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Article

Probiotic Potential of Pediococcus acidilactici SWP-CGPA01: Alleviating Antibiotic-Induced Diarrhea and Restoring Hippocampal BDNF

by
You-Zuo Chen
1,
Chieh-Ting Chen
1,
Tsung-Wei Shih
1,2,
Wei-Hsuan Hsu
3,
Bao-Hong Lee
4 and
Tzu-Ming Pan
1,5,*
1
SunWay Biotech Co., Ltd., New Taipei City 221012, Taiwan
2
Department of Food Science, Fu Jen Catholic University, New Taipei City 42062, Taiwan
3
Department of Food Safety/Hygiene and Risk Management, National Cheng Kung University, Tainan 701401, Taiwan
4
Department of Horticultural Sciences, National Chiayi University, Chiayi 60004, Taiwan
5
Department of Biochemical Science and Technology, National Taiwan University, Taipei 106319, Taiwan
*
Author to whom correspondence should be addressed.
Microbiol. Res. 2025, 16(12), 261; https://doi.org/10.3390/microbiolres16120261
Submission received: 31 October 2025 / Revised: 9 December 2025 / Accepted: 11 December 2025 / Published: 15 December 2025
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Abstract

Gut microbiota dysbiosis is increasingly being recognized as a major contributor to host metabolic imbalance, immune dysfunction, and neurophysiological disorders. Probiotics are known to modulate intestinal metabolism and exert systemic effects through the gut–brain axis. Herein, we evaluated the safety and probiotic potential of Pediococcus acidilactici SWP-CGPA01 (SWP-CGPA01) under antibiotic-induced microbiota dysbiosis. Genomic and phenotypic analyses verified its safety profile, supporting its suitability for use in food and nutritional applications. In a mouse model of antibiotic-induced dysbiosis, SWP-CGPA01 supplementation alleviated diarrhea and restored hippocampal brain-derived neurotrophic factor expression. These findings demonstrate that SWP-CGPA01 is a safe and functionally active probiotic with the potential to maintain gastrointestinal and neurotrophic homeostasis under gut microbiota dysbiosis.

1. Introduction

The gut microbiota forms a dynamic and complex ecosystem essential for maintaining host health through nutrient metabolism, immune regulation, intestinal barrier integrity, and protection against pathogens. Antibiotic exposure is one of the most potent factors that disrupt this ecosystem, inducing rapid and profound shifts in microbial diversity and function within days of administration [1]. Such dysbiosis disrupts carbohydrate fermentation and bile acid transformation, leading to osmotic and metabolic imbalances that can result in antibiotic-associated diarrhea [2,3]. Beyond local gastrointestinal effects, microbial dysbiosis also alters the production of key metabolites such as short-chain fatty acids (SCFAs) and tryptophan-derived indoles, which are important mediators of gut–brain communication [4,5]. These metabolites influence neuroinflammatory signaling and regulate the expression of brain-derived neurotrophic factor (BDNF), a key regulator of synaptic plasticity and cognitive function. Antibiotic-induced reductions in SCFAs and indole derivatives have been linked to decreased hippocampal BDNF levels, ultimately impairing neurophysiological homeostasis [6,7]. Therefore, restoring microbial balance is vital not only for intestinal health but also for maintaining neurotrophic signaling along the gut–brain axis.
Given the detrimental consequences of gut microbiota dysbiosis, probiotics have garnered increasing attention as a promising approach to restore microbial homeostasis and support host metabolic health. Probiotics help restore beneficial microbes while inhibiting pathogens through competitive exclusion, acid and bacteriocin production, and the modulation of intestinal pH and redox balance [8]. Beyond their local intestinal effects, probiotics are increasingly being recognized for their ability to influence distal organs through metabolism-dependent mechanisms [9]. Certain psychobiotic strains influence the gut–brain axis by regulating microbiota-derived metabolites that link the gut and the brain [10]. Among these, SCFAs such as butyrate and propionate can cross the blood–brain barrier and enhance the expression of BDNF, while microbial tryptophan catabolism influences the kynurenine and serotonin pathways involved in mood and cognition [11,12]. Probiotic supplementation has been shown to improve cognitive performance and alleviate anxiety- or depression-like behaviors in both animal models and human clinical trials [13,14].
Pediococcus acidilactici is a lactic acid bacterium with a long-standing history of safe use in fermented foods and has been included in the European Food Safety Authority’s Qualified Presumption of Safety (QPS) list [15]. It is widely distributed in fermented vegetables, dairy, and meats, as well as in the human gastrointestinal tract. Its production of lactic acid and class IIa bacteriocins contributes to its antimicrobial efficacy against pathogens including Listeria monocytogenes [16]. Beyond its traditional role in food fermentation, P. acidilactici has attracted increasing attention for its probiotic potential. Multiple strains have demonstrated the ability to modulate gut microbiota composition, enhance metabolic balance, and alleviate inflammation. For instance, P. acidilactici pA1c and FZU106 improve glucose and lipid metabolism in metabolic disorders induced by high-fat diets [17,18]. Genomic and metabolomic studies in P. acidilactici strains have identified gene clusters associated with complex carbohydrate utilization and SCFA biosynthesis [19,20]. Furthermore, P. acidilactici GLP06 and 72N produce bioactive metabolites with antibacterial and anti-inflammatory properties, further supporting their contribution to intestinal health and immune regulation [21,22]. Importantly, P. acidilactici has recently been implicated in gut–brain axis modulation. Notably, Tian et al. reported that P. acidilactici CCFM6432 alleviated anxiety-like behaviors and corrected stress-induced gut microbial imbalances in mice, highlighting its emerging role as a psychobiotic candidate capable of influencing both metabolic and neurophysiological processes [23].
Collectively, these findings suggest that P. acidilactici exerts multifaceted benefits by restoring microbial and immune homeostasis and by potentially modulating neurotrophic signaling pathways. Although P. acidilactici has been reported to confer beneficial effects on host metabolism and mental health, its role under conditions of microbiota dysbiosis remains unclear. Herein, we evaluated the safety and potential probiotic characteristics of the newly isolated P. acidilactici SWP-CGPA01 (SWP-CGPA01). Genomic and phenotypic analyses confirmed its safety profile, and in a mouse model of antibiotic-induced microbiota dysbiosis, oral administration of SWP-CGPA01 alleviated diarrhea and enhanced hippocampal BDNF expression. These results highlight SWP-CGPA01 as a safe and promising probiotic candidate with dual functionality in restoring gut microbial balance and supporting gut–brain axis regulation.

