Screening and characterization of Limosilactobacillus reuteri L16 and its probiotic properties in Hy-Line Brown chicks

Abstract

With the increasingly restricted use of antimicrobial growth promoters (AGPs) in poultry production, host-derived probiotics have attracted growing attention as green feed additives for improving growth performance and intestinal health. In this study, 84 lactic acid bacteria (LAB) strains were isolated from feces of healthy Hy-Line Brown laying hens using MRS agar supplemented with 2 % CaCO₃. After screening for acid and bile salt tolerance, strains L16 and L20 were selected based on antibacterial activity, cell surface properties, safety, and genomic features. Average nucleotide identity (ANI) and whole-genome phylogenetic analyses identified both strains as Limosilactobacillus reuteri (L. reuteri). Genomic characterization revealed relatively complete metabolic pathways, genetic information processing systems, and gene clusters associated with probiotic functionality and antimicrobial potential. In vivo, L16 significantly improved growth performance in Hy-Line Brown chicks, as evidenced by increased body weight and average daily gain, reduced feed conversion ratio, and enhanced thymus and bursa of Fabricius (BF) indices. Moreover, L16 increased jejunal villus height (VH) and the villus height-to-crypt depth ratio (VH/CD), upregulated tight junction proteins (Occludin and ZO-1), decreased IFN-γ, and increased IL-10 levels, indicating enhanced intestinal barrier function and immunomodulatory capacity. 16S rRNA gene sequencing further showed that L16 modulated gut microbiota composition by enriching beneficial taxa, including Levilactobacillus brevis and Luoshenia tenuis. Overall, L16 exerted growth-promoting and gut health–improving effects comparable to those of bacitracin methylene disalicylate (BMD), while producing more favorable changes in body weight, average daily gain, and immune organ development. These findings highlight the potential of L16 for further development and application as a probiotic feed additive in poultry production.

Introduction

Lactic acid bacteria (LAB) are a group of Gram-positive, non-spore-forming bacteria that ferment carbohydrates to produce lactic acid and are typically anaerobic or facultatively anaerobic (Anumudu et al., 2024). These bacteria are widely distributed and can thrive in a broad range of ecological niches, including fermented foods, silage, plants, compost, and the oral, gastrointestinal, and reproductive tracts of humans and animals (Mejia-Caballero et al., 2025). Morphologically, LAB are generally coccoid or rod-shaped, catalase-negative, and non-motile, and they usually exhibit strong tolerance to acidic conditions and bile salts (Gizachew et al., 2023).

Food safety and food security have attracted widespread attention. In response to these concerns, many countries and regions have enacted regulations to govern antibiotic use and have partially or completely restricted the application of antimicrobial growth promoters (AGPs) (Bai et al., 2017; Zhang et al., 2021). Against this backdrop, probiotics have gained increasing attention as potential alternatives to AGPs because of their safety, lack of drug residues, ability to maintain intestinal microbial homeostasis, enhance host immune function, and promote animal growth (Deng et al., 2021; Montoro et al., 2016). Among these probiotics, Limosilactobacillus reuteri (L. reuteri) can influence lipid metabolism and produce bioactive compounds such as lactic acid, reutericyclin, and bile salt hydrolase, all of which play important roles in maintaining normal host physiological functions (Du et al., 2023; Foley et al., 2021; Hou et al., 2015). Previous studies have shown that L. reuteri can enhance intestinal barrier function, preserve the integrity of tight junction proteins, modulate the gut microbiota, and alleviate inflammation. For example, dietary supplementation with L. reuteri SL001 has been reported to improve growth performance, immune function, antioxidant status, and intestinal morphology and microbiota in broiler chickens (Chai et al., 2023); L. reuteri LR1 has been shown to improve intestinal morphology and barrier function in weaned piglets (Yi et al., 2018); L. reuteri XY227 promotes growth performance and modulates lipid metabolism in finishing pigs by improving intestinal morphology and altering the gut microbiota (Xie et al., 2025); in addition, L. reuteri SXDT-32 alleviates intestinal inflammation in piglets by producing short-chain fatty acids (SCFAs) that inhibit the PI3K-Akt pathway, providing an innovative approach for the treatment and prevention of bacteria-induced colitis (Chen et al., 2025). Although some probiotics intended for human use may also be used in animals, it is generally recommended that human probiotics be derived from human- or food-associated sources, as such strains are considered safer and exhibit a greater capacity to adhere to human intestinal epithelial cells (Sanders, 2008; Zhang et al., 2025a). Therefore, when selecting probiotic strains, those isolated from the same host species are generally more likely to colonize the target host efficiently and exert more targeted probiotic effects (Da Silva et al., 2024).

LAB are diverse and widely distributed, with significant differences in species composition and functional characteristics among strains from different sources. Therefore, in the present study, fecal samples from Hy-Line Brown laying hens were used to isolate and identify LAB, followed by standard in vitro and in vivo evaluations and whole-genome bioinformatic analysis. Through screening for acid tolerance, bile salt tolerance, antibacterial activity, cell surface properties, and safety, L. reuteri strains with superior overall performance were selected for further investigation to evaluate their potential probiotic applications in poultry growth, immunity, and intestinal health, thereby providing a scientific basis and strain resources for microbiota-based interventions in poultry production.

Materials and methods

Sample collection, strain isolation, and identification

Fifty fecal samples were collected from healthy adult Hy-Line Brown laying hens at a poultry farm in Mianyang, Sichuan Province, China. A 1 g aliquot of each sample was suspended in sterile phosphate-buffered saline (PBS; Biosharp, China) and serially diluted 10-fold. Then, 100 μL of the 10⁻⁴ to 10⁻⁷ dilutions was spread onto MRS agar plates (Hopebio, China) supplemented with 2 % CaCO₃ (Chron Chemicals, China) and incubated anaerobically at 37 °C for 24 h. Single colonies producing a clear zone were selected, streaked three times on MRS plates for purification, and identified via Gram staining (Biosharp, China). Genomic DNA was extracted using a bacterial genomic DNA extraction kit (TIANGEN, China). The 16S rRNA gene was amplified using the universal primers 27F (AGAGTTTGATCCTGGCTCAG) and 1492R (GGCTACCTTGTTACGACTT) (Sangon, Shanghai, China). The PCR products were examined by 1 % agarose gel electrophoresis, sequenced by Sangon Biotech, and identified by comparison with sequences in the NCBI BLAST database. The isolated strains were mixed with 50 % glycerol at a 1:1 ratio and stored at −80 °C for subsequent use.

Tolerance assays

Acid and bile salt tolerance were evaluated as described by Liu et al. with minor modifications (Liu et al., 2021). All 84 isolated LAB strains were subjected to tolerance testing. After three successive activations, bacterial suspensions were adjusted to an OD₆₀₀ of approximately 1.0 and inoculated at 1 % (v/v) into MRS broth adjusted to pH 2, whereas unadjusted MRS broth served as the control. Following incubation at 37 °C for 3 h, the cultures were serially diluted from 10⁻¹ to 10⁻⁸, and 100 μL aliquots of the 10⁻³ to 10⁻⁸ dilutions were spread onto MRS agar plates. After incubation at 37 °C for 48 h, plates containing 30 to 300 colonies were counted. Acid tolerance was expressed as the survival rate, calculated as follows: survival rate (%) = (viable cell count in the treatment group / viable cell count in the control group) × 100 %.

For the bile salt tolerance assay, MRS broth supplemented with 0.3 % or 0.5 % porcine bile salts (Aladdin, USA) was used, with MRS broth serving as the control. The subsequent experimental procedures were performed as described for the acid tolerance assay above. For the phenol tolerance assay, bacterial suspensions were inoculated into MRS broth containing 0.4 % phenol (Chronchem, Chengdu, China) and incubated at 37 °C for 24 h, after which absorbance was measured at 620 nm (Reuben et al., 2019, 2020).

