamber following dilution (1:200) in Dacie’s solution (Blaxhall & Daisley 1973). Total hemoglobin concentration (g dL^-1) was determined using the hemoglobincyanide method (Collier 1944) with a commercial kit (Labtest, Lagoa Santa, MG, Brazil). Mean corpuscular hemoglobin (MCH) concentration was also calculated (Ranzani-Paiva et al. 2013). Plasma glucose concentration (mg dL^-1) was evaluated using a drop of blood introduced on a glucose test strip, and the dosage was determined by the FreeStyle Optium Neo glucometer (Abbott, Maidenhead, BRK, England) immediately after blood collection. For plasma lactate (mmol L^-1), blood samples were centrifuged for 10 min at 1400 ×g for plasma separation and the concentration was determined using an enzymatic colorimetric assay (Interkit, Belo Horizonte, MG, Brazil) (Barham & Trinder 1972, Shimojo et al. 1989, Trinder 1969).

Serum lysozyme concentration (µg mL^-1) was assessed according to the methodology described by Ellis (1990). Standard solutions of chicken egg lysozyme L6876 (Sigma-Aldrich Chemical Co., Saint Louis, MO, USA) were prepared to generate a standard curve. Subsequently, 90 μL of serum was used to measure the initial and final absorbance using spectrophotometry, and the serum lysozyme activity was determined based on the lysis of the gram-positive bacterium Micrococcus lysodeikticus (Sigma-Aldrich Chemical Co., Saint Louis, MO, USA). The reduction in sample absorbance was converted to an estimate of lysozyme concentration (μg mL^-1) using the linear equation of the standard lysozyme curve.

Total serum protein (g dL^-1) was quantified using a colorimetric method (Analisa, Belo Horizonte, MG, Brazil) (Gornall et al. 1949). Serum albumin (g dL^-1) and total cholesterol (mg dL^-1) concentrations were measured using enzymatic colorimetric assays (Analisa, Belo Horizonte, MG, Brazil) (Allain et al. 1974, Doumas et al. 1971). Total globulin concentration was obtained by subtracting albumin concentration from total protein concentration. Absorbance was measured at 540 nm for lactate, 492 nm for lysozyme, 545 nm for total serum proteins, 630 nm for albumin, and 500 nm for cholesterol, on a Coleman 33D digital spectrophotometer.

Metagenomic analysis of the intestinal microbiota

For the intestinal microbiota analysis, DNA was extracted from the stool pools of six individuals from the same aquarium (three pools per treatment) at the end of the feeding trial. For sample collection, the fish were euthanized through a medullary section, the ventral surface of the abdomen was opened, and stool was removed aseptically from the entire intestine and immediately stored at −80°C. Stool collection was performed according to Suphoronski et al. (2019). For bacterial DNA extraction, the QIAamp DNA Stool Mini Kit (QIAGEN, Hilden, Germany) was used, and the manufacturer’s recommendations were followed. Following extraction, DNA integrity was confirmed using 1% agarose gel electrophoresis.

Subsequently, the DNA samples were sent to NGS Soluções Genômicas (Piracicaba, SP, Brazil) for sequencing (paired-end library) on the Illumina MiSeq platform. For this, primers for the V3–V4 regions containing adapters for Illumina MiSeq sequencing were used for PCR amplification of the 16S rRNA gene. A first PCR (16S rRNA V3-V4) was performed under the following conditions: 95°C for 3 min, followed by 25 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, and a final extension at 72°C for 5 min. A second PCR was subsequently performed using the index sequences under the following conditions: 95°C for 3 min, followed by 12 cycles of 95°C for 30 s, 55°C for 30 s, and 72°C for 30 s, and a final extension at 72°C for 5 min. The PCRBio Ultra Mix (PCR Biosystems, London, United Kingdom) was used both reactions, and the AMPure XP beads (Beckman Coulter, Brea, CA, USA) were used for purification. The samples were then grouped into sequencing libraries. Amplicons were sequenced on the Illumina MiSeq platform using a paired-end 250-cycles V3 MiSeq reagent kit.

All bioinformatic analyses were performed on Mothur software (v.1.36.1) following the methodologies described by Kozich et al. (2013) and Schloss et al. (2009), with some modifications. The obtained sequences were aligned with the SILVA database, and homopolymers, nonspecific amplifications, redundancies, and chimeras were removed using VSEARCH algorithm. The sequences were classified into operational taxonomic units (OTUs) for taxonomic comparison. To reduce the bias caused by non-uniform sequence numbers, a subsample of 70,787 reads per sample was created for data normalization, and the Shannon and Simpson indices were calculated.

Statistical analysis

For the statistical analysis of productive performance, blood parameters, and diversity indices of gut microbiota, after verifying the homogeneity of the variances and normality of the residues, the data were subjected to the analysis of variance; for parameters that showed significant differences, the means were compared using Duncan’s test at a significance level of 5%. When the assumptions of the homogeneity of variances and normality of the residues were not met, the data were subjected to Kruskal–Wallis nonparametric test (Kruskal & Wallis 1952), and the means compared using the Dunn test at a significance level of 5%. All analyses were performed using R software (R Core Team 2017).

Analysis of molecular variance (AMOVA) was used for the statistical comparison of the structure of the microbial communities, performed using Mothur software (v.1.36.1). The Metastats tools of Mothur were used to determine the differentially represented OTUs between groups. A Venn diagram was generated to display microbial assemblages common to the four treatments.

RESULTS

Growth parameters

Regarding growth parameters, there were no differences (P > 0.05) in final weight, total length, standard length, weight gain (g and %), specific growth rate, feed intake, feed conversion ratio, protein efficiency ratio, and survival rate among the treatments (Table I). However, β-glucans supplementation affected the condition factors calculated based on both total [CF (TL)] and standard [CF (SL)] length. The CF (TL) values of fish that received the diet supplemented with 0.2% β-glucans (P < 0.05) were higher than those of fish that received the control diet (Table I). Conversely, the CF (SL) values of fish that received the diet supplemented with 0.2% β-glucans were higher than those of fish that received control diet and diets supplemented with the other concentrations of β-glucans (P < 0.05) (Table I).

Table I
Growth parameters of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations (mean ± standard deviation).