2. Materials and Methods

2.1. Strains and Culture Conditions

The Pediococcus acidilactici SWP-CGPA01 strain (commercial name ExoBDNF®; Sunway Biotech Co., Ltd., New Taipei City, Taiwan) was isolated from chicken intestines in Taiwan and deposited in the National Collection of Industrial Food and Marine Bacteria (NCIMB; Aberdeen, UK) under the accession number NCIMB 44102. Pediococcus acidilactici BCRC 17599, Staphylococcus aureus BCRC 12154 (ATCC 6538), and Salmonella enterica subsp. enterica BCRC 10747 (ATCC 14028) were obtained from the Bioresource Collection and Research Center (BCRC; Hsinchu City, Taiwan). All strains were stored at −80 °C in their respective growth media supplemented with 50% glycerol. Before use, SWP-CGPA01 and BCRC 17599 were sub-cultured in De Man–Rogosa–Sharpe (MRS) broth (BD Difco, Franklin. Lakes, NJ, USA) at 37 °C for 24 h, whereas the pathogenic strains were cultured in nutrient broth (BD Difco, USA) at 37 °C for 24 h.

2.2. Genome Sequencing and Analysis

Genomic DNA for long reads was obtained using Oxford Nanopore Technologies (ONT; Oxford, UK) sequencing and for short reads, Illumina sequencing was carried out using the QIAGEN Genomic-tip 20/G Kit (QIAGEN, Hilden, Germany). The quality of all extracted genomic DNA was determined using a QuantiFluor® dsDNA System (Promega Corporation, Madison, WI, USA). Extracted genomic DNA was sequenced using both ONT GridION (Oxford, UK) for longer raw reads and the Illumina Mi-Seq paired-end 301bp × 2 mode (Illumina, San Diego, CA, USA) for larger numbers of high-accuracy short reads. ONT raw data obtained from the sequencer was decoded and demultiplexed using built-in software, and raw reads without suitable barcodes or absent barcodes were discarded. The ONT and Illumina raw reads were subjected to QC and trimming using the QIAGEN CLC Genomics Workbench 21 QC workflow. Illumina reads were trimmed at a quality limit of Q20 with automatic adapter trimming and a minimum read length cut-off of 15 bp. ONT reads with a mean quality < Q7 or a read length < 500 bp were removed.
Hybrid de novo genome assembly and polishing were performed using the long-read workflow in QIAGEN CLC Genomics Workbench 21 (QIAGEN, Aarhus, Denmark). The completeness of the assembled genome was assessed by Benchmarking Universal Single-Copy Orthologs (BUSCO) version 5.4.4 using the lactobacillales_odb10 dataset. Gene prediction and annotation were conducted via the NCBI Prokaryotic Genome Annotation Pipeline (National Center for Biotechnology Information, Bethesda, MD, USA).
To assess safety-related traits, the genome was compared to virulence factor databases for the existence of known pathogenic and toxin-producing genes using BLASTp or BLASTn (both included in NCBI BLAST+, version 2.15.0). The cut-off values were e-value < 1.0 × 10−5, >60% coverage and >70% identity, and the databases used for comparison included MvirDB (last updated April 2012) [24], VFDB (last updated March 2023) [25], CGE VirulenceFinder 2.0 [26], CGE PathogenFinder 1.1 [27], and PAIDB 2.0 [28]. All hits were reviewed to predict possible functions and the closest organism to determine the pathogenicity risk of the gene. Hemolysin genes were screened via VFDB, mucin degradation genes were identified using dbCAN 4.0 [29], and antibiotic resistance genes were searched using NCBI AMRFinderPlus version 3.11.2 [30], CARD (version 3.2.6) [31], ResFinder (version 4.3.1) [32], and ARG-ANNOT (version V6) [33].
Microbial biogenic amine-producing genes of histidine decarboxylase, tyrosine decarboxylase, ornithine decarboxylase, agmatine deiminase, and lysine decarboxylase were collected from NCBI GenBank, and the BLAST databases (last updated June 2023) were constructed. The whole-genome sequence of the strains was compared against the blast databases to determine the existence of the known genes responsible for the production of biogenic amines by BLASTp and BLASTn. The cut-off values were e-value < 1.0 × 10−5, >60% coverage, and >70% identity. KofamScan 1.3.0 software [34] was used to confirm biogenic amine-producing genes.
Detection of genomic islands, insertion sequences, prophages, plasmids, and CRISPR-Cas elements was achieved using IslandViewer 4 [35], ISEScan (version 1.7.2.3) [36], PhageBoost (version 0.1.7) [37], PlasClass (version 0.1.1) [38], and CRISPRCasFinder (version 4.3.2) [39], respectively.
The NCBI genome database was accessed to acquire 19 genome sequences of P. acidilactici strains for the study. Subsequently, the whole-genome multi-locus sequence typing (wgMLST) analysis was conducted utilizing chewBBACA 3.1.2 software [40].