Assessment of antibacterial activity

Activated LAB cultures were centrifuged at 5000 rpm for 2 min, and the cell-free supernatants (CFSs) were collected. The CFSs were filtered through 0.22 μm syringe filters to remove bacterial cells and stored at 4 °C until use. The CFS of Lactiplantibacillus plantarum NC8 (College of Animal Science and Technology, Jilin Agricultural University) was used as the positive control, with MRS broth serving as the negative control. The indicator strains, Salmonella Typhimurium (S. Typhimurium) ATCC 14028, Salmonella Enteritidis (S. Enteritidis) ATCC 13076, Escherichia coli (E. coli) ATCC 25922, and Staphylococcus aureus (S. aureus) ATCC 43300 (all obtained from the American Type Culture Collection), were subcultured three consecutive times in LB medium. The bacterial suspensions were adjusted to an OD₆₀₀ of approximately 0.5 and spread uniformly onto Mueller-Hinton agar (MHA) plates (Oxoid, UK). Wells approximately 6 mm in diameter were punched into the agar, and 100 μL of each LAB CFS was added to each well. Three replicate wells were prepared for each sample. After diffusion at 4 °C for approximately 3 h, the plates were incubated overnight at 37 °C, and inhibition zone diameters were recorded (Asghar et al., 2016).

Determination of cell surface properties

Activated LAB cultures were centrifuged at 5000 rpm at 4 °C to harvest the cells, washed twice with PBS, and resuspended to a final concentration of 10⁸ CFU/mL. For the auto-aggregation assay, bacterial suspensions were vortexed thoroughly and incubated statically at 37 °C for 3, 6, and 24 h. The absorbance of the upper suspension at OD₆₀₀ was then measured, and the auto-aggregation rate was calculated as follows: auto-aggregation (%) = [1 − (Aₜ/A₀)] × 100 % (Jiang et al., 2023; Qureshi et al., 2020).

For the hydrophobicity assay, 3 mL of bacterial suspension was mixed separately with 1 mL of xylene, ethyl acetate (Chronchem, Chengdu, China), or n-hexadecane (Macklin, Shanghai, China). After vortexing for 2 min, the mixtures were allowed to stand for 10 min to permit phase separation. The OD₆₀₀ of the aqueous phase (A_{10 min}) was measured, and hydrophobicity was calculated as follows: hydrophobicity (%) = [1 − (A_{10 min}/A₀)] × 100 % (Jiang et al., 2023; Qureshi et al., 2020).

For the co-aggregation assay, LAB and each pathogenic strain (S. Enteritidis ATCC 13076, S. Typhimurium ATCC 14028, S. aureus ATCC 43300, and E. coli ATCC 25922) were adjusted separately to an OD₆₀₀ of approximately 0.5 and then mixed at equal volumes. The mixtures were shaken at 200 rpm for 5 min and then incubated statically for 2 h. A 2 mL suspension containing a single bacterial strain was incubated under the same conditions and used as the control group. After incubation, the OD₆₀₀ values of the supernatants were measured. The co-aggregation rate was calculated as follows: co-aggregation = [(A_lab + A_pat)/2] − A_mix] / [(A_lab + A_pat)/2], where A_mix represents the absorbance of the mixed suspension, and A_lab and A_pat represent the absorbance values of the LAB and pathogen suspensions, respectively (Armas et al., 2017; Reuben et al., 2019).

For the ileal adhesion assay, ileal tissues were aseptically collected from healthy chickens, washed with PBS, and treated with PBS containing penicillin-streptomycin (Gibco, USA) for 30 min. The tissues were then cut into pieces of approximately 1 cm² and incubated with LAB suspensions at 10⁸ CFU/mL for 3 h. After incubation, the tissues were washed three times with PBS to remove non-adherent bacteria, homogenized, and plated onto MRS agar, with LAB cultures not subjected to the adhesion assay plated in parallel as the control group. Following incubation at 37 °C for 48 h, viable colonies were counted. The adhesion rate was calculated as follows: adhesion rate (%) = (viable cell count adhering to ileal tissue / viable cell count in the control group) × 100 % (Abbasiliasi et al., 2017; Reuben et al., 2020; Shahbaz et al., 2024).

Safety assessment of LAB

Hemolysis assay: cool MRS agar medium to approximately 40 °C, then add 5 % (v/v) defibrinated sheep blood and mix thoroughly to prepare blood agar plates. Each strain was streaked onto the plates and incubated at 37 °C for 24 h, after which hemolytic activity was examined (Abbasiliasi et al., 2017). Streptococcus suis (S. suis) BNCC357698 (BNCC, Beijing, China), a β-hemolytic strain, was used as the positive control and streaked onto Columbia blood agar plates (CaringBio, China) (Huligere et al., 2022; Zheng et al., 2021).

Antibiotic susceptibility was determined using the Kirby-Bauer disk diffusion method (Chen et al., 2020). Activated bacterial suspensions were adjusted to the 0.5 McFarland standard (approximately 1.5 × 10⁸ CFU/mL) and spread evenly onto MRS agar plates. After the plates had dried, antibiotic disks were applied using an eight-position disk dispenser (Oxoid, UK). The nine antibiotics tested were clindamycin (10 μg), erythromycin (15 μg), cefoxitin (15 μg), penicillin (10 IU), oxacillin (5 μg), florfenicol (30 μg), amoxicillin (10 μg), doxycycline (30 μg), and ampicillin (10 μg) (Liofilchem, Italy). The plates were incubated at 37 °C for 24 h, and inhibition zone diameters were measured. Based on the diameter of the inhibition zone, strains were classified as susceptible (≥21 mm), intermediate (16–20 mm), or resistant (≤15 mm) (Reuben et al., 2020; Zheng et al., 2021).

Whole-genome sequencing and bioinformatics analysis of LAB

Genome DNA extraction, sequencing, quality control, and assembly of isolated strains: LAB strains cultured overnight were centrifuged at 12,000 rpm and 4 °C for 10 min to collect the cells, which were then washed with sterile water. High-quality genomic DNA was extracted from the bacterial cells using a DNA extraction kit (magnetic bead-based; T07-100, China) according to the manufacturer’s instructions. DNA was fragmented to approximately 400 bp using a Covaris M220, followed by library preparation with the NEXTFLEX Rapid DNA-Seq Kit and sequencing on an Illumina NovaSeq 6000 (2 × 150 bp). Raw data were filtered using fastp to obtain high-quality reads, followed by assembly with SPAdes (v4.1.0) and genome quality assessment using CheckM (v1.2.3) (Chen et al., 2018; Parks et al., 2015).

Whole-genome analysis was conducted on 14 LAB isolates to evaluate their safety and functional characteristics. ABRicate (v1.0.1) was used to screen the assembled genomes against its integrated ResFinder, VFDB, and PlasmidFinder databases for the identification of resistance genes, virulence factors, and plasmid-associated sequences. Genome annotation was carried out using Prokka (v1.14.6) and visualized through the Proksee online server (https://proksee.ca); CRISPR-Cas system types were identified using CRISPRCasTyper (v1.6.4). Annotation files were generated using the eggNOG-mapper online server (http://eggnog-mapper.embl.de/), and COG, GO, and KEGG classifications were analyzed with TBtools-II (v2.341). CAZymes were analyzed using the dbCAN3 online tool (https://bcb.unl.edu/dbCAN2/index.php). Phylogenetic analysis was performed using the TYGS online server (https://tygs.dsmz.de) to generate initial phylogenetic trees, and the FastME 2.1.6.1 software was used to construct a balanced minimum evolution tree with 100 bootstrap replicates. The resulting Newick tree was visualized, with species/subspecies highlighted. ANI values were calculated using the JSpecies online platform (https://jspecies.ribohost.com/jspeciesws/). Genes associated with probiotic functions were identified through Prokka annotation. The BAGEL 4 online platform (http://bagel4.molgenrug.nl/) was used for the prediction and analysis of antimicrobial peptide and ribosomally synthesized and post-translationally modified peptides (RiPPs) gene clusters.

