Encapsulated Bacillus sp. THPS1, a novel thermophilic probiotic, enhances productivity and metabolic health in laying hens

Abstract

Encapsulated probiotics, sustainable alternatives to antibiotic growth promoters in poultry production, enhance productivity and physiological health. Comparative evidence on strain-specific encapsulated Bacillus probiotics and their combined effects on production performance, egg quality, metabolic indicators, and hematological profiles in laying hens is insufficient. This study evaluated three encapsulated Bacillus strains (THPS1, PWR01, and OYNH19) for sporulation, encapsulation, and spore release efficiencies. A feeding trial in laying hens supplemented with 1 × 10⁶ spores/g feed was conducted over 4 weeks. Production performance, egg quality traits, serum lipid profiles, stress hormone levels, and hematological parameters were assessed. Sporulation and encapsulation efficiencies were consistently exceeded 96 %, while spore release efficiency exhibited significant variation across strains. OYNH19 demonstrated lower release efficiency compared to THPS1 and PWR01 strains (p = 0.042). Dietary supplementation with THPS1 significantly enhanced feed conversion ratio (FCR) (0.23 ± 0.01), resulting in a 23 % reduction compared to the control and other probiotic treatments (p = 0.001). Notably, egg production rate and body weight (BW) remained unchanged. However, egg weight (EW) was exhibited a significant increase in the THPS1 group by week 4 (65.22 ± 4.67 g; p = 0.041), without any adverse effects on eggshell or internal quality traits. Furthermore, THPS1 supplementation was associated with reduced serum triglyceride concentrations and distinct multivariate clustering, indicating coordinated alterations in production, metabolic, and hematological variables. Overall, encapsulated Bacillus sp. THPS1 demonstrated superior efficacy in optimizing feed efficiency while maintaining physiological stability.

Graphical abstract

Introduction

The global poultry industry is under growing pressure to meet the increasing protein demands while simultaneously reducing antibiotic use in animal production. Intensive layer farms, characterized by their high stocking densities and genetic selection, frequently encounter challenges in the form of infectious diseases and stress-induced productivity declines (Namrata et al., 2025). Historically, sub-therapeutic antibiotic growth promoters were incorporated into livestock feed to boost performance and prevent disease. However, this practice has been restricted due to its association with the accelerated development of antimicrobial resistance (AMR) (Rafiq et al., 2022). In recent years, many countries have implemented regulations or outright prohibited the non-therapeutic use of antibiotics in livestock diets as a means of safeguarding public health (Ojotu et al., 2025). A promising alternative is the utilization of probiotics, which are live beneficial microorganisms that contribute to improved host health when administered in appropriate quantities (BERBEROĞLU et al., 2025). In poultry production, probiotics can facilitate gut microbiota balance, nutrient absorption, and immune response, ultimately resulting in enhanced growth and production performance (Dangsawat et al., 2025; Jha et al., 2020).

Among various probiotic candidates, spore-forming Bacillus species have gained significant attention as feed additives (Popov et al., 2021; Saggese et al., 2021). In contrast to lactic-acid bacteria, which are susceptible to heat and acidic environments, Bacillus probiotics form resilient endospores that withstand feed pellet processing, prolonged storage, and the low pH of the gastrointestinal tract, conferring a distinct stability advantage (Elshaghabee et al., 2017; Mwamburi et al., 2024; Sihamok et al., 2025). This resilience ensures that a substantial number of viable cells reach the intestine, a crucial prerequisite for probiotic efficacy. These characteristics make Bacillus an ideal probiotic genus for application in layer hen diets, where feed processing conditions and extended supply chains can otherwise diminish the potency of more vulnerable microbes. To enhance the delivery of probiotic, encapsulation technologies have been engineered to protect bacteria throughout the upper digestive tract. Encapsulation involves confining probiotic cells within a biocompatible matrix (e.g. sodium alginate, polysaccharides, or protein gels) that shields them from adverse environmental factors, including gastric acidity and bile (Appamano et al., 2025; Jan et al., 2025; Yang et al., 2024).

Numerous studies have investigated the effects of probiotic and encapsulated-probiotic supplementation on laying hens, consistently demonstrating positive impacts on production metrics and product quality. Probiotic-fed hens exhibit a reduced feed-to-egg ratio and produce eggs characterized by enhanced shell strength or internal quality (Onbaşılar et al., 2025; Wang et al., 2024). Some Bacillus-based probiotics have also been demonstrated to enhance egg weight (EW) or decrease the prevalence of defective eggshells in flocks (Dangsawat et al., 2025; Oketch et al., 2024). Beyond production efficiency, probiotics can beneficially modulate metabolic indicators. It has been reported that probiotic supplementation frequently lowers serum cholesterol and triglyceride levels in poultry, while simultaneously increasing beneficial high-density lipoprotein, thereby contributing to improved lipid profiles (Gheorghe et al., 2022; Zarezadeh et al., 2022). These effects not only improve animal health but could also translate to nutritionally improved poultry products. However, not all physiological responses to probiotics are consistently observed across studies. The magnitude of benefits tends to be strain-specific, and results can vary depending on the probiotic strain’s characteristics, dosage, and the hens' baseline health status. Previous study demonstrated that adding B. subtilis to hen diets did not significantly alter acute stress responses during a tonic immobility test, suggesting that the influence of probiotics on neuroendocrine stress markers is not yet fully elucidated (Soroko and Zaborski, 2020). While the production and metabolic benefits of probiotics in poultry are well documented, there remains a knowledge gap regarding their comparative efficacy across different strains and their impacts on comprehensive health in laying hens.

In light of these gaps, recent research efforts have increasingly concentrated on the identification and assessment of promising probiotic strains exhibiting unique functional characteristics, particularly those derived from extreme or under-explored environments. Bacillus species are ubiquitous in nature, and environmental isolates from high-temperature or otherwise challenging habitats may possess enhanced stress tolerance, sporulation capacity, and metabolic adaptability, making them promising probiotic candidates for industrial applications (Mwamburi et al., 2024).