2.3. Antimicrobial Susceptibility Testing

The minimum inhibitory concentration (MIC) of antibiotics was determined for each test strain using the broth microdilution method in accordance with ISO 10932: 2012 [41], which is a standard and reputable method. Eight antibiotics—gentamicin, streptomycin, tetracycline, erythromycin, clindamycin, ampicillin, chloramphenicol, and kanamycin—were used in this study in accordance with recommendations for the assessment of bacterial susceptibility to antimicrobials (EFSA, 2018) [42]. According to ISO 10932: 2012, individual colonies were suspended in sterile saline, adjusted to McFarland 1, and then diluted in the LSM medium and inoculated into pre-coated microdilution plates. The plates were incubated anaerobically at 37 °C for 48 h, and MIC values were determined visually as the lowest antibiotic concentration preventing visible bacterial growth. Each assay was performed in triplicate.

2.4. Mucin Degradation Assay

Following the method described previously [43], 10 μL of 24 h bacterial cultures was inoculated onto the surface of the 0.5% porcine submaxillary mucin (PSM; M1778, Sigma-Aldrich, St. Louis, MO, USA) agar without glucose and 0.5% PSM agar supplemented with 3% glucose. Salmonella enterica subsp. enterica BCRC 10747 was used as the positive control. The plates were incubated at 37 °C for 72 h under both aerobic and anaerobic conditions and were stained with 0.1% amido black in 3.5 M acetic acid for 30 min and then washed with 1.2 M acetic acid. Mucin degradation was determined by observing the mucin lysis zone around the colony. All assays were performed in triplicate.

2.5. Hemolytic Activity Assay

Following the methods described by Casarotti et al. [44], the bacterial cultures were streaked onto Columbia blood agar plates containing 5% sheep blood (BD Difco, USA) and incubated at 37 °C for 48 h under both aerobic and anaerobic conditions. The Staphylococcus aureus BCRC 12154 strains were used as the positive controls, and all assays were performed in triplicate. Hemolytic activity was interpreted according to standard definitions: α-hemolysis (greenish or brownish discoloration), β-hemolysis (clear transparent zone), and γ-hemolysis (no visible change around colonies).

2.6. Biogenic Amine Analysis

Pediococcus acidilactici SWP-CGPA01 was inoculated into 10 mL MRS broth. After incubation at 37 °C for 24 h, the concentrations of seven biogenic amine compounds were determined. The 0.5 mL supernatant of the cultured medium was mixed with 1.5 mL of 0.4 M HClO4 for 1 h and centrifuged at 12,000× g for 10 min to collect the supernatant. The 250 μL supernatant was mixed with 25 μL of 2 M NaOH and 75 μL of saturated NaHCO3 and then reacted at 50 °C for 45 min. Subsequently, 500 μL of 5 mg/mL dansyl chloride and 25 μL of 25% NH4OH were added to the reaction mixture. Finally, the volume was increased to 1.5 mL with acetonitrile. The samples were mixed and centrifuged at 2500× g for 5 min to obtain the supernatant and then filtered through a 0.22 μm membrane for analysis.
The analysis was carried out on a Waters Alliance 2695 system with an RP-18 column (Li Chro CART 250-4, 5 μm, Merck, Darmstadt, Germany) with a LiChroCART 4-4 Guard Column (RP-18, 5 μm) (Merck, Darmstadt, Germany) and a manu-CART NT cartridge holder (Merck, Darmstadt, Germany). The conditions and gradient for HPLC were based on previously reported methods and were further modified [45,46]. The flow rate was 1 mL/min, the column temperature was 40 °C, the detection wavelength was 254 nm (Waters 2996 photodiode array detector), and the injection volume was 20 μL. The 0.1 M ammonium acetate and 100% acetonitrile were used as the mobile phases A and B. The following gradient was used for the analysis: time = 0 min, 50% A and 50% B; time = 19 min, 10% A and 90% B; time = 24 min, 10% A and 90% B; time = 25 min, 50% A and 50% B; time = 33 min, 50% A and 50% B. The standards of seven biogenic amine compounds, including β-phenylethylamine hydrochloride, putrescine dihydrochloride, cadaverine dihydrochloride, histamine dihydrochloride, tyramine hydrochloride, spermidine trihydrochloride, and spermine tetrahydrochloride, were used. All chemicals were obtained from Sigma-Aldrich (St. Louis, MO, USA).

2.7. Gastric Acid–Bile Salt Tolerance Test

The formula of simulated gastric and small intestinal juices was adapted from previous studies [47]. The components of simulated gastric fluid per liter include 2 g of NaCl, 3.2 g of pepsin, and 7 mL of HCl, with the pH adjusted to 3. The components of simulated intestinal fluid per liter include 6.8 g of KH2PO4, 10 g of trypsin, and 77 mL of NaOH, with the pH adjusted to 6.8. The initial bacterial suspension was adjusted to approximately 1 × 109 CFU/mL. It was then mixed with pH 3 artificial gastric fluid at a 1:10 ratio. The mixture was incubated at 37 ± 1 °C for 3 h (from 0 to 3 h), and after centrifugation at 2500× g for 10 min to remove the artificial gastric fluid, an equal amount of artificial intestinal fluid containing 0.3% bile salts was added, and the mixture was thoroughly suspended and continued to incubate at 37 ± 1 °C for another 3 h (from 3 to 6 h). At each digestion time point (0–6 h), the bacterial suspension was collected and serially diluted, and 100 μL of each dilution was spread onto MRS agar plates for viable counting.