Animal experiment design

Seventy-two one-day-old Hy-Line Brown chicks were randomly assigned to one of four groups: a control group, the AGP group (Bacitracin methylene disalicylate, BMD), an L16 group, and an L20 group, with three replicates per group and six chicks per replicate. No significant differences in initial body weight were observed between the groups. The control group was fed a basal diet; the AGP group received 0.05 g of BMD per kilogram of basal diet (Gulizia et al., 2024; Oladokun and Adewole, 2023); the L16 and L20 groups received 10⁹ CFU of the L16 or L20 strain per kilogram of basal diet (Cui et al., 2024), respectively. The chicks were housed in cages with ad libitum access to feed and water. The experimental period lasted for 42 days (Chai et al., 2023; Zhang et al., 2025a), during which the general health and mental state of the chicks were monitored daily.

Measurement of growth performance and immune organ indices

Growth performance assessment: body weight of the chicks in each treatment group was recorded weekly after a 12 h fasting period, and feed consumption was measured weekly during the experimental period. The average daily feed intake (ADFI), average daily gain (ADG), and feed conversion ratio (FCR) were calculated for days 1–21 and 22–42, with FCR calculated as ADFI/ADG (Zhang et al., 2025a).

Immune organ index determination: on days 21 and 42, six chicks from each treatment group were randomly selected, weighed, anesthetized, and euthanized. The internal organs were examined for gross lesions, and the organ indices of the spleen, thymus, and bursa of Fabricius (BF) were calculated using the formula: organ index = [organ weight (g) / pre-slaughter body weight (g)] × 100 (Melese et al., 2025).

Effects of L. reuteri supplementation on the intestinal health of chicks

Intestinal morphology analysis: on days 21 and 42 of the feeding period, jejunal tissue samples were collected and fixed in 4 % paraformaldehyde. The samples were then dehydrated using an automated tissue processor, embedded in paraffin, and stained with hematoxylin and eosin (H&E) (Li and Fu, 2024). Sections were examined using a digital trinocular camera microscope (BA210 Digital, Motic Industrial Group Co., Ltd.) to measure villus height (VH) and crypt depth (CD).

Real-time quantitative PCR analysis: total RNA was extracted from jejunal tissue using TRIzol reagent, and cDNA was synthesized using All-In-One 5X RT MasterMix (abm, Canada). Genomic DNA was removed using gDNA Eraser (Beyotime, Shanghai, China). RT-qPCR was performed using SYBR qPCR Master Mix (Vazyme, Nanjing, China) on a Bio-Rad real-time PCR system (USA). The reaction was initiated with an initial denaturation at 95 °C for 30 s, followed by 40 cycles (each consisting of denaturation at 95 °C for 10 s and annealing/extension at 60 °C for 30 s). Finally, the melting curve was collected using the instrument’s default settings. Each sample was tested in quadruplicate, with GAPDH as the internal control. Relative mRNA expression levels were calculated using the 2^⁻ΔΔCt method. Primer sequences were designed using Primer-BLAST, and the specific sequences are provided in supplementary Table S.1.

16S rRNA gene amplicon sequencing: on day 42 of the experiment, three chicks per group were randomly selected for cecal content collection. Genomic DNA was extracted using the TIANamp Stool DNA Kit (TIANGEN, China) and quantified using a Nanodrop spectrophotometer. The V3-V4 hypervariable regions of the bacterial 16S rRNA gene were amplified using the primers 338F (5′-ACTCCTACGGGAGGCAGCA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) and subjected to paired-end sequencing on the Illumina NovaSeq-PE250 platform. Raw data were processed using the DADA2 plugin in QIIME 2 (v2024.5) for quality control, denoising, paired-end read merging, and Amplicon Sequence Variant (ASV) identification. Taxonomic information was obtained through database alignment. Low-abundance ASVs were removed, and subsequent analyses, including species composition, alpha diversity, and PCoA-based beta diversity visualization, were conducted based on the resulting abundance matrix. Differences in community structure between groups were assessed using PERMANOVA (Adonis), and linear discriminant analysis effect size (LEfSe) analysis was performed to identify differentially abundant taxa.

Statistical analysis

Data are presented as mean ± standard deviation (SD). Statistical analyses were performed using GraphPad Prism (v10.3.1), R (v4.3.3), and IBM SPSS Statistics (v27.0.1). A P-value < 0.05 was considered statistically significant.

Results

Isolation and identification of LAB strains

Eighty-four LAB strains were isolated in this study and designated L1-L84. The isolation profiles and 16S rRNA gene-based identification results are shown in Fig. 1A and B, respectively. After purification, the isolates formed smooth, milky-white colonies. On MRS agar containing 2 % CaCO₃, distinct clear zones were observed around the colonies. Microscopic examination after Gram staining revealed that all isolates were Gram-positive, with rod-shaped or coccoid cells. Representative colony morphology and Gram-stained cell morphology are presented in Fig. 1C.

Fig. 1.

Isolation and identification of LAB strains. (A) Species distribution of the 84 isolated LAB strains. (B) PCR amplification of the 16S rRNA gene in selected strains. (C) Colony morphology of selected LAB strains on MRS agar and representative Gram-stained microscopic images. The red arrow in the leftmost panel indicates a clear zone formed by the isolate on MRS agar supplemented with 2 % CaCO₃.

Tolerance to simulated gastrointestinal conditions

As shown in Fig. 2A, acid tolerance was evaluated in 84 isolates, among which 24 strains showed survival rates above 3 %. L23 exhibited the highest survival rate (20.87 %), with no significant difference compared with L26, L14, L39, L13, L35, L76, L16, L63, or L3 (P > 0.05). However, its survival rate was significantly higher than those of L5, L54, L84, L8, L25, L80, L2, L15, and L79 (P < 0.05), and higher than those of L56, L20, L50, L82, and L64 (P < 0.01).

Fig. 2.

Tolerance and antimicrobial activity of LAB. (A) Survival of LAB in MRS medium at pH 2, with strain L23 as the reference. (B) Survival of LAB in MRS medium supplemented with 0.4 % phenol, with strain L50 as the reference. (C) Survival of LAB in MRS medium supplemented with 0.3 % and 0.5 % porcine bile salts, with strain L26 as the reference. (D–G) Antimicrobial activity of LAB against S. Enteritidis ATCC 13076, S. Typhimurium ATCC 14028, S. aureus ATCC 43300, and E. coli ATCC 25922. Data are shown as mean ± SD (n = 3). Statistical analyses were performed using ordinary one-way ANOVA for panels (A) and (B) and two-way ANOVA for panel (C), followed by Dunnett’s or Tukey’s multiple comparisons test, respectively, as appropriate. Ns indicates no significant difference; * P < 0.05, ** P < 0.01, *** P < 0.001 and **** P < 0.0001.

Because L13, L14, and L15 showed poor stability during subculturing, they were excluded from subsequent analysis. The remaining 21 isolates were tested for bile salt tolerance (Fig. 2C). Fourteen strains survived in MRS broth containing both 0.3 % and 0.5 % porcine bile salts. Of these, L26, L2, L5, L76, L3, L56, L39, and L16 showed survival rates above 10 % at 0.3 % bile salts, whereas L3, L39, L5, L26, L76, L56, and L80 maintained survival rates above 5 % at 0.5 % bile salts.

As shown in Fig. 2B, in MRS broth containing 0.4 % phenol, strains L50, L16, L76, L56, and L20 exhibited relatively high tolerance, with no significant difference observed between L50 and L16 (P > 0.05). In contrast, strains L5, L80, L39, and L35 showed relatively poor tolerance and differed significantly from L50 (P < 0.0001).