Despite the growing genomic and in vitro characterization of such strains, the in vivo efficacy, especially when delivered in encapsulated form, remains insufficiently validated. In this context, the present study aimed to compare three encapsulated Bacillus strains (THPS1, PWR01, and OYNH19) regarding their sporulation, encapsulation, and spore release efficiencies, as well as their effects on production performance, egg quality traits, serum lipid profiles, stress hormone levels, and hematological parameters in laying hens. This study integrates technological performance with in vivo physiological outcomes to elucidate strain-specific responses and guide the selection of effective encapsulated probiotics for antibiotic-free egg production systems.

Materials and methods

Bacterial strains and culture conditions

Three Bacillus sp. strains used in this study included THPS1 (isolated from hot springs in Thailand) (Mwamburi et al., 2024), PWR01 (cup lump rubber serum), and OYNH19 (chicken feces) (Appamano et al., 2021). Stock cultures were maintained at –80°C in Luria-Bertani (LB) broth (Himedia™, India) containing 20 % (v/v) glycerol. For experimental use, bacterial strains were streaked on Nutrient Agar (NA, Himedia™, India) and incubated at 37°C for 24 h. Single colonies were transferred to LB broth and cultured at 37°C with shaking at 150 rpm for 18-24 h.

Bacterial identification and phylogenetic analysis

Genomic DNA was extracted using a Genomic DNA Mini Kit (Blood/Culture Cell) (Geneaid Biotech Ltd., Taiwan) and used as a template for PCR amplification of the 16S rRNA gene. Amplification was performed with Taq DNA polymerase following previously described methods (Katsura et al., 2001; Kawasaki et al., 1993; Yamada et al., 2000). The 16S rRNA region was amplified using universal primers 20F (5′-GAG TTT GAT CCT GGC TCA G-3′; positions 9–27) and 1500R (5′-GTT ACC TTG TTA CGA CTT-3′; positions 1509–1492), according to the E. coli numbering system (Brosius et al., 1981).

PCR reactions (100 µL) contained 15–20 ng of genomic DNA, 2.0 µmol of each primer, 2.5 U of Taq polymerase, 2.0 mM MgCl₂, 0.2 mM dNTPs, and 10 µL of 10× Taq buffer (pH 8.8) comprising 750 mM Tris-HCl, 200 mM (NH₄)₂SO₄, and 0.1 % Tween20. Amplification was carried out in a DNA Engine Dyad® Thermal Cycler (Bio-Rad) with an initial denaturation at 94°C for 3 min, followed by 25 cycles of denaturation at 94°C for 1 min, annealing at 50°C for 1 min, and extension at 72°C for 2 min, and a final extension at 72°C for 3 min. PCR products were verified on a 0.8 % (w/v) agarose gel, purified using a GenePHlow™ Gel/PCR Kit (Geneaid), and stored at –20°C.

Purified PCR products (approximately 1500 bp) were directly sequenced using an ABI Prism® 3730XL DNA sequencer (Applied Biosystems). Single- and double-strand sequencing was performed using primers 27F, 518F, 800R, and 1492R. The obtained sequences were assembled using the Cap contig assembly program in BioEdit v.7.2. The obtained nucleotide sequences were compared with those available in the GenBank database using the BLASTN program of the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nih.gov/). Subsequently, DNA sequences of similar length were aligned to classify homologous genes, and phylogenetic analysis of the 16S rRNA gene was performed using MEGA software (v.12; Molecular Evolutionary Genetics Analysis, Center for Evolutionary Medicine and Informatics, The Biodesign Institute, USA). A phylogenetic tree was generated using the neighbor-joining method with 1,000 bootstrap replications. Sequence alignment was performed using a multiple sequence alignment program (MAFFT) v.7.0, and Bayesian analysis was conducted in MrBayes v.3.2.7a under the GTR model.

Spore production and sporulation efficiency assessment

The spore encapsulation procedure was followed in accordance with the previously reported protocols (Dangsawat et al., 2025). Spore production was conducted following established protocols with modifications. Overnight LB cultures were spread onto Difco Sporulation Medium (DSM) agar plates, and any excess liquid was carefully removed. To induce sporulation, plates were incubated at 30°C for 72 h. Subsequently, spores were harvested by scraping the DSM surface with a sterile spreader and suspending them in sterile distilled water. The spore suspensions were washed three times by centrifugation (8,000 × g, 10 min, 4°C) and resuspension in sterile distilled water. To assess sporulation efficiency, two treatment groups were established: (i) heat-treated spores (80°C for 10 min) to eliminate vegetative cells, and (ii) non-heat-treated spores. Both groups were serially diluted (10⁻¹ to 10⁻⁶) in 0.85 % sterile sodium chloride solution. Dilutions 10⁻⁴, 10⁻⁵, and 10⁻⁶ were spread on NA plates in triplicate and incubated at 37°C for 24 h. Colony-forming units (CFU) were counted, and the sporulation efficiency was calculated as follows:

$$\text{Sporulation}\text{efficiency}(\%)=\frac{\text{CFU}\text{of}\text{heat}\text{treated}\text{spores}}{\text{CFU}\text{of}\text{non}\text{heat}\text{treated}\text{spores}}\mathrm{x}100$$

All treatment were performed with three independent biological replicates per treatment (n = 3). In addition, microscopic verification of spore formation was performed by preparing wet mounts from DSM cultures. A loopful of sporulated culture was mixed with ice-cold sterile distilled water on a glass slide, covered with a coverslip, and observed under phase-contrast microscopy at 1,000 × magnification. The presence of phase-bright endospores was recorded.

Spore encapsulation in sodium alginate

Spore encapsulation was conducted using extrusion method, as outlined in Appamano et al. (2025). Briefly, a 2 % (w/v) sodium alginate solution was prepared by dissolving food-grade sodium alginate powder in sterile distilled water with continuous stirring until completely dissolved. The spore suspension (1 × 10⁹ spores/mL) was mixed with the sodium alginate solution at a 1:1 (v/v) ratio and gently homogenized. The spore-alginate mixture was loaded into a sterile syringe (10 mL) fitted with a 21-gauge needle and extruded dropwise into a 0.1 M CaCl₂ solution under gentle magnetic stirring. Upon contact, the alginate droplets instantly gelled, forming spherical beads. The beads were allowed to harden in the CaCl₂ solution for 30 min at room temperature. Following gelation, they were separated from the CaCl₂ solution using a sterile sieve and washed 3 times with 0.85 % sodium chloride solution to remove excess calcium ions. The washed beads were then stored in 0.1 % peptone solution (pH 6.0) at 4°C until use. A portion of the beads was dried in a hot-air oven at 60°C until constant weight for feed incorporation. Encapsulation was conducted in three independent experimental batches (n = 3) to ensure reproducibility.