2.8. Animals and In Vivo Experimental Design

Balb/c mice (6 weeks old, male) were obtained from the National Center for Biomodels (NCB), NIAR, Taiwan. They were housed under controlled conditions of temperature (20–22 °C), humidity (55–65%), and a 12 h light/dark cycle, where the first 7 days were an acclimation period. The mice had free access to standard laboratory diets and were housed in an AAALAC-certified animal facility, with space provided by NCB. All experiments were conducted in accordance with the Guide for the Use and Care of Laboratory Animals and approved by the IACUC (IACUC number: NLAC-111-H-001) of NCB, Taiwan.
Eighteen mice were randomly assigned to three groups (n = 6 per group), with each group having an equal average body weight. The control group was given PBS, while low- and high-dose groups received SWP-CGPA01 with 7.5 × 108 and 1.5 × 109 CFU/kg body weight, respectively, which was administered once daily by oral gavage throughout the experiment. Fecal samples were collected, and selective enumeration of lactic acid bacteria and Bifidobacterium spp. was performed from day 1 to day 7 after the oral administration of SWP-CGPA01 began. The transgalactosylated oligosaccharide (TOS)–propionate dry powder media and the lithium-mupirocin (MUP) selective supplement were purchased from Merck. The transgalactosylated oligosaccharide–mupirocin medium (TOS-MUP) agar was prepared according to the provided guidelines. Approximately 30–80 mg of feces was homogenized in sterile PBS and subjected to serial dilutions, after which lactic acid bacteria were enumerated on MRS agar, and Bifidobacterium spp. were enumerated on TOS–MUP selective agar plates. After 21 days of the oral administration of SWP-CGPA01, the mice were treated twice daily with 3 g/kg of lincomycin hydrochloride (Sigma-Aldrich) for 3 days, following the protocol of a previous study [48,49,50]. The diarrhea status of all mice was assessed daily according to the scoring criteria from previously published work [49]. Immunohistochemistry was performed using the Leica Bond-Max automated staining system (Leica Biosystems, Nussloch, Germany) and the Leica DS9800 BOND Polymer Refine Detection Kit (Leica Biosystems, Nussloch, Germany). The anti-BDNF primary antibody (ab226843; Abcam, Cambridge, UK) was diluted to 1:500 for staining, and ImageJ version 1.53 was used to measure the mean gray intensity in hippocampal regions of the same area size.

2.9. Statistics

The results are expressed as the means ± SDs. Statistics were analyzed using the open-source software of SciPy in Python 3.12. All pairwise comparisons (control vs. LD and control vs. HD) were analyzed using the Mann–Whitney U test to ensure consistent and conservative statistical inference across figures. A p-value < 0.05 was considered statistically significant.

3. Results

3.1. Genotypic Characterization-Based Safety Assessment of P. acidilactici SWP-CGPA01

The whole-genome sequence provides information essential for bacterial identification and genotypic characterization. We adopted a strategy using both ONT and Illumina platforms to combine long reads with insufficient accuracy and short, high-precision reads to reveal the genome sequence of the SWP-CGPA01 strain (GenBank: NZ_CP188825). A genome-based approach was utilized for both the taxonomic classification of the SWP-CGPA01 strain and the assessment of its safety profile. The assembled genome consisted of a single contig with a size of 1.96 Mb and a +GC content of 42.1% (Figure 1A). Gene prediction and annotation revealed a total of 1869 genes, including 15 rRNA and 56 tRNA genes (Supplementary Table S1). The assembly demonstrated a completeness score of 99.8% via an evaluation with BUSCO software (Supplementary Table S2). SWP-CGPA01 was identified as P. acidilactici based on the evaluation of average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values (Supplementary Table S3), where threshold values of 95% ANI and 70% DDH are commonly used to differentiate species [51]. The Genome BLAST Distance Phylogeny (GBDP) method [52] was utilized to infer genome-to-genome distances for species delimitation and to construct a whole-genome-based phylogeny of the SWP-CGPA01 strain (Figure 1B). The core genome multi-locus sequence typing (cgMLST) allele profiles for the 20 P. acidilactici strains were used to construct the minimum spanning tree based on a comparison of 1348 core genes. The minimum spanning tree analysis revealed a close genetic relationship between strain SWP-CGPA01 and DSM 20284 (Figure 1C).

3.2. Bioinformatic-Based Identification of Antibiotic Resistance and Pathogenicity of P. acidilactici SWP-CGPA01

NCBI AMRFinderPlus, CARD, ResFinder, and ARG-ANNOT were used to identify the presence of antibiotic resistance genes in the SWP-CGPA01 genome. The results demonstrated that the predicted and known antibiotic resistance genes were absent. Pathogenicity analysis was performed by comparing these genes against databases of known virulence factors, such as MvirDB, VFDB, Virulence Finder, PathogenFinder, and PAIDB. No significant similarity was found between the sequences of the predicted genes and known virulence factors in the SWP-CGPA01 genome. Moreover, the BLAST search results against VFDB databases showed that the SWP-CGPA01 genome lacked any genes encoding hemolysin (Supplementary Table S4). Analysis using dbCAN identified three genes encoding mucin-degrading enzymes, including one fucosidase gene and two β-galactosidase genes (Supplementary Table S5). The ability of SWP-CGPA01 to produce biogenic amines was predicted via BLAST searches against a database constructed from microbial biogenic amine-producing genes, including those encoding histidine decarboxylase, tyrosine decarboxylase, ornithine decarboxylase, agmatine deiminase, and lysine decarboxylase. This result indicated that the genes related to biogenic amine generation were not identified in the SWP-CGPA01 genome (Supplementary Table S6). The genome analysis revealed no evidence of antibiotic resistance, virulence factors, or biogenic amine-related genes, apart from a potential mucin degradation capability.