Antimicrobial activity

The antimicrobial activities of the LAB isolates against the tested pathogens are presented in Fig. 2D–G and supplementary Fig. S.1. NC8 (14.38 ± 0.08 mm) and L35 (13.75 ± 0.70 mm) showed the strongest inhibition against S. Enteritidis ATCC 13076. Most isolates also inhibited E. coli ATCC 25922, among which L35 (14.63 ± 0.87 mm) and NC8 (13.85 ± 0.36 mm) exhibited the largest inhibition zones. Against S. aureus ATCC 43300, the strongest inhibitory activity was observed for NC8 (16.52 ± 0.70 mm) and L80 (15.50 ± 0.64 mm). By contrast, inhibitory activity against S. Typhimurium ATCC 14028 was limited, with only L2 (12.15 ± 1.05 mm) and NC8 (10.39 ± 0.62 mm) showing measurable inhibition.

Determination of cell surface properties

Auto-aggregation results are shown in Fig. 3A. After 3 h, strains L3, L2, L20, L80, L5, L50, L16, L76, and L56 exhibited significantly higher auto-aggregation rates than the other five strains (P < 0.05). After 6 h, L5 showed a significantly higher auto-aggregation rate than L25, L26, L35, and L39 (P < 0.0001). After 24 h, all strains except L39, L26, and L35 reached auto-aggregation rates above 80 %, with L20 showing the highest value. Overall, L26, L35, and L39 exhibited relatively weak auto-aggregation ability.

Fig. 3.

Evaluation of cell surface properties and safety of LAB. (A) Auto-aggregation ability of LAB after 3, 6, and 24 h of static incubation. Statistical significance was assessed relative to strain L2 at 3 and 24 h and relative to strain L5 at 6 h; (B) Cell surface hydrophobicity of LAB assessed using n-hexadecane, ethyl acetate, and xylene, with statistical significance determined relative to strain L2. (C) Adhesion of LAB strains to ileal tissue, with statistical significance determined relative to strain L2. (D) Hemolytic activity of LAB. Data are shown as mean ± SD (n = 3). Statistical analyses for panels (A–C) were performed using ordinary one-way ANOVA followed by Dunnett’s multiple comparisons test. Ns indicates no significant difference; *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

As shown in Fig. 3B, L2 and L20 displayed the highest hydrophobicity in n-hexadecane (P < 0.0001), whereas L5, L80, and L25 showed the lowest values. In ethyl acetate, L20, L2, and L26 exhibited significantly higher hydrophobicity than the other strains (P < 0.0001), with L25 showing the lowest value. In xylene, hydrophobicity values exceeded 80 % in L20, L2, L76, L16, L35, L26, and L50, whereas those of L8, L25, L80, and L5 were below 10 % and significantly lower than those of the remaining strains (P < 0.001). Overall, L2 and L20 showed the strongest hydrophobicity toward the tested organic solvents.

Co-aggregation results are summarized in Table 1. After 2 h of co-incubation, L20 showed the highest co-aggregation rate with S. Typhimurium ATCC 14028. For S. Enteritidis, L50 and L20 did not differ significantly from each other (P > 0.05), but both showed significantly higher co-aggregation rates than the remaining strains (P < 0.05). L3 showed the highest co-aggregation rate with E. coli (P < 0.05). Against S. aureus, L3, L5, L20, and L80 all exhibited co-aggregation rates above 40 %, significantly higher than those of the other strains (P < 0.05). Taken together, L20 exhibited the strongest co-aggregation ability with the tested pathogens.

Table 1.

Co-aggregation experiments between LAB and pathogenic bacteria.

Indicator strain	S. Typhimurium ATCC 14028	S. Enteritidis ATCC 13076	E. coli ATCC 25922	S. aureus ATCC 43300
L2	8.00 ± 0.29c	6.63 ± 0.25ef	3.21 ± 1.94gh	29.80 ± 0.60def
L3	13.97 ± 0.93bc	10.22 ± 1.21bc	26.29 ± 6.04a	47.85 ± 2.73a
L5	14.04 ± 2.69bc	7.19 ± 0.44de	14.35 ± 6.46b	46.30 ± 5.78ab
L8	19.07 ± 0.52b	6.53 ± 0.19ef	12.76 ± 2.53bcd	33.29 ± 0.71cd
L16	19.67 ± 0.93b	4.01 ± 2.91gh	9.86 ± 0.92cdef	32.38 ± 1.09de
L20	30.07 ± 16.66a	16.14 ± 2.56a	8.85 ± 0.33def	43.11 ± 1.64b
L25	19.16 ± 5.97b	8.91 ± 1.08cd	9.00 ± 1.85def	28.32 ± 0.30ef
L26	14.80 ± 5.90bc	4.63 ± 2.79fgh	2.00 ± 1.38h	21.82 ± 3.44g
L35	19.63 ± 1.55b	11.23 ± 0.85b	6.30 ± 1.24fg	31.24 ± 0.18de
L39	10.83 ± 0.11bc	9.64 ± 0.73bc	11.55 ± 0.62bcde	33.51 ± 0.53cd
L50	12.73 ± 2.55bc	14.35 ± 0.36a	13.37 ± 1.07bc	36.86 ± 2.74c
L56	7.39 ± 1.43c	1.01 ± 0.09i	3.47 ± 2.55gh	25.98 ± 1.02f
L76	15.23 ± 0.59bc	9.02 ± 0.98cd	12.91 ± 0.65bcd	32.05 ± 0.63de
L80	8.87 ± 1.80c	3.46 ± 0.70h	2.43 ± 0.37gh	43.01 ± 6.70b
NC8	12.56 ± 3.38bc	5.69 ± 0.80efg	8.02 ± 1.52ef	29.70 ± 0.43def

Note: ^(a-i)Significant differences (P < 0.05) among all bacteria strains tested at same time. The data are expressed as the mean ± SD (n = 3).

Adhesion to chicken ileal tissue is shown in Fig. 3C. L80 (17.03 % ± 2.31 %) and L3 (15.99 % ± 3.43 %) exhibited the strongest adhesion, followed by L16 (11.38 % ± 2.51 %), L5 (11.13 % ± 0.91 %), and L20 (10.22 % ± 3.67 %). The other strains showed comparatively weak adhesion.

In vitro safety evaluation of LAB

As shown in Fig. 3D, S. suis BNCC 357698 produced a clear hemolytic zone, indicating β-hemolysis, whereas none of the 14 LAB isolates showed hemolytic zones, indicating γ-hemolysis. These results demonstrate that all 14 LAB isolates were non-hemolytic.

Antimicrobial susceptibility results are presented in Table 2. All isolates were susceptible to florfenicol; 93 % were susceptible to penicillin and amoxicillin, 86 % to clindamycin, doxycycline, and ampicillin, 79 % to erythromycin, 21 % to cefoxitin, and 14 % to oxacillin.

Table 2.

Antibiotic sensitivity test results.

Strain	CD	E	FOX	P	OX	FFC	AML	DXT	AMP
L2	S	S	R	S	R	S	S	S	S
L3	S	S	S	S	S	S	S	S	S
L5	S	S	I	S	R	S	S	S	I
L8	S	S	R	R	R	S	I	S	S
L16	S	S	R	S	R	S	S	S	S
L20	S	S	R	S	R	S	S	S	S
L25	S	I	I	S	R	S	S	S	S
L26	I	I	I	S	R	S	S	R	S
L35	S	S	S	S	S	S	S	R	S
L39	I	S	I	S	R	S	S	S	S
L50	S	I	I	S	R	S	S	S	S
L56	S	S	I	S	I	S	S	S	S
L76	S	S	S	S	I	S	S	S	S
L80	S	S	R	S	R	S	S	S	I

Note: CD=Clindamycin, E=Erythromycin, FOX=Cefoxitin, P=Penicillin, OX=Oxacillin, FFC=Florfenicol, AML=Florfenicol, DXT=Doxycycline, AMP=Ampicillin. *R= Resistance, I=Intermediate, S=Sensitive.