Characterization of alginate beads

Bead size measurement

The diameter of alginate beads was measured before and after drying using a digital vernier caliper (accuracy ± 0.01 mm). A minimum of 30 randomly selected beads from each batch were measured, and the mean diameter was calculated (Dangsawat et al., 2025).

Encapsulation efficiency

Encapsulation efficiency was determined by disrupting the alginate matrix and quantifying the encapsulated spores. One gram of alginate beads was homogenized in 9 mL of phosphate buffer (pH 7.0, 0.1 M) using a sterile homogenizer for 5 min to completely dissolve the alginate and release the spores. The homogenate was centrifuged at 5,000 × g for 5 min at 4°C, and the supernatant was then collected. Released spores were enumerated by performing serial 10-fold dilutions in 0.85 % sodium chloride solution. Appropriate dilutions were spread on NA plates in triplicate and incubated at 37°C for 24 h. Encapsulation efficiency was evaluated in three independent biological replicates per strain (n = 3) (Dangsawat et al., 2025). The encapsulation efficiency was calculated as follows:

$$\text{Encapsulation}\text{efficiency}(\%)=\frac{\text{Number}\text{of}\text{viable}\text{spores}\text{in}\text{beads}}{\text{Initial}\text{number}\text{of}\text{spores}\text{added}}\mathrm{x}100$$

Spore release efficiency

To evaluate the spore release efficiency, 1 gram of alginate beads was suspended in 9 mL of phosphate buffer (pH 7.0, 0.1 M) and incubated on a rotary shaker (150 rpm) at 37°C for 2 h. Following incubation, the buffer was collected, and released spores were counted by serial dilution and plating on NA, as described previously (Dangsawat et al., 2025). All measurements were performed in triplicate for each bacterial strain. The release efficiency was calculated as follows:

$$\text{Release}\text{efficiency}(\%)=\frac{\text{Number}\text{of}\text{spores}\text{releases}\text{after}2\mathrm{h}}{\text{Total}\text{number}\text{of}\text{encapsulated}\text{spores}}\mathrm{x}100$$

Experimental animals and feeding trial

Experimental animals

The animal experiment was conducted under the approval of the Institutional Animal Care and Use Committee, Prince of Songkla University (Approval No. AG148/2024). Twenty Hi-sex Brown laying hens at 23 weeks of age were obtained from TM Feed Products Co., Ltd (Nakorn Pathom, Thailand). All hens were healthy, with no previous history of disease or medication.

Experimental design and dietary treatments

A completely randomized design was employed for the experimental design. The twenty hens were randomly allocated into four experimental groups (n = 5 hens per group). Hens were randomly distributed to treatment groups using a computer-generated randomization sequence to minimize allocation bias. The experimental period lasted for 5 weeks (from the 23rd to 28th week of age). The experimental groups were divided as follows: Group 1 (Control group): Received basal diet without probiotic supplementation; Group 2 (THPS1): Basal diet supplemented with 1 × 10⁶ spores/g of encapsulated Bacillus sp. THPS1; Group 3 (PWR01): Basal diet supplemented with 1 × 10⁶ spores/g of encapsulated Bacillus sp. PWR01; and Group 4 (OYNH19): Basal diet supplemented with 1 × 10⁶ spores/g of encapsulated Bacillus sp. OYNH19 (Table 1). The dried encapsulated spores were incorporated into the basal diet using a laboratory mixer to achieve uniform distribution. The spore viability in the supplemented feed was verified by plate counting before feeding (Dangsawat et al., 2025).

Table 1.

Formulation and nutrient composition of the basal diet used in the feeding trial.

Ingredient	Amount (%)
Corn	54.60
Soybean meal (44 % CP)	25.20
Rice bran	4.00
Fish meal (55 % CP)	2.00
Oyster shell	8.30
Dicalcium phosphate (18 % P)	2.17
Plant oil	3.00
DL-Methionine	0.13
Salt	0.30
Premix1	0.30
Proximate analysis
Crude protein	17.00
Metabolizable energy (kcal/kg)	2800
Crude fiber	3.55
Crude fat	6.06
Calcium	4.08
Available phosphorus	0.45
Lysine	0.91
Methionine	0.42

¹Premix: 2.0 MIU vitamin A, 0.32 MIU vitamin D₃, 2,000 mg vitamin E, 330 mg vitamin K₃, 220 mg vit B₁, 450 mg vitamin B₂, 4.5 mg vitamin B₁₂, 600 mg niacin, 100 mg copper, 150 mg iodine, 130 mg cobalt, 10 g iron, 8.8 g manganese, 8.8 g zinc, 25 g preservative, up to 1 kg filter.

Production performance and egg quality assessment

Production performance analysis

Data were recorded daily for each hen and summarized weekly (5 hens per treatment). Body weights were measured weekly using a digital scale (accuracy ± 1 g) in the morning before feeding. Feed intake was calculated by weighing feed offered and subtracting feed residues daily. The following parameters were measured:

$$\text{Feed}\text{intake}\left(\mathrm{g}/\text{bird}/\text{day}\right)=\frac{\text{Total}\text{feed}\text{consumed}\text{per}\text{bird}}{\text{Number}\text{of}\text{feeding}\text{days}}$$

$$\text{Body}\text{weight}\text{change}\left(\text{BW},\mathrm{g}\right)=\frac{\text{Final}\text{BW}\left(\text{week}5\right)}{\text{Initial}\text{BW}\left(\text{week}0\right)}$$

$$\text{Egg}\text{production}(\%)=\frac{\text{Number}\text{of}\text{eggs}\text{collected}}{\text{Number}\text{of}\text{hens}}\mathrm{x}100$$

$$\text{Average}\text{egg}\text{weight}\left(\mathrm{g}\right)=\frac{\text{Total}\text{weight}\text{of}\text{all}\text{eggs}\text{collected}}{\text{Number}\text{of}\text{eggs}}\mathrm{x}100$$

$$\text{Egg}\text{mass}\left(\mathrm{g}/\text{bird}/\text{day}\right)=\frac{\text{Average}\text{egg}\text{weight}\left(\mathrm{g}\right)}{\text{Egg}\text{production}\text{rate}}$$

$$\text{Feed}\text{conversion}\text{ratio}\left(\text{FCR}\right)=\frac{\text{Total}\text{feed}\text{intake}\left(\mathrm{g}\right)}{\text{Total}\text{egg}\text{mass}\left(\mathrm{g}\right)}$$