3.3. Phenotypic Characterization-Based Safety Assessment of P. acidilactici SWP-CGPA01

The antibiotic susceptibility of SWP-CGPA01 was determined by the broth microdilution method against eight antibiotics according to the European Food Safety Authority (EFSA) guidelines [42]. The MIC values for the SWP-CGPA01 strain were 128 μg/mL for kanamycin, 32 μg/mL for streptomycin, 16 μg/mL for tetracycline and chloramphenicol, 8 μg/mL for gentamicin, 1 μg/mL for ampicillin, 0.25 μg/mL for erythromycin, and 0.063 μg/mL for clindamycin (Table 1).
The ability to degrade mucin and exhibit hemolytic activity is regarded as a feature of bacterial pathogenicity, indicating that the bacterial strains under study are unsuitable for application in food products due to the potential risks of mucosal invasion by the bacteria themselves, the presence of toxins and other pathogens, and the lysis of the host’s red blood cells. The potential hemolytic activity of SWP-CGPA01 was assessed using the blood agar plating method. Staphylococcus aureus BCRC 12154 (positive control) showed β-hemolysis with colorless zones around the cell colonies, whereas SWP-CGPA01 showed no hemolysis and no change in color in the periphery of the colonies (Figure 2A). A mucin degradation assay was performed using agar plates containing 0.5% PSM. SWP-CGPA01 failed to grow on 0.5% PSM agar without glucose under either anaerobic or aerobic conditions, and no lysis zone formation was observed around SWP-CGPA01 colonies on 0.5% PSM agar supplemented with 3% glucose (Figure 2B). These findings indicate that SWP-CGPA01 does not exhibit mucin degradation activity in the tested medium, regardless of the presence of glucose.
Biogenic amines are low-molecular-weight decarboxylation products of amino acids formed during microbial fermentation [53]. Histamine and tyramine are regarded as the most toxic and food safety-relevant biogenic amines, raising concerns about their presence in fermented foods. As mentioned previously, genomic analysis indicated the absence of known genes associated with biogenic amine production in SWP-CGPA01. To experimentally test this prediction, we analyzed the concentrations of seven specific biogenic amines (β-phenylethylamine, putrescine, cadaverine, histamine, tyramine, spermidine, and spermine) in the spent culture medium of SWP-CGPA01 using HPLC. These biogenic amine compounds were not detected in the samples, indicating the absence of biogenic amine production by the SWP-CGPA01 strain when cultivated anaerobically at 37 °C in MRS broth (Supplementary Table S7). This phenotypic result is consistent with the genotypic data, confirming that strain SWP-CGPA01 does not produce these biogenic amines under the in vitro tested conditions.

3.4. Effects of P. acidilactici SWP-CGPA01 in Antibiotic-Associated Gut Microbiota Dysbiosis

The results indicated that during the initial 0–3 h of the gastric acid resistance test conducted at pH 3, the survival rate of SWP-CGPA01 remained at 100% by the end of the third hour. Subsequently, during exposure to 0.3% bile salts from 3 to 6 h, viability remained at 99.57% (Supplementary Table S8). These results demonstrate that the SWP-CGPA01 strain exhibits strong tolerance to conditions simulating human gastrointestinal transit.
An in vivo experiment was conducted to evaluate the safety and potential health benefits of daily supplementation with SWP-CGPA01. As shown in Figure 3A, mice received oral administration of SWP-CGPA01 for a total of 21 days. During the initial 7-day supplementation phase, fecal counts of lactic acid bacteria and Bifidobacterium spp. were determined using MRS and TOS–MUP selective agar plates, respectively. By day 3, both bacterial populations were significantly elevated in mice receiving 7.5 × 108 CFU/kg BW (LD group) or 1.5 × 109 CFU/kg BW (HD group) of SWP-CGPA01 (Figure 3B,C). However, these increases were not maintained thereafter. Throughout the 21-day supplementation, no adverse effects were observed at either dose, including changes in body weight, food or water intake, activity levels, or stool consistency. Following this period, the mice were administered lincomycin to induce gut microbiota dysbiosis, while daily SWP-CGPA01 supplementation was continued. No significant differences in body weight were observed among groups during antibiotic treatment (Figure 3D). On day 2 post-lincomycin exposure, both LD and HD groups displayed significantly higher fecal counts of lactic acid bacteria and Bifidobacterium spp. than the control group (Figure 3E,F).
Antibiotic treatment typically induces diarrhea, an effect attributed to the elimination of gut microbiota, subsequent disruption of digestive metabolism, and altered intestinal osmotic balance [2,3]. Consistent with previous reports, lincomycin-treated control mice developed loose stools and elevated diarrhea scores during the treatment period [49,50]. In contrast, mice receiving high-dose SWP-CGPA01 showed significantly reduced diarrhea severity on the first day after cessation of lincomycin treatment compared with both the control and low-dose groups (Figure 4A). Furthermore, daily oral administration of high-dose SWP-CGPA01 resulted in significantly higher levels of BDNF expression in the hippocampus compared to the control group (Figure 4B). Collectively, these results indicate that SWP-CGPA01 effectively attenuates antibiotic-induced diarrhea and enhances hippocampal BDNF expression, suggesting its potential to mitigate lincomycin-induced gut dysbiosis and modulate the gut–brain axis.