	β-glucans concentrations
Parameter	Control	0.05%	0.1%	0.2%	P-value
IW (g)	5.29 ± 0.96	5.30 ± 0.95	5.22 ± 0.99	5.24 ± 0.78	0.9767
FW (g)	9.04 ± 1.76	8.94 ± 1.66	8.77 ± 1.59	9.16 ± 1.48	0.6146
TL (cm)	7.61 ± 0.46	7.51 ± 0.56	7.45 ± 0.50	7.50 ± 0.47	0.5694
SL (cm)	5.88 ± 0.36	5.84 ± 0.46	5.79 ± 0.38	5.78 ± 0.35	0.6496
WG (g)	3.79 ± 0.70	3.65 ± 0.26	3.59 ± 0.85	3.92 ± 0.32	0.8598
WG (%)	71.42 ± 9.93	69.16 ± 8.13	68.54 ± 13.76	75.00 ± 8.12	0.8068
SGR	1.28 ± 0.14	1.25 ± 0.11	1.24 ± 0.19	1.33 ± 0.11	0.6780
FI (g)	4.01 ± 0.30	4.16 ± 0.14	3.97 ± 0.35	4.21 ± 0.13	0.4996
FCR	1.10 ± 0.08	1.14 ± 0.10	1.16 ± 0.11	1.08 ± 0.06	0.5572
PER	2.40 ± 0.18	2.31 ± 0.19	2.28 ± 0.23	2.45 ± 0.14	0.5813
CF (TL)	2.03 ± 0.18b	2.10 ± 0.17ab	2.10 ± 0.18ab	2.16 ± 0.21a	0.0244
CF (SL)	4.42 ± 0.42b	4.47 ± 0.44b	4.48 ± 0.41b	4.75 ± 0.51a	0.0057
SR (%)	97.50 ± 5.00	100.00 ± 0.0	97.50 ± 5.00	100.00 ± 0.0	0.5433

• IW: initial weight, FW: final weight, TL: total length, SL: standard length, WG: weight gain, SGR: specific growth rate, FI: feed intake, FCR: feed conversion ratio, PER: protein efficiency ratio, CF: condition factor, SR: survival rate. Different letters in the same row indicate significant differences (P < 0.05) among treatments.

Blood parameters

RBC count and hemoglobin, MCH, lysozyme, total protein, albumin, globulin, total cholesterol, glucose, and lactate concentrations (mean ± standard deviation) are presented in Table II. After 42 days of feeding, β-glucans supplementation did not affect blood parameters at any concentration (P > 0.05).

Table II
Red blood cells (RBC) count and hemoglobin, mean corpuscular hemoglobin (MCH), lysozyme, total proteins, albumin, globulins, total cholesterol, glucose and lactate concentrations (mean ± standard deviation) in the blood samples of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations.

	β-glucans concentrations
Parameters	Control	0.05%	0.1%	0.2%	P-value
RBC (×106 μL-1)	1.41 ± 0.45	1.13 ± 0.37	1.63 ± 0.40	1.23 ± 0.32	0.0725
Hemoglobin (g dL-1)	5.17 ± 1.04	4.41 ± 0.82	4.63 ± 1.75	4.62 ± 0.83	0.6161
MCH (g dL-1)	39.24 ± 11.95	40.28 ± 6.56	28.55 ± 4.84	38.73 ± 7.09	0.1927
Lysozyme concentration (µg mL-1)	3.17 ± 1.88	2.99 ± 1.69	3.58 ± 1.48	3.58 ± 0.31	0.9173
Total serum proteins (g dL-1)	4.30 ± 0,69	4.47 ± 0.50	3.96 ± 0.83	4.64 ± 0.44	0.2151
Serum albumin (g dL-1)	1.36 ± 0.57	1.20 ± 0.22	1.10 ± 0.19	1.12 ± 0.22	0.6546
Globulins (g dL-1)	2.95 ± 0.70	3.28 ± 0.41	2.83 ± 0.45	3.57 ± 0.35	0.2365
Total serum cholesterol (mg dL-1)	177.96 ± 42.11	170.84 ± 13.60	177.74 ± 11.40	166.71 ± 22.49	0.9189
Plasma glucose (mg dL-1)	52.86 ± 16.64	47.63 ± 20.74	38.63 ± 8.14	40.13 ± 14.42	0.2759
Plasma lactate (mmol L-1)	2.36 ± 0.76	2.05 ± 0.36	1.95 ± 0.49	1.91 ± 0.71	0.4808

Intestinal microbiota

A total of 1,005,662 contigs were generated from the sequence reads. Following quality control, a total of 962,686 contigs were generated and aligned in the SILVA database to obtain information on OTUs present in the samples. The subsample yielded the coverage higher than 99.9%, indicating good representativeness of the total microbial population. Based on all sequences obtained from the intestinal microbiota of Pterophyllum scalare that received diets supplemented with different β-glucans concentrations, 260 genera belonging to 20 phyla were identified. Of these 260, respectively 157, 143, 154, and 194 genera were recorded in samples from the control, 0.05, 0.1, and 0.2% groups. Among the identified phyla, Firmicutes, Fusobacteria, Proteobacteria, and Bacteroidetes were the most abundant in samples from all β-glucans groups (Figure 1). At the genus level, Cetobaterium was the most abundant in the control, 0.05%, and 0.1% groups, and Phascolarctobacterium was the most abundant in the 0.2% group (Figure 2). However, the abundance of Phascolarctobacterium (Firmicutes) was significantly higher (P < 0.05) in all β-glucans groups than in the control group (Table III). Moreover, the abundance of Lachnospiraceae_unclassified (Firmicutes) differed between the 0.1% and 0.2% β-glucans groups (Table III).

Figure 1
Ten most abundant phyla in the intestinal microbiota of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations.

Figure 2
Fifteen most abundant genera in the intestinal microbiota of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations.

Table III
Number of sequences for the five most abundant genera in the intestinal microbiota of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations (mean ± standard deviation).

	β-glucans concentrations
Genus	Control	0.05%	0.1%	0.2%
Cetobacterium (Fusobacteria)	22,103 ± 11,507	21,665 ± 2,313	18,961 ± 7,737	16,482 ± 7,275
Phascolarctobacterium (Firmicutes)	8,436 ± 6,771b	16,687 ± 1,489a	16,922 ± 1,185a	20,541 ± 6,506a
Bacteroidales_unclassified (Bacteroidetes)	9,406 ± 8,756	3,443 ± 323	3,760 ± 4,190	2,863 ± 979
Bacteroides (Bacteroidetes)	6,965 ± 8,444	2,668 ±348	3,992 ± 2,446	5,134 ± 3,383
Lachnospiraceae_unclassified (Firmicutes)	5,156 ± 2,387ab	3,429 ± 1,904ab	6,354 ± 2,262a	2,181 ± 357b