Egg quality analysis

Egg quality was assessed at the end of the experimental period (week 5) using 15 eggs per treatment group collected over 3 consecutive days (5 eggs per day). The following parameters were measured as follows (Yoruk et al., 2004):

Egg weight (EW, g): Individual eggs were weighed using a digital balance

Eggshell strength (ESS, kg/cm²): Measured using an eggshell force gauge

Eggshell thickness (SST, mm): Measured at three locations (blunt end, equator, and sharp end) using a micrometer, and the average was calculated

Eggshell weight (ESW, g): Shells were dried at 105°C overnight and weighed

Eggshell percentage (%): (ESW/EW) × 100

Yolk weight (YW, g): Yolk was carefully separated and weighed

Albumen weight (AW, g): EW - (YW + Shell weight)

Yolk color (YC): Assessed using the Roche yolk color fan (score 1-15)

Haugh unit (HU) = 100 × log (H - 1.7W^0.37 + 7.6) where H is albumen height (mm) and W is egg weight (g)

Blood sample collection and processing

At the end of the experimental period (week 5), blood samples were collected from all hens (n = 5 per group) in the morning after overnight fasting. Blood was drawn from the brachial vein using sterile needles and syringes. Two blood samples were collected for each hen. For hematology analysis, approximately 2 mL of whole blood was collected, and samples were gently mixed by inversion and kept on ice until analysis. For serum biochemical analysis, approximately 3 mL of blood was collected into non-anticoagulant tubes and allowed to clot at room temperature for 30 min. Samples were centrifuged at 3,000 × g for 15 min at 4°C. Serum was carefully collected and stored at –20°C until analysis.

Hematological analysis

Complete blood counts (CBC) were performed using automated hematology analyzer of blood collection. The following parameters were measured: Total white blood cell count (WBC, cells/µL), red blood cell count (RBC, ×10⁶ cells/µL), hemoglobin concentration (Hb, g/dL), hematocrit (Hct, %), mean corpuscular volume (MCV, fL), mean corpuscular hemoglobin (MCH, pg), mean corpuscular hemoglobin concentration (MCHC, %), and platelet count (thrombocytes, cells/µL). Differential WBC were performed by preparing blood smears stained with Wright-Giemsa stain (Blumenreich, 1990). A minimum of 100 white blood cells were counted and classified as: heterophils (%), lymphocytes (%), monocytes (%), eosinophils (%), and basophils (%).

Serum biochemical analysis

Triglyceride and cholesterol determination

Serum triglyceride concentrations (n = 5 per treatment) were determined using an enzymatic colorimetric method based on the hydrolysis of triglycerides to glycerol, followed by enzymatic oxidation and color development. Absorbance was measured spectrophotometrically according to the method described by (Fossati and Prencipe, 1982).

Serum total cholesterol levels (n = 5) were measured using an enzymatic colorimetric assay, in which cholesterol esters are hydrolyzed and oxidized, producing a colored complex proportional to cholesterol concentration. The assay was performed following the method described previously (Allain et al., 1974).

Cortisol determination

Serum cortisol concentrations (n = 5 per treatment) were determined using an immunoassay-based method (enzyme-linked or radioimmunoassay), based on the competitive binding of cortisol to specific antibodies. Cortisol levels were quantified by comparison with a standard curve as described by Foster and Dunn (1974).

Glucocorticoid determination

Serum corticosterone concentrations in laying hens (n = 5 per treatment) were measured using a commercially available enzyme-linked immunosorbent assay (ELISA) kit validated for avian species (DetectX® Corticosterone ELISA Kit, Arbor Assays, Catalog No. K014-H1). Blood sample (1–2 mL) was collected from the wing vein within ≤ 3 min after initial handling to minimize stress. The blood was allowed to clot at room temperature for 20–30 min and then centrifuged at 2,500 × g for 10 min at 4°C to separate serum. The serum was aliquoted into 100–200 µL microtubes and stored at −80°C until analysis. Prior to ELISA, serum samples were thawed at room temperature and diluted 1:5 with assay buffer. All standards and quality controls (low, medium, high) as well as samples were added to the ELISA plate in duplicate. Plates were incubated at room temperature for 60 min and washed according to the manufacturer’s instructions. Substrate solution was added, and the reaction was stopped after 15 min. Optical density was measured at 450 nm using a UV–Visible Spectrophotometer (Shimadzu UV-1800, Japan). Corticosterone concentrations were calculated from a standard curve using 4-parameter logistic regression and adjusted for dilution factors. All samples were analyzed in duplicate, and the mean values were reported. The intra-assay and inter-assay coefficients of variation were <5 % and < 7 %, respectively, and recovery of spiked samples ranged from 75 to 110 %, confirming the accuracy and precision of the assay. Results were expressed as ng/mL.

Statistical analyses

Normality of data distribution was assessed using the Shapiro–Wilk test, and homogeneity of variances was evaluated using the chi-square test. Data were analyzed using one-way analysis of variance to assess the effects of dietary treatments. When a significant treatment effect was detected, Duncan’s multiple range test was applied for post-hoc comparisons among treatment means. Statistical significance was set at p < 0.05. Results are presented as means ± standard error of the mean (SEM). All statistical analyses were performed using R software (version 4.3.1; R Foundation for Statistical Computing, Austria). Pearson’s correlation coefficients were calculated using the stats package, with correlation matrices visualized using the corrplot package. Principal component analysis (PCA) was conducted using the FactoMineR package, and results were visualized using the factoextra package. All graphical representations were generated using the ggplot2 package.