4. Discussion

Probiotics have emerged as a vital strategy for mitigating the adverse effects of antibiotic therapy. Recent studies have highlighted their role not only in restoring gut microbial diversity but also in modulating the gut–brain axis. Whole-genome analyses provide precise taxonomic delineation and are widely adopted for in silico safety assessments of probiotic candidates [54]. In this study, genomic and comparative analyses confirmed that Pediococcus acidilactici SWP-CGPA01 (SWP-CGPA01) belongs to a species listed under the European Food Safety Authority’s Qualified Presumption of Safety (QPS) category [15], underscoring its suitability for human consumption. The genome of SWP-CGPA01 lacked genes associated with virulence, hemolysin, or biogenic amine synthesis, and no transferable antibiotic resistance determinants were detected. Given that pathogenic bacteria often exhibit traits such as hemolysis, mucin degradation, and biogenic amine production, we further performed these phenotypic assays to experimentally validate the absence of virulence-associated characteristics predicted by the genomic analysis. According to the EFSA guidelines, when a strain exhibits antibiotic resistance, it is essential to distinguish between intrinsic and acquired resistance to assess the risk of horizontal gene transfer [55]. In the case of SWP-CGPA01, the observed resistance to kanamycin, tetracycline, and chloramphenicol is likely intrinsic, and no genetic elements associated with transmissible resistance were identified, indicating a low risk of horizontal transfer [56]. Genomic screening identified two genes encoding α-L-fucosidase and β-galactosidase, which are enzymes that were previously reported to participate in mucin O-glycan deconstruction in other intestinal bacteria [57,58]. However, in vitro assays confirmed that SWP-CGPA01 lacked mucin-degrading activity, indicating that the presence of these genes does not confer this phenotype. This discrepancy is consistent with reports that glycosidase-encoding genes alone are insufficient for mucin degradation, which typically requires a broader set of mucin-targeting enzymes and specific substrate conditions. This observation supports the view that SWP-CGPA01’s galactosidase activity is primarily involved in galactose and lactose utilization, a common metabolic trait in P. acidilactici [20], whereas fucosidase may have a limited or substrate-specific function unrelated to mucin degradation. Taken together, genomic and phenotypic analyses corroborate the safety of SWP-CGPA01 as a probiotic strain intended for dietary use.
Building upon its safety profile, the probiotic potential of SWP-CGPA01 was further evaluated in vivo. Oral administration of SWP-CGPA01 increased the abundance of lactic acid bacteria and Bifidobacterium spp. in mouse feces during the early supplementation phase, suggesting a transient microbial rebalancing effect [59]. The maintenance of stable body weight and normal activity throughout the 21-day trial confirmed the strain’s safety upon prolonged ingestion. Following antibiotic-induced gut dysbiosis, SWP-CGPA01 supplementation markedly reduced diarrhea severity and accelerated the recovery of beneficial gut microbes. These findings indicate that SWP-CGPA01 can mitigate lincomycin-induced dysbiosis, likely by restoring microbial metabolism, alleviating intestinal inflammation, and maintaining osmotic equilibrium within the intestinal lumen [48,49,50]. While the cecal index did not differ significantly among groups, the reduced cecal size in SWP-CGPA01-treated mice may reflect the normalization of cecal volume associated with recovery from antibiotic-induced bloating (Supplementary Figure S1) [60]. This recovery likely promotes the clearance of undigested substrates and primary bile acids, thereby reducing luminal osmolarity and fluid secretion [5] and ultimately alleviating diarrhea [2]. The capacity of SWP-CGPA01 to restore beneficial microbial populations may therefore facilitate the re-establishment of intestinal metabolic homeostasis, thereby alleviating osmotic disturbances and ultimately mitigating diarrhea symptoms.
Gut microbiota dysbiosis has been increasingly linked to neurological alterations, including anxiety-like behavior, impaired cognition, and disrupted neurotrophic signaling [4]. Such dysbiosis leads to an imbalance in microbiota-derived metabolites and neurotransmitters, which can disrupt physiological communication along the gut–brain axis and consequently affect brain function [61]. Lincomycin exposure profoundly alters these microbial pathways, reducing SCFA production [62] and disrupting bile acid metabolism, which in turn diminishes hippocampal brain-derived neurotrophic factor (BDNF) expression and induces behavioral alterations associated with impaired gut–brain signaling [6,63]. Although behavioral and metabolomic assessments were not conducted in the present study, oral supplementation with P. acidilactici SWP-CGPA01 alleviated antibiotic-induced diarrhea and increased the abundance of lactic acid bacteria and Bifidobacterium spp., suggesting a partial restoration of gut microbial and metabolic homeostasis. The observed upregulation of hippocampal BDNF expression may be attributed to this microbiota-driven metabolic recovery and its downstream influence on gut–brain axis communication. Although modest, this increase is considered biologically meaningful in the context of neurotrophic responses reported for probiotic interventions.
Previous studies have investigated the metabolic and psychobiotic properties of P. acidilactici mainly in diet- or stress-induced models [18,23], yet its functional role under antibiotic-induced microbiota dysbiosis has remained unexplored. This pattern aligns with findings from other probiotic strains, including Lactobacillus and Bifidobacterium species, which also demonstrate context-dependent psychobiotic or metabolic benefits across different models of dysbiosis. The present findings extend this understanding by demonstrating that P. acidilactici SWP-CGPA01 retains probiotic efficacy under gut microbiota dysbiosis conditions. These results highlight its potential to maintain gastrointestinal and neurotrophic homeostasis. However, this study has several limitations that should be acknowledged. Behavioral assessments and metabolomic profiling were not included, which restricts our ability to directly link microbial changes and neurotrophic responses to functional outcomes. In addition, long-term effects and clinical relevance remain to be verified. Future studies should therefore incorporate behavioral measurements and targeted metabolomic analyses to identify key metabolites (such as SCFAs and tryptophan-derived compounds) that may mediate the observed neurotrophic response. Such research will help clarify the mechanistic pathways involved and further define the functional significance of SWP-CGPA01 in the gut–brain axis.