• Different letters in the same row indicate significant differences (P < 0.05) among treatments. P-value generated by Metastats for the comparison between different diets for each of the five most abundant genera: Cetobacterium: Control x 0.05%: 0.8158; Control x 0.1%: 0.8908; Control x 0.2%: 0.6833; 0.05% x 0.1%: 0.5808; 0.05% x 0.2%: 0.2481; 0.1% x 0.2%: 0.7403. Phascolarctobacterium: Control x 0.05%: 0.0439; Control x 0.1%: 0.0416; Control x 0.2%: 0.0363; 0.05% x 0.1%: 0.9262; 0.05% x 0.2%: 0.5596; 0.1% x 0.2%: 0.5683. Bacteroidales_unclassified: Control x 0.05%: 0.3126; Control x 0.1%: 0.5234; Control x 0.2%: 0.2326; 0.05% x 0.1%: 0.9012; 0.05% x 0.2%: 0.3400; 0.1% x 0.2%: 0.7611. Bacteroides: Control x 0.05%: 0.5088; Control x 0.1%: 0.7416; Control x 0.2%: 0.8307; 0.05% x 0.1%: 0.5168; 0.05% x 0.2%: 0.2855; 0.1% x 0.2%: 0.8190. Lachnospiraceae_unclassified: Control x 0.05%: 0.4911; Control x 0.1%: 0.5908; Control x 0.2%: 0.1045; 0.05% x 0.1%: 0.0662; 0.05% x 0.2%: 0.2161; 0.1% x 0.2%: 0.0117.

The Shannon and Simpson indices did not differ among the groups (Table IV). However, the observed species richness (Sobs) significantly differed among the treatments, with a higher value in the 0.2% β-glucans group than in the other groups (Table IV). The rarefaction curve (Figure 3) demonstrated that the composition of the microbial community in fish that received the diet supplemented with 0.2% β-glucans was different from that in fish that received other diets. The Venn diagram (Figure 4) demonstrated that the number of OTUs shared between the groups was similar, although there was a greater overlap between the 0.2% and the other groups. Furthermore, the number of exclusive OTUs was higher for the 0.2% β-glucans group than for the other groups.

Figure 3
Rarefaction curve for each β-glucans concentration presenting the number of reads (x-axis) relative to the number of operational taxonomic units (OTUs) (y-axis).

Figure 4
Venn diagram showing the overlap between operational taxonomic units (OTUs) for the intestinal microbiota of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations.

Table IV
Shannon index, Simpson index, and observed species richness (Sobs) of the gut microbiota of Pterophyllum scalare juveniles fed diets supplemented with different β-glucans concentrations (mean ± standard deviation).

	Control	0.05%	0.1%	0.2%	P-value
Shannon	2.53 ± 0.32	2.57 ± 0.11	2.59 ± 0.17	2.70 ± 0.23	0.8176
Simpson	0.14 ± 0.06	0.14 ± 0.03	0.14 ± 0.03	0.13 ± 0.04	0.9890
Sobs	107.33 ± 6.03b	107.33 ± 7.57b	107.00 ± 10.39b	134.33 ± 15.50a	0.0307

• Different letters in the same row indicate significant differences (P < 0.05) among treatments.

DISCUSSION

Effects of β-glucans on growth parameters

Among the evaluated growth parameters, only CF was affected by β-glucans supplementation. Previously, the effects of dietary S. cerevisiae β-glucans on CF increase have already been reported in some fish species, such as pompano (Trachinotus ovatus) (Do-Huu 2020), snakehead (Channa striata) (Munir et al. 2016), Nile tilapia (Oreochromis niloticus) (Liranço et al. 2013), and Caspian trout (Salmo trutta caspius) (Jami et al. 2019). Therefore, CF can be applied as an indirect measure of energy reserves (Camara et al. 2011), indicating the significance of the observed effect. For a given length (higher CF), a fish with a greater weight is considered healthier than the one with a lower weight, since the extra weight indicates extra energy reserves, allowing less susceptibility to environmental stressors (Morado et al. 2017). Thus, CF can be used as an indicator of fish welfare as it can offer information on chronic stresses, diseases, water contamination, and nutritional status (Lemos et al. 2015, Rocha et al. 2005). Previous studies have already demonstrated the efficiency of CF as an indicator of food availability (Morado et al. 2017), proper feed types (Takahashi et al. 2010), and proper diet composition (Ighwela et al. 2011). Therefore, despite the lack of effects on other growth parameters, higher CF values in the 0.2% group indicates a better nutritional status of fish that received this diet.

Furthermore, the positive effects of dietary S. cerevisiae β-glucan supplementation for 42 days on growth parameters other than CF have already been reported. For instance, in a study by Aramli et al. (2015), supplementation with 0.1%, 0.2%, and 0.3% β-glucans improved the FW and SGR of Persian sturgeon (Acipenser persicus) juveniles, with the highest values recorded in the 0.2% group. In another study by Ji et al. (2017), the WG and SGR of rainbow trouts (Oncorhynchus mykiss) receiving diets supplemented with 0.1% and 0.2% β-glucans were higher than those of fish receiving the control diet and the diet supplemented with 0.05% β-glucans, with the highest values recorded in the 0.2% group. Additionally, Guzmán-Villanueva et al. (2014) reported that in Pacific red snapper (Lutjanus peru) juveniles, supplementation with 0.1% and 0.2% β-glucans increased WG and SGR and supplementation with 0.1% β-glucans also improved FW. As the present study used the same feeding duration and β-glucans concentrations as the previous studies, the effects of β-glucans may be species-specific. In the culture of most ornamental fish species, including angelfish, the target of selection is not growth, as in the culture of fish used for human consumption, which was likely reflected in less intense growth and less evident effects on most parameters. Furthermore, studies evaluating the effects of dietary inclusion of S. cerevisiae β-glucans in Nile tilapia (Liranço et al. 2013, Welker et al. 2012) and pompano (Do-Huu et al. 2016) have demonstrated changes in growth performance during the supplementation period. Thus, additional studies on angelfish involving evaluations during the feeding period and experiments over longer durations are warranted to demonstrate the efficiency of β-glucans in improving other performance parameters.

Effect of β-glucans on hematological, immunological, and biochemical parameters

Previous studies have shown that the source, concentration, and period of β-glucans supplementation (Aramli et al. 2015, El-Boshy et al. 2010, Welker et al. 2012) determine the presence of effects on blood parameters. In the present study, MacroGard®, a commercial product extracted from S. cerevisiae containing a minimum of 60% β-1,3/1,6- glucans, was the source used. Some studies using the same supplementation concentrations as the present study have demonstrated the effect of dietary yeast β-glucans on the modulation of RBC counts and hemoglobin, lysozyme, total protein, albumin, globulin, total cholesterol, and glucose concentrations (Cao et al. 2019, Ghaedi et al. 2015, Montoya et al. 2018, Talpur et al. 2014). Meanwhile, some studies have also reported the lack of effects on hematological, immunological, and biochemical blood parameters at the same concentrations (Cao et al. 2019, Del Rio-Zaragoza et al. 2011, Kühlwein et al. 2014, Siwicki et al. 2010, Welker et al. 2012).