Results

Phylogenetic analysis of bacterial isolate

The phylogenetic relationships of the selected strains were inferred using a neighbor-joining tree based on 16S rRNA gene sequences (Fig. 1). The tree showed clear clustering of the isolates within Bacillus and Lysinibacillus lineages, supported by bootstrap values ranging from 57 % to 100 %. The Bacillus strain THPS1 clustered closely with B. aryabhattai, while PWR01 grouped within the Lysinibacillus clade, closely related to Lysinibacillus fusiformis and other Lysinibacillus reference strains. OYNH19 clustered within the Bacillus group, close to B. cereus and related species. Distinct separation among the major clades indicated clear taxonomic differentiation between Bacillus, Lysinibacillus, and Rossellomorea reference species.

Fig. 1.

Phylogenetic analysis of the 16S rRNA gene of the isolate and related taxa. A neighbor-joining (NJ) tree with 1,000 bootstrap replications assessed node support (bootstrap values: 57 %−100 %). Bayesian inference was performed in MrBayes v3.2.7a under the GTR substitution model to confirm tree topology.

Sporulation efficiency of Bacillus trains

Sporulation and encapsulation efficiencies exhibited no notable variations among strains, whereas spore release efficiency exhibited a significant difference, and alginate bead diameter remained unaffected by strain, drying, or their interaction (Fig. 2).

Fig. 2.

Morphology, efficiencies, and bead size across strains. (A) Representative micrographs of sporulating cells for THPS1, PWR01, and OYNH19 (scale bars 40 μm). (B) Sporulation efficiency ( %). (C) Encapsulation efficiency ( %). (D) Spore release efficiency (%); different letters indicate significant differences among strains (multiple comparisons following one-way testing). (E) Bead size (mm): left, two-way ANOVA effect estimates (±95% CI) for strain, time (after–before), and strain × time interaction; right, bead size before and after treatment by strain. p-values are reported within panels.

Sporulation efficiency varied between strains, ranging from 96.21 ± 1.88 % to 98.12 ± 0.98 %. THPS1 (98.12 ± 0.98 %), PWR01 (96.21 ± 1.88 %), and OYNH19 (96.45 ± 5.38 %) demonstrated no statistically significant differences (p = 0.496). Encapsulation efficiency also showed no significant difference among strains: THPS1 (87.96 ± 3.70 %), PWR01 (83.87 ± 15.30 %), and OYNH19 (77.19 ± 3.89 %) (p = 0.398). In contrast, spore release efficiency exhibited significant differences among strains (p = 0.042). OYNH19 demonstrated a lower mean release efficiency (86.72 ± 2.39 %) than THPS1 (96.71 ± 5.73 %) and PWR01 (95.35 ± 4.16 %), whereas THPS1 and PWR01 did not exhibit a statistically significant difference. In addition, the diameter of the alginate bead before drying varied between 3.40 ± 0.051 and 3.55 ± 0.043 mm across strains, while their diameter after drying ranged from 3.33 ± 0.031 to 3.40 ± 0.025 mm. A two-way analysis of variance revealed no significant effects of strain (p = 0.535–0.690), drying (p = 0.633), or strain × drying interaction (p = 0.585) on the diameter of the bead.

Effects of probiotic supplementation on production performance

Egg production, feed intake, and FCR

Production performance parameters remained consistent across dietary treatments throughout the experimental period, with no notable fluctuations in egg production or BW, while feed efficiency exhibited variations among groups (Fig. 3). Egg production percentage ranged from 91.42 % to 100.00 % across all groups, indicating no significant differences (p = 0.122). Similarly, BW changes during the 4-week experimental period demonstrated no significant differences among groups (p = 0.896), ranging from 9.30 ± 13.94 g (THPS1) to 15.36 ± 10.10 g (OYNH19). Feed intake data showed variation among groups (92.54 to 120.00 g/day). Notably, THPS1 supplementation resulted in the most favorable FCR at 0.23 ± 0.01, which was significantly lower compared to the control (0.30 ± 0.02), PWR01 (0.31 ± 0.03), and OYNH19 (0.31 ± 0.03) groups (p = 0.001).

Fig. 3.

Effects of dietary treatments on production performance of laying hens over four experimental weeks. (A) Hierarchical clustering heatmaps illustrating standardized responses (Z-scores) of production-related parameters, including total egg weight, total number of eggs, egg production rate, feed intake, feed consumed, feed remaining, and feed conversion ratio for eggs during Week 1 to Week 4. (B) Feed intake, (C) feed remaining, and (D) feed consumed across weeks. Bars represent mean values, and different lowercase letters above bars within the same week indicate significant differences among treatments (p < 0.05).

Egg weight and quality parameters

Dietary supplementation with encapsulated Bacillus sp. THPS1 at a concentration of 1 × 10⁶ spores/g feed resulted in a substantial improvement in EW by the fourth week of the experiment (Fig. 4). The THPS1 group produced eggs with a weight of 65.22 ± 4.67 g, which was significantly higher than the control group (57.22 ± 5.13 g), the PWR01 group (59.50 ± 2.13 g), and the OYNH19 group (58.80 ± 4.19 g) (p = 0.041) (Fig. 4). This represents a 14 % increase in EW compared to the control group. No significant differences were observed among treatment groups for ESS (5.13 to 5.66 kg/cm³), EST (0.39 to 0.40 mm), ESW (6.24 to 7.13 g), YW (12.96 to 13.82 g), and YC scores (13.78 to 14.30) (p > 0.05) (Fig. 4).

Fig. 4.

Hierarchical clustering heatmaps showing the effects of dietary treatments on egg quality traits at week 1 (A), week 2 (B), week 3 (C), and week 4 (D), respectively. Heatmaps display standardized values (Z-scores) of egg quality parameters, including egg weight, eggshell weight, eggshell thickness, eggshell strength, yolk weight, yolk color score (Roche scale), albumen height, and Haugh unit.

Effects of probiotic supplementation on blood lipid profiles

Serum triglycerides

Dietary supplementation with encapsulated probiotics resulted in reduced serum triglyceride concentrations compared to the control group (Fig. 5). The THPS1 group exhibited the lowest triglyceride level at 971.0 mg/dL, representing a 15.1 % reduction compared to the control group (1144.4 mg/dL). PWR01 and OYNH19 groups showed intermediate values at 1069.3 mg/dL and 1104.5 mg/dL, respectively. However, no statistical analyses were observed (p > 0.05).