5. Conclusions

Pediococcus acidilactici SWP-CGPA01 shows promise as a safe probiotic capable of supporting gut and gut–brain health during antibiotic-induced dysbiosis. In this study, it reduced diarrhea, aided microbial recovery, and helped maintain hippocampal BDNF levels, indicating a potential role in preserving key physiological functions when the gut microbiota is disturbed.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/microbiolres16120261/s1: Table S1. General genome features of P. acidilactici SWP-CGPA01; Table S2. Genome completeness assessment for P. acidilactici SWP-CGPA01; Table S3. Pairwise comparison of average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values between P. acidilactici SWP-CGPA01 and the closely related type strains; Table S4. Hemolysin encoding gene analyses of P. acidilactici SWP-CGPA01; Table S5. Mucin degradation gene analyses of P. acidilactici SWP-CGPA01; Table S6. Biogenic amine production gene analyses of P. acidilactici SWP-CGPA01; Table S7. Determination of seven biogenic amines in the spent culture medium of P. acidilactici SWP-CGPA01; Table S8. Viability of P. acidilactici SWP-CGPA01 during simulated gastric acid and bile salt digestion; Figure S1. Representative images of the cecum and measurement of the cecum index.

Author Contributions

Y.-Z.C. performed data analysis and interpretation and wrote the manuscript. C.-T.C. assisted with whole-genome sequencing, adhesion assays, and digestion tolerance tests. T.-W.S. provided research guidance and contributed to discussions on the study design. W.-H.H. and B.-H.L. provided methodological support. T.-M.P. supported research supervision, project administration, and conceptualization. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki. All procedures involving animal handling were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of the National Center for Biomodels (NCB, Taiwan) under approval number NLAC-111-H-001 on 13 October 2020.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

Y. Z. Chen, T. W. Shih, and T. M. Pan are employed by SunWay Biotech Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SWP-CGPA01Pediococcus acidilactici SWP-CGPA01
WGSWhole-genome sequence
BDNFBrain-derived neurotrophic factor
SCFAsShort-chain fatty acids
ONTOxford Nanopore Technology
BUSCOsBenchmarking Universal Single-Copy Orthologs
wgMLSTWhole-genome multi-locus sequence typing
MICMinimum inhibitory concentration
PSMPorcine submaxillary mucin
MRSDe Man–Rogosa–Sharpe
HPLCHigh-performance liquid chromatography
NCBNational Center for Biomodels
IACUCInstitutional Animal Care and Use Committee
TOSsTransgalactosylated oligosaccharides
MUPLithium-Mupirocin
TOS-MUPTransgalactosylated oligosaccharides–mupirocin medium
ANIAverage nucleotide identity
dDDHDigital DNA-DNA hybridization
GBDPGenome BLAST Distance Phylogeny
cgMLSTCore genome multi-locus sequence typing
EFSAEuropean Food Safety
QPSQualified Presumption of Safety