Overall, the effects of different β-glucans concentrations vary widely, likely depending on the duration of supplementation. In this regard, some studies demonstrate that these effects may vary over the experimental period. Among them, Sánchez-Martínez et al. (2017) observed for channel catfish (Ictalurus punctatus) the effect of β-glucans on reducing RBC counts during the five weeks of feeding. Amphan et al. (2019), observed the effects of supplementation on lysozyme activity in Nile tilapia (O. niloticus) in the first, second and third weeks of feeding, which did not occur in the following five weeks. Also for Nile tilapia, Liranço et al. (2013) found that the administration of β-glucans provided higher hemoglobin concentrations at 30 and 90 days compared to 60 days of feeding. For Rohu (Labeo rohita), Misra et al. (2006) observed a large variation in the influence of supplementation throughout the feeding period, with effects on total serum protein and globulin at 28 and 42 days; on albumin at 14, 28 and 42 days; and on glucose at 14, 28, 42 and 56 days. Such evidence demonstrates that the duration of supplementation is an extremely important factor when using β-glucans as a feed additive for fish. Therefore, such effects could have been verified in the present study if blood samples were also collected during the supplementation period. However, this was not possible because of the small volume of blood in Pterophyllum scalare juveniles, which allows only a single collection.

Effects of β-glucans on intestinal microbiota

Our results demonstrated the efficiency of the dietary inclusion of S. cerevisiae β-glucans in modulating the intestinal microbiota composition by shaping the dominance of certain taxa and diversity of bacterial populations; our findings are consistent with previous reports (Carda-Diéguez et al. 2014, Harris et al. 2020, Jung-Schroers et al. 2016, 2019). In the present study, Firmicutes, Fusobacteria, Proteobacteria and Bacteroidetes were observed to be the dominant phyla in Pterophyllum scalare, similar to the reports in Nile tilapia (Oreochromis niloticus) (Souza et al. 2020a,b), discus fish (Symphysodon haraldi) (Zhang et al. 2021), and several African cichlids (Baldo et al. 2015). For instance, in a study by Baldo et al. (2019), Proteobacteria, Fusobacteria, Firmicutes, Bacteroidetes, and Planctomycetes constituted the core microbiota (taxonomic components shared by at least 90% of the individuals) of several African and Central American cichlid species. In the present study, Firmicutes, Fusobacteria, Proteobacteria, and Bacteroidetes together accounted for 97.93% of the total reads obtained. At the genus level, Cetobacterium (Fusobacteria) was the most abundant in the control, 0.05% β-glucan, and 0.1% β-glucans groups. Similarly, Cetobacterium was one of the most abundant genera in other omnivorous cichlids, such as Oreochromis niloticus (Souza et al. 2020a,b) and Astatotilapia burtoni (Faber-Hammond et al. 2019), as well as other cichlids from the Amazon basin, such as Symphysodon haraldi (Zhang et al. 2021). Although bacteria from the gastrointestinal tract of Pterophyllum scalare have already been isolated and identified (Monroy-Dosta et al. 2012, Ramirez & Dixon 2003), no study has evaluated the composition of intestinal microbiota in this species. Thus, the present study is the first to report the dominance of these taxa in Pterophyllum scalare; nonetheless, further studies are required to consolidate all information.

Some beneficial intestinal microbes use indigestible substances, generating metabolites that can be used as the energy sources by fish (Yukgehnaish et al. 2020). In the present study, Bacteroidales_unclassified (Bacteroidetes) and Bacteroides (Bacteroidetes) were some of the most abundant taxa. Bacteria from the phylum Bacteroidetes possess an excellent polysaccharide degradation capacity, producing several enzymes for the breakdown of various glycans, including yeast β-glucans (Lapébie et al. 2019, Temple et al. 2017). In addition to Bacteroides, Parabacteroides (Bacteroidetes) and Phascolarctobacterium (Firmicutes) were also some of the most abundant genera in the present study. Bacteroides and Parabacteroides are among the major succinate producers (Wu et al. 2017), while Phascolarctobacterium spp. use succinate as an energy source (Tran et al. 2020, Watanabe et al. 2012, Wu et al. 2017). Therefore, the coexistence of Bacteroides and Phascolarctobaterium may be beneficial for both taxa (Ikeyama et al. 2020). Thus, following supplementation, the degradation of β-glucans by bacteria of the phylum Bacteroidetes likely created conditions suitable for a significant increase in the abundance of Phascolarctobacterium.

Phascolarctobacterium has been detected in some studies evaluating the intestinal microbiota of fish, albeit not as one of the most abundant taxa (Bao et al. 2020, Basili et al. 2020, Meng et al. 2018). In the present study, Phascolarctobacterium was abundant in the intestine of fish fed the β-glucans-supplemented diets, possibly characterizing it as a genus forming the core microbiota of the species. To the best of our knowledge, the present study is the first to record Phascolarctobacterium as one of the most abundant genera in the intestinal microbiota of fish. The intestinal microbiome may be shaped by various factors, such as host genetics and intestinal physiology as well as the symbiotic relationships among the gut bacteria themselves (Tarnecki et al. 2017). Such symbiotic relationships may explain the abundance of specific taxa in Pterophyllum scalare but not in other species. The presence of bacteria of the genus Phascolarctobacterium has been linked to the decrease in the body weight of zebrafish (Danio rerio) exposed to the fungicide carbendazim (Bao et al. 2020) as well as to lipid metabolism in common carp (Cyprinus carpio) exposed to copper (Meng et al. 2018). However, further studies are required to verify these relationships in fish under normal non-stressful conditions. Simultaneously, bacteria of the Lachnospiraceae family have been implicated in increased blood glucose levels, decreased plasma insulin levels, and increased liver and mesenteric adipose tissue weights in mice genetically predisposed to obesity (Kameyama & Itoh 2014). However, the lower proportion of these bacteria in fish fed the diet supplemented with 0.2% β-glucans than in those fed the diet supplemented with 0.1% β-glucans in the present study presented no link with any of the evaluated parameters.