Bioinformatic analysis of LAB genomes

Analysis of safety-related genes: clean reads from the 14 LAB strains were assembled using SPAdes (v4.1.0), and resistance genes were predicted with ABRicate (v1.0.1) against the ResFinder database. L2 carried the lincosamide resistance gene lnuC (identity = 98.99 %), whereas L26 and L35 both carried the tetracycline resistance gene tetW (identity = 98.12 % and 97.86 %, respectively). The predicted genotypes of L26 and L35 were consistent with their doxycycline-resistant phenotypes (Table 2). No virulence genes were detected in any of the strains based on screening against the VFDB database. PlasmidFinder analysis (identity ≥ 80 %) further suggested the presence of plasmid-associated sequences in L2, L3, L5, L56, L76, and L80. Given the potential role of plasmids in the dissemination of resistance and virulence determinants, as well as their possible impact on genetic stability, strains lacking plasmid-associated sequences may be preferable for probiotic development (Disastra et al., 2025).

General genomic features: based on the combined evaluation of probiotic traits and safety-related genes, L16 and L20 were selected for further study. Prokka annotation (v1.14.6) showed that the L16 genome comprised 2,208,400 bp and contained 2,198 predicted coding sequences, with a G+C content of 38.53 %. The L20 genome comprised 2,064,081 bp and contained 1,969 coding sequences, with a G+C content of 38.83 %. L16 contained 74 tRNAs, 1 tmRNA, and six copies each of 23S, 5S, and 16S rRNA genes, whereas L20 contained 71 tRNAs, 1 tmRNA, and six copies each of 23S, 5S, and 16S rRNA genes. CRISPRCasTyper analysis (v1.6.4) identified two CRISPR-Cas systems in L16, assigned to subtypes II-A and III-A, with subtype probabilities of 96.4 % and 46.4 %, respectively. In contrast, L20 harbored a single type I-B CRISPR-Cas system with a subtype probability of 99.7 %. The genomic features of L16 and L20 are presented in Fig. 4A.

Fig. 4.

Genomic features and functional annotation of LAB strains L16 and L20. (A) Circular maps of the genomes of L16 and L20. (B) COG functional classification of the genomes of L16 and L20. (C) KEGG pathway classification of the genomes of L16 and L20. (D) GO functional classification of the genomes of L16 and L20. (E) CAZy annotation classification of the genomes of L16 and L20.

Functional annotation and genomic analysis: the COG database classifies homologous proteins into 26 functional categories (Galperin et al., 2015). COG annotation showed that genes in both L16 and L20 were mainly assigned to functions related to information storage and processing, metabolism, and cellular processes and signaling, with genes involved in amino acid, nucleotide, and carbohydrate transport and metabolism, as well as cell wall/membrane/envelope biogenesis, being particularly abundant (Fig. 4B). The KEGG database is used to analyze genes and metabolic pathways (Kanehisa et al., 2006). KEGG annotation further indicated that genes in both strains were predominantly enriched in metabolism, followed by genetic information processing and environmental information processing, with substantial representation of carbohydrate, amino acid, and nucleotide metabolism, as well as membrane transport (Fig. 4C). GO annotation classifies gene functions into three categories: cellular components, molecular functions, and biological processes (Ashburner et al., 2000). GO annotation revealed that most genes were associated with biological processes and were mainly related to metabolic processes, catalytic activity, cellular process, and binding (Fig. 4D). The CAZy database is used for the classification and annotation of carbohydrate-active enzymes (Cantarel et al., 2009). CAZy analysis showed that both strains encoded glycosyltransferases (GTs), glycoside hydrolases (GHs), and carbohydrate-binding modules (CBMs), suggesting that they may be capable of degrading and utilizing complex carbohydrates and may thereby promote host digestion and nutrient absorption (Fig. 4E).

ANI analysis and phylogenetic reconstruction: ANI values above 95 % are widely accepted as the species boundary for bacteria (Jain et al., 2018). As shown in Fig. 5A, L16 and L20 shared an ANI value of 97 % with each other, and both strains also exhibited ANI values above 95 % with L. reuteri subsp. porcinus 3c6T, L. reuteri subsp. murium lpuph1T, and L. reuteri JCM 1112. Whole-genome phylogenetic analysis based on TYGS further showed that L16 and L20 clustered with L. reuteri subsp. porcinus 3c6T. These results identified both L16 and L20 as L. reuteri.

Fig. 5.

Average nucleotide identity (ANI) analysis, phylogenetic reconstruction, and areas of interest (AOIs) prediction of LAB strains L16 and L20. (A) The left panel shows ANI values between L16, L20, and reference strains, and the right panel shows the whole-genome-based phylogenetic tree of L16 and L20. (B) Predicted AOIs in the genomes of L16 and L20.

Identification of genes associated with probiotic traits: identifying functional genes in the genome based on probiotic properties helps clarify their probiotic mechanisms. As shown in Table 3, both L16 and L20 harbored genes associated with acid tolerance, bile salt tolerance, cholesterol assimilation, antioxidant activity, antimicrobial activity, adhesion, and biofilm formation. These genes may contribute to survival under gastrointestinal stress, intestinal colonization, cholesterol reduction, reactive oxygen species scavenging, and sustained antagonism against pathogens, indicating broad probiotic potential.

Table 3.

Common genes associated with probiotic traits in the genomes of L16 and L20.

Gene name	Gene annotation	UniProtKB
Acid and bile resistance/cholesterl assimilation
gadC	Glutamate/gamma-aminobutyrate antiporter	O30417
yhdG	amino acid permease	O07576
clpE	ATP-dependent Clp protease	Q9S5Z2
dps	DNA protection during starvation protein	Q9KWH3
nhaC	Na(+)/H(+) antiporter	O07553
napA	Na(+)/H(+) antiporter	P26235
dltD	D-alanyl-lipoteichoic acid biosynthesis protein	Q2FZW3
dnaK	Chaperone protein	O87777
grpE	nucleotide exchange factor GrpE	Q97S73
adhA	alcohol dehydrogenase AdhA	P9WQC1
adhE	Aldehyde-alcohol dehydrogenase	P0A9Q7
aldC	Alpha-acetolactate decarboxylase	Q8L208
pyk	Pyruvate kinase	P34038
cbh	Choloylglycine hydrolase	Q06115
arcC	Carbamate kinase	P13982
Oxidative stress resistance
oxyR	Hydrogen peroxide-inducible genes activator	P0ACQ4
perR	Peroxide-responsive repressor PerR	Q2G282
spxA	Regulatory protein Spx	O31602
trxA	Thioredoxin	P14949
trxB	Thioredoxin reductase	P80880
msrA	Peptide methionine sulfoxide reductase MsrA	P54154
clpP	ATP-dependent Clp protease proteolytic subunit	Q9RQI6
nox	NADH oxidase	P37061
nrdH	Glutaredoxin-like protein NrdH	Q48708
Anti-pathogenic effect
luxS	S-ribosylhomocysteine lyase	Q9RRU8
map	Methionine aminopeptidase 1	P19994
Adhesion-related
ltas	Lipoteichoic acid synthase	Q7A1I3
lspA	Lipoprotein signal peptidase	Q9HVM5
epsD	glycosyltransferase EpsD	P71053
nagB	Glucosamine-6-phosphate deaminase	Q8DV70
Biofilm formation/persistence
msrB	Peptide methionine sulfoxide reductase MsrB	E6ESW1
clpC	ATP-dependent Clp protease ATP-binding subunit ClpC	Q7A797
luxS	S-ribosylhomocysteine lyase	Q9RRU8
cpdA	3′,5′-cyclic adenosine monophosphate phosphodiesterase CpdA	D4P095
bmr3	Multidrug resistance protein 3	P96712
copA	Copper-exporting P-type ATPase	Q2FV64
gtfA	UDP-N-acetylglucosamine–peptide N-acetylglucosaminyltransferase GtfA subunit	Q9AET5

Bacteriocins and RiPP gene clusters were further predicted in the genomes of L16 and L20 using BAGEL 4. As shown in Fig. 5B, four potential areas of interest (AOIs) were identified in L16, including three Enterolysin A (EnlA)-like regions and one sactipeptide-related region, with core peptide similarity values of 31.579 %, 36.646 %, 37.013 %, and 66.225 %, respectively. In L20, two AOIs were predicted, including one Enterolysin A-like region and one sactipeptide-related region, with core peptide similarity values of 39.041 % and 66.867 %, respectively.