Fig. 5.

Heatmap of serum biochemical and hematological parameters across experimental groups. Values were Z-score normalized by parameter and hierarchically clustered for blood parameters. Blue and red annotation bars denote the control and probiotic-treated groups, respectively.

Serum cholesterol

Probiotic supplementation resulted in variable effects on total serum cholesterol levels (Fig. 4). The PWR01 group showed the highest cholesterol level at 241.4 mg/dL, which was significantly higher than both the control (139.2 mg/dL) and THPS1 (138.5 mg/dL) groups. The OYNH19 group had an intermediate cholesterol level of 197.9 mg/dL, which was also significantly different from the control and THPS1 groups but lower than PWR01. Notably, the THPS1 group-maintained cholesterol levels similar to the control.

Effects of probiotic supplementation on stress hormones

Serum cortisol concentrations were undetectable (reported as 0 µg/dL) in all treatment groups, including the control (Fig. 5). The absence of detectable cortisol suggests that the experimental hens were not experiencing significant physiological stress during the study period.

Effects of probiotic supplementation on hematological parameters

Complete blood count analysis revealed that all hematological parameters remained within physiologically normal ranges for laying hens across all treatment groups, indicating that probiotic supplementation did not adversely affect blood cell profiles (Fig. 5).

White blood cell counts analysis

Total WBC varied among groups, with the OYNH19 group showing the highest count at 12,000 cells/µL, followed by the control (8,300 cells/µL) and PWR01 (8,000 cells/µL) groups. The THPS1 group had the lowest WBC at 4,000 cells/µL.

Differential WBC demonstrated that lymphocytes were the predominant cell type across all groups (66-79 %), followed by heterophils (17-30 %) and monocytes (2-7 %). No eosinophils or basophils were detected in any groups. The heterophil to lymphocyte (H:L) ratio ranged from 21.5 % (control) to 45.5 % (THPS1). Lower H:L ratios generally indicate reduced stress levels, though all values remained within acceptable ranges.

Red blood cell parameters

RBC counts showed variation among groups, with the control group exhibiting the highest count at 2.37 × 10⁶ cells/µL, followed by OYNH19 (2.21 × 10⁶ cells/µL), PWR01 (1.28 × 10⁶ cells/µL), and THPS1 (0.61 × 10⁶ cells/µL). In addition, Hb concentrations followed a similar pattern, with the control group showing the highest level at 10.8 g/dL, followed by OYNH19 (10.2 g/dL), PWR01 (6.1 g/dL), and THPS1 (2.8 g/dL). Hct values were also highest in the control group (31.5 %), followed by OYNH19 (29.6 %), PWR01 (17.3 %), and THPS1 (7.6 %).

Red blood cell indices

MCV was highest in the PWR01 group at 135.2 fL, followed by OYNH19 (133.9 fL), control (132.9 fL), and THPS1 (124.6 fL). MCH showed a similar trend, with PWR01 having the highest value at 47.7 pg, followed by OYNH19 (46.2 pg), control (45.5 pg), and THPS1 (45.9 pg). Furthermore, MCHC was highest in the THPS1 group at 36.8 %, followed by PWR01 (35.3 %), control (34.3 %), and OYNH19 (34.5 %).

Platelet counts

Platelet (thrombocyte) counts ranged from 21,000 cells/µL (OYNH19) to 27,000 cells/µL (control), with PWR01 at 24,500 cells/µL and THPS1 at 23,000 cells/µL.

Pearson correlation and principal component analysis

Pearson correlation analysis identified significant associations among production, egg quality, hematological, and biochemical variables (Fig. 6). Total egg number correlated positively with total EW (r = 0.613) and egg production (r = 0.99). Feed intake was perfectly and inversely associated with feed remaining (r = −0.98) and perfectly associated with feed consumed (r = 0.99), while FCR correlated negatively with feed intake (r = −0.730) and positively with feed consumed (r = 0.772). Egg weight showed negative correlations with feed intake (r = −0.610) and feed consumed (r = −0.610), and ESS correlated positively with EST (r = 0.555). Albumen height was positively associated with YW (r = 0.605), and HU showed a very strong correlation with albumen height (r = 0.974).

Fig. 6.

Pearson correlations (p < 0.05) among production performance, egg quality, hematological, and biochemical variables. Circle size represents the absolute value of the correlation coefficient (|r|), and color indicates direction and magnitude (blue: negative; red: positive).

Hematological variables exhibited strong interrelationships: heterophils and lymphocytes were strongly inversely correlated (r = −0.943), and the heterophil-to-lymphocyte (H:L) ratio correlated almost perfectly with heterophils (r = 0.998) and inversely with lymphocytes (r = −0.962). Hemoglobin and hematocrit were nearly perfectly correlated (r = 0.999), and both were strongly associated with erythrocyte indices, including MCV (r = 0.711–0.958), MCH (r = 0.802–0.806), and MCHC (r = −0.846 to −0.976). Triglyceride concentration correlated positively with feed intake (r = 0.932) and feed consumed (r = 0.932), and negatively with feed remaining (r = −0.932), while cholesterol showed moderate associations with feed-related traits (r ≈ 0.494–0.499).

PCA revealed clear multivariate separation among dietary treatments, with the first two components explaining 65.8 % of the total variance (PC1: 53.5 %; PC2: 12.3 %; Fig. 7A). Samples from the control, OYNH19, PWR01, and THPS1 groups formed distinct clusters along PC1 and PC2, with non-overlapping confidence ellipses between THPS1 and the other treatments on PC1. PC1 was primarily driven by lymphocytes, feed consumed, feed intake, feed remaining, MCHC, H:L ratio, heterophils, triglycerides, MCH, and hemoglobin, each contributing above the expected average (Fig. 7B). In contrast, variables with the highest contributions to PC2 included total number of eggs, egg production, total egg weight, monocytes, and cholesterol, all exceeding the average contribution threshold (Fig. 7C).

Fig. 7.