As mentioned earlier, the supplementation of 0.2% β-glucans increased CF. There is evidence that CF is a reliable measure for estimating energy reserves in juveniles which store energy as proteins (Schloesser & Fabrizio 2017). Specifically, Munir et al. (2016) observed in snakehead juveniles an increase in CF accompanied by an increase in proteins and a decrease in body lipids in fish fed diets supplemented with S. cerevisiae β-glucans. However, as the body composition was not evaluated in the present study, we could not determine whether the increase in CF was a result of lipid or protein accumulation. Thus, the data generated in the present study do not demonstrate any association between intestinal microbiota and energy metabolism in Pterophyllum scalare. Owing to their proximity to humans, ornamental fish, similar to other pets, can live longer but are at a greater risk of obesity (Sicuro 2018). Therefore, further studies are warranted to better understand the involvement of intestinal microbiota in energy metabolism in ornamental fish; this information can be useful to optimize the quality of life of these fish.

Furthermore, compared with fish receiving the other diets, fish receiving the diet supplemented with 0.2% β-glucans showed a higher observed species richness (Sobs), suggesting better conditions for the development of a greater number of taxa. Consistently, the rarefaction curve, which is the representation of species richness plotted against the number of sequences (species density) (Dias & Bonaldo 2012), demonstrated differences in intestinal microbiota between fish fed the diet supplemented with 0.2% β-glucans and those fed the other diets. Similarly, the Venn diagram showed differences in gut microbial composition between fish fed the diet supplemented with 0.2% β-glucans and those fed the other diets. These results demonstrated that only the highest of the tested concentrations of β-glucans could modulate the intestinal microbiota of Pterophyllum scalare in a more complex manner. In a study by Jung-Schroers et al. (2016), common carps fed diets containing β-glucans exhibited increased bacterial diversity and decreased Vibrio spp. abundance in the intestine; according to the authors, a more diverse microflora possesses a greater ability to exclude pathogenic bacteria through competition for adhesion sites and nutrients. Therefore, changes in the composition of intestinal microbiota may be related to conditions that are more advantageous for certain taxa and indirectly affect other taxa. Thus, the dietary supplementation of 0.2% β-glucans promoted the formation of a distinct bacterial community by benefiting certain taxa while indirectly harming or benefiting other bacteria. To our best knowledge, the present study is the first to evaluate and record the intestinal microbiota of Pterophyllum scalare. Additional research is warranted to better understand gut microbial composition in this species. Additionally, the effects of β-glucans on gut microbes must be further elucidated.

CONCLUSIONS

Under the experimental conditions of the present study, the dietary supplementation of 0.2% β-glucans increased the CF and positively modulated the intestinal microbiota of juvenile angelfish, without affecting other performance parameters and blood parameters.

ACKNOWLEDGMENTS

The authors thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação Araucária, and the Programa de Pós-Graduação em Ciência Animal da Universidade Estadual de Londrina for financial support during the study. The authors also thank Biorigin (Lençóis Paulista, São Paulo/Brazil) for providing β-glucans used in the experiment (MacroGard®). Finally, we thank Nutricon (Araçoiaba da Serra, São Paulo/Brazil) for donating the feed used in the experiment.