Dietary supplementation with L. reuteri improves growth performance and immune organ indices in Hy-Line Brown chicks

Throughout the experiment, birds remained healthy with normal feed and water intake. From day 1 to 21, the L16 group exhibited significantly higher body weight than the L20 (P < 0.01) and control groups (P < 0.05), along with increased ADG (vs. L20, P < 0.05) and reduced FCR (vs. L20, P < 0.01). From day 22 to 42, L16 maintained significantly greater body weight than both L20 and control groups (P < 0.0001), and higher ADG than L20 (P < 0.05), while no differences were observed in ADFI or FCR among groups (Fig. 6A–D). These findings indicate that L16 was more effective in promoting body weight gain and improving feed efficiency.

Fig. 6.

Effects of L. reuteri supplementation on growth performance and immune organ indices in Hy-Line Brown chicks. (A-D) Growth performance, including body weight (BW), average daily feed intake (ADFI), average daily gain (ADG), and feed conversion ratio (FCR), during days 1–21 and 22–42. (E, F) Immune organ indices, including the spleen, bursa of Fabricius (BF), and thymus, on days 21 and 42, respectively. Data are presented as mean ± SD. Statistical analyses were performed using two-way ANOVA, with treatment group and time as the two factors, followed by Tukey’s multiple-comparisons test. Sample sizes were as follows: n = 9 for BW (A), n = 3 for ADFI (B), ADG (C), and FCR (D), and n = 6 for immune organ indices (E–F). The absence of significance labels indicates no statistically significant difference. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001 indicate increasing levels of significance.

Necropsies performed after euthanasia on days 21 and 42 revealed no obvious lesions in any organs. At day 21, the thymus index was significantly higher in the L16 group than in the control group (P < 0.01). At day 42, the BF index was significantly higher in the L16 group than in the other three groups (P < 0.01) (Fig. 6E–F). These findings suggest that L16 promoted the development of immune organs, particularly the thymus and BF.

Effects of L. reuteri supplementation on intestinal parameters in chicks

Jejunal morphology was assessed in chicks at 21 and 42 days of age. At day 21, no significant differences in jejunal villus height (VH) or crypt depth (CD) were observed among the four groups (P > 0.05). At day 42, VH was significantly higher in the BMD and L16 groups than in the L20 and control groups (P < 0.05), and the VH/CD ratio showed the same trend (P < 0.05), whereas CD did not differ significantly among groups (P > 0.05) (Fig. 7H–N). These findings indicate functional differences among L. reuteri strains, with L16 showing a stronger ability to promote jejunal development and improve intestinal morphology associated with nutrient absorption.

Fig. 7.

Effects of L. reuteri supplementation on jejunal mucosal development and absorption-related morphological parameters in Hy-Line Brown chicks. (A-C, H-J) Jejunal VH, CD, and VH/CD in different groups at 21 and 42 days of age. (D-G, K-N) Jejunal epithelial morphology of chicks in the BMD, L16, L20, and control groups (from left to right) at 21 and 42 days of age, respectively. Statistical analyses for panels (A-C) and (H-J) were performed using ordinary one-way ANOVA followed by Dunnett’s multiple comparisons test. The absence of significance labels indicates no statistically significant difference; data are presented as mean ± SD (n = 6), with *P < 0.05, **P < 0.01 indicating increasing levels of significance.

RT-qPCR analysis of jejunal samples after 42 days of supplementation showed that, compared with the control group, the L16 group exhibited significantly higher relative mRNA expression of Occludin (P < 0.01) and ZO-1 (P < 0.05) (Fig. 8B, C), whereas Claudin-1 expression did not differ significantly among groups (P > 0.05) (Fig. 8A). Among the cytokine genes associated with pro-inflammatory responses and immune activation, the relative mRNA expression of IFN-γ was significantly lower in the L16 group than in the control group (P < 0.05) (Fig. 8D), and the relative mRNA expression of IL-6 was significantly lower in the L16 group than in the L20 group (P < 0.05) (Fig. 8H). No significant differences were observed in IL-12B, IL-1β, or IL-2 expression among the groups (P > 0.05) (Fig. 8E–G). In addition, IL-10 expression was significantly upregulated in both the BMD and L16 groups (P < 0.05) (Fig. 8I). Together, these results indicate that L16 more effectively improved jejunal barrier function and mucosal homeostasis by enhancing tight junction-related gene expression and anti-inflammatory responses.

Fig. 8.

Effects of L. reuteri supplementation on jejunal gene expression in 42-day-old chicks. (A–C) Intestinal barrier-related genes. (D–H) Pro-inflammatory and immune activation-related cytokine genes. (I) Anti-inflammatory cytokine gene. Statistical analyses for all panels were performed using ordinary one-way ANOVA followed by Dunnett’s multiple comparisons test. Data are presented as mean ± SD (n = 3), with *P < 0.05, **P < 0.01 indicating increasing levels of significance.

L. reuteri supplementation alters the cecal microbial community structure in chicks

To assess the effects of L. reuteri L16 and L20 on the gut microbiota of Hy-Line Brown chicks, 16S rRNA gene amplicon sequencing was performed on cecal contents. Fig. 9C shows that 342 ASVs were shared across all four groups, whereas the numbers of group-specific ASVs were 2,206, 1,910, 1,740, and 2,114 in the BMD, L16, L20, and control groups, respectively. The BMD group contained the highest number of unique ASVs, whereas L16 and L20 induced comparatively modest changes in community composition. Notably, the L16 group harbored more unique ASVs than the L20 group, suggesting a stronger modulatory effect on the cecal microbiota.

Fig. 9.

Effects of L. reuteri supplementation on the cecal microbiota of Hy-Line Brown chicks at 42 days of age. (A) Phylum-level microbial composition. (B) Genus-level microbial composition. (C) Venn diagram showing ASV distribution in the cecal microbiota. (D) Differentially abundant taxa identified by LEfSe analysis (LDA score > 2, P < 0.05). (E) Principal coordinates analysis (PCoA). (F) Alpha diversity analysis. Data are presented as the mean ± SD (n = 3). Statistical comparisons of alpha diversity indices were performed using the Kruskal-Wallis test followed by Dunn’s post hoc test. P < 0.05 was considered statistically significant.

At the phylum level, the cecal microbiota was dominated by Bacillota, Bacteroidota, and Pseudomonadota (Fig. 9A). Compared with the control group, the relative abundance of Bacillota was significantly increased in the BMD group (P < 0.05), whereas an increasing trend was observed in the L16 group (P = 0.0781). In parallel, the relative abundance of Bacteroidota was significantly reduced in the BMD group (P < 0.05) and showed a decreasing trend in the L16 group (P = 0.0736), whereas no significant change was observed in the L20 group (P = 0.9996).