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Microbiolres 16 00261 g001
Figure 1. Overview of the whole genome of the SWP-CGPA01 strain and its evolutionary tree. (A) The genome map of SWP-CGPA01 was drawn using Proksee viewer v0.6.6. The outside ring displays the coding sequence (CDS; blue) and ribosomal RNA (rRNA; red). The inside ring shows G/C skew information in the positive-sense strand (+; green color) and negative-sense strand (−; purple color). (B) The phylogenetic tree was created from GBDP distances calculated from genome sequences. The branch lengths are scaled in terms of the GBDP distance formula d5. The numbers above the branches are GBDP pseudo-bootstrap support values > 60% from 100 replications, with an average branch support of 31.1%. (C) The minimum spanning tree illustrating the phylogenetic relationship based on the wgMLST allelic profiles of 20 P. acidilactici strains.
Figure 1. Overview of the whole genome of the SWP-CGPA01 strain and its evolutionary tree. (A) The genome map of SWP-CGPA01 was drawn using Proksee viewer v0.6.6. The outside ring displays the coding sequence (CDS; blue) and ribosomal RNA (rRNA; red). The inside ring shows G/C skew information in the positive-sense strand (+; green color) and negative-sense strand (−; purple color). (B) The phylogenetic tree was created from GBDP distances calculated from genome sequences. The branch lengths are scaled in terms of the GBDP distance formula d5. The numbers above the branches are GBDP pseudo-bootstrap support values > 60% from 100 replications, with an average branch support of 31.1%. (C) The minimum spanning tree illustrating the phylogenetic relationship based on the wgMLST allelic profiles of 20 P. acidilactici strains.
Microbiolres 16 00261 g001
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Figure 2. In vitro evaluation of hemolytic and mucin degradation activity of P. acidilactici SWP-CGPA01. (A) Hemolytic activity assessed on Columbia agar supplemented with 5% sheep blood under aerobic (left panel) and anaerobic (right panel) conditions. Staphylococcus aureus BCRC 12154 was used as the positive control. (B) Mucin degradation evaluated on 0.5% PSM agar under aerobic (left panel) and anaerobic (right panel) conditions. Salmonella enterica subsp. enterica BCRC 10747 was used as the positive control.
Figure 2. In vitro evaluation of hemolytic and mucin degradation activity of P. acidilactici SWP-CGPA01. (A) Hemolytic activity assessed on Columbia agar supplemented with 5% sheep blood under aerobic (left panel) and anaerobic (right panel) conditions. Staphylococcus aureus BCRC 12154 was used as the positive control. (B) Mucin degradation evaluated on 0.5% PSM agar under aerobic (left panel) and anaerobic (right panel) conditions. Salmonella enterica subsp. enterica BCRC 10747 was used as the positive control.
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Figure 3. P. acidilactici SWP-CGPA01 increases and restores the population of lactic acid bacteria and Bifidobacterium spp. in the intestine. (A) Schematic timeline showing daily oral gavage of SWP-CGPA01 for the entire experiment, including during lincomycin treatment. Fecal samples were collected for the enumeration of lactic acid bacteria and Bifidobacterium spp. using MRS and TOS-MUP selective agar plates, respectively. (B,C) Fecal counts of lactic acid bacteria and Bifidobacterium spp. after 3 days of SWP-CGPA01 supplementation. (D) Body weight changes following lincomycin treatment. (E,F) Fecal counts of lactic acid bacteria and Bifidobacterium spp. on day 2 post-lincomycin treatment. Selective enumeration of lactic acid bacteria and Bifidobacterium spp. was performed using MRS agar and TOS–MUP selective agar plates, respectively. n = 6 per group. Statistical analysis of bacterial counts performed using Mann–Whitney U test. * p-value < 0.05; Low-dose SWP-CGPA01 group = LD; high-dose SWP-CGPA01 group = HD.
Figure 3. P. acidilactici SWP-CGPA01 increases and restores the population of lactic acid bacteria and Bifidobacterium spp. in the intestine. (A) Schematic timeline showing daily oral gavage of SWP-CGPA01 for the entire experiment, including during lincomycin treatment. Fecal samples were collected for the enumeration of lactic acid bacteria and Bifidobacterium spp. using MRS and TOS-MUP selective agar plates, respectively. (B,C) Fecal counts of lactic acid bacteria and Bifidobacterium spp. after 3 days of SWP-CGPA01 supplementation. (D) Body weight changes following lincomycin treatment. (E,F) Fecal counts of lactic acid bacteria and Bifidobacterium spp. on day 2 post-lincomycin treatment. Selective enumeration of lactic acid bacteria and Bifidobacterium spp. was performed using MRS agar and TOS–MUP selective agar plates, respectively. n = 6 per group. Statistical analysis of bacterial counts performed using Mann–Whitney U test. * p-value < 0.05; Low-dose SWP-CGPA01 group = LD; high-dose SWP-CGPA01 group = HD.
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Figure 4. P. acidilactici SWP-CGPA01 reduces diarrhea scores and increases hippocampal BDNF levels in a mouse model of antibiotic-induced dysbiosis. (A) Diarrhea scores assessed on day 1 after lincomycin withdrawal (post-lincomycin day 1). Representative fecal images from three randomly selected mice per group are shown in the left panel. (B) Hippocampal expression of BDNF evaluated by immunohistochemistry. n = 6 per group. Statistical analysis of BDNF levels and diarrhea scores was performed using Mann–Whitney U test. * p-value < 0.05; *** p-value < 0.001. Low-dose SWP-CGPA01 group = LD; high-dose SWP-CGPA01 group = HD.
Figure 4. P. acidilactici SWP-CGPA01 reduces diarrhea scores and increases hippocampal BDNF levels in a mouse model of antibiotic-induced dysbiosis. (A) Diarrhea scores assessed on day 1 after lincomycin withdrawal (post-lincomycin day 1). Representative fecal images from three randomly selected mice per group are shown in the left panel. (B) Hippocampal expression of BDNF evaluated by immunohistochemistry. n = 6 per group. Statistical analysis of BDNF levels and diarrhea scores was performed using Mann–Whitney U test. * p-value < 0.05; *** p-value < 0.001. Low-dose SWP-CGPA01 group = LD; high-dose SWP-CGPA01 group = HD.
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Table 1. Minimum inhibitory concentration (MIC) values of antibiotics for P. acidilactici SWP-CGPA01 and P. acidilactici BCRC 17599.
Table 1. Minimum inhibitory concentration (MIC) values of antibiotics for P. acidilactici SWP-CGPA01 and P. acidilactici BCRC 17599.
AntibioticsCut-Off Values of Pediococcus spp. (mg/L)SWP-CGPA01BCRC 17599
MICs (mg/L)MICs (mg/L)
Ampicillin412
Gentamicin1684
Kanamycin6412864
Streptomycin643264
Erythromycin10.250.25
Clindamycin10.0630.032
Tetracycline81616
Chloramphenicol4164
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Chen, Y.-Z.; Chen, C.-T.; Shih, T.-W.; Hsu, W.-H.; Lee, B.-H.; Pan, T.-M. Probiotic Potential of Pediococcus acidilactici SWP-CGPA01: Alleviating Antibiotic-Induced Diarrhea and Restoring Hippocampal BDNF. Microbiol. Res. 2025, 16, 261. https://doi.org/10.3390/microbiolres16120261

AMA Style

Chen Y-Z, Chen C-T, Shih T-W, Hsu W-H, Lee B-H, Pan T-M. Probiotic Potential of Pediococcus acidilactici SWP-CGPA01: Alleviating Antibiotic-Induced Diarrhea and Restoring Hippocampal BDNF. Microbiology Research. 2025; 16(12):261. https://doi.org/10.3390/microbiolres16120261

Chicago/Turabian Style

Chen, You-Zuo, Chieh-Ting Chen, Tsung-Wei Shih, Wei-Hsuan Hsu, Bao-Hong Lee, and Tzu-Ming Pan. 2025. "Probiotic Potential of Pediococcus acidilactici SWP-CGPA01: Alleviating Antibiotic-Induced Diarrhea and Restoring Hippocampal BDNF" Microbiology Research 16, no. 12: 261. https://doi.org/10.3390/microbiolres16120261

APA Style

Chen, Y.-Z., Chen, C.-T., Shih, T.-W., Hsu, W.-H., Lee, B.-H., & Pan, T.-M. (2025). Probiotic Potential of Pediococcus acidilactici SWP-CGPA01: Alleviating Antibiotic-Induced Diarrhea and Restoring Hippocampal BDNF. Microbiology Research, 16(12), 261. https://doi.org/10.3390/microbiolres16120261

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