REFERENCES

• ABREU JS, BRINN RP, GOMES LC, MCCOMB DM, BALDISSEROTTO B, ZAIDEN SF, URBINATI EC & MARCON JL. 2014. Effect of beta 1,3 glucan in stress responses of the pencilfish (Nannostomus trifasciatus) during transport within the rio Negro basin. Neotrop Ichthyol 12: 623-628.
• ALLAIN CA, POON LS, CAHN CSG, RICHMOND W & FU PC. 1974. Enzymatic determination of total serum cholesterol. Clin Chem 20: 470-475.
• AMPHAN S, UNAJAK S, PRINTRAKOON C & AREECHON N. 2019. Feeding-regimen of β-glucan to enhance innate immunity and disease resistance of Nile tilapia, Oreochromis niloticus Linn., against Aeromonas hydrophila and Flavobacterium columnare. Fish Shellfish Immunol 87: 120-128.
• ARAMLI MS, KAMANGAR B & NAZARI RM. 2015. Effects of dietary b-glucan on the growth and innate immune response of juvenile Persian sturgeon, Acipenser persicus. Fish Shellfish Immunol 47: 606-610.
• AZIMIRAD M, MESHKINI S, AHMADIFARD N & HOSEINIFAR SH. 2016. The effects of feeding with synbiotic (Pediococcus acidilactici and fructooligosaccharide) enriched adult Artemia on skin mucus imune responses, stress resistance, intestinal microbiota and performance of angelfish (Pterophyllum scalare). Fish Shellfish Immunol 54: 516-522.
• BALDO L, RIERA JL, SALZBURGER W & BARLUENGA M. 2019. Phylogeography and ecological niche shape the cichlid fish gut microbiota in Central American and African Lakes. Front Microbiol 10: 2372.
• BALDO L, RIERA JL, TOOMING-KLUNDERUD A, ALBÀ MM & SALZBURGER W. 2015. Gut microbiota dynamics during dietary shift in Eastern African cichlid fishes. PLoS ONE 10: e0127462.
• BAO Z, ZHAO Y, WU A, LOU Z, LU H, YU Q, FU Z & JIN Y. 2020. Sub-chronic carbendazim exposure induces hepatic glycolipid metabolism disorder accompanied by gut microbiota dysbiosis in adult zebrafish (Daino rerio). Sci Total Environ 739: 140081.
• BARHAM D & TRINDER P. 1972. An improved colour reagent for the determination of blood glucose by the oxidase system. Analyst 97: 142-145.
• BASILI D, LUFTI E, FALCINELLI S, BALBUENA-PECINO S, NAVARRO I, BERTOLUCCI C, CAPILLA E & CARNEVALI O. 2020. Photoperiod Manipulation Affects Transcriptional Profile of Genes Related to Lipid Metabolism and Apoptosis in Zebrafish (Danio rerio) Larvae: Potential Roles of Gut Microbiota. Microb Ecol 79: 933-946.
• BLAXHALL PC & DAISLEY KW. 1973. Routine haematological methods for use with fish blood. J Fish Biol 5: 771-781.
• CAMARA EM, CARAMASCHI EP & PETRY AC. 2011. Fator de condição: bases conceituais, aplicações e perspectivas de uso em pesquisas ecológicas com peixes. Oecol Aust 15: 249-274.
• CAO H, YU R, ZHANG Y, HU B, JIAN S, WEN C, KAJBAF K, KUMAR V & YANG G. 2019. Effects of dietary supplementation with β-glucan and Bacillus subtilis on growth, fillet quality, immune capacity, and antioxidant status of Pengze crucian carp (Carassius auratus var. Pengze). Aquaculture 508: 106-112.
• CARDA-DIÉGUEZ M, MIRA A & FOUZ B. 2014. Pyrosequencing survey of intestinal microbiota diversity in cultured sea bass (Dicentrarchus labrax) fed functional diets. FEMS Microbiol Ecol 87: 451-459.
• COLLIER HB. 1944. Standardization of blood haemoglobin determinations. Can Med Assoc J 50: 550-552.
• DEL RIO-ZARAGOZA OB, FAJER-ÁVILA EJ & ALMAZÁN-RUEDA P. 2011. Influence of β-glucan on innate immunity and resistance of Lutjanus guttatus to an experimental infection of Dactylogyrid monogeneans. Parasite Immunol 33: 483-494.
• DIAS SC & BONALDO AB. 2012. Abundância relativa e riqueza de espécies de aranhas (Arachnida, Araneae) em clareiras originadas da exploração de petróleo na bacia do rio Urucu (Coari, Amazonas, Brasil). Bol Mus Para Emílio Goeldi. Ciênc Nat 7: 123-152.
• DO-HUU H. 2020. Influence of dietary β-glucan on length-weight relationship, condition factor and relative weight of pompano fish (Trachinotus ovatus, family carangidae). Int J Fish Aquat Stud 8: 85-91.
• DO-HUU H, SANG HM & THUY NTT. 2016. Dietary β-glucan improved growth performance, Vibrio counts, haematological parameters and stress resistance of pompano fish, Trachinotus ovatus Linnaeus, 1758. Fish Shellfish Immunol 54: 402-410.
• DOUMAS BT, WATSON WA & BIGG HG. 1971. Albumin standards and the measurement of serum albumin with bromcresol green. Clin Chim Acta 31: 87-96.
• EL-BOSHY ME, EL-ASHRAM AM, ABDEL HAMID FM & GADALLA HA. 2010. Immuno-modulatory effect of dietary Saccharomyces cerevisiae, β-glucan and laminaran in mercuric chloride treated Nile tilapia (Oreochromis niloticus) and experimentally infected with Aeromonas hydrophila. Fish Shellfish Immunol 28: 802-808.
• ELLIS AE. 1990. Lysozyme Assays. In: STOLEN JS, FLETCHER TC, ANDERSON DP, ROBERSON BS & VAN MUISWINKEL WB (Eds), Techniques in Fish Immunology, Fair Haven: SOS Publications, New Jersey, USA, p. 101-103.
• FABER-HAMMOND JJ, COYLE KP, BACHELLER SK, ROBERTS CG, MELLIES JL, ROBERTS RB & RENN SCP. 2019. The intestinal environment as an evolutionary adaptation to mouthbrooding in the Astatotilapia burtoni cichlid. FEMS Microbiol Ecol 95: fiz016.
• FAO. 2016. The State of World Fisheries and Aquaculture 2016. Contributing to food security and nutrition for all. Rome: FAO, 200 p.
• FUJIMOTO RY, VENDRUSCOLO L, SCHALCH SHC & MORAES FR. 2006. Avaliação de três diferentes métodos para o controle de monogenéticos e Capillaria sp. (nematoda: capillariidae), parasitos de acará-bandeira (Pterophyllum scalare Liechtenstein, 1823). Bol Inst Pesca 32: 183-190.
• FURLAN-MURARI PJ, LIMA ECS, SOUZA FP, URREA-ROJAS AM, PUPIM ACE, ARAÚJO EJA, MELETTI PC, LEAL CNS, FERNANDES LL & LOPERA-BARRERO NM. 2022. Inclusion of β-1, 3/1, 6-glucan in the ornamental fish, Jewel tetra (Hyphessobrycon eques), and its effects on growth, blood glucose, and intestinal histology. Aquac Int 30: 501-515.
• GHAEDI G, KEYVANSHOKOOH S, AZARM HM & AKHLAGHI M. 2015. Effects of dietary β-glucan on maternal immunity and fry quality of rainbow trout (Oncorhynchus mykiss). Aquaculture 441: 78-83.
• GORNALL AG, BARDAWILL CS & DAVID MM. 1949. Determination of serum proteins by means of the biuret reaction. J Biol Chem 177: 751-766.
• GUZMÁN-VILLANUEVA LT, ASCENCIO-VALLE F, MACÍAS-RODRÍGUEZ ME & TOVAR-RAMÍREZ D. 2014. Effects of dietary β-1,3/1,6-glucan on the antioxidante and digestive enzyme activities of Pacific red snapper (Lutjanus peru) after exposure to lipopolysaccharides. Fish Physiol Biochem 40: 827-837.