At the genus level, the control and L20 groups showed relatively higher abundances of Clostridium, Cytophaga, Blautia, and Hungatella (Fig. 9B). Both BMD (P < 0.0001) and L16 (P < 0.05) significantly reduced the abundance of Cytophaga. Blautia abundance showed a slight decrease in the L16 (P = 0.5542) and L20 (P = 0.1633) groups, whereas BMD significantly reduced Blautia abundance (P = 0.0012) and significantly increased Hungatella abundance (P < 0.0001). LEfSe analysis (Fig. 9D) identified differentially abundant taxa among the four groups (LDA score > 2). The control group was enriched in Clostridium perfringens (C. perfringens) and Lentilactobacillus hilgardii, whereas the BMD group was enriched in anaerobic taxa such as Hungatella hathewayi and Neglectibacter timonensis. The L16 group was enriched in Luoshenia tenuis (L. tenuis) and Levilactobacillus brevis (L. brevis), suggesting that L16 supplementation selectively promoted LAB-related and potentially beneficial gut-associated taxa. In contrast, the enrichment of Agathobaculum massiliense in the L20 group suggests that L20 supplementation altered the cecal microbiota in a manner distinct from that of the other treatments.

Alpha diversity analysis revealed limited overall effects of the treatments on cecal microbial richness and diversity (Fig. 9F). The Simpson index (P = 0.04) and Pielou’s evenness index (P = 0.029) indices were higher in the BMD group than in the L20 group, whereas the other α-diversity indices were similar across groups. PCoA showed clear separation of the BMD group from the other groups, while the L16 and L20 groups exhibited only modest shifts in community composition (Fig. 9E).

Discussion

LAB are widely used as biotherapeutic agents because of their diverse health-promoting effects in animals (Al-Khalaifa et al., 2019). They play important roles in maintaining gut microbial homeostasis, modulating host immunity, and improving overall host health (Ye et al., 2020; Zheng et al., 2021). With increasing consumer demand for safer and higher-quality livestock and poultry products, the application of LAB for improving animal health and production performance has attracted considerable attention (Aristimuno Ficoseco et al., 2018). In the AGP control used in this study, BMD is a commonly used antibiotic growth promoter that primarily interferes with bacterial cell wall synthesis, exhibits greater activity against Gram-positive bacteria, and contributes to the maintenance of intestinal homeostasis (Rivera-Pérez et al., 2021). However, residues of BMD can be found not only in animal-derived food products but also in animal excreta, thereby increasing the risk of horizontal transfer of antibiotic resistance genes among soil microorganisms (Krysiak et al., 2021; Zhang et al., 2022). In recent years, probiotics have been increasingly investigated as alternatives to AGPs in livestock production, both for controlling bacterial infections and for promoting growth performance (Abd El-Hack et al., 2020).

Tolerance to gastric acid and bile salts is essential for probiotic survival during gastrointestinal transit (Noguchi et al., 2022; Venema et al., 2019). Gastric pH generally ranges from 2.0 to 3.5 depending on age, breed, and feeding status (Reuben et al., 2019). In the present study, 24 LAB isolates remained viable after exposure to pH 2 for 3 h, and 10 of these showed survival rates above 10 %, consistent with previous reports (Blajman et al., 2015; Garcia-Hernandez et al., 2016). Given that bile salt concentrations in the chicken duodenum and cecum are approximately 0.175 % and 0.008 %, respectively (Lin et al., 2003; Reuben et al., 2019), bile tolerance was assessed at 0.3 % and 0.5 %. Fourteen isolates survived under both conditions and were therefore retained for further characterization. Phenol, a toxic metabolite generated by amino acid deamination in the gastrointestinal tract, can further challenge bacterial survival (Reuben et al., 2020; Sathyabama et al., 2012). All 14 selected isolates remained viable after 24 h in MRS medium containing 0.4 % phenol, and strains L50, L16, L76, L56, and L20 showed OD₆₀₀ values above 1, indicating relatively strong phenol tolerance.

Because probiotic traits are highly strain-dependent, the 14 selected isolates were further evaluated for antimicrobial activity, surface characteristics, adhesion, and safety. As natural biopreservatives, LAB can produce antimicrobial metabolites during fermentation, including organic acids, bacteriocins, and hydrogen peroxide (Mokoena et al., 2021). Because Escherichia coli, Salmonella spp., and Staphylococcus aureus are among the most common pathogens in poultry (Kathayat et al., 2022), the present study investigated the inhibitory activity of LAB against these pathogens. In the present study, the isolates showed the weakest inhibitory activity against S. Typhimurium, but varying degrees of inhibition against S. Enteritidis, S. aureus, and E. coli. Whole-genome sequencing and phylogenetic analysis showed that all strains except L5 and L80 belonged to L. reuteri, whereas L5 and L80 were identified as Pediococcus acidilactici (P. acidilactici). Wishna-Kadawarage et al. reported that L. reuteri produces relatively low levels of lactic acid and formic acid, two metabolites considered major contributors to anti-S. Typhimurium activity, which may partly explain the weak inhibition observed here (Wishna-Kadawarage et al., 2024). However, Zhang et al. reported that L. reuteri isolated from laying hens exhibited strong activity against S. Typhimurium (Zhang et al., 2025b). In addition, Jazi et al. found that dietary supplementation with P. acidilactici, which can produce lactic acid and bacteriocins, reduced cecal colonization of S. Typhimurium in challenged broilers, although this effect was less pronounced than that achieved by combined supplementation with P. acidilactici, mannan oligosaccharides, and butyrate (Jazi et al., 2018). Collectively, these findings indicate that the antagonistic activity of LAB against pathogens is highly strain-specific and may be closely associated with strain origin, metabolite composition, and environmental context.

Auto-aggregation is thought to facilitate colonization and persistence in the gastrointestinal tract (Wang et al., 2024), and L20 showed the highest auto-aggregation rate among the tested strains. Surface hydrophobicity is also commonly used as an indicator of adhesion potential, and Pringsulaka et al. suggested that hydrophobicity toward n-hexadecane of at least 40 % may serve as a useful probiotic screening criterion (Pringsulaka et al., 2015). In the present study, L2, L3, L16, L20, and L50 met this criterion. Co-aggregation may further help restrict pathogen colonization in the intestine (Zhang et al., 2025b), and the relatively strong co-aggregation of these isolates with S. aureus suggests a potential role in limiting colonization by this pathogen. Consistently, adhesion assays using chicken ileal tissue showed that L80, L3, L5, L16, and L20 adhered more strongly than the other isolates.

Safety is a prerequisite for probiotic applications. According to FAO guidelines, probiotic strains should not pose a risk to the host (Shahbaz et al., 2024). None of the 14 LAB isolates showed hemolytic activity. In addition, combined analysis using VFDB, ResFinder, and PlasmidFinder showed that L8, L16, L20, L25, L39, and L50 lacked detectable virulence genes, resistance genes, and plasmid-associated sequences, indicating favorable safety profiles. Antimicrobial susceptibility testing further showed that most strains were resistant to cefoxitin and oxacillin but remained susceptible to the other tested antibiotics. This pattern may reflect intrinsic resistance mechanisms, including broad-spectrum β-lactamases, nonspecific multidrug efflux systems, and low cell wall permeability (Duche et al., 2023).

Based on phenotypic performance and safety-related genomic analysis, L16 and L20 were selected for further investigation. Functional annotation using COG, KEGG, GO, and CAZy indicated that both strains were enriched in genes related to carbohydrate, amino acid, and nucleotide metabolism, as well as translation and membrane transport. GO analysis further supported the predominance of genes involved in metabolic processes, catalytic activity, and membrane-associated functions. Together, these annotations indicate that L16 and L20 harbor genes potentially involved in nutrient metabolism, membrane transport, and stress-related adaptation, suggesting a genomic basis for their putative metabolic versatility and environmental adaptability. This is consistent with previous findings for L. reuteri TPC32 (Kong et al., 2024). Genome mining also identified genes associated with acid tolerance, bile salt tolerance, cholesterol assimilation, antioxidant activity, antimicrobial function, adhesion, and biofilm formation, as well as predicted bacteriocin-associated clusters such as EnlA- and sactipeptide-related regions. However, these findings were based on genome annotation and in silico prediction, and the expression or activity of these genes was not validated at the transcriptional or translational level in the present study. Therefore, the presence of these genes suggests that L16 and L20 may possess functional potential related to gastrointestinal survival, intestinal colonization, and antagonism against pathogens, but these putative functions require further experimental validation.