Principal component analysis of production performance, egg quality, and hematological variables across dietary treatments. (A) PCA score plot showing separation of Control, OYNH19, PWR01, and THPS1 groups along Dim1 (53.5 %) and Dim2 (12.3 %), with 95 % confidence ellipses. (B) Variable contributions to Dim1, with the dashed red line indicating the average expected contribution. (C) Variable contributions to Dim2, with bars exceeding the dashed red line representing variables contributing more than the average to the principal component.

Discussion

The dietary inclusion of encapsulated Bacillus probiotics resulted in significant improvements in laying hen performance, particularly in feed conversion efficiency. Hens that receiving Bacillus sp. THPS1 exhibited a 23 % lower FCR compared to the controls, indicating enhanced conversion of feed into egg mass. This enhancement in FCR is consistent with recent reports of probiotic supplementation in layers. For instance, a 16-week trial conducted by Hakami et al. (2025) demonstrated that hens fed diets containing various Bacillus strains exhibited significantly improved FCR compared to un-supplemented controls. The efficient feed utilization observed in the THPS1 group suggests that the probiotic enhanced nutrient digestibility and absorption in the gut. This is biologically plausible, as Bacillus species such as B. subtilis and B. coagulans produce extracellular enzymes (e.g., proteases, amylases, and cellulases) that facilitate the breakdown of feed components (Danilova and Sharipova, 2020; Schallmey et al., 2004; Zhou et al., 2020). By enhancing digestive capacity and nutrient uptake, the probiotics likely reduced the feed input required per unit of egg production. Notably, overall egg production in our study remained high rates (91–100 %) across groups without any substantial differences among treatments. The absent of a change in egg-laying rate aligns with some short-term probiotic studies where baseline production is already near its maximal. However, improvements in feed efficiency without compromising egg number are beneficial, as they indicate the hens on probiotic-maintained production with reduced feed requirements are more efficient. Other studies have reported probiotic-induced enhancements in egg production over extended durations (Dangsawat et al., 2025; Obianwuna et al., 2022; Onbaşılar et al., 2025). In the present 4-week trial, the high control performance may have obscured any subtle gains in egg quantity, but the FCR improvement indicates a distinct advantage of the THPS1 strain. This finding holds significant economic importance for the poultry industry, as feed costs are a major component of production; a more than 20 % improvement in FCR can substantially reduce feeding costs per egg produced. One of the most notable findings was the enhancement on EW with Bacillus sp. THPS1 supplementation. By the 4 weeks, eggs from the THPS1 group exhibited a significant higher weight compared to those from the control group (65.2 g vs 57.2 g). Notably, this increase in egg size did not compromise egg quality. Essential shell attributes, including strength, thickness, and weight, and internal quality parameters such as YW, AH, HU, and YC, remained statistically comparable across all groups and fell within the acceptable ranges for Hi-sex Brown hens. The ability of THPS1 to enhance EW without adversely affecting shell integrity or composition indicates improved nutrient allocation towards egg formation. In practical terms, heavier eggs are economically advantageous, provided shell quality is maintained, which our results corroborate. Hakami et al. (2025) reported that a combination of B. subtilis and B. licheniformis demonstrated the heaviest eggs in their study, while other probiotic treatments also elevated overall egg mass compared to the controls. Similarly, a recent study isolated a potential probiotic B. aryabhattai and demonstrated that encapsulated supplementation significantly improved EW, shell thickness, and HU in layer chickens (Dangsawat et al., 2025). These findings align with the observed improvements in external and internal egg quality. It is noteworthy that increasing egg size can occasionally compromise egg production due to limited nutrient resources. In the current study, however, egg production did not significantly decline with the larger eggs, suggesting that THPS1 facilitated hens' ability to better meet the nutritional demands of both egg production and egg size. One possible mechanism is enhanced nutrient utilization, as probiotics likely facilitated greater uptake of proteins, amino acids, and minerals (e.g. calcium), which are essential for egg formation (Bryden et al., 2021; Khan et al., 2020; Krysiak et al., 2021). Indeed, Bacillus probiotics have been reported to improve calcium absorption and facilitate improved shell mineralization, which may explain why shell quality was sustained even as EW increased (Abdelqader et al., 2013; Wang et al., 2021; Zou et al., 2021). Overall, the probiotic-assisted improvement of EW, coupled with unchanged shell quality, suggests that THPS1 supplementation enabled hens to allocate more nutrients to each egg without physiological strain.

Dietary probiotics exhibited a measurable impact on the blood lipid profile of the hens. In this study, all probiotic-supplemented groups demonstrated a trend towards reduced serum triglycerides compared to the control group, with the THPS1 group achieving the most significant reduction. Although this decrease did not attain statistical significance in this study, the observed direction is consistent with numerous studies reporting lipid-lowering effects of probiotics in poultry. Probiotic bacteria can influence lipid metabolism through various mechanisms, including the deconjugation of bile acids, the assimilation of cholesterol, and the augmentation of fatty acid oxidation (Deng et al., 2020; Pavlović et al., 2012; Wu et al., 2022). Recent research conducted on laying hens has indicated a notable reduction in serum cholesterol levels in probiotic-treated groups. Furthermore, in certain instances, probiotic treatment has been associated with a decrease in triglyceride levels.. Wang et al. (2024) observed that hens fed a compound probiotic had markedly lower total cholesterol than controls, and they also noted a decline in serum triglyceride levels, suggesting improved lipid regulation. Mechanistically, probiotics can enhance intestinal lipase activity, facilitating the breakdown of dietary fats into fatty acids and glycerol, thereby reducing circulating lipid levels (Wang et al., 2017; Wu et al., 2022). It is encouraging that THPS1 achieved triglyceride reduction without concomitant increases in cholesterol levels, as hypertriglyceridemia in laying hens is associated with fatty liver syndrome and other metabolic issues (Al-Khalidi, 2023; Huang et al., 2022; Zhang et al., 2024). Our findings suggest a potential health-promoting aspect of THPS1. By regulating blood lipid levels, THPS1 probiotic might contribute to enhanced liver health and metabolic equilibrium in high-yielding hens.