• HARRIS SJ, BRAY DP, ADAMEK M, HULSE DR, STEINHAGEN D & HOOLE D. 2020. Effect of β-1/3,1/6-glucan upon immune responses and bacteria in the gut of healthy common carp (Cyprinus carpio). J Fish Biol 96: 444-455.
• IGHWELA KA, AHMED AB & ABOL-MUNAFI AB. 2011. Condition Factor as an Indicator of Growth and Feeding Intensity of Nile Tilapia Fingerlings (Oreochromis niloticus) Feed on Different Levels of Maltose. Am-Eurasian J Agric Environ Sci 11: 559-563.
• IKEDA AK, ZUANON JAS, SALARO AL, FREITAS MBD, PONTES MD, SOUZA LS & SANTOS MV. 2011. Vegetable oil sources in diets for freshwater angelfish (Pterophyllum scalare, Cichlidae): growth and thermal tolerance. Arq Bras Med Vet Zootec 63: 670-677.
• IKEYAMA N, MURAKAMI T, TOYODA A, MORI H, IINO T, OHKUMA M & SAKAMOTO M. 2020. Microbial interaction between the succinate-utilizing bacterium Phascolarctobacterium faecium and the gut comensal Bacteroides thetaiotaomicron. MicrobiologyOpen 9: e1111.
• JAMI MJ, KENARI AA, PAKNEJAD H & MOHSENI M. 2019. Effects of dietary β-glucan, mannan oligosaccharide, Lactobacillus plantarum and their combinations on growth performance, immunity and immune related gene expression of Caspian trout, Salmo trutta caspius (Kessler, 1877). Fish Shellfish Immunol 91: 202-208.
• JI L, SUN G, LI J, WANG Y, DU Y, LI X & LIU Y. 2017. Effect of dietary b-glucan on growth, survival and regulation of immune processes in rainbow trout (Oncorhynchus mykiss) infected by Aeromonas salmonicida. Fish Shellfish Immunol 64: 56-67.
• JUNG-SCHROERS V, ADAMEK M, JUNG A, HARRIS S, DÓZA OS, BAUMER A & STEINHAGEN D. 2016. Feeding of b-1,3/1,6-glucan increases the diversity of the intestinal microflora of carp (Cyprinus carpio). Aquac Nutr 22: 1026-1039.
• JUNG-SCHROERS V, HARRIS S, ADAMEK M, JUNG A & STEINHAGEN D. 2019. More is not always better - The influence of different concentrations of dietary β-glucan on the intestinal microbiota of tinfoil barb (Barbonymus schwanenfeldii). Bull Eur Assoc Fish Pathol 39: 122-132.
• KAMEYAMA K & ITOH K. 2014. Intestinal Colonization by a Lachnospiraceae Bacterium Contributes to the Development of Diabetes in Obese Mice. Microbes Environ 29: 427-430.
• KARADAL O, GÜROY D & TÜRKMEN G. 2017. Effects of feeding frequency and Spirulina on growth performance, skin coloration and seed production on kenyi cichlids (Maylandia lombardoi). Aquac Int 25: 121-134.
• KOZICH JJ, WESTCOTT SL, BAXTER NT, HIGHLANDER SK & SCHLOSS PD. 2013. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq. Appl Environ Microbiol 79: 5112-5120.
• KRUSKAL WH & WALLIS WA. 1952. Use of ranks in one-criterion variance analysis. J Am Stat Assoc 47: 583-621.
• KÜHLWEIN H, MERRIFIELD DL, RAWLING MD, FOEY AD & DAVIES SJ. 2014. Effects of dietary b-(1,3)(1,6)-D-glucan supplementation on growth performance, intestinal morphology and haemato-immunological profile of mirror carp (Cyprinus carpio L.). J Anim Physiol Anim Nutr 98: 279-289.
• LAPÉBIE P, LOMBARD V, DRULA E, TERRAPON N & HENRISSAT B. 2019. Bacteroidetes use thousands of enzyme combinations to break down glycans. Nat Commun 10: 2043.
• LEMOS JRG, OLIVEIRA AT, SANTOS MQC, PEREIRA CN, NASCIMENTO RB & TAVARES-DIAS M. 2015. Influência do transporte na relação peso-comprimento e fator de condição de Paracheirodon axelrodi (Characidae). Biota Amazônia 5: 22-26.
• LIN S, PAN Y, LUO L & LUO L. 2011. Effects of dietary b-1,3-glucan, chitosan or raffinose on the growth, innate immunity and resistance of koi (Cyprinus carpio koi). Fish Shellfish Immunol 31: 788-794.
• LIRANÇO ADS, CIARLINI PC, MORAES G, CAMARGO ALS & RAMAGOSA E. 2013. Mannanoligosaccharide (mos) and ß-glucan (ß-glu) in dietary supplementation for Nile tilapia juveniles dept in cages. Pan-Am J Aquat Sci 8: 112-125.
• MEENA DK ET AL. 2013. Beta-glucan: an ideal immunostimulant in aquaculture (a review). Fish Physiol Biochem 39: 431-457.
• MENG XL, LI S, QIN CB, ZHU ZX, HU WP, YANG LP, LU RH, LI WJ & NIE GX. 2018. Intestinal microbiota and lipid metabolism responses in the common carp (Cyprinus carpio L.) following copper exposure. Ecotoxicol Environ Saf 160: 257-264.
• MISRA CK, DAS BK, MUKHERJEE SC & PATTNAIK P. 2006. Effect of long term administration of dietary β-glucan on immunity, growth and survival of Labeo rohita fingerlings. Aquaculture 255: 82-94.
• MONROY-DOSTA MC, BARRERA TC, PERRINO FJF, REYES LM, GUTIÉRREZ HH & SUÁREZ SC. 2012. Bacteria with Probiotic Capabilities Isolated from the Digestive Tract of the Ornamental Fish Pterophyllum scalare. In: RIGOBELO EC (Ed), Probiotic in animals, London: IntechOpen, London, UK, p. 231-246.
• MONTOYA LNF, FAVERO GC, ZANUZZO FS & URBINATI EC. 2018. Distinct β-glucan molecules modulates differently the circulating cortisol levels and innate immune responses in matrinxã (Brycon amazonicus). Fish Shellfish Immunol 83: 314-320.
• MORADO CN, ARAÚJO FG & GOMES ID. 2017. The use of biomarkers for assessing effects of pollutant stress on fish species from a tropical river in Southeastern Brazil. Acta Sci Biol Sci 394: 431-439.
• MUNIR MB, HASHIM R, MANAF MSA & NOR SAM. 2016. Dietary prebiotics and probiotics influence the growth performance, feed utilisation, and body indices of snakehead (Channa striata) fingerlings. Trop Life Sci Res 27: 111-125.
• NAGATA MM, TAKAHASHI LS, GIMBO RY, KOJIMA JT & BILLER JD. 2010. Influência da densidade de estocagem no desempenho produtivo do acará-bandeira (Pterophyllum scalare). Bol Inst Pesca 36: 9-16.
• PETIT J & WIEGERTJES GF. 2016. Long-lived effects of administering b-glucans: Indications for trained immunity in fish. Dev Comp Immunol 64: 93-102.
• RAMIREZ RF & DIXON BA. 2003. Enzyme production by obligate intestinal anaerobic bacteria isolated from oscars (Astronotus ocellatus), angelfish (Pterophyllum scalare) and Southern flounder (Paralichthys lethostigma). Aquaculture 227: 417-426.
• RANZANI-PAIVA MJT, PÁDUA SB, TAVARES-DIAS M & EGAMI MI. 2013. Métodos para análises hematológicas em peixes. Maringá: EDUEM, 140 p.
• R CORE TEAM. 2017. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Accessed from: https://www.r-project.org/