The early-life stage is a critical period for the establishment of the intestinal microbiota and the development of the immune system in laying-type chickens, and the long-term effects of probiotics on intestinal health and immune function often require sustained intervention to become evident (Jha et al., 2020; Naeem and Bourassa, 2025). Chai et al. reported that L. reuteri SL001 significantly improved body weight gain, ADG, and ADFI in broilers while reducing FCR relative to the antibiotic group (Chai et al., 2023). Similarly, birds receiving L16 in the present study showed greater body weight gain and better feed efficiency throughout the trial, together with enhanced development of the thymus and BF on days 21 and 42. These findings suggest that L16 may promote both growth and immune organ development.

Intestinal homeostasis depends on coordinated regulation of the physiological state and the physical, biochemical, immune, and microbial barriers. VH, CD, and VH/CD are key indicators of intestinal digestive and absorptive capacity (Duan et al., 2023; Wang et al., 2020). Previous studies have shown that L. reuteri strains can improve intestinal morphology by increasing VH and the VH/CD or reducing CD (Huang et al., 2023). In the present study, clear strain-specific differences were observed. At 42 days of age, L16 significantly increased jejunal VH and the VH/CD ratio without affecting crypt depth, suggesting improved mucosal development and absorptive potential, whereas L20 exerted only limited effects. These structural changes were consistent with the transcriptional data: L16 significantly upregulated the tight junction-related genes Occludin and ZO-1, reduced expression of the pro-inflammatory cytokine IFN-γ, and increased expression of the anti-inflammatory cytokine IL-10. Together, these findings indicate that L16 enhanced jejunal barrier integrity and mucosal homeostasis while suppressing inflammatory responses. Zhang et al. similarly reported that dietary probiotic supplementation increased jejunal IL-10 expression while decreasing the pro-inflammatory cytokine IL-12 in broilers (Zhang et al., 2025a). Collectively, the effects of L16 on villus structure, tight junction function, and immune regulation further support its probiotic potential in improving nutrient absorption and maintaining intestinal health. More broadly, these observations reinforce the strain-specific nature of probiotic function, as also reported in other Lactobacillus species (Chin et al., 2024).

The gut microbiota is essential for nutrient utilization, immune regulation, and host health, and disruption of this community can impair barrier function and promote chronic inflammation (Zhang et al., 2025c). In this study, both BMD and L16 altered the cecal microbiota of Hy-Line Brown chicks, but in clearly different ways. Although both BMD and L16 increased Bacillota and decreased Bacteroidota, the overall microbial shifts induced by BMD appeared broader and less selective, as reflected by reductions in Cytophaga and Blautia, enrichment of Hungatella, and changes in multiple anaerobic taxa. In contrast, L16 preferentially enriched L. brevis and L. tenuis, suggesting a more targeted promotion of LAB-related and potentially beneficial commensal taxa. Given the reported probiotic and intestinal protective functions of these bacteria, such changes may be more conducive to maintaining gut homeostasis (Rahmati-Joneidabad et al., 2024). L20, by comparison, exerted only a modest effect on the cecal microbiota. Moreover, the enrichment of C. perfringens in the control group suggests that untreated birds may carry a higher load of potentially harmful taxa. Overall, these findings support the view that L16 modulates the cecal microbiota in a manner more consistent with probiotic-mediated maintenance of intestinal homeostasis than BMD.

Although BMD, L16, and L20 had limited effects on most measures of cecal α-diversity, BMD significantly increased community evenness and showed clear separation from the other groups in PCoA, indicating a stronger effect on cecal microbial structure. By comparison, L16 and L20 induced only modest shifts, suggesting that L. reuteri acted through targeted ecological modulation rather than broad microbial restructuring. Chai et al. reported that dietary supplementation with SL001 did not significantly alter alpha diversity indices in broilers (Chai et al., 2023). Notably, greater microbial diversity does not necessarily reflect a healthier gut ecosystem, as increased diversity may reduce community stability (Coyte et al., 2015). BMD inhibits bacterial cell wall synthesis by disrupting the bactoprenol cycle and is primarily active against Gram-positive bacteria, including C. perfringens, but it may also non-specifically inhibit some beneficial microbes (Adetunji et al., 2024; Gadde et al., 2018). In contrast, probiotics modulate the intestinal microbiota through competitive colonization and production of antimicrobial compounds, thereby exhibiting greater specificity and host adaptability. Collectively, these findings suggest that L16 exerts a more typical probiotic effect on gut microbiota regulation than BMD.

Conclusion

In this study, 84 LAB strains were isolated from the feces of Hy-Line Brown laying hens. Based on acid tolerance, bile salt tolerance, antibacterial activity, cell surface properties, and safety evaluation, L. reuteri L16 and L20 were selected as strains with superior overall probiotic potential. Genomic analysis showed that both strains possessed favorable features related to metabolism and membrane transport and harbored multiple probiotic-associated genes and bacteriocin biosynthetic clusters. Further in vivo experiments demonstrated that L16 promoted growth, enhanced immune organ development, improved intestinal barrier function, and beneficially modulated the gut microbiota in Hy-Line Brown layer chicks, supporting its potential development as a probiotic feed additive for poultry.

The limitations of this study include the relatively small sample size in the animal experiment, which may affect the statistical power and representativeness of the results. In addition, this study mainly evaluated early growth, immune development, and intestinal health parameters, but did not assess the effects during the laying period or include a pathogen-challenge model; therefore, it cannot directly demonstrate the protective effects of L. reuteri under infectious conditions. Future studies should increase the sample size, further evaluate the effects of L16 and L20 during the laying period, and systematically clarify their regulatory mechanisms on intestinal barrier function, immune responses, and the gut microbiota through pathogen-challenge experiments, dose optimization, and combined application with other probiotics or postbiotics. Furthermore, engineering chassis strains to enhance probiotic traits and functionality may provide more precise and effective microbial preparations for improving poultry health and production performance.

Ethical approval

All animal experiments were approved by the Animal Ethics Committee (AEC) of the College of Life Sciences, Sichuan University (License No. SYXK (Chuan) 2013-185). All experimental procedures and animal care were conducted in accordance with the guidelines for animal management of Sichuan University.

Funding

This work was supported by the National Key Research and Development Program of China (No. 2023YFC2307100), the National Natural Science Foundation of China (No. 32373014), the Earmarked Fund for China Agriculture Research System (No. CARS-40-K14), and the Key R&D Program of Sichuan Province and Sichuan University (Nos. 2025NSFJQ0038 and 26H0416).

Data availability

The genome assemblies of the 14 LAB isolates generated in this study have been deposited in the GenBank database under BioProject accession number PRJNA1333881, while the 16S rRNA amplicon sequencing data generated from cecal contents of Hy-Line Brown laying hens have been deposited in the CNGB Sequence Archive (CNSA) of the China National GeneBank DataBase (CNGBdb) under accession number CNP0009220 (https://www.db.cngb.org/).

CRediT authorship contribution statement

Ting Xu: Writing – original draft, Investigation, Formal analysis, Data curation. Qian Chen: Writing – review & editing, Investigation, Data curation. Jiao Ma: Writing – review & editing, Investigation, Data curation. Ke Wu: Writing – review & editing, Methodology. Zhiqian Su: Investigation. Dong You: Investigation. Renqiao Wen: Writing – review & editing, Methodology. Tiejun Zhang: Formal analysis, Data curation. Hongning Wang: Writing – review & editing, Supervision, Funding acquisition, Conceptualization. Anyun Zhang: Writing – review & editing, Supervision, Funding acquisition, Conceptualization.

Disclosures

The authors declare no conflict of interest.