In the current study, probiotic supplementation did not adversely affect the stresses or hematological health of hens. All experimental groups, including the control, exhibited undetectable cortisol levels in serum, indicating minimal physiological stress during the experiment. This could be attributed to effective husbandry practices and the absence of deliberate stressors. Probiotics may have also contributed to maintaining a stable gut environment, indirectly buffering stress, as a healthy microbiota is known to influence the gut–adrenal axis (Shini and Bryden, 2021). A common stress indicator in poultry is the heterophil-to-lymphocyte (H:L) ratio. In our study, H:L ratios ranged from approximately 0.22 in control birds to 0.46 in the THPS1 group. All these values are within normal limits for laying hens and do not indicate chronic stress (Campo and Davila, 2002). The slightly higher H:L of hens in the group that received THPS1 probiotic could be a normal variation. Notably, no eosinophils or basophils were detected in any groups, and lymphocytes remained the predominant white cell type in all birds, reflecting a healthy immune profile. These observations align with the hypothesis that Bacillus probiotics do not induce systemic stress or inflammation in poultry. Instead, some studies have found that probiotics can mitigate stress responses under challenging conditions (Hakami et al., 2025).

Hematologically, all measured parameters remained within physiological limits, indicating no adverse effects on blood cell profiles. Minor variations in blood counts were noted between groups. However, these differences did not appear to reflect any pathologies. It is well-established that blood cell counts in laying hens can exhibit fluctuation due to various factors, including age, reproductive cycle stage, and nutrition absorption. Occasionally, these fluctuations may manifest as mild anemia, as hens allocate significant resources towards egg production (Ekinci et al., 2023; Lessire et al., 2017). This finding concurs with previous studies demonstrating that feeding B. subtilis to layer chickens did not adversely affect hematological indices and even exhibited a tendency to improve certain immune parameters (Park and Kim, 2015; Park et al., 2018). In the current study, while we did not evaluate cytokine or immunoglobulin indicators, the normal white cell differentials and the H:L ratios indirectly suggest that immune homeostasis was preserved. The differential effects observed among THPS1, PWR01, and OYNH19 strains can be attributed to their distinct functional traits and probiotic capacities. All strains demonstrated comparable high sporulation and encapsulation efficiencies, ensuring the delivery of a robust dose of viable spores to the hens. However, the spore release efficiency from the beads was significantly lower for OYNH19 compared to THPS1 and PWR01. This suggests that fewer OYNH19 cells were available for colonization or exerting effects in the gut, potentially explaining why OYNH19 exhibited the least impact on performance (no improvement in FCR or EW) and even a trend toward higher WBC (possibly indicating the host immune system reacting to a less effective or different gut colonization pattern). In contrast, THPS1 released spores with remarkable efficiency, potentially resulting in enhanced gut colonization and consequently more pronounced benefits. As noted above, Bacillus probiotics secrete a suite of digestive enzymes (Gong et al., 2018; Jiang et al., 2022). Enhanced digestion would increase the availability of amino acids and energy for egg production, thereby supporting development of larger eggs and enhancing FCR (Obianwuna et al., 2022). Additionally, Bacillus species produce metabolites such as short-chain fatty acids (SCFAs) (Sihamok et al., 2025), which can stimulate intestinal villus development and nutrient transportation. Xu et al. (2022) demonstrated that feeding B. coagulans to laying hens resulted in alterations in the cecal microbiota and increased SCFA concentrations, which correlated with enhanced egg production and quality. A comparable effect could be observed with THPS1; by modulating the gut microbial community, the probiotic could establish a more conductive environment for nutrient absorption.

Gut flora modulation is a well-recognized probiotic action mode. Beneficial Bacillus strains can inhibit pathogens and promote commensal bacteria, leading to a more stable microbiome (Grant et al., 2018). A balanced gut microbiome reduces subclinical inflammation and improves gut barrier integrity (Chen et al., 2015; Ducatelle et al., 2018). In our findings, the absence of any inflammatory response and the preservation of normal gut-derived parameters suggest that THPS1 contributed to gut health. Enhanced gut barrier function and diminished pathogen load enable the hen to redirect more nutrients to productive functions (e.g., eggs production) rather than immune responses. This is corroborated by research demonstrating that B. licheniformis supplementation enhanced intestinal barrier function and systemic immunity in layer chickens, thereby boosting egg production (Hakami et al., 2025). The study on the efficacy of probiotics for laying hens in the current study presented certain limitations, including a relatively short trial duration and a restricted scope of parameters assessed. Future research should assess the trial duration, incorporate multiple laying phases, and the analysis of gut microbiota, nutrient digestibility, and inflammatory biomarkers. By doing so, a more comprehensive understanding of the effects of probiotics on laying hens can be gained.

Conclusion

Dietary supplementation with encapsulated Bacillus sp. THPS1 at 1 × 10⁶ spores/g feed improved FCR by 23 % in laying hens, maintaining stable egg production and BW. THPS1 supplementation significantly increased EW by week 4 without affecting eggshell quality, yolk characteristics, or albumen-related traits. Probiotic supplementation modulated metabolic and hematological profiles, reducing serum triglyceride concentrations and separating dietary treatments in PCA analyses. In conclusion, encapsulated Bacillus sp. THPS1 is a functional probiotic capable of enhancing feed efficiency and selected production outcomes in laying hens while preserving physiological homeostasis.

Funding

This project was financially supported by Prince of Songkla University, Surat Thani Campus, Surat Thani, Thailand.

Data availability

The datasets generated and analyzed during this study are available from the corresponding authors upon reasonable request.

CRediT authorship contribution statement

Waraphorn Sihamok: Writing – original draft, Methodology, Investigation. Orathai Dangsawat: Writing – original draft, Methodology, Investigation. Rachapong Sukhawong: Methodology, Investigation. Wasinee Boonamee: Methodology, Investigation. Kraibhumi Thongpan: Methodology, Investigation. Jessada Rattanawut: Writing – review & editing, Resources, Formal analysis. Rapeewan Sowanpreecha: Writing – review & editing, Supervision, Resources. Luu Tang Phuc Khang: Writing – review & editing, Formal analysis, Data curation. Papungkorn Sangsawad: Writing – review & editing, Visualization, Supervision, Formal analysis, Conceptualization. Nguyen Vu Linh: Writing – review & editing, Visualization, Supervision, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Sk Injammul Islam: Methodology, Formal analysis. Patima Permpoonpattana: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Disclosures

The authors declare no competing financial interests or conflicts of interest related to this work.