  » https://www.r-project.org/
• RIBEIRO FAS, PRETO BL & FERNANDES JBK. 2008. Sistemas de criação para o acará-bandeira (Pterophyllum scalare). Acta Sci Anim Sci 30: 459-466.
• RIBEIRO FAS, RODRIGUES LA & FERNANDES JBK. 2007. Desempenho de juvenis de Acará-Bandeira (Pterophyllum scalare) com diferentes níveis de proteína bruta na dieta. Bol Inst Pesca 33: 195-203.
• ROCHA MA, RIBEIRO ELA, MIZUBUTI IY, SILVA LDF, BOROSKY JC & RUBIN KCP. 2005. Use of the alometric and the fulton condition factors to compare the carp (Cyprinus carpio) considering sexes and ages. Semin Cienc Agrar 26: 429-434.
• RODRÍGUEZ I, CHAMORRO R, NOVOA B & FIGUERAS A. 2009. β-glucan administration enhances disease resistance and some innate immune responses in zebrafish (Danio rerio). Fish Shellfish Immunol 27: 369-373.
• RUSSO R, YANONG RPE & MITCHELL H. 2006. Dietary beta-glucans and nucleotides enhance resistance of red-tail black shark (Epalzeorhynchos bicolor, fam. Cyprinidae) to Streptococcus iniae infection. J World Aquac Soc 37: 298-306.
• SÁNCHEZ-MARTÍNEZ JG, RÁBAGO-CASTRO JL, VÁZQUEZ-SAUCEDA ML, PÉREZ-CASTAÑEDA R, BLANCO-MARTÍNEZ Z & BENAVIDES-GONZÁLEZ F. 2017. Effect of β-glucan dietary levels on immune response and hematology of channel catfish Ictalurus punctatus juveniles. Lat Am J Aquat Res 45: 690-698.
• SCHLOESSER RW & FABRIZIO MC. 2017. Condition indices as surrogates of energy density and lipid content in juveniles of three fish species. Trans Am Fish Soc 146: 1058-1069.
• SCHLOSS ET AL. 2009. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75: 7537-7541.
• SELVARAJ V, SAMPATH K & SEKAR V. 2005. Administration of yeast glucan enhances survival and some non-specific and specific immune parameters in carp (Cyprinus carpio) infected with Aeromonas hydrophila. Fish Shellfish Immunol 19: 293-306.
• SHIMOJO N, NAKA K, NAKAJIMA C, YOSHIKAWA C, OKUDA K & OKADA K. 1989. Test-strip method for measuring lactate in whole blood. Clin Chem 35: 1992-1994.
• SICURO B. 2018. Nutrition in ornamental aquaculture: the raise of anthropocentrism in aquaculture? Rev Aquac 10: 791-799.
• SIWICKI AK, SCHULZ P, ROBAK S, KAZUŃ K, KAZUŃ B, GŁĄBSKI E & SZCZUCIŃSKA E. 2015. Influence of β-glucan Leiber® Beta-S on selected innate immunity parameters of European eel (Anguilla anguilla) in an intensive farming system. Cent Eur J Immunol 40: 5-10.
• SIWICKI AK, ZAKÉS Z, TERECH-MAJEWSKA E, KAZUN´ K, LEPA A & GLABSKI E. 2010. Dietary Macrogard reduces Aeromonas hydrophila mortality in tench (Tinca tinca) through the activation of cellular and humoral defence mechanisms. Rev Fish Biol Fish 20: 435-439.
• SOUZA FP ET AL. 2020a. Effect of β-glucan in water on growth performance, blood status and intestinal microbiota in tilapia under hypoxia. Aquac Rep 27: 100369.
• SOUZA FP ET AL. 2020b. Effects of dietary supplementation with a microalga (Schizochytrium sp.) on the hemato-immunological, and intestinal histological parameters and gut microbiota of Nile tilapia in net cages. PLoS ONE: e0226977.
• SUPHORONSKI SA ET AL. 2019. Effects of a phytogenic, alone and associated with potassium diformate, on tilapia growth, immunity, gut microbiome and resistance against francisellosis. Sci Rep 9: 6045.
• SUSHILA N, DAS BK, RATHINAM RB & TRIPATHI G. 2022. Strategies for enhanced adaptive immune responses of Pterophyllum scalare larvae against Aeromonas hydrophila. Aquac Res 53: 2586-2596.
• TAKAHASHI LS, SILVA TV, FERNANDES JBK, BILLER JD & SANDRE LCG. 2010. Efeito do tipo de alimento no desempenho produtivo de juvenis de acará-bandeira (Pterophyllum scalare). Bol Inst Pesca 36: 1-8.
• TALPUR AD, MUNIR MB, MARY A & HASHIM R. 2014. Dietary probiotics and prebiotics improved food acceptability, growth performance, haematology and immunological parameters and disease resistance against Aeromonas hydrophila in snakehead (Channa striata) fingerlings. Aquaculture (426-427): 14-20.
• TARNECKI AM, BURGOS FA, RAY CL & ARIAS CR. 2017. Fish intestinal microbiome: diversity and symbiosis unravelled by metagenomics. J Appl Microbiol 123: 2-17.
• TEMPLE MJ, CUSKIN F, BASLÉ A, HICKEY N, SPECIALE G, WILLIAMS SJ, GILBERT HJ & LOWE EC. 2017. A Bacteroidetes locus dedicated to fungal 1,6-β-glucan degradation: Unique substrate conformation drives specificity of the key endo-1,6- β -glucanase. J Biol Chem 292: 10639-10650.
• TRAN NT, LI Z, WANG S, ZHENG H, AWEYA JJ, WEN X & LI S. 2020. Progress and perspectives of short-chain fatty acids in aquaculture. Rev Aquac 12: 283-298.
• TRINDER P. 1969. Enzymatic determination of glucose in blood serum. Ann Clin Biochem 6: 24-27.
• TÜRNAL D, SCHIMIDT H, KÜRZINGER H & BÖHM KH. 2000. Potency testing of ß-glucan immunostimulating effect in food for ornamental fish. Bull Eur Assoc Fish Pathol 20: 143-147.
• WATANABE Y, NAGAI F & MOROTOMI M. 2012. Characterization of Phascolarctobacterium succinatutens sp. nov., an asaccharolytic, succinate-utilizing bacterium isolated from human feces. Appl Environ Microbiol 78: 511-518.
• WELKER TL, LIM C, YILDIRIM-AKSOY M & KLESIUS PH. 2012. Use of diet crossover to determine the effects of β-glucan supplementation on immunity and growth of Nile Tilapia, Oreochromis niloticus. J World Aquac Soc 43: 335-348.
• WU F, GUO X, ZHANG J, ZHANG M, OU Z & PENG Y. 2017. Phascolarctobacterium faecium abundant colonization in human gastrointestinal tract. Exp Ther Med 14: 3122-3126.
• YUKGEHNAISH K, KUMAR P, SIVACHANDRAN P, MARIMUTHU K, ARSHAD A, PARAY BA & AROCKIARAJ J. 2020. Gut microbiota metagenomics in aquaculture: factors influencing gut microbiome and its physiological role in fish. Rev Aquac 12: 1903-1927.
• ZHANG Z, SWAIN T, BØGWALD J, DALMO RA & KUMARI J. 2009. Bath immunostimulation of rainbow trout (Oncorhynchus mykiss) fry induces enhancement of inflammatory cytokine transcripts, while repeated bath induce no changes. Fish Shellfish Immunol 26: 677-684.
• ZHANG Y, WEN B, MENG LJ, GAO JZ & CHEN ZZ. 2021. Dynamic changes of gut microbiota of discus fish (Symphysodon haraldi) at different feeding stages. Aquaculture 531: 735912.

Publication Dates

• Publication in this collection
  04 Mar 2024
• Date of issue
  2024

History

• Received
  12 Sept 2023
• Accepted
  29 Dec